International Review of Neurobiology, Volume 63

International REVIEW OF Neurobiology Volume 63 International REVIEW OF Neurobiology Volume 63 SERIES EDITORS RONALD...

Author: Ronald J. Bradley | Adron R. Harris | Peter Jenner

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International REVIEW OF

Neurobiology Volume 63

International REVIEW OF

Neurobiology Volume 63 SERIES EDITORS RONALD J. BRADLEY Department of Psychiatry, College of Medicine The University of Tennessee Health Science Center Memphis, Tennessee, USA

R. ADRON HARRIS Waggoner Center for Alcohol and Drug Addiction Research The University of Texas at Austin Austin, Texas, USA

PETER JENNER Division of Pharmacology and Therapeutics GKT School of Biomedical Sciences King’s College, London, UK

EDITORIAL BOARD PHILIPPE ASCHER TAMAS BARTFAI FLOYD E. BLOOM MATTHEW J. DURING PAUL GREENGARD KINYA KURIYAMA HERBERT Y. MELTZER SALVADOR MONCADA SOLOMON H. SNYDER CHEN-PING WU

ROSS BALDESSARINI COLIN BLAKEMORE DAVID A. BROWN KJELL FUXE SUSAN D. IVERSEN BRUCE S. MCEWEN NOBORU MIZUNO TREVOR W. ROBBINS STEPHEN G. WAXMAN RICHARD J. WYATT

International REVIEW OF

Neurobiology EDITED BY

RONALD J. BRADLEY Department of Psychiatry, College of Medicine The University of Tennessee Health Science Center Memphis, Tennessee, USA

R. ADRON HARRIS Waggoner Center for Alcohol and Drug Addiction Research The University of Texas at Austin Austin, Texas, USA

PETER JENNER Division of Pharmacology and Therapeutics GKT School of Biomedical Sciences King’s College, London, UK

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CONTENTS

Contributors............................................................................

ix

Mapping Neuroreceptors at work: On the Definition and Interpretation of Binding Potentials after 20 years of Progress Albert Gjedde, Dean F. Wong, Pedro Rosa-Neto, and Paul Cumming I. Twenty Years of Progress . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . .. II. Remaining Issues . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . .. III. Solutions . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . .. References . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . ..

1 9 19 19

Mitochondrial Dysfunction in Bipolar Disorder: From 31P-Magnetic Resonance Spectroscopic Findings to Their Molecular Mechanisms Tadafumi Kato I. II. III. IV. V. VI.

Introduction . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . .. Phosphorus-31 Magnetic Resonance Spectroscopy .. . . . . . . . . . . . . . . . . . . . . . . . .. Near-Infrared Spectroscopy . . .. . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . .. Molecular Genetic Findings. . .. . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . .. Roles of Mitochondrial Calcium Regulation . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . .. Conclusions. . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . .. References . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . ..

21 22 26 28 33 34 35

Large-Scale Microarray Studies of Gene Expression in Multiple Regions of the Brain in Schizophrenia and Alzheimer’s Disease Pavel L. Katsel, Kenneth L. Davis, and Vahram Haroutunian I. II. III. IV.

Introduction . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . .. Gene Expression Profiling Using Microarrays: Technologies Overview. .. Postmortem Brains and Gene Expression Studies. .. . . . . . . . . . . . . . . . . . . . . . . . .. Comparison of Gene Expression Profiles among Normal Brain Regions . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . ..

v

41 43 49 57

vi

CONTENTS

V. Gene Expression Profiles of Brain Regions in Alzheimer’s Disease. . . .. . . . VI. Gene Expression Profiling in Schizophrenia . . . . .. . . . . . . . . . . . . . . . . . . . . . . . .. . . . VII. Future Perspectives . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . .. . . . References. . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . .. . . .

59 63 68 70

Regulation of Serotonin 2C Receptor PRE-mRNA Editing By Serotonin Claudia Schmauss I. Introduction . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . .. . . . II. Modification of RNA Sequences by RNA Editing via Hydrolytic Deaminations of Adenosines . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . .. . . . III. Enzymes Responsible for A-to-I Editing and Their Substrate Requirements . . . . .. . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . .. . . . IV. A-to-I Editing of the 5-HT2C Receptor Pre-mRNA . . . . . . . . . . . . . . . . . . . . . . . .. . . . V. Modulation of 5-HT2C Receptor Function by RNA Editing . . . . . . . . . . . . .. . . . VI. 5-HT2C Pre-mRNA Editing Responses to Sustained Changes of Postsynaptic 5-HT2C Receptor Activation. . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . .. . . . VII. 5-HT2C Pre-mRNA Editing in the Human Prefrontal Cortex and Alterations in Editing-Site Preferences in Brains of Subjects with Major Depression . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . .. . . . VIII. Conclusions and Future Directions . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . .. . . . References. . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . .. . . .

83 84 86 87 88 91

93 96 97

The Dopamine Hypothesis of Drug Addiction: Hypodopaminergic State Miriam Melis, Saturnino Spiga, and Marco Diana I. II. III. IV. V. VI.

Drug Addiction as a Brain Disease . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . .. . . . The Mesolimbic Dopamine System . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . .. . . . Behavioral Animal Models . .. . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . .. . . . Biochemical Studies . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . .. . . . Primate Studies . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . .. . . . Conclusions . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . .. . . . References. . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . .. . . .

102 105 115 120 126 130 131

Human and Animal Spongiform Encephalopathies are Autoimmune Diseases: A Novel Theory and Its supporting Evidence Bao Ting Zhu I. Introduction . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . .. . . . II. A New Theory on the Mechanism of Pathogenesis of Spongiform Encephalopathies (SEs). . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . .. . . . III. Supporting Evidence . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . .. . . .

155 158 169

CONTENTS

IV. Early Diagnosis, Treatment, and Prevention of Various SE Diseases . . . . .. V. Conclusions. . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . .. References . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . ..

vii 180 182 184

Adenosine and Brain Function Bertil B. Fredholm, Jiang-Fan Chen, Rodrigo A. Cunha, Per Svenningsson, and Jean-Marie Vaugeois I. II. III. IV. V. VI. VII.

Introduction . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . .. Regulation of Brain Adenosine Levels in the Central Nervous System . .. Adenosine Receptors. . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . .. Functions of Adenosine Receptors. . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . .. Adenosine–Dopamine Interactions in Brain . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . .. Phenotypes of Knockout Mice. . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . .. Adenosine Receptors and Protection against Ischemic and Excitotoxic Brain Injuries. . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . .. Adenosine A2A Receptors and Neurodegenerative Disorders. . . . . . . . . . . . . .. Adenosine Receptors and Psychiatric Disorders . . . .. . . . . . . . . . . . . . . . . . . . . . . . .. Adenosine and the Regulation of Sleep–Wake Cycles . . . . . . . . . . . . . . . . . . . . . .. Adenosine and Epilepsy . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . .. Adenosine and Pain. . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . .. References . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . ..

192 192 196 208 212 216

Index........................................................................................ Contents of Recent Volumes ....................................................

271

VIII. IX. X. XI. XII.

223 228 234 236 238 240 241

283

CONTRIBUTORS

Numbers in parentheses indicate the pages on which the authors’ contributions begin.

Jiang-Fan Chen (191), Department of Neurology, Boston University School of Medicine, Boston, Massachusetts 02118 Paul Cumming (1), Center of Functionally Integrative Neuroscience, Aarhus University Hospitals, Aarhus Denmark 8000; and Department of Radiology, Johns Hopkins Medical Institutions, Baltimore, Maryland 21287 Rodrigo A. Cunha (191), Faculty of Medicine, Center for Neuroscience of Coimbra, University of Coimbra, Coimbra 3004-504, Portugal Kenneth L. Davis (41), Department of Psychiatry, The Mount Sinai School of Medicine, New York, New York 10029 Marco Diana (101), G. Minardi Laboratory of Cognitive Neuroscience, Department of Drug Sciences, University of Sassari, 01700 Sassari, Italy Bertil B. Fredholm (191), Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm S-171 77, Sweden Albert Gjedde (1), Center of Functionally Integrative Neuroscience, Aarhus University Hospitals, Aarhus Denmark 8000; and Department of Radiology, Johns Hopkins Medical Institutions, Baltimore, Maryland 21287 Vahram Haroutunian (41), Department of Psychiatry, The Mount Sinai School of Medicine, New York, New York 10029 Tadafumi Kato (21), Laboratory for Molecular Dynamics of Mental Disorders, Brain Science Institute, RIKEN, Saitama 351-0198, Japan Pavel L. Katsel (41), Department of Psychiatry, The Mount Sinai School of Medicine, New York, New York 10029 Miriam Melis (101), B. B. Brodie Department of Neuroscience, University of Cagliari, 09042 Monserrato, Italy Pedro Rosa-Neto (1), Center of Functionally Integrative Neuroscience, Aarhus University Hospitals, Aarhus Denmark 8000; and Department of Radiology, Johns Hopkins Medical Institutions, Baltimore, Maryland 21287

ix

x

CONTRIBUTORS

Claudia Schmauss (83), Department of Psychiatry and Neuroscience, Columbia University, College of Physicians and Surgeons; and New York State Psychiatric Institute, New York, New York 10032 Saturnino Spiga (101), Department of Animal Biology and Ecology, University of Cagliari, 09126 Cagliari, Italy Per Svenningsson (191), Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm S-171 77, Sweden Jean-Marie Vaugeois (191), CNRS FRE2735, IFRMP 23, Faculty of Medicine and Pharmacy, Rouen 76183, France Dean F. Wong (1), Center of Functionally Integrative Neuroscience, Aarhus University Hospitals, Aarhus Denmark 8000; and Department of Radiology, Johns Hopkins Medical Institutions, Baltimore, Maryland 21287 Bao Ting Zhu (155), Department of Basic Pharmaceutical Sciences, College of Pharmacy, University of South Carolina, Columbia, South Carolina 29208

MAPPING NEURORECEPTORS AT WORK: ON THE DEFINITION AND INTERPRETATION OF BINDING POTENTIALS AFTER 20 YEARS OF PROGRESS

Albert Gjedde, Dean F. Wong, Pedro Rosa-Neto, and Paul Cumming Center of Functionally Integrative Neuroscience, Aarhus University Hospitals Aarhus, Denmark 8000; and Department of Radiology Johns Hopkins Medical Institutions Baltimore, Maryland 21287

I. Twenty Years of Progress II. Remaining Issues A. Definition of Binding Potential B. Definition and Sensitivity of Michaelis Constant C. Sensitivity to Non–Steady State D. Interpretation of Binding Potential Change III. Solutions References

I. Twenty Years of Progress

Positron-emitting radioligands and radiolabeled substrates of transmitter synthesizing enzymes were created as early as 1983 for the in vivo imaging of brain tissue with positron emission tomography (PET) (Wagner et al., 1983) (Fig. 1). Although this class of tracers generally has advanced the search for mechanisms that regulate neurotransmission in the living human brain, the methods of image analysis and interpretation still arouse controversy. We discuss four specific issues in this chapter, after a brief summary of some of the important maps of neuroreceptors that have been at work over the last 20 years. The use of radioligand imaging to establish maps of the functional anatomy of neuroreceptor–radioligand interaction in vivo was discussed at great lengths at an important meeting in Sweden between Uppsala and Stockholm in 1983, and later Gjedde et al. (1986) and Wong et al. (1986a,b) summarized some of the relevant kinetics. The summary presented a model of the kinetic interactions between neuroreceptors and radioligands, which is still the basis of analysis of most imaging studies of radioligand binding, although alternative and less model-dependent analysis methods increasingly have been discussed and used. INTERNATIONAL REVIEW OF NEUROBIOLOGY, VOL. 63

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Copyright 2005, Elsevier Inc. All rights reserved. 0074-7742/05 $35.00

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FIG. 1. Binding to N-[11C]methylspiperone (NMSP) to dopamine D2, D3, and D4 and serotonin 5-HT2A, receptors in human brain. Pseudo-colors use rainbow scale, with red being the highest and blue the lowest recorded radioactivity concentration. Recolored for posterity. [ Used with permission from Wagner, H. N., Jr., Burns, H. D., Dannals, R. F., Wong, D. F., Langstrom, B., Duelfer, T., Frost, J. J., Ravert, H. T., Links, J. M., Rosenbloom, S. B., Lukas, S. E., Kramer, A. V., and Kuhar, M. J. (1983). Imaging dopamine receptors in the human brain by positron tomography. Science 221, 1264–1266.] (See Color Insert.)

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The original and still current model owes its existence to the first derivation of the in vivo kinetics of 2-deoxyglucose uptake by the brain since 1974 (Plum et al., 1976; SokoloV et al., 1977). A typical rendition of the model is shown in Fig. 2, which includes most of the vascular and tissue compartments believed to be occupied at one time or another by most radioligand tracers in daily use. The kinetic relationships described in the model gave rise to linked diVerential equations (an original set is shown in Fig. 3), which were soluble by simple and standard methods that were already applied routinely to PET images of the brain uptake of fluorodeoxyglucose (FDG) uptake in vivo. The nomenclature is somewhat diVerent from the one commonly used today, motivated then by a desire to adhere to the traditional practices of capillary physiologists, who are wont explicitly to consider the diVerence between the tracer concentrations in the bloodstream and the exchange compartment in the tissue as the driving force of the uptake. The equations in Fig. 3 show that the total mass of the ligand in brain continues to rise only as long as the gradient between blood and tissue remains positive, and that eventually it approaches a constant value of the mass of tracer in brain tissue relative to the concentration in the circulation and then occupies the apparent steady-state volumes of distribution predicted in Fig. 4 for the

FIG. 2. Early but still current model of radioligand binding to neuroreceptors. Core or center of model (three middle compartments) is based on compartment kinetics introduced by SokoloV et al. (1977) for 2-deoxyglucose uptake by rat brain, supplemented by compartments relevant to neuroreceptor ligands, including compartments of nonspecific and nonsaturable binding in the circulation and in the brain tissue, as well as compartments of labeled metabolites in circulation and the tissue. The initial vascular distribution volume of the tracer (V0) is not actually the vascular volume itself but a smaller fraction that depends on the extraction fraction. The two compartments of nonspecifically and specifically bound radioligand in the tissue, respectively, are defined by the magnitudes of the transfer coeYcients K1 through k4, of which K1 is the clearance of the blood flow of the tracer (hence, given with an uppercase K ), and k2 through k4 are rate constants of relaxation (decay) of their respective compartments in the direction indicated by the arrows. [ Used with permission from Gjedde (1990).]

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FIG. 3. Linked diVerential equations describing accumulation of masses of exchangeable (‘‘free’’) and bound (Mf and Mb) radioligand. Vf is the steady-state volume of distribution of the unbound ligand, Ca is its arterial concentration, is the time constant of depletion of the Mf compartment, k4 is the rate of dissociation of the ligand from the receptors, and K is the net clearance of the ligand from the circulation to the brain in the absence of dissociation from the receptors. Comparison with Fig. 2 shows that Vf ¼ K1 =ðk2 þ k3 Þ; ¼ 1=ðk2 þ k3 Þ; and K ¼ K1 k3 =ðk2 þ k3 Þ. [ Used with permission from Gjedde, A., Wong, D. F., and Wagner, H. N., Jr. (1986). Transient analysis of irreversible and reversible tracer binding in human brain in vivo. In ‘‘PET and NMR: New Perspectives in Neuroimaging and Clinical Neurochemistry’’ (L. Battistin, Ed.). Alan R. Liss, New York.]

FIG. 4. Blockade: Approach of total mass of radioligand toward apparent steady-state volume of distribution. Simulation shows steady-state plateau depending on magnitude of time constant of depletion of Mf compartment (). Graph shows predicted eVect of blocking binding by setting k3 ¼ 0 before uptake so that K ¼ 0 and and Vf are both increased. Abscissa is ‘‘exposure time,’’ equal to integral of Ca, relative to Ca (Gjedde, 1982). Ordinate is apparent volume of distribution of ligand in tissue, equal to (Mf þ Mb)=Ca. If Ca is constant, abscissa is real time, and ordinate is proportional to actual uptake. The latter approach was later accomplished by the ‘‘programmed infusion’’ method. [ Used with permission from Gjedde, A., Wong, D. F., and Wagner, H. N., Jr. (1986). Transient analysis of irreversible and reversible tracer binding in human brain in vivo. In ‘‘PET and NMR: New Perspectives in Neuroimaging and Clinical Neurochemistry’’ (L. Battistin, Ed.). Alan R. Liss, New York.]

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presence and absence of specific binding sites. The prediction that the magnitude of the steady-state volume of distribution depends on the concentration of the ligand was confirmed in early experiments, in which unlabeled ligand in suYcient quantity indeed displaced the labeled tracer from its binding sites, as shown for the benzodiazepine receptors in primate cortex in Fig. 5. Michaelis and Menten’s steady-state solution to the diVerential equations of ligand association with and dissociation from binding sites (1913) recast the solution to the equations of Fig. 3 in the terms of ligand concentration in relation to the maximum binding capacity and aYnity of the receptors for the ligand, which in turn redefined the steady-state volume of distribution as shown in Fig. 6. This formalism was first applied to the analysis of the N-[11C]methylspiperone (NMSP) images as exemplified in Fig. 1. The results of an early analysis of four healthy humans are shown in Table I. The estimates of constants of the diVerential equations were obtained by nonlinear regression analysis. As an early example of multireceptor kinetics, the analysis simultaneously considered

FIG. 5. Displacement: Displacement of [11C]flumazenil, a radioligand of the cortical benzodiazepine receptors in the brain of nonhuman primates. The apparent steady-state volume of distribution is lowered from a higher to a lower level of steady-state binding by administration of pharmacologically active but unlabeled quantity of the same ligand (flumazenil) used as tracer. [ Data used with permission from Hantraye, P., Brouillet, E., Fukuda, H., Chavoix, C., Guibert, B., Dodd, R. H., Prenant, C., Crouzel, M., Naquet, R., and Maziere, M. (1988). Benzodiazepine receptors studied in living primates by positron emission tomography: Antagonist interactions. Eur. J. Pharmacol. 153, 25–32.]

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FIG. 6. Derivation of steady-state volume of distribution of a radioligand. B0 max is the total number of available binding sites, assumed to be lower than the total number of sites in the absence of other ligands, for example, the neurotransmitter itself. B0 max is defined from the Michaelis–Menten equation as the expression k3Vd=kon, where Vd is the aqueous volume of solution in brain tissue and kon is the association constant of the ligand. In this early treatment, KD is the tissue Michaelis–Menten dissociation constant defined as the expression Vdk4=kon. The term indicated by is the binding potential, equal to the ratios B=Mf and k3=k4. The close observer will note an inconsistency in the transient and steady-state interpretations of k3 and k4, which individually are not defined for the standard equations when Mf is non–steady state. [ Used with permission from Gjedde et al. (1986).]

TABLE I DISTRIBUTION AND BINDING CONSTANTS FOR NMSP BINDING IN CAUDATE NUCLEUS OF FOUR HEALTHY VOLUNTEERS IN VIVO IN THE ABSENCE AND PRESENCE OF A THERAPEUTIC DOSE OF HALOPERIDOL, 4 HOURS AFTER ORAL ADMINISTRATION Caudate

Variable (ml=g) (minutes) Vf (ml=g) K (ml=g=min) (ratio) K1 (ml=g=min) k2 (=min) k3 (=min)

Before haloperidol (mean SD) (n ¼ 4) 2.9 9.9 1.8 0.073 3.1 0.15 0.051 0.052

0.2 1.8 0.5 0.010 1.1 0.02 0.007 0.006

After haloperidol (mean SD) (n ¼ 4) 2.5 12.2 2.3 0.017 0.2 0.20 0.076 0.008

0.3 2.2 0.3a 0.001a 0.1a 0.04 0.008 0.0006a

a Significantly diVerent (paired t test) at p < .01. Note: In the table, the Greek letter symbolizes the partition volume, equal to the K1=k2 ratio. _ legends to Figs. 3–5. The estimates of k were believed to The remaining symbols are defined in the 3 reflect the very high-aYnity binding of the radioligand to dopamine receptors, while the estimates of were believed to reflect the lower aYnity and hence reversible binding to serotonin receptors in caudate nucleus. From Gjedde et al. (1986).

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NMSP’s irreversible binding to dopamine receptors (k4 ¼ 0) and reversible binding to serotonin receptors (k4 6¼ 0), both in the caudate nucleus. The analysis revealed 85% occupancy of dopamine D2=D4 receptors in the caudate nucleus by the neuroleptic haloperidol in the presence of a therapeutic dose, assessed from the decline of k3, and provided the first evidence of the degree of saturation required for optimal eVect. The analysis also revealed a 94% occupancy of the serotonin receptors, assessed from the decline of . Replications have shown the latter estimate to be much too high, with the degree of blockade of serotonin 5-hydroxytryptamine subtype 2A (5-HT2A) receptors by a therapeutic dose of haloperidol being closer to 25% (Goyer et al., 1996). The diVerence may have been caused by either haloperidol blockade of nonspecific binding sites in the caudate nucleus, release of dopamine and serotonin in response to the administration of the neuroleptic, or both, possibly combined with the bias inherent in the dual-receptor analysis attempted in this study, in which any deviation from irreversibility of the radioligand binding was assigned to the alleged reversible binding to serotonin receptors. For comparison and assessment of progress, we provide maps of dopamine and serotonin receptor sites in the human brain in Fig. 7. The maps were constructed separately from the binding potentials of more selective radioligands of the dopamine D2 and D3 receptors in the striatum and the serotonin 5-HT1A receptors in the cerebral cortex of healthy humans. The selective radioligands did not bind to the dopamine D4 or serotonin 5-HT2A receptors. The definition of the binding potential provided in Fig. 6 implicitly considered the natural ligands of the neuroreceptors, the neurotransmitters themselves, as inhibitors of the radioligand, in the definition of the number of available binding sites, B0max . This led to the later claim (first made in an application to the erstwhile Medical Research Council of Canada in 1989) that neuroreceptor maps of radioligand binding in theory provide important clues to the release and reuptake of respective endogenous transmitters. Subsequent estimates of the release and reuptake of neurotransmitters have been based almost exclusively on the somewhat elusive changes of the binding potential that sometimes occurs in parallel with cognitive or pharmacodynamic activity in human and animal brains. It is the basic tenet of this approach that the changes can be ascribed to the specific release of a single class of neurotransmitter, but incontrovertible proof of this claim has not been provided in every case. Another example of the use of binding potentials to estimate release of a neurotransmitter is shown in Fig. 8, in which the oral treatment of patients with attention-deficit=hyperactivity disorder (ADHD) with 20 mg of the cocaine analog and dopamine reuptake inhibitor methylphenidate is believed to increase the synaptic concentration of dopamine and hence block the binding of the radioligand [11C]raclopride to such an extent that the binding is significantly less than in the patients’ untreated state. Unlike the previous maps of radioligand

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FIG. 7. Comparison of WAY 100635 and raclopride binding potentials in a three-dimensional reconstruction and orthogonal sections of human brain in vivo. Binding potentials are rendered in pseudo-colors according to the rainbow (WAY 100635) and ‘‘hot-metal’’ (raclopride) scales. Note that potentials reach values of 3 to 4 for both radioligands. [ Personal communication from Mette Møller, M. D., and Pedro Rosa-Neto, M. D., Aarhus PET Center, (2004).] (See Color Insert.)

interaction with neuroreceptors, these images are actual maps of the significance of the decline of the binding potential in every region of the brains of the patients after the administration of the drug, overlaid on an average magnetic resonance imaging (MRI) scan of the anatomy of the many brains included in the study. The maps convincingly show that significant decline occurred only in the striatum of the brains, implying to the researchers that the decline is representative of an increase of the endogenous ligand in the vicinity of its receptors. However, what proof exists of this contention? This is the question raised in the following sections. In the following sections, we discuss the main problems aVecting the interpretations of the impressive maps of neuroreceptors at work, including (1) the discrepant meanings of the various measures called binding potential by diVerent practitioners, (2) the uncertain definition of the Michaelis half-saturation constant and its consequent sensitivity to external influences, (3) the sensitivity of the steady-state measures of binding potential, maximum receptor number, and Michaelis half-saturation constant to the absence of a fully established steady

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FIG. 8. Maps of significant changes of [11C]raclopride binding potential after administration of 20 mg of methylphenidate to teenagers (1 girl, 8 men; age 13.7 1.8 years) diagnosed with attentiondeficit=hyperactivity disorder (ADHD). The pseudo-color scale shows the probability of the change of binding potential being due to chance. The parametric map is overlaid on an average magnetic resonance imaging scan of the anatomy of the patients’ brains. [ Used with permission from Rosa-Neto, P., Lou, H. C., Cumming, P., Pryds, O., Karrebaek, H., Lunding, J., and Gjedde, A. (2004). Methylphenidate-evoked changes in striatal dopamine correlate with inattention and impulsivity in adolescents with attention deficit hyperactivity disorder. Neuroimage (in press).] (See Color Insert.)

state, and (4) the various interpretations of binding potential change reported by the diVerent practitioners of neuroreceptor mapping.

II. Remaining Issues

A. DEFINITION OF BINDING POTENTIAL The first problem is the uncertain definition of the binding potential, which tends to yield mutually incompatible results in the hands of diVerent users. The term was introduced in one of the earliest models of neuroreceptor kinetics, presented by Mintun et al. (1984). The model demonstrated that the receptor quantity Bmax (i.e., the number of binding sites) and K1 D (i.e., the binding aYnity) were inseparable in vivo. Instead, they introduced the term binding potential for the ratio Bmax =KD , said to be indicative of the capacity of a brain region to bind a ligand specifically, although the binding potential defined this way is equally indicative of the capacity to bind the ligand nonspecifically. This nonspecific binding of the radioligand to proteins in tissue and plasma is the most important

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factor aVecting the binding potential, yet it is not easily ascertained in vivo. Probably the authors had the bound=free (B=F) ratio of receptor–ligand studies in mind. However, unlike the B=F term, which is unitless in vitro, where the numerator and denominator refer to the same volume, the numerator and denominator of the Bmax=KD term, as defined by Mintun et al. (1984), refer to diVerent volumes. In the hands of Mintun et al. (1984), the binding potential of the radioligand [18F]spiperone in the striatum of primates averaged 19.4, which was said to compare favorably with values obtained from studies in vitro. No unit was given, but the unit represents the volume of plasma per unit volume of tissue, determined as the ratio of radioactivity concentration in brain tissue, corrected for 95% (measured as fraction 1-f2) nonspecific binding of the ‘‘free’’ radioligand in the tissue to radioactivity concentration in arterial blood, corrected for 90% (fixed as fraction 1-f1) nonspecific binding of the radioligand in the circulation. The diversity of the many nomenclatures used contributes to the complexity. Few authors adhere religiously to the letter of the Bmax =KD definition of the binding potential relative to an aqueous solvent (Laruelle, 2000). Some authors give the binding potential relative to plasma volume in the original sense of Mintun et al. (1984). However, most researchers now determine the binding potential relative to the tissue mass or volume, so that it equals the steady-state k3=k4 ratio and the number of specifically bound molecules relative to all other molecules of the radioligand in the tissue. This is the ratio of Gjedde et al. (1986), the ratio B of Gjedde and Wong (2001), and the ratio V3’’ of Laruelle (2000). The 5% free tissue fraction ( f2) and the 10% plasma fraction ( f1) of [18F ]spiperone in relation to the Bmax=KD measure of 19.4 ml of plasma per milliliter of brain tissue in the original study of Mintun et al. (1984) predicts a binding potential of 9.7 when given as the ratio of bound to free tissue contents of the tracer (Bmax=[Ve KD(pl)]). The three types of binding potential are listed in Table II, where Ve is the partition volume, equal to the ratios K1=k2 and f1=f2. Table II shows that the confusion can be great if diVerent authors report mutually inconsistent binding potentials calculated from measured or assumed whole-blood, plasma, tissue, interstitial, or aqueous concentrations, diVering sometimes by several orders of magnitude. The issue is not easily resolved because truly aqueous concentrations are diYcult to determine in vivo, with commensurately error-prone results. The present state of confusion calls for the adoption of the simple definition of the B=F ratio as the number of saturably bound molecules of the ligand for each molecule not so bound in the tissue. The advantages of this convention are manifold: These binding potentials emulate the familiar B=F ratio of in vitro studies as a true ratio of bound to unbound or nonspecifically bound molecules; they relate directly to the Scatchard and Eadie–Hofstee plots of maximum binding and aYnity in vivo; and the binding potentials defined in this way can

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TABLE II RADIOLIGAND BINDING POTENTIALS IN HUMAN STRIATUM Binding potential (ml cm3) Symbol (reference)

Definition

Calculation 1

Calculation 2

Binding potential bðbrÞ Vd ¼ bðbrÞ =f2 B(aq) a.m. (Laruelle, relative to 2000) plasma water B(pl) a.m. bðbrÞ Ve ¼ f1 bðbrÞ =f2 Binding potential f1 bðaqÞ (Mintun relative to et al., plasma 1984) B(br) a.m. Binding potential bðaqÞ =Vd ¼ f2 bðaqÞ (Gjedde relative to et al., tissue 1986)

Spiperone Raclopride 200

20

20

2

10

3

be determined directly from the tissue uptake in the absence of plasma samples from the circulation. The definition of the binding potential as the steady-state ratio of bound to unbound ligand lends itself to model-independent analysis of PET images of radioligand accumulation in specifically binding and nonbinding regions of the brain, if both exist. An example of this is shown in Fig. 9 for dopamine D2 and D3 receptors in human striatum in which the binding potential was determined to be 2.9.

B. DEFINITION AND SENSITIVITY OF MICHAELIS CONSTANT The second problem is related to the first: It raises the issue of the many factors that influence the half-saturation concentration of a ligand, be it the radioligand itself or its solvent (KD) or an exogenous (KI) or endogenous (Ka) competitor. When the ligand is its own inhibitor, the half-inhibition constant indicates the ability to reduce the binding of the radioligand by half. The half-saturation constant of the radioligand is then known as the IC50, the half-inhibition constant of the radioligand. In vivo, the solvent to which this concentration refers may be water, intracellular fluid, extracellular fluid, plasma, or whole blood, but diVerent authors do not always identify the solvent to which their results refer. Gjedde and Wong (2001) calculated the magnitudes of the IC50 of haloperidol derived from tissue, plasma, or water solvent samples. The values varied by

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FIG. 9. Model-independent estimate of binding potential. Monoexponential approach of [11C]raclopride binding to steady-state binding potential in the striatum of 15 healthy volunteers. Ordinate is the ratio of the area under the time–activity curvesR recorded in the striatum R T and a T reference region devoid of dopamine receptors (cerebellum), y ¼ 0 ðMf ðtÞ þ Mb ðtÞÞdt= 0 Mr ðtÞdt. Abscissa is ‘‘exposure time’’ for fully reversible accumulation, equal to the ratio of the dual integration of the regionR radioactivity to the single integration of the reference region radioactivity: R Treference Ru T x ¼ 0 0 Mr ðtÞdt du= 0 Mr ðtÞdt, which has unit of time. This is the dual-integration ERLiBiRD (estimation of reversible ligand binding and receptor density) plot. The curve rises from approximate unity to the steady-state value of unity plus the binding potential (1 þ B). In this case, the binding potential was estimated to be 2.90 0.01 (S.E.). [ Unpublished data from Dean F. Wong; analysis from Gjedde, A. (2003). Modeling metabolite and tracer kinetics. In ‘‘Molecular Nuclear Medicine’’ (L. E. Feinendegen, W. W. Shreeve, W. C. Eckelman, Y. W. Bahk, and H. N. Wagner, Jr., Eds.). Springer-Verlag, Berlin, Heidelberg.]

two orders of magnitude (Table III). The variability of saturation and inhibition constants is due not only to the solvent to which they refer. Other factors, some of which are diYcult to monitor in vivo, are summarized in Fig. 10. Among the factors is the eVect of the inhibition on the release and concentration of native neurotransmitters and the possible eVect of the native neurotransmitter (agonist) on the aYnity of the receptor toward the radioligand. The antagonist concentration relative to its own half-saturation constant (i) is the main determinant of the eVect, which also includes the relative concentration of the native neurotransmitter, or agonist (a). This treatment takes into account the release of the native transmitter, it calls attention to the uncertainties associated with the total eVect, and it calls into question the explanation of the simple

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TABLE III IC50 VALUES OF LIGANDS INHIBITING RADIOLIGAND BINDING, RELATIVE TO THREE SOLVENTS Ligand aYnity (pmol cm3)

Calculation Solvent Symbol Plasma KI(aq) water Plasma KI(pl) Brain KI(br) tissue

I

II KiðbrÞ =Vd ¼ f2 KiðbrÞ

KiðaqÞ =f1 KiðbrÞ =Ve ¼ f2 KiðbrÞ =f1 Vd KiðaqÞ ¼ KiðaqÞ =f2

Spiperone Haloperidol Raclopride 0.12

0.043

1.2 2.4

1.3 3.8

1.2 12.0 8.0

Source: Used with permission from Gjedde, A., and Wong, D. F. (2001). Quantification of neuroreceptors in living human brain. V. Endogenous neurotransmitter inhibition of haloperidol binding in psychosis. J. Cereb. Blood Flow Metab. 21, 982–994.

FIG. 10. Summary of factors influencing the magnitude of the apparent aYnity of a neuroreceptor toward a radioligand, measured in arterial plasma, which is subject to inhibition by an exogenous neurotransmitter antagonist (IC50). The definitions of the terms are shown in the graph: i is the exogenous inhibitor, a the endogenous agonist inhibitor, G the relative change of the receptors’ aYnity to the endogenous agonist inhibitor, and the relative change of endogenous agonist inhibitor caused by the action of an exogenous inhibitor. The inherent half-inhibition aqueous concentration of the antagonist is KI, and the fraction of the inhibitor bound to plasma proteins is fI(pl), equal to f1 in Table III. [ Used with permission from Gjedde, A., and Wong, D. F. (2001). Quantification of neuroreceptors in living human brain. V. Endogenous neurotransmitter inhibition of haloperidol binding in psychosis. J. Cereb. Blood Flow Metab. 21, 982–994.]

Michaelis–Menten type of competition commonly applied to the interpretation of the eVect. If aYnities are aVected in obscure ways, one cannot directly gauge the concentration of a native neurotransmitter assumed to underlie the decline of the radioligand’s binding potential. Table IV is a case in point. It lists the IC50 values of therapeutic doses of haloperidol competing with the radioligand NMSP as determined by Gjedde and Wong (2001) in five groups of psychiatric patients or healthy volunteers. The IC50

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TABLE IV VARIABLE AVERAGE IC50 VALUES OF HALOPERIDOL INHIBITING NMSP BINDING IN FIVE GROUPS OF PATIENTS Diagnosis

State (n)

Group

CI(pl) (nM)

(min)

(I) (min)

KIC50(pl) (nM)

Healthy

Control (22)

I

7.1 0.6

22 3

116 18

1.7 0.5

Bipolar illness

Nonpsychotic (7) Psychotic (7)

II III

7.6 1.8 13.3 3.9

14 1 32 4

104 9 105 13

1.0 0.2 5.8 3.7

Schizophrenia

Drug naive (22) Drug free (5)

IV V

15.3 3.7 26.1 16.2

24 4 20 9

117 21 136 62

4.0 0.6 4.6 0.9

Used with permission from Gjedde, A., and Wong, D. F. (2001). Quantification of neuroreceptors in living human brain. V. Endogenous neurotransmitter inhibition of haloperidol binding in psychosis. J. Cereb. Blood Flow Metab. 21, 982–994.

values were very diVerent for the five groups, in keeping with the dissimilar haloperidol concentrations, suggesting that a factor other than the haloperidol concentration itself has intervened. This factor is likely to be dopamine, but the eVect is instantiated in the several ways shown in Fig. 10 and thus need not be due simply to the magnitude of dopamine’s intrasynaptic concentration.

C. SENSITIVITY TO NON–STEADY STATE The third problem is the application of the Michaelis–Menten solution to non–steady states in vivo. With few exceptions (Lassen et al., 1995), common experimental designs disturb the steady state required for the calculation of the binding potentials used to infer the dynamic changes of endogenous neurotransmitters in vivo. This is particularly true of the experiments in which the tracer undergoes a programmed infusion designed to carry it to a steady state that is subsequently violated by the provoked release of the endogenous neurotransmitter. Lassen et al. (1995), on the other hand, correctly designed an experiment in which the nonlabeled inhibitor at pharmacologically active doses reached a steady state after prolonged infusion, whereas the tracer, chosen to trace the receptor availability at diVerent concentrations of the unlabeled inhibitor, was administered as a bolus. The steady state was maintained by always injecting the tracer as a bolus of high specific activity. The first study was performed as a tracer-alone study. The second study was performed at a steady-state receptor occupancy of about 50%, achieved by a prolonged constant infusion of nonlabeled (‘‘cold’’) flumazenil (Ro 15-1788), starting 2 hours before the bolus tracer injection and continuing until the end of scanning period (Fig. 11).

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FIG. 11. The plasma concentrations of unlabeled (‘‘cold’’) flumazenil in five healthy human volunteers during infusion begun 2 hours earlier with a 30-minute priming at infusion at double the rate of the sustained infusion, which was continued for the next 3.5 hours. [ Used with permission from Lassen, N. A., Bartenstein, P. A., Lammertsma, A. A., Prevett, M. C., Turton, D. R., Luthra, S. K., Osman, S., Bloomfield, P. M., Jones, T., Patsalos, P. N., O’Connell, M. T., Duncan, J. S., and Andersen, J. V. (1995). Benzodiazepine receptor quantification in vivo in humans using [11C]flumazenil and PET: application of the steady-state benzodiazepine receptor quantification in vivo in humans using [11C]flumazenil and principle. J. Cereb. Blood Flow Metab. 15, 152–165.]

The approach has limitations because pharmacological doses of the unlabeled ligand may not be tolerable for the duration of the experiment, which often runs into hours. The advantages nonetheless exceed the disadvantages in carefully selected cases, but few replications have been attempted. The approach of Lassen et al. (1995) diVers fundamentally from the experimental design of current applications, in which it is the radioligand that reaches steady state after prolonged infusion and the unlabeled inhibitor that is given instantaneously as a bolus. The unlabeled inhibitor, or the release of a native neurotransmitter, disrupts the carefully maintained steady state. Often, the infusion of the radioligand lasts for hours to ensure the coveted steady state, yet the single brief intervention may invalidate this carefully established equilibrium. Both the bolus administration of the unlabeled exogenous competitor and the major release of one or more native competitors disrupt the steady state by pharmacologically interfering with the binding of the radioligand and transiently preventing the bound and unbound pools of radioligand from maintaining the constant ratio consistent with steady state. As demonstrated in Fig. 12, standard determinations of binding potential do not yield clear answers from the violated steady state. Researchers commonly discover that the calculated binding potential fails to return to the value existing before the pharmacodynamic perturbation, despite return of the extracellular dopamine concentration to its baseline level, indicating

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FIG. 12. Reverse experimental design seeks steady state of radioligand and disrupts steady state by native neurotransmitter release in this rare comparison between imaging and underlying neurochemical data. Shown are (top panel) representative time courses in the striatum and the cerebellum of accumulation of the radioligand [11C]raclopride in monkey brain after bolus and infusion for 100 minutes. At 40 minutes, the monkeys received amphetamine at 0.3 mg=kg of body weight, causing an immediate reversal of the radioligand uptake. Corresponding dopamine concentrations (bottom panel) in extracellular space of the striatum are also shown, determined in microdialysis samples. A comparison (middle panel) of the two predictions of the binding potential, one from top panel and one from bottom panel, is given. In middle panel, predictions of the binding

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that factors other than the inhibitor concentration i (see Fig. 10) also changed during the perturbation. These could include the aYnity of the receptor to the native ligand or the reduction of the number of receptors by internalization (Ginovart et al., 2004).

D. INTERPRETATION OF BINDING POTENTIAL CHANGE The fourth problem is the uncertain relationship between the binding potential of a receptor system and its occupancy by endogenous neurotransmitter in the baseline. In the simplest definition, the binding potential (B) is given by the equation B ¼ Bo=(1 þ a), where Bo is the binding potential in the theoretical and complete absence of bound ligand, and a is the concentration of the neurotransmitter in the vicinity of the receptor, normalized against the inhibitory constant of the transmitter. The experimental perturbation further reduces the binding potential to the value Bi ¼ Bo=(1 þ i þ a), where i is any provoked increase of an inhibitor. These are the simplest possible descriptions of the binding potential, but the reality is a good deal more complicated, as shown in Figs. 10 and 13. The ratio (B Bi)=B commonly is used as an index of the provoked increase of the neurotransmitter. Figure 14 shows that the ratio is an index of the increase of receptor occupancy, equal exactly to the endogenous neurotransmitter occupancy, only if no neurotransmitter occupies the receptor in the baseline (Fig. 14). In contrast, the ratio (B Bi)=Bi is the index of the relative increase of the neurotransmitter, exactly equal to the increase only if no neurotransmitter occupies the receptor in the baseline (which of course is likely to be

FIG. 13. Extended definition of the binding potential based on the extended definition of the Michaelis constant in Fig. 10. The term i symbolizes the ratio Ci=Ki, whereas the term a symbolizes the ratio Ca=Ka. The term G symbolizes the change of neurotransmitter aYnity caused by a provoked increase of the neurotransmitter, K0 a=Ka. The term symbolizes the provoked increase of the neurotransmitter.

potential from time course of radioligand accumulation in binding and nonbinding region (cerebellum) in the top panel diVers markedly from binding potential predicted from actual measurements of dopamine, indicating that the simple competition model based on competitor concentration fails to predict actual radioligand time courses. [ Used with permission from Endres et al. (1997).]

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FIG. 14. Occupancy and concentration indices derived from Fig. 13, describing changes of binding potentials caused by perturbation provoking release of endogenous transmitter. The upper equation is the change of binding potential relative to the baseline binding potential that yields apparent occupancy of inhibitor. The lower equation is the change of the binding potential relative to the inhibited binding potential that yields apparent concentration of inhibitor relative to inhibitor constant. The equations assume that no external competitors are present, and that the presence of the endogenous neurotransmitter in the baseline is negligible.

FIG. 15. Estimates of baseline binding potential pB (displayed as pBo) and inhibited binding potential pBi (displayed as pBMP) in patients with attention-deficit=hyperactivity disorder (ADHD) treated with methylphenidate. The ratios pB=pB (displayed as delta=pBo) and pB=pBi (displayed as delta=pBMP) yield estimates of the occupancy (0.125) and relative concentration (0.150) of the change of intrasynaptic dopamine eVected by the drug treatment. These estimates are not exact because of the likelihood of the presence of baseline dopamine and aYnity changes generated by the dopamine increase. [ Used with permission from Rosa-Neto, P., Lou, H. C., Cumming, P., Pryds, O., Karrebaek, H., Lunding, J., and Gjedde, A. (2004). Methylphenidate-evoked changes in striatal dopamine correlate with inattention and impulsivity in adolescents with attention deficit hyperactivity disorder. Neuroimage (in press).]

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the case with few receptor systems). This is seen also from the range of values possible for the two calculations of relative decline. The use of the equations shown in Fig. 14 is illustrated in Fig. 15, which shows the result of the analysis applied to the study of methylphenidate treatment in patients with ADHD shown in Fig. 8.

III. Solutions

The analysis of remaining issues and problems suggested a number of solutions. First, the discussion of the diVerent definitions of the binding potential suggests that the most convenient definition is the familiar unitless ratio of the number of bound molecules for each molecule not so bound, commonly known as the B=F ratio when it is measured in vitro. Second, the discussion of the uncertain measurements of aYnity constants suggests that the solvent to which it is referred must always be given explicitly. Third, the discussion of the unstable steady state of current studies of dopamine release and the resulting tenuous relationship between the measures of binding potential and the underlying dopamine concentration suggests that the change of binding potential should not be referred to as dopamine ‘‘release,’’ but as dopamine receptor ‘‘activation,’’ ‘‘availability,’’ or ‘‘occupation.’’ Finally, the discussion of the uncertain meaning of the commonly calculated decline of binding potential, relative to the baseline potential, after pharmacodynamic or cognitive challenges, suggests that the ratio be used only as an index of endogenous neurotransmitter occupancy and not as an index of concentration. An index of neurotransmitter level can be obtained by calculating the decline relative to the declined potential.

References

Endres, C. J., Kolachana, B. S., Saunders, R. C., Su, T., Weinberger, D., Breier, A., Eckelman, W. C., and Carson, R. E. (1997). Kinetic modeling of [11C]raclopride: Combined PET-microdialysis studies. J. Cereb. Blood Flow Metab. 17, 932–942. Ginovart, N., Wilson, A. A., Houle, S., and Kapur, S. (2004). Amphetamine pretreatment induces a change in both D2-receptor density and apparent aYnity: A [11C]raclopride positron emission tomography study in cats. Biol. Psychiatry 55, 1188–1194. Gjedde, A. (1982). Calculation of glucose phosphorylation from brain uptake of glucose analogs in vivo: A re-examination. Brain Res. Rev. 4, 237–274. Gjedde, A. (1990). Modeling the dopamine system in vivo. In ‘‘In vivo Imaging of Neurotransmitter Functions in Brain, Heart, and Tumors’’ (D. E. Kuhl, Ed.). Frontiers in Nuclear Medicine, American College of Nuclear Physicians, U.S. Department of Energy, Washington, DC.

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Gjedde, A. (2003). Modelling metabolite and tracer kinetics. In ‘‘Molecular Nuclear Medicine’’ (L. E. Feinendegen, W. W. Shreeve, W. C. Eckelman, Y. W. Bahk, and H. N. Wagner, Jr., Eds.). Springer-Verlag, Berlin, Heidelberg. Gjedde, A., and Wong, D. F. (2001). Quantification of neuroreceptors in living human brain. V. Endogenous neurotransmitter inhibition of haloperidol binding in psychosis. J. Cereb. Blood Flow Metab. 21, 982–994. Gjedde, A., Wong, D. F., and Wagner, H. N., Jr. (1986). Transient analysis of irreversible and reversible tracer binding in human brain in vivo. In ‘‘PET and NMR: New Perspectives in Neuroimaging and Clinical Neurochemistry’’ (L. Battistin, Ed.). Alan R. Liss, New York. Goyer, P. F., Berridge, M. S., Morris, E. D., Semple, W. E., Compton-Toth, B. A., Schulz, S. C., Wong, D. F., Miraldi, F., and Meltzer, H. Y. (1996). PET measurement of neuroreceptor occupancy by typical and atypical neuroleptics. J. Nucl. Med. 37, 1122–1127. Hantraye, P., Brouillet, E., Fukuda, H., Chavoix, C., Guibert, B., Dodd, R. H., Prenant, C., Crouzel, M., Naquet, R., and Maziere, M. (1988). Benzodiazepine receptors studied in living primates by positron emission tomography: Antagonist interactions. Eur. J. Pharmacol. 153, 25–32. Ishizu, K., Smith, D. F., Bender, D., Danielsen, E., Hansen, S. B., Wong, D. F., Cumming, P., and Gjedde, A. (2000). Positron emission tomography of radioligand binding in porcine striatum in vivo: Haloperidol inhibition linked to endogenous ligand release. Synapse 38, 87–101. Laruelle, M. (2000). Imaging synaptic neurotransmission with in vivo binding competition techniques: A critical review. J. Cereb. Blood Flow Metab. 20, 423–451. Lassen, N. A., Bartenstein, P. A., Lammertsma, A. A., Prevett, M. C., Turton, D. R., Luthra, S. K., Osman, S., Bloomfield, P. M., Jones, T., Patsalos, P. N., O’Connell, M. T., Duncan, J. S., and Andersen, J. V. (1995). Benzodiazepine receptor quantification in vivo in humans using [11C]flumazenil and PET: Application of the steady-state benzodiazepine receptor quantification in vivo in humans using [11C]flumazenil and principle. J. Cereb. Blood Flow Metab. 15, 152–165. Logan, J., Wolf, A. P., Shiue, C. Y., and Fowler, J. S. (1987). Kinetic modeling of receptor-ligand binding applied to positron emission tomographic studies with neuroleptic tracers. J. Neurochem. 48, 73–83. Mintun, M. A., Raichle, M. E., Kilbourn, M. R., Wooten, G. F., and Welch, M. J. (1984). A quantitative model for the in vivo assessment of drug binding sites with positron emission tomography. Ann. Neurol. 15, 217–227. Plum, F., Gjedde, A., Samson, F., Eds. (1976). ‘‘Neuroanatomical Functional Mapping by the Radioactive 2-Deoxy-D-glucose Method’’. Neurosciences Research Program Bulletin, Boston. Rosa-Neto, P., Lou, H. C., Cumming, P., Pryds, O., Karrebaek, H., Lunding, J., and Gjedde, A. (2004). Methylphenidate-evoked changes in striatal dopamine correlate with inattention and impulsivity in adolescents with attention deficit hyperactivity disorder. Neuroimage (in press). SokoloV, L., Reivich, M., Kennedy, C., Des Rosiers, M. H., Patlak, C. S., Pettigrew, K. D., Sakurada, O., and Shinohara, M. (1977). The [14C]deoxyglucose method for the measurement of local cerebral glucose utilization: Theory, procedure, and normal values in the conscious and anesthetized albino rat. J. Neurochem. 28, 897–916. Wagner, H. N., Jr., Burns, H. D., Dannals, R. F., Wong, D. F., Langstrom, B., Duelfer, T., Frost, J. J., Ravert, H. T., Links, J. M., Rosenbloom, S. B., Lukas, S. E., Kramer, A. V., and Kuhar, M. J. (1983). Imaging dopamine receptors in the human brain by positron tomography. Science 221, 1264–1266. Wong, D. F., Gjedde, A., and Wagner, H. N., Jr. (1986). Quantification of neuroreceptors in the living human brain. I. Irreversible binding of ligands. J. Cereb. Blood Flow Metab. 6, 137–146. Wong, D. F., Gjedde, A., Wagner, H. N., Jr., Dannals, R. F., Douglass, K. H., Links, J. M., and Kuhar, M. J. (1986). Quantification of neuroreceptors in the living human brain. II. Inhibition studies of receptor density and aYnity. J. Cereb. Blood Flow Metab. 6, 147–153. Wong, D. F., Young, D., Wilson, P. D., Meltzer, C. C., and Gjedde, A. (1997). Quantification of neuroreceptors in the living human brain. III. D2-like dopamine receptors: Theory, validation, and changes during normal aging. J. Cereb. Blood Flow Metab. 17, 316–330.

MITOCHONDRIAL DYSFUNCTION IN BIPOLAR DISORDER: FROM 31 P-MAGNETIC RESONANCE SPECTROSCOPIC FINDINGS TO THEIR MOLECULAR MECHANISMS

Tadafumi Kato Laboratory for Molecular Dynamics of Mental Disorders Brain Science Institute, RIKEN Saitama 351-0198, Japan

I. Introduction II. Phosphorus-31 Magnetic Resonance Spectroscopy A. What Is Magnetic Resonance Spectroscopy? B. Findings in 31P-MRS C. Findings in 1H-MRS III. Near-Infrared Spectroscopy A. Cerebrovascular Response to Cognitive and Physiological Tasks B. Pathophysiological Implication of Altered Cerebrovascular Response in Mood Disorders IV. Molecular Genetic Findings A. Clinical Genetics B. What Is Mitochondrial DNA? C. Mitochondrial DNA Polymorphisms=Homoplasmic Mutations D. Mitochondrial DNA Deletions E. Mutations of Nuclear Genes Causing Multiple Deletions of mtDNA F. Heteroplasmic Point Mutations of mtDNA G. Nuclear-Encoded Mitochondrial Genes V. Roles of Mitochondrial Calcium Regulation VI. Conclusions References

I. Introduction

Bipolar disorder is one of the major mental disorders characterized by recurrent manic and depressive episodes, and it aVects approximately 0.8% of the population (Goodwin and Jamison, 1990). Alteration of monoaminergic neurotransmission was postulated in the pathophysiology of bipolar disorder based on the mechanism of action of antidepressants and antipsychotics. Because these agents are symptomatic treatment for depressive or manic episodes, monoaminergic dysfunction represents the pathophysiology of these episodes rather than the etiological basis of recurrence of these episodes. Thus, the neurobiological basis of bipolar disorder needs to be studied independently to monoamine theory. INTERNATIONAL REVIEW OF NEUROBIOLOGY, VOL. 63

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Because no specific gene is established as a causative factor and no histopathological finding has been well replicated in bipolar disorder, we cannot focus on a specific molecule, for example, such as amyloid precursor peptide in the case of Alzheimer’s disease. Thus, wide-ranged strategies are needed to study bipolar disorder. Major strategies include pharmacology, neuroimaging, postmortem brain study, peripheral blood cells, and genetics. Among them, neuroimaging is only one method of knowing the biochemical event occurring in the brains of living patients with the disorder. However, the parameters that can be measured by neuroimaging techniques are limited, and the eVects of drugs are diYcult to rule out in clinical settings. Thus, results of neuroimaging studies need to be tested by other complementary strategies, to reinforce the findings obtained from neuroimaging.

II. Phosphorus-31 Magnetic Resonance Spectroscopy

A. What Is Magnetic Resonance Spectroscopy? Among various neuroimaging techniques, magnetic resonance spectroscopy (MRS) is the only method that can measure various important molecules in the brain without applying any external agents. It can examine not only the concentration of metabolites but also that of several important biochemical parameters, such as relaxation time, enzyme activity, and intracellular pH level. Because basic principles of MRS are summarized elsewhere (Kato et al., 1998a), only a brief introduction is given here. Nuclei having odd numbers of protons (or atomic number) have magnetic properties, for example, 1H, 31P, 19F, and 7Li. The nuclear spin resonates and absorbs energy applied by the radiofrequency (RF) pulse of a particular frequency (Larmor frequency) under a strong magnetic field. When the nuclear spin returns to the previous state, it emits electromagnetic waves. This emission is referred to as free induction decay (FID), and the overall process is called relaxation. The concentration of nuclei is related to the intensity of FID observed. The Larmor frequency depends on the type of nuclei and the type of chemical bonding with other nuclei. The slight diVerence of resonance frequency depending on the molecular structure is called the chemical shift. Using the diVerence of chemical shift, the same nuclei in diVerent molecules can be discriminated. The data obtained by MRS depend largely on the parameters used for the measurement, as well as on the method of postacquisition processing. Thus, the data obtained by diVerent methods cannot be directly compared with each other. To obtain localized MRS signals from a particular region of the brain, various signal localization methods are used. The signals obtained by diVerent

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Fig. 1. Phosphorus-31 magnetic resonance spectroscopic image obtained from the human brain. ATP, adenosine triphosphate; PCr, phosphocreatine; PDE, phosphodiester; Pi, inorganic phosphate; PME, phosphomonoester; ppm, parts per million.

methods have diVerent meanings, which makes it diYcult to interpret the data obtained. In the 31P-magnetic resonance spectra of the brain, seven major peaks can be resolved: phosphomonoester (PME), inorganic phosphate (Pi), phosphodiester (PDE), phosphocreatine (PCr), and three phosphate residues from adenosine triphosphate (, , and -ATP) (Fig. 1). The PME peak originates from several metabolites such as phosphocholine (PC) and phosphoethanolamine (PE), precursors of membrane phospholipids. Sugar phosphates including inositol-1-phosphate also contribute to this peak. Most of the signals in the PDE peak in vivo arise from mobile membrane phospholipids. Soluble PDEs such as glycerophosphocholine (GPC) and glycerophosphoethanolamine (GPE) (degeneration products of membrane phospholipids) also contribute to the PDE signal in vivo. The Pi peak 2 contains the signals from H2 PO 4 and HPO4 having diVerent chemical shifts. However, these two molecules give a single peak, because of their fast exchange. By measuring the chemical shift of this peak, one can calculate the intracellular pH level. PCr is a high-energy phosphate made from ATP and creatine (Cr) catalyzed by creatine kinase. B. Findings in

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1. Membrane Phospholipids An initial 31P-MRS study in bipolar disorder was reported in 1991 (Kato et al., 1991). This study was performed to test the hypothesis that the phosphoinositide pathway is enhanced in bipolar disorder. Because lithium was found

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to inhibit inositol monophosphatase and cause accumulation of inositol phosphates (Berridge et al., 1982), it was postulated that the phosphoinositide pathway is enhanced in bipolar disorder (Soares and Mallinger, 1997). Studies in peripheral blood cells showed that the agonist-stimulated phosphoinositide-linked calcium response was enhanced in bipolar disorder (Yamawaki et al., 1998). Because it had been reported that agonist-stimulated accumulation of inositol-1-phosphate could be measured by 31P-MRS as the increased PME peak during lithium treatment (Renshaw et al., 1987), phosphoinositide turnover might be measured by 31P-MRS during lithium treatment. In this study, manic patients with bipolar disorder treated with lithium had increased PME level (Kato et al., 1991), whereas euthymic patients had lower PME levels compared with drug-free control patients despite that they were treated with lithium (Kato et al., 1993). Studies of healthy volunteers showed that PME is increased after lithium treatment (Yildiz et al., 2001a), and this increase was enhanced when amphetamine challenge was performed after lithium treatment (Silverstone et al., 2002). This is partly compatible with the data in bipolar disorder, but reduced PME in the euthymic state could not be well explained. Because reduced PME was replicated in the frontal (Deicken et al., 1995a) and temporal lobes (Deicken et al., 1995b) in drug-free euthymic patients with bipolar disorder, this could not be well explained by the eVects of lithium but may be related to pathophysiology. The increased PME level in the depressive state was found in patients with bipolar disorder treated without lithium (Kato et al., 1994, 1995) and patients with major depression (Volz et al., 1998). Thus, PME level may change with mental state, independent of the eVects of lithium. A metaanalysis supported these findings (Yildiz et al., 2001b). In 2004, Modica-Napolitano and Renshaw reported that phosphoethanolamine, one of the constitutions of PME, inhibits mitochondrial function using isolated mitochondria. This finding may link the alteration in membrane phospholipids with mitochondrial dysfunction, seen in bipolar disorder. 2. High-Energy Phosphates PCr was decreased in the frontal lobes of patients with bipolar depression (Kato et al., 1992, 1994), which correlated with their Hamilton Depression Rating Scale scores (Kato et al., 1995). Barbiroli et al. (1993) reported a decrease in PCr in patients with mitochondrial encephalomyopathies such as chronic progressive external ophthalmoplegia (CPEO). Volz et al. (1998) reported a reduction in ATP in the frontal lobes of patients with major depression. To study the biochemical mechanism of this finding, we performed a photic stimulation experiment in euthymic patients with bipolar disorder (Murashita et al., 2000). In lithium-resistant patients with bipolar disorder, recovery of reduced PCr after the photic stimulation was significantly slower than in healthy controls.

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At that time, no other study had been reported using a similar method in other disorders. Kato et al. (1998c) reported that PCr decreased during photic stimulation but increased just after the stimulation in patients with MELAS syndrome (i.e., mitochondrial encephalopathy, lactic acidosis, and stroke-like episodes). This finding in MELAS syndrome was diVerent from the finding in bipolar disorder. However, slow recovery of PCr after photic stimulation was also reported in patients with CPEO without any central nervous system symptoms (Rango et al., 2001). CPEO is a mitochondrial disorder caused by multiple deletions of mitochondrial DNA (mtDNA). As noted later in this chapter, comorbidity of depression or bipolar disorder is reported in several cases with CPEO, suggesting that patients with bipolar disorder might have subtle mitochondrial dysfunction in the brain. 3. Intracellular pH During the course of our 31P-MRS study, we noticed the unexpected finding that intracellular pH level was decreased in the frontal cortex of patients with bipolar disorder only in the euthymic state (Kato et al., 1993). Intracellular pH level in these patients did not diVer from controls in the manic and depressive states. This finding was diYcult to interpret because there were few reports of other medical conditions showing reduced pH level. Only a few medical conditions were reported to be associated with reduced pH level, including vasoconstriction after subarachnoid hemorrhage (Brooke et al., 1994) and sodium bicarbonate infusion (Nakashima et al., 1996). Among antipsychotics, only clozapine aVected intracellular pH level (Riehemann et al., 2002), but none of our patients was treated with clozapine. Lack of stimulation-dependent pH increase was reported in CPEO (Rango et al., 2001). Rae et al. (1996) reported that intracellular pH level was related to intelligence quotients in children, but such a relationship was not observed in adults (Rae et al., 2003). The finding of reduced pH in euthymic patients with bipolar disorder was not replicated in the study of the other group using magnetic resonance spectroscopic imaging (MRSI) (Deicken et al., 1995a,b), possibly because of the diVerence in methodology. When MRSI was used, smaller data points and use of phase encoding reduced the accuracy of chemical shift measurement. Thus, replication studies using larger data points without phase encoding may be needed. Kato et al. (1998b) also found reduced pH levels in a small number of drug-free euthymic patients with bipolar disorder. Thus, reduced pH level may be related to the pathophysiology of the illness rather than the eVects of medication. Reduced pH level was associated with a positive response to maintenance lithium treatment (Kato et al., 2000), suggesting that reduced pH level is a biochemical characteristic of a subgroup of patients with bipolar disorder who respond well to lithium treatment.

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Hamakawa et al. (2004) reported that a reduced intracellular pH level in the euthymic state was replicated in the basal ganglia in an independent patient population using a head coil and outer volume suppression method, which can detect the MRS signals from three-dimensional regions without using phase encoding. Surprisingly, reduced pH level was also seen in the ‘‘whole-head’’ spectra, suggesting that a reduced pH level might reflect the metabolic abnormality at the cellular level rather than reduced activity of a specific brain region. The biochemical process causing a reduced intracellular pH level in bipolar disorder is not known yet. C. Findings in 1H-MRS Hamakawa et al. (1999) tried to replicate the reduced PCr using proton MRS and reported that the Cr–PCr level was decreased in the frontal lobes of patients with bipolar disorder. Although the reduced Cr level in the frontal lobes of patients with bipolar disorder was not replicated in subsequent studies (Cecil et al., 2002; Moore et al., 2000a,b; Winsberg et al., 2000), reduced Cr in the hippocampus was reported (Deicken et al., 2003). A reduction in N-acetyl aspartate (NAA) was reported in the frontal cortex (Cecil et al., 2002; Winsberg et al., 2000) and the hippocampus (Bertolino et al., 2003; Deicken et al., 2003). The biochemical background of reduction of NAA has not been identified yet, but it suggests some abnormality in neuronal integrity. NAA reportedly increased after lithium treatment (Moore et al., 2000b; Silverstone et al., 2003). This was assumed to reflect the neuroprotective eVects of lithium. In 2004, Dager et al. reported that lactate was increased in the brains of drugfree patients with bipolar disorder, suggesting mitochondrial dysfunction in bipolar disorder.

III. Near-Infrared Spectroscopy

A. Cerebrovascular Response to Cognitive and Physiological Tasks Several findings suggest that intracellular pH level may be related to altered vascular regulation; reduced pH was reported in subarachnoid hemorrhage (Brooke et al., 1994), hypoperfusion of the frontal cortex was reported in some neuroimaging studies of patients with bipolar disorder (Strakowski et al., 2000), and reduction of pH level was significantly associated with white matter hyperintensity (WMH) (Kato et al., 1998b). Thus, we speculated that impaired vascular regulation might be one possible cause of reduced pH level.

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For this purpose, we measured the cerebral vasoreactivity to verbal fluency task (VFT) in the left frontal cortex of euthymic patients with bipolar disorder using one-channel near-infrared spectroscopy (NIRS). The response to the VFT was significantly attenuated in patients with bipolar disorder (Matsuo et al., 2002). Other studies using functional magnetic resonance imaging showed inconsistent results on the hemodynamic response to cognitive stimuli (Strakowski et al., 2000). Some studies showed reduced response, whereas others showed increased response. However, the vascular response to a ‘‘frontal lobe task’’ such as the VFT could be aVected by cognitive disturbance in patients with bipolar disorders, which may confound the results. Measurement of the response to chemical stimuli can assess vascular response, eliminating the eVects of cognitive factors. Thus, we applied the hyperventilation task to the patients. In addition to the reduced response to the VFT, response to hyperventilation also showed a tendency to decrease in patients with bipolar disorder (Matsuo et al., 2002). To rule out the possible alteration of cerebral lateralization and the eVects of reduced eVort to hyperventilation in the patients, Matsuo et al. (2002) used a multichannel NIRS system, and other physiological parameters were simultaneously measured in a subsequent study (Matsuo et al., 2004). Reduced response to VFT was replicated in both frontal lobes. A slight but nonsignificant trend of lower response to hyperventilation was observed in patients with bipolar disorder. However, this might be due to the smaller eVort for hyperventilation, because the diVerence in oxygen saturation after hyperventilation was significantly smaller in patients with bipolar disorder. To assess vascular response to chemical stimuli without being aVected by the patients’ eVort, Matsuo et al. (2004) started a study to measure carbon dioxide (CO2)–induced vasodilation using NIRS. The preliminary analysis showed that response to CO2 was reduced in drug-free patients with major depression, which was correlated with the WMH (Matsuo et al., 2004). This suggested that one possible cause of reduced intracellular pH level was altered vascular regulation. However, such an alteration of vascular regulation alone cannot explain decreased intracellular pH level in the brains of patients with bipolar disorder, because there was no significant decrease in pH level in patients with major depression (Kato et al., 1992), although altered vascular response was a common finding in bipolar disorder and major depression (Matsuo et al., 2002).

B. Pathophysiological Implication of Altered Cerebrovascular Response in Mood Disorders NIRS mainly measures blood volume in microvessels, rather than larger vessels. The mechanism of activity-dependent cerebrovascular regulation in microvessels has not been well elucidated yet. A finding by Zonta et al. (2003)

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suggests that astrocyte calcium signaling plays an important role in the dilation of microvessels. Astrocyte dysfunction is postulated in bipolar disorder based on the findings of reduced serum levels of S100 (Schroeter et al., 2002), reduced number of glial cells in the postmortem brains (Ongur et al., 1998; Rajkowska et al., 2001), and altered gene expression of aquaporin-4 encoding water channel that is expressed on the end feet of astrocyte and regulates the permeability of water at the blood–brain barrier (Iwamoto et al., 2004). Because calcium signaling abnormalities were reported in peripheral blood cells (Kato et al., 2003a; Yamawaki et al., 1998), altered astrocyte calcium signaling could be one of the causes of altered vascular regulation.

IV. Molecular Genetic Findings

A. Clinical Genetics In addition to the aforementioned findings suggesting mitochondrial dysfunction in bipolar disorder by 31P-MRS, another study suggested the role of mitochondria. Although the high number of mother-to-child transmissions of mood disorder is a traditional finding, McMahon et al. (1995) proposed a new explanation for this finding. By analyzing the pedigrees collected for linkage analysis, McMahon et al. (1995) found that the parent-of-origin eVect (POE) might be involved in bipolar disorder. The POE refers to the phenomenon that the sex of the parent transmitting the disease aVects the severity or age at onset of the oVspring (Kato et al., 1996; Lambert and Gill, 2002). These include more aVected mothers compared with aVected fathers, higher prevalence rate of mood disorder among maternal relatives compared with paternal relatives, younger age at onset in the proband with an aVected father compared with those with an aVected mother, and more maternally inherited pedigrees compared with paternally inherited pedigrees (McMahon et al., 1995). They suggested that this finding could be explained by mitochondrial transmission. Although some of these initial findings by McMahon et al. (1995) were not replicated by subsequent studies, this hypothesis facilitated the study of mtDNA in bipolar disorder.

B. What Is Mitochondrial DNA? mtDNA is a circular 16-kb molecule contained in cells in multiple copies. mtDNA is maternally inherited, except for a rare case with a mitochondrial myopathy caused by the mutation occurring on paternally transmitted mtDNA.

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Many diseases caused by mutations of mtDNA have been reported (Kato, 2001), including diseases caused by point mutations, such as MELAS syndrome and MERRF syndrome (i.e., myoclonus with epilepsy and with ragged red fibers), and the diseases caused by deletion such as CPEO, Kearns-Sayre syndrome (KSS), and Pearson’s syndrome. In these disorders, mutant mtDNA coexist with wild-type mtDNA. This phenomenon is referred to as heteroplasmy. Functional significance of these heteroplasmic mutations has been characterized using transmitochondrial hybrid cells (cybrids). On the other hand, functional consequences of homoplasmic mtDNA polymorphisms have not been elucidated. The other kind of mitochondrial disorder is caused by the point mutations of nuclear genes regulating mtDNA, which result in multiple deletions of mtDNA.

