Neurology Volume 72(20) May 19, 2009

This week in Neurology® Highlights of the May 19 issue

Less Alzheimer disease neuropathology in medicated hypertensive than nonhypertensive persons In the absence of clear prescribing guidelines for antihypertensive medications in the very elderly, this research suggests a potential benefit against Alzheimer disease–associated neuropathology. In this postmortem

Longitudinal and cross-sectional analysis of atrophy in pharmacoresistant temporal lobe epilepsy In patients with pharmacoresistant temporal lobe epilepsy, progressive brain atrophy, likely representing seizureinduced damage, occurs over a mean interval of 2.5 years. This paper suggests that as soon as the intractability with medication is established, patients with epilepsy should undergo a comprehensive MRI examination and be evaluated for surgery. See p. 1747; Editorial, p. 1718

study sample with mean age at death of 83.4 years, there was substantially less Alzheimer disease neuropathology in medicated hypertensive than normotensive subjects. See p. 1720; Editorial, p. 1716; see also p. 1727

Duration of antihypertensive drug use and risk of dementia: A prospective cohort study This large, prospective, population-based cohort study investigated the association between duration of antihypertensive drug use and the risk of dementia and Alzheimer disease. The authors found that antihypertensive drug use was associated with 8% risk reduction of dementia per year of use for persons ⱕ75 years.

SEPT9 gene sequencing analysis reveals recurrent mutations in hereditary neuralgic amyotrophy Hereditary neuralgic amyotrophy is an autosomal dominant disorder that manifests as recurrent, episodic, painful brachial neuropathies. A recurrent mutation in SEPT9 is a frequent cause of hereditary neuralgic amyotrophy. This paper provides further evidence that this mutation is the molecular basis of some cases of hereditary neuralgic amyotrophy. See p. 1755

Quality of life in multiple sclerosis is associated with lesion burden and brain volume measures

The authors conducted a 1H-MRS study in patients with mild

Aspects of health-related quality of life (HRQOL), which captures a disease’s impact on well-being, correlate with brain atrophy and lesion load in multiple sclerosis. Since brain atrophy predicts subsequent disability, future studies should evaluate whether HRQOL, easily assessed in the clinical setting, also predicts long-term multiple sclerosis outcomes.

dementia and mild cognitive impairment (MCI) to investigate

See p. 1760

See p. 1727; Editorial, p. 1716; see also p. 1720

A multicenter 1H-MRS study of the medial temporal lobe in AD and MCI

the multicenter feasibility of 1H-MRS. They demonstrate the feasibility of 1H-MRS of the medial temporal lobe in mild dementia and MCI, which should be a prerequisite for the application of 1H-MRS in future clinical trials. See p. 1735

Differences in retinal vessels support a distinct vasculopathy causing lacunar stroke The authors use retinal vessels as a novel method of gaining information about the distinct vasculopathy causing lacunar stroke, which may ultimately lead to different treatments for lacunar stroke. They demonstrate that retinal venules are wider in lacunar stroke as compared to cortical stroke. See p. 1773

Podcasts can be accessed at www.neurology.org

Copyright © 2009 by AAN Enterprises, Inc.

1715

EDITORIAL

Hypertension and late-life dementia A real link?

David S. Knopman, MD

Address correspondence and reprint requests to Dr. D.S. Knopman, Department of Neurology, Mayo Clinic, 200 First Street SW, Rochester, MN 55905 [email protected]

Neurology® 2009;72:1716–1717

In this issue of Neurology®, two articles discuss the role of hypertension in late-life dementia. One, a clinical-neuropathologic study,1 reports that persons who were treated for hypertension in midlife were less demented clinically and had less Alzheimer disease (AD) pathology than either hypertensive patients who were not treated or nonhypertensive patients. The second article2 was from an epidemiologic study that found that antihypertensive use was associated with a reduction in dementia risk, more so in persons ⬍75 years old. Taken together with the very large body of literature on the relationship of midlife and late-life hypertension to late-life dementia, the findings offer some encouragement for prevention of dementia. Although the two current studies are observational, they complement results from primary prevention trials. While the results are not uniform,3 some largescale randomized controlled trials of antihypertensive medications have shown reductions in incident dementia or improvements in cognition.4-7 The concordance of observational studies and at least a few clinical trials in antihypertensive treatment is a rare bright spot in the otherwise dismal track record of other putative interventions for dementia such as hormone replacement in women, statins, nonsteroidal antiinflammatory drugs, vitamin B12, and vitamin E therapies. Congratulations are not yet in order, however. There are many complexities and nuances to the story. There has been a persistent question as to whether the type of antihypertensive medication makes a difference on cognitive outcomes. While there are reasons why one drug might be superior to others based on mechanisms of action, the evidence is not consistent. In neither of the current studies1,2 was there a consistent signal favoring one class of antihypertensive drug. Other studies have made various claims4,6,8,9 for specific drug classes. The choice of an

antihypertensive that is optimal for prevention of dementia is not going to be resolved by the two current studies, but the suggestion is that the specific drug or drug class does not make a difference. The age at onset of hypertension appears to have a substantial impact on the association between hypertension and dementia. Hypertension in midlife is clearly a major risk factor for later life cardiovascular and cerebrovascular disease as well as dementia. In contrast, in late life, blood pressure appears to have a J-shaped relationship to dementia because low blood pressure in late life emerges as a risk factor.10,11 In fact, there is an increasing prevalence of hypotension with advancing age.12 As a consequence, not all studies find hypertension to be a risk factor for dementia in late life.13 To make matters more complicated, hypotension in the elderly could either cause brain injury through ischemia and hypoperfusion, or itself could be a consequence of the brain disease that either directly affects the central control of blood pressure or indirectly leads to poor oral intake and weight loss. So, in order to demonstrate the effects of hypertension on dementia, it is probably in midlife and early elderly years where therapy needs to be directed. Later, among more elderly persons (roughly, over age 75 years), treatment of hypertension may have less value, as shown by one of the current studies.2 At some point in the aging process, somewhere but not exactly at age 75 years, the balance among blood pressure, cerebral autoregulation, and brain metabolism must change. Perhaps the higher existing disease burden of either AD or cerebrovascular pathology together with aging changes in the conduit and microvessels in the very elderly preclude benefits from treating hypertension. The rising prevalence of hypotension12 with advancing age due to central or peripheral nervous system disease might also interact with attempts to treat hypertension. Another possibility to account for the alteration in association of

See pages 1720 and 1727 e-Pub ahead of print on February 18, 2009, at www.neurology.org. From the Department of Neurology, Mayo Clinic, Rochester, MN. Supported by grants U01 AG 06786 (Mayo Alzheimer’s Disease Patient Registry) and P50 AG 16574 (Mayo Alzheimer’s Disease Research Center) from the National Institute on Aging and the Robert H. and Clarice Smith and Abigail Van Buren Alzheimer’s Disease Research Program. Disclosure: D.S.K. has served on a Data Safety Monitoring Board for Sanofi-Aventis Pharmaceuticals and is an investigator for clinical trials sponsored by Elan Pharmaceuticals and Forest Pharmaceuticals. 1716

Copyright © 2009 by AAN Enterprises, Inc.

hypertension and dementia with advancing age is that some of the age-related differences in response to hypertension and its treatment could reflect survival biases, in which premature cardiovascular death in hypertensive patients culled out persons without other protective mechanisms. Finally, it is not clear whether the consequences of hypertension or the target of the antihypertensive drugs are on AD pathology or cerebrovascular pathology. The obvious pathogenetic mechanism for hypertension would be endothelial dysfunction, leading to microinfarction and more widespread cerebral ischemia.14-16 But pivotal studies from the Honolulu Asia Aging Study17 as well as the current neuropathologic study1 suggest that at least some of hypertension’s impact is on AD pathology. Microvascular mechanisms for ␤-amyloid clearance could conceivably be altered by endothelial changes from hypertension.18 Some antihypertensive drugs such as calcium channel blockers19 or angiotensin-converting enzyme inhibitors20 could interact with ␤-amyloid trafficking. Regardless of the pathophysiologic target or mechanism, the evidence that hypertension earlier in life plays an important role in late-life dementia is consistent. It may not be a major determinant, but greater attention to the role of hypertension’s impact on the brain is warranted. Because hypertension is so common, its treatment would impact a large segment of the population at risk for late-life dementia. REFERENCES 1. Hoffman LB, Schmeidler J, Lesser GT, et al. Less Alzheimer disease neuropathology in medicated hypertensive than nonhypertensive persons. Neurology 2009;72:1720 – 1726. 2. Haag MDM, Hofman A, Koudstaal PJ, Breteler MMB, Stricker BHC. Duration of antihypertensive drug use and risk of dementia: a prospective cohort study. Neurology 2009;72:1727–1734. 3. Lithell H, Hansson L, Skoog I, et al. The Study on Cognition and Prognosis in the Elderly (SCOPE): principal results of a randomized double-blind intervention trial. J Hypertens 2003;21:875–886. 4. Hanon O, Forette F. Treatment of hypertension and prevention of dementia. Alzheimer Dement J Alzheimer Assoc 2005;1:30–37. 5. Forette F, Seux ML, Staessen JA, et al. Prevention of dementia in randomised double-blind placebo-controlled Systolic Hypertension in Europe (Syst-Eur) trial. Lancet 1998;352:1347–1351.

6. Tzourio C, Anderson C, Chapman N, et al. Effects of blood pressure lowering with perindopril and indapamide therapy on dementia and cognitive decline in patients with cerebrovascular disease. Arch Intern Med 2003;163:1069–1075. 7. Bosch J, Yusuf S, Pogue J, et al. Use of ramipril in preventing stroke: double blind randomised trial. BMJ 2002;324: 699–702. 8. Khachaturian AS, Zandi PP, Lyketsos CG, et al. Antihypertensive medication use and incident Alzheimer disease: the Cache County Study. Arch Neurol 2006;63:686–692. 9. Guo Z, Fratiglioni L, Zhu L, Fastbom J, Winblad B, Viitanen M. Occurrence and progression of dementia in a community population aged 75 years and older: relationship of antihypertensive medication use. Arch Neurol 1999;56:991–996. 10. Guo Z, Viitanen M, Winblad B, Fratiglioni L. Low blood pressure and incidence of dementia in a very old sample: dependent on initial cognition. J Am Geriatr Soc 1999;47: 723–726. 11. Verghese J, Lipton RB, Hall CB, Kuslansky G, Katz MJ. Low blood pressure and the risk of dementia in very old individuals. Neurology 2003;61:1667–1672. 12. Low PA. Prevalence of orthostatic hypotension. Clin Auton Res 2008;18 suppl 1:8–13. 13. Johnson KC, Margolis KL, Espeland MA, et al. A prospective study of the effect of hypertension and baseline blood pressure on cognitive decline and dementia in postmenopausal women: the Women’s Health Initiative Memory Study. J Am Geriatr Soc 2008;56:1449–1458. 14. Thal DR, Ghebremedhin E, Orantes M, Wiestler OD. Vascular pathology in Alzheimer disease: correlation of cerebral amyloid angiopathy and arteriosclerosis/lipohyalinosis with cognitive decline. J Neuropathol Exp Neurol 2003;62:1287–1301. 15. Vinters HV, Ellis WG, Zarow C, et al. Neuropathologic substrates of ischemic vascular dementia. J Neuropathol Exp Neurol 2000;59:931–945. 16. Esiri MM, Wilcock GK, Morris JH. Neuropathological assessment of the lesions of significance in vascular dementia. J Neurol Neurosurg Psychiatry 1997;63:749–753. 17. Petrovitch H, White LR, Izmirilian G, et al. Midlife blood pressure and neuritic plaques, neurofibrillary tangles, and brain weight at death: the HAAS: Honolulu-Asia Aging Study. Neurobiol Aging 2000;21:57–62. 18. Zlokovic BV. Neurovascular mechanisms of Alzheimer’s neurodegeneration. Trends Neurosci 2005;28:202–208. 19. Lopez-Arrieta JM, Birks J. Nimodipine for primary degenerative, mixed and vascular dementia. Cochrane Database Syst Rev 2002; CD000147. 20. Ohrui T, Tomita N, Sato-Nakagawa T, et al. Effects of brain-penetrating ACE inhibitors on Alzheimer disease progression. Neurology 2004;63:1324–1325.

Neurology 72

May 19, 2009

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EDITORIAL

Temporal lobe epilepsy is a progressive neurologic disorder Time means neurons!

Gregory D. Cascino, MD, FAAN

Address correspondence and reprint requests to Dr. G.D. Cascino, Mayo Clinic, 200 First Street SW, Rochester, MN 55905 [email protected]

Neurology® 2009;72:1718–1719

Temporal lobe epilepsy (TLE) is the most common type of partial or localization-related seizure disorder. The amygdala and hippocampus in the medial temporal lobe are important epileptogenic regions, so it is not surprising that in individuals with partial seizures1,2 and TLE the most common pathology is mesial temporal sclerosis (MTS) with prominent neuronal loss and gliosis in the hippocampus.2,3 The high diagnostic yield of MRI as a sensitive and specific indicator of MTS has been confirmed2,3; the most common finding is unilateral hippocampal atrophy with a concordant signal intensity alteration.3 The initial response to antiepileptic drug (AED) therapy in partial epilepsy is highly predictive of long-term outcome, with the most effective AED treatment often being the first or second medications administered.4 Approximately one-third of patients with partial epilepsy have pharmacoresistance or intractable seizures. TLE is considered to be intractable when the patient has medically refractory seizures that are physically or socially disabling. The ability to drive and thereby to obtain or maintain competitive employment may be affected; these individuals may be unable to be a productive or participating member of society. Associated neurologic comorbid conditions in patients with intractable TLE include cognitive impairment, speech and language disorders, depression, and AED toxicity. In selected patients, these associated symptoms, e.g., memory decline, may be significant and progressive. Epilepsy surgery is the most effective “curative” management for patients with intractable TLE.5,6 Clinical outcome studies have demonstrated that TLE may be a surgically remediable epileptic syndrome. A randomized control trial of surgery vs AED therapy showed the superior efficacy of surgical excision of the epileptogenic zone.5 Patients with MRIidentified unilateral MTS may represent a highly favorable group for consideration of epilepsy surgery.6 A comprehensive neurologic evaluation is performed before surgery to assess the relationship

between the imaging findings and the site of seizure onset. Unfortunately, the duration of epilepsy in patients undergoing surgical treatment is often measured in decades and not years.6 This prolonged period of intractability may be associated with progressive psychosocial deprivation, cognitive impairment, and AED adverse effects. In this issue of Neurology®, Bernhardt et al.7 evaluated cortical thickness on MRI and revealed that progressive neocortical atrophy occurs in patients with intractable TLE and is correlated with epilepsy duration. A longitudinal analysis was used in 18 patients with a mean interscan interval of 2.5 years (range, 7–90 months). A cross-sectional analysis was performed in 121 patients correlating epilepsy duration and MRI. The longitudinal analysis showed that atrophy was most prominent in patients with a longer duration of epilepsy (greater than 14 years) in the frontocentral and parietal regions. Aging effects did not produce these specific imaging alterations. The progressive neocortical atrophy occurred over a mean interval of 2.5 years. The investigators postulated that the MRI findings were related to chronic seizure activity. There is compelling evidence that TLE may be a progressive neurologic disorder that requires early and effective treatment.8-10 Prolonged AED therapy that is unable to render a patient seizure-free may reduce the likelihood of an excellent psychosocial rehabilitation following successful epilepsy surgery. The goals of treatment in partial epilepsy are to render the individual seizure-free allowing the patient to perform normal activities, e.g., driving, legally and safely. The study of Bernhardt et al.7 provides a unique quantitative assessment in patients with TLE and indicates that regions of the brain remote from the lobe of seizure onset may be adversely affected with significant changes in cerebral cortical structure. Potentially, these alterations may be proconvulsant or be important for the development of comorbidity. The pathophysiology of the progressive temporal

See page 1747 e-Pub ahead of print on March 25, 2009, at www.neurology.org. From the Department of Neurology and Division of Epilepsy, Mayo Clinic, Rochester, MN. Disclosure: Dr. Cascino serves as an editorial board member of Neurology®, is funded by NIH R01 grant (EPGP: Epilepsy Phenome Genome Project), and receives research support from the Mayo Foundation and NeuroPace, Inc., Mountain View, CA. 1718

Copyright © 2009 by AAN Enterprises, Inc.

lobe and extratemporal atrophy may be the recurrent seizure activity in these patients and the important anatomic connection of the limbic network.1,8-10 The present study and others support the need for earlier intervention in patients with medically refractory TLE. Failure of appropriate AED medications to reduce seizures to a significant extent should prompt a diagnostic investigation, including high-quality MRI head and video-EEG monitoring, for patients to be considered for earlier surgical intervention. Epilepsy surgery is not a procedure of last resort for patients who may be highly favorable candidates. There is now a broad consensus that recurrent seizures may significantly alter brain structure and function. Time means neurons! REFERENCES 1. Pitka¨nen A, Sutula TP. Is epilepsy a progressive disorder? Prospects for new therapeutic approaches in temporal lobe epilepsy. Lancet Neurol 2002;1:173–181. 2. Luby M, Spencer DD, Kim JM, deLanerolle N, McCarthy G. Hippocampal MRI volumetrics and temporal lobe substrates in medial temporal lobe epilepsy. Magn Reson Imaging 1995;13:1065–1071.

3. Cascino GD. Neuroimaging in epilepsy: diagnostic strategies in partial epilepsy. Semin Neurol 2008;28: 523–532. 4. Brodie MJ, Kwan P. Staged approach to epilepsy management. Neurology 2002;58(8 suppl 5):S2–S8. 5. Wiebe S, Blume WT, Girvin JP, Eliasziw M. A randomized controlled trial of surgery for temporal-lobe epilepsy. N Engl J Med 2001;345:311–318. 6. Cohen-Gadol AA, Wilhelmi BG, Collignon F, et al. Longterm outcome of epilepsy surgery among 399 patients with nonlesional seizure foci including mesial temporal lobe sclerosis. J Neurosurg 2006;104:513–524. 7. Bernhardt BC, Worsley KJ, Kim H, Evans AC, Bernasconi A, Bernasconi N. Longitudinal and cross-sectional analysis of atrophy in pharmacoresistant temporal lobe epilepsy. Neurology 2009;72:1747–1754. 8. Sutula TP. Mechanisms of epilepsy progression: current theories and perspectives from neuroplasticity in adulthood and development. Epilepsy Res 2004;60:161–171. 9. Bonilha L, Rorden C, Appenzeller S, Coan AC, Cendes F, Li LM. Gray matter atrophy associated with duration of temporal lobe epilepsy. Neuroimage 2006;32:1070–1079. 10. Tasch E, Cendes F, Dubeau F, Andermann F, Arnold DL. Neuroimaging evidence of progressive neuronal loss and dysfunction in temporal lobe epilepsy. Ann Neurol 1999; 45:568–576.

Neurology 72

May 19, 2009

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ARTICLES

Less Alzheimer disease neuropathology in medicated hypertensive than nonhypertensive persons L.B. Hoffman, PhD J. Schmeidler, PhD G.T. Lesser, MD M.S. Beeri, PhD D.P. Purohit, MD H.T. Grossman, MD V. Haroutunian, PhD

Address correspondence and reprint requests to Dr. L. Hoffman, Psychiatry, Room 4F20, Bronx VA Medical Center, 130 West Kingsbridge Road, Bronx, NY 10468 [email protected]

ABSTRACT

Objective: To test the hypothesis that use of antihypertensive medication is associated with lower Alzheimer disease (AD) neuropathology.

Methods: This was a postmortem study of 291 brains limited to those with normal neuropathology or with uncomplicated AD neuropathology (i.e., without other dementia-associated neuropathology) in persons with or without hypertension (HTN) who were and were not treated with antihypertensive medications. Neuritic plaque (NP) and neurofibrillary tangle (NFT) densities, quantified in selected brain regions according to the Consortium to Establish a Registry for Alzheimer’s Disease (CERAD) neuropathologic criteria, with additional cortical NP counts, yielded 24 neuropathologic regional measures or summaries. Medicated hypertension (HTN-med; n ⫽ 77), nonmedicated HTN (HTN-nomed; n ⫽ 42), and non-HTN (no-HTN; n ⫽ 172) groups were compared by analyses of variance.

Results: The HTN-med group had significantly less neuropathology than the no-HTN group. The no-HTN group averaged over 50% higher mean NP and NFT ratings, and double the mean NP count, of the HTN-med group. The HTN-nomed group had significantly more neuropathology than the HTN-med group, but not significantly less than the no-HTN group.

Conclusions: There was substantially less Alzheimer disease (AD) neuropathology in the medicated hypertension group than the nonhypertensive group, which may reflect a salutary effect of antihypertensive medication against AD-associated neuropathology. Neurology® 2009;72:1720–1726 GLOSSARY AD ⫽ Alzheimer disease; ANCOVA ⫽ analysis of covariance; ANOVA ⫽ analysis of variance; BB ⫽ ␤-blockers; BMI ⫽ body mass index; CCB ⫽ calcium channel blockers; CDR ⫽ Clinical Dementia Rating scale; CERAD ⫽ Consortium to Establish a Registry for Alzheimer’s Disease; DBP ⫽ diastolic blood pressure; EC ⫽ entorhinal cortex; HAAS ⫽ Honolulu Asia Aging Study; Hipp ⫽ hippocampus; HTN ⫽ hypertension; IPL ⫽ inferior parietal lobule; JHH ⫽ Jewish Home and Hospital; MFG ⫽ midfrontal gyrus; MSSM ⫽ Mount Sinai School of Medicine; NFT ⫽ neurofibrillary tangle; NH ⫽ nursing homes; NP ⫽ neuritic plaque; OC ⫽ occipital calcarine cortex; OFG ⫽ orbital frontal cortex; SBP ⫽ systolic blood pressure; STG ⫽ superior temporal gyrus.

Hypertension has been associated with cognitive decline, dementia, vascular dementia, and Alzheimer disease (AD) in some studies1-5 but not others.6-9 Elevated systolic blood pressure (SBP) or diastolic blood pressure (DBP) levels, or both, have been reported decades before onset of AD symptoms.4,10-12 Elevated midlife SBP was associated with lower brain weight and increased neuritic plaque (NP) densities in neocortex and hippocampus (Hipp), and elevated DBP was associated with increased NFT densities in Hipp.13 Additionally, elevated midlife SBP and DBP14 were correlated with late-life hippocampal atrophy on MRI in untreated patients clinically diagnosed with AD. Antihypertensive treatments have been associated with lower incidence of clinically diagnosed AD and better cognitive function15-17; similarly, treatment of hypertensive subjects was associated with lower dementia risk.18-20 However, the specific classes of anti-HTN medication Editorial, page 1716 See also page 1727 e-Pub ahead of print on February 18, 2009, at www.neurology.org. From the Departments of Psychiatry (L.B.H., J.S., M.S.B., H.T.G., V.H.), Geriatrics and Adult Development (G.T.L.), and Pathology (D.P.P.), Mount Sinai School of Medicine, New York; Jewish Home & Hospital (G.T.L.), New York; and JJ Peters Veterans Affairs Medical Center (H.T.G., V.H.), Bronx, NY. Supported by NIA grants AG02219 and AG05138 and the Dextra Baldwin McGonagle and Joseph E. and Norma G. Saul Foundations. Disclosure: The authors report no disclosures. 1720

Copyright © 2009 by AAN Enterprises, Inc.

Table 1

Demographic and clinical comparisons by HTN status

Attribute

HTN-med

HTN-nomed

No-HTN

Total

F (2, df), p or ␹2 (2), p

Age at death, y, mean ⴞ SD (n)

85.36 ⫾ 9.06 (77)

85.52 ⫾ 10.93 (42)

82.05 ⫾ 10.71 (172)

83.43 ⫾ 10.43 (291)

3.74 (2, 288), 0.025

Education category, mean ⴞ SD (n)

2.39 ⫾ 1.05 (41)

2.30 ⫾ 0.98 (20)

2.53 ⫾ 0.92 (38)

2.42 ⫾ 0.98 (99)

0.39 (2, 96), 0.681

Sex (female), % (n)

59.7 (46)

64.3 (27)

58.7 (101)

59.8 (174)

0.81 (2), 0.435

Race (white), % (n)

68.8 (53)

83.3 (35)

89.5 (154)

83.2 (242)

16.28 (2), ⬍0.0005

CDR, mean ⴞ SD (n)

1.81 ⫾ 1.56 (77)

2.42 ⫾ 1.91 (42)

2.96 ⫾ 1.82 (172)

2.58 ⫾ 1.83 (291)

11.51 (2, 288), ⬍0.0005

APOE ␧4, % (n)

39.7 (29)

33.3 (13)

42.3 (69)

40.4 (111)

1.08 (2), 0.584

BMI, mean ⴞ SD (n)

22.96 ⫾ 6.89 (64)

22.46 ⫾ 6.74 (33)

21.29 ⫾ 5.55 (85)

22.09 ⫾ 6.28 (182)

1.37 (2, 179), 0.257

One-way analysis of variance (F) or Pearson ␹2 for dichotomies compared three groups of subjects based on hypertension (HTN) and medication status (HTN-med, HTN-nomed, and no-HTN). Demographic characteristics were age at death, education level, sex, and race. Clinical characteristics were Clinical Dementia Rating scale (CDR), presence of an APOE ␧4 allele, and body mass index (BMI).

with salutary properties have been inconsistent. The associations between HTN and clinically diagnosed AD4 and hippocampal atrophy14 were less apparent in medicated than nonmedicated subjects. In contrast, several investigators failed to find treatment effects in reducing late-life AD or dementia,21-24 which may reflect methodologic factors including variance in estimates of dementia prevalence,25 and imprecision of clinical diagnoses in distinguishing among the various types of dementia.25,26 Alternatively, overmedication may induce hypotension, which has been correlated with cognitive deficits in persons 80 years and older.27,28 Interestingly, lower dementia risk has been reported in elderly subjects with persistent elevated BP, despite antihypertensive treatments, compared to normotensive subjects29 and to controlled medicated hypertensive subjects.19 This postmortem study was designed to determine the specific association of AD neuropathology with midlife or late-life HTN, and the effect of antihypertensive treatments. The extent of neuropathology was evaluated by Consortium to Establish a Registry for Alzheimer’s Disease (CERAD),30 NP and NFT density ratings, and quantitative neocortical NP counts. Persons with sole or comorbid cerebrovascular disease were excluded to permit direct study of the association of HTN and treatment of HTN with the cardinal neuropathologic lesions of AD. METHODS Subjects. Postmortem brains were received over a period of 20 years by the Mount Sinai School of Medicine

(MSSM) Department of Psychiatry Brain Bank. Demographic characteristics from the 291 subjects are shown in table 1. Brains were donated by the next of kin of deceased residents of the Jewish Home and Hospital (JHH) in Manhattan and Bronx, NY, and other New York City area nursing homes (NH) or elder-living facilities participating in studies of aging and early dementia. All assessments were approved by the institutional review boards of the JHH and MSSM; consent for autopsy and neurobiological studies of the brain was obtained from the legal next of kin of all donors. Inclusion criteria were age at death at least 60 years and either normal brain tissue or primary neuropathology with only AD-associated lesions30 as described below.

Assessment of HTN. Extensive medical records, with a medical history and physical examination at admission and medical examinations monthly, were available on all subjects. HTN status was based upon a diagnosis by the admitting or primary care physician (a geriatrician or internist), or from documented treatment with antihypertensive medications. When hypertension was not specifically addressed in the medical record, the American Heart Association criterion for abnormal blood pressure of ⱖ140/90 mm Hg31 was used, while recognizing that specific values may be less clinically meaningful in the elderly.32 Information on duration and treatment of HTN before NH admission was not consistently available.

Antihypertensive medications. Hypertensive subjects were further classified as medicated or not medicated according to their recorded medication histories and supervised intake. The sample was grouped into 77 (26.5%) HTN-med, 42 (14.4%) HTN-nomed, and 172 (59.1%) no-HTN. Medications were classified into pharmacologic categories.33 Only four categories that included over 10% of the 77 HTN-med subjects were used for analysis: ACE inhibitors including angiotensin receptor blocking agents, ␤-blockers (BB), calcium channel blockers (CCB), and thiazide diuretics. For each pair of categories of HTN medications, at least six subjects took both. Cognitive and functional assessment. The Clinical Dementia Rating scale (CDR) assesses cognitive and functional impairments associated with dementia and provides specific severity criteria for classifying subjects as no dementia (CDR ⫽ 0), questionable dementia (CDR ⫽ 0.5), or increasing levels of severity of dementia from CDR ⫽ 1 to CDR ⫽ 5.34 A previously described multistep approach was applied for the postmortem assignment of CDR for all subjects, based on cognitive and funcNeurology 72

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Table 2

CERAD neuropathologic comparisons by HTN status

Diagnosis

HTN-med, % (n)

HTN-nomed, % (n)

No-HTN, % (n)

Total, % (n)

Normal (1)

37.7 (29)

31.0 (13)

22.7 (39)

27.8 (81)

Definite AD (2)

40.3 (31)

54.8 (23)

68.0 (117)

58.8 (171)

Probable AD (3)

7.8 (6)

9.5 (4)

4.7 (8)

6.2 (18)

Possible AD (4)

14.3 (11)

4.8 (2)

4.7 (8)

7.2 (21)

Pearson ␹2 ⫽ 20.56 (df ⫽ 6) compared three groups of subjects based on HTN and medication status (HTN-med, HTN-nomed, and no-HTN). p ⬍ 0.002. AD ⫽ Alzheimer disease; CERAD ⫽ Consortium to Establish a Registry for Alzheimer’s Disease; HTN ⫽ hypertension.

tional status during the last 6 months of life.35,36 Research staff, blind to both the hypotheses being tested and to neuropathology findings, conducted structured CDR assessments of subjects during life, reviewed detailed neuropsychological testing results and medical records, and whenever possible, conducted in-depth structured interviews with staff, family caregivers, or both, to obtain information about antemortem functional and cognitive status. The CDR average score for the 6-month perimortem period was 2.58 ⫾ 1.83, reflecting generally moderate to severe dementia.

Neuropathologic assessment. The neuropathologic assessment procedures we used have been described in detail.35,36 Standardized representative blocks from superior and midfrontal gyrus (MFG), orbital cortex, basal ganglia with basal forebrain, amygdala, Hipp (rostral and caudal levels with adjacent parahippocampal and inferior temporal cortex), superior temporal gyrus (STG), parietal cortex (angular gyrus), calcarine cortex, hypothalamus with mammillary bodies, thalamus, midbrain, pons, medulla, cerebellar vermis, and lateral cerebellar hemisphere were examined using hematoxylin and eosin, modified Bielschowsky, modified thioflavin S, and anti-␤ amyloid and anti-tau when necessary. Neuropathologists (e.g., D.P.P.) were blinded to all clinical and psychometric data while evaluating slides for presence and extent of relevant neuropathologic lesions. Every case was evaluated for the extent of neuropathologic lesions using the CERAD neuropathologic battery30 to quantify NPs and NFTs in seven previously defined regions (Hipp [CA1], entorhinal cortex [EC], amygdala, MFG, STG, the inferior parietal lobule [IPL], and the occipital calcarine cortex [OC]) using the four-point CERAD scale (0 ⫽ none, 1 ⫽ sparse, 3 ⫽ moderate, 5 ⫽ severe).35,36 Additionally, quantitative data regarding NP densities were collected in five cortical regions (MFG, orbital frontal cortex, STG, IPL, and OC) using previously published methods36 and mean plaque density per mm2 was calculated for each region. The qualitative CERAD neuropathologic diagnoses were also evaluated (table 2). The neuropathology-based inclusion/ exclusion criteria for the selected cases were similar to those already described.37 They consisted of persons whose neuropathologic examination revealed either no significant neuropathology (CERAD30 neuropathology diagnosis of 1) or primary neuropathology of AD (CERAD neuropathology diagnosis of 2 [definite AD], 3 [probable AD], or 4 [possible AD]), with no significant secondary diagnoses (e.g., significant cerebrovascular lesions [as defined by CERAD or Tomlinson et al.38] or Lewy bodies with or without NPs and NFTs).

Statistical analyses. One-way analysis of variance (ANOVA), or Pearson ␹2 for dichotomies, compared three groups of sub1722

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jects based on HTN and medication status (HTN-med, HTNnomed, and no-HTN) on demographic (age at death, educational level, sex, and race) and clinical (CDR, presence of an APOE ␧4 allele, and body mass index [BMI]) characteristics. ANOVA compared HTN-med, HTN-nomed, and noHTN groups on 24 direct neuropathologic measures: regional CERAD NP and NFT ratings from all seven brain regions, sums of NP and NFT ratings from neocortex (MF, SMT, IP, and OV) and all seven regions, and the five NP counts and their mean. To describe the pattern of group differences, similar ANOVAs were calculated for each pair of groups. The Holm39 procedure was used to control for 24 multiple tests of significance of NP and NFT densities, at the 0.05 experiment-wise significance level. For these analyses, comparing the different diagnostic and medication categories (HTN-med, HTN-nomed, and noHTN), only Holm-corrected significances of p ⬍ 0.05 are reported unless otherwise indicated. Additionally, to provide an overall measure of AD-associated neuropathology that was not penalized for multiple comparisons, a quantitative neuropathologic average for AD-associated lesions was calculated from the standardized scores of the 19 distinct regional NP and NFT density measurements. Analyses of HTN medication categories and pairs of categories were limited to HTN-med subjects, excluding HTN-nomed subjects. Analysis of covariance (ANCOVA) compared subjects using or not using the HTN medication category, controlling for use of the other HTN medication categories. For each pair of HTN medication categories, a two-way ANCOVA assessed the effects on neuropathology of the two categories, with the other HTN medication categories as covariates. ANCOVA was also used to evaluate the effect of controlling for age at death, educational level, sex, race, presence of the APOE ␧4 allele, or BMI when comparing the three groups on neuropathology measures and the neuropathologic average. CDR was not used as a covariate because the requirement of homogeneous regression coefficients necessary for ANCOVA was often not satisfied. RESULTS Comparisons of the three groups on the demographic and clinical characteristics used as covariates in secondary analyses are presented in table 1. The average age at death was 83.4 ⫾ 10.4 years; 174 (59.8%) were female. No-HTN subjects were slightly younger at death than those in the other two groups (p ⫽ 0.025; F ⫽ 3.74; df ⫽ 2,288). The three groups differed on race (p ⬍ 0.0005; ␹2 ⫽ 16.28; df ⫽ 2); white subjects included fewer HTN-med and more no-HTN subjects than all others. HTNmed subjects had the lowest level of dementia (lowest CDR) and no-HTN subjects had the highest (p ⬍ 0.0005; F ⫽ 11.51; df ⫽ 2,288). Correspondingly, HTN-med subjects had the highest proportions of CERAD normal, and lowest of CERAD definite AD diagnoses, whereas no-HTN subjects had fewest CERAD normal and most CERAD definite AD (p ⬍ 0.002; ␹2 ⫽ 20.56; df ⫽ 6; see table 2). The groups did not differ on educational level, sex, presence of the APOE ␧4 allele, or BMI. Comparisons of the three groups on the direct neuropathology density measures and the neuro-

Figure

Means and standard errors of means for three groups based on hypertension (HTN) and medication status

*p ⬍ 0.05 for analysis of variance comparing the three groups after Holm correction for multiple tests of significance. (A) Alzheimer disease (AD) neuritic plaque (NP) density scores. Left axis: Consortium to Establish a Registry for Alzheimer’s Disease (CERAD) rating scores reflecting NP density (with and without cores) for specific brain regions: hippocampus (Hipp), amygdala (Amyg), entorhinal cortex (EC), mid frontal cortex (MF), superior middle temporal cortex (SMT), inferior parietal cortex (IP), and occipital primary visual cortex (OC). Right axis: Sum of CERAD rating scores: NP1 sums MF, SMT, IP, and OC; NP2 sums Hipp, Amyg, EC, MF, SMT, IP, and OC. (B) AD neurofibrillary density scores. Left axis: CERAD rating scores reflecting neurofibrillary tangle density in various brain regions (Hipp, Amyg, EC, MF, SMT, IP, and OC). All except NFT in Hipp EC and OV were significant (p ⬍ 0.021 to p ⬍ 0.0005). Right axis: Sum of CERAD rating scores: NFT1 sums MF, SMT, IP, and OC; NFT2 sums Hipp, Amyg, EC, MF, SMT, IP, and OC. (C) Mean plaque density per mm2: total NP counts (with and without cores) in CERAD-defined neocortical brain regions: middle frontal gyrus (MFG), orbital frontal cortex (OFG), SMT, inferior parietal lobule (IPL), OC, and their mean. (D) Neuropathologic average of standardized NP and NFT density measurements. HTN-med vs no-HTN, p ⬍ 0.0005.

pathologic average are presented in the figure. HTNmed subjects had the least and no-HTN subjects had the most NP and NFT neuropathology (p ⱕ 0.009 with 20 having p ⬍ 0.0005; F ⫽ 4.83 to 17.09; df ⫽ 2,269 to 2,287), except for NFTs in Hipp and EC, where group differences were not significant. The neuropathologic average for AD-associated lesions also differed (p ⬍ 0.0005; F ⫽ 13.56; df ⫽ 2,259). Controlling for age at death, educational level, sex, race, presence of the APOE ␧4 allele, or BMI by ANCOVA yielded comparable effect sizes, for analyses of the direct regional neuropathology measures and the neuropathologic average among the three groups. The significance of brain regional differences among the three groups reflected differences between pairs of groups. There was significantly less neuropathology in the HTN-med than the no-HTN group except NFT in Hipp (p ⱕ 0.011 with 21 comparisons having p ⬍ 0.0005; F ⫽ 6.56 to 33.89; df ⫽ 1,229 to 1,246). The neuropathologic average also differed (p ⬍ 0.0005; F ⫽ 27.56; df ⫽ 1,221). When

comparing HTN-med and HTN-nomed groups, lower neuropathology was noted in NFT ratings in MF and NP counts in IPL and the mean (p ⫽ 0.002 to 0.001; F ⫽ 10.26 to 11.69; df ⫽ 1,116 to 1,117). In contrast, there were no significant differences between the HTN-nomed and no-HTN groups. Additionally, 16 of the remaining differences between the HTN-med and HTN-nomed groups had p ⬍ 0.05 without correction for multiple testing, but no differences between HTN-nomed and no-HTN groups achieved p ⬍ 0.05. None of the comparisons involving the effects of antihypertensive medication categories or pairs of categories on NP or NFT neuropathology achieved statistical significance after correcting for multiple comparisons. Nonetheless, in all evaluations of medication categories with p ⬍ 0.05, medication users of BB or CCB had less neuropathology than nonusers (p ⫽ 0.045 to 0.021; F ⫽ 4.13 to 5.52; df ⫽ 1,87 to 1,88). The results of this study showed consistently and robustly less AD-associated neuropa-

DISCUSSION

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1723

thology in hypertensive persons who had been treated pharmacologically for HTN relative to normotensive subjects. The only exception was no effect of HTN or medication on NFT density in the hippocampus. Since hippocampal involvement has been implicated in the course of AD and in normal aging, the relatively late-life postmortem assessments performed in this study may not have been sensitive to HTN and HTN medication effects in this region.35 The present results identified differences between HTN-med and HTN-nomed groups but not between HTN-nomed and no-HTN groups. Thus differences observed in the severity of AD-associated pathology are more likely to be attributable to HTN medication than to HTN per se. This is consistent with clinical findings of lower dementia risk in subjects with persistent elevated BP, despite antihypertensive treatments.19,29 Furthermore, these results, consistent with the Honolulu Asia Aging Study (HAAS) and Rotterdam findings,13,14 provide a neuropathologic basis to support the clinical18,20 and population studies4,15-17,19 that found significant reductions in dementia and AD risk in persons treated with antihypertensive medications. Antiamyloidogenic and neuroprotective effects of the antihypertensive drug valsartan were reported in the Tg2576 AD mouse model, even at a dose corresponding to half the lowest recommended dose for HTN treatment in humans,33 providing evidence that at least some antihypertensive medications can directly affect biologic processes involved in AD. Together with these results, this study suggests that antihypertensive medications may have a salutary effect against ADassociated neuropathology. The findings that HTN-nomed subjects had comparable neuropathology to no-HTN subjects differ in part from the HAAS,13 where nonmedicated subjects with normal midlife DBP had less AD neuropathology than nonmedicated subjects who had borderline or high midlife DBP. Many clinical comparisons of hypertensive subjects to nonmedicated normotensive subjects— both medicated and nonmedicated—showed either no effects of HTN or deleterious effects consistent with HAAS. Discrepant results among these studies may be attributed not only to diagnostic criteria differences for HTN and dementia, but also to age-related differences: defining midlife and late life, at study entry, and for hypertension diagnosis. The present findings of uniformly less neuropathology in untreated hypertensive subjects than normotensive subjects, although not significant, are consistent with a clinical report of better cognitive performance in untreated hypertensive subjects compared with normotensive subjects in a very old population.29 Furthermore, the 1724

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pattern that emerges from a review of the longitudinal and cross-sectional investigations of HTN and cognitive functioning is that, although elevated midlife hypertension is associated with cognitive decline in late life, mild hypertension after 70 years of age may be protective against AD-associated neuropathologic lesions.40 Further studies are necessary to investigate how the possibly nonlinear relationship of BP and cognition decline varies with age. The differences between the current findings and the HAAS neuropathologic results may be attributable to the operationalization of hypertension as midlife DBP, compared with a late-life or prior diagnosis of hypertension in the present study. Additionally, there were major demographic differences between the two studies: HAAS subjects were community-based, all male, and all of Japanese descent, in contrast to our NH sample, of which the majority had dementia, were women, and were Caucasians. Finally, the no-HTN group was more likely than the HTN-nomed group to include subjects with hypotension, which has been correlated with cognitive deficits in persons 80 years and older.27,28 A potential confound in the present study is that hypertension in the HTN-med group was presumably more severe than in the HTN-nomed group. This possibility suggests the need for caution in attributing the current findings to the beneficial effects of HTN medications alone. Intuitive interpretations and results from the population studies cited above would suggest that the more severely ill subjects should have had more neuropathology. Therefore, this cannot explain the significantly lower levels of AD-associated neuropathology observed in the HTN-med group of this study. In the present study, the three groups differed significantly in dementia severity (CDR), consistent with the very strong correlations between neuropathology and CDR. A medication effect on neuropathology is consistent with differences in cognitive performance observed in some clinical studies of HTN medication effects.18,20 The groups also differed significantly in age at death, albeit minimally with mean differences less than 3.5 years, but ANCOVA adjusting for the effect of age at death did not change the results. Similarly, ANCOVAs of the three groups, controlling for educational level, sex, race, presence of an APOE ␧4 allele, or BMI, showed comparable results, suggesting that the conclusion of observed group differences was not appreciably influenced by these characteristics. The analyses of antihypertensive medication categories and pairs of categories, limited to HTN-med subjects, had reduced power due to the relatively small sample. Thus findings with p ⬍ 0.05 that did

not reach significance after correction for multiple tests should be interpreted with caution. However, all drug category results with p ⬍ 0.05 indicated that treated subjects had less neuropathology than untreated subjects. The exploratory nature of these comparisons warrants caution, but they provide impetus for future prospective investigations of the effects of different classes of potentially beneficial anti-HTN medications as well as interactions among them. The apparent effects of HTN medication must be interpreted with caution due to the cross-sectional design of this and all postmortem observational studies. This study was further limited by the lack of reliable information on the etiology, extent, and severity of prestudy enrollment hypertension, length and effectiveness of preenrollment therapy, changing criteria for the diagnosis and treatment of HTN over time, medications used before late-life enrollment in our longitudinal study and consequent potential misclassification of subjects. Thus, although the current study suggests that treatment of HTN may beneficially influence the hallmark neuropathologic lesions of AD and AD-associated dementia, firm conclusions must await confirmatory and prospective studies. In contrast to the limitations of prestudy HTN history outlined above, a strength of this study was that its observations (averaging approximately 3.5 years) regarding HTN status and HTN medications were based on close supervision and well-maintained medical records. Misclassification among the three groups was therefore unlikely, given the comprehensive, supervised medical care and detailed records in the nursing home/hospital setting, as opposed to selfreport and often self-medicating practices among community dwellers. Even if some hypertensive subjects were medicated before entering this study but not during it (perhaps due to therapeutic prejudice by physicians reticent to treat a chronic condition in patients with advanced cognitive loss), misclassification of HTN-med subjects as HTN-nomed would only reduce the strength but not change the direction of the observed effects. Similarly, if subjects were diagnosed with hypertension before entering this study and not medicated, but not diagnosed as hypertensive during the study, misclassification of HTNnomed subjects as no-HTN would tend to reduce the magnitude of any differences between these two groups. Additionally, both types of misclassification would reduce the differences between the HTN-med and no-HTN groups. Therefore, the highly significant findings demonstrating consistently robust differences of lower AD neuropathology in HTN-med than no-HTN subjects can be viewed with relatively high confidence. The relatively large sample sizes

used in this study and the use of quantitative counts as well as qualitative CERAD ratings provide additional confidence in the results. AUTHOR CONTRIBUTIONS Statistical analysis was performed by James Schmeidler and Lisa B. Hoffman.

Received September 4, 2008. Accepted in final form January 5, 2009. REFERENCES 1. Luchsinger JA, Reitz C, Honig LS, Tang MX, Shea S, Mayeux R. Aggregation of vascular risk factors and risk of incident Alzheimer disease. Neurology 2005;65:545–551. 2. Elias MF, Wolf PA, D’Agostino RB, Cobb J, White LR. Untreated blood pressure level is inversely related to cognitive functioning: The Framingham Study. Am J Epidemiol 2008;138:353–364. 3. Peila R, White LR, Petrovich H, et al. Joint effect of the APOE gene and midlife systolic blood pressure on late-life cognitive impairment: the Honolulu-Asia Aging Study. Stroke 2001;32:2882–2887. 4. Launer LJ, Ross GW, Petrovitch H, et al. Midlife blood pressure and dementia: the Honolulu-Asia Aging Study. Neurobiol Aging 2000;21:49–55. 5. Skoog I, Gustafson D. Hypertension and related factors in the etiology of Alzheimer’s disease. Ann NY Acad Sci 2002;977:29–36. 6. Yoshitake T, Kiyohara Y, Kato I, et al. Incidence and risk factors of vascular dementia and Alzheimer’s disease in a defined elderly Japanese population: the Hisayama Study. Neurology 1995;45:1161–1168. 7. Morris MC, Scherr PA, Hebert LE, Glynn RJ, Bennett DA, Evans DA. Association of incident Alzheimer disease and blood pressure measured from 13 years before to 2 years after diagnosis in a large community study. Arch Neurol 2001;58:1640–1646. 8. Yamada M, Kasagi F, Sasaki H, Masunari N, Mimori Y, Suzuki G. Association between dementia and midlife risk factors: the Radiation Effects Research Foundation Adult Health Study. J Am Geriatr Soc 2003;51:410–414. 9. Lindsay J, Laurin D, Verreault R, et al. Risk Factors for Alzheimer’s disease: a prospective analysis from the Canadian Study of Health and Aging. Am J Epidemiol 2002; 156:445–453. 10. Skoog I, Lernfelt B, Landahl S, et al. 15-year longitudinal study of blood pressure and dementia. Lancet 1996;347: 1141–1145. 11. Kivipelto M, Helkala EL, Laakso MP, et al. Midlife vascular risk factors and Alzheimer’s disease in later life: longitudinal, population based study. BMJ 2001;322:1447–1451. 12. Kilander L, Nyman H, Boberg M, Hansson L, Lithell H. Hypertension is related to cognitive impairment: a 20-year follow-up of 999 men. Hypertension 1998;31:780–786. 13. Petrovitch H, White LR, Izmirilian G, et al. Midlife blood pressure and neuritic plaques, neurofibrillary tangles, and brain weight at death: the HAAS: Honolulu-Asia Aging Study. Neurobiol Aging 2000;21:57–62. 14. Korf ESC, White LR, Scheltens P, Launer LJ. Midlife blood pressure and the risk of hippocampal atrophy: the Honolulu Asia Aging Study. Hypertension 2004;44:29–34. 15. Guo ZC, Fratiglioni L, Zhu L, Fastbom J, Winbald B, Viitanen M. Occurrence and progression of dementia in a community population aged 75 years and older: relationNeurology 72

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Duration of antihypertensive drug use and risk of dementia A prospective cohort study

M.D.M. Haag, PharmD A. Hofman, PhD P.J. Koudstaal, PhD M.M.B. Breteler, PhD B.H.C. Stricker, PhD

Address correspondence and reprint requests to Dr. Bruno H.C. Stricker, Department of Epidemiology, Erasmus Medical Center, P.O Box 2040, 3000 CA Rotterdam, The Netherlands [email protected]

ABSTRACT

Background: The evidence from prospective observational research for a protective effect of antihypertensive drug use on the risk of dementia is far from uniform. Duration of follow-up was limited and relied mainly on baseline drug exposure data without information on duration of use. We investigated the association between the duration of antihypertensive use and risk of dementia.

Methods: We followed 6,249 participants (mean 68.4 years, 60% women) of a prospective, population-based cohort from baseline (1990 –1993) until 2005 for incident dementia. Continuous data on filled prescriptions came from pharmacy records. Total cumulative duration of antihypertensive use was expressed in years. We subtracted a latent 4-year period before the date of dementia diagnosis in the quantification of exposure duration to avoid potential bias in antihypertensive prescription due to prodromal changes in blood pressure or cognition. With Cox regression models, we calculated crude and adjusted hazard ratios (HRs) of all dementia and Alzheimer disease (AD) with antihypertensive use vs never used. Results: Compared to never used, antihypertensive use was associated with a reduced risk of all dementia (adjusted HR per year of use 0.95; 95% confidence interval [CI] 0.91– 0.99). We observed an 8% (95% CI ⫺15% to ⫺1%) risk reduction per year of use for persons ⱕ75 years, whereas for persons ⬎75 years this was 4% (95% CI ⫺11% to 4%). Equivalent estimates were observed for AD. No apparent differences were observed among different types of antihypertensive drugs. Conclusions: Antihypertensive drug use was associated with 8% risk reduction of dementia per year of use for persons ⱕ75 years. Neurology® 2009;72:1727–1734 GLOSSARY ACE ⫽ angiotensin-converting enzyme; AD ⫽ Alzheimer disease; AT2 ⫽ angiotensin-2; ATC ⫽ Anatomic Therapeutic Chemical; BMI ⫽ body mass index; BP ⫽ blood pressure; CCB ⫽ calcium channel blocker; CHD ⫽ coronary heart disease; CI ⫽ confidence interval; DBP ⫽ diastolic blood pressure; DHP ⫽ dihydropyridine; DM ⫽ diabetes mellitus; DSM ⫽ Diagnostic and Statistical Manual of Mental Disorders; GMS ⫽ Geriatric Mental State schedule; HR ⫽ hazard ratio; MI ⫽ myocardial infarction; MMSE ⫽ Mini-Mental State Examination; NINCDS-ADRDA ⫽ National Institute of Neurological and Communicative Disorders and Stroke–Alzheimer’s Disease and Related Disorders Association; NINDS-AIREN ⫽ National Institute of Neurological Disorders and Stroke–Association Internationale pour la Recherche en l’Enseignement en Neurosciences; OR ⫽ odds ratio; RR ⫽ relative risk; SBP ⫽ systolic blood pressure.

Hypertension is a risk factor for cerebrovascular disease and consequently for vascular dementia. The association between hypertension and Alzheimer disease (AD) is less clear.1 Follow-up studies generally showed that high blood pressure in midlife is associated with an increased risk of AD.2 In contrast, high blood pressure later in life appears to lower the risk of AD.3 It was also suggested that in the preclinical stage of AD blood pressure declines, possibly due to imminent disease.4 Editorial, page 1716 See also page 1720 e-Pub ahead of print on February 18, 2009, at www.neurology.org. From the Departments of Epidemiology (M.D.M.H., A.H., M.M.B.B., B.H.C.S.), Neurology (P.J.K.), and Internal Medicine (B.H.C.S.), Erasmus Medical Center, Rotterdam; and Inspectorate for Health Care (B.H.C.S.), The Hague, The Netherlands. The Rotterdam Study is supported by the Erasmus Medical Center and Erasmus University Rotterdam, the Netherlands Organization for Scientific Research, the Netherlands Organization for Health Research and Development, the Research Institute for Diseases in the Elderly, the Ministry of Education, Culture and Science, the Ministry of Health, Welfare and Sports, the European Commission, and the Municipality of Rotterdam. Disclosure: The authors report no disclosures. Copyright © 2009 by AAN Enterprises, Inc.

1727

Table 1

Prospective observational studies on the association between antihypertensive drug use and risk of dementia Age, y Design (mean)

Ref.

Description

36, 37

Kungsholmen Project; 1st and 2nd phase

Cohort

ⱖ75 (85.3)

38

EPESE

Cohort

ⱖ65 (72)

39

Rotterdam Study

Cohort

ⱖ55 (68.1)

40

CSHA

Casecontrol

ⱖ65 (72)

18

Kungsholmen Project

Cohort

ⱖ75

5

Baltimore Longitudinal Study of Aging

Cohort

ⱖ60 (67.1)

1,092

32

Cache Cohort County Study

ⱖ65 (74.1)

3,227

6

Honolulu Asia Aging Study on Japanese American men

ⱖ72 (76)

1,294

Cohort

No. 1,301

Follow-up, y Outcome

Exposure assessment

Covariates

Main results

3.0

Dementia (n ⫽ 199)

Baseline interview

Age, sex, MMSE, education, SBP or DBP, heart disease, stroke

1st phase: RR all dementia with any antihypertensive use, RR 0.7 (95% CI, 0.6–1.0) vs no use; 2nd phase: RR dementia 0.8 (95% CI, 0.6–1.0) and AD 0.7 (95% CI, 0.5–0.9) vs no use

4

AD (NINCDSADRDA) (n ⫽ 90)

Baseline interview

Age, sex, education

4-year risk of AD vs no use with: any antihypertensive use OR 0.66 (95% CI 0.68–2.61); thiazides OR 1.33 (95% CI 0.68–2.61); K⫹ sparing diuretics OR 0.63 (95% CI 0.72–0.96); loop diuretics OR 1.06 (95% CI 0.37–3.06); ␤-blockers OR 0.91 (95% CI 0.26–3.17)

6,416

2.2

Dementia (DSM-III-R, n ⫽ 118), AD (NINCDSADRDA, n ⫽ 82)

Baseline interview

Age, sex, BMI, stroke, smoking, DM, MMSE, BP, living situation, peripheral arterial disease

Risk of dementia vs no use with: any antihypertensive use RR 0.67 (95% CI 0.45–1.00); CCB RR 0.70 (95% CI 0.32–1.52); diuretics RR 0.83 (95% CI 0.33–1.30); risk of AD vs no use with any antihypertensive use RR 0.77 (95% CI 0.49–1.24)

4,088

5

AD (DSMIV, n ⫽ 194)

Baseline survey

Age, sex, education

Risk of AD with any antihypertensive use vs no use OR 0.91 (95% CI 0.64 –1.30)

5.7

AD (DSMIII-R, n ⫽ 204)

Baseline interview

Age, sex, MMSE, vascular disease, education

Risk of AD for any antihypertensive drug use vs no use RR 0.6 (95% CI 0.5–0.9)

AD (NINCDSADRDA, n ⫽ 115)

Interview every 2 years

Age, sex, SBP, DBP, education, smoking, heart problems

Risk of AD vs no use of CCBs for: CCB RR 0.63 (95% CI 0.31–1.28); DHPCCB RR 0.30 (95% CI 0.07–1.25); nonDHP-CCB RR 0.82 (95% CI 0.37–1.83)

3.2

Dementia (DSM-III-R, n ⫽ 185), AD (NINDSAIREN, n ⫽ 104)

Baseline interview or medical records if institutionalized

Age, sex, stroke, education, APOE-4, DM, MI, BP, hypercholesterolemia

Risk of AD with; antihypertensive drug use vs no use HR 0.64 (95% CI 0.41– 0.98), diuretics vs no diuretics HR 0.57; 95 CI% 0.33–0.94), K⫹ sparing diuretics vs no K⫹ sparing diuretics HR 0.26 (95% CI 0.08–0.64), ACE-i vs no ACE-i HR 1.17 (95% CI 0.65–1.96), CCB vs no CCB HR 0.91 (95% CI 0.50– 1.55), ␤-blockers vs no ␤-blockers HR 0.67 (95% CI 0.24–1.13)

5.0

Dementia (n ⫽ 108), AD (n ⫽ 65)

Interview at each follow-up visit; data on duration of use at last visit

Age, education, BMI, smoking, CHD, stroke, ankle-brachial index, APOE-4

Risk of dementia: HR 0.94 (95% CI 0.89 to 0.99) and risk of AD HR 0.96 (95% CI 0.93 to 0.99), per year of antihypertensive use

634

966

11

MMSE ⫽ Mini-Mental State Examination; SBP ⫽ systolic blood pressure; DBP ⫽ diastolic blood pressure; RR ⫽ relative risk; AD ⫽ Alzheimer disease; NINCDS-ADRDA ⫽ National Institute of Neurological and Communicative Disorders and Stroke–Alzheimer’s Disease and Related Disorders Association; OR ⫽ odds ratio; CI ⫽ confidence interval; BMI ⫽ body mass index; DSM ⫽ Diagnostic and Statistical Manual of Mental Disorders; DM ⫽ diabetes mellitus; BP ⫽ blood pressure; CCB ⫽ calcium channel blocker; DHP ⫽ dihydropyridine; NINDS-AIREN ⫽ National Institute of Neurological Disorders and Stroke– Association Internationale pour la Recherche en l’Enseignement en Neurosciences; MI ⫽ myocardial infarction; HR ⫽ hazard ratio; ACE ⫽ angiotensinconverting enzyme; CHD ⫽ coronary heart disease.

Evidence from observational research for a protective effect of antihypertensive drugs on the risk of dementia has been far from uniform (table 1). With the exception of two studies,5,6 a major shortcoming of previous observational studies was the availability of merely baseline data on antihypertensive treatment. This considerably increases the chance of exposure misclassification during follow-up and, moreover, prohibits investigation of treatment duration. The intricate relation between blood pressure, age, and dementia risk can also be responsible for the variance in the observed relationships. Fur1728

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thermore, prodromal changes in blood pressure and cognitive decline could lead to changes in antihypertensive prescription or drug intake, both leading to bias.4,7 Hence, the years immediately preceding clinical onset of dementia may not provide the relevant risk period to investigate the effect of antihypertensive drugs on dementia risk. We investigated the association between duration of antihypertensive drug use and the risk of all dementia and AD in a large prospective population-based cohort study, taking into account a latent period in the quantification of treatment duration.8

METHODS Study population. The Rotterdam Study is a prospective, population-based cohort study of age-related disorders.9 The medical ethics committee at Erasmus MC, Rotterdam, the Netherlands, approved the study. Between 1990 and 1993, all persons aged ⱖ55 years living in Ommoord, a district of Rotterdam, were invited to participate. Of 10,275 eligible persons, 7,983 (78%) signed informed consent. Of these, 7,528 (94%) were screened for dementia and 7,046 were free of dementia at baseline.10 Follow-up examinations, including screening and clinical workup for dementia, were conducted in 1993–1994, 1997–1999, and 2000 –2004. In addition, the cohort was continuously monitored for major disease outcomes and death through linkage with records of general practitioners, the Regional Institute for Outpatient Mental Health Care, and bimonthly updates from the municipality records. This resulted in a virtually complete follow-up for dementia until January 1, 2005. Nearly all persons (99.7%) were registered at one or more of seven automated pharmacies serving the Ommoord area. Records of all filled prescriptions were available from January 1, 1991. To ensure at least 6 months medication history, we excluded persons for whom follow-up ended before July 1, 1991.

Assessment of drug exposure. Complete data on filled prescriptions were available on a day-to-day basis from the pharmacy prescription database in automated form. This included the product name, international non-proprietary name, Anatomic Therapeutic Chemical (ATC) code, total number of delivered units (e.g., tablets/capsules), prescribed daily number of units, date of delivery, and drug dosage. The duration of a prescription is calculated as the number of delivered units divided by the prescribed daily number of units. In addition to overall antihypertensive use, we distinguished among the most commonly used types of antihypertensive drugs in the Netherlands, as classified by ATC code. These included ␤-blocking agents, thiazides and high ceiling diuretics, calcium-channel blockers, angiotensin converting enzyme (ACE) inhibitors, angiotensin-2 (AT2) antagonists, and other antihypertensive drugs (centrally acting sympathicolytics, peripheral acting sympathicolytics, and agents acting on arteriolar smooth muscle).

Diagnosis of AD. The diagnosis of dementia was made following a three-step protocol. Screening was done with the Mini-Mental State Examination (MMSE) and Geriatric Mental State schedule (GMS) organic level for all persons.11,12 Screen-positives (MMSE score ⬍26 or GMS organic level ⬎0) underwent the Cambridge examination for mental disorders of the elderly.13 Persons who were suspected of having dementia underwent more extensive neuropsychological testing. When available, imaging data were used. In addition, the total cohort was continuously monitored for incident dementia through computerized linkage between the study database and digitalized medical records from general practitioners and the Regional Institute for Outpatient Mental Health Care. The diagnosis of dementia was made in accordance with internationally accepted criteria for dementia (DSM-III-R), AD (National Institute of Neurological and Communicative Disorders and Stroke–Alzheimer’s Disease and Related Disorders Association), and vascular dementia (National Institute of Neurological Disorders and Stroke– Association Internationale pour la Recherche en l’Enseignement en Neurosciences) by a panel of a neurologist, neurophysiologist, and research physician, blinded to drug exposure of the study population.14-16

Other covariates. Covariates included age, sex, education level, systolic and diastolic blood pressure, current smoking, total

serum cholesterol, body mass index, diabetes mellitus, and cardiovascular and cerebrovascular disease. Education was assessed at the baseline interview and dichotomized into low education (primary education only or low vocational training) and high education (intermediate-level vocational training, secondary education, or university). Smoking status was also self-reported and categorized as ever or never. Total serum cholesterol was measured in nonfasting blood drawn at baseline. Sitting blood pressure was measured on the right upper arm using a random-zero sphygmomanometer. The average of two measurements at one occasion was used. Diabetes mellitus was defined as a nonfasting or 2-hour post load glucose level of ⱖ11.1 mmol/L or antidiabetic medication use at baseline. Cardiovascular disease included myocardial infarction, coronary artery bypass graft, percutaneous transluminal coronary angioplasty, and atrial fibrillation. Cerebrovascular disease included TIA and stroke. Both prevalent and incident cardiovascular and cerebrovascular events were taken into account. APOE genotyping was performed on coded DNA samples, and participants were classified by presence of an APOE-␧4 allele.

Statistical analyses. We calculated the hazard ratio (HR) and 95% confidence intervals (CI) of the risk of all dementia and AD associated with antihypertensive use using a Cox proportional hazards model with antihypertensive use as time-dependent covariate. Calendar time was used as the time-axis in the model to account for changes in prescription guidelines and availability of antihypertensive drugs over time. For all subjects, we calculated the duration of follow-up between start of study and diagnosis of dementia, death, or end of the study period, whichever came first. Because lowering of blood pressure and changes in cognition occur during the latent phase of disease, physicians might change antihypertensive treatment in the prodromal period of dementia. Calculating the cumulative exposure until the date of diagnosis would not take into account such disease-related changes in prescription and this might bias our risk estimates. To avoid this type of bias, we subtracted a potential latent period from the date of diagnosis, for quantification of exposure duration.8 Based on the current knowledge regarding the course of blood pressure1 and cognition in the latent phase of dementia,17 we considered a 4-year prodromal phase for our main analysis. Consequently, at each date of diagnosis minus 4 years we determined cumulative duration of drug until that date for both the person who developed dementia as well as for all persons in the remainder of the cohort. Total cumulative duration of antihypertensive use was expressed in years and as categorical variable based on tertiles of total use at end of follow-up being no use, ⬍1.6 year use, from 1.6 to 5.3 years use, and ⬎5.3 years use. Never use of antihypertensive drugs was the reference in all analyses. In a sensitivity analysis we investigated whether associations differed if we subtracted 2 years from the date of diagnosis or if we used the original date of diagnosis. We anticipated that the association might be modified by age, since the association between blood pressure and dementia appears to be different at older age. Therefore, we reperformed the analyses for persons ⱕ75 years and ⬎75 years of age. Likewise, we investigated whether the associations were different for carriers and noncarriers of an APOE-␧4 allele, by adding an interaction term to a model, and by stratified analyses.18 Using the same exposure definitions, we also investigated the association between separate types of antihypertensive drugs and risk of dementia. A cohort member could contribute person-time to more than one class of antihypertensive drug if a person had used more than one antihypertensive drug during follow-up. Neurology 72

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Table 2

Baseline characteristics of the study population (n ⴝ 6,249)

Characteristics

Values

Age, y, mean (ⴞSD)

68.2 (8.3)

Sex (% women)

3,749 (60)

Smoking, ever, n (%)

3,985 (63.7)

Diabetes mellitus, n (%)

574 (9.2)

Systolic blood pressure, mm Hg, mean (ⴞSD)

139.0 (21.6)

Cardiovascular disease, n (%)*

945 (15.2)

Cerebrovascular disease, n (%)†

303 (4.8)

Total cholesterol, mmol/L, mean (ⴞSD)

6.7 (1.2)

Body mass index, kg/m2, mean (ⴞSD)

26.4 (3.6)

Primary education, low vocational training or less, n (%)

2,275 (36.4)

*Myocardial infarction, coronary artery bypass graft, percutaneous transluminal coronary angioplasty, atrial fibrillation, and heart failure. †Stroke or transient ischemic attack.

All analyses were adjusted for age, sex, and systolic and diastolic blood pressure (model I). To adjust for potential confounders we additionally included smoking, total serum cholesterol, education, body mass index, diabetes mellitus, and cardiovascular and cerebrovascular disease (model II). Missing values for continuous variables were imputed with linear regression analyses using sex, age, and dementia outcome as determinants. For categorical variables we used a missing indicator for missing values. Analyses were performed with SPSS 16.0 and SAS 9.1 software.

In total, 6,249 persons were included in the analysis. In table 2, baseline characteristics of the study population are given. Persons were followed up to 13.3 years (average 8.0 years), with a total of 49,829 person-years of follow up. During follow-up, 527 persons developed dementia, of whom 432 were diagnosed with AD, 50 with vascular dementia, and

RESULTS

Table 3

45 with other types of dementia. The total number of filled antihypertensive prescriptions during follow-up was 54,584. Of the 527 persons who developed dementia, 264 persons had used antihypertensive drugs during follow-up, whereas 263 persons never used antihypertensive drugs. Compared to never used, antihypertensive use was associated with a reduced risk of all dementia. HRs for AD were nearly equivalent (table 3). There was an evident duration–response relationship as the risk of all dementia decreased with longer duration of cumulative use, resulting in a 5% risk reduction per year of use (table 3). Correspondingly, the strongest risk reduction was observed with long-term use of antihypertensive drugs (⬎5.3 years), whereas shortterm use of antihypertensive drugs (⬍1.6 years) was not associated with a reduced risk of dementia or AD. The association between antihypertensive use and dementia was modified by age (pinteraction ⫽ 0.003). For people aged ⱕ75 years, antihypertensive drugs reduced the risk of dementia with 8% per year of use (table 4). For people aged ⬎75 years, we observed a risk reduction of 4% per year of use. Although the protective effect of antihypertensive drugs on dementia risk seemed stronger for carriers of an APOE-␧4 allele, numbers across strata were low and the interaction between APOE-␧4 and antihypertensive drug use was not significant (pinteraction ⫽ 0.9) (data not shown). No apparent differences among the various types of antihypertensive drugs were observed. Adjusted HRs of all dementia per year of use were as follows: 0.97 (95% CI 0.90 –1.05) for thiazide diuretics; 0.89 (95% CI 0.78 –1.01) for high ceiling diuretics; 0.93 (95% CI 0.87–1.00) for ␤-blockers; 1.00 (95% CI 0.91–1.09) for calcium channel antagonists; 1.07

Hazard ratios (HR) of all dementia and Alzheimer disease with use of antihypertensive drugs All dementia (n ⴝ 527)

Alzheimer disease (n ⴝ 432)

HR (95% CI) Cases Never use

263

HR (95% CI)

Model I*

Model II† 1.00 (ref)

Cases 214

Model I*

Model II† 1.00 (ref)

Antihypertensive drug use <1.6 y

126

0.94 (0.75–1.17)

0.90 (0.72–1.13)

102

0.92 (0.73–1.18)

0.91 (0.71–1.17)

1.6–5.3 y

98

0.77 (0.60–0.99)

0.72 (0.56–0.93)

83

0.75 (0.57–0.98)

0.73 (0.55–0.96)

>5.3 y

40

0.71 (0.49–1.03)

0.68 (0.47–0.99)

33

0.70 (0.47–1.05)

0.69 (0.46–1.05)

Per year treatment

264

0.95 (0.91–1.00)‡

0.95 (0.90–0.99)

218

0.95 (0.90–0.99)

0.94 (0.90–0.99)

*Model I: age, sex, and systolic and diastolic blood pressure adjusted. †Model II: as model I, additionally adjusted education, smoking, total serum cholesterol, body mass index, diabetes mellitus, and cardiovascular and cerebrovascular disease. ‡Upper limit of confidence interval ⬍1.00, p ⬍ 0.05. 1730

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Table 4

Hazard ratios (HR) of all dementia and Alzheimer disease with use of antihypertensive drugs across strata of age All dementia

Alzheimer disease

HR (95% CI) Cases

HR (95% CI)

Model I*

Model II†

Cases

Model I*

Model II†

<75 years of age Never use

139

1.00 (ref)

110

1.00 (ref)

Antihypertensive use <1.6 y

60

1.08 (0.80–1.47)

1.03 (0.75–1.41)

48

1.11 (0.78–1.57)

1.11 (0.78–1.56)

1.6–5.3 y

42

0.72 (0.50–1.03)

0.68 (0.47–0.99)

32

0.66 (0.44–1.00)

0.67 (0.55–1.02)

>5.3 y

19

0.59 (0.36–0.99)

0.56 (0.33–0.95)

14

0.56 (0.31–1.01)

0.57 (0.41–1.04)

Per year treatment

121

0.93 (0.87–0.99)

0.92 (0.86–0.98)

94

0.91 (0.85–0.98)

0.92 (0.85–0.99)

>75 years of age Never use

124

1.00 (ref)

104

1.00 (ref)

Antihypertensive use <1.6 y

66

0.81 (0.60–1.10)

0.76 (0.56–1.04)

54

0.79 (0.56–1.10)

0.75 (0.53–1.06)

1.6–5.3 y

56

0.75 (0.53–1.05)

0.68 (0.48–0.96)

51

0.76 (0.53–1.09)

0.70 (0.48–1.02)

>5.3 y

21

0.89 (0.52–1.52)

0.83 (0.48–1.43)

19

0.90 (0.51–1.59)

0.85 (0.48–1.51)

Per year treatment

143

0.98 (0.91–1.04)

0.97 (0.90–1.04)

124

0.97 (0.90–1.04)

0.96 (0.89–1.04)

*Model I: age, sex, and systolic and diastolic blood pressure adjusted. †Model II: as model I, additionally adjusted education, smoking, total serum cholesterol, body mass index, diabetes mellitus, and cardiovascular and cerebrovascular disease.

(95% CI 0.99 –1.09) for ACE inhibitors, 0.85 (95% CI 0.44 –1.66) for AT2 antagonists; and 1.04 (95% CI 0.88 –1.24) for other antihypertensive drugs. Similar estimates were found for AD risk. In the sensitivity analyses, estimates for risk of dementia gradually attenuated if shorter prodromal periods were considered. We observed a 4% risk reduction (0% to 7%, p ⫽ 0.03) if 2 years were subtracted from the date of diagnosis to 3% (0% to 6%, p ⫽ 0.03) per year of antihypertensive use if the original date of diagnosis was used. In the general population, we found that antihypertensive drug use was associated with decreased risk of all dementia and AD with 8% per year of use for people ⱕ75 years of age. No apparent differences were observed among the various types of antihypertensive drugs. Strengths of our study design included its prospective design, large number of participants, a general population-based setting, and the long follow-up period of over 8 years average. Moreover, we used pharmacy records for the assessment of antihypertensive drug use. This greatly reduces the chance of exposure misclassification as opposed to baseline exposure data or periodic reassessment of drug use and allows for an accurate estimation of exposure duration. In an earlier study, we demonstrated that there was a high concordance between pharmacy fillDISCUSSION

ing data of cardiovascular drugs and actual use according to a patient interview.19 Moreover, we were able to subtract 4 years from the date of clinical diagnosis of dementia to avoid potentially biased risk estimates as a result of changes in antihypertensive prescription due to blood pressure changes or cognitive decline in the prodromal phase of dementia. Nevertheless, some issues warrant consideration. First, the 4-year period is an average estimation of the prodromal period based on the available data from literature. There is, however, limited longitudinal data on the course of blood pressure before clinical dementia. Data from the Kungsholmen Project shows that blood pressure markedly decreases over a 3-year period preceding diagnosis of dementia.20 The Go¨teborg longitudinal study revealed that a decline in systolic blood pressure between age 70 and 75 was the only predictor of dementia with onset at age 75 to 79.21 Likewise, estimations of the intervals between cognitive decline and dementia vary from 1.5 years to up to 10 years, but generally suggest a more rapid decline in the last 2 to 3 years before diagnosis.22-24 In a sensitivity analysis, we also investigated the association of antihypertensive drug use and dementia subtracting only 2 years from the date of diagnosis for quantification of exposure duration, and also the date of diagnosis itself. Though protective effects of antihypertensive drug use on dementia Neurology 72

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risk were still observed, the attenuation of the protective effect in these analyses suggests that, at least in part, the protective effect of antihypertensive drugs may be obscured in the prodromal phase of dementia. Second, we have to consider potential bias due to confounding by indication, since the indication for antihypertensive drug use, i.e., hypertension, is associated with the outcome of interest, i.e., dementia.7 However, given the complex association between hypertension and dementia, it is difficult to predict the direction of this effect. If hypertension increases the risk of dementia,2 than our estimates would underestimate the true protective effect. Instead, if hypertension would protect against dementia in persons above ⬍75 years of age,3 then confounding by indication could lead to a spurious protective effect on dementia for antihypertensive drugs. However, this is refuted by our finding of no benefit of antihypertensive drug use on dementia risk for persons ⬎75 years. Finally, our analyses for the separate types of antihypertensive drugs must be interpreted in light of low numbers within the different antihypertensive drug categories. Since some antihypertensive drugs are preferred when certain comorbidities apply, the differences observed among the various antihypertensive drugs, though small, may be explained by differences in underlying comorbidity rather than by a true difference in physiologic effect. No data are available on the indication for drug use. Low numbers also prohibited further investigation across strata of age in the analyses of the separate antihypertensive drugs. Numerous studies have investigated the association between antihypertensive drug use and the risk of dementia. Thus far, findings have been inconsistent. Considerable methodologic differences exist among studies. Clinical trials mainly included patients ⬎60 years of age with, in four out of five trials, a systolic blood pressure of ⱖ160 mm Hg.25-30 Some trials had a significant number of patients who were lost to follow-up31 or allowed for usual antihypertensive treatment other than the study drug in the placebo group,28,31 which further complicates the interpretation of their findings. The null findings in four out of five trials have also been attributed to the limited duration of follow-up.25,28-30 Nonetheless, in the Syst-EUR trial, antihypertensive treatment reduced the risk of dementia by no less than 50% after a mere 2 years of follow-up26 and again in an openlabel extension of the same trial after 3.9 years of follow-up.27 However, as with most of the studies previously performed, the Syst-Eur trial had a small number of dementia endpoints. Besides the limited duration of follow-up, most observational studies relied on baseline data on antihypertensive treatment, 1732

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which can lead to considerable misclassification of drug exposure during follow-up (table 1). Furthermore, only two out of eight of the prospective observational studies investigated whether associations depended on duration of antihypertensive drug use.6,32 In the Cache County Study, the protective effect of antihypertensive drugs was observed regardless of duration of use as assessed at baseline.32 In a cohort of Japanese men, the risk of dementia was reduced by 6% with each additional year of antihypertensive treatment, based on self-reported duration of drug use at the final examination.6 Considerable differences in both setting and design hamper a direct comparison of these findings to our study. Nevertheless, both studies suggest that the protective effect depends on the duration of antihypertensive drug use. Our observation of a stronger protective effect for people ⱕ75 years of age corresponds with the view that an increased blood pressure earlier in life increases the risk of dementia, whereas high blood pressure in older persons may not necessarily put persons at higher risk for dementia.1 The pathologic processes through which hypertension is thought to influence dementia pathology are many. High blood pressure can result in severe atherosclerosis, leading to cerebral hypoperfusion.33 Changes in cerebral white matter can also occur as a result of sustained high blood pressure.34 Other than the blood pressure lowering effect of antihypertensive drugs, it has been suggested that certain antihypertensive drugs exert a more direct effect on dementia pathology. For example, the intracellular buildup of calcium in neurons can be neurotoxic and thus calcium channel blockers might result in neuroprotection.35 However, our findings do not support an advantage of one antihypertensive drug over another. Other studies have also investigated the different types of antihypertensive drugs in relation to dementia risk, but findings have been largely inconsistent. The types of antihypertensive drugs for which reductions were shown included ACE inhibitors, AT2 blockers, potassium-sparing diuretics, and dihydropyridine calcium channel blockers. The fact that, across both clinical and observational studies, various types of antihypertensive drugs have been identified as a having a particular beneficial effect on dementia suggests that this is the play of chance rather than that actual differences exist. Hence, we consider it more likely that effect of antihypertensive drugs on blood pressure in itself underlies the protective effect of these drugs. For future research, a more mechanistic approach, such as the use of imaging markers of cerebral pathology, would be desirable to understand the biologic basis of the association between antihypertensive drugs and dementia.

Given the established benefit of antihypertensive drugs on prevention of cardiovascular disease, current evidence constitutes a limited basis for advocating a universal antihypertensive treatment policy for the sole purpose of dementia prevention. Further insight on the association between blood pressure and dementia and the effect of antihypertensive drugs on this association could nonetheless provide important information on pathologic pathways leading to dementia.

13.

14.

15.

AUTHOR CONTRIBUTIONS Mendel Haag contributed to the study design, performed the data analysis, and drafted the manuscript. Peter Koudstaal contributed to the data collection. Albert Hofman contributed to the study design. Bruno Stricker and Monique Breteler contributed to the study design, data analysis, and drafting of the manuscript. All authors reviewed, edited, and approved the final version of the manuscript. The principal author takes full responsibility for the data, the analyses, and interpretation and the conduct of the research. All authors had full access to the study data.

Received October 10, 2008. Accepted in final form January 9, 2009.

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cerebrovascular disease. Arch Intern Med 2003;163:1069– 1075. Lithell H, Hansson L, Skoog I, et al. The Study on Cognition and Prognosis in the Elderly (SCOPE): principal results of a randomized double-blind intervention trial. J Hypertens 2003;21:875–886. Peters R, Beckett N, Forette F, et al. Incident dementia and blood pressure lowering in the Hypertension in the Very Elderly Trial cognitive function assessment (HYVET-COG): a double-blind, placebo controlled trial. Lancet Neurol 2008;7:683–689. McGuinness B, Todd S, Passmore AP, Bullock R. Systematic review: Blood pressure lowering in patients without prior cerebrovascular disease for prevention of cognitive impairment and dementia. J Neurol Neurosurg Psychiatry 2008;79:4–5. Khachaturian AS, Zandi PP, Lyketsos CG, et al. Antihypertensive medication use and incident Alzheimer disease: the Cache County Study. Arch Neurol 2006;63:686–692. Skoog I, Gustafson D. Update on hypertension and Alzheimer’s disease. Neurol Res 2006;28:605–611. Pantoni L, Garcia JH. Pathogenesis of leukoaraiosis: a review. Stroke 1997;28:652–659.

35. 36.

37.

38.

39.

40.

Marx J. Alzheimer’s disease: fresh evidence points to an old suspect: calcium. Science 2007;318:384–385. Guo Z, Fratiglioni L, Zhu L, Fastbom J, Winblad B, Viitanen M. Occurrence and progression of dementia in a community population aged 75 years and older: relationship of antihypertensive medication use. Arch Neurol 1999;56:991–996. Qiu C, von Straussu E, Fastbom J, Winblad B, Fratiglioni L. Low blood pressure and risk of dementia in the Kungsholmen project: a 6-year follow-up study. Arch Neurol 2003;60:223–228. Morris MC, Scherr PA, Hebert LE, Glynn RJ, Bennett DA, Evans DA. Association of incident Alzheimer disease and blood pressure measured from 13 years before to 2 years after diagnosis in a large community study. Arch Neurol 2001;58:1640–1646. in ’t Veld BA, Ruitenberg A, Hofman A, Stricker BH, Breteler MM. Antihypertensive drugs and incidence of dementia: the Rotterdam Study. Neurobiol Aging 2001;22: 407–412. Lindsay J, Laurin D, Verreault R, et al. Risk factors for Alzheimer’s disease: a prospective analysis from the Canadian Study of Health and Aging. Am J Epidemiol 2002; 156:445–453.

More Ways to Meet Your Maintenance of Certification Requirements New NeuroSAE™ Now Available! Now you can get additional practice with the new 2008 version of the popular AAN NeuroSAE (Neurology Self-Assessment Examination). The 2007 and 2008 versions of this unique practice test are designed to help you meet the American Board of Psychiatry and Neurology (ABPN) selfassessment requirement for Maintenance of Certification. ● Content outline based on the outline used for the ABPN’s cognitive examination for recertification in clinical neurology ● 100 Multiple-choice questions help you determine strengths and areas for improvement ● Convenient—take online on your own schedule ● Receive feedback by subspecialty area and suggestions for further reading ● Compare your performance to other neurologists ● $99/examination for AAN members and $149/examination for nonmembers Take one— or both—versions. Visit www.aan.com/neurosae today!

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A multicenter 1H-MRS study of the medial temporal lobe in AD and MCI

F. Jessen, MD O. Gu¨r, MD W. Block, PhD G. Ende, PhD L. Fro¨lich, MD T. Hammen, MD J. Wiltfang, MD T. Kucinski, MD H. Jahn, MD R. Heun, MD W. Maier, MD H. Ko¨lsch, PhD J. Kornhuber, MD F. Tra¨ber, PhD

Address correspondence and reprint requests to Dr. Frank Jessen, Department of Psychiatry, University of Bonn, SigmundFreud-Str. 25, D-53105 Bonn, Germany [email protected]

ABSTRACT

Objective: The need for biological markers of Alzheimer disease (AD) is constantly increasing. Proton magnetic resonance spectroscopy (1H-MRS) studies have provided consistent evidence for a reduction of the neuronal marker N-acetylaspartate (NAA) in patients with AD. Within the German Competence Network on Dementia, we conducted a 1H-MRS study in patients with mild dementia and mild cognitive impairment (MCI) at four sites to investigate the multicenter feasibility of 1H-MRS.

Methods: In total, 130 patients with dementia (98 AD, 32 non-AD), 136 subjects with MCI (70 of AD type, 66 of non-AD type), and 45 unimpaired control subjects were included. Single-volume 1 H-MRS of the left medial temporal lobe was performed at long and short echo times. Metabolites were quantified and metabolic ratios were determined. Results: We found a significant reduction of NAA concentration in patients with AD as compared to healthy volunteers and compared to patients with MCI of AD type. NAA/Cr (creatine/phosphocreatine) was also lower in patients with AD compared to control subjects. NAA, choline compounds, and Cr were lower in patients with AD compared to patients with non-AD dementia. Conclusions: We demonstrated the multicenter feasibility of proton magnetic resonance spectroscopy (1H-MRS) of the medial temporal lobe in mild dementia and mild cognitive impairment, which is a prerequisite for the application of 1H-MRS in large-scale clinical trials. Since the concentration measures of the metabolites are adjusted for brain tissue volume, these findings are indicators of biochemical pathology beyond brain atrophy. Neurology® 2009;72:1735–1740 GLOSSARY 1 H-MRS ⫽ proton magnetic resonance spectroscopy; AD ⫽ Alzheimer disease; ADL ⫽ activities of daily living; ANOVA ⫽ analysis of variance; Cho ⫽ choline compounds; CND ⫽ Competence Network on Dementia; Cr ⫽ creatine/phosphocreatine; MCI ⫽ mild cognitive impairment; MI ⫽ myo-inositol; MTL ⫽ medial temporal lobe; NAA ⫽ N-acetylaspartate; TE ⫽ echo time; TR ⫽ repetition time; VOI ⫽ volume of interest.

There is a growing need for biological indicators of pathology in Alzheimer disease (AD).1 Proton magnetic resonance spectroscopy (1H-MRS) is a neuroimaging candidate for early AD detection and disease monitoring. Numerous 1H-MRS studies have shown a reduction of the amino acid N-acetylaspartate (NAA) as an indicator for neuronal mitochondrial function and density.2,3 The reduction of NAA in AD, however, is only weakly correlated with brain atrophy and the combined analysis of NAA concentrations and volumetric measures provides better diagnostic accuracy in separating patients with AD from healthy controls than each method by itself.4,5 Longitudinally, a progressive decrease of NAA levels correlates with clinical symptom progression in patients with AD.6,7 Recent studies have shown a reduction of NAA concentra-

From the Departments of Psychiatry (F.J., R.H., W.M., H.K.) and Radiology (O.G., W.B., F.T.), University of Bonn; Central Institute of Mental Health (G.E., L.F.), Mannheim; Center Epilepsy Erlangen, Clinics of Neurology (T.H.), and Department of Psychiatry (J.K., J.W.), University Erlangen; Department of Psychiatry (J.W.), University Essen, Germany; Department of Neuroradiology (T.K.), Karolinska University Hospital, Stockholm, Sweden; Department of Psychiatry (H.J.), University Hamburg, Germany; and Department of Psychiatry (R.H.), Division of Neuroscience, University of Birmingham, UK. This study is part of the German Competence Network on Dementia and was funded by the German Federal Ministry for Education and Research (Bundesministerium fu¨r Bildung und Forschung [BMBF]), grant O1GI 0102. Disclosure: The authors report no disclosures. Medical Devices: 1.5 T Philips Gyroscan Intera (Philips, Best, Netherlands); 1.5 T Siemens Magnetom Vision, 1.5 T Siemens Magnetom Sonata (Siemens, Erlangen, Germany). Copyright © 2009 by AAN Enterprises, Inc.

1735

Table 1

Numbers of recruited subjects by site and diagnostic category MCI (n ⴝ 136)

Dementia (n ⴝ 130) Non-AD

AD type

Non-AD type

Center

AD

Controls

1

43

6

19

8

10

2

7

9

15

35

5

3

18

7

12

4

6

4

30

10

24

19

24

Total

98

32

70

66

45

MCI ⫽ mild cognitive impairment; AD ⫽ Alzheimer disease.

tions in subjects with mild cognitive impairment (MCI) who later decline to dementia.7-9 Reduction of NAA is also detectable in asymptomatic familial AD mutation carriers.10 Finally, NAA increases with acetylcholinesterase inhibitor treatment in AD, and this increase correlates with clinical treatment response.11-13 Other detectable metabolites are choline compounds (Cho), reflecting cell membrane turnover, and creatine/phosphocreatine (Cr), indicating cell energy metabolism. For both, the data regarding AD are not consistent.2 Additionally, the glial marker myo-inositol (MI) can be measured at short echo times

Table 2

Demographic, clinical, and neuropsychological characteristics of participants Dementia

MCI

AD

Non-AD

AD type

Non-AD type

Controls

F/M

59/39

10/22

35/35

26/40

24/21

Mean age, y (SD)

71.3 (6.5)

68.9 (9.2)

67.8 (8.0)

65.2 (8.9)

65.4 (7.8)

ApoE4, %

66.3

53.1

51.4

31.8

11.1

Mean Mini-Mental State Examination score (SD)

24.7 (3.7)

24.6 (5.4)

26.9 (4.0)

27.7 (1.7)

28.9 (1.0)

Immediate verbal recall (max: 30)

12.1 (3.9)

12.7 (4.7)

16.9 (4.2)

17.6 (3.9)

22.8 (2.6)

Delayed verbal recall (max: 10)

2.0 (1.9)

3.6 (2.3)

5.3 (2.3)

5.7 (1.8)

7.8 (1.9)

Figure copying

9.1 (1.8)

9.2 (2.0)

9.9 (1.3)

10.3 (1.1)

10.4 (1.1)

Figure recall

2.8 (2.7)

4.7 (3.3)

6.0 (3.9)

7.4 (3.0)

8.8 (2.5)

Bayer Activities of Daily Living scale score

3.6 (1.9)

3.0 (1.5)

1.8 (1.1)

2.1 (1.4)

1.2 (0.3)

Clinical Dementia Rating scale score

0.8 (0.3)

0.8 (0.3)

0.5 (0.0)

0.5 (0.0)

0.0 (0.0)

Neuropsychological data are taken from the Consortium to Establish a Registry for Alzheimer’s Disease battery. MCI ⫽ mild cognitive impairment; AD ⫽ Alzheimer disease. 1736

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(TE). MI concentration appears to increase in patients with AD.2 To date, all 1H-MRS data in AD have been derived from single-center studies. Here, we report a multicenter single volume 1H-MRS study of the medial temporal lobe (MTL) in patients with mild dementia and MCI. The reproducibility of the protocol has been reported earlier.14 METHODS Subjects. All participants were recruited within the early diagnostic and prognostic program of the Competence Network on Dementia (CND) at each of the four participating sites (Bonn, Erlangen, Hamburg, Mannheim). Subjects with mild dementia (Mini-Mental State Examination ⬎19) of any etiology (n ⫽ 130) and with MCI (n ⫽ 136) were included in this 1H-MRS study. All diagnoses were established within consensus conferences of physicians and neuropsychologists at each site. An informant was required in all cases. The diagnosis of MCI was established in an operationalized fashion. Cognitive impairment was defined by performance below 1 SD of the age-, gender- and education-adjusted mean in any of the tested cognitive domains (Wechsler Memory Scale immediate and delayed story recall, Consortium to Establish a Registry for Alzheimer’s Disease verbal immediate and delayed recall, category verbal fluency, naming, figure copying, figure recall, Trail Making Test A and B). Overall cognitive function was rated with the Clinical Dementia Rating scale. Activities of daily living (ADL) were assessed with the Bayer Activities of Daily Living Scale. A score ⬍4 points was considered to reflect grossly intact ADL. Subjective cognitive decline was assessed with the subjective memory complaints scale.15 In eight patients with MCI, impairment was not reported by the subject, but by the informant. MCI was defined 1) by reported cognitive decline, 2) by impaired cognitive function, 3) by grossly intact ADL as described above, and 4) after exclusion of dementia according to clinical judgment by geriatric psychiatrists.16 Diagnostic MRI scans were read by neuroradiologists. The structured rating included the estimate quantity of vascular lesions (infarct zones, subcortical lacunes, focal and diffuse white matter lesions). According to the protocol of the CND, subjects with MCI were assigned to MCI of AD type if memory impairment was present and if there was no evidence of significant cerebrovascular disease in clinical examination or on MRI. Other cases were diagnosed with MCI of non-AD type. Patients with dementia were diagnosed with probable AD according to National Institute of Neurological and Communicative Disorders and Stroke– Alzheimer’s Disease and Related Disorders Association criteria17 or with dementia of other etiologies according to standard criteria. For this report, all other etiologies are combined as non-AD dementia. All sites also included unimpaired healthy volunteers (n ⫽ 45) who did not have any neurologic or psychiatric disorder or any severe medical condition to serve as control subjects. By definition, these healthy subjects performed within age-, gender-, and education-adjusted normal limits on all applied neuropsychological measures. All participants were above 50 years of age. Table 1 lists the recruited numbers of patients in each diagnostic category at each site. Table 2 lists demographic,

Figure

Position of the 1H-MRS volume of interest in the left medial temporal lobe

clinical, and neuropsychological data. All participants gave informed consent to the entire CND protocol including the 1 H-MRS examination. The protocol was approved by the ethical committee of each participating site.

Proton MR spectroscopy. All four MR scanners were operating at a magnetic field of 1.5 T and used a radiofrequency transmit/receive head coil suited for cerebral MRI and magnetic resonance spectroscopy (1.5 T Philips Gyroscan Intera, 2 ⫻ 1.5 T Siemens Magnetom Vision, Best, Netherlands; 1.5 T Siemens Magnetom Sonata, Erlangen, Germany). Details on the scanners and the initial multicenter reproducibility study are given elsewere.14 Throughout the cross-sectional study, all centers followed on-site quality management regarding the recording of the 1 H-MRS data. The spectroscopic volume of interest (VOI) of 35 ⫻ 25 ⫻ 20 mm was positioned in the left MTL in temporal angulation and was centered on the hippocampus (figure). The VOI included most of the hippocampal body and parts of its head, of the amygdala, and of the parahippocampal gyrus. Left and right borders in the axial slice were determined by the brainstem and the inferior horn of the lateral ventricle. The angulation of the VOI was achieved either directly by appropriate switching of the magnetic field gradients or by reclining the subject’s head in an adequate position. Anatomic magnetic resonance scans were obtained for image-guided positioning of the voxel. Watersuppressed 1H-MRS spectra with volume selection by point resolved spectroscopy were acquired with repetition time (TR) ⫽ 2,000 msec/TE ⫽ 272 and TE ⫽ 30 msec with 128 signal averages. Sampling of 512 data points with 1 kHz bandwidth corresponded to a nominal frequency resolution of 2 Hz/ point. Metabolite signal ratios of NAA, Cho, and Cr and the ratio NAA/Cr were determined from the spectra with TE ⫽ 272 msec, while the MI and the signal ratios MI/NAA were taken from the short-TE spectra. For quantification, unsuppressed spectra of the VOI were acquired with TR/TE 3,000/272 msec and 32 averages to use the tissue water signal as an internal reference. To determine NAA/H2O concentration ratios by extrapolation to TE 0 and to correct for the CSF contents within the voxel, T2 relaxation times and relative fractions of tissue water

and of CSF were obtained from a series of seven unsuppressed spin echo spectra with different echo times (TE ⫽ 30/70/136/ 272/400/700/1,000 msec), TR ⫽ 6,000 msec, and four signal averages each (multistack). Due to slight variations in the software equipment of the different sites, this multistack sequence varied slightly with regard to TE (reference site: see above, site 2: TE ⫽ 30/70/136/272/400/700/900 msec, site 3: TE ⫽ 30/70/ 100/136/200/272/300 msec, site 4: TE ⫽ 30/70/100/136/200/ 272 msec).

Postprocessing. The JAVA version of the MRUI software package (jMRUI) was used for handling the different export data formats (Philips SDAT/SPAR, Siemens Numaris RDA) from the participating sites for off-line data processing at the reference center (Bonn).18,19 Matched Lorentz-Gauss filtering (with filter widths identical for all sites) was applied to improve the signalto-noise ratio and to convert the lines into a Gaussian shape. Operator-independent quantification was performed using the AMARES algorithm of the MRUI software package.20 T2 relaxation times and relative fractions of tissue water and CSF were obtained by a bi-exponential, four-parameter fit to the multistack series. Absolute metabolite concentrations in mmol/L brain tissue were then derived from the concentration ratios NAA/H2O and from (Cr, Cho, MI)/NAA extrapolated to TE 0 (metabolite T2 values used in this extrapolation were taken from measurements in healthy controls performed at the reference site). Data quality control. All data were subject to a multilevel data quality control procedure. After scanning, the raw data were centrally collected at the reference site. By visual inspection gross artifacts were identified and scans of poor quality were eliminated. After postprocessing, the standard deviations of the individual metabolite peak intensities, represented by the Crame´r-Rao bounds of the AMARES fit, were used to estimate fit quality and to assess the accuracy of the results.21 Variance coefficients (expressed as percentage SD of the peak intensity) of the NAA/H20 ratio and of all other peaks in relation to the NAA peak were calculated using error propagation. If the variance coefficient for an individual peak in a data set exceeded 50% or if it amounted to more than three times the median value of the variance estimate of this peak over all datasets, the measure of this peak was excluded. This procedure led to the exclusion of datasets with poor individual peak fit. The vast majority of long TE (272 msec) dataset could be used. Three measures of NAA (one dementia, two controls), four of Cho (one dementia, one MCI, one control), and three of Cr (one dementia, two controls) were excluded by this procedure. A much larger portion of short TE (30 msec) datasets did not survive this data quality control procedure (22 dementia, 17 MCI, 6 control), yielding a lower number of MI measures compared with long TE measures of the other metabolites. Statistics. In an initial step, we tested the between-site variability of the 1H-MRS measures (center effects) among the healthy comparison group for each metabolite and metabolic ratio by analysis of variance (ANOVA). For comparison of patient groups, we performed a z transformation of all metabolites and metabolic ratios. The z score is obtained by subtracting the mean metabolite measure of the control group from the metabolic measure of an individual and by dividing this by the SD of the control group. By calculating the z score for each site with the site-specific control group, the data are normalized with regard to center effects. We tested the group differences of z-transformed concentrations of NAA, Cho, Cr, and MI, and of the z-transformed ratios Neurology 72

May 19, 2009

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Table 3

Center effects of all metabolites within the control group Partial ␩2

Center 1

Center 2

Center 3

Center 4

p

NAA

11.7 (1.0)

11.2 (1.3)

11.9 (1.5)

15.0 (3.7)

0.005

0.27

Cho

3.2 (0.5)

2.6 (0.7)

2.6 (0.4)

3.7 (0.9)

0.003

0.38

Cr

9.1 (1.7)

7.7 (1.4)

8.3 (1.2)

13.6 (3.8)

⬍0.001

0.48

MI

6.4 (1.9)

5.0 (2.6)

7.0 (2.0)

7.9 (4.2)

NS

0.05

NAA/Cr

2.1 (0.3)

2.3 (0.4)

2.2 (0.3)

1.7 (0.2)

⬍0.001

0.56

MI/NAA

0.7 (0.3)

0.6 (0.2)

0.7 (0.1)

0.7 (0.5)

NS

0.01

NAA ⫽ N-acetylaspartate; Cho ⫽ choline compounds; Cr ⫽ creatine/phosphocreatine; MI ⫽ myo-inositol.

NAA/Cr and NAA/MI between patients with AD and control subjects with individual ANOVA. For those metabolites or metabolic ratios that differed between these groups, we included MCI of AD type in the ANOVA. In addition, we compared all metabolites and metabolic ratios between AD and non-AD patients and between patients with MCI of AD type and MCI of non-AD type. Gender was included as additional factor and age as a covariate in all ANOVAs. To further assess the magnitude of center effects within each diagnostic group, partial ␩2 as an effect size estimate was calculated by ANOVA with center as factor for each group. Gender was included as an additional factor and age as a covariate. RESULTS Among control subjects, there were significant center effects for all metabolites and the metabolic ratios obtained from long TE (272 msec) data (NAA, Cho, Cr, NAA/Cr). Post hoc analysis revealed that one individual site measured higher concentrations of all metabolites and lower NAA/Cr ratios. There were no center effects observed for MI and MI/NAA obtained at TE ⫽ 30 msec (table 3). Within the patient groups, the center effect size estimate partial ␩2 were only greater than the control group’s partial ␩2 in the MCI of AD type group for NAA (0.40) and Cho (0.41) and in the AD group for NAA (0.30). To account for the center effects, z-transformed data were used for multicenter analyses. NAA concentrations were lower in patients with AD compared with controls (F ⫽ 8.05, df ⫽ 1, p ⫽ 0.005). The metabolic ratio NAA/Cr was also lower in patients with AD in comparison with the control subjects (F ⫽ 3.96, df ⫽ 1, p ⫽ 0.049). None of the other metabolic concentrations or metabolic ratios differed between these two groups. Neither gender nor age was associated with any metabolic concentration or metabolic ratio. After inclusion of MCI of AD type in the ANOVA, the diagnostic group effect on NAA remained (F ⫽ 4.49, df ⫽ 2, p ⫽ 0.010). Post hoc tests (Scheffe) revealed lower NAA concentrations in patients with AD in comparison with control subjects (p ⫽ 0.045) and in comparison with the MCI group (p ⫽ 0.015). MCI and comparison subjects did not differ with respect to NAA concentration (p ⫽ 0.24). 1738

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The diagnostic group effect on the NAA/Cr ratio was not significant after inclusion of patients with MCI of AD type. Comparison between patients with AD and non-AD dementia revealed lower NAA (F ⫽ 20.15, df ⫽ 1, p ⬍ 0.001), lower Cho (F ⫽ 18.25, df ⫽ 1, p ⬍ 0.001), and lower Cr concentrations (F ⫽ 26.15, df ⫽ 1, p ⬍ 0.001) in patients with AD. MI concentrations and the metabolic ratios NAA/Cr and MI/NAA did not differ between these groups. The comparison of AD type MCI and non-AD type MCI subjects did not reveal any difference between metabolic concentrations or metabolic ratios. Table 4 lists all metabolic concentrations and metabolic ratios, including z-transformed data of all diagnostic groups. DISCUSSION In this study, we demonstrated the feasibility of multicenter 1H-MRS of the medial temporal lobe in patients with mild dementia and MCI. Our protocol provided quantified metabolic measures and metabolic ratios. We replicated the reduction of NAA concentrations in patients with AD, which has been observed previously in several singlecenter studies.2 It needs to be stressed that the NAA concentration is reduced in relation to brain tissue volume, indicating NAA reduction as a measure of neuronal pathology beyond brain atrophy. We also found a reduction of the metabolic ratio NAA/Cr that is mostly reported in 1H-MRS studies. In MCI, the concentration of NAA was higher than in the AD group, but not different from the healthy volunteers. Some single-center studies have reported reduced NAA in MTL structures in MCI,8,22 in particular in those subjects who later decline to dementia. The longitudinal follow-up of the present cohort will provide estimates of decline prediction in MCI by 1H-MRS in a large scale multicenter approach. Also, the criterion for cognitive impairment within the CND is a performance below 1 SD on any cognitive test. This is a liberal threshold and may lead to inclusion of more subjects without predementia MCI than in studies with stricter MCI criteria such as performance below 1.5 SD on cognitive tests. We did not find increased MI concentrations in AD, which has been reported in other studies mainly from different brain regions. The number of short TE scans with sufficient quality to measures MI in our study was lower than that of long TE scans, yielding lower statistical power. Additionally, the SD of MI measures was high. This is in agreement with other studies, highlighting the particular difficulties of measuring MI in the MTL.23 Short TE measures

Table 4

Means and SD of metabolic concentrations and ratios of all diagnostic groups Dementia AD

NAA (mmol/L brain tissue)

Non-AD

11.7 (2.4)

No.

95

z Scores

⫺0.62 (1.36)*†

Cho (mmol/L brain tissue)

z Scores

⫺0.37 (1.33)†

No.

96

z Scores

0.005 (1.30)†

61

0.007 (1.5)

0.029 (1.59)

3.1 (0.7) 65

1.07 (1.48) 11.5 (2.3)

6.6 (2.9)

6.6 (3.9)

0.4 (1.34)

11.1 (3.9) 42

0.49 (1.78)

⫺0.003 (0.97)

6.0 (3.3) 52

7.1 (3.4)

No.

62

z Scores

0.048 (0.96)

0.40 (1.42)

0.25 (1.24)

⫺0.18 (1.13)

0.04 (0.90)

1.86 (0.47)

1.77 (0.50)

1.93 (0.35)

1.93 (0.47)

1.82 (0.58)

NAA/Cr

43

0.012 (0.98)

9.8 (2.7)

7.1 (3.1)

19

3.3 (0.9) 42

57

0.58 (1.69)

0.008 (0.98)

3.1 (0.7)

⫺0.09 (1.37)

67

1.93 (2.39)

13.3 (3.2) 42

57

10.5 (3.0)

27

Controls

12.4 (2.6)

69

3.3 (0.5) 27

10.0 (2.8)

Non-AD type

12.6 (2.3)

0.76 (1.68)

2.9 (0.8) 96

MI (mmol/L brain tissue)

AD type

13.1 (2.1) 28

No.

Cr (mmol/L brain tissue)

MCI

No.

98

31

66

63

z Scores

⫺0.46 (1.31)‡

⫺0.96 (1.54)

⫺0.38 (1.13)

⫺0.18 (1.13)

MI/NAA No. z Scores

0.73 (0.36) 57 0.28 (1.14)

0.64 (0.37) 19

0.70 (0.25) 43

0.12 (1.12)

45 0.06 (0.98)

0.63 (0.34) 52

0.24 (0.87)

32

0.19 (1.22)

0.70 (0.37) 36 0.06 (0.92)

Note that the mean measures of the metabolites are affected by center effects. As an example, one center systematically obtained lower NAA/Cr values and recruited most healthy control subjects, yielding a lower multicenter mean NAA/Cr ratio in control subjects compared with patients with AD. The normalization to the control group of each site by z transformation accounts for this effect. Accordingly, the z-transformed data are the basis for the statistical analyses. In the case of NAA/Cr, the z-transformed measures are lower in the AD group than in the controls. *Lower compared to healthy control subjects (p ⫽ 0.045) and to patients with MCI of AD type (p ⫽ 0.015). †Lower in patients with AD compared with non-AD patients (NAA: p ⬍ 0.001, Cho: p ⬍ 0.001, Cr: p ⬍ 0.001). ‡Lower compared to healthy controls (p ⫽ 0.049) only, if patients with MCI of AD type were not included in the analysis of variance. Detailed statistics are given in the text. MCI ⫽ mild cognitive impairment; AD ⫽ Alzheimer disease; NAA⫽ N-acetylaspartate; Cho ⫽ choline compounds; Cr ⫽ creatine/phosphocreatine; MI ⫽ myo-inositol.

of MI within the MTL may not be of use in multicenter 1H-MRS studies in dementia. Patients with AD showed lower NAA, Cho, and Cr levels than patients with non-AD dementia, indicating the distinct neuronal pathology of the MTL that characterizes AD. The number of 1H-MRS studies investigating the MTL structures with regard to the differentiation of AD vs non-AD dementias is very small. In one study, patients with AD showed lower NAA in the MTL in comparison with controls, while patients with subcortical vascular dementia did not differ from controls with respect to NAA levels.24 Beyond this, metabolic differences between dementia types have been reported for other brain regions.25 Our data particularly reflect the high reliability of NAA reduction in the MTL in AD, supporting the robustness of this biochemical measure of neuronal pathology. In our initial reproducibility article, we found an intercenter variation within one subject of 3.9% for NAA and of below 10% for all other metabolites.14 In the present study, however, we did ob-

serve center effects for the long TE measure. The identification of the source of center effects in a patient population is difficult, because the characteristics of the patients may vary between sites. The comparison of healthy subjects, however, revealed that one site had systematically higher metabolic concentrations and lower NAA/Cr ratios than the other sites. First, this demands statistical consideration and highlights the need for healthy comparison groups at each site in multicenter studies. Second, the design of future multicenter 1H-MRS studies needs to incorporate reference values of the metabolic measures for each site, which was not implemented in this study. Keeping this in mind, we propose NAA measures as an additional biomarker candidate for AD due to 1) the robustness of assessment in single and multicenter studies, 2) the high consistency of NAA reduction in patients with AD in numerous studies, 3) the independence of the NAA reduction of other imaging markers, like brain atrophy, 4) the lack of need Neurology 72

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1739

for tracers and radiation, and 5) the rapid examination time. Combined analyses with other AD biomarkers will specify the individual contribution of 1 H-MRS in characterizing pathology in AD.

13.

AUTHOR CONTRIBUTIONS F.J. performed the statistical analyses.

14.

Received October 17, 2008. Accepted in final form February 11, 2009. 15. REFERENCES 1. Cummings JL, Doody R, Clark C. Disease-modifying therapies for Alzheimer disease: challenges to early intervention. Neurology 2007;69:1622–1634. 2. Kantarci K. 1H magnetic resonance spectroscopy in dementia. Br J Radiol 2007;80:S146–S152. 3. Moffett JR, Ross B, Arun P, Madhavarao CN, Namboodiri AM. N-acetylaspartate in the CNS: from neurodiagnostics to neurobiology. Prog Neurobiol 2007;81: 89–131. 4. Schuff N, Capizzano AA, Du AT, et al. Selective reduction of N-acetylaspartate in medial temporal and parietal lobes in AD. Neurology 2002;58:928–935. 5. Jessen F, Traeber F, Freymann N, et al. A comparative study of the different N-acetylaspartate measures of the medial temporal lobe in Alzheimer’s disease. Dement Geriatr Cogn Disord 2005;20:178–183. 6. Jessen F, Block W, Tra¨ber F, et al. Decrease of N-acetylaspartate in the MTL correlates with cognitive decline of AD patients. Neurology 2001;57:930–932. 7. Kantarci K, Weigand SD, Petersen RC, et al. Longitudinal 1H MRS changes in mild cognitive impairment and Alzheimer’s disease. Neurobiol Aging 2007;28:1330–1339. 8. Chantal S, Braun CM, Bouchard RW, Labelle M, Boulanger Y. Similar 1H magnetic resonance spectroscopic metabolic pattern in the medial temporal lobes of patients with mild cognitive impairment and Alzheimer disease. Brain Res 2004;1003:26–35. 9. Modrego PJ, Fayed N, Pina MA. Conversion from mild cognitive impairment to probable Alzheimer’s disease predicted by brain magnetic resonance spectroscopy. Am J Psychiatry 2005;162:667–675. 10. Godbolt AK, Waldman AD, MacManus DG, et al. MRS shows abnormalities before symptoms in familial Alzheimer disease. Neurology 2006;66:718–722. 11. Krishnan KR, Charles HC, Doraiswamy PM, et al. Randomized, placebo-controlled trial of the effects of donepezil on neuronal markers and hippocampal volumes in Alzheimer’s disease. Am J Psychiatry 2003;160:2003– 2011. 12. Jessen F, Traeber F, Freymann K, Maier W, Schild HH, Block W. Treatment monitoring and response prediction

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with proton MR spectroscopy in AD. Neurology 2006;67: 528–530. Modrego PJ, Pina MA, Fayed N, Dı´az M. Changes in metabolite ratios after treatment with rivastigmine in Alzheimer’s disease: a nonrandomised controlled trial with magnetic resonance spectroscopy. CNS Drugs 2006;20: 867–877. Tra¨ber F, Block W, Freymann N, et al. A multicenter reproducibility study of single-voxel 1H-MRS of the medial temporal lobe. Eur Radiol 2006;16:1096–1103. Jorm AF, Christensen H, Korten AE, Henderson AS, Jacomb PA, Mackinnon A. Do cognitive complaints either predict future cognitive decline or reflect past cognitive decline? A longitudinal study of an elderly community sample. Psychol Med 1997;27:91–98. Winblad B, Palmer K, Kivipelto M, et al. Mild cognitive impairment: beyond controversies, towards a consensus: report of the International Working Group on Mild Cognitive Impairment. J Intern Med 2004;256:240–246. McKhann G, Drachman D, Folstein M, et al. Clinical diagnosis of Alzheimer’s disease: report of the NINCDSADRDA Work Group under the auspices of Department of Health and Human Services Task Force on Alzheimer’s Disease. Neurology 1984;34:939–944. Naressi A, Couturier C, Devos JM, et al. Java-based graphical user interface for the MRUI quantitation package. MAGMA 2001;12:141–152. van den Boogaart A, van Hecke P, van Huffel S, GraveronDemilly D, van Ormondt D, de Beer R. MRUI: a graphical user interface for accurate routine MRS data analysis. Presented at 13th annual meeting of the European Society for Magnetic Resonance in Medicine and Biology (ESMRMB); 1996; Prague. Abstract. Vanhamme L, van den Boogaart A, van Huffel S. Improved method for accurate and efficient quantification of MRS data with use of prior knowledge. J Magn Reson 1997;129:35–43. Cavassila S, Deval S, Huegen C, van Ormondt D, Graveron-Demilly D. Crame´r-Rao bounds: an evaluation tool for quantitation. NMR Biomed 2001;14:278–283. Chao LL, Schuff N, Kramer JH, et al. Reduced medial temporal lobe N-acetylaspartate in cognitively impaired but nondemented patients. Neurology 2005;64:282–289. Dixon RM, Bradley KM, Budge MM, Styles P, Smith AD. Longitudinal quantitative proton magnetic resonance spectroscopy of the hippocampus in Alzheimer’s disease. Brain 2002;125:2332–2341. Schuff N, Capizzano AA, Du AT, et al. Different patterns of N-acetylaspartate loss in subcortical ischemic vascular dementia and AD. Neurology 2003;61:358–364. Kantarci K, Petersen RC, Boeve BF, et al. 1H MR spectroscopy in common dementias. Neurology 2004;63: 1393–1398.

Association between late-life body mass index and dementia The Kame Project

T.F. Hughes, PhD, MPH A.R. Borenstein, PhD, MPH E. Schofield, MPH Y. Wu, PhD E.B. Larson, MD, MPH

Address correspondence and reprint requests to Dr. Tiffany F. Hughes, Department of Psychiatry, University of Pittsburgh School of Medicine, 3811 O’Hara St., Pittsburgh, PA 15213 [email protected]

ABSTRACT

Objective: To examine the association between body mass index (BMI), waist circumference (WC), and waist-to-hip ratio (WHR) and risk of dementia and its subtypes in late life.

Methods: Participants were members of the Kame Project, a population-based prospective cohort study of 1,836 Japanese Americans living in King County, WA, who had a mean age of 71.8 years and were dementia-free at baseline (1992–1994), and were followed for incident dementia through 2001. Cox proportional hazards models were used to estimate the risk of dementia, Alzheimer disease (AD), and vascular dementia (VaD) controlling for demographic and lifestyle characteristics and vascular comorbidities as a function of baseline BMI, WC, and WHR and change in BMI over time.

Results: Higher baseline BMI was significantly associated with a reduced risk of AD (hazard ratio [HR] ⫽ 0.56, 95% confidence interval [CI] ⫽ 0.33– 0.97) in the fully adjusted model. Slower rate of decline in BMI was associated with a reduced risk of dementia (HR ⫽ 0.37, 95% CI ⫽ 0.14 – 0.98), with the association stronger for those who were overweight or obese (HR ⫽ 0.18, 95% CI ⫽ 0.05– 0.58) compared to normal or underweight (HR ⫽ 1.00, 95% CI ⫽ 0.18 –5.66) at baseline.

Conclusion: Higher baseline body mass index (BMI) and slower declining BMI in late life are associated with a reduced risk of dementia, suggesting that low BMI or a faster decline in BMI in late life may be preclinical indicators of an underlying dementing illness, especially for those who were initially overweight or obese. Neurology® 2009;72:1741–1746 GLOSSARY AD ⫽ Alzheimer disease; BMI ⫽ body mass index; CI ⫽ confidence interval; DSM-IV ⫽ Diagnostic and Statistical Manual of Mental Disorders, 4th edition; HR ⫽ hazard ratio; VaD ⫽ vascular dementia; WC ⫽ waist circumference; WHR ⫽ waist-to-hip ratio.

Evidence suggests that weight loss precedes the diagnosis of dementia1-4 and may be the result of preclinical pathophysiologic changes.5 Increased adiposity also is associated with an increased risk of dementia.6-8 These paradoxical findings are likely related to the long preclinical phase of dementia and the problem that associations between various risk or protective factors and dementia depend upon when they are measured in relation to the clinical onset of disease. In this regard, overweight or obesity in midlife may be more appropriately considered a risk factor, while declining weight in late life may be considered a preclinical indicator of the disease. The purpose of the current study is to examine the relation between late-life adiposity, measured by body mass index (BMI), waist circumference (WC), and waist-to-hip ratio (WHR), and incident dementia, Alzheimer disease (AD), and vascular dementia (VaD). We used data from the Kame Project, a prospective cohort study of Japanese Americans in King County, WA, to calculate the risk of dementia, AD, and VaD as a function of baseline adiposity, and to further determine whether change in BMI is associated with risk. We hypothesized that higher adiposity at baseline and slower rate of decline in BMI would be associated with decreased risk of dementia and its subtypes.

From the Department of Psychiatry (T.F.H.), University of Pittsburgh, PA; the Department of Epidemiology and Biostatistics (A.R.B., E.S., Y.W.), University of South Florida, Tampa; and the Group Health Center for Health Studies (E.B.L.), University of Washington, Seattle. Disclosure: The authors report no disclosures. Copyright © 2009 by AAN Enterprises, Inc.

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METHODS Study population. Participants were members of the Kame Project, a population-based prospective study of community- and institution-dwelling Japanese Americans 65 years and older living in King County, WA. The study was carried out between May 1992 and December 2001 and consisted of five time points (baseline and follow-ups at approximately 2, 4, 6, and 8 years). The study was approved by the University of Washington Human Subjects Committee and supported by a Japanese American Community Advisory Board, and written informed consent was obtained from all participants. A more detailed description of the study has been presented elsewhere.9 From the 3,045 participants enumerated in a study census of Japanese Americans in King County, WA, in November 1991, 1,985 individuals participated in the baseline examination between May 1992 and September 1994 (65.2%). Of these, 149 were identified as prevalent cases of dementia and 1,836 were dementia-free at baseline and eligible for follow-up to detect incident dementia. Of these 1,836 participants, 1,615 (88.0%) had anthropometric data, of whom 137 were missing follow-up data due to death, loss to follow-up, or refusal to participate, leaving 1,478 (80.5%) participants for the current analysis. During the entire study period (mean ⫽ 7.8 years; SD ⫽ 0.3), 129 incident dementia cases, 71 incident AD cases, and 22 incident VaD cases were documented in the sample with complete data for this analysis.

Dementia diagnosis. The diagnosis of dementia was based on a two-stage case ascertainment process consisting of cognitive screening followed by a clinical diagnostic evaluation. Trained interviewers first administered the Cognitive Abilities Screening Instrument10 to assess cognition at baseline and at each biennial. Participants who scored 86 or less of a possible 100 points were referred for full standard clinical and neuropsychological evaluation. The clinical evaluation consisted of physical, neurologic, and laboratory examinations by study physicians9 and informant interviews including the Clinical Dementia Rating Scale.11 Trained psychometrists administered the Consortium to Establish a Registry for AD12 neuropsychological test battery and other tests.9 A consensus committee determined the presence of dementia and its subtypes based on the DSM-IV13 criteria for dementia, the National Institute of Neurological and Communicative Disorders and Related Disorders Association14 criteria for AD, and a number of criteria for VaD.15,16 A more detailed description of the diagnostic procedure can be found elsewhere.9 Anthropometric measures. At the baseline examination, anthropometric measurements including standing height, weight, WC, and hip circumference were taken by trained interviewers and recorded for each participant. Only weight was measured at each of the follow-up examinations. BMI (weight [kg] over height squared [m2]) was considered the primary index of body weight since it is scaled according to height, and was categorized as obese (BMI ⱖ25.0), overweight (BMI ⫽ 23.0 –24.9), normal (BMI ⫽ 18.5–22.9), and underweight (BMI ⬍18.5) according to cutoffs proposed by the International Obesity Taskforce for Asian populations17 for descriptive purposes. WC (inches) and WHR (WC [in] over hip circumference [in]) were considered secondary measures of adiposity. Fixed slope parameters for each participant were calculated using random effects modeling and served as the measure of rate of change in BMI across the study period (mean ⫽ ⫺0.07, SD ⫽ 0.16). Covariates. The demographic characteristics of gender (men/ women) and education (dichotomized from the original continuous variable as less than high school/high school or greater) were included as covariates. In addition, baseline values were 1742

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elicited for current or past smoking status (yes/no), current or past alcohol consumption (yes/no), and regular exercise (yes/no). Self-reported history of cardiovascular conditions including hypertension (yes/no), hypercholesterolemia (yes/no), angina pectoris (yes/no), diabetes (yes/no), heart attack (yes/no), TIA (yes/ no), and stroke (yes/no) were collected at baseline. Information on ApoE genotype status was available for 1,056 (57.2% [of 1,836]) participants from the first biennial assessment who also had adiposity measures.

Statistical analyses. The association between the adiposity measures and risk of incident dementia, AD, and VaD was examined using Cox proportional hazard regression models to estimate hazard ratios (HRs) and 95% confidence intervals (CIs), with age at onset as the time scale and age at entry as the truncation variable.18 Three separate models were calculated for continuous baseline BMI, WC, and WHR and continuous change in BMI: 1) adjusting for age, 2) additionally adjusting for gender and education, and 3) additionally adjusting for smoking status, alcohol consumption, regular exercise, hypertension, hypercholesterolemia, angina pectoris, diabetes, heart attack, TIA, and stroke. We also added a quadratic term for BMI when investigating the association between baseline BMI and dementia to account for the nonlinear relation observed graphically, which produced a better fitting model. A multiplicative interaction term between baseline BMI and change in BMI was estimated in fully adjusted proportional hazard regression models for dementia to determine whether the association between change in BMI and dementia depended upon baseline BMI. All analyses were conducted using SAS version 919 with p values less than 0.05 (two-tailed) interpreted as being significant.

The average age of the participants at baseline (n ⫽ 1,478) was 71.8 years, 55.3% were women, and 75.8% had at least high school education or greater. The average BMI was 24.3 (range 15.4 – 47.3), with 39.6% obese, 24.6% overweight, 32.7% normal weight, and 3.1% underweight. In terms of the other covariates at baseline, 48.9% were current or past smokers; 37.1% were current or past drinkers of alcohol; 65.2% reported regular physical activity; 46.8% reported hypertension; 5.3% reported having a coronary artery attack; 3.3% reported having a TIA; 2.6% reported a stroke; 16.6% reported diabetes; 12.3% reported hypercholesterolemia; 5.5% reported angina; and 20.6% were ApoE ␧4 allele positive. The current sample did not differ from the dementia-free cohort (n ⫽ 1,836) with respect to any of the covariates except age and education, where the current sample was 0.9 years younger (t ⫽ ⫺2.78; p ⫽ 0.004) and 46.0% had greater than or equal to high school education compared to the dementia-free cohort (54.0%; ␹2 ⫽ 7.13, p ⫽ 0.008). The characteristics of the sample by BMI category at baseline are shown in table 1. Those who were underweight were more likely to be women, less likely to be a current or past smoker or alcohol drinker, and less likely to have high cholesterol or RESULTS

Table 1

Baseline sample characteristics by BMI category among 1,478 participants 65 years and older in the Kame Project (1992–2001) BMI category

Dementia, n ⴝ 129 Alzheimer disease, n ⴝ 71 Vascular disease, n ⴝ 22

<18.5 (n ⴝ 46)

18.5–22.9 (n ⴝ 484)

13.04

10.33

6.06

8.72

0.12

4.35

5.79

3.03

5.13

0.30

1.20

0.29

4.35

1.86

23.0 –24.9 (n ⴝ 363)

1.10

>25.0 (n ⴝ 585)

p Value*

Age, mean (SD), n ⴝ 1,478

72.99 (6.47)

72.10 (5.80)

71.79 (5.06)

71.41 (4.43)

Sex, % female, n ⴝ 1,478

82.61

71.07

52.34

41.88

⬍0.001

Education, % > high school, n ⴝ 1,478

71.74

76.86

74.10

76.41

0.71

0.06

Alcohol, % yes, n ⴝ 1,478

26.09

33.47

36.91

41.20

0.03

Smoking, % yes, n ⴝ 1,478

34.78

41.12

48.48

56.58

⬍0.001

Hypertension, % yes, n ⴝ 1,478

39.13

36.78

48.76

54.53

⬍0.001

6.52

7.32

16.62

14.14

⬍0.001

Hypercholesterolemia, % yes, n ⴝ 1,465 Diabetes mellitus, % yes, n ⴝ 1,467

10.87

13.15

16.62

19.97

0.02

Angina pectoris, % yes, n ⴝ 1,460

0.00

4.80

4.76

6.92

0.12

Stroke, % yes, n ⴝ 1,471

4.35

1.87

2.76

2.91

0.60

TIA, % yes, n ⴝ 1,469

2.22

2.90

3.88

3.45

0.85

Physical activity, % regular, n ⴝ 1,431

50.00

64.67

68.26

64.84

0.12

ApoE, % ␧4 positive, n ⴝ 1,056

27.27

19.77

23.11

19.24

0.52

*Analysis of variance for continuous variables or ␹2 test for categorical variables. BMI ⫽ body mass index.

diabetes. Those who were of normal weight were the least likely to have hypertension. Table 2 shows the associations between baseline and change in BMI and risk of dementia, AD, and Table 2

VaD. BMI at baseline was inversely associated with dementia, AD, and VaD, but was only significant for AD in the fully adjusted model. We did not find that the risk of dementia, AD, and VaD was associated

Hazard ratios for incident dementia by baseline BMI and change in BMI over study period among participants 65 years and older in the Kame Project (1992–2001) Dementia Cases/ unaffected

Alzheimer disease

Vascular dementia

HR (95% CI)

Cases/ unaffected

HR (95% CI)

Cases/ unaffected

HR (95% CI)

Baseline BMI Model 1*

129/1,349

0.93 (0.51⫺1.69)

69/1,398

0.63 (0.35⫺1.12)

22/1,418

0.82 (0.20⫺3.32)

Model 2†

129/1,349

0.89 (0.49⫺1.61)

69/1,399

0.60 (0.34⫺1.06)

22/1,418

0.73 (0.19⫺2.88)

Model 3‡

108/1,294

0.78 (0.42⫺1.44)

59/1,333

0.56 (0.33⫺0.97)

19/1,351

0.66 (0.13⫺3.36)

Model 4§

74/943

0.80 (0.38⫺1.68)

43/971

0.68 (0.31⫺1.51)

12/991

0.40 (0.06⫺2.51)

129/1,349

0.58 (0.22⫺1.49)

69/1,398

0.37 (0.17⫺1.15)

22/1,418

0.73 (0.07⫺7.35)

BMI change Model 1* Model 2†

129/1,349

0.59 (0.23⫺1.54)

69/1,398

0.37 (0.11⫺1.22)

22/1,418

0.80 (0.08⫺7.97)

Model 3‡

108/1,294

0.37 (0.14⫺0.98)

59/1,333

0.32 (0.09⫺1.08)

19/1,351

0.41 (0.03⫺5.34)

Model 4§

74/943

0.31 (0.09⫺1.02)

43/971

0.21 (0.06⫺0.80)

12/991

0.43 (0.02⫺10.60)

*Model adjusted for age. †Model adjusted for sex and education. ‡Model additionally adjusted for alcohol, smoking, hypertension, hypercholesterolemia, diabetes, angina pectoris, stroke, TIA, and physical activity. § Model additionally adjusted for ApoE ␧4 status. HR ⫽ hazard ratios; BMI ⫽ body mass index; CI ⫽ confidence interval. Neurology 72

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1743

Figure

Association between BMI change over the study period and dementia depends on baseline BMI

The x-axis shows baseline body mass index (BMI), and the y-axis shows the hazard ratio (HR) for change in BMI over the study period and dementia controlling for baseline BMI, age, and education.

with WC and WHR at baseline (data not shown). The risk of dementia and AD was reduced with a slower rate of BMI decline during the study period in the fully adjusted model where an average BMI decline of 1.06 units less per year (1.15 for AD) was associated with a 63% reduced risk (68% for AD), although the point estimate for AD was marginally significant. Adjusting for the presence of the ApoE ␧4 allele did not substantially change the results, but did strengthen the association between rate of change in BMI and the risk of dementia and AD. A significant interaction between baseline BMI and change in BMI was found for dementia (HR ⫽ 0.73, 95% CI ⫽ 0.53– 0.99, p for interaction ⫽ 0.048). The reduction in risk of dementia with slower BMI decline was greater with increasing BMI at baseline (figure) where there was a significant reduction in risk for those whose baseline BMI was overweight or obese (HR ⫽ 0.18, 95% CI ⫽ 0.05– 0.58) compared to those who were normal or underweight (HR ⫽ 1.00, 95% CI ⫽ 0.18 –5.66). DISCUSSION In this analysis from the Kame Project, we report that the risk for AD was reduced with higher late-life BMI at baseline and that the risks of dementia and AD were reduced with a slower rate of BMI decline over a follow-up period of approximately 8 years. More importantly, the extent to which change in BMI was associated with dementia depended upon baseline BMI such that overweight or obese participants at baseline had a more pronounced reduction in risk with slower decline in BMI compared to normal or underweight participants. These findings suggest that late-life adiposity is associated with the risk of dementia, where high and slowly declining BMI reduce the risk; or con1744

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versely, that low or fast declining BMI may be preclinical indicators for dementia. The risk for dementia is believed to develop across the lifespan as the pathologic hallmarks have been detected decades before its clinical presentation. Because of its long prodromal period, assessing the characteristics of a risk factor is time-dependent and the potential for reverse causality exists. Our finding of a reduced risk of AD with higher baseline BMI is suggestive of a protective effect of higher BMI in late life, similar to findings from the Kungsholmen Project6 and the Chicago Health and Aging Project.20 This is different from what has been shown in midlife, where overweight or obesity increased the risk of dementia and AD.8 Our findings are in accord with others who have shown weight loss in later life to be a risk factor for dementia1,2 and for weight loss to precede the diagnosis of dementia.3,4 Hence, it may be that a nonlinear association exists where higher adiposity in midlife increases the risk of dementia and its subtypes, and that pathophysiologic changes associated with dementia then lead to declines in adiposity in late life.5 Measures of central fat distribution, including WC and WHR, are known to increase the risk of coronary heart disease21 and mortality22 more than total body weight. Evidence suggests that central obesity in midlife23 and late life24 increases the risk of dementia and AD. Our findings do not support a link between WC or WHR in late life and dementia risk. These findings are partially in accord with those of the Northern Manhattan study where continuous WC was not associated with dementia, AD, or dementia associated with stroke. The same study did, however, find that the risk of dementia associated with stroke was increased for the largest WC quartile compared to the smallest WC quartile.7 Additional studies at both midlife and late life are needed to further elucidate whether central adiposity is associated with the risk for dementia and its subtypes. The finding that overweight or obese participants had a reduced risk of dementia with slower decline in BMI compared to those who were normal or underweight may reflect a floor effect. Those who are normal or underweight at baseline have less weight to lose compared to those who are overweight or obese, which would lessen their rate of change in BMI over the course of the study. It may also be that those who were normal or underweight at the beginning of the study and were losing weight at a faster rate were lost to follow-up since this weight loss could affect overall health. Taken together, the results suggest that having a slow rate of a decline in weight if previously overweight or obese may reduce risk more than being overweight or obese alone in late life.

The use of BMI categories for Asian populations in our study resulted in a high number (39.6%) of obese (BMI ⬎25) participants at baseline compared to the United States prevalence of 12% in the early 1990s.25 Using the Caucasian BMI cutpoints reduced this number to 5.0% for obese (BMI ⬎30) with the remaining 3.1% underweight (BMI ⬍18.5), 57.3% normal (BMI ⫽ 18.5–25), and 34.6% overweight (BMI ⫽ 25–30). Since 96% of the participants in the Kame Project were 100% Japanese,9 and twin studies have shown that genetic influences on BMI are substantial,26 we considered the Asian, rather than Caucasian, categories to be more appropriate for our sample. Furthermore, studies have shown that Asians in general have higher body fat, greater centralized distribution of body fat, and higher WHR than Caucasians with lower or similar BMIs, which highlights the importance of redefining the categories to assess health risks in our sample.17 Despite this descriptive difference, we believe that our main findings are generalizable beyond Japanese American or Asian populations since we used continuous measures of baseline BMI and change in BMI that were independent of BMI categories. Several biologic processes may explain the association between high and slower decline in BMI and reduced risk of dementia. Higher weight in late life may offer protection by increasing insulin-growth factor I levels,27 increasing leptin hormone levels known to be involved in regulation of synaptic plasticity in the hippocampus,28 and increasing the production of estrogen,29 all of which have been shown to be associated with better cognitive performance.30,31 Slower decline in BMI over the course of the study may indicate that preclinical changes associated with dementia are not occurring. Brain areas that control weight (i.e., mesial temporal cortex)32 are affected during the preclinical dementia phase that may lead to weight loss. Weight loss may also result from predementia apathy,33 reduced olfactory function,34 difficulty in eating,35 or inadequate nutrition36 due to cognitive impairment. There are both strengths and limitations of this study that should be acknowledged. The first strength is that the association between various measures of adiposity and incident dementia and two of its subtypes were examined. Also, the study included both community and institutionalized individuals, minimizing any selection bias that may result from including only those healthy enough to remain independent in the community. Finally, we adjusted for multiple variables that would likely confound any associations between adiposity and dementia. Limitations of this study include the relatively short follow-up period, which increases the potential

for reverse causality to explain the findings. Also, our sample was limited to Americans who were of Japanese ancestry and thus may limit the generalizability to other populations. We also assumed that height was constant throughout the study period even though studies have shown that women and men lose 0.2 to 0.3 cm per year between the ages of 70 and 90 years37; however, any error introduced would likely nondifferentially overestimate the rate of decline in BMI and not bias the findings. It is also possible that using BMI as our measure of weight may have underestimated adiposity in the elderly who generally have less lean body mass,38 which would have attenuated our findings. Finally, we had insufficient power to detect a relationship between adiposity and VaD, but did find similar point estimates as dementia and AD. Others studies with more power have shown a stronger effect for VaD than AD,7 suggesting that adiposity may exert its influence on dementia with a vascular origin. Received November 4, 2008. Accepted in final form February 13, 2009.

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Hughes CP, Berg L, Danziger WL, Coben LA, Martin RL. A new clinical scale for the staging of dementia. Br J Psychiatry 1982;140:566–572. Morris JC, Heyman A, Mohs RC, et al. The Consortium to Establish a Registry for Alzheimer’s Disease (CERAD): part I: clinical and neuropsychological assessment of Alzheimer’s disease. Neurology 1989;39:1159–1165. American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders: DSM-IV. Washington, DC: American Psychiatric Association; 1994. McKhann G, Drachman D, Folstein M, Katzman R, Price D, Stadlan EM. Clinical diagnosis of Alzheimer’s disease: report of the NINCDS-ADRDA Work Group under the auspices of the Department of Health and Human Services Task Force on Alzheimer’s Disease. Neurology 1984;34:939–944. Chui HC, Victoroff JI, Margolin D, Jagust W, Shankle R, Katzman R. Criteria for the diagnosis of ischemic vascular dementia proposed by the State of California Alzheimer’s Disease Diagnostic and Treatment Centers. Neurology 1992;42:473–480. Roman GC, Tatemichi TK, Erkinjuntti T, et al. Vascular dementia: diagnostic criteria for research studies: report of the NINDS-AIREN International Workshop. Neurology 1993;43:250–260. Kanazawa M, Yoshiike N, Osaka T, Numba Y, Zimmet P, Inoue S. Criteria and classification of obesity in Japan and Asia-Oceania. Asia Pacific J Clin Nutr 2002;11:S732–S737. Korn EL, Graubard BI, Midthune D. Time-to-event analysis of longitudinal follow-up of a survey: choice of the time-scale. Am J Epidemiol 1997;145:72–80. SAS Institute. SAS System for Microsoft Windows (version 9). Cary, NC: SAS Institute Inc; 2003. Sturman MT, de Leon CF, Bienias JL, Morris MC, Wilson RS, Evans DA. Body mass index and cognitive decline in a biracial community population. Neurology 2008;70:360–367. Yarnell JW, Patterson CC, Thomas HF, Sweetnam PM. Central obesity: predictive value of skinfold measurements for subsequent ischemic heart disease at 14 years follow-up in the Caerphilly Study. Int J Obes Relat Metab Disord 2001;25:1536–1549. Mason C, Craig CL, Katzmarzyk PT. Influence of central and extremity circumferences on all-cause mortality in men and women. Obesity 2008;16:2690–2695. Whitmer RA, Gustafson DR, Barrett-Connor E, Haan MN, Gunderson EP, Yaffe K. Central obesity and increased risk of dementia more than three decades later. Neurology 2008;71:1057–1064. Razay G, Vreugdenhil A, Wilcock G. Obesity, abdominal obesity and Alzheimer disease. Dement Geriatr Cogn Disord 2006;22:173–176.

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25. Mokdad AH, Serdula MK, Dietz WH, Bowman BA, Marks JS, Koplan JP. The spread of the obesity epidemic in the United States, 1991–1998. JAMA 1999;282:1519– 1522. 26. Stunkard AJ, Harris JR, Pedersen NL, McClearn GE. The body-mass index of twins who have been reared apart. N Engl J Med 1990;322:1483–1487. 27. Yamamoto H, Kato Y. Relationship between plasma insulin-growth like factor I (IGF-I) levels and body mass index (BMI) in adults. Endocr J 1993;4:41–45. 28. Harvey J, Solovyova N, Irving A. Leptin and its role in hippocampal synaptic plasticity. Prog Lipid Res 2006;45: 369–378. 29. Singh M, Dykens JA, Simpkins JW. Novel mechanisms for estrogen-induced neuroprotection. Exp Biol Med 2006;231:514–521. 30. Okereke O, Kang JH, Ma J, Hankinson SE, Pollak MN, Grodstein F. Plasma IGF-I levels and cognitive performance in older women. Neurobiol Aging 2007;28:135– 142. 31. Oomura Y, Hori N, Shiraishi T, Fukunaga K, Takeda H, Tsuji M. Leptin facilitates learning and memory performance and enhances hippocampal CA1 long-term potentiation and CaMK II phosphorylation in rats. Peptides 2006;27:2738–2749. 32. Grundman M, Corey-Bloom J, Jerigan T, Archibald S, Thal LJ. Low body weight in Alzheimer’s disease is associated with mesial temporal cortex atrophy. Neurology 1996;46:1585–1591. 33. Friedland RP, Fritsch T, Smyth KA, Koss E, Lerner AJ, Chen CH. Patients with Alzheimer’s disease have reduced activities in midlife compared with healthy control-group members. Proc Natl Acad Sci USA 2001; 98:3440–3445. 34. Djordjevic J, Jones-Gotman M, De Sousa K, Chertkow H. Olfaction in patients with mild cognitive impairment and Alzheimer’s disease. Neurobiol Aging 2008;29:693–706. 35. Chang CC, Roberts BL. Feeding difficulty in older adults with dementia. J Clin Nurs 2008;17:2266–2274. 36. Shatenstein B, Kergoat MJ, Reid I. Poor nutrient intakes during 1-year follow-up with community-dwelling older adults with early-state Alzheimer dementia compared to cognitively intact matched controls. J Am Diet Assoc 2007;107:2091–2099. 37. Sorkin JD, Muller DC, Andres R. Longitudinal change in the heights of men and women: consequential effects on body mass index. Epidemiol Rev 1999;21:247–260. 38. Elmadfa I, Meyer AL. Body composition, changing physiological functions, and nutrient requirements of the elderly. Ann Nutr Metab 2008; 52 suppl 1: 2–5.

Longitudinal and cross-sectional analysis of atrophy in pharmacoresistant temporal lobe epilepsy B.C. Bernhardt, BSc K.J. Worsley, PhD H. Kim, PhD A.C. Evans, PhD A. Bernasconi, MD N. Bernasconi, MD, PhD

Address correspondence and reprint requests to Dr. Neda Bernasconi, Montreal Neurological Institute, 3801 University Street, Montreal, Quebec, Canada H3A 2B4 [email protected]

ABSTRACT

Background: Whether recurrent epileptic seizures induce brain damage is debated. Disease progression in epilepsy has been evaluated only in a few community-based studies involving patients with seizures well controlled by medication. These studies concluded that epilepsy does not inevitably lead to global cerebral damage.

Objective: To track the progression of neocortical atrophy in pharmacoresistant temporal lobe epilepsy (TLE) using longitudinal and cross-sectional designs. Methods: Using a fully automated measure of cortical thickness on MRI, we studied a homogeneous sample of patients with pharmacoresistant TLE. In the longitudinal analysis (n ⫽ 18), fixedeffect models were used to quantify cortical atrophy over a mean interscan interval of 2.5 years (range ⫽ 7 to 90 months). In the cross-sectional analysis (n ⫽ 121), we correlated epilepsy duration and thickness. To dissociate normal aging from pathologic progression, we compared aging effects in TLE to healthy controls. Results: The longitudinal analysis mapped progression in ipsilateral temporopolar and central and contralateral orbitofrontal, insular, and angular regions. In patients with more than 14 years of disease, atrophy progressed more rapidly in frontocentral and parietal regions that in those with shorter duration. The cross-sectional study showed progressive atrophy in the mesial and superolateral frontal, and parietal cortices.

Conclusions: Our combined cross-sectional and longitudinal analysis in patients with pharmacoresistant temporal lobe epilepsy demonstrated progressive neocortical atrophy over a mean interval of 2.5 years that is distinct from normal aging, likely representing seizure-induced damage. The cumulative character of atrophy underlies the importance of early surgical treatment in this group of patients. Neurology® 2009;72:1747–1754 GLOSSARY GM ⫽ gray matter; TLE ⫽ temporal lobe epilepsy; WM ⫽ white matter.

Supplemental data at www.neurology.org

In temporal lobe epilepsy (TLE), a considerable body of MRI studies has established that structural brain abnormalities extend beyond the hippocampus to involve other mesial and limbic structures.1,2 Although the pathogenesis of such changes is not fully understood, experimental3 and human cognitive studies4 suggest that they may be related to recurrent seizures.5 MRI provides a unique tool to evaluate the effects of disease progression in vivo using cross-sectional and longitudinal designs.6 Due to the difficulty in obtaining reliable estimates of seizure counts, cross-sectional studies usually correlate morphometric measurements with duration of epilepsy. The drawback of this approach is the confounding effect of age, because it is highly correlated to duration. On the other hand, correcting for age may fail to yield significant results due to decreased effect size. However, cross-sectional studies generally offer the advan-

Editorial, page 1718 e-Pub ahead of print on February 25, 2009, at www.neurology.org. From the Departments of Neurology (B.C.B., H.K., A.C.E., A.B., N.B.) and Mathematics and Statistics (K.J.W.), Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada. Supported by a grant from the Canadian Institutes of Health Research (CIHR). B.B. was supported by the German National Merit Foundation and the German Academic Exchange Service. Disclosure: The authors report no disclosures. Copyright © 2009 by AAN Enterprises, Inc.

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Table 1 Group

Demographic and clinical data in the cross-sectional sample Age, y

Male

Duration, y

SF

HA, n (%)

Surgery

Engel I

Controls (41)

33 ⫾ 12 (20–66)

19

NA

NA

NA

NA

NA

L TLE (54)

34 ⫾ 10 (16–54)

19

15 ⫾ 11 (0–42)

8 (1–150)

40 (74)

43

28

R TLE (49)

35 ⫾ 10 (18–55)

21

15 ⫾ 11 (0–49)

7 (1–330)

30 (61)

38

29

Age and duration of epilepsy are presented as mean ⫾ SD (range); SF is presented as median (range) seizure frequency per month. SF ⫽ seizure frequency; HA ⫽ number of patients with hippocampal atrophy ipsilateral to the seizure focus (percentage of patients in the group); Engel I ⫽ seizure-free, i.e. Class I postsurgical outcome in Engel’s classification; TLE ⫽ temporal lobe epilepsy.

tage of large sample sizes. Longitudinal designs based on relatively short interscan intervals remove potential aging confounds. Moreover, as they control for intersubject variability, statistical sensitivity to detect subtle changes increases. Importantly, they allow the quantification of morphologic changes over time, thus inferring causality. In patients with pharmacoresistant TLE, longer disease duration has been consistently associated with progressive atrophy of mesiotemporal lobe structures, including the hippocampus and entorhinal cortex.7-9 Whether recurrent seizures in these patients induce neocortical damage remains unclear. Since patients with intractable seizures rarely refuse surgical treatment, only one previous longitudinal study has been preformed in this cohort.9 Thus, progressive neocortical damage has been evaluated only in a few community-based studies involving patients with seizures well controlled by medication.10,11 These studies concluded that epilepsy does not inevitably lead to global cerebral damage, which may develop insidiously over a period longer than 3.5 years. Analyzing cortical thickness on highresolution MRI offers a reliable, direct, and biologically meaningful index to quantify neocortical atrophy.12 Moreover, combining thickness measurement13 with powerful surface-based registration achieves optimal preservation of local surface topology and anatomic correspondence between individuals.14 Using such techniques in TLE, we have previously shown widespread atrophy in the temporal and frontocentral cortices.15 Our purpose was to track progression of neocortical atrophy in intractable TLE on MRI using longitudinal and cross-sectional designs. 1748

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METHODS Subjects. We randomly selected from our database 121 patients referred to our hospital for the investigation of medically intractable TLE and no mass lesion (malformations of cortical development, tumor, or vascular malformations). Demographic and clinical data were obtained through interviews with the patients and their relatives. TLE diagnosis and lateralization of the seizure focus were determined by a comprehensive evaluation including detailed history, video-EEG telemetry, and neuropsychological assessment in all patients. The hippocampus was segmented manually on MRI according to our previously described protocols.2 Based on a volumetric assessment that takes into account absolute volume and interhemispheric asymmetry, we classified patients into those with hippocampal atrophy and those with normal hippocampal volume. Eighteen patients refused to undergo surgery at the first evaluation by our epilepsy team. These patients, however, agreed to have repeated MRI scans. Seven of them eventually followed our recommendation and were operated at subsequent hospitalizations. For patients who underwent surgery, we determined surgical outcome according to Engel’s modified classification scheme.16 Qualitative pathologic examination17 of the resected tissue revealed hippocampal sclerosis in 59 (65%) patients and temporal cortex gliosis in 12 (13%). Due to subpial aspiration, specimens were unsuitable for histopathology in 20 (22%) patients. In total, 42 serial MR scans with at least 2 scans (range ⫽ 2 to 5) per subject were available. All images were acquired on the same MR scanner. The interval between the first and last scan was 31 ⫾ 21 months (range ⫽ 7 to 90). These scans were examined in the longitudinal analysis. We analyzed the remaining 103 patients together with the first scan of the longitudinal sample in the cross-sectional analysis. The control group for cross-sectional analysis consisted of 41 age- and sex-matched healthy individuals (19 men; age 20 – 66 years, mean 33 ⫾ 12 years). The Ethics Committee of the Montreal Neurological Institute and Hospital approved the study and written informed consent was obtained from all participants. Demographic and clinical data of all subjects are shown in tables 1 and 2.

MRI acquisition and processing. MR images were acquired on a 1.5 T Gyroscan (Philips Medical Systems, Eindhoven, Netherlands) using a three-dimensional T1-fast field echo sequence providing an isotropic voxel size of 1 mm3. Images underwent correction for intensity nonuniformity18 and were linearly registered into a standardized stereotaxic space based on the Talairach atlas.19 For cortical thickness measurements, registered images were classified into gray matter (GM), white matter (WM), and CSF. We applied the Constrained Laplacian Anatomic Segmentation using Proximity algorithm13 that iteratively warps a surface mesh to fit the boundary between WM and GM in the classified im-

Table 2 Group

Demographic and clinical data in the longitudinal sample Age, y

Male

Duration, y

SF 10 (2–30)

L TLE (8)

27 ⫾ 10 (17–46)

6

16 ⫾ 13 (1–39)

R TLE (10)

35 ⫾ 12 (17–48)

6

20 ⫾ 12 (7–43)

HA, n (%)

6 (4–330)

Surgery

Engel I

4 (50)

3

2

8 (80)

7

5

Age and duration of epilepsy are presented as mean ⫾ SD (range); SF is presented as median (range) seizure frequency per month. SF ⫽ seizure frequency; HA ⫽ number of patients with hippocampal atrophy ipsilateral to the seizure focus (percentage of patients in the group); Engel I ⫽ seizure-free, i.e. Class I postsurgical outcome in Engel’s classification; TLE ⫽ temporal lobe epilepsy.

age. It then expands the WM/GM boundary along a Laplacian map to generate an outer surface along the GM/CSF boundary. Surfaces were nonlinearly aligned to a surface template20 using a 2D registration procedure.14 We applied the inverse of the linear registration matrix and measured cortical thickness in native space as the distance between corresponding vertices of inner and outer surface across 40,962 points in each hemisphere. Thickness data were blurred using a surface-based diffusion smoothing kernel of 20 mm FWHM that preserves cortical topology.21

Statistical analysis. Analyses were conducted using the SurfStat (http://www.math.mcgill.ca/keith/surfstat/) toolbox for Matlab. Cross-sectional analysis. We correlated disease duration and seizure frequency with mean hemispheric cortical thickness and thickness at each vertex. As seizure frequency followed a highly right-skewed distribution, it was log-transformed before analysis. Hemispheres were pooled together according to side of seizure focus to increase statistical power. To correct for potential effects of age, we correlated age with cortical thickness in patients and controls separately. Linear models for mean hemispheric thickness and vertex-wise analysis contained a group and age main effect term, and a group ⫻ age interaction effect term. We assessed age-related differences in cortical thickness between groups by testing the significance of the interaction term. Longitudinal analysis. To examine the effects of the interscan interval, we fitted linear fixed-effects models containing time from baseline scan and subject intercept as effects on mean hemispheric cortical thickness and thickness at each vertex. We tested for a negative effect of time from baseline scan. Hemispheres were pooled together according to side of seizure focus to increase statistical power. To examine interactions between duration of epilepsy and disease progression, we factorized duration of epilepsy with respect to its median (14 years) into short (i.e., ⬍14 years) and long (i.e., ⱖ14 years). We then fitted a fixed-effects model as above with the factorized duration as an additional term, and tested on the interaction between time from baseline scan and factorized duration. Correction for multiple comparisons. In all vertex-wise analyses, we used random-field theory for nonisotropic images to detect significant clusters.22 This controlled the chance of ever reporting a false positive to be below 0.05. Cortical significance maps were also displayed at an uncorrected level of p ⬍ 0.005. RESULTS Cross-sectional analysis. Effects of duration.

Duration of epilepsy was negatively correlated with mean hemispheric cortical thickness ipsilateral (t ⫽ ⫺2.0, p ⬍ 0.03) and contralateral (t ⫽ ⫺2.7, p ⬍ 0.01) to the seizure focus (figure 1A). Vertex-wise analysis (figure 1B) revealed cortical thinning in ipsi-

lateral mesiotemporal, orbitofrontal (p ⬍ 0.0001), and parietal (p ⬍ 0.02) regions, as well as in a large portion of the contralateral frontal lobe convexity (p ⬍ 0.0001), including the prefrontal, premotor, and central areas. Effects of seizure frequency. Seizure frequency was negatively correlated with mean hemispheric cortical thickness ipsilateral to the seizure focus (t ⫽ ⫺1.99, p ⬍ 0.05). Vertex-wise analysis (figure e-1 on the Neurology® Web site at www.neurology. org) revealed cortical thinning in ipsilateral centroparietal regions (p ⬍ 0.001). Further trends (p ⬍ 0.005) were seen in ipsilateral posterior cingulate and frontal cortices bilaterally. Effects of age. In controls, there were no negative effects of aging on mean left and right hemispheric cortical thickness (figure e-2A). In patients with TLE, aging was associated with decreased cortical thickness in the left (LTLE: t ⬍ ⫺4.48, p ⬍ 0.0001; RTLE: t ⬍ ⫺4.08, p ⬍ 0.001) and right hemisphere (LTLE: t ⬍ ⫺3.16, p ⬍ 0.002; RTLE: t ⬍ ⫺3.15, p ⬍ 0.002). In the left hemisphere, the slope in both TLE groups was steeper than in controls (LTLE: t ⬍ ⫺1.95, p ⬍ 0.03; RTLE: t ⬍ ⫺1.89, p ⬍ 0.04). Similar effects were seen in the right hemisphere, but did not reach significance. Vertex-wise analysis (figure e-2B) in controls showed a cluster of negative age effects in left inferior frontal cortex (p ⬍ 0.0001). The effects of aging were similar in both TLE groups. In LTLE, clusters of negative age effects were located bilaterally in frontal and central (p ⬍ 0.0001), left posterior insular (p ⬍ 0.05), posterior mesiotemporal (p ⬍ 0.05), and right prefrontal and cuneal (p ⬍ 0.05) cortices. In RTLE, clusters of negative age effects were found bilaterally in frontal and central (p ⬍ 0.0001), parietal (p ⬍ 0.0001), temporooccipital (p ⬍ 0.04), and left prefrontal (p ⬍ 0.005) cortices. Vertex-wise analysis of differences in aging (figure e-2C) revealed multiple areas in frontal and occipital areas, with stronger effects in patients compared to controls. In LTLE, a cluster was found in left medial frontal and central regions (p ⬍ 0.01). In RTLE, clusters of Neurology 72

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Figure 1

Cross-sectional analysis

Effects of duration on (A) mean cortical thickness (black dots represent individual patients with temporal lobe epilepsy; the solid black line describes the linear regression model) and (B) thickness at each vertex. Significances have been thresholded at p ⬍ 0.005. Peak positions and resolution elements (i.e., resels) of significant clusters after random field theory correction are shown (cluster threshold t ⬎3.2, cluster extent threshold 0.8 resels).

steeper aging effects were found in the left medial and lateral frontal (p ⬍ 0.002), left occipital (p ⬍ 0.0001), and right parietal (p ⬍ 0.0001) cortices. Longitudinal analysis. Effects of interscan interval. We

found a progressive decrease in mean cortical thickness in the hemisphere ipsilateral (⫺0.016 ⫾ 0.009 mm/ year; t ⫽ ⫺2.20, p ⬍ 0.02) and contralateral to the focus (⫺0.022 ⫾ 0.009 mm/year; t ⫽ ⫺2.88, p ⬍ 0.01) (figure 2A). Annual rates of cortical atrophy (figure 2B) exceeded 0.05 mm/year in bilateral prefrontal, insular, frontocentral; ipsilateral entorhinal; and contralateral temporal and posterior cingulate regions. Vertex-wise analysis (figure 2C) revealed progressive cortical atrophy in contralateral insular and posterior cingulate (p ⬍ 0.05) regions. Moreover, additional areas of atrophy were found in bilateral frontal (orbitofrontal and superior frontal), parietal, and temporal (ipsilateral temporopolar and contralateral lateral temporal) areas (p ⬍ 0.005, uncorrected). Interaction between epilepsy duration and disease progression. 1750

We found a faster progression of atrophy in

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patients with long duration of epilepsy (ⱖ14 years) compared to those with shorter duration (⬍14 years) in the hemisphere ipsilateral (t ⫽ 2.12, p ⬍ 0.03) and contralateral (t ⫽ 1.84, p ⬍ 0.05) to the focus (figure 3). Vertex-wise analysis showed that in patients with longer disease, cortical atrophy progressed faster in bilateral frontocentral (ipsilateral: p ⬍ 0.002; contralateral: p ⬍ 0.04) and ipsilateral parietal (p ⬍ 0.01) regions. DISCUSSION This study combines both crosssectional and longitudinal designs to assess the impact of disease progression on the neocortex in intractable TLE. In the cross-sectional study, we took advantage of a large sample of patients with a wide range of epilepsy durations and compared aging effects to healthy controls, dissociating pathologic progression from normal aging. In the longitudinal analysis, we used fixed-effect models to precisely quantify cortical change over time. Importantly, we applied conservative corrections for multiple comparisons using random field theory,

Figure 2

Longitudinal analysis

Effect of interscan interval on (A) changes in mean hemispheric cortical thickness (gray lines connect the MR scans, indicated as black dots; the mixed-effects model is plotted as a solid black line); (B) vertex-wise mean annual rate of cortical thinning (in mm/year) in blue; (C) regions of vertex-wise progressive thinning (p ⬍ 0.005) in blue. Peak positions and resolution elements (i.e., resels) of significant clusters after random field theory correction are shown (cluster threshold t ⬎3.5, cluster extent threshold 0.8 resels).

which ensures with 95% confidence that no reported result is a type 1 error despite the large number of tests performed.22 The purpose of our cross-sectional analysis was to study the overall effect of duration of epilepsy on neocortical thickness. We found progressive atrophy in ipsilateral orbitofrontal, mesiotemporal, and postcentral, as well as in contralateral prefrontal areas. In a previous cross-sectional study using cortical thickness, progressive atrophy was found in somatomotor and parahippocampal regions.23 Aging effects, however, were not dissociated from those related to disease duration. As disease duration is highly correlated with age, statistically controlling for aging severely reduces the sensitivity to detect significant effects. In our study, we opted to separate these effects by statistically comparing aging in patients to that in healthy controls. Similarly to previously reported data,24

in controls we found neocortical atrophy related to aging in the inferior and middle frontal cortices. Aging effects in patients, while somewhat similar in topography to those of duration of epilepsy, were considerably more extensive and involved virtually the entire frontal lobe. However, after comparison to controls, differences became limited to smaller portions of the mesial frontal and superior frontal lobe convexity, as well as the parietal cortex. This analysis therefore confirms that progressive atrophy in TLE is distinct from aging. Using relatively short follow-up periods in a longitudinal design allows controlling for aging effects. Since a subject is compared to his or her own baseline, such design provides a true measure of change over time required to infer causality between seizures and atrophy. However, adequately powered longitudinal analyses are difficult to perform as they entail the combination of several factors, such as repeated Neurology 72

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Figure 3

Longitudinal analysis

Interaction between duration of epilepsy and disease progression. Superior view showing areas undergoing faster progression of atrophy (p ⬍ 0.005) in patients with longer disease duration (ⱖ14 years). Peak positions and resolution elements (i.e., resels) of clusters after random field theory correction are shown (cluster threshold t ⬎3.5, cluster extent threshold 0.8 resels).

scans performed on the same hardware, reliable and sensitive image postprocessing, and availability of a relatively large group of patients. In our study, we specifically aimed to assess cortical changes in a homogeneous cohort of patients with pharmacoresistant TLE. We localized progressive thinning in ipsilateral temporopolar and central, as well as contralateral orbitofrontal, insular, and angular regions, over a mean interscan period of 2.5 years. Strongest effects were seen in prefrontal and frontal regions, with rates of atrophy in the order of 0.1 mm/ year. As drug-responding patients with TLE are generally not referred to our tertiary center, we could not include a sizeable sample of these patients for comparison. A previous semiquantitative longitudinal MRI study over a median interval of 3.5 years10 failed to detect significant progression of cortical atrophy in patients with relatively benign, pharmacologically controlled forms of epilepsy. Although elevated proportions of patients with TLE had progressive subtle diffuse atrophy compared to healthy controls,11 the authors concluded that these changes resulted mainly from an initial precipitating insult and aging, and not from the disease. There are a number of differences between these studies and our work. First, we have assessed progressive changes in a homogeneous group of patients with intractable TLE, while previous data10,11 were based on groups of community-based patients with various types of pharmacologically controlled epilepsy. From a methodologic point of view, our approach is more sensitive and more reproducible since it does not require any operator intervention.11 Indeed, in contrast to a rater-based 1752

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measurement of change,10 automatically assessing cortical thickness is an unbiased and more direct measurement of atrophy. The algorithm used has been validated against phantom data, and crossvalidated against other MRI surface extraction surface software, showing superior reproducibility.25 Importantly, by avoiding surface self-intersection, it provides the most accurate geometry of the reconstructed surface, thus a topologically sound representation of the cortical mantle.25 In our analysis, the use of a nonlinear 2D surface registration14 in addition to the linear volumetric registration ascertains optimal correspondence of thickness measurements from homologous regions across subjects, thus increasing the sensitivity to detect significant changes. Moreover, in contrast to volumetry, measuring thickness across thousands of points allows precise mapping of the topography of GM atrophy. The pattern of progressive atrophy encompasses both group differences of frontocentral cortical thinning and alterations of limbic network organization in orbitofrontal and posterior cingulate and angular gyri that we recently reported in TLE.15 Seizures have been shown to increase markers of excitability, such as glutamate.26 Furthermore, TLE has been associated with disruptions in cortical GABA-A-ergic circuits, potentially contributing to the genesis or maintenance of seizure activity.27 Excessive metabolic activation resulting from a disrupted balance in these systems may in turn promote epileptogenicity and excitotoxicity, possibly through cellular reorganization.3 This may result in neuronal death and plasticity in both seizure-generating regions, and in neocortical circuits affected by seizure spread.28 Thus, it is plausible that changes observed in the current study may be related to the combined effects of neuronal disconnection and seizure-related damage. However, the putative effects of genetic factors and antiepileptic drugs on atrophy progression cannot be ruled out. The genetic makeup of an individual is thought to influence susceptibility to precipitating events, development of plasticity in neuronal networks, and pharmacoresistance.29,30 On the other hand, we could not control for the effects of drugs since our patients had been on multiple and varying antiepileptic medication for several years. Effects of drugs on the neocortex are largely unknown. While some studies suggest that phenytoin31 induces cerebellar atrophy and valproic acid32 pseudoatrophy of the brain, others have shown that these drugs may have neuroprotective effects and promote neurogenesis.33,34 A recent randomized controlled trial35 demonstrated that 58% of surgically treated patients were seizure free at 1 year, compared with 8% of medically treated patients. The resulting practice guideline rec-

ommends that patients with partial seizures and failed first-line antiepileptic medications should be referred to an epilepsy surgery center, and that those who meet the criteria for temporal lobe resection should be offered surgery.36 Referral for evaluation, however, tends to occur many years after medications have failed, despite the fact that further medication trials are ineffective once intractability sets in.35 During this time, patients are at increased risk of mortality37 and disability. Neocortical atrophy in our patients with epilepsy for longer than 14 years progressed more rapidly than in those with shorter disease duration. Arguably, our results in pharmacoresistant patients may not directly apply to those amenable with optimized medical treatment. However, recent observations from prospective studies in community-based centers indicate that up to 35% of children with TLE may develop intractability.38 Therefore, in light of functional data in humans showing progressive cognitive decline4 and evidence demonstrating that recurrent epileptic discharges provoke an extension of the epileptogenic network,39 our findings support the view that early surgery should be offered to patients with pharmacoresistant TLE.40

7.

8.

9.

10. 11.

12.

13.

14.

15.

16. AUTHOR CONTRIBUTIONS Statistical analysis was conducted by B. Bernhardt (Department of Neurology) and K. Worsley (Department of Mathematics).

17. ACKNOWLEDGMENT The authors thank the individuals who participated in this study.

18.

Received August 20, 2008. Accepted in final form December 15, 2008.

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Bernasconi N, Natsume J, Bernasconi A. Progression in temporal lobe epilepsy: differential atrophy in mesial temporal structures. Neurology 2005;65:223–228. Theodore WH, Bhatia S, Hatta J, et al. Hippocampal atrophy, epilepsy duration, and febrile seizures in patients with partial seizures. Neurology 1999;52:132–136. Fuerst D, Shah J, Shah A, Watson C. Hippocampal sclerosis is a progressive disorder: a longitudinal volumetric MRI study. Ann Neurol 2003;53:413–416. Liu RS, Lemieux L, Bell GS, et al. Progressive neocortical damage in epilepsy. Ann Neurol 2003;53:312–324. Liu RS, Lemieux L, Bell GS, et al. Cerebral damage in epilepsy: a population-based longitudinal quantitative MRI study. Epilepsia 2005;46:1482–1494. MacDonald D, Kabani N, Avis D, Evans AC. Automated 3-D extraction of inner and outer surfaces of cerebral cortex from MRI. Neuroimage 2000;12:340–356. Kim JS, Singh V, Lee JK, et al. Automated 3-D extraction and evaluation of the inner and outer cortical surfaces using a Laplacian map and partial volume effect classification. Neuroimage 2005;27:210–221. Robbins S, Evans AC, Collins DL, Whitesides S. Tuning and comparing spatial normalization methods. Med Image Anal 2004;8:311–323. Bernhardt BC, Worsley KJ, Besson P, et al. Mapping limbic network organization in temporal lobe epilepsy using morphometric correlations: insights on the relation between mesiotemporal connectivity and cortical atrophy. Neuroimage 2008;42:515–524. Engel J, Jr., Van Ness PC, Rasmussen T, Ojemann LM. Outcome with respect to epileptic seizures. In: Engel J, Jr., ed. Surgical Treatment of the Epilepsies, 2nd ed. New York: Raven; 1993:609–621. Meencke HJ, Veith G. Hippocampal sclerosis in epilepsy. In: Lu¨ders H, ed. Epilepsy Surgery. New York: Raven; 1991:705–715. Sled JG, Zijdenbos AP, Evans AC. A nonparametric method for automatic correction of intensity nonuniformity in MRI data. IEEE Trans Med Imaging 1998; 17:87–97. Collins DL, Neelin P, Peters TM, Evans AC. Automatic 3D intersubject registration of MR volumetric data in standardized Talairach space. J Comput Assist Tomogr 1994;18:192–205. Lyttelton O, Boucher M, Robbins S, Evans A. An unbiased iterative group registration template for cortical surface analysis. Neuroimage 2007;34:1535–1544. Lerch JP, Evans AC. Cortical thickness analysis examined through power analysis and a population simulation. Neuroimage 2005;24:163–173. Worsley KJ, Andermann M, Koulis T, MacDonald D, Evans AC. Detecting changes in nonisotropic images. Hum Brain Mapp 1999;8:98–101. Lin JJ, Salamon N, Lee AD, et al. Reduced neocortical thickness and complexity mapped in mesial temporal lobe epilepsy with hippocampal sclerosis. Cereb Cortex 2007; 17:2007–2018. Salat DH, Buckner RL, Snyder AZ, et al. Thinning of the cerebral cortex in aging. Cereb Cortex 2004;14:721–730. Lee JK, Lee JM, Kim JS, Kim IY, Evans AC, Kim SI. A novel quantitative cross-validation of different cortical surface reconstruction algorithms using MRI phantom. Neuroimage 2006;31:572–584.

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Magarinos AM, McEwen BS, Flugge G, Fuchs E. Chronic psychosocial stress causes apical dendritic atrophy of hippocampal CA3 pyramidal neurons in subordinate tree shrews. J Neurosci 1996;16:3534–3540. Wiebe S, Blume WT, Girvin JP, Eliasziw M. A randomized, controlled trial of surgery for temporal lobe epilepsy. N Engl J Med 2001;345:311–318. Engel J, Jr., Wiebe S, French J, et al. Practice parameter: temporal lobe and localized neocortical resections for epilepsy: report of the Quality Standards Subcommittee of the American Academy of Neurology, in association with the American Epilepsy Society and the American Association of Neurological Surgeons. Neurology 2003;60:538– 547. Sperling MR, Feldman H, Kinman J, Liporace JD, O’Connor MJ. Seizure control and mortality in epilepsy. Ann Neurol 1999;46:45–50. Berg AT, Vickrey BG, Testa FM, et al. How long does it take for epilepsy to become intractable? A prospective investigation. Ann Neurol 2006;60:73–79. Bartolomei F, Chauvel P, Wendling F. Epileptogenicity of brain structures in human temporal lobe epilepsy: a quantified study from intracerebral EEG. Brain 2008;131: 1818–1830. Langfitt JT, Wiebe S. Early surgical treatment for epilepsy. Curr Opin Neurol 2008;21:179–183.

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SEPT9 gene sequencing analysis reveals recurrent mutations in hereditary neuralgic amyotrophy M.C. Hannibal, MD, PhD E.K. Ruzzo, BS L.R. Miller, BS B. Betz, BS J.G. Buchan, BS D.M. Knutzen, MS K. Barnett, MS M.L. Landsverk, PhD A. Brice, MD E. LeGuern, MD, PhD H.M. Bedford, MD B.B. Worrall, MD, MSc S. Lovitt, MD S.H. Appel, MD E. Andermann, MD, PhD T.D. Bird, MD P.F. Chance, MD

Address correspondence and reprint requests to Dr. Mark C. Hannibal, Neurogenetics Laboratory, 1959 NE Pacific St., Health Sciences RR236, Box 356320, Division of Genetics and Developmental Medicine, Department of Pediatrics, University of Washington School of Medicine, Seattle, WA 981956320 [email protected]

ABSTRACT

Background: Hereditary neuralgic amyotrophy (HNA) is an autosomal dominant disorder that manifests as recurrent, episodic, painful brachial neuropathies. A gene for HNA maps to chromosome 17q25.3 where mutations in SEPT9, encoding the septin-9 protein, have been identified.

Objective: To determine the frequency and type of mutations in the SEPT9 gene in a new cohort of 42 unrelated HNA pedigrees.

Methods: DNA sequencing of all exons and intron-exon boundaries for SEPT9 was carried out in an affected individual in each pedigree from our HNA cohort. Genotyping using microsatellite markers spanning the SEPT9 gene was also used to identify pedigrees with a previously reported founder haplotype.

Results: Two missense mutations were found: c.262C⬎T (p.Arg88Trp) in seven HNA pedigrees and c.278C⬎T (p.Ser93Phe) in one HNA pedigree. Sequencing of other known exons in SEPT9 detected no additional disease-associated mutations. A founder haplotype, without defined mutations in SEPT9, was present in seven pedigrees.

Conclusions: We provide further evidence that mutation of the SEPT9 gene is the molecular basis of some cases of hereditary neuralgic amyotrophy (HNA). DNA sequencing of SEPT9 demonstrates a restricted set of mutations in this cohort of HNA pedigrees. Nonetheless, sequence analysis will have an important role in mutation detection in HNA. Additional techniques will be required to find SEPT9 mutations in an HNA founder haplotype and other pedigrees. Neurology® 2009;72:1755–1759 GLOSSARY HNA ⫽ hereditary neuralgic amyotrophy; SNP ⫽ single nucleotide polymorphism; STR ⫽ short tandem repeat; UTR ⫽ untranslated region.

Hereditary neuralgic amyotrophy (HNA) is an autosomal dominant disorder characterized by painful, episodic, focal motor and sensory attacks, primarily affecting the nerves of the brachial plexus.1-3 Associated findings in some individuals with HNA include relative hypotelorism, occasional cleft palate, and skin folds or creases on the neck or forearm.1 A gene for HNA was localized to human chromosome 17q25.3 in several pedigrees.4-6 In probands of six unrelated HNA pedigrees linked to chromosome 17q25.3, we identified three different point mutations in the alternatively spliced SEPT9 gene that encodes septin 9 proteins.7 One mutation was a c.-131G⬎C transversion in the 5= untranslated region (UTR) found in a Turkish family (nucleotide is based on SEPT9 transcript variant 3, RefSeq NM_006640.4 in GenBank).8-10 Additionally, two mutations causing missense changes in septin-9 protein isoform c, c.262C⬎T (p.Arg88Trp) and c.278C⬎T (p.Ser93Phe), were detected in Europeans and North American descendants of Europeans (RefSeq NP_006631.2).8,9 Additional HNA pedigrees from Europe and North America have the c.262C⬎T mutation.11,12

Supplemental data at www.neurology.org Authors’ affiliations are listed at the end of the article. Supported by funds from the NIH (National Institute of Neurological Disorders and Stroke), NS38181 (P.F.C. and M.C.H.); The Neuropathy Association, New York, NY (M.C.H. and P.F.C.); and the Allan and Phyllis Treuer Endowed Chair for Genetics and Development (P.F.C.). Disclosure: Dr. Chance has received Speaker’s Bureau honoraria from Athena Diagnostics, Inc. Dr. Bird has received licensing fees from Athena Diagnostics, Inc. Medical Device: Gentra Puregene Blood Kit (Qiagen, Valencia, CA). Copyright © 2009 by AAN Enterprises, Inc.

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Table

Hereditary neuralgic amyotrophy SEPT9 mutation analysis summary

Pedigree

Cited in

K4003

7

K4009

This report

K4020

This report

K4024

11

Mutation position*†

No. controls examined‡

Genomic: g.Chr17:72,909,975C⬎T

K4026

This report

cDNA: SEPT9_v3 c.262C⬎T (NM_006640.4)

K4027

This report

Protein: SEPT9c p.Arg88Trp (NP_006631.2)

K4033

This report

K4052

This report

K4059

This report

K4018

7

K4012

This report

⬎100

Genomic: g.Chr17:72,909,993C⬎T cDNA: SEPT9_v3 c.278C⬎T (NM_006640.4)

⬎100

Protein: SEPT9c p.Ser93Phe (NP_006631.2)

*Position of the SEPT9 mutation on the genome assembly obtained from the UCSC Genome Browser, NCBI Build 36.1, March 2006 (hg18).35,36 †Position of the mutation, numbered from the first nucleotide of the initiation codon of SEPT9_v3 transcript variant and amino acid position in SEPT9c protein isoform.9,10 ‡Additional sequence data of this region show these mutations are absent from a large number of controls.7

In this study, we undertook sequence analysis of the SEPT9 gene in a large cohort of 42 pedigrees with HNA that were not included in our HNA gene identification report.7 This analysis was performed to confirm that SEPT9 is the critical gene for HNA, to search for additional mutations, and to estimate the likelihood of detecting mutations in this gene given a clinical phenotype consistent with HNA. METHODS Clinical evaluations. A diagnosis of HNA was established based on published criteria, including the presence of autosomal dominant inheritance.3,13 These clinical features typically included a history of one or more sudden onset, painful attacks in the neck, shoulder, or arm, followed by focal paresis, sensory disturbances, and muscle atrophy. Typically, the attacks involved the brachial plexus; however, other peripheral nerves (e.g., lumbosacral plexus, phrenic nerve) were affected in some cases. Probands and other affected and at risk subjects were evaluated by P.F.C., T.D.B., or referring physicians. Written consent was obtained from the subjects. The Human Subjects Division at the University of Washington approved this study. The clinical features for eight pedigrees included in this cohort of 42, K4001, K4004, K4006, K4012 (SAL819), K4026 (S Family), K4027 (G Family), K4028, and K4043 (classic type), have been described previously.1,14-17 We excluded pedigrees in our cohort that do not link to chromosome 17q25.3: K4008, K4016, and K4044 (chronic undulating type).17,18

Molecular genetic analysis. Genomic DNA was isolated from peripheral blood or lymphoblastoid cell lines of subjects by standard methods using a Gentra Puregene Blood Kit (Qiagen, Valencia, CA). DNA from an affected individual from each pedigree was subjected to SEPT9 mutational analysis by sequencing 1756

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known exons and adjacent intron-exon boundaries. Typically, the proband was chosen to be sequenced because we often had the best clinical evidence that they had features of HNA. For larger pedigrees, both clinical and genetic criteria were used to choose an affected individual who had an affected parent and, if possible, an affected offspring. The regions surrounding exons of the SEPT9 gene were amplified by thermal cycling and subjected to bidirectional sequencing according to previously published methods.7 Thermal cycling primers are provided in table e-1 on the Neurology® Web site at www.neurology.org. In each proband where nucleotide changes that varied from the human genome reference sequence were found, the sequence was examined for known single nucleotide polymorphisms (SNPs) and segregation with disease in the pedigree. At least 100 individuals in a control population, unaffected by HNA, were also examined by direct sequencing or restriction fragment length polymorphism analysis to determine if the same SEPT9 variant was present in a healthy, unrelated population (table).

Founder haplotype genotyping. Short tandem repeat (STR) markers, which were used previously to define the conserved shared block in the original five HNA founder pedigrees, were used to determine if pedigrees in the present cohort also possessed the founder haplotype.7,19 Following amplification with the STR primers, products were sized on an ABI 3100 Genetic Analyzer (Applied Biosystems, Foster City, CA). Segregation patterns of the alleles were determined, and haplotypes constructed in a manner to minimize crossovers. RESULTS Identification of SEPT9 mutations and

mutation segregation. We screened a total of 42 ped-

igrees with HNA. SEPT9 gene mutations are summarized in the table. The locations of the genomic changes are shown, along with the position in transcript variant SEPT9_v3 and the corresponding protein isoform SEPT9c. Two of the previously reported SEPT9 mutations were also identified among these 42 HNA pedigrees, the c.262C⬎T (p.Arg88Trp) and the c.278C⬎T (p.Ser93Phe) mutation.7,11,12 In seven pedigrees, K4009, K4020, K4026, K4027, K4033, K4052, and K4059, the c.262C⬎T mutation was found in affected individuals. In one pedigree, K4012, from France, the c.278C⬎T mutation was identified. Segregation of these mutations within HNA pedigrees is shown in the figure. No other causal mutations were found in the other 34 pedigrees, although one coding, nonsynonymous single nucleotide polymorphism (SNP rs34587622 in dbSNP) was found to segregate with HNA in a subset of seven.20 The rs34587622 SNP, c.380C⬎T, changes the proline at amino acid position 128 to leucine in SEPT9 isoform c (p.Pro127Leu in NP_006631.2). This SNP was found initially in a single proband, who also possessed the c.262C⬎T (p.Arg88Trp) mutation, and in controls during candidate gene sequencing in HNA pedigrees.21 The c.380T allele is present within five founder haplotype HNA pedigrees previously identified.7,19 This allele also segregates with HNA in 7 of 42 pedigrees in this cohort that all bear the com-

Figure

Segregation of SEPT9 gene mutations in HNA pedigrees

Females are shown as circles and males as squares. Affected persons are represented by darkened figures, presumed affected individuals have diagonal black lines, and crossslatted figures are deceased. Question marks within figures indicate inadequate clinical data and may indicate some individuals who were obligate carriers without pain attacks. If DNA was available from an individual, the sequencing result is indicated below the identifier. (A) Pedigrees with the g.Chr17:72,909,975C⬎T, c.262C⬎T, p.Arg88Trp mutation. (B) Pedigree with g.Chr17:72,909,993C⬎T, c.278C⬎T, p.Ser93Phe mutation.

mon North American founder haplotype (data not shown). However, because the c.380C⬎T allele is present in 28% (29/104) of control individuals of Caucasian descent, and the dbSNP database finds it in 15.4% (4/26) of North Americans and 5% (6/ 120) of Europeans, we do not believe it is a causal mutation.20 DISCUSSION To date, three point mutations (c.131G⬎C, c.262C⬎T, and c.278C⬎T) and a ge-

netic founder haplotype have been identified in HNA pedigrees supporting a critical role for the SEPT9 gene.7,11,12 Combining the results from the 42 pedigrees in this report with the 7 pedigrees previously reported from our laboratory, we detected SEPT9 mutations in 22.4% (11/49) of our total cohort.7,11 A further 24.5% of these HNA pedigrees possess the founder haplotype defined by the markers previously reported.7,19 The moderate mutation detection rate may be due to several factors. First, our present methods may be unable to detect small SEPT9 insertions, deletions, inversions, or other gene rearrangements. For example, it will likely be necessary to undertake complete genomic sequencing of SEPT9 in a subject having the founder haplotype in order to detect a causal mutation in this subset of HNA pedigrees. Second, more subtle regulatory mutations may occur outside of the region of exons and intronexon boundaries that could, in turn, influence the relative abundance of specific SEPT9 alternative 5= exon isoforms. Third, genetic heterogeneity does exist for HNA. To date, the gene for HNA in five pedigrees has been shown to be unlinked to markers in the 17q25.3 region.17,18,22 In some cases, HNA pedigrees are not large enough to confirm or exclude chromosome 17q25.3 linkage. Fourth, the potential for phenocopies may exist, with familial clustering of similar, but distinct multifocal, painful neuropathies that may be caused by peripheral nerve vasculitis, an example of which can be seen in proximal diabetic neuropathy or diabetic amyotrophy.23,24 HNA is the first Mendelian disorder shown to be due to mutations in a member of the septin gene family of related proteins. The septin gene family includes at least 14 members in humans.25,26 Septins participate in cytokinesis and cellular trafficking and have been studied for their relationship to neoplasia.27 Transcriptional and potentially translational regulation of the SEPT9 gene is complex.28 SEPT9 appears to be expressed ubiquitously, but information regarding the distribution and abundance of the various septin-9 protein isoforms in normal tissues is limited.29 The longer isoforms of septin-9 have unique short N-terminal polypeptides and share a proline-rich domain that is found only in the septin-4 and septin-8 proteins.25 Septin-9 has been shown to colocalize with other septins and with septin intermediate filaments that associate with actin microfilaments and microtubules.30,31 At the transcriptional level, the SEPT9 gene shows a remarkable number of alternative first exons. These multiple 5= alternative transcription start sites, as well as possible alternative splicing within the final exon, potentially create dozens of protein isoforms.28 The two mutations reported here, c.262C⬎T Neurology 72

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at g.Chr17:72,909,975C⬎T and c.278C⬎T at g.Chr17:72,909,993C⬎T, can lead to missense mutations in the translated product of the SEPT9_v1, SEPT9_v2, and SEPT9_v3 transcripts, but are in the 5= untranslated region of SEPT9_v4 and SEPT9_v4* transcripts.28,32 This diversity of transcripts has made analysis of the functional consequences of SEPT9 gene mutations difficult.32 Under hypoxic conditions, the c.262C⬎T mutation reportedly affects the level of translation of the SEPT9_v4 transcript, encoding SEPT9 protein isoform e (GenBank NM_001113494.1 and NP_001106966.1).32 The HNA-associated mutations in SEPT9_v3, p.Arg88Trp and p.Ser93Phe, altered the colocalization of mutant septin-9 protein isoform c with septin-4 and septin-11 in mesenchymal and epithelial murine mammary gland NMuMG cells.33 These mutations also perturb the regulation of septin-9containing filaments by Rho/Rhotekin signaling.33 Thus, this N-terminal proline-rich domain, in which these mutations reside, may regulate specific interactions of septin-9 with other septins or other cellular proteins as proposed by Nagata et al.31,34 These findings are only the first steps in determining how mutations in SEPT9 lead to the distinctive phenotype seen in HNA. The mechanism of how SEPT9 mutations lead to a brachial neuropathy and other features of HNA remains unknown. In this study, we provided further evidence that mutation of the SEPT9 gene is the molecular basis of some cases of HNA. We also found that the detection rate for SEPT9 mutations in pedigrees consistent with this disorder is low. This is due to few identifiable mutations found by our present mutation analysis strategy of sequencing SEPT9 exons. This strategy has not found a mutation in the significant fraction of HNA pedigrees that harbor a genetic founder chromosome. Clearly, identification of the specific SEPT9 mutation associated with the genetic founder will greatly improve the clinical usefulness of SEPT9 analysis as a diagnostic and predictive tool for HNA. AUTHORS’ AFFILIATIONS From the Departments of Pediatrics (M.C.H., E.K.R., L.R.M., B.B., J.G.B., D.M.K., K.B., M.L.L., P.F.C.), Neurology (T.D.B., P.F.C.), and Medicine (T.D.B.), University of Washington School of Medicine, Seattle; Seattle Children’s Hospital (M.C.H., P.F.C.); Geriatric Research Education and Clinical Center (T.D.B.), VA Puget Sound Health Care System, Seattle; Department of Genetics and Cytogenetics (A.B., E.L.), INSERM, UMR S679, Pierre and Marie Curie Paris VI University, Pitie´Salpeˆtrie´re Medical School, AP-HP, Pitie´-Salpeˆtrie´re Hospital, Paris, France; Genetics Programme (H.M.B.), North York General Hospital, Toronto, Ontario, Canada; Departments of Neurology and Public Health Sciences (B.B.W.), University of Virginia Health System, Charlottesville; Department of Neurology (S.H.A), Methodist Neurological Institute (S.L.), Houston, TX; and Departments of Neurology & Neurosurgery 1758

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and Human Genetics (E.A.), Neurogenetics Unit, Montreal Neurological Hospital and Institute, McGill University, Montreal, Quebec, Canada.

ACKNOWLEDGMENT The authors thank Jonathan Adkins and Melissa Eckert for DNA isolation and lymphoblastoid cell line establishment and all of the clinical contributors, patients, and families for facilitating pedigree identification and obtaining research materials.

Received August 11, 2008. Accepted in final form February 13, 2009. REFERENCES 1. Jeannet PY, Watts GD, Bird TD, Chance PF. Craniofacial and cutaneous findings expand the phenotype of hereditary neuralgic amyotrophy. Neurology 2001;57:1963– 1968. 2. van Alfen N, van Engelen BG. The clinical spectrum of neuralgic amyotrophy in 246 cases. Brain 2006;129:438– 450. 3. Hannibal MC, van Alfen N, Chance PF, van Engelen BGM. Hereditary neuralgic amyotrophy. Available at: http://www.genetests.org. Accessed August 10, 2008. 4. Pellegrino JE, Rebbeck TR, Brown MJ, Bird TD, Chance PF. Mapping of hereditary neuralgic amyotrophy (familial brachial plexus neuropathy) to distal chromosome 17q. Neurology 1996;46:1128–1132. 5. Wehnert M, Timmerman V, Spoelders P, Meuleman J, Nelis E, Van Broeckhoven C. Further evidence supporting linkage of hereditary neuralgic amyotrophy to chromosome 17q. Neurology 1997;48:1719–1721. 6. Sto¨gbauer F, Young P, Timmerman V, et al. Refinement of the hereditary neuralgic amyotrophy (HNA) locus to chromosome 17q24-q25. Hum Genet 1997;99:685–687. 7. Kuhlenba¨umer G, Hannibal MC, Nelis E, et al. Mutations in SEPT9 cause hereditary neuralgic amyotrophy. Nat Genet 2005;37:1044–1046. 8. den Dunnen JT, Antonarakis SE. Mutation nomenclature extensions and suggestions to describe complex mutations: a discussion. Hum Mutat 2000;15:7–12. 9. Pruitt KD, Tatusova T, Maglott DR. NCBI reference sequences (RefSeq): a curated non-redundant sequence database of genomes, transcripts and proteins. Nucleic Acids Res 2007;35:D61–D65. 10. Benson DA, Karsch-Mizrachi I, Lipman DJ, Ostell J, Wheeler DL. GenBank. Nucleic Acids Res 2008;36:D25– D30. 11. Laccone F, Hannibal MC, Neesen J, Grisold W, Chance PF, Rehder H. Dysmorphic syndrome of hereditary neuralgic amyotrophy associated with a SEPT9 gene mutation: a family study. Clin Genet 2008;74:279–283. 12. Hoque R, Schwendimann RN, Kelley RE, Bien-Willner R, Sivakumar K. Painful brachial plexopathies in SEPT9 mutations: adverse outcome related to comorbid states. J Clin Neuromuscul Dis 2008;9:379–384. 13. Kuhlenba¨umer G, Sto¨gbauer F, Timmerman V, DeJonghe P. Diagnostic guidelines for hereditary neuralgic amyotrophy or heredofamilial neuritis with brachial plexus predilection. on behalf of the European CMT consortium. Neuromuscul Disord 2000;10:515–517. 14. Taylor RA. Heredofamilial mononeuritis multiplex with brachial predilection. Brain 1960;83:113–137. 15. Jacob JC, Andermann F, Robb JP. Heredofamilial neuritis with brachial predilection. Neurology 1961;11: 1025–1033.

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Hall PA, Russell SE. The pathobiology of the septin gene family. J Pathol 2004;204:489–505. McIlhatton MA, Burrows JF, Donaghy PG, Chanduloy S, Johnston PG, Russell SE. Genomic organization, complex splicing pattern and expression of a human septin gene on chromosome 17q25.3. Oncogene 2001;20:5930–5939. Scott M, Hyland PL, McGregor G, Hillan KJ, Russell SE, Hall PA. Multimodality expression profiling shows SEPT9 to be overexpressed in a wide range of human tumours. Oncogene 2005;24:4688–4700. Surka MC, Tsang CW, Trimble WS. The mammalian septin MSF localizes with microtubules and is required for completion of cytokinesis. Mol Biol Cell 2002;13:3532– 3545. Nagata K, Asano T, Nozawa Y, Inagaki M. Biochemical and cell biological analyses of a mammalian septin complex, Sept7/9b/11. J Biol Chem 2004;279:55895–55904. McDade SS, Hall PA, Russell SE. Translational control of SEPT9 isoforms is perturbed in disease. Hum Mol Genet 2007;16:742–752. Sudo K, Ito H, Iwamoto I, Morishita R, Asano T, Nagata K. SEPT9 sequence alternations causing hereditary neuralgic amyotrophy are associated with altered interactions with SEPT4/SEPT11 and resistance to Rho/Rhotekinsignaling. Hum Mutat 2007;28:1005–1013. Nagata K, Inagaki M. Cytoskeletal modification of rho guanine nucleotide exchange factor activity: identification of a rho guanine nucleotide exchange factor as a binding partner for Sept9b, a mammalian septin. Oncogene 2005; 24:65–76. Lander ES, Linton LM, Birren B, et al. Initial sequencing and analysis of the human genome. Nature 2001;409: 860–921. Karolchik D, Baertsch R, Diekhans M, et al. The UCSC genome browser database. Nucleic Acids Res 2003;31: 51–54.

New Guidelines Examine Safety of Women with Epilepsy and Pregnancy New evidence-based practice guidelines developed by the American Academy of Neurology in full collaboration with the American Epilepsy Society show the relative safety for women with epilepsy to become pregnant, but caution against taking one particular epilepsy drug, which can cause birth defects. The guidelines were published in the April 27, 2009, online issue of Neurology® and were presented at the AAN’s Annual Meeting in Seattle. The guidelines were also published electronically in Epilepsia, the journal of the International League Against Epilepsy. They represent an update of the 1998 guideline, “Management Issues for Women with Epilepsy.”

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Quality of life in multiple sclerosis is associated with lesion burden and brain volume measures E.M. Mowry, MD A. Beheshtian, MD E. Waubant, MD, PhD D.S. Goodin, MD B.A. Cree, MD, PhD, MCR P. Qualley, MA R. Lincoln, BS M.F. George, BA R. Gomez, BS S.L. Hauser, MD D.T. Okuda, MD D. Pelletier, MD

Address correspondence and reprint requests to Dr. Ellen M. Mowry, University of California, San Francisco, UCSF Multiple Sclerosis Center, 350 Parnassus Ave., Suite 908, San Francisco, CA 94117 [email protected]

ABSTRACT

Background: Health-related quality of life (HRQOL) is reduced in multiple sclerosis (MS). It is unclear whether HRQOL is associated with white matter lesion burden or measures of brain atrophy.

Methods: A cross-sectional baseline analysis of 507 patients with MS in a prospective cohort study at the University of California, San Francisco was performed. Multivariate linear regression models were used to determine whether MRI measures were associated with the Emotional WellBeing and Thinking/Fatigue subscale scores of the Functional Assessment in Multiple Sclerosis, a validated HRQOL measure in MS. The difference in each MRI metric associated with a minimal clinically important difference in each HRQOL subscale was calculated.

Results: Higher T1 lesion load (15 mL; p ⫽ 0.024), normalized T1 lesion volume (20 mL; p ⫽ 0.016), or T2 lesion load (25 mL; p ⫽ 0.028) was associated with worse scores for Emotional Well-Being. Meaningfully lower scores on this subscale were correlated with lower normalized gray matter volume (118 mL; p ⫽ 0.037). Reduced Thinking/Fatigue scores were associated with higher normalized T1 lesion volume (21 mL; p ⫽ 0.024), or T2 lesion load (22 mL; p ⫽ 0.010) and with lower normalized gray matter (87 mL; p ⫽ 0.004), white matter (85 mL; p ⫽ 0.025), or brain parenchymal (98 mL; p ⫽ 0.001) volume.

Conclusions: Aspects of health-related quality of life (HRQOL) in multiple sclerosis are associated with MRI evidence of white matter lesions and brain atrophy. These findings strengthen the argument for the use of HRQOL outcome measures in trials and suggest that lesion burden on conventional MRI is important for HRQOL. Neurology® 2009;72:1760–1765 GLOSSARY CIS ⫽ clinically isolated syndrome; DMT ⫽ disease-modifying therapy; EDSS ⫽ Expanded Disability Status Scale; EWB ⫽ Emotional Well-Being; FAMS ⫽ Functional Assessment in Multiple Sclerosis; FOV ⫽ field of view; HRQOL ⫽ health-related quality of life; IQR ⫽ interquartile range; IRSPGR ⫽ inversion recovery spoiled gradient-recalled; PASAT ⫽ Paced Auditory Serial Addition Test; PPMS ⫽ primary progressive multiple sclerosis; PRMS ⫽ progressive relapsing multiple sclerosis; MS ⫽ multiple sclerosis; MSFC ⫽ Multiple Sclerosis Functional Composite; nBPV ⫽ normalized brain parenchymal volume; NEX ⫽ number of excitations; nGMV ⫽ normalized gray matter volume; nT1LV ⫽ normalized T1 lesion volume; nWMV ⫽ normalized white matter volume; RRMS ⫽ relapsing–remitting multiple sclerosis; SPMS ⫽ secondary progressive multiple sclerosis; TE ⫽ echo time; TI ⫽ inversion time; TF ⫽ Thinking/Fatigue; TR ⫽ repetition time; UCSF ⫽ University of California, San Francisco.

Measures of health-related quality of life (HRQOL) are considered more comprehensive in capturing the overall impact of multiple sclerosis (MS) than physical disability scales such as the Expanded Disability Status Scale (EDSS).1 As a result, the US Food and Drug Administration now mandates the incorporation of HRQOL measures into MS clinical trials.2 It is postulated that irreversible neuroaxonal loss, which begins in the early stages of MS and is in part independent of new lesion formation,3-7 may be the primary contributor to disease progression. Although patients with early MS often have normal or only mildly abnormal neurologic examinations, they often report reduced HRQOL scores.1,8 We hypothesized that such reduced HRQOL Supplemental data at www.neurology.org From the Department of Neurology, University of California, San Francisco, CA. Supported in part by grants from the NIH (NS26799, AI067152, R01 NS049477, U19 AI067152, K23 NS048869), the National Multiple Sclerosis Society (RG 3517), a research grant from GlaxoSmithKline, and gifts from the Signe Ostby Foundation and the Friends of Amy. This work was also made possible by a Partners MS Center Clinical Fellowship Award, a Genentech Fellowship Award, and a National Multiple Sclerosis Society Sylvia Lawry Fellowship Award (to E.M.M.). D.P. is a Harry Weaver Neuroscience Scholar of the National Multiple Sclerosis Society. Disclosure: The authors report no disclosures. Medical Device: 3-Tesla GE Excite scanner (GE Healthcare Technologies, Waukesha, WI). 1760

Copyright © 2009 by AAN Enterprises, Inc.

may be related to neurodegeneration in MS. As such, we sought to determine whether there is an association between aspects of HRQOL, specifically emotional well-being and thinking and fatigue, and disease burden as assessed by highresolution MRI techniques. Establishing such an association would further support the use of patient-reported HRQOL outcomes in MS trials. METHODS Research participants. The protocol was approved by the Committee on Human Research at the University of California, San Francisco (UCSF), and informed consent was obtained from all participants. White (Hispanic and nonHispanic) patients aged 18 –70 years with an EDSS score less than 8.0 were recruited for inclusion in this study between July 2004 and September 2005, primarily from the UCSF Multiple Sclerosis Center. The diagnosis of MS or clinically isolated syndrome (CIS) was required and was made using the International Panel criteria.9,10 CIS was defined as the first well-defined neurologic clinical demyelinating event lasting more than 48 hours. In patients presenting with CIS, the brain MRI had to meet three of four Barkhof criteria.10 Patients were not enrolled if they had experienced a clinical relapse or had received treatment with glucocorticosteroids within the previous month, if they were participating in a study of nonapproved medications for MS, or if they were unable to undergo MRI. Patients with medical conditions that could put them at risk by participating in the study or who had recently abused drugs or alcohol were also excluded.

Clinical and laboratory assessments. For all subjects, the baseline EDSS and Multiple Sclerosis Functional Composite (MSFC) scores were measured.11,12 Additional data included age at disease onset and at enrollment, sex, disease subtype, disease duration, and treatment status (use of disease-modifying therapy [DMT] at the time of study).

Health-Related Quality-of-Life assessment. To assess aspects of HRQOL, the Emotional Well-Being and Thinking/ Fatigue subscales of the Functional Assessment in Multiple Sclerosis (FAMS)13 version 4 were administered within 2 weeks of the brain MRI scans. The FAMS is a validated HRQOL instrument that uses self-assessment based on how well patients agree with statements about aspects of quality of life in the past 7 days. Scores ranging from 0 (not at all) to 4 (very much) were assigned to the Emotional Well-Being (seven questions) and Thinking/Fatigue (nine questions) sections. The raw scores of negatively worded questions, per the protocol, were reversed so that higher item and subscale scores reflected better HRQOL.13 Subscale summary scores were generated based on the answers to the questions; the possible range for Emotional Well-Being was therefore 0 to 28 (with 28 reflecting the best possible score), whereas for Thinking/Fatigue, the scores range from 0 to 36 (with 36 reflecting the best possible score). MRI protocol. Image acquisition. Brain MRI scans were performed in all subjects after entry into the study, and analyses were performed without knowledge of disease subtype, duration, treatment history, or performance on HRQOL measures. MRI images were acquired using an eight-channel phased array coil in reception and a body coil in transmission on a 3-tesla GE Excite scanner (GE Healthcare Technologies, Waukesha, WI). Each MRI examination included scout localizers and axial dual-echo

spin echo sequences (echo time [TE] at 20 and 90 msec, repetition time [TR] ⫽ 2,000 msec, 512 ⫻ 512 ⫻ 44 matrix, 240 ⫻ 240 ⫻ 132-mm3 field of view [FOV], slice thickness ⫽ 3 mm, interleaved). A high-resolution inversion recovery gradient-echo T1-weighted isotropic, volumetric sequence (three-dimensional inversion recovery spoiled gradient-recalled (IRSPGR) 1 ⫻ 1 ⫻ 1 mm3, 180 slices) was also performed (TE/TR/inversion time [TI] ⫽ 2/7/400 msec, flip angle ⫽ 15°, 256 ⫻ 256 ⫻ 180 matrix, 240 ⫻ 240 ⫻ 180-mm3 FOV, number of excitations [NEX] ⫽ 1). Conventional spin echo, T1-weighted images were acquired 5 minutes after administration of a single dose (0.1 mM/kg) of contrast agent (TE/TR ⫽ 8/467 msec, 256 ⫻ 256 ⫻ 44 matrix, 240 ⫻ 240 ⫻ 132-mm3 FOV, NEX ⫽ 1). Lesion identification. Brain lesions were identified on the baseline high-resolution T1-weighted, T2-weighted, and proton density–weighted images. Regions of interest were manually drawn on the high-resolution three-dimensional IRSPGR T1weighted images based on a semiautomated pixel intensity threshold with manual editing, using in-house software, and T1 lesion masks were created.14 Brain tissue segmentation and normalization. Brain segmentation and normalization were performed using SIENAX (Image Analysis Group, Oxford, UK), a fully automated technique. T1 lesion masks (described above) were incorporated into the SIENAX program to correct for misclassifications of parenchymal tissue while high-resolution T1-weighted images were segmented into images representing the volume of each voxel containing gray matter, white matter, CSF, and white matter lesions. The lesion masks overrode all SIENAX tissue classifications. Normalized tissue volumes were calculated by summing the lesion-corrected, partial volume estimate maps, multiplied by the brain scaling factor calculated by the SIENAX program yielding the following metrics: normalized T1 lesion volume (nT1LV), normalized white matter volume (nWMV), normalized gray matter volume (nGMV), normalized brain parenchymal volume (nBPV), and nT1LV/nWMV.

Statistical analyses. Calculations and statistical analyses were performed using Stata 10.0 statistical software (StataCorp, College Station, TX). Means ⫾ SDs or medians (with interquartile ranges) were used to summarize demographic and clinical data. Linear regression models were used to examine the relation between HRQOL scores and MRI predictors of interest. Based on estimates from the literature, we used the Cohen formulation of the (standardized) effect size, a method in which a standardized effect size of 0.20 is deemed a “small” effect size, which can be considered the equivalent of the minimal clinically important difference.15 The standardized effect size is multiplied by the baseline SD of the HRQOL scale/subscale score to obtain a corresponding effect size on the actual scale. Using the standard deviations obtained here for Emotional Well-Being (4.85) and for Thinking/Fatigue (8.63), the corresponding minimal clinically important differences were calculated to be 0.97 and 1.73 points. We then determined the difference in each individual predictor (MRI parameter) that was associated with the minimal clinically important difference on these subscales and, from this, rescaled each predictor. We generated new linear regression models and calculated the 95% confidence interval (CI) surrounding these rescaled regression lines. Rather than using automated methodologies, we added covariates to the multivariate models that were considered as potential confounders a priori or were necessary for face validity, including age at enrollment, sex, disease duration, and DMT status. Treatment was considered important because DMTs have, in some MS studies, indepenNeurology 72

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Table 1

Demographic characteristics of the study cohort (n ⴝ 507)

Age at disease onset, mean ⴞ SD, y

33 ⫾ 9

Age at study entry, mean ⴞ SD, y

43 ⫾ 10

Disease duration, median (IQR), y

6 (⬍1 to 37)

Female, no. (%)

344 (68)

Clinical subtype, no. (%)

Emotional Well-Being. In the univariate analyses (not

CIS

82 (16)

RRMS

358 (71)

SPMS

48 (9)

PPMS or PRMS

19 (4)

EDSS, median (IQR)

1.5 (0 to 6.5)

MSFC Z score, median (IQR)

0.2 (⫺2.7 to 1.1)

PASAT

0.3 (⫺3.7 to 1.2)

Nine-hole peg test

0.1 (⫺2.5 to 1.9) ⫺0.2 (⫺0.6 to 7.4)

Timed 25-ft walk No. (%) on disease-modifying therapy

289 (57)

IQR ⫽ interquartile range; CIS ⫽ clinically isolated syndrome; RRMS ⫽ relapsing–remitting multiple sclerosis; SPMS ⫽ secondary progressive multiple sclerosis; PPMS ⫽ primary progressive multiple sclerosis; PRMS ⫽ progressive relapsing multiple sclerosis; EDSS ⫽ Expanded Disability Status Scale; MSFC ⫽ Multiple Sclerosis Functional Composite; PASAT ⫽ Paced Auditory Serial Addition Test.

dently predicted HRQOL.16,17 Disability and disease subtype appeared to be mediators (part of the causal pathway between the MRI predictor and the outcome) rather than confounders and were therefore not included in the final multivariate models because to do so would represent overadjustment for the particular research question. Mediation was assessed using the technique recommended by Vittinghoff et al.18

Five hundred seven patients whose characteristics are presented in table 1 were enrolled in the study. The majority had relapsing–remitting MS (n ⫽ 358 patients; 71%) or CIS (n ⫽ 82; 16%). Most patients reported difficulties with both emotional well-being and thinking and fatigue. The mean (⫾SD) score for the Emotional Well-Being subscale was 22.5 ⫾ 4.9 points; for the Thinking/ Fatigue subscale, it was 23.5 ⫾ 8.6 points. The unRESULTS

Table 2

MRI characteristics of cohort (baseline) Mean ⴞ SD

Parameter (baseline)

Median (interquartile range)

Normalized gray matter volume, mL

975 ⫾ 74

981 (750–1,130)

Normalized white matter volume, mL

607 ⫾ 44

608 (503–719)

Normalized brain parenchymal volume, mL Normalized T1 lesion volume, mL Ratio of normalized T1 lesion volume to normalized white matter volume

1,589 ⫾ 88 7 ⫾ 11 0.011 ⫾ 0.020

1,601 (1,345–1,785) 3 (0.05–66) 0.005 (0.00008–0.09464)

T2 lesion load, mL

8 ⫾ 13

3 (0.003–71)

T1 lesion load, mL

4⫾8

2 (0.04–43)

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transformed distribution of responses to the questions is presented in table e-1 on the Neurology® Web site at www.neurology.org. The descriptive statistics for brain MRI parameters are presented in table 2. Five hundred one of the 507 enrolled patients had a gadolinium-enhanced scan performed; 81 (16%) had at least one enhancing lesion. shown), worse scores for Emotional Well-Being were associated with higher T2 and T1 lesion load as well as with nT1LV and nT1LV/nWMV ratio. On the other hand, substantially better scores for Emotional WellBeing were predicted by larger nGMV, nBPV, and nWMV. The results of the multivariate analyses are shown in table 3. Higher nGMV was correlated with higher scores for Emotional Well-Being; clinically important differences (0.97 points) in this HRQOL subscale were associated with a 118-mL difference in nGMV. There was a trend for higher nBPV to correlate with higher HRQOL scores. There did not appear to be an association of nWMV and Emotional Well-Being, although the confidence intervals are wide enough that a relationship cannot be completely excluded. Differences in T1 and T2 lesion volumes were associated with clinically meaningful differences in selfreported Emotional Well-Being in the multivariate models (table 4). A 15 mL greater T1 lesion load, a 20 mL greater nT1LV, or a 25 mL greater T2 lesion load corresponded to a clinically meaningful reduction in this aspect of HRQOL. The presence of one or more contrast-enhancing lesions did not seem to be associated with this subscale score (0.23 points; 95% CI ⫺0.94, 1.41; p ⫽ 0.70). DMT was not independently associated with the outcome in any of the models. Thinking/Fatigue. In the univariate analyses (not

shown), larger nGMV, nWMV, or nBPV was associated with substantially better Thinking/Fatigue scores. Conversely, higher T2 and T1 lesion load, nT1LV, and nT1LV/nWMV ratio were associated with worse scores for this subscale. In the multivariate models, higher nBPV, nGMV, and nWMV were strongly related to better Thinking/Fatigue scores; volumes associated with a meaningful difference ranged from 85 mL (nWMV) to 98 mL (nBPV). Because the role of disease subtype as a mediator in the nGMV and Thinking/Fatigue model was weaker, we added it to the multivariate model but found no substantive changes compared with when it was not in the model (a 93-mL difference in nGMV predicted a meaningful difference in Thinking/Fatigue; 95% CI 0.44, 2.81; p ⫽ 0.007). As seen for Emotional Well-Being, small differences in lesion volume were associated with worse scores for

Table 3

Results of multivariate analyses for MRI predictors of Emotional Well-Being

Predictor

MRI difference (mL) associated with a 0.97-point increase in EWB

nGMV

118

0.06, 1.89

nWMV

223

⫺1.31, 3.25

0.40

177

⫺0.10, 2.04

0.076

MRI difference (mL) associated with a 0.97-point decrease in EWB

95% CI for 0.97-point decrease in EWB

p Value

⫺1.76, ⫺0.18

0.016

⫺1.78, ⫺0.16

0.020

nBPV

Normalized T1 lesion volume

20

Normalized T1 lesion volume to normalized white matter volume ratio

0.04

95% CI for 0.97-point increase in EWB

p Value 0.037

T2 lesion load

25

⫺1.83, ⫺0.11

0.028

T1 lesion load

15

⫺1.81, ⫺0.13

0.024

Each row represents one of the multivariate analyses in which the primary predictor was the MRI measure noted in the first column; covariates included age at onset, sex, and disease-modifying therapy. Each MRI parameter was rescaled after determining the amount of change in that predictor associated with a 0.97-point difference in the Emotional Well-Being (EWB) outcome. The rescaled predictor was then used as the primary predictor so that the 95% confidence intervals (CIs) surrounding these point estimates could be obtained. nBPV ⫽ normalized brain parenchymal volume; nGMV ⫽ normalized gray matter volume; nWMV ⫽ normalized white matter volume.

Thinking/Fatigue. A 21-mL (nT1LV) to 22-mL (T2 lesion load) greater lesion burden correlated with a clinically meaningful decrement in Thinking/Fatigue. The association between the subscale score and T1 lesion load was somewhat attenuated, and the presence of a contrast-enhancing lesion was not associated with this subscale (0.02 points; 95% CI ⫺2.04, 2.07; p ⫽ 0.99). DMT was not independently associated with the outcome in any of the models. DISCUSSION Fatigue and reductions in emotional and cognitive health are common in patients with MS, contributing substantially to the impact of the disease on daily life. In a well-characterized, singlecenter cohort of subjects with relatively little disabil-

Table 4

ity, we demonstrate that patients’ perceptions of how MS impacts these aspects of health correlate with both MRI lesion burden and brain volume, in particular gray matter volume. These associations persisted independent of treatment status, an important finding because DMTs by themselves have been shown in some studies to influence HRQOL.16,17 Brain atrophy in MS is thought to be caused both by direct axonal damage associated with lesion development and tissue loss accruing independently of new lesion development. Atrophy, particularly of the gray matter, begins early in the course of the disease, when changes in the clinical examination, except as related to relapses, may be less apparent.4,7,19,20 Neuroaxonal loss,

Results of multivariate analyses for MRI predictors of Thinking/Fatigue

Predictor

MRI difference (mL) associated with a 1.73-point increase in TF

nGMV

87

0.56, 2.90

0.004

nWMV

85

0.22, 3.24

0.025

nBPV

98

0.70, 2.76

0.001

Normalized T1 lesion volume Normalized T1 lesion volume to normalized white matter volume ratio

95% CI for 1.73-point increase in TF

p Value

MRI difference (mL) associated with a 1.73- point decrease in TF

95% CI for 1.73-point decrease in TF

p Value

21

⫺3.23, ⫺0.23

0.024

⫺3.34, ⫺0.12

0.036

0.04

T2 lesion load

22

⫺3.05, ⫺0.41

0.010

T1 lesion load

19

⫺3.58, 0.12

0.066

Each row represents one of the multivariate analyses in which the primary predictor was the MRI measure noted in the first column; covariates included age at onset, sex, and disease-modifying therapy. Each MRI parameter was rescaled after determining the amount of change in that predictor associated with a 1.73-point difference in the Thinking/Fatigue (TF) outcome. The rescaled predictor was then used as the primary predictor so that the 95% confidence intervals (CIs) surrounding these point estimates could be obtained. nBPV ⫽ normalized brain parenchymal volume; nGMV ⫽ normalized gray matter volume; nWMV ⫽ normalized white matter volume. Neurology 72

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a major contributor to atrophy, is thought to underlie the long-term development of disability in patients with MS. Neuroaxonal loss seems to have a more prominent effect on gray matter than on white matter volume, because reductions in gray matter volume are prominent early in the disease course and increase as the duration of the disease increases, whereas the rate of white matter atrophy is much lower and relatively constant.19,21 Reduced gray matter volume has been shown to be associated with long-term disability.20-23 The strong association of Emotional Well-Being and Thinking/ Fatigue scores and atrophy, particularly with nGMV, together with the strong association of atrophy and neuroaxonal loss, implies that neuro-axonal loss may be a contributor to reduced HRQOL in MS. HRQOL outcomes may therefore represent clinical correlates of this disease process. These observations strengthen the rationale for incorporating HRQOL instruments into MS clinical trials, particularly of those in which the prevention of disability with putative neuroprotective agents is the primary outcome measure. In addition to being associated with atrophy, Emotional Well-Being and Thinking/Fatigue scores correlated with lesion load/volume; smaller differences in lesion volume than in parenchymal volume correlated with a meaningful difference in the HRQOL outcomes. These findings are important because they suggest that even the lesion burden as assessed on standard clinical MRI may have an important impact on patients’ well-being. Furthermore, there is some indication that lesion burden is also associated with disability.22 Other studies have evaluated the association of patient-reported fatigue outcomes and MRI features in MS.24-30 Fatigue was not associated with brain parenchymal fraction in a cross-sectional analysis of 134 patients but was associated longitudinally.30 Another study showed that some aspects of HRQOL could be predicted by lesions or atrophy in specific anatomic locations in the brain.27 Fatigue in MS and in other chronic conditions in which it plays a prominent role, such as chronic fatigue syndrome, has been shown to have imaging correlates on functional MRI,31-33 and in a small study of chronic fatigue syndrome, affected patients had less gray matter volume than healthy controls.34 Although consistent with these previous reports, the present study demonstrates stronger associations between global MRI measures of disease burden and HRQOL. Reduced cognition, as measured by neuropsychological batteries, has been shown to strongly correlate with brain atrophy35 and lesion burden36; some studies have shown that the correlation of cognition is stronger with the former than with the latter.37,38 The results of these previous studies support our findings that 1764

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self-reported cognitive dysfunction is strongly associated with brain atrophy. Despite the large size of this cohort, our work has some limitations. The original study was not designed to evaluate overall HRQOL as a primary outcome measure. As such, some aspects of HRQOL, particularly those capturing physical and social well-being, were not evaluated in this cohort and need to be explored in future studies. Furthermore, because estimates of clinically important differences in the Emotional WellBeing and Thinking/Fatigue FAMS subscales are not available in the literature, we used standardized effect size benchmarks to estimate the minimal clinically important difference. Although there is good rationale for such an approach, the responsiveness of these FAMS subscales needs to be studied longitudinally. In addition, we cannot conclude that the association between HRQOL measures and nGMV is solely related to atrophy, because lesions in the cortical gray matter are difficult to detect on MRI. A longitudinal analysis in our cohort is currently under way. In addition to assessing the long-term correlation between HRQOL and radiographic burden of disease, we will also determine whether these HRQOL subscales predict subsequent brain atrophy and disability. In one study, early accumulation of fatigue was a better predictor of longer-term reductions in brain atrophy than the MSFC.37 Moreover, two small reports have suggested that some aspects of HRQOL are weakly associated with subsequent decline in physical function.39,40 Therefore, further evaluation of HRQOL as a predictor of MS outcomes should be pursued. If such predictive value can be established, patientreported HRQOL may gain a more prominent role not only in the research arena, but also in the clinical care of patients with MS. AUTHOR CONTRIBUTIONS Statistical analyses were performed by E.M. Mowry.

ACKNOWLEDGMENT The authors thank Dr. Patricia Katz for her constructive advice and the patients who generously agreed to serve as study participants.

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study of multiple sclerosis patients. Mult Scler 2000;6: 373–377. van der Werf SP, Jongen PJ, Lycklama a Nijeholt GJ, et al. Fatigue in multiple sclerosis: interrelations between fatigue complaints, cerebral MRI abnormalities and neurological disability. J Neurol Sci 1998;160:164–170. Mainero C, Faroni J, Gasperini C, et al. Fatigue and magnetic resonance imaging activity in multiple sclerosis. J Neurol 1999;246:454–458. Bakshi R, Miletich RS, Henschel K, et al. Fatigue in multiple sclerosis: cross-sectional correlation with brain MRI findings in 71 patients. Neurology 1999;53:1151–1153. Janardhan V, Bakshi R. Quality of life and its relationship to brain lesions and atrophy on magnetic resonance images in 60 patients with multiple sclerosis. Arch Neurol 2000; 57:1485–1491. Codella M, Rocca MA, Colombo B, Martinelli-Boneschi F, Comi G, Filippi M. Cerebral grey matter pathology and fatigue in patients with multiple sclerosis: a preliminary study. J Neurol Sci 2002;194:71–74. Codella M, Rocca MA, Colombo B, Rossi P, Comi G, Filippi M. A preliminary study of magnetization transfer and diffusion tensor MRI of multiple sclerosis patients with fatigue. J Neurol 2002;249:535–537. Marrie RA, Fisher E, Miller DM, Lee JC, Rudick RA. Association of fatigue and brain atrophy in multiple sclerosis. J Neurol Sci 2005;228:161–166. Filippi M, Rocca MA, Colombo B, et al. Functional magnetic resonance imaging correlates of fatigue in multiple sclerosis. Neuroimage 2002;15:559–567. Cook DB, O’Connor PJ, Lange G, Steffener J. Functional neuroimaging correlates of mental fatigue induced by cognition among chronic fatigue syndrome patients and controls. Neuroimage 2007;36:108–122. Rocca MA, Agosta F, Colombo B, et al. fMRI changes in relapsing-remitting multiple sclerosis patients complaining of fatigue after IFN␤-1A injection. Hum Brain Mapp 2007;28:373–382. de Lange FP, Kalkman JS, Bleijenberg G, Hagoort P, van der Meer JW, Toni I. Gray matter volume reduction in the chronic fatigue syndrome. Neuroimage 2005;26:777–781. Christodoulou C, Krupp LB, Liang Z, et al. Cognitive performance and MR markers of cerebral injury in cognitively impaired MS patients. Neurology 2003;60:1793–1798. Rovaris M, Filippi M, Falautano M, et al. Relation between MR abnormalities and patterns of cognitive impairment in multiple sclerosis. Neurology 1998;50:1601–1608. Benedict RH, Weinstock-Guttman B, Fishman I, Sharma J, Tjoa CW, Bakshi R. Prediction of neuropsychological impairment in multiple sclerosis: comparison of conventional magnetic resonance imaging measures of atrophy and lesion burden. Arch Neurol 2004;61:226–230. Zivadinov R, Sepcic J, Nasuelli D, et al. A longitudinal study of brain atrophy and cognitive disturbances in the early phase of relapsing-remitting multiple sclerosis. J Neurol Neurosurg Psychiatry 2001;70:773–780. Visschedijk MA, Uitdehaag BM, Klein M, et al. Value of health-related quality of life to predict disability course in multiple sclerosis. Neurology 2004;63:2046–2050. Nortvedt MW, Riise T, Myhr KM, Nyland HI. Quality of life as predictor for change in disability in MS. Neurology 2000;55:51–54.

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Deficient intracortical inhibition (SICI) during movement preparation after chronic stroke F.C. Hummel, MD B. Steven, MSc J. Hoppe, MD K. Heise, MSc G. Thomalla, MD L.G. Cohen, MD C. Gerloff, MD

Address correspondence and reprint requests to Dr. Friedhelm C. Hummel, Department of Neurology, University Medical Center Hamburg-Eppendorf, 20246 Hamburg, Germany [email protected]

ABSTRACT

Background: In healthy subjects, preparation to move is accompanied by motor cortical disinhibition. Poor control of intracortical inhibitory function in the primary motor cortex (M1) might contribute to persistent abnormal motor behavior in the paretic hand after chronic stroke.

Methods: Here, we studied GABAergic short intracortical inhibition (SICI) in the ipsilesional M1 in well-recovered chronic stroke patients (n ⫽ 14; 63.8 ⫾ 3.0 years) engaged in preparation to move the impaired hand in a reaction time paradigm.

Results: The main finding was an abnormal persistence of SICI in the ipsilesional M1 during movement preparation that was absent in age-matched controls (n ⫽ 14). Additionally, resting SICI was reduced in the patient group relative to controls. Conclusions: Our findings document a deficit of dynamic premovement modulation of intracortical inhibition in the ipsilesional primary motor cortex of patients with chronic stroke. This abnormality might contribute to deficits in motor control of the paretic hand, presenting a possible target for correction in the framework of developing novel therapeutic interventions after chronic stroke. Neurology® 2009;72:1766–1772 GLOSSARY CS ⫽ conditioning magnetic stimulus; FDI ⫽ first digital interosseus muscle; ISI ⫽ interstimulus interval; JTT ⫽ Jebsen-Taylor Hand Function Test; M1 ⫽ primary motor cortex; MEP ⫽ motor evoked potential; RC ⫽ recruitment curves; RM-ANOVA ⫽ repeated measures analyses of variance; rMT ⫽ resting motor threshold; RT ⫽ reaction time; SICI ⫽ short interval intracortical inhibition; TMS ⫽ transcranial magnetic stimulation; US ⫽ unconditioned stimulus.

Ischemic stroke results in motor impairment and changes in inhibitory and excitatory intracortical function.1-3 Interactions between intracortical inhibitory and excitatory processes within the primary motor cortex (M1) are crucial for motor control and change in the process of generation of a voluntary movement (at the immediate premovement stage).4-11 GABAergically mediated short intracortical inhibition (SICI) can be studied using a wellestablished paired pulse transcranial magnetic stimulation (TMS) method.12 Previous work demonstrated premovement modulation of SICI, characterized by a release from inhibition (disinhibition) prior to the onset of a voluntary movement in healthy subjects.7-9 The ability to evaluate SICI in association with performance of a voluntary movement added another perspective to our understanding of intracortical inhibitory circuits and, in fact, seems to enhance the specificity of this technique for some pathologic states of the central motor system. For example, in patients with dystonia, premovement SICI and SICI at rest showed substantially different effects with reduction in SICI at rest and persistent lack of modulation of SICI during movement preparation.7

From the Brain Imaging and Neurostimulation Laboratory (F.C.H., B.S., J.H., K.H., G.T., C.G.), Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany; and Human Cortical Physiology and Stroke Neurorehabilitation Section (F.C.H., L.G.C.), National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD. Supported by a grant from the Alexander von Humboldt Foundation (Feodor-Lynen) to F.H., by the Deutsche Forschungsgemeinschaft (SFB 550 A13 to F.H.), by the FFM of the University of Hamburg (NWF04/07 to F.H.), and by the intramural National Institute of Neurological Disorders and Stroke program, NIH. Disclosure: The authors report no disclosures. Medical Device: Magstim 200 magnetic stimulator (Magstim Company, Whitland, Dyfed, UK). 1766

Copyright © 2009 by AAN Enterprises, Inc.

Figure 1

Experimental design

Short interval intracortical inhibition was determined at (A) rest and (B) at four different timings prior to movement onset (T1–T4, T4 being closest to movement onset). Timings were adjusted to the individual reaction times. Mean reaction times were 208.5 msec (⫾8.3 msec) for stroke patients and 216.9 msec (⫾9.5 msec) for controls. MEP ⫽ motor evoked potential; TMS ⫽ transcranial magnetic stimulation.

Previous studies evaluating motor cortex excitability in the acute and subacute stages after stroke1,3,13-18 showed decreased resting SICI in the ipsilesional M1, an abnormality that may normalize in the chronic stage.15,17-19 Movement-related changes in SICI in stroke patients intending to move the paretic hand have not been investigated. Here, we hypothesized that dynamic modulation of premovement SICI, as described in healthy subjects,7-9 would be impaired in the ipsilesional M1 of chronic stroke patients moving the paretic hand. METHODS Subjects. Fourteen right-handed chronic stroke patients (mean age 63.8 ⫾ 3.0, seven women, eight left hemispheric strokes) with a history of a single subcortical ischemic cerebral infarct not involving M1 at least 1 year before the study with good recovery of hand function that allowed them to perform the required motor task were recruited for the study. However, the patients still showed deficits in performance of skilled motor tasks such as the Jebsen-Taylor Hand Function Test (JTT; see Results section20). Upper extremity Fugl-Meyer scores ranged between 54 and 65 points (maximum 66), Medical Research Council between 4.2 and 5, and the Ashworth Spasticity Scale between 0 and 2. Fourteen healthy right-handed age-matched volunteers (mean age 63.9 ⫾ 2.7, nine women) participated as controls. Written informed consent was obtained from all subjects according to the Declaration of Helsinki21 and from the local Ethics Committee at NIH and Hamburg.

Experimental design. Initially, subjects familiarized with the reaction time (RT) task. They performed 20 trials to characterize

each individual’s RT in the absence of TMS. Subsequently, we characterized resting motor thresholds (rMT)22 in each individual as required to determine the settings for TMS stimulation. Then the subjects performed the RT task while paired- and single-pulse TMS was applied. At the end of the experimental session, recruitment curves and SICI were investigated at rest (for details, see below).

Transcranial magnetic stimulation. A paired-pulse paradigm was used to assess intracortical inhibition at rest and in the process of the generation of a voluntary movement.7,8,12 In the standard paired pulse paradigm, a subthreshold conditioning stimulus (CS) is followed by a suprathreshold unconditioned stimulus (US). Short interval intracortical inhibition (SICI) takes place at interstimulus intervals (ISIs) of 1– 6 msec and reflects the activation of local GABAergic connections.22-25 In our study, SICI was investigated at an ISI of 3 msec based on previous studies.4,22,24 The CS and the US were delivered through a figure-of-eight coil (80 mm wing diameter) connected to two Magstim 200 magnetic stimulators (Magstim Company, Whitland, Dyfed, UK). The coil was placed over the hand motor area of the ipsilesional hemisphere with the handle pointing backwards and laterally approximately 45° to the interhemispheric line. The CS intensity was 80% rMT, a standardized value used in previous reports with a good relation to SICI thresholds,7,22,24,26 which allowed proper comparison of SICI across patient and control groups. Unconditioned TMS pulses were applied at an intensity that evoked unconditioned MEPs of ⬃1 mV in both patients and controls. All measurements were evaluated in the ipsilesional M1 of the stroke patients and the corresponding M1 of agematched controls. The optimal scalp position for eliciting MEPs in the first dorsal interosseous (FDI) muscle of the paretic hand (patients) and corresponding hand (controls) was determined and the position was marked with a pen. Rest measurements. Motor threshold (rMT) was defined as the minimal output of the stimulator that produced MEPs of ⬎50 ␮V in at least 5 out of 10 consecutive trials (figure 1A). Recruitment curves (RC) to systematically increasing TMS stimuli (100%–150% of rMT) and SICI were also measured at rest. Premovement measurements. Paired pulses (US and CSUS) were delivered at different time intervals preceding movement onset in a reaction time paradigm in pseudo-randomized order at four different timings (T1–T4) (figure 1B). T1–T4 were adjusted to each subject’s RT according to a well-described procedure,27,28 and ranged between 125 and 240 msec after the go signal (corresponding to an average T1 ⫽ 63% of RT, T2 ⫽ 75%, T3 ⫽ 87%, T4 ⫽ 97%). A minimum of 10 trials per condition and timing were recorded (13.4 ⫾ 0.6 trials). EMG recording. EMG activity was recorded from the FDI muscle of the paretic hand using surface electrodes positioned in a belly-tendon montage. The amplified and bandpass filtered (50 Hz–1 kHz) EMG signals were digitized and stored on a laptop using a data collection program (CED 1902 amplifier, sampling rate 5 kHz, bandpass filter 50 Hz–1 kHz, Signal Software, Cambridge Electronic Devices, Cambridge, UK). All data were analyzed off-line. Simple reaction time task. Subjects were instructed to respond to a visual go signal by performing an index finger abduction motion of the paretic hand as quickly as possible. The go signal appeared at random intervals (6 – 8 seconds) and the subjects were instructed to avoid anticipation of the go signal and to relax their hand while the fixation point was present. RT was Neurology 72

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Figure 2

Short interval intracortical inhibition (SICI) during rest

RESULTS Reaction times. RT were comparable in the two groups (216.9 msec ⫾ 9.5 msec healthy elderly, 208.5 msec ⫾ 8.3 msec stroke patients; t[26] ⫽ 0.67, p ⫽ 0.50), consistent with the patient inclusion criteria (patients with substantial initial paralysis but subsequent recovery to the level they were able to carry out the required RT task).

Jebsen-Taylor hand function test. JTT values in the

Stroke patients in black, age-matched controls in white. Note the difference between patients and controls, with reduced SICI in patients. The y-axis displays SICI in percentage of the unconditioned motor evoked potential (MEP) amplitude; thus values below 100% correspond to inhibition and values above 100% correspond to facilitation. Asterisk indicates p ⬍ 0.05.

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patients (37.4 ⫾ 2.8 seconds, n ⫽ 11) were higher than in controls (27.4 ⫾ 1.6 seconds; t ⫽ 3.1, n ⫽ 5; p ⫽ 0.008). JTT values in patients were also higher relative to a second healthy control group from our laboratory (29.2 ⫾ 1.4 seconds, t ⫽ 2.6, n ⫽ 10; p ⫽ 0.02). Resting motor thresholds. Stroke patients and con-

defined as the time interval (in milliseconds) between the go signal and the onset of the EMG-burst in the FDI muscle.

trols had comparable rMTs (42 ⫾ 3% stroke patients, 46 ⫾ 2% healthy elderly, t[26] ⫽ 1.232, p ⫽ 0.23).

Data analysis. Premovement measurements. All trials with

Recruitment curves. No difference in RC was ob-

EMG activity on visual inspection before TMS were discarded from further analysis. In each subject, MEP amplitudes, measured peak to peak, were sorted according to stimulation condition (SICI, single pulse) and premovement timing (T1–T4). The unconditioned MEP amplitudes at T1–T4 were measured separately to quantify overall corticomotor excitability changes in the premovement period. SICI was expressed as the percentage of the mean MEP amplitude induced by unconditioned magnetic pulses obtained at that particular timing. In this way, differences in SICI could not be attributed to changes in the unconditioned MEP amplitude. The analysis of data acquired during rest was carried out using the same procedures. All results are given as mean ⫾ SE. Statistical analysis was performed using Statistical Package for the Social Sciences (SPSS) software (SPSS Inc., Chicago, IL). In line with our a priori hypothesis of a difference in SICI between the two groups (stroke patients, controls) closest to movement onset,7,27,28 unpaired two-samples t test (two-tailed) at the closest premovement timing (T4) was used first to compare the two groups. Additionally, we evaluated the changes of the premovement SICI across the two groups using a repeated measures analyses of variance (RM-ANOVA) with premovement timing(timing 1– 4) as a within-subjects factor and group(stroke patients, healthy elderly) as a between-subjects factor. We also expressed the magnitude of SICI at T4 relative to T1 (normalized extent of modulation ⫽ SICI at T4/SICI at T1 ⫻ 100%) to better characterize changes in SICI relative to movement onset. We also calculated a RM-ANOVA for unconditioned MEP amplitudes (same within- and between-subject factors as mentioned above) to ensure that our results could not solely be attributed to a between-group difference in development of amplitude changes in unconditioned MEP amplitude at T1–T4. Measurements during rest. Resting SICI was evaluated using unpaired two-sample t tests (two-tailed). RC were analyzed using RM-ANOVA with the factors group(stroke patients, healthy elderly) and intensity(100 –150% MT). RM-ANOVA was Greenhouse-Geisser corrected if necessary. rMT and RT of the stroke patients and controls were compared with unpaired two-samples t tests (two-tailed).

served in the stroke patients compared to controls. RM-ANOVA showed an effect of intensity (F ⫽ 32.5, p ⬍ 0.05), but not group (F ⫽ 1.40, p ⫽ 0.25) or group(stroke patients, healthy elderly) ⫻ intensity(100%–150% MT) interaction (F ⫽ 0.58, p ⫽ 0.52).

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SICI and unconditioned MEP amplitudes at rest. SICI

at rest was reduced in the ipsilesional M1 of the stroke patients (78.2 ⫾ 9.7) compared to controls (49.3 ⫾ 6.0; t[26] ⫽ 2.54, p ⬍ 0.05; figure 2) in the absence of differences in US MEP amplitudes (0.71 mV ⫾ 0.17 mV stroke patients and 0.83 mV ⫾ 0.22 mV controls, t[26] ⫽ ⫺0.41, p ⫽ 0.7). There was no significant correlation between SICI at rest and JTT or RT values. Premovement unconditioned MEP amplitude. As ex-

pected, there was an effect of timing(timing 1– 4) (F ⫽ 5.12, p ⬍ 0.05) but not group(stroke patients, healthy elderly) (F ⫽ 0.14, p ⫽ 0.71) or timing (timing 1– 4) ⫻ group(stroke, healthy elderly) interaction (F ⫽ 1.23, p ⫽ 0.28) on US MEP amplitude. A two-sample t test showed no difference in US MEP amplitudes at timing 4 (T4) between patients (2.39 mV ⫾ 0.47) and controls (2.14 mV ⫾ 0.38; t[26] ⫽ 0.41, p ⫽ 0.7), consistent with a progressive increase in corticospinal recruitment preceding movement onset comparable in patients and controls (figure 3). Premovement SICI. Both groups showed comparable

SICI in the early phase of movement preparation, which remained stable and unmodulated in patients and changed to facilitation in controls close to movement onset (figure 4). This group difference was sig-

Figure 3

Unconditioned stimulus amplitudes in preparation of movements as measured at timings T1–T4 before movement onset

The x-axis displays the timing of the application of the transcranial magnetic stimulation pulses (T1–T4; T4 is closest to movement onset). The y-axis displays motor evoked potential amplitudes in mV. Note that unconditioned stimulus amplitudes were comparable in both groups.

nificant at T4 (paired t test T1 vs T4: t[13] ⫽ ⫺2.26, p ⬍ 0.05; figure 4, A and B). A two-sample t test yielded a difference of SICI between groups at T4 (t[26] ⫽ ⫺2.23, p ⬍ 0.05). RM-ANOVA revealed an effect of group(stroke patients, healthy elderly) (F ⫽ 4.46, p ⬍ 0.05) and timing(timing 1– 4) ⫻ group(stroke, healthy elderly) interaction (F ⫽ 3.19, p ⬍ 0.05) on premovement SICI. The premovement modulation of SICI (at T4 relative to T1) also differed across groups (figure 4C; t[26] ⫽ ⫺2.13, p ⬍ 0.05). The factor timing(timing 1– 4) (F ⫽ 1.73, p ⫽ 0.19) did not show effects on SICI. There were no significant correlations between SICI modulation and JTT or RT performance. We studied eight patients with a left and six with a right hemisphere stroke. RM-ANOVA did not show significant effects of timing(timing 1-4) (F ⫽ 1.44, p ⫽ 0.25), HEM(right vs left) (F ⫽ 1.08, p ⫽ 0.32), or the interaction term (F ⫽ 1.99, p ⫽ 0.15) on SICI. Correlation between SICI at rest and modulation of premovement SICI. There was no significant correla-

tion between the single pulse amplitude at rest and the magnitude of modulation of the single pulse amplitude (R ⫽ 0.15; p ⫽ 0.63), the rMT and SICI levels at rest (R ⫽ ⫺0.23, p ⫽ 0.43), or rMT and SICI modulation (R ⫽ ⫺0.15; p ⫽ 0.62) in patients. There was a correlation in this group between the amount of SICI at rest and the magnitude of modulation of SICI (R ⫽ ⫺0.37, p ⫽ 0.03, one-tailed; the larger SICI at rest [less inhibition], the smaller the modulation). DISCUSSION The main finding of this study was a twofold abnormality of GABAergically mediated SICI in the ipsilesional M1 in a group of wellrecovered chronic stroke patients.4,29,30 SICI was re-

duced at rest and abnormally persistent during paretic hand movement preparation relative to healthy age-matched controls without adequate modulation close to movement onset. All patients who took part in the study showed an initial paralysis followed by substantial motor recovery. They were all able to perform the required task and generated clear, recordable muscle bursts from the paretic FDI muscle in response to the go signals in the reaction time task. Of note is that reaction times were comparable between patients and controls although the patients still had clear functional deficits particularly obvious during performance of more complex motor tasks, such as, e.g., the JTT (stroke patients: JTT ⫽ 37.4 ⫾ 2.8 seconds, vs controls: JTT ⫽ 27.4 ⫾ 1.6 seconds). Disinhibition of the ipsilesional M1 at rest has been reported in the acute and subacute stages after ischemic stroke.1,13,14 We now found that this abnormality may persist into the chronic stage of the disease in patients with good recovery when compared to healthy age-matched controls. A recent report showed no differences in resting SICI in the healthy and affected hemisphere in patients 2 to 96 months after stroke but patients’ results in that study were not compared to age-matched controls.16 The mechanisms underlying these findings are not clear. Recent animal data also showed changes in cortical excitability after small cortical lesions associated with functional recovery. In humans, enhanced resting motor cortical excitability (or reduced inhibition) has been proposed as a possible contributing mechanism18 to the recovery process,14,31 possibly influenced by interactions with secondary motor areas, such as the premotor cortex or the supplementary motor area32,33 or even with homologous areas of the opposite hemisphere.27,28 Because motor deficits in patients are most pronounced while performing a motor task, we hypothesized that abnormalities in intracortical function might manifest themselves more prominently in the premovement period, when patients intend to move the paretic hand. In healthy subjects, SICI decreases and turns into facilitation during voluntary movements, a mechanism thought to facilitate activation of focal motor regions engaged in task performance and adequate fractionation of muscle activity.4,7,8,34 This modulation warrants accurate motor performance. In the patient group, we found an abnormal persistence of SICI in ipsilesional M1 in the period immediately preceding a movement of the paretic hand relative to controls, who demonstrated facilitation. So far there is not sufficient experimental evidence to determine whether disturbed SICI modulaNeurology 72

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Figure 4

SICI in preparation of movements as measured at timings T1–T4 before movement onset

(A) Short interval intracortical inhibition (SICI) in preparation of movements as measured at four timings (T1–T4) before movement onset (mean ⫾ SEM; T4 is closest to movement onset). Mean reaction times were comparable for stroke patients and for controls. Stroke patients are shown with the black line, controls with the dotted line. The x-axis displays the timing of the application of the transcranial magnetic stimulation (TMS) pulses (T1–T4); the y-axis displays SICI in percentage of the unconditioned motor evoked potential (MEP) amplitude; thus values below 100% correspond to inhibition and values above 100% correspond to facilitation. *p ⬍ 0.05. (B) Examples of the raw data from one control subject (I) and one stroke patient (II) at timings 1– 4 (T1–T4) in the premovement period. MEPs evoked by single pulses (SP) and by paired pulses with an interstimulus interval of 3 msec (SICI) are shown. Note the increase of MEP size from T1 to T4 in the healthy subject which is lacking in the stroke patient (black dotted frame). (C) SICI modulation. Normalized extent of modulation of SICI is shown at timing T4 in percentage of T1 (T1 ⫽ 100%) for each subject. Gray squares ⫽ stroke patients; black circles ⫽ age-matched controls. *p ⬍ 0.05. SICI ⫽ short interval intracortical inhibition.

tion during movement preparation after stroke represents an adaptive or maladaptive response. However, in healthy subjects physiologic modulation of motor cortical excitability before and during movement has been well characterized and linked to normal motor behavior.7,8 In contrast, abnormal modulation of motor cortical excitability has been linked with abnormal motor function in movement disorders like dystonia and in stroke.7,28 Persistence of SICI is the key feature of abnormal modulation.7 Therefore, we consider it unlikely that the present findings during movement preparation represent adaptation rather than a persisting abnormality. At rest, however, patients showed disinhibition. It is possible that disinhibition at rest in the chronic stage 1770

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might contribute to a reduction in the range of operational premovement modulation available when moving the paretic hand. Furthermore, it is possible that after stroke the ipsilesional M1 attempts to compensate for its inability to generate proper voluntary movement by increasing resting motor cortical excitability. The novel finding of SICI abnormalities after chronic stroke reported in this study may contribute to the understanding of the effects of interventions that modulate the excitability of the ipsilesional M1 in stroke patients.35-39 For example, enhancing the excitability of the ipsilesional M1 by noninvasive cortical stimulation is associated with improved skilled motor functions of the paretic hand.36 In addition, enhanced motor cortical excitability (determined at rest) is corre-

lated with the amount of behavioral improvement.36 Based on the present data it can be speculated that enhancing neuronal activity in the ipsilesional M1, induced by, e.g., cortical stimulation,37 might contribute to normalize SICI (by extending the range of operation for modulation) associated with movements. It remains to be determined if the premovement abnormality reported here with motions of the paretic hand relates in a cause-effect manner with the magnitude of the deficit. From an electrophysiologic point of view, our findings could not be explained by different recruitment of corticomotoneuronal connections in the premovement period since both groups showed comparable modulation and absolute unconditioned MEP amplitudes close to movement onset, nor by differences in rMT or RC, which did not differ across groups. It would be interesting in the future to adjust the intensity of the CS to induce comparable SICI levels at rest, an issue beyond the goals of our investigation focused on the comparison between patients and controls, and to randomize the presentation of stimulus intensities for determination of RC. As we included patients with dominant and nondominant hemispheric lesions, it remains an open question whether there are differences in SICI modulation between these two groups. In the present sample, we did not find differences between patients with lesions in the dominant vs nondominant hemisphere. Finally, it should be kept in mind that our results apply to a subgroup of patients with good motor recovery after predominantly small subcortical lesions. The situation in patients with more severe deficits or extensive cortical-subcortical lesions might differ. The behavioral relevance of the present finding of deficient SICI modulation in patients has to be determined in detail in upcoming studies.

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AUTHOR CONTRIBUTIONS Statistical analysis was performed by B. Steven and F.C. Hummel.

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stimulation: direct recording of epidural activity in conscious humans. J Neurophysiol 2006;96:1765–1771. Hallett M. Transcranial magnetic stimulation and the human brain. Nature 2000;406:147–150. Ziemann U. TMS and drugs. Clin Neurophysiol 2004; 115:1717–1729. Orth M, Snijders AH, Rothwell JC. The variability of intracortical inhibition and facilitation. Clin Neurophysiol 2003;114:2362–2369. Duque J, Hummel F, Celnik P, Murase N, Mazzocchio R, Cohen LG. Transcallosal inhibition in chronic subcortical stroke. Neuroimage 2005;28:940–946. Murase N, Duque J, Mazzocchio R, Cohen LG. Influence of interhemispheric interactions on motor function in chronic stroke. Ann Neurol 2004;55:400–409. Brouwer BJ, Schryburt-Brown K. Hand function and motor cortical output poststroke: are they related? Arch Phys Med Rehabil 2006;87:627–634. Carmichael ST, Tatsukawa K, Katsman D, Tsuyuguchi N, Kornblum HI. Evolution of diaschisis in a focal stroke model. Stroke 2004;35:758–763. Nudo RJ. Recovery after damage to motor cortical areas. Curr Opin Neurobiol 1999;9:740–747. Baumer T, Bock F, Koch G, et al. Magnetic stimulation of human premotor or motor cortex produces interhemi-

spheric facilitation through distinct pathways. J Physiol 2006;572:857–868. 33. Civardi C, Cantello R, Asselman P, Rothwell JC. Transcranial magnetic stimulation can be used to test connections to primary motor areas from frontal and medial cortex in humans. Neuroimage 2001;14:1444–1453. 34. Ridding MC, Pearce SL, Flavel SC. Modulation of intracortical excitability in human hand motor areas: the effect of cutaneous stimulation and its topographical arrangement. Exp Brain Res 2005;163:335–343. 35. Fregni F, Boggio PS, Mansur CG, et al. Transcranial direct current stimulation of the unaffected hemisphere in stroke patients. Neuroreport 2005;16:1551–1555. 36. Hummel F, Celnik P, Giraux P, et al. Effects of noninvasive cortical stimulation on skilled motor function in chronic stroke. Brain 2005;128:490–499. 37. Hummel FC, Cohen LG. Non-invasive brain stimulation: a new strategy to improve neurorehabilitation after stroke? Lancet Neurol 2006;5:708–712. 38. Hummel FC, Voller B, Celnik P, et al. Effects of brain polarization on reaction times and pinch force in chronic stroke. BMC Neurosci 2006;7:73. 39. Takeuchi N, Chuma T, Matsuo Y, Watanabe I, Ikoma K. Repetitive transcranial magnetic stimulation of contralesional primary motor cortex improves hand function after stroke. Stroke 2005;36:2681–2686.

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Differences in retinal vessels support a distinct vasculopathy causing lacunar stroke

F.N. Doubal, MRCP T.J. MacGillivray, PhD P.E. Hokke, MD B. Dhillon, FRCOphth M.S. Dennis, MD J.M. Wardlaw, FRCR

Address correspondence and reprint requests to Fergus N. Doubal, Bramwell Dott Building, Western General Hospital, Crewe Road, Edinburgh EH4 2XU, UK [email protected]

ABSTRACT

Background: Lacunar stroke is common, but the etiology of the small vessel abnormality is unknown. Retinal vessels share ontogeny, size, and physiologic characteristics with cerebral small vessels, and retinopathy is associated with stroke. We compared retinal microvessel appearance as a surrogate for cerebral small vessels in patients with lacunar and large artery cortical ischemic stroke.

Methods: We prospectively recruited patients with lacunar ischemic stroke and cortical stroke controls. We took digital retinal photographs of each eye. We assessed central retinal artery equivalent (CRAE) and central retinal vein equivalent (CRVE) diameters and arteriovenous ratios (AVRs) using semiautomated computer software methods and quantified arteriovenous nicking and focal arteriolar narrowing.

Results: Among 212 patients (105 lacunar, 107 cortical strokes) of mean age 68 years (SD 12 years), AVR was decreased (0.76 vs 0.78, p ⫽ 0.03) and CRVE was increased (44.9 pixels/218 ␮m vs 42.8 pixels/208 ␮m, p ⫽ 0.01) in lacunar patients compared with cortical patients, but CRAE did not differ (33.2 pixels/161 ␮m vs 33.7 pixels/163 ␮m, p ⫽ 0.4). On multivariable analysis, increased CRVE was associated with lacunar stroke subtype (p ⫽ 0.03) and younger age (p ⬍ 0.001) after correcting for other vascular risk factors. Arteriovenous nicking and focal arteriolar narrowing did not differ between ischemic stroke subtypes.

Conclusions: Retinal venules are wider and arteriovenous ratios are smaller in patients with lacunar strokes compared with those in patients with cortical strokes. Neurology® 2009;72:1773–1778 GLOSSARY AVN ⫽ arteriovenous nicking; AVR ⫽ arteriovenous ratio; CI ⫽ confidence interval; CRAE ⫽ central retinal artery equivalent; CRVE ⫽ central retinal vein equivalent; FAN ⫽ focal arteriolar narrowing; FLAIR ⫽ fluid-attenuated inversion recovery; MR ⫽ magnetic resonance; NA ⫽ not applicable; NASCET ⫽ North American Symptomatic Carotid Endarterectomy Trial; NIHSS ⫽ NIH Stroke Scale; OR ⫽ odds ratio.

Twenty-five percent of all ischemic stroke is lacunar,1 but the exact etiology remains unknown.2 Lacunar strokes are caused by disease in a single perforating artery. Large artery atheroma and cardiac embolism, the common causes of most cortical ischemic strokes, probably account for only 15% to 20% of lacunar strokes, suggesting that other mechanisms may be responsible for the majority of lacunar stroke.2 However, visualizing the cerebral small vessel morphologic changes is difficult. Postmortem findings generally reflect late-stage changes and the vessels themselves are too small to visualize in detail using current human imaging methods. Retinal and cerebral small vessels are developmentally related, of similar size, and share physiologic characteristics.3 The retinal vascular bed can be directly visualized noninvasively with retinal photography. Retinal microvascular abnormalities are associated with stroke4,5: retinal vessel widths predict future risk of stroke6-8 and may be associated with a previous Supplemental data at www.neurology.org From the Division of Clinical Neurosciences (F.N.D., P.E.H., M.S.D., J.M.W.), University of Edinburgh; Wellcome Trust Clinical Research Facility (T.J.M.), Western General Hospital, Edinburgh; Princess Alexandra Eye Pavilion (B.D.), University of Edinburgh; and SFC Brain Imaging Research Centre (J.M.W.), University of Edinburgh, UK. F.N.D. is funded by the Wellcome Trust (075611). The Chief Scientists Office (Scotland) funded the brain imaging (CZB-4-281). Disclosure: The authors report no disclosures. Medical Devices: 1.5T Signa Horizon MR/I 1.5T HDX scanner (operating under a research collaboration with GE Medical Systems, Milwaukee, WI, operating as IGE in the UK); digital retinal camera (CR-DGi; Canon USA Inc., Lake Success, NY). Copyright © 2009 by AAN Enterprises, Inc.

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cerebral infarction9,10; arteriovenous nicking (AVN) and focal arteriolar narrowing (FAN) are associated with infarcts on magnetic resonance (MR) brain scanning.9,10 However, although some studies suggest that there are associations between retinal changes and lacunar stroke, there is little information about whether retinal appearances truly differ in ischemic stroke subtypes. This is because these studies either did not subtype ischemic stroke6 or only investigated asymptomatic lacunes seen on MR scanning, which are of uncertain relevance to clinical stroke.4,11,12 Therefore, we studied retinal arteriolar and venular widths, FAN, and AVN in patients presenting with acute lacunar and cortical ischemic stroke to test the hypothesis that the retinal small vessels would be morphologically different in patients with lacunar stroke compared with patients with large artery cortical atherothromboembolic stroke. We prospectively recruited consecutive patients with clinical lacunar or mild cortical stroke seen at our hospital stroke service, aiming to recruit all relevant patients as consecutively as possible. We used patients with cortical stroke as controls to identify any findings specific to lacunar stroke. Normal agematched controls or a nonstroke control group would only allow us to identify differences due to any stroke, not to stroke subtype. Furthermore, cortical stroke patients have risk factor profiles and medications similar to those of patients with lacunar stroke, thus controlling for potential confounders. METHODS All patients were examined by an experienced stroke physician. We assessed stroke severity with the NIH Stroke Scale (NIHSS)13 and classified the stroke clinical syndrome (lacunar or cortical) according to the Oxfordshire Community Stroke Project classification.14 We defined mild cortical stroke syndrome as a maximum clinical deficit of weakness or sensory loss in the face, arm, or leg; loss of higher cerebral dysfunction (dysphasia or neglect); weakness in more than one limb in the presence of loss of higher cerebral function (all in keeping with a partial anterior circulation stroke); or a homonymous hemianopia suggestive of occipital cortical infarct (in keeping with a cortical posterior circulation stroke).14 We defined lacunar stroke as per the classic lacunar syndromes (pure motor weakness or sensory loss or both in face and arm, arm and leg, or all three; ataxic hemiparesis; or clumsy hand dysarthria syndrome).14 We also classified stroke subtype using radiologic criteria (whether the recent infarct on MRI was cortical or lacunar) and used both the clinical and radiologic classification to assign a final stroke 1774

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subtype classification.14 Where the clinical classification differed from the radiologic classification, the radiologic classification was used, because using clinical criteria alone may result in misclassification of cortical and lacunar infarcts in up to 20% of cases.15 This study was approved by the local research ethics committee, and all patients gave written informed consent. Patients underwent usual investigations for stroke (brain imaging as below, carotid Doppler ultrasound, electrocardiogram, blood tests, and other tests if indicated). We recorded personal medical history of diabetes (physician-diagnosed history of diabetes), hypertension (physician-diagnosed history of hypertension), ischemic heart disease (physician-diagnosed history of angina, myocardial infarction, coronary angioplasty, or bypass grafting), peripheral vascular disease (physician-diagnosed history of or symptoms of intermittent claudication), cigarette smoking status, and medication use. We defined symptomatic carotid stenosis as greater than 50% measured with the North American Symptomatic Carotid Endarterectomy Trial (NASCET) method in the relevant artery.16 We defined atrial fibrillation as either a physician-diagnosed history of atrial fibrillation or an electrocardiogram showing atrial fibrillation. Patients had cerebral MRI at presentation, on a 1.5T Signa Horizon MR/I 1.5T HDX scanner (operating under a research collaboration with GE Medical Systems, Milwaukee, WI, operating as IGE in the UK) with 22 mT m–1 maximum strength gradients. Diagnostic MRI included axial diffusion-weighted, T2-weighted, fluid-attenuated inversion recovery (FLAIR) and gradient echo sequences (details available on request). All patients had six-field retinal photography (centered on the disk, macula, lateral macula, nasal to the disk, upper arcade, and lower arcade) of the left and right eyes, with 1% tropicamide eye drops where necessary, using a digital retinal camera (CRDGi; Canon USA Inc., Lake Success, NY).

MRI analysis. All MRI scans were coded for the presence, location, and size of the recent infarct and any old infarcts or hemorrhages. A recent infarct was a hyperintense area on diffusion imaging with corresponding reduced signal on apparent diffusion coefficient with or without increased signal on FLAIR or T2-weighted imaging, in a distribution compatible with an arterial territory. Lacunar infarcts were in the cerebral hemispheric white matter, basal ganglia, or brain stem and ⬍2 cm diameter if recent (subcortical lesions ⬎2 cm were classed as striatocapsular or cortical because they are caused by large artery disease). Retinal image analysis. All retinal images were analyzed blind to clinical and brain imaging features. Each color retinal image was stored within OptoMize® (Digital Healthcare, Cambridge, UK) software as tagged image file format files. For measurement of arteriovenous ratio (AVR), central retinal artery equivalent (CRAE), and central retinal vein equivalent (CRVE), retinal images were analyzed using a custom-written validated image analysis program (within MatLab: The MathWorks, Natick, MA). Each image was processed and converted to grayscale. Left and right eye vessel widths are highly correlated,17 and we randomly chose one image centered on the optic disk from one eye from each patient. The software drew a circle delineating the optic disk. The grader identified the six largest arterioles and venules passing through a zone between half and one disk diameter away from the border of the disk and on each vessel identified two points between which the software measured the vessel profile at multiple (5–20) locations (figure) with microdensitrometry. The vessel width was calculated for each profile as the width of the intensity profiles at half the height of the intensity profile peak.18 We validated this process with

Figure

Grayscale retinal photograph showing lower half of optic disk and surrounding arterioles and venules showing vessel tracking and width measurement technique (white arrow)

Bland–Altman plots comparing software performance to best human measurement (with a caliper on images that had been enlarged) and found no evidence of systematic bias and a mean difference between human and software measurements for 50 randomly chosen vessels of 0.006 pixels (95% confidence interval [CI] ⫺3.3 to 3.3 pixels). We summarized the widths of the six largest arterioles by producing a CRAE using a previously described formula which accounts for asymmetry of branching vessels.19 We also summarized the widths of the six largest venules to produce a CRVE and calculated the AVR as CRAE divided by CRVE. To convert the pixel measurements obtained from the image to absolute measurements (microns), we assumed that the average disk diameter was 1,850 ␮m.20 We used our cohort mean disk diameter of 381 pixels and multiplied all of our pixel measurements by 4.855 (1,850/381) to convert pixels to microns. In a randomly chosen sample of 20 retinal images, the intraclass correlation coefficients for intrarater reliability (assessments 1 month apart) were excellent (0.94 for CRAE, 0.98 for CRVE, and 0.91 for AVR). Using a second grader (T.J.M.), the intraclass correlation coefficients for interrater reliability were excellent (0.95 for CRAE, 0.89 for CRVE, and 0.90 for AVR). A physician (F.N.D.) specifically trained in retinal vessel assessment coded the presence (no, questionable, yes) and severity (mild, moderate, severe) of AVN and presence (no, questionable, yes) and severity (mild, severe) of FAN. We defined AVN as a reduced width of a venule on either side of an arteriole where the arteriole crossed the venule and FAN as a focal length of narrowing to at least two-thirds of the width of the proximal and distal arteriole.20 All questionable lesions were graded (present, not present) by an ophthalmologist with a specialist interest in retinal disease. This method of assessment has intrarater ␬ scores of 0.87 for AVN and 0.80 for FAN.21

Statistical analysis. We compared baseline characteristics between the lacunar and cortical stroke groups with the Student t test, ␹2 test for association, and Fisher exact test. CRAE, CRVE, and AVR were normally distributed, and we

compared unadjusted CRAE, CRVE, and AVR between groups with the Student t test. We performed multiple linear regression analysis with stroke subtype, age, and vascular risk factors as explanatory variables and CRAE, CRVE, and AVR as the dependent variable. CRAE and CRVE were covariates and were therefore modeled together. We dichotomized FAN and AVN data into present vs absent and used binary logistic regression to assess differences between stroke subtypes, correcting for vascular risk factors. We used odds ratios (ORs) with 95% CIs to examine associations between retinal and other features. All analysis was performed with Minitab (version 14; Minitab Inc., State College, PA). Sample size calculation based on existing literature on retinal findings in stroke4 suggested that 197 patients would be needed to detect a difference of prevalence of FAN or AVN of 10% with 80% power at the 0.05 significance level between stroke subtypes. RESULTS We recruited 220 patients. Eight were excluded (6 had poor-quality photographs; 2 had missing photographs), leaving 212 for analysis of FAN and AVN and 206 with photographic quality permitting analysis of vessel widths. Of the 212 patients, there were 105 lacunar strokes and 107 cortical strokes. The mean age was 68.1 years (SD 11.5 years), and the median NIHSS score was 2 (interquartile range 2–3) (table 1). The lacunar stroke patients were younger, with marginally higher stroke severity and lower rates of atrial fibrillation, symptomatic carotid stenosis ⬎50% NASCET, and ischemic heart disease than cortical strokes.

Vessel widths. Two hundred six patients contributed to this analysis. For the total study population, the mean CRAE was 33.47 pixels (162 ␮m), the mean CRVE was 43.87 pixels (212 ␮m), and the mean AVR was 0.77. CRAE and CRVE were correlated with a Pearson correlation coefficient of 0.66. Patients with lacunar stroke had increased CRVE (44.9 [SD 5.5] vs 42.9 [SD 6.4] pixels, p ⫽ 0.01), decreased AVR (0.76 [SD 0.1] vs 0.78 [SD 0.1] pixels, p ⫽ 0.03), and similar CRAE compared with patients with cortical stroke (33.2 [SD 4.4] vs 33.7 [SD 4.3] pixels, p ⫽ 0.4). Table 2 shows the adjusted associations with arteriolar and venular widths. Increased CRVE was significantly and independently associated with lacunar stroke subtype, younger age, and increased CRAE (after correcting for the presence of diabetes, hypertension, and sex). Increased CRAE was significantly and independently associated with female sex and increased CRVE (correcting for age, diabetes, hypertension, and stroke subtype). Decreased AVR was significantly and independently associated with lacunar stroke subtype and younger age (correcting for diabetes, hypertension, and sex). We performed a sensitivity analysis excluding patients with a history of stroke and found that in 186 Neurology 72

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Table 1

Baseline characteristics of lacunar and cortical stroke subgroups

Characteristic

Lacunar stroke

Cortical stroke

n

105

107

Age, mean (SD), y

66.2 (11.5)

70.0 (11.3)

62 (59)

73 (68)

Male, no. (%) Median NIHSS

3

p Value for difference between groups

0.017 0.163 ⬍0.001

2

Atrial fibrillation, no. (%)

4 (4)

14 (13)

0.02

Symptomatic carotid stenosis >50%, no. (%)

4 (4)

13 (12)

0.02

Diabetes

19 (18)

12 (11)

0.15

Ischemic heart disease

14 (13)

31 (29)

0.004

5 (5)

5 (5)

0.97

Hypertension

59 (56)

70 (65)

0.17

TIA

17 (16)

11 (10)

0.19

8 (8)

12 (11)

0.52

Stroke

Groups are compared with two-sample t test (age), Mann–Whitney U test (NIH Stroke Scale [NIHSS]), and differences in proportions (all others).

patients the results were similar to those presented in table 2, although the association between increased venular width and lacunar stroke subtype was strengthened (data not shown). Arteriovenous nicking and focal arteriolar narrowing.

Two hundred twelve patients contributed to this analysis. AVN was present in 83 of 107 patients (78%) with cortical stroke and 85 of 105 patients (81%) with lacunar stroke (difference ⫽ 3%, 95% CI ⫺7% to 14%, p ⫽ 0.53). FAN was present in 28 of 107 patients (26%) with cortical stroke and 37 of 105 patients (35%) with lacunar stroke (difference ⫽ 9%, 95% CI ⫺3% to 21%, p ⫽ 0.15). The distributions of FAN and AVN by stroke subtype are given

Table 2

Associations between vessel widths and key patient variables on multivariable linear regression showing ␤ coefficient and p value for CRAE, CRVE, and AVR CRAE

Explanatory variable Age Male Lacunar stroke subtype

␤

CRVE

⫺1.1

AVR

␤

p Value

0.12

⫺0.11

⬍0.001*

0.02*

⫺0.10

p Value 0.03

0.3

⫺0.02

0.047*

0.02

0.97

⫺0.29

Hypertension

⫺0.95

0.05

0.94

0.15

CRAE

NA

0.88

⬍0.001*

⬍0.001*

0.002

⫺0.01

1.33

0.48

p Value 0.002

0.87

0.29

CRVE

␤

0.03*

-0.48

Diabetes

0.74

NA

0.002 ⫺0.02

0.8 0.06

NA NA

All analyses are corrected for the presence of the other variables in the table. *p ⬍ 0.05. CRAE ⫽ central retinal artery equivalent; CRVE ⫽ central retinal vein equivalent; AVR ⫽ arteriovenous ratio; NA ⫽ not applicable. 1776

Retinal microvessel morphology differs between lacunar and cortical ischemic stroke subtypes. Increased retinal venular diameters and decreased AVR are both independently associated with lacunar rather than cortical stroke subtype. These results suggest that there may be a distinct small vessel vasculopathy in cerebral small vessel disease. We have not demonstrated a strong association between retinal arteriolar diameter, FAN, or AVN and lacunar stroke subtype. The cross-sectional design means that we can only report on associations, so we do not know whether these retinal vessel differences are long-standing and predispose to the lacunar phenotype, or are acquired in later life as part of the lacunar disease. Nor can we tell whether they are causative or associative. The parity of arteriolar measurements (width, AVN, and FAN) between stroke subtypes coupled with associations between hypertension and AVN and decreased arteriolar width suggest that arteriolar features reflect exposure to vascular risk factors. In response to these risk factors, some patients may develop lacunar and others a large artery (cortical) stroke phenotype. No previous studies have compared quantitative vessel width measurement, AVN, or FAN between ischemic stroke subtypes. Previous studies did not subtype stroke and compared retinal arteriolar parameters between subjects with stroke and those without.4 Those that combined arteriolar and venular diameters into the dimensionless AVR produced conflicting results about associations with both future stroke and history of stroke.6-8,22 Changes in AVR were previously thought to reflect only arteriolar narrowing,20 known to change in response to systemic disease, but it is now known that venular diameter also varies.23 Those studies that analyzed arteriolar and venular widths separately found that the increase in AVR predicting the presence of any stroke (of any subtype) compared with absence of stroke was due to venular widening rather than arteriolar narrowing.6,11,24 Reports vary regarding the associations between AVN and FAN and any stroke,8-10,22,25 which may reflect methodologic difficulties in identifying DISCUSSION

Medical history, no. (%)

Peripheral vascular disease

in table e-1 on the Neurology® Web site at www. neurology.org. We performed binary logistic regression to adjust for the baseline risk factor and age imbalances between the cortical and lacunar stroke groups with FAN or AVN as the dependent variable (dichotomized to present or absent). Only hypertension independently predicted the presence of AVN; no risk factors were independently associated with FAN (table 3). Excluding patients with a history of stroke did not alter these results.

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Table 3

Multivariable binary logistic regression for associations with presence of FAN and AVN OR predicting presence of AVN (95% CI)

p Value

OR predicting presence of FAN (95% CI)

p Value

Age

0.98 (0.95–1.01)

0.16

0.99 (0.96–1.02)

0.52

Male

0.89 (0.43–1.82)

0.75

1.13 (0.61–2.10)

0.70

Diabetes

1.29 (0.45–3.68)

0.63

0.83 (0.35–1.96)

0.67

Hypertension

2.05 (1.00–4.19)

0.049*

1.18 (0.62–2.25)

0.61

Lacunar stroke subtype

1.18 (0.59–2.37)

0.63

1.55 (0.84–2.84)

0.16

*p ⬍ 0.05. FAN ⫽ focal arteriolar narrowing; AVN ⫽ arteriovenous nicking; OR ⫽ odds ratio; CI ⫽ confidence interval.

stroke. Studies that showed an association with stroke tended to use MRI-based definitions of cerebral infarct rather than clinical definitions. It is uncertain what “holes” in the brain represent,12 and stroke diagnosis based on case-record assessment is of limited accuracy.26 We did not find differences in retinopathy between lacunar and cortical stroke27 despite many previous reports of associations between retinopathy and stroke.4 The lack of differences in arteriolar changes between stroke subtypes in our study could be because the retinal arteriolar circulation does not reflect cerebrovascular disease or because the arteriolar differences were too small to identify in this study. Alternatively retinal features may simply reflect exposure to systemic risk factors and are not specific for small vs large artery disease. Two population-based studies showed that increased venular diameter predicted future risk of any clinical stroke.6,24 One study found larger CRVE in subjects with lacunes seen on MRI.11 Increased venular width is associated with plasma markers of inflammation28-30 and decreased arteriolar oxygen saturation levels.31 Thus, increased venular diameter could reflect an inflammatory component in patients with lacunar stroke. The strengths of the present study are the subtyping of ischemic stroke, the use of cortical stroke patients to control for potential confounding risk factors, and that stroke was diagnosed by a stroke expert with MR at presentation. We maintained careful blinding of brain and retinal images to each other and to clinical features throughout. We used detailed retinal photos, careful training of retinal graders, and validated assessment methods. CRAE and CRVE are correlated; therefore, models assessing multivariable associations with either need to correct for the other, as we did.32 To minimize confounding of stroke subtyping, we performed a sensitivity analysis excluding patients with a history of previous stroke, which did not change the results for the total study population. A larger sample size might be

needed to show differences in arteriolar diameters, FAN, and AVN. We have also used a concrete definition of small vessel disease, i.e., clinically evident lacunar stroke with best available imaging backup rather than a purely imaging- or clinical-based definition or one with uncertain relevance even to stroke. In summary, we have shown that retinal venules are wider in patients with lacunar stroke compared with patients with cortical stroke. This suggests that there may be a distinct vasculopathy causing lacunar stroke. AUTHOR CONTRIBUTIONS F.N. Doubal conducted all statistical analysis.

ACKNOWLEDGMENT Brain imaging took place in the SFC Brain Imaging Research Centre (www.sbirc.ac.uk). Retinal photographs were taken in the Wellcome Trust Clinical Research Facility, Western General Hospital, Edinburgh.

Received September 11, 2008. Accepted in final form February 18, 2009.

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Ikram MK, de Jong FJ, Vingerling JR, et al. Are retinal arteriolar or venular diameters associated with markers for cardiovascular disorders? The Rotterdam Study. Invest Ophthalmol Vis Sci 2004;45:2129–2134. Wong TY, Kamineni A, Klein R, et al. Quantitative retinal venular caliber and risk of cardiovascular disease in older persons: the Cardiovascular Health Study. Arch Intern Med 2006;166:2388–2394. Wong TY, Klein R, Sharrett AR, et al. The prevalence and risk factors of retinal microvascular abnormalities in older persons: the Cardiovascular Health Study. Ophthalmology 2003;110:658–666. Piriyawat P, Smajsova M, Smith MA, et al. Comparison of active and passive surveillance for cerebrovascular disease: the Brain Attack Surveillance in Corpus Christi (BASIC) project. Am J Epidemiol 2002;156:1062–1069. Doubal FN, Dhillon B, Dennis MS, Wardlaw JM. Retinopathy in ischemic stroke subtypes. Stroke 2009;40:389– 393. Wong TY, Islam FMA, Klein R, et al. Retinal vascular caliber, cardiovascular risk factors, and inflammation: the Multi-Ethnic Study of Atherosclerosis (MESA). Invest Ophthalmol Vis Sci 2006;47:2341–2350. Klein R, Klein BEK, Knudtson MD, Wong TY, Tsai MY. are inflammatory factors related to retinal vessel caliber? The Beaver Dam Eye Study. Arch Ophthalmol 2006;124: 87–94. de Jong FJ, Ikram MK, Witteman JC, Hofman A, de Jong PT, Breteler MM. Retinal vessel diameters and the role of inflammation in cerebrovascular disease. Ann Neurol 2007;61:491–495. de Jong FJ, Vernooij MW, Ikram MK, et al. Arteriolar oxygen saturation, cerebral blood flow, and retinal vessel diameters: the Rotterdam Study. Ophthalmology 2008; 115:887–892. Liew G, Sharrett AR, Kronmal R, et al. Measurement of retinal vascular caliber: issues and alternatives to using the arteriole to venule ratio. Invest Ophthalmol Vis Sci 2007; 48:52–57.

m.AAN.com: Put the AAN in the Palm of Your Hand AAN.com, the Academy’s award-winning site for neurology resources, has gone mobile. Read more about the special mobile website exclusively available for Academy members at www.aan.com/mobile. Log on to m.aan.com and access your Academy’s web resources on the go. Visit m.aan.com—it’s as close as your phone.

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CLINICAL IMPLICATIONS OF NEUROSCIENCE RESEARCH

Oligodendrocytes Susceptibility to injury and involvement in neurologic disease

Section Editor Eduardo E. Benarroch, MD

Eduardo E. Benarroch, MD

Address correspondence and reprint requests to Dr. Eduardo E. Benarroch, Department of Neurology, Mayo Clinic, West 8A Mayo Bldg., 200 First Street SW, Rochester, MN 55905 [email protected]

Oligodendrocytes are the myelin-producing cells in the CNS and are critical for function and survival of the axons. Oligodendrocytes and their precursors are highly susceptible to excitotoxic damage, oxidative stress, and effects of cytokines. Glutamate and other neurotransmitters triggering calcium (Ca2⫹) signaling have a major role in both normal oligodendrocyte development and oligodendrocyte injury in white matter disorders such as periventricular leukomalacia (PVL), multiple sclerosis (MS), ischemic stroke, traumatic brain or spinal injury, radiation necrosis, and leukodystrophies. Oligodendrocytes may also have a central role in multiple system atrophy (MSA). These topics have been extensively covered in several excellent reviews1-8 and some of the most salient points are summarized here. MULTIPLE FUNCTIONS OF OLIGODENDROCYTES Oligodendrocytes originate from progenitor

cells that express the NG2 (neuron glia 2) chondroitin sulfate proteoglycan and platelet-derived growth factor–␣ (PDGF-␣) receptor in their cell membrane (figure 1). After migration, oligodendrocyte progenitor cells reach their destination and begin to differentiate; they upregulate expression of myelin proteins, increase the number and complexity of their processes, and begin to form membrane wraps around the axons.1 The oligodendrocytes and the axons form a functional unit and have complex reciprocal interactions. The mature oligodendrocytes form the compact myelin internodes in the CNS; each oligodendrocyte can produce up to 30 –50 myelin segments in different axons. The presence of the myelin sheath is critical for fast saltatory conduction of the action potential, which depends both on the insulating properties of myelin and the clustering of voltage-

gated sodium (Na⫹) channels at the nodes of Ranvier. Therefore, the primary consequence of oligodendrocyte death is axonal demyelination, resulting in delay or block of conduction of the action potential in the axon. However, the oligodendrocytes are also critical for maintenance of axon structure and survival.1 Studies in vitro and in transgenic mouse models indicate that the presence of a myelin sheath increases the axon diameter by promoting local accumulation and phosphorylation of neurofilament subunits9; is essential for clustering of sodium (Na⫹) channels at the nodes of Ranvier10; and is necessary for normal axonal transport11 and structural integrity of the axon.12 Oligodendrocytes may exert a neuroprotective function, as they provide trophic support for the neuronal cell bodies by producing several trophic factors.1 RECEPTORS IN OLIGODENDROCYTES AND AXON-TO-OLIGODENDROCYTE SIGNALING

The normal formation of myelinated axons requires a precise matching between the number of oligodendrocytes generated from precursor cells and the length of axons to be myelinated. Neurotransmitters released by electrically active axons, including glutamate, adenosine triphosphate (ATP), and adenosine, can influence all stages of oligodendrocyte development, primarily via calcium (Ca2⫹)-dependent mechanisms.3-5 Oligodendrocytes and their precursors express many neurotransmitter receptors that mediate these effects5 (table). Glutamate has a critical role in axon-oligodendrocyte interactions. Glutamate activates AMPA (␣-amino-3hydroxy-5-methyl-4-isoxazolepropionic acid), kainate, and NMDA receptors in oligodendrocytes. AMPA/ kainate receptors are predominantly expressed in the oligodendrocyte cell body whereas NMDA receptors are

GLOSSARY AMPA ⫽ ␣-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid; ATP ⫽ adenosine triphosphate; EAAT ⫽ excitatory amino acid transporters; GABA ⫽ ␥-aminobutyric acid; GCI ⫽ glial cytoplasmic inclusion; MS ⫽ multiple sclerosis; MSA ⫽ multiple system atrophy; NG2 ⫽ neuron glia 2; NO ⫽ nitric oxide; NOS ⫽ nitric oxide synthase; OPC ⫽ oligodendrocyte progenitor cell; PDGF-␣ ⫽ platelet-derived growth factor–␣; PVL ⫽ periventricular leukomalacia; TNF ⫽ tumor necrosis factor. From the Department of Neurology, Mayo Clinic, Rochester, MN. Disclosure: The author reports no disclosures. Copyright © 2009 by AAN Enterprises, Inc.

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Figure 1

Structural organization and receptor distribution of oligodendrocytes and oligodendrocyte progenitor cells (OPCs)

Oligodendrocytes originate from progenitor cells that express the neuron glia 2 (NG2) chondroitin sulfate proteoglycan. Oligodendrocytes and their precursors express AMPA (␣-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid), kainate, and NMDA receptors for glutamate and adenosine triphosphate (ATP)– gated P2 ⫻ 7 receptors. AMPA/kainate receptors are predominantly expressed in the cell body and NMDA receptors in the myelinating processes. The AMPA, kainate, and NMDA receptors are permeable to calcium (Ca2⫹). The NG2⫹ glia include OPCs that receive excitatory and inhibitory synaptic inputs from myelinated or unmyelinated axons and extend processes to the nodes of Ranvier. Glutamate may also be released from reverse action of the excitatory amino acid transporters (EAAT) unexpressed both in the axons and oligodendrocytes.

expressed in the processes forming the myelin sheath (figure 1).3-5 Glutamate receptors in oligodendrocytes differ from those expressed in most neurons in several features that predispose the oligodendrocyte to cytotoxic injury (table). In oligodendrocytes, AMPA receptors lack GluR2 subunits and are thus permeable to Ca2⫹. Whereas in neurons activation of NMDA receptors requires neuronal depolarization to allow removal of the voltage-dependent blockade of the NMDA channel pore by extracellular magnesium (Mg2⫹), NMDA receptors in oligodendrocytes show very weak voltagedependent block by extracellular Mg2⫹ and may be therefore activated even at resting potential in vitro.3-5 Expression of ionotropic glutamate receptors is developmentally regulated. In human brain white 1780

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matter, Ca2⫹ permeable AMPA/kainate receptors are abundantly expressed in oligodendrocyte precursors and premyelinating oligodendrocytes. Both in culture and in brain slices, activation of these receptors inhibits PDGF-induced proliferation and promotes migration and differentiation of oligodendrocytes precursor cells.5 A special type of glial cells, defined by the cell-surface expression of the NG2 proteoglycan, receives direct synaptic excitatory or inhibitory input from axons.1-3,13 These NG2⫹ cells probably constitute a heterogeneous population1 referred to as polydendrocytes; some may constitute oligodendrocyte precursor cells,3,13 whereas others may constitute a distinct type of glia.14 Glutamate is released from typical synapses on NG2⫹ glia15 and a subset of

Table

Neurotransmitter receptors relevant to oligodendrocyte development and vulnerability to injury

Receptor Special features in oligodendrocytes AMPA

2⫹

Ca

permeable (lack GluR2 subunits)

Implications Decrease OPC proliferation in response to PDGF and promote migration

Localized in cell body, particularly of immature oligodendrocytes

Mediate synaptic excitation of and action potential firing in NG2⫹ glia (OPC)

Downregulated in mature oligodendrocytes

Mediate cytotoxic injury, particularly in vulnerable OPCs and immature oligodendrocytes

Ca2⫹ permeable

Decrease OPC proliferation in response to PDGF and promote migration

Localized in cell body, particularly of immature oligodendrocytes

Mediate cytotoxic injury, particularly in vulnerable OPCs and immature oligodendrocytes

Downregulated in mature oligodendrocytes

Sensitize oligodendrocytes to attack by complement

Weak blockade by extracellular Mg2⫹ (contain NR2C/NR3 subunits)

May control myelination

Localized in distal processes forming the myelin sheath

Excessive activation leads to water influx, swelling, and disruption of the myelin sheath

GABAA

Evokes depolarization in oligodendrocytes (due to elevated intracellular Cl⫺ concentration)

Decrease proliferation and promote migration; may contribute to oligodendrocyte damage and demyelination

P2 X 7

Ca2⫹ channel activated by ATP release from axons and astrocytes

Decrease proliferation and promote migration and myelination; mediate cytotoxic injury

A2

Stimulated by adenosine released from axons or astrocytes Decrease proliferation and promote migration, or converted from ATP in the extracellular space differentiation, and myelination

Kainate

NMDA

AMPA ⫽ ␣-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid; OPC ⫽ oligodendrocyte precursor cells; PDGF ⫽ plateletderived growth factor; GABA ⫽ ␥-aminobutyric acid; ATP ⫽ adenosine triphosphate.

these cells have been shown to fire action potentials in response to activation of AMPA receptors.13 These excitable NG2⫹ cells, like astrocytes, extend processes to nodes of Ranvier.14 The physiologic role of the NG2⫹ glia is unclear; it has been suggested that generation of action potentials in these cells may serve to initiate their differentiation into myelinating oligodendrocytes3,13 or provide instructions to nearby oligodendrocytes and axons to improve nodal axonal conduction.16 The excitable NG2⫹ glial cells have much greater vulnerability to ischemia and glutamate-triggered toxicity than their nonexcitable counterparts.13 Since in adult CNS, NG2⫹ glia respond rapidly to insults and may be able to regenerate oligodendrocytes, loss of excitable NG2⫹ glia may be an important feature of excitotoxic damage and impaired remyelination of white matter in adult CNS. However, the AMPA/kainate receptors are downregulated in human mature oligodendrocytes17 and these developmental changes may be relevant to the particular susceptibility of oligodendrocyte precursors and immature oligodendrocytes to anoxia or ischemia.6 The preferential location of NMDA receptors in the distal process of oligodendrocytes suggests their possible role in controlling axon– oligodendrocyte interactions.3-5 Mature oligodendrocytes are exposed to glutamate released via reversal of glutamate transport in axons during the action potential in normal condition and particularly in conditions associated with energy

failure.18,19 In addition to glutamate, ATP may also regulate oligodendrocyte development; ATP binds P2⫻7 receptors, which are Ca2⫹ channels that promote oligodendrocyte differentiation.3-5 However, these receptors may also contribute to toxicity in these cells.20 MECHANISMS OF OLIGODENDROCYTE INJURY Oxidative damage. Oligodendrocytes are par-

ticularly susceptible to oxidative injury (figure 2).1 Predisposing factors include their high metabolic rate and ATP requirement for the synthesis of large amounts of myelin membrane, the high production of hydrogen peroxide in peroxisomes, and the large intracellular stores of iron.1 Whereas iron is critical for myelin production,21 this metal can also trigger free radical formation and lipid peroxidation, via conversion of hydrogen peroxide into hydroxyl radicals. Oligodendrocytes have low concentration of the antioxidant glutathione and this predisposes to accumulation of intracellular hydrogen peroxide.1 Excitotoxicity. Oligodendrocytes and their precursors are highly susceptible to glutamate-induced excitotoxicity. Oligodendrocytes express the excitatory amino acid transporter (EAAT)-1 and EAAT-2 and are the predominant cells for glutamate clearance in human white matter.2,3 In conditions associated with ATP depletion affecting ion gradients, reverse function of these glutamate transporters may lead to glutamate release from both oligodendrocytes and axons.18,19 ATP released from axons, astrocytes, or microglia in response to inNeurology 72

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Figure 2

Some proposed mechanisms of oligodendrocyte toxicity

Oligodendrocytes are susceptible to injury triggered by excessive activation of calcium (Ca2⫹)-permeable AMPA (␣-amino3-hydroxy-5-methyl-4-isoxazolepropionic acid), kainate, and NMDA glutamate receptors and adenosine triphosphate (ATP)–activated P2 ⫻ 7 receptors. Predisposing factors include high production of hydrogen peroxide (H2O2) and the large intracellular stores of iron (Fe2⫹). In conditions of energy failure reversal of the excitatory amino acid transporters (EAAT) may lead to glutamate release from both oligodendrocytes and axons. Accumulation of cytosolic Ca2 activates synthesis of nitric oxide (NO); accumulation in the mitochondria leads to production of superoxide ion (O2 ⫺) that reacts with NO to produce peroxynitrite and release of proapoptotic factors that activate caspases. Microglia release cytokines that trigger or potentiate toxicity in oligodendrocytes. For example, tumor necrosis factor (TNF)–␣ impairs EAAT function and activates death receptors in oligodendrocytes (not shown).

jury may also elicit oligodendrocyte toxicity.20 Glutamate- and ATP-induced oligodendrocyte toxicity primarily depends on excessive Ca2⫹ influx.2,4,22-24 Accumulation of Ca2⫹ within mitochondria leads to production of oxygen free radicals and release of proapoptotic factors that activate caspases; excessive cytosolic Ca2⫹ activates calpains, phospholipases, endonucleases, and nitric oxide (NO) synthase (NOS). The reaction of NO with superoxide leads to the production of peroxynitrite, which is toxic to oligodendrocytes.25 The preferential location of NMDA receptors on the distal processes of oligodendrocytes renders the myelin sheaths particularly vulnerable to excitotoxic insults, leading to osmotic swelling, loosening, and vacuolation.2 Blockade of AMPA/kainate or NMDA receptors attenuates white matter injury in several animal models,22,24,26,27 suggesting that both types of receptors mediate glutamate-induced toxicity in oligodendrocytes. However, cultured human adult oligodendrocytes express low levels of ionotropic re1782

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ceptors and are resistant to AMPA/kainate-mediated excitotoxicity,17 suggesting that these results should be extrapolated with caution to adult human white matter disease. Blockade of P2⫻7 also has a neuroprotective effect in vitro.20 Role of the microglia. Microglia present at the sites of injury have an important role in triggering or potentiating oligodendrocyte injury by several mechanisms. Both resting and activated microglia may release glutamate via a cystine-glutamate antiporter,28 as well as proinflammatory cytokines, such as tumor necrosis factor (TNF)–␣, which impair expression or function of glutamate transporters in astrocytes and oligodendrocytes. TNF␣ can also trigger oligodendrocyte apoptosis both via death receptors or by activation of sphingomyelinase and release of ceramide.1 There is in vitro evidence that cytokine-induced oligodendrocyte injury may be mediated by iron and involves mitochondrial dysfunction.29 Activated

microglia may also release peroxynitrite, which is damaging to oligodendrocytes.25 CLINICAL CORRELATIONS Periventricular leu-

komalacia. PVL in premature infants is characterized

by diffuse injury of deep cerebral white matter initiated by cerebral ischemia and, in a subset of cases, intrauterine or neonatal infection. The main target of injury is premyelinating oligodendrocytes. These cells are particularly vulnerable to excitotoxic damage and the effect of cytokines due to their high expression of Ca2⫹permeable AMPA and NMDA receptors and glutamate transporters, abundant production of free radicals, and delayed development of antioxidant defenses.6 Microglia has a critical role in triggering oligodendrocyte injury in this disorder.6 Multiple sclerosis. Oligodendrocyte apoptosis and se-

lective loss of myelin-associated glycoprotein are characteristic of early MS lesions defined as pattern III by Lucchinetti et al.30 Other authors propose that oligodendrocyte apoptosis in the absence of significant inflammation (i.e., prephagocytic stage) is an initial event of all new MS plaque formation.7,31 Glutamate-triggered toxicity may have a major role in loss of oligodendrocytes and myelin in MS. Findings on biopsy material32 and studies using magnetic resonance spectroscopy33 show increased glutamate concentration in acute lesions and normal-appearing white matter in patients with MS. Glutamate accumulation may be due to several mechanisms, including release from reactive microglia via the cystineglutamate antiporter system28; excessive glutamate production by glutaminase and reduced degradation by glutamate dehydrogenase and glutamine synthetase32; or reduced expression of EAAT-1 and EATT-2 in oligodendrocytes.34 There is also upregulation of Ca2⫹-permeable AMPA receptors in active MS lesion borders.35 The presence of high levels of iron in both oligodendrocytes and in MS lesions suggests an important role of iron-promoted oxidative injury in the pathogenesis of this disease.36 Peroxynitrite has been proposed as an important trigger of oligodendrocyte apoptosis in MS.37 A study on a single MS case showed strong upregulation of neuronal NOS and accumulation of nitrotyrosine (reflecting peroxynitrite-mediated damage) in oligodendrocytes distant from the area of active demyelination.38 This suggests that upregulation of neuronal NOS and protein nitration in oligodendrocytes may constitute early changes in MS.38 There is also upregulation of ␣-synuclein expression in adult oligodendrocytes in normal-appearing white matter in both MS and in an experimental model of experimental allergic encephalomyelitis.39 Alpha-synuclein

increases sensitivity of oligodendrocytes to oxidative stress in vitro as demonstrated in transgenic mouse models.40 Multiple system atrophy. MSA is a sporadic, progres-

sive, adult onset disorder characterized by autonomic failure associated with parkinsonism, cerebellar ataxia, corticospinal tract signs, or combinations thereof. This disorder is neuropathologically defined by the presence of filamentous ␣-synuclein– containing inclusions, particularly in the cytoplasm of oligodendrocytes.41 These glial cytoplasmic inclusions (GCIs) are associated with neuronal loss, reactive gliosis, iron deposition, and myelin degeneration, particularly in the putamen, substantia nigra pars compacta, cerebellum, pons, inferior olivary nucleus, medullary reticular formation, and preganglionic autonomic nuclei. The finding of GCIs as a pathologic hallmark of MSA has led to the suggestion that this disease represents an oligodendrocyte synucleinopathy.8 Transgenic mouse models with targeted overexpression of human ␣-synuclein (SCNA) gene in oligodendrocytes provide indirect evidence in support of this possibility.40,42 In these models, accumulation of human ␣-synuclein is associated with GCIs and apoptosis in oligodendrocytes, particularly in the setting of oxidative stress.40 The relationship between oligodendrocyte injury and neuronal degeneration in MSA is poorly understood. Some findings suggest that oligodendrocyte involvement may precede neuronal loss, as discussed in a recent review.8 Secondary microglial activation may have a prominent role in neurodegeneration in MSA.43 Several pharmacologic approaches have been shown to exert neuroprotective effects in transgenic mouse models of MSA. These include rifampin, which inhibits ␣-synuclein aggregation in oligodendrocytes44; rasagiline, which exerts antioxidant action45; and minocycline, which reduces microglial activation.43 PERSPECTIVE Oligodendrocytes are lipid factories that form a functional unit with the axon. This interaction is critical for oligodendrocyte development, myelin formation, and structural integrity and survival of the axon and perhaps the neurons. Due to their high metabolic activity, iron content, and expression of Ca2⫹ permeable receptors, oligodendrocytes are vulnerable to oxidative and nitrosative damage induced by glutamate, ATP, or cytokines in a wide variety of conditions affecting the nervous system. These mechanisms provide several targets for oligodendrocyte protection. However, further studies and well-designed clinical trials are necessary to extrapolate the findings on experimental animals to human neurologic disease. Neurology 72

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Clinical/Scientific Notes

Suraj Ashok Muley, MD Gareth J. Parry, MD

ANTIBIOTIC RESPONSIVE DEMYELINATING NEUROPATHY RELATED TO LYME DISEASE

Neuropathies that occur in the context of Lyme disease are commonly related to axonal degeneration.1 Acute demyelinating neuropathy has also been described2 and the possibility of chronic demyelinating neuropathy (CDN) has been raised.3 We report a patient who developed a demyelinating neuropathy in the context of Lyme disease. Treatment of the infection led to marked clinical and electrophysiologic recovery, suggesting an infectious rather than an immune-mediated pathogenesis. Case report. A 56-year-old Caucasian man developed numbness and tingling in his feet in August 2002 that within a few days spread symmetrically to the fingertips and hands. He reported weakness with heavy manual labor over the ensuing 8 weeks. He denied ataxia, cranial nerve, respiratory, or autonomic symptoms. There was no history of diabetes, thyroid disease, or renal disease. There was no exposure to toxins, chemicals, or tick bites. Family history was unremarkable and there was no history of tobacco or alcohol abuse. Cranial nerve examination was normal. Motor examination revealed normal strength in shoulder abduction and elbow flexion bilaterally but strength was Medical Research Council (MRC) grade 4 in elbow extension, wrist extension, and finger extension. In the legs, there was weakness only in bilateral hip flexion (MRC 4). He was globally areflexic with downgoing toes. Sensation to temperature, pinprick, and light touch was reduced up to the knees on both sides. Proprioception was normal but vibratory perception was reduced at the toes and ankles. Coordination, gait, and Romberg test were unremarkable. Complete blood count, serum immunofixation, erythrocyte sedimentation rate, and anti-ENA, GM-1, GD-1b, SGPG, MAG, sulfatide, GALOP, and Hu antibodies were negative. Serum Lyme ELISA, western blot (by Centers for Disease Control and Prevention criteria), and CSF Lyme titer were positive; with ELISA, immunoglobulin G (IgG) titer was 1.2 (positive ⬎1.09), IgM was negative, and with western blot six IgG bands (18, 39, 41, 58, 66, 93) were seen. CSF revealed one erythrocyte, two

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leukocytes, and protein of 67 mg/dL but IgG index and IgG synthesis rate were normal. No oligoclonal bands were identified. Nerve conduction studies showed conduction slowing and abnormal temporal dispersion consistent with an acquired demyelinating neuropathy (table). EMG of muscles of the left arm and leg was normal without evidence of denervation. The patient was treated with ceftriaxone for 4 weeks beginning 8 weeks after the onset of symptoms. After completion of his antibiotic treatment he reported marked improvement in his symptoms over a few days; the extent and severity of numbness had regressed and weakness had resolved. Examination revealed normal strength with hypesthesia to the mid-calf level. Ankle reflexes were absent, knee reflexes were reduced, and reflexes had returned to normal in the arms. Electrophysiologic studies had also returned to normal apart from persistent prolongation of distal motor latencies; conduction slowing, temporal dispersion, and prolongation of F latencies had resolved (table). CSF analysis revealed no cells. CSF protein and glucose were both 53 mg/dL. CSF Lyme IgG and IgM titers were negative. The patient remains symptom-free at the current time, more than 5 years since the initial presentation, suggesting that the illness was monophasic. Discussion. The clinical picture of diffuse areflexia, progressive weakness and numbness, CSF protein elevation, and severe slowing in nerve conduction velocities was diagnostic of a demyelinating neuropathy. Whether the neuropathy was a form of chronic inflammatory demyelinating polyneuropathy (CIDP) or a monophasic acute neuropathy such as Guillain-Barre´ syndrome (GBS) was not clear. Our impression was that the neuropathy was more consistent with CIDP than with GBS, given that Inflammatory Neuropathy Cause and Treatment (INCAT) criteria for CIDP were met. Although the possibility of an infection having triggered an immune response cannot be ruled out, the fact that weakness, sensory loss, and electrophysiologic changes reversed with antibiotic treatment alone (without immunosuppression) suggests that

Table

Electrophysiology Distal latency (msec)

Amplitude (mV)

Conduction velocity (m/s)

F wave latency (msec)

Before treatment Motor nerve Left median

7.3

2.4 (TD)

39.5

33.8

Left ulnar

4.6

5.04 (TD)

41

38.3

14.5

1.77 (TD)

41.5

Not done

5.1

2.93 (TD)

37.5

Not done

Right sural

5.93 ␮V

36.8

Left ulnar

No response

Left median

No response

Right median Right ulnar Sensory nerve

After treatment Left median

4.6

8.3

53.1

29.8

Left ulnar

3.8

8.1

52.6

30.3

Right median

5.6

6.09

52.1

Not done

Right ulnar

4.2

7.62

60

Not done

Left peroneal

5

5.88

52.5

Not done

TD ⫽ temporal dispersion.

From the Department of Neurology, University of Minnesota. Disclosure: The authors report no disclosures. Received November 14, 2008. Accepted in final form January 26, 2009. Address correspondence and reprint requests to Dr. Suraj Ashok Muley, Associate Professor of Neurology, University of Minnesota, 420 Delaware St. SE, Minneapolis, MN 55455; [email protected] Copyright © 2009 by AAN Enterprises, Inc. ACKNOWLEDGMENT The authors thank Sandra Hanson, MD, Park Nicollet Clinic, Minneapolis, MN.

1.

the neuropathy was probably directly related to Borrelia infection, rather than to an immune-mediated process. Similar improvement with antibiotic treatment has also been described in the distal symmetric neuropathy that occurs with chronic Lyme infection.4,5 Demyelinating neuropathy in the context of Lyme disease has not been well documented. Severe conduction slowing and conduction block consistent with chronic demyelination in a patient with Lyme

I. Martinez-Torres, MD M.I. Hariz, MD, PhD L. Zrinzo, MD, MSc, FRCS(Ed) T. Foltynie, MRCP, PhD P. Limousin, MD, PhD

infection and two other patients with possible acute demyelinating neuropathy have been described.2,3 It is unclear whether those patients responded to immunosuppression or to treatment of the infection. Our case indicates that a demyelinating neuropathy occurs with chronic Borrelia infection and provides a rationale for routine Lyme testing in such patients. Unlike the immune-mediated demyelinating neuropathies, it responds to antibiotic therapy. Early recognition is important given the excellent response to treatment.

IMPROVEMENT OF TICS AFTER SUBTHALAMIC NUCLEUS DEEP BRAIN STIMULATION

Deep brain stimulation (DBS) of the medial thalamic nuclei and globus pallidus internus (GPi)1,2 has been tried in the treatment of medically refractory Tourette syndrome (TS). Subthalamic nucleus (STN) is the target most commonly used for DBS in Parkinson disease (PD). A double-blind randomized study has shown the efficacy of STN-DBS in obsessive compulsive disorder (OCD),3 which is considered within the spectrum of TS. We report a patient with PD who also had a history of TS in whom bilateral STN-DBS improved both PD and tics. Case report. A 38-year-old man with an 8-year history of PD was referred for DBS consideration. He had a history of tics that began at the age of 7 and improved by the age of 12. Tics increased in adult-

2.

3.

4.

5.

Meier C, Grahmann F, Engelhardt A, Dumas M. Peripheral nerve disorders in Lyme borreliosis: nerve biopsy studies from eight cases. Acta Neuropathol 1989;79:271–278. Halperin J, Luft BJ, Volkman DJ, Dattwyler RJ. Lyme neuroborreliosis: peripheral nervous system manifestations. Brain 1990;113:1207–1221. Halperin JJ, Little BW, Coyle PK, Dattwyler RJ. Lyme disease: cause of a treatable peripheral neuropathy. Neurology 1987;37:1700–1706. Logigian EL, Kaplan RF, Steere AC. Chronic neurologic manifestations of Lyme disease. N Engl J Med 1990;323: 1438–1444. Logigian EL. Peripheral nervous system Lyme borreliosis. Semin Neurol 1997;17:25–30.

hood prior to the diagnosis of PD. No changes of tics were noticed following the onset of PD or dopaminergic medication. No treatment for tics was ever prescribed. Prior to surgery he had motor and phonic tics and compulsion of checking that doors were locked. A single exon 5 deletion in the parkin gene was detected. Quadripolar 3389 DBS electrodes (Medtronic, Minneapolis, MN) were implanted bilaterally in the STN under local anesthesia and connected a few days later to a pulse generator (Kinetra威, Medtronic). The position of each electrode’s contact was calculated using preoperative and postoperative stereotactic MRI and the software Framelink (Medtronic). The active contacts were located in the dorsal tip of the STN on the left side and adjacent to the medial border of the center of the STN on the right. Stimulation was monopolar with pulse width 60 ␮sec and frequency 130 Hz. AmpliNeurology 72

May 19, 2009

1787

Table

UPDRS motor part scores and tics quantification Postoperative Preoperative

UPDRS III

OffM/OnS

OffM/OffS

OnM/OnS

OnM/OffS

OffM

OnM

6 mo

1y

6 mo

1y

6 mo

1y

6 mo

1y

49

19

17

21

43

57

11

10

NA

NA

160/43

173/91

15/8

5/0

65/6

47/1

33/21

12/3

52/9

47/2

203

264

23

5

71

48

54

15

61

49

Tics* Motor/phonic Total

The table shows the clinical scores of the Unified Parkinson’s Disease Rating Scale (UPDRS) motor part and tics quantification, counted on a 10-minute videotape preoperatively and at 6 months and 1 year after DBS. Postoperatively, parkinsonian symptoms and tics were assessed in different conditions of medication and stimulation. Off-medication was defined by 1 night of dopaminergic medication withdrawal. Off-stimulation assessments were done after 15 minutes of turning the stimulation off. *10-minute videotape (5 min observed/5 min unobserved) for each condition following the rush video protocol. OffM ⫽ off medication; OnM ⫽ on medication; OnS ⫽ on stimulation; OffS ⫽ off stimulation; NA ⫽ not available.

tude was progressively increased over time to 3.0 volts for the left STN and 3.2 for the right, in parallel with a reduction in dopaminergic medication. The patient reported a subjective amelioration of tics before stimulation was started. An improvement of both tics and parkinsonian symptoms was observed once the stimulation was initiated. At 1 year, STN DBS produced a 57% improvement in the motor part of the Unified Parkinson’s Disease Rating Scale and allowed a 56% reduction in dopaminergic medication dosage. Tics frequency diminished by 89% at 6 months and 97% at 1 year, counted on a 10minute videotape by a blinded investigator. Switching off the stimulation produced an immediate increase in tic frequency (table). The compulsion improved but did not resolve completely. Discussion. Coexistence of TS and PD has previously been described, with the evolution of PD or dopaminergic medication having variable effects on TS manifestations.4 Although the more than 50% reduction in dopaminergic medication could in part explain the improvement of tics, the immediate deterioration in tics frequency after switching off the stimulation suggests a direct impact of STN stimulation. The remaining improvement observed in the off-stimulation assessment compared to preoperative could be explained by a long-term tic-suppressant effect of STN DBS, as stimulation was left off only for 15 minutes. A microlesion effect could account for the amelioration reported by the patient prior to stimulation onset. From a physiologic perspective, STN occupies a privileged position influencing both output nuclei of the basal ganglia, GPi and substantia nigra (SN) reticulata. Several findings link the STN with behavioral changes that may improve with 1788

Neurology 72

May 19, 2009

STN-DBS.3 Franc¸ois et al.5 found that stereotyped behaviors in nonhuman primates, resembling tics and compulsive disorders, were related to dysfunction of the limbic parts of the globus pallidus externus, the STN, and the SN reticulata, rather than to dysfunction of the GPi. Involvement of the SN in TS was also found in a functional MRI study.6 Furthermore, stimulation of the anterior STN was effective in reducing stereotypes in a primate model of behavioral disorder7 and STN DBS in PD can also result in behavioral changes. Indeed, the small size of this nucleus may allow modulation of abnormal neuronal activity of both limbic and sensorimotor territories, more easily than GPi or thalamic DBS. This report suggests that the STN may be a potential target for DBS in TS. STN-DBS would allow modulation of both limbic and sensorimotor territories and may provide a quicker relief of symptoms than medial thalamic nuclei or GPi stimulation. From the Unit of Functional Neurosurgery, Sobell Department of Motor Neuroscience and Movement Disorders, Institute of Neurology, UCL, Queen Square, London, UK. The University College London Hospitals and University College London (UCLH/UCL) receive a proportion of funding from the Department of Health’s National Institute for Health Research (NIHR) Biomedical Research Centres funding scheme. The Unit of Functional Neurosurgery is supported by the Parkinson’s Appeal. I.M.T. is supported by a Postgraduated Grant of the Fundacion Caja Madrid. Disclosure: The authors report no disclosures. Medical Devices: Pulse generator (Kinetra威) and quadripolar 3389 DBS electrodes (Medtronic, Minneapolis, MN). Received October 2, 2008. Accepted in final form January 30, 2009. Address correspondence and reprint requests to Dr. Irene MartinezTorres, 33 Queen Square, Box 146, WC1N 3BG, London, UK; [email protected] Copyright © 2009 by AAN Enterprises, Inc.

1.

2.

3.

4.

Ackermans L, Temel Y, Visser-Vandewale V. Deep brain stimulation in Tourette’s syndrome. Neurotherapeutics 2008;5:339–344. Welter ML, Mallet L, Houeto JL, et al. Internal pallidal and thalamic stimulation in patients with Tourette syndrome. Arch Neurol 2008;65:952–957. Mallet L, Polosan M, Nermatollah J, et al. Subthalamic nucleus stimulation in severe obsessive-compulsive disorder. N Engl J Med 2008;359:2121–2134. Kumar R, Lang AE. Coexistence of tics and parkinsonism: evidence for non-dopaminergic mechanism in tic pathogenesis. Neurology 1997;49:1699–1701.

5.

6.

7.

Franc¸ois C, Grabli D, McCairn K, et al. Behavioural disorders induced by external globus pallidus dysfunction in primates II: anatomical study. Brain 2004;127: 2055–2070. Bohlhalter S, Goldfine A, Matteson S, et al. Neuronal correlates of tic generation in Tourette syndrome: an event-related functional MRI study. Brain 2006;129: 2029–2037. Baup N, Grabli D, Karachi C, et al. High-frequency stimulation of the anterior subthalamic nucleus reduces stereotypes behaviours in primates. J Neurosci 2008;27: 8785–8788.

Editor’s Note to Authors and Readers: Levels of Evidence coming to Neurology® Effective January 15, 2009, authors submitting Articles or Clinical/Scientific Notes to Neurology® that report on clinical therapeutic studies must state the study type, the primary research question(s), and the classification of level of evidence assigned to each question based on the classification scheme requirements shown below (left). While the authors will initially assign a level of evidence, the final level will be adjudicated by an independent team prior to publication. Ultimately, these levels can be translated into classes of recommendations for clinical care, as shown below (right). For more information, please access the articles and the editorial on the use of classification of levels of evidence published in Neurology.1-3 REFERENCES 1. French J, Gronseth G. Lost in a jungle of evidence: we need a compass. Neurology 2008;71:1634 –1638. 2. Gronseth G, French J. Practice parameters and technology assessments: what they are, what they are not, and why you should care. Neurology 2008;71:1639 –1643. 3. Gross RA, Johnston KC. Levels of evidence: taking Neurology® to the next level. Neurology 2008;72:8 –10.

Neurology 72

May 19, 2009

1789

Clinical/Scientific Notes

Suraj Ashok Muley, MD Gareth J. Parry, MD

ANTIBIOTIC RESPONSIVE DEMYELINATING NEUROPATHY RELATED TO LYME DISEASE

Neuropathies that occur in the context of Lyme disease are commonly related to axonal degeneration.1 Acute demyelinating neuropathy has also been described2 and the possibility of chronic demyelinating neuropathy (CDN) has been raised.3 We report a patient who developed a demyelinating neuropathy in the context of Lyme disease. Treatment of the infection led to marked clinical and electrophysiologic recovery, suggesting an infectious rather than an immune-mediated pathogenesis. Case report. A 56-year-old Caucasian man developed numbness and tingling in his feet in August 2002 that within a few days spread symmetrically to the fingertips and hands. He reported weakness with heavy manual labor over the ensuing 8 weeks. He denied ataxia, cranial nerve, respiratory, or autonomic symptoms. There was no history of diabetes, thyroid disease, or renal disease. There was no exposure to toxins, chemicals, or tick bites. Family history was unremarkable and there was no history of tobacco or alcohol abuse. Cranial nerve examination was normal. Motor examination revealed normal strength in shoulder abduction and elbow flexion bilaterally but strength was Medical Research Council (MRC) grade 4 in elbow extension, wrist extension, and finger extension. In the legs, there was weakness only in bilateral hip flexion (MRC 4). He was globally areflexic with downgoing toes. Sensation to temperature, pinprick, and light touch was reduced up to the knees on both sides. Proprioception was normal but vibratory perception was reduced at the toes and ankles. Coordination, gait, and Romberg test were unremarkable. Complete blood count, serum immunofixation, erythrocyte sedimentation rate, and anti-ENA, GM-1, GD-1b, SGPG, MAG, sulfatide, GALOP, and Hu antibodies were negative. Serum Lyme ELISA, western blot (by Centers for Disease Control and Prevention criteria), and CSF Lyme titer were positive; with ELISA, immunoglobulin G (IgG) titer was 1.2 (positive ⬎1.09), IgM was negative, and with western blot six IgG bands (18, 39, 41, 58, 66, 93) were seen. CSF revealed one erythrocyte, two

1786

Neurology 72

May 19, 2009

leukocytes, and protein of 67 mg/dL but IgG index and IgG synthesis rate were normal. No oligoclonal bands were identified. Nerve conduction studies showed conduction slowing and abnormal temporal dispersion consistent with an acquired demyelinating neuropathy (table). EMG of muscles of the left arm and leg was normal without evidence of denervation. The patient was treated with ceftriaxone for 4 weeks beginning 8 weeks after the onset of symptoms. After completion of his antibiotic treatment he reported marked improvement in his symptoms over a few days; the extent and severity of numbness had regressed and weakness had resolved. Examination revealed normal strength with hypesthesia to the mid-calf level. Ankle reflexes were absent, knee reflexes were reduced, and reflexes had returned to normal in the arms. Electrophysiologic studies had also returned to normal apart from persistent prolongation of distal motor latencies; conduction slowing, temporal dispersion, and prolongation of F latencies had resolved (table). CSF analysis revealed no cells. CSF protein and glucose were both 53 mg/dL. CSF Lyme IgG and IgM titers were negative. The patient remains symptom-free at the current time, more than 5 years since the initial presentation, suggesting that the illness was monophasic. Discussion. The clinical picture of diffuse areflexia, progressive weakness and numbness, CSF protein elevation, and severe slowing in nerve conduction velocities was diagnostic of a demyelinating neuropathy. Whether the neuropathy was a form of chronic inflammatory demyelinating polyneuropathy (CIDP) or a monophasic acute neuropathy such as Guillain-Barre´ syndrome (GBS) was not clear. Our impression was that the neuropathy was more consistent with CIDP than with GBS, given that Inflammatory Neuropathy Cause and Treatment (INCAT) criteria for CIDP were met. Although the possibility of an infection having triggered an immune response cannot be ruled out, the fact that weakness, sensory loss, and electrophysiologic changes reversed with antibiotic treatment alone (without immunosuppression) suggests that

Table

Electrophysiology Distal latency (msec)

Amplitude (mV)

Conduction velocity (m/s)

F wave latency (msec)

Before treatment Motor nerve Left median

7.3

2.4 (TD)

39.5

33.8

Left ulnar

4.6

5.04 (TD)

41

38.3

14.5

1.77 (TD)

41.5

Not done

5.1

2.93 (TD)

37.5

Not done

Right sural

5.93 ␮V

36.8

Left ulnar

No response

Left median

No response

Right median Right ulnar Sensory nerve

After treatment Left median

4.6

8.3

53.1

29.8

Left ulnar

3.8

8.1

52.6

30.3

Right median

5.6

6.09

52.1

Not done

Right ulnar

4.2

7.62

60

Not done

Left peroneal

5

5.88

52.5

Not done

TD ⫽ temporal dispersion.

From the Department of Neurology, University of Minnesota. Disclosure: The authors report no disclosures. Received November 14, 2008. Accepted in final form January 26, 2009. Address correspondence and reprint requests to Dr. Suraj Ashok Muley, Associate Professor of Neurology, University of Minnesota, 420 Delaware St. SE, Minneapolis, MN 55455; [email protected] Copyright © 2009 by AAN Enterprises, Inc. ACKNOWLEDGMENT The authors thank Sandra Hanson, MD, Park Nicollet Clinic, Minneapolis, MN.

1.

the neuropathy was probably directly related to Borrelia infection, rather than to an immune-mediated process. Similar improvement with antibiotic treatment has also been described in the distal symmetric neuropathy that occurs with chronic Lyme infection.4,5 Demyelinating neuropathy in the context of Lyme disease has not been well documented. Severe conduction slowing and conduction block consistent with chronic demyelination in a patient with Lyme

I. Martinez-Torres, MD M.I. Hariz, MD, PhD L. Zrinzo, MD, MSc, FRCS(Ed) T. Foltynie, MRCP, PhD P. Limousin, MD, PhD

infection and two other patients with possible acute demyelinating neuropathy have been described.2,3 It is unclear whether those patients responded to immunosuppression or to treatment of the infection. Our case indicates that a demyelinating neuropathy occurs with chronic Borrelia infection and provides a rationale for routine Lyme testing in such patients. Unlike the immune-mediated demyelinating neuropathies, it responds to antibiotic therapy. Early recognition is important given the excellent response to treatment.

IMPROVEMENT OF TICS AFTER SUBTHALAMIC NUCLEUS DEEP BRAIN STIMULATION

Deep brain stimulation (DBS) of the medial thalamic nuclei and globus pallidus internus (GPi)1,2 has been tried in the treatment of medically refractory Tourette syndrome (TS). Subthalamic nucleus (STN) is the target most commonly used for DBS in Parkinson disease (PD). A double-blind randomized study has shown the efficacy of STN-DBS in obsessive compulsive disorder (OCD),3 which is considered within the spectrum of TS. We report a patient with PD who also had a history of TS in whom bilateral STN-DBS improved both PD and tics. Case report. A 38-year-old man with an 8-year history of PD was referred for DBS consideration. He had a history of tics that began at the age of 7 and improved by the age of 12. Tics increased in adult-

2.

3.

4.

5.

Meier C, Grahmann F, Engelhardt A, Dumas M. Peripheral nerve disorders in Lyme borreliosis: nerve biopsy studies from eight cases. Acta Neuropathol 1989;79:271–278. Halperin J, Luft BJ, Volkman DJ, Dattwyler RJ. Lyme neuroborreliosis: peripheral nervous system manifestations. Brain 1990;113:1207–1221. Halperin JJ, Little BW, Coyle PK, Dattwyler RJ. Lyme disease: cause of a treatable peripheral neuropathy. Neurology 1987;37:1700–1706. Logigian EL, Kaplan RF, Steere AC. Chronic neurologic manifestations of Lyme disease. N Engl J Med 1990;323: 1438–1444. Logigian EL. Peripheral nervous system Lyme borreliosis. Semin Neurol 1997;17:25–30.

hood prior to the diagnosis of PD. No changes of tics were noticed following the onset of PD or dopaminergic medication. No treatment for tics was ever prescribed. Prior to surgery he had motor and phonic tics and compulsion of checking that doors were locked. A single exon 5 deletion in the parkin gene was detected. Quadripolar 3389 DBS electrodes (Medtronic, Minneapolis, MN) were implanted bilaterally in the STN under local anesthesia and connected a few days later to a pulse generator (Kinetra威, Medtronic). The position of each electrode’s contact was calculated using preoperative and postoperative stereotactic MRI and the software Framelink (Medtronic). The active contacts were located in the dorsal tip of the STN on the left side and adjacent to the medial border of the center of the STN on the right. Stimulation was monopolar with pulse width 60 ␮sec and frequency 130 Hz. AmpliNeurology 72

May 19, 2009

1787

Table

UPDRS motor part scores and tics quantification Postoperative Preoperative

UPDRS III

OffM/OnS

OffM/OffS

OnM/OnS

OnM/OffS

OffM

OnM

6 mo

1y

6 mo

1y

6 mo

1y

6 mo

1y

49

19

17

21

43

57

11

10

NA

NA

160/43

173/91

15/8

5/0

65/6

47/1

33/21

12/3

52/9

47/2

203

264

23

5

71

48

54

15

61

49

Tics* Motor/phonic Total

The table shows the clinical scores of the Unified Parkinson’s Disease Rating Scale (UPDRS) motor part and tics quantification, counted on a 10-minute videotape preoperatively and at 6 months and 1 year after DBS. Postoperatively, parkinsonian symptoms and tics were assessed in different conditions of medication and stimulation. Off-medication was defined by 1 night of dopaminergic medication withdrawal. Off-stimulation assessments were done after 15 minutes of turning the stimulation off. *10-minute videotape (5 min observed/5 min unobserved) for each condition following the rush video protocol. OffM ⫽ off medication; OnM ⫽ on medication; OnS ⫽ on stimulation; OffS ⫽ off stimulation; NA ⫽ not available.

tude was progressively increased over time to 3.0 volts for the left STN and 3.2 for the right, in parallel with a reduction in dopaminergic medication. The patient reported a subjective amelioration of tics before stimulation was started. An improvement of both tics and parkinsonian symptoms was observed once the stimulation was initiated. At 1 year, STN DBS produced a 57% improvement in the motor part of the Unified Parkinson’s Disease Rating Scale and allowed a 56% reduction in dopaminergic medication dosage. Tics frequency diminished by 89% at 6 months and 97% at 1 year, counted on a 10minute videotape by a blinded investigator. Switching off the stimulation produced an immediate increase in tic frequency (table). The compulsion improved but did not resolve completely. Discussion. Coexistence of TS and PD has previously been described, with the evolution of PD or dopaminergic medication having variable effects on TS manifestations.4 Although the more than 50% reduction in dopaminergic medication could in part explain the improvement of tics, the immediate deterioration in tics frequency after switching off the stimulation suggests a direct impact of STN stimulation. The remaining improvement observed in the off-stimulation assessment compared to preoperative could be explained by a long-term tic-suppressant effect of STN DBS, as stimulation was left off only for 15 minutes. A microlesion effect could account for the amelioration reported by the patient prior to stimulation onset. From a physiologic perspective, STN occupies a privileged position influencing both output nuclei of the basal ganglia, GPi and substantia nigra (SN) reticulata. Several findings link the STN with behavioral changes that may improve with 1788

Neurology 72

May 19, 2009

STN-DBS.3 Franc¸ois et al.5 found that stereotyped behaviors in nonhuman primates, resembling tics and compulsive disorders, were related to dysfunction of the limbic parts of the globus pallidus externus, the STN, and the SN reticulata, rather than to dysfunction of the GPi. Involvement of the SN in TS was also found in a functional MRI study.6 Furthermore, stimulation of the anterior STN was effective in reducing stereotypes in a primate model of behavioral disorder7 and STN DBS in PD can also result in behavioral changes. Indeed, the small size of this nucleus may allow modulation of abnormal neuronal activity of both limbic and sensorimotor territories, more easily than GPi or thalamic DBS. This report suggests that the STN may be a potential target for DBS in TS. STN-DBS would allow modulation of both limbic and sensorimotor territories and may provide a quicker relief of symptoms than medial thalamic nuclei or GPi stimulation. From the Unit of Functional Neurosurgery, Sobell Department of Motor Neuroscience and Movement Disorders, Institute of Neurology, UCL, Queen Square, London, UK. The University College London Hospitals and University College London (UCLH/UCL) receive a proportion of funding from the Department of Health’s National Institute for Health Research (NIHR) Biomedical Research Centres funding scheme. The Unit of Functional Neurosurgery is supported by the Parkinson’s Appeal. I.M.T. is supported by a Postgraduated Grant of the Fundacion Caja Madrid. Disclosure: The authors report no disclosures. Medical Devices: Pulse generator (Kinetra威) and quadripolar 3389 DBS electrodes (Medtronic, Minneapolis, MN). Received October 2, 2008. Accepted in final form January 30, 2009. Address correspondence and reprint requests to Dr. Irene MartinezTorres, 33 Queen Square, Box 146, WC1N 3BG, London, UK; [email protected] Copyright © 2009 by AAN Enterprises, Inc.

1.

2.

3.

4.

Ackermans L, Temel Y, Visser-Vandewale V. Deep brain stimulation in Tourette’s syndrome. Neurotherapeutics 2008;5:339–344. Welter ML, Mallet L, Houeto JL, et al. Internal pallidal and thalamic stimulation in patients with Tourette syndrome. Arch Neurol 2008;65:952–957. Mallet L, Polosan M, Nermatollah J, et al. Subthalamic nucleus stimulation in severe obsessive-compulsive disorder. N Engl J Med 2008;359:2121–2134. Kumar R, Lang AE. Coexistence of tics and parkinsonism: evidence for non-dopaminergic mechanism in tic pathogenesis. Neurology 1997;49:1699–1701.

5.

6.

7.

Franc¸ois C, Grabli D, McCairn K, et al. Behavioural disorders induced by external globus pallidus dysfunction in primates II: anatomical study. Brain 2004;127: 2055–2070. Bohlhalter S, Goldfine A, Matteson S, et al. Neuronal correlates of tic generation in Tourette syndrome: an event-related functional MRI study. Brain 2006;129: 2029–2037. Baup N, Grabli D, Karachi C, et al. High-frequency stimulation of the anterior subthalamic nucleus reduces stereotypes behaviours in primates. J Neurosci 2008;27: 8785–8788.

Editor’s Note to Authors and Readers: Levels of Evidence coming to Neurology® Effective January 15, 2009, authors submitting Articles or Clinical/Scientific Notes to Neurology® that report on clinical therapeutic studies must state the study type, the primary research question(s), and the classification of level of evidence assigned to each question based on the classification scheme requirements shown below (left). While the authors will initially assign a level of evidence, the final level will be adjudicated by an independent team prior to publication. Ultimately, these levels can be translated into classes of recommendations for clinical care, as shown below (right). For more information, please access the articles and the editorial on the use of classification of levels of evidence published in Neurology.1-3 REFERENCES 1. French J, Gronseth G. Lost in a jungle of evidence: we need a compass. Neurology 2008;71:1634 –1638. 2. Gronseth G, French J. Practice parameters and technology assessments: what they are, what they are not, and why you should care. Neurology 2008;71:1639 –1643. 3. Gross RA, Johnston KC. Levels of evidence: taking Neurology® to the next level. Neurology 2008;72:8 –10.

Neurology 72

May 19, 2009

1789

NEUROIMAGES

Autosomal recessive spastic ataxia of Charlevoix-Saguenay

Figure 1

Atrophy of the vermis, mainly of the upper part on a T2-weigthed image (A, arrow), and linear hypointensities in the pons on fluidattenuated inversion recovery image (B, arrow)

Figure 2

A 40-year-old woman with delayed motor milestones and high arches since childhood was investigated for a progressive gait disorder from the age of 24 years. On clinical examination, a spastic and ataxic gait was present, with mild ataxia in upper limbs, dysarthria, and nystagmus. Nerve conduction study/EMG revealed a demyelinating neuropathy. MRI of the brain (figure 1) and fundus photography (figure 2) suggested autosomal recessive spastic ataxia of Charlevoix-Saguenay (ARSACS)1 and the diagnosis was genetically confirmed.2 The combination of spinocerebellar ataxia with demyelinating neuropathy, superior vermis atrophy, and pontine linear hypointensities should prompt the diagnosis of ARSACS, which may be an underdiagnosed condition outside Quebec.

Color (A) and black and white (B) picture of fundus revealing hypermyelinated fibers in the retina, which are present in some cases of autosomal recessive spastic ataxia of Charlevoix-Saguenay

Philip Van Damme, MD, PhD, Philippe Demaerel, MD, PhD, Werner Spileers, MD, PhD, Wim Robberecht, MD, PhD, Leuven, Belgium Disclosure: The authors report no disclosures. Address correspondence and reprint requests to Dr. Philip Van Damme, Neurology Department, U.Z. Leuven, Herestraat 49, 3000 Leuven, Belgium; [email protected] 1. 2.

1790

Martin MH, Bouchard JP, Sylvain M, St-Onge O, Truchon S. Autosomal recessive spastic ataxia of Charlevoix-Saguenay: a report of MR imaging in 5 patients. AJNR Am J Neuroradiol 2007;28:1606–1608. Engert JC, Berube P, Mercier J, et al. ARSACS, a spastic ataxia common in northeastern Quebec, is caused by mutations in a new gene encoding an 11.5-kb ORF. Nat Genet 2000;24:120–125.

Copyright © 2009 by AAN Enterprises, Inc.

RESIDENT & FELLOW SECTION Section Editor Mitchell S.V. Elkind, MD, MS

Carsten Finke, MD Christoph J. Ploner, MD

Address correspondence and reprint requests to Dr. Carsten Finke, Department of Neurology, Charite´-Universita¨tsmedizin Berlin, Campus Charite´ Mitte, Charite´platz 1, D-10117 Berlin, Germany [email protected]

Pearls & Oy-sters: Vestibular neuritis or not? The significance of head tilt in a patient with rotatory vertigo

The ocular tilt reaction (OTR) is a central vestibular disorder that is characterized by the triad of head tilt, skew deviation, and ocular torsion. CLINICAL PEARL

As the OTR frequently shows an incomplete manifestation, a head tilt can be the only apparent clinical sign of significant brainstem disorders. Hence, even a slight head tilt should be thoroughly investigated.

CLINICAL OY-STER

A 48-year-old man presented after sudden onset of a severe, persistent rotatory vertigo associated with nausea, vomiting, and postural imbalance. Examination revealed a horizontaltorsional spontaneous nystagmus with the quick phases beating to the right ear. The nystagmus was attenuated by fixation as examined by Frenzel goggles. Head impulse test was positive to the left. When attempting to walk and during Romberg testing he fell to his left side. Except for a head tilt to the right (see video on the Neurology® Web site at www. neurology.org), no other neurologic deficit was observed. The patient’s medical history revealed no neurologic disorders. Quantitative caloric testing showed a canal paresis of the left vestibular organ. Taken together, the initial clinical presentation was highly suggestive of a left vestibular neuritis. However, due to the head tilt, an extended neuroophthalmologic examination was performed that revealed a discrete but complete OTR to the right with head tilt, mild skew deviation (2° left hypertropia), ocular torsion (right eye excyclotropia 4°, left eye no cyclotropia), and a tilt of the subjective visual vertical to the right (right eye 7° to the right, left eye 4° to the right). In contrast to the sparse clinical signs, cerebrospinal MRI showed multiple T2-hyperintense lesions of the right dorsolateral medulla oblongata, left mesencephalon, right medial cerebellar peduncle, corpus callosum, pericallosal white matter, and three lesions in the spinal cord. Reconstruction of the lesion of the CASE REPORT

dorsolateral medulla oblongata according to the atlas of Paxinos and Huang1 revealed damage to the right spinal, medial, superior, and lateral vestibular nuclei. Reconstruction of the mesencephalic lesion showed involvement of the left interstitial nucleus of Cajal (INC) (figure). No further brainstem lesions were observed. No enhancement of the eighth cranial nerve, as occasionally described for vestibular neuritis,2 was seen. CSF analysis revealed no pleocytosis and normal protein, glucose, and lactate, but oligoclonal bands in CSF only. Visual evoked potentials (VEP) showed a delayed P100 on the left. The cerebrospinal lesion pattern, the inflammatory CSF changes, and the abnormal VEP were suggestive of a demyelinating process. According to the revised McDonald Criteria, a clinically isolated syndrome (CIS) was diagnosed and treatment with IV steroids was initiated. On follow-up 4 weeks later, the patient had recovered from vertigo and nausea and had no nystagmus on examination. However, the head tilt to the right persisted. MRI showed no new lesions. Seven months later, the head tilt was still detectable, but neuroophthalmologic examination showed only a slight tilt of the subjective visual vertical to the right (both eyes 2°) and no skew deviation or ocular torsion. Cerebrospinal MRI showed no new lesions. The clinical presentation comprised a left peripheral vestibular syndrome suggestive of vestibular neuritis and a right central vestibular syndrome manifesting as OTR. The latter is characterized by the triad of head tilt, skew deviation, and ocular torsion.3 Additionally, a tilt of subjective visual vertical (SVV) is observed. The head is tilted toward the lower eye. Ocular torsion manifests as incyclotropia of the upper eye and excyclotropia of the lower eye, i.e., the upper poles of the eyes rotate toward the lower ear. Pathogenetic substrate is a vestibular tone imbalance caused by unilateral lesions of the graviceptive vestibular pathways that run from the otoliths and the vertical semicircular canals to the ocular motor nuclei and the rostral integration centers for

Supplemental data at www.neurology.org From the Department of Neurology, Charite´-Universita¨tsmedizin Berlin, Germany. Disclosure: The authors report no disclosures. Copyright © 2009 by AAN Enterprises, Inc.

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Figure

Cerebral MRI revealing (A) a left mesencephalic lesion affecting the interstitial nucleus of Cajal and (B) T2-hyperintense lesions of the right dorsolateral medulla oblongata affecting the spinal, medial, superior, and lateral vestibular nuclei

vertical and torsional eye movements (INC and riMLF). They also provide input to vestibular thalamic nuclei and cortical areas involved in perception of verticality.4 Altogether, lesions of these projections lead to the clinical syndrome involving ocular motor (ocular torsion, skew deviation), perceptual (SVV tilt), and postural (head tilt) dysfunction. As the graviceptive vestibular pathways cross at a lower pontine level, direction of the ocular tilt reaction holds a clinically relevant topographic value: with peripheral and pontomedullary lesions below the crossing all tilt effects (ocular motor, perceptual, and postural) are ipsiversive, i.e., the ipsilateral eye is undermost. With pontomesencephalic lesions all tilt effects are contraversive, i.e., the contralateral eye is undermost. Hence, the OTR to the right in our patient cannot be explained by a left-sided peripheral vestibular syndrome but must rather be attributed to the lesion of the vestibular nuclei in the right dorsolateral medulla or to the lesion of the INC in the left mesencephalon. As pontomedullary lesions typically cause a disconjugated ocular torsion and pontomesencephalic lesions, a conjugated ocular torsion,5 damage to the vestibular nuclei appears to be the cause of OTR in our patient. The two vestibular syndromes that differ in localization (peripheral vs central) and side (right vs left) could point to separate pathogenetic mechanisms, i.e., an inflammatory brainstem lesion and an incidental left peripheral vestibular neuritis. Alternatively, the peripheral vestibular syndrome may have resulted from a MRI-negative plaque at the root entry zone of the left eighth nerve causing a vestibular pseudoneuritis.6 Such a strategically localized lesion causes a vestibular syndrome mimicking vestibular neuritis in clinical presentation and calorimetric testing. However, there is no means to reliably differentiate between these two possibilities.

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Recently, the reliability of clinical examination in the differentiation of vestibular neuritis from vestibular pseudoneuritis was investigated.7 It was shown that single clinical signs provide only limited sensitivity and specificity, except for skew deviation that indicated a vestibular pseudoneuritis with a high specificity. In our case, the key for the diagnosis of a central vestibular syndrome in addition to the obvious peripheral vestibular syndrome lay in recognizing the head tilt to the right side as an incompatible component of a left peripheral vestibular syndrome. Recognizing this incompatibility and consequently assuming an additional vestibular disease called for further investigations that finally led to the correct diagnosis. ACKNOWLEDGMENT The authors thank Dr. Juri Katchanov for recording the patient video.

REFERENCES 1. Atlas of the Human Brainstem. San Diego: Academic Press; 1995. 2. Brodsky MC, Donahue SP, Vaphiades M, Brandt T. Skew deviation revisited. Surv Ophthalmol 2006;51:105–128. 3. Rabinovitch HE, Sharpe JA, Sylvester TO. The ocular tilt reaction: a paroxysmal dyskinesia associated with elliptical nystagmus. Arch Ophthalmol 1977;95:1395–1398. 4. Brandt T, Dieterich M. Vestibular syndromes in the roll plane: topographic diagnosis from brainstem to cortex. Ann Neurol 1994;36:337–347. 5. Brandt T, Dieterich M. Skew deviation with ocular torsion: a vestibular brainstem sign of topographic diagnostic value. Ann Neurol 1993;33:528–534. 6. Thomke F, Hopf HC. Pontine lesions mimicking acute peripheral vestibulopathy. J Neurol Neurosurg Psychiatry 1999;66:340–349. 7. Cnyrim CD, Newman-Toker D, Karch C, Brandt T, Strupp M. Bedside differentiation of vestibular neuritis from central “vestibular pseudoneuritis.” J Neurol Neurosurg Psychiatry 2008;79:458–460.

RESIDENT & FELLOW SECTION Section Editor Mitchell S.V. Elkind, MD, MS

I. Yabe, MD, PhD H. Nishimura, MD S. Tsuji-Akimoto, MD, PhD M. Niino, MD, PhD H. Sasaki, MD, PhD

Teaching NeuroImages: Lumbar nerve roots metastasis from prostatic adenocarcinoma Figure

Lumbar nerve roots metastasis from prostatic adenocarcinoma

Address correspondence and reprint requests to Dr. Ichiro Yabe, Department of Neurology, Hokkaido University Graduate School of Medicine, N15 W7 Kita-ku, Sapporo 060-8638, Japan [email protected]

(A) T1-weighted gadolinium-enhanced MRI demonstrating abnormally swollen L4 and L5 nerve roots on the left (arrow). (B) Fludeoxyglucose-PET showed abnormal uptake (standardized uptake value; 4.11) in L4 and L5 nerve roots (circle). (C) Immunostaining by prostate-specific antigen (PSA) antibody showed PSA-positive malignant cells (⫻1,000).

A 74-year-old man had radiculitis in the left lower extremity for 1 year. He had undergone radical prostatectomy for prostatic adenocarcinoma 8 years previously. MRI and fludeoxyglucose (FDG)-PET

revealed abnormal swelling and FDG uptake in the left L4 and L5 nerve roots without other systemic metastases (figure, A and B). Although CSF was normal except for high prostate-specific antigen level,

From the Department of Neurology, Hokkaido University Graduate School of Medicine, Sapporo, Japan. Disclosure: The authors report no disclosures. Copyright © 2009 by AAN Enterprises, Inc.

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metastatic prostate carcinoma was diagnosed via needle biopsy as diagnosis with CSF was not routinely performed1 (figure, C). He was treated with luteinizing hormone-releasing hormone agonist without deterioration. Lumbar nerve roots metastasis should be considered in patients with a history of prostate cancer and radicular symptoms.2

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REFERENCES 1. Orphanos G, Ioannidis G, Michael M, Kitrou G. Prostatespecific antigen in the cerebrospinal fluid: a marker of local disease. Med Oncol Epub 2008 Oct 2. 2.

Ladha SS, Spinner RJ, Suarez GA, Amrami KK, Dyck PJ. Neoplastic lumbosacral radiculoplexopathy in prostate cancer by direct perineural spread: an unusual entity. Muscle Nerve 2006;34:659–665.

Correspondence

QUANTITATIVE RISK-BENEFIT ANALYSIS OF NATALIZUMAB

To the Editor: I read with interest the analysis by Thompson et al.1 that assessed the risks and benefits of natalizumab in relapsing multiple sclerosis (MS). The study is based on an incorrect assumption and does not consider another fatal complication besides progressive multifocal leukoencephalopathy (PML). Following reports of the development of PML under natalizumab therapy, it is currently approved in a subgroup of patients with MS who “have had an inadequate response to, or are unable to tolerate, alternate therapies.”2 However, this indication is based on the observed effect of natalizumab in two studies that did not examine its impact in the selective subgroup of patients with MS who already had not responded to immunosuppressive therapy.3 Ironically, it seems that natalizumab is indicated for a clinical setting in which it was not tested. The current therapeutic approach in MS is based on the unproven assumption that relapses in MS are due to acute CNS inflammation and therefore immunomodulating or immunosuppressive therapies are aimed at preventing the immune response. The hypothesis that an immunosuppressive agent will work where others have failed requires proof. If MS is a syndrome and not a single disease entity, failure to respond to several immunomodulating therapies may render the usage of another agent futile.4 Thus, extrapolating the findings observed in previous studies to this analysis is irrelevant to the current indications of natalizumab use and therefore cannot be used in the proposed model. Natalizumab has been associated with a fatal case of herpes encephalitis, herpes meningitis,5 several cases of recurrent herpes zoster, and herpes labialis.6 Consequently, another potential fatal complication of natalizumab was not discussed in this analysis. Israel Steiner, Jerusalem, Israel Disclosure: The author reports no disclosures.

Reply from the Authors: We thank Dr. Steiner for his interest in our work. His first point regarding the inconsistency between the AFFIRM trial population and the subpopulation of patients with MS

most likely to be treated with natalizumab is an acknowledged limitation to our model. Only a well-designed trial can definitively assess the effects of natalizumab in the subpopulation of patients for which it is indicated. However, US Food and Drug Administration approval of natalizumab for patients not responding to other therapies indicates that they accept similar efficacy between this subpopulation and the original trial participants. In our model, we assessed cohorts with increased baseline disability and increased risk of disability progression and found that those factors did not significantly change the results. We prefer this approach rather than stating that existing data are inadequate. We also agree with Dr. Steiner that there may be new information about the risks of natalizumab arising over time. However, while Dr. Steiner considers this a weakness of our model, we consider it a strength. An advantage of this model is that it can accommodate new risk information as it emerges, whether it is to refine PML risk (now estimated to be 2 per 6,600 patients treated over 18 months or more7) or to incorporate new risks (e.g., the development of other serious infectious complications such as herpes encephalitis). We believe that our model can help clinicians, patients, and regulators incorporate this new information into their decision-making. R.G. Holloway, J.P. Thompson, K. Noyes, E.R. Dorsey, S.R. Schwid, Rochester, NY Disclosure: K.N., R.G.H., and S.R.S. were supported in part by contract HC0071 from the National Multiple Sclerosis Society. K.N. was supported in part by research grant K01 AG 20980 from the National Institute on Aging. E.R.D. was supported in part by an American Academy of Neurology Clinical Research Training Fellowship. R.G.H. was supported in part by grant K24 NS4 2098 from the National Institute of Neurological Disorders and Stroke. S.R.S. has received research funding from Biogen, Serono, and Teva and honoraria for educational and consulting activities from Berlex, Biogen, Serono, and Teva. The project described was partially supported by grant number 1 UL1 RR024160 – 01 from the National Center for Research Resources (NCRR), a component of the NIH and the NIH Roadmap for Medical Research, and its contents are solely the responsibility of the authors and do not necessarily represent the official view of NCRR or NIH. Information on NCRR is available at http://www.ncrr.nih.gov/. Information on ReNeurology 72

May 19, 2009

1791

engineering the Clinical Research Enterprise can be obtained from http://nihroadmap.nih.gov/clinicalresearch/overviewtranslational.asp. Copyright © 2009 by AAN Enterprises, Inc. 1.

2. 3. 4. 5. 6.

7.

Thompson JP, Noyes K, Dorsey ER, Schwid SR, Holloway RG. Quantitative risk-benefit analysis of natalizumab. Neurology 2008;71:357–364. Available at: http://www.tysabri.com/tysbProject/tysb. portal. Accessed August 5, 2008. Ropper AH. Selective treatment of multiple sclerosis. N Engl J Med 2006;354:965–967. Steiner I, Sriram S. The “one virus, one disease” model of multiple sclerosis is too constraining. Ann Neurol 2007;62:529. Ransohoff RM. Natalizumab for multiple sclerosis. N Engl J Med 2007;35:2622–2629. Kister I, Herbert J. Three cases of herpes reactivation in MS patients on natalizumab monotherapy. The 23rd Congress of the European Committee for the Treatment and Research in Multiple Sclerosis (ECTRIMS), Prague, 2007. National Multiple Sclerosis Society. Two new cases of PML develop in people with MS taking Tysabri. Available at: http://www.nationalmssociety.org/news/news-detail/ index.aspx?nid⫽260. Accessed August 12, 2008.

PROGNOSTIC SIGNIFICANCE OF BLOOD PRESSURE VARIABILITY AFTER THROMBOLYSIS IN ACUTE STROKE

To the Editor: We read the article by Delgado et al.1 with interest. The authors present an independent association between blood pressure (BP) variability and diffusion-weighted imaging (DWI) lesion growth in ischemic stroke due to middle cerebral artery (MCA) occlusion. The authors hypothesize that systemic BP fluctuations may negatively influence the ischemic penumbra in non-recanalized MCA occlusions. This association was not observed in patients who recanalized after recombinant tissue plasminogen activator. We would like to consider several issues. In most complete MCA occlusions, insular involvement is present due to the direct supply from the main MCA trunk. Unfortunately, the authors have not recorded the insular injury. Lesions within the insular cortex are crucial in the pathogenesis of autonomic dysfunction in acute stroke including baroreflex impairment and sympathetic overdrive activation. This may result in increased BP variability.2 Furthermore, strokes affecting the insular cortex may be more prone to growth apart from initial lesion volume.3 In the resulting autonomic imbalance, risks include proinflammatory cytokine production, elevated body temperature, hyperglycemia, and increased blood– brain barrier permeability.4 It is possible that BP variability is associated with insular lesions and reflects an underlying complex autonomic impairment which may contribute to infarct size growth. Recent data showed that beta blocker use was associated with 1792

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less severe stroke, implying that modulation of stroke-related autonomic dysfunction with beta blockers may reduce stroke size.5 We agree that increased BP variability in MCA occlusions with insular involvement may influence the stroke growth. However, other mechanisms should be considered. In addition, the issue of what should be considered causal and what can be considered an association remains unclear. Marek Sykora, Jennifer Diedler, Thorsten Steiner, Heidelberg, Germany Disclosure: The authors report no disclosures.

Reply from the Authors: We thank Dr. Sykora et al. for their interest in our recent article evaluating the prognostic relevance of BP variability on DWI lesion growth and clinical outcome in patients with acute stroke after thrombolysis.1 They consider the role of insular cortex infarction and abnormal autonomic activity in the pathophysiology of BP variability and ischemic lesion growth. The investigation of the pathophysiologic mechanisms underlying BP variability in acute stroke was beyond the scope of this study. Our goal was to explore the impact of BP variability on ischemic lesion growth in relation to the occurrence of recanalization, not the causes of BP variability in acute stroke. The occlusion of a cerebral artery and its course is considered the first link in the pathogenic chain of BP changes.6 Various pathophysiologic mechanisms have been proposed to explain this phenomenon, including central autonomic dysautoregulation secondary to insular cortex damage after MCA territory stroke.7 The insula is particularly vulnerable to ischemia after M1 or M2 MCA occlusion due to the lack of pial collateral supply and has been associated with larger infarct size.8 Unfortunately, we do not have information on the presence and extent of insular involvement in our patients. Because all patients had a documented MCA occlusion, we expect insular ischemia to be initially present in similar proportion in both recanalization and non-recanalization groups. Although non-recanalized patients had a slightly higher DWI volume on admission, the relationship between BP variability and DWI lesion growth was independent of baseline infarct size. However, we could hypothesize that the impact of BP fluctuations on DWI-lesion growth might be affected by an increased insular damage in the setting of a persisting MCA occlusion, resulting in more profound and lasting hemodynamic instability. The nonrecanalization group had higher BP variability compared to the recanalization group. We agree with Sykora and colleagues that there may be additional dysautonomic-related mechanisms

secondary to insula infarction contributing to infarct growth. Whether acute BP variability is associated with increased infarct progression itself or is simply a marker of a more complex catecholamine-based dysfunction is unclear. Raquel Delgado-Mederos, Carlos A. Molina, Barcelona, Spain Disclosure: The authors report no disclosures. Copyright © 2009 by AAN Enterprises, Inc. 1.

2.

3.

4.

5.

6.

7.

8.

Delgado-Mederos R, Ribo M, Rovira A, et al. Prognostic significance of blood pressure variability after thrombolysis in acute stroke. Neurology 2008;71:552–558. Sykora M, Diedler J, Rupp A, Turcani P, Steiner T. Impaired baroreceptor reflex sensitivity in acute stroke is associated with insular involvement, but not with carotid atherosclerosis. Stroke 2008 (in press). Ay H, Arsava EM, Koroshetz WJ, Sorensen AG. Middle cerebral artery infarcts encompassing the insula are more prone to growth. Stroke 2008;39:373–378. Emsley HC, Smith CJ, Tyrrell PJ, Hopkins SJ. Inflammation in acute ischemic stroke and its relevance to stroke critical care. Neurocrit Care 2008;9:125–138. Laowattana S, Oppenheimer SM. Protective effects of beta-blockers in cerebrovascular disease. Neurology 2007; 68:509 –514. Mattle HP, Kappeler L, Arnold M, et al. Blood pressure and vessel recanalization in the first hours after ischemic stroke. Stroke 2005;36:264 –268. Meyer S, Strittmatter M, Fischer C, Georg T, Schmitz B. Lateralization in autonomic dysfunction in ischemic stroke involving the insular cortex. Neuroreport 2004;15:357–361. Fink JN, Selim MH, Kumar S, Voetsch B, Fong WC, Caplan LR. Insular cortex infarction in acute middle cerebral artery territory stroke: predictor of stroke severity and vascular lesion. Arch Neurol 2005;62:1081–1085.

To the Editor: Delgado-Mederos et al.1 consider the issue of blood pressure regulation in acute hemispheric ischemic stroke and effectively demonstrate the difference in blood pressure variability in nonrecanalized patients with low and high physical morbidity. The authors also show that blood pressure variability is independently associated with diffusionweighted imaging (DWI) lesion growth and clinical course. However, in nonrecanalized patients, the baseline perfusion was different in both groups but not statistically significant (table 2). It has been shown that low hemispheric perfusion demonstrated by perfusion-weighted imaging (PWI) correlates with the penumbra and the future infarct size.2 While this PWI–DWI mismatch might be statistically insignificant, it is clinically relevant in this case. These patients might be inherently vulnerable and blood pressure variability might increase the infarct size. Archit C. Bhatt, MD, MPH, Muhammad U. Farooq, MD, East Lansing, MI, USA Disclosure: The authors report no disclosures. Editor’s Note: The authors of the article were offered the opportunity to respond but declined. Copyright © 2009 by AAN Enterprises, Inc. 1.

2.

Delgado-Mederos R, Ribo M, Rovira A, et al. Prognostic significance of blood pressure variability after thrombolysis in acute stroke. Neurology 2008;71:552–558. Lubya M, Waracha S. Reliability of MR perfusionweighted and diffusion-weighted imaging mismatch measurement methods. Am J Neuroradiol 2007;28: 1674 –1678.

Save These Dates for AAN CME Opportunities! Mark these upcoming dates on your calendar for these exciting continuing education opportunities, where you can catch up on the latest neurology information. AAN Annual Meetings ● April 10 –17, 2010, Toronto, Ontario, Canada, Toronto Convention Centre ● April 9 –16, 2011, Honolulu, Hawaii, Hawaii Convention Center

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Correspondence

QUANTITATIVE RISK-BENEFIT ANALYSIS OF NATALIZUMAB

To the Editor: I read with interest the analysis by Thompson et al.1 that assessed the risks and benefits of natalizumab in relapsing multiple sclerosis (MS). The study is based on an incorrect assumption and does not consider another fatal complication besides progressive multifocal leukoencephalopathy (PML). Following reports of the development of PML under natalizumab therapy, it is currently approved in a subgroup of patients with MS who “have had an inadequate response to, or are unable to tolerate, alternate therapies.”2 However, this indication is based on the observed effect of natalizumab in two studies that did not examine its impact in the selective subgroup of patients with MS who already had not responded to immunosuppressive therapy.3 Ironically, it seems that natalizumab is indicated for a clinical setting in which it was not tested. The current therapeutic approach in MS is based on the unproven assumption that relapses in MS are due to acute CNS inflammation and therefore immunomodulating or immunosuppressive therapies are aimed at preventing the immune response. The hypothesis that an immunosuppressive agent will work where others have failed requires proof. If MS is a syndrome and not a single disease entity, failure to respond to several immunomodulating therapies may render the usage of another agent futile.4 Thus, extrapolating the findings observed in previous studies to this analysis is irrelevant to the current indications of natalizumab use and therefore cannot be used in the proposed model. Natalizumab has been associated with a fatal case of herpes encephalitis, herpes meningitis,5 several cases of recurrent herpes zoster, and herpes labialis.6 Consequently, another potential fatal complication of natalizumab was not discussed in this analysis. Israel Steiner, Jerusalem, Israel Disclosure: The author reports no disclosures.

Reply from the Authors: We thank Dr. Steiner for his interest in our work. His first point regarding the inconsistency between the AFFIRM trial population and the subpopulation of patients with MS

most likely to be treated with natalizumab is an acknowledged limitation to our model. Only a well-designed trial can definitively assess the effects of natalizumab in the subpopulation of patients for which it is indicated. However, US Food and Drug Administration approval of natalizumab for patients not responding to other therapies indicates that they accept similar efficacy between this subpopulation and the original trial participants. In our model, we assessed cohorts with increased baseline disability and increased risk of disability progression and found that those factors did not significantly change the results. We prefer this approach rather than stating that existing data are inadequate. We also agree with Dr. Steiner that there may be new information about the risks of natalizumab arising over time. However, while Dr. Steiner considers this a weakness of our model, we consider it a strength. An advantage of this model is that it can accommodate new risk information as it emerges, whether it is to refine PML risk (now estimated to be 2 per 6,600 patients treated over 18 months or more7) or to incorporate new risks (e.g., the development of other serious infectious complications such as herpes encephalitis). We believe that our model can help clinicians, patients, and regulators incorporate this new information into their decision-making. R.G. Holloway, J.P. Thompson, K. Noyes, E.R. Dorsey, S.R. Schwid, Rochester, NY Disclosure: K.N., R.G.H., and S.R.S. were supported in part by contract HC0071 from the National Multiple Sclerosis Society. K.N. was supported in part by research grant K01 AG 20980 from the National Institute on Aging. E.R.D. was supported in part by an American Academy of Neurology Clinical Research Training Fellowship. R.G.H. was supported in part by grant K24 NS4 2098 from the National Institute of Neurological Disorders and Stroke. S.R.S. has received research funding from Biogen, Serono, and Teva and honoraria for educational and consulting activities from Berlex, Biogen, Serono, and Teva. The project described was partially supported by grant number 1 UL1 RR024160 – 01 from the National Center for Research Resources (NCRR), a component of the NIH and the NIH Roadmap for Medical Research, and its contents are solely the responsibility of the authors and do not necessarily represent the official view of NCRR or NIH. Information on NCRR is available at http://www.ncrr.nih.gov/. Information on ReNeurology 72

May 19, 2009

1791

engineering the Clinical Research Enterprise can be obtained from http://nihroadmap.nih.gov/clinicalresearch/overviewtranslational.asp. Copyright © 2009 by AAN Enterprises, Inc. 1.

2. 3. 4. 5. 6.

7.

Thompson JP, Noyes K, Dorsey ER, Schwid SR, Holloway RG. Quantitative risk-benefit analysis of natalizumab. Neurology 2008;71:357–364. Available at: http://www.tysabri.com/tysbProject/tysb. portal. Accessed August 5, 2008. Ropper AH. Selective treatment of multiple sclerosis. N Engl J Med 2006;354:965–967. Steiner I, Sriram S. The “one virus, one disease” model of multiple sclerosis is too constraining. Ann Neurol 2007;62:529. Ransohoff RM. Natalizumab for multiple sclerosis. N Engl J Med 2007;35:2622–2629. Kister I, Herbert J. Three cases of herpes reactivation in MS patients on natalizumab monotherapy. The 23rd Congress of the European Committee for the Treatment and Research in Multiple Sclerosis (ECTRIMS), Prague, 2007. National Multiple Sclerosis Society. Two new cases of PML develop in people with MS taking Tysabri. Available at: http://www.nationalmssociety.org/news/news-detail/ index.aspx?nid⫽260. Accessed August 12, 2008.

PROGNOSTIC SIGNIFICANCE OF BLOOD PRESSURE VARIABILITY AFTER THROMBOLYSIS IN ACUTE STROKE

To the Editor: We read the article by Delgado et al.1 with interest. The authors present an independent association between blood pressure (BP) variability and diffusion-weighted imaging (DWI) lesion growth in ischemic stroke due to middle cerebral artery (MCA) occlusion. The authors hypothesize that systemic BP fluctuations may negatively influence the ischemic penumbra in non-recanalized MCA occlusions. This association was not observed in patients who recanalized after recombinant tissue plasminogen activator. We would like to consider several issues. In most complete MCA occlusions, insular involvement is present due to the direct supply from the main MCA trunk. Unfortunately, the authors have not recorded the insular injury. Lesions within the insular cortex are crucial in the pathogenesis of autonomic dysfunction in acute stroke including baroreflex impairment and sympathetic overdrive activation. This may result in increased BP variability.2 Furthermore, strokes affecting the insular cortex may be more prone to growth apart from initial lesion volume.3 In the resulting autonomic imbalance, risks include proinflammatory cytokine production, elevated body temperature, hyperglycemia, and increased blood– brain barrier permeability.4 It is possible that BP variability is associated with insular lesions and reflects an underlying complex autonomic impairment which may contribute to infarct size growth. Recent data showed that beta blocker use was associated with 1792

Neurology 72

May 19, 2009

less severe stroke, implying that modulation of stroke-related autonomic dysfunction with beta blockers may reduce stroke size.5 We agree that increased BP variability in MCA occlusions with insular involvement may influence the stroke growth. However, other mechanisms should be considered. In addition, the issue of what should be considered causal and what can be considered an association remains unclear. Marek Sykora, Jennifer Diedler, Thorsten Steiner, Heidelberg, Germany Disclosure: The authors report no disclosures.

Reply from the Authors: We thank Dr. Sykora et al. for their interest in our recent article evaluating the prognostic relevance of BP variability on DWI lesion growth and clinical outcome in patients with acute stroke after thrombolysis.1 They consider the role of insular cortex infarction and abnormal autonomic activity in the pathophysiology of BP variability and ischemic lesion growth. The investigation of the pathophysiologic mechanisms underlying BP variability in acute stroke was beyond the scope of this study. Our goal was to explore the impact of BP variability on ischemic lesion growth in relation to the occurrence of recanalization, not the causes of BP variability in acute stroke. The occlusion of a cerebral artery and its course is considered the first link in the pathogenic chain of BP changes.6 Various pathophysiologic mechanisms have been proposed to explain this phenomenon, including central autonomic dysautoregulation secondary to insular cortex damage after MCA territory stroke.7 The insula is particularly vulnerable to ischemia after M1 or M2 MCA occlusion due to the lack of pial collateral supply and has been associated with larger infarct size.8 Unfortunately, we do not have information on the presence and extent of insular involvement in our patients. Because all patients had a documented MCA occlusion, we expect insular ischemia to be initially present in similar proportion in both recanalization and non-recanalization groups. Although non-recanalized patients had a slightly higher DWI volume on admission, the relationship between BP variability and DWI lesion growth was independent of baseline infarct size. However, we could hypothesize that the impact of BP fluctuations on DWI-lesion growth might be affected by an increased insular damage in the setting of a persisting MCA occlusion, resulting in more profound and lasting hemodynamic instability. The nonrecanalization group had higher BP variability compared to the recanalization group. We agree with Sykora and colleagues that there may be additional dysautonomic-related mechanisms

secondary to insula infarction contributing to infarct growth. Whether acute BP variability is associated with increased infarct progression itself or is simply a marker of a more complex catecholamine-based dysfunction is unclear. Raquel Delgado-Mederos, Carlos A. Molina, Barcelona, Spain Disclosure: The authors report no disclosures. Copyright © 2009 by AAN Enterprises, Inc. 1.

2.

3.

4.

5.

6.

7.

8.

Delgado-Mederos R, Ribo M, Rovira A, et al. Prognostic significance of blood pressure variability after thrombolysis in acute stroke. Neurology 2008;71:552–558. Sykora M, Diedler J, Rupp A, Turcani P, Steiner T. Impaired baroreceptor reflex sensitivity in acute stroke is associated with insular involvement, but not with carotid atherosclerosis. Stroke 2008 (in press). Ay H, Arsava EM, Koroshetz WJ, Sorensen AG. Middle cerebral artery infarcts encompassing the insula are more prone to growth. Stroke 2008;39:373–378. Emsley HC, Smith CJ, Tyrrell PJ, Hopkins SJ. Inflammation in acute ischemic stroke and its relevance to stroke critical care. Neurocrit Care 2008;9:125–138. Laowattana S, Oppenheimer SM. Protective effects of beta-blockers in cerebrovascular disease. Neurology 2007; 68:509 –514. Mattle HP, Kappeler L, Arnold M, et al. Blood pressure and vessel recanalization in the first hours after ischemic stroke. Stroke 2005;36:264 –268. Meyer S, Strittmatter M, Fischer C, Georg T, Schmitz B. Lateralization in autonomic dysfunction in ischemic stroke involving the insular cortex. Neuroreport 2004;15:357–361. Fink JN, Selim MH, Kumar S, Voetsch B, Fong WC, Caplan LR. Insular cortex infarction in acute middle cerebral artery territory stroke: predictor of stroke severity and vascular lesion. Arch Neurol 2005;62:1081–1085.

To the Editor: Delgado-Mederos et al.1 consider the issue of blood pressure regulation in acute hemispheric ischemic stroke and effectively demonstrate the difference in blood pressure variability in nonrecanalized patients with low and high physical morbidity. The authors also show that blood pressure variability is independently associated with diffusionweighted imaging (DWI) lesion growth and clinical course. However, in nonrecanalized patients, the baseline perfusion was different in both groups but not statistically significant (table 2). It has been shown that low hemispheric perfusion demonstrated by perfusion-weighted imaging (PWI) correlates with the penumbra and the future infarct size.2 While this PWI–DWI mismatch might be statistically insignificant, it is clinically relevant in this case. These patients might be inherently vulnerable and blood pressure variability might increase the infarct size. Archit C. Bhatt, MD, MPH, Muhammad U. Farooq, MD, East Lansing, MI, USA Disclosure: The authors report no disclosures. Editor’s Note: The authors of the article were offered the opportunity to respond but declined. Copyright © 2009 by AAN Enterprises, Inc. 1.

2.

Delgado-Mederos R, Ribo M, Rovira A, et al. Prognostic significance of blood pressure variability after thrombolysis in acute stroke. Neurology 2008;71:552–558. Lubya M, Waracha S. Reliability of MR perfusionweighted and diffusion-weighted imaging mismatch measurement methods. Am J Neuroradiol 2007;28: 1674 –1678.

Save These Dates for AAN CME Opportunities! Mark these upcoming dates on your calendar for these exciting continuing education opportunities, where you can catch up on the latest neurology information. AAN Annual Meetings ● April 10 –17, 2010, Toronto, Ontario, Canada, Toronto Convention Centre ● April 9 –16, 2011, Honolulu, Hawaii, Hawaii Convention Center

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Correspondence

QUANTITATIVE RISK-BENEFIT ANALYSIS OF NATALIZUMAB

To the Editor: I read with interest the analysis by Thompson et al.1 that assessed the risks and benefits of natalizumab in relapsing multiple sclerosis (MS). The study is based on an incorrect assumption and does not consider another fatal complication besides progressive multifocal leukoencephalopathy (PML). Following reports of the development of PML under natalizumab therapy, it is currently approved in a subgroup of patients with MS who “have had an inadequate response to, or are unable to tolerate, alternate therapies.”2 However, this indication is based on the observed effect of natalizumab in two studies that did not examine its impact in the selective subgroup of patients with MS who already had not responded to immunosuppressive therapy.3 Ironically, it seems that natalizumab is indicated for a clinical setting in which it was not tested. The current therapeutic approach in MS is based on the unproven assumption that relapses in MS are due to acute CNS inflammation and therefore immunomodulating or immunosuppressive therapies are aimed at preventing the immune response. The hypothesis that an immunosuppressive agent will work where others have failed requires proof. If MS is a syndrome and not a single disease entity, failure to respond to several immunomodulating therapies may render the usage of another agent futile.4 Thus, extrapolating the findings observed in previous studies to this analysis is irrelevant to the current indications of natalizumab use and therefore cannot be used in the proposed model. Natalizumab has been associated with a fatal case of herpes encephalitis, herpes meningitis,5 several cases of recurrent herpes zoster, and herpes labialis.6 Consequently, another potential fatal complication of natalizumab was not discussed in this analysis. Israel Steiner, Jerusalem, Israel Disclosure: The author reports no disclosures.

Reply from the Authors: We thank Dr. Steiner for his interest in our work. His first point regarding the inconsistency between the AFFIRM trial population and the subpopulation of patients with MS

most likely to be treated with natalizumab is an acknowledged limitation to our model. Only a well-designed trial can definitively assess the effects of natalizumab in the subpopulation of patients for which it is indicated. However, US Food and Drug Administration approval of natalizumab for patients not responding to other therapies indicates that they accept similar efficacy between this subpopulation and the original trial participants. In our model, we assessed cohorts with increased baseline disability and increased risk of disability progression and found that those factors did not significantly change the results. We prefer this approach rather than stating that existing data are inadequate. We also agree with Dr. Steiner that there may be new information about the risks of natalizumab arising over time. However, while Dr. Steiner considers this a weakness of our model, we consider it a strength. An advantage of this model is that it can accommodate new risk information as it emerges, whether it is to refine PML risk (now estimated to be 2 per 6,600 patients treated over 18 months or more7) or to incorporate new risks (e.g., the development of other serious infectious complications such as herpes encephalitis). We believe that our model can help clinicians, patients, and regulators incorporate this new information into their decision-making. R.G. Holloway, J.P. Thompson, K. Noyes, E.R. Dorsey, S.R. Schwid, Rochester, NY Disclosure: K.N., R.G.H., and S.R.S. were supported in part by contract HC0071 from the National Multiple Sclerosis Society. K.N. was supported in part by research grant K01 AG 20980 from the National Institute on Aging. E.R.D. was supported in part by an American Academy of Neurology Clinical Research Training Fellowship. R.G.H. was supported in part by grant K24 NS4 2098 from the National Institute of Neurological Disorders and Stroke. S.R.S. has received research funding from Biogen, Serono, and Teva and honoraria for educational and consulting activities from Berlex, Biogen, Serono, and Teva. The project described was partially supported by grant number 1 UL1 RR024160 – 01 from the National Center for Research Resources (NCRR), a component of the NIH and the NIH Roadmap for Medical Research, and its contents are solely the responsibility of the authors and do not necessarily represent the official view of NCRR or NIH. Information on NCRR is available at http://www.ncrr.nih.gov/. Information on ReNeurology 72

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engineering the Clinical Research Enterprise can be obtained from http://nihroadmap.nih.gov/clinicalresearch/overviewtranslational.asp. Copyright © 2009 by AAN Enterprises, Inc. 1.

2. 3. 4. 5. 6.

7.

Thompson JP, Noyes K, Dorsey ER, Schwid SR, Holloway RG. Quantitative risk-benefit analysis of natalizumab. Neurology 2008;71:357–364. Available at: http://www.tysabri.com/tysbProject/tysb. portal. Accessed August 5, 2008. Ropper AH. Selective treatment of multiple sclerosis. N Engl J Med 2006;354:965–967. Steiner I, Sriram S. The “one virus, one disease” model of multiple sclerosis is too constraining. Ann Neurol 2007;62:529. Ransohoff RM. Natalizumab for multiple sclerosis. N Engl J Med 2007;35:2622–2629. Kister I, Herbert J. Three cases of herpes reactivation in MS patients on natalizumab monotherapy. The 23rd Congress of the European Committee for the Treatment and Research in Multiple Sclerosis (ECTRIMS), Prague, 2007. National Multiple Sclerosis Society. Two new cases of PML develop in people with MS taking Tysabri. Available at: http://www.nationalmssociety.org/news/news-detail/ index.aspx?nid⫽260. Accessed August 12, 2008.

PROGNOSTIC SIGNIFICANCE OF BLOOD PRESSURE VARIABILITY AFTER THROMBOLYSIS IN ACUTE STROKE

To the Editor: We read the article by Delgado et al.1 with interest. The authors present an independent association between blood pressure (BP) variability and diffusion-weighted imaging (DWI) lesion growth in ischemic stroke due to middle cerebral artery (MCA) occlusion. The authors hypothesize that systemic BP fluctuations may negatively influence the ischemic penumbra in non-recanalized MCA occlusions. This association was not observed in patients who recanalized after recombinant tissue plasminogen activator. We would like to consider several issues. In most complete MCA occlusions, insular involvement is present due to the direct supply from the main MCA trunk. Unfortunately, the authors have not recorded the insular injury. Lesions within the insular cortex are crucial in the pathogenesis of autonomic dysfunction in acute stroke including baroreflex impairment and sympathetic overdrive activation. This may result in increased BP variability.2 Furthermore, strokes affecting the insular cortex may be more prone to growth apart from initial lesion volume.3 In the resulting autonomic imbalance, risks include proinflammatory cytokine production, elevated body temperature, hyperglycemia, and increased blood– brain barrier permeability.4 It is possible that BP variability is associated with insular lesions and reflects an underlying complex autonomic impairment which may contribute to infarct size growth. Recent data showed that beta blocker use was associated with 1792

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less severe stroke, implying that modulation of stroke-related autonomic dysfunction with beta blockers may reduce stroke size.5 We agree that increased BP variability in MCA occlusions with insular involvement may influence the stroke growth. However, other mechanisms should be considered. In addition, the issue of what should be considered causal and what can be considered an association remains unclear. Marek Sykora, Jennifer Diedler, Thorsten Steiner, Heidelberg, Germany Disclosure: The authors report no disclosures.

Reply from the Authors: We thank Dr. Sykora et al. for their interest in our recent article evaluating the prognostic relevance of BP variability on DWI lesion growth and clinical outcome in patients with acute stroke after thrombolysis.1 They consider the role of insular cortex infarction and abnormal autonomic activity in the pathophysiology of BP variability and ischemic lesion growth. The investigation of the pathophysiologic mechanisms underlying BP variability in acute stroke was beyond the scope of this study. Our goal was to explore the impact of BP variability on ischemic lesion growth in relation to the occurrence of recanalization, not the causes of BP variability in acute stroke. The occlusion of a cerebral artery and its course is considered the first link in the pathogenic chain of BP changes.6 Various pathophysiologic mechanisms have been proposed to explain this phenomenon, including central autonomic dysautoregulation secondary to insular cortex damage after MCA territory stroke.7 The insula is particularly vulnerable to ischemia after M1 or M2 MCA occlusion due to the lack of pial collateral supply and has been associated with larger infarct size.8 Unfortunately, we do not have information on the presence and extent of insular involvement in our patients. Because all patients had a documented MCA occlusion, we expect insular ischemia to be initially present in similar proportion in both recanalization and non-recanalization groups. Although non-recanalized patients had a slightly higher DWI volume on admission, the relationship between BP variability and DWI lesion growth was independent of baseline infarct size. However, we could hypothesize that the impact of BP fluctuations on DWI-lesion growth might be affected by an increased insular damage in the setting of a persisting MCA occlusion, resulting in more profound and lasting hemodynamic instability. The nonrecanalization group had higher BP variability compared to the recanalization group. We agree with Sykora and colleagues that there may be additional dysautonomic-related mechanisms

secondary to insula infarction contributing to infarct growth. Whether acute BP variability is associated with increased infarct progression itself or is simply a marker of a more complex catecholamine-based dysfunction is unclear. Raquel Delgado-Mederos, Carlos A. Molina, Barcelona, Spain Disclosure: The authors report no disclosures. Copyright © 2009 by AAN Enterprises, Inc. 1.

2.

3.

4.

5.

6.

7.

8.

Delgado-Mederos R, Ribo M, Rovira A, et al. Prognostic significance of blood pressure variability after thrombolysis in acute stroke. Neurology 2008;71:552–558. Sykora M, Diedler J, Rupp A, Turcani P, Steiner T. Impaired baroreceptor reflex sensitivity in acute stroke is associated with insular involvement, but not with carotid atherosclerosis. Stroke 2008 (in press). Ay H, Arsava EM, Koroshetz WJ, Sorensen AG. Middle cerebral artery infarcts encompassing the insula are more prone to growth. Stroke 2008;39:373–378. Emsley HC, Smith CJ, Tyrrell PJ, Hopkins SJ. Inflammation in acute ischemic stroke and its relevance to stroke critical care. Neurocrit Care 2008;9:125–138. Laowattana S, Oppenheimer SM. Protective effects of beta-blockers in cerebrovascular disease. Neurology 2007; 68:509 –514. Mattle HP, Kappeler L, Arnold M, et al. Blood pressure and vessel recanalization in the first hours after ischemic stroke. Stroke 2005;36:264 –268. Meyer S, Strittmatter M, Fischer C, Georg T, Schmitz B. Lateralization in autonomic dysfunction in ischemic stroke involving the insular cortex. Neuroreport 2004;15:357–361. Fink JN, Selim MH, Kumar S, Voetsch B, Fong WC, Caplan LR. Insular cortex infarction in acute middle cerebral artery territory stroke: predictor of stroke severity and vascular lesion. Arch Neurol 2005;62:1081–1085.

To the Editor: Delgado-Mederos et al.1 consider the issue of blood pressure regulation in acute hemispheric ischemic stroke and effectively demonstrate the difference in blood pressure variability in nonrecanalized patients with low and high physical morbidity. The authors also show that blood pressure variability is independently associated with diffusionweighted imaging (DWI) lesion growth and clinical course. However, in nonrecanalized patients, the baseline perfusion was different in both groups but not statistically significant (table 2). It has been shown that low hemispheric perfusion demonstrated by perfusion-weighted imaging (PWI) correlates with the penumbra and the future infarct size.2 While this PWI–DWI mismatch might be statistically insignificant, it is clinically relevant in this case. These patients might be inherently vulnerable and blood pressure variability might increase the infarct size. Archit C. Bhatt, MD, MPH, Muhammad U. Farooq, MD, East Lansing, MI, USA Disclosure: The authors report no disclosures. Editor’s Note: The authors of the article were offered the opportunity to respond but declined. Copyright © 2009 by AAN Enterprises, Inc. 1.

2.

Delgado-Mederos R, Ribo M, Rovira A, et al. Prognostic significance of blood pressure variability after thrombolysis in acute stroke. Neurology 2008;71:552–558. Lubya M, Waracha S. Reliability of MR perfusionweighted and diffusion-weighted imaging mismatch measurement methods. Am J Neuroradiol 2007;28: 1674 –1678.

Save These Dates for AAN CME Opportunities! Mark these upcoming dates on your calendar for these exciting continuing education opportunities, where you can catch up on the latest neurology information. AAN Annual Meetings ● April 10 –17, 2010, Toronto, Ontario, Canada, Toronto Convention Centre ● April 9 –16, 2011, Honolulu, Hawaii, Hawaii Convention Center

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Section Editors Christopher J. Boes, MD Kenneth J. Mack, MD, PhD

Book Review

NEUROMUSCULAR DISORDERS

edited by Anthony A. Amato, MD, and James A. Russell, DO, 832 pp., New York, McGraw-Hill Companies, Inc., 2008, $179 (hardcover) Neuromuscular medicine has grown into a large field of neurology and is now a recognized subspecialty by the Accreditation Council for Graduate Medical Education with fellowship training. The American Board of Psychiatry and Neurology now offer subspecialty certification. Recognizing these advancements, Dr. Anthony A. Amato and Dr. James A. Russell provide a text which addresses this rapidly evolving field. While not as comprehensive as other classic textbooks that review peripheral neuropathies, myopathies, and neuromuscular transmission disorders individually, the authors provide a very clinically relevant text that is all-inclusive and offers a practical approach to diagnosis and management for trainees and practicing neurologists. The first section of the book is composed of three chapters discussing the approach to patients with neuromuscular disease. The first chapter provides an excellent review discussing the strategic approach to neuromuscular disease. There is a comprehensive review of the signs and symptoms and localization based on the area of the neuromuscular system involved. The second chapter reviews pertinent testing, particularly electrodiagnostic evaluation, for neuromuscular diseases and how this testing can be used to aid in characterization and diagnosis. The third chapter provides a review of nerve and muscle histopathology with beautiful color illustrations. The second section of the book reviews specific neuromuscular disorders. The disorders are described according to localization along the peripheral

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neuraxis from the anterior horn cell to the muscle. Because this text is written entirely by the two authors, the text flows very well. All of the chapters follow the same format: discussion of clinical features, laboratory features, histopathology, pathogenesis, differential diagnosis, evaluation, and treatment. In general, the chapters are thorough although some are more detailed and provide more referencing than other chapters. The authors provide an evidencebased approach to treatment when available; however, in many areas of neuromuscular medicine, there is little evidence-based guidance for treatment. In this setting, the authors use their extensive knowledge and experience to provide recommendations to clinicians. The one criticism of the textbook concerns the editing. There are several typographical errors throughout the text, and some factual errors as well as inconsistencies in formatting of the text. Supplementation of the text with tables, figures, and imaging is done to an appropriate extent to illustrate key points. Dr. Amato and Dr. Russell provide an important addition to the neuromuscular reference library. I would recommend this text to resident trainees, those pursuing fellowship training in neuromuscular disease or preparing for board certification examinations, and neurologists searching for a text that comprehensively reviews the diseases involving the neuromuscular system in a manageable and clinically relevant format. Reviewed by Michelle L. Mauermann, MD Disclosure: The author reports no disclosures. Copyright © 2009 by AAN Enterprises, Inc.

Calendar

Neurology® publishes short announcements of meetings and courses related to the field. Items must be received at least 6 weeks before the first day of the month in which the initial notice is to appear. Send Calendar submissions to Calendar, Editorial Office, Neurology®, Suite 214, 20 SW 2nd Ave., P.O. Box 178, Rochester, MN 55903 [email protected]

2009 MAY 28 –30 6th International Headache Seminary. Focus on Headaches: New Frontier in Mechanisms and Management will be held at the Grand Hotel des Iles Borromees in Stresa (Italy); tel/fax 02 7063 8067; [email protected]. JUN. 8 –12 Leksell Gamma Knife® Perfexion™ Introductory Course will be held at the Gamma Knife Center in Cleveland, OH. Contact Martha Tobin at (216) 445-3449 or (800) 2232273, ext 53449, or at [email protected] for seminar details. JUN. 12 Mellen Center Regional Symposium on Multiple Sclerosis will be held at the InterContinental Hotel & Bank of America Conference Center in Cleveland, OH. Contact Martha Tobin at (216) 445-3449 or (800) 223-2273, ext 53449, or at [email protected] for seminar details. JUN. 16 –20 14th Annual meeting of the International Society for the History of the Neurosciences, including special sessions on Darwin and ‘Neurology and War,’ will be held at Charleston, South Carolina. For information, visit www.ishn.org or e-mail [email protected]. JUN. 19 –24 Epileptology Symposium will be held at the InterContinental Hotel & Bank of America Conference Center, in Cleveland, OH. Contact Martha Tobin at (216) 445-3449 or (800) 223-2273, ext 53449, or at [email protected] for seminar details. JUL. 7–10 SickKids Centre for Brain & Behaviour International Symposium. [email protected]; www.sickkids.ca/ learninginstitute. JUL. 16 –18 Mayo Clinic Neurology in Clinical Practice2009 will be held at the InterContinental Hotel, Chicago, IL. Mayo CME: tel (800) 323-2688; [email protected]; http:// www.mayo.edu/cme/neurology-neurologic-surgery.html. JUL. 22–28 Spine Review 2009 will be held at Cleveland Clinic’s Lutheran Hospital in Cleveland, OH. Contact Martha Tobin at (216) 445-3449 or (800) 223-2273, ext 53449, or at [email protected] for seminar details.

SEP. 12–15 13th Congress of the European Federation of Neurological Societies will be held in Florence, Italy. For more information: tel ⫹41 22 908 0488; http://www.kenes.com/efns2009/ index.asp; [email protected]. SEP. 16 –19 Annual Conference of the German Genetics Society will be held at Cologne, Germany; tel 49(0)3641-3-5332-22; [email protected]. SEP. 25 Practical Pearls in Neuro-Ophthalmology–International Symposium in Honour of Dr. James Sharpe will be held on September 25, 2009 at the University of Toronto Conference Centre, Toronto, Ontario. For further information contact the Office of Continuing Education & Professional Development, Faculty of Medicine, University of Toronto: tel (416) 978-2719; (888) 512-8173; fax (416) 946-7028; [email protected]; http://events.cmetoronto.ca/website/index/OPT0907. OCT. 8 –11 The Third World Congress on Controversies in Neurology. Full information is available at: ComtecMed - Medical Congresses, PO Box 68, Tel-Aviv, 61000 Israel; tel ⫹972– 3-5666166; fax ⫹972–3-5666177; [email protected]; www.comtecmed.com/cony. OCT. 11 Symposium on Etiology, Pathogenesis, and Treatment of Parkinson’s Disease and Other Movement Disorders will be held at the Baltimore Marriott Waterfront Hotel, in Baltimore, Maryland. www.Parkinson-Study-Group.org. OCT. 24 –30 19th World Congress of Neurology, WCN 2009, will be held in Bangkok, Thailand. www.wcn2009bangkok.com. OCT. 29 –30 Clinical Trials on Alzheimer’s Disease will be held in Las Vegas at the Lou Ruvo Brain Institute. For more information, please visit www.ctad.fr. NOV. 19 –22 The Sixth International Congress on Vascular Dementia will be held Barcelona, Spain. For further details, please contact: Kenes International 17 Rue du Cendrier, P.O. Box 1726, CH-1211, Geneva 1, Switzerland; tel ⫹41 22 908 0488; fax ⫹41 22 732 2850; [email protected]; http://www.kenes.com/vascular. DEC. 3– 6 Neuromodulation 2009 Encore will be held at Wynn Las Vegas in NV. Contact Martha Tobin at (216) 445-3449 or (800) 223-2273, ext 53449, or at [email protected] for seminar details.

AUG. 6 –9 Decision Neuroscience Symposium to be held at the 2009 American Psychological Association (APA) Annual Convention in Toronto, Canada. For mor information, please see http://www.jnpe.org/english.html.

DEC. 7–11 Leksell Gamma Knife® Perfexion™ Introductory Course will be held at the Gamma Knife Center in Cleveland, OH. Contact Martha Tobin at (216) 445-3449 or (800) 2232273, ext 53449, or at [email protected] for seminar details.

AUG. 17–19 Leksell Gamma Knife® Perfexion™ Upgrade Course will be held at the Gamma Knife Center in Cleveland, OH. Contact Martha Tobin at (216) 445-3449 or (800) 223-2273, ext 53449, or at [email protected] for seminar details.

2010 MAY 2–7 11th International Child Neurology Congress will be held in Cairo, Egypt; http://www.icnc2010.com/. Neurology 72

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In the next issue of Neurology® Volume 72, Number 21, May 26, 2009 www.neurology.org THE MOST WIDELY READ AND HIGHLY CITED PEER-REVIEWED NEUROLOGY JOURNAL

THIS WEEK IN Neurology®

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Highlights of the May 26 issue

EDITORIALS

Reduced circulating angiogenic cells in Alzheimer disease S.-T. Lee, K. Chu, K.-H. Jung, H.-K. Park, et al.

VIEWS & REVIEWS

Migraine and cardiovascular disease: Possible mechanisms of interaction M.E. Bigal, T. Kurth, H. Hu, N. Santanello, et al.

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Abnormal glycosylation of the ␣-dystroglycan: Deficient sugars are no good Haluk Topaloglu

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A fresh twist on carotid artery dissections Scott E. Kasner and Jens P. Dreier

CLINICAL/SCIENTIFIC NOTES

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Leptomeningeal enhancement in patients with moyamoya disease Pil-Wook Chung and Kwang-Yeol Park

Congenital muscular dystrophies with defective glycosylation of dystroglycan: A population study E. Mercuri, S. Messina, C. Bruno, M. Mora, et al.

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Varicella zoster infection of the brainstem followed by Brown-Séquard syndrome M.S. Mathews, G.C. Sorkin, and M. Brant-Zawadzki

Aspirin vs anticoagulation in carotid artery dissection: A study of 298 patients D. Georgiadis, M. Arnold, et al.

NEUROIMAGES

ARTICLES

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Statin therapy after first stroke reduces 10-year stroke recurrence and improves survival H.J. Milionis, S. Giannopoulos, M. Kosmidou, et al.

Interhemispheric and intrahemispheric language reorganization in complex partial epilepsy L.R. Rosenberger, J. Zeck, M.M. Berl, E.N. Moore, et al.

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Predictors of individual visual memory decline after unilateral anterior temporal lobe resection M.F. Dulay, H.S. Levin, M.K. York, E.M. Mizrahi, et al.

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Brain and ventricular volumetric changes in frontotemporal lobar degeneration over 1 year D.S. Knopman, C.R. Jack, Jr., J.H. Kramer, et al. Effects of the menopause transition and hormone use on cognitive performance in midlife women G.A. Greendale, M.-H. Huang, R.G. Wight, et al.

Subject to change

Superior divisional oculomotor paresis due to intracavernous internal carotid artery aneurysm J.Y. Kwon, H.S. Song, and J.S. Kim

RESIDENT & FELLOW SECTION

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Clinical Reasoning: A 52-year-old man with spells of altered consciousness and severe headaches T.M. Burrus, J.D. Burns, J. Huston III, G. Lanzino, et al.

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Teaching NeuroImages: Macrocephaly with subcortical calcifications in vein of Galen aneurysmal malformation S. Sharma, N. Sankhyan, and A. Kumar

Silent brain infarcts and leukoaraiosis in young adults with first-ever ischemic stroke J. Putaala, M. Kurkinen, V. Tarvos, O. Salonen, et al.

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PATIENT PAGE

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Statins and stroke David C. Tong

CORRESPONDENCE

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Generic lamotrigine for epilepsy Stiff eyes in stiff-person syndrome

FUTURE ISSUES

Abstracts In the Next Issue of Neurology®

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