Sports Med 2010; 40 (3): 183-187 0112-1642/10/0003-0183/$49.95/0
CURRENT OPINION
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Measuring Deficits in Visually Guided Action Post-Concussion Jason Locklin,1 Lindsay Bunn,1 Eric Roy 2 and James Danckert1 1 Department of Psychology, University of Waterloo, Waterloo, Ontario, Canada 2 Department of Kinesiology, University of Waterloo, Waterloo, Ontario, Canada
Abstract
Recent concussion research has led to the development of computerized test batteries designed to measure working memory and psychomotor speed deficits in acute stage post-concussion. These tests lack a measure of motor control deficits, which may linger well after other symptoms have remitted. For athletes, this may mean returning to play while still uncoordinated or neurologically fragile. The present research involved the development of a visuomotor pointing task designed to induce a speed-accuracy trade off to measure motor planning and execution performance in concussed athletes. Data collected using this tool were contrasted with CogSport, a commercially available computerized test battery designed to assess residual cognitive effects of concussion in athletes. Results suggest that a motor task may be able to detect long-term effects of concussion not measurable with CogSport. If future research can confirm these findings, we suggest that a measure of motor control may need to be added to existing batteries to improve their sensitivity to long term effects.
Concussion is a well known injury in contact sports such as football or ice hockey; however, epidemiological data indicate that concussion is the most common form of head injury experienced by all athletes,[1] even those participating in non-contact sports, and at any level of play.[2] Concussions are particularly troubling for athletes who are not only at a greater risk for concussion than the population at large, but must face the difficult decision of when to return to play – a situation where they are likely to experience further impacts.[3] Returning to play while neurologically fragile, and potentially uncoordinated, increases the risk of further injury and developing a rare, but potentially life-threatening, second impact syndrome (SIS). SIS is controversial, but thought to occur when an athlete sustains a second head injury while recovering from a previous
concussion. It is postulated that this second impact results in more severe complications than concussion.[4-6] Several test batteries are currently used with athletes to monitor recovery and inform returnto-play decisions. The current research employed CogSport (CogState, Melbourne, VIC, Australia), a commonly used computer-administered neuropsychological test battery. CogSport has been shown to provide sensitive measures of cognitive recovery post concussion, as well as good test-retest reliability and resistance to performance ‘faking’.[7] One important metric missing from CogSport and other test batteries in use today is a measure of visually controlled movements.[8] While several tests do involve rapid motor components (e.g. digit symbol substitution, simple reaction time (RT) tasks used in CogSport and
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ImPACT (Pittsburgh, PA, USA),[7,9] these tasks are more accurately described as measuring psychomotor speed as opposed to precise visuomotor control. In fact, little attention has been paid to visuomotor control in athletes postconcussion,[10,11] which is striking given the visuomotor requirements in-game, and this is despite evidence of a range of motor changes after moderate to severe head injury, including finger tapping,[12] gait,[13] and reaching and grasping.[13,14] Beyond an ecologically important metric, the addition of a measure of fine motor control may also improve the sensitivity of existing neuropsychological test batteries.[15,16] In fact, there is some evidence of residual upper limb and oculomotor deficits up to a year after injury, which is months after recovery of other cognitive measures.[17] The current research employed an objectpointing task that explicitly invoked a speedaccuracy trade off, which should conform to Fitts’ law.[18] Fitts’ law implies that by varying precision requirements of the task, ballistic pointing movements should be executed with corresponding levels of difficulty (i.e. high precision trials would be executed more slowly). By contrasting athletes with and without a history of concussion on this motor task with their performance on CogSport, the objective of the current research was to determine the potential of a visuomotor task as a measure of concussion recovery in athletes.
1. Methods 1.1 Participants
The experimental group included 16 male and 4 female athletes from a variety of university sports ranging in age from 17 to 23 years (mean = 19; SD = 2), three of whom were lefthanded. Half of the athletes had experienced concussions in the past (CA; table I) with the other half acting as one control group (NCA). A second control group consisted of 20 righthanded, non-athlete (NA) university students (13 male, 7 female) aged 18–27 years (mean = 21; SD = 3) with no prior history of concussion or head injury. All participants had normal to corrected vision, no neurological deficits or abnormalities and had normal arm mobility. All participants were recruited from the University of Waterloo and gave written informed consent in accordance with the University of Waterloo Ethics Committee. 1.2 Apparatus and Procedure
All three groups performed the motor task, while only the two athlete groups were tested with CogSport. Four Pentium desktop computers were used to administer CogSport, three of which were equipped with touch screens for use in the motor task (one 15-inch and one 17-inch View Sonic E70fB [Walnut, CA, USA], and one
Table I. Concussion data for concussed athletes Sex
Sport
No. of concussions
Time since concussion
No. of symptomsa
Symptom severityb
1
M
Hockey
5
<1 wk
12
2.00
2
M
Football
4
1 wk
11
3.25
3
F
Soccer
2
1 mo
5
0.50
4
M
Football
2
7–12 mo
5
2.50
5
M
Rugby
6
>1 y
11
0.40
6
M
Football
3
>1 y
2
0.00
7
M
Football
2
>1 y
2
0.20
8
M
Football
2
>1 y
10
0.65
9
F
Soccer
2
>1 y
7
0.40
M
Football
1
>1 y
5
0.30
Athlete no.
10 a
Most recent concussion.
b
Average current symptom severity(/6).
F = female; M = male.
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Sports Med 2010; 40 (3)
Measuring Action Post-Concussion
2. Results 2.1 CogSport
The simple reaction time metric from CogSport was chosen for analysis, as it has been suggested to be highly sensitive to change postconcussion[20,21] and was the test with a measure that was most directly comparable to the motor task (i.e. both tasks have a reaction time component). The two groups of athletes did not respond at significantly different speeds (t(18) = 0.031; p = 0.98). Plotting individual CA against the mean (– SD) of NCA for the simple reaction time task
a
b 2.67
2.65
2.55
2.45
2.35
Mean log10 RT (CogSport Simple RT task)
2.75 Mean log10 RT (collapsed across target size)
17-inch NEC AccuSync90 [Tokyo, Japan] all set to 85 Hz and 1024 · 768 px). The touch screens were individually calibrated for each participant. The motor task was programmed using E-Prime software (Psychology Software Tools, Pittsburgh, PA, USA). Each trial began with the participant placing an index finger on a fixation square at the bottom centre of the touch screen. After a randomized delay, a target would appear near the top centre of the screen. Participants were instructed to point as quickly and accurately as possible to the target. To manipulate the difficulty of the pointing movements, the size of the target was also randomized. Targets consisted of open squares with sides of 4, 8, 15 and 29 mm, the largest of which subtended approximately 2.7 of visual angle. Participants completed 40 trials (ten per target size) with each hand. For the CA, post-concussion symptoms were documented using a section of the McGill Abbreviated Concussion Evaluation (a condensed paper-and-pencil questionnaire), and a check-list of symptoms presented at the beginning of CogSport. For the NA, history of previous head injury was collected via an on-line questionnaire. The Waterloo Handedness Questionnaire[19] was administered to all participants. The test order and the hand used to begin the motor task were both counterbalanced.
185
2.57
2.47
2.37
2.27
Fig. 1. Response time latencies on the motor task and CogSport. (a) Mean log10 reaction time (RT) data from the motor task for the ten athletes with a previous history of concussion (open circles) plotted against the mean log10 RT (dark horizontal line) and the corresponding standard deviations (grey area) of athletes without concussion. (b) Mean log10 RT data from CogSport for the ten athletes with previous concussion (open circles) plotted against the mean log10 RT (dark horizontal line) and the corresponding standard deviations (grey area) of athletes without concussion.
demonstrates that CA perform normally on the task (figure 1b). 2.2 Motor Task
A three-way mixed factorial design ANOVA was conducted between the three groups, on the log10 RT data.1 Hand used (dominant hand vs non-dominant hand) and target size (4, 8, 15, 29 mm) were included as within-subject factors. There was a main effect of target size (F(3, 111) = 15.83; p < 0.001), indicating that reaction times were faster to larger targets (i.e. speedaccuracy trade-off according to Fitts’ Law). No other main effect or interaction reached significance, although the three-way interaction between group, target size and hand approached significance (F(6, 111) = 2.03; p = 0.07). Surprisingly, post hoc exploration revealed that NCA showed a significant target size by hand interaction (F(3, 27) = 4.68; p = 0.01). Additional post hoc exploration with data collapsed across hand and target size revealed
1 Response time was log10 transformed to normalize the distribution. This was necessitated by the fact that CogSport reports log10 transformed data by default. Thus, to make performance on each task comparable, the same transformation was performed on the motor task data.
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Sports Med 2010; 40 (3)
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a trend towards a main effect of group (F(2, 37) = 2.458; p = 0.078). Although non-significant, CA were slower overall at responding to targets than either NA (t(28) = 2.021; p = 0.053) or NCA (t(18) = -1.766; p = 0.094). The two healthy groups did not significantly differ from one another (t(28) = 0.530; p = 0.60). Mean response time (collapsed across target and hand) for each of the CA was plotted against the mean and standard deviation for the NCA (figure 1a). Unlike the simple reaction time metric in CogSport (figure 1b), five of the concussed athletes fell well outside the normal range of performance. That is, these five CA were strikingly slower than normal. The performance of the concussed athletes was not related to symptom severity ratings (at testing; r = 0.018; p = 0.96), number of concussions (r = -0.176; p = 0.62) or number of concussive symptoms (r = -0.107; p = 0.77). Performance on CogSport and the motor task were uncorrelated (r = 0.04; p = 0.91), and only one CA performed outside of a normal range on both tasks (z > 1; athlete number 8 from table I). 3. Discussion The current research tested a fine motor task based on Fitts’ law[18] where participants rapidly pointed to targets on a touch screen computer. A ballistic pointing task based on Fitts’ Law was chosen as a measure of visuomotor control because it included a range of precision requirements, inherently involving a difficulty component that provided a good opportunity to identify lingering deficits. The results indicate that, while the task may be sensitive to the consequences of concussion, it was overall performance speed that showed decrements in some of the concussed athletes, and not changes in speed-accuracy trade offs. Future research placing different constraints on visuomotor performance will be necessary to flesh out the parameters of the general slowing in performance hinted at here. The goal of the task was to provide a measure significantly more challenging to the visuomotor system than a simple button press. The results indicate that, given a more varied methodological ª 2010 Adis Data Information BV. All rights reserved.
approach, and larger sample sizes, this research direction may be fruitful. Given the small sample size, it is perhaps not surprising that group differences were not large. Further research is needed to determine whether the bimodal distribution observed here in the CA group represents a subset of injured individuals with motor changes – a result hinted at in our sample, but not borne out in our limited analysis of available demographic and symptom data. While the task provides results that suggest potential planning deficits, the sensitivity of the measure may be muted by the relatively low difficulty level of the task. Pointing to static targets that always appear in the same location may simply be too easy to reveal deficits in visuomotor control. Increasing the trial-to-trial variability of the task, perhaps by placing the target in different positions, could increase the number of new parameters required for the motor plan of each trial to increase sensitivity to planning deficits. The complexity and, potentially, the sensitivity to deficits in motor action could be improved by adding a choice-reaction time component, using moving targets, or introducing an aspect of online updating of motor plans (e.g. via a target perturbation task). Nevertheless, the current results are in agreement with previous findings,[15-17] which suggest that supplementing a computer-administered test such as CogSport with a measure of fine motor control could improve sensitivity. This is not to suggest that CogSport, and other batteries like it, are not sufficient for detecting the acute effects of concussion. Instead, we would suggest that in their current state, such tests may miss subtle, longer-lasting changes in fine motor performance. The current research indicates that reaction time, a measure of movement planning ability, will be a potentially useful measure in the development of sensitive measures of the longlasting effects of concussion. 4. Conclusion In summary, we have shown that a fine motor task such as target-directed pointing, may well be more sensitive to the long-term effects of Sports Med 2010; 40 (3)
Measuring Action Post-Concussion
concussion. Future research should explore this possibility further in larger samples, with a longitudinal focus (as opposed to retrospective as in the current case) and with a broader range of complex visuomotor tasks (e.g. intercepting moving targets) that would also represent a more ecologically valid approach to the study of concussion among athletes. Acknowledgements This work was supported by National Sciences and Engineering Research Council (NSERC) of Canada, and Canada Research Chair (Tier II) awards to James Danckert. The authors have no conflicts of interest that are directly relevant to the content of this study.
References 1. Delaney JS, Lacroix VJ, Leclerc S, et al. Concussions among university football and soccer players. Clin J Sport Med 2002; 12 (6): 331-8 2. Powell JW, Barber-Foss KD. Traumatic brain injury in high school athletes. JAMA 1999; 282 (10): 958-63 3. Echemendia RJ, Cantu RC. Return to play following sportsrelated mild traumatic brain injury: the role for neuropsychology. Appl Neuropsychol 2003; 10 (1): 48-55 4. Cantu R, Voy R. Second impact syndrome: a risk in any contact sport. Physician Sportsmed 1995; 23 (6): 27-35 5. McCrory P. Does second impact syndrome exist? Clin J Sport Med 2001 Jul; 11 (3): 144-9 6. McCrory PR, Berkovic SF. Second impact syndrome. Neurology 1998 Mar; 50 (3): 677-83 7. Collie A, Maruff P, Makdissi M, et al. CogSport: reliability and correlation with conventional cognitive tests used in postconcussion medical evaluations. Clin J Sport Med 2003 Jan; 13 (1): 28-32 8. Collie A, Makdissi M, Maruff P, et al. Cognition in the days following concussion: comparison of symptomatic versus asymptomatic athletes. J Neurol Neurosurg Psychiatry 2006 Feb; 77 (2): 241-5 9. Iverson GL, Lovell MR, Collins MW. Validity of ImPACT for measuring processing speed following sports-related concussion. J Clin Exp Neuropsychol 2005; 27 (6): 683-9
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10. Cremona-Meteyard SL, Geffen GM. Persistent visuospatial attention deficits following mild head injury in Australian Rules football players. Neuropsychologia 1994 Jun; 32 (6): 649-62 11. Killam C, Cautin RL, Santucci AC. Assessing the enduring residual neuropsychological effects of head trauma in college athletes who participate in contact sports. Arch Clin Neuropsychol 2005 Jul; 20 (5): 599-611 12. Haaland KY, Temkin N, Randahl G, et al. Recovery of simple motor skills after head injury. J Clin Exp Neuropsychol 1994; 16 (3): 448-56 13. Kuhtz-Buschbeck JP, Stolze H, Go¨lge M, et al. Analyses of gait, reaching, and grasping in children after traumatic brain injury. Arch Phys Med Rehabil 2003 Mar; 84 (3): 424-30 14. Haggard P, Miall RC, Wade D, et al. Damage to cerebellocortical pathways after closed head injury: a behavioural and magnetic resonance imaging study. J Neurol Neurosurg Psychiatry 1995 Apr; 58 (4): 433-8 15. Guskiewicz KM. Postural stability assessment following concussion: one piece of the puzzle. Clin J Sport Med 2001 Jul; 11 (3): 182-9 16. Guskiewicz KM, Ross SE, Marshall SW. Postural stability and neuropsychological deficits after concussion in collegiate athletes. J Athlet Train 2001 Sep; 36 (3): 263-73 17. Heitger MH, Jones RD, Dalrymple-Alford JC, et al. Motor deficits and recovery during the first year following mild closed head injury. Brain Inj 2006 Jul; 20 (8): 807-24 18. Fitts PM. The information capacity of the human motor system in controlling the amplitude of movement. J Exp Psychol Gen 1954 Jun; 47 (6): 381-91 19. Steenhuis R, Bryden M. Different dimensions of hand preference that relate to skilled and unskilled activities. Cortex 1989 Jun; 25 (2): 289-304 20. Makdissi M, Collie A, Maruff P, et al. Computerised cognitive assessment of concussed Australian Rules footballers. Br J Sports Med 2001 Oct; 35 (5): 354-60 21. Collie A, Darby D, Maruff P. Computerised cognitive assessment of athletes with sports related head injury. Br J Sports Med 2001 Oct; 35 (5): 297-302
Correspondence: Dr James Danckert, Department of Psychology, University of Waterloo, 200 University Avenue West, Waterloo, Ontario, N2L 3G1, Canada. E-mail:
[email protected]
Sports Med 2010; 40 (3)
Sports Med 2010; 40 (3): 189-206 0112-1642/10/0003-0189/$49.95/0
REVIEW ARTICLE
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New Horizons for the Methodology and Physiology of Training Periodization Vladimir B. Issurin Elite Sport Department, Wingate Institute, Netanya, Israel
Contents Abstract. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1. Traditional Model of Periodization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1 History of Training Periodization as a Scientific Problem and Coaching Concept . . . . . . . . . . . . 1.1.1 Precursors of Periodization Training in Ancient Rome and Greece. . . . . . . . . . . . . . . . . . . . 1.1.2 Contemporary Stage of Developing Training Periodization . . . . . . . . . . . . . . . . . . . . . . . . . 1.2 Basic Positions of the Traditional Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2.1 Generalized Concept of ‘Load-Recovery’ Interaction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2.2 Principles of Periodized Training . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2.3 Hierarchy of Periodized Training Cycles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2.4 Variations of the Traditional Annual Cycle Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.3 Major Limitations of Traditional Periodization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2. Alternative Models of Periodization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 Factors Affecting the Revision of Traditional Periodization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Periodization Charts in Team Sports . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3 Linear and Non-Linear Periodization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4 Non-Traditional Models of Training Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4.1 Annual Performance Trends of Great Athletes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4.2 Concentrated Unidirectional Training Plans. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3. Block Periodization as an Alternative Approach to High-Performance Training . . . . . . . . . . . . . . . . . . 3.1 Earliest Efforts to Implement Block Periodization. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Scientific Concepts Affecting the Block-Periodized Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2.1 Cumulative Training Effect . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2.2 Residual Training Effect . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 Basic Positions of Block-Periodized Training . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3.1 Basic Principles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3.2 Taxonomy of Mesocycle Blocks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3.3 Compiling an Annual Cycle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4. Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Abstract
189 190 191 191 191 191 191 192 193 193 193 194 195 195 196 197 197 197 198 198 199 199 200 201 201 201 202 203
The theory of training was established about five decades ago when knowledge of athletes’ preparation was far from complete and the biological background was based on a relatively small amount of objective research findings. At that time, traditional ‘training periodization’, a division of the entire seasonal programme into smaller periods and training units, was proposed and elucidated. Since then, international sport and sport science have experienced tremendous changes, while the traditional training
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periodization has remained at more or less the same level as the published studies of the initial publications. As one of the most practically oriented components of theory, training periodization is intended to offer coaches basic guidelines for structuring and planning training. However, during recent decades contradictions between the traditional model of periodization and the demands of high-performance sport practice have inevitably developed. The main limitations of traditional periodization stemmed from: (i) conflicting physiological responses produced by ‘mixed’ training directed at many athletic abilities; (ii) excessive fatigue elicited by prolonged periods of multi-targeted training; (iii) insufficient training stimulation induced by workloads of medium and low concentration typical of ‘mixed’ training; and (iv) the inability to provide multi-peak performances over the season. The attempts to overcome these limitations led to development of alternative periodization concepts. The recently developed block periodization model offers an alternative revamped approach for planning the training of high-performance athletes. Its general idea proposes the sequencing of specialized training cycles, i.e. blocks, which contain highly concentrated workloads directed to a minimal number of targeted abilities. Unlike the traditional model, in which the simultaneous development of many athletic abilities predominates, block-periodized training presupposes the consecutive development of reasonably selected target abilities. The content of block-periodized training is set down in its general principles, a taxonomy of mesocycle blocks, and guidelines for compiling an annual plan.