C. Mitochondrial DNA Polymorphisms=Homoplasmic Mutations McMahon et al. (2000) tried to examine their hypothesis that POE observed in bipolar disorder may be caused by maternal transmission of mtDNA mutations responsible for bipolar disorder. They sequenced whole mitochondrial genome in nine probands with bipolar disorder in the maternally transmitted bipolar pedigrees. They found four polymorphisms nominally significantly associated with bipolar disorder, including one nonsynonymous polymorphism in complex I, 10398A. However, after the correction of multiple testing, this association was not statistically significant. Kato et al. (2001) also screened mtDNA polymorphisms in 43 patients with bipolar disorder using the single-stranded conformation polymorphism method and found that only one polymorphism, 10398A, was significantly associated with bipolar disorder. The fact that these two studies using diVerent strategies gave the similar conclusion supported the significance of the 10398 polymorphism in bipolar disorder. Kato et al. (2003a) examined the relationship between calcium response to a proton ionophore, carbonyl cyanide m-chlorophenylhydrazone (CCCP), in lymphoblastoid cells obtained from patients with bipolar disorder and controls and found that calcium response to CCCP was diVerent between 10398 polymorphisms. This suggested that the 10398A polymorphism might alter mitochondrial calcium level. Washizuka et al. (2003a) reported that having mtDNA 10398A was associated with a positive lithium response. Another group (Kirk et al., 1999) also sequenced the whole mitochondrial genome in 25 patients with bipolar disorder. Although they did not find any polymorphism associated with bipolar disorder, they reported that closely related haplogroup was decreased in the patient group compared with controls, suggesting selection against maternal lineage in this disorder.

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Munakata et al. (2004) sequenced the whole mitochondrial genome in seven patients with bipolar disorder having comorbid signs and symptoms suggestive of a mitochondrial abnormality, such as ptosis or muscle weakness. Munakata et al. (2004) found a rare missense mutation, 3644T!C, in the complex I subunit (NDI), which was associated with bipolar disorder.

D. Mitochondrial DNA Deletions Another type of pathogenetic mtDNA mutation is the large-scale deletion, the type of mutation found in CPEO, KSS, and Pearson’s syndrome. Although a single deletion is usually sporadic, multiple deletions characterized by a mixture of various types of deletions are inherited in an autosomal dominant or recessive manner. Suomalainen et al. (1992) reported of a patient with CPEO who showed severely retarded depression before the onset of CPEO and had multiple deletions in the postmortem brain. This case report facilitated the study of the deletion in the brains of patients with mood disorders. Stine et al. (1993) examined the brains of patients with bipolar disorder and suicide victims using Southern blot analysis. However, no deletion was detected. Kato et al. (1997a) used semiquantitative polymerase chain reaction (PCR) to quantify the 4977bp deletion, one of the frequently seen deletions sometimes referred to as ‘‘common deletion,’’ in the same DNA samples as those used in the report by Stine et al. (1993). This analysis revealed that deletion was significantly increased in the brains of patients with bipolar disorder (Kato et al., 1997a). However, the level of the deletion was at most 0.6%. Because the energy defect could be observed only when the deleted mtDNA exceeds 50% (Porteous et al., 1998), this small amount of deletion does not seem to aVect mitochondrial function. However, it could not be ruled out that this could be a ‘‘tip of iceberg’’ of multiple deletions. Kakiuchi et al. (in press) studied the levels of the mtDNA using two TaqMan probes, one located in the frequently deleted region (ND4) and the other in the rarely deleted region (ND1) (He et al., 2002), to test whether the multiple deletions are accumulated in the brains of patients with bipolar disorder (Kakiuchi et al., in press). However, there was no significant alteration of ND4=ND1 ratio in the postmortem brains of patients with bipolar disorder. There is another possibility that a small amount of deletion can cause functional impairment as a dominant negative manner. In an attempt to identify those bipolar patients with subclinical CPEO, Kato and Takahashi (1996) examined the 4977bp deletion in leukocytes, showing that deletion was detectable by a nested PCR method in two patients with bipolar disorder. Increased levels of the 4977bp deletion were confirmed in one

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of these patients by semiquantitative PCR (Kato et al., 1997b). In addition, Kato and Kakiuchi (unpublished findings) used quantitative PCR analysis with TaqMan probes to quantify the multiple deletions in leukocytes of patients with bipolar disorder, which is suggestive of accumulation of multiple deletions in a subgroup of bipolar patients.

E. Mutations of Nuclear Genes Causing Multiple Deletions of mtDNA Mutations of nuclear genes causing multiple deletions of mtDNA were identified. These include Twinkle (mtDNA helicase) (Spelbrink et al., 2001), ANT1 (adenine nucleotide translocator-1) (Kaukonen et al., 2000), POLG (polymerase-) (Van Goethem et al., 2001), and WFS1 (Inoue et al., 1998). Although mutations of WFS1 cause Wolfram syndrome, others cause CPEO. Interestingly, comorbidity with mood disorders has been reported in the mutations of all these four genes (Mancuso et al., 2004; Siciliano et al., 2003; Spelbrink et al., 2001; Suomalainen et al., 1992; Swift et al., 1990). A pedigree with the ANT1 mutation, in which all aVected members had bipolar disorder before the onset of CPEO, supported the possible link between multiple deletions of mtDNA with bipolar disorder (Siciliano et al., 2003). In the case of WFS1, the probands with Wolfram syndrome were frequently comorbid with mood disorders (Swift et al., 1990). Furthermore, nonaVected carriers of the WFS1 mutation also have higher risk of suicide and psychiatric hospitalization (Swift et al., 1991). These findings suggest that multiple deletions due to mutations of nuclear genes can cause mitochondrial diseases, and one of their characteristic symptoms is mood disorder. Many studies of mutation screening of WFS1 in bipolar disorder have been reported, but the hypothesis that a significant portion of patients with bipolar disorder are heterozygous carriers of the WFS1 mutation was not supported (Evans et al., 2000; Furlong et al., 1999; Kato et al., 2003b; Middle et al., 2000; Ohtsuki et al., 2000; Serretti et al., 2003; Torres et al., 2001). There is no report of mutation screening of the other three genes causing multiple deletions of mtDNA.

F. Heteroplasmic Point Mutations of mtDNA There are many case reports that patients with MELAS syndrome had psychotic symptoms (Kato, 2001). The high frequency of comorbid depression was reported in patients with mitochondrial diabetes mellitus caused by the 3243 mutation of mtDNA (Miyaoka et al., 1997), and there is a case report of depression caused by the 3243 mutation (Onishi et al., 1997).

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Kato et al. (2001) screened the 3243 mutation in leukocyte DNA in 135 patients with bipolar disorder using the restriction fragment length polymorphism (RFLP) PCR method, but none of the patients had the mutation. However, a small amount of heteroplasmic mutation can be overlooked by RFLP PCR. In addition, such a heteroplasmic mutation should be examined in the brain. Further analysis of heteroplasmic point mutations in the brains of patients with bipolar disorder is needed.

G. Nuclear-Encoded Mitochondrial Genes Although some of the subunits of the mitochondrial electron transport chain are encoded in mtDNA, most of them are encoded in the nuclear genome. Because the mtDNA 10398 polymorphism alters an amino acid in the complex I (NADH dehydrogenase [ubiquinone]) subunit, nuclear-encoded complex I subunit genes may also be associated with bipolar disorder. Among the nuclear-encoded complex I genes, NDUFV2 is of particular interest, because it encodes one of the major complex I proteins and is located on chromosome 18p11, one of the replicated linkage loci. Washizuka et al. (2003b) screened mutations in all exons and exon–intron junctions but did not find any polymorphisms=mutations in patients with bipolar disorder. On the other hand, patients with bipolar I disorder showed significantly reduced messenger RNA (mRNA) expression in lymphoblastoid cells. Thus, Washizuka et al. (2003b) screened the upstream region of NDUFV2 and found that one polymorphism, 602A>G, was associated with bipolar II disorder, and the haplotype of the upstream region was significantly associated with bipolar disorder. Washizuka et al. (2004) further screened the upstream region of this gene and found the other polymorphism associated with bipolar disorder, 3542G>A. The association with the haplotype of these two polymorphisms was partly replicated in European American parents–proband trios obtained from the National Institute of Mental Health (NIMH). One of these SNPs, 602G>A, was found to alter promoter activity (Washizuka et al., 2004). Thus, polymorphisms of NDUFV2 were suggested to be a genetic risk factor for bipolar disorder. It was also found that NDUFV2 was downregulated in the postmortem brains of patients with bipolar disorder (Karry et al., 2004), as well as in the hippocampus of the animal models of depression (Nakatani et al., 2004). These findings suggest that NDUFV2 has an important role in the pathophysiology of bipolar disorder. Konradi et al. (2004) reported that expression levels of mitochondria-related genes were downregulated in postmortem brains of patients with bipolar disorder, suggesting mitochondrial dysfunction. A wide range of downregulation of genes related to the mitochondrial respiratory chain was replicated in the postmortem brains of bipolar disorder patients (Iwamoto et al., 2004). However,

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this finding was largely aVected by the medication. In drug-free patients with bipolar disorder, a small subset of mitochondrial genes was upregulated (Iwamoto et al., 2004).

V. Roles of Mitochondrial Calcium Regulation

Although these neuroimaging and molecular genetic studies suggest possible roles of mitochondrial dysfunction in bipolar disorder, how mitochondrial dysfunction relates to the pathophysiology of bipolar disorder is still not clear. The mitochondrial electron transport chain generates a proton gradient across the mitochondrial inner membrane. This proton gradient is the source of the membrane potential across the mitochondrial inner membrane and a driving force of adenosine triphosphate (ATP) production by complex V, F1F0-ATPase. However, when the proton gradient is lost, F1F0-ATPase makes a proton gradient consuming ATP. Based on this unexpected behavior of F1F0-ATPase, it was revealed that the mitochondrial membrane potential is important not only for ATP production but also for uptake of calcium into the mitochondrial matrix. The mechanisms of the transport of calcium across the mitochondrial inner membrane have not been identified yet. Mitochondrial calcium uptake is mediated by two mechanisms: mitochondrial calcium uniporter and ‘‘rapid mode.’’ Although the mitochondrial calcium uniporter was physiologically characterized by organelle patch clamp (Kirichok et al., 2004), the molecule responsible for this function has not been identified. Cardiolipin, a mitochondria-specific phospholipid, is reported to have an important role in calcium uptake by mitochondria (Zazueta et al., 2003). The eZux of calcium from the mitochondrial matrix is mediated by the permeability transition pore (mtPTP) and the mitochondrial sodium calcium exchanger (mSCE). The molecule responsible for mSCE has not been identified. mtPTP is a complex that consists of proteins on the mitochondrial inner and outer membranes, which forms a large pore across both of these membranes (Sharpe et al., 2004). When this pore is opened, large proteins leak into the cytosol, resulting in apoptotic cell death. However, the physiological function of the brief opening of mtPTP has been postulated (PfeiVer et al., 2001). mtPTP consists of several proteins, voltage-dependent anion channel, cyclophilin D, porin, and the adenine nucleotide (adenosine diphosphate=ATP) translocator. Calcium in mitochondria is an important accelerator of mitochondrial enzymes and plays a part in mediating the apoptotic process. In addition, mitochondrial calcium uptake has been suggested to have a role in neuroplasticity (Ben-Shachar and Laifenfeld, 2004; Weeber et al., 2002). Knockout mice of porin, one of the important molecules for mtPTP, had an abnormality in fear

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Fig. 2. Mitochondria hypothesis of bipolar disorder.

conditioning, learning, and synaptic plasticity (Weeber et al., 2002). Pharmacological inhibition of mtPTP by cyclosporin A also impairs synaptic plasticity (Levy et al., 2003). The synaptic terminal and dendrite are rich in mitochondria, and some spines also contain mitochondria (Chicurel and Harris, 1992). Highfrequency stimulation causing long-term potentiation produces a selective increase in mitochondrial calcium uptake (Stanton and Schanne, 1986). These findings suggest that mitochondrial calcium regulation is important for neural plasticity. The role of neuroplasticity has been postulated in bipolar disorder (Manji and Duman, 2001). Altered mitochondrial calcium regulation due to mitochondrial dysfunction may cause a subtle alteration of neural plasticity and finally bipolar disorder (Fig. 2). When Bcl-2, an antiapoptotic protein on the mitochondrial outer membrane, is overexpressed, the IP3-mediated calcium response in mitochondria is reduced (Pinton et al., 2000) and synaptic stability is changed (Jonas et al., 2003). Because both lithium and valproate upregulate Bcl-2 (Chen et al., 1999), mitochondrial calcium levels may be altered in patients with bipolar disorder, which is improved by mood stabilizers.

VI. Conclusions

In this chapter, we have introduced the evidence suggesting mitochondrial dysfunction in bipolar disorder and presented a hypothesis that altered mitochondrial calcium regulation causes impaired neural plasticity, which results in bipolar disorder. Further studies will clarify the role of mitochondrial dysfunction in bipolar disorder.

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LARGE-SCALE MICROARRAY STUDIES OF GENE EXPRESSION IN MULTIPLE REGIONS OF THE BRAIN IN SCHIZOPHRENIA AND ALZHEIMER’S DISEASE

Pavel L. Katsel, Kenneth L. Davis, and Vahram Haroutunian Department of Psychiatry, The Mount Sinai School of Medicine New York, New York 10029

I. Introduction II. Gene Expression Profiling Using Microarrays: Technologies Overview A. Data-Mining Strategies B. Reproducibility of the Data III. Postmortem Brains and Gene Expression Studies A. Agonal State B. Postmortem Interval C. Tissue Fixation and Storage D. Tissue pH E. Age of Subjects at Death F. Gender G. Medication and Substance Abuse IV. Comparison of Gene Expression Profiles among Normal Brain Regions V. Gene Expression Profiles of Brain Regions in Alzheimer’s Disease VI. Gene Expression Profiling in Schizophrenia VII. Future Perspectives References I. Introduction

It took about 13 years to complete the working draft map of the human genome. More than 1 million expression sequence tags have been catalogued, corresponding to an estimated 31,000 protein-encoding human genes (Baltimore, 2001). However, the function, regional expression, and regulation of most of these genes have yet to be determined. The assignment of the molecular and cellular functions of these genes will likely be elaborated in the continuation of the Human Genome Project. Two major approaches to determine functions of gene products at the nucleic acid level are used. The structural approach is based on ascertainment of homologies of sequence-specific motifs encoding structural domains, thus providing clues to gene function. The second approach for exploring the functions of gene products is by determining the expression patterns of the genes of interest and attributing functions based on known expression patterns. Although numerous studies have been performed to establish expression patterns for individual genes INTERNATIONAL REVIEW OF NEUROBIOLOGY, VOL. 63

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or groups of genes, analysis of available expression data has not yet reached the point to permit assignment of specific gene expression signatures to specific functions in most cases. In addition to classic molecular biology methods for establishing expression profiles from single gene to several more genes, such as Northern blots, RNAse protection assays, and so on, a major advance in the past decade has been the development of high-throughput technologies that permit simultaneous expression profiling of thousand or tens of thousands of genes. These methods include diVerential display, serial analysis of gene expression (SAGE), and arraybased technologies, consisting of complementary DNA (cDNA) and oligonucleotide microarrays. The last two methods allow simultaneous analysis of the expression of thousands of transcripts providing static information about gene expression (tissue, cell, and time point) and dynamic information (relationship of the expression pattern of a single gene, or a set of genes, to the expression patterns of other genes). These technologies provide powerful tools for neuroscientists that oVer the potential to elevate the molecular genetic approach to the systems level for studying the human brain in normal and pathological states. A quick overview of publications related to the use of microarrays in neuroscience shows that from the initial array-related publication year 1999, the number of published reports increased 10-fold by 2001 and 20-fold by 2003 (Fig. 1). Knowledge of regional gene expression patterns of the human brain is essential to understanding the molecular biology of normal and pathological brain function and physiology. DiVerences in gene expression can reflect morphological and phenotypic diVerences while indicating cellular responses to signaling elicited by environmental stimuli. Unlike the genome, transcription

Fig. 1. Microarray-related publications in neuroscience.

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profiles are highly dynamic, changing relatively rapidly in response to internal and external environmental stimuli or even to pre-programmed events such as cell cycle programs and apoptosis. These alterations of gene expression patterns can help identify ‘‘candidate’’ genes associated with pathophysiological processes in the human brain and can provide an exciting new avenue for research on psychiatric and neurodegenerative disorders. In this chapter, we assess the status of microarray technology and datamining strategies as they relate to the analysis of postmortem brain with a focus on schizophrenia (SZ), Alzheimer’s disease (AD), and tissue- and donor-quality requirements.

II. Gene Expression Profiling Using Microarrays: Technologies Overview

The core principle of microarrays and many other molecular biology techniques is hybridization between pairs of nucleic acids, where one member of the pair is immobilized onto a solid surface. In classic methods such as Northern or Southern blotting, samples derived from the tissues of interest are separated and immobilized on membranes, and the abundance of specific DNA or RNA transcripts is estimated by hybridization to specific probes. Oligonucleotide and cDNA arrays modify this approach in several significant ways. Most importantly, the sample–probe relationship is reversed. In oligonucleotide arrays, thousands of gene-specific complementary polynucleotides (15–60 nt) are derived from the 30 end of messenger RNA (mRNA) transcripts and are individually arrayed (immobilized) onto a solid matrix. Sample RNA is then applied to this array and hybridization to each of the immobilized probes is quantified simultaneously. AVymetrix GeneChip arrays are the most popular oligonucleotide arrays used by researchers worldwide. The GeneChip probe is typically composed of a set of polynucleotides (25 nt each) for each transcript of interest consisting of 11–20 probe pairs carefully chosen to correspond to sequence regions proximal to the 30 end (the tiled region) of the targeted gene. Each probe pair is composed of a perfect match (PM) polynucleotide complement to the ‘‘tiled region’’ and a mismatch (MM) polynucleotide complement, which is the same as the PM polynucleotide with one MM base in the middle (13th nt). The purpose of this PM and MM pairing is to use hybridization to the MM sequence as a measure of nonspecific hybridization. This matrix, containing probes to tens of thousands of expression sequence tags, is then probed with fluorescently tagged cDNA representation or cRNA derived from the specimen under study. This scheme permits the simultaneous quantitation of the expression level of tens of thousands of genes present in the sample of interest. Not surprisingly, the wealth of data generated from even a single experimental sample poses significant data analysis

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and data-mining challenges. Some of the nascent data-mining strategies that have been developed for the analysis of data derived from these kinds of arrays are discussed later in this chapter. GeneChip arrays represent only one of several conceptually similar approaches that have been developed for high-throughput gene expression analysis. Complementary DNA arrays represent a second popular approach in which polymerase chain reaction (PCR) products (between 0.6 and 2.4 kb) representing specific genes are spotted and immobilized on solid matrices. The arrays are then probed with fluorescently tagged cDNA representation of RNA pools from test and reference samples (e.g., experimental and control samples). Quantification of relative message abundance is based on a direct comparison between the ‘‘test’’ and ‘‘reference’’ samples, thus providing an internal control for the measurement. The quality and reproducibility of data from these cDNA arrays are highly dependent on the quality of the cDNA clone collections used to construct the arrays. Additionally, to date, cDNA arrays require relatively greater amounts of hybridization RNA for screening of large cDNA arrays (10,000–20,000 cDNA) (Becker et al., 2002), limiting the range of experimental circumstances under which they can be optimally used. The targets in both GeneChip and cDNA arrays are labeled single-strand representations of cellular mRNA pools. A serious limitation of the application of these techniques is the relatively poor detection limit of labeled RNA, which requires substantial amounts (2–200 g) of extracted RNA for hybridization. In the case of the analysis of brain-derived specimens, this means that RNA must be isolated from relatively large amounts of tissue, which in turn limits the analysis of gene expression to homogenates derived from multiple cell types. To overcome this limitation, methods of linear amplification of RNA (from cDNA) using RNA polymerases have been developed (Lockhart et al., 1996; Phillips and Eberwine, 1996; Van Gelder et al., 1990). These methods, however, introduce the risk of misrepresenting the quantity of low-abundance mRNAs in the initially extracted mRNA pool, making it diYcult to draw strong conclusions regarding the relative abundances of the expression of diVerent specific RNAs in the same sample. The development of methods for the detection of low-abundance transcripts continues to be an active area of research and development. The success of such approaches is pivotal to the eVective application of microarray technologies to the analysis of discrete cellular populations and subcellular fractions.

A. Data-Mining Strategies Prior to data analysis, normalization of microarray data is a critical step to standardize variations resulting from array fabrication and the hybridization procedures. Several methods of normalization have been used, including those

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that are based on normalizing to the expression level of ‘‘housekeeping’’ genes, global normalization to overall gene expression in the entire array, spike-in controls, and dilution series (Li et al., 2002). AVymetrix Microarray Suite version 5.0 (MAS 5.0) and DNA Chip Analyzer version 1.3 (dChip 1.3) are two of the most popular methods used for analyzing hybridization results from high-density oligonucleotide-based microarray experiments. Irizarry et al. (2003) developed a method known as robust multiarray average (RMA) and compared it to the AVymetrix MAS 5.0 and dChip 1.3 methods using data generated from AVymetrix GeneChip–based experiments. The RMA method had better precision for lower expression values, resulting in up to a fivefold reduction of replicate variance as compared to dChip 1.3 or MAS 5.0. Additionally, RMA had high specificity and sensitivity for fold-change analysis for the detection of diVerentiated transcripts. Thus, in general, analysis of low-level data using widely used methods such as MAS 5.0, dChip 1.3 PM-MM and PM-only models, and RMA has shown that model-based methods using dChip PM–only probes and RMA consistently gave less variable results (Galfalvy et al., 2003; Han et al., 2004; Irizarry et al., 2003). MAS 5.0, on the other hand, appeared to be more accurate for moderate foldchange values but was found to be biased toward the null (fold change ¼ 1) at larger fold-change values. Better performance of RMA was later reproduced in a separate study, although for some tasks, it did not outperform the dChip method (Han et al., 2004). A good way to compare diVerent methods of normalization, expression index computation, and downstream methods is to compare the obtained results against other accurate mRNA expression level analysis methods, such as the spike-in concentration methods for a spectrum for selected genes or independent expression measurement validation using methods other than microarray hybridization, such as real-time RT-CPR, or Northern blot analysis of specifically identified transcripts (Li and Hung Wong, 2001). An alternative approach that uses a set of sex chromosome–linked genes as an internal standard for the assessment of the quality of the data and for setting the statistical criteria of diVerentially expressed genes has been introduced (Galfalvy et al., 2003). This method is applicable to all microarray studies that include male and female subjects. Data derived from microarrays are useful for predicting or dissecting the probable roles of transcripts of known and previously unknown function. Clustering techniques (Eisen et al., 1998) provide one approach toward data reduction and grouping of genes within unbiased statistically defined functional units. This group of methods has been well developed over the past several years. Clustering techniques are based on exploratory multivariate statistical methods that attempt to find ‘‘natural’’ groupings of variables, gene expression values in the context of microarray data mining, based on the degree of association in the expression levels of gene. One end result of cluster analysis is a cluster image display containing dendrograms (tree diagrams) that show the grouping of arrays and

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genes according to the degree of their association, such that the degree of association is strong between members of the same cluster and weak between members of diVerent clusters. Thus, families of genes can be identified based on the closeness of association in their expression levels. Genes whose expression values cluster together in microarray experiments are assumed to have similar molecular functions or to subserve similar functional systems. This assumption has been confirmed in the number of microarray studies (Eisen et al., 1998; Miki et al., 2001; Nishizuka et al., 2002). For example, in one study of SZ (Hakak et al., 2001), seven genes clustered closely together and were downregulated in their expression levels in SZ. Analysis of these closely clustered genes indicated that they were all related to functions involving myelination. Clustering methods can be divided into two classes: supervised and unsupervised (Eisen et al., 1998). In supervised clustering, vectors are classified with respect to known reference parameters. When no external reference is used in clustering, it is called unsupervised clustering. Because we have little knowledge of the expected gene expression pattern for most conditions, the unsupervised clustering method is often favored. Expression data can be clustered in two ways: hierarchical and nonhierarchical. Hierarchical clustering allows detection of high-order relationships between clusters of profiles, whereas most nonhierarchical classification methods work by allocating expression profiles to a predefined number of clusters, with no assumptions regarding intercluster relationships. Aggregative hierarchical clustering variants (Eisen et al., 1998) such as average, single, and complete linkage are still the most common choices for the analysis of gene expression patterns. A typical aggregative hierarchical clustering output represents data in the shape of a binary tree where the most similar patterns are clustered in a hierarchy of nested subsets (Sokal and Michener, 1958). Nonhierarchical methods such as quality clusters or k means are used as an alternative to hierarchical clustering. These algorithms use a predefined number of clusters (much like predefined numbers of factors in factor analysis methods) and iterative reallocation of cluster members to minimize the overall intracluster dispersion (Tamames et al., 2002). The main disadvantage of standard hierarchical and nonhierarchical clustering methods is that they work very slowly when tens of thousands of transcripts are to be analyzed. Neural networks have been proposed to overcome this problem (Herrero and Dopazo, 2002; Herrero et al., 2001; Oliveros et al., 2000; Tamayo et al., 1999). Unsupervised neural network algorithms, such as selforganizing maps (SOM) (Kohonen, 1999; Kohonen and Somervuo, 2002) and the self-organizing tree algorithm (SOTA) (Herrero et al., 2001; Wang et al., 1998) provide robust frameworks appropriate for clustering a large amount of data. Among the main disadvantages of SOM and SOTA are the arbitrary fixed numbers of clusters that must be defined similar to k-means methods. In addition, over-represented artifactual profiles, frequently present in array results, tend to

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produce an output in which these types of profiles populate the vast majority of clusters. Consequently, potentially interesting profiles tend to map into only a few clusters, causing decreased resolution of these clusters (Tamames et al., 2002). A number of statistical methods can be used as defining criteria for significance of gene expression alterations of the identified ‘‘candidate genes.’’ These include simple two-group comparison methods such as t tests or Wilcoxon tests. However, because microarray output consists of data for thousands of transcripts, it raises the possibility of increased false discovery rate and type I error. To minimize the false discovery rate in the detection of candidate genes, other selection criteria and statistical methods can be implemented, including, for example, combinations of statistical methods with a fold-change algorithm or examining microarray expression data against a prespecified contrast model (contrast analysis) (Neter et al., 1996). A regression analysis can also be used when more than two groups are compared. Multiple covariants, such as diagnosis, medical treatment, or substance abuse, age, gender, and tissue factors (mentioned in the next chapter) can also be added (Bunney et al., 2003) to the regression model. Fold-change algorithms have been used traditionally as an index of the magnitude of diVerences in gene expression levels between groups of samples. DiVerent stringency filtering conditions can be used to identify a subset of diVerentiated genes that change with conventionally accepted levels of statistical reliability (e.g., p .05). Under low-stringency filtering conditions, a set of diVerentiated genes incorporate transcripts with lower fold-change amplitude compared to high-stringency conditions. The low-stringency method reduces the risk of type II errors (errors of omission) at the expense of type I errors (errors of commission). Thus, the downside of the low-stringency filtering conditions is the possibility of an elevated false discovery rate, whereas high-stringency strategies increase the risk of missing true between group diVerences (type II errors) in gene expression (Blalock et al., 2003). Low-stringency filtering approaches have some important advantages over the high-stringency conditions. For example, the probability of detection of larger numbers of functionally related genes is increased, providing a more comprehensive picture of the associated processes and pathways (Blalock et al., 2003). The type I error risk can then be overcome by replication and the use of other techniques to confirm or reject hypotheses generated by the ‘‘first-pass’’ microarray approach (see later discussion). Selected transcripts that meet user-determined criteria can also be linked to gene ontology (GO), pathway identifier, genome, and protein-related databases for quick, albeit potentially inaccurate, characterization. Development of methods to extract the functional information from multiple available sources is extremely complex, especially for experiments performed on genomewide DNA chips, and has received relatively little attention. A number of web sites have been developed to aid in the identification of functional attributes and

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include DAVID, database for annotation, visualization, and integrated discovery (http:==david.niaid.nih.gov=david=upload.asp); NCBI (http:==www.ncbi.nlm.nih. gov); the NINDS=NIMH Microarray Consortium (http:==arrayconsortium. cnmcresearch.org); Gene Ontology Consortium (http:==www.geneontology.org= index.shtml); Bioconductor (http:==www.bioconductor.org); and a joint project between EMBL and the Sanger Institute, Ensembl (e!) (http:==www.ensembl.org=). For GO analyses, the functional attributes of each gene or gene product fall into three major categories according to the Gene Ontology Consortium: (1) molecular function, (2) cellular components–localization, (3) biological processes– physiological pathways. A number of studies have taken advantage of GO analysis to better understand changes resulting from gene expression profiling of the brain in healthy and pathological states (Kobayashi et al., 2004; Pavlidis et al., 2004).

B. Reproducibility of the Data Reproducibility is one of the most important factors in gene expression array experiments. The reproducibility of data is aVected by multiple factors, ranging from variability in array fabrication, diVerences in transcript segments probed, sample RNA preparation, and hybridization conditions to image acquisition and image processing. To address intersubject variability, as with other assays, replication (multiple numbers of samples of each type) is an important feature of array experiments. Replication can take several forms, including running the same samples on diVerent microarrays of the same or diVerent platform type (i.e., cDNA based and oligonucleotide based). The most robust, albeit often impractical, approach is to employ all of the forms. As with other experimental approaches, the larger the sample size, the greater the power of statistical analyses and the lower the chance of both type I and type II errors. A second approach to replication is to repeat the same microarray study in an independent sample of cases and accept as true only those gene expression changes that are reproduced in both independent samples. Finally, replication of gene expression results for targets of interest using a completely diVerent methodology, such as Northern blot analysis of quantitative reverse transcriptase PCR (RT-PCR) is a highly favored and recommended approach. The serious challenge in microarray data analysis is the assessment of reliability of measurement. Because of the need to perform multiple procedures or steps in microarray experiments, the risk of random and systematic errors is very high. A number of reports have noted variability that arises from day-to-day changes, even if experiments are carried out by the same technician using the same equipment and identical conditions. When sources of variability were

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investigated, which included sample-to-sample variation, daily eVect, and residual variations, more than 59% of the variability came from daily eVects and residual variability, regardless of the method of analysis (MAS 5.0, dChip, and RMA), with up to 11% due to day-to-day variations alone (Han et al., 2004). Even minor diVerences in protocol or conditions tended to add significant noise to the system and internal consistency. These findings suggest that to avoid biases due to day-to-day variations experiments must be designed to take such variability into account and distribute cases and test conditions evenly across study days. Pooling of RNA samples from diVerent cases and controls is another alternative solution to reducing variability and defraying the total cost of an experiment (Peng et al., 2003). For example, one study suggested that by increasing the number of subjects in the pool, the number of arrays used can be reduced without significantly reducing analytical precision (Kendziorski et al., 2003). Pooling is most advantageous when biological variations are considered larger than the variations attributable to technical factors. Pooling, however, should not be used when the goal of the research is to correlate gene expression with some other variables measured at the subject level or to identify gene profiles that help classify individual subjects and predict their group allocation. Pooling may also result in the loss of the data on variables that may have been ignored initially.

III. Postmortem Brains and Gene Expression Studies

One of the most significant applications of microarray technologies has been in studies aiming to determine gene expression profiles in the normal human brain and in pathological states such as AD, SZ, and bipolar disorder (Blalock et al., 2004; Colangelo et al., 2002; Geschwind, 2003; Ginsberg et al., 2000, 2004; Hakak et al., 2001; Iwamoto et al., 2004; Kim et al., 2003; Li et al., 2002; Middleton et al., 2002; Mirnics et al., 2001a,b; Pasinetti and Ho, 2001; Paulson et al., 2003; Pongrac et al., 2002; Ruotolo et al., 2003; Tkachev et al., 2003; Vawter et al., 2001). As discussed earlier, the core principle of microarray analysis is nucleic acid hybridization, which requires that reasonably intact RNA be recoverable from the test specimens. RNA structural integrity is usually assessed by the proportion of high-molecular-weight RNA, which is usually measured=expressed as the ratio of 28S:18S ribosomal RNA. A 28S:18S ratio of 2.0 is considered indicative of high-quality intact RNA. Ribosomal RNA ratios of 2.0 are virtually impossible to achieve in isolates from postmortem human tissue samples. In fact, isolated total RNAs with rRNA ratios greater than 1.0 can provide good-quality intact mRNA, and such isolates perform well in various

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applications, including microarray analyses. It should also be kept in mind that intact ribosomal RNA does not always signify intact mRNA in a sample. A number of reports have demonstrated the feasibility of using mRNA extracted from postmortem brain tissues for molecular cloning, construction of libraries and translation assays, indicating that RNA transcripts can be suYciently preserved for many types of studies, including microarray analysis (de Sauvage and Octave, 1989; Gilbert et al., 1981; Johnson et al., 1986; Octave et al., 1988; Soreq et al., 1986; Vitek et al., 1988). Here, we provide an overview of the factors that may influence the integrity and yield of RNA extracted from autopsy brain tissues.

A. Agonal State Premortem factors such as rapidity of death and agonal state do not significantly aVect the overall yield of RNA from autopsy tissues (Cummings et al., 2001; Harrison et al., 1991; Perrett et al., 1988) but can significantly influence the integrity of RNA and the integrity of specific transcripts (Guillemette et al., 1986; Harrison et al., 1995; Tomita et al., 2004). Hypoxia is one of the key agonal events (Hynd et al., 2003) that aVect RNA quality. Prolonged hypoxia increases tissue lactate, which lowers pH level (Hardy et al., 1985; Perry et al., 1982). Induced brain acidosis might influence RNA in two ways: by aVecting gene transcription and by aVecting the integrity of mRNA through activation of acid ribonucleases. Though not extensively documented, brain tissue pH level may aVect cell integrity and gene expression diVerently in diVerent cell types (e.g., glia vs neurons). For example, oligodendrocytes are known to be particularly vulnerable to hypoxia and acidosis (Lyons and Kettenmann, 1998). The oligodendrocyte RNA pool comprises a significant proportion of the total RNA pool of gray matter, and its degradation might cause divergences in gene expression profiles (Mirnics et al., 2001a). In addition, degradation of mRNA due to the other factors that are associated with agonal state (e.g., pyrexia, hypoglycemia, dehydration, and hypertension) (Hardy et al., 1985) might be facilitated in some cell types relative to others. Heat shock protein 70 mRNA, for example, is apparently degraded in neurons several times more rapidly than in glia (Pardue et al., 1994). Other terminal event=transcript vulnerabilities have also been documented. For example, a significant diagnosisindependent inverse correlation between the amount of M1 muscarinic receptor mRNA and the duration of terminal coma was reported in an in situ hybridization study of human brain (Harrison et al., 1991). Thus, it is important (1) to eliminate from study samples derived from subjects with protracted agonal states; (2) to use statistical covariate techniques to control for variability resulting from invariable diVerences in agonal state; and (3) to match case and control

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cases on tissue pH and on as many other agonal state and cause-of-death variables as possible.

B. Postmortem Interval The delay between death and tissue collection and preservation is referred to as the postmortem interval (PMI). Typical PMIs for samples used in neurobiological studies range from 4 to 36 hours (Hardy et al., 1985). PMI does not appear to significantly aVect the recovery of total RNA or mRNA (Castensson et al., 2000; Johnson et al., 1986; Preece and Cairns, 2003). Although it is accepted that PMI may critically aVect the preservation of some brain neuropeptides and neurotransmitters (Arranz et al., 1996; Dodd et al., 1988; Palmer et al., 1988; Thorsell et al., 2001), most transcripts are remarkably stable postmortem (Barton et al., 1993; Godfrey et al., 2000; Harrison, 1996; Johnston et al., 1996; Perrett et al., 1988). PMI seems to have relatively minor eVects on gene expression profiles in microarray studies (Bahn et al., 2001; Tomita et al., 2004). Other studies, however, have suggested ongoing (for up to 46 hours) prominent upregulation of transcripts involved in protein biosynthesis, oxidative stress, and apoptosis in autopsy samples from skeletal muscles when compared to surgically removed samples (Sanoudou et al., 2004). This PMI eVect does not seem to necessarily generalize to all organ systems because in samples from human brain derived at autopsy, out of 16 analyzed transcripts, only mRNA levels of the CYP26A1 gene, which belongs to the cytochrome P450 superfamily, showed significant change associated with prolong PMIs (Castensson et al., 2000). It should also be kept in mind that individual mRNA transcripts demonstrate intrinsic decay rates ranging from a few minutes to days (Tourriere et al., 2002). The decay of mRNA is controlled by decapping and de-adenylation, as well as by diVerent trans-acting factors interacting with cis elements within mRNAs, such as AU-rich regions (AREs) containing AUUUA repeats. Additionally, as mentioned earlier in this chapter, the degradation of the same transcript may be more robust in some cell types than in others (Pardue et al., 1994). As estimated in a microarray study of mRNA decay rates in two human cell lines, transcription factor mRNAs were among the ‘‘fast-decaying’’ mRNAs with half-lives less than 2 hours. In contrast, biosynthetic protein mRNAs had significantly slower average decay rates (Yang et al., 2003). The average estimated half-life of most mRNAs is on the order of hours (Hargrove and Schmidt, 1989). Thus, RNA seems less aVected by PMI, with possible inactivation of its normal processes of degradation resulting from rapid energy depletion (adenosine triphosphate [ATP] decrease) following death (Barton et al., 1993).

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C. Tissue Fixation and Storage Appropriate tissue preservation and storage are prerequisites for meaningful results from gene expression studies. Appropriate fixation and storage of tissue specimens ensures maximal retention of biochemical, molecular, and structural integrity of autopsy tissue. Traditional methods, such as formalin-fixed paraYnembedded tissue blocks have been intensively evaluated for nucleic acid isolation by classic molecular biology techniques. Even though some partial degradation of RNA and DNA from paraYn-embedded tissue blocks has been demonstrated, mRNA has often been suYciently preserved to allow gene expression analysis by RT-PCR, Northern blots, RNase protection assay and by in situ hybridization (Godfrey et al., 2000; Jackson et al., 1990). A large number of novel fixatives for tissue preservation are commercially available, and many have been evaluated for their utility for downstream applications involving RNA analysis (Van Deerlin et al., 2002). It is generally acknowledged, however, that higher yields of RNA should be expected from frozen tissue than from fixed tissues (Barton et al., 1993; Johnson et al., 1986). Another limiting factor is the potential degradation of RNA after prolonged storage of frozen tissues. Some data suggest that after freezing, RNA undergoes some degradation compared to unfrozen tissue, as indicated by the formation of breakdown products of 28S rRNA (Ross et al., 1992). One evaluation of the ‘‘shelf life’’ of frozen brain tissue found that 5 years of storage at 70 C may compromise use of mRNA for library construction, but that full- or partial-length transcripts can be extracted and amplified by RT-PCR for subsequent analysis (Leonard et al., 1993). Thus, transcript analysis–grade RNA appears to be stable over an extended number of years (15 years) if maintained at low temperatures without thawing (Yasojima et al., 2001). In summary, these studies have shown that reliable mRNA expression data may be obtained from the postmortem brains with even relatively long autolysis times if the tissue has been stored frozen at low temperatures without thawing and if agonal state and acidosis were not severe. Although tissue fixation may not severely hamper gene expression analysis, better quality RNA and higher RNA yields are achieved in postmortem brain specimens if they are snap frozen soon after death.

D. Tissue pH As mentioned previously, alterations in brain pH level can occur as a consequence of processes associated with agonal state, such as hypoxia or cerebral ischemia (Wester et al., 1985). Presumably, mRNA should be very vulnerable to the lower pH level because of the activation of acid RNases (Barton et al., 1993).

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Brains from subjects who died after terminal illnesses with protracted agonal states have been found to have lower pH levels and to possess a high concentration of lactate than brains from subjects with sudden death (Hardy et al., 1985; Perry et al., 1982; Yates et al., 1990). No significant diVerences in pH level appear to exist between diVerent brain regions (Johnston et al., 1997), and pH has been found stable during PMI and long-term storage while frozen (Harrison et al., 1995; Ravid et al., 1992). Thus, pH level can serve as a relatively convenient surrogate for agonal state and as an indicator or screening tool for potential RNA quality. Although no significant correlation between the brain pH level and the total RNA yield has been found (Preece and Cairns, 2003), evidence for RNA vulnerability to low pH level has been observed (Harrison et al., 1995; Kingsbury et al., 1995). Thus, avoiding tissues with low pH level and matching tissue pH level across comparison groups is advisable for microarray studies on autopsy brain samples. However, pH level should not necessarily serve as an indicator only of poor agonal state because in autopsy tissues from subjects with neurodegenerative disorders, pH level change may be associated with increased gliosis—a hallmark of neurodegeneration—and may be a reflection of the very disease process that is under study (Isacson and Sofroniew, 1992; Yates et al., 1990).

E. Age of Subjects at Death Alterations in gene expression occur in a range of human central nervous system (CNS) diseases, particularly in those that are age related. Few data on the relationship between nucleic acid stability and age at death are available. There is a correlation between DNA stability and age (Kinzinger and Holtz, 1992). Moreover, DNA fragmentation as a process associated with apoptosis is increased with age (de Luca et al., 1996; Mukherjee and Adams, 1997; Tompkins et al., 1997). Zinc ions bioavailability is also limited with aging, and this limitation can promote apoptosis (Erickson et al., 1997; Giacconi et al., 2003; Giannakis et al., 1991; Mocchegiani et al., 2001; Saito et al., 2000). In addition to being a modulator of synaptic transmission and cellular signaling (Li et al., 2003; Weiss et al., 2000), Zn2þ appears to be a important regulator of gene transcription, and its limited availability may decrease expression of numerous genes containing regulatory cis elements for zinc-containing transcription factors in their promoter regions (Czupryn et al., 1992; Hechtenberg and Beyersmann, 1993). Studies in the rat have shown an age-dependent increase in brain acid RNase activity, which can be due to increased levels of the enzyme or the degenerating lysosomes with age (Alberghina and GiuVrida Stella, 1988a,b). Significant negative correlations were found between age at death and -actin mRNA levels (Preece and Cairns, 2003). These eVects of age should not necessarily be viewed

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as sources of experimental artifact, rather they appear to be aspects of natural development and aging. Thus, although postmortem RNA abundance and stability may change as a function of the age of the subject, measures to match cases and controls as closely as possible for age should help avoid experimental artifacts introduced by age.

F. Gender Gender diVerences may aVect brain gene expression profiles in the brain (Iwamoto et al., 2004; Vawter et al., 2004a). Gender-specific genes residing on X and Y chromosomes that undergo inactivation are frequently among the most diVerentiated transcripts when groups not closely matched for sex are compared (Katsel and Haroutunian, unpublished data; Vawter et al., 2004a). Strong alterations of expression levels of genes that escape X or Y inactivation have been also demonstrated in humans (Chowers et al., 2003; Galfalvy et al., 2003; Iwamoto et al., 2004; Roth et al., 2002). Additionally, lower levels of mRNA of the serotonin receptors (1E and 5A), D5 dopamine receptor, and neuronspecific enolase (NSE) have been found in men (Castensson et al., 2000), and diVerences in the expression levels of genes encoding proteins involved in hormone-mediated signaling can also be expected. Other studies, however, have shown opposite results: The mRNA levels of NSE in women were decreased when compared to men in both control subjects and subjects with AD (Preece and Cairns, 2003). The X-inactivation status for a particular gene can be tissue or cell specific (Chowers et al., 2003; Vawter et al., 2004a). Additionally, some of these genderspecific genes are involved in RNA management, such as DDX3 (Iwamoto et al., 2004; Katsel and Haroutunian, unpublished data) and its Y-chromosome homolog DBY (Galfalvy et al., 2003; Iwamoto et al., 2004; Vawter et al., 2004a), as well as in the control of gene transcription, SMCY, ZFY (Galfalvy et al., 2003), and may therefore influence brain transcription profiles in a genderdependent manner. Surprisingly, the catechol-O-methyltransferase (COMT) gene, which is linked to susceptibility to SZ (Egan et al., 2001; Gogos et al., 1998; Karayiorgou et al., 1998; Murphy et al., 1999) and located at the chromosomal locus 22q11, has been found to be influenced by sex, and its mRNA levels have been reported to be significantly lower in men (Iwamoto et al., 2004). These results underscore the importance of considering complex interactions between sex and the expression of genes of interest in interpreting gene expression results. It is evident that simply disregarding X or Y chromosome–associated genes is not an adequate strategy, and a thorough understanding of the interactions of any specific gene of interest with sex is important to the interpretation of RNA expression results.

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G. Medication and Substance Abuse Common CNS-acting drugs, such as antipsychotics or antidepressants, undoubtedly have an eVect on neurotransmitters (e.g., dopamine and serotonin), receptors, and associated signaling pathways (Crow et al., 1980). In animal studies (rat prefrontal cortex [PFC]), acute clozapine treatment revealed diVerential expression of genes involved in presynaptic function and in the regulation of intracellular calcium, including chromogranin A, synaptotagmin V, and calcineurin A (Kontkanen et al., 2002). Other evidence suggests that chronic antidepressant treatment may have an eVect on neuronal plasticity in the CNS via upregulation of GAP-43 mRNA and protein levels (Chen et al., 2003). Analysis of metabolic genes in SZ has shown reductions in the expression of genes involved in the regulation of ornithine and polyamine metabolism, the mitochondrial malate shuttle system, the trans-carboxylic acid cycle, aspartate and alanine metabolism, and ubiquitin metabolism and has raised the possibility that these changes may in part be compensatory eVects of antipsychotic drug treatment on gene expression levels (Middleton et al., 2002). Substance abuse dependence may also be associated with adaptive changes in gene expression in the brain. In animal studies, morphine treatments result in increased mRNA expression of c-Fos (Gutstein et al., 1998), G proteins (Przewlocka et al., 1994), and calbindin (Tirumalai and Howells, 1994). It is, therefore, likely that alteration in synaptic proteins such as arc or ania-3 contributes to the long-term plasticity changes underlying addiction (Ammon et al., 2003). Similarly, withdrawal from substance abuse clearly can significantly aVect gene expression (Ammon et al., 2003; Bhat et al., 1992) and can be expected to result in adaptive changes in the expression of many target genes. Chronic cocaine abuse induces decreases and increases in the expression of a number of genes such as those associated with energy metabolism in mitochondria, phosphatidylinositol-4 kinase, the regulator of G protein–signaling protein 4 (RGS4) (Yuferov et al., 2003), immediate early genes and their eVectors, synaptic proteins such as arc (Fosnaugh et al., 1995) and synaptotagmin IV (Yuferov et al., 2003) and some myelin-related genes (Albertson et al., 2004). Alcoholism is one of the most prevalent forms of substance abuse. Changes in brain gene expression are thought to be responsible for the tolerance, dependence, and neurotoxicity produced by chronic alcohol use and abuse (HoVman et al., 2003). Analysis of expression levels between alcoholics and nonalcoholics has revealed a selective reprogramming of gene expression in some brain regions. Consistent changes in the expression levels of genes involved in cell cycle regulation, several neuron-specific genes, protein traYcking–related genes, myelin-related genes, and genes encoding proteins participating in calcium, cyclic adenosine monophosphate (cAMP), and thyroid signaling pathways (Lewohl et al., 2000); protein traYcking–related genes and genes encoding

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proteins participating in calcium, cAMP, and thyroid signaling pathways (Mayfield et al., 2002); genes encoding mitochondrial proteins and genes participating in multiple signaling pathways and associated with ubiquitination (Sokolov et al., 2003) have been found in chronic alcoholics. In addition, the 1 isoform of the -aminobutyric acid A (GABAA) receptor mRNA was expressed diVerentially across two cortical regions and between controls and alcoholics (Lewohl et al., 1997). These mRNA expression changes were later confirmed at the protein level (Lewohl et al., 2001). These data suggest that multiple pathways may be important for the neuropathology and altered neuronal function observed in alcoholism (Mayfield et al., 2002). At the same time, these results emphasize the need for not only considering the confound of a history of alcoholism in studies in which modification of gene expression by alcohol is not the aim of the study, but for excluding specimens derived from alcohol abusers in such studies. Cigarette smoking is perhaps the most widespread form of addiction. Nicotine appears to be the primary psychoactive agent in tobacco responsible for addiction (Henningfield and Heishman, 1995; Li et al., 2002), and its habitforming actions appear to be triggered primarily via nicotinic acetylcholine receptors expressed on dopaminergic neurons in the ventral tegmental area that project to the nucleus accumbens (Pontieri et al., 1996). Depending on the concentration, nicotine may activate diVerent signaling pathways in a region-specific manner including inositol-triphosphate receptor (Ins[1,4,5]P3) coupled to intracellular calcium release (Gueorguiev et al., 1999; Sabban and Gueorguiev, 2002; Zhang and Melvin, 1994), which subsequently results in the activation of many other signaling pathways from CRE-dependent gene expression regulation to stress-activated protein kinases, JNK=SAPK (Bito and Takemoto-Kimura, 2003; Bito et al., 1997). Microarray experiments from the PFC and nucleus accumbens indicate that chronic nicotine administration results in increased production of inositol phosphates, modulation of growth factors and cytokines, and increased expression of genes implicated in remyelination and axonal growth (Li et al., 2002). Therefore, by eliciting intracellular calcium release and modulation of inositol phosphate levels, nicotine becomes a highly modulatory substance in the regulation of many cellular events including signaling and transcription. Thus, it is clear that microarray studies of alcohol, nicotine, and substance abuse can contribute significantly to our knowledge of the neurobiological consequences of substance abuse and perhaps to the underlying core features of addiction. On the other hand, it is also clear that substance abuse can be a significant source of artifact in microarray studies where the study of substance abuse is not the primary focus. In these instances, substance abuse can be incidental to the study aims, but a significant factor influencing gene expression. These complex alterations in gene expression that result from treatments with drugs with CNS activity and addiction make matching cases of interest

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with controls very diYcult in the relatively small proportion of subjects whose brains are generally available for study and who have met the numerous other inclusion criteria discussed earlier. To circumvent these obstacles, three major approaches (Hynd et al., 2003) can be used when planning microarray studies: (1) arranging patients in groups according to treatment or addiction history when analyzing data; (2) delineating drug eVect on gene expression pattern in various brain regions in animal models; and (3) using subjects who do not have evidence of the targeted disorder but have a similar drug treatment or abuse history.

IV. Comparison of Gene Expression Profiles among Normal Brain Regions

Determining gene expression profiles of diVerent brain regions is crucial for understanding brain physiology, function, and associated neurological disorders, as well as the relationships between diVerent brain regions. The mammalian brain is divided into structurally and functionally distinct regions. Gene expression profiles within these regions are likely to vary in accordance with the distribution of cell types, function, and brain circuitry. From this perspective the use of microarray technology to define region-specific pattern of gene expression is advantageous over conventional molecular biology methods because it permits the uniform examination of the normalized expression pattern of thousands of genes simultaneously in the same specimens. Despite the extensive heterogeneity of brain tissue, some studies have shown evidence that brain regions of animals and humans exhibit remarkable similarities in their gene expression patterns (Li et al., 2002). Some microarray experiments in animals, however, suggested that this similarity may be the result of an inability to accurately determine the expression levels of transcripts that are expressed at low levels or transcripts that are expressed in specialized cells with a low density of distribution (Bonaventure et al., 2002; Dent et al., 2001; Konu et al., 2001; Lein et al., 2004; Pavlidis and Noble 2001; Zirlinger et al., 2001). For example, experiments that have combined laser-capture microdissection with microarray methods of specific subnuclei of the amygdala have demonstrated distinct nucleus-specific gene expression patterns (Dent et al., 2001; Zirlinger et al., 2001). Significant progress in this area has been made in molecular mapping of the hippocampus where microarray gene expression techniques have been combined with high-throughput in situ hybridization (Lein et al., 2004). Using an alternative approach, as unpublished studies in our laboratory have shown that although the absolute expression levels of various genes in diVerent brain regions may be only modestly diVerent, their inter-relationships or intercorrelations can vary dramatically from brain region to brain region.

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Regional gene expression analysis of the human brain using microarray technology is still at the earliest stages of exploration. One report documented region-specific gene expression profiles from postmortem human tissues by comparing gene expression in the cerebellum to two cerebral cortex regions: the dorsolateral PFC (DLPFC) and the anterior cingulate cortices (Evans et al., 2003). Analysis of gene expression profiles from highly divergent brain regions, cerebellum versus either of the two cortical regions, revealed more than 1000 transcripts that were diVerentially expressed. Comparison of gene expression divergences between the structurally more similar neocortical regions, on the other hand, revealed only a few diVerentially expressed transcripts. Detected region-specific gene classes represented those involved in signal transduction machinery, neurogenesis, synaptic transmission, and transcription factors. Similarly, three region-specific marker genes were identified by SAGE in white matter, thalamus, and cerebellum from the same normal brain. The neurogenic diVerentiation 1 gene (NEUROD1) was enriched in cerebellum, cocaine- and amphetamine-regulated transcript (CART) in thalamus and neurogranin (NRGN) in white matter (Siu et al., 2001). We have compared gene expression profiles from the frontal, cingulate, temporal, parietal, and occipital cortices, as well as from the caudate, hippocampus, and putamen of 12 autopsy brains of elderly subjects who had no history of psychiatric disorders and showed no discernible neuropathological lesions. Crosscomparison of analyzed regions showed an apparent decrease in expression levels of myelin-associated genes in DLPFC and other frontal cortical regions relative to the temporal, parietal, and occipital cortices (Haroutunian et al., 2003a). It is not clear whether this decrease is a specific feature of the frontal cortex and an indicator of a lower degree of myelination in DLPFC, or whether it results from processes associated with normal aging. Nevertheless, it is known that the PFC is a late-developing region that is characterized by the late myelination of its axonal connections perhaps due to its greatest expansion in the course of both evolution and individual maturation (Fuster, 2002). Note, however, that these diVerences in regional gene expression patterns in normal controls are independent of the changes in myelin gene expression that are evident in disease states such as SZ and AD (see later discussion). Comparison of gene expression across all analyzed cortical regions demonstrated few diVerences in expression patterns within diVerent cortical regions even though these regions are implicated in diVerent functions. These results confirmed the findings of a previously reported study that was based on a more restricted regional analysis (Evans et al., 2003). On the other hand, cross-comparison of noncortical regions (caudate, hippocampus, and putamen) identified significantly higher numbers of transcript expression diVerences, ranging from threefold to fivefold, between these regions. Similar values were observed when these noncortical regions were compared to various cortical regions (Haroutunian et al., 2003a).

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V. Gene Expression Profiles of Brain Regions in Alzheimer’s Disease

Altered patterns of gene expression are implicated in the initiation and progression of neurodegenerative disorders such as AD and Parkinson’s diseases. These alterations arise not just from inheritable genetic origins or from susceptibility genes for the specific form of the disorder but also from the continual interplay of these elements with environmental factors that modulate the ongoing activities of the CNS. Microarray technology has the potential not only to detect susceptibility genes but also to examine complete gene expression profiles that may help unravel the molecular substrates of the pathophysiology of these diseases. AD is the most common form of the neurodegenerative disorders in humans (Haroutunian and Davis, 2003; Selkoe, 1996). It is characterized by progressive impairment in cognitive function during aging. The overlap of the pathophysiological process involved in AD and the CNS changes that occur as a natural part of the aging process introduce some analytical and conceptual considerations that must be carefully examined and accommodated in the design of studies. These issues are no more grave for microarray studies than they are for other studies of the neurobiology of AD and have been thoroughly addressed (Haroutunian and Davis, 2003; Selkoe, 1996). The most significant of these considerations is the need for careful age-matching of cases and controls. The neuropathological hallmarks of the brains from patients with AD include extracellular -amyloid– containing plaques, intracellular neurofibrillary tangles (NFTs) composed of abnormally phosphorylated tau, and degeneration of cholinergic neurons of the basal forebrain (Davies and Maloney, 1976; Davis et al., 1999; Haroutunian et al., 1998, 1999; Whitehouse et al., 1982). Given the widespread regional distribution of these pathological features within AD brains, a large number of the brain regions have been examined in diVerent microarray studies (Blalock et al., 2004; Colangelo et al., 2002; Ginsberg et al., 2000; Hata et al., 2001; Ho et al., 2001; Loring et al., 2001; Mufson et al., 2002; Pasinetti, 2001; Yao et al., 2003). In one approach to accessing gene expression profiles of pathological changes in AD, diVerences between NFT-bearing hippocampal CA1 neurons and apparently healthy normal neurons from the same region were sought using complementary DNA (cDNA) microarrays (Ginsberg et al., 2000). NFT-bearing neurons in brains of patients with AD showed significant reductions (between twofold and fivefold) in several classes of mRNAs that are known to encode proteins previously implicated in AD neuropathology, including phosphatases and kinases, cytoskeletal proteins, synaptic proteins, glutamate receptors, and dopamine receptors. In addition, mRNA levels of genes not previously implicated in AD were reduced in NFT neurons (Ginsberg et al., 2000). This group of transcripts included focal adhesion kinase (FAK or PTK2), a kinase that participates in a

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number of signaling pathways; glutaredoxin that is regulated by oxidative stress; as well as activity-regulated cytoskeleton (arc)–associated protein, an immediateearly gene that is enriched in neuronal dendrites and implicated in synaptic plasticity (Lyford et al., 1995). When homogenates of AD tissues from the same region (hippocampal CA1) were compared to control samples in an oligonucleotide-based microarray study using the AVymetrix GeneChip platform, a similar generalized reduction in the expression levels of several groups of transcripts was observed (Colangelo et al., 2002). These findings support the hypothesis of widespread transcriptional alterations in AD based on the observed reduction of mRNA levels of Zn2þ-containing transcription factors and proteins involved in Zn2+ homeostasis. The CA1 region of the hippocampus also showed decreased levels of transcripts involved in neurotrophic support and synaptic plasticity. In contrast, there was an apparent robust (threefold or more) upregulation of genes involved in apoptosis and in neuroinflammatory signaling, indicating ongoing processes associated with inflammation and cellular death in moderately aVected AD hippocampal CA1 region cells. Regional diVerences in gene expression, especially diVerences in gene expression of regions that are neuropathologically involved in the AD processes to a greater or lesser extent, have been explored using the cluster analysis methodology described earlier. Cluster analysis of altered genes between controls and cases with moderate dementia demonstrated consistent downregulation of neurotransmitter signaling, cytoskeleton, protein, amino acid, and fatty acid metabolism genes in the entorhinal cortex but not in the visual cortex where evidence of AD neuropathology was scant (Pasinetti, 2001). Hata et al. (2001) used cDNA arrays to follow a diVerent approach by comparing gene expression in the hippocampus containing NFT-associated lesions from patients in the early stages of AD to gene expression in the parietal cortex from the same patient who lacked NFT lesions, presumably by virtue of the early stage of their disease. Candidate genes that significantly upregulated or downregulated only in the AD brain but did not represent regional diVerences in control brains were examined. Calcineurin A (PPP3CB) was the most upregulated transcript in the NFT-bearing hippocampus and its overexpression was predominantly localized to pyramidal neurons of the hippocampus of the AD brain. It is tempting to link the PPP3CB mRNA increase to processes opposing hyperphosphorylation of tau or activation of proapoptotic pathways in early stages of AD. Although PPP3CB mRNA levels were increased in AD samples, it is not clear why mRNA levels of two other isoforms of calcineurin catalytic subunit (A, PPP3CA and A, PPP3CC) remained unchanged in early AD and what their role would be in the ongoing processes during early stages of AD. However, the finding that only one of three isoforms of PPP3CB was significantly altered in its expression in AD underscores one of the significant advantages of microarray gene expression analysis. Unlike the more traditional

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single-transcript molecular analysis techniques, the use of high-density microarrays reveals diVerences and points to possible isoform-specific diVerences that may not necessarily be revealed unless isoform-specific hypotheses are being investigated. In a study using oligonucleotide-based microarrays, gene expression profiles from the hippocampus of 22 incipient AD subjects were compared to those of matched controls. Identified candidate genes were additionally tested against pathological (NFT scores) and cognitive parameters confirming correlation of their expression levels with these parameters (Blalock et al., 2004). Categorization of candidate genes on the basis of their involvement in biological processes revealed upregulation of many transcription factor=signaling genes regulating proliferation and diVerentiation, including tumor suppressors, oligodendrocyte growth factors, and protein kinase A modulators. In addition, upregulation of adhesion, apoptosis, lipid metabolism, and initial inflammatory processes, and downregulation of protein folding=metabolism=transport and some energy metabolism and signaling pathways occurred, indicating apparent collapse of protein transport in the early stages of disease. Based on these findings, the authors proposed a new model of AD pathogenesis in which initial alterations in axon– myelin interactions lead to stimulation of neurite growth and remyelination responses. The basal forebrain and the cholinergic neurons of the nucleus basalis of Meynert are particularly susceptible to degeneration in AD (Davies and Maloney, 1976; Davis et al., 1999; Whitehouse et al., 1982). Cholinergic basal forebrain neurons provide the predominant source of cholinergic innervation to the cerebral cortex and hippocampus and play critical roles in the modulation of learning, memory, and attention (Geula, 1998; Mesulam et al., 1983). Dysfunction and degeneration of these neurons results in severe deficiencies of presynaptic cholinergic markers in advanced AD (Davis et al., 1999). RNA from cholinergic basal forebrain neurons immunostained with antibodies to the P75 neurotrophin receptor from controls and patients with AD was subjected to analysis using custom microarray probes for neurotransmitters, synaptic proteins, glial markers, AD-susceptibility genes, and others (Mufson et al., 2002). Similar to the study of hippocampal CA1 neurons (Ginsberg et al., 2000), downregulation of genes encoding synaptic proteins and protein phosphatases (PP1 and PP1) and a remarkable upregulation of cathepsin D were found in cholinergic basal forebrain neurons in AD. Neurotrophin receptors trkB and trkC mRNAs were also selectively downregulated in these cholinergic neurons, whereas p75NTR mRNA levels remained stable even in late stages of AD (Mufson et al., 2002). Reduced activity of protein phosphatases (PP1 and PP2A) has been implicated in hyperphosphorylation of tau, which is often viewed as the basis of NFT pathology and subsequent cytoskeleton destabilization and synaptic loss in

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vulnerable neurons in AD. Reduced expression of genes encoding synaptic proteins may be associated with the early phase of cognitive decline in AD (Pasinetti, 2001). Loss of synapses in the frontal cortex is well documented and correlates with cognitive decline in AD (Terry et al., 1991). However, molecular mechanisms underlying synaptic dysfunction and loss have remained unclear. In microarray analyses of samples from the frontal cortex of subjects with AD, reduced expression of several genes that are involved in synaptic vesicle traYcking was found, but similar reductions for other genes involved in diVerent synaptic functions have not been identified, strengthening the possible link between synaptic vesicle–traYcking pathways, synaptic malfunction, and AD pathogenesis (Yao et al., 2003). The involvement of genes associated with synaptic function has been refined further and has been ascribed to changes associated with the earliest stages of the clinical progression of the disease. Ho et al. (2001) studied the entorhinal (a region of high susceptibility to AD neuropathology) and visual (a cortical region that becomes involved only during the late stages of the disease process) cortices of cases characterized by the earliest clinically detectable stage of AD using cDNA microarrays to identify genes that may be associated with cognitive decline and the initiation of pathophysiological processes associated with AD. Among the genes whose expression was altered in the cerebral cortex, expression levels of synapsins—synaptic vesicle proteins that play an important role in neurotransmitter release—were found to be altered during the transition from normal cognitive function to early dementia. Synapsin-Ia, -IIa, and -IIIa were selectively decreased in the entorhinal but not visual cortex. Gene expression in the amygdala and cingulate cortex of AD cases has also been examined in cDNA microarray experiments (Loring et al., 2001). Comparison of samples from AD cases with controls showed that 118 of the 7050 sequences examined were diVerentially expressed in these two regions in AD relative to controls. Most of the identified ‘‘candidate genes’’ were downregulated and functionally categorized to signal transduction, energy metabolism, stress response, cytoskeleton, calcium binding, and synaptic vesicle synthesis and function. Among upregulated genes were those associated with chronic inflammation, cell adhesion, cell proliferation, and protein synthesis, confirming earlier results and suggesting an ongoing pathophysiological process associated with AD. In summary, the microarray studies described here have in general confirmed hypotheses regarding gene expression changes in AD that would be predicted from studies performed using more conventional low-throughput methodologies. Where the microarray studies have excelled has been in showing the coordinated gene expression changes that are present in diVerent stages of the disease process and especially large-scale changes associated with pathology at the cellular level. In addition, these microarray studies have played a significant hypothesisgenerating role by identifying changes in gene expression that would otherwise not have been addressed by low-throughput candidate gene approaches.

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VI. Gene Expression Profiling in Schizophrenia

SZ, like most other psychiatric disorders, is complex in origin. SZ typically manifests in late adolescence or early adult life with major, progressive, and usually irreversible deterioration from the previous level of functioning. It was initially viewed as a new form of neuronal degeneration and dementing disease (Woods, 1998). Lack of consistent data on loss of neurons in diVerent brain regions in SZ (Haroutunian and Davis, 2000, 2003; Harrison, 1999) and no, or only scant and inconsistent, evidence of increased gliosis in SZ (Arnold et al., 1996; Roberts et al., 1986), which is regarded as a hallmark of neuronal degeneration, have since suggested that SZ is unlikely to be a neurodegenerative disorder in the traditional sense and have suggested a neurodevelopmental hypothesis of SZ. Twin and adoption studies indicate that SZ possesses a strong genetic component (Sawa and Snyder, 2002), with heritability estimated at 80% (Harrison and Owen, 2003; Lewis et al., 2003; Sullivan et al., 2003). However, no single gene that may cause alterations resulting in manifestation of SZ symptoms has been identified. Genome-linkage studies performed on cohorts of patients from diVerent geographical regions have mapped genetic loci that confer susceptibility to SZ to multiple chromosomes, including 22q11-q13, 1q42.1, 18p, 15q15, 13q34, 13q32, 12q24, 11q14-q21, 1q21-q22, 10q22.3, 8p21, 6q13-q26, 6p22.3, 6p23, 5q11.2-q13.3 (O’Donovan et al., 2003). This may indicate that SZ, like other complex diseases, may require a certain combination of genetic abnormalities to become symptomatically manifest and may reflect not a single disease entity with a single genetic cause, but a multiform disorder with distinct genetic abnormalities that lead to similar symptoms, much like heart disease. Furthermore, various prenatal, perinatal, and postnatal nongenetic factors are also known to contribute to the complex clinical phenotype of SZ (Murray et al., 1992). Consensus between these and other etiological views of SZ is likely to be reached through a systematic approach that incorporates interactions between genetic predisposition, developmental, and environmental factors (Gottesman and Gould, 2003). The interplay between each of these factors will likely produce changes in transcriptional profiles in diVerent brain regions of schizophrenics who can be analyzed in microarray experiments. Although a number of brain regions have been implicated in the pathophysiology of SZ, the dorsolateral PFC has been singled out as a major site of dysfunction on the basis of considerable clinical, neuroimaging, and postmortem studies and has thus been almost exclusively targeted by most microarray studies (Haroutunian and Davis, 2000). Given the wealth of evidence implicating the DLPFC in SZ, it is not surprising that the first two microarray studies (Hakak et al., 2001; Mirnics et al., 2000) described SZ-related gene expression profiles in

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this area. Hakak et al. (2001) used the AVymetrix GeneChip to examine gene expression profiles of the DLPFC in postmortem specimens from persons with SZ and controls. Among identified gene expression changes in the DLPFC of SZ cases, the most striking were deficits in genes whose expression is enriched in myelin-forming oligodendrocytes and implicated in the formation and maintenance of myelin sheaths. These findings suggest that myelin sheaths and oligodendrocytes may be functionally impaired in SZ. Most of the SZ subjects used in this study, however, received prolonged medication treatment that raised the possibility of neuroleptic medications treatment eVect on the expression levels of identified genes. Several studies examining gene expression profiles in the neuroleptic-treated animals, however, did not indicate significant alterations in the expression of oligodendrocytes-specific genes (Mirnics et al., 2001b; Pierri et al., 1999; Pongrac et al., 2002). Additionally, comparison of two subgroups of schizophrenics—antipsychotic medication–treated patients and patients free of antipsychotic medications for at least 6 weeks before death (i.e., more than six half-lives after chronic treatment with haloperidol [Kornhuber et al., 1999]) showed no significant diVerences in the expression levels of identified genes, suggesting that this deficit is most parsimoniously attributed to the disease (Hakak et al., 2001). These findings were later confirmed in a new sample of cases using quantitative RT-PCR (Hof et al., 2002). In an independent study, downregulation of genes encoding major oligodendrocyte and myelination proteins, as well as transcription factors for these genes in DLPFC of SZ and additionally in bipolar disorder, was confirmed by microarrays and other validation methods (Tkachev et al., 2003). Decrease of proteolipid protein 1 (PLP1) mRNA—a major myelin protein—was also detected across most SZ samples in another study (Pongrac et al., 2002). These findings are in agreement with data from neuropathological studies that have reported a reduction in glial cell density by 15–20% (Cotter et al., 2001a,b, 2002) and by 33% (Stark et al., 2004) in the anterior cingulate cortex, as well as a layer-specific reduction in DLPFC (BA 9) by 22–28% in layer III (Hof et al., 2002, 2003), and by 32% in layer V (Rajkowska et al., 2002) of schizophrenics. In our study we compared gene expression profiles from multiple brain regions including the frontal, cingulate, temporal, parietal, and occipital cortices, as well as in three subcortical regions (caudate, hippocampus, and putamen) of 13 elderly SZ and matching 12 control subjects postmortem by AVymetrix GeneChip-based microarrays. A group of 12 oligodendrocytes=myelin genes involved in maturation of myelin sheaths including genes identified in previous study (Hakak et al., 2001) was enriched among candidate genes in cingulated and temporal gyri and in the hippocampus relative to other analyzed regions, confirming their involvement in the disease process. Collectively, our data suggest that the integrity of axon–myelin interaction may be impaired. We also reported significant changes in the gene expression of the superior temporal and cingulate

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cortex in SZ relative to other areas examined. Unexpectedly, the DLPFC, which is considered the major site of dysfunction in SZ, showed the lowest number of altered genes (Katsel et al., 2004). Data from a number of studies indicated synaptic pathology in SZ, which is most apparent in early adulthood (Raedler et al., 1998). Glia, previously seen only as supporting cells, are increasingly appreciated as regulators of neurogenesis, synaptic network formation, and neuron electrical activity (Goldman, 2003; Newman, 2003; Ransom et al., 2003; Slezak and Pfrieger, 2003). Glial cell abnormalities may significantly influence synapse formation in development and modulate neuronal transmission and plasticity during adulthood (Honer et al., 1999; Sawa et al., 2004). Groups of genes involved in neuronal development and plasticity, as well as in GABA neurotransmission pathways, were also found upregulated in SZ (Hakak et al., 2001). Somewhat contradictory to these findings was a downregulation of several genes involved in GABA neurotransmission and postsynaptic signal transduction found in another study examining gene expression profiles of the DLPFC in SZ using cDNA microarrays (Mirnics et al., 2000). A major finding of this study was a consistent decrease in the expression of genes related to presynaptic secretory release, including N-ethylmaleimide–sensitive factor and synapsin II in DLPFC (area 9) from postmortem SZ brains (Mirnics et al., 2000). Genes related to glutamate neurotransmission were also found to be dramatically reduced, but that may be secondary to the altered presynaptic function (Mirnics et al., 2000; Pongrac et al., 2002). These results are generally consistent with previously reported decreases in the number of axon terminals and dendritic spines in this region (Garey et al., 1998). Vawter et al. (2002) using cDNA microarrays on pooled samples from DLPFC of SZ subjects has also found downregulation of a number of genes encoding presynaptic nerve terminal proteins including those identified in the aforementioned study (Mirnics et al., 2000). Similar alterations in gene expression of six synaptic genes were also found in the superior temporal gyrus in SZ, although these changes were likely reflecting age-related changes rather than abnormalities in a specific synaptic function (Sokolov et al., 2000). A subsequent study from Mirnics et al. (2001b) using samples from DLPFC of the same set of SZ subjects reported decreases in the expression levels of G protein signaling 4 (RGS4), indicating additional abnormalities associated with synaptic function. RGS proteins are important negative regulators of duration of G protein signaling and are likely associated with postsynaptic membranes. Therefore, downregulation of RGS4 could be compensatory to the decreased presynaptic release (Mirnics et al., 2000), and RGS4 deficit, thus, may indicate increased duration of G protein signaling in postsynaptic cells. Moreover, RGS4 resides in chromosomal locus 1q21-22 previously linked to SZ (Brzustowicz et al., 2000). Of 70 genes mapped to this SZ susceptibility locus and present on the microarray, only RGS4 gene expression was consistently altered (Mirnics et al.,

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2001b). Additionally, genetic association studies have revealed increased transmission of allelic variations in the 50 region of the RGS4 in several regionally distinct populations of patients with SZ (Chowdari et al., 2002). Although reduced G protein levels have been reported in the temporal cortex and other areas of schizophrenic brains (Okada et al., 1991, 1994; Yang et al., 1998), there have been contradictory findings as well ( Jope et al., 1998). Mimmack et al. (2002) identified robust upregulation of several genes encoding high-density lipoproteins—apolipoproteins L1, L2, and L4—in the DLPFC of subjects with SZ from diVerent geographical regions. These authors also pointed to the fact that ApoL gene cluster resides in close proximity (22q12.3) to another gene linked to susceptibility of SZ: catechol-O-methyltransferase (COMT) (Gogos et al., 1998; Karayiorgou et al., 1998) at the locus 22q11, which is also linked to velocardiofacial syndrome, a disorder that is associated with incidence of SZ in about 30% of patients (Murphy et al., 1999). However, it is not clear how findings of upregulation in mRNA levels of ApoL genes and susceptibility locus 22q11-13 may contribute to the processes underlining SZ, because microdeletions in 22q11 locus (Bassett and Chow, 1999) are usually associated with the susceptibility to SZ. Additionally, molecular and cellular functions of proteins encoded by ApoL genes remain unclear. Two additional genes mapped to the same chromosomal region 22q11-q13 were among the most diVerentiated genes identified in the other microarray study (Vawter et al., 2001). These are tyrosine 3-monooxygenase=tryptophan 5-monooxygenase activation protein (YWHAH) gene encoding protein 14-3-3, which is likely involved in a number of cellular signaling pathways and neurofibromin 2 (NF2) gene. The NF2 gene was found to be downregulated in DLPFC, and YWHAH was downregulated in the middle temporal cortex (area 21) and cerebellum of medication-treated SZ subjects, but not in ‘‘drug-naive’’ schizophrenics (Vawter et al., 2001), making it diYcult to draw consistent conclusions. However, that medications thought to be at least partially eYcacious in the treatment of the disease aVected the expression of these genes suggests that they may be involved in treatment response or that they may participate in the disease process in a complex and, as yet, poorly understood way. Alterations in the metabolism of the DLPFC of SZ were reported in the number of studies (Berman et al., 1986; Buchsbaum et al., 1992; Weinberger et al., 1986) and have been suggested to underlie the cognitive deficit in SZ (GoldmanRakic, 1991; Park and Holzman, 1992). A cDNA microarray study performed on the samples from the SZ subjects used in previous reports (Mirnics et al., 2000, 2001b) identified a highly specific pattern of metabolic alterations in the DLPFC of SZ subjects that includes genes involved in the regulation of ornithine-polyamine metabolism, the mitochondrial malate shuttle system, the trans-carboxylic acid cycle, aspartate and alanine metabolism, and ubiquitin metabolism (Middleton et al., 2002). Examination of the expression levels of these

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genes in haloperidol-treated monkeys indicated an unlikely eVect of medication treatments. Moreover, prominent drug-associated increases in expression of malate dehydrogenase were noted, raising the possibility of a therapeutic eVect of antipsychotic medications that may temporarily correct detected abnormalities. Decreased expression levels of malate dehydrogenase in the DLPFC have been confirmed in an independent set of samples using quantitative PCR, although this deficit was characteristic of DLPFC only from male schizophrenics, indicating gender-dependent alteration in gene expression of this enzyme (Vawter et al., 2004b). In another report employing transcriptomics, proteomics, and metabolomics approaches, alterations in mRNAs of energy metabolism and oxidative stress genes were found to be highly specific to SZ (Prabakaran et al., 2004). These alterations in the expression levels of metabolic genes may underlie the detected synaptic dysfunction in SZ (Hakak et al., 2001; Mirnics et al., 2000, 2001b; Sokolov et al., 2000; Vawter et al., 2002). The vast majority of the measurable metabolic fluctuations in brain occur at synapses (Nudo and Masterton, 1986; SokoloV, 1977, 1979). Indeed, the processes of synaptic vesicle release and assembly, as well as transmitter synthesis and postsynaptic signaling, are all energy dependent and require substantial amounts of ATP production. Although these gene expression studies provide important leads for future studies, it is sobering to note that a direct study of some of the enzymes that they encode has failed to unmask specific changes in the activity of multiple enzymes involved in energy metabolism (Bubber et al., 2003, 2004). In contrast to the brain homogenate approach to sampling, which encompasses superimposed gene expression profiles from diVerent populations of brain cells including neuronal, glial, epithelial, and vascular cells, single cell sampling methods aim to delineate alterations that occur selectively within defined cell population. Hemby et al. (2002) attempted single-cell gene expression profiling on stellate cells from layer II of entorhinal cortex obtained from a small group of postmortem brains of elderly SZ and matching controls using cDNA microarrays. This study, again, confirmed gene expression level alterations for synaptic markers (synaptophysin, synaptotagmin-I, synaptotagmin-IV; SNAP-23, and SNAP-25) and diVerent glutamate receptor subunits (GluR3, GluR5, and NMDAR1) previously implicated in SZ (Dracheva et al., 2001; Eastwood and Harrison, 1999; Eastwood et al., 1995; Haroutunian et al., 2003b; Honer et al., 1999; Humphries et al., 1996; Ibrahim et al., 2000; Mirnics et al., 2000; Richardson-Burns et al., 2000; Sokolov et al., 2000; Thompson et al., 1998; Young et al., 1998). These findings are not only important in their own right, but they underscore the feasibility and desirability of identifying disease-associated abnormalities at the cellular level. This and similar approaches are poised to reveal gene expression deficits and profiles with enough neuroanatomical fidelity to permit a true pursuit of systems- and circuit-level defects in disease and normal function.

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Taken together, the results of the microarray studies discussed suggest that there is both neuronal and glial involvement in SZ disease process. Studies of brain development and neural regeneration indicate a dynamic interplay between neural and oligodendroglial mechanisms in regulating synaptic plasticity and axonal sprouting. How oligodendrocytes and neurons interact to produce the neurobiological and behavioral abnormalities associated with SZ is still unclear, but it is reasonable to presume that oligodendrocyte abnormalities may impair the organization of the periaxonal as well as nodal regions in neurons and lead to abnormal impulse propagation and disruption of circuitry, connectivity, and synaptic function. It is abundantly clear, however, that the use of microarray technology to study the neurobiology of SZ in postmortem specimens has uncovered abnormalities in the expression of not only genes and neurobiological systems that were previously unsuspected, but that these methodologies have given us a much broader picture of potentially coordinated systems-level deficits that may underlie this disease. VII. Future Perspectives

This chapter of microarray technique and studies of brain physiology and associated neurological disorders has shown that significant progress has been made in several directions. This progress has included the development of better arrays fabrication methods (such as manufacturing of single whole-genome chips or 100K single-nucleotide polymorphisms chips), method instrumentation, and novel data-mining techniques, each with its own strengths, and better awareness of critical issues and confounding factors that have an impact on interpretation of the obtained data. Further development of these components of microarray techniques will lead to improvements in the quality of the data derived and to the more eYcient and evidence-based mining of the information embedded in gene expression profiles. Microarray studies have already helped in the identification of candidate genes and have generated testable hypotheses of the mechanisms of neurological disorders. There are as many important areas of future progress that can be enumerated as there are researchers working on microarray gene expression studies. The following are some areas for future development that do seem to be of general importance, especially to postmortem studies on the human brain and CNS disorders. Defining gene expression atlas of human brain regions in development, adulthood, and aging: This includes systematic examination of gene expression profiles within various brain regions in accordance with the distribution of cell types, function, and brain circuitry. Creating molecular maps of diVerent

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regions is important for understanding normal brain physiology and the processes underlying complex psychiatric disorders. Several studies to obtain gene expression profiles of diVerent brain regions have been already attempted on both animal and human tissues (Blalock et al., 2003; Evans et al., 2003; Lein et al., 2004). For diseases such as SZ and AD, which are clearly developmental in nature (late adolescence to young adulthood and advanced age, respectively), understanding the ‘‘natural’’ age-associated changes in gene expression is critically important. Defining susceptibility regions in various pathologies: Identifying brain regions of greatest vulnerability to diVerent disease processes may result in determining the specific cell populations that are at greatest risk and lead to a better understanding of their molecular substrates. Identifying brain regions of vulnerability includes not only macroscopic regions such as particular gyri or nuclei, but also specific cortical lamina, specific cell groups within regions, and specific cell types or cell regions such as neuronal dendrites (Davis et al., 2004; Ginsberg et al., 2004). A combination of cellular level dissection and resolution of gene expression with well-defined disease and phenotypic information and microarray technology will help refine our understanding of disease processes and basic CNS function. Defining and refining the phenotypes that are studied by gene expression profiling: As gene expression profiling studies become more broadly available, the caveats that have historically been applicable to studies of postmortem tissue (Haroutunian and Davis, 2002) become more important, and adherence to strict standards for inclusion and exclusion of samples for study become imperative. These issues have been most strikingly underscored by the discussion earlier in this chapter regarding gene expression and the influence of drugs (whether used in treatment or abuse), age, gender, and diagnosis. It is increasingly clear that as gene expression profiling studies become more technically sophisticated, the need for better and better control of experimental sources of variance and accurate phenotypic stratification of study subjects becomes more crucial. Defining single-nucleotide polymorphism profiles of individual patients: With the availability of the 100,000 single-nucleotide polymorphisms GeneChip (AVymetrix), it will be attractive to use microarray technology to define groups of subjects with common polymorphism of genes linked to psychiatric disorders. It will be possible to group subjects not only along disease or behavioral dimensions, but also along common and uncommon polymorphisms. Thus, for example, it will become increasingly interesting to explore gene expression profiles within diagnostic and behavioral groups when these groups have been further stratified along polymorphic dimensions that have been linked to behavioral or disease features (Harrison and Owen, 2003). Studies using specific polymorphisms and specific genes of

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interest have already begun (Weickert et al., 2004), but the combination of high-throughput gene expression and polymorphism profile technologies is likely to take this exciting avenue of research to the next level.

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REGULATION OF SEROTONIN 2C RECEPTOR PRE-mRNA EDITING BY SEROTONIN

Claudia Schmauss Department of Psychiatry and Neuroscience, Columbia University College of Physicians & Surgeons and New York State Psychiatric Institute New York, New York 10032

I. Introduction II. Modification of RNA Sequences by RNA Editing via Hydrolytic Deaminations of Adenosines III. Enzymes Responsible for A-to-I Editing and Their Substrate Requirements IV. A-to-I Editing of the 5-HT2C Receptor Pre-mRNA V. Modulation of 5-HT2C Receptor Function by RNA Editing VI. 5-HT2C Pre-mRNA Editing Responses to Sustained Changes of Postsynaptic 5-HT2C Receptor Activation VII. 5-HT2C Pre-mRNA Editing in the Human Prefrontal Cortex and Alterations in Editing-Site Preferences in Brains of Subjects with Major Depression VIII. Conclusions and Future Directions References

I. Introduction

The primary transcript of the gene encoding the 5-hydroxytryptamine 2C (5-HT2C; serotonin 2C) receptor is modulated by RNA editing. In this posttranscriptional process, five closely spaced adenosines, located within a sequence encoding the second intracellular loop of the seven-transmembrane–spanning G protein–coupled receptor, are converted to inosine to alter the coding potential of three triplet codons. Theoretically, 32 5-HT2C messenger RNA (mRNA) isoforms could result from this editing, and they would encode 24 diVerent receptor isoforms. Results of pharmacological studies have demonstrated that 5-HT2C pre-mRNA editing modulates signaling at central serotonergic synapses and that the magnitude of this modulation depends on the extent of editing and on distinct editing-site preferences. Moreover, 5-HT2C pre-mRNA editing is regulated by the cognate neurotransmitter serotonin (i.e., 5-HT). Interestingly, results of human postmortem studies indicate altered editing-site preferences in brains of suicide victims with a history of major depression that lead to increased expression of 5-HT2C mRNA isoforms encoding receptors with compromised functional properties. In this chapter, these findings are discussed within the context of the normal serotonin-dependent regulation of 5-HT2C pre-mRNA editing. INTERNATIONAL REVIEW OF NEUROBIOLOGY, VOL. 63

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II. Modification of RNA Sequences by RNA Editing via Hydrolytic Deaminations of Adenosines

RNA editing is a co-transcriptional or post-transcriptional process that alters the nucleotide sequence of the genomically encoded primary transcript. In premRNA, single nucleotide changes can introduce start and stop codons, novel splice sites, and shifts in the open reading frame. Moreover, because inosines are read as guanosines by the translational machinery, exonic adenosine-to-inosine (A-to-I) editing can cause single amino acid changes at functionally important positions. Hence, pre-mRNA editing is a mechanism that increases the protein diversity and the complexity of regulatory processes. In higher eukaryotes, base conversion appears to be the major type of nuclear RNA editing, and the most prevalent reactions are hydrolytic deaminations of genomically encoded cytidines (C) or adenosines (A) to yield uridines (U) and inosines (I), respectively (Bass, 2002, Keegan et al., 2001; Maas et al., 2003; Schaub and Keller, 2002). The nucleotide inosine was first detected in cytoplasmic transfer RNA (tRNA) and later in pre-mRNA and viral transcripts (Schaub and Keller, 2002). The inosine content is highest in neural tissues, and it is estimated that one inosine should be present in 17,000 nucleotides (Paul and Bass, 1998). However, only a few transcripts have been identified that are a substrate for site-specific A-to-I editing, and almost all of them encode membrane proteins that function either as voltage- or ligand-gated ion channels or G protein–coupled neurotransmitter receptors (Schmauss and Howe, 2002; Seeburg, 2002; Seeburg and Hartner, 2003). Moreover, all these substrates for site-specific A-to-I editing were discovered by serendipity, and together, they represent only a minor fraction of the total inosine content of the brain (Paul and Bass, 1998). Systematic approaches to identifying novel A-to-I editing sites are likely to discover many more substrates for A-to-I editing. For example, a comparative analysis of genomic sequences of the fruit fly, Drosophila, identified 16 novel substrates for A-to-I editing that together provide 53 additional editing sites. All of these mRNAs are expressed in the central nervous system (CNS) and function in either electrical or chemical neurotransmission (Hoopengardner et al., 2003). Moreover, computational sequence alignments of expressed sequences with their human genomic counterparts mapped more than 12,000 A-to-I editing sites in more than 1600 genes. Interestingly, virtually all of these editing sites were found in noncoding regions, and 92% of these editing sites were found in Alu repeats (Levanon et al., 2004). The concentration of editing sites in Alu sequences can (at least partially) be explained by the design of this analysis, which was based on the selection of long stretches of double-stranded RNA (dsRNA) molecules, that is, a structure more likely formed between repetitive elements. Nevertheless, the study

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of Levanon et al. (2004) supports the idea that one role of A-to-I editing in noncoding regions of RNAs is to modify the stability of the RNA duplex. Moreover, as suggested by Levanon et al. (2004), the pronounced concentration of editing sites in Alu sequences could indicate that A-to-I editing also acts as an anti-transposition mechanism. Such a putative function joins the growing list of other functions of A-to-I editing in noncoding RNAs that have been identified. Among those are a role of RNA editing in preventing dsRNA from entering the RNA interference pathway (Tonkin and Bass, 2003) and altering the expression of regulatory micro-RNAs (Luciano et al., 2004). The extent to which site-specific A-to-I editing in exon sequences of mRNAs alters the functional properties of the encoded protein varies widely. A paradigmatic example of ‘‘life-saving,’’ site-specific A-to-I editing is the editing of the GluR-B Q=R site (Higuchi et al., 2000). The GluR-B gene encodes a subunit of the -amino-3-hydroxy-5-methylisoxazole propionate (AMPA) class of glutamate receptors that participates in the hetero-tetrameric assembly of glutamate receptors. Editing of the Q=R site changes a genomically encoded glutamine (Q) to an arginine (R). This single amino acid change occurs at a critical position of the peptide sequence that is involved in forming the channel pore, and it substantially decreases the calcium permeability of the receptor. Q=R-site editing of GluR-B is presently the only known vertebrate A-to-I editing site that is edited in more than 99.9% of all transcripts of the GluR-B gene, suggesting that this A-to-I editing corrects a genomic error. This is supported by results of studies on knockout mice showing that GluR-B transcripts must be edited when present to prevent early onset seizure and postnatal lethality (Higuchi et al., 2000). In contrast to the near-complete editing of the Q=R site of GluR-B, all other examples of site-specific A-to-I editing in exon sequences vary in frequency, and although editing also leads to amino acid changes in the respective peptides, these changes produce less dramatic phenotypes. This includes editing of the primary transcript of the 5-HT2C receptor, the first G protein–coupled receptor known to be edited. As outlined later, 5-HT2C pre-mRNA can be edited at five closely spaced sites that are located within a sequence encoding the second intracellular loop of the seven-transmembrane–spanning receptor (Burns et al., 1997; Niswender et al., 1999). This editing modulates signaling at central serotonergic synapses, and the magnitude of this modulation depends on the extent of editing at all five sites and on distinct editing-site preferences. Although 5-HT2C pre-mRNA editing modulates the eYciency with which the edited receptor couples to G protein, the cognate neurotransmitter (5-HT) itself can regulate 5-HT2C pre-mRNA editing (Gurevich et al., 2002a,b). Finally, the significance of 5-HT2C pre-mRNA editing in vivo is further underscored by findings of significant alterations in 5-HT2C pre-mRNA editing in the prefrontal cortex of suicide victims with a history of major depression, an illness thought to be associated with blunted signaling at serotonergic synapses in the forebrain neocortex (Gurevich et al., 2002b).

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III. Enzymes Responsible for A-to-I Editing and Their Substrate Requirements

The known A-to-I–edited RNAs are substrates for a group of enzymes known as adenosine deaminases acting on RNA (ADAR). These enzymes catalyze A-to-I conversions and they are expressed throughout the metazoan kingdom (Bass, 2002; Keegan et al., 2001, 2004; Schaub and Keller, 2002). In lower metazoans, such as Drosophila melanogaster and Caenorhabditis elegans, only one ADAR gene has been found (Schaub and Keller, 2002). In humans, however, three ADAR genes have been identified and (in the order of their discovery), they are named ADAR1, ADAR2, and ADAR3. ADAR1 and ADAR2 are expressed in all tissues. Both ADARs promiscuously deaminate adenosines present in extended dsRNA and viral transcripts, and they edit pre-mRNA transcripts in a sitespecific manner. ADAR3 is exclusively expressed in distinct anatomical regions of the CNS. The enzyme, however, was found to be catalytically inactive on synthetic dsRNA and known pre-mRNA substrates in vitro, although it can bind both single-stranded RNA and dsRNA. This has led to the suggestion either that the substrates for ADAR3 have yet to be identified or that the role of ADAR3 is to modulate the activity of ADAR1 and ADAR2 by competing for their RNA binding sites (Chen et al., 2000). ADARs are single polypeptides and they require no cofactor for enzyme activity. All ADARs share common domain features. These include an N-terminal region of varying length, a variable number of dsRNA binding domains, and a catalytic domain located at the carboxyl terminus of the peptide (Bass, 2002; Keegan et al., 2004; Schaub and Keller, 2002). Several isoforms of ADAR1 and ADAR2 have now been identified, and they exhibit diVerent editing activities (Schaub and Keller, 2002). The expression of ADAR1, for example, is under the control of four promoters. Whereas three of these promoters are constitutively active, the fourth promotor is interferon inducible, and the use of this promotor results in the generation of a predominantly cytoplasmic protein of 150 kd. Transcripts generated under the control of the constitutive promoters lead to the generation of exclusively nuclear proteins of 110 kd that lack the first 295 amino acids of the 150-kd form. Interestingly, ADAR2 pre-mRNA itself is a substrate for A-to-I editing. A single conversion of an intronic adenosine to inosine generates a new 30 splice site. Cleavage of this site results in a 47-nt insertion close to the start codon and shifts the open reading frame so that a shorter and inactive protein is translated that lacks both the dsRNA binding and the catalytic domain (Rueter et al., 1999). This autoediting of ADAR2 is thought to regulate endogenous levels of ADAR2. ADAR enzymes probably bind to many transcripts, but binding and catalysis are independent events (Keegan et al., 2004). Although ADARs were originally thought to act as monomers, evidence suggests that catalytic ADARs are dimers.

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Studies conducted in vitro have shown that dimerization requires RNA binding and that the assembly of ADAR dimers on the substrate RNA is necessary for catalysis to occur (Cho et al., 2003; Gallo et al., 2003; Jaikaran et al., 2002). ADARs do not primarily recognize specific nucleotide sequences of their substrates (Bass, 2002). Rather, the specificity of A-to-I editing is highly dependent on the duplex structure, its length, and the stability of the targeted RNA. Sitespecific A-to-I modification requires a dsRNA structure that is formed by intramolecular base pairing between sequences encompassing the editing site and an editing-site complementary sequence (ECS) often located in the downstream intron (Bass, 2002; Schaub and Keller, 2002; Schmauss and Howe, 2002). Completely double-stranded substrates are promiscuously deaminated, but sitespecific editing is supported by duplexes that are interrupted by mismatches, bulges, and internal loops. It is thought that structural disruptions of the duplex RNA structure at or near the editing site facilitates the recognition by ADARs and possibly facilitate base flipping of the targeted adenosine, a mechanism thought to accompany the deamination reaction (Bass, 2002; Schaub and Keller, 2002).

IV. A-to-I Editing of the 5-HT2C Receptor Pre-mRNA

As mentioned earlier in this chapter, the 5-HT2C receptor is the first G protein–coupled receptor known to be edited (Burns et al., 1997). The five exonic editing sites of 5-HT2C pre-mRNA are named A, B, C 0 (alternatively called E ), C, and D and, as shown in Fig. 1, editing at these sites alters three triplet codons. Editing at the A, D, and AB sites converts genomically encoded isoleucines (I) to valines (V). Editing at the B site converts an isoleucine to a methionine, and editing at the C site converts the genomically encoded asparagine (N) to a serine (S). Combined editing at the C0 and C sites generates a glycine (G) instead of the asparagine, and editing at the C0 site alone converts this asparagine to an aspartate (D). These site-specific editing events are catalyzed by ADAR1 and ADAR2 (Burns et al., 1997). Studies on knockout mice provide evidence for an almost exclusive role of ADAR2 in editing the D site and ADAR1 in editing A and B sites (Hartner et al., 2004; Higuchi et al., 2000; Wang et al., 2000a, 2004). The latter finding confirmed results of previous in vitro editing studies showing that three splice variants of ADAR1 eYciently edit the A site but not the D site (Liu et al., 1999). Because inactivation of both ADAR1 and ADAR2 completely abolishes 5HT2C pre-mRNA editing (Hartner et al., 2004), it appears that both ADAR1 and ADAR2 edit the C0 and C sites. It is, thus, plausible that the 50 editing-site preference of ADAR1 (A and B sites) and the corresponding 30 preference of

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FIG. 1. 5-HT2C pre–messenger RNA (pre-mRNA) duplex encompassing the editing region and changes in the coding potentials that result from A-to-I editing. (Top) Nucleotide sequence of the edited region of the 5-HT2C pre-mRNA aligned to the editing-site complementary sequence of the downstream intron. The position of the editing sites is indicated by arrows. (Bottom) Sequence of the 5-HT2C gene containing the editing region. The amino acids encoded by the gene are listed on top of the sequence and their changes in the coding potentials resulting from site-specific A-to-I editing are listed below the sequence. (See Color Insert.)

ADAR2 (D site) would decrease or increase access of the catalytic domain to the C0 and C sites when editing at A, B, or D sites is, respectively, increased or decreased (i.e., when more or less A, B, and D sites are occupied by the enzymes). This is supported by findings that decreased editing at the D site in the prefrontal cortex (PFC) of suicide victims with a history of major depression occurs together with increased editing at the C0 and C sites (Gurevich et al., 2002b), and that chronic fluoxetine treatment increases D-site editing by ADAR2, but editing of the C0 and C sites (which also requires ADAR2) is decreased (Gurevich et al., 2002a). In summary, editing could theoretically generate 32 additional mRNA isoforms that together encode 24 receptor isoforms. The position of the five editing sites within a sequence encoding the second intracellular domain of the receptor, a region thought to be of importance for optimal G protein activation, suggested that this editing modulates the ability of the receptor to activate G protein. As outlined later in this chapter, several studies have now demonstrated a clear link between 5-HT2C pre-mRNA editing and G protein–receptor coupling eYciency.

V. Modulation of 5-HT2C Receptor Function by RNA Editing

As outlined earlier in this chapter, A-to-I editing of 5-HT2C pre-mRNA alters the coding potentials of three triplet codons and hence the amino acid sequence at positions 156 (I), 158 (N), and 160 (I) of the predicted second intracellular loop

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(IL2) of this G protein–coupled receptor. This section summarizes results of pharmacological studies on various edited constructs expressed in transfected cells that illustrate the functional impairments of edited receptors compared with their nonedited isoform. The main eVector of 5-HT2C receptor–G protein activation is phospholipase C (PLC), and the Gq subunit of heterotrimeric G proteins mediates endogenous 5-HT2C receptor activation of PLC to stimulate the production of inositol phosphate and diaglycerol (Chang et al., 2000). The first report on the functional consequences of RNA editing for PLC activation described a 10- to 15-fold reduction in the coupling to phosphoinositol hydrolysis of the VGV (ABCD sites edited) isoform (Burns et al., 1997). This study pointed not only to a role of 5-HT2C pre-mRNA editing in modulating receptor–G protein interaction, it also provided further support for a role of the IL2 on G protein coupling. In addition, computer simulations that explored conformational properties of the edited IL2 (VGV) in comparison with nonedited IL2 (INI) revealed diVerences in the preferred spatial orientations with nonedited IL2 leading to larger populations of structures oriented toward the seventh transmembrane bundle and thus, greater spatial proximity to the third intracellular loop, whose role in G protein coupling is well established (Visiers et al., 2001). Subsequent studies analyzed in more detail how various edited isoforms diVer from nonedited isoforms in their ability to activate Gq protein, and the main findings of these studies are summarized in Table I. The study of Niswender et al. (1999) revealed a 5-, 9-, and 40-fold shift in the potency of 5-HT, ()-1-(-4-iodo2,5-dimethoxyphenyl)-2-aminopropane (DOI), and N,N-dimethyltryptamine (DMT), respectively, to stimulate PLC via activation of the edited isoform VSV (ABCD sites edited). This reduction was even larger (26-fold for 5-HT, 43-fold for DOI, and 91-fold for DMT) for the fully edited VGV isoform. In contrast, receptors edited at the A or D site alone, as well as transcripts edited at A(B)C or CD sites coupled to their cognate G protein in a manner indistinguishable from nonedited receptors (Niswender et al., 1999). Subsequent studies examined four additional isoforms that result from BCD-, C0 D, AC0 C, and C0 CD sites editing (MSV, IDV, VGI, and IGV isoforms) (Wang et al., 2000b). BCD- and C0 D-edited isoforms, like ABCD-edited isoforms, were also found to exhibit a fourfold reduction in PLC activation in response to serotonin stimulation. Moreover, AC0 C- and C0 CD-edited isoforms, like fully edited isoforms, exhibited a 13to 15-fold reduction in serotonin-stimulated PLC activation. Altogether, these studies indicate that 5-HT2C receptor isoforms encoded by transcripts edited at the ABCD sites, as well as other partially edited transcripts containing at least an inosine at the C0 site, exhibit a fourfold reduction in their ability to activate G protein. For fully edited receptor isoforms and other partially edited isoforms that are edited at least at the C0 and C site, this reduction is even larger (15- to 25-fold).

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TABLE I 5-HT2C PRE-mRNA EDITING REDUCES CONSTITUTIVE ACTIVITY AND SEROTONIN-STIMULATED PHOSPHOLIPASE C ACTIVATION

mRNA isoform

Receptor isoform

Nonedited

INI

A site edited D site edited ABC sites edited CD sites edited ABC0 CD sites edited ABCD sites edited

VNI INV VSI

BCD sites edited

MSV

C0 D sites edited AC0 C sites edited

IDV VGI

C0 CD sites edited

IGV

VGV VSV

5-HT2C R constitutive activity (relative to INI isoform)

5-HT–mediated stimulation of PLC (relative to INI isoform)

Reference value — — —

Reference value Unaltered Unaltered Unaltered

18-fold reduced Fourfold reduced

15- to 26-fold reduced Fourfold to fivefold reduced

12-fold reduced — Fivefold reduced Fivefold reduced

Fourfold reduced Fourfold reduced 15-fold reduced

References Niswender et al., 1999

Burns et al., 1997 Niswender et al., 1999; Wang et al., 2000b

Wang et al., 2000b

15-fold reduced

Consistent with its eVect on G protein activation, editing also aVects the aYnity of agonists for 5-HT2C receptors. This eVect was found to be proportional to the agonist’s intrinsic activity. Hence, reduced aYnities were larger for full agonists compared with partial agonists, and the aYnity of antagonists was unaVected (Fitzgerald et al., 1999). Moreover, ABCD- and ABC0 CD-edited receptors mediate agonist-stimulated calcium release that is both blunted and delayed when compared to nonedited receptor isoforms (Price and SandersBush, 2000). In addition to the reduced G protein activation in response to agonist stimulation, editing also reduces the constitutive activities of various receptor isoforms when compared to nonedited receptors (see Table I). Basal [3H]-inositol monophosphate productions were found to be 4- to 5-fold lower for ABCD-edited receptors (HerrikDavis et al., 1999; Niswender et al., 1999; Wang et al., 2000b), 5-fold lower for AC0 Cand C0 CD-edited isoforms, 12-fold lower for BCD-edited isoforms, and 18-fold lower for fully edited receptors (Wang et al., 2000b), and inverse agonists were consistently found to have no eVect in reversing the (substantially reduced) agonist-independent receptor activity of these receptor isoforms.

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Although the significance of constitutive activity in vivo remains to be established (especially for neocortical 5-HT2C receptors), a reduction or silencing of constitutive activity may have significant consequences for the traYcking and desensitization of 5-HT2C receptors. Marion et al. (2004) found that the magnitude of constitutive activity correlates with the ability of the receptor to bind -arrestin-2, which promotes endocytosis mediated by a GIRK=-arrestin-2– dependent mechanism. This reduces the cell surface expression of constitutively active receptors, and by virtue of a reduced interaction of edited receptors with -arrestin-2, the desensitization of these receptors with compromised ability to activate G protein would be slower compared with nonedited receptors (i.e., they would be available for agonist binding for a longer period). Another consequence of extensive 5-HT2C pre-mRNA editing appears to be an altered pattern of activation of heterotrimeric G proteins, which can shift preferred intracellular signaling pathways. For example, whereas nonedited 5-HT2C receptors can activate both Gq and a member of the G12 family of G proteins, G13, ABCD- and ABC0 CD-edited receptor isoforms can only activate Gq (Price et al., 2001). Furthermore, only nonedited receptors that couple to G13 can activate phospholipase D (PLD) via transactivation of the small G protein RhoA. Fully edited receptors, however, have lost the ability to stimulate transactivation of RhoA and PLD (McGrew et al., 2004). These findings led to the suggestion that RNA editing of the 5-HT2C receptor also modulates the activity of signaling pathways linked to actin cytoskeleton organization and regulated exocytosis, and Berg et al. (2001) suggested that fully edited isoforms are not capable of adopting ligand-specific conformations that would enable a diVerential interaction with diVerent signaling molecules. In summary, the link between 5-HT2C pre-mRNA editing and altered receptor function is now clearly established. The key outcome of 5-HT2C receptor editing is a downregulation of constitutive and agonist-stimulated receptor activity. This is due to substantially decreased basal and agonist-stimulated G protein–coupling eYciency, decreased agonist aYnity, and 5-HT potency, as well as coupling of diVerent G protein -subunits.

VI. 5-HT2C Pre-mRNA Editing Responses to Sustained Changes of Postsynaptic 5-HT2C Receptor Activation

Whereas 5-HT2C pre-mRNA editing modulates signaling at serotonergic synapses, sustained changes in serotonergic neurotransmission also lead to altered 5-HT2C pre-mRNA editing. This was first evident in studies using mice treated subacutely and chronically with the serotonin-selective reuptake blocker fluoxetine hydrochloride (also known as Prozac), a widely prescribed antidepressant

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drug (Table II). Chronic treatment of mice with fluoxetine altered editing of forebrain neocortical 5-HT2C pre-mRNA editing at three sites: It significantly increased editing at the C0 site, increased editing at the C site, and significantly decreased editing at the D site (Gurevich et al., 2002b). Interestingly, opposite changes in editing frequencies of these three sites were found in brains of patients with major depression (see later discussion), suggesting that chronic fluoxetine treatment can prevent the depression-specific changes in 5-HT2C pre-mRNA editing. At the time these data were published, it was still unclear whether fluoxetine elicited these changes in 5-HT2C pre-mRNA editing because fluoxetine elevates the synaptic concentration of 5-HT due to its blockade of 5-HT uptake, or whether the eVects of fluoxetine are due to its additional pharmacological property, namely competitive antagonism at 5-HT2C receptors (Ni and Miledi, 1997). Hence, to test more directly whether sustained increases and decreases of serotonergic neurotransmission involving 5-HT2C receptors alter 5-HT2C pre-mRNA editing in a bidirectional manner, Gurevich et al. (2002a) depleted mice of the neurotransmitter 5-HT and treated another group of mice

TABLE II 5-HT2C PRE-MRNA EDITING IN THE FOREBRAIN NEOCORTEX OF ADULT MALE 129SV MICE TREATED WITH DRUGS AFFECTING SEROTONERGIC AND DOPAMINERGIC NEUROTRANSMISSION

Treatment Saline 3-Day fluoxetinea 28-Day fluoxetine

Changes in editing site preferences

DOIb Haloperidolc

Normal editing phenotype Significantly decreased C0 -site editing Significantly decreased C0 -site editing Decreased C-site editing Significantly increased D-site editing No eVect Significantly decreased C0 -site editing Decreased C-site editing Significantly increased D-site editing Significantly increased C0 -site editing No eVect

Clozapined

No significant eVect

20% 5-HT depletion 80% 5-HT depletion

a

References Gurevich et al., 2002b Gurevich et al., 2002b Gurevich et al., 2002b

Gurevich et al., 2002a Gurevich et al., 2002a

Gurevich et al., 2002a M. T. Englander and C. S. (unpublished data) M. T. Englander and C. S. (unpublished data)

A serotonin-selective reuptake inhibitor and a 5-HT2C receptor antagonist. ()-1-(-4-iodo-2,5-dimethoxyphenyl)-2-aminopropane, a partial 5-HT2A=2C receptor agonist. c A typical neuroleptic drug blocking signaling through dopamine D2-like receptors. d An atypical neuroleptic drug blocking signaling through dopamine D2-like receptors and possibly a partial inverse 5-HT2C receptor agonist. b

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with the 5-HT2A=2C receptor partial agonist DOI. Results of these studies illustrated clearly that editing of 5-HT2C pre-mRNA is regulated in a serotonin-dependent manner (Table II). In 5-HT–depleted animals, editing at the C0 and C site is significantly decreased. This leads to a significantly increased expression of 5-HT2C mRNA isoforms encoding receptors with increased sensitivity to serotonin. Conversely, sustained activation of 5-HT2–like receptors with DOI results in significantly increased editing at the C0 site and leads to significantly increased expression of mRNA isoforms encoding 5-HT2C receptors with decreased sensitivity to serotonin. Moreover, the very similar results obtained with 5-HT–depleted and fluoxetine-treated animals further suggest that the eVects of fluoxetine on 5-HT2C pre-mRNA editing are due to its antagonist action at 5-HT2C receptors (Gurevich et al., 2002b). To this end, alterations in 5-HT2C pre-mRNA editing were only found for drugs aVecting serotonergic neurotransmission. Drugs blocking the D2 class of dopamine receptors, including the atypical neuroleptic drug clozapine (also thought to be a partial inverse agonist at 5-HT2C receptors; Umberto Spampinato, personal communication), have no significant eVect on 5-HT2C pre-mRNA editing when administered over a period of 4 days (Table II). Other studies further suggest that neither cocaine nor reserpine (drugs aVecting dopaminergic and to a lesser extent serotonergic neurotransmission) treatments significantly aVect 5-HT2C pre-mRNA editing (Iwamoto and Kato, 2002). In summary, studies on mice treated with drugs aVecting serotonergic neurotransmission involving 5-HT2C receptors have shown for the first time that 5-HT2C pre-mRNA editing is modulated by its cognate neurotransmitter.

VII. 5-HT2C Pre-mRNA Editing in the Human Prefrontal Cortex and Alterations in Editing-Site Preferences in Brains of Subjects with Major Depression

5-HT2C receptors are widely distributed in the brain, and in the adult brain, they are thought to play a role in regulating mood, appetite, anxiety, and sexual behavior (Roth et al., 1998). Moreover, because 5-HT2C receptor expression matures relatively late in postnatal development (Morilak and Ciaranello, 1993; Roth et al., 1991), they are also thought to be involved in late developmental maturation processes such as neuronal diVerentiation and dendritic maturation. Studies on 5-HT2C receptor knockout mice, however, found no substantial CNS abnormalities resulting from the constitutive inactivation of the receptor (Gaspar et al., 2003). However, several studies implicate the 5-HT2C receptor in the development of synaptic plasticity: (1) Mice lacking 5-HT2C receptors have deficits in hippocampal long-term potentiation (Tecott et al., 1995); (2) 5-HT2C receptors play a prominent role in the development of synaptic plasticity in the

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visual cortex during the critical period for optical dominance (Edagawa et al., 2001); (3) As described in the preceding section, RNA editing of 5-HT2C receptors responds to sustained changes in serotonergic neurotransmission, and altered serotonergic neurotransmission is thought to contribute to the pathophysiology of major depression (Gurevich et al., 2002a,b). In view of the known functions mediated by 5-HT2C receptors and their potential role in major psychopathologies, several groups have begun to test whether patients with major mental disorders would exhibit diVerences in 5-HT2C pre-mRNA editing (Schmauss, 2003). This was not an easy task because region-specific editing can generate multiple 5-HT2C receptor isoforms. In the human PFC, for example, Gurevich et al. (2002b) found that the majority of 5-HT2C mRNA is edited and 23 mRNA isoforms encode 15 diVerent receptors. Nevertheless, 15 of these mRNA isoforms (including the fully edited 5-HT2C mRNA) were only rarely detected (i.e., in less than 1% of all sequences). In brains of healthy human subjects, eight abundant mRNA isoforms (coding for seven receptor isoforms) represented more than 80% of all mRNA isoforms. Among those, the AC0 C-edited isoform that encodes a receptor with greatest reduction in G protein–coupling eYciency was found in more than 25% of all mRNAs, and mRNAs edited at the ABCD or A site were found in more than 10% of all sequences. Five additional mRNA isoforms (the nonedited, AD-, ABD-, ACD-, AC0 CD-edited isoforms) were found in 5–10% of all sequences. The results of this extensive nucleotide sequence analysis demonstrated the necessity of analyzing about 50 5-HT2C mRNA sequences for each tissue to reliably characterize editing at all five sites and, importantly, to obtain a replicable estimate of the relative percentages of major edited isoforms. For example, Sodhi et al. (2001) compared only 50 sequences pooled from five controls to 50 sequences pooled from five schizophrenic subjects (Brodmann’s area 46). This comparison revealed a reduction in editing-site frequencies at each of the five editing sites in the PFC of schizophrenics, which was largely due to the expression of the nonedited 5-HT2C mRNA receptor variant, which was found in 20% of the schizophrenic samples but not detected in controls. In contrast, Dracheva et al. (2003) performed a more extensive nucleotide sequence analysis to characterize 5-HT2C pre-mRNA editing (Brodmann’s area 46) in a very old population of long-term hospitalized schizophrenics in comparison to controls and found no diVerences between these groups. It must be stressed, however, that the old age of the subjects studied in the latter study complicates comparisons with all other studies that were conducted with tissues on substantially younger subjects. As long as a clear picture of the developmental profile of 5-HT2C pre-mRNA editing in humans remains elusive, the possibility that editing is more aVected by advanced age than by the chronic disease remains to be tested. Other studies replaced the laborious nucleotide sequence analysis with primer-extension–based analyses. This approach is limited to a maximum of three of

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the five editing sites and, hence, provides no information about the relative percentages of the major edited isoforms. Nevertheless, Niswender et al. (2001) analyzed 5-HT2C mRNA extracted from the left PFC (Brodmann’s areas 8 and 9) of 13 schizophrenic subjects, 13 subjects with major depression, and 13 controls. A primer-extension analysis of A-, C-, and D-site editing revealed no diVerences between the three groups. However, a comparison between suicide victims and controls, as well as suicide victims and nonsuicide victims with a psychiatric disorder, revealed a small (but significant) increase in A-site editing. A trend toward increased A-site editing in suicide victims (Brodmann’s area 10) was also reported by Iwamoto and Kato (2003) who performed a modified primer-extension analysis of editing at the A and D site. In both studies, no comprehensive nucleotide sequence analyses were conducted to confirm these findings. To date, the largest diVerences in 5-HT2C pre-mRNA editing were found in the PFC (Brodmann’s area 9) of patients with major depression. By comparing results of depressed suicide victims with their matched controls, Gurevich et al. (2002b) found significant diVerences in the mean percentages of AC0 C- and Asite edited isoforms. The expression of the AC0 C-edited mRNA was significantly (twofold) higher in depressed suicide victims. As illustrated in Table I, this mRNA isoform, like the fully edited mRNA, encodes a receptor protein that activates G protein least eYciently. In contrast, the expression of the A-site–edited isoform, that like nonedited 5-HT2C mRNA encodes a fully functional receptor, is significantly (more than twofold) reduced in depressed suicide victims. The diVerences are also evident when the frequencies of successful editing at all five sites were calculated for all sequences obtained from controls and depressed suicide victims. 5-HT2C mRNA sequences of depressed suicide victims were found to have significantly increased editing at the C0 site, a trend toward significantly increased editing at the C site and significantly decreased editing at the D site. These changes in editing-site preferences occur in the absence of changes in cytoplasmic expression levels of 5-HT2C mRNA, and none of the prefrontal cortical 5-HT2C pre-mRNAs were found to be spliced alternatively to yield the truncated nonfunctional 5-HT2Ctr mRNA isoform. Moreover, these changes were exactly opposite from those detected in mice treated chronically with the antidepressant drug fluoxetine (Gurevich et al., 2002b). We have completed a second study in which 15 additional subjects were analyzed (5 controls, 5 suicide victims with a history of major depression, 5 schizophrenic nonsuicides and suicides). These subjects were grouped into five closely matched triplets, each composed of one control, one depressed suicide, and one schizophrenic subject. An extensive nucleotide sequence analysis revealed essentially the same results obtained in the first study (Gurevich et al., 2002b) when depressed suicide victims were compared to their matched controls. Depressed suicide victims expressed significantly more 5-HT2C mRNA edited at the A(B)C0 C sites. Moreover, transcripts expressed in depressed suicide victims

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show the same changes in editing-site preferences, namely significantly increased editing at the C0 and C site and significantly decreased editing at the D site. No significant changes were found in schizophrenic subjects, regardless of whether they committed suicide (M. T. Englander, S. Dulawa, V. Arango, J. J. Mann, A. Dwork, G. Rosoklija, and C. S., unpublished results, 2004). In summary, altered editing of 5-HT2C pre-mRNA results from significant changes in editing-site preferences of the C0 , C, and D site. As shown earlier, under normal conditions, editing of these sites was also found to be regulated in a serotonin-dependent manner (Gurevich et al., 2002a). In brains of depressed patients, however, editing significantly increases the pool of 5-HT2C mRNA encoding receptors with reduced function (Schmauss, 2003). Such decreased serotonergic signaling elicited by RNA editing could, thus, accentuate the sequelae of lower forebrain serotonergic neurotransmission thought to underlie major depression. Interestingly, it has long been known that recombinant interferon- (IFN-), used in the treatment of malignant tumors, multiple sclerosis, and viral hepatitis, induces severe depressive symptoms. Yang et al. (2004) tested whether IFN- treatment would aVect 5-HT2C pre-mRNA editing by virtue of inducing increased expression of the IFN-inducible expression of the 150-kd ADAR1 isoform. Indeed, Yang et al. (2004) found that increased IFN-–induced ADAR1 expression in human glioblastoma cells alters the editing pattern of 5-HT2C pre-mRNA by increasing editing at the predominant target sites for ADAR1 (A and B) and the C site, thus suggesting the possibility that this increased editing, in particular increased C-site editing, contributes to the depression-like side eVects observed with cytokine treatment.

VIII. Conclusions and Future Directions

At first glance, the alterations in 5-HT2C pre-mRNA editing may appear to be at odds with the normal serotonin-dependent regulation of 5-HT2C premRNA editing. However, there is no direct evidence that the eVects of serotonin on 5-HT2C pre-mRNA editing per se are defective in the PFC of patients with major depression. In fact, a more plausible explanation could be that the sensitivity of 5-HT2C pre-mRNA editing response to even minute increases of 5-HT release is increased in depressed brains and, thus, ultimately leads to the editing pattern described here. Studies have shown significant changes in 5-HT2C pre-mRNA editing in the forebrain of mice that were treated with drugs aVecting serotonergic transmission. Future studies on these animals that investigate the eVects of behavioral (rather than pharmacological) manipulations on 5-HT2C pre-mRNA editing

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could provide meaningful insights into the modulation of 5-HT2C pre-mRNA editing by behavioral states that characterize depression. A number of animal paradigms have now been developed that are known to alter 5-HT release and that rely on such behavioral despair responses of the animal that are not only thought to mimic depression, but that are also susceptible to chronic (but not acute) antidepressant treatment. It is also still unclear whether there is a genetic determinant for 5-HT2C premRNA editing-site preferences that are specific for patients with major depression. For example, such a determinant could be a polymorphism in the intron of the 5HT2C gene that encompasses the editing complementary sequence and alters the duplex RNA structure and, hence, the recognition of distinct editing sites by ADARs. Furthermore, a brain-specific guide snoRNA with sequence complementarity to the editing region of the 5-HT2C mRNA has been identified. Intriguingly, its putative site for 20 -O-methylation of the mRNA is the C-editing site (Cavaille et al., 2000). Methylation can reduce the rate of deamination such that the extent of C-site editing might be determined by an interplay between methylation and deamination. It would, therefore, be of great interest to compare the expression of this snoRNA in postmortem brains of depressed subjects and their controls. Finally, although the analysis of 5-HT2C pre-mRNA editing in vivo is laborious, its sensitive regulation by various stimuli makes 5-HT2C pre-mRNA a prime substrate for future studies on the role of A-to-I editing in synaptic neurotransmission and diseases of the CNS.

References

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Cho, D. S., Yang, W., Lee, J. T., Shiekattar, R., Murray, J. M., and Nishikura, K. (2003). Requirement of dimerization for RNA editing activity of adenosine deaminases acting on RNA. J. Biol. Chem. 278, 17093–17102. Dracheva, S., Elhakem, S. L., Marcus, S. M., Siever, L. J., McGurk, S. R., and Haroutunian, V. (2003). RNA editing and alternative splicing of human serotonin 2C receptor in schizophrenia. J. Neurochem. 87, 1402–1412. Edagawa, Y., Saito, H., and Abe, K. (2001). Endogenous serotonin contributes to a developmental decrease in long-term potentiation in the rat visual cortex. J. Neurosci. 21, 1532–1537. Fitzgerald, L. W., Iyer, G., Conklin, D. S., Krause, C. M., Marshall, A., Patterson, J. P., Tran, D. P., Jonak, G. J., and Hartig, P. R. (1999). Messenger RNA editing of the human 5-HT2C receptor. Neuropharmacology 21, 82S–90S. Gallo, A., Keegan, L. P., Ring, G. M., and O’Connell, M. A. (2003). An ADAR that edits transcripts encoding ion channel subunits functions as a dimer. EMBO J. 22, 3421–3430. Gaspar, P., Cases, O., and Maroteaux, L. (2003). The developmental role of serotonin: News from mouse molecular genetics. Nat. Rev. Neurosci. 4, 1002–1012. Gurevich, I., Englander, M. T., Adlersberg, M., Siegal, N., and Schmauss, C. (2002a). Modulation of serotonin 2C receptor editing by sustained changes in serotonergic neurotransmission. J. Neurosci. 22, 10529–10532. Gurevich, I., Tamir, H., Arango, V., Dwork, A., Mann, J. J., and Schmauss, C. (2002b). Altered editing of serotonin 2C receptor pre-mRNA in the prefrontal cortex of depressed suicide victims. Neuron 43, 349–356. Hartner, J. C., Schmittwolf, C., Kispert, A., Mueller, A. M., Higuchi, M., and Seeburg, P. H. (2004). Liver disintegration in the mouse embryo by deficiency in RNA editing enzyme ADAR1. J. Biol. Chem. 279, 4894–4902. Herrik-Davis, K., Grinde, E., and Niswender, C. (1999). Serotonin 5-HT2C receptor RNA editing alters receptor basal activity: Implications for serotonergic signal transduction. J. Neurochem. 73, 1711–1717. Higuchi, M., Maas, S., Single, F. N., Hartner, J., Rozov, A., Burnashev, N., Feldmeyer, D., Sprengel, R., and Seeburg, P. H. (2000). Point mutation in an AMPA receptor gene rescues lethality in mice deficient in the RNA-editing enzyme ADAR2. Nature 399, 75–80. Hoopengardner, B., Bhalla, T., Staber, C., and Reenan, R. (2003). Nervous system targets of RNA editing identified by comparative genomics. Science 301, 832–836. Iwamoto, K., and Kato, T. (2002). EVect of cocaine and reserpine administration on RNA editing of rat 5-HT2C receptor estimated by primer extension combined with denaturing high-performance liquid chromatography. Pharmacogenomics J. 2, 335–340. Iwamoto, K., and Kato, T. (2003). RNA editing of serotonin 2C receptor in human postmortem brains of major mental disorders. Neuroscience Lett. 346, 169–172. Jaikaran, D. C., Collins, C. H., and MacMillan, A. M. (2002). Adenosine to inosine editing by ADAR2 requires formation of a ternary complex on the GluR-B R=G site. J. Biol. Chem. 277, 37624–37629. Keegan, L. P., Gallo, A., and O’Connell, M. A. (2001). The many roles of an RNA editor. Nat. Rev. Genet. 2, 869–878. Keegan, L. P., Leroy, A., Sproul, D., and O’Connell, M. A. (2004). Adenosine deaminases acting on RNA (ADARs): RNA editing enzymes. Genome Biology 5, 209. Levanon, E. Y., Eisenberg, E., Yelin, R., Nemzer, S., Hallegger, M., Shemesh, R., Fligelman, Z. Y., Shoshan, A., Pollock, S. R., Sztybel, D., Olshansky, M., Rechavi, G., and Jantsch, M. (2004). Systematic identification of abundant A-to-I editing sites in the human transcriptome. Nat. Biotechnology 22, 1001–1005. Liu, Y., Emeson, R. B., and Samuel, C. E. (1999). Serotonin-2C receptor pre-mRNA editing in rat brain and in vitro by splice variants of the interferon-inducible double stranded RNA-specific adenosine deaminase ADAR1. J. Biol. Chem. 274, 18351–18358.

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Luciano, D. J., Mirsky, H., Vendetti, N., and Maas, S. (2004). RNA editing of a miRNA precursor. RNA 10, 1174–1177. Maas, S., Rich, A., and Nishikura, K. (2003). A-to-I RNA editing: Recent news and residual mysteries. J. Biol. Chem. 278, 1391–1394. Marion, S., Weiner, D. M., and Caron, M. G. (2004). RNA editing induces variation in desensitization and traYcking of 5-hydroxytryptamine 2C receptor isoforms. J. Biol. Chem. 279, 2945–2954. McGrew, L., Price, R. D., Hackler, E., Chang, M. S. S., and Sanders-Bush, E. (2004). RNA editing of the human serotonin 5-HT2C receptor disrupts transactivation of the small G-protein RhoA. Mol. Pharmacol. 65, 252–256. Morilak, D. A., and Ciaranello, R. D. (1993). Ontogeny of 5-hydroxytryptamine 2 receptor immunoreactivity in the developing rat brain. Neurosci. 55, 869–880. Ni, Y.G., and Miledi, R. (1997). Blockade of 5-HT2C serotonin receptors by fluoxetine (Prozac). Proc. Natl. Acad. Sci. USA 94, 2036–2040. Niswender, C., Copeland, S. C., Herrik-Davis, K., Emeson, R. B., and Sanders-Bush, E. (1999). RNA editing of the human serotonin 5-hydroxytryptamine 2C receptor silences constitutive activity. J. Biol. Chem. 274, 9472–9478. Niswender, C. M., Herrick-Davis, K., Dilley, G., Meltzer, H. Y., Overholser, J. C., Stockmeier, C. A., Emeson, R. B., and Sanders-Bush, E. (2001). RNA editing of the human serotonin 5-HT2C receptor: Alterations in suicide and implications for serotonergic pharmacology. Neuropsychopharmacology 24, 478–491. Paul, M. S., and Bass, B. L. (1998). Inosine exists in mRNA at tissue-specific levels and is most abundant in brain mRNA. EMBO J. 17, 1120–1127. Price, R. D., and Sanders-Bush, E. (2000). RNA editing of the human 5-HT2C receptor delays agonist-stimulated calcium release. Mol. Pharmacol. 58, 859–862. Price, R. D., Weiner, D. M., Chang, M. S. S., and Sanders-Bush, E. (2001). RNA editing of the human serotonin 5-HT2C receptor alters receptor-mediated activation of G13 protein. J. Biol. Chem. 276, 44663–44668. Roth, B. L., Hamblin, M. W., and Ciaranello, R. D. (1991). Developmental regulation of 5-HT2 and 5-HT1C mRNA and receptor levels. Dev. Brain Res. 58, 51–58. Roth, B. L., Willins, D. L., Kristiansen, K., and Kroetze, W. K. (1998). 5-hydroxytryptamine2-family receptors (5-hydroxytryptamine2A, 5-hydroxytryptamine2B, 5-hydroxytryptamine2C): Where structure meets function. Pharmacol. Ther. 79, 231–257. Rueter, S. M., Dawson, T. R., and Emeson, R. B. (1999). Regulation of alternative splicing by RNA editing. Nature 399, 75–80. Schaub, M., and Keller, W. (2002). RNA editing by adenosine deaminases generates RNA and protein diversity. Biochemie 84, 791–803. Schmauss, C. (2003). Serotonin 2C receptors: Suicide, serotonin, and runaway RNA editing. The Neuroscientist 9, 237–242. Schmauss, C., and Howe, J. R. (2002). RNA editing of neurotransmitter receptors in the mammalian brain. Science’s stke. Available at: www.stke.org=cgi=content=full=OC_sigtrans;2002=133=pe26. Seeburg, P. H. (2002). A-to-I editing: New and old sites, functions and speculations. Neuron 35, 17–20. Seeburg, P. H., and Hartner, J. (2003). Regulation of ion channel=neurotransmitter receptor function by RNA editing. Curr. Opinion Neurobiol. 13, 279–283. Sodhi, M. S., Burnet, P. W. J., MakoV, A. J., Kerwin, R. W., and Harrison, P. J. (2001). RNA editing of the 5-HT2C receptor is reduced in schizophrenia. Mol. Psychiatry 6, 373–379. Tecott, L. H., Sun, L. M., Akana, S. F., Strack, A. M., Lowenstein, D. H., Dallman, M. F., and Julius, D. (1995). Eating disorder and epilepsy in mice lacking 5-HT2C serotonin receptors. Nature 374, 542–546.

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Tonkin, L. A., and Bass, B. L. (2003). Mutations in RNAi rescue aberrant chemotaxis of ADAR mutants. Science 302, 1725. Visiers, I., Hassan, S. A., and Weinstein, H. (2001). DiVerences in conformational properties of the second intracellular loop (IL2) in 5-HT2c receptors modified by RNA editing can account for G protein coupling eYciencies. Protein Eng. 14, 409–414. Wang, Q., Khillan, J., Gadue, P., and Nishikura, K. (2000a). Requirement of the RNA editing deaminase ADAR1 gene for embryonic erythropoiesis. Science 290, 1765–1768. Wang, Q., O’Brien, P., Chen, C.-X., Cho, D.-S. C., Murray, J. M., and Nishikura, K. (2000b). Altered G protein–coupling functions of RNA editing isoform and splicing variant serotonin 2C receptors. J. Neurochem. 74, 1290–1300. Wang, Q., Miyakoda, M., Yang, W., Khillan, J., Stachura, D. L., Weiss, M. J., and Nishikura, K. (2004). Stress-induced apoptosis associated with null mutation of ADAR1 RNA editing deaminase gene. J. Biol. Chem. 279, 4952–4961. Yang, W., Wang, Q., Kanes, S., Murray, J. M., and Nishikura, K. (2004). Altered RNA editing of serotonin 5-HT2C receptor induced by interferon: Implications for depression associated with cytokine therapy. Mol. Brain Res. 124, 70–78.

THE DOPAMINE HYPOTHESIS OF DRUG ADDICTION: HYPODOPAMINERGIC STATE

Miriam Melis,y Saturnino Spiga,z and Marco Diana*

*G. Minardi Laboratory of Cognitive Neuroscience, Department of Drug Sciences University of Sassari, 01700 Sassari, Italy B.B. Brodie Department of Neuroscience, University of Cagliari, 09042 Monserrato, Italy z Department of Animal Biology and Ecology, University of Cagliari, 09126 Cagliari, Italy

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I. Drug Addiction as a Brain Disease II. The Mesolimbic Dopamine System A. Intrinsic Properties B. AVerent Regulation C. Response to Acute Drugs D. Response to Chronic Drugs E. Activity After Withdrawal from Chronic Administration III. Behavioral Animal Models A. Self-Administration Studies B. Intracranial Self-Stimulation C. Place-Conditioning Studies IV. Biochemical Studies A. Microdialysis B. Biomolecular Investigations C. Microanatomical Studies V. Primate Studies A. Nonhuman Primates B. Humans VI. Conclusions References

Drug addiction is a brain disorder caused by the repetitive use of various chemicals which alter normal functioning of the central nervous system with consequent behavioral abnormalities. In the search to understand which neurotransmitter systems play upon this behavioral pathology, dopamine has long been thought to play a prima donna role. However, its primary role is commonly and erroneously attributed to the increase in activity after acute administration of addicting drugs. On the contrary, the mesolimbic dopamine transmission appears to be drastically reduced in its tonic activity when measured in animal models, which mimic the human condition of drug addiction, and in the available human studies conducted in addicted subjects. This paper is a systematic review of the pertinent literature which strongly supports this concept. Various

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experimental approaches such as electrophysiological, biochemical, behavioral, biomolecular and even anatomical, show that dopamine neurons work insuYciently in the crucial phases of the entire drug addiction cycle such as withdrawal from chronic treatment. This hypodopaminergic state is viewed as one of the main causes that triggers drug-seeking and taking, even after prolonged drug-free periods, perpetuating the vicious cycle. In addition, albeit reduced in its activity, the system remains hyperresponsive to abused drugs conferring long-lasting vulnerability to the system. We propose that decreased dopamine function in addicted subjects results in a decreased interest to non drug-related stimuli and increased sensitivity to the drug of choice. Targeting the dopamine system with pharmacological agents, not necessarily classic receptor-oriented drugs, aimed at restoring dopamine transmission may reveal useful new avenues in the treatment of this socially debilitating brain pathology.

I. Drug Addiction as a Brain Disease

Although the phenomenon of drug abuse has been typically perceived as a ‘‘moral’’ (Musto, 1997; O’Brien and Fishman, 2002) defect (and still is by some) and=or character weakness, the persuasive nature of data emerging from rigorous scientific investigation renders this view obsolete and no longer tenable. It is widely and increasingly recognized, nowadays, as a brain disease. This holds true for the scientific community and its ample recognition leans on support from a number of institutions that provide means to investigate its pathophysiological basis. Indeed, not diVerent from traditional diseases, drug addiction bears with it a number of biological abnormalities that have been documented by employing behavioral, electrophysiological, biochemical, and morphological methods, all of which point at an altered brain physiology, which justifies the label disease. Although repetitive use of drugs aVects diVerent organs (i.e., alcohol aVects the liver), the primary target appears to be the brain—thus, brain disease. The conceptualization of drug addiction as a brain pathology has profound social reflections because it implies a total absence of moral connotation, and thus, a drug abuser is not a ‘‘criminal’’ but simply a ‘‘patient’’ who needs treatment irrespective of the causes that triggered the drug-taking behavior. Once accepted, the disease concept prompts further questions: What has occurred in the brain of an addicted individual? A simple attempt to provide an answer will spur such an enormous amount of data that it would be impossible to cover in a chapter; however, a neurotransmitter system (i.e., the mesolimbic dopamine [DA] system) appears to be modified in its functioning more than others and appears to fluctuate diVerently and predictably, depending on acute drug

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challenge, chronic drug treatments, and withdrawal conditions, irrespective of the chemical abused. This is not to say that other systems are not involved or important in the pathophysiology of addiction. It simply suggests that the DA system participates in the most harmful consequences of repetitive drug use and is a major determinant of craving and relapse even after drug-free periods. Accordingly, the DA system reduces its activity under circumstances that mimic ‘‘urge’’ (craving) for the drug that drives behavior toward seeking and ultimately obtaining (drug taking) the desired molecule, thus perpetuating the cycle. In brief, the ‘‘dopamine hypothesis’’ contends that a hypodopaminergic state characterizes animal models of drug addiction and addicted human brains, and the frequently cited increase in activity after acute drug challenge plays only a minor initial role in the context of the disease and its development over time. Neurobiological mechanisms thought to be at the basis of the disease have been reviewed extensively. In 1978, in an elegant series of studies (Fouriezos et al., 1978; Wise, 1978), Wise first hypothesized that activation of the reward system was closely associated with an increased activity of DA-containing pathways (Corbett and Wise, 1980), and not noradrenergic (Corbett and Wise, 1979; Yokel and Wise, 1975, 1976) pathways, produced by electrical self-stimulation of ascending DA fibers. In particular, the mesolimbic pathway, which projects from the ventral tegmental area (VTA) to the nucleus accumbens (NAcc) has been hypothesized to mediate reward of pleasant stimuli such as various addictive drugs (Bozarth and Wise, 1981; De Wit and Wise, 1977; Yokel and Wise, 1975; 1976), drinking (Gerber et al., 1981), food (Wise et al., 1978a,b), and even sex (Balfour et al., 2004). Today the role of the mesolimbic DA system is well established: Intracranial self-stimulation (ICSS) electrodes located in the lateral hypothalamus or in the medial forebrain bundle indirectly stimulate (Yeomans, 1989; Yeomans et al., 1993, 2000) (depolarize) ascending DA-containing fibers whose synaptic terminals release DA, which in turn binds postsynaptic DA receptors, thereby potentiating DA neurotransmission. In addition, chemical lesions of DA fibers (Fibiger, 1978; Fibiger et al., 1976) or administration of DA antagonists (Fibiger, 1978; Fibiger et al., 1976) produces a decreased sensitivity to ICSS. Although the issue of neuroleptic-induced motor performance deficits was initially suspected as the cause of ICSS disruption (Fibiger et al., 1976), additional experiments confirmed the major role played by DA in reward (Wise and Bozarth, 1982). A large amount of experimental studies have been carried out with the purpose of clarifying the link between DA and reward, but a detailed account of the specific literature is beyond the scope of this chapter. The reader is referred to the recent excellent reviews (Di Chiara, 1999; Hyman and Malenka, 2001; Kakade and Dayan, 2002; Robbins and Everitt, 1996; Salamone et al., 1997; Schultz,

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1998a,b), which have attempted to disentangle the complex role of DA in animal behavior. In spite of the tremendous amount of data, the role of DA neurons in the physiology of reward is still a matter of intense scientific debate. One influential theory suggests that mesolimbic DA mediates reward through pleasurable eVects of addictive drug (Wise and Bozarth, 1982), and other works suggest that DA signals interest in reward (Stewart, 1984), the expectation that reward is forthcoming (Schultz, 1998a,b), or wanting reward as opposed to liking it (Berridge and Robinson, 1998; Robinson and Berridge, 1993). Still others argue about the prominent role that DA plays in incentive motivation (Di Chiara, 1999; Di Chiara et al., 1999) or appetitive learning (Cardinal and Everitt, 2004; Robbins and Everitt, 2002). DA neuronal activity may be part of a continuum in which these cells modify firing rate and=or pattern according to the pleasantness=aversiveness of the stimulus. Indeed, experiments using drugs of abuse as a stimulus, pleasant when acutely administered or unpleasant as during withdrawal, support this conclusion (Pulvirenti and Diana, 2001). In addition, experiments not employing drugs, but various experimental conditions, further support this notion. Schultz et al. (1997) have shown that when a monkey receives a reward (apple), DA neurons increase their firing rate but not when the light that signals the reward is turned on. After training, DA neurons increase their activity when the animal sees the light (conditioning stimulus) and not when it receives the actual reward (apple). However, if after the light, the reward is not presented, DA neurons ‘‘decrease’’ their firing activity. These experiments indicate that DA neurons are sensitive to both like (reward) and dislike (absence of an ‘‘expected’’ reward). The increase in firing observed after learning upon turning on the light suggests that the ‘‘reward value’’ is now attributed (by the animal) to the light that signals the forthcoming ‘‘real’’ reward. Accordingly, Ungless et al. (2004), working with anesthetized rats, have shown that tyrosine hydroxylase–positive (THþ) units decrease their firing in aversive circumstances, whereas electrophysiologically similar units, probably not dopaminergic and certainly not THþ, do not. Collectively, these experiments are reminiscent of those employing drugs of abuse as a stimulus (see later discussion) and strongly support the assertion of a direct signaling of DA neurons of pleasant=unpleasant conditions. In this chapter, we assume that an acute drug challenge is a pleasant stimulus, whereas withdrawal from chronic administration is perceived as an unpleasant or aversive situation. Controversy and disagreement with respect to the interpretation of data is common in the scientific literature; literature on the involvement of dopaminergic neurons in drug addiction is no exception. Where relevant, we point out some of the current areas of contention and discuss them in light of more recent findings.

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II. The Mesolimbic Dopamine System

A. Intrinsic Properties A first detailed description of the dopaminergic systems in the rat brain revealed three discrete regions containing about 75% of the DA neurons contained in the entire brain (Dahlstrom and Fuxe, 1964). The DA cells located within the VTA project to the limbic subcortical areas (i.e., NAcc, amygdala, and olfactory tubercle) and to the limbic cortices (i.e., medial prefrontal, cingulated, and entorhinal), thereby constituting the mesolimbocortical system (Anden et al., 1966; Bjorklund and Lindvall, 1975; Lindvall and Bjorklund, 1974; Loughlin and Fallon, 1983; Ungerstedt, 1971). This chapter focuses on mesolimbic DA neurons, which have been extensively characterized by means of electrophysiological techniques both in vivo (Aghajanian and Bunney, 1977; Bunney et al., 1973; Ungless et al., 2004) and in vitro (Grace and Onn, 1989; Johnson and North, 1992b; Lacey et al., 1990). In vivo, VTA DA neurons display a typical firing pattern that is either single spiking or consisting of bursts of action potentials (Bunney et al., 1973; Grace and Bunney, 1984a,b). The bursting mode has been shown to be more eYcient in increasing DA outflow in the terminal regions than the single-spike firing mode (Bean and Roth, 1991; Diana and Tepper, 2002; Gonon, 1988; Gonon and Buda, 1985; Overton and Clark, 1997); therefore, it might mediate synaptic changes and contribute to reward-related learning processes (Gonon, 1988; Reynolds and Wickens, 2002; Reynolds et al., 2001; Schultz et al., 1997; Wightman and Robinson, 2002; Williams and Millar, 1990). The action potential of a typical midbrain DA neuron has a characteristic triphasic shape of a width greater than 2 ms (Bunney et al., 1973; Diana and Tepper, 2002; Grace and Bunney, 1983a,b, 1984a; Groves et al., 1975), which has been more properly refined to be greater than 1.1 ms when measured from the start of the action potential to the negative trough (Ungless et al., 2004). Interestingly, this latter study showed, for the first time since the first characterization, that in vivo the VTA also possesses a third class of cells that are neither dopaminergic nor GABAergic, although they resemble dopaminergic cells based on their electrophysiological properties. Consistently, an in vitro study previously showed that the VTA does possess a subset of cells that are nondopaminergic but that do exhibit similar anatomical and electrophysiological features to DA cells in the VTA (Cameron et al., 1997). In the intact brain (Grace and Bunney, 1983a,b, 1984a,b), it has been diYcult to evaluate the intrinsic properties of these cells because of the mutual interactions, multiple inputs, and strong feedback from the target areas and within the VTA. However, intracellular recordings of midbrain DA neurons in vivo have

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established that DA units display long membrane time constants (5–14 ms), high input resistance (RIN; between 18 and 45 MegaOhms) and resting membrane potentials (RMPs) greater than 50 mV (Grace and Bunney, 1983c, 1984b). In agreement with extracellular recordings of VTA DA cells (Bunney et al., 1973; Ungless et al., 2004), intracellular analysis carried out in vivo has shown that DA neurons have long-duration action potentials (2–5 ms) followed by an afterhyperpolarization period (AHP) (3 mV, 1–6 ms) related to activation of a calcium-dependent potassium current (IKCa). VTA DA cells in vitro are mainly characterized by a regular (pacemaker-like), single-spike spontaneous firing ( Johnson and North, 1992b; Lacey, 1993) presumably because of the loss of extrinsic aVerents impinging on these neurons. The action potential has a long duration (>2 ms), a pronounced AHP, and a sag component, which is mediated by a hyperpolarization-activated, cyclic nucleotide–regulated cation channels (Ih) evoked in response to hyperpolarizing pulses (Grace and Onn, 1989; Johnson and North, 1992b; Mercuri et al., 1995; Richards et al., 1997). Interestingly, NeuhoV et al. (2002) have demonstrated that DA midbrain subpopulations significantly diverge from a single electrophysiological phenotype (Kitai et al., 1999) and that diVerences in Ih, probably corresponding to diVerent densities of functional Ih channels, might be an important mechanism responsible for the functional diversity of DA cells. Particularly, NeuhoV et al. (2002) demonstrated that VTA DA cells positively labeled for calbindin (CBþ) and evoking small Ih currents displayed an irregular discharge at higher frequencies with a prolonged AHP. This rebound delayztended to be longer in CBþ DA neurons whose position was closer to the midline of the midbrain. Because these CBþ VTA DA cells displayed fast pacemaker frequencies (>5 Hz), a number of authors suggested that they might represent the subpopulation of VTA DA neurons projecting to the prefrontal cortex (Chiodo et al., 1984; Gariano et al., 1989). Conversely, CB VTA DA cells localized laterally within the VTA responding with large Ih currents are more likely to form the mesolimbic pathway (Carr and Sesack, 2000; Oades and Halliday, 1987). Ih currents are not essential for setting the RIN of DA neurons (Mercuri et al., 1995), although they play a key role at more hyperpolarized potentials (around 100 mV) (Amini et al., 1999). The RIN of DA neurons in vitro is significantly higher (up to 300 MegaOhms) than that observed in vivo, which might be the result of deaVerentation of the slice preparation (Grace and Bunney, 1983a,c). It is widely accepted that a Naþ-dependent current mainly contributes to the slow oscillatory potentials (SOPs) (Grace and Onn, 1989; Nedergaard et al., 1993; Ping and Shepard, 1996). Additionally, Amini et al. (1999) provided elegant evidence for the Ca2þ-dependent mechanisms underlying SOP. They demonstrated that SOPs are due to activation of l-type Ca2þ currents (ICa,L), leading to

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depolarization of the membrane and increased levels of intracellular Ca2þ. The Ca2þ increase, in turn, activates small-conductance IK,Ca (IK,Ca,SK), hyperpolarizes the cell membrane, and depresses ICa,L and intracellular Ca2þ levels (Amini et al., 1999). This spontaneous pacemaker activity can be blocked by dihydropyridines (Mercuri et al., 1995) because the Ca2þ conductance mediating the SOP is dihydropyridine sensitive (Ping and Shepard, 1999). The regular firing pattern is dependent on activation of 4-aminopyridine (4-AP)–sensitive currents (IA), which slow the recovery of membrane potential ( VM) (Silva et al., 1990). In vitro VTA DA cells can also display burst activity when N-methyl-daspartate (NMDA) and the small-conductance Ca2þ-dependent Kþ channel (SK) blocker, apamin, are applied (Seutin et al., 1993). Otherwise, DA cells can switch from the pacemaker-like firing to a bursting mode when group I mGluRs are activated and SK reduced (Mercuri et al., 1993; Prisco et al., 2002; Zheng and Johnson, 2002). Both types might bear relevance in information coding and ultimately result in the translation of the glutamatergic signal into the dopaminergic one onto their target neurons in the forebrain.

B. Afferent Regulation The striking diVerences between the characteristics of VTA DA cells recorded in vivo and in vitro reveal the weight of the inputs on the control of both the spontaneous activity of these neurons (Johnson and North, 1992b) and the somatodendritic DA release (Chen and Rice, 2002), which contributes to the regulation of the burst firing through a network feedback mechanism (Paladini et al., 2003). VTA DA cells possess an additional self-regulatory mechanism that involves the endocannabinoid system, a novel class of retrograde messengers (Piomelli, 2003). In fact, VTA DA cells release endocannabinoids in an activity-dependent manner, which depresses glutamatergic aVerents on mesolimbic DA cells (Melis et al., 2004a) and ultimately their own firing activity and pattern (Melis et al., 2004b). The aVerent inputs to VTA DA neurons comprise glutamatergic (Alheid et al., 1998; Carr and Sesack, 2000; Charara et al., 1996; Christie et al., 1985; Sesack and Pickel, 1992; Smith et al., 1996; Taber et al., 1995; Thierry et al., 1983), GABAergic (Spanagel and Weiss, 1999; Waddington and Cross, 1978), cholinergic (Garzon et al., 1999; Oakman et al., 1995; Semba and Fibiger, 1992; Woolf, 1991), serotonergic (Herve et al., 1987), and noradrenergic fibers (Bayer and Pickel, 1990). 1. Glutamatergic Main sources of glutamatergic inputs to the VTA arise from the prefrontal cortex (Carr and Sesack, 2000; Christie et al., 1985; Sesack and Pickel, 1992; Smith et al., 1996; Taber et al., 1995; Thierry et al., 1983), the pedunculopontine

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region (Charara et al., 1996; Kelland et al., 1993), and the bed nucleus of the stria terminalis (Alheid et al., 1998; Georges and Aston-Jones, 2001, 2002). Through activation of ionotropic (Chergui et al., 1993; Wang and French, 1993a,b, 1995) and metabotropic receptors (Mercuri et al., 1993; Shen and Johnson, 1997), glutamate is thought to regulate the spontaneous activity of VTA DA cells in vivo (Charlety et al., 1991; GrenhoV et al., 1988; Svensson and Tung, 1989). Consistently, in vitro, electrical stimulation of the aVerents elicits postsynaptic currents mediated by activation of ionotropic ( Johnson and North, 1992b; Mercuri et al., 1992b; Seutin et al., 1990) and=or metabotropic receptors (Mercuri et al., 1992b; Shen and Johnson, 1997; Zheng and Johnson, 2002). Activation of ionotropic receptors causes depolarization of VTA DA neurons, typically accompanied by an increased cell firing rate or bursting activity (Meltzer et al., 1997; Mercuri et al., 1996; Mereu et al., 1991; Paladini et al., 1999; Seutin et al., 1990; Wang and French, 1993b). Particular emphasis has been placed on the study of the role played by glutamatergic inputs onto VTA DA neurons, given the growing body of evidence suggesting that this transmission in the VTA plays an important role in the actions of many drugs of abuse and addiction (Kalivas and Stewart, 1991; Kauer, 2004; Pulvirenti and Diana, 2001). 2. GABAergic VTA dopaminergic neurons receive GABAergic inputs from two major sources: the medium spiny neurons of the NAcc and the interneurons of the VTA (Diana and Tepper, 2002; Spanagel and Weiss, 1999; Waddington and Cross, 1978). Thus far, it appears that the primary inhibitory regulation of DA cells comes from collaterals of GABAergic projection neurons within the VTA (Churchill et al., 1992; SteVensen et al., 1998) in a similar way to the substantia nigra pars compacta (Tepper et al., 1995). Interestingly, besides having local connections onto DA cells ( Johnson and North, 1992b), a subset of VTA GABA cells project to other areas, such as the NAcc (Van Bockstaele and Pickel, 1995), thus providing an output diVerent from the dopaminergic one (SteVensen et al., 1998). GABA hyperpolarizes VTA DA cells through activation of either GABAA or GABAB receptors (Diana and Tepper, 2002; Johnson and North, 1992b; Erhardt et al., 2002) presumably originating from distinct sets of presynaptic fibers and regions (Sugita et al., 1992). GABA-mediated hyperpolarization of VTA DA neurons results from the opening of Cl and Kþ channels following activation of GABAA and GABAB receptors, respectively ( Johnson and North, 1992b; Lacey et al., 1988). 3. Cholinergic The cholinergic input to VTA DA cells arises in the pedunculopontine and laterodorsal tegmental nuclei (Garzon et al., 1999; Oakman et al., 1995; Semba and Fibiger, 1992; Woolf, 1991). Acetylcholine, through activation of muscarinic

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and nicotinic receptors expressed on DA neurons (Clarke and Pert, 1985; Cortes and Palacios, 1986; Schwartz, 1986; Wada et al., 1989), depolarizes DA neurons in vitro (Calabresi et al., 1989a; Grillner and Mercuri, 2002; Lacey et al., 1990a) and excites them in vivo (GrenhoV et al., 1986; Mereu et al., 1987), although this eVect desensitizes rapidly (Pidoplichko et al., 1997; Yin and French, 2000). The initial fast response seems to be mediated by nicotinic receptors, whereas muscarinic receptors are responsible for a prolonged response (Yeomans et al., 2001). Also, muscarinic and nicotinic receptors may mediate diVerent types of reward, such as eating and tobacco smoking, respectively (Rada et al., 2000; Watkins et al., 2000). 4. Serotonergic Dense serotonergic aVerents from the raphe nuclei to VTA DA neurons are reported to be inhibitory (Herve et al., 1987) through activation of 5-HT2C receptors (Di Mascio et al., 1998; Gobert et al., 2000). In vitro studies, however, have reported heterogeneous responses of VTA DA neurons to bath application of serotonin (5-HT): In fact, DA cells can be either depolarized, hyperpolarized, or even not aVected (Pessia et al., 1994). 5-HT, through activation of 5-HT2C receptors, depolarizes (Pessia et al., 1994) DA cells, while by acting on 5-HT1A receptors hyperpolarizes the tertiary cells within the VTA (Cameron et al., 1997). Thus far, the actions of 5-HT on VTA DA cells appear rather complex given its eVects on synaptic transmission (Cameron and Williams, 1994; Johnson et al., 1992; Jones and Kauer, 1999). In fact, early work has reported 5-HT to inhibit GABAB-mediated synaptic currents ( Johnson et al., 1992) via activation of 5-HT1B located on a subset of GABAergic presynaptic terminals (Sugita et al., 1992), thus disinhibiting DA cells (Cameron and Williams, 1994). More recently, activation of presynaptic 5-HT receptors has been demonstrated to depress excitatory synaptic transmission onto VTA DA cells ( Jones and Kauer, 1999), providing an alternative explanation for the observed amphetamine-induced reduction of burst firing of VTA DA cells. 5. Noradrenergic The noradrenergic aVerents to the VTA arise from the locus coeruleus (Bayer and Pickel, 1990) and have long been thought to make the firing pattern more regular without aVecting the firing rate (GrenhoV and Svensson, 1989; GrenhoV et al., 1993, 1995). Noradrenaline, in vitro, induces an inward current (depolarization) through activation of 1 receptors (GrenhoV et al., 1995). However, Paladini and Williams (2004) demonstrated that brief activation of 1 receptors increased an SK (calcium-dependent potassium conductance) and mediated an outward current (hyperpolarization) that completely desensitizes during application of noradrenaline. Thus, either depolarization or hyperpolarization of VTA DA cells would appear to depend on duration of activation of noradrenergic receptors (Paladini and Williams, 2004).

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C. Response to Acute Drugs By altering the amount of excitatory and inhibitory inputs onto the DA neuron, a drug influences neuronal excitability and, therefore, the behavioral actions of DA itself. The positive=rewarding eVects of nearly all drugs of abuse, as well as natural rewards, are associated with activation of the mesolimbic DA system (Koob, 1992b,c). This eVect is extremely relevant given that the abuse liability of a drug is enhanced by rapidity of onset. As a result, eVects occurring soon after drug administration are associated with it and are more likely to trigger a chain of events leading to compulsive drug taking. In vivo, acute eVects of drugs of abuse are not homogeneous. Most substances of abuse (such as ethanol, morphine, nicotine, and cannabinoids) increase the spontaneous activity, in terms of firing rate and busting activity, of VTA DA neurons (Diana et al., 1998a; French, 1997; Gessa et al., 1985, 1998; GrenhoV et al., 1986; Gysling and Wang, 1983; Matthews and German, 1984; Melis et al., 2000; Mereu et al., 1987). Interestingly, acetaldehyde, which is the principal metabolite of ethanol, has also been reported to increase VTA DA neuronal activity (Foddai et al., 2004). Because, traditionally, acetaldehyde was considered simply an aversive metabolite of ethanol, this study suggests that it might actually contribute to the positive motivational properties of ethanol itself (Quertemont, 2004; Rodd-Henricks et al., 2002, 2003). On the contrary, psychostimulants, such as cocaine and amphetamine, decrease VTA DA neuronal activity by blocking DA reuptake, thereby increasing DA release and activating feedback mechanisms (Bunney et al., 1973; Einhorn et al., 1988; Groves et al., 1975). Amphetamine has been shown to produce opposing eVects on DA neuronal activity: a DA-mediated feedback inhibition, a 5-HT–mediated suppression of excitatory inputs ( Jones and Kauer, 1999), and an 1-mediated excitation (Shi et al., 2000). However, the overall eVects mediated by other psychostimulants (e.g., cocaine, methamphetamine, and methylphenidate) lead to inhibition of DA cells, given that they mimic amphetamine eVects (1-mediated excitation) on these neurons only in the presence of D2 receptor antagonists (Shi et al., 2000). In vitro studies have helped to understand the underlying mechanisms of action of addictive drugs. For instance, morphine-induced excitation of DA neurons results from a hyperpolarizing eVect on VTA GABA interneurons ( Johnson and North, 1992a). In particular, activation of -opioid receptors located on GABA, but not DA, cells accounts for this hyperpolarization. Thus, a reduced GABA-mediated synaptic input to DA cells leads to their depolarization through a disinhibition mechanism. Conversely, ethanol actions on DA neurons seem to be direct, given that it depolarizes mechanically dissociated DA cells (Brodie and Appel, 1998), but does not aVect synaptic transmission (Brodie et al., 1990). Specifically, the mechanisms underlying ethanol-induced

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excitation of DA cells involve reduction of the amplitude of the AHP (Brodie and Appel, 1998) and of small conductance calcium-activated potassium currents (Brodie et al., 1999). Additionally, ethanol actions on VTA DA cells might be produced by its metabolite acetaldehyde, which directly produces an inward current (Melis and Diana, personal observations, 2004) and, therefore, increases VTA DA neuronal activity (Foddai et al., 2004). In contrast, nicotine exerts direct actions on DA neurons by acting on nicotinic acetylcholine receptors (nAChRs) (Calabresi et al., 1989a). However, the observations that nicotine activates and rapidly desensitizes DA cells (Calabresi et al., 1989a; Picciotto et al., 1998; Pidoplichko et al., 1997) do not provide an explanation for the persistent increased extracellular DA levels detected in the NAcc (Schilstrom et al., 1998). Nonetheless, an elucidation of its long-lasting eVects has been oVered. In fact, nicotine also binds to and activates presynaptic nAChRs located on glutamatergic aVerents, thus enhancing excitatory synaptic transmission to the VTA (Mansvelder and McGehee, 2000). More specifically, activation of presynaptic nAChRs induces long-term potentiation (LTP) of excitatory inputs to VTA DA cells, which outlasts nAChRs desensitization. Additionally, nicotine transiently enhances GABAergic synaptic transmission, which is followed by persistent depression, and shifts DA cell activity toward excitation (Mansvelder et al., 2002). Despite their high-abuse liability, the actions of cannabinoids on VTA DA cells have long been a matter of debate, and the mechanism of their actions is still poorly understood given that the detection of CB1 receptors in the VTA has long been unsupportive (Herkenham et al., 1991). However, immunohistochemical studies have shown a co-localization of CB1 receptors with TH in the VTA (Marinelli and Mercuri, unpublished observations, 2004; Wenger et al., 2003) and ultimately suggest a functional role for these receptors in the VTA (Marinelli and Mercuri, unpublished observations). In addition, cannabinoids have been shown to activate CB1 receptors in the VTA, inhibit presynaptic GABA release (Szabo et al., 2000), and enhance presynaptic glutamate release in the posterior VTA (Melis, personal observations, 2004), thus providing an explanation for the excitation observed on VTA DA neurons in vivo (Cheer et al., 2003; Diana et al., 1998a; French, 1997; French et al., 1997; Gessa et al., 1998). Regarding the actions produced by psychostimulants, much attention has been focused on the fact that their rewarding and reinforcing properties occur mainly through modulation of DA transmission through an interference with the DA transporter (Ritz et al., 1987; Seiden et al., 1993; Wise, 1996a,b). Amphetamine is preferentially a DA releaser, whereas cocaine is a blocker of DA transporter (Lacey et al., 1990b; Mercuri et al., 1992; Sonders et al., 1997). Amphetamine blocks and reverses the DA transporter, which leads to increased extracellular DA and in turn activates D2 receptors. Thus, depression of voltagedependent Ca2þ currents downstream activation of D2 receptors prevents the induction of long-term depression (LTD) at excitatory synapses on DA neurons

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( Jones et al., 2000). As a result, a transient blockade of LTD might provide a time window during which the LTP may be facilitated. Like amphetamine, cocaineinduced depression of dopaminergic neuronal activity depends on activation of D2 receptor (Brodie and Dunwiddie, 1990; Lacey et al., 1990b). However, cocaine has minimal actions on the firing rate of VTA DA cells at low concentrations (Brodie and Dunwiddie, 1990; Bunney et al., 2000). On the contrary, neuronal adaptations resembling LTP take place in the VTA and result from a single in vivo exposure to cocaine (Ungless et al., 2001). More specifically, cocaine exposure enhances excitatory, relative to inhibitory, inputs, thus resulting in potentiated excitatory synapses on DA neurons. Consequently, LTP cannot be induced at excitatory synapses as if synapses were already maximally potentiated (Ungless et al., 2001).

D. Response to Chronic Drugs Investigations examining the acute eVects of drugs of abuse provide comprehension of their cellular sites of action but do not give relevant information about the neural changes related to the phenomenon of continuous drug exposure needed to provide realistic experimental models of drug addiction. The path to drug addiction begins with the act of taking drugs, which then becomes chronic, with relapses possible even after long periods of abstinence. Therefore, studying the eVects of chronic exposure to drugs of abuse on the mesolimbic DA system is more relevant in the context of drug addiction than studying their acute eVects. Only few investigations have addressed the issue of the eVects of chronic exposure to addictive drugs on VTA DA neurons (Brodie, 2002; Diana, 1996, 1998; Diana et al., 1992a, 1993a; Rasmussen and Czachura, 1995; Wu and French, 2000), although several electrophysiological studies were carried out during withdrawal in vivo (Diana et al., 1993b, 1995, 1998b, 1999; Lee et al., 1999; Marinelli et al., 2003; Rasmussen and Czachura, 1995; Shen and Chiodo, 1993) and in vitro (Bailey et al., 1998, 2001; Bonci and Williams, 1996, 1997; Manzoni and Williams, 1999; Manzoni et al., 1998). In particular, although chronic morphine and cannabinoids do not alter the spontaneous activity of VTA DA cells (Diana et al., 1995; Wu and French, 2000), a chronic nicotine regimen decreased it (Rasmussen and Czachura, 1995). As for chronic ethanol, conflicting results have been found in vitro and in vivo (Brodie, 2002; Diana et al., 1992a). More specifically, the spontaneous activity of VTA DA neurons was found to be higher in ethanol-treated rats in vivo (Diana et al., 1992a), while no diVerences were observed in mice in vitro (Brodie, 2002). In addition, VTA-DA neurons recorded from ethanol-treated mice showed greater responses to ethanol-induced eVects but showed decreased responses to bath-applied GABA, suggesting that a sensitization might occur during chronic ethanol

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treatment (Brodie, 2002). Consequently, VTA DA neurons appear to adapt to the presence of the addicting drugs without necessarily changing their own responsiveness to the drug itself. However, once the body has adjusted to the presence of a drug, clear symptoms of withdrawal may result when its use stops. Hence, VTA DA neurons undergo adaptive changes that might be unmasked during withdrawal from addicting drugs. The withdrawal syndrome occurs upon suspension of a chronic regimen, but not from a single exposure to drugs of abuse. This is a particularly relevant issue given that a great number of misinterpretations of the eVects of a chronic regimen and=or withdrawal come from investigations carried out some time after acute or subchronic exposures.

E. Activity After Withdrawal from Chronic Administration The withdrawal syndrome, by definition (DSM-IV, 2000), begins some time (typically within hours) after the drug administration ceases and unmasks a state of physical dependence. The presence of a somatic withdrawal syndrome is among the most concrete evidences of addiction in rodent studies (Deroche-Gamonet et al., 2004; Diana, 1998b; Pulvirenti and Diana, 2001).The signs and symptoms of withdrawal have long been considered rebound eVects to the drug that can be unmasked once the drug is withdrawn from the body (O’Brien, 2001). Thus, one might predict that the eVects of acute exposure and withdrawal on VTA DA neuronal activity would be opposite. Indeed, the past decade has seen a growing body of evidence indicating that acute withdrawal from addictive drugs results in major changes in the physiology of VTA DA neurons. Ethanol withdrawal decreases spontaneous activity of rat VTA DA neurons in vivo (Diana et al., 1992b, 1993b) and mice in vitro (Bailey et al., 1998) with no diVerence in the number of spontaneously active cells (Diana et al., 1995b; Shen and Chiodo, 1993). This hypoactivity of DA cells correlates well with a reduction of extracellular DA levels in the NAcc (Diana et al., 1993b; Fadda and Rossetti, 1998; Rossetti et al., 1992a) and might represent the neural basis of the dysphoric state observed upon abrupt interruption of chronic ethanol. Interestingly, this hypodopaminergic state outlasts the physical signs of withdrawal (Bailey et al., 2001; Diana et al., 1996) and can be terminated by administration of ethanol itself (Diana et al., 1993b, 1996), suggesting a role for VTA DA neurons in the longlasting consequences of chronic ethanol ingestion (Pulvirenti and Diana, 2001). Similarly, morphine withdrawal causes a profound decline of firing rate and bursting activity of VTA DA cells (Diana et al., 1995a), which persists long after the behavioral signs of withdrawal have ceased (Diana et al., 1999). The adaptive changes occurring at the synaptic level and underlying the reduction in spontaneous activity of VTA DA cells in vivo have been intensively investigated

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(Bonci and Williams, 1996, 1997; Manzoni and Williams, 1999). In fact, during acute withdrawal from prolonged morphine administration, an upregulation of the cAMP-dependent cascade produces a long-lasting increased probability of GABA release in the VTA (Bonci and Williams, 1996, 1997). Additionally, an increased sensitivity to presynaptic inhibition by both group 2 mGluRs and GABAB receptors results in a reduced release of glutamate (Manzoni and Williams, 1999). Thus, withdrawal from chronic morphine modifies both inhibitory and excitatory inputs to VTA DA cells, though in opposite ways. Interestingly, while VTA-DA neurons appear to be back to normal within 2 weeks after acute withdrawal, acute morphine administration produced greater responses in rats with a history of morphine dependence than in controls (Diana et al., 1999). This latter finding suggests an increased sensitivity of VTA DA cells to morphine itself, which may be relevant to the phenomenon of drug craving and relapse (Diana et al., 1999; Pulvirenti and Diana, 2001). These studies strengthen the notion that VTA DA neurons are involved in the mechanisms accounting for the subjective aversive components of withdrawal (dysphoria), rather than the somatic facets of it. Cannabinoid withdrawal eVects on VTA DA neuronal activity (Diana et al., 1998b) are reminiscent of those reported for ethanol and morphine. More interestingly, a reduction in VTA DA neuronal function is also observed when somatic signs of withdrawal are not detectable (Diana et al., 1998b). Furthermore, when a pharmacologically precipitated withdrawal is induced with the specific cannabinoid antagonist SR 141716A, the somatic signs of withdrawal accompany the dampened VTA DA neuronal activity (Diana et al., 1998b). Similarly, nicotine withdrawal produced a decline of firing rate of VTA DA neurons that rapidly (within 2 days) returned to control levels (Liu and Jin, 2004; Rasmussen and Czachura, 1995). Like the eVects of withdrawal from other drugs of abuse (Diana et al., 1993b, 1995, 1998b), the number of spontaneously active DA cells was not altered at any time after nicotine withdrawal. Thus, this study, together with other investigations (Bailey et al., 1998, 2001; Diana et al., 1992, 1993b, 1995a, 1998b), suggests that the hypodopaminergic state accompanying the acute phases of withdrawal is not mediated by depolarization inactivation of DA neurons but most likely reflects alterations of intrinsic properties and extrinsic aVerent regulatory mechanisms (Bonci and Williams, 1996, 1997; Diana and Tepper, 2002; Manzoni and Williams, 1999; Pulvirenti and Diana, 2001) modified by a chronic drug regimen and disclosed by withdrawal. Cocaine withdrawal eVects on VTA DA neuronal activity seem to aVect the burst firing pattern (Gao et al., 1998). In fact, during the early withdrawal phases a reduced bursting activity of VTA DA cells was observed, which returned to normal within 7 days. In addition, alteration in sensitivity of D2 receptors (autoreceptors) seems to play an important role in cocaine-induced modifications

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of spontaneous activity of VTA DA neurons during the first week of withdrawal (Ackerman and White, 1992; Gao et al., 1998; Lee et al., 1999; Marinelli et al., 2003). Consequently, short-term treatment with D2 receptor agonists restores the hypodopaminergic neuronal function (Lee et al., 1999; Marinelli et al., 2003), thus representing a potential treatment for intermediate withdrawal phases. The spontaneous activity of VTA DA neurons does not seem to be altered during amphetamine withdrawal (Lee and Ellinwood, 1989), but repeated exposure to amphetamine produces long-lasting changes in the modulation of glutamatergic synaptic transmission by amphetamine in the NAcc (Li and Kauer, 2004).

III. Behavioral Animal Models

A. Self-Administration Studies Over the past 40 years, experimental psychologists have been developing and refining behavioral models of addiction. Using inventive animal protocols, they have designed behavioral animal models both practical and highly reproducible. Although the human condition of the disease cannot always be reproduced in the finest detail, control over the experimental conditions such as species, environment, nutrition, drug dose, and pattern of administration can be monitored accurately (Bozarth, 1987). Among behavioral animal models, self-administration has a prominent significance because it reflects an operant (active) behavior phenomenologically identical to the human condition. In the initial work, rats were used as experimental subjects for the intravenous injection of drugs (Weeks, 1962). Subsequently, the method has been refined and adapted to primates (Goldberg, 1973; Thompson and Schuster, 1964) and other mammals (Balster et al., 1976; Bedford et al., 1980; Criswell and Ridings, 1983; GriYths et al., 1975; Jones and Prada, 1973; Lukas et al., 1982). Basically, the experimental animal presses a lever and receives a bolus of the drug. An intravenous catheter is connected to a pump, which delivers the intravenous fluid injections. The experimental preparation is, therefore, a chronically intravenous catheterized animal, which may be semi-restrained in a chair (e.g., primates) or allowed to freely move within the experimental chamber (e.g., rodents) during the self-administration session. A drug is considered to be self-administered when either the rate of drug responding is greater than the rate of response on a control lever (which results in saline injections), or when the response rate is greater in the subject whose response produces drug injections compared to its yoked control (Davis and Nichols, 1963; Pickens and Thompson, 1975). More specifically, the diVerence between the

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response rate by the animal in the active cage and the animal in the yoked control cage provides an index of the reinforcing properties of the drug itself. Consequently, the drug serves as a reinforcer when a naive animal initiates self-administration of the drug with a rate of lever-pressing that exceeds the control lever or saline responding. The reinforcing properties of the drug can be evaluated by either turning oV the injection pump or replacing the drug solution with saline (or vehicle) (Schuster and Thompson, 1969). The animal will then increase the response rate until will stop, eventually. This behavior is termed extinction (Pickens and Harris, 1968; Pickens and Thompson, 1968; Weeks, 1962; Winger and Woods, 1973). Several schedules of reinforcement are available today (Ator and GriYths, 2003; Johanson, 1978; Katz, 1989; Spealman and Goldberg, 1978; Young and Woods, 1981) and enable to specify the possibility that an animal is responding to obtain the drug. The most common schedule requires an animal to press the lever for a fixed number of times to obtain an injection (termed fixed ratio [FR] schedule). Thus, the self-administration rate within a session varies depending on the eVects of the drug and=or the duration of the time out (Ator and GriYths, 2003). An alternative schedule is the fixed interval (FI), when after a fixed period of time the first response (but not those preceding or following) produces the delivery of the drug. The progressive ratio (PR) schedule of reinforcement is the most used paradigm to assess the rank order of potency among diVerent drugs of abuse (Ator and GriYths, 2003; Gardner, 2000). Under this schedule, the highest response requirement a drug will sustain represents the so-called ‘‘breaking point’’ (Richardson and Roberts, 1996; StaVord et al., 1998), which can vary according to the determined progression within or across the sessions and typically represents the amount of ‘‘work’’ the subject is willing to perform to obtain a bolus of the drug. Thus, it is possible to build dose–eVect curves for a certain drug by comparing the maximum breaking points obtained under the same experimental procedures. Another option to compare reinforcing properties of drugs of abuse is the choice procedure, where the response requirement to obtain one of two substances is significantly higher (Ator and GriYths, 2003). Because of its route of administration, the intravenous self-administration model is almost instantaneous, although the delivery apparatus can have some disadvantages (e.g., viable long-term catheters and solubility of drugs). Though limited (e.g., aversive taste and fluid restriction), oral selfadministration has been successfully established and proved useful in the study of ethanol intake (Evans and Levin, 2003; Meisch, 2001). In particular, to overcome the most limiting problem of this procedure (aversive taste of ethanol), the fluid has been sweetened to habituate the animal to the taste while it is exposed to increasing concentrations of ethanol (Meisch and Henningfield, 1977; Meisch and Lemaire, 1991; Turkkan et al., 1989).

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Drugs abused by humans have been demonstrated to be readily self-administered by laboratory animals. Indeed, animals will maintain self-administration for psychostimulants such as amphetamine, methamphetamine, cocaine, phencyclidine (Balster et al., 1973, 1976; Bedford et al., 1980; Carroll et al., 1979; Goldberg, 1973; Lukas et al., 1984; Pickens and Harris, 1968; Risner, 1982; Risner and Jones, 1975; Stretch and Gerber, 1970; Thompson and Pickens, 1970; Yokel and Pickens, 1973), opiates such as heroin, morphine, and congeners (Blakesley et al., 1972; Harrigan and Downs, 1978; Lukas et al., 1981), ethanol (Deneau et al., 1969; Smith and Davis, 1974; Weeks, 1962), nicotine (Ator and GriYths, 1983; Deneau and Inoki, 1967; Goldberg et al., 1981; Lang et al., 1977; Risner and Goldberg, 1983), and THC ( Justinova et al., 2003; Tanda et al., 2000). This model allows researchers to extend the knowledge on the neurobiological mechanisms involved in such behaviors and to design and ultimately assess the potential therapeutic value of pharmacological agents. In fact, this behavioral animal model also allows examining the compulsive nature of both drug-seeking and drug-taking behaviors, which cannot be explained on the basis of the acute rewarding properties of the drugs (Bechara et al., 1998; Hutcheson et al., 2001). More specifically, accumulating evidence suggests that the withdrawal phase leads to an increased consummatory behavior of diverse drugs of abuse such as ethanol, opiates, cocaine, and nicotine (Grasing et al., 2003; Hutcheson et al., 2001; Khantzian, 1985; Koob, 1996; Mucha et al., 1986; Valdez et al., 2004; Weiss et al., 1996, 2001). Consequently, the avoidance of the withdrawal syndrome represents a motivational state, in addition to the intrinsic rewarding properties of the drug, which ultimately increases the incentive value of the drug itself. As a result, the aversive signs of withdrawal produce a craving for the drug and increase the self-administration behavior to avert the abstinence phase. This can be explained in light of the compelling evidence (electrophysiological, biochemical, and behavioral) suggesting that neuroadaptive changes occurring within the mesolimbic DA pathway lead to a hypofunctioning DA system during withdrawal (see Chapters 2 and 4 for electrophysiological, biochemical, and anatomical evidence). Accordingly, the decreased mesolimbic dopaminergic transmission occurring during acute withdrawal from ethanol can be restored when the animals increase the self-administration rate (Weiss et al., 1996). Therefore, the observations that ethanol-dependent rats will work more during the acute phase of withdrawal to obtain ethanol, whose consumption reverses the withdrawal-associated decreased DA levels (Weiss et al., 1996), and DA neurons firing (Diana et al., 1993) support the view that the dysphoric state accompanying abrupt interruption of ethanol (and more in general of drug abuse) is causally related to the hypodopaminergic state that outlasts somatic signs of withdrawal (Bailey et al., 2001; Diana et al., 1996) and can be terminated by administration of ethanol itself (Diana et al., 1993b, 1996; Weiss et al., 1996).

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B. Intracranial Self-Stimulation Another behavioral model used to investigate the rewarding=addicting properties of a drug in laboratory animals is the intracranial self-stimulation (ICSS) method (Kornetsky et al., 1979). This procedure is based on the observation that rats will press a lever to pass a small current through electrodes located in various brain areas (Olds and Milner, 1954), including those that give course to the ascending DA-containing axons projecting to the forebrain. This method consists of placing a stimulating electrode in the medial forebrain bundle or other brain areas (such as lateral hypothalamus, VTA, prefrontal cortex, NAcc, etc.) and allowing animals to self-stimulate so neuronal reward circuits are activated. As a result, laboratory animals can directly activate (self-stimulate) those brain circuits that natural and conditioned reinforcers stimulate (Bozarth and Wise, 1981; Goeders and Smith, 1983; Hoebel et al., 1983; Phillips and LePiane, 1980; Phillips et al., 1981). Once the lever-pressing behavior is established, the diVerence is made by changing the intensity and=or duration of the ICSS pulse in the presence of a drug. Thus, a relationship between the abuse liability of drugs such as morphine and cocaine and their ability to lower the threshold for ICSS in rat reward brain regions was first found by Kornetsky et al. (1979). Subsequently, all addictive drugs, when acutely administered, have been found to lower the threshold of stimulation required to maintain ICSS (Bespalov et al., 1999; Gardner and Vorel, 1998; Gardner et al., 1988; Hayes and Gardner, 2004; Herberg et al., 1993; Williams et al., 1991). Drugs of abuse such as cocaine (Markou and Koob, 1991), amphetamine (Harrison et al., 2001; Kokkinidis and Zacharko, 1980; Paterson et al., 2000), ethanol (Schulteis et al., 1995), morphine (Schulteis et al., 1994), and nicotine (Epping-Jordan et al., 1998; Harrison et al., 2001) enhance the reinforcing impact of such electrical stimulation. Conversely, acute withdrawal from diverse drugs of abuse precipitates a deficit in brain reward function, which can be indexed by elevated ICSS reward thresholds. These increases in brain stimulation threshold, to maintain ICSS, have been observed for the major drugs of abuse, such as opiates (Schaefer and Michael, 1986; Schulteis et al., 1994), cocaine (Markou and Koob, 1992), amphetamine (Cryan et al., 2003a; Lin et al., 1999; Wise and Munn, 1995), ethanol (Schulteis et al., 1995), and nicotine (Cryan et al., 2003b; Epping-Jordan et al., 1998; Kenny et al., 2003). In particular, morphine-dependent rats needed an increased threshold current to restore ICSS during acute withdrawal (Schaefer and Michael, 1986). In addition, Kenny et al. (2003) provided further evidence for the role of the VTA in ICSS during acute nicotine withdrawal. Indeed, either activation or blockade of group II mGluRs within the VTA elevated or decreased,

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respectively, ICSS thresholds in nicotine-dependent rats (Kenny et al., 2003). Therefore, increased ICSS thresholds constitute a good behavioral animal model of the aversive motivational state associated with the negative reinforcement of drug withdrawal in dependent animals and add further evidence to the notion that VTA DA cells and their projections play a key role in perpetuating the addiction cycle (Diana, 1996, 1998; Shippenberg and Koob, 2002). Because accumulating evidence points to neuroadaptive changes induced by long-term abuse of addicting drugs in the mesolimbic regions, it is reasonable to consider that these alterations are involved in the aversive state emerging during withdrawal and motivate the continued use of the drug itself.

C. Place-Conditioning Studies The place-conditioning paradigm is a pavlovian conditioning procedure in which the animal learns to prefer an environment that is paired with drug eVects. This behavioral animal model mimics some aspect of the human condition of addiction. In fact, recovering addicts often return to drug intake when exposed to stimuli and=or environments associated with former use of the drug. Basically, animals are allowed to explore two distinct environments, which are usually diVerent in color and=or pattern and are connected by an open door. The time spent in each compartment is recorded. Subsequently, the door connecting the two compartments is closed and one of the two compartments is paired every other day with a drug (which represents the unconditioned stimulus [UCS]) or vehicle exposure. This procedure is repeated for several days. On test day, the animal is not given any injection but has free access to both compartments, which are again connected by the open door. The time spent in the compartment associated with the drug is considered an index of the reinforcing value of the UCS. The diVerence between the time spent in the drug- versus vehicle-paired compartment is an indication of the rewarding eVects of the drug. The opposite is true for an aversive USC. Thus, this behavioral model provides an animal model of the subjective eVects of the drug. Importantly, the context serves as a signal that the drug produces changes at a cellular level. Drugs abused by humans are able to induce, when acutely administered, conditioned place preference in laboratory animals (Tzschentke, 1998) with the exception of THC. In fact, THC can induce either conditioned place preference or aversion depending on the dose and=or the timing of injections (Braida et al., 2001; Lepore et al., 1995; Sanudo-Pena et al., 1997; Valjent and Maldonado, 2000), and opiate receptors (i.e., and ) seem to play opposite roles (Ghozland et al., 2002). Conditioned place aversion is more generally produced by aversive emotional states such as withdrawal from chronic treatment with drugs of abuse (Funada et al., 1993;

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Mucha and Herz, 1985). Particularly, this paradigm is one of the most sensitive indices of the motivational (aVective) symptoms of drug withdrawal because it can be produced in dependent animals even though they do not show physical signs of withdrawal (Schulteis et al., 1994). In fact, opiate-dependent animals given low doses of antagonist, which would produce motivational but not somatic signs of withdrawal, show aversion to the environment paired with the abstinence (Mucha, 1987; Schulteis et al., 1994; Stinus et al., 1990). Additionally, conditioned place aversion is shown by animals experiencing both ethanol withdrawal and hangover (Morse et al., 2000), as well as cocaine and nicotine withdrawal (Ise et al., 2000; Suzuki et al., 1996). Consequently, drug withdrawal associated with diverse though convergent motivational aversive components plays an important role in maintaining addictive behavior. More specifically, this type of context- and experience-dependent plasticity seems to highlight the VTA as the key structure involved in drug addiction (Kim et al., 2004). Because VTA DA neurons are uniformly inhibited by aversive stimuli (Ungless et al., 2004), the neuroadaptive changes in mesolimbic DA transmission observed during and even long after acute withdrawal (see Chapters 2 and 4 for electrophysiological, biochemical and anatomical evidence) appear to be the most likely perturbations accounting for and contributing to addictive behavior.

IV. Biochemical Studies

A. Microdialysis Microdialysis is the most widely used technique to monitor extracellular DA levels and is believed to reflect its synaptic concentrations (Imperato and Di Chiara, 1984; Zetterstrom et al., 1983). This procedure allows the monitoring of DA levels in the extracellular space in living tissue and behaving animals (Westerink, 1995). Basically, a dialysis cannula is implanted in the brain region of interest and small molecules such as DA can freely exchange across the membrane of the probe down the concentration gradient. The dialysate is collected and analyzed. It is noteworthy that the exchange of molecules can take place in both directions, so it is possible not only to collect endogenous molecules but also to introduce exogenous compounds. This technique has high sensitivity and specificity for DA, although the probe size is large (Ø > 200 m) and the time resolution is low. In fact, because the samples can be collected only in a minute time scale (usually between 5 and 20 minutes), certain dynamics are undetected, thus resulting in a lack of temporal integration especially with electrophysiological methods. Thus, this technique cannot discriminate between

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the spatiotemporal patterns of DA release that lead to diverse behavioral actions of DA and to activation of synaptic versus nonsynaptic DA receptors (Agnati et al., 1995; Zoli and Agnati, 1996). Nonetheless, in vivo microdialysis studies have greatly helped the understanding of the neuropharmacological basis of normal and abnormal behavior (Hoebel et al., 1992). In fact, by means of the microdialysis procedure, it has consistently been shown that drugs abused by humans, such as psychostimulants, nicotine, opiates, ethanol, and THC, acutely increase extracellular DA levels in the NAcc (Bradberry and Roth, 1989; Carboni et al., 1989, 2001; Chiamulera et al., 2001; Di Chiara and Imperato, 1985, 1988; Hernandez and Hoebel, 1988; Murphy et al., 2001; Zocchi et al., 1998), and preferentially in the shell subregion of this nucleus, as opposed to its core counterpart (Di Chiara, 2002; Hedou et al., 1999a,b; Heidbreder and Feldon, 1998; Pontieri et al., 1995; Tanda et al., 1997; Zocchi et al., 2003). In line with electrophysiological and behavioral studies, the aversive phase of acute withdrawal is accompanied by a reduction of extracellular DA levels in the NAcc as estimated by microdialysis (Rossetti et al., 1992). Importantly, the changes in extracellular DA levels in this brain region have been observed during acute withdrawal from chronic ethanol (Diana et al., 1993b; Rossetti et al., 1992; Weiss et al., 1996), morphine (Acquas et al., 1991; Pothos et al., 1991; Rossetti et al., 1992), cocaine (Parsons et al., 1991; Robertson et al., 1991; Rossetti et al., 1992; Weiss et al., 1992), amphetamine (Rossetti et al., 1992), nicotine (Hildebrand et al., 1998; Rada et al., 2001), and THC (Tanda et al., 1999). In addition, these changes do not occur in other terminal regions such as the prefrontal cortex (Bassareo et al., 1995; Hildebrand et al., 1998) and do not seem to be correlated with somatic signs of abstinence. Notably, these decreased levels of extracellular DA in the NAcc, together with the dramatically reduced spontaneous activity of VTA DA cells during and after acute drug withdrawal (Bailey et al., 1998; Diana et al., 1993b, 1995, 1995a, 1998a; Gao et al., 1998; Liu and Jin, 2004), strengthen the hypothesis that the hypofunction of mesolimbic DA neurotransmission plays a pivotal role in the aversive state of withdrawal and possibly contributes to renewed drug use.

B. Biomolecular Investigations Biomolecular investigations have oVered insightful data on the genetic basis of drug addiction and still open new avenues into perspectives of therapeutically useful drugs. The molecular studies of drug addiction have provided a better understanding of the mechanisms leading to long-term changes in the brain and ultimately behavior of drug addicts by using animal models of this disease (Nestler and Aghajanian, 1997).

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One of the most widely used biomolecular techniques is the candidate gene method. This approach provides useful insights into the influence of specific genes in the regulation of behaviors such as drug addiction, because a candidate gene (or protein) is related to the human disease and therefore considered to be a human risk factor (Nestler, 2001a,b). To correlate a gene to a behavior, manipulation (disruption or enhancement) of a gene within an animal is required, as well as the use of transgenic, knockout and knockin mice. Lastly, by selectively breeding animals within a population that has either a very high or a very low level of a specific trait (e.g., ethanol consumption), it is possible to generate selected lines. This approach has been particularly useful in the field of alcoholism because lines with diVerent types of sensitivity, preference, or aversion to ethanol have been generated (Phillips, 2002). By means of these diverse biomolecular approaches, researches have focused their investigations on the changes occurring when DA is released by VTA DA cells in the terminal regions (e.g., limbic forebrain) in behavioral animal models of drug addiction. Because drugs of abuse alter the amount and time of DA released at the synapses, they might in turn aVect the second-messenger cascades downstream activation of DA receptors, such as the cAMP pathway, and intracellular signaling proteins, as well as transcription factors (Bohn et al., 2000; Carlezon et al., 1998; Kelz et al., 1999; Nestler, 2000, 2001a,b). In fact, compelling evidence suggests that upregulation and=or saturation of the cAMP–PKA dependent pathway (Bonci and Williams, 1996, 1997; Melis et al., 2002; Self et al., 1998; Terwilliger et al., 1991) and activation of cAMP–response element-binding protein (CREB) take place in the mesolimbic system after exposure to diverse drugs of abuse such as ethanol, opiates, cocaine, and amphetamine (Asher et al., 2002; Carlezon et al., 1998; Lu et al., 2003; McClung and Nestler, 2003; Shaw-Lutchman et al., 2002, 2003). Interestingly, some of these drugs (cocaine, amphetamine, and opiates) share the ability to alter the expression of immediate early genes, which, therefore, might represent one of the key elements in the molecular changes underlying drug addiction (Altman, 1996; Conneally and Sparkes, 1998; Hope et al., 1992; Mackler and Eberwine, 1991). Additionally, a specific molecular change seems to exclusively occur after chronic exposure to diverse drugs of abuse (e.g., opiates, cocaine, and nicotine) and to persist long after drug intake ceases. This change involves induction of FosB (a truncated form of the FosB gene) in the NAcc and the striatum, which appears as a hallmark of long-lasting adaptations associated with addiction (Chen et al., 1995; Hope et al., 1994; Kelz et al., 1999; McClung and Nestler, 2003; Moratalla et al., 1996; Nestler et al., 2001a, b; Nye and Nestler, 1996; Pich et al., 1997). By using another biomolecular technique (DNA microarray) (Geschwind, 2001), it has also been possible to establish a putative target for FosB and implicate its signaling pathway in the long-term adaptive changes

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of NAcc neurons to cocaine (Ang et al., 2001; Nestler et al., 2001). Additionally, induction of FosB is particularly significant because it mediates stimulation of cyclin-dependent kinase-5 (Cdk5), which appears to be involved in the increased density of dendritic spines on NAcc neurons after chronic cocaine exposure (Bibb et al., 2001; Norrholm et al., 2003). Taken together, these studies suggest that altered regulation of neuronal gene expression in the mesolimbic DA system, ultimately leading to morphological (see next paragraph) and functional (see previous paragraphs) changes of the system itself, might also explain the need for a continued drug intake in the development of addiction and in the maintenance of such behavior long after drug withdrawal.

C. Microanatomical Studies Functional alterations accompanying persistent drug intake may represent the phenotype of structural changes occurring at the level of synaptic connections (such as abnormal density and morphology of dendritic spines, synapse loss, and ultimately abnormal synaptic plasticity) and other morphological changes of mesolimbic DA cells. Dendritic spines ‘‘decorate’’ plasma membranes of several types of ‘‘spiny’’ units in the CNS and appear like knots (they can be thin, stubby, or mushroom shaped) lining on the dendritic shafts and represent independent brain units (Shepherd, 1996). They increase dendritic surface area and modify the electrical signals from synaptic inputs and appear as dynamic structures that can be formed, modified in shape, or eliminated depending on the synaptic activity (Shepherd, 1996). Indeed, a number of studies have suggested that stimulationinduced changes in dendritic spines are related to increased long-term synaptic changes and information processing (Comery et al., 1996; Cox et al., 2003; Daw et al., 1993; Geinisman, 2000; Geinisman et al., 1989; Hayashi et al., 2004; Lynch et al., 1988; Schiller et al., 1998). Thus, size, shape, and number of dendritic spines proportionally aVect synaptic plasticity; larger spines have larger heads and constricted necks and support stronger synaptic transmission (El-Husseini et al., 2000; Murthy et al., 2001; Shepherd, 1996). Because VTA DA neurons (Fig. 1) synapse with dendritic spine necks of medium spiny neurons (Freund et al., 1984) of the NAcc (Fig. 2), drug-induced changes in the structural and functional properties of neurons within the mesolimbic DA system might be relevant in the molecular and cellular basis of longterm behavioral changes observed during drug addiction (Nestler, 1996, 2001b, 2004). In particular, medium spiny neurons of the NAcc receive both excitatory and dopaminergic aVerents on the heads and necks of the dendritic spines, respectively, whose integrated actions result in fine-tuning the spontaneous

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Fig. 1. Schematic drawing of ventral tegmental area (VTA) dopamine (DA) cell morphology during normal and addicted states. VTA DA neurons from a rat of the control group (normal state) are depicted in gray, whereas a VTA DA cell from a rat undergoing acute withdrawal from morphine (addicted state) is overlapping in black. Note that cell size (e.g., area, perimeter) is smaller during the addicted state. Drawing is proportional to actual measures observed experimentally.

Fig. 2. Confocal images of the nucleus accumbens (NAcc) during normal and addicted states. Each is the projection of a three-dimensional reconstruction of medium spiny neurons within the shell of the NAcc. (Left panel) Medium spiny neuron from a rat of the control group (normal state). Note that dendrites are branched and enriched with spines. (Right panel) Medium spiny neuron from a rat undergoing acute withdrawal from morphine (addicted state). Note that dendrites are less branched and possess fewer spines.

neuronal activity (Pickel and Sesack, 1997). For instance, by using conventional fluorescent microscopy, it has been shown that morphine-dependent animals undergoing acute withdrawal have a dramatic reduction (about 25%) in the size of VTA DA cells (Sklair-Tavron et al., 1996), although changes were ascribed to

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chronic morphine (Spiga et al., 2003a) as well as in the density of dendritic spines selectively in secondary dendrites (Diana et al., 2003b) of medium spiny neurons of the NAcc (Robinson and Kolb, 1999a). Similarly, by using confocal laser scanning microscopy, it has been demonstrated that during acute withdrawal from chronic morphine the morphological features (e.g., circularity, area, and perimeter) of VTA DA neurons are profoundly reduced (Spiga et al., 2003). These changes might reflect intracellular alterations occurring in these neurons, such as decreased neurofilament proteins (Beitner-Johnson et al., 1992) and impaired functions such as reduced axonal transport from the VTA to the NAcc (Beitner-Johnson and Nestler, 1993). This reduction in area, perimeter, and circularity, in line with the ‘‘size principle’’ (Henneman et al., 1965a,b; Shepherd, 1994; Somjen et al., 1965) might ultimately represent an additional plastic change that renders the neurons more excitable, to overcome the hypodopaminergic state observed electrophysiologically and biochemically (see Chapters 2 and 4 for electrophysiological and biochemical evidence). Likewise, VTA DA cells are reduced in their size during acute withdrawal from chronic ethanol (Diana et al., 2003a). Additionally, the observation that VTA DA cells have reduced size during acute withdrawal from THC (Spiga et al., 2003b) further suggests that irrespective of the abused substance, VTA DA neurons are reduced in size upon withdrawal. On the other hand, repeated treatment with psychostimulants, such as cocaine and amphetamine, changes the morphology of medium spiny neurons in the NAcc and increases the density of dendritic spines and the number of branched spines on these neurons, thus resulting in augmented arborization that persists long after the last drug exposure (Robinson and Kolb, 1997, 1999b). Similarly, rats self-administering cocaine show increased density and arborization of dendritic spines on the medium spiny neurons of the shell of the NAcc and the pyramidal neurons of the neocortex (Robinson et al., 2001). In a similar fashion, repeated nicotine administration dramatically enhances dendritic length and spine density of NAcc medium spiny neurons (Brown and Kolb, 2001). The changes in spine density on medium spiny neurons of the NAcc and VTA DA cells’ morphology are of particular interest because of their functional role in synaptic transmission and plasticity (Blanpied and Ehlers, 2004; El-Husseini et al., 2000; Murthy et al., 2001; Shepherd, 1996). In particular, augmented density of dendritic spines seems to be a consequence of a change in the number of synaptic inputs onto dendrites (Peters and Feldman, 1976; Wilson et al., 1983) and results in increased synaptic eYcacy (Luscher et al., 2000; Malinow et al., 2000; Scannevin and Huganir, 2000). These morphological abnormalities strengthen the view that an abnormal (hypofunctioning) mesolimbic dopaminergic system represents a key substrate involved in and contributing to drug addiction.

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V. Primate Studies

A. Nonhuman Primates Nonhuman primates share with humans 95% of their genetic makeup (Britten, 2002). Studies carried out in nonhuman primates are critical to the understanding of drugs’ eVects on the body and the brain, as well as the extent to which these changes can be reversed by pharmacological treatments. Electrophysiological recordings of midbrain DA neurons in nonhuman primates have shown them to be stimulated by novel unpredictable rewards and reward-associated stimuli (Schultz, 1998a,b). Interestingly, these neurons are capable of distinguishing between reward and nonreward objects (Romo and Schultz, 1990) and to respond to aversive stimuli with a decreased spontaneous activity (Schultz et al., 1997). Thus, midbrain DA cells are activated when rewards occur without being predicted, are depressed when the predicted reward is omitted, and do not respond when the reward is delivered when predicted (Schultz, 1998a, 1999; Schultz et al., 1997). Particularly, with repeated pairing (stimulus þ reward ¼ reward-predicting stimulus), the reward becomes predicted by the conditioned stimulus and the DA neurons cease to respond. However, if the reward fails to occur, DA cells respond with decreased activity at the time the reward is expected (Schultz et al., 1997). Thus, DA neurons play a role in the behavioral adaptation to new situations and salient stimuli in the environment (Schultz, 1998b). When drugs of abuse such as cocaine (Bradberry, 2000, 2002; Bradberry et al., 2000) and ethanol (Bradberry, 2002) are acutely administered to nonhuman primates, increased extracellular DA levels are detected. This might explain the reinforcing properties of these drugs in nonhuman primates (Spealman et al., 1989). Indeed, increased dopaminergic transmission might facilitate the consolidation of memory of drug experience and help elucidate why nonhuman primates will maintain self-administration for drugs of abuse such as ethanol (Meisch and Stewart, 1994), cocaine (Bradberry et al., 2000), heroin (Mello et al., 1995), and THC (Tanda et al., 2000). The mesolimbic DA system of nonhuman primates also undergoes major changes during chronic drug exposure, particularly after chronic psychostimulants. In fact, increased activity of TH (Vrana et al., 1993), density of the DA transporter (Farfel et al., 1992; Howell and Wilcox, 2001; Letchworth et al., 2001), and downregulation of D1 (Moore et al., 1998a) and D2 receptors have been observed (Farfel et al., 1992; Ginovart et al., 1999; Moore et al., 1998b). Although the development of physical dependence on drugs of abuse such as opiates (Krystal and Redmond, 1983; Redmond and Huang, 1982) and ethanol (Pieper, 1975) has been explored in nonhuman primates, very little is

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known about the neuronal adaptations aVecting and occurring in the mesolimbic dopaminergic system following continuous drug intake and unmasked by drug withdrawal. A behavioral study examining withdrawal from cocaine selfadministration in monkeys and reporting disruption of the schedule-controlled behavior (Woolverton and Kleven, 1988) suggested that this disruption might cause abrupt changes in DA transmission leading to reinstatement of drug seeking and self-administration. However, whether this disruption reflects a tonically reduced DA receptor stimulation or the absence of phasic DA release due to a decreased activity of DA cells remains to be established. Nonetheless, because DA neuronal responses to aversive stimuli are similar across species (Chiodo et al., 1980; Guarraci and Kapp, 1999; Mirenowicz and Schultz, 1994; Romo and Schultz, 1987; Ungless et al., 2004), we can assume that reduced phasic DA release associated with a dampened spontaneous activity of DA units might play a major role during acute withdrawal. Additionally, indirect evidence supports the idea of a dysfunctional mesolimbic DA system in monkeys following chronic drug intake; indeed, Jentsch et al. (2000) showed that repeated exposure to psychostimulants such as phencyclidine induced increased impulsive behavior, possibly resulting from dysfunction of corticolimbic circuits associated with reward and behavioral inhibition ( Jentsch et al., 1999). Accordingly, the ‘‘impulsivity’’ shown by monkeys in response to reward-related stimuli (Jentsch et al., 1999) is supported by evidence of deficits in frontal-cortical cognitive function, such as the loss of inhibitory control, resembling those observed in drug abusers (McKetin and Mattick, 1998; Rogers et al., 1999).

B. Humans Brain imaging techniques have been applied to the study of neurobiological mechanisms of addiction with results unobtainable from virtually any other method. These studies provide insights of great scientific value in understanding the pathophysiology of addiction (Daglish and Nutt, 2003). These relatively new methods enable experimenters to evaluate neural activity or activation via blood flow with positron emission tomography (PET) using radiolabeled water or via glucose metabolism. With single-photon emission computed tomography (SPECT), blood flow can be estimated using technetium-99, and lastly, functional magnetic resonance imaging (f MRI) methods produce images of the blood oxygen level–dependent (BOLD) response, which, in theory, reflects neuronal activation or inhibition. In addition, by administering a ligand, one can monitor receptor occupancy, thereby obtaining additional information on receptor function and ultimately neurotransmission. In the case of dopaminergic systems, the most frequently employed radioligand is 11C-raclopride, which monitors D2 receptors and other tools such as [11C] d-threomethylphenidate

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are frequently used and believed to reflect dynamics of the DA transporter (Volkow et al., 1996). By using these methodologies, Boileau et al. (2003) has shown that ethanol administration in healthy volunteers results in a decreased 11 C-raclopride in the ventral striatum leading to increased dopaminergic transmission. Similarly, cocaine and methylphenidate produce significant reductions in D2 receptors, which are associated with decreased metabolism in the cingulate gyrus and orbitofrontal cortex (Volkow et al., 1999a,b), and these changes correlate well with subjective feelings of ‘‘high’’ after the psychostimulants (Volkow et al., 1997). In addition, the level of receptor occupancy appears to predict the degree of drug-induced pleasantness (Fowler et al., 1999; Volkow et al., 1999c). All these studies demonstrate that the potentiation of the dopaminergic response after various addicting compounds observed in laboratory animals can also be detected in humans. However, as previously stated, the altered brain physiology of the addicted brain limits the significance of these informative experiments in the context of drug addiction. Evaluations after chronic drug intake, and in some cases withdrawal, are nonetheless available and are discussed below. D2 receptors have been measured in opiate-dependent subjects and after naloxone-precipitated withdrawal (Wang et al., 1997). Although a reduction of D2 binding was documented as compared with controls, naloxone did not induce any appreciable change in the striatum of opiate-addicted humans. The reduced D2 binding could be seen in contrast to the hypodopaminergic state theorized here, because the classic denervation theory would predict the opposite. However, it should be recalled that D2 binding simply indicates number of receptors, and in animal models, a reduction of dendritic spines (preferential location of DA receptors) has been observed in medium spiny neurons of the NAcc (Diana et al., 2003b; Robinson and Kolb, 1999a), which represent the main dopaminoceptice cell type in the forebrain. Thus, whereas the D2 binding may, in some cases, reflect dopaminergic transmission, other structural changes produced by chronic morphine and withdrawal should be taken into account and in any event support the hypodopaminergic state outlined in this chapter. On the other hand, the lack of detection of naloxone-induced changes could simply be due to the dorsal-striatal level of investigation, instead of the ventral part. D2 receptor availability is also known to be lower in abstinent alcoholdependent patients (Hietala et al., 1994), whereas the DA transporter seems to be unaVected (Volkow et al., 1996). Similarly, cocaine abusers show reduced 11 C-raclopride binding at rest (as compared to healthy controls) and an increased response to cocaine challenge (Schlaepfer et al., 1997; Volkow et al., 1999a). Though limited in number, human studies in addicted populations, using various drugs, support the concept that dopaminergic transmission is reduced in the brain of dependent subjects, and the response to drug challenge is higher than controls (Lingford-Hughes and Nutt, 2003; Lingford-Hughes et al., 2003; Volkow

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Fig. 3. Schematic summary of changes occurring in the mesolimbic dopaminergic system during the addicted state. (Top) Normal state depicts a control ventral tegmental area (VTA) dopamine (DA) neuron projecting to the nucleus accumbens (NAcc). Shown in the VTA are VTA DA cell and presynaptic glutamatergic (GABAB receptor is represented as a orange square) and GABAergic terminals. Shown in the VTA DA cell are tyrosine hydroxylase (TH) and DA vesicles. Shown in the NAcc are, in addition to TH and DA, DA receptors (D1DA and D2DA), components of the intracellular cyclic adenosine monophosphate (cAMP) system (AC, adenylate cyclase; cAMP; protein kinase A [PKA], cAMP-dependent protein kinase) and possible substrates such as CREB (cAMPresponse element-binding protein) fosB (a truncated form of the FosB gene) and jun ( jun gene), as well as major outputs of this region (CTX, prefrontal cortex; HIP, hippocampus; VP, ventral pallidum; AMY, amygdala). Note the axodendritic synapse between the dopaminergic terminal and the spine necks of NAcc medium spiny neuron in the inset. Also, note that gray lines indicate a normal condition, whereas thick black lines increased activity, and dashed gray lines decreased activity. (Bottom) Addicted state depicts a smaller VTA DA neuron projecting to the NAcc after withdrawal from chronic drug exposure. TH levels are decreased (dashed gray arrow) in the VTA DA cells body and increased in the terminal region of the NAcc (thick black arrow). In the NAcc medium spiny neuron AC, cAMP, and PKA activities are increased; changes that could account for the D1DA receptor supersensitivity (thick black arrow) and reduced number of D2DA receptors. It should be noted that alterations in dopaminergic transmission influence spine density and number within the medium spiny neuron of the NAcc.

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et al., 2004). These two facts are in line with the preclinical literature described in preceding chapters and support the idea of a hypodopaminergic state that characterizes the addicted brain. VI. Conclusions

The last few decades have produced a wealth of experimental data on the neurobiological basis of drug addiction both in laboratory animals and in clinical settings with human subjects, drastically improving our knowledge of the disease. The present analysis of the literature suggests that the mesolimbic DA system (Fig. 3) displays a reduced spontaneous activity after chronic drug intake and withdrawal—crucial phases of addiction. In experimental animal models, when direct measures of DA neurons’ functioning (such as electrophysiological models to monitor cells firing and pattern, and biochemical models such as microdialysis to monitor DA release) are employed, a reduction in spontaneous activity is reported irrespective of the addicting chemical. When methods such as placeconditioning studies, self-administration, and ICSS are applied, aversion, increased self-administration, and higher current thresholds (BP) respectively, are observed in similar conditions. Studies of human addicts coherently report a reduction of D2 receptors and a reduction in DA release (Volkow et al., 2004). Collectively, these data support the concept of a hypodopaminergic state at both presynaptic and postsynaptic level. The reduction in spine density observed in rats correlates well with the reduction in postsynaptic D2 receptors in humans and would further impoverish an already defective DA transmission, thereby ‘‘weakening’’ the entire system. Targeting these abnormalities therapeutically will make it possible to develop pharmacological tools more eYcacious than those available. The strong consonance between experimental animal data and human findings renders drug addiction one of the human pathologies in which the term ‘‘evidence-based medicine’’ appears to be adequately applied. Acknowledgments

We thank William, Chiara, and Sonia for their continuous and unconditioned emotional support, which provided the necessary brain conditions to put this work together. Our gratitude is extended to M. Pistis, A. L. Muntoni, M. Pisano, Z. L. Rossetti, G. L. Gessa, R. Pirastu, and many other tireless and enthusiastic companions of endless and (not always so) peaceful scientific discussions, which have helped in shaping the ideas outlined in this chapter and have significantly contributed to the experimental and intellectual work that forms the basis of this chapter. We also thank William T. Dunn, III, for language editing the manuscript. This work was supported, in part, by grants from M.I.U.R. and R.A.S.

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HUMAN AND ANIMAL SPONGIFORM ENCEPHALOPATHIES ARE AUTOIMMUNE DISEASES: A NOVEL THEORY AND ITS SUPPORTING EVIDENCE

Bao Ting Zhu Department of Basic Pharmaceutical Sciences, College of Pharmacy University of South Carolina, Columbia, South Carolina 29208

I. Introduction II. A New Theory on the Mechanism of Pathogenesis of Spongiform Encephalopathies (SEs) A. Mechanisms for the Antibody-Mediated Formation and Accumulation of PrPsc B. Mechanism for the Production of Anti-PrPsc Autoimmune Antibodies C. Mechanism for the Pathogenesis of Central Nervous System Lesions in Spongiform Encephalopathies D. Some Additional Details Concerning the Proposed New Theory III. Supporting Evidence A. Evidence from Animal Studies in Support of the Proposed Novel Theory that SEs Are Autoimmune Diseases B. A Brief Explanation for the Apparent Existence of Multiple ‘‘Prion Strains’’ and ‘‘Species Barriers’’ C. A Brief Explanation for the Autoimmune Origin of Various Human and Animal SE Diseases IV. Early Diagnosis, Treatment, and Prevention of Various SE Diseases A. Early Diagnosis of SEs B. Treatment Strategy for SEs C. Prevention of SEs V. Conclusions References

I. Introduction

Spongiform encephalopathies (SEs) are fatal degenerative diseases of the central nervous system (CNS) that can occur both in animals and in humans (Collinge, 2001; Collinge and Palmer, 1997; Kimberlin and Walker, 1988; Prusiner, 1993, 1998, 2001; Prusiner and McKinley, 1987; Weissmann, 1991a,b). In animals, the most common form is scrapie found in sheep, and the other forms of SEs include transmissible mink encephalopathy, chronic wasting disease of mule deer and elk, feline spongiform encephalopathy, and bovine spongiform encephalopathy (BSE). BSE, often called ‘‘mad cow’’ disease, is most worrisome and is believed to be the cause for a certain form of SEs in humans who consumed meat and=or oVal products from diseased cattle INTERNATIONAL REVIEW OF NEUROBIOLOGY, VOL. 63

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(Anderson et al., 1996; Gibbs, 1996; Nathanson et al., 1997; U.S. Department of Agriculture [USDA], 2003; Wilesmith et al., 1991). The commonly known forms of human SEs include Creutzfeldt-Jakob disease (CJD), familial fatal insomnia, juru, and Gerstmann-Straussler-Scheinker syndrome (Prusiner, 1993, 1998, 2001; Prusiner and McKinley, 1987; Will, 2003). Human SE diseases may appear as sporadic, genetic, or apparently transmissible diseases (Prusiner, 1998, 2001; Prusiner and McKinley, 1987). Pathological studies revealed that SE diseases in animals and humans often produce over a long period progressive neuronal loss, astrogliosis, and characteristic spongiform-like changes in the brain tissue, which is often filled with amyloid-like deposits (Collinge, 2001; Collinge and Palmer, 1997; Kimberlin and Walker, 1988; Prusiner, 1993, 1998, 2001; Prusiner and McKinley, 1987; Weissmann, 1991a,b). Before Dr. T. Alper and her colleagues first suggested in the 1960s that the agent that caused scrapie in sheep might have the ability to replicate itself without the presence of nucleic acid (Alper et al., 1966, 1967; Latarjet et al., 1970), SEs had been generally suspected of having a viral origin (Alpers, 1968; Gajdusek et al., 1965, 1966; Hadlow and Eklund, 1968). Extensive additional studies by Dr. Stanley B. Prusiner et al. (1982, 1993, 1998) had led to a strong conclusion that the pathogenic agent in animal and human SEs indeed lacked nucleic acid and consisted mainly, if not exclusively, of proteins. Their conclusion was based on their earlier finding that various procedures that were well known to destroy nucleic acid and viruses did not appear to significantly reduce infectivity, whereas procedures that denatured or degraded protein drastically reduced infectivity. In 1982, Dr. Prusiner introduced the term ‘‘prion’’ to distinguish this new class of proteinaceous pathogens from viruses, bacteria, fungi, and other known pathogens. Studies have shown that the normal cellular prion protein (PrPc) and the disease-causing prion protein (PrPsc) are glycoproteins composed of about 250 amino acid residues, and their basic amino acid sequences appear to be identical (Prusiner, 1993, 1998, 2001; Prusiner and McKinley, 1987). Although many details remain unclear, it is believed that the tertiary configurations of these two proteins are very diVerent. Studies of the three-dimensional structure of the animal PrPc proteins selectively expressed in Escherichia coli showed that the PrPc contained predominantly -helical domains and had almost no sheets (Billeter et al., 1997; Donne et al., 1997; Gasset et al., 1992; Huang et al., 1994; Riek et al., 1996; Zhang et al., 1997). It was predicted that PrPsc contains predominantly sheets. Accordingly, the PrP protein is believed to have two stable configurations (i.e., PrPc and PrPsc), and the safe PrPc configuration is normally adopted, and rarely it would automatically switch to the pathogenic PrPsc configuration. Studies have shown that PrPc and PrPsc have very diVerent biochemical and biophysical properties: PrPc was soluble in non-denaturing

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detergents, but PrPsc was not; PrPc was readily digested by proteases, but PrPsc was markedly resistant to proteases; PrPc was heat sensitive, but PrPsc was partially heat resistant (Prusiner, 1993, 1998, 2001; Prusiner and McKinley, 1987). Most prion researchers believed that these diVerent properties of PrPc and PrPsc are solely due to the diVerent tertiary configurations adopted. Dr. Prusiner and colleagues proposed that PrPsc alone was responsible for the transmission of the SE diseases and believed that PrPsc was infectious. This theory has now become a widely held doctrine concerning the pathogenesis of various animal and human SE diseases (Aguzzi et al., 2001; Bamborough et al., 1996; Clarke et al., 2001; Collinge and Palmer, 1997; Huang et al., 1994; Kimberlin and Walker, 1988; Prusiner, 1993, 1998, 2001; Prusiner and McKinley, 1987; Telling et al., 1996a,b; Weissmann, 1991a,b; Wickner et al., 2001; Zhang et al., 1997). Mechanistically, it is believed that the disease-causing PrPsc protein can propagate itself through physically contacting the normal cellular PrPc and causing it to unfold and flip from its usual configuration to adopt the aberrant shape (Bamborough et al., 1996; Clarke et al., 2001; Prusiner, 1993, 1998, 2001; Prusiner and McKinley, 1987; Weissmann, 1991a,b; Wickner et al., 2001). It was also suggested that this change of configuration initiates a cascade in which the newly converted PrP would start to alter the shape of other normally shaped PrPc molecules in an exponential manner. The conversion of normal PrPc to PrPsc has been suggested to occur inside the neurons (Ma and Lindquist, 2002; Ma et al., 2002), and PrPsc accumulates within the intracellular vesicles known as lysosomes. The filled lysosomes eventually would burst and cause damage to the cells, thereby leaving small holes and PrPsc deposits in the aVected brain tissue. Details of the prevailing explanations concerning the mechanisms of prioncaused diseases can be found in many elegantly written review articles (Aguzzi et al., 2001; Bamborough et al., 1996; Clarke et al., 2001; Collinge and Palmer, 1997; Kimberlin and Walker, 1988; Prusiner, 1993, 1998, 2001; Prusiner and McKinley, 1987; Telling et al., 1996a,b; Weissmann, 1991a,b; Wickner et al., 2001). Although I believe that PrPsc (which is a long-lasting and weakly immunogenic protein), possibly along with other long-lasting and immunogenic macromolecules, plays important roles in the development of human and animal SEs, I also believe that many of the prevailing mechanistic explanations on the pathogenesis of SEs are incorrect. In this chapter, a new theory is developed as an alternative to the currently prevailing explanations for the pathogenic mechanism of SEs. The proposed theory suggests that various human and animal SEs are essentially autoimmune type of diseases. A detailed explanation of the proposed theory, along with a discussion of the available experimental evidence in its support, is provided.

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II. A New Theory on the Mechanism of Pathogenesis of Spongiform Encephalopathies (SEs)

I hypothesize that a key step in the pathogenic process leading toward the development of various known forms of SE diseases involves the production of specific autoimmune antibodies against PrPsc and possibly other immunogenic macromolecules ( proteins or non-proteins) present in the CNS. As precisely explained later in this chapter, the autoimmune antibodies produced against PrPsc are not only directly responsible for the conversion of PrPc to PrPsc, but they are also directly responsible for the accumulation of PrPsc in the CNS and other peripheral tissues. Most importantly, the production of autoimmune antibodies against PrPsc and=or other cellular macromolecules is also responsible for the antibody-mediated chronic autoimmune attack of PrP-expressing cells (such as neurons), contributing to the development of neurological lesions and clinical symptoms characteristic of various SE diseases.

A. Mechanisms for the Antibody-Mediated Formation and Accumulation of PrPsc It is believed that the majority of the normal cellular PrPc always adopt the usual stable tertiary configuration. However, it is also conceivable that a very small fraction of the cellular PrPc protein may transiently adopt other possible tertiary configurations as a result of the normal intramolecular thermodynamic movements. Because these transient tertiary configurations are thermodynamically unstable, PrPc normally could not assume such unstable configurations for any significant length of time, and usually they would almost instantly revert back to the normal stable configuration. However, when specific autoimmune antibodies against immunogenic PrPsc are produced and present in the body, they may also bind to the transiently misshapen PrPc molecules that happen to adopt the PrPsc-like configuration, and thereby stabilize them in the aberrant configuration for a much longer time (Fig. 1). It is hypothesized that when the misshapen configurations of the PrP protein are stabilized by the binding of the antibodies, some of the usually inaccessible amino acid residues may become accessible for further covalent modifications (e.g., glycosylation). These covalent modifications may permanently stabilize the PrP protein in the abnormal PrPsc configuration. Notably, although most prion researchers thought that the conversion of PrPc to PrPsc solely involves configurational changes of the PrP protein (Aguzzi et al., 2001; Bamborough et al., 1996; Borchelt et al., 1990; Clarke et al., 2001; Collinge and Palmer, 1997; Kimberlin and Walker, 1988; Pan et al., 1993; Prusiner, 1993, 1998, 2001; Prusiner and McKinley, 1987; Telling et al., 1996a,b; Weissmann, 1991a,b; Wickner et al., 2001), I believe that the patterns of covalent

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Fig. 1. Explanation for the antibody-mediated conversion of PrPc to PrPsc. (A) The normal cellular PrP protein (PrPc) is schematically depicted, which contains the extracellular and intracellular domains. The small circles represent the original post-translational covalent modifications (such as glycosylation) of some of the amino acid residues. (B) The transiently misshapen PrP protein is shown, which happens to adopt a configuration that is similar or identical to the configuration of the PrPsc (depicted in E). Because configuration B is thermodynamically unstable, usually it would instantly revert to the stable configuration A. However, when the anti-PrPsc autoimmune antibody (Ab) is present (please note that this antibody would also have cross-reactivity for the PrPsc-like misshapen configuration B), the configuration B could be stabilized by the binding of the antibody, resulting in the formation of the antibody-PrP complex (C). When PrP is stabilized by the antibody in configuration C, some of the originally inaccessible amino acid residues would become readily accessible for further covalent modifications, which eventually would lead to the formation of PrPsc. Note that the additionally modified amino acid residues following antibody binding are marked with small triangles. (D) represents the antibody-PrPsc complex, whereas (E) represents PrPsc alone without an antibody bound to it.

modifications in PrPc and PrPsc are very diVerent, and they are important determinants of their diVerent configurations, their diVerent biophysical properties, and their diVerent immunogenic property. A detailed discussion of the supporting evidence for the diVerent patterns of covalent modifications of PrPc and PrPsc is provided in Section II.D, later in this chapter. Although the functions of the cellular PrPc are still unclear (Bueler, 1992), it is reasonable to assume that the normal PrPc serves certain physiological functions

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for those cells that express the protein (Collinge, 1994). When specific antibodies are tightly bound to the transiently misshapen PrPc proteins and stabilize them in the PrPsc-like abnormal configurations (presumably functionally inactive), the cells being targeted by the antibodies would falsely sense that they do not have enough PrPc molecules (and its associated functions), and subsequently this may result in increased expression of the cellular PrPc protein. Because most of the expressed PrPc molecules, sooner or later, would be targeted by the autoimmune antibodies, more and more PrPc would need to be expressed, and consequently a vicious cycle may ensue. Accordingly, at late stages of the pathogenic process, overexpression of the cellular PrPc protein may occur, possibly accompanied by PrPsc accumulation and plaque formation. This new mechanistic theory also explains that the structures of the newly formed PrPsc would be very similar and sometimes even identical to the structures of the original PrPsc protein against which the antibodies were formed. A schematic illustration of the explanation is provided in Fig. 2. B. Mechanism for the Production of Anti-PrPsc Autoimmune Antibodies As mentioned earlier in this chapter, PrPsc exists in stable yet abnormal tertiary configurations that are very diVerent from the configuration of the normal cellular PrPc. The abnormal configuration of PrPsc would make it a new immunogenic entity that could trigger the body’s immune system to generate specific antibodies. Notably, because PrPsc is highly resistant to digestion by proteases, this would allow PrPsc and some of its peptide fragments to form deposits and thus may stay in the body for a long time. As a result, the body’s immune system would have ample time to interact with these immunogenic proteinaceous deposits and gradually develop specific antibodies against the PrPsc protein and its peptide fragments. Here, it needs to be explained as to where the immunogenic PrPsc protein in a patient or an animal initially comes from. It is hypothesized that one of the sources of the initial PrPsc is through oral ingestion of the meat and=or oVal products from animals with SE. It has been documented that some of the orally ingested PrPsc particles could be absorbed intact (undigested) across the intestinal wall at the Peyer’s patches (Prinz et al., 2003). These unique structures are part of the mucosal-associated lymphoid tissue (MALT) where large immunogenic particles (such as microorganisms) are usually presented to the body’s immune system. Because PrPsc molecules are far more resistant to various proteases than other ingested proteins (including the normal PrPc), and because they are usually present as clustered particles, it is possible that a fraction of the orally ingested PrPsc molecules are taken up into the body largely undigested through the MALT. Lymphoid cells then phagocytize the PrPsc particles and travel to

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Fig. 2. Explanation for the structural similarities between the newly-formed PrPsc and the original PrP against which the antibodies are produced. The two large ovular circles on the left depict two diVerent PrPsc proteins which have diVerent patterns of covalent modifications and also diVerent 3-D configurations. Please note that each of the PrPsc proteins in the ovular circle also has a specific antibody molecule bound to it, i.e., the antibody X is bound to the configuration-A PrPsc, and the antibody Y is bound to the configuration-B PrPsc. The two sets of the antibodies (X and Y) are specifically produced against these two configurationally diVerent PrPsc proteins. Because each set of the antibodies would have their own specificity for recognizing the immunogenic configuration of the PrPsc protein, the antibody X would preferentially recognize the transiently misshapen configuration (A) of the PrP protein but probably would not recognize its configuration B. Likewise, the antibody Y would preferentially recognize the misshapen configuration (B) but probably not the configuration (A). As depicted above, it is rather easily understood that the autoimmune antibodies (X or Y) would have the tendency to copy the configuration of the original PrPsc (against which the antibodies were specifically produced) to the newly formed PrPsc. sc

lymphoid sites such as lymph nodes, spleen, and tonsils for inducing the production of specific antibodies. In line with this explanation, analyses of various tissues collected from animals with SE diseases have shown that their visceral lymphoreticular and secretory organs were among the organs=tissues that had the highest titers of PrPsc at early disease stages (Farquhar et al., 1994; Hilton et al., 2002; Kimberlin and Walker, 1989; Vankeulen et al., 1996).

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After a person has orally ingested PrPsc-rich meat and=or oVal products from the BSE cattle, the initial antibodies produced in the recipient would be highly specific for the bovine PrPsc. However, some subsets of the antibodies may retain certain degrees of cross-reactivity against the human PrP molecules when they transiently adopt the bovine PrPsc-like misshapen configurations (as a result of the thermodynamic intramolecular movements). Accordingly, the production of the initial antibodies against the bovine PrPsc would lead to an initial antibodymediated immune attack of the recipient’s CNS and other peripheral tissues that express the PrP protein. The extent of such an antibody-mediated autoimmune attack is, in a significant part, determined by the cross-reactivity and quantity of the antibodies being produced. Following the initial attack of the human PrPc by the anti-bovine PrPsc antibodies, human PrPsc would gradually be formed. The human PrPsc, when accumulated in the body (not necessarily in the CNS) in substantial quantities, would also serve as immunogen and lead to the production of additional antibodies that would have a higher specificity for the human PrPsc. In the case of most laboratory animals that were induced to develop SEs, the source of PrPsc was usually through experimental inoculations of the brain tissues or extracts from animals or humans with SE. The process for the production of initial and subsequent antibodies is essentially the same as described earlier. Notably, when PrPsc from animals with SE was inoculated into the same types of healthy animals (e.g., mouse PrPsc was inoculated into healthy mice of the same strain), the initial antibodies produced would have rather high specificity and aYnity for the transiently misshapen mouse PrPc. As such, the disease incubation period usually would be much shorter compared to that when the PrPsc obtained from the SE animals of one species was inoculated into the healthy animals of another species. The explanation provided here can be used to explain many of the known experimental observations related to the apparent ‘‘species barrier’’ of the SE diseases. For instance, laboratory studies have consistently shown that when the standard method of experimental inoculation of diseased tissue extracts was used to pass the SE disease from one animal species to another, it was generally accompanied by a significant prolongation of the incubation time compared to the passage within the same strain of animals (Pattison and Jones, 1968). However, the subsequent passages of the disease within the new strain of animals usually became much easier, with a reduced and stabilized incubation time. Further discussion on this topic is provided later in Section III.B. Lastly, it should be noted that some earlier studies showed that the titers of the autoimmune antibodies produced during the development of SE diseases in animals were usually very low, which was strikingly diVerent from the high circulating levels of antibodies produced following tissue=organ transplantation or pathogenic organism invasion. The low levels of anti-PrPsc autoimmune antibodies produced were likely due to host tolerance to this protein. Consistent with this explanation, an earlier study showed that PrPsc became far more

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immunogenic in the PrPo=o null mice (which did not express PrPc) than in the PrPþ=þ mice (Prusiner et al., 1993). The relatively low levels of the autoimmune antibodies for PrPsc found in SE animals and patients should not be taken as evidence to exclude autoimmune attack as a crucial pathogenic factor; instead, these preliminary observations only suggested that the autoimmune attack against the PrPsc-expressing cells likely was very mild compared to the much stronger autoimmune response and attack following organ transplantation or pathogen invasion. The suggestion for the long-term involvement of a mild autoimmune attack of the CNS cells during the pathogenesis of SE is fully consistent with the unusually long incubation time needed for the development of the disease in both animals and humans.

C. Mechanism for the Pathogenesis of Central Nervous System Lesions in Spongiform Encephalopathies One of the pathological characteristics of various human and animal SE diseases is the death of CNS neurons. Here, an important question is how does PrPsc cause neuronal death? As explained below, the production of specific autoimmune antibodies is also directly responsible for the development of characteristic neurological lesions and clinical symptoms of SEs through two major mechanisms: 1. When specific antibodies are tightly bound to the misshapen PrP proteins in the plasma membrane of the CNS cells, the antibody–antigen complexes would subsequently attract other components of the immune system, resulting in an antibody-mediated autoimmune attack of the PrP-expressing cells. Such chronic autoimmune attack is expected to induce inflammatory responses surrounding the targeted cells and cause chronic neurological lesions. There were several lines of experimental observations that strongly supported this hypothesis (discussed in Section III.A). 2. When the transiently misshapen PrPc molecules are bound with the antibodies and particularly when they are already converted to the functionally inactive PrPsc, it is believed that the PrPsc would sooner or later be translocated to the intracellular vesicles and ultimately to the lysosomes where various proteases are present for the normal degradation of misfolded proteins. However, because PrPsc is highly resistant to many isoforms of proteases, subsequently the lysosomes may be overloaded with undigestible PrPsc or its peptide fragments. The overloading of lysosomes with undigestible PrPsc would also contribute to the formation of pathogenic neuronal lesions or even neuronal death. In cases of neuronal death, the undigestible PrPsc or its fragments (likely in clusters) would be released and accumulated in the region where the neurons once were, and the death of

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the neurons would leave small holes, which could be readily seen in brain histopathological slides. In support of this explanation, there is some evidence that the structures of the lysosomes of the aVected neurons were very diVerent from normal control neurons, and in some cases, the lysosomes were loaded with PrPsc or its fragments. Based on the mechanistic explanations provided here, it should be noted that although the presence of PrP plaques in the CNS serves as a useful pathological indicator for the occurrence of the SE disease, their presence is not believed to be the major cause for the accompanying neuronal lesions. It is predicted that in some cases if the antibody-mediated autoimmune attack is rather severe (due to the presence of higher-titer and=or higher-aYnity autoimmune antibodies), then the CNS neurons may be damaged and ultimately destroyed within a relatively shorter period and there may not be enough time for PrPsc to accumulate and form deposits. Notably, another important factor that would aVect the extent of PrPsc plaque formation is the degree of PrPsc resistance to various endogenous proteases. If some of the PrPsc proteins, because of their diVerent configurations and covalent modifications, are less resistant to proteases than others, then their accumulation may be significantly less than those that are more resistant to proteases. In line with this explanation, there are many experimental observations from SE patients or laboratory animals showing that the formation of PrPsc plaques did not appear to be closely correlated with the extent of neurological impairment. For instance, it has been repeatedly observed that some prions caused SE diseases quickly, whereas others did so slowly. It was reported that although macaque monkeys and marmosets both developed neurological disease several years after inoculation with the bovine PrPsc (Baker et al., 1993), only the macaques exhibited numerous PrP plaques similar to those found in human vCJD (Lasme´ zas et al., 1996). Although the precise tissue=cellular distribution of PrP protein in animals and humans is still not known, there are experimental data showing that in addition to the CNS, many peripheral tissues also express this protein (Baldwin et al., 1992). It is possible that some of the PrP-expressing peripheral tissues are important initial targets for the antibody-mediated autoimmune attack, resulting in the initial accumulation of human PrPsc in these tissues. Because the antibodies against the immunogenic PrPsc are produced in peripheral lymphatic tissues where the concentrations of these antibodies are highest, these lymphatic tissues likely are the initial targets for the PrPsc autoimmune antibodies, eventually resulting in PrPsc accumulation in these tissues. In line with this explanation, studies have shown that PrPsc in animals inoculated with PrPsc usually first accumulate in visceral lymphoreticular and secretory organs, and later it started to accumulate in the CNS (Farquhar et al., 1994; Hilton et al., 2002; Kimberlin and Walker, 1989; Vankeulen et al., 1996). Considering the

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concentrations of specific antibodies present in various tissues, most CNS neurons are probably exposed to far lower levels of the antibodies (because of the blood–brain barrier), which would be one of the factors that may contribute to the very slow progression of the neurological lesions. In addition to the concentrations of specific antibodies surrounding the target cells in a given tissue, another important factor that would also determine the extent of neuronal lesions and PrPsc accumulation is the original levels of cellular PrPc required for fulfilling the normal physiological functions. If a given tissue basically does not express PrPc for its normal functions, then this tissue may not be targeted by the autoimmune antibodies, and likewise, it may not accumulate PrPsc. On the other hand, if a tissue normally expresses much higher levels of PrPc for physiological functions than other organs, this tissue would have a shorter incubation time for the development of characteristic pathological changes and would have higher levels of PrPsc accumulation after the anti-PrP antibody-mediated autoimmune attack. In partial support of this suggestion, an earlier study showed that transgenic mice overexpressing the mouse PrPc became particularly susceptible to develop SE diseases with a shorter incubation time after inoculation with the mouse PrPsc (Telling et al., 1996a,b). Lastly, it is of note that the antibody-mediated chronic autoimmune attack of most peripheral target sites is expected to be less consequential clinically as oppose to the CNS neurons, which are generally deprived of the ability to regenerate in case of neuronal death. Accordingly, it is possible that although many types of tissues=cells in the body might become the targets for the antibodymediated autoimmune attack during the development of an SE disease, CNS pathology and symptoms may become most pronounced and the consequences likely are most devastating.

D. Some Additional Details Concerning the Proposed New Theory For clarity and better understanding, in this Section I provide some additional clarification of a few important issues that are related to the proposed new theory, as well as its diVerence from the current prion hypothesis. 1. Most proponents of the prevailing prion hypothesis hold the unwavering view that the only diVerence between PrPc and PrPsc is configurational, which means that the diVerent biophysical and pathogenic properties of PrPc and PrPsc are solely determined by their diVerent tertiary configurations. In my view, however, the stabilization of the unusual configurations of PrPsc is largely determined by its diVerent patterns of covalent modifications (such as glycosylation). The binding of an autoimmune antibody to the transiently misshapen PrPc would initially stabilize it in an abnormal PrPsc-like configuration, but the subsequent

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covalent modifications of some of the amino acid residues that are normally not accessible may help further stabilize it in aberrant configurations. This suggestion is consistent with a number of experimental observations: (1) PrPsc and PrPc were both known to be post-translationally modified to an extensive degree, and PrPsc was formed in vivo only after the protein had been glycosylated (Bamborough et al., 1996). Also, analysis of PrPsc obtained from the brain of patients who died of vCJD showed that the PrP glycoforms had quite diVerent patterns from those found for sporadic or iatrogenic CJD (Caughey and Raymond, 1991). (2) The disease-causing ability of PrPsc and PrPc was drastically diVerent, with a ratio of about 100,000:1 (Prusiner, 1993, 1998, 2001; Prusiner and McKinley, 1987). (3) Although pure PrPsc isolated from diseased brain tissue was highly pathogenic, almost all of the studies have failed thus far to create the same degree of infectivity by only modifying the configuration of the bacterially expressed normal PrPc—a crucial prediction of the current prion hypothesis. Similarly, it has been unsuccessful for prion researchers to abolish the structure and pathogenic activity of PrPsc with specific agents or solutions and then to restore its activity by reinstating the original structure. (4) It should be noted that the diVerences in the glycosylation pattern of PrPc and PrPsc usually were not accounted for in most of the studies that were designed to determine the structural diVerences between PrPsc and PrPc, because the proteins were deglycosylated before structural and sequence analyses. Taken together, all these observations consistently suggested that the diVerent biophysical and pathogenic properties of PrPsc and PrPc likely are not just determined by their diVerent tertiary configurations, and in my view, the diVerent patterns of covalent modifications play a crucial role in the stabilization of the unique configurations of PrPsc as well as for the creation of its immunogenic and pathogenic properties. 2. One of the core elements of the currently prevailing prion hypothesis is that PrPsc can replicate itself through interacting directly with the cellular PrPc and then imparting its misshapen configuration onto PrPc in an exponential manner. This explanation was, in part, based on some of the earlier studies that showed that in vitro incubations of PrPc in the presence of PrPsc (insoluble as deposits) appeared to increase the formation of the proteinaceous deposits compared to that when PrPc was incubated alone. There are diVerent explanations for the observations. Here I like to use the precipitation of sodium chloride (NaCl) from a supersaturated NaCl solution as an example to help make a simple point. As we know, the supersaturated NaCl solution is rather unstable, and NaCl will tend to precipitate out over time. During the formation of NaCl precipitates from a supersaturated NaCl solution, if small pieces of the NaCl crystal are already present, then the speed for the formation of NaCl precipitates usually is much faster than that without the preexisting crystals. The reason is that before the islands of NaCl crystals are formed, it is usually more diYcult for NaCl molecules in solution to precipitate out, but when small NaCl crystals are already

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present, the process becomes much easier. Similar explanations can be used to account for the in vitro observations that when the PrPsc was already present as insoluble deposits, its presence would make it easier for the transiently misshapen PrPc protein to form precipitates on top of the PrPsc deposits. 3. One of the pathological characteristics for various human and animal SE diseases is the death of CNS neurons. As discussed earlier, the proposed new theory provided a precise mechanistic explanation for the pathogenesis of neuronal death in SE diseases. However, the prevailing explanations oVered by the prion hypothesis have been debatable, and controversies still abound. The earlier explanation suggests that the conversion of normal PrPc to PrPsc occurs inside the neurons, and PrPsc accumulates within the intracellular vesicles known as lysosomes. The filled lysosomes could then burst and cause damage to the cells (Prusiner, 1993, 1998, 2001; Prusiner and McKinley, 1987). However, a somewhat diVerent mechanistic explanation was later fashioned (Ma and Lindquist, 2002; Ma et al., 2002), and it was suggested that a certain fraction of the misfolded PrPc protein never reached the plasma membrane, but instead they re-entered the cytosol through retro-translocation from the endoplasmic reticulum, a process known for many misfolded proteins to be directed back to the proteasomes for disposal. The accumulation of the PrP protein in the cytosol would then cause rapid neuronal death. This explanation was based on studies by Ma et al. (2002) and Ma and Lindquist (2002), showing that a form of the prion protein that was specifically targeted toward the cytosol caused rapid neurodegeneration in mice. However, there are a few problems about this modified mechanistic explanation. First, the particular form of the PrP protein observed in these studies did not acquire resistance to proteases, which has been one of the best known characteristics of PrPsc for years. Second, the experimental studies by Drisaldi et al. (2003) suggested that the cytosolic PrP protein still retained its signaling peptide (which is normally removed after the protein entered the endoplasmic reticulum), and it did not appear to contain the glycosyl phosphatidylinositol anchor needed for attachment to cellular membrane (Drisaldi et al., 2003; Harros, 2003). Accordingly, this observation raised the possibility that the PrP protein described in studies by Ma et al. (2002) and Ma and Lindquist (2002) might never enter the endoplasmic reticulum, and thus, it might not have undergone retro-translocation as these researchers had purported. 4. The normal cellular PrPc protein appears to have a rather wide tissue distribution besides the CNS (Baldwin et al., 1992). Earlier studies showed that when various tissues from SE animals were analyzed, their visceral lymphoreticular and secretory tissues were among the organs=tissues that had the highest titers of PrPsc (Farquhar et al., 1994; Hilton et al., 2002; Kimberlin and Walker, 1989; Vankeulen et al., 1996). Based on these observations, most prion researchers believe that the PrPsc first replicated itself within the richly innervated peripheral lymphatic tissues, and later PrPsc propagated back up along the axons

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to the spinal cord and eventually to the brain, causing clinical symptoms (Aguzzi, 1997; Follet et al., 2002; Glatzel and Aguzzi, 2000; Nicotera, 2001). I think that this mechanistic explanation, which was fashioned according to the well-known model of the slow viral infection of the CNS, was incorrect. The proposed new theory suggests that the antibody-mediated conversion of PrPc to PrPsc may first lead to the accumulation of PrPsc in peripheral tissues (particularly the lymphoreticular and secretory organs where the antibody titers are highest), and later the antibodies may slowly attack the CNS, gradually leading toward the formation and accumulation of PrPsc and the development of typical pathological changes in the CNS. The reason for the slow progression of the CNS pathogenesis during SE diseases is, in a significant part, because the CNS neurons were usually exposed to much lower levels of the autoimmune antibodies than many other peripheral tissues. 5. It is of note that an earlier study has shown that some of the older transgenic mice that overexpressed the normal PrPc protein eventually also developed an illness characterized by rigidity and diminished grooming (Westaway et al., 1994a). Additional analyses of these animals indicated that they eventually also developed neurodegeneration and destruction in both muscle tissues and peripheral nerves. The exact causes for these pathogenic changes (which somewhat resembles SEs) remain unclear. Although the production of anti-PrP autoimmune antibodies could not be ruled out, it is also likely that the disease state observed in these mice might have resulted from the chronic disturbance of the normal physiological functions of PrPc. 6. The proposed new theory suggests that other immunogenic proteinaceous and=or nonprotein particles sometimes may also be present in tissues from SE animals, and these immunogens may be able to stay in the body for a long time (because of their resistance to enzymatic digestion). Their long-term presence is expected to induce the production of specific autoimmune antibodies in the recipient. These autoimmune antibodies would target antigens with diVerent cellular distributions in the CNS as compared to the PrP protein, and their involvement could be an important factor that diversifies clinical and pathological findings. The presence of other CNS immunogens likely is one of the major underlying causes for the apparent presence of diVerent strains of prions (discussed in Section III.B). When the same crude extracts (with the same combination of various disease-causing immunogens) were inoculated into the same type of animals in the same experiment, the patterns of pathological changes and clinical symptoms were, as expected, always very similar. A good example for the suspected involvement of other immunogenic proteinaceous particles is the pathogenic -amyloid protein found in Alzheimer’s disease. It is well known that -amyloid protein shares similar biophysical and pathogenic properties as PrPsc, but it is a totally diVerent protein. The proposed theory on the pathogenesis of SEs also naturally leads to the suggestion that

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Alzheimer’s disease likely is another autoimmune-type disease that preferentially aVects the CNS of the elderly. In fact, there is a considerable amount of experimental evidence in scientific literature that provides support for this novel hypothesis [a detailed discussion provided elsewhere (Zhu, 2005)]. In this context, I also like to note that there may be potentially unavoidable untoward eVects associated with the recent clinical trials that were designed to stimulate the body’s production of antibodies for -amyloid plaques as a prevention and treatment strategy for Alzheimer’s disease. Given the new mechanistic understanding developed here, it is very likely that such a strategy may not work as intended, rather it may do the opposite, accelerating the development of Alzheimer’s disease.

III. Supporting Evidence

In light of the new mechanistic explanations developed here, I believe that many of the explanations based on the prevailing prion hypothesis are incorrect. Instead of detailing my reasons and critiques about why they may be incorrect, here I would prefer to mainly focus on providing a discussion of the available evidence that supports the proposed new theory on the mechanism of SE pathogenesis. There is a rather large body of laboratory and clinical evidence (discussed later) that all points to a coherent unified pathogenic mechanism that various human and animal SE diseases are autoimmune-type diseases largely aVecting the CNS. Notably, the experimental data and findings discussed in this chapter are rather incomplete and scattered throughout the biomedical literature, and often they were incorrectly construed in the original papers to support opposing hypotheses. Nevertheless, these data, when interpreted in the context of the proposed new theory, form a collective body of coherent evidence that provides strong support for the validity of the theory.

A. Evidence from Animal Studies in Support of the Proposed Novel Theory that SEs Are Autoimmune Diseases 1. Studies have shown that mice with severe combined immunodeficiency (SCID) generally were highly resistant to the development of SE following inoculation with the PrPsc-rich extracts (Brown et al., 1997; Fraser et al., 1996; Klein et al., 1997; Mabbott and Bruce, 2001; O’Rourke et al., 1994; Taylor et al., 1996). 2. Consistent with the previous observation, other studies have further shown that a functionally proficient B lymphocyte system (which produces specific antibodies) was required for the development of SE in an animal model after

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inoculation of extracts from diseased brain tissue (Klein et al., 1997). Notably, some earlier studies have also suggested that mice deficient in B lymphocytes might still develop SE diseases when PrPsc was directly injected into the brain or very high doses of PrPsc were used (Brandner et al., 1996; Brown et al., 1999; Fraser et al., 1996; Frigg et al., 1999; Klein et al., 1997; Mabbott and Bruce, 2001; Taylor et al., 1996). It was possible that small amounts of the autoimmune antibodies against the mouse PrPsc might still be formed in these animals when they were either intracerebrally challenged with PrPsc or received very high doses of PrPsc. This suggestion was consistent with the general knowledge that these B lymphocyte-deficient mice could still produce small amounts of antibodies. 3. Studies have shown that the PrP null mice (PrPo=o) (i.e., those animals with both alleles of the PrPc gene disrupted) would not develop SEs after inoculation of the brain extracts from diseased mice (Bueler et al., 1993; Sailer et al., 1994). The explanation for the observation is rather simple on the basis of the proposed new theory. Although specific antibodies against the mouse PrPsc were believed to be produced in PrPo=o null mice after inoculation with the mouse PrPsc, these antibodies were unable to cause usual pathogenic lesions in the recipient’s brain tissue because the brain cells did not express PrPc (the precursor for the misshapen PrPsc), and accordingly, the antibodies could not cause an autoimmune attack of the brain tissue. A further extension of this observation showed that PrPo=o mice with a reconstituted PrPþ=þ lymphoreticular system and carrying a PrPþ=þ mouse graft developed the typical pathological changes only in the graft, but not in the recipient’s brain, after inoculation with diseased brain tissues (Brandner et al., 1996; Fraser et al., 1996). To explain this observation, I like to note that the normal cellular PrPc protein present in the brain graft is assumed to be not immunogenic to the PrPþ=þ mouse lymphoreticular system, and accordingly, antibodies against mouse PrPc most likely would not be produced. However, when the animals were inoculated with diseased brain tissue containing mouse PrPsc, specific antibodies against PrPsc would be produced because the mouse PrPsc is weakly immunogenic to the mouse lymphoreticular system. The produced antibodies would only target the PrP-expressing brain graft but not the recipient’s brain, which lacked PrPc, and accordingly, the pathogenic changes would only be seen in the brain graft but not in the recipient’s brain. 4. Studies have shown that the mouse PrP gene diVers from the hamster PrP gene at 16 codons (out of 254 codons). Normally, mice inoculated with hamster PrPsc rarely developed an SE disease. However, when the transgenic mice were made to carry the Syrian hamster PrP gene in addition to its own PrP gene, the animals started to make both mouse and hamster PrP proteins (DeArmond and Prusiner, 1995; Prusiner et al., 1990; Scott et al., 1989). These transgenic mice after selectively inoculated with the hamster PrPsc developed the SE disease. Their brains tested positive only for the hamster PrPsc but were essentially

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negative for the mouse PrPsc. Similarly, when these animals were selectively inoculated with the mouse PrPsc, they also developed SEs, but their brains tested positive only for the mouse PrPsc. These observations have been incorrectly construed by prion researchers to suggest that the PrPsc preferentially converted the cellular PrPc with a homologous composition to the corresponding PrPsc. They believed that the preferential ability of PrPsc to physically attract PrPc with the same amino acid sequence for direct intermolecular interactions between them was the main reason for the described experimental observations. According to the proposed new theory on the pathogenesis of SE, it is rather clear that in transgenic mice expressing both mouse and hamster PrP proteins, inoculation of the mouse PrPsc would only lead to the production of antibodies specific for the misshapen mouse PrP, eventually leading to the formation of the mouse PrPsc. The hamster PrPsc would not be formed assuming that the antibodies had little cross-reactivity for the misshapen hamster PrP protein. Similarly, when these mice were inoculated with the hamster PrPsc, only the hamster PrPsc would be formed. Here, it is tempting to also point out that in the described experiments, if the hamster PrP transgene in mice can produce hamster PrPc that serves similar physiological functions as does the mouse PrPc, then we can predict that the accumulation of the mouse PrPsc in the CNS will be rather minimum. The reason is that when the mouse PrPc is functionally inactivated by the binding of the autoimmune antibodies, the targeted cell may not need to drastically increase the expression of the mouse PrPc because the hamster PrPc protein can still compensate for much of the needed physiological functions normally provided by the mouse PrPc. 5. Another line of important evidence for the proposed new theory came from studies using the PrPo=o null mice that received a hamster PrP transgene, which was precisely placed under the transcriptional control of either a glial cellspecific promoter or a neuron-specific promoter so that the hamster PrPc could be selectively expressed in either type of the cells (Race et al., 1995; Raeber et al., 1997). After an intracerebral challenge with the hamster PrPsc, the glial cells and the neurons each could develop characteristic disease-state histopathology independently, but the same PrPsc inoculation did not cause pathological changes in PrPo=o mice. The observations from these elegant experiments agreed perfectly with the proposed new theory that the production of specific antibodies is needed for the development of SE. When the hamster PrP was selectively expressed in neurons, then the specific antibodies would only target neurons, but when PrP was selectively expressed in glial cells, then the antibodies would only target glial cells. 6. There were some experimental findings that are in line with the hypothesis that the antibody-mediated chronic autoimmune attack of the CNS, along with chronic inflammatory responses, is intimately linked to the development of SE

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diseases. First, elevated lymphocytes and other white blood cells were present in the aVected regions of the CNS (Betmouni and Perry, 1999; Betmouni et al., 1996; Mabbott and Bruce, 2001). Second, the cytokine levels were elevated after prion inoculation (Mabbott and Bruce, 2001), along with other serological indicators of a CNS inflammation (Coe et al., 2001). Third, an earlier study showed that the complement system of the recipient body could facilitate prion pathogenesis (Klein et al., 2001). This finding is particularly interesting because it is consistent with the suggested role for the antibody-mediated autoimmune attack of CNS in SE pathogenesis. Lastly, an early study showed that administration of a corticosteroid markedly inhibited the development of an SE disease in mice (Outram et al., 1974). Taken together all the evidence discussed here, the antibody-mediated chronic autoimmune attack, along with the associated inflammatory responses, plays a crucial role in the development of neuronal lesions associated with SEs. Here, it is also of note that the CNS inflammatory responses described here usually only occurred at a very mild level during SE pathogenesis, which was in contrast to the massive white blood cell infiltration commonly seen during CNS viral infections. The mild inflammatory responses in the CNS likely reflected the very low levels of the autoimmune antibodies produced for PrPsc. However, in most of the biomedical literature, these experimental observations were only construed by prion researchers as evidence for excluding viral infection as the etiological origin for SEs.

B. A Brief Explanation for the Apparent Existence of Multiple ‘‘Prion Strains’’ and ‘‘Species Barriers’’ Many studies have shown that animals inoculated with brain extracts from SE animals or humans usually have distinguishable pathological characteristics on the basis of the disease incubation time, location of the brain lesions, patterns of the spongiform changes, and the profiles of PrPsc glycoforms (Bruce and Dickinson, 1987; Bruce et al., 1989, 1991, 1994; Dickinson and Meikle, 1969; Fraser and Dickinson, 1968; Hill and Collinge, 2001; Kimberlin and Walker, 1978; Klein et al., 2001; Lloyd et al., 2001; Outram et al., 1974; Race et al., 2002; Robinson et al., 1995; Somerville et al., 1997). The time course for the development of various CNS pathological changes appeared to be largely determined by the structural characteristics of the inoculated PrPsc and the recipient’s PrPc protein (Bruce et al., 1989, 1991; Kimberlin and Walker, 1988; Prusiner and McKinley, 1987; Race et al., 2002; Weissmann, 1991a,b). To explain these phenomena, it was suggested that PrPsc has diVerent ‘‘strains,’’ which carry information directly encoding their own biological properties (Bock and Marsh,

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1988; Bruce et al., 1991; Kimberlin and Walker, 1988; Prusiner and McKinley, 1987; Ridley and Baker, 1996; Weissmann, 1991a,b). Enormous eVorts have already been made to characterize the disease incubation time and the profiles of spongiform changes in various strains of mice (Bruce and Dickinson, 1987; Bruce et al., 1989, 1991, 1994; Dickinson and Meikle, 1969; Fraser and Dickinson, 1968; Hill and Collinge, 2001; Kimberlin and Walker, 1978). For instance, it has been suggested that there were as many as 15 or more strains of scrapie (on the basis of the diVerent latency and lesion patterns) that could be propagated in the same inbred mouse strain. In addition to the apparent existence of multiple strains for the diseasecausing PrPsc, it appeared that there were clear species barriers (i.e., PrPsc from one animal species often was very diYcult to cause similar diseases in animals of another species). It was first reported in the 1960s that it was very diYcult to make rodents develop SE diseases by inoculating them with the brain extracts from scrapie sheep. Studies using laboratory animals have also shown that when the hamster PrPsc was inoculated into mice, many (but not all) of the animals lived a long SE-free life and did not accumulate PrPsc in their brains. Similarly, many of the hamsters inoculated with mouse PrPsc did not develop SE. The prevailing explanation for the multiple prion strains has been that PrPsc could adopt multiple configurations, and it could serve as a template for copying its structural information to the recipient PrPc through direct physical interactions between the PrPsc and PrPc, and ultimately transforming PrPc into PrPsc. When PrPsc was folded in one way, it might convert PrPc to the pathogenic PrPsc with a higher eYciency, giving rise to a shorter incubation time. Folded in another way, it might work less eYciently. It was further suggested that one PrPsc might be attracted to neuronal populations in one part of the brain, whereas another form of PrPsc may be attracted to neurons elsewhere, thereby producing diVerent profiles of pathogenic brain lesions and clinical symptoms. Similarly, the explanation for the species barriers oVered by the prion hypothesis was based on the assumption that PrPsc preferentially interacted with the PrPc protein of a homologous composition and converted it into PrPsc, whereas PrPsc could not convert the PrPc protein from a diVerent species with a slightly diVerent structure. The proposed new theory oVers completely diVerent mechanistic alternative explanations for the apparent existence of multiple PrPsc strains. It is suggested that the apparent existence of diVerent strains of prion most likely was caused by a combination of the following two major factors. The first factor is the presence of PrPsc with diVerent immunogenic determinants, which are largely determined by the steric structures=configurations of the PrPsc protein. Consequently, the autoimmune antibodies targeting the PrP molecules with diVerently misshapen configurations may be produced. Furthermore, these antibodies may target diVerent regions (i.e., intracellular vs

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extracellular) of the PrP protein. Depending on where the PrP molecule the antibodies bind to, the antibody-stabilized misshapen PrP may eventually have rather diVerent patterns of covalent modifications (such as glycosylation), and these diVerently modified PrP proteins may also have diVerential susceptibility to digestion by various proteases contained in lysosomes. These variables, when present in diVerent combinations, are expected to diversify the pathological changes seen in SE. The second factor is the possible involvement of other long-lasting immunogenic macromolecules. This possibility would become more likely when crude extracts from diseased brain tissues were used to inoculate animals to induce SE. Many earlier studies have noted that the pathogenic features of the SE disease in the same strain of animals inoculated with isolated PrPsc were noticeably diVerent from those in animals inoculated with the diseased brain tissue. When the whole tissues or the crude extracts from SE animals were used for inoculation, it is expected that varying titers of the autoimmune antibodies for various immunogenic cellular macromolecules would be produced, and they may have varying degrees of cross-reactivity against the recipient’s brain tissue. In addition, because these immunogens may have quite diVerent distribution in the CNS, eventually the localization of the pathogenic lesions may vary significantly. Notably, the presence of -amyloid plaques in the brain of patients with Alzheimer’s disease serves as a good example for the possible involvement of other protease-resistant immunogenic proteinaceous particles. According to the proposed new theory, it is also suggested that the apparent species barriers of SE diseases are largely attributable to the dissimilar immunogenic determinants of the PrPsc proteins (as well as the presence of other immunogenic macromolecules) from diVerent animal species. If the immunogenicity of the PrPsc proteins from two animal species is highly similar, then the anti-PrPsc antibodies produced for one species may also have considerable crossreactivity with the PrP from the other species, and thus, there would be no apparent species barriers between these two species. However, if the antibodies could not recognize the PrP protein of the recipient animal, they may not cause significant pathogenic lesions in the recipient’s CNS. Studies have also shown that the passage of the SE disease from one species to another using experimental inoculations of the diseased tissue extracts, if ever occurred, was generally accompanied by a significant prolongation of the incubation time relative to the passage of SE disease within the same species. According to the new theory, the markedly longer incubation time is due to the fact that two diVerent sets of antibodies might need to be produced. As explained earlier (Section II.C), the initial set of antibodies were produced in response to the inoculated PrPsc, and the second set of antibodies were produced at a later time after the recipient’s PrPc molecules had been converted to the immunogenic PrPsc. However, when some of the recipient animals from another species had already developed SE,

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the subsequent passage of the disease within the new species usually would have very high incidence and a consistently short incubation time. Here, it is also worth noting that the similarity in the amino acid sequences of diVerent PrP proteins from diVerent species of animals is not entirely proportional to their similarity in immunogenicity. The immunogenicity is determined not only by the amino acid sequence of a protein, but also by its tertiary structure (configuration). There are many known examples that certain amino acid residues in a given protein play a more important role than other amino acid residues in determining the steric configurations of a protein and thus its immunogenicity. In light of the proposed new theory on pathogenesis, it is reasonable to suggest that the so-called ‘‘species barriers’’ are probably not as strict as usually thought. There are some experimental observations in line with this suggestion. For instance, the brain extracts from BSE cattle could cause similar SE diseases in cattle, sheep, mice, pigs, and mink after intracerebral inoculations. Similarly, the brain extracts (containing PrPsc protein) from cattle, nyala, kudu, and domestic cats have been found to cause SE in C57BL, VM, and F1(C57BL VM) mice after intracerebral inoculations, and all of these extracts gave very similar disease incubation times. Along the same line of thinking, it is also reasonable to suggest that the PrPsc proteins from diVerent poultry animals may share varying degrees of similarity to the human PrPsc in certain antigenicity-determining regions. If this were the case, humans would be susceptible to the development of SE diseases if they were exposed to suYciently high doses of PrPsc (along with other pathogenic proteinaceous particles) from diseased cattle or other poultry animals, although the pathogenic activity of the immunogens from various animals may be substantially diVerent from each other. This diVerence in the immunogenicity of the PrPsc proteins from various poultry animals may, to a great extent, determine the severity of the pathogenic process.

C. A Brief Explanation for the Autoimmune Origin of Various Human and Animal SE Diseases Clinical observations have shown that the development of various animal and human SE diseases, whether sporadic, inherited, or acquired, is consistent with the hypothesis that they are autoimmune-type diseases on this topic aVecting the CNS. A brief overview of the animal and human SE diseases is provided later. 1. SE Diseases in Animals In animals, the most common form of SEs is scrapie found in sheep, and the other forms of SEs include transmissible mink encephalopathy, chronic wasting disease of mule deer and elk, feline spongiform encephalopathy, and BSE.

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BSE, also called ‘‘mad cow disease,’’ was first identified by G. A. Wells and J. W. Wilesmith after it began striking cows in Great Britain, causing them to become uncoordinated and unusually apprehensive (Wilesmith and Wells, 1991). It was estimated that as many as 1 million cattle have been sick with BSE in the past several decades, and near 200,000 cattle (primarily dairy cows) have died of BSE within the past 2 decades (USDA, 2003). The mean incubation time for BSE was estimated to be about 5 years, and most cattle usually did not manifest the disease because they were slaughtered between 2 and 3 years of age. Although sporadic or inherited SEs may occur in animals, the source of the apparent epidemic in the past few decades has been traced to a food supplement that included meat and bone meal (MBM) from dead sheep, among which a few of them might have developed SEs. The MBM was prepared from the oVal of sheep, cattle, pigs, and chickens and used as a protein-rich nutritional supplement, and it was primarily fed to dairy cows (Anderson et al., 1996; Gibbs, 1996; Nathanson et al., 1997; USDA, 2003; Wilesmith and Wells, 1991; Wilesmith et al., 1991). The animals could be exposed to PrPsc from sick animals with SE diseases as a result of oral feeding of the MBM. Notably, there are a number of possible reasons for the higher occurrence of SE diseases in cattle than in other animals: (1) The MBM was primarily fed to dairy cows (Anderson et al., 1996; Nathanson et al., 1997; USDA, 2003; Wilesmith and Wells, 1991; Wilesmith et al., 1991). (2) The development of SEs usually took a long incubation period (Dickinson et al., 1975). Comparing most of the common poultry animals, dairy cows usually were kept alive for a much longer time than other animals (such as pigs, sheep, and chickens), and thus, they would have much higher chances to develop full-blown SE diseases. It is also suggested that the sporadic SE diseases in animals (and also in humans) are due to aberrant formation of autoimmune antibodies against the PrP and possibly other CNS proteins. It occurs rarely, and usually it has a long and slow progression period. It is conceivable that the risk for an animal to develop sporadic SEs may be markedly elevated due to genetic predispositions (such as mutations or polymorphism) related to the target protein (PrPc) and=or the production of antibodies. There are many cases of human PrP gene mutations that are known to be linked to an elevated risk for SE diseases (discussed later). However, it should also be noted that mutations of the PrP gene, in some rare cases, can also reduce the risk for SE diseases. For instance, it is known that sheep with the Arg=Arg polymorphism at position 171 were essentially resistant to scrapie (Belt et al., 1995; Hunter et al., 1993, 1997; Oppenheimer, 1983; O’Rourke et al., 1997; Parry, 1962; Westaway et al., 1994b). The possible explanation for this phenomenon is that Arg=Arg polymorphism of the sheep PrPc may alter its structure or its ability to transiently adopt certain misshapen configurations, thus allowing it to evade the recognition and attack by the antibodies produced against PrPsc from cattle or other sheep without the Arg/Arg polymorphism.

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2. SE Diseases in Humans a. Kuru. Kuru was found among the Fore highlanders of Papua New Guinea (Collinge and Palmer, 1997; Gajdusek, 1977; Prusiner, 1993; Wilesmith and Wells, 1991; Wilesmith et al., 1991). Many highlanders became aZicted with a strange fatal disease marked by the loss of coordination (ataxia) and often later by dementia. It is believed that the aVected individuals acquired Kuru through ritual cannibalism (i.e., the Fore tribe reportedly honored the dead by eating their brains). Because the practice was stopped several decades ago, Kuru has virtually disappeared. The pathogenic explanation according to the proposed theory is that oral ingestion of PrPsc and=or other long-lasting immunogenic macromolecules from diseased human brains would lead to the production of specific autoimmune antibodies against the human PrP and=or other macromolecules present in the human brain. These autoimmune antibodies would lead to accumulation of PrPsc and=or other protease-resistant proteins in the CNS. Moreover, the antibodies would also bring on a chronic autoimmune attack of the CNS cells, ultimately resulting in the development of the disease. b. Creutzfeldt-Jakob Disease. Cases of CDJ have been found worldwide, with dementia as a usual clinical manifestation. Often it occurred sporadically, roughly striking one person in a million, typically at age about 60 years (Collinge and Palmer, 1997; Prusiner and McKinley, 1987). For the apparently sporadic CJD, the likely cause is due to the abnormal production of autoimmune antibodies against the human PrP protein or other immunogenic components in the CNS. Similar to the production of autoimmune antibodies involved in many other types of autoimmune diseases, the mechanism for the aberrant production of autoimmune antibodies against CNS neurons is not clear at present. When the antibodies against the CNS components are produced, they would cause a chronic autoimmune attack of the CNS cells that express these proteins, gradually leading toward the development of CJD. It is also known that a small number of the CJD cases are iatrogenic. The known causes for iatrogenic CJD mainly included the use of human growth hormone and gonadotropins derived from cadaveric pituitaries (before recombinant hormones became available), dura mater grafts, transplanted corneas, and improperly sterilized depth electrodes (Bateman et al., 1995; Bernoulli et al., 1997; Billette de Villemeur et al., 1996; Britton et al., 1995; Brown et al., 1992, 1993; Centers for Disease Control and Prevention, 1989; Cousens et al., 1997; DuVy et al., 1974; Esmonde et al., 1993; Heckmann et al., 1997; Lane et al., 1994; Lugaresi et al., 1986; Miyashita et al., 1991; PHS Interagency Coordinating Committee, 1997; Thadani et al., 1988; Will, 2003; Will et al., 1996). More than 90 young adults have developed iatrogenic CJD after treatment with cadaveric human growth hormone, with incubation time ranging from 3 years to more than 20 years (Billette de Villemeur et al., 1996; Brown et al., 1992; PHS

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Interagency Coordinating Committee, 1997; Villemeur et al., 1996). Dura mater grafts implanted during neurosurgical procedures seemed to have caused more than 60 cases of CJD, with an incubation time ranging from 1 year to more than 14 years (DuVy et al., 1974; Gajdusek, 1977; Hunter et al., 1997; Oppenheimer, 1983; O’Rourke et al., 1997; Parry, 1962). It is suggested that the development of iatrogenic CJD was caused by autoimmune antibodies produced against the brain tissue of the recipient. Because many of the iatrogenic CJD have apparent sources of the pathogenic human immunogens, the case for the role of autoimmune antibodies in pathogenesis is somewhat clearer. However, a few intriguing questions related to this explanation are worth noting here: If the major immunogen that eventually led to the development of iatrogenic CJD was the human PrPsc, then this would mean that a small but significant fraction of people might actually have considerable amounts of PrPsc in their brain and other tissues yet without clear clinical symptoms of an SE disease at the time of death. If this was the case, then the further question is what were the natural causes that had led to the formation of PrPsc in these elderly donors? It is possible that age-related oxidative damage to various proteins (including PrPc) may be among the causes for increased conversion of PrPc to PrPsc over time. On the other hand, it may also be possible that other immunogenic proteins or even nonprotein macromolecules may be involved in the development of autoimmune antibodies that target the recipient’s brain, causing similar neurological lesions seen in iatrogenic CJD. Somewhat in line with this suggestion, the clinical manifestations of the iatrogenic human CJD were noticeably diVerent from those of sporadic CJD. Also, some studies indicated that PrPsc from the brain of patients who died of iatrogenic CJD had a diVerent pattern of glycoforms than PrPsc from sporadic CJD or vCJD patients. Cases of new variant CJD (called vCJD) occurring in recent history in Great Britain and France have prompted suspicion that these human cases were causally linked to the occurrence of BSE in those countries (Cousens et al., 1997). Although most of the sporadic CJD cases occurred around 60 years or older, most of the patients with vCJD were about 40 years or even younger (quite similar to iatrogenic CJD). The neuropathology of vCJD patients was found to be unusual, with numerous PrP amyloid plaques surrounded by intense spongiform degeneration. It is suggested that vCJD patients might have previously been exposed to bovine PrPsc due to consumption of the meat and=or oVal products from diseased cattle. It is expected that the titers of the autoimmune antibodies for human PrP protein in vCJD patients might be comparatively higher than the antibodies present in sporadic CJD patients. Consequently, vCJD would progress more rapidly, due to stronger antibody-mediated autoimmune attacks of neurons and other peripheral tissues that express the PrP protein. This hypothesis can be experimentally tested in diVerent ways, such as through determining the titers=aYnities of the autoimmune antibodies for both bovine and human PrPsc

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proteins and determining the chronic CNS inflammatory responses mediated by the autoimmune antibodies. It is of note that while the bovine PrPsc has been suspected of causing human vCJD cases (Cousens et al., 1997), the general perception has been that the contaminated meat and=or oVal products from other SE animals (such as sheep, pigs, and chickens) may not be as pathogenic or not pathogenic at all to humans. This perception was, in part, based on some epidemiological data suggesting the lack of a link between sheep scrapie and the occurrence of human CJD in sheepfarming countries, although a few apparent cases were widely reported that farmers who had ‘‘mad cows’’ in their herds had died of vCJD. According to the proposed new theory, although it is possible that the human antibodies produced against the PrPsc proteins from noncattle poultry animals may have little or no cross-reactivity against the human PrP protein, the more likely possibility is that the antibodies also have certain degrees of cross-reactivity for the human PrP protein. Therefore, humans most likely could also develop SE diseases through consuming contaminated meat and=or oVal products from noncattle poultry animals, although the pathogenic activity of PrPsc from diVerent poultry animals may vary markedly. It should also be noted that there are other possible reasons that might have contributed to the apparent lack of an association between sheep scrapie and human vCJD. As already mentioned earlier, dairy cows usually were kept alive for a much longer time than other animals, and thus, they had more time to develop the full-blown BSE. Also, because PrPsc usually would accumulate at high levels in the CNS and other tissues at late stages of the SE disease, this would mean that tissues from BSE cattle likely were more pathogenic than tissues from other poultry animals that might have early stage SE diseases. In addition, human consumption of beef worldwide was far greater in quantity than sheep meat. Lastly, in the past several decades, the numbers of cattle with BSE were far greater than the numbers of other poultry animals with SE diseases. All these factors might have contributed to the fact that there has been no reported case of human vCJD that could be directly linked to the consumption of meat and=or oVal products from sheep or other poultry animals. It is of note that the banning of the widespread practice of feeding the MBM to cattle and sheep in 1988 has contributed, in a very important way, to the sharp decrease of the SE cases in animals (Anderson et al., 1996; Gibbs, 1996; Nathanson et al., 1997; USDA, 2003; Wilesmith et al., 1991), which was somewhat reminiscent of the disappearance of Kuru in the Fore people of New Guinea several decades ago. This ban would also help reduce the risk of human SE diseases. c. Gerstmann-Straussler-Scheinker Syndrome and Fatal Familial Insomnia. GerstmannStraussler-Scheinker syndrome (GGS) and fatal familial insomnia (FFI), first described by Lugaresi, Medori and colleagues 18 years ago (Lugaresi et al.,

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1986), usually are inherited and typically appear in midlife. Most of the GGS and FFI cases seemed to occur in humans without any indications of having been spread from one host to another, and in some families they appeared to be inherited (Lugaresi et al., 1986; Monari et al., 1994). Cloning of the PrP gene obtained from a man who had GGS in his family and was dying of it himself revealed a point mutation in codon 102, with leucine substituted for proline in the PrP protein. Following this initial finding, later it was further discovered the presence of the same genetic mutation in other patients with GSS, and the high incidence in the aVected families was statistically significant, thus suggesting a genetic linkage between PrP mutations and human SE diseases. Now about 20 mutations of the PrP gene in families with inherited SE diseases have been uncovered, and several of these mutations have been found to be genetically linked to SE diseases. It is hypothesized here that these mutations may make the PrPc protein more readily adopt other aberrant configurations, which may have a higher chance for stabilization through covalent modifications, gradually leading toward the formation and accumulation of protease-resistant, immunogenic PrPsc and its fragments. When PrPsc and its fragments are formed and gradually accumulated in the body, it would lead to the production of autoimmune antibodies. The anti-PrPsc antibodies would lead to autoimmune attacks of the CNS and peripheral tissues that express the PrP protein, in addition to causing further accumulation of the PrPsc in the targeted cells (ultimately in lysosomes).

IV. Early Diagnosis, Treatment, and Prevention of Various SE Diseases

A. Early Diagnosis of SEs Based on the proposed theory on the mechanism of pathogenesis of various SEs, there are far easier ways to determine whether a person or an animal has developed certain forms of SEs simply by measuring the titers of antibodies for the human and animal prions, as well as antibodies for other proteinaceous and nonprotein antigens present in the brain tissue from animals and humans who died of various forms of SEs. Here, it should be noted that when a person develops SE because of prior consumption of the meat and=or oVal products from diseased cattle, that person may produce antibodies against both bovine PrPsc and human PrPsc. The initial antibodies produced are for the bovine PrPsc because of the exposure to bovine PrPsc in contaminated beef, and these antibodies likely also have some cross-reactivity for the misshapen human PrP (which transiently adopts the bovine PrPsc-like structure). However, when the initial antibodies against the bovine PrPsc are produced, they would gradually lead to

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the formation of human PrPsc. The human PrPsc, when formed in substantial amounts in the body may further serve as an immunogen and induce the formation of specific antibodies against it. These antibodies are expected to have a higher aYnity for the human PrPsc than for the bovine PrPsc (diVerent from the initial antibodies produced against the bovine PrPsc). Accordingly, it would be necessary to compare the titers and aYnities of the antibodies for both animal and human PrPsc proteins. A comparison of their titers and aYnities may provide useful clues about the origin and stages of the disease. It is suggested that, for instance, at early stages of the human SE disease that resulted from ingesting contaminated beef, the antibodies were expected to have a higher titer and aYnity for the bovine PrPsc than for the human PrPsc, but at late stages, the antibodies might have increased aYnity for the human PrPsc. The proposed antibody-based serological assays would be far easier and would provide more rapid early diagnosis than the presently used bioassays for detecting bovine PrPsc in mice, which are very insensitive and usually take a long time (up to years) to yield results.

B. Treatment Strategy for SEs According to the proposed new theory on the pathogenesis of SEs, it is suggested that certain immune suppressants may be highly eVective agents for the treatment of SEs. In support of this novel hypothesis, an early study has shown that administration of a corticosteroid markedly inhibited the development of an SE disease in mice (Outram et al., 1974). It is possible that immune suppressants with preferential activity toward antibody formation and antibodymediated autoimmune attack and inflammation may be particularly useful. Also, certain anti-inflammatory agents with a strong CNS activity may also be highly useful as part of a drug therapy.

C. Prevention of SEs The earlier implementation of the ban on the use of MBM as part of the animal feed was a very eVective measure to reduce the incidence of SE diseases in poultry animals (Anderson et al., 1996; Gibbs, 1996; Nathanson et al., 1997), and such a ban should be strictly reinforced for the prevention of SE diseases. In November 1989, the bovine oVal ban, which prohibited human consumption of CNS and lymphoid tissues from cattle older than 6 months, would also help further reduce the risk for humans to acquire SE diseases. This specific legislation was partly based on an earlier study showing that the highest titers of PrPsc were found in these tissues in sheep (Hadlow et al., 1982). Although all these measures

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would assist in reducing the risk of human SE diseases through ingesting contaminated animal meat and oVal products, it should be noted that it is vitally important to be able to test all cattle and some other poultry animals for SE diseases before they are slaughtered for human consumption. Rapid serological assays as proposed in this chapter may provide a means for rapid and reliable tests for SE diseases in live animals. Lastly, it is of note that because PrPsc is partially heat-resistant, thoroughly cooking the meat (particularly beef and ram) may help destroy the highly antigenic structures of the PrPsc and possibly other similar antigenic macromolecules and thus may help reduce the risk. Conversely, eating raw or undercooked beef may increase the risk for acquiring the immunogenicity-proficient PrPsc protein.

V. Conclusions

During the past several decades, a very large number of SE cases have been reported in animals (cattle in particular). Investigations of SE diseases in the past decade have taken on new importance with the reports of some two dozen cases of vCJD in teenagers and adults. Because almost all known cases were reported from Great Britain and France, it was thus suggested that BSE likely was passed to humans through the consumption of beef and=or oVal products from diseased cattle. Extensive investigations by Prusiner et al. over the past 3 decades have led to the conclusion that the pathogenic agents in animal and human SEs consisted mainly of proteins. Their conclusion was, in part, based on their earlier findings that various procedures that were well known to destroy nucleic acid and viruses did not appear to significantly reduce infectivity, whereas procedures that denatured or degraded protein drastically reduced infectivity. Dr. Prusiner et al. proposed that PrPsc alone was responsible for transmitting an infectious disease. This theory has now become a widely accepted doctrine concerning the pathogenesis of various animal and human SE diseases. Although I believe that PrPsc, possibly along with other immunogenic proteinaceous and=or nonprotein particles, plays an important role in the development of human and animal SEs, I think that the explanations provided by the prevailing prion hypothesis concerning the pathogenic mechanisms of SE diseases likely are incorrect. Based on the available experimental evidence, a novel theory has been developed in this paper, which suggested that various known forms of human and animal SE diseases are autoimmune-type diseases. A key step in the pathogenic process leading toward the development of SE involves the production of specific autoimmune antibodies against PrPsc and possibly other long-lasting antigenic macromolecules present in the brain. As precisely explained here, the autoimmune antibodies produced against PrPsc are not only

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responsible for the conversion of the normal cellular PrPc protein to the diseasecausing PrPsc, but they are also responsible for the accumulation of PrPsc in the brain and other peripheral tissues. This mechanistic theory also explained that the antibodies have the tendency to copy the configurational features of the parent PrPsc to the newly formed daughter PrPsc. Most importantly, the antibodies are responsible for the initiation of an antibody-mediated chronic autoimmune attack of the targeted cells (such as neurons), which would produce pathological changes and clinical symptoms characteristic of the SE diseases. The proposed novel theory is strongly supported by an overwhelming body of existing experimental data scattered in the biomedical literature. The theory also provided novel strategies for early diagnosis, prevention, and treatment of various SE diseases. It is also suggested that besides PrPsc, other long-lasting highly antigenic macromolecules may also be involved in the pathogenesis of various SE diseases. Each of these antigenic macromolecules may have quite diVerent cellular distribution in the CNS as compared to PrPsc. As a result, the clinical manifestations (which, in part, are determined by the diVerent locations of the brain lesions) are expected to vary considerably. The proposed theory also oVered unique insights into the pathogenesis of other neurodegenerative diseases, such as Alzheimer’s disease, Parkinson’s disease, Huntington’s disease, and amyotrophic lateral sclerosis. There are marked similarities in all these diseases, and here I like to use Alzheimer’s disease as an example to highlight this notion. In Alzheimer’s disease, the insoluble, protease-resistant -amyloid protein or its peptide fragments, which are major components of the amyloid proteins share many of the known disease-causing biophysical properties as PrPsc. The histopathological characteristics (such as loss of neurons, formation of proteinaceous particles in the brain, and spongiform formation) between Alzheimer’s disease and various SE diseases are strikingly similar. In addition, during the development of Alzheimer’s disease, modest levels of infiltration of lymphocytes and white blood cells, as well as other clinical signs of an antibodymediated mild inflammatory response were characteristically present. There were also studies suggesting that chronic use of anti-inflammatory agents was associated with a decreased risk for Alzheimer’s disease. Therefore, it is suggested that the human Alzheimer’s disease likely is another autoimmune-type disease preferentially aVecting the CNS (Zhu, 2005). Measuring the titers of the circulating autoimmune antibodies against the -amyloid plaques and other antigenic components involved may provide a means for the early diagnosis of the disease. In addition, it is also suggested that certain immune suppressants and antiinflammatory agents may be useful drugs for the treatment and prevention of Alzheimer’s disease. Lastly, it should be noted that there may be potentially unavoidable untoward eVects associated with the recent clinical trials that were designed to stimulate the body’s production of antibodies for -amyloid plaques

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as a prevention and treatment strategy for Alzheimer’s disease. In light of the new mechanistic understanding developed here, it seems almost certain that such a strategy may not work as intended, but it may do the opposite, accelerating the development of Alzheimer’s disease.

Acknowledgments

I thank Dr. Karen Xiaomeng Xu at the Lexington Medical Center (South Carolina) for her helpful suggestions for the manuscript. I also want to express my indebtedness to many researchers in this field that their equally important research work has been left out of the reference list below because of space constraint.

References

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ADENOSINE AND BRAIN FUNCTION

Bertil B. Fredholm,* Jiang-Fan Chen,y Rodrigo A. Cunha,z Per Svenningsson,* and Jean-Marie Vaugeoisx

*Department of Physiology and Pharmacology, Karolinska Institutet Stockholm S-171 77, Sweden Department of Neurology, Boston University School of Medicine, Boston Massachusetts 02118 z Faculty of Medicine, Center for Neuroscience of Coimbra, University of Coimbra Coimbra 3004-504, Portugal, and x CNRS FRE2735, IFRMP 23, Faculty of Medicine and Pharmacy Rouen 76183, France y

I. Introduction II. Regulation of Brain Adenosine Levels in the Central Nervous System III. Adenosine Receptors A. Cellular and Subcellular Localization B. Pharmacological Tools to Study Adenosine Receptors C. Signaling Via Adenosine Receptors D. Regulation of Receptor Expression and Signaling IV. Functions of Adenosine Receptors A. Regulation of Nerve Activity B. Regulation of Transmitter Release C. Other Functions D. Interaction with Other Transmitter Systems V. Adenosine–Dopamine Interactions in Brain A. General Considerations B. Heterodimerization of Adenosine–Dopamine Receptors as a Molecular Basis for Direct Receptor–Receptor Interaction in the Striatum C. Endogenous Adenosine Acting on A2A Receptors Can Also Exert Excitatory Tone on Striatal Neurons by D2 Receptor–Independent Mechanisms D. DARPP-32 as a Potential Molecular Target for Integrating Adenosine and Dopamine Signaling at the Cellular and Network Levels in the Striatum VI. Phenotypes of Knockout Mice VII. Adenosine Receptors and Protection against Ischemic and Excitotoxic Brain Injuries A. A1 Receptor Activation Produces Predominantly Neuroprotective EVects B. Blockade or Inactivation of A2A Receptors OVers Neuroprotection C. Neuroprotection by A2A Receptor Agonists May Be Mediated through Modulation of Inflammation D. Complex Actions of A1 and A2A Receptors at Multiple Cellular Elements: Implications for Treatment of Neuropsychiatric Disorders VIII. Adenosine A2A Receptors and Neurodegenerative Disorders A. A2A Receptors and Parkinson’s Disease B. Adenosine Receptors and Huntington’s Disease C. Adenosine Receptors and Alzheimer’s Disease

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IX. Adenosine Receptors and Psychiatric Disorders A. Adenosine Receptors and Schizophrenia B. Adenosine Receptors and Addictive Behaviors X. Adenosine and the Regulation of Sleep–Wake Cycles XI. Adenosine and Epilepsy XII. Adenosine and Pain References

I. Introduction

Adenosine is an endogenous neuromodulator that influences many functions in the central nervous system (CNS). The levels of adenosine increase when there is an imbalance between rates of energy use and rates of energy delivery. Thus, increased neuronal activity, and particularly hypoxia or ischemia, results in markedly elevated levels of adenosine (Newby, 1991). Because adenosine tends to reset the energy balance, it has been called a retaliatory metabolite (Newby, 1984), and its potential role as an endogenous neuroprotective agent both in ischemia and following seizures has been repeatedly emphasized (de Mendonc˛ a et al., 2000; Dunwiddie and Masino, 2001; Fredholm, 1996; Marangos, 1991; Marangos et al., 1990; Phillis and Goshgarian, 2001; Picano and Abbracchio, 2000; Rudolphi et al., 1992b; Von Lubitz, 2001). Another major impetus for studies of the role of adenosine in brain function has been the realization that many of the eVects of the most widely used of all psychoactive compounds, caVeine, is exerted by blocking eVects of adenosine (Daly, 1977; Fredholm, 1980; Fredholm et al., 1999; Sattin and Rall, 1970). As discussed later in this chapter, one important implication of this is that at least some eVects of adenosine are exerted already under basal conditions. Over the past decade, studies with pharmacological tools and using genetically modified mice have revealed other roles of adenosine. This chapter examines some of these, but the interested reader is referred to other reviews, cited where appropriate, to get a more complete picture. II. Regulation of Brain Adenosine Levels in the Central Nervous System

One must clearly understand that adenosine does not act as a classical neurotransmitter: It is not stored in vesicles, it is not released by exocytosis, it does not appear to transfer information unidirectionally from presynaptic to postsynaptic components, and it does not act only or predominantly in synapses. Instead, adenosine fulfills a double role (Cunha, 2001a), acting both as a homeostatic transcellular messenger and as a neuromodulator, controlling neurotransmitter

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release and neuronal excitability. The former role is common to all cells, whereas the latter is of particular interest in brain. Adenosine can appear in the extracellular milieu through three mechanisms: (1) the release of adenosine as such through nucleoside transporters (Geiger and Fyda, 1991) after an increase in the intracellular levels of adenosine or a reversal of the sodium gradient; (2) the extracellular formation of adenosine through the ectonucleotidase pathway on release of adenine nucleotides, especially adenosine triphosphate (ATP); and (3) the extracellular formation of adenosine after release of cyclic adenosine monophosphate (cAMP) (Dunwiddie and Masino, 2001; Latini and Pedata, 2001). The third pathway has been proposed to be of relevance in the release of adenosine triggered by particular signals that raise cAMP in cell culture systems (Rosenberg and Li, 1995) but has been found to be of minor importance in more integrated neuronal preparations when physiological parameters aVected by adenosine are being studied (Brundege et al., 1997). Release of adenosine after its intracellular formation has been clearly shown following hypoxia or metabolic poisoning and following field stimulation of brain slices (Cunha, 2001a; Dunwiddie and Masino, 2001; Latini and Pedata, 2001). Under such conditions, there is an imbalance between energy supply and demand, leading to a net hydrolysis of intracellular ATP. Via a series of steps, this intracellular ATP is converted to adenosine, leading to a dramatic increase in the intracellular concentration of adenosine, which, at rest, is around 50 nM. The presence of nonconcentrative bidirectional nucleoside transporters will then force extracellular adenosine levels to rise in parallel with intracellular adenosine. Given that intracellular ATP levels are some 100,000 times higher than adenosine levels, it is obvious that substantial changes in adenosine levels can occur without any major changes in ATP levels. Indeed, extracellular adenosine can be formed without any measurable change in the energy status of CNS preparations (Doolette, 1997; Mitchell et al., 1993). Given that the energy demanded—and hence the use of ATP—is substantial in localized neuronal compartments (e.g., to maintain ion balance), it is clear that there could be massive local adenosine formation. Nevertheless, it is diYcult to understand how ATP hydrolysis and intracellular adenosine formation could explain extracellular adenosine buildup in less than 20 ms (Mitchell et al., 1993). Also, release of adenosine through nucleoside transporters appears to be at odds with the ability of inhibitors of nucleoside transport to potentiate the eVects of endogenous adenosine (Cunha, 2001a; Fredholm et al., 1994b; Latini and Pedata, 2001), which indicates that the role of nucleoside transporters is mostly to clear up rather than to mediate adenosine release, at least in nonstressful situations. The importance of the equilibrative nucleoside transporter type 1 (ENT-1) in regulating extracellular adenosine levels has also been demonstrated in knockout mice lacking this protein (Choi et al., 2004). ENT-1 knockout mice exhibit a reduced adenosine tone, reflected by decreased adenosine-mediated

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inhibition of glutamate excitatory postsynaptic currents. This result is compatible with ENT being involved in releasing adenosine, so the issue remains unsettled. Adenosine is also formed by extracellular catabolism of released adenine nucleotides, mainly ATP, through the ectonucleotidase pathway (Cunha, 2001b; Zimmermann, 2000). In fact, unlike adenosine, ATP is present in synaptic vesicles and the vesicular release of ATP on stimulation of nerve terminals is well documented (Cunha, 2001a), but it is possible that ATP is released also by nonexocytotic mechanisms (Bodas et al., 2000; Bodin and Burnstock, 2001; Vizi and Sperla´ gh, 1999). Both astrocytes and dendritic compartments are apparently devoid of a fast exocytotic apparatus, and yet they are also able to release ATP (Caciagli et al., 1988; Queiroz et al., 1997) by a mechanism largely unknown (Arcuino et al., 2002; Coco et al., 2003; Joseph et al., 2003; Newman, 2003). The role of ectonucleotidases in forming extracellular adenosine is diYcult to study because it is diYcult to eVectively block an enzyme system that is extremely eYcient and where the enzymes and the eVector systems (i.e., the receptors) are in very close proximity (Cunha, 2001b; Cunha et al., 1998; Dunwiddie et al., 1997a; Masino et al., 2002). Indeed, the elegant work of Dale (2002) has demonstrated the crucial role of ectonucleotidases to control the buildup of adenosine as a function of neuronal activity. It should also be pointed out that neurochemical studies have concluded that the extracellular adenosine, which is relevant for modulation of synaptic transmission, might originate not only from nerve terminals but also from the activated postsynaptic component (Cunha, 2001a; Dunwiddie and Fredholm, 1997; Dunwiddie and Masino, 2001; Latini and Pedata, 2001) and from surrounding nonneuronal cells (Rochon et al., 2001). Thus, several mechanisms contribute to the formation of extracellular adenosine, and diVerent stimuli will generate extracellular adenosine in diVerent ways. Figure 1 schematically represents the possible contributions of the various compartments in the CNS to control the extracellular levels of purines. Clearance of extracellular adenosine mostly occurs through the action of the nonconcentrative nucleotide transporters, the activity of which can be regulated by the activation of adenosine receptors (ARs) through protein kinase pathways (Delicado et al., 1991). The eVectiveness of the uptake system is guaranteed by the eYcient intracellular metabolism of adenosine. Indeed, adenosine can either be converted into inosine through adenosine deaminase or be phosphorylated into AMP via adenosine kinase. Comparison of the equilibrium kinetic parameters of each of the enzymes suggests that adenosine kinase is important at low levels of intracellular adenosine, with adenosine deaminase coming into play only when large amounts of adenosine have to be cleared. Thus, adenosine kinase inhibitors are able to increase the extracellular levels of adenosine under physiological conditions, whereas adenosine deaminase inhibitors are able to increase the extracellular levels of adenosine during metabolic insults (Lloyd and Fredholm, 1995; Sciotti and Van Wylen, 1993). This probably reflects the relative importance

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Fig. 1. Schematic representation of adenosine formation and adenosine actions in diVerent cell types in brain. DiVerent cell types (microglia, astrocytes) and subcellular compartments (presynaptic boutton and dendritic region of neurons) can release both adenosine triphosphate (ATP) (gray lines) and adenosine (black lines). They are endowed with ectonucleotidases (filled circles) to convert ATP into adenosine and with adenosine transporters (cylinders) to bidirectionally transport adenosine through the plasma membrane. Also, all compartments are equipped with some of the adenosine receptors (A1, A2A, A2B, and A3; rectangles). In terms of intracellular metabolism of adenosine, all cell types and compartments can convert ATP into adenosine monophosphate (AMP) and AMP into ATP (dashed line presented only in the presynaptic boutton). In the presynaptic boutton, there is a substrate cycle between AMP and adenosine formation, involving adenosine kinase and 50 -nucleotidase (50 -N). The catalytic eYciency of this substrate cycle in other subcellular compartments or cell types in the central nervous system is not known. In astrocytes, the clearup of adenosine through the uptake system involves adenosine deaminase, whereas in nerve terminals it involves adenosine kinase. The information in the figure is incomplete and sometimes the evidence for a particular localization is rather poor.

of neuronal versus nonneuronal uptake of adenosine because the two enzymatic activities have apparently diVerent cellular locations, with adenosine kinase being enriched in neurons and adenosine deaminase being more abundant in astrocytes (Ceballos et al., 1994). It should also be mentioned that adenosine can be deaminated extracellularly into its inactive metabolite inosine through an ectoadenosine deaminase (Franco et al., 1997), although the relevance of this pathway for adenosine clearance in the CNS remains to be established (Cunha, 2001b). An alternative pathway for intracellular metabolism of adenosine is via the S-adenosylhomocysteine pathway (Schrader et al., 1981). Although this pathway

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is of relevance for the control of intracellular and extracellular levels of adenosine in cardiomyocytes, for instance (Schrader et al., 1981), it appears to be of limited importance in the CNS (Reddington and Pusch, 1983). The balance between the eVectiveness of adenosine release and clear-up will give rise to a transient extracellular buildup of adenosine. However, the presumably diVerent location of release sites and uptake sites makes it diYcult to estimate an extracellular concentration of adenosine. One should instead discuss the amplitude and time course of an extracellular adenosine gradient, rather than concentration. Pharmacological manipulation of the activity of nucleoside transporters and AR responses has led to an estimate of the transient concentration of adenosine facing A1 receptors (A1Rs) between 200 and 400 nM in the rat brain (Dunwiddie and Diao, 1994). This estimate of an eVective concentration of adenosine in a synapse is one order of magnitude higher than that found in the superfusate of CNS preparations (Cunha, 2001a) or in cortical cups (Phillis et al., 1987) but is similar to that found in microdialysis studies without stimulating or insulting the CNS (Balları´n et al., 1991; Hagberg et al., 1987). Upon stimulation (During and Spencer, 1992) or under stressful conditions (Hagberg et al., 1987), the extracellular amounts of adenosine can reach tenths of micromolar. However, microdialysis probes cannot estimate synaptic adenosine and are usually engulfed by astrocytic processes (Benveniste et al., 1989), which can eYciently release and metabolize extracellular purines (Caciagli et al., 1988; Gu et al., 1996; Lai and Wong, 1991). Likewise, the available enzymatic electrodes used to monitor extracellular adenosine (Frenguelli et al., 2003) are too large to record the rapidly changing adenosine concentration gradients in the synaptic cleft. Clearly, further experimental data are required to allow us to understand the nature of the purines released, as well as the cellular and subcellular compartments responsible for this release in diVerent pathophysiological situations in the CNS. Finally, the precise location of the sites of formation and removal of extracellular adenosine and its sites of action (i.e., receptors) needs to be pinpointed to clarify the relation between extracellular adenosine gradients and the diVerential activation of each AR subtype.

III. Adenosine Receptors

ARs were defined in the 1970s, partly based on the ability of methylxanthines such as theophylline and caVeine to act as antagonists (Fredholm et al., 1994a). The existence of at least two receptors—now called A1 and A2—that inhibit and stimulate adenylyl cyclase, respectively, was defined by 1980 (Londos et al., 1980; van Calker et al., 1979). During the ensuing decade, relatively selective agonists and antagonists were developed and A1Rs were partially purified (Fredholm et al., 1994a). Despite

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that ARs were well characterized and partially purified, the first two ARs cloned, A1 and A2A, came from a library of orphan receptors from the dog thyroid (Libert et al., 1991; Maenhaut et al., 1990). Soon the same receptors were cloned from rat and human (Furlong et al., 1992; Mahan et al., 1991), and a related receptor, the A2BR, was cloned from rat brain (Stehle et al., 1992). These receptors had all been predicted from extensive pharmacological studies. The fourth receptor, A3, was more unexpected (Zhou et al., 1992). By now these four ARs have been cloned from several mammalian and nonmammalian species. A1, A2A, and A2B receptors are well conserved among mammals, but A3Rs show considerable structural variability. The coding region of all four ARs is split up by an intron in a region corresponding to the second intracellular loop (Fredholm et al., 2000). Already when the structure of the A1R was first reported, the presence of two major transcripts was noted. Transcripts containing three exons, called exons 4, 5, and 6, were found in all tissues expressing the receptor, whereas transcripts containing exons 3, 5, and 6 are also found in tissues such as brain, testis, and kidney, which express high levels of the receptor (Ren and Stiles, 1994, 1995). There are two promoters, a proximal one denoted promoter A and a distal one denoted promoter B, which are about 600 bp apart. The rat A2AR gene is composed of two exons and encodes two clusters of alternative transcripts initiated from two independent promoters that diVer in the length of their 50 -untranslated region (Chu et al., 1996). The 4.8-kb promoter proximal DNA fragment of the rat A2AR gene contains important cis elements to direct expression in many brain areas (Lee et al., 2003). Three new exons in mouse A2AR genes and six exons in human A2AR genes (all 50 exons encoding for 50 UTR) were identified recently by bioinformatics and molecular analyses (Yu et al., 2004). Some newly identified exons appear to have tissue-specific expression patterns, and they are likely a result of usage of multiple, alternative promoters. It should also be mentioned that the human A2AR is polymorphic. In particular, a (silent) T1083C mutation occurs in various populations, more frequently in whites than in Asians (Deckert et al., 1996). The rat A2BR shows two hybridizing transcripts of 1.8 and 2.2 kb, where the latter is the dominant one (Stehle et al., 1992). This could, in analogy with the aforementioned discussion, suggest the presence of multiple promoters. The human A3R shows two transcripts: The most abundant is approximately 2 kb and the less abundant one about 5 kb (Atkinson et al., 1997), perhaps indicating similarities with the A1R gene. Some characteristics of the receptors are summarized in Table I. Other details can be found in reviews by Fredholm et al. (2000, 2001a).

A. Cellular and Subcellular Localization The distribution of receptors tells us where agonists and antagonists given to the intact organism can act. In addition, even the rather low levels of endogenous adenosine present under basal physiological conditions have the potential to

198 Gs, Golf

[3H]DPCPX; [3H]CHA

Several commercial and noncommercial peptide antibodies Human 326 aa P30542; rat 326 aa, P25099

Gi, Go

Radioligands

Antibodies

G protein coupling

Structural information (accession numbers)

[3H]CGS 21680; [3H]SCH 58261; [3H]ZM 241385 Several commercial and non-commercial peptide antibodies Human 410 aa, P29274; rat 409 aa, P30543; mouse 409 aa, UO5672

DPCPX 8-cyclopentyltheophylline, WRC0571

Selective antagonists

Gs, Gq

MRS1754, enprofylline, 1-butyl-8-[4-(4-benzyl) (piperazino2-oxyethoxy)phenyl] xanthine ([3H]ZM 241385; [3H]DPCPX) [3H]MRS1754 Some commercial and noncommercial peptide antibodies Human 328 aa, P29275; rat 332 aa, P29276; mouse 332 aa, UO5673

None

CGS 21680, HE-NECA, CV-1808, CV-1674, ATL146e selective: SCH 58261 moderately selective: ZM 241385, KF 17387, CSC

CPA, CCPA, CHA

Adenosine A2BR A2b, Rs; AA2BR

Adenosine A2AR A2a, Rs; AA2AR

Adenosine A1R

Ri; AA1R

Previous=alternative names Selective agonists

Receptor

TABLE I Some Properties of the Adenosine Receptors

Some commercial and noncommercial peptide antibodies Human 318 aa, P33765; rat 320 aa P28647 (alternative splicing in rat can yield product with 337 aa); mouse 320 aa, AF069778 Gi

[3H]MRE3008-F20

MRS1220, MRE3008-F20, MRS1191; MRS1523

Cl-IB-MECA

AA3A

Adenosine A3R

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Association with diseases

Knockout phenotype

Gene name= chromosomal location Main physiological function(s)

Expression pattern in nervous system

Acute and chronic pain?, Renal failure, sleep disorders?, epilepsy?, obesity?, brain and cardiac ischemia?

Asthma?

Enhancement of mediator release from mast cells (some species); preconditioning (some species)

Relaxation of smooth muscle in vasculature and intestine; inhibition of monocyte and macrophage function, stimulation of mast-cell mediator release (some species)

Regulation of sensorimotor integration in basal ganglia; inhibition of platelet aggregation and polymorphonuclear leukocytes; vasodilation, protection against ischemic damage, stimulation of sensory nerve activity Anxiety, hypoalgesia, hypertension, increased tolerance to ischemia, altered sensitivity to motor stimulant drugs, decreased platelet aggregation Parkinson’s disease, inflammatory reactions

Bradycardia; inhibition of lipolysis; reduced glomerular filtration; tuberoglomerular feedback, antinociception; reduction of sympathetic and parasympathetic activity; presynaptic inhibition; neuronal hyperpolarization; ischemic preconditioning Anxiety, hyperalgesia, decreased tolerance to hypoxia, loss of tuberoglomerular feedback

Inflammatory reactions, asthma? Cardiac ischemia?

Altered inflammatory reactions, decreased edema, altered release of inflammatory mediators

chr 1p21-13

Low levels: Most of brain (rat, mouse)

Intermediate levels: Cerebellum (human?), hippocampus (human?)

chr 17p11.2-12

Low levels: Adrenal gland, pituitary gland

Intermediate levels: Blood vessels, eye, median eminence, mast cells (human?)

chr 22g11.2

High expression: Striatopallidal GABAergic neurons (in caudate putamen, nucleus accumbens, tuberculum olfactorium), olfactory bulb Low levels: Rest of brain

chr 1q32.1

Intermediate levels: Other brain regions

High expression: Brain (cortex, cerebellum, hippocampus); dorsal horn of spinal cord; eye, adrenal gland

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activate receptors where they are abundant, but not where they are sparse (Fredholm et al., 2001b; Kenakin, 1993, 1995; Svenningsson et al., 1999c). There is much information on the distribution of the A1Rs and A2ARs from several diVerent species, because good pharmacological tools including radioligands (see later discussion) are available. In addition, several studies have used antibodies to localize A1Rs and A2ARs in brain (Hettinger et al., 2001; Rosin et al., 1998; Swanson et al., 1995). In the case of the A2BRs and A3Rs, the data are less impressive. Here, localization determinations tend to rely on the expression of the corresponding messenger RNA (mRNA). Some of this information is summarized in Table I and Fig. 1. A1R mRNA is widespread in the brain, with the highest levels in cell bodies in the hippocampus, cerebellum, and cerebral cortex (Mahan et al., 1991; Reppert et al., 1991). Studies using immunohistochemistry (IHC) and ligand autoradiography have shown a mismatch between A1R protein and the corresponding mRNA in several regions of the CNS ( Johansson et al., 1993a; Swanson et al., 1995). Much of the diVerential distribution can probably be explained by the fact that most A1Rs are present at nerve terminals (Rebola et al., 2003b; TetzlaV et al., 1987). For example, a careful examination of the distribution of A1R mRNA and protein in hippocampus showed that the mRNA is enriched in cell bodies in the granular layer of the dentate gyrus and the pyramidal layers of CA1 and CA3, whereas [3H]DPCPX binding and A1R immunoreactivity is predominantly found in the dentate hilus stratum moleculare, stratum lacunosum, stratum radiatum, and stratum oriens (Swanson et al., 1995). Double immunofluorescence experiments showed that A1R protein co-localizes with SMI-31, which labels axons, but to a lesser extent with mitogen-activated protein (MAP) 2a/b, which labels cell bodies and dendrites, or with synaptophysin, which labels synapses. However, biochemical fractionation and electron microscopic studies with radioligands (which overcome the problem that antibodies cannot gain access to epitopes located in the synaptic cleft) clearly show an enrichment of A1Rs in synapses (Rebola et al., 2003b; TetzlaV et al., 1987), in agreement with the predominant synaptic role of A1Rs (see later discussion). Although mostly found in neurons, A1Rs are located also in other cell types in the brain. In fact, A1Rs are also present in astrocytes (Biber et al., 1997), microglia (Gebicke-Haerter et al., 1996), and oligodendrocytes (Othman et al., 2003). The general distribution of A1Rs is similar between rodents and humans (Fastbom et al., 1987; Schindler et al., 2001; Svenningsson et al., 1997). Initial attempts to localize A1Rs in the living brain using [11C]KF 15372 and [11C]MPDX and positron emission tomography (PET) have been made (Noguchi et al., 1997; Shimada et al., 2002). A2AR mRNA is highly enriched in the striatum (Fink et al., 1992; SchiVmann et al., 1991b; Svenningsson et al., 1997). Lower levels are also found in extrastriatal areas, such as lateral septum, cerebellum, cortex, and hippocampus (Cunha et al., 1995b; Dixon et al., 1996; Svenningsson et al., 1997). Most striatal

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neurons (95%) are GABAergic projection neurons. These neurons can be divided into two major subtypes based on their target areas and neuropeptide contents. One subpopulation projects to the globus pallidus and contains enkephalin. Another subpopulation projects to the substantia nigra pars reticulata/the entopeduncular nucleus and contains substance P and dynorphin. Interestingly, A2ARs are selectively expressed in the enkephalin-containing striatopallidal neurons (Augood and Emson, 1994; Fink et al., 1992; SchiVmann et al., 1991b; Svenningsson et al., 1997). In addition to the GABAergic projection neurons, there are also cholinergic and GABAergic interneurons in the striatum. It is still controversial whether these interneurons contain A2ARs. Studies using in situ hybridization (ISH) have been unable to detect A2AR mRNA in interneurons (Augood and Emson, 1994; SchiVmann et al., 1991b; Svenningsson et al., 1997), but a single-cell PCR study did detect it in cholinergic interneurons (Richardson et al., 2000). Studies using IHC and ligand autoradiography show high levels of A2ARs in all subregions of striatum ( Jarvis and Williams, 1988; Parkinson and Fredholm, 1990; Rosin et al., 1998). In addition, high levels of A2ARs have also been found in the globus pallidus. These receptors are located on nerve terminals from the striatal projection neurons that innervate the globus pallidus (Rosin et al., 1998). Using A2AR-selective antibodies and IHC at the light- and electron-microscopic levels, Rosin et al. (1998) and Hettinger et al. (2001) have shown striatal A2ARs in most neuronal compartments, such as in dendrites, in terminals of axon collaterals, and in soma. A minority of these A2ARs are located presynaptically, particularly in about 50% of the thalamocortical glutamatergic nerve terminals that actually drive the basal ganglia circuitry (Rodrigues et al., 2004). However, the highest levels are found in the postsynaptic density (Rodrigues et al., 2004) and dendritic spines (Hettinger et al., 2001; Rosin et al., 1998) that form asymmetrical synapses. These synapses receive input from glutamatergic terminals and are excitatory. This predominant postsynaptic localization of A2ARs suggests that they may play an important role in the regulation of thalamocortical– striatal synaptic plasticity. Indeed, a functional correlate to this anatomical finding has been demonstrated, namely that N-methyl d-aspartate (NMDA) receptor–dependent long-term potentiation in the nucleus accumbens is significantly attenuated by selective A2AR antagonists and in A2AR knockout mice (d’Alcantara et al., 2001). The high abundance of A2ARs in the basal ganglia does not mean that A2ARs are absent from other brain regions. In fact, A2ARs are also located in astrocytes (Li et al., 2001; Nishizaki et al., 2002), microglia (Kust et al., 1999), and blood vessels throughout the brain (Coney and Marshall, 1998; Shin et al., 2000). A2ARs are also expressed in neurons in the neocortex and the limbic cortex (Lopes et al., 2004; Rebola et al., 2002, 2003c), where they are predominantly present in nerve terminals, albeit with a density 20 times lower than that found in the basal

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ganglia (Lopes et al., 2004). The distribution of A2ARs is similar in rodents and humans (Martinez-Mir et al., 1991; SchiVmann et al., 1991b). However, the levels of extrastriatal A2ARs appear to be higher in humans than in rodents (Svenningsson et al., 1997). Because there is accumulating evidence for a critical role of A2ARs in the pathophysiology of several neurological and psychiatric disorders, most notably Parkinson’s disease and schizophrenia, it will be of great interest to be able to monitor the levels of A2ARs in the living brain using PET. For this purpose, various ligands, including [11C]KW6002, [11C]IS-DMPX, [11C]KF 18446, and [11C]KF 17837, have been developed (Hirani et al., 2001; Ishiwata et al., 2000; Stone-Elander et al., 1997). However, these PET ligands do not appear ideal because nonspecific extrastriatal binding is high. However, it has been shown that SCH 58261 can be used to label receptors in vivo (El Yacoubi et al., 2001d). Biochemical studies have demonstrated low levels of ARs that we would now call A2BRs on most neurons and glial cells (Daly, 1977), and ISH studies specifically have demonstrated the presence of A2BR mRNA in the hypophyseal pars tuberalis (Stehle et al., 1992), though at a considerably lower density than A1Rs and A2ARs. The levels of A3Rs in the brain are also low, but there appear to be species-specific diVerences, with the levels being higher in sheep and humans than in rodents (Linden et al., 1993; Salvatore et al., 1993). The expression of A3Rs in neurons has even been questioned (Rivkees et al., 2000), but both pharmacological (Costenla et al., 2001) and receptor-binding studies (Dı´azHerna´ ndez et al., 2002), as well as immunological and single-cell PCR studies (Lopes et al., 2003b), have demonstrated their presence in nerve terminals of cortical and hippocampal neurons. A3Rs are also expressed in astrocytes (Wittendorp et al., 2004) and microglial cells (Hammarberg et al., 2003). In addition, blood vessels in brain, as elsewhere, contain A2A, A2B, and A3 receptors (Tabrizchi and Bedi, 2001).

B. Pharmacological Tools to Study Adenosine Receptors To be truly useful in receptor classification, agonists and antagonists should diVer in potency by at least two orders of magnitude at diVerent receptors. Few compounds used in classifying ARs fulfill that criterion. Nevertheless, given judicious use of agonists and antagonists at A1, A2A, and A3 receptors, strong conclusions can be drawn from in vitro experiments. Some tools are shown in Table I. The situation is less fortunate in vivo, because many compounds have complicated pharmacokinetics because of very high lipid solubility. In addition, diVerences in potency at the four ARs may be oVset by huge diVerences in receptor abundance. In the case of human, rat, and mouse A1Rs, the full agonist CCPA (and to a somewhat lesser extent CPA and CHA) and the antagonist DPCPX are quite

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useful. A minor problem with DPCPX is that it also interacts with appreciable aYnity with A2BRs, but binding of DPCPX is virtually eliminated in the brain of animals lacking the A1R ( Johansson et al., 2001), showing that actions at brain A1Rs are likely to be the most important when this drug is administered. For the A1R, partial agonists are available as well, including compounds substituted in the C8-position (Roelen et al., 1996) or the ribose 50 substituent (van der Wenden et al., 1998). These compounds show tissue selectivity in vivo, as expected given that partial agonists are much more eYcacious where receptors are abundant and where there are more ‘‘spare receptors.’’ Another interesting class of compounds acting on A1Rs are the so-called allosteric enhancers. The prototype here is PD81,723 (Bruns and Fergus, 1990), which has been shown by various research groups to (allosterically) increase agonist binding and eVect (Baraldi et al., 2003; Figler et al., 2003; Linden, 1997; Soudijn et al., 2002). Such compounds have interesting pharmacological properties. NECA was long considered to be a selective A2R agonist, but this view can no longer be upheld. Instead, NECA must be viewed as a nonselective AR agonist. The related compound CGS 21680 was developed as an A2AR selective agonist (Hutchison et al., 1989), but it is less potent and less selective in humans than in rats (Kull et al., 1999). Another problem with CGS 21680 as a tool is that it binds to sites unrelated to A2ARs (Cunha et al., 1996b; Johansson et al., 1993b; Lindstro¨ m et al., 1996). We have found that this site is dependent on A1Rs but not on A2ARs (Halldner et al., 2004; Lopes et al., 2004). This means that at least in organs or cells with few A2ARs, eVects of CGS 21680 must be viewed with skepticism, unless proper antagonism of CGS 21680 responses by selective A2AR antagonists is shown. There are several useful A2AR antagonists. The most selective so far is SCH 58261. The structurally related ZM 241385 is more readily available (Poucher et al., 1995) but shows appreciable aYnity to human (but not rodent) A2BRs (Ongini et al., 1999). It has been used as a ligand in screening for A2BR selective compounds (Hayallah et al., 2002). There are also important diVerences between these two closely related compounds in their ability to block functional responses (El Yacoubi et al., 2000b). In the case of A2BRs, the most potent agonists have aYnities only marginally below 1 M, and their selectivity is negligible. The situation is somewhat more favorable in the case of antagonists, where some potent and relatively selective antagonists have been found for human A2BRs (Kim et al., 2000). Perhaps the most selective compounds that are useful also in vivo are PSB-50 and PSB-1115 (Abo-Salem et al., 2004; Hayallah et al., 2002); however, their potency and selectivity toward nonhuman A2BRs still needs to be evaluated. In contrast to the other ARs, the A3R is notably insensitive to several xanthines. Hence, most A3R antagonists, such as dihydropyridines, pyridines, and flavonoids, have a non-xanthine structure (Baraldi et al., 2000). One of the

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most selective compounds (for human, but not rat, A3Rs) is MRE-3008-F20, which is also a useful antagonist radioligand at human A3Rs (Varani et al., 2000), whereas MRS1191 and MRS1220 may be used as antagonists for rodent A3Rs (Fredholm et al., 2001a). The chemical class of the A3R antagonists suggests that these drugs may well have several actions unrelated to A3Rs, but the agonist chloro-IB-MECA (but not IB-MECA) appears to be a useful tool. Even with this there are potential problems: Because A1Rs largely outnumber A3Rs in the brain and Cl-IB-MECA can also bind (Lopes et al., 2003a) and activate (Klotz et al., 1998) A1Rs, some of the eVects of Cl-IB-MECA might be mediated by A1Rs. Finally, some allosteric enhancers for A3Rs have been synthesized, but they have not yet been widely used (Gao et al., 2002).

C. Signaling Via Adenosine Receptors The A1Rs and A2Rs were initially subdivided on the basis of their ability to inhibit and stimulate adenylyl cyclase, respectively (Londos et al., 1980; van Calker et al., 1979). Indeed, A1Rs and A2Rs are coupled to members of the Gi group and Gs group of G proteins, respectively (see Table I). Evidence has also been presented that although the A2AR is coupled to Gs in most peripheral tissues, it is coupled to Golf in the striatum (Kull et al., 2000). The A3R can also couple to Gi proteins, although actions mediated by Gq proteins were reported (Abbracchio et al., 1995). The G protein coupling of A2BRs in the brain remains to be resolved, but endogenous A2BRs of HEK 293 cells, human HMC-1 mast cells and canine BR mast cells may be dually coupled to Gs and Gq (Auchampach et al., 1997; Linden et al., 1999). In addition, there is some evidence from transfection experiments that the ARs may signal via other G proteins, but whether such coupling is physiologically important is not known. After activation of the G proteins, enzymes and ion channels are aVected, as can be predicted from what is known about G protein signaling. Thus, A1Rs mediate inhibition of adenylyl cyclase, activation of several types of Kþ channels (probably via ,-subunits), inactivation of N, P, and Q-type Ca2þ channels, activation of phospholipase C, and so on. Activation of A1Rs can dose and time dependently phosphorylate and thereby activate ERK1/2 via ,-subunits released from pertussis toxin–sensitive Gi/o proteins and phosphoinositol-3-kinase (Dickenson et al., 1998; Faure et al., 1994; Schulte and Fredholm, 2000). This list of transducing systems potentially under control of A1R activation illustrates the pleiotropic nature of ARs. Although A1Rs are still assumed to be negatively coupled to adenylyl cyclase, the control by A1Rs of neurotransmitter release appears to be unrelated to the modification of cAMP levels (Cunha, 2001a). Given that many of the steps in the signaling cascade involve signal amplification, it is not surprising that the position of the dose–response curve for agonists will

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depend on which particular eVect is measured (Baker et al., 2000). For instance, the EC50 value for ERK1/2 phosphorylation in transfected CHO cells lies in the nanomolar range, whereas cAMP production is half-maximally activated around 1–5 M of NECA. This emphasizes that G protein–coupled ARs can have substantially diVerent potencies on diVerent signaling pathways in the same cellular system. This pleiotropic capacity to activate diVerent transducing systems is not limited to A1Rs but is also observed for the other ARs. Thus, although A2ARs are assumed to be coupled to Gs (or Golf) proteins and to increase in cAMP levels, several groups have documented the ability of neuronal A2ARs to control neurotransmitter release in a manner independent of cAMP levels and mostly dependent on the control of protein kinase C activity (Cunha and Ribeiro, 2000a,b; Gubitz et al., 1996; Norenberg et al., 1998; Queiroz et al., 2003; Rebola et al., 2003c). The A3R activates ERK1/2 phosphorylation in human fetal astrocytes (Neary et al., 1998) and in microglial cells (Hammarberg et al., 2003). This plethora of transducing systems known to be activated by ARs probably reflects the fact that ARs have multiple roles and subcellular localizations in brain tissue. Thus, it is likely that the diVerent roles fulfilled by ARs in diVerent locations might involve the preferential activation of diVerent transducing systems in each case.

D. Regulation of Receptor Expression and Signaling The diVerent AR subtypes diVer with regard to control of their expression and their rate of desensitization/resensitization (Olah and Stiles, 2000). The A1R gene has at least two promoters and diVerent exons in the 50 -untranslated region that can assemble and give rise to diVerent transcripts (Ren and Stiles, 1995, 1998). The transcription factors involved in the control of CNS expression of A1Rs are largely unknown, unlike their counterparts in the heart (Rivkees et al., 1999). Glucocorticoids (Gerwins and Fredholm, 1991) and thyroid hormones (Fideu et al., 1994) can regulate the expression of A1Rs. Glucocorticoids upregulate A1Rs by acting through multiple regulatory sites, including a serum response element, AP1, and TATA box (Ren and Stiles, 1999). Moreover, adrenalectomy causes a reduction in the expression of A1R mRNA and [3H]DPCPX binding in the brain (Svenningsson and Fredholm, 1997). These eVects are counteracted by replacement treatment with dexamethasone. These results suggest that some types of stress might alter A1R expression. The 50 -untranslated region of the rat A2AR gene also displays two alternative promoters, although it lacks the diversity of exons found in the A1R gene (Chu et al., 1996; Lee et al., 1999). A combined bioinformatics and molecular analysis revealed six additional variants of exon-1 in humans (named h1A, h1B, h1C,

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h1D, h1E, and h1F) and three in mice (m1A, m1B, and m1C) (Yu et al., 2004), all of which encode the 50 -untranslated region. Importantly, these A2AR transcripts with diVerent exon-1 variants displayed tissue-specific expression patterns. For instance, the mouse exon-m1A was detected only in brain (specifically in striatum) and the human exon-h1D mRNA in the lymphoreticular system (Yu et al., 2004). This raises the possibility of generating multiple tissue-specific A2AR mRNA species by alternative promoters with varying regulatory susceptibility. The A2AR expression is sensitive to hypoxia (Kobayashi and Millhorn, 1999), although the mechanisms by which this control is achieved are not fully understood. Cytokines can also upregulate A2ARs (Trincavelli et al., 2002), suggesting that the expression of this receptor may be modified in brain conditions in which neuroinflammation is present. All AR subtypes desensitize upon prolonged exposure to agonists (Olah and Stiles, 2000). Overall, it appears that A3Rs and A2ARs desensitize faster than A1Rs (Cunha, 2001a; Olah and Stiles, 2000). This is in good agreement with the functional stability of A1R-mediated depression of synaptic transmission (Dunwiddie and Masino, 2001; Wetherington and Lambert, 2002). Nonetheless, A1R function is modified on the time scale of hours to days, as illustrated by the opposite eVects of acute and chronic treatment with A1R ligands in in vivo models of ischemia (de Mendonc˛ a et al., 2000; Jacobson et al., 1996). The ability of A2ARs to modulate transmitter release is prone to rapid desensitization (Cunha, 2001a), although it has been pointed out that the motor responses mediated by A2ARs are not modified by long-term activation of A2ARs (Fredholm et al., 2003). Given that there are diVerent molecular elements involved in the control of G protein coupling and eventual sequestration of metabotropic receptors (Krupnick and Benovic, 1998), and given diVerences in the transducing system (see earlier discussion), it is likely that functional desensitization may occur with diVerent time courses in diVerent cell types or subcellular compartments (Wetherington and Lambert, 2002). Activation of other G protein–coupled receptors (GPCRs) may desensitize ARs. The A1R-mediated responses are prone to modulation by several other modulatory systems, such as metabotropic glutamate receptors or muscarinic acetylcholine receptors (Cunha, 2001a). In particular, it has been proposed that both A2ARs (Dixon et al., 1997; Lopes et al., 2002) and A3Rs (Dunwiddie et al., 1997b; Lopes et al., 2003a) can downregulate A1Rs through a protein kinase C– dependent pathway. However, such cross-desensitization might only play a role in fine-tuning adenosine modulation because there are few changes in other ARs when one receptor is genetically deleted. The density of the diVerent ARs is ontogenetically regulated. A1Rs and A2ARs are already present at early developmental time points (Doriat et al., 1996; Johansson et al., 1997; Rivkees, 1995), but the expression, the density, and the eYciency of A1Rs and A2ARs increase at birth and most conspicuously during P5 to P15 (Doriat et al., 1996; Geiger et al., 1984; Johansson et al., 1997;

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Rivkees, 1995). A consistent case arguing for a role of A1Rs in axonal maturation has been raised by Rivkees et al. (2001), and blockade of A1Rs in fetuses may play a key role in preventing periventricular leukomalacia (Turner et al., 2002, 2003). However, under nonpathological conditions, it seems that the eYciency of the A1 ˚ de´ n et al., 2001; Dumas and neuromodulatory system is limited in the newborn (A Foster, 1998). The fact that ARs are immature at birth should be kept in mind when considering the use of cultured cells from the CNS as experimental models to study purinergic modulation (Nicolas et al., 1994), because these preparations are obtained from embryos or newborns. In fact, we have noted that cultured neurons from the rat hippocampus and cerebral cortex are endowed with A1, A2A, and A3 receptors, but the relative densities and the subcellular location of these receptors appear diVerent from those found in acutely dissociated preparations from mature animals (N. Rebola and R. A. Cunha, unpublished observations). As is detailed later in this chapter, some of the conditions in which manipulation of the adenosine neuromodulatory system has therapeutic potential (Parkinson’s disease, epilepsy, or neuroprotection) are of particular relevance in the elderly. Thus, it is important to consider whether ARs are modified in elderly individuals. It has consistently been observed that A1R density decreases in aged animals (Cunha et al., 1995a, 2001b; Pagonopoulou and Angelatou, 1992; Sebastia˜ o et al., 2000a; Sperla´ gh et al., 1997). Despite the decreased density, there seems to be a greater tonic activation of A1Rs (Sebastia˜ o et al., 2000a) because of modified extracellular metabolism of adenosine (Cunha et al., 2001a). In the striatum of aged animals, there is a nearly 20–30% reduction in the expression (SchiVmann and Vanderhaeghen, 1993b) and density of A2ARs (Cunha et al., 1995a; Olsson and Pearson, 1990; Popoli et al., 1998a), but the A2AR-mediated control of motor function is essentially preserved (Popoli et al., 1998b). This could be due to the even larger reduction in dopaminergic D2 receptor (D2R) density (Olsson and Pearson, 1990; Popoli et al., 1998a). In contrast, there is a marked increase in the density, G protein coupling, and functional role of A2ARs in the limbic cortex of aged animals (Cunha et al., 1995a; Lopes et al., 1999a; Rebola et al., 2003c). This observation is particularly interesting in light of the relation between caVeine consumption and lower incidence of Parkinson’s disease (Ascherio et al., 2001; Ross et al., 2000; Schwarzschild et al., 2002) and Alzheimer’s disease (Maia and de Mendonc˛ a, 2002) that is paralleled by the protective eVects of A2AR antagonists against neurotoxicity caused by MPTP (Chen et al., 2001b; Ikeda et al., 2002) and -amyloid peptide (Dall’lgna et al., 2003). Also, the opposite changes in the densities of inhibitory A1 and facilitatory A2ARs in the neocortex and limbic cortex of aged animals have led to the proposal (Rebola et al., 2003c) that the adenosine neuromodulation system may be re-set on aging to compensate the general loss of synaptic eYciency found in the elderly (Barnes, 1994).

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IV. Functions of Adenosine Receptors

A. Regulation of Nerve Activity The most widely recognized eVect of adenosine on nerve activity is the inhibition of neurotransmitter release and neuronal excitability and involves the activation of A1Rs (Dunwiddie, 1985; Dunwiddie and Masino, 2001; Fredholm and Dunwiddie, 1988; Phillis and Wu, 1981). A1Rs are more eVective in depressing excitatory than inhibitory transmission in the CNS (see Cunha [2001a] for references to works showing an A1R-mediated modulation of GABA release in some CNS areas). This inhibition of excitatory transmission largely depends on the activation of presynaptic A1Rs (Proctor and Dunwiddie, 1987; Thompson et al., 1992) that inhibit the release of glutamate (Ambro´ sio et al., 1997; Barrie and Nicholls, 1993; Fastbom and Fredholm, 1985). A1Rs are also located postsynaptically in distal dendrites (TetzlaV et al., 1987) and in the postsynaptic density (Rebola et al., 2003b) where they control NMDA receptor function (de Mendonc˛ a et al., 1995; Klishin et al., 1995) and voltagesensitive calcium channels (Klishin et al., 1995; Mogul et al., 1993). This ability of adenosine to inhibit via A1R activation the main molecular entities involved in signal integration at the dendritic level is probably related to the ability of adenosine to control synaptic plasticity phenomena (de Mendonc˛ a and Ribeiro, 1997). In more proximal dendrites and in the cell body, activation of A1Rs mainly controls potassium conductances leading to a membrane hyperpolarization (Greene and Haas, 1991). This postsynaptic eVect of adenosine acting via A1R activation is not of primary importance to control synaptic transmission (Lu¨ scher et al., 1997) but appears to be critically involved in controlling burst-like activity in CNS neurons (Dragunow, 1988; Dunwiddie, 1999). In fact, adenosine is particularly eVective in controlling after-discharge hyperpolarization, an eVect that has been proposed to be the basis for the anticonvulsant eVect of adenosine (Dragunow, 1988; Dunwiddie, 1999), as is detailed later. In contrast to the abundant literature focusing on the impact of A1Rs on nerve activity, little is known about the less abundant ARs. A2ARs have been proposed to modulate NMDA receptor function in the striatum (Nash and Brotchie, 2000; Norenberg et al., 1998). Also, a role for A2Rs has been proposed in the control of nerve conduction through modulation of voltage-sensitive sodium channels (Lobo and Ribeiro, 1992), an issue that certainly deserves further attention in view of the potential usefulness of A2AR antagonists as antiepileptics (El Yacoubi et al., 2001c). Some of the proposed actions are illustrated in Fig. 2.

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Fig. 2. Some eVects of adenosine in the synaptic cleft. Extracellular adenosine can be formed from released adenosine triphosphate (ATP) that is extracellularly metabolized by the ectonucleotidase pathway (ecto–adenosine triphosphatase [ATPase] and=or ecto-ATP diphosphohydrolase, NTDPase, and ecto-50 -nucleotidase, 50 -N), as well as from the release of adenosine as such through bidirectional adenosine transporters (T). One important eVect of adenosine in the central nervous system is its ability to control neurotransmitter release. This is accomplished by activation of either inhibitory A1 receptors or facilitatory A2A receptors that might control neurotransmitter release through control of voltage-sensitive calcium channels (VSCCs). For further details see text.

B. Regulation of Transmitter Release Clearly, the main way in which adenosine controls nerve function in physiological situations and at low-frequency stimulation appears to be through control of release of neurotransmitters (Cunha, 2001a; Dunwiddie and Masino, 2001; Fredholm and Dunwiddie, 1988), including peptides (Carruthers et al., 2001; Mauborgne et al., 2002). The most widely recognized eVect of adenosine is its ability to inhibit the release of neurotransmitters through A1R activation. The mechanisms

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by which A1Rs control the release of neurotransmitters are still unclear. Two main hypotheses have been pursued: (1) inhibition of calcium entry through inhibition mainly of N-type voltage-sensitive calcium channels (Ribeiro, 1995) and (2) decrease of the aYnity of the release apparatus for calcium (Silinsky et al., 1999). However, as first noted in 1995 by Ribeiro, it appears that adenosine might inhibit the spontaneous and the evoked release of neurotransmitters diVerently. Most of the experiments addressing the molecular mechanisms by which A1Rs control neurotransmitter release in the CNS studied spontaneous rather than evoked release of neurotransmitters. Indeed, A1Rs may use several ways to inhibit transmitter release, and the importance of the diVerent mechanisms probably depends on the way transmitter release was evoked (Fredholm and Dunwiddie, 1988). Besides inhibition via A1Rs, facilitation via A2Rs has been described. The A2AR-mediated facilitation of neurotransmitter release normally displays small amplitude (Cunha, 2001a). In many regions the A2AR-mediated facilitation is seen only if A1Rs are present (Lopes et al., 2002), but A2ARs also facilitate the release of neurotransmitters independently of A1Rs, as best exemplified by their ability to control the evoked release of GABA (Brooke et al., 2004; Cunha and Ribeiro, 2000a; Gubitz et al., 1996), which is mostly A1R-insensitive (Cunha, 2001a). The mechanism by which A2ARs facilitate the evoked release of neurotransmitters is mostly unknown but may involve cAMP (Gubitz et al., 1996; Kirk and Richardson, 1995; Mori et al., 1996; Rebola et al., 2002, 2003c) as well as protein kinase C (Cunha and Ribeiro, 2000a,b; Gubitz et al., 1996; Kirk and Richardson, 1995; Lopes et al., 2002). In conclusion, the adenosine-mediated control of neurotransmitter release appears to result from a balanced activation of inhibitory A1Rs and facilitatory A2ARs, an idea that has been experimentally confirmed in diVerent brain areas and in relation to diVerent neurotransmitters including glutamate, acetylcholine, and serotonin (Cunha, 2001a). As discussed previously in detail (Cunha, 2001a), it is likely that the two receptor subtypes might be activated diVerentially according to the source (Cunha et al., 1996a) and to the amounts (Correia-de-Sa and Ribeiro, 1996; Correia-de-Sa et al., 1996; Cunha et al., 1996c; Jin and Fredholm, 1997) of extracellular adenosine formed (see Fig. 2 for a schematic representation).

C. Other Functions The study of adenosine neuromodulation has mostly been restricted to studying the direct eVects of adenosine on nerve activity and neurotransmitter release. This has left mostly unexplored other potential functions mediated by adenosine in the CNS such as controlling the rate of metabolism of neurons and astrocytes (Ha˚ berg et al., 2000; Hammer et al., 2001), axonal growth (Rivkees et al., 2001), or axonal guidance (Corset et al., 2000; Stein et al., 2001), which are

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probably part of the more general role as trophic factors that has been ascribed to purines (Rathbone et al., 1999). Even with respect to the control of the extracellular levels of neurotransmitters, studies have documented the possibility that A2ARs may indirectly control the levels of extracellular glutamate by controlling the function of glutamate transporters in glial cells (Li et al., 2001; Nishizaki et al., 2002). Astrocytes are endowed with all the known subtypes of ARs that control astrogliosis and the release of neuroactive substances (Ciccarelli et al., 2001). In fact, the proliferation of astrocytes is stimulated by A2Rs (Hindley et al., 1994) and apparently by A3Rs (Abbracchio et al., 1998), whereas A1Rs inhibit reactive astrogliosis (Ciccarelli et al., 1994). Furthermore, A2Rs can stimulate the release of interleukin-6 (IL-6) (Fiebich et al., 1996a), whereas A1Rs trigger the release of nerve growth factor and of S100- (Ciccarelli et al., 1999). Given the promising therapeutic impact of A2AR activation in the control of inflammatory reactions (Ohta and Sitkovsky, 2001), there is renewed interest in the potential impact of ARs on the control of microglia function. Microglial cells express A1, A2A, and A3, but not A2BRs (Fiebich et al., 1996a). Initial studies revealed that A1Rs and A2ARs cooperated in controlling calcium transients (Ogata et al., 1996) and proliferation (Gebicke-Haerter et al., 1996) in cultured microglial cells. Activation of A2ARs has also been reported to activate cyclooxygenase-2 (Fiebich et al., 1996a), trigger nerve growth factor expression (Heese et al., 1997), and regulate Kþ channel expression (Kust et al., 1999). However, both in macrophages and in dendritic cells, the ARs play diVerent roles in the control of the release of cytokines in resting and activated cells (Hasko et al., 2000). This aspect, which may be of critical importance to understand the role of adenosine in neurodegenerative diseases and in ischemic episodes, has so far not been investigated in microglia or in infiltrating lymphoid cells. Finally, another potential role of adenosine that may also aVect neuronal function is the known ability of adenosine to control vascular resistance (Olsson and Pearson, 1990). This has been observed to occur also in CNS vessels through A2AR activation (Coney and Marshall, 1998; Shin et al., 2000), but the relevance of this modulation has not yet been explored in pathological situations.

D. Interaction with Other Transmitter Systems The neuromodulation exerted by the adenosinergic system probably exceeds the simple control of the release of neurotransmitter and should more adequately be viewed as a modulatory system able to control the responsiveness of nerve terminals to diVerent signaling molecules. The concept of the adenosine system as a modulator of modulators (Sebastia˜ o and Ribeiro, 2000) highlights the potential of adenosine to fine-tune synaptic activity. It was first noted at the neuromuscular junction that A2ARs played a permissive role for the modulatory roles of peptides

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such as CGRP (Correia-de-Sa and Ribeiro, 1994). This notion has been extended to the CNS with the observations that the modulatory eVects of peptides such as calcitonin gene–related peptide (CGRP) (Sebastia˜ o et al., 2000b) and brainderived neurotrophic factor (BDNF) (Dio´ genes et al., 2004) in hippocampal preparations are strictly dependent on the tonic activation of A2ARs. The mechanisms of this permissive eVect are not yet understood. An interesting observation is that TrkA receptors in PC12 cells and TrkB receptors in hippocampal neurons are activated after treatment with adenosine in the absence of neurotrophins (Lee and Chao, 2001; Rajagopal et al., 2004). This transactivation by adenosine involves A2ARs and can be inhibited by the Src family–specific inhibitor PP1 or by K252a, an inhibitor of Trk receptors. Interestingly, the A2A-mediated transactivation of Trk receptors appears to occur on intracellular membranes (Rajagopal et al., 2004). Another aspect of interactions of ARs with other receptor systems is the possibility of the formation of homo-oligomers of A1Rs (Ciruela et al., 1997) or A2ARs (Dio´ genes et al., 2004) or hetero-oligomers involving ARs (see the next section). This has been demonstrated for A1R/P2Y1R dimers in heterologously expressed systems and in the hippocampal formation (Yoshioka et al., 2001, 2002), as well as for A1R/metabotropic glutamate receptors type 1 (mGluR1) (Ciruela et al., 2001) and A2AR/mGluR5 (Ferre´ et al., 2002), apart from A1R–D1R and A2AR–D2R interactions, which are dealt with in the next section. This possible hetero-dimerization of ARs with receptors for diVerent ligands may shed light on some of the atypical pharmacological profiles that have been reported (Cunha and Ribeiro, 2000a; Cunha et al., 1996b) and introduces the idea of coincidence detection to the field of neuromodulation (Angers et al., 2002). Several other examples of interaction between transmitter systems could be listed. However, rather than doing that, we concentrate on presenting in some detail the interactions between adenosine and dopamine.

V. Adenosine–Dopamine Interactions in Brain

A. General Considerations ARs (A1Rs and A2ARs in particular) are expressed at moderate to high levels in the brain areas enriched with dopaminergic innervation, thus providing an anatomical basis for interaction between these neurotransmitter systems. In as early as 1976, evidence for interaction between adenosine and dopamine receptors began to surface (Fredholm et al., 1976). With molecular cloning of multiple dopamine receptors (DRs) and ARs during the 1990s, significant progress was made toward our understanding of specific interactions between

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subtypes of DRs (D1-like and D2-like) (Bunzow et al., 1988; Missale et al., 1998) and ARs (A1, A2A) in brain (Fredholm et al., 1994a; SchiVmann and Vanderhaeghen, 1993a). Behavioral and neurochemical studies provided strong evidence for an antagonistic interaction between ARs and DRs and strongly suggest a specific and antagonistic interaction between A2ARs and D2Rs and possibly A1Rs and D1Rs in striatum (Ferre´ et al., 1997; Morelli and Pinna, 2001; Ongini and Fredholm, 1996; Svenningsson et al., 1999b). These results have been reviewed (Ferre´ et al., 1997; Moreau and Huber, 1999; Morelli and Pinna, 2001; Ongini and Fredholm, 1996; Ribeiro et al., 2002; Sebastia˜ o and Ribeiro, 2000; Svenningsson et al., 1999a). Perhaps because of the lack of specific pharmacological tools to study these receptors, no evidence for specific interaction between A2B and A3 and dopamine receptors has yet been obtained. We focus on studies during the past 5 years, paying particular attention to three conceptual aspects: (1) heterodimerization of ARs and DRs as a molecular basis for direct (intramembrane) receptor–receptor interaction; (2) endogenous adenosine acting on A2ARs, exerting an excitatory tone on striatal neurons via D2R-independent mechanisms; and (3) DARPP-32 as a potential molecular target for integrating adenosine and dopamine signaling at the cellular and network levels.

B. Heterodimerization of Adenosine–Dopamine Receptors as a Molecular Basis for Direct Receptor–Receptor Interaction in the Striatum For the last 3–5 years, evidence has mounted in support of dimerization of GPCRs as a common molecular mechanism for cross-talk among various G protein signaling pathways (Devi and Brady, 2000). Heteromeric dimerization of GPCRs has been demonstrated for many important neurotransmitter receptors, such as dopamine D1/D5 receptors and GABAA receptors (Liu et al., 2000) and dopamine D2 and somatostatin SSTR5 receptors (Rocheville et al., 2000). For purinergic receptors, a study reported heteromeric association of A1R with P2Y1 receptor, leading to an A1R with P2Y1-like receptor pharmacology (Yoshioka et al., 2002), as well as for A1R/metabotropic glutamate receptors type 1 (mGluR1) (Ciruela et al., 2001) and A2AR/mGluR5 (Ferre´ et al., 2002). Direct receptor–receptor interaction between A2ARs and D2Rs was proposed by Ferre´ et al., in 1991 and is widely accepted as a possible mechanism for many neurochemical and behavioral interactions between the two systems (Ferre´ et al., 1997, 1998; Fuxe et al., 2001; Pinna et al., 2001; Svenningsson et al., 1999b). The A2ARs and D2Rs are highly co-localized in striatopallidal neurons (Fink et al., 1992; SchiVmann and Vanderhaeghen, 1993a). In contrast, A1Rs and D1Rs are expressed at a relatively high level in striatonigral neurons (Gerfen et al., 1990; Rivkees

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et al., 1995), but A1Rs are equally abundant in striatopallidal neurons (Ferre´ et al., 1996). At the electron-microscopic level, both A2ARs and D2Rs have been shown to locate mostly on the dendritic spines of the striatopallidal GABA neurons (Hersch et al., 1995; Hettinger et al., 2001; Yung et al., 1995), providing an anatomical basis for receptor–receptor interactions at the cellular level. The intramembrane interaction between A2ARs and D2Rs was proposed by Ferre´ et al., in 1991, based on the finding that activation of A2ARs reduces the binding aYnity of D2R agonists to their receptor in striatal membrane preparations from rats. Later studies with co-immunoprecipitation and confocal microscopic analysis provide further evidence supporting the direct receptor–receptor interaction for adenosinergic and dopaminergic systems. For example, in mouse fibroblast Ltk cells co-transfected with D1Rs and A1Rs, heteromeric A1 and D1 receptor complexes immunoprecipitate intact but are disrupted by pretreatment with D1R agonists (Gine´ s et al., 2000). Activation of A1Rs resulted in clustering (coaggregation) of A1Rs and D1Rs. Heteromeric receptor complexes of human D2Rs (long form) and A2ARs were demonstrated by co-immunoprecipitation and by fluorescence resonance energy transfer (FRET) in co-transfected SHSY5Y neuroblastoma cells and mouse fibroblast Ltk cells (Canals et al., 2003; Hillion et al., 2002). Upon A2AR or D2R agonist treatment, the A2A–D2 heteromeric receptor complex undergoes co-aggregation, co-internalization, and co-desensitization of both A2ARs and D2Rs. The intramembrane antagonistic receptor–receptor interactions between A2ARs and D2Rs are apparently more evident in ventral than dorsal striatum (Ferre´ , 1997).

C. Endogenous Adenosine Acting on A2A Receptors Can Also Exert Excitatory Tone on Striatal Neurons by D2 Receptor–Independent Mechanisms A series of pharmacological studies using depletion of dopamine or blockade of D2Rs suggest that A2AR-mediated eVects do not necessarily depend on the functional integrity of dopaminergic systems. In fact, the A2AR-mediated stimulatory eVect is manifested best when dopaminergic tone is removed. For example, Svenningsson et al. (1999a) showed that acute profound depletion of dopamine resulted in marked induction of c-fos mRNA in the striatum, which was antagonized by either D2 agonists or A2A antagonists. This study provides compelling evidence indicating that this A2AR-mediated stimulatory eVect on c-fos expression is normally masked by a D2-mediated inhibitory tone. Such results may be best explained by an opposing independent A2A and D2R modulation of cellular responses, that is, A2AR activation by endogenous adenosine may exert an excitatory influence on striatopallidal neurons, independent of D2Rs (Svenningsson et al., 1999a).

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The dopamine-independent action of the A2AR received further experimental support from studies in D2R knockout mice when several groups demonstrated that A2AR agonists and antagonists produced behavioral and neurochemical responses in the absence of D2Rs. For example, A2AR antagonists (KW6002, CSC, and caVeine) and A2A agonists stimulate and depress motor activity, respectively, in the absence of D2Rs (Aoyama et al., 2000; Chen et al., 2001a). At the cellular level, inactivation of A2ARs does not aVect basal enkephalin mRNA expression but reverses the D2R knockout-induced enkephalin mRNA expression in A2AR–D2R double knockout mice, suggesting that the stimulatory eVect of the A2AR is manifest best when D2R-mediated inhibitory tone is removed (as in Parkinson’s disease). In agreement with these findings, caVeine and CSC increase locomotor activity and induce c-fos expression in the cortex in mutant mice completely deficient in dopamine (Kim and Palmiter, 2003). However, it should be noted that CGS 21680–induced GABA release is blunted in D2R knockout mice, and A2AR antagonist–induced motor stimulation is reduced when comparing knockout mice with wild-type mice (Zahniser et al., 2000), suggesting that A2AR signaling may be downregulated to compensate for lifelong D2R deficiency. Nonetheless, these studies with mutant mice deficient in D2Rs or dopamine argue that striatal A2ARs exert their neural function partly or entirely independent of D2Rs. Thus, endogenous adenosine may act at A2ARs not only as an inhibitory modulator of dopaminergic neurotransmission (as proposed by the A2AR–D2R direct interaction model) but also as a tonic excitatory modulator of striatopallidal neurons (opposing D2R function through its independent cellular actions) (Chen et al., 2001a; Svenningsson et al., 1999a). Moreover, such tonic stimulation of A2ARs is essential for normal striatal function, such as neuroadaptation underlying striatal plasticity in response to various neural stimuli. Indeed, a tonic excitatory eVect of the A2AR is required for the expression of immediate early genes (Svenningsson et al., 1999a) and neuropeptides (Chen et al., 2001a), as well as phosphorylation of the dopamine- and cAMP-regulated phosphoprotein of 32-kd (DARPP-32) in striatum (Svenningsson et al., 2000b).

D. DARPP-32 as a Potential Molecular Target for Integrating Adenosine and Dopamine Signaling at the Cellular and Network Levels in the Striatum DARPP-32 is expressed in all medium-sized spiny neurons, in both the direct and the indirect pathway. Stimulation of D1Rs or A2ARs or blockade of D2Rs increases DARPP-32 phosphorylation in the distinct cell populations of the striatum, as indicated by the additivity of DARPP-32 phosphorylation (Svenningsson et al., 1998). Blockade of A2ARs or stimulation of D2Rs not only abolishes A2A agonist– or D2R antagonist–induced DARPP-32 phosphorylation

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but also antagonizes the D1R agonist–induced DARPP-32 phosphorylation in striatum (Svenningsson et al., 2000a). This interaction is blocked in the presence of TTX, suggesting trans-synaptic (network) cross-talk by A2ARs and D1Rs (Lindskog et al., 1999). Thus, DARPP-32 may be an important integration site for cross-talk between A2AR- and D1R-containing striatal neurons. This integration at DARPP-32 by two distinct pathways provides a possible molecular explanation for the long-known behavioral interaction between A2ARs and D1Rs. For example, the A2AR antagonist SCH 58261 markedly potentiates rotational behavior (Morelli et al., 1994) and c-fos expression (Pollack and Fink, 1996) induced by the D1R agonist SKF81297. At the systemic level, Lindskog et al. (2002) showed that caVeine-induced motor activity is greatly reduced in DARPP-32 knockout mice or mice treated with the selective A2AR antagonist SCH 58261, indicating that DARPP-32 is required for persistent motor stimulation by caVeine and SCH 58261. In addition to reducing DARPP-32 phosphorylation at the Thr34 site by blocking A2ARs (Svenningsson et al., 2000a), caVeine treatment increases phosphorylation at the Thr75 site of DARPP-32 via an inhibitory feedback loop of protein kinase A (PKA), leading to further reduction of PKA activity through feedback inhibition (Bibb et al., 1999; Lindskog et al., 2002; Nishi et al., 2000). Thus, DARPP-32 appears to be an important molecular target at which adenosine and dopamine signaling can be integrated by regulation of phosphorylation at Thr34, which converts it into a powerful phosphatase inhibitor, and by regulation of phosphorylation at Thr75, which inhibits PKA.

VI. Phenotypes of Knockout Mice

The current availability of knockout mice for three subtypes of ARs, namely A1, A2A, and A3 receptors, should enable further clarification of their functions and their potential as drug targets. DiVerent features of the phenotypes could also provide clues to the roles of defects in AR genes in human disease. A1Rs are abundantly expressed in the brain, especially at the terminals of excitatory nerve endings (see Section III). The presence of high densities of A1Rs in brain areas involved in multiple functions, such as hippocampus, cerebellum, and cerebral cortex, suggests that the phenotype of A1 knockout mice might diVer from that of wild-type mice. Johansson et al. (2001) have characterized A1R knockout mice, bred on a 129/C57BL background. As expected, the hypothermia elicited by A1R agonists was absent in A1R knockout mice. Behavioral tests to evaluate sensorimotor reflexes revealed no diVerences between A1R knockout and A1R wild-type mice; similarly, no diVerences were seen for total locomotor activity over a 24-hour period. Interestingly, anxiety-related behavior in the

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classic light–dark box test was increased in the A1R knockout mice, as shown by a reduction in the number of entries into as well as the total time spent in the lit compartment compared with A1R wild-type mice. This being the case, might the increased sensitivity to caVeine reported in patients with panic disorders (Boulenger et al., 1984) be linked to a disorder of adenosine neuromodulation at A1Rs in brain? The role of adenosine as an endogenous analgesic substance has also been evaluated (Johansson et al., 2001). A1Rs are abundant in mouse spinal cord, with the highest levels in the outer lamina of the dorsal horns, where the density of receptors was close to that observed in the hippocampus. A1Rs were responsible for the analgesic eVects of intrathecally administered A1 agonist. The A1R knockout mice reacted faster to thermal pain than A1R wild-type mice. However, this increase was not matched by an increased sensitivity to mechanical stimulation. It was suggested that endogenous adenosine acting at A1Rs decreases nociception mediated via C fibers. These results also suggest that the A1R may be a target for the development of antinociceptive drugs. As noted earlier in this chapter, adenosine is generally believed to protect tissues against negative consequences of hypoxia and ischemia. Hence, the survival of adult animals after a hypoxic challenge may be reduced if A1Rs are absent or blocked ( Johansson et al., 2001). However, the opposite is observed in newborns, where A1R activation appears to play a detrimental role in neuronal survival (Turner et al., 2004). Thus, the loss of white matter, which is a typical consequence of hypoxia in the newborn, appears to be mediated by adenosine acting on A1Rs (Turner et al., 2003). Thus, blockade of ARs, even incomplete blockade like that achieved by caVeine, reduces such white matter loss (Turner et al., 2003). In fact, the consequences of prenatal hypoxic ischemia in rats are actually reduced if the dams have been given caVeine (Bona et al., 1995). Additional results were reported by Gimenez-Llort et al. (2002) from a series of paradigms selected to assess the relevance of A1Rs in several behavioral functions. Again, no diVerences in overall spontaneous motor activity were detected over a 23-hour period, but activity was reduced in some parts of the light–dark cycle. These results would go well together with the eVect of moderate doses of caVeine promoting wakefulness and disrupting normal sleep and with the fact that A1Rs are likely to be involved in regulating the sleep–wake rhythms in mice (Sigworth and Rea, 2003). The A1R knockout mice showed a decrease in exploratory behavior in the open field and in the hole board, results that could reflect an anxiogenic state in A1R knockout mice. Accordingly, increased anxiety was noticed in the elevated plus maze and in the light–dark box tests. However, another strain of A1R knockout mice with a similar genetic background displayed a normal overall level of motor activity, with very modest behavioral changes in the direction of increased anxiety (Lang et al., 2003).

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DiVerent environmental conditions likely have contributed substantially to the behavioral discrepancies between the two lines. Several studies have suggested AR involvement in the modulation of aggressive behavior. In agreement with the decrease of oVensive behavior induced by a selective stimulation of A1Rs (Navarro et al., 2000), an enhanced aggressive behavior was observed in A1R knockout isolated mice in the resident–intruder aggression test ( Johansson et al., 2001). In Morris water-maze tests, no diVerences were found in spatial reference and working memory, suggesting that endogenous adenosine would not mediate working memory processes (Gime´ nez-Llort et al., 2002). Intact spatial cognition in the water maze, together with mildly altered emotional reactions to the watermaze environment, was reported by Lang et al. (2003). This is in clear contrast to several studies showing that locally administered selective A1R agonists and antagonists modify diVerent forms of learning and memory (Corodimas and Tomita, 2001; Kopf et al., 1999; Pereira et al., 2002; Pitsikas and Borsini, 1997). This clearly indicates that adaptive changes in the A1R knockout mice must overcome the adenosine control of mnemonic functions. Interestingly, A1R knockout mice had reduced survival rate as compared to A1R wild-type mice (Gime´ nez-Llort et al., 2002). The reduced life span may be linked to a progress of disturbances in cardiovascular, hepatic, and renal systems, in which A1Rs are likely to play an important role in the normal physiology. Two lines of A2AR knockout mice are also available. In the line of Ledent et al. (1997), A2AR knockout mice were in a CD1 outbred background, whereas in the line of Chen et al. (1999), mice were bred onto a C57BL/6 background. Both lines of A2AR knockout mice are viable and breed normally. Blood pressure and heart rate are increased, as well as platelet aggregation (Ledent et al., 1997). Given the distribution of A2ARs in the CNS, particular attention has been paid to the potential roles of A2ARs in brain function. A2ARs are highly expressed in the dorsal and ventral striatum, where they could be involved in the physiological control of motor activity. In most studies performed so far (Berrendero et al., 2003; Chen et al., 1999, 2000; Ledent et al., 1997), the exploratory behavior of A2AR knockout mice was reduced as compared to wild-type mice. However, this reduction of locomotor activity is not an invariable characteristic of A2AR knockout mice because A˚ de´ n et al. (2003) found a small increase in basal locomotor activity at 4 weeks of age in the A2AR knockout mice compared with A2AR wild-type mice. It should be emphasized that a major physiological role of A2AR stimulation is to modulate locomotor activity. As expected, treatment with the A2A agonist CGS 21680 strongly reduces locomotor activity in A2AR wildtype mice and has no significant eVect on A2AR knockout mice (Chen et al., 1999; Ledent et al., 1997). The only known biochemical eVect of caVeine in the brain in concentrations relevant to daily intake of coVee is blockade of A1Rs and A2ARs (Fredholm et al., 1999), the latter receptors being more sensitive to low

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doses of caVeine than the former ones. Because caVeine is extensively used in humans, an examination of its eVects provides another means of assessing the roles of A1Rs and A2ARs. Indeed, studies of caVeine eVects in AR knockout mice support the predictions. CaVeine has a mild stimulant eVect in A2AR wild-type mice and is a strong depressant of locomotor activity in A2AR knockout mice (Ledent et al., 1997). Thus, A2ARs appear strongly implicated in the stimulant eVect of caVeine. In fact, caVeine dose dependently decreases locomotion in A2AR knockout mice over a large range of doses (El Yacoubi et al., 2000a). This eVect probably results from the other biological eVects of caVeine, with the blockade of A1Rs being a candidate. However, the role of A1Rs in the eVects of caVeine on motor activity is less clear. Recently, Halldner et al. (2004) showed that the A1R is not required for the stimulatory eVect of caVeine, which, however, is facilitated in A1R knockout mice. The results also suggest that the inhibitory eVects of higher doses of caVeine are not due to blockade of the A1R, but that it is likely an eVect independent of AR. A2AR knockout mice revealed higher spontaneous anxiety-like responses in two diVerent anxiety-like behavioral tests, the elevated plus maze and the light– dark box (Berrendero et al., 2003; El Yacoubi et al., 2000c; Ledent et al., 1997). Thus, A2AR knockout mice and one strain of A1R knockout mice exhibit increased anxiety consistent with the well-known pronounced anxiogenic eVects of high doses of caVeine, which will presumably block most of both AR subtypes, but low doses do not. Despite several studies using pharmacological tools performed with rodent models (El Yacoubi et al., 2000c; Florio et al., 1998; Imaizumi et al., 1994; Jain et al., 1995), there is no clear consensus concerning the role of A1Rs and A2ARs in anxiety. However, it has been proposed that A1R agonists display anxiolytic eVects in screening tests, whereas in some cases, but not consistently, A1R antagonists may display anxiogenic eVects. On the other hand, whether the A2AR also plays a major role in anxiety states is not yet clear. Selective A2AR antagonists seem to be devoid of eVects in rodent tests (El Yacoubi et al., 2000c). However, human data have shed fresh light on the potential role of A2ARs in the anxiogenic eVects of caVeine. In a study conducted by Alsene et al. (2003), the association between variations in anxiogenic responses to caVeine and polymorphisms in the A1R and A2AR genes was examined. A significant association was found between self-reported anxiety after oral administration of 150 mg of caVeine and two linked polymorphisms at positions 1976 and 2592 on the A2AR gene. An enhanced aggressive behavior was observed in isolated male A2AR knockout mice using the resident-intruder test (Ledent et al., 1997). The increased aggressiveness observed in both A1R knockout mice and A2AR knockout mice is in agreement with the increase of oVensive behavior induced by selective blockade of either A1Rs or A2ARs (M. El Yacoubi and J.-M. Vaugeois, unpublished observations). These results suggest that both AR subtypes are involved in the eVect

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of adenosine on aggressiveness. The link between these eVects and the increase in nervousness and irritability reported in humans (Fredholm et al., 1999) after chronic administration of high doses of caVeine remains a matter of speculation. A2ARs, like A1Rs, appear to modulate pain. The response of A2AR knockout mice to acute pain stimuli was slower in the hot plate and tail-flick tests compared with A2AR wild-type mice (Ledent et al., 1997). Similar reduced pain responses were also found when a tail-immersion test was used (Berrendero et al., 2003). This higher nociceptive threshold suggests that the peripheral lack of A2AR predominates over the spinal defect. Thus, depending on the site of action and the receptor activated (A1 or A2A), adenosine may exert very diVerent eVects on pain. This variety of eVects may explain why caVeine has analgesic eVects against some, but not all, types of pain (Fredholm et al., 1999). Among new therapeutic approaches to Parkinson’s disease, the modulation of dopamine-mediated striatal functions through the blockade of A2ARs is being investigated (see later discussion). Drugs that aVect Parkinson’s disease also aVect drug-induced catalepsy, a state in which animals remain immobile for long periods in awkward postures that are imposed on them. Catalepsy, assessed using the elevated bar test, was reduced, as compared with A2AR wild-type mice, in A2AR knockout mice subjected to acute administration of dopamine D1R and D2R antagonists or acetylcholine muscarinic receptor agonists (El Yacoubi et al., 2001b). These results suggest that A2ARs influence not only dopamine D2Rs- and D1Rs-mediated eVects but also acetylcholine muscarinic receptor–mediated eVects. Interestingly, caVeine and muscarinic receptor antagonists act in synergy to inhibit haloperidol-induced catalepsy (Moo-Puc et al., 2003). The results on catalepsy show that deletion of the A2AR reduces the dysfunction of basal ganglia motor circuitry caused by drugs acting at dopamine and acetylcholine receptors. They confirm that selective A2AR antagonists might be eVective therapies for Parkinson’s disease. In behavioral procedures used to screen potential antidepressants, such as tail suspension and forced swim tests, A2AR knockout mice were found to be less sensitive to ‘‘depressant’’ challenges than their wild-type litter mates, being less immobile than A2AR wild-type mice on both tests (El Yacoubi et al., 2001a). Consistently, A2AR blockers reduced the immobility times in tail-suspension and forced swim tests. Altogether the results support the hypothesis that blockade of the A2AR might be an interesting target for the development of eVective antidepressant agents. Although their mode of action in potentially alleviating mood disorders is unknown, modulation of dopamine transmission might play a role (El Yacoubi et al., 2001a). Clinical trials with selective A2AR antagonists will be necessary to determine whether these receptors are involved in human mood disorders. Another pathology in which A2AR agonists might be beneficial is schizophrenia (see later discussion). Patients with schizophrenia show impairments in the

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sensorimotor gating that normally prevents excessive irrelevant sensory stimuli from disturbing integrative mental processes in the brain. This impairment is expressed as reduced prepulse inhibition (PPI) and reduced startle habituation. In experimental animals, dopaminergic and AR agonists and antagonists modulate both parameters. Wang et al. (2003) measured PPI and startle habituation in mice that lack functional A2ARs and found that startle amplitude, startle habituation, and PPI were significantly reduced in A2AR knockout mice, providing evidence that this receptor may be involved in their regulation and supporting the feasibility of the development of antipsychotic drugs with A2AR agonist properties (Ferre´ , 1997). Adenosine has been proposed as an endogenous anticonvulsant (see later discussion). The cessation of chronic ethanol intake or ‘‘ethanol withdrawal’’ is an experimental procedure recognized to produce seizures in mice. This convulsant activity is associated with an increase in excitatory neurotransmission in brain. Whereas A2AR knockout and wild-type mice ingested similar amounts of ethanol during forced ethanol consumption, the severity of handling-induced convulsions during withdrawal was significantly reduced in the A2AR knockout mice as compared with that in A2AR wild-type mice. Because the selective A2AR antagonist ZM 241385 also attenuated the intensity of withdrawal-induced seizures, it was suggested that selective A2AR antagonists may be useful in the treatment of alcohol withdrawal (El Yacoubi et al., 2001c). Male and female A2AR knockout mice consumed significantly more ethanol than wild-type mice (Naassila et al., 2002), and the ethanol consumption was also related to ethanol preference. Relative to A2AR wild-type mice, A2AR knockout mice were found to be less sensitive to the sedative and hypothermic eVects of ethanol. No major diVerence in the development of tolerance to ethanol-induced hypothermia was found between the two phenotypes, although female A2AR knockout mice acquired tolerance more slowly. These results suggest that activating the A2ARs may play a role in suppressing alcohol-drinking behavior and is associated with the sensitivity to the intoxicating eVects of acute ethanol administration. A popular belief is that coVee can antagonize the intoxicating eVects of alcohol. However, the molecular mechanisms that might underlie this oVsetting action of coVee remain poorly identified. To investigate the possible involvement of the A2AR in the behavioral sensitivity to high doses of ethanol, El Yacoubi et al. (2003) assessed the hypnotic eVect of ethanol in A2AR knockout mice and A2AR wild-type mice. The duration of the loss of righting reflex following acute ethanol administration was shorter for A2AR knockout mice than for A2AR wild-type mice, whereas the decrease in body temperature was not diVerent between the two phenotypes. Dipyridamole, an inhibitor of adenosine uptake, increased the sleep time observed after administration of ethanol in A2AR wild-type mice but not in A2AR knockout mice. The selective A2AR antagonist SCH 58261, but not the selective A1R antagonist DPCPX, shortened the duration of the loss of

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righting reflex induced by ethanol. Thus, results obtained with drugs mimicked results seen in receptor-deficient mice. The nonselective AR antagonist caVeine (25 mg/kg) also reduced ethanol-induced hypnotic eVects. These results indicate that the activation of A2ARs that follows an increase in extracellular adenosine levels caused by the administration of high doses of ethanol plays a role in its hypnotic eVects. Thus, A2AR antagonists may be useful therapeutic agents for alleviating ethylic coma. The role of ARs in cerebral ischemia appears to be age dependent (see the next chapter). Attenuated focal ischemic brain damage has been reported in adult A2AR knockout mice compared with wild-type mice (Chen et al., 1999). On the other hand, aggravated brain damage is observed after hypoxic ischemia in immature 7-day-old A2AR knockout mice (A˚ de´ n et al., 2003). These results suggest that in contrast to the situation in adult animals, A2ARs play an important protective role in neonatal hypoxic ischemic brain injury. These opposite eVects of both A1R and A2AR in neuroprotection in adult and in newborn animals is further discussed in the next section. The consequences of genetic deletion of A2ARs on psychostimulant-induced behavioral responses have been examined. As discussed elsewhere in this chapter, the results demonstrate that A2AR deficiency selectively attenuates amphetamineinduced and cocaine-induced locomotor responses (Chen et al., 2000). Paradoxical results are obtained by genetic and pharmacological approaches because A2AR agonists can attenuate psychostimulant responses. Among possible explanations, it should be noted that in vivo microdialysis in the striatum of A2AR knockout mice revealed a chronic 45% decrease in the extracellular dopamine concentration (Dassesse et al., 2001). The functional striatal hypodopaminergic activity in mice lacking A2ARs fits with the attenuated locomotor responses induced by indirect dopamine agonists such as amphetamine and cocaine. The modulatory role of A1Rs and A2ARs in the brain is well established. In contrast, although A3Rs have been implicated in various peripheral organ system functions, including regulating cellular components of the immune system (Salvatore et al., 2000) and cardiovascular function (Cerniway et al., 2001), less is known about their functions in the CNS, partly because of the lack of specific A3R ligands and the low density of the receptors (Rivkees et al., 2000). Mice with a deletion of the A3R have undergone behavioral tests. A3R knockout mice manifested a decreased sensitivity to some painful stimuli, as evidenced by the increase in latency in the hot-plate, but not the tail-flick, test. Thus, A3Rs supraspinally located may play a role in processing nociceptive information. Significant increases in some aspects of motor function were also observed in A3R knockout mice (Fedorova et al., 2003). Evidence for a slight increase in locomotor activity was observed in three tests (open-field, elevated plus-maze, light–dark box), a finding consistent with the depression of motor activity observed after administration of an A3R agonist ( Jacobson et al., 1993). In the

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elevated plus-maze and light–dark box, A3R knockout mice showed no signs of anxiety (Fedorova et al., 2003). Although A2AR antagonists have been proposed as antidepressants (El Yacoubi et al., 2001a), A3R knockout mice showed an increase in the amount of time spent immobile on the two tests of behavioral depression, the forced swim test and the tail-suspension test (Fedorova et al., 2003). Interestingly, this response is not adequately explained by a decrease in motor activity, as A3R knockout mice displayed increased locomotion (Fedorova et al., 2003). Therefore, adenosine may modulate in complex manner physiological functions associated with key regions involved in mood regulation; the relationships of A2ARs and A3Rs with depressive illness and their clinical relevance need further investigation. Finally, deletion of the A3R had a detrimental eVect in a model of mild hypoxia, suggesting the possible use of A3R agonists in the treatment of ischemic degenerative conditions of the CNS.

VII. Adenosine Receptors and Protection against Ischemic and Excitotoxic Brain Injuries

Increased extracellular adenosine in response to ischemia and hypoxia has long been shown to act predominantly as a neuroprotectant during cerebral ischemia and other neuronal insults. In the past few years, we were surprised to learn that despite the well-documented neuroprotective properties of adenosine, adenosine may under some circumstances contribute to neurotoxicity, neuronal damage, and death (de Mendonc˛ a et al., 2000). This apparent paradoxical eVect of adenosine may in part reflect complex actions of adenosine on multiple subtypes of ARs (A1, A2A, A2B, and A3) with unique distribution among brain regions and unique coupling with G protein receptors and associated signal pathways (Fredholm et al., 1994a, 2001a). In addition a single subtype of AR located on diVerent neuronal, glial and vascular components can sometimes have opposite eVects (Fredholm et al., 1994a, 2001a).

A. A1 Receptor Activation Produces Predominantly Neuroprotective Effects The neuroprotective eVect of adenosine against brain injury in adult animals has been largely attributed to A1R stimulation, as A1R-specific agonists and antagonists consistently attenuate and potentiate brain damage, respectively. Activation of A1Rs has been well documented to protect against ischemic brain injury in adult animal models of global and transient focal ischemia (Rudolphi et al., 1992a,b; Von Lubitz et al., 1994a,b, 1995a). A similar neuroprotection is

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demonstrated in models of excitotoxicity within the hippocampus induced by kainate and quinolinic acid (MacGregor et al., 1993, 1997) and dopaminergic neurotoxicity induced by methamphetamine in the striatum (Delle Donne and Sonsalla, 1994). Blum et al. (2002b) showed that subcutaneous infusion of another type of A1 agonist, adenosine amine congener, reduced brain damage and prevented striatal degeneration induced by the mitochondrial toxin 3-nitropropionic acid, an animal model of Huntington’s disease. It was also shown that A1R upregulation and activation attenuates neuroinflammation and demyelination in an animal model of multiple sclerosis (Marchi et al., 2002). Other studies have also clearly demonstrated the neuroprotective properties of A1R activation under epileptic conditions (see Section XI, later in this chapter, for a detailed discussion). Thus, activation of A1Rs oVers neuroprotection against a wide range of neural insults in adult animals. A1R-mediated neuroprotection is generally explained by the action of A1Rs on presynaptic sites to reduce the release of excitatory neurotransmitters (de Mendonc˛ a et al., 2000; Fredholm, 1996; Rudolphi et al., 1992a) and by the activation of A1Rs at postsynaptic sites, resulting in G protein–dependent activation of inwardly rectifying Kþ channels leading to hyperpolarization (Dunwiddie and Masino, 2001). In addition, adenosine can inhibit NMDA action (de Mendonca et al., 1995; Klishin et al., 1995), reducing Ca2þ entry and excitotoxicity in adult animals (Fredholm, 1996; Scanziani et al., 1992). The net result of presynaptic and postsynaptic A1R activity is reduced neuronal excitability. Genetic depletion of A1R reduces the neuronal response to hypoxia in hippocampal slices from adult animals ( Johansson et al., 2001). However, surprisingly, there was no significant diVerence between A1R knockout mice and wild-type animals in the extent of damage after middle cerebral artery (MCA) occlusion (Olsson et al., 2004). An important pharmacological phenomenon termed effect inversion should also be noted. EVect inversion was first observed in studies examining A1R ligand modulation of ischemic brain damage (Von Lubitz et al., 1994a). Chronic treatment with the A1R agonist CPA or the antagonist DPCPX was shown to exacerbate and attenuate neuronal loss, respectively (Von Lubitz et al., 1994a), in contrast to neuroprotection by A1R agonists and exacerbation of tissue damage by A1R antagonists after acute treatment. This diVerence between the results of acute and chronic exposure was later also observed in caVeine’s eVect on cognition, seizure activity, and ischemic brain injury (Georgiev et al., 1993; Jacobson et al., 1996) and methamphetamine toxicity (Delle Donne and Sonsalla, 1994). EVect inversion appears to be selective for A1 ligands (including mixed A1R/A2AR antagonists such as caVeine), as the phenomenon is not seen after chronic treatment of normal or dopamine-depleted animals with A2AR antagonists (de Mendonc˛ a et al., 2000; Halldner et al., 2000; Jacobson et al., 1996; Pinna et al., 2001).

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The results so far reviewed indicate that the acute activation of A1Rs aVords neuroprotection in adult animals, although the results obtained in A1R knockout mice suggest that the eVect is not fundamental. However, the opposite is observed in newborns, where A1R activation appears to be detrimental to neuronal survival (Bona et al., 1995; Turner et al., 2003, 2004). This may be due to a diVerent eVect of NMDA receptor activation and of intracellular calcium in immature versus mature neurons. In fact, whereas the activation of NMDA receptors and the rise in intracellular free calcium concentrations are two welldefined hallmarks of neurotoxicity in neurons from adult animals (Mody and MacDonald, 1995), these features appear to be fundamental for the survival of immature neurons (Turner et al., 2004). The elegant work of Klishin et al. (1995) and de Mendonca et al. (1995) showed that A1R activation in cultured cortical neurons (from newborn rats) decreased NMDA receptor function in a manner analogous to that found in adult rats, but this led to decreased neuronal viability, as did several manipulations that decreased intracellular free calcium concentrations (Turner et al., 2004). Thus, it appears that ARs function in the same way in newborn as in adult animals, but that the mechanism underlying neuronal death is fundamentally diVerent in mature and immature neurons.

B. Blockade or Inactivation of A2A Receptors Offers Neuroprotection Whereas A1R activation confers adenosine’s neuroprotection, the tonic activation of A2ARs may in fact contribute to neuronal injury in several neurological disease models. The potential neuroprotection by A2AR antagonists was first reported in a global ischemia model (Gao and Phillis, 1994; Rudolphi et al., 1992b) and has been further substantiated in other ischemic models and in the excitotoxicity model in the hippocampus ( Jones et al., 1998a,b; Ongini et al., 1997; Phillis, 1995; Von Lubitz et al., 1994a, 1995a,b). Pharmacological studies using A2A selective antagonists have been fairly consistent in showing reduced ischemic brain damage in adult animal models of global, focal, permanent, or transient ischemia (Gao and Phillis, 1994; Monopoli et al., 1998; Phillis, 1995; Von Lubitz et al., 1995a,c) and in the excitotoxicity model (Behan and Stone, 2002; Jones et al., 1998a,b). Remarkably, the neuroprotection aVorded by SCH 58261 in adult animals was observed only at a very low dose (0.01 mg/kg), 100–1000 fold lower than the dose needed to stimulate motor activity (1–10 mg/kg). An inverse dose–response relationship of SCH 58261 has now been demonstrated in both quinolinate lesion model and global ischemic models (Monopoli et al., 1998; Popoli et al., 2002) and may reflect limited selectivity of SCH 58261 for A2ARs versus A1Rs. To overcome the intrinsic limitation of partial specificity of A2AR agents, mice lacking A2ARs have been developed (Chen et al., 1999; Ledent et al., 1997). In

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agreement with these pharmacological studies, the volume of cerebral infarction and the associated neurological deficit induced by transient filament occlusion of the MCA are significantly attenuated in A2AR knockout mice (Chen et al., 1999). Thus, pharmacological and genetic studies support that A2ARs play an important role in the development of ischemic and excitotoxicity in adult animals, and A2AR antagonists may develop into treatment for ischemic injury. A massive release of excitatory amino acids during brain ischemia and excitotoxicity is believed to play a critical role in subsequent neuronal death. A2AR agonists have been shown to enhance the release of glutamate under ischemic and nonischemic conditions (Lopes et al., 2002; Marcoli et al., 2003; O’Regan et al., 1992; Rodrigues et al., 2004; Rudolphi et al., 1992b) and in synaptosomal and slice preparations at concentrations as low as 1012 M (but see Dunwiddie and Fredholm, 1997; Lopes et al., 2002; Marchi et al., 2002; Rodrigues et al., 2004; Sebastiao and Ribeiro, 1996). Thus, this facilitating eVect of A2A agonists has been attributed to either an eVect on glutamatergic terminals (Nikbakht and Stone, 2001; Rebola et al., 2003c; Rodrigues et al., 2004) or an indirect eVect of downregulation of A1R-mediated inhibition (Lopes et al., 2002). In addition, A2ARs may trans-synaptically modulate glutamate release in striatum and cortex through a basal ganglia network loop. The enhancement of glutamate release by the A2AR may be due to its positive coupling to the cAMP–PKA signaling pathway, leading to increased Ca2þ influx (Dunwiddie and Fredholm, 1997; Gubitz et al., 1996). As a consequence, pharmacological blockade or transgenic deficiency of the A2AR may aVord neuroprotection after ischemia in adult animals because of reduced glutamate release and excitotoxicity. A2ARs enhance glutamate release both in the striatum (where A2ARs are abundant but predominantly located postsynaptically) and in the cortical regions (where A2ARs are sparse but predominantly located presynaptically). This might explain the apparent mismatch between regional protection (greater in cortical than striatal regions) and A2AR density (highest in striatum) (Dunwiddie and Fredholm, 1997; O’Regan et al., 1992; Sebastiao and Ribeiro, 1996). Studies have provided results indicating that glial A2ARs may also play an important role in control of glutamate eZux. The A2A agonist CGS 21680 enhances glutamate eZux from cultured astrocytic glial cells from cortex or brainstem (Li et al., 2001; Nishizaki et al., 2002). Voltage-clamp recording suggests that this eVect occurs without aVecting presynaptic glutamate release or postsynaptic glutamatergic conductance. Further analysis suggested that A2AR regulation of a specific glial glutamate transporter (GLT-1) may account for this eVect (Nishizaki et al., 2002). The demonstration of glutamate neurotransmission by the glial A2ARs in the CNS may also help explain the involvement of A2ARs in a wide range of animal models of neurological disorders. This proposal gains credence because there is increasing evidence that much of the massive increase in glutamate levels seen in ischemia is due less to exocytotic release than to reversal

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of sodium-dependent glutamate transporters in either glial cells or neurons (Gemba et al., 1994; Madl and Burgesser, 1993).

C. Neuroprotection by A2A Receptor Agonists May Be Mediated through Modulation of Inflammation A2AR agonists are neuroprotective in several experimental models. CGS 21680 attenuates kainate-induced hippocampal lesion after systemic administration but is ineVective after local injection, indicating a possible systemic element in this eVect (such as circulating inflammatory cells) ( Jones et al., 1998b). Local administration of CGS 21680 into striatum has been shown to reduce brain damage in a model of cerebral hemorrhage injury (Mayne et al., 2001). Similarly, the newly developed A2A agonist ATL-146e has been shown to attenuate ischemia-reperfusion injury in both spinal cord and kidney (Cassada et al., 2002; Fiser et al., 2002; Okusa et al., 2000). The mechanism of this protection was proposed to be related to A2AR-mediated eVects on the vascular and inflammatory systems. Several A2AR-mediated nonneuronal eVects on, say, vasodilation (Ngai et al., 2001; Winn et al., 1985), inhibition of platelet aggregation (Ledent et al., 1997; Sandoli et al., 1994), and suppression of neutrophil superoxide generation (Cronstein et al., 1983, 1990) may account for the protection A2AR agonists oVer to neurons and other cellular elements. Furthermore, A2AR agonists appear to inhibit inflammation by attenuating release of proinflammatory cytokines such as tumor necrosis factor- (TNF-) and interleukin-12 (IL-12) (Hasko et al., 2000; Ohta and Sitkovsky, 2001). Finally, A2ARs may modulate nitric oxide synthase and cyclooxygenase in glial cells, and this could contribute to the pathogenesis of brain injury (Brodie et al., 1998; Fiebich et al., 1996b).

D. Complex Actions of A1 and A2A Receptors at Multiple Cellular Elements: Implications for Treatment of Neuropsychiatric Disorders The apparently paradoxical finding that both A2AR antagonists and A2AR agonists have protective eVects may reflect the complex actions of A2ARs at multiple (neuronal, glial, and vascular) elements, each with potentially opposing eVects on cell death. A2AR antagonists may exert their neuroprotective eVect at an early phase of injury by reducing glutamate release (a main injury mechanism in ischemic and excitotoxicity models). In the later inflammatory phase, A2A antagonists may have an adverse eVect. This also highlights the need to carefully monitor any inflammatory eVects of A2AR antagonists that are being evaluated

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for their therapeutic potential in the treatment of neurological disorders such as Parkinson’s disease. Because activation of A1Rs and A2ARs after a cerebral insult may have opposing eVects, such as neuroprotection by A1Rs and exacerbation by A2ARs, at least in adult animals (Cunha, 2001a), the variable results obtained with nonspecific adenosine antagonists such as caVeine and theophylline may be explained (de Mendonc˛ a et al., 2000; Rudolphi et al., 1992b). On the basis of opposing eVects of activation of A1Rs and A2ARs during brain injury and possible functional interaction described earlier, it also raises the possibility of combining A1 agonists (or agents that increase intracellular adenosine levels) and A2A antagonists to provide better neuroprotection against brain injury than either strategy alone. It should be noted that in contrast to the neuroprotection observed in adult A2AR knockout mice (Chen et al., 1999), genetic inactivation of the A2ARs in neonatal mice exacerbates ischemia-induced brain injury (A˚ de´ n et al., 2003). The same was observed for A1R activation (see previous section), confirming the hypothesis that ARs in the neurons of newborns probably function in the same way as in adults, but the mechanism underlying neuronal death is fundamentally diVerent in mature and immature neurons. The diVerent results pertaining to A2ARs and neuroprotection are summarized in Table II.

VIII. Adenosine A2A Receptors and Neurodegenerative Disorders

A. A2A Receptors and Parkinson’s Disease In the past decade, specific A2A antagonists have emerged as promising pharmacological agents for the treatment of Parkinson’s disease, primarily because of their co-localization with D2Rs and the profound antagonistic interaction between adenosine and dopamine systems (see earlier discussion) (Ferre´ et al., 1997, 2001; Morelli and Pinna, 2001; Richardson et al., 1999). Based on their motor enhancement function, A2A antagonists have been tested extensively in animal models of Parkinson’s disease, including models in nonhuman primates (Grondin et al., 1999; Kanda et al., 1998, 2000), and are now entering clinical phase II trials (Bara-Jimenez et al., 2003; Hauser et al., 2003). Here, we briefly summarize the development of A2AR antagonists in the treatment of Parkinson’s disease based on (1) extensive animal studies, particularly studies in nonhuman primates, demonstrating motor enhancement and leading to clinical trials of KW6002 against Parkinson’s disease, (2) animal studies indicating a novel ability of A2AR antagonists to increase motor activity with a low propensity to induce dyskinesia, and (3) mounting evidence suggesting that

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TABLE II A2A Receptor–Modulated Neuroprotection in the Central Nervous System

Neurological disorders

Animal models

Pharmacological and genetic manipulations

References

Neuroprotection by A2AR inactivation Stroke

Global ischemia Focal ischemia MCAO

Excitotoxicity

Kainate Free radicals

Huntington’s disease

Quinolinic acid 3-nitropropionate 3-nitropropionate 3-nitropropionate

Parkinson’s disease

MPTP MPTP 6-OHDA

Protection by A2AR antagonist Protection by A2AR antagonist Protection in A2AR knockout mice Protection by A2AR antagonist Protection by A2AR antagonist Protection by A2AR antagonist Protection by A2AR antagonist Protection in A2AR knockout mice Protection by A2AR antagonist Protection by A2AR antagonist Protection in A2AR knockout mice Protection by A2AR antagonist

Phillis, 1995

Exacerbated brain injury in A2A knockout mice Protection by A2AR agonist Protection by A2AR agonist Protection by A2AR agonist Protection by A2AR agonist

˚ de´ n et al., 2003 A

Monopoli et al., 1998 Chen et al., 1999 Jones et al., 1998a,b Behan and Stone, 2002 Popoli et al., 2002 Fink et al., 2004 Fink et al., 2004 Blum et al., 2002a Chen et al., 2001b Chen et al., 2001b Ikeda et al., 2002

Neuroprotection by A2AR activation Stroke

Neonatal hypoxic ischemia

Excitotoxicity

Ischemic spinal cord injury Kainate

Huntington’s disease

3-nitropropionate

Cerebral hemorrhage

Collagenase IV

Cassada et al., 2002; Fiser et al., 2002 Jones et al., 1998b Blum et al., 2002b Mayne et al., 2001

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A2AR antagonists oVer neuroprotective eVects that may slow down or halt degeneration of dopaminergic neurons. Earlier studies have clearly demonstrated that blockade of A2ARs by antagonists increases motor activity in normal and dopamine-depleted animals. Thus, nonselective AR antagonists (caVeine and theophylline) (Ferre´ et al., 1992; Ongini and Fredholm, 1996) and the A2A-specific antagonists (SCH 58261 and KW6002) (Morelli and Pinna, 2001; Ongini and Fredholm, 1996; Pinna et al., 1996, 2001) increase rotational behavior in hemiparkinsonian mice and reverse the motor deficit observed in MPTP-treated mice. In normal mice, the motor enhancement elicited by A2AR antagonists is modest, but in dopamine-depleted mice it is significantly increased, suggesting a selective motor enhancement eVect in models of Parkinson’s disease. The mechanism of motor enhancement has been attributed to three possible eVects of the A2A antagonists: an antagonistic direct receptor–receptor (A2A–D2) interaction at the membrane level (Ferre´ et al., 1991; Fuxe et al., 1998); opposing but independent eVects of A2AR and D2R signaling (Aoyama et al., 2000; Chen et al., 2001a; Svenningsson et al., 1999b); or A2AR modulation of GABA release (Mori et al., 1996; Richardson et al., 1999; Shindou et al., 2001). These rodent studies have been extended to other species: In MPTP-treated nonhuman primates, A2A antagonists such as KW6002 reverse the motor deficiency (Grondin et al., 1999; Kanda et al., 1998, 2000). Motor stimulation was observed after acute treatment and after repeated treatment up to 21 days (Halldner et al., 2000; Kanda et al., 1998, 2000). In a rodent model of Parkinson’s disease, A2AR antagonists stimulated motor activity alone or in synergy with dopaminergic agents such as l-DOPA or D1R and D2R agonists (Pinna et al., 1996; Pollack and Fink, 1995, 1996; Shiozaki et al., 1999). These studies led to the first clinical trial of the A2A antagonist KW6002 for patients with early (or late-stage) Parkinson’s disease (Bara-Jimenez et al., 2003; Hauser et al., 2003). The initial results are encouraging because they appear to confirm the motor stimulant eVect alone and by prolonging the l-DOPA eVect in patients with Parkinson’s disease. An interesting feature of A2A antagonists shown by studies in nonhuman primates is that the drug stimulates motor activity without eliciting dyskinesia. This finding is potentially significant because dyskinesia is a debilitating motor complication that occurs after long-term l-DOPA treatment. Synergism between A2AR antagonists and l-DOPA on motor enhancement suggests that co-administration of A2AR antagonists allows reduction of the dose of l-DOPA, thus reducing the risk of development of dyskinesia (Pinna et al., 2001). Moreover, genetic inactivation of A2AR attenuated the sensitization seen on repeated l-DOPA administration, indicating that activation of A2ARs is required for development of behavioral sensitization after long-term treatment with l-DOPA (Fredduzzi et al., 2002). This is further supported by demonstration of selective attenuation of psychostimulant amphetamine-induced locomotor sensitization in

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A2AR knockout mice (Chen et al., 2003). Also consistent with this notion, the A2AR antagonist 8-(3-chlorostryryl caVeine) (CSC) reversed the shortening of the duration of the motor responses to l-DOPA in rodents (Bove´ et al., 2002). The most encouraging finding is the observation that co-administration of KW6002 with apomorphine in MPTP-treated nonhuman primates abolishes the development of dyskinesia (Bibbiani et al., 2003). However, KW6002 did not modify the abnormal involuntary movement in another rodent model of dyskinesia (Lundblad et al., 2003). Further studies are clearly needed to understand this important feature of A2A antagonists in Parkinson’s disease. The most promising development in A2A antagonists in the treatment of Parkinson’s disease is that these substances not only provide symptomatic relief but also appear to have neuroprotective eVects. In 2000, Ross et al. reported a large prospective study showing an inverse relationship between caVeine consumption and the risk of developing Parkinson’s disease in a 30-year follow-up of 8004 Japanese American men enrolled in the prospective longitudinal Honolulu Heart Program. This finding is further substantiated by two ongoing cohort studies, the Health Professionals’ Follow-Up Study (HPFS) and the Nurses’ Health Study (NHS), involving 47,351 men and 88,565 women (Ascherio et al., 2001). These studies firmly established a relationship between increased caVeine consumption and decreased risk of developing Parkinson’s disease in men (Ascherio et al., 2001). Intriguingly, this inverse relationship is not seen in women (Ascherio et al., 2003). The epidemiological association between caVeine consumption and Parkinson’s disease is further supported by the emergence of animal studies supporting such a causal relationship (Chen et al., 2001b; Gevaerd et al., 2001; Ikeda et al., 2002; Xu et al., 2002). Co-administration of caVeine not only provides neuroprotection against MPTP-induced loss of dopamine content and dopaminergic terminals in striatum (Chen et al., 2001b; Xu et al., 2002) but also attenuates the loss of dopaminergic neurons in the substantial nigra (Ikeda et al., 2002; Oztas et al., 2002). CaVeine also reverses the memory impairment induced by intranigral injection of MPTP in rats (Gevaerd et al., 2001). Interestingly, caVeine-induced neuroprotection appears to persist even after repeated treatment for 7 days (in contrast to the rapid development of tolerance to the motor stimulant eVect) (Xu et al., 2002) and is similarly observed for caVeine metabolites such as theophylline and paraxanthine. This protection is likely mediated by A2ARs because various antagonists including SCH 58261, DMPX, KW6002, and CSC (but not the A1 antagonist DPCPX) attenuate MPTP-induced dopaminergic neurotoxicity (Chen et al., 2001b). Similarly, genetic depletion of the A2AR also reduces MPTP-induced striatal damage (Chen et al., 2001b). These studies provide a neurobiological basis for the inverse relationship between increased caVeine consumption and reduced risk of developing Parkinson’s disease. This also raises the exciting possibility that A2A antagonists may oVer a neuroprotective strategy to slow or even halt degeneration of dopaminergic neurons.

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How the A2AR or its blockade aVects dopaminergic neuronal death remains uncertain. A cellular mechanism was proposed to explain how A2AR antagonists may attenuate neurotoxicity in the MPTP model of Parkinson’s disease (Ikeda et al., 2002). Blockade of A2ARs reduced cAMP in dopaminergic neurons, leading to increased vesicular sequestration of MPPþ (the active toxic metabolite of MPTP). Because A2ARs are expressed largely in GABAergic striatopallidal output neurons (Fink et al., 1992; SchiVmann and Vanderhaeghen, 1993a) and at a low level on the dopaminergic nigrostriatal neurons (Dixon et al., 1996; Hettinger et al., 2001), striatal A2AR blockade likely protects dopaminergic neuron survival through a polysynaptic feedback loop involving the A2AR-laden striatopallidal neurons (Chen et al., 2001b; Schwarzschild et al., 2002). However, as discussed earlier (see Section VIII, Table II), A2A antagonists provide a broader neuroprotective eVect, now extending from the hippocampus to the frontal cortex and from the substantia nigra to the striatum. Thus, a working hypothesis that involves A2AR modulation of a generalized CNS process such as glutamate release and inflammation processes has become more compelling (as discussed earlier) (Schwarzschild et al., 2002).

B. Adenosine Receptors and Huntington’s Disease Three lines of experimental evidence suggest a potential role of A2ARs in the pathogenesis of Huntington’s disease: (1) A2ARs are highly enriched in the striatum (Fink et al., 1992; SchiVmann et al., 1991a), the locus of the initial and most severe neurodegeneration in Huntington’s disease (DiFiglia, 1990; Mitchell et al., 1999). The A2AR is localized to striatopallidal neurons in which early degenerative changes occur. This unique anatomical localization makes A2ARs an attractive potential therapeutic target. (2) Neurochemical studies of mice bearing the Huntington’s disease mutation show that some of the earliest changes in gene expression include a reduction in expression of the A2ARs, suggesting a possible involvement in the pathogenesis of Huntington’s disease (Cha et al., 1998, 1999; Glass et al., 2000). A report by Blum et al. (2002a) showed that in an animal model in which Huntington’s disease is induced by the mitochondrial toxin 3-nitropropionic acid, A2ARs in the lesioned site are downregulated, but the A2AR binding sites are strongly upregulated within the spared medial striatum. 3) Evidence shows that inactivation of A2ARs has neuroprotective eVects against several neuronal insults, including ischemic brain injury (Chen et al., 1999; Monopoli et al., 1998; Phillis, 1995), MPTP-induced dopaminergic neurotoxicity (Chen et al., 2001b; Ikeda et al., 2002), and excitotoxicity induced by kainate or quinolinic acid ( Jones et al., 1998a,b). Selective striatal lesioning by the excitotoxin quinolinate produces a pathology that resembles that observed in patients with Huntington’s disease and thus has been widely used as an animal model of Huntington’s disease. An early study

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suggested that administration of the A2A antagonist CGS 21680 attenuated amphetamine-induced hyperlocomotor activity, tested 2 weeks after intrastriatal injection of quinolinic acid (Popoli et al., 1994). Intrastriatal injection of the A2A antagonist DMPX has been shown to prevent the quinolinate-induced electroencephalographic (EEG) abnormalities in the frontal cortex (Reggio et al., 1999). Interestingly, in 2002 Popoli et al. demonstrated that the A2A antagonist SCH 58261 reduces the eVect of quinolinate on motor activity, EEG changes, and striatal gliosis. This neuroprotective eVect is selective for the low dose (0.01 mg/kg) of SCH 58261 and is probably mediated through a presynaptic mechanism, that is, by blocking glutamate release in the striatum after quinolinic acid lesioning (Popoli et al., 2002). On the other hand, Blum et al. (2002b) reported that the A1R agonist adenosine amine congener (ADAC) reduces 3-nitropropionic acid–induced striatal damage, another neurochemical model of Huntington’s disease. Moreover, findings in A2AR knockout mice show that loss of striatal neurons induced by systemically administered 3-nitropropionic acid is markedly reduced in the absence of the A2AR or in the presence of the A2AR antagonist CSC (Fink et al., 2004). Similarly, intrastriatal infusion of the A2AR antagonist DMPX also reduced striatal damage induced by the mitochondrial toxin malonate (Alfinito et al., 2003). These neurotoxins (3-nitropropionate, malonate, or quinolinate) also induce neurochemical damage that resembles the pathology of Huntington’s disease. Thus, if the findings showing protective eVects can be extended and confirmed in the genetic model of the disease, A2AR antagonists may represent a plausible strategy with which to treat Huntington’s disease, for which no eVective pharmacological treatment is available.

C. Adenosine Receptors and Alzheimer’s Disease Based on the ability of A2AR activation to enhance acetylcholine release in cortical regions (Cunha et al., 1994, 1995b; Jin and Fredholm, 1997; Rebola et al., 2002), it was suggested that A2AR-mediated enhancement of acetylcholine in the cortex and other brain areas may be beneficial for patients with Alzheimer’s disease (Ribeiro et al., 2003). However, a retrospective study reported an inverse relation between caVeine consumption and Alzheimer’s disease (Maia and de Mendonc˛ a, 2002). Likewise, caVeine eVectively prevented the neuronal death triggered by exposure to the 1–42 peptide fragment of -amyloid protein (Dall’lgna et al., 2003), presumably a causative factor in Alzheimer’s disease (Hardy and Selkoe, 2002). This eVect was mimicked by a selective A2AR antagonist, but not by a selective A1R antagonist (Dall’lgna et al., 2003). Accordingly, it was reported that A2ARs were upregulated in cortical regions of patients with Alzheimer’s disease (Angulo et al., 2003), whereas A1Rs, though functional (Angulo et al., 2003), were downregulated (Deckert et al., 1998a). Thus, it appears

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that caVeine and possibly A2AR antagonists might have a beneficial eVect in managing Alzheimer’s disease, although this remains to be firmly established. This beneficial eVect of AR antagonists on a pathology chiefly characterized by mnemonic defects is in accordance with the ability of caVeine to aVect memory performance (Angelucci et al., 2002; Hauber and Bareiss, 2001). However, whether this is a direct eVect on memory processing or an indirect result of the general mood-enhancing properties of caVeine is still debatable (Hameleers et al., 2000; Rogers and Dernoncourt, 1998). It also remains to be established which ARs may be involved in the diVerent processes of learning and memory retrieval. In fact, it has been described that both A1R and A2AR antagonists may have beneficial eVects in memory processing in rodents (Corodimas and Tomita, 2001; Kopf et al., 1999; Pitsikas and Borsini, 1997). This contrasts with the opposite eVects of A1R and A2AR antagonists on the control of long-term potentiation (de Mendonc˛ a and Ribeiro, 1997), an in vitro correlate of learning and memory (Lynch, 2004). Thus, the role of ARs, if any, in cognition is very poorly understood.

IX. Adenosine Receptors and Psychiatric Disorders

A. Adenosine Receptors and Schizophrenia Profound interactions between adenosine and dopamine systems highlight the possibility that A2AR agonists and antagonists may have antipsychotic and propsychotic (psychomimetic) properties, respectively, through their modulation of the dopaminergic system. Genetic screening has indicated an association between polymorphism of the A2AR gene and the development of schizophrenia and panic disorder (Deckert et al., 1996, 1997, 1998b). The A2A agonist CGS 21680 has been shown to reduce spontaneous locomotor activity and antagonize psychostimulant-induced motor activity (Rimondini et al., 1997, 1998). Interestingly, the ED50 value for induction of catalepsy and for antagonizing amphetamine-induced motor activity for CGS 21680 is similar to that of atypical antipsychotic drugs such as clozapine, as opposed to the typical antipsychotic drug haloperidol (Rimondini et al., 1997). Similarly, CGS 21680 administration decreased apomorphine-induced behavioral unrest, arousal, and stereotypies in nonhuman primates (Andersen et al., 2002). The PPI test assesses the ability of humans or animals to filter through largely ‘‘noise’’ stimuli. Disruption of this sensory motor gating function is considered a behavioral hallmark of schizophrenia, and thus, the PPI test is considered a valid animal model for screening the eVectiveness of antipsychotic drugs. Theophylline administration changes the PPI responses in human volunteers to values similar to those found in patients with schizophrenia (Ghisolfi et al., 2002) and some of

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the participant volunteers even reported ‘‘positive symptoms.’’ PPI was also significantly reduced in A2AR knockout mice compaired to their wild-type littermates (Wang et al., 2003). In animal models, intra-accumbens infusion of CGS 21680 reverses dopamine agonist–induced disruption of PPI (Hauber and Koch, 1997). Systemic administration of CGS 21680, however, did not aVect dopamine agonist–induced disruption of PPI in animals, although CGS 21680 attenuates PCP-induced disruption of PPI. These studies seem to suggest that the A2AR may aVect psychotic behaviors not through modulation of the dopaminergic system, but through the glutamatergic system (Lara and Souza, 2000).

B. Adenosine Receptors and Addictive Behaviors Given that the dopaminergic system is an indispensable component of the reward pathway, adenosine–dopamine interaction (described earlier) indicates that drugs acting at ARs may indirectly influence addictive behaviors. Following chronic cocaine treatment, adenosine concentration is increased at presynaptic terminals (Bonci and Williams, 1996). Increased adenosine acting at A1Rs could either inhibit GABA release to disinhibit dopamine cells (Bonci and Williams, 1996) or produce more eVective burst firing by glutamatergic terminals (Fiorillo and Williams, 2000). Conversely, following cocaine withdrawal, adenosine uptake is increased and presynaptic sensitivity to adenosine is decreased (Manzoni et al., 1998). Repeated injection of psychostimulants to induce locomotor sensitization is a widely used animal model with several features of addictive behaviors (Pierce and Kalivas, 1997; Robinson and Berridge, 1993). Pharmacological and genetic studies suggest an important role for adenosine in behavioral sensitization. However, the eVects diVer depending on the particular AR subtype and sensitizing stimulus involved (El Yacoubi et al., 2001c; Shimazoe et al., 2000; Weisberg and Kaplan, 1999). For example, activation of A2ARs is critical to the establishment of behavioral sensitization by amphetamine (Chen et al., 2003). On the other hand, the A2A agonist CGS 21680 attenuates sensitization to repeated methamphetamine administration (Shimazoe et al., 2000). Additional studies are warranted to address the role of ARs in the development of psychostimulant behavioral sensitization. CaVeine, arguably the most widely used psychoactive drug, acts at brain A1Rs and A2ARs to produce a psychostimulant eVect. CaVeine has been shown to prevent the extinction of cocaine self-administration in rodents (Kuzmin et al., 1999; Schenk et al., 1996; Worley et al., 1994) and appears to have some rewarding eVects that induce place preference conditioning in rats (Bedingfield et al., 1998). This eVect is probably mediated by caVeine acting at A1Rs (Kuzmin et al., 1999). On the other hand, CGS 21680 and NECA inhibit the initiation of cocaine self-administration (Knapp et al., 2001). At the neurochemical level,

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mixed results have been obtained concerning dopamine release in nucleus accumbens and prefrontal cortex in response to caVeine (Acquas et al., 2002; Solinas et al., 2002). The propensity of caVeine and related drugs to induce addictive behavior remains a controversial issue under intensive study (Daly and Fredholm, 1998; Fredholm et al., 1999).

X. Adenosine and the Regulation of Sleep–Wake Cycles

CaVeine is widely used to improve wakefulness, and the main actions of caVeine are mediated by brain ARs (Fredholm et al., 1999). Thus, it was logical to propose that adenosine might be an endogenous regulator of sleep–wake cycles (Radulovacki, 1985), especially as adenosine analogs induced a sleep-like state (Radulovacki et al., 1984). Accumulating evidence supports the view that adenosine may play a critical role in the promotion of sleep (Porkka-Heiskanen et al., 1997, 2002; Rainnie et al., 1994). Such evidence generally falls into two categories: in vivo measurement of adenosine levels during sleep–wake cycles and the eVects of pharmacological manipulation of adenosinergic tone on the sleep–wake cycle. Extracellular adenosine levels undergo cyclic changes during the sleep–wake cycle. Using in vivo microdialysis, Porkka-Heiskanen et al. (1997, 2002) showed that extracellular adenosine levels in rat basal forebrain, a key sleep-regulating region, progressively increase during prolonged wakefulness and decrease during subsequent recovery sleep. This increase in adenosine levels appears selective for the basal forebrain areas, as there are no cyclic changes in extracellular adenosine levels in cortex and four other subcortical areas during prolonged wakefulness in cat (Porkka-Heiskanen et al., 2002). These results suggest that adenosine regulates the transition from wakefulness to sleep. Although enzymes responsible for adenosine formation and metabolism show typical diurnal variations, the increase in adenosine levels is apparently not a consequence of alterations in adenosine enzyme activity, because their activity in the basal forebrain and cortex did not change after prolonged wakefulness (Alanko et al., 2003; Mackiewicz et al., 2003). Others have observed motor-activity–dependent increases in extracellular adenosine levels in the hippocampus and striatum (but not the hypothalamus) (Huston et al., 1996). Intriguingly, sleep deprivation produces opposite eVects on A1R and A2AR mRNA levels in the rat. Three and six hours after sleep deprivation, the level of A1R mRNA increases in basal forebrain, whereas the level of A2AR mRNA and the A2AR binding density decrease in the olfactory tubercle (Basheer et al., 2001). Additional compelling evidence comes from the eVects of pharmacological manipulation of adenosine on sleep physiology. For example, direct infusion of adenosine or the adenosine transport blocker nitrobenzylthioinosine into the

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basal forebrain induced sleep–wake profiles similar to those seen after sleep deprivation in the cat (Porkka-Heiskanen et al., 1997). Similarly, adenosine perfusion in this area reduced wakefulness in both the cat and the rat (Basheer et al., 1999; Portas et al., 1997; Strecker et al., 2000). Intra-brain infusion of AR agonists and antagonists promotes and reduces sleep, respectively, in various species including humans (Basheer et al., 2000; Lin et al., 1997). Adenosineinduced sleep-promoting eVects can be blocked by benzodiazepine receptor antagonists, suggesting that AR-mediated sleep regulation may involve GABAergic transmission (Mendelson, 2000). The eVect of adenosine on sleep may be present during early developmental stages because adenosine-mediated inhibition of rapid eye movement (REM)–like behavior can be demonstrated in fetal sheep (Koos et al., 2002). Interestingly, aged animals displayed increased levels of adenosine but less sleep, suggesting that the coupling mechanism between adenosine and sleep is impaired during aging (Murillo-Rodriguez et al., 2004). These observations strongly support the view that adenosine functions as a homeostatic factor in the physiological regulation of sleep. This is consistent with the hypothesis that during the wakeful period, increased neuronal and metabolic activities result in ATP catabolism (Kalinchuk et al., 2003), leading to increased levels of adenosine. Adenosine, in turn, reduces neuronal activity in basal forebrain where neuronal discharge during wakefulness is highest (Porkka-Heiskanen et al., 2002). Both A1Rs and A2ARs have been shown to contribute to regulation of the sleep–wake cycle (Marks et al., 2003). The A1R acts at cholinergic neurons in the basal forebrain, a critical area for regulation of arousal, to promote sleep (Porkka-Heiskanen et al., 2002). In vivo infusion of adenosine or the highly selective A1R agonist N6-cyclopentyl adenosine in this nucleus increases both the propensity to sleep and the intensity of delta waves upon falling asleep (Alam et al., 1999; Benington et al., 1995; Portas et al., 1997; Schwierin et al., 1996; Thakkar et al., 2003). Conversely, infusion of the A1 antagonist cyclopentyl-1,3-dimethylxanthine (CPT) increases wakefulness and decreases sleep (Strecker et al., 1999). Whole-cell extracellular recordings in cholinergic zone neurons in slices of the basal forebrain demonstrated that adenosine exerts a strong inhibitory tone on these neurons (Rainnie et al., 1994). Inhibition of cholinergic neurons comes about through an increase in the inwardly rectifying potassium current, resulting in postsynaptic hyperpolarization. A second messenger system involving the activity of nuclear factor-B (NF-B) and IP3 receptor–regulated Ca2þ release from intracellular Ca2þ stores has been implicated in this process (Basheer et al., 2002). With such strong pharmacological evidence for an A1R-induced sleep eVect, it is surprising to learn that the amounts of non-REM sleep and REM sleep are indistinguishable in wild-type and A1R knockout mice after 24 hours of baseline, followed by 6 hours of sleep deprivation (Stenberg et al., 2002). Developmental compensation in these mutant mice may be a confounding factor. On the other hand, Ronan

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et al. (2002) produced laterodorsal tegmental nucleus-specific A1R depletion using injection of adeno-associated virus vector expressing Cre recombinase into floxed A1R mice. These results showed that bilateral depletion of A1R in this brain region was suYcient to increase total baseline waking during the last 6 hours of the light cycle (Ronan et al., 2002). A separate study aiming to identify the mechanism through which endogenous prostaglandin D2 (PGD2) promotes sleep led to the discovery that adenosine, acting at A2ARs in the subarachnoid space, promoted sleep (Satoh et al., 1996). The sleep eVect induced by PGD2 is blocked by intraperitoneal injection of the A2AR-specific antagonist KF 17837, indicating that endogenous adenosine acting at A2ARs may be a mediator of the PGD2-induced sleep eVect (Satoh et al., 1996). Furthermore, infusion of the selective A2AR agonist CGS 21680 (but not the A1R agonist CHA) into the rostral basal forebrain induced slow-wave sleep for the first 12 hours of the nighttime period (Satoh et al., 1996, 1998, 1999). When infused into the medial pontine reticular formation in rats, CGS 21680 was 10-fold more potent than the A1R agonist CHA, inducing REM sleep (Marks et al., 2003). Sleep induced by the A2AR agonist CGS 21680 is followed by a strong rebound of wakefulness after the cessation of CGS 21680 infusion (Gerashchenko et al., 2000). The major site responsible for A2AR-mediated sleep is apparently located in or near the rostral basal forebrain as shown by a sleeppromoting eVect and c-Fos expression after local infusion of CGS 21680 (Satoh et al., 1999). Furthermore, CGS 21680–induced sleep is almost completely abolished in A2AR knockout mice, confirming the specificity of CGS 21680 for A2ARs (Qu et al., 2002). A possible anatomical pathway for A2AR-mediating PGD2-induced sleep was mapped by Fos-positive neurons (Satoh et al., 1999; Scammell et al., 2001), but the accuracy of this pathway remains to be seen.

XI. Adenosine and Epilepsy

Several studies using diVerent animal or in vitro models of epilepsy concluded that adenosine and/or A1R agonists display anticonvulsant properties (Dragunow, 1988; Dunwiddie, 1999). This anticonvulsant eVect of adenosine could result from an inhibition of the evoked release of glutamate, but mainly from the hyperpolarizing action of adenosine mediated by activation of potassium channels (Dunwiddie, 1980; Khan et al., 2001; Lee et al., 1984). Thus, adenosine is particularly eVective in controlling secondary after-discharges and in reducing the rate of interictal spiking in brain slice models of epilepsy (Dunwiddie, 1980; Lee et al., 1984). Likewise, in animal models of epilepsy, adenosine and/or A1R agonists can increase the threshold for seizure induction and can arrest seizures (Dragunow, 1988; Dunwiddie, 1999). Another potential benefit of adenosine and

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A1R agonists for the management of epileptic complications is the neuroprotective role of adenosine (de Mendonc˛ a et al., 2000; Fredholm, 1997), which is particularly relevant in view of the extensive neuronal cell death occurring as a consequence of seizure activity (Bengzon et al., 1997; Cavazos et al., 1994; Tasch et al., 1999). Not only exogenously added adenosine or A1R agonists but also endogenous adenosine can control seizure activity. There is a rapid and massive release of adenosine during such stimulation that induces seizures (Berman et al., 2000; During and Spencer, 1992; Lewin and Bleck, 1981; Winn et al., 1980). Moreover, the seizure-induced increase in the extracellular levels of adenosine is longlasting. A role for adenosine as a mediator of much of the postictal depression is supported by the finding that antagonists of ARs can reduce the duration of postictal depression (Kulkarni et al., 1989; Whitcomb et al., 1990). However, except in the CA3 region of the hippocampus, where AR antagonists cause a persistent paroxysmal activity (Alzheimer et al., 1993; Ault et al., 1987; Dunwiddie, 1980), the blockade of ARs is by itself not suYcient to trigger seizures in naive animals, or preparations (Dunwiddie, 1999) and AR antagonists do not seem to alter the course of a seizure per se (Whitcomb et al., 1990). However, AR antagonists can prolong epileptic seizures (Dragunow and Robertson, 1987; Whitcomb et al., 1990) and can convert a pattern of recurrent seizures into status epilepticus (Eldridge et al., 1989; Young and Dragunow, 1994). In spite of the large seizure-induced increase in the extracellular levels of adenosine, further increasing the levels of endogenous extracellular adenosine can increase the threshold for seizure induction (Huber et al., 2001; Zhang et al., 1993). This suggests that repeated seizures may influence the adenosine neuromodulatory system. In fact, there is a reduction in the density of A1Rs upon induction of a chronic pattern of seizures (Ekonomou et al., 2000; Glass et al., 1996; Ochiishi et al., 1999; Rebola et al., 2003a), and there are complex changes in the extracellular metabolism of purines (Rebola et al., 2003a). Thus, after seizures, there is an increased release of ATP (Wieraszko and Seyfried, 1989), a decrease in the activity of ecto-ATP diphosphohydrolases (Bonan et al., 2000a,b; Nagy et al., 1990; Rebola et al., 2003a), a marked increase in the activity of ecto-50 -nucleotidase (Rebola et al., 2003a; Schoen et al., 1999), and a lower density of nucleoside transporters (Pagonopoulou and Angelatou, 1998). Overall, these modifications suggest a greater formation and longer half-life of ATP-derived adenosine (Rebola et al., 2003a), which contrasts with the requirement of higher doses of A1R agonists to produce anticonvulsant eVects as status epilepticus progresses (Young and Dragunow, 1994). However, this makes sense in light of the hypothesis that ATP-derived adenosine leads to a preferential activation of facilitatory A2ARs rather than inhibitory A1Rs (Cunha et al., 1996a, 2001b). Interestingly, the density of A2ARs is upregulated in the cerebral cortex and hippocampus of fully kindled rats (Rebola et al., 2002), and reports described

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robust anticonvulsant eVects of A2AR antagonists in the threshold of seizure induction, the same being observed in A2AR knockout mice (El Yacoubi et al., 2001c; Vaugeois et al., 2003). Though still requiring considerable experimental confirmation, these preliminary observations open a new conceptual possibility to interfere with seizure induction and eventually epileptogenesis and seizureinduced neuronal degeneration based on interference with A2ARs. This is particularly interesting given that lower doses of A2AR antagonists seem to be required to hit central versus peripheral A2ARs (Fredholm et al., 2003), that the central eVects of A2ARs antagonists seem to stabilize over time (see Fredholm et al., 2003), and that there is an increased density and functional relevance of A2ARs in the neocortex and in the limbic cortex on aging (Lopes et al., 1999b; Rebola et al., 2003c, 2004) when epilepsy complications are prevalent.

XII. Adenosine and Pain

The role of adenosine in the regulation of pain has been reviewed (Sawynok and Liu, 2003; Sollevi et al., 1995). CaVeine has long been used as an adjuvant in analgesic preparations and is believed to be particularly beneficial against headache (Ward et al., 1991) and postischemic pain (Myers et al., 1997). Part of the reason for the eVect on headaches could be that headache is a typical sign of caVeine withdrawal, which may be forced upon patients, for example, by operative procedures, and withdrawal is clearly alleviated by caVeine (Weber et al., 1993). These caVeine eVects are well correlated with blood flow changes (Couturier et al., 1997). However, caVeine has not only been reported to be analgesic but also to block the analgesic eVects of morphine and other opioids (Ahlijanian and Takemori, 1985; De Lander and Hopkins, 1986). In mice, intrathecal administration of adenosine analogs or the elevation of adenosine by blocking adenosine kinase (Keil and DeLander, 1992) leads to analgesia, apparently mediated by A1Rs ( Johansson et al., 2001). This is observed also in humans (Eisenach et al., 2002a,b). Furthermore, elimination of A1Rs increases the response of mice to painful stimuli (see Section VI). ARs, mainly A1Rs, are present in the spinal cord (Geiger et al., 1984). A more careful immunohistochemical analysis reveals that most of these A1Rs are present on a subset of interneurons (Brooke et al., 2004; Schulte et al., 2003), but exactly how they regulate pain transmission is unknown. A completely diVerent possibility to explain the analgesic eVect of caVeine is enhancement of cholinergic transmission in the brain (Ghelardini et al., 1997). This could be due to the actions on acetylcholine release or on the rate of firing of cholinergic neurons, actions likely caused by A1Rs. By blocking these eVects, caVeine would be expected to exacerbate pain rather than alleviate it.

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Indeed, adenosine can sometimes induce pain. For example, intravenous administration of adenosine can provoke pain resembling angina pectoris (Sylve´ n et al., 1987). There is also some evidence that adenosine may cause hyperalgesia (Pappagallo et al., 1993). Given that activation of spinal A1Rs attenuates thermal hyperalgesia (Yamamoto et al., 2003), the adenosine-induced hyperalgesia should be mediated by other receptors. Because only A1Rs are abundant in spinal cord, these hyperalgesia-inducing ARs are most likely located elsewhere. A3Rs may indirectly aVect pain in diVerent ways. They appear to be involved in the inflammatory reaction induced by carrageenan, because swelling is markedly reduced in A3R knockout mice (Wu et al., 2002). Heat hyperalgesia was also reduced. By contrast, A3 antagonists are reported to produce thermal hyperalgesia (Abo-Salem et al., 2004). The eVects are thus not very consistent, and this is perhaps what one might expect if the receptor is involved in modulating the inflammatory reactions, rather than directly aVecting pain transmission. A2AR knockout mice exhibit hypoalgesia, and this was attributed to elimination of peripheral hyperalgesia (Berrendero et al., 2003). Evidence was produced that A2BR antagonists can be antinociceptive (Abo-Salem et al., 2004), whereas selective A2AR antagonists are not. Furthermore, administration of A2BR antagonists has eVects that synergize with morphine (Abo-Salem et al., 2004). Thus, ARs may play many roles in pathways that contribute to pain. Spinal A1Rs are clearly playing a role in reducing nociception, whereas A2ARs and A2BRs, located elsewhere, may enhance nociception. Finally, A3Rs may significantly modify inflammatory reactions and, indirectly, pain. Clearly much additional work is needed to pinpoint sites and mechanisms of action, as well as roles in chronic pain states.

Acknowledgments

The authors’ research was supported i.a. by the Swedish Science Council (project no. 02553), by National Institutes of Health (USA, NS37405 and NS41083) grants, and by Fundac˛ a˜ o para a Cieˆ nciae para a Tecnologia (grant no. 44740/02).

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INDEX

A

Huntington’s disease and, 224, 229, 232–233 hypoxia and, 192, 193, 199, 206, 217, 223, 224 inflammation modulation and, 206, 224, 227, 232 inflammatory reactions and, 211, 227–228, 229, 241 ischemia/models and, 192, 206, 211, 217, 222, 223, 225–228, 229, 232, 240 knockout mice and, 193–194, 199, 201, 215, 216–225, 228, 229, 230, 233, 237, 238, 240, 241 L-DOPA and, 230–231 microglia and, 200–202, 205, 211 nerve activity regulation and, 208, 209 neuromodulation and, 207, 210–212, 217 neuroprotective effect of receptors in, 223–228, 229 neurotransmitter release and, 192–193, 204, 205, 208–211, 213 nucleoside transporter mechanism and, 193, 239 pain and, 199, 217, 220, 222, 240–241 Parkinson’s disease and, 199, 201–202, 207, 215, 220, 228–232 pharmacological tools in study of, 202–204 PPI and, 221, 234–235 receptor expression and, 205–207 receptor localization and, 197, 200–202 receptors of, 196–197, 198–199, 200–212 regulation of, 192–196 signaling and, 193, 204–205, 207, 208, 211, 213, 215, 216, 226, 230 sleep-wake cycles and, 217, 221, 236–238 striatum and, 200–201, 204, 207, 208, 213–216, 218, 222, 224, 226, 227, 231, 232–233, 236 SZ and, 202, 220–221, 234–235 treatment of disorders and, 205, 206, 212, 214, 216, 218, 221, 223, 224, 226–228, 230–231, 233–236

AD. See Alzheimer’s disease ADAR. See Adenosine deaminases, acting on RNA Adenosine deaminases, acting on RNA (ADAR), in serotonin C2 receptor regulation, 86–88 Adenosine, in brain function. See also Adenosine receptors; Dopamine receptors AD and, 207, 233–234, 239 addiction and, 234–235 adenosine pathways and, 195 amyloid deposits and, 207, 233 astrocytes and, 194–196, 200, 201–202, 205, 210–211, 226 ATP and, 193, 194, 195, 209, 237, 239 blockading receptors and, 207, 215, 217, 218–220, 225–227, 230–232, 239 caffeine and, 192, 218–220, 235–236 cAMP pathways and, 193, 198, 199, 204–205, 210, 215, 226, 232 cytokines/receptors and, 206, 211, 227 DARPP-32 and, 212–213, 215–216 dopamine receptor interactions and, 212–216, 220 ectonucleotidase pathway and, 193, 194, 195 in energy supply/demand, 192, 193 ENT-1 and, 193–194 epilepsy and, 207, 238–240 ethanol and, 221–222 excitatory action of, 194, 201, 208, 213–216, 221, 224, 226 excitotoxicity model and, 223–227, 229, 232 in exocytotic apparatus and, 192–194, 227 GABA and, 199, 201, 208, 210, 213, 214, 215, 230, 232, 235, 237 glutamate release and, 226, 227–228, 232, 233 G-protein and, 198, 204, 206, 207, 213, 223, 224, 233 heterodimerization, of AR/DR and, 213–214 hippocampus and, 198, 200, 207, 216, 217, 224, 225, 232, 236, 239–240 271

272

INDEX

Adenosine pathways, adenosine/brain function and, 195 Adenosine receptors (AR) adenylyl cyclase and, 196–197 agonists/antagonists, in study of, 202–204 blockading receptors and, 207, 215, 217, 218–220, 225–227, 230–232, 239 caffeine/theophylline and, 196–197 calcium channels and, 208, 209 DARPP-32, DRs and, 215–216 differential activity of, 209–210, 212 DPCPX ligand and, 202–203, 205 GABAergic projection neurons and, 200–201, 208 G-proteins and, 204, 206, 207 IHC and, 200, 201 NMDA and, 201, 208, 224, 225 PET and, 200, 202 properties of, 198, 199 radioligands, in study of, 200, 201 sodium channels and, 208, 209 transcripts of, 197 variants of, 196–200 Adenosine triphosphate (ATP), adenosine, brain function and, 193, 194, 195, 209, 237, 239 Adenylyl cyclase, ARs and, 196–197 ADHD. See Attention-deficit/hyperactivity disorder Affymetrix, in gene expression, 43, 44, 45, 60, 64, 69 Afterhyperpolarization period (AHP), in drug addiction, 106, 111 Agonal state, in postmortem brain, gene expression and, 49–51, 52, 53 Agonists/antagonists, in study of AR, 202–204 AHP. See Afterhyperpolarization period Alzheimer’s disease (AD), 43 adenosine, brain function and, 207–239 brain profiling and, 43, 49, 59–62 NFTs and, 59–61 SE comparison to, 168–169, 174, 182, 183 substance abuse, gene expression and, 55–57 Amphetamines drug addiction and, 110, 112, 115, 117, 118, 121, 122, 125 knockout mice affected by, 222 mapping neuroreceptors and, 16

Amyloid deposits adenosine/brain function and, 207, 233 in SE, 156, 168–169, 174, 176, 178, 183 Analysis, model-dependent, in mapping neuroreceptors, 1, 3 Animal models in ICSS/drug addiction, 118–119 place conditioning/drug addiction and, 119–120 in SE, 156, 160–164, 167, 168, 170, 172–176, 178–180, 182 self-administration/drug addiction and, 115–118, 130 Anti-PrPsc antibodies, in SE, 158–163, 180–181 Apoptosis, gene expression, in SZ/AD and, 43, 51, 53, 60, 61 AR. See Adenosine receptors Asterocytes, bipolar disorder and, 28 Astrocytes, adenosine, brain function and, 194–196, 200, 201–202, 205, 210–211, 226 A-to-I editing, pre-mRNA enzymes/substrates, in serotonin 2C receptor regulation, 86–87 in serotonin 2C receptor regulation, 87–88 ATP. See Adenosine triphosphate Attention-deficit/hyperactivity disorder (ADHD), mapping neuroreceptors, 7, 9, 18, 19 Autoimmune diseases, SE and, 157, 162–166, 168–173, 175, 177–178, 180–182 B Base conversions, 84 deamination/methylation interaction in, 97 deaminations, of adenosine and, 84–85 Benzodiazepine receptors, in mapping neuroreceptors, 5, 15 B/F ratio. See Bound/free molecule ratio Binding constants, in mapping neuroreceptors, 5, 6 Binding potentials changes in, 17–19 in mapping neuroreceptors, 7–11, 13 Biomolecular studies, on drug addiction, 121–123, 130 Bipolar disorder. See also Mitochondrial dysfunction, in bipolar disorder

INDEX

asterocyte dysfunction and, 28 gene expression, in SZ/AD and, 49 lithium treatment of, 24, 25 mapping neuroreceptors and, 14 mRNA expression in, 32 polymorphism and, 29 VFT and, 27 Blockade approach ARs and, 207, 215, 217, 218–220, 225–227, 230–232, 239 to mapping neuroreceptors, 4, 7 Bound/free molecule (B/F) ratio, in mapping neuroreceptors, 4, 10, 19 Bovine spongiform encephalopathies (BSE), 155, 162, 175–176, 178, 179, 182 Brain/CNS lesions, in SE, 158, 163–165, 170, 172–174, 178, 183 BSE. See Bovine spongiform encephalopathies C Caffeine adenosine/brain function and, 192, 218–220, 235–236 ARs and, 196–197 knockout mice and, 217, 218–220, 221–222 Calcium channels, ARs and, 208, 209 Calcium dependent mechanisms, in drug addiction, 107 Calcium regulation cardiolipin and, 33 mitochondrial dysfunction and, 33–34 cAMP pathways. see Cyclic adenosine monophosphate pathways cAMP-dependent cascade, in drug addiction, 114 cAMP-PKA dependent pathway, in drug addiction, 122 Candidate genes in drug addiction, 122 in gene expression, 43, 47, 60, 62 Cannabinoids/THC, drug addiction and, 107, 110, 111, 113, 114, 117, 119, 121, 125, 126 Cardiolipin, calcium regulation and, 33 cDNA microarray methods, in gene expression, in SZ/AD, 42, 43, 44, 60, 66, 67 Cerebrovascular responses, mitochondrial dysfunction and, 26–27 Cholinergic regulation, in drug addiction, 109

273

Chronic progressive external opthalmoplegia (CPEO), 24–25, 29, 31 CJD. See Creutzfeldt-Jakob disease Clozapine, in serotonin 2C receptor regulation, 91–93 Clustering techniques in gene expression, 45–47, 60 hierarchical v. non-hierarchical, 46 SOM/SOTA algorithms in, 46–47 CNS inflammation, in SE, 163, 171–172, 178, 181, 183 Cocaine, drug addiction and, 110, 112, 115, 117–123, 125–128 Constitutive activity, in serotonin 2C receptor regulation, 90, 91 Covalent chemical modifications, in SE, 158–159, 164, 165–166, 173–174, 180 CPEO. See Chronic progressive external opthalmoplegia Cr. See Creatine Craving, in drug addiction, 103, 114, 117 Creatine (Cr), mitochondrial dysfunction and, 23–24, 26 Creutzfeldt-Jakob disease (CJD), SE and, 156, 164, 166, 177–179 Cross-reactivity, in SE, 159, 162, 171, 174, 179, 180 Cyclic adenosine monophosphate (cAMP) pathways, adenosine/brain function and, 193, 198, 199, 204–205, 210, 215, 226, 232 Cytokines/receptors, adenosine/brain function and, 206, 211, 227 D DA. See Dopamine DARPP-32. See Dopamine/cAMP regulated phosphoprotein Data-mining strategies, in microarray gene expression, 44–48 Depression, serotonin 2C receptor regulation and, 96–97 Diagnosis, treatment, of SE, 180–181, 182–183 Displacement approach, mapping neuroreceptors and, 5 DLPFC. See Dorsolateral prefrontal cortex Dopamine (DA). See also Dopamine receptors; Drug addiction, dopamine hypothesis D2 receptors/drug addiction and, 112, 115, 121, 122, 126–128, 129, 130

274

INDEX

Dopamine (DA). See also Dopamine receptors; Drug addiction, dopamine hypothesis (cont.) mapping neuroreceptors and, 14, 15, 16, 17, 19 Dopamine receptors (DR) adenosine receptors, interactions with, 212–213 AR interactions and, 212–216, 220 ARs, direct interactions with, 212–213 DARPP-32, ARs and, 215–216 excitatory role, of adenosine with, 214–215 gene expression and, 54, 55 in mapping neuroreceptors, 1, 2, 5, 6, 7, 8, 12, 19 Dopamine/cAMP regulated phosphoprotein (DARPP-32), adenosine, brain function and, 212–213, 215–216 Dopaminergic transmission, in drug addiction, 117, 126, 128, 129 Dorsolateral prefrontal cortex (DLPFC), in SZ/AD, 58, 63, 64, 65, 66, 67 Double strand RNA (dsRNA) in RNA interference pathway, 85 in serotonin 2C receptor regulation, 84, 85, 86, 87 DPCPX ligand, in study of ARs, 202–203, 205 Drosphila studies, in serotonin 2C receptor regulation, 84, 86 Drug action, in serotonin 2C receptor regulation, 91–93 Drug addiction, dopamine hypothesis AHPs and, 106, 111 amphetamines in, 110, 112, 115, 117, 118, 121, 122, 125 animal models, ICSS in, 118–119 animal models/place conditioning in, 119–120 animal models/self-administration, 115–118, 130 biochemical studies/biomolecular in, 121–123, 130 biochemical studies/microanatomical in, 123–125, 130 biochemical studies/microdialysis in, 120–121, 130 as brain disease, 102–105 calcium dependent mechanisms in, 107 cannabinoids/THC in, 107, 110, 111, 113, 114, 117, 119, 121, 125, 126

cocaine in, 110, 112, 115, 117–123, 125–128 craving in, 103, 114, 117 dopamine D2 receptors in, 112, 115, 121, 122, 126–128, 129, 130 dopaminergic transmission in, 117, 126, 128, 129 ethanol in, 110, 111, 113–114, 116–118, 120, 121, 122, 125–128 GABA in, 109, 111, 113, 114, 129 GABAergic regulation in, 106, 108–109, 111 5-HT in, 109, 110 ICSS in, 103–104, 118–119, 130 mesolimbic DA neurons in, 103, 105–115 morphine in, 110, 111, 113, 114, 117, 118, 121, 123, 124, 125, 128 NAcc in, 103, 104, 107, 108, 111, 113, 115, 118, 121–123, 124, 125–127, 129 neurobiological mechanisms in, 103–105 nicotine/receptors in, 109–115, 117, 119–122, 125 primate studies/human in, 127–130 primate studies/non-human in, 126–127 psychostimulants in, 110, 112, 117, 125, 127, 128 regulation, cholinergic in, 109 regulation, glutametergic in, 108 regulation, noradrenergic in, 109–110 regulation, serotonergic in, 109 responses, to acute drugs in, 110–112 responses, to chronic drugs in, 112–113 reward stimulus and, 103–105, 109, 110, 112, 117–119, 126, 127 spiny neurons and, 123, 124, 125 striatum in, 122, 128 TH+ in, 104–105 VTA DA neurons in, 103, 106–115, 118–120, 123–125, 129 withdrawal, acute drugs in, 113, 114, 117, 118–121, 124, 125, 127 withdrawal and, 104, 112–114, 117–119, 121, 123, 128, 129, 130 withdrawal, chronic drugs and, 103, 105, 113–115, 120 Drug addiction studies. See also Drug addiction, dopamine hypothesis PET and, 127 dsRNA. See double strand RNA

INDEX

E ECS. See Editing site complementary sequence Ectonucleotidase pathways, adenosine/in brain function and, 193, 194, 195 Editing site complementary sequence (ECS), serotonin 2C receptor and, 87 Endoplasmic reticulum, in SE, role of, 167 ENT-1. See Equilabrative nucleoside transporter Epilepsy, adenosine/brain function and, 207, 238–240 Equilabrative nucleoside transporter (ENT-1), adenosine/brain function and, 193–194 Ethanol adenosine/brain function and, 221–222 drug addiction and, 110, 111, 113–114, 116–118, 120, 121, 122, 125–128 knockout mice, in adenosine studies and, 221 Excitatory action, of adenosine, 194, 201, 208, 213–216, 221, 224, 226 Excitotoxicity model, adenosine/brain function and, 223–227, 229, 232 Exocytotic apparatus, adenosine/brain function and, 192–194, 227 F Fatal familial insomnia (FFI), SE and, 179–180 FDG. See Fluorodeoxyglucose FFI. See Fatal familial insomnia Flumazenil, in mapping neuroreceptors, 5, 14, 15 Fluorodeoxyglucose (FDG), 3 Fluoxetine, in serotonin 2C receptor regulation, 91–93 G GABA in adenosine/brain function, 199, 200–201, 208, 210, 213, 214, 215, 230, 232, 235, 237 drug addiction and, 109, 111, 113, 114, 129 GABA receptors, gene expression, in SZ/AD and, 57, 65 GABAergic regulation, in drug addiction, 106, 108–109, 111 Gene expression, in schizophrenia/Alzheimer’s disease AD brain profiling and, 43, 49, 59–62 Affymetrix and, 43, 44, 45, 60, 64, 69

275

agonal state, in postmortem brain and, 49–51, 52, 53 apoptosis and, 43, 51, 53, 60, 61 candidate genes and, 43, 47, 60, 62 classic approach to, 42–43 clustering techniques in, 45–47, 60 data reproducibility in, 48–49 data-mining strategies for, 44–48 DLPFC in, 58, 63, 64, 65, 66, 67 expression pattern approach to, 41–42 future perspectives for, 63–68 GABA receptors in, 57, 65 microarray-based technology and, 42–44, 45–48, 59–62, 64, 66–68 normal brain function v., 57–59 PCR and, 44, 45, 48, 52, 64 PMI, in postmortem brain and, 51 postmortem brains used in, 49–50 potential experimental errors in, 48–49, 52, 56–57 SAGE and, 42 sample fixation/storage in, 52 sample pH and, 52–53 sample preparation in, 49–50 in situ hybridization and, 50, 52, 57 structural approach to, 41–42 subject age at death and, 53–54 subject gender and, 54 subject medication/substance abuse and, 55–57 SZ brain profiling and, 43, 49, 63–68 Gene ontology (GO), gene expression, in SZ/AD and, 47–48 Gerstmann-Straussler-Scheinker syndrome (GGS), SE and, 179–180 GGS. See Gerstmann-Straussler-Scheinker syndrome Gliosis, SZ and, 53, 63, 65, 68 GluR-B gene, serotonin 2C receptor regulation and, 85 Glutamate release, in brain function, 226, 227–228, 232, 233 Glutametergic regulation, in drug addiction, 108 GO. See Gene ontology G-proteins adenosine/brain function and, 198, 204, 206, 207, 213, 223, 224, 233 ARs and, 204, 206, 207 in serotonin 2C receptor regulation, 83–85, 88–91, 94, 95

276

INDEX

H Half-inhibition constant (IC50), in mapping neuroreceptors, 11–12, 13, 14 Haloperidol, in mapping neuroreceptors, 6, 7, 11, 13–14 Hamilton Depression Rating Scale, 24 Heterodimerization, of AR/DR, 213–214 Hippocampus, adenosine/brain function and, 198, 200, 207, 216, 217, 224, 225, 232, 236, 239–240 5-HT, drug addiction and, 109, 110 Human subjects, in SE, 156, 157, 163, 164, 167, 169, 172, 175–180 Huntington’s disease, adenosine and, 224, 229, 232–233 5-Hydroxytryptamine 2C (5-HT2c). See Serotonin 2C Hypoxia, adenosine and, 192, 193, 199, 206, 217, 223, 224

amphetamine effects in, 222 analgesic effects, of adenosine in, 217 anxiety in, 219, 223 caffeine effects on, 217, 218–220, 221–222 catalepsy and, 220 cocaine effects in, 222 depressant challenge and, 220 ethanol and, 221 exploratory behavior in, 217 hypothermia and, 216 hypoxia effects in, 217, 222 ischemia effects in, 217, 222 life span of, 218 light-dark box test in, 216–217, 223 locomotor activity in, 216, 217, 219, 222 memory in, 218 Morris water-maze test in, 218 pain stimuli in, 222, 223 subtypes of, 216 KSS. See Kearns-Sayre syndrome

I

L

ICSS. See Intracranial self-stimulation IHC. See Immunohistochemistry Immunogenicity, in SE, 168–169, 174, 175 Immunohistochemistry (IHC), ARs and, 200, 201 In situ hybridization, gene expression, in SZ/AD and, 50, 52, 57 Inflammation modulation, by adenosine, 206, 224, 227, 232 Inflammatory reactions, of adenosine/brain function, 211, 227–228, 229, 241 Inoculation experiments, SE and, 162, 164–165, 170–175 Intracranial self-stimulation (ICSS), in drug addiction, 103–104, 118–119, 130 Ischemia/models adenosine/brain function and, 192, 206, 211, 217, 222, 223, 225–228, 229, 232, 240 in knockout mice, 217, 222

L-DOPA, adenosine/brain function and, 230–231 Lithium treatment, in bipolar disorder, mitochondrial dysfunction and, 24, 25, 29 Lymphoid cells, in SE, 160–161, 164, 167, 168–171, 181, 183 Lysosomes, in SE, 157, 163, 164, 167, 174, 180

K Kearns-Sayre syndrome (KSS), 29, 30 Kinetic interactions, in mapping neuroreceptors, 1, 4–5 Knockout mice, in adenosine studies, 193–194 aggression in, 218, 219–220

M Magnetic resonance imaging (MRI), in mapping neuroreceptors, 8 Magnetic resonance spectroscopy (MRS), in mitochondrial dysfunction, 22–23 MALT. See Mucosal-associated lymphoid tissue Mapping neuroreceptors, 1, 2 ADHD and, 7, 9, 18, 19 analysis/model-dependent in, 1, 3 benzodiazepine receptors and, 5, 15 B/F ratio in, 4, 10, 19 binding constants in, 5, 6 binding potential changes in, 17–19 binding potentials in, 7–11, 13 blockade approach to, 4, 7 displacement approach to, 5 dopamine receptors and, 1, 2, 5, 6, 7, 8, 12, 19 experimental considerations in, 8–9

INDEX

IC50 in, 11–12, 13, 14 kinetic interactions in, 1, 4–5 Michaelis-Menten solution in, 5, 6, 8–9, 11–14, 17 MRI in, 8 neurotransmitters/endogenous in, 7, 12, 14, 16, 17, 18 NMSP receptors and, 1, 2, 5, 7, 13, 14 non-steady state sensitivity in, 14–17 PET in, 1, 3, 4, 5, 15 radioligands in, 1, 2, 3, 4, 7–11, 12, 13 serotonin receptors and, 1, 2, 6, 7, 8 steady-state disruption in, 15, 16, 17 steady-state volume/distribution in, 4, 5, 6 striatum and, 7, 10, 11, 12, 16 substrates, radiolabeled in, 1 MBM. See Meat/bone meal Meat/bone meal (MBM), in SE, 176, 179, 181 MELAS syndrome, bipolar disorder and, 25, 29, 31 Membrane phospholipids, mitochondrial dysfunction and, 23–24 MERRF syndrome, bipolar disorder and, 29 Mesolimbic DA neurons, in drug addiction, 103, 105–115 Mesolimbic dopamine system. See Drug addiction, dopamine hypothesis Messenger RNA (mRNA) expression, in bipolar disorder, 32 expression, in SZ/AD, 43–45, 50, 52–54, 56, 60, 64, 66 Methylphenidate, in mapping neuroreceptors, 7, 9, 18, 19 Michaelis-Menten solution. See also Kinetic Interactions in mapping neuroreceptors, 5, 6, 8–9, 11–14, 13, 17 Microanatomical studies, on drug addiction, 123–125, 130 Microarray-based technology cDNA methods in, 42, 43, 44, 60, 66, 67 in drug addiciton studies, 122–123 in gene expression, 42–44, 45–50, 59–62, 64, 66–68 RMA and, 45, 49 Microdialysis studies, in drug addiction, 120–121, 130 Microglia, in brain function, 200–202, 205, 211 Mitochondrial DNA (mtDNA) deletions in, 30–31

277

heteroplasmic point mutations in, 31–32 nuclear deletions in, 31 polymorphisms in, 29–30 Mitochondrial dysfunction, in bipolar disorder. See also Bipolar disorder 1 H-MRS findings on, 26 astrocyte dysfunction and, 28 calcium regulation, role in, 33–34 cerebrovascular responses in, 26–28 membrane phospholipids and, 23–24 molecular genetics in, 28–32 monoaminergic dysfunction and, 21–22 mRNA expression in, 32 mtDNA deletions in, 30–31 mtDNA heteroplasmic point mutations in, 31–32 mtDNA nuclear deletions in, 31 mtDNA polymorphisms in, 29–30 near-infrared spectroscopy in, 26–28 neuroimaging and, 22 neuroplasticity and, 33, 34 nuclear encoded mitochondrial genes in, 32 PCr and, 23–24, 26 pH/intracellular and, 25–26 phosphoinositide pathway and, 23–24 phosphorus-31 MRS and, 22–23, 28 PME and, 23–26 Monoaminergic dysfunction, mitochondrial dysfunction and, 21–22 Morphine, drug addiction and, 110, 111, 113, 114, 117, 118, 121, 123, 124, 125, 128 MRI. See Magnetic resonance imaging mRNA. See Messenger RNA mRNA expression, in bipolar disorder, 32 MRS. See Magnetic resonance spectroscopy mtDNA. See Mitochondrial DNA Mucosal-associated lymphoid tissue (MALT), in SE, 160 Mutation linkage, to SE, 180 N N-methyl D-aspartate (NMDA), adenosine receptors and, 110, 208, 224, 225 N-[11C]methylspiperone (NMSP), in mapping neuroreceptors, 1, 2, 5, 7, 13, 14 NAA, See N–acetyl aspartate NAcc. See Nucleus accumbens N-acetyl aspartate (NAA), in mitochondrial dysfunction, 26

278 Near-infrared spectroscopy (NIRS), mitochondrial dysfunction and, 26–28 Neurofibrillary tangles (NFT), in AD, 59–61 Neuromodulation, in brain function, 207, 210–212, 217 Neuronal death, in SE, 163, 165, 167, 183 Neuroprotective effect, of receptors, adenosine/brain function and, 223–228, 229 Neuroreceptors. See Mapping neuroreceptors Neurotransmitter release, in adenosine function, 192–193, 204, 205, 208–211, 213 Neurotransmitters, endogenous, in mapping neuroreceptors, 7, 12, 14, 16, 17, 18 NFT. See Neurofibrillary tangles Nicotine/nicotine receptors, in drug addiction, 109–115, 117, 119–122, 125 NIRS. See Near-infrared spectroscopy NMDA, See N–methyl D–aspartate NMSP. See N-[11C]methylspiperone Noradrenergic regulation, in drug addiction, 109–110 Northern blot analysis, 52 Nuclear encoded mitochondrial genes, mitochondrial dysfunction and, 32 Nucleoside transporter mechanism, adenosine/ brain function and, 193, 239 Nucleus accumbens (NAcc), in drug addiction, 103–104, 107–108, 111, 113, 115, 118, 121–123, 124, 125–127, 129 Null mice, in SE research, 162–163, 170–171 O Opiates/opiate receptors, in drug addiction, 117–122, 126, 128 P Pain, adenosine/brain function and, 199, 217, 220, 222, 240–241 Parent-of-origin effect (POE), in mitochondrial dysfunction, 28, 29 Parkinson’s disease and, adenosine function in, 199, 201–202, 207, 215, 220, 228–232 Pathogenesis, of SE, 156, 158, 160, 163, 165–170, 173–175, 177–179, 182

INDEX

Pathology, of SE, 156, 165, 171, 178 Patient age, in SE, 178 PCR. See Polymerase chain reaction PCr. See Phosphocreatine Pearson’s syndrome, 29, 30 PET. See Positron emission tomography Phosphocreatine (PCr), mitochondrial dysfunction and, 23–24, 26 Phosphoinositide pathway, mitochondrial dysfunction and, 23–24 Phosphomonoester (PME), in mitochondrial dysfunction, 23–26 Phosphorus-31 Magnetic resonance spectroscopy (MRS). See Magnetic resonance spectroscopy PME. See Phosphomonoester PMI. See Postmortem interval POE. See Parent-of-origin effect Polymerase chain reaction (PCR), 30–31 gene expression, in SZ/AD and, 44, 45, 48, 52, 64 RFLP and, 32 Positron emission tomography (PET) adenosine receptors and, 200, 202 in drug addiction studies, 127 in mapping neuroreceptors, 1, 3, 4, 5, 15 Postmortem interval (PMI), in SZ/AD, 51 PPI. See Prepulse inhibition Prepulse inhibition (PPI), in adenosine, brain function, 221, 234–235 Primate studies, in drug addiction human, 127–130 non-human, 126–127 Prion protein (PrP) antibody-mediated conversion, in SE and, 157, 158, 159, 167, 168, 178, 182 configuration, in SE and, 156, 157, 158–162, 164–166, 173, 175, 176, 180, 182 Prion protein, celluar (PrPc), accumulation in SE, 158–160 Prion protein, disease causing (PrPsc), accumulation, in SE, of, 157, 158, 160, 162–165, 167, 168, 171, 173, 179, 182 Prions, 156, 157, 158, 164–169, 171, 172–173, 180, 182. See also Spongiform encephalopathies (SE), new theory

INDEX

multiple strains, in SE, 168, 172–174 protease resistance, in SE, 157, 160, 163, 164, 167, 168, 174, 177, 180, 183 replication process, in SE and, 156, 166, 167–168 resistance, to SE and, 169–170, 176 Protease resistance, in SE, 157, 160, 163, 164, 167, 168, 174, 177, 180, 183 Proteinaceous deposits, in SE, 160, 166–167 Prozac. See Fluoxetine PrP. See Prion protein PrP antibody-mediated conversion, in SE, 157, 158, 159, 167, 168, 178, 182 PrPc. See Prion protein, celluar PrPsc. See Prion protein, disease causing Psychostimulants, in drug addiction, 110, 112, 117, 125, 127, 128 R Raclopride in drug addiction studies, 127–128 in mapping neuroreceptors, 7, 8, 9, 11, 12, 13, 16 Radioligands, in AR studies, 200, 201 Radioligands, positron-emitting, in mapping neuroreceptors, 1, 2, 3, 4, 7–11, 12, 13 Receptor expression/signaling, in adenosine, brain function, 205–207 Restriction fragment length polymorphism (RFLP), 32 Reward stimulus, drug addiction and, 103–105, 109, 110, 112, 117–119, 126, 127 RFLP. See Restriction fragment length polymorphism Ribosomal RNA (rRNA), 49–50, 52 RNA interference pathway, dsRNA in, 85 Robust multiarray average (RMA), 45, 49 rRNA. See Ribosomal RNA S SAGE. See Serial analysis of gene expression Schizophrenia (SZ). See also Gene expression, in schizophrenia/Alzheimer’s disease

279

adenosine in, 202, 220–221, 234–235 brain profiling and, 43, 49, 63–68 gliosis and, 53, 63, 65, 68 mapping neuroreceptors and, 14 substance abuse, in gene expression and, 55–57 Scrapie, in sheep, SE and, 155, 156, 173, 175, 176, 179 SE. See Spongiform encephalopathies Serial analysis of gene expression (SAGE), in SZ/AD, 42 Serological indicators, of SE, 172, 181 Serotonergic regulation,, in drug addiction, 109 Serotonin 2C (5-HT2c) receptor regulation. See also Serotonin receptors ADARs and, 86–88 A-to-I editing, pre mRNA, 87–88 base conversions and, 84 Caenorhabditis studies and, 84, 86 constitutive activity and, 90, 91 deamination/methylation interaction in, 97 deaminations, of adenosine and, 84–85 in depression, 96–97 Drosphila studies and, 84, 86 drugs affecting, 91–93 dsRNA in, 84, 85, 86, 87 ECS and, 84 enzyme/substrates, in A-to-I editing, 86–87 GluR-B gene and, 85 G-protein in, 83–85, 88–91, 94, 95 inosines in, 84 modulation of function in, 88–91, 96–97 mRNA isoforms of, 83, 89, 94 pre-mRNA editing, in depression and, 93–97 pre-mRNA editing/neurotransmission and, 91–93 serotonin dependent activity in, 96–97 in suicides, 95–96 in SZ, 94, 95–96 tRNA, cytoplasmic and, 84 Serotonin receptors gene expression and, 54, 55 mapping neuroreceptors and, 1, 2, 6, 7, 8 Signaling, adenosine/brain function and, 193, 204–205, 207, 208, 211, 213, 215, 216, 226, 230

280

INDEX

Sleep-wake cycles, adenosine/brain function and, 217, 221, 236–238 Sodium channels, ARs and, 208, 209 SOM/SOTA algorithms, clustering techniques and, 46–47 Southern blot analysis, 30 Species barriers, in SE, 162, 173–175 Spiny neurons, in drug addiction, 123, 124, 125 Spiperone, in mapping neuroreceptors, 10, 11, 13 Spongiform encephalopathies (SE), new theory, 155–158. See also Prions amyloid deposits in, 156, 168–169, 174, 176, 178, 183 in animals, 156, 160–164, 167, 168, 170, 172–176, 178–180, 182 anti-PrPsc antibodies in, 158–163, 180–181 as autoimmune diseases, 157, 162–166, 168–173, 175, 177–178, 180–182 AZ comparison to, 168–169, 174, 182, 183 brain/CNS lesions in, 158, 163–165, 170, 172–174, 178, 183 BSE and, 155, 162, 175–176, 178, 179, 182 CJD/vCJD and, 156, 164, 166, 177–179 CNS inflammation in, 163, 171–172, 178, 181, 183 covalent modifications in, 158–159, 164, 165–166, 173–174, 180 cross-reactivity in, 159, 162, 171, 174, 179, 180 diagnosis, treatment of, 180–181, 182–183 endoplasmic reticulum role in, 167 FFI and, 179–180 GGS and, 179–180 glycosylation reactions and, 158, 159, 165–167, 173–174 in humans, 156, 157, 163, 164, 167, 169, 172, 175–180 immunogenicity in, 168–169, 174, 175 infection process, 157 inoculation experiments with, 162, 164–165, 170–175 lymphoid cell role in, 160–161, 164, 167, 168–171, 181, 183 lysosomes in, 157, 163, 164, 167, 174, 180 MALT in, 160 MBM and, 176, 179, 181 mutation linkage to, 180

neuronal death and, 163, 165, 167, 183 origins of, 178–179, 181, 182 pathogenesis of, 156, 158, 160, 163, 165–170, 173–175, 177–179, 182 pathology of, 156, 165, 171, 178 patient age and, 178 prevention of, 181–182 prion multiple strains in, 168, 172–174 prions in, 156, 157, 158, 164–169, 171, 172–173, 180, 182 protease resistance in, 157, 160, 163, 164, 167, 168, 174, 177, 180, 183 proteinaceous deposits and, 160, 166–167 PrP antibody-mediated conversion in, 157, 158, 159, 167, 168, 178, 182 PrP configuration and, 156, 157, 158–162, 159, 161, 164–166, 173, 175, 176, 180, 182 PrP null mice in, 162–163, 170–171 PrPc accumulation in, 158–160 PrPsc accumulation in, 157, 158, 160, 162–165, 167, 168, 171, 173, 179, 182 replication process in, 156, 166, 167–168 resistance to, 169–170, 176 scrapie in sheep and, 155, 156, 173, 175, 176, 179 serological indicators of, 172, 181 species barriers in, 162, 173–175 transgenic mice and, 170–171 Striatum in adenosine/brain function, 200–201, 204, 207, 208, 213–216, 218, 222, 224, 226, 227, 231, 232–233, 236 in drug addiction studies, 122, 128 mapping neuroreceptors and, 7, 10, 11, 12, 16 Substance abuse, gene expression, in SZ/AD and, 55–57 Substance abuse, in gene expression, SZ and, 55–57 SZ. See Schizophrenia T TH+. See Tyrosine hydroxylase-positive Transfer RNA (tRNA), cytoplasmic, in 5-HT2c receptor regulation and, 84 Transgenic mice, in SE research, 170–171

INDEX

tRNA. See transfer RNA Tyrosine hydroxylase-positive (TH+), in drug addiction, 104–105 V Ventral tegmental area (VTA), DA neurons/ drug addiction and, 103, 106–115, 118–120, 123–125, 129 Verbal fluency task (VFT), 27 VFT. See Verbal fluency task VTA. See Ventral tegmental area

281

W White matter, in knockout mice, 217 White matter hyperintensity (WMH), 26, 27 Withdrawal, from drug addiction, 104, 112–114, 117–119, 121, 123, 128, 129, 130 acute drugs and, 113, 114, 117, 118–121, 124, 125, 127 chronic drugs and, 103, 105, 113–115, 120 WMH. See White matter hyperintensity Wolfram syndrome, 31

CONTENTS OF RECENT VOLUMES

Volume 37

Memory and Forgetting: Long-Term and Gradual Changes in Memory Storage Larry R. Squire

Section I: Selectionist Ideas and Neurobiology in

Implicit Knowledge: New Perspectives on Unconscious Processes Daniel L. Schacter

Population Thinking and Neuronal Selection: Metaphors or Concepts? Ernst Mayr

Section V: Psychophysics, Psychoanalysis, and Neuropsychology

Selectionist and Neuroscience Olaf Sporns

Instructionist

Ideas

Selection and the Origin of Information Manfred Eigen

Phantom Limbs, Neglect Syndromes, Repressed Memories, and Freudian Psychology V. S. Ramachandran

Section II: Populations

Neural Darwinism and a Conceptual Crisis in Psychoanalysis Arnold H. Modell

Development

and

Neuronal

Morphoregulatory Molecules and Selectional Dynamics during Development Kathryn L. Crossin

A New Vision of the Mind Oliver Sacks

Exploration and Selection in the Early Acquisition of Skill Esther Thelen and Daniela Corbetta

index

Population Activity in the Control of Movement Apostolos P. Georgopoulos

Volume 38

Section III: Functional Integration in the Brain

Segregation

and

Reentry and the Problem of Cortical Integration Giulio Tononi Coherence as an Organizing Principle of Cortical Functions Wolf Singerl

Regulation of GABAA Receptor Function and Gene Expression in the Central Nervous System A. Leslie Morrow Genetics and the Organization of the Basal Ganglia Robert Hitzemann, Yeang Olan, Stephen Kanes, Katherine Dains, and Barbara Hitzemann

Section IV: Memory and Models

Structure and Pharmacology of Vertebrate GABAA Receptor Subtypes Paul J. Whiting, Ruth M. McKernan, and Keith A. Wafford

Selection versus Instruction: Use of Computer Models to Compare Brain Theories George N. Reeke, Jr.

Neurotransmitter Transporters: Biology, Function, and Regulation Beth Borowsky and Beth J. Hoffman

Temporal Mechanisms in Perception Ernst Po¨ppel

283

Molecular

284

CONTENTS OF RECENT VOLUMES

Presynaptic Excitability Meyer B. Jackson

Volume 40

Monoamine Neurotransmitters in Invertebrates and Vertebrates: An Examination of the Diverse Enzymatic Pathways Utilized to Synthesize and Inactivate Biogenic Amines B. D. Sloley and A. V. Juorio

Mechanisms of Nerve Cell Death: Apoptosis or Necrosis after Cerebral Ischemia R. M. E. Chalmers-Redman, A. D. Fraser, W. Y. H. Ju, J. Wadia, N. A. Tatton, and W. G. Tatton

Neurotransmitter Systems in Schizophrenia Gavin P. Reynolds

Changes in Ionic Fluxes during Cerebral Ischemia Tibor Kristian and Bo K. Siesjo

Physiology of Bergmann Glial Cells Thomas Mu¨ ller and Helmut Kettenmann

Techniques for Examining Neuroprotective Drugs in Vitro A. Richard Green and Alan J. Cross

index Volume 39

Techniques for Examining Neuroprotective Drugs in Vivo Mark P. Goldberg, Uta Strasser, and Laura L. Dugan

Modulation of Amino Acid-Gated Ion Channels by Protein Phosphorylation Stephen J. Moss and Trevor G. Smart

Calcium Antagonists: Their Role in Neuroprotection A. Jacqueline Hunter

Use-Dependent Regulation Receptors Eugene M. Barnes, Jr.

GABAA

Sodium and Potassium Channel Modulators: Their Role in Neuroprotection Tihomir P. Obrenovich

Synaptic Transmission and Modulation in the Neostriatum David M. Lovinger and Elizabeth Tyler

NMDA Antagonists: Their Role in Neuroprotection Danial L. Small

The Cytoskeleton and Neurotransmitter Receptors Valerie J. Whatley and R. Adron Harris

Development of the NMDA Ion-Channel Blocker, Aptiganel Hydrochloride, as a Neuroprotective Agent for Acute CNS Injury Robert N. McBurney

Endogenous Opioid Regulation of Hippocampal Function Michele L. Simmons and Charles Chavkin

The Pharmacology of AMPA Antagonists and Their Role in Neuroprotection Rammy Gill and David Lodge

Molecular Neurobiology of the Cannabinoid Receptor Mary E. Abood and Billy R. Martin

GABA and Neuroprotection Patrick D. Lyden

of

Genetic Models in the Study of Anesthetic Drug Action Victoria J. Simpson and Thomas E. Johnson Neurochemical Bases of Locomotion and Ethanol Stimulant Effects Tamara J. Phillips and Elaine H. Shen Effects of Ethanol on Ion Channels Fulton T. Crews, A. Leslie Morrow, Hugh Criswell, and George Breese index

Adenosine and Neuroprotection Bertil B. Fredholm Interleukins and Cerebral Ischemia Nancy J. Rothwell, Sarah A. Loddick, and Paul Stroemer Nitrone-Based Free Radical Traps as Neuroprotective Agents in Cerebral Ischemia and Other Pathologies Kenneth Hensley, John M. Carney, Charles A. Stewart, Tahera Tabatabaie, Quentin Pye, and Robert A. Floyd

CONTENTS OF RECENT VOLUMES

Neurotoxic and Neuroprotective Roles of Nitric Oxide in Cerebral Ischemia Turgay Dalkara and Michael A. Moskowitz

Sensory and Cognitive Functions Lawrence M. Parsons and Peter T. Fox

A Review of Earlier Clinical Studies on Neuroprotective Agents and Current Approaches Nils-Gunnar Wahlgren

Skill Learning Julien Doyon

index

Volume 41

Section V: Clinical and Neuropsychological Observations Executive Function and Motor Skill Learning Mark Hallett and Jordon Grafman

Section I: Historical Overview

Verbal Fluency and Agrammatism Marco Molinari, Maria G. Leggio, and Maria C. Silveri

Rediscovery of an Early Concept Jeremy D. Schmahmann

Classical Conditioning Diana S. Woodruff-Pak

Section II: Anatomic Substrates

Early Infantile Autism Margaret L. Bauman, Pauline A. Filipek, and Thomas L. Kemper

The Cerebrocerebellar System Jeremy D. Schmahmann and Deepak N. Pandya Cerebellar Output Channels Frank A. Middleton and Peter L. Strick Cerebellar-Hypothalamic Axis: Basic Circuits and Clinical Observations Duane E. Haines, Espen Dietrichs, Gregory A. Mihailoff, and E. Frank McDonald Section III. Physiological Observations Amelioration of Aggression: Response to Selective Cerebellar Lesions in the Rhesus Monkey Aaron J. Berman Autonomic and Vasomotor Regulation Donald J. Reis and Eugene V. Golanov Associative Learning Richard F. Thompson, Shaowen Bao, Lu Chen, Benjamin D. Cipriano, Jeffrey S. Grethe, Jeansok J. Kim, Judith K. Thompson, Jo Anne Tracy, Martha S. Weninger, and David J. Krupa

Olivopontocerebellar Atrophy and Friedreich’s Ataxia: Neuropsychological Consequences of Bilateral versus Unilateral Cerebellar Lesions The´re`se Botez-Marquard and Mihai I. Botez Posterior Fossa Syndrome Ian F. Pollack Cerebellar Cognitive Affective Syndrome Jeremy D. Schmahmann and Janet C. Sherman Inherited Cerebellar Diseases Claus W. Wallesch and Claudius Bartels Neuropsychological Abnormalities in Cerebellar Syndromes—Fact or Fiction? Irene Daum and Hermann Ackermann Section VI: Theoretical Considerations Cerebellar Microcomplexes Masao Ito

Visuospatial Abilities Robert Lalonde

Control of Sensory Data Acquisition James M. Bower

Spatial Event Processing Marco Molinari, Laura Petrosini, and Liliana G. Grammaldo

Neural Representations of Moving Systems Michael Paulin

Section IV: Functional Neuroimaging Studies Linguistic Processing Julie A. Fiez and Marcus E. Raichle

285

How Fibers Subserve Computing Capabilities: Similarities between Brains and Machines Henrietta C. Leiner and Alan L. Leiner

286

CONTENTS OF RECENT VOLUMES

Cerebellar Timing Systems Richard Ivry

Volume 43

Attention Coordination and Anticipatory Control Natacha A. Akshoomoff, Eric Courchesne, and Jeanne Townsend

Early Development of the Drosophila Neuromuscular Junction: A Model for Studying Neuronal Networks in Development Akira Chiba

Context-Response Linkage W. Thomas Thach

Development of Larval Body Wall Muscles Michael Bate, Matthias Landgraf, and Mar Ruiz Gmez Bate

Duality of Cerebellar Motor and Cognitive Functions James R. Bloedel and Vlastislav Bracha Section VII: Future Directions Therapeutic and Research Implications Jeremy D. Schmahmann

Volume 42 Alzheimer Disease Mark A. Smith Neurobiology of Stroke W. Dalton Dietrich Free Radicals, Calcium, and the Synaptic Plasticity-Cell Death Continuum: Emerging Roles of the Trascription Factor NFB Mark P. Mattson AP-I Transcription Factors: Short- and LongTerm Modulators of Gene Expression in the Brain Keith Pennypacker

Development of Electrical Properties and Synaptic Transmission at the Embryonic Neuromuscular Junction Kendal S. Broadie Ultrastructural Correlates of Neuromuscular Junction Development Mary B. Rheuben, Motojiro Yoshihara, and Yoshiaki Kidokoro Assembly and Maturation of the Drosophila Larval Neuromuscular Junction L. Sian Gramates and Vivian Budnik Second Messenger Systems Underlying Plasticity at the Neuromuscular Junction Frances Hannan and Yi Zhong Mechanisms of Neurotransmitter Release J. Troy Littleton, Leo Pallanck, and Barry Ganetzky Vesicle Recycling at the Drosophila Neuromuscular Junction Daniel T. Stimson and Mani Ramaswami Ionic Currents in Larval Muscles of Drosophila Satpal Singh and Chun-Fang Wu

Ion Channels in Epilepsy Istvan Mody

Development of the Adult Neuromuscular System Joyce J. Fernandes and Haig Keshishian

Posttranslational Regulation of Ionotropic Glutamate Receptors and Synaptic Plasticity Xiaoning Bi, Steve Standley, and Michel Baudry

Controlling the Motor Neuron James R. Trimarchi, Ping Jin, and Rodney K. Murphey

Heritable Mutations in the Glycine, GABAA, and Nicotinic Acetylcholine Receptors Provide New Insights into the Ligand-Gated Ion Channel Receptor Superfamily Behnaz Vafa and Peter R. Schofield

Volume 44

index

Human Ego-Motion Perception A. V. van den Berg Optic Flow and Eye Movements M. Lappe and K.-P. Hoffman

CONTENTS OF RECENT VOLUMES

The Role of MST Neurons during Ocular Tracking in 3D Space K. Kawano, U. Inoue, A. Takemura, Y. Kodaka, and F. A. Miles Visual Navigation in Flying Insects M. V. Srinivasan and S.-W. Zhang Neuronal Matched Filters for Optic Flow Processing in Flying Insects H. G. Krapp A Common Frame of Reference for the Analysis of Optic Flow and Vestibular Information B. J. Frost and D. R. W. Wylie Optic Flow and the Visual Guidance of Locomotion in the Cat H. Sherk and G. A. Fowler Stages of Self-Motion Processing in Primate Posterior Parietal Cortex F. Bremmer, J.-R. Duhamel, S. B. Hamed, and W. Graf Optic Flow Perception C. J. Duffy

Analysis

for

Self-Movement

Neural Mechanisms for Self-Motion Perception in Area MST R. A. Andersen, K. V. Shenoy, J. A. Crowell, and D. C. Bradley Computational Mechanisms for Optic Flow Analysis in Primate Cortex M. Lappe Human Cortical Areas Underlying the Perception of Optic Flow: Brain Imaging Studies M. W. Greenlee

287

Brain Development and Generation of Brain Pathologies Gregory L. Holmes and Bridget McCabe Maturation of Channels and Receptors: Consequences for Excitability David F. Owens and Arnold R. Kriegstein Neuronal Activity and the Establishment of Normal and Epileptic Circuits during Brain Development John W. Swann, Karen L. Smith, and Chong L. Lee The Effects of Seizures of the Hippocampus of the Immature Brain Ellen F. Sperber and Solomon L. Moshe Abnormal Development and Catastrophic Epilepsies: The Clinical Picture and Relation to Neuroimaging Harry T. Chugani and Diane C. Chugani Cortical Reorganization and Seizure Generation in Dysplastic Cortex G. Avanzini, R. Preafico, S. Franceschetti, G. Sancini, G. Battaglia, and V. Scaioli Rasmussen’s Syndrome with Particular Reference to Cerebral Plasticity: A Tribute to Frank Morrell Fredrick Andermann and Yuonne Hart Structural Reorganization of Hippocampal Networks Caused by Seizure Activity Daniel H. Lowenstein Epilepsy-Associated Plasticity in gammaAmniobutyric Acid Receptor Expression, Function and Inhibitory Synaptic Properties Douglas A. Coulter

What Neurological Patients Tell Us about the Use of Optic Flow L. M. Vaina and S. K. Rushton

Synaptic Plasticity and Secondary Epileptogenesis Timothy J. Teyler, Steven L. Morgan, Rebecca N. Russell, and Brian L. Woodside

index

Synaptic Plasticity in Epileptogenesis: Cellular Mechanisms Underlying Long-Lasting Synaptic Modifications that Require New Gene Expression Oswald Steward, Christopher S. Wallace, and Paul F. Worley

Volume 45 Mechanisms of Brain Plasticity: From Normal Brain Function to Pathology Philip. A. Schwartzkroin

Cellular Correlates of Behavior Emma R. Wood, Paul A. Dudchenko, and Howard Eichenbaum

288

CONTENTS OF RECENT VOLUMES

Mechanisms of Neuronal Conditioning David A. T. King, David J. Krupa, Michael R. Foy, and Richard F. Thompson

Biosynthesis of Neurosteroids and Regulation of Their Synthesis Synthia H. Mellon and Hubert Vaudry

Plasticity in the Aging Central Nervous System C. A. Barnes

Neurosteroid 7-Hydroxylation Products in the Brain Robert Morfin and Luboslav Sta´ rka

Secondary Epileptogenesis, Kindling, and Intractable Epilepsy: A Reappraisal from the Perspective of Neuronal Plasticity Thomas P. Sutula Kindling and the Mirror Focus Dan C. McIntyre and Michael O. Poulter Partial Kindling and Behavioral Pathologies Robert E. Adamec The Mirror Epileptogenesis B. J. Wilder

Focus

and

Secondary

Hippocampal Lesions in Epilepsy: A Historical Review Robert Naquet Clinical Evidence for Secondary Epileptogensis Hans O. Luders Epilepsy as a Progressive (or Nonprogressive ‘‘Benign’’) Disorder John A. Wada Pathophysiological Aspects of Landau-Kleffner Syndrome: From the Active Epileptic Phase to Recovery Marie-Noelle Metz-Lutz, Pierre Maquet, Annd De Saint Martin, Gabrielle Rudolf, Norma Wioland, Edouard Hirsch, and Chriatian Marescaux

Neurosteroid Analysis Ahmed A. Alomary, Robert L. Fitzgerald, and Robert H. Purdy Role of the Peripheral-Type Benzodiazepine Receptor in Adrenal and Brain Steroidogenesis Rachel C. Brown and Vassilios Papadopoulos Formation and Effects of Neuroactive Steroids in the Central and Peripheral Nervous System Roberto Cosimo Melcangi, Valerio Magnaghi, Mariarita Galbiati, and Luciano Martini Neurosteroid Modulation of Recombinant and Synaptic GABAA Receptors Jeremy J. Lambert, Sarah C. Harney, Delia Belelli, and John A. Peters GABAA-Receptor Plasticity during LongTerm Exposure to and Withdrawal from Progesterone Giovanni Biggio, Paolo Follesa, Enrico Sanna, Robert H. Purdy, and Alessandra Concas Stress and Neuroactive Steroids Maria Luisa Barbaccia, Mariangela Serra, Robert H. Purdy, and Giovanni Biggio

Local Pathways of Seizure Propagation in Neocortex Barry W. Connors, David J. Pinto, and Albert E. Telefeian

Neurosteroids in Learning and Processes Monique Valle´e, Willy Mayo, George F. Koob, and Michel Le Moal

Multiple Subpial Assessment C. E. Polkey

Neurosteroids and Behavior Sharon R. Engel and Kathleen A. Grant

Transection:

A

Clinical

The Legacy of Frank Morrell Jerome Engel, Jr. Volume 46 Neurosteroids: Beginning of the Story Etienne E. Baulieu, P. Robel, and M. Schumacher

Memory

Ethanol and Neurosteroid Interactions in the Brain A. Leslie Morrow, Margaret J. VanDoren, Rebekah Fleming, and Shannon Penland Preclinical Development of Neurosteroids as Neuroprotective Agents for the Treatment of Neurodegenerative Diseases Paul A. Lapchak and Dalia M. Araujo

CONTENTS OF RECENT VOLUMES

Clinical Implications of Circulating Neurosteroids Andrea R. Genazzani, Patrizia Monteleone, Massimo Stomati, Francesca Bernardi, Luigi Cobellis, Elena Casarosa, Michele Luisi, Stefano Luisi, and Felice Petraglia Neuroactive Steroids and Central Nervous System Disorders Mingde Wang, Torbjo¨rn Ba¨ ckstro¨m, Inger Sundstro¨m, Go¨ran Wahlstro¨m, Tommy Olsson, Di Zhu, Inga-Maj Johansson, Inger Bjo¨rn, and Marie Bixo Neuroactive Steroids in Neuropsychopharmacology Rainer Rupprecht and Florian Holsboer Current Perspectives on the Role of Neurosteroids in PMS and Depression Lisa D. Griffin, Susan C. Conrad, and Synthia H. Mellon

289

Processing Human Brain Tissue for in Situ Hybridization with Radiolabelled Oligonucleotides Louise F. B. Nicholson In Situ Hybridization of Astrocytes and Neurons Cultured in Vitro L. A. Arizza-McNaughton, C. De Felipe, and S. P. Hunt In Situ Hybridization on Organotypic Slice Cultures A. Gerfin-Moser and H. Monyer Quantitative Analysis of in Situ Hybridization Histochemistry Andrew L. Gundlach and Ross D. O’Shea Part II: Nonradioactive in Situ hybridization Nonradioactive in Situ Hybridization Using Alkaline Phosphatase-Labelled Oligonucleotides S. J. Augood, E. M. McGowan, B. R. Finsen, B. Heppelmann, and P. C. Emson

index

Volume 47

Combining Nonradioactive in Situ Hybridization with Immunohistological and Anatomical Techniques Petra Wahle

Introduction: Studying Gene Expression in Neural Tissues by in Situ Hybridization W. Wisden and B. J. Morris

Nonradioactive in Situ Hybridization: Simplified Procedures for Use in Whole Mounts of Mouse and Chick Embryos Linda Ariza-McNaughton and Robb Krumlauf

Part I: In Situ Hybridization with Radiolabelled Oligonucleotides In Situ Hybridization with Oligonucleotide Probes Wl. Wisden and B. J. Morris

index

Cryostat Sectioning of Brains Victoria Revilla and Alison Jones

Volume 48

Processing Rodent Embryonic and Early Postnatal Tissue for in Situ Hybridization with Radiolabelled Oligonucleotides David J. Laurie, Petra C. U. Schrotz, Hannah Monyer, and Ulla Amtmann

Assembly and Intracellular GABAA Receptors Eugene Barnes

Trafficking

of

Processing of Retinal Tissue for in Situ Hybridization Frank Mu¨ ller

Subcellular Localization and Regulation of GABAA Receptors and Associated Proteins Bernhard Lu¨ scher and Jean-Marc Fritschy D1 Dopamine Receptors Richard Mailman

Processing the Spinal Cord for in Situ Hybridization with Radiolabelled Oligonucleotides A. Berthele and T. R. To¨lle

Molecular Modeling of Ligand-Gated Ion Channels: Progress and Challenges Ed Bertaccini and James R. Trudel

290

CONTENTS OF RECENT VOLUMES

Alzheimer’s Disease: Its Diagnosis and Pathogenesis Jillian J. Kril and Glenda M. Halliday DNA Arrays and Functional Genomics in Neurobiology Christelle Thibault, Long Wang, Li Zhang, and Michael F. Miles

The Treatment of Infantile Spasms: An Evidence-Based Approach Mark Mackay, Shelly Weiss, and O. Carter Snead III

index

ACTH Treatment of Infantile Spasms: Mechanisms of Its Effects in Modulation of Neuronal Excitability K. L. Brunson, S. Avishai-Eliner, and T. Z. Baram

Volume 49

Neurosteroids and Infantile Spasms: The Deoxycorticosterone Hypothesis Michael A. Rogawski and Doodipala S. Reddy

What Is West Syndrome? Olivier Dulac, Christine Soufflet, Catherine Chiron, and Anna Kaminski

Are there Specific Anatomical and/or Transmitter Systems (Cortical or Subcortical) That Should Be Targeted? Phillip C. Jobe

The Relationship between encephalopathy and Abnormal Neuronal Activity in the Developing Brain Frances E. Jensen

Medical versus Surgical Treatment: Which Treatment When W. Donald Shields

Hypotheses from Functional Neuroimaging Studies Csaba Juha´ sz, Harry T. Chugani, Ouo Muzik, and Diane C. Chugani Infantile Spasms: Unique Sydrome or General Age-Dependent Manifestation of a Diffuse Encephalopathy? M. A. Koehn and M. Duchowny

Developmental Outcome with and without Successful Intervention Rochelle Caplan, Prabha Siddarth, Gary Mathern, Harry Vinters, Susan Curtiss, Jennifer Levitt, Robert Asarnow, and W. Donald Shields Infantile Spasms versus Myoclonus: Is There a Connection? Michael R. Pranzatelli

Histopathology of Brain Tissue from Patients with Infantile Spasms Harry V. Vinters

Tuberous Sclerosis as an Underlying Basis for Infantile Spasm Raymond S. Yeung

Generators of Ictal and Interictal Electroencephalograms Associated with Infantile Spasms: Intracellular Studies of Cortical and Thalamic Neurons M. Steriade and I. Timofeev

Brain Malformation, Epilepsy, and Infantile Spasms M. Elizabeth Ross

Cortical and Subcortical Generators of Normal and Abnormal Rhythmicity David A. McCormick Role of Subcortical Structures in the Pathogenesis of Infantile Spasms: What Are Possible Subcortical Mediators? F. A. Lado and S. L. Moshe´ What Must We Know to Develop Better Therapies? Jean Aicardi

Brain Maturational Aspects Relevant to Pathophysiology of Infantile Spasms G. Auanzini, F. Panzica, and S. Franceschetti Gene Expression Analysis as a Strategy to Understand the Molecular Pathogenesis of Infantile Spasms Peter B. Crino Infantile Spasms: Criteria for an Animal Model Carl E. Stafstrom and Gregory L. Holmes index

CONTENTS OF RECENT VOLUMES

Volume 50 Part I: Primary Mechanisms How Does Glucose Generate Oxidative Stress In Peripheral Nerve? Irina G. Obrosova Glycation in Diabetic Neuropathy: Characteristics, Consequences, Causes, and Therapeutic Options Paul J. Thornalley Part II: Secondary Changes Protein Kinase C Changes in Diabetes: Is the Concept Relevant to Neuropathy? Joseph Eichberg Are Mitogen-Activated Protein Kinases Glucose Transducers for Diabetic Neuropathies? Tertia D. Purves and David R. Tomlinson Neurofilaments in Diabetic Neuropathy Paul Fernyhough and Robert E. Schmidt Apoptosis in Diabetic Neuropathy Aviva Tolkovsky Nerve and Ganglion Blood Flow in Diabetes: An Appraisal Douglas W. Zochodne Part III: Manifestations Potential Mechanisms of Neuropathic Pain in Diabetes Nigel A. Calcutt Electrophysiologic Measures of Diabetic Neuropathy: Mechanism and Meaning Joseph C. Arezzo and Elena Zotova Neuropathology and Pathogenesis of Diabetic Autonomic Neuropathy Robert E. Schmidt Role of the Schwann Cell in Diabetic Neuropathy Luke Eckersley

291

Nerve Growth Factor for the Treatment of Diabetic Neuropathy: What Went Wrong, What Went Right, and What Does the Future Hold? Stuart C. Apfel Angiotensin-Converting Enzyme Inhibitors: Are there Credible Mechanisms for Beneficial Effects in Diabetic Neuropathy? Rayaz A. Malik and David R. Tomlinson Clinical Trials for Drugs Against Diabetic Neuropathy: Can We Combine Scientific Needs With Clinical Practicalities? Dan Ziegler and Dieter Luft index

Volume 51 Energy Metabolism in the Brain Leif Hertz and Gerald A. Dienel The Cerebral Glucose-Fatty Acid Cycle: Evolutionary Roots, Regulation, and (Patho) physiological Importance Kurt Heininger Expression, Regulation, and Functional Role of Glucose Transporters (GLUTs) in Brain Donard S. Dwyer, Susan J. Vannucci, and Ian A. Simpson Insulin-Like Growth Factor-1 Promotes Neuronal Glucose Utilization During Brain Development and Repair Processes Carolyn A. Bondy and Clara M. Cheng CNS Sensing and Regulation of Peripheral Glucose Levels Barry E. Levin, Ambrose A. Dunn-Meynell, and Vanessa H. Routh

Part IV: Potential Treatment

Glucose Transporter Protein Syndromes Darryl C. De Vivo, Dong Wang, Juan M. Pascual, and Yuan Yuan Ho

Polyol Pathway and Diabetic Peripheral Neuropathy Peter J. Oates

Glucose, Stress, and Hippocampal Neuronal Vulnerability Lawrence P. Reagan

292

CONTENTS OF RECENT VOLUMES

Glucose/Mitochondria in Neurological Conditions John P. Blass Energy Utilization in the Ischemic/Reperfused Brain John W. Phillis and Michael H. O’Regan Diabetes Mellitus and the Central Nervous System Anthony L. McCall Diabetes, the Brain, and Behavior: Is There a Biological Mechanism Underlying the Association between Diabetes and Depression? A. M. Jacobson, J. A. Samson, K. Weinger, and C. M. Ryan Schizophrenia and Diabetes David C. Henderson and Elissa R. Ettinger Psychoactive Drugs Affect Glucose Transport and the Regulation of Glucose Metabolism Donard S. Dwyer, Timothy D. Ardizzone, and Ronald J. Bradley index

Neural Control of Salivary S-IgA Secretion Gordon B. Proctor and Guy H. Carpenter Stress and Secretory Immunity Jos A. Bosch, Christopher Ring, Eco J. C. de Geus, Enno C. I. Veerman, and Arie V. Nieuw Amerongen Cytokines and Depression Angela Clow Immunity and Schizophrenia: Autoimmunity, Cytokines, and Immune Responses Fiona Gaughran Cerebral Lateralization and the Immune System Pierre J. Neveu Behavioral Conditioning of the Immune System Frank Hucklebridge Psychological and Neuroendocrine Correlates of Disease Progression Julie M. Turner-Cobb The Role of Psychological Intervention in Modulating Aspects of Immune Function in Relation to Health and Well-Being J. H. Gruzelier index

Volume 52

Volume 53

Neuroimmune Relationships in Perspective Frank Hucklebridge and Angela Clow

Section I: Mitochondrial Structure and Function

Sympathetic Nervous System Interaction with the Immune System Virginia M. Sanders and Adam P. Kohm Mechanisms by Which Cytokines Signal the Brain Adrian J. Dunn Neuropeptides: Modulators of Responses in Health and Disease David S. Jessop

Immune

Mitochondrial DNA Structure and Function Carlos T. Moraes, Sarika Srivastava, Ilias Kirkinezos, Jose Oca-Cossio, Corina van Waveren, Markus Woischnick, and Francisca Diaz Oxidative Phosphorylation: Structure, Function, and Intermediary Metabolism Simon J. R. Heales, Matthew E. Gegg, and John B. Clark

Brain–Immune Interactions in Sleep Lisa Marshall and Jan Born

Import of Mitochondrial Proteins Matthias F. Bauer, Sabine Hofmann, and Walter Neupert

Neuroendocrinology of Autoimmunity Michael Harbuz

Section II: Primary Respiratory Chain Disorders

Systemic Stress-Induced Th2 Shift and Its Clinical Implications Ibia J. Elenkov

Mitochondrial Disorders of the Nervous System: Clinical, Biochemical, and Molecular Genetic Features Dominic Thyagarajan and Edward Byrne

CONTENTS OF RECENT VOLUMES

Section III: Secondary Respiratory Chain Disorders Friedreich’s Ataxia J. M. Cooper and J. L. Bradley Wilson Disease C. A. Davie and A. H. V. Schapira

293

The Mitochondrial Theory of Aging: Involvement of Mitochondrial DNA Damage and Repair Nadja C. de Souza-Pinto and Vilhelm A. Bohr index

Hereditary Spastic Paraplegia Christopher J. McDermott and Pamela J. Shaw Cytochrome c Oxidase Deficiency Giacomo P. Comi, Sandra Strazzer, Sara Galbiati, and Nereo Bresolin Section IV: Toxin Induced Mitochondrial Dysfunction Toxin-Induced Mitochondrial Dysfunction Susan E. Browne and M. Flint Beal Section V: Neurodegenerative Disorders Parkinson’s Disease L. V. P. Korlipara and A. H. V. Schapira Huntington’s Disease: The Mystery Unfolds? A˚sa Peterse´n and Patrik Brundin Mitochondria in Alzheimer’s Disease Russell H. Swerdlow and Stephen J. Kish Contributions of Mitochondrial Alterations, Resulting from Bad Genes and a Hostile Environment, to the Pathogenesis of Alzheimer’s Disease Mark P. Mattson Mitochondria and Amyotrophic Lateral Sclerosis Richard W. Orrell and Anthony H. V. Schapira

Volume 54 Unique General Anesthetic Binding Sites Within Distinct Conformational States of the Nicotinic Acetylcholine Receptor Hugo R. Ariaas, William, R. Kem, James R. Truddell, and Michael P. Blanton Signaling Molecules and Receptor Transduction Cascades That Regulate NMDA ReceptorMediated Synaptic Transmission Suhas. A. Kotecha and John F. MacDonald Behavioral Measures of Alcohol Self-Administration and Intake Control: Rodent Models Herman H. Samson and Cristine L. Czachowski Dopaminergic Mouse Mutants: Investigating the Roles of the Different Dopamine Receptor Subtypes and the Dopamine Transporter Shirlee Tan, Bettina Hermann, and Emiliana Borrelli Drosophila melanogaster, A Genetic Model System for Alcohol Research Douglas J. Guarnieri and Ulrike Heberlein index

Section VI: Models of Mitochondrial Disease Models of Mitochondrial Disease Danae Liolitsa and Michael G. Hanna Section VII: Defects of Oxidation Including Carnitine Deficiency Defects of Oxidation Including Carnitine Deficiency K. Bartlett and M. Pourfarzam Section VIII: Mitochondrial Involvement in Aging

Volume 55 Section I: Virsu Vectors For Use in the Nervous System Non-Neurotropic Adenovirus: a Vector for Gene Transfer to the Brain and Gene Therapy of Neurological Disorders P. R. Lowenstein, D. Suwelack, J. Hu, X. Yuan, M. Jimenez-Dalmaroni, S. Goverdhama, and M.G. Castro

294

CONTENTS OF RECENT VOLUMES

Adeno-Associated Virus Vectors E. Lehtonen and L. Tenenbaum Problems in the Use of Herpes Simplex Virus as a Vector L. T. Feldman Lentiviral Vectors J. Jakobsson, C. Ericson, N. Rosenquist, and C. Lundberg Retroviral Vectors for Gene Delivery to Neural Precursor Cells K. Kageyama, H. Hirata, and J. Hatakeyama

Processing and Representation of SpeciesSpecific Communication Calls in the Auditory System of Bats George D. Pollak, Achim Klug, and Eric E. Bauer Central Nervous System Control of Micturition Gert Holstege and Leonora J. Mouton The Structure and Physiology of the Rat Auditory System: An Overview Manuel Malmierca Neurobiology of Cat and Human Sexual Behavior Gert Holstege and J. R. Georgiadis

Section II: Gene Therapy with Virus Vectors for Specific Disease of the Nervous System

index

The Principles of Molecular Therapies for Glioblastoma G. Karpati and J. Nalbatonglu

Volume 57

Oncolytic Herpes Simplex Virus J. C. C. Hu and R. S. Coffin

Cumulative Subject Index of Volumes 1-25

Recombinant Retrovirus Vectors for Treatment of Brain Tumors N. G. Rainov and C. M. Kramm

Volume 58

Adeno-Associated Viral Vectors for Parkinson’s Disease I. Muramatsu, L. Wang, K. Ikeguchi, K-i Fujimoto, T. Okada, H. Mizukami, Y. Hanazono, A. Kume, I. Nakano, and K. Ozawa HSV Vectors for Parkinson’s Disease D. S. Latchman Gene Therapy for Stroke K. Abe and W. R. Zhang Gene Therapy for Mucopolysaccharidosis A. Bosch and J. M. Heard index

Volume 56 Behavioral Mechanisms and the Neurobiology of Conditioned Sexual Responding Mark Krause NMDA Receptors in Alcoholism Paula L. Hoffman,

Cumulative Subject Index of Volumes 26–50

Volume 59 Loss of Spines and Neuropil Liesl B. Jones Schizophrenia as a Disorder of Neuroplasticity Robert E. McCullumsmith, Sarah M. Clinton, and James H. Meador-Woodruff The Synaptic Pathology of Schizophrenia: Is Aberrant Neurodevelopment and Plasticity to Blame? Sharon L. Eastwood Neurochemical Basis for an Epigenetic Vision of Synaptic Organization E. Costa, D. R. Grayson, M. Veldic, and A. Guidotti Muscarinic Receptors in Schizophrenia: Is There a Role for Synaptic Plasticity? Thomas J. Raedler

CONTENTS OF RECENT VOLUMES

295

Serotonin and Brain Development Monsheel S. K. Sodhi and Elaine Sanders-Bush

Volume 60

Presynaptic Proteins and Schizophrenia William G. Honer and Clint E. Young

Microarray Platforms: Introduction and Application to Neurobiology Stanislav L. Karsten, Lili C. Kudo, and Daniel H. Geschwind

Mitogen-Activated Protein Kinase Signaling Svetlana V. Kyosseva Postsynaptic Density Scaffolding Proteins at Excitatory Synapse and Disorders of Synaptic Plasticity: Implications for Human Behavior Pathologies Andrea de Bartolomeis and Germano Fiore Prostaglandin-Mediated Signaling in Schizophrenia S. Smesny Mitochondria, Synaptic Plasticity, and Schizophrenia Dorit Ben-Shachar and Daphna Laifenfeld Membrane Phospholipids and Cytokine Interaction in Schizophrenia Jeffrey K. Yao and Daniel P. van Kammen Neurotensin, Schizophrenia, and Antipsychotic Drug Action Becky Kinkead and Charles B. Nemeroff Schizophrenia, Vitamin D, and Brain Development Alan Mackay-Sim, Franc¸ois Fe´ron, Darryl Eyles, Thomas Burne, and John McGrath Possible Contributions of Myelin and Oligodendrocyte Dysfunction to Schizophrenia Daniel G. Stewart and Kenneth L. Davis Brain-Derived Neurotrophic Factor and the Plasticity of the Mesolimbic Dopamine Pathway Oliver Guillin, Nathalie Griffon, Jorge Diaz, Bernard Le Foll, Erwan Bezard, Christian Gross, Chris Lammers, Holger Stark, Patrick Carroll, Jean-Charles Schwartz, and Pierre Sokoloff S100B in Schizophrenic Psychosis Matthias Rothermundt, Gerald Ponath, and Volker Arolt Oct-6 Transcription Factor Maria Ilia NMDA Receptor Function, Neuroplasticity, and the Pathophysiology of Schizophrenia Joseph T. Coyle and Guochuan Tsai index

Experimental Design and Low-Level Analysis of Microarray Data B. M. Bolstad, F. Collin, K. M. Simpson, R. A. Irizarry, and T. P. Speed Brain Gene Expression: Genomics and Genetics Elissa J. Chesler and Robert W. Williams DNA Microarrays and Animal Models of Learning and Memory Sebastiano Cavallaro Microarray Analysis of Human Nervous System Gene Expression in Neurological Disease Steven A. Greenberg DNA Microarray Analysis of Postmortem Brain Tissue Ka´ roly Mirnics, Pat Levitt, and David A. Lewis index

Volume 61 Section I: High-Throughput Technologies Biomarker Discovery Using Molecular Profiling Approaches Stephen J. Walker and Arron Xu Proteomic Analysis of Mitochondrial Proteins Mary F. Lopez, Simon Melov, Felicity Johnson, Nicole Nagulko, Eva Golenko, Scott Kuzdzal, Suzanne Ackloo, and Alvydas Mikulskis Section II: Proteomic Applications NMDA Receptors, Neural Pathways, and Protein Interaction Databases Holger Husi Dopamine Transporter Network and Pathways Rajani Maiya and R. Dayne Mayfield Proteomic Approaches in Drug Discovery and Development Holly D. Soares, Stephen A. Williams, Peter J. Snyder, Feng Gao, Tom Stiger,

296

CONTENTS OF RECENT VOLUMES

Christian Rohlff, Athula Herath, Trey Sunderland, Karen Putnam, and W. Frost White Section III: Informatics Proteomic Informatics Steven Russell, William Old, Katheryn Resing, and Lawrence Hunter

Volume 62 GABAA Receptor Structure–Function Studies: A Reexamination in Light of New Acetylcholine Receptor Structures Myles H. Akabas

Section IV: Changes in the Proteome by Disease

Dopamine Mechanisms and Cocaine Reward Aiko Ikegami and Christine L. Duvauchelle

Proteomics Analysis in Alzheimer’s Disease: New Insights into Mechanisms of Neurodegeneration D. Allan Butterfield and Debra Boyd-Kimball

Proteolytic Dysfunction in Neurodegenerative Disorders Kevin St.P. McNaught

Proteomics and Alcoholism Frank A. Witzmann and Wendy N. Strother

Neuroimaging Studies in Bipolar Children and Adolescents Rene L. Olvera, David C. Glahn, Sheila C. Caetano, Steven R. Pliszka, and Jair C. Soares

Proteomics Studies of Traumatic Brain Injury Kevin K. W. Wang, Andrew Ottens, William Haskins, Ming Cheng Liu, Firas Kobeissy, Nancy Denslow, SuShing Chen, and Ronald L. Hayes Influence of Huntington’s Disease on the Human and Mouse Proteome Claus Zabel and Joachim Klose Section V: Overview of the Neuroproteome Proteomics—Application to the Brain Katrin Marcus, Oliver Schmidt, Heike Schaefer, Michael Hamacher, Andre´ van Hall, and Helmut E. Meyer index

Chemosensory G-Protein-Coupled Receptor Signaling in the Brain Geoffrey E. Woodard Disturbances of Emotion Regulation after Focal Brain Lesions Antoine Bechara The Use of Caenorhabditis elegans in Molecular Neuropharmacology Jill C. Bettinger, Lucinda Carnell, Andrew G. Davies, and Steven L. McIntire index