Sport science is widely held to be the major contributor to progress in sport, and in particular to the enhancement of athletic training. Its general theory sets out and summarizes the most meaningful basic assumptions regarding the essence, terminology, major effects and scientific background for training athletes. Training periodization is definitely one of the most practically oriented branches of training theory. It was established in general in the 1960s and was initially based on the experience of highperformance sport in the former USSR and physiological surveys published by prominent Soviet scientists at that time.[1-4] A little later, training periodization was conceptualized,[5] republished in many countries[6-9] and took on the status of a universal and monopolistic background for training planning and analysis. Certainly, the continued evolution of sport and sport science has contributed to an enormous accumulation of knowledge, evidence and training technologies. Nonetheless, the traditional model of periodization as established about five decades ago has not changed much since then. ª 2010 Adis Data Information BV. All rights reserved.
During this time, and especially in recent years, alternative approaches to training design have appeared, mostly in professional reports and coaches’ magazines, and have been subjected to little, if any, serious scientific consideration. The purpose of this paper is to review training periodization in the light of the outcomes of previous and recent studies of the traditional model and up-to-date versions of training design. 1. Traditional Model of Periodization As athletic training becomes more strenuous and professional, the need for a scientific background for conscious planning becomes more desirable. Thus, ‘training periodization’ met the expectations of practice: it was described as the purposeful sequencing of different training units (long duration, medium duration and short-term training cycles and sessions) so that athletes could attain the desired state and planned results. This section introduces a brief history of training periodization and its basic tenets, which underlie the popular traditional model used worldwide. Sports Med 2010; 40 (3)
New Horizons for Training Periodization
1.1 History of Training Periodization as a Scientific Problem and Coaching Concept 1.1.1 Precursors of Periodization Training in Ancient Rome and Greece
The history of ancient medicine and philosophy provides us with memorable milestones of training theory. These pieces of human creation include the names of great ancient thinkers such as Galen and Philostratus. The famous Roman physician and philosopher Galen (Claudius Aelius Galenus, second century AD) in his treatise Preservation of Health proposed the original categorization of exercises, which can be qualified as the precursor of contemporary periodization for strength training.[10] His exercises with sequences from ‘‘exercises with strength but without speed’’ to developing ‘‘speed apart from strength and force’’ and, finally, to ‘‘intense exercises combining strength and speed,’’[11] astonish us by their logic and creativity, although they can be questioned in the light of contemporary knowledge. Another example of annual periodization can be found in the essay Gymnasticus of the prominent ancient Greek scientist Philostratus, ‘the Athenian’, who also lived in the second century AD.[12] His description of pre-Olympic preparation contains a compulsory 10-month period of purposeful training followed by 1 month of centralized preparation in the city Elis prior to the Olympic Games. This final part of the annual cycle resembles pre-Olympic training camps practiced by any national squads today. The guidelines set down by Philostratus, which sequence small, medium and large workloads within a 4-day training cycle, can serve as a brilliant illustration of the ancient approach to short-term planning. 1.1.2 Contemporary Stage of Developing Training Periodization
The foundations of the contemporary theory of periodization were first proposed in the former USSR, where textbooks for coaches and physical education students called for the division of the entire preparation process into separate periods of general and more specialized training.[13] This separation into general preparation, encompassing training for cardiorespiratory fitness, general ª 2010 Adis Data Information BV. All rights reserved.
191
coordination and basic athletic abilities, and specialized preparation with a focus on sportspecific traits, remains till now. This general approach was adopted in most sports, and earlier textbooks on skiing,[14] swimming[15] and track and field[16] were written based on these commonly accepted approaches. In the 1950s, a number of physiological surveys were published.[1-4] At the same time, studies provided serious biological background support and a scientific basis for the guidelines. However, the first serious summary of up-to-date scientific and empiric concepts was compiled by Lev P. Matveyev,[5] making him the recognized founder of the traditional theory of training periodization. Actually, training periodization – meaning ‘the subdivision of the seasonal programme into smaller periods and training cycles’ – appears to be an important and indispensable part of training theory. 1.2 Basic Positions of the Traditional Model
The basic positions of the traditional theory of training periodization include: (i) a general elucidation of load and recovery in view of the supercompensation concept; (ii) general principles of periodized training; (iii) the hierarchy of periodized training cycles; and (iv) proposed variations of the annual cycle. Let us consider each of these positions. 1.2.1 Generalized Concept of ‘Load-Recovery’ Interaction
Perhaps the first scientifically based explanation of fitness enhancement was offered in the mid-1950s by Soviet biochemist Yakovlev,[2,17] who reported on the supercompensation cycle after a single workout. The phenomenon of supercompensation is based on the interaction between load and recovery (figure 1). The supercompensation cycle is induced by the physical load, which serves as the stimulus for further reaction. The single load, which is considered the first phase of the cycle, causes fatigue and acute reduction in the athlete’s work capability. The second phase is characterized by marked fatigue and a pronounced process of recovery; consequently, towards the end of this phase the Sports Med 2010; 40 (3)
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Work capability Load
Phases
Fatigue and recovery
Supercompensation
Return to pre-load level
Fig. 1. The supercompensation cycle, showing the trend of work capability following a single load.[2]
athlete’s work capability increases and reaches pre-load levels. During the third phase, work capability continues to increase, surpassing the previous level and achieving the climax, which corresponds to the supercompensation phase. In the fourth phase, work capability returns to the pre-load level. This load-recovery pattern has been proven using the depletion and restoration of biochemical substances such as creatine phosphate[18,19] or glycogen.[20,21] A similar trend was noticed using various physiological estimates[22] and sportspecific tests.[23,24] Based on the supercompensation theory, Matveyev[25] proposed a general scheme of several-load summation. According to this scheme a number of workouts can be performed while the athlete is still fatigued, and the supercompensation effect can be induced following a specific training cycle but not a single workout. This position formed the foundation for compiling small training cycles (microcycles) and designing pre-competition training. 1.2.2 Principles of Periodized Training
A number of specialized principles were proposed by Matveyev[25] and popularized in further publications on training theory. One of the basic tenets determining the general concept of periodized training is the ‘principle of cyclical training design’. This principle applies to periodic cycles in athletic training. Over a long period, the many components of long-term training repeat ª 2010 Adis Data Information BV. All rights reserved.
and return periodically. The rationales for this approach pertain to: an habitual rhythm of working days and vacation; the cyclical character of adaptation that presupposes periodical regeneration of adaptability; the sharing of main tasks that allows the development of general and sportspecific motor abilities, technical and tactical skills; and the competition schedule, which strongly determines the apexes of athletes’ preparation and periodic changes in the training programme. The principle of ‘unity of general and specialized preparation’ emphasized the importance of specific workloads during a long period of early season training, and the necessity of general conditioning workouts within the period of frequent competitions. It is worthy of note that this principle was claimed at a time when ‘seasonal’ impacts were much stronger than they are today. Such sports as skiing, skating, rowing, ice hockey and soccer were strictly determined by seasonal conditions. Correspondingly, stressing the linkage between general and specialized preparation was necessary for both methodical and organizational reasons. Another meaningful principle called ‘waveshape design of training workloads’ was postulated during the 1950s for short-term (weekly programme) and for long-term (annual cycle) planning design. This principle proclaimed the need to alternate days of high load and lower load, sequencing large, medium and small workloads. The physiological sense of this principle was supported by the outcomes of biochemical and physiological studies conducted at that time.[1-4] The findings of post-exercise recuperation showed that such sequencing of workloads facilitates the probability of favourable training responses and the prevention of excessive fatigue accumulation. Similarly, the mediumsize waves in monthly training and large waves in the annual training plan were intended to refresh athletes’ adaptability and avoid the monotony of repetitive training routines. The ‘principle of continuity’ was postulated at a time when interruptions in training were relatively frequent and excusable. The principle claimed that such interruptions are very harmful biologically, pedagogically and organizationally. Sports Med 2010; 40 (3)
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It also proposed that breaks in training for recuperation and social needs should be thoroughly planned, whereas sporadic breaks should be totally excluded. Nowadays, with the majority of high-performance athletes training at professional and semiprofessional levels, the importance of this principle is still relevant although now it seems quite trivial. 1.2.3 Hierarchy of Periodized Training Cycles
As stated in the introduction, the general concept of periodized training was proposed in the 1960s and has been adopted by many generations of analysts and coaches (table I). The upper level of the hierarchical periodized system belongs to multi-year preparation, where the Olympic quadrennial cycle is of particular importance. The next level of the hierarchy is represented by the macrocycles, which usually last 1 year but can be shortened to half a year and even less. The macrocycles are divided into training periods, which fulfil a key function in traditional theory: they divide the macrocycle into two major parts, the first for more generalized and preliminary work (preparatory period), and the second for more event-specific work and competitions (competition period). In addition, a third and the shortest period is set aside for active recovery and rehabilitation. The next two levels of the hierarchy are reserved for the mesocycles (medium-size training cycles) and microcycles Table I. The hierarchical structure and content of periodized training cycles[5,6] Preparation component and its duration
Content
Multi-year preparation (years)
Long-lasting systematic athlete training composed of 2-year or 4-year (quadrennial) cycles
Macrocycle (months)
Large size training cycle (frequently annual cycle) that includes preparatory, competition and transition periods
Mesocycle (weeks)
Medium size training cycle consisting of a number of microcycles
Microcycle (days)
Small size training cycle consisting of a number of days; frequently 1 week
Workout (h/min)
A single training session that is performed individually or within a group
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(small-size training cycles); the bottom part belongs to workouts and exercises, which are the building blocks of the entire training system. Because the periods are the most meaningful components in the traditional theory, their particularities and content are clearly prescribed. The preparatory period programme should contain extensive, high volume, diversified exercises to develop mostly general physical and technical abilities, whereas the competitive period should be focused on more intensified, specialized exercises of reduced volume, including participation in competitions. The biological background of such a design presupposes a gradual enhancement of athletes’ adaptability induced by increasing training stimulation. 1.2.4 Variations of the Traditional Annual Cycle Model
The earlier versions of periodized plans were oriented to macrocycles lasting an entire season. Such a planning approach can be defined as a ‘one-peak annual plan’. In the early 1960s, such a design corresponded to many seasonal sports such as rowing, cycling, skating and skiing. The appearance of various sport facilities and the general progress of sport made it necessary to expand competitive practice. Thus, the one-peak annual design became insufficient and ‘two-peak annual plans’ were introduced. However, further progress in sport facilities, diversification of competitions and increased professionalism of training led to the elaboration of ‘three-peak preparation models’,[26,27] which became the last commonly recognized modification of traditional periodization (figure 2). 1.3 Major Limitations of Traditional Periodization
Although the traditional model proposes a sequencing of different targets (from general to specific; from extensive to more intensive work, etc.), the predominant methodical approach is predicated on the simultaneous development of many targeted abilities. For instance, preparatory period training for high-performance athletes in endurance, combat sports, ball games and aesthetic sports usually contains a programme for Sports Med 2010; 40 (3)
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Transition period Competition period Preparatory period
Athletic result related to seasonal best (%)
100 98 96 100 98 96 100 98 96
Fig. 2. One-peak, two-peak and three-peak annual cycles, displaying the annual trend of athletic results related to the seasonal best achievement.
the development of general aerobic ability, muscle strength and strength endurance, improvement of general coordination, general explosive ability and general speed, basic mental and technical preparation, mastery of the tactical repertory, treatment of previous injuries, etc. Each of these targets requires specific physiological, morphological and psychological adaptation, and many of these workloads are not compatible, causing conflicting responses. These disadvantages of the traditional model may be negligible for low-level athletes, where a complex mixed programme makes training more attractive and entertaining. However, for high-performance athletes the limitations of traditional periodization raise serious obstacles to further progress (table II). Obviously, these limitations substantially decrease the quality of training. Unlike novices and medium-level athletes, who require relatively low training stimulation to progress, high-performance athletes enhance their preparedness and performance through large amounts of training stimuli that can hardly be obtained using traditional multi-targeted mixed training. One additional drawback of the traditional model is its inability to enable athletes to partiª 2010 Adis Data Information BV. All rights reserved.
cipate successfully in many competitions. The traditional periodization proposes one-, two- and three-peak designs, where the annual cycle consists of one, two or three macrocycles.[24-26] However, even the three-peak design does not satisfy the international sport trend towards competitions throughout the year. The multi-peak tendency of modern top-level sport is in obvious contradiction to traditional periodization.[28] All of these circumstances and factors contributed to the search for alternative training approaches, which were offered by creative coaches and scientists and are considered below. 2. Alternative Models of Periodization The initial impetus to reform traditional periodization first began among prominent coaches in different sports when they saw that the instructions for training management restricted their creativity and didn’t allow their athletes to attain their highest achievements. Attempts to improve the traditional model were cosmetic in character at first; however, in the early 1980s, reformation tendencies became stronger. The most influential factors evincing this revision were the substantial Sports Med 2010; 40 (3)
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changes occurring at that time in world sport and athletic training. 2.1 Factors Affecting the Revision of Traditional Periodization
A number of factors effected a reformation of the traditional training system and encouraged a search for alternative approaches. These factors included limitations of traditional periodization in terms of the concurrent development of several motor and technical abilities (table II), and dramatic changes in world sport in recent decades. Evidently, the tremendous changes in world sport over recent decades had a strong influence on the evolution of the training process. Despite the uniqueness of each sport, these changes appeared to have an overall tendency worldwide, with a number of main characteristics. An increase in the total number of competitions:[24,44] correspondingly, their contribution to training stimuli has increased dramatically. Financial motivation of top athletes, which became much stronger than previously. Closer cooperation and sharing among world coaches, which led to enhancement of training quality and level of athletic performances. The struggle against illegal pharmacological interventions, which affected and which led to the prevention of such harmful technologies in high-performance sport.[45] Implementation of advanced sport technologies and training methods such as monitoring of
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heart rate, blood lactate, movement rate, etc.;[35,46] improvement of medical follow-up methods;[47,48] and elaboration of advanced training equipment and new materials.[49-51] These advances, combined with increased sharing of successful planning approaches among coaches, have spurred tremendous progress in training methodology. 2.2 Periodization Charts in Team Sports
It has been widely acknowledged for some time that preparation planning in team sports differs drastically from planning routines in individual athletic disciplines. Several surveys of team sports report the adoption of periodized models of the traditional concept.[52,53] However, many recent publications declare that basing training programmes on the ‘classic model’ of periodization is counterproductive for most team sports.[54-56] The playing season for team sports like football, rugby, basketball, ice hockey, etc. lasts 20–35 weeks in Europe and North America.[56,57] It has been shown that a training design following traditional planning precepts leads to dramatic reductions in lean body mass,[42] maximal strength of relevant muscle groups,[58,59] maximal anaerobic power[60] and even maximal speed.[61] Application of the traditional model is still realistic for junior and low-level athletes, whose competition phases are relatively short and can be considered similar to those of individual sports. However, to consider the playing season
Table II. Major limitations of traditional periodization for training high-performance athletes Factor
Limitations
Energy supply
Lack of sufficient energy supply for concurrent performance of diversified workloads[28-30]
Cellular adaptation
Training consequences such as mitochondrial biogenesis, synthesis of myofibril proteins and synthesis of anaerobic enzymes presuppose separate pathways of biological adaptation[31-33]
Post-exercise recovery
Because different physiological systems require different periods of recuperation, athletes do not get sufficient restoration[34-36]
Compatibility of various workloads
Exercises combining various modalities often interact negatively due to energy deficit, technical complexity and/or neuromuscular fatigue[37-39]
Mental concentration
Performance of stressed workloads demands high levels of mental concentration that cannot be directed at many targets simultaneously[40,41]
Sufficiency of training stimuli for progress
Sport-specific progress of high-level athletes demands large amounts of training stimuli that cannot be obtained by concurrent training for many targets[24,42]
Competitive activity
Inability to provide multi-peak preparation and successful performances during the entire annual cycle[37,43]
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Phases
Pre-season
In-season
Postseason break
AR MC GS
TP SSSP MS SSE
MC TTS SSE
AR PR
Low to medium
Medium to high
High to very high
Low
3−4 weeks
6−20 weeks
15−35 weeks
1−4 weeks
Duration Load
Offseason
Targets
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Fig. 3. Schematic presentation of an annual preparation chart in team sports.[40,41,49] AR = active recovery; GS = general strength; MC = metabolic conditioning; MS = maximal speed; PR = psychological recovery; SSE = sport-specific endurance; SSSP = sport-specific strength and power; TP = technique perfection; TTS = techno-tactical skills.
of qualified athletes from the viewpoint of traditional periodization leads to an absurd situation in which the climax phase of annual preparation consists of 20–30 competitive microcycles. In this situation the generalized concepts of peaking and tapering make no sense. Perhaps this is one of the reasons that many experts in team sports avoid utilizing traditional terms such as preparatory and competition periods and use team sportspecific terms like ‘off-season’, ‘pre-season’ and ‘in-season’ training.[56,62] A general presentation of the annual cycle for qualified players specifies the relevant phases of their preparation in terms of duration, dominant training targets and load level (figure 3). Of course, because of the variation among team sports, national competition calendars and the particularities of training for different age groups, it is impossible to compile a universal chart model. It can be suggested that training in off-season and pre-season phases can resemble training in the traditional periodization approach.[56] A careful inspection of the preparation programmes proposed for high-performance players reveals that even this is highly restricted. Indeed, the traditional model facilitates the acquisition of an optimal combination of all sportspecific abilities to ensure peak performances for ª 2010 Adis Data Information BV. All rights reserved.
a limited number of days, whereas rational preparation planning in team sports presupposes the maintenance of sport-specific preparedness over 4- to 8-month periods. From a physiological viewpoint, the importance of rationally periodized training in team sports cannot be underestimated. The long playing season with its large number of stressful games frequently leads to harmful consequences such as pronounced catabolic responses,[61,63] musculoskeletal disorders and a high incidence of injuries.[56] Reasonably structured training that avoids conflicting physiological responses facilitates the beneficial maintenance of sport-specific preparedness and prevents a decline in relevant physiological capabilities and traits.[62,64,65] 2.3 Linear and Non-Linear Periodization
Attempts to reform and rationalize traditional periodization were undertaken by several researchers and training analysts. Their intention was to update the traditional model and to distinguish between so-called ‘linear’ and ‘non-linear’ periodization.[66,67] Proponents of the revised version proceeded from the assumption that traditional periodization postulates a gradual progressive increase in intensity and can therefore be termed a linear model. In contrast, the non-linear model offers drastic variations of intensity within the weekly and daily programme. This ‘variation factor’ was especially emphasized in the term ‘undulating periodization’[66] that was attached to the non-linear model. In reality, traditional periodization does not ignore – and even requires – wave-shaped fluctuations of workloads within the single-day, micro- and mesocycles; it also does not restrict the amplitude of these variations. Moreover, the principle of wave-shape training design emphasizes the importance of this variation factor (see section 1.2.2). This inconsistency of the proposed concept was noted by Stone and co-authors.[68,69] Apparently the traditional model is both ‘non-linear’ and ‘undulating’, whereas the ‘linear model’ looks extremely artificial and contradicts general physiological and methodic demands. The opponents of this concept correctly declared that the use of terminology Sports Med 2010; 40 (3)
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such as ‘linear’ and ‘non-linear’ is misleading.[70] The author completely supports this position and assumes that such is the case when an attempt is made to attach non-traditional terms to well known traditional training approaches. 2.4 Non-Traditional Models of Training Design
As noted in sections 2.1, 2.2 and 2.3, the alternatives to traditional periodization models were created both by practitioners (prominent coaches and athletes) and scientists. This section presents examples of such alternatives. 2.4.1 Annual Performance Trends of Great Athletes
One of the typical characteristics of contemporary high-performance sport is multi-peak preparation for attaining excellent results throughout a season, and not two to three times as in traditional periodization. The examples of world-leading athletes from individual sports demonstrate incredible stability in peak performances at relatively short intervals (14–43 days) between peaks.[44,71] The diagram in figure 4 displays the annual performance trend of one of the greatest track and field athletes, Sergei Bubka (USSR [since 1991 Ukraine]), who earned an Olympic gold medal in 1988 and five World Championship gold medals in pole vault. His world record (614 cm) stands to this day. 620
Result (cm)
610 600 590 580 570
The graph indicates six peaks where the athlete obtained 12 results higher than 590 cm that corresponds to the result of the winner at the 2009 World Championship. A brief analysis of this athlete’s annual performance trend reveals the following characteristics about his personal model of periodized training. During a period of about 250 days, Sergei Bubka took part in a long series of competitions; this period was preceded by pre-season preparation that lasted about 3 months, during which time he did not take part in official tournaments. During a period of 9 months the athlete took part in a number of competitions and his results ranged from 92% to 100% of personal best; this extensive competitive practice provided the athlete with very strong training stimuli. The intervals between peak performances varied from 12 to 43 days (usually 22–27); this time span was sufficient for active recovery but absolutely unrealistic in order to fulfil any periods of the generalized preparation as proposed in traditional periodization.[24-27] It is obvious that this long time span (9 months) during which the athlete successfully competed at the world-class level cannot be subdivided into traditional preparatory and competition periods. On the other hand, the athlete’s basic abilities (maximal strength, aerobic regeneration capacity) needed to be maintained at a sufficient level. Therefore, the appropriate short-term training cycles for basic abilities and recovery were incorporated into his programme. Of course, Sergei Bubka is a unique athlete, but the example of his preparation is typical for contemporary high-performance sport, as can be seen by similar examples for other great athletes.[44,71] Obviously, the traditional scheme does not provide such a multi-peak preparation design, and great athletes and their coaches had to find their own periodization models as alternatives to the traditional approach. 2.4.2 Concentrated Unidirectional Training Plans
560 Jan
Feb
Mar
Apr
May
Jun
Jul Aug
Sep
Fig. 4. The annual pole vault performance trend of Sergei Bubka in the 1991 season.[28]
ª 2010 Adis Data Information BV. All rights reserved.
The concept of concentrated unidirectional training was proposed by Verchoshansky[72] for preparation in the power disciplines. This training design was tested during preparation of Sports Med 2010; 40 (3)
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high jumpers, who executed a 4-week mesocycle of highly concentrated strength training followed by a restitution mesocycle lasting 2 weeks during which the athletes focused on perfecting technical skills, speed exercises and general fitness training. During the first loading mesocycle the relevant strength indicators decreased gradually; however, during the subsequent restitution mesocycle these indices increased to a higher level than had been recorded prior to the training programme. The author recommends repeating this combination of loading and restitution mesocycles during the annual cycle. The gains obtained in strength and power can be explained as part of the long-lasting delayed effect (LLDE), which is a subject deserving special consideration. The author claims that LLDE is conditioned by highly concentrated, large-volume workloads during the first phase, and reduced workloads in the second phase.[73] The concept presupposes that the lower the decrease the functional indices move in the first phase, the higher they will increase in the second phase; the duration of the first phase varies in duration from 4 to 12 weeks. Correspondingly, a similar time span is expected for positive after-effects following this concentrated training. The idea of concentrated unidirectional training has been discussed extensively in the literature,[74-76] and was transferred from the power disciplines to other sports, specifically in a longterm study of qualified adult basketball players.[76] The annual cycle was subdivided into two macrocycles lasting 23 and 19 weeks. Each macrocycle consisted of three stages: (i) a loading phase of strength and power workloads (8 and 3 weeks, respectively); (ii) a restitution phase (2 and 3 weeks, respectively); and (iii) a competition stage, where the players took part in regional championship (13 weeks in both cases). The experimental group, which had no control counterpart, significantly enhanced results in power tests, and their dynamics corresponded to the trend proposed by the LLDE concept. Unfortunately, the authors did not report the results of the athletes in the basketball tournament, which was definitely the team’s first priority. It can be suggested that a reduction of functional backª 2010 Adis Data Information BV. All rights reserved.
ground during prolonged loading phases can have a deleterious effect on sport-specific preparedness and reduce the effectiveness of team practice. In conclusion, it is worth noting that performances in most sports require manifestations of multiple physical and technical abilities. This definitely restricts application of the unidirectional training concept to the actual design of preparation programmes. 3. Block Periodization as an Alternative Approach to High-Performance Training In the early 1980s, the term ‘training blocks’ became popular and widely used among highperformance coaches. Of course, it was not conceptualized initially and was found mostly in coaches’ jargon. Nevertheless, in its most comprehensive connotation it referred to ‘‘a training cycle of highly concentrated specialized workloads.’’[37] Such cycles contain a large volume of exercises directed at a minimal number of targeted abilities. As a planning approach, training blocks seemed an alternative to traditional multi-targeted mixed training, which was under extensive criticism by creative coaches and researchers. Gradually, successful attempts to implement training blocks led to the appearance of a preparation system called ‘block periodization’. As a new methodological approach, block periodization has been dealt with in several publications, which are considered below. 3.1 Earliest Efforts to Implement Block Periodization
It can be suggested that the first attempts to implement training blocks in practice were not documented and survive mostly from anecdotal reports. However, at least three successful experiences in block-periodized training were systematized and published. One of the pioneers in reforming traditional periodization was Dr Anatoly Bondarchuk, who coached the gold, silver and bronze medal winners in the hammer throw at the 1988 and 1992 Olympic Games and many other top-level Sports Med 2010; 40 (3)
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athletes. The system he created comprised three types of properly specialized mesocycle blocks: developmental blocks, in which workload levels gradually increase to maximum; competitive blocks, in which the load level is stabilized and athletes focus on competitive performance; and restoration blocks, in which athletes utilize active recovery and prepare for the next developmental programme. The sequencing and timing of these blocks depends on the competition schedule and on individual athlete’s responses.[77,78] A similar block-periodized model was proposed and implemented in the preparation of toplevel canoe-kayak paddlers.[79] Three types of mesocycle blocks were elucidated: accumulation, which was devoted to developing basic abilities such as general aerobic endurance, muscle strength, and general movement techniques; transformation, which focused on developing more specific abilities like combined aerobic-anaerobic or anaerobic endurance, specialized muscle endurance, and proper event-specific technique; and realization, which was designed as a pre-competitive training phase and focused mainly on race modelling, obtaining maximal speed and recovery prior to the forthcoming competition. These three mesocycles were combined into a separate training stage, lasting 6–10 weeks, which ended with competition; a number of training stages formed the annual macrocycle. The radically reformed preparation programmes resulted in outstanding performances of the USSR national canoe-kayak team, who earned three gold and three silver medals in the 1988 Seoul Olympic Games and eight and nine gold medals in the World Championships of 1989 and 1990, respectively.[80] One more successful experiment with this approach was conducted by world-renowned swimming expert Gennadi Touretski, who coached Alexander Popov (Russia) – five-time Olympic Champion and multiple World and European champion – and Michael Klim (Australia) – two-time Olympic champion, multiple World champion and medal winner. Touretski subdivided the annual cycle into a number of stages lasting 6–12 weeks, where each one comprised four training blocks in the followª 2010 Adis Data Information BV. All rights reserved.
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ing sequence: preparation, general, specific and competitive.[81] Later, the author modified this taxonomy and called them the general block, which focused on aerobic and varied coordinative workloads, the specific block, which was devoted to developing event-specific energetic mechanisms and competitive speed, and the competitive block, which corresponds to what today is commonly called ‘tapering’, and culminates with competition.[82] This stage is usually followed by a short recovery cycle. Despite the obvious uniqueness of each sport in which these experiments were undertaken, the principal methodological demands of training were almost identical: The authors created training blocks in which workloads focus on a minimal number of targets. The total number of proposed blocks is relatively small (three to four). This is in contrast to the traditional theory, in which the mesocycle taxonomy includes 9–11 types.[6,24-27] The duration of a single mesocycle block ranges from 2 to 4 weeks, which allows the desired biochemical, morphological and coordinative changes to occur without excessive fatigue accumulation. The joining of single mesocycles forms a training stage: their correct sequencing is beneficial to competitive performance, i.e. peaking. 3.2 Scientific Concepts Affecting the Block-Periodized Model
At least two contemporary scientific concepts had a distinct impact on the establishment of the block periodization preparation system: the cumulative training effect and the residual training effect. 3.2.1 Cumulative Training Effect
In terms of competitive sport, the cumulative effect of long-term training is the primary factor that, to a great extent, determines an athlete’s success. The cumulative training effect can be expressed as ‘‘changes in physiological capabilities and level of physical/technical abilities resulting from a long-lasting athletic preparation.’’[37] Sports Med 2010; 40 (3)
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Correspondingly it can be reflected by two groups of indicators: (i) physiological and biochemical variables, which characterize changes in the athlete’s biological status; and (ii) variables of sport-specific abilities and athletic performance, which characterize changes in the athlete’s preparedness. The functional limits of the various physiological systems cannot be increased to the same extent, and different physiological indicators of cumulative training effects vary within their appropriate range. The most pronounced changes can be obtained in aerobic abilities. More specifically, purposeful endurance training can dramatically increase aerobic enzymes, the number of mitochondria, myoglobin content and muscle capillarization.[83,84] Unlike aerobic ability determinants, the characteristics of anaerobic metabolism can be improved to a lesser extent. This applies to anaerobic enzymes and particularly to peak blood lactate and creatine phosphate storage, with increases that are relatively small even when training is highly intensive.[85,86] Cumulative training effects attained in various sport-specific abilities strongly depend on changes in the physiological variables mentioned above. Thus, the improvement rate in aerobic endurance disciplines is much higher than in events demanding maximal anaerobic power and capacity. Gains in maximal strength are determined by changes in the musculoskeletal system and the neural contraction mechanism.[87] Managing the cumulative training effect presupposes the planning and regulation of workloads over relatively long periods, which involves competence in training periodization. The concept of cumulative training effect is extremely important for both traditional and block periodization models, although the usual trend of physiological and sport-specific variables differs in each alternative system. Multi-targeted mixed training, typical of the traditional model, causes an increase in basic athletic abilities in the preparatory period followed by their decline in the subsequent competition period, whereas the sport-specific abilities are suppressed in the prolonged preparatory period and increase during the competition period. The block periodization ª 2010 Adis Data Information BV. All rights reserved.
system with its multi-peak preparation allows athletes to maintain both basic and sport-specific abilities in a relatively narrow range during the entire season.[71,77] 3.2.2 Residual Training Effect
The residual training effect concept is relatively new and is less known than other types of training outcomes. Long-lasting training is intended to develop many motor abilities, which remain at a heightened level for a given period after training cessation. This retention belongs to another special type of training effect called the ‘residual training effect’, which can be characterized as ‘‘the retention of changes induced by systematic workloads beyond a certain time period after the cessation of training.’’[37] The general approach to ‘training residuals’ induced by ‘residual effects of training’ was conceptualized initially by Brian and James Counsilman,[88] and focused mainly on the longterm aspects of biological adaptation. They logically proposed the existence of long-lasting training residuals as an important background element of training theory. From the viewpoint of general adaptation and long-lasting sport preparation, long-term training residuals are very important. However, for designing training programmes, short-term training residuals are of primary importance. The phenomenology of the residual training effect is closely connected with the process of detraining, which may occur selectively according to specific abilities when they are not stimulated by sufficient training.[89-91] When training is designed in the traditional manner and many abilities are developed simultaneously, the risk of de-training is negligible because each target (given physical or technical abilities) receives some portion of the stimuli. However, if these abilities are developed consecutively, as proposed by the block periodization system, the problem of de-training becomes important. Indeed, if an athlete develops one ability and loses another one at the same time, the coach should take into account the duration of the positive effect of a given type of training after its cessation and how fast the athlete will lose the attained ability level when he/she Sports Med 2010; 40 (3)
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Table III. Factors affecting the duration of short-term training residuals[37,88,92,93] Factor
Influence
1. Duration of training before cessation
Longer training causes longer residuals
2. Load concentration level of training before cessation
Highly concentrated training compared with complex multi-component training causes shorter residuals
3. Age and duration of sport career of athletes
Older and more experienced athletes have longer residuals
4. Character of preparation after cessation of concentrated training
Use of appropriate stimulatory loads allows prolonged residuals and prevents fast de-training
5. Biological nature of developing abilities
Abilities associated with pronounced morphological and biochemical changes like muscle strength and aerobic endurance have longer residuals; anaerobic alactic and glycolitic abilities have shorter residuals
stops training for it. In other words, the coach has to know the residual effect of each type of training. The duration of training residuals varies depending on several methodological and physiological factors (table III). It can be concluded that the prediction, evaluation and programming of cumulative and residual training effects appear to be meaningful and even indispensable components of blockperiodized preparation. 3.3 Basic Positions of Block-Periodized Training
The basic positions of block-periodized training contain: (i) general principles; (ii) a taxonomy of mesocycle blocks; and (iii) guidelines for compiling an annual plan.
abilities within a single block (the alternative is complex mixed training in which many abilities are developed simultaneously). Furthermore, in a majority of sports, the number of decisive sportspecific abilities exceeds the number of abilities that can be trained simultaneously in a block with highly concentrated workloads. Thus, the third principle proposes that consecutive development is the only possible approach for training design in a block periodization system. Finally, the fourth principle demands implementation of an appropriate taxonomy of mesocycle blocks, which allows for structuring the preparation and compiling block-periodized programmes (see section 3.3.2). Therefore, medium-sized training cycles, called mesocycle blocks, are the most prominent embodiment of the block periodization concept in general.
3.3.1 Basic Principles
The principles articulate the general idea of block periodization and summarize the outcomes of previous studies (table IV).[71,93-95] The first and most crucial basic principle calls for a high concentration of training workloads within a given block. This means directing a large number of exercises and tasks to selected target abilities while others are not subjected to training stimulation. Of course, such a highly concentrated training programme is possible only for a minimal number of athletic abilities. In reality this leads to the allocation of 60–70% of the entire time budget to developing two to three targets, with the remaining time spent on restoration, warming up and cooling down. This important feature is declared in the second principle, which postulates a minimization of the number of target ª 2010 Adis Data Information BV. All rights reserved.
3.3.2 Taxonomy of Mesocycle Blocks
It is easy to see that the proposed general principles lead ultimately to a taxonomy of mesocycle blocks, which serves the practical needs of compiling training programmes. The ‘taxonomy of mesocycle blocks’, as already mentioned, is formed from three specialized types: (i) accumulation, (ii) transmutation, and (iii) realization. The first type is devoted to developing basic abilities such as general aerobic endurance and cardiorespiratory fitness, muscular strength and basic coordination. This mesocycle is characterized by relatively high volume and reduced intensity of workloads. Its duration varies from 2 to 6 weeks. The second type focuses on sport-specific abilities like special (aerobic-anaerobic or glycolitic) endurance, strength Sports Med 2010; 40 (3)
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Table IV. Basic principles of block periodization training[94,95] Basic principles
Comments
High concentration of training workloads
Provides sufficient training stimulation for high-performance athletes
Minimal number of target abilities within a single block
Necessary to provide highly concentrated training stimulation
Consecutive development of many abilities
Usually the number of decisive abilities exceeds the number of abilities developed within a single block
Compilation and use of specialized mesocycle blocks
Specialized mesocycle blocks – i.e. accumulation, transmutation and realization – form the content of block periodization training
endurance, proper technique and tactics; this is the most exhausting training cycle and usually lasts about 2–4 weeks. The third type is intended to restore the athletes and prepare them for the forthcoming competition. It contains drills for modelling competitive performance and a sportspecific programme for quick active recovery. This ranges from 8 to 15 days.[95] Joining three mesocycle blocks forms a single training stage that concludes with a specific competition. Unlike traditional periodization, in which the mixed training programme is intended to develop many abilities, the consecutive development of targeted abilities typical of block periodization produces training stimuli for several functions, while the other abilities decrease. In this view, the duration of residual training effects becomes of primary importance. The correct sequencing of the mesocycles within the training stage makes it possible to obtain ‘‘optimal superposition of residual training effects’’,[37] so as to allow competitive performance at a high level for all motor and technical abilities. This possibility arises because the training residuals of basic abilities last much longer than the residuals of more specific abilities, while the residuals of maximal speed and event-specific readiness are the shortest.[93,94] Thus, the total length of a single training stage ranges from 5 to 10 weeks, depending on competition frequency and sportspecific factors. 3.3.3 Compiling an Annual Cycle
Based on the above, designing an annual cycle can be viewed as a sequence of more or less autonomous stages, where similar aims are attained by means of partially renewed and qualitatively improved training programmes. A test battery ª 2010 Adis Data Information BV. All rights reserved.
repeated at each stage together with competitive performance results will help to monitor the training process and provide feedback that can be used for ongoing evaluation and programme rectification. Finally, the number of training stages in an annual cycle depends on the particularities of a given sport, its calendar of important competitions, etc., and usually varies from four to seven stages. The typical annual cycle of blockperiodized training is shown in figure 5. The temporal structure of the annual plan is formed first of all by the chronology of the training stages. These stages are determined by the schedule of mandatory and targeted competitions and by the possible duration of several mesocycle blocks. Thus, training stage duration varies from 3 months (usually in early season) to 25 days (usually late in the season, depending on the frequency of mandatory competitions). Based on the general demands of the training stage chronology, additional competitions, training camps and medical examinations can be initiated. Generally speaking, when coaches compile annual plans they face a dilemma: the liberal ‘easy’ plan will not lead to success, but the strenuous ambitious programme can engender excessive fatigue and be followed by failure. Viewed in this way, the block-periodized design has obvious benefits. Because of the similarity of sequential stages, coaches can formulate the plan of subsequent blocks based on feedback from the previous stage of training. The most stressful phases of work – i.e. the transmutation mesocycles – can be shortened, lengthened or modified after changes in the athletes’ responses. In the lead-up to a targeted competition, coaches can review the tapering programme two to three times and approve the most favourable version. Sports Med 2010; 40 (3)
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Targeted event 5 4 3 2 1
Stages
Accumulation mesocycles
Transmutation Realization Competitions, mesocycles mesocycles reference points
New Horizons for Training Periodization
I
II
III
Preparation period
IV
V
VI
Competition period
Fig. 5. Schematic chart of a block-periodized annual cycle. The importance of competitions is depicted in reference points ranging from 1 (the lowest level) to 5 (targeted competition).[94,95]
4. Conclusions The challenge of this paper was to introduce training periodization by citing the early efforts of the pioneers and trying to present its most up-to-date versions by summarizing recently introduced concepts and evidence. An indispensable part of the theory of athletes’ preparation, training periodization encompasses both academic elements (generalized biological concepts, physiological background, theory of training) and practically oriented subjects (alternative coaching concepts, implementation of training blocks, etc.), which are equally important. The long history of traditional training periodization indicates its staying power as one of the most conservative scholastic components of training theory. The five decades in which training periodization has been used have been enough to demonstrate the merits and weaknesses of the traditional model. Its benefits derive from a more reasonable structuring of long-term preparation, whereas its drawbacks emerge from the conflicting responses produced by multi-targeted mixed ª 2010 Adis Data Information BV. All rights reserved.
training (table II). The non-traditional model, called ‘block periodization’, proposes a revamped training system, where the sequencing of mesocycle blocks exploits the favourable interaction of cumulative and residual training effects. Acknowledgements No sources of funding were used to assist in the preparation of this review. The author has no conflicts of interest that are directly relevant to the content of this review.
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7. Zheliazkov T. Theory and methodology of sport training: textbook for Sport University. Sofia: Medicina i Fizcultura; 1981 8. Martin D. Grundlagen der trainingslehre. Schorndorf: Verlag Karl Hoffmann, 1980 9. Bompa T. Theory and methodology of training: the key to athletic performance. Boca Raton (FL): Kendall/Hunt, 1984 10. Gardiner NE. Athletics of the ancient world. Oxford: University Press, 1930 11. Robinson RS, editor. Sources for the history of Greek athletics. Cincinnati (OH): Privately printed, 1955 12. Drees L. Olympia, gods, artists and athletes. New York (NY): Praeger, 1968 13. Gorinevsky VV. Body’s culture: movement exercises of physical culture. Moscow: Izdatelstvo Narkomzdrava, 1927 14. Bergman BI. Skiing: textbook for universities of physical education [in Russian]. Moscow: FiS Publisher, 1940 15. Shuvalov VI. Swimming, water polo and diving: textbook for universities of physical education [in Russian]. Moscow: FiS Publisher, 1940 16. Vasiljev GV, Ozolin NG, editors. Track and field: textbook for universities of physical education [in Russian]. Moscow: FiS Publisher, 1952 17. Jakovlev NN. Sportbiochemie. Leipzig: Barth Verlag, 1977 18. Chagovets NR. Biochemical changes in muscles in restitution after physical work. Ukr Biochem J 1957; 29: 450-7 19. Saltin B, Essen B. Muscle glycogen, lactate, ATP, and CP in intermittent exercise. In: Pernov B, Salin B, editors. Muscle metabolism during exercise. New York: Plenum Press, 1971; 419-27 20. Hermansen L, Hultman E, Saltin B. Muscle glycogen during prolonged severe exercise. Acta Physiol Scand 1967; 71: 129-38 21. Terjung RL, Baldwin KM, Winder WW, et al. Glycogen repletion in different type of muscle and liver after exhausting exercise. Am Physiol 1974; 226: 1387-95 22. Gorkin MJ. Big loads and basics of sport training. Theory Pract Phys Cult 1962; 6: 45-9 23. Vrzhesnevsky VV. Impact of workload in swimming. Theory Pract Phys Cult 1964; 10: 61-5 24. Platonov VN. General theory of athletes’ preparation in the Olympic sports. Kiev: Olympic Literature, 1997 25. Matveyev LP. Fundamental of sport training. Moscow: Progress Publishers, 1981 26. Ozolin NG. The modern system of sport training [in Russian]. Moscow: FiS Publisher, 1970 27. Matveyev LP. The bases of sport training [in Russian]. Moscow: FiS Publisher, 1977 28. Booth FW, Baldwin KM. Muscle plasticity: energy demand and supply processes. In: Rowell LB, Shepherd JT, editors. Handbook of physiology, section 12 – exercise: regulation and integration of multiple systems. New York (NY): Oxford University Press, 1996: 1075-123 29. Putman C, Xu X, Gilles E, et al. Effects of strength, endurance and combined training on myosin heavy chain content and fibre-type distribution in humans. Eur J Appl Physiol 2004; 92: 376-84
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48. Urhausen A, Kindermann W. Diagnosis of overtraining: what tools do we have? Sports Med 2002; 32: 95-102 49. Dal Monte A. Sport and technology: from laboratory to practical applications [abstract 2C]. VIIth IOC World Congress on Sport Sciences; 2003 Oct 7-11; Athens, Greece 50. Massarini M, Galvani C. Development of hightech training machines to satisfy fitness centers and Olympic training centers [abstract 17C]. VIIth IOC World Congress on Sport Sciences; 2003 Oct 7-11; Athens, Greece 51. Michanetzis G, Missurlis Y. Advances in technology and sports performance: the material aspect [abstract 15C]. VIIth IOC World Congress on Sport Sciences; 2003 Oct 7-11; Athens, Greece 52. Gracham J. Periodization research and example application. Strength Cond J 2002; 24 (6): 62-70 53. Bompa TO, Carrera MC. Peak conditioning for volleyball. In: Reeser JC, Bahr R, editors. Handbook of sports medicine and science: volleyball. London: Blackwell Science Ltd, 2003: 29-44 54. Baker D. Applying the in-season periodization of strength and power training to football. NSCA Journal 1998; 20 (2): 18-27 55. Hoffman J, Kanc J. Strength changes during an in-season resistance training program in football. J Strength Cond Res 2003; 17 (1): 109-14 56. Gamble P. Periodization training for team sports athletes. Strength Cond J 2006; 28 (5): 56-66 57. Bangsbo J. Fitness training in football: a scientific approach. Bagsvaerd: HO+Storm, 1994 58. Schneider V, Arnold B, Martin K, et al. Detraining effect in college football players during the competitive season. Strength Cond J 1998; 12: 42-5 59. Astorino T, Tam PA, Rietshel JC, et al. Changes in physical fitness parameters during a competitive field hockey season. J Strength Cond Res 2004; 18 (4): 850-4 60. Hakkinen K. Changes in physical fitness profile in female volleyball players during the competitive season. J Sports Med Phys Fitness 1993; 33: 223-32 61. Kraemer WJ, French DN, Paxton NJ, et al. Changes in exercise performance and hormonal concentrations over a big ten soccer season in starters and nonstarters. J Strength Cond Res 2004; 18 (1): 121-8 62. Baker D. The effects of an in-season of concurrent training on the maintenance of maximal strength and power in professional and college-aged rugby league football players. J Strength Cond Res 2001; 15 (2): 172-7 63. Carli G, Di Prisco CL, Martelli G, et al. Hormonal changes in soccer players during an agonistic season. J Sports Med Phys Fitness 1982; 22: 489-94 64. Newton RU, Rogers RA, Volek JS. Four weeks of optimal resistance training at the end of season attenuates declining jump performance of women volleyball players. J Strength Cond Res 2006; 20 (4): 955-1 65. Baker D, Wilson G, Caylon R. Periodization: the effect on strength of manipulating volume and intensity. J Strength Cond Res 1994; 8: 235-42 66. Fleck S, Kraemer W. Designing resistance training programs. 2nd ed. Champaign (IL): Human Kinetics, 1987 67. Bradley-Popovich G. Nonlinear versus linear periodization models. Strength Cond J 2001; 23 (1): 42-3
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68. Stone MH, O’Bryant HS. Letter to the editor. J Strength Cond Res 1995; 9 (2): 125-7 69. Stone MH, Wathen D. Letter to the editor. J Strength Cond Res 2001; 23 (5): 7-9 70. Plisk SS, Stone MH. Periodization strategies. Strength Cond J 2003; 25 (6): 19-37 71. Issurin V. Block periodization versus traditional training theory: a review. J Sports Med Phys Fitness 2008; 48 (1): 65-75 72. Verchoshansky YV. Programming and organization of training process [in Russian]. Moscow: FiS Publisher, 1985 73. Verchoshansky YV. Bases of special physical preparation of athletes [in Russian]. Moscow: FiS Publisher, 1988 74. Viru A. Adaptation in sports training. Boca Raton (FL): CRC Press; 1995 75. Tschiene P. Il nuovo orientamento delle structure dell’allenamento. Scuola dello Sport 2000; Anno XIX (47-48): 13-21 76. Moreira A, Olivera PR, Okano AH, et al. Dynamics of power measures alterations and the posterior long-lasting training effect on basketball players submitted to the block training system. Rev Bras Med Esporte 2004; 10 (4): 251-7 77. Bondarchuk AP. Training of track and field athletes. Kiev: Health Publisher (Zdorovie), 1986 78. Bondarchuk AP. Constructing a training system. Track Technique 1988; 102: 3254-269 79. Issurin V, Kaverin V. Planning and design of annual preparation cycle in canoe-kayak paddling. In: Samsonov EB, Kaverin VF, editors. Grebnoj sport (rowing, canoeing, kayaking) [in Russian]. Moscow: FiS Publisher, 1985: 25-9 80. Kaverin V, Issurin V. Performance analysis and preparation: concept of the USSR canoe-kayak national team in the XXIV Seoul Olympic Games. Sport-Science Gerald 1989; 17 (1-2): 45-7 81. Pyne DB, Touretski G. An analysis of the training of Olympic sprint champion Alexandre Popov. Australian Swim Coach 1993; 10 (5): 5-14 82. Touretski G. Preparation of sprint events: 1998 ASCTA Convention. Canberra, ACT: Australian Institute of Sport, 1998 83. Volkov N. Biochemistry of sport. In: Menshikov V, Volkov N, editors. Biochemistry. Moscow: Fizkultura i sport, 1986: 267-381 84. McArdle WD, Katch F, Katch V. Exercise physiology. Philadelphia/London: Lea & Febiger, 1991 85. Fox LE, Bowers RW, Foss ML. The physiological basis for exercises and sport. Madison (NY): Brown & Benchmark Publishers, 1993 86. Wilmore JH, Costill DL. Training for sport and activity: the physiological basis of the conditioning process. Champaign (IL): Human Kinetics, 1993 87. Komi PV. Training of muscle strength and power: interaction of neuromotoric, hypertrophic, and mechanical factors. Int J Sports Med 1986; 7: 10-5 88. Counsilman BE, Counsilman J. The residual effects of training. J Swim Res 1991; 7: 5-12 89. Steinacker JM, Lormes W, Lehman M, et al. Training of rowers before world championships. Med Sci Sports Exerc 1998; 30: 1158-63
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90. Steinacker JM, Lormes W, Kellman M, et al. Training of junior rowers before world championships: effect on performance, mood state and selected hormonal and metabolic responses. J Sports Med Phys Fitness 2000; 40: 327-35 91. Mujika I, Padilla S. Cardiorespiratory and metabolic characteristics of detraining in humans. Med Sci Sports Exerc 2001; 33: 413-21 92. Zatsiorsky VM. Science and practice of strength training. Champaign (IL): Human Kinetics, 1995 93. Issurin V, Lustig G. Klassification, Dauer und praktische Komponenten der Resteffekte von Training. Leistungsport 2004; 34 (3): 55-9
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94. Issurin V. A modern approach to high-performance training: the Block Composition concept. In: Blumenstein B, Lidor R, Tenenbaum G, editors. Psychology of sport training. Oxford: Meyer & Meyer Sport, 2007: 216-34 95. Issurin V. Block periodization: breakthrough in sport training. Muskegon (MI): Ultimate Training Concepts, 2008
Correspondence: Professor Vladimir B. Issurin, Elite Sport Department, Wingate Institute, Wingate Post Office, Netanya 42902, Israel. E-mail:
[email protected]
Sports Med 2010; 40 (3)
Sports Med 2010; 40 (3): 207-227 0112-1642/10/0003-0207/$49.95/0
REVIEW ARTICLE
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The Effect of the Menstrual Cycle on Exercise Metabolism Implications for Exercise Performance in Eumenorrhoeic Women Tanja Oosthuyse1 and Andrew N. Bosch2 1 School of Physiology, University of the Witwatersrand Medical School, Johannesburg, South Africa 2 UCT/MRC Research Unit for Exercise Science and Sports Medicine, University of Cape Town, Cape Town, South Africa
Contents Abstract. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1. Effects of the Ovarian Hormones on Exercise Performance. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1 Short Duration or Maximal Exercise Intensities. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2 Submaximal Exercise Intensities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2.1 Time to Exhaustion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2.2 Time Trial Performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2. Ovarian Hormones and Metabolism . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 Carbohydrate Metabolism . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1.1 Stable Isotopic Measures of Systemic Glucose Kinetics in Eumenorrhoeic Women . . . . . . 2.1.2 Indirect Estimation of Muscle Glycogen Use . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1.3 Muscle Glycogen Content Quantified from Muscle Biopsies . . . . . . . . . . . . . . . . . . . . . . . . 2.1.4 Conclusion of the Influence of the Ovarian Hormones on Carbohydrate Metabolism. . . 2.2 Fat Metabolism . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2.1 Systemic Glycerol Kinetics as a Measure of Lipolytic Rate . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2.2 Plasma Free Fatty Acid Kinetics and Oxidation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2.3 Intramyocellular Stores and Use During Exercise . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2.4 50 -AMP-Activated Protein Kinase, a Key Regulator of Cellular Metabolism, is Influenced by Oestrogen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2.5 Conclusion of the Influence of the Ovarian Hormones on Fat Metabolism. . . . . . . . . . . . . 2.3 Influence of Ovarian Hormones on Protein Metabolism . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3. Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Abstract
207 210 210 210 210 211 213 213 213 215 216 217 218 218 219 221 221 222 222 223
The female hormones, oestrogen and progesterone, fluctuate predictably across the menstrual cycle in naturally cycling eumenorrhoeic women. Other than reproductive function, these hormones influence many other physiological systems, and their action during exercise may have implications for exercise performance. Although a number of studies have found exercise performance – and in particular, endurance performance – to vary between menstrual phases, there is an equal number of such studies reporting no differences. However, a comparison of the increase in the oestrogen concentration (E) relative to progesterone concentration (P) as the E/P ratio (pmol/ nmol) in the luteal phase in these studies reveals that endurance performance may only be improved in the mid-luteal phase compared with the early
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follicular phase when the E/P ratio is high in the mid-luteal phase. Furthermore, the late follicular phase, characterized by the pre-ovulatory surge in oestrogen and suppressed progesterone concentrations, tends to promote improved performance in a cycling time trial and future studies should include this menstrual phase. Menstrual phase variations in endurance performance may largely be a consequence of changes to exercise metabolism stimulated by the fluctuations in ovarian hormone concentrations. The literature suggests that oestrogen may promote endurance performance by altering carbohydrate, fat and protein metabolism, with progesterone often appearing to act antagonistically. Details of the ovarian hormone influences on the metabolism of these macronutrients are no longer only limited to evidence from animal research and indirect calorimetry but have been verified by substrate kinetics determined with stable tracer methodology in eumenorrhoeic women. This review thoroughly examines the metabolic perturbations induced by the ovarian hormones and, by detailed comparison, proposes reasons for many of the inconsistent reports in menstrual phase comparative research. Often the magnitude of increase in the ovarian hormones between menstrual phases and the E/P ratio appear to be important factors determining an effect on metabolism. However, energy demand and nutritional status may be confounding variables, particularly in carbohydrate metabolism. The review specifically considers how changes in metabolic responses due to the ovarian hormones may influence exercise performance. For example, oestrogen promotes glucose availability and uptake into type I muscle fibres providing the fuel of choice during short duration exercise; an action that can be inhibited by progesterone. A high oestrogen concentration in the luteal phase augments muscle glycogen storage capacity compared with the low oestrogen environment of the early follicular phase. However, following a carboloading diet will super-compensate muscle glycogen stores in the early follicular phase to values attained in the luteal phase. Oestrogen concentrations of the luteal phase reduce reliance on muscle glycogen during exercise and although not as yet supported by human tracer studies, oestrogen increases free fatty acid availability and oxidative capacity in exercise, favouring endurance performance. Evidence of oestrogen’s stimulation of 50 -AMPactivated protein kinase may explain many of the metabolic actions of oestrogen. However, both oestrogen and progesterone suppress gluconeogenic output during exercise and this may compromise performance in the latter stages of ultra-long events if energy replacement supplements are inadequate. Moreover, supplementing energy intake during exercise with protein may be more relevant when progesterone concentration is elevated compared with menstrual phases favouring a higher relative oestrogen concentration, as progesterone promotes protein catabolism while oestrogen suppresses protein catabolism. Furthermore, prospective research ideas for furthering the understanding of the impact of the menstrual cycle on metabolism and exercise performance are highlighted.
In many fields of physiology, sex is considered to be a variable that should be ‘controlled for’. Therefore, men and women are expected to respond differently to various interventions or conª 2010 Adis Data Information BV. All rights reserved.
ditions. Often, sample groups are restricted to including only men, possibly because male physiology remains relatively consistent from day to day. Conversely, women between the ages of Sports Med 2010; 40 (3)
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FSH Oestrogen Progesterone LH EF
Day 1 (onset of menstruation)
MF
LF
EL
Day 14 ovulation
ML
LL
Day 28
Fig. 1. Diagrammatic representation of the cyclical changes in the female sex hormones that characterize the various menstrual phases. 17b-Oestradiol is the primary oestrogen secreted, but may be metabolized further to form oestrone and oestriol, which are less potent oestrogens.[2] The luteinizing hormone (LH) surge commences 36 hours before ovulation occurs.[3] EF = early follicular; EL = early luteal; FSH = follicle-stimulating hormone; LF = late follicular; LL = late luteal; MF = mid follicular; ML = mid luteal.
approximately 13 and 50 years experience a circamensal rhythm termed the menstrual cycle, where the ovarian hormones fluctuate predictably over, on average, 23–38 days.[1] The ovarian hormones, oestrogen and progesterone, are secreted from the ovaries and to a lesser extent from the adrenal glands in women.[2] Although these hormones primarily function to support reproduction, they have been reported to influence other physiological systems. For this reason, studies have been conducted to compare established responses in men with the response in women. However, in these studies women are studied mostly only during the early stages of their menstrual cycle when the ovarian hormones are considered to be at their lowest, so as to avoid the ‘moving target’ scenario. Women, however, function and compete in sporting events at all stages of the menstrual cycle. Therefore, some researchers have enª 2010 Adis Data Information BV. All rights reserved.
deavoured to compare physiological responses in women between identified phases of the menstrual cycle, corresponding to accepted concentration ranges for the ovarian hormones (figure 1). The menstrual cycle is broadly divided into two phases – the follicular phase (FP) and the luteal phase (LP) – which are separated by ovulation. The system involved in the regulation thereof is termed the hypothalamic-pituitaryovarian axis, and is thoroughly reviewed by Reilly[1] and Birch.[4] Unfortunately, this field of research is plagued with many inconsistent findings, but it is possible that most inconsistencies can be solved by a closer examination of the hormone interactions. Part one of this review considers studies that have compared exercise performance between menstrual phases. Part two presents a detailed review of the effects of the ovarian hormones (as they naturally occur during the various menstrual Sports Med 2010; 40 (3)
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phases) on substrate metabolism during exercise at submaximal intensities. Although the ovarian hormones are known to influence other physiological systems (such as the respiratory, thermoregulatory, and cardiovascular systems, and even muscle satellite cell activation), these fall outside the scope of the current review. 1. Effects of the Ovarian Hormones on Exercise Performance 1.1 Short Duration or Maximal Exercise Intensities
. The maximum oxygen consumption (VO2max) and time to exhaustion in maximal ramp tests are mostly unchanged by menstrual phase.[5-14] However, there is one report of a 2% lower . VO2max in the mid-luteal (ML) phase compared with the early follicular (EF) phase. [14] and another in which a 13% decrease in VO2max after 4 months of oral contraceptive use was realtitude dwellers tended to ported.[10] Conversely, . have a higher VO2max (p = 0.06) in the LP compared with the FP,[15] possibly due to the increased respiratory drive in the LP, which may facilitate a slightly higher oxygen saturation.[9] However, such findings are not found in women who are acutely exposed to altitude.[9] Nonetheless, it may be worthwhile to consider the potential for the progesterone-induced increase in respiratory drive in the LP to benefit maximal exercise at high altitudes in well-acclimatized athletic eumenorrhoeic women. Conversely, others have reported that the higher respiratory drive in the LP jeopardizes maximal exercise performance in non-athletes due to the increased sensation of dyspnoea,[12] although the increased respiratory drive did not influence maximal performance in athletes.[12] In this regard, exercise-induced bronchoconstriction in asthmatic athletes is more severe during the ML phase compared with the mid-follicular (MF) phase following an incremental ramp test to exhaustion.[16] However, a consistently higher respiratory rate throughout 90 minutes of submaximal exercise in the ML phase compared with the EF phase has been found to not increase ª 2010 Adis Data Information BV. All rights reserved.
metabolic demand, and therefore should not influence rate of fatigue.[17] It appears fairly consistent from curve-fitting methods that the exercise intensity that induces the point of inflection corresponding to either the lactate or ventilatory thresholds remains unchanged by menstrual phase.[7,11-13,18] However, one study has found that the ventilatory thresh. old occurs at a higher percentage of VO2max in the EF phase compared with the late follicular (LF) and ML phases.[6] Moreover, Forsyth et al.[18] found that the intensity corresponding to 4 mmol/L lactate threshold was higher in the LP than FP. Similarly, others,[5,19-21] but not all,[6-8,22-25] have reported lower blood lactate concentrations during exercise in the LP compared with FP, thus suggesting the potential for a decreased blood lactate accumulation during exercise and hence, by implication, lower anaerobic glycolysis in the LP. Performances in all-out sprints and in measures of muscle strength have been found to be best during menstruation.[26-28] However, others have found no differences in a Wingate performance test between menstruation and LP[29] or in 10-second sprints between MF and ML phases.[30] In summary, menstrual phase has been found only occasionally to influence maximal aerobic or anaerobic performances. However, various physiological changes (such as respiratory drive) associated with the ovarian hormones, other than simply alterations to metabolism, may influence exercise at such high intensities. 1.2 Submaximal Exercise Intensities 1.2.1 Time to Exhaustion
Low dose oestrogen supplementation to ovariectomized rats has been shown to improve time to exhaustion in a prolonged submaximal treadmill run by 20% compared with sham injected rats.[31] Endurance time continued to improve with increasing oestrogen dose, resulting in up to a 42% improvement when oestrogen was increased within physiological concentrations compared with sham-injected controls,[31] and 50% improvements with a supraphysiological dose of oestrogen.[31] These massive improvements in endurance capacity coincided with glycogen-sparing Sports Med 2010; 40 (3)
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Table I. Relative changes in the ovarian hormones between the follicular (FP) and luteal phase (LP) in relation to submaximal endurance performance Magnitude of increase in oestrogen in LP above FP
E/P in LP
Result
Reference
Time to exhaustion at submaximal intensity 2.28-fold
12.3
NS; EF vs ML
33
2.87-fold
8
NS; EF vs ML
9
2-fold
21.3
p < 0.02; ML > MF
5
3.85-fold
18
p < 0.07; ML > MF
23
Time trial performance 2.3-fold
5.5
p < 0.05 MF faster than ML without CHO supplement
22
2.5-fold
6
NS; MF vs ML with CHO supplement
22
9.7
NS; MF vs ML following a normal or CHO-loading diet
34
NS; EF vs ML but tendency for LF faster than EF (p = 0.027)
35
1.4-fold 4-fold
18.5
CHO = carbohydrate; EF = early follicular; E/P = oestrogen to progesterone ratio; LF = late follicular phase; MF = mid-follicular phase; ML = mid-luteal phase; NS = not significant.
in the red and white vastus muscle, myocardium and liver.[31] However, time to exhaustion at submaximal exercise intensity is a measure of endurance capacity rather than a direct measure of exercise performance,[32] although it can provide an indication of an athlete’s potential for endurance events. Such protocols do not have a high reproducibility, and studies have reported coefficients of variation as high as 30% when using these tests[32] thus reducing the statistical power of comparison between interventions, in this case between menstrual phases. Nonetheless, in humans, two studies have reported an effect of menstrual phase on endurance capacity. The first study found that following 40 minutes of submaximal cycling at low to moderate intensities, time to exhaustion at 90% of maximum power output was doubled in the ML phase compared with the MF phase.[5] This coincided with lower blood lactate levels in the ML phase.[5] The second study had a smaller sample size (n = 6); possibly because of this, the (on average) 10% . longer time to exhaustion at 70% VO2max in the ML phase compared with the MF phase did not quite reach significance (p < 0.07).[23] Conversely, two further studies . also compared time to exhaustion at 70% VO2max and did not find any difference between the EF and ML phase,[9,33] with or without carbohydrate supplements during exercise.[33] ª 2010 Adis Data Information BV. All rights reserved.
While all these studies demonstrated a 2-fold or greater increase in oestrogen from the follicular to luteal phase, the oestrogen to progesterone concentration ratio (E/P; pmol/nmol) differed noticeably. Studies reporting a better performance in the LP had a higher E/P ratio, while the studies that found no change in endurance time had a lower E/P ratio (table I). This observation implies that the higher relative progesterone concentration in the latter studies impeded the metabolic benefits of oestrogen that may have been more prominent during the LP of the former studies. However, 6 days of transdermal oestrogen supplementation in amenorrhoeic women failed . to alter time to exhaustion at 85% VO2max that was preceded by 90 minutes of submaximal running.[36] In this study though, the transdermal oestrogen supplement resulted in only modest increases in circulating oestrogen, to levels typically experienced in the early to mid-FP. Furthermore, while the duration of oestrogen exposure was sufficient to lower glucose kinetics, it may have been too short to produce certain other oestrogen effects, such as muscle glycogensparing during exercise.[37] 1.2.2 Time Trial Performance
Exercise protocols with a fixed endpoint – such as time to complete a given distance, or to expend a given amount of energy or distance Sports Med 2010; 40 (3)
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covered in a fixed time period etc. – are a good measure of exercise performance, having hightest-retest reproducibility as described by a low coefficient of variability (1–3%).[32,38] Three studies have measured time trial performance between menstrual phases.[22,34,35] Campbell et al.[22] compared the time to expend a given amount of energy after completing a 2-hour . submaximal session at 70% VO2max in the MF and ML phase with and without carbohydrate supplements in overnight fasted subjects. They observed a 13% improvement in time trial performance in the MF phase without carbohydrate supplementation during exercise.[22] This better MF performance was associated with higher carbohydrate use and whole body rate of glucose appearance (hepatic glucose production) and rate of disappearance (or glucose uptake), suggesting a better capacity for carbohydrate use in the MF phase.[22] An increased capacity for carbohydrate utilization is beneficial in short duration time trial events that take place at high intensities. This observation of better time trials in the MF phase[22] coincides well with another study from the same authors who found oestrogen to promote contraction-stimulated glucose uptake and hepatic glycogenolysis during exercise in ovariectomized rats during a short, high intensity run, while progesterone antagonized these responses.[39] The pre-exercise MF phase average oestrogen concentration was relatively high (360 pmol/L)[22] and hence oestrogen may have promoted glucose uptake into muscles during these trials. In addition, despite a 2.5-fold increase in oestrogen in the ML phase over the MF phase, the E/P ratio in the ML phase was comparatively low (5–6) (table I).[22] Thus, the relatively high progesterone concentration during the trials in the ML phase may have countered the benefits of an elevated oestrogen concentration and produced a worse performance. However, the use of carbohydrate supplements during exercise elevated the glucose rate of appearance, disappearance and plasma glucose use, providing sufficient fuel-of-choice to promote an optimal performance in a short duration, high intensity time trial, regardless of menstrual phase.[22] ª 2010 Adis Data Information BV. All rights reserved.
Oosthuyse & Bosch
McLay et al.[34] also compared cycling time trial performance (over 16 km) in the MF and ML phase after a lengthy submaximal exercise period (75 minutes). These authors found no difference in finishing time between menstrual phases when subjects participated following 3 days of either a normal mixed diet or a carbohydrate-loading diet. Unfortunately, the authors allowed the subjects to view their power output throughout the time trial, and this may have been a potential shortfall as subjects would have been able to consciously regulate their exercise intensity to match their previous time trial. Moreover, the group average oestrogen concentration increased by a meagre 1.4-fold more from the MF to ML phase, while the average progesterone concentration in the ML phase was substantial, resulting in an E/P ratio of only 9.7 (table I),[34] thus possibly partly explaining the lack of difference in performances. A study was also performed in our laboratory to assess cycling time trial performance during the EF, LF and ML phase of the menstrual cycle.[35] The inclusion of the LF phase in this comparison is a novel contribution to the literature and is motivated by the many oestrogeninduced metabolic effects (see section 2) that should promote performance in such an event. In our subjects who participated in a non-fasted state, time trial performance was also not significantly different between the EF and ML phase.[35] However, we observed a strong tendency for better performance in the LF phase compared with the EF phase (p = 0.027), but this did not quite reach significance with Bonferroni correction applied for three multiple comparisons.[35] Nevertheless, the results suggest a positive influence of oestrogen on performance in such events. Conversely, the coincident increase of progesterone in the ML phase may have antagonized the benefits of an elevated oestrogen concentration despite a high E/P ratio (18.5) in the ML phase and average 4-fold increase in oestrogen. However, subjects in this study[35] and the study by McLay et al.[34] participated roughly 2 hours postprandially, which may have alleviated the metabolic demand that is thought necessary to potentiate ovarian hormone influences, Sports Med 2010; 40 (3)
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particularly regarding carbohydrate metabolism. Nonetheless, evidence of oestrogen’s capacity to promote cycling time trial performance without progesterone antagonizm was still evident in the LF phase in the study by Oosthuyse et al.,[35] despite subjects exercising 2 hours postprandially. In summary, only eight studies in total have considered menstrual phase variations in endurance exercise performance. Of the eight studies, four have reported menstrual cycle variations. Thus, the potential for naturally cycling ovarian hormones to alter performance can neither be excluded nor confirmed. However, strong evidence from animal research, specifically for oestrogen-induced promotion of better endurance capacity, and the various menstrual phase-associated metabolic perturbations discussed in part two of this review should provide motivation for further endurance performance studies. Future studies should consider the increase in oestrogen relative to progesterone in the LP and the absolute magnitude of increase in oestrogen between any two menstrual phases. Furthermore, all exercise trials to date have been limited to <2 hours in duration. The metabolic influences of oestrogen in promoting fat use and spare glycogen stores should best support performances in ultra-endurance events. Thus, future studies should investigate menstrual phase variations in ultra-endurance events and consider including the LF phase, which coincides with maximal increases in oestrogen independent of changes in progesterone. 2. Ovarian Hormones and Metabolism Both oestrogen and progesterone are reported to alter metabolic responses. However, in this respect, progesterone displays largely antioestrogenic effects.[39-41] D’Eon et al.[42] have proposed that a metabolic response to changes in the ovarian hormones occurs only when the E/P ratio is sufficiently elevated and the magnitude of the increase in oestrogen from the EF to the phase of comparison such as LF or ML is at least in the order of 2-fold more. Nutritional status is also a determining variable, since most variations in metabolism between menstrual phases are reported ª 2010 Adis Data Information BV. All rights reserved.
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when subjects participate in a study following an overnight fast, whereas a positive nutritional state may lessen the impact of the ovarian hormones.[22] 2.1 Carbohydrate Metabolism 2.1.1 Stable Isotopic Measures of Systemic Glucose Kinetics in Eumenorrhoeic Women
In a fasted state, glucose rate of appearance (Ra) is solely determined by endogenous glucose production, which is predominantly controlled by hepatic gluconeogenesis and glycogenolysis. Glucose rate of disappearance (Rd) is dependent on insulin-mediated glucose uptake and contraction-mediated glucose transport, with the latter predominating during exercise. Glucose Ra and Rd are naturally related to each other and primarily influenced by the rate of glucose utilization.[25] A number of studies have found that the Ra and Rd of glucose during exercise is attenuated by either therapeutic increases in circulating oestrogen[36,37,42,43] or with the coincident rise in oestrogen and progesterone during the ML phase of the menstrual cycle versus the EF phase.[19,22,44] Therefore, the ovarian hormoneinduced decrease in glucose kinetics is most likely an oestrogen-associated effect and is one that progesterone does not antagonize but may in fact potentiate.[42] Glucose Ra was dependent on hepatic glucose production in all of the above studies, as the subjects did not receive any form of exogenous glucose during exercise and participated following an overnight fast (besides D’Eon et al.,[42] where differences in glucose kinetics did not quite reach significance). Therefore, the ovarian hormone-induced reduction in glucose kinetics noted in the above studies is supposedly due to the ability of oestrogen to hamper hepatic gluconeogenesis.[45] This hypothesis is supported by a study performed in carbohydrate-depleted women, where blood glucose was maintained during submaximal exercise in the MF phase but concentrations dropped progressively during exercise in the ML phase.[20] However, Horton et al.[25] hypothesized that the effect of oestrogen on hepatic glucose output Sports Med 2010; 40 (3)
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Table II. Comparison of menstrual phase studies investigating plasma glucose kinetics during exercise with consideration of nutritional status and the absolute exercise intensity . Reference (year) Menstrual phases Training status Glucose Raa Exercise Significance Absolute VO2 . intensity (mmol/kg/min) VO2max (mL/kg/min) . (mL/kg/min) (%VO2max) Overnight fasted studies Horton et al.[25] (2002)
EF vs MF vs ML
39.9 – 5.8
50
20.2
20 vs 20 vs 18
NS
Zderic et al.[19] (2001)
EF vs ML
48.2 – 1.1
42 52
20.2 25.1
20 vs 18 33.7 vs 28.8
NS p < 0.05
Campbell et al.[22] (2001) EF vs ML
53.5 – 0.9
69
36.8
33 vs 25
p < 0.05
Devries et al.[44] (2006)
MF vs ML (part OC)
39 – 2
65
25.4
53 vs 49
p = 0.03
Ruby et al.[36] (1997)
Am; PL vs 72 h E vs 144 h E
45.5 – 5.6
65
29.2
21.9 vs 18.9 vs 18.9
p < 0.05
Carter et al.[43] (2001)
M; PL vs E
53.3 – 6.7
60
31.1
48 vs 42
p < 0.05
Devries et al.[37] (2005)
M; PL vs E
44 – 2
65
28.6
65 vs 60
p = 0.04
Roughly 3-hours postprandial studies D’Eon et al.[42] (2002)
GnRH agonist vs E vs E + P
42.5 – 8
54
23 (96 watts)
51 vs 45.6 vs 43.3
(0.05 < p < 0.1) for E and E + P < GnRHa
Suh et al.[24] (2002)
EF vs ML
43.6 – 2
45 65
20 (59 watts) 29 (97 watts)
27.7 vs 28.3 38.9 vs 40.6
NS NS
53.5 – 0.9
70
37.8
46 vs 43
NS
Exogenous glucose ingestion during exercise Campbell et al.[22] (2001) EF vs ML a
Some glucose Ra values are only approximations as estimated from figures.
Am = amenorrhoeic women; E = exogenous oestrogen supplements; E + P = exogenous oestrogen and progesterone supplements; EF = early follicular phase; GnRHa = gonadotropic-releasing hormone agonist that will suppress endogenous oestrogen and progesterone secretion; M = male subjects; MF = mid-follicular phase; ML . . = mid-luteal phase; NS = not significantly different; OC = oral contraceptive; PL = placebo; Ra = rate of appearance; VO2 = oxygen uptake; VO2max = maximal oxygen uptake.
appears to become noticeable only when the exercise intensity is sufficient to increase the demands on glucose utilization to above a certain ‘critical level’. At this ‘critical level’ the demand on endogenous glucose production is sufficiently elevated such that the effect of oestrogen suppression on gluconeogenesis is evident in a reduced glucose Ra. As illustrated by Horton et al.,[25] this is clearly supported by comparing the glucose kinetic results of Campbell et al.,[22] Horton et al.[25] and Zderic et al.[19] (table II). When the subjects in the study by . Zderic et al.[19] exercised at approximately 50% VO2max, glucose Ra was significantly lower in the ML phase versus the EF phase. However, no difference was noted between menstrual phases when . these subjects exercised at only 42% VO2max.[19] Thus, when there was less of a demand on endogenous glucose production, and an increased reliance on lipid utilization, no menstrual phase effect was evident in glucose kinetics. In the study ª 2010 Adis Data Information BV. All rights reserved.
by Horton et al.,[25] the subjects were slightly less trained than those in the study by Zderic et al.[19] Therefore, when the subject groups of the two studies exercised at an equal intensity of 50% . VO2max, the absolute workload was lower in the study by Horton et al.[25] Thus, the lower absolute workload demanded a lower total fuel utilization and hence lower glucose utilization with less demand on endogenous glucose production and consequently a lower glucose Ra. At this lower glucose Ra no difference was observed between the EF, MF and ML phases,[25] as was similarly. observed in the study by Zderic et al.[19] at 42% VO2max. In contrast, well-trained subjects in the. study by Campbell et al.[22] exercised at 70% VO2max. This higher intensity exercise increased the demand on endogenous glucose production above the ‘critical level’ and produced a noticeable difference in glucose Ra between the EF and ML phase. A study by Devries et al.[44] that included both eumenorrhoeic women and Sports Med 2010; 40 (3)
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women on oral contraceptives confirms these findings, with glucose Ra 6% lower in the LP compared with the FP when subjects exercised at . 65% VO2max following an overnight fast. However, when subjects in the study by Campbell et al.[22] received an energy drink during exercise the difference in glucose Ra between menstrual phases was no longer significant, possibly because glucose Ra was now largely determined by exogenous glucose absorption (table II).[25] This theory can be extended to include subjects who exercise only a few hours postprandially (but do not receive glucose supplements during exercise).[24,42] Under these conditions it appears that the demands on glucose utilization need to exceed an even higher critical level before a difference in glucose kinetics between menstrual phases becomes evident (table II). It would be interesting to challenge this hypothesis with a study in which glucose kinetics parameters are measured in subjects ex. ercising at high intensities of >70% VO2max following a short postprandial period, in various menstrual phases. Thus, in summary, glucose kinetics appears to be influenced by menstrual phase when the energy demand of exercise is sufficiently high to pressurise endogenous glucose production. However, it appears that the postprandial period is a major determinant of the level of the demand on endogenous glucose production that is necessary before the influence of menstrual phase becomes evident. This can be explained as oestrogen or oestrogen and progesterone impose a restriction on endogenous glucose production by suppressing gluconeogenesis.[45] However, when exercise follows a short postprandial period it would be expected that hepatic glycogenolysis would provide a greater proportional contribution to endogenous glucose production than from gluconeogenesis relative to a condition that imposes a longer fasting period. Finally, when exogenous glucose is provided throughout exercise the influence of menstrual phase on glucose kinetics is negligible, as this condition minimizes the demand on endogenous glucose production.[22] However, future studies should consider the influence of menstrual phase or ovarian horª 2010 Adis Data Information BV. All rights reserved.
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mone concentration on glucose kinetics during ultra-long events even with exogenous glucose supplements as, ultimately, gluconeogenic output will become increasingly relevant. 2.1.2 Indirect Estimation of Muscle Glycogen Use
Glucose metabolic tracer studies often make the assumption that 100% of glucose uptake (Rd) is oxidized and therefore glucose Rd approximates plasma glucose oxidation rate. The difference between total carbohydrate oxidation estimated by indirect calorimetry and glucose Rd provides an estimate of muscle glycogen use during exercise. However, this is a crude assumption, as the percentage of glucose Rd oxidized is probably closer to 60–90% and may vary depending on the study conditions; thus, the calculation underestimates glycogen use and should be considered as minimal muscle glycogen utilization.[46] In fact, when such indirect estimates of muscle glycogen use were compared with actual muscle biopsy measures, the values did not correlate.[44] Furthermore, while muscle biopsy data revealed menstrual phase differences between muscle glycogen use during exercise, no differences were evident when based on indirect tracer estimates in the same sample group.[44] Possibly, for these reasons, some studies measuring glucose kinetics have not estimated muscle glycogen use,[24,25,43] which may explain why others have found no difference in estimated glycogen use between menstrual phases[22] or with oestrogen treatment.[24] Therefore, the results from indirect muscle glycogen estimations must be considered in light of the possible limitations of the method. However, some studies that reported a lower glucose uptake (Rd) with elevated oestrogen[42] or oestrogen and progesterone[19] also reported lower estimated muscle glycogen use during exercise under these conditions compared with EF phase conditions. Interestingly, D’Eon et al.[42] found that pharmacologically elevated oestrogen plus progesterone resulted in greater estimated muscle glycogen use during exercise compared with a condition of suppressed ovarian hormones. Such a finding is contrary to reports from other authors whose muscle biopsy data suggest Sports Med 2010; 40 (3)
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muscle glycogen sparing in the LP, in which oestrogen and progesterone concentrations are elevated.[47] However, the rise in ovarian hormones in the study by D’Eon et al.[42] was not natural, and although during the oestrogen plus progesterone condition oestrogen was elevated to within normal LP levels, progesterone increased to around 151.4 nmol/L (47.6 ng/mL), which is higher than normal LP levels. Thus, the findings of D’Eon et al.[8] suggest that progesterone may antagonize glycogen sparing. The muscle glycogen sparing that has been reported to occur in the LP[19,47] must be largely due to the elevated oestrogen levels that occur during this phase and could possibly be more pronounced during the LF phase where oestrogen alone is elevated. Furthermore, D’Eon et al.[42] described an interesting inverse correlation in which free fatty acid (FFA) concentration explained 50% of the variance in estimated muscle glycogen use, where FFA concentration was greater with oestrogen supplementation. This possibly infers that an oestrogen-induced increased FFA availability promoted glycogen sparing during exercise.[42] Therefore, the influence of oestrogen and progesterone on muscle glycogen utilization may depend on their influence on FFA availability or oxidation. 2.1.3 Muscle Glycogen Content Quantified from Muscle Biopsies
Estimation of muscle glycogen content by muscle biopsy in eumenorrhoeic women suggests that the hormone milieu in the LP promotes muscle glycogen storage[23,34,48] compared with the FP. Of particular note, given the current interest in multistage events, Nicklas et al.[23] reported greater muscle glycogen repletion following a period of induced glycogen depletion in the LP compared with the FP. However, a carbohydrate-loading diet increased muscle glycogen stores in the FP to the higher values previously attained in the LP when following a normal diet,[34] but the carbohydrate-loading diet failed to increase muscle glycogen stores further in the LP.[34] Thus, carbohydrate loading balances the capacity for muscle glycogen storage between the FP and LP.[34] ª 2010 Adis Data Information BV. All rights reserved.
However, a recent study by Devries et al.[44] used a subject group comprising of part eumenorrhoeic women and part women using triphasic oral contraceptives and found no difference in resting muscle glycogen stores between the follicular and LP. Moreover, oestrogen supplementation in men resulted in a trend for lower resting muscle glycogen with a moderate oestrogen dose,[49] or significantly lower resting glycogen stores with a higher oestrogen dose compared with placebo treatment.[37] However, the oestrogen exposure period in these latter studies may have been too short to promote glycogen storage, or oestrogen supplementation may have decreased the calorie intake[50] of the men when compared with placebo treatment, because although their diet was self-controlled it was not rigorously regulated.[37] Nonetheless, in support of the latter findings, rat studies using male[51] or ovariectomized female rats[31,39] where the quantity of food-intake was controlled, reported no change in resting muscle glycogen stores following oestrogen and/or progesterone treatment. However, one such study did report an increase in liver glycogen stores with oestrogen supplements in ovariectomized rats compared with progesterone, combined progesterone and oestrogen, or placebo treatment,[39] thus demonstrating the potential for oestrogen to maximize glycogen stores. However, we cannot exclude the possibility of interspecies differences in carbohydrate metabolism. Nevertheless, oestrogen has been shown to increase muscle glycogen synthase activity.[52] Moreover, oestrogen deficiency is associated with insulin resistance[53] and higher insulin concentrations.[42] Furthermore, intravenous oestrogen in postmenopausal women promoted insulin actions by increasing insulin-stimulated glucose uptake at rest during a hyperinsulinaemic clamp.[54] Other studies have also reported insulin sensitivity to be heightened in the presence of oestrogen[53,55] but often report no change in insulin responsiveness to a large glucose load.[53,55-57] Thus, we would expect increases in oestrogen concentration to promote glycogen storage. Moreover, the similar carbohydrate-loaded glycogen stores between menstrual phases could be Sports Med 2010; 40 (3)
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explained by the previously reported lack of an oestrogen effect on insulin responsiveness to a larger glucose load. Conversely, increases in progesterone concentration are associated with a decrease in the insulin-responsive glucose transporter (GLUT4) content in insulin-sensitive tissue[39] and insulin resistance;[58-60] hence, progesterone most likely counters glycogen storage. Given the controversy in the findings of resting muscle glycogen stores between studies from naturally cycling eumenorrhoeic women and oestrogen-supplemented studies, further studies are necessary to clarify whether the ovarian hormones alter resting muscle glycogen stores. A number of studies have reported lower rates of glycogen use during exercise in the LP compared with the FP based on biopsy samples taken before and after 60 minutes of exercise at 70% . VO2max.[44,47] In addition, one such study found that muscle glycogen use during exercise was negatively correlated with oestrogen concentration.[47] More specifically, Devries et al.[44] isolated muscle glycogen into proglycogen and macroglycogen fractions and found women in the FP used 30% more proglycogen and 16% more macroglycogen and together 24% more total muscle glycogen during exercise than when in their LP. However, their sample group included both eumenorrhoeic women and women using oral contraceptives. Previously, the same group of researchers found no evidence of muscle glycogen sparing during endurance exercise in men receiving oestrogen supplements compared with placebo treatment.[37,49] However, the authors’ speculate that the period of oestrogen treatment or sex differences in oestrogen receptor density may explain the lack of effect in the men.[44] Animal research consistently finds that oestrogen treatment results in skeletal muscle glycogen sparing during exercise.[31,39,51] However, despite the greater pre-exercise liver glycogen in oestrogen-treated ovariectomized rats in the study by Campbell and Febbraio,[39] after 30 minutes of submaximal running at 0.35 m/sec, liver glycogen stores were no longer significantly different between ovarian hormone treatments. ª 2010 Adis Data Information BV. All rights reserved.
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These results suggest a greater rate of hepatic glycogenolysis with oestrogen treatment. This is contrary to the finding of Kendrick et al.[31] where after 2 hours of submaximal running at the same intensity (0.37 m/sec) marked hepatic glycogen sparing was reported with oestrogen treatment in oophorectomized rats. The discrepancy in liver glycogen metabolism with oestrogen treatment may be related to the difference in exercise duration of the two studies. Therefore, the greater hepatic glycogen use with oestrogen treatment in the study by Campbell and Febbraio[39] may reflect initial responses to exercise that are characterized by an early-phase higher dependence on carbohydrate metabolism. Thus, the findings from this study reflect the capacity of oestrogen to increase glucose availability and, moreover, uptake into specifically type I muscle fibres during periods of demand.[39] In fact, two animal studies have found oestrogen to potentiate contraction-stimulated glucose uptake (50% increases have been reported with oestrogen replacement relative to oestrogen deficiency by ovariectomy).[39,55] Conversely, the findings of Kendrick et al.[31] depict metabolic preferences of prolonged exercise where the presence of increased oestrogen may promote a different response that includes liver glycogen sparing, which, in that study, coincided with substantial increases in endurance capacity. 2.1.4 Conclusion of the Influence of the Ovarian Hormones on Carbohydrate Metabolism
In summary, evidence from metabolic studies suggests that oestrogen and progesterone have various effects on carbohydrate metabolism. Oestrogen promotes insulin sensitivity and possibly greater glycogen storage, while progesterone promotes insulin resistance. Oestrogen promotes contraction-stimulated glucose uptake into type I muscle fibres during short duration exercise, which should be beneficial for performance in higher intensity aerobic exercise, while progesterone antagonizes this action.[39] Thus, the increase in oestrogen relative to progesterone may determine the influence of the ovarian hormones during the LP on insulin-stimulated and contraction-stimulated glucose uptake and so Sports Med 2010; 40 (3)
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variably influence glycogen storage and plasma glucose availability during exercise. However, whole body systemic glucose kinetics is reduced during prolonged exercise, with increases in oestrogen alone or in combination with progesterone. Such a decrease in whole body glucose kinetics is possibly due to suppression of hepatic gluconeogenic production when the exercise intensity is sufficiently intense to put pressure on the system. Gluconeogenic suppression may jeopardize exercise performance when glycogen stores are limited. However, muscle glycogen stores are spared during exercise in the LP or in rats with oestrogen supplementation and should promote better endurance. Although researchers investigating menstrual phase comparisons have extensively studied carbohydrate metabolism during exercise, isotopic tracer measures of plasma glucose oxidation rate are still lacking. 2.2 Fat Metabolism
While occasionally indirect calorimetry measurements suggest greater whole body lipid use during exercise in the LF or ML phase compared with EF or MF phase,[11,19,22,61] this is not consistently reported.[24,25,44,62,63] However, when oestrogen supplements are administered independently of progesterone, the respiratory exchange ratio (RER) is lower during exercise compared with placebo in men[37] or compared with oestrogen and progesterone supplements together or gonadotropin-releasing hormone (GnRH) agonists (suppressed ovarian secretion) in women.[42] 2.2.1 Systemic Glycerol Kinetics as a Measure of Lipolytic Rate
Determination of glycerol Ra by tracer methodology is routinely used as an index of whole body lipolytic rate.[64] This is based on the assumption that following triacylglycerol hydrolysis in muscle and adipose tissue, glycerol must be released into the blood. Glycerol must be rephosphorylated by the enzyme glycerol kinase, present only in the liver and to a lesser degree in the kidneys before it can be reused in triacylglyª 2010 Adis Data Information BV. All rights reserved.
cerol re-esterification. Therefore, it is assumed that hepatic clearance of glycerol from the blood is the only significant route of irreversible loss of a glycerol tracer.[64] However, this assumption has been challenged, as some authors[65] have found that only half of the glycerol Ra is taken up by the splanchnic bed and therefore the periphery must be taking up the rest. Secondly, the findings of others[66] suggest that muscle may metabolize a significant amount of glycerol and therefore not all of the glycerol released by intramuscular triacylglycerol hydrolysis will appear in the bloodstream. Nonetheless, glycerol kinetics have been compared at rest and during submaximal exercise in eumenorrhoeic women in their EF and ML phase and then after 4 months of oral contraceptive supplementation.[67] No significant difference was found between menstrual phases in a subsample (n = 5), but oral contraceptive use increased glycerol Ra during submaximal exercise (n = 8). Oral contraceptive use also resulted in higher cortisol concentration, which is presumably causative of the heightened lipolytic rate.[67] A further study has examined glycerol kinetics during moderate intensity exercise in eumenorrhoeic women and included the MF phase – which is associated with moderate increases in oestrogen independent of progesterone – in their comparison.[62] These authors also found no significant variation in glycerol kinetics between menstrual phases. However, the average increase in oestrogen in the MF and ML phases was modest (265 and 393 pmol/L, respectively). Furthermore, exogenous oestrogen supplements given to amenorrhoeic women[36] or men[43] also failed to alter glycerol kinetics during submaximal exercise. However, the increase in oestrogen in the amenorrhoeic women was modest, approximating only FP levels. Conversely, the oral supplements in the men increased oestrogen to supraphysiological levels, and whether sex differences in lipolytic regulation[68,69] may have obscured an oestrogen effect on glycerol kinetics is indeterminate. In addition, the possibility of a sex difference in the response to oestrogen treatment cannot be excluded, as the receptor population of the endogenous sex hormones are Sports Med 2010; 40 (3)
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reportedly different between sexes.[70] Nonetheless, the limited evidence to date suggests that oestrogen and the ovarian milieu of the LP do not alter whole body systemic glycerol kinetics and, by inference, lipolytic rate during exercise. Oestrogen’s stimulation and progesterone’s antagonizm of growth hormone response to exercise,[71] however, suggest oestrogen may stimulate lipolysis, but consideration of the E/P ratio in the LP would be prudent. Animal research presents convincing evidence to suggest that oestrogen can in fact increase lipolytic rate during exercise. For example, Beniot et al.[72] reported a heightened sensitivity to catecholamines in oestrogen-supplemented rats, with a corresponding increase in hormone-sensitive lipase activity. These authors suggest that oestrogen acts via its catechol-oestrogen derivative to potentiate the lipolytic action of adrenaline (epinephrine) by competing with catecholamines for catecholO-methyltransferase.[72] In addition, Hansen et al.[73] demonstrated an increase in lipolysis and reduced fatty acid synthesis in isolated fat cells from oestrogen-treated rats, while progesterone had no effect compared with control/ unsupplemented rats. Oestrogen supplementation in male rats has also been found to alter lipoprotein lipase (LPL) activity in a tissue-specific fashion.[74] While adipocyte LPL activity was reduced, muscle LPL activity was increased, promoting a redistribution of lipids from adipose to muscle tissue. Consequently, oestrogen supplementation not only elevated resting intramuscular lipid content but also promoted triacylglycerol esterification during submaximal exercise in the red vastus muscle, as triacylglycerol content was even greater post-exercise than at rest.[74] Therefore, whole body glycerol kinetics would not be able to elucidate oestrogen’s tissue-specific action but instead presents the overall summated response. However, it must be considered that interspecies differences may occur in the regulation of lipid metabolism.[75] Encouraged by the overwhelming evidence from animal studies, future studies should consider tissue-specific glycerol kinetics using methods such as arteriovenous balance during exercise ª 2010 Adis Data Information BV. All rights reserved.
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in various menstrual phases including the LF phase, occurring approximately 2 days before ovulation and in which oestrogen peaks. 2.2.2 Plasma Free Fatty Acid Kinetics and Oxidation
FFA Ra provides an index of plasma FFA availability and measures the release of fatty acids that are primarily derived from the hydrolysis of adipose tissue triacylglycerol into plasma.[69] When used as a measure of lipolytic response, FFA Ra does not account for triacylglycerol re-esterification.[76] FFA Rd measures the rate of uptake into tissues and has been used as an estimate of plasma FFA oxidation rate;[77] however, this is a crude estimate as the actual proportion of FFA uptake that is oxidized can vary and has been reported to be as low as 50%.[78] A number of studies have considered plasma FFA kinetics,[79-81] dietary FFA uptake into body stores[82] and plasma triacylglycerol kinetics[81] between menstrual phases,[79,81,82] and with and without oestrogen supplements in postmenopausal women[80] at rest. All studies reported no differences between menstrual phases or treatments. In fact, a similar FFA Ra at rest between menstrual phases is not surprising, as animal studies confirm that basal lipolysis is unchanged or even suppressed in the presence of oestrogen compared with oestrogen deficiency.[52,83] Conversely, oestrogen enhances catecholamine sensitivity as is noted by an upregulated lipolytic response to catecholamine stimulation with oestrogen treatment.[72,83] More recently, plasma FFA kinetics and oxidation have been compared during submaximal exercise during various menstrual phases in eumenorrhoeic women.[62,63] Jacobs et al.[63] performed a longitudinal study comparing plasma FFA metabolic response in the EF and ML phases and then with subsequent oral contraceptive use. Unfortunately, their menstrual phase comparison was reduced to a sample size of five, which limited the statistical power of the comparison. Considering this limitation they reported no significant differences in the rates of whole body fat oxidation, plasma FFA oxidation, non-plasma FFA oxidation or plasma FFA Sports Med 2010; 40 (3)
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rate of appearance or disappearance or rate of re-esterification.[63] The average oestrogen concentration in the ML phase was a modest 311 pmol/L and the E/P ratio was fairly low, at 9. Furthermore, they failed to make use of the acetate correction factor in their calculation of plasma FFA oxidation, which is now established as necessary for more accurate estimates of plasma FFA oxidation rate.[84] The acetate correction factor accounts for the proportion of tracer-derived carbon label that is retained in the products of secondary exchange reactions that occur with tricarboxylic acid cycle intermediates instead of being released as carbon dioxide.[84] Our laboratory has observed significant variability in the acetate correction factor between menstrual phases.[85] The correction factor was lower in the ML phase compared with the EF phase.[85] We speculate that this may be associated with increased protein catabolism during exercise in the ML phase, as reported by others.[86] That is, the increased flux through transamination pathways may result in a slightly greater proportion of FFA tracer-derived carbon label isotope being retained in the products of subsidiary reactions with tricarboxylic acid cycle intermediates. Thus, in order to further increase the sensitivity of the comparison of plasma FFA oxidation rate between menstrual phases, it would be necessary to simultaneously derive the acetate correction factor and plasma FFA oxidation for each menstrual phase. Shortly following the study by Jacobs et al.,[63] a second study by Horton et al.[62] considered FFA kinetics during moderate exercise in the EF versus MF versus ML phases. The MF phase is characterized by a gradual increase in oestrogen concentration independently of progesterone. The authors found no variation in FFA Ra or Rd between menstrual phases. However, the average oestrogen concentration recorded in the MF phase of the study by Horton et al.[62] was moderate (264 pmol/L), and even the ML phase oestrogen value (393 pmol/L) was fairly modest for this menstrual phase, resulting in a low E/P ratio of 10.7. These authors, as with Jacobs et al.,[63] agreed that the magnitude of increase in oestrogen and the oestrogen increase relative to progesterª 2010 Adis Data Information BV. All rights reserved.
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one may be an important factor determining the impact of the ovarian hormones on fat metabolism. Horton et al.[62] went on to presume that variations may be noticeable in the LF or periovulatory period when oestrogen is elevated independently of progesterone. Such speculations are based on compelling evidence from animal studies. Ovariectomy reduces the activity of key enzymes in fat metabolism, i.e. carnitine palmitoyl transferase-I (CPT-I) and beta-3-hydroxyacyl-CoA dehydrogenase (b–HAD).[40] Oestrogen restores the activity of these enzymes, while progesterone inhibits these positive actions when oestrogen is at physiological concentrations.[40] However, a supraphysiological concentration of oestrogen overrides the negative effects of progesterone.[40] Interestingly, the difference in b-HAD activity with oestrogen treatment was only evident in muscle sections composed primarily of type I fibres[40] and not in sections of predominantly type II fibres.[40,52] Nonetheless, this rat model demonstrates the ability of the ovarian hormones to alter the capacity for skeletal muscle to oxidize FFAs by directly impacting on the cellular metabolic pathways. In an initial pilot study performed in our laboratory, we measured plasma palmitate Ra and Rd with a continuous infusion of 1-13C palmitate during moderate intensity exercise over 90 minutes in eumenorrhoeic women (n = 5) who were 3-hours postabsorptive (Oosthuyse and Bosch, unpublished observations). The women all completed the trial twice, once in the EF phase and then again in either the LF (or periovulatory) phase or ML phase or late luteal (LL) phase. The intention was to obtain the full range of ovarian hormones and E/P ratios that may occur during a menstrual cycle. We found that plasma palmitate Ra was highly correlated with E/P ratio (r = 0.85; p = 0.06) and was significant between plasma palmitate Rd and E/P ratio (r = 0.89; p = 0.04). A trend for a relationship between palmitate Ra, Rd and oestrogen concentration was evident. However, due to the limited sample size, no definite conclusions can be drawn. Nonetheless, this pilot study provides motivation for further investigations of exercising FFA metabolism of this kind that consider oestrogen and progesterone Sports Med 2010; 40 (3)
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variability between subjects and from one day to the next even within a menstrual phase. In summary, a first glance at the latest work covering plasma FFA kinetics and oxidation during exercise suggests no menstrual phase or ovarian hormone effect. All researchers in the field agree that considering interindividual and intraindividual variability in ovarian hormones and the relative ratio of E/P as they change even within a menstrual phase is imperative in convincingly identifying whether the fluctuations in oestrogen and progesterone, as occurs naturally across the menstrual cycle and specifically the LF phase, alter lipid metabolism during prolonged exercise.
2.2.3 Intramyocellular Stores and Use During Exercise
No study to date has considered the influence of the menstrual phase on intramyocellular lipid (IMCL) stores and use during exercise. Although an indirect estimation of IMCL use in exercise can be attained from isotopic tracer methods (by calculating the difference between whole body lipid oxidation and plasma FFA oxidation), it represents a rough estimate because it cannot differentiate IMCL oxidation from plasma triacylglycerol oxidation.[63] A number of recent studies have investigated variability in IMCL stores and use during exercise between men and women.[87-94] A full discussion of the findings of these sex-comparative studies is beyond the scope of the current review. However, researchers should carefully consider these findings when designing studies to consider variations in IMCL stores and use during exercise between menstrual phases. In particular, such future studies should consider menstrual variations in IMCL use during ultra-long endurance exercise, as Devries et al.[89] reported a higher percentage association between IMCL droplets and mitochondria following 90 minutes of exercise in women compared with men, where no sex differences were found before exercise. Ovarian hormone effects on IMCL use may become more apparent during the latter stages of ultra-events. ª 2010 Adis Data Information BV. All rights reserved.
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2.2.4 50 -AMP-Activated Protein Kinase, a Key Regulator of Cellular Metabolism, is Influenced by Oestrogen
Recent advances in the metabolic regulatory actions of 50 -AMP-activated protein kinase (AMPK) suggest that it is the major cellular energy regulator driving metabolic processes to promote ATP production.[95,96] Increased AMPK activity corresponds with increased GLUT4 content, contraction-stimulated glucose uptake and increased cellular fatty acid uptake, although evidence for a dominant role over the regulation of fat oxidation is not yet conclusive.[95] Evidence of oestrogen affecting AMPK activity[83] draws together the many previously suspected, but often elusive, actions of oestrogen. Specifically, AMPK is known to increase translocation of fatty acid translocase (FAT/CD36) and plasma membrane-bound fatty acid-binding protein (FABPpm).[96] FABPpm is abundant and therefore not limiting FFA uptake, but an increase in FAT/CD36 will increase FFA transport and oxidation and thus may limit FFA uptake. Since oestrogen is thought to stimulate AMPK activity,[83] it could be speculated that oestrogen will increase FFA uptake when sufficiently elevated in eumenorrhoeic women. Although AMPK’s role in enhancing fat oxidation has come under recent scrutiny,[97] AMPK is thought to inhibit the enzyme glycerol-3-phosphate acyltransferase, which initiates triacylglycerol synthesis, and acetyl-CoA carboxylase (ACC), which regulates the production of malonyl-CoA.[96] Malonyl-CoA is well known as a potent inhibitor of CPT-I and thus entry of long chain fatty acids (LCFAs) into mitochondria. Furthermore, AMPK is thought to increase the activity of malonyl-CoA decarboxylase, which breaks down malonyl-CoA to acetylCoA.[96] Thus, AMPK should promote entry of LCFA into beta oxidation. The study by D’Eon et al.[83] demonstrates the role of oestrogen in regulating fat metabolism via genomic and non-genomic pathways. Oestrogen promotes leanness and decreases adipocyte size by decreasing fatty acid uptake into adipose tissue (via decreased expression of lipoprotein lipase [LPL]), decreasing lipogenesis (via decreased expression of ACC-1 and fatty acid synthase [FAS]) Sports Med 2010; 40 (3)
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and increasing catecholamine stimulated lipolysis, but not basal lipolysis (via increased expression of the phosphoprotein, perilipin).[83] Oestrogen alters gene expression by binding to the oestrogen receptor response elements located in the promoters of target genes and thereby regulates liver X receptor a (LXRa) and sterol regulatory element-binding protein 1c (SREBP-1c), which regulate the transcriptional expression of ACC-1 and FAS.[83] However, the genomic influence of oestrogen in muscle and liver differ from that of adipocytes.[83] In muscle and liver, oestrogen upregulates the transcription factor peroxisome proliferation activator receptor-d (PPAR-d), which leads to the increased expression of various enzymes (LPL, pyruvate dehydrogenase kinase, acyl-CoA oxidase, and uncoupling protein 2 and 3), which promotes energy dissipation and the oxidation of FFA.[83] Moreover, oestrogen-treated ovariectomized mice displayed 5-fold increased AMPK activity in skeletal muscle compared with placebo-treated mice.[83] The AMPK response to oestrogen occurred rapidly in a time- and dose-dependent manner via binding to membrane-bound oestrogen receptors and thus stimulating increased fat uptake into mitochondria.[83] Interestingly, recent findings have shown that the expression of oestrogen receptors a and b in skeletal muscle increases with the level of endurance training,[98] and hence it is interesting to question whether a greater oestrogenstimulated AMPK response could be expected in skeletal muscles of endurance-trained athletes. However, oestrogen’s stimulation of AMPK is not aided by adipokines, as the study by D’Eon et al.[83] found leptin and adiponectin concentration to be lower in oestrogen-treated mice, possibly due to the smaller adipocyte size in the oestrogentreated group and oestrogen’s inhibition of SREBP-1c. Other studies have also found oestrogen to decrease adiponectin concentration in pregnancy.[99] However, one study showed large fluctuations in adiponectin in women across the menstrual cycle, but no association with the ovarian hormone profile was evident.[100] D’Eon et al.[83] suggest that the ‘oestrogen effect’ is largely a result of oestrogen’s manipulaª 2010 Adis Data Information BV. All rights reserved.
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tion of the following targets: SREBP-1c, PPAR-d and AMPK. In fact, although oestrogen may act independently on SREBP-1c and PPAR-d, cellular and transcriptional regulation afforded by AMPK[96] mimics many of the observations reported in the oestrogen-treated mice in the study by D’Eon et al.[83] Thus, it is tempting to propose that oestrogen’s activation of AMPK is the major key to the metabolic perturbations of oestrogen. Further work in this area is suggested. Studies in eumenorrhoeic women should consider variations in the AMPK response to exercise across the menstrual cycle and to test for associations between oestrogen and/or progesterone concentration and changes in the AMPK response to exercise. 2.2.5 Conclusion of the Influence of the Ovarian Hormones on Fat Metabolism
Animal research presents strong evidence that oestrogen promotes lipolysis and increases plasma FFA availability during exercise, increases intramuscular lipid stores and increases cellular capacity for FFA oxidation. Recent evidence suggests that many of oestrogen’s metabolic actions may occur through AMPK stimulation and activation of transcription factors. Such optimization of lipid metabolism with oestrogen would promote an ideal metabolic response for endurance exercise. However, isotopic tracer studies in resting or exercising eumenorrhoeic women have reported no differences in systemic glycerol or FFA kinetics. Future lipid metabolic studies should consider the magnitude of increase in oestrogen between menstrual phases and the increase in oestrogen relative to progesterone during the LP. Furthermore, studies focusing on tissue-specific metabolism in women may help to explain the divergent findings of animal and human research. 2.3 Influence of Ovarian Hormones on Protein Metabolism
Recent tracer studies have consistently found amino acid oxidation to be greater in the LP compared with the FP at rest.[101-103] Kriengsinyos et al.[101] observed the strongest correlation between measurements of phenylalanine oxidation and progesterone, suggesting that progesterone Sports Med 2010; 40 (3)
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has the greatest impact on amino acid catabolism in the LP. Furthermore, the greater amino acid oxidation in the LP coincided with greater dietary lysine requirement in the LP compared with the FP.[101] Reports on amino acid flux are less consistent. One study has reported greater flux in the LP compared with the FP at rest,[102] while others reported no differences.[101,103] Some have also found non-oxidative leucine disposal (NOLD) to be lower in the LP, suggesting less protein synthesis.[103] In a study in which ovarian hormone secretion was suppressed by administration of a gonadotropin releasing hormone agonist, it was found that leucine turnover and NOLD were attenuated compared with normally cycling women.[103] Thus, the ovarian hormones support maintenance of normal protein turnover in women, and as catabolism varies across menstrual phase, protein requirement varies coincidently. Evidence of greater protein catabolism during exercise in the LP is provided by earlier studies. Bailey et al.,[33] found the concentration of various amino acids (i.e. alanine, glutamine, proline and isoleucine) to be lower in the ML phase compared with the EF phase at rest and during prolonged submaximal exercise in subjects exercising 3 hours postabsorptively. This suggests greater amino acid catabolism during exercise in the LP. However, the amino acid concentration difference between phases was smaller if a carbohydrate supplement was ingested during exercise compared with a placebo drink.[33] Lamont et al.,[86] also reported that protein catabolism was greater during the ML phase compared with the EF phase as measured by total urea nitrogen excretion over 4 days, including a 60-minute . period of exercise at 70% VO2max. Total urinary urea nitrogen excretion over the exercise period was also greater in the ML phase compared with the EF phase.[86] In contrast to the seemingly catabolic stimulation of protein metabolism in the LP, recent evidence suggests a positive influence of oestrogen in reducing protein oxidation.[104] For example, oral oestrogen supplementation in men reduced leucine oxidation by 16% at rest and during exercise compared with placebo treatment and so accounted for an increase in the protein balª 2010 Adis Data Information BV. All rights reserved.
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ance (calculated as the difference between total protein synthesis and breakdown) by 8 mg of protein/kg/h at rest and 17 mg of protein/kg/h during exercise.[104] A recent study examined the rate of myofibrillar and connective tissue protein synthesis following one-legged kicking exercise in two groups of eumenorrhoeic women.[105] One group participated in the FP and the other in the LP. No differences between phases were reported, although this study may have been limited by the statistical unpaired design.[105] Further studies regarding protein or amino acid kinetics and oxidation during exercise across the menstrual cycle are warranted. In summary, the ovarian hormones have a noticeable influence on protein metabolism at rest and during exercise, which is often seen as increased catabolism in the LP. It appears that progesterone is responsible for the consistent finding of increased protein catabolism in the LP,[101] while oestrogen may reduce protein catabolism.[104] It would be interesting to investigate whether the E/P ratio in the LP is important in determining the extent of protein catabolism in this menstrual phase. Furthermore, studies in eumenorrhoeic women in the late follicular or pre-ovulatory phase to verify oestrogen’s capacity to reduce protein oxidation would be valuable. Such studies conducted during exercise are necessary to determine the protein requirements of female athletes participating in endurance competition. 3. Conclusions The potential of the ovarian hormones to impose major metabolic aberrations to carbohydrate, lipid and protein metabolism has been reported from both human and animal studies, and suggests repercussions for exercise performance in eumenorrhoeic women (as detailed in the summary following each subsection). However, the influences of the ovarian hormones on the various metabolic pathways appear highly complex and often tissue specific. Furthermore, oestrogen and progesterone have mostly opposing influences on the various systems, and responses Sports Med 2010; 40 (3)
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may be dependent on the concentrations of the respective ovarian hormones. Moreover, the extent of metabolic demand will also determine whether the ovarian hormone influences are physiologically significant. Consideration of these details is important for appreciating the effect on performance during different types of exercise. Consequently, menstrual phase-associated changes to the various metabolic measurements are not consistently identified. By inference, this may explain the inconsistency in the reports of menstrual phase-associated changes to exercise performance. The findings of menstrual phase studies may be confounded by the high variability in the concentrations of ovarian hormones between subjects and from day to day within subjects during any particular menstrual phase. For this reason, investigating relations between metabolic and exercise performance parameters and the change in the ovarian hormone concentrations between the menstrual phases and/or the E/P ratio should increase the sensitivity of studies for identifying metabolic or performance changes caused by the naturally cycling ovarian hormones. Acknowledgements Studies cited in this review as unpublished findings were supported by grants from the University of the Witwatersrand Research Council, Medical Research Council of South Africa and the National Research Foundation. The authors have no conflicts of interest that are directly relevant to the content of this review.
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59. Elkind Hirsch KE, Sherman LD, Malinak R. Hormone replacement therapy alters insulin sensitivity in young women with premature ovarian failure. J Clin Endocrinol Metab 1993; 76: 472-5 60. Ezenwaka EC, Akanji AO, Adejuwon CA, et al. Insulin responses following glucose administration in menstruating women. Int J Gynaecol Obstet 1993; 42: 155-9 61. Hackney AC, Curley CS, Nicklas BJ. Physiological responses to submaximal exercise at the mid-follicular, ovulatory and mid-luteal phases of the menstrual cycle. Scand J Med Sci Sports 1991; 1: 94-8 62. Horton TJ, Miller EK, Bourret K. No effect of menstrual cycle phase on glycerol or palmitate kinetics during 90 min of moderate exercise. J Appl Physiol 2006; 100: 917-25 63. Jacobs KA, Casazza GA, Suh S-H, et al. Fatty acid reesterification but not oxidation is increased by oral contraceptive use in women. J Appl Physiol 2005; 98: 1720-31 64. Wolfe RR. Radioactive and stable isotope tracers in biomedicine: principles and practice of kinetic analysis. New York: Wiley-Liss, Inc., 1992 65. Landau BR, Wahren J, Previs SF, et al. Glycerol production and utilization in humans: sites and quantification. Am J Physiol 1996; 271: E1110-7 66. Elia M, Kahn K, Calder G, et al. Glycerol exchange across the human forearm assessed by a combination of tracer and arteriovenous exchange techniques. Clin Sci 1993; 84: 99-104 67. Casazza GA, Jacobs KA, Suh S-H, et al. Menstrual cycle phase and oral contraceptive effects on triglyceride mobilization during exercise. J Appl Physiol 2004; 97: 302-9 68. Hellstro¨m L, Blaak E, Hagstro¨m-Toft E. Gender differences in adrenergic regulation of lipid mobilization during exercise. Int J Sports Med 1996; 17: 439-47 69. Mittendorfer B, Horowitz JF, Klein S. Effect of gender on lipid kinetics during endurance exercise of moderate intensity in untrained subjects. Am J Physiol 2002; 283: E58-65 70. Haffner SM, Valdez RA. Endogenous sex hormones: impact on lipids, lipoproteins, and insulin. Am J Med 1995; 98: 40S-7S 71. Faria ACS, Bekenstein LW, Booth Jr RA, et al. Pulsatile growth hormone release in normal women during the menstrual cycle. Clin Endocrin 1992; 36: 591-6 72. Benoit V, Valette A, Mercier L, et al. Potentiation of epinephrine-induced lipolysis in fat cells from estrogen-treated rats. Biochem Biophys Res Comm 1982; 109: 1186-91 73. Hansen FM, Fahmy N, Nielsen JH. The influence of sexual hormones on lipogenesis and lipolysis in rat fat cells. Acta Endocrin 1980; 95: 566-70 74. Ellis GS, Lanza-Jacoby S, Gow A, et al. Effects of estradiol on lipoprotein lipase activity and lipid availability in exercised male rats. J Appl Physiol 1994; 77: 209-15 75. Spriet LL. Regulation of fat/carbohydrate interaction in human skeletal muscle during exercise. Adv Exp Med Biol 1998; 441: 249-61 76. Romijn JA, Coyle EF, Sidossis LS, et al. Substrate metabolism during different exercise intensities in endurancetrained women. J Appl Physiol 2000; 88: 1707-14
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77. Romijn JA, Coyle EF, Sidossis LS, et al. Regulation of endogenous fat and carbohydrate metabolism in relation to exercise intensity and duration. Am J Physiol 1993; 265: E380-91 78. Friedlander AL, Casazza GA, Horning MA, et al. Effects of exercise intensity and training on lipid metabolism in young women. J Appl Physiol 1998; 275: E853-63 79. Heiling VJ, Jensen MD. Free fatty acid metabolism in the follicular and luteal phases of the menstrual cycle. J Clin Endocrinol Metab 1992; 74: 806-10 80. Jensen MD, Martin ML, Cryer PE, et al. Effects of estrogen on free fatty acid metabolism in humans. Am J Physiol 1994; 266: E914-20 81. Magkos F, Patterson BW, Mittendorfer B. No effect of menstrual cycle phase on basal very-low-density lipoprotein triglyceride and apolipoprotein B-100 kinetics. Am J Physiol 2006; 291: E1243-9 82. Uranga AP, Levine J, Jensen M. Isotope tracer measures of meal fatty acid metabolism: reproducibility and effects of the menstrual cycle. Am J Physiol 2005; 288: E547-55 83. D’Eon TM, Souza SC, Aronovitz M, et al. Estrogen regulation of adiposity and fuel partitioning: evidence of genomic and non-genomic regulation of lipogenic and oxidative pathways. J Biol Chem 2005; 280 (43): 35983-91 84. Sidossis LS, Coggan AR, Gastadelli A, et al. A new correction factor for use in tracer estimations of plasma fatty acid oxidation. Am J Physiol 1995; 269: E649-56 85. Oosthuyse T, Bosch AN, Jackson S. Effect of menstrual phase on the acetate correction factor used in metabolic tracer studies. Can J Appl Physiol 2003; 28: 818-30 86. Lamont LS, Lemon PWR, Bruot BC. Menstrual cycle and exercise effects on protein catabolism. Med Sci Sports Exerc 1987; 19: 106-10 87. White LJ, Ferguson MA, McCoy S, et al. Intramyocellular lipid changes in men and women during aerobic exercise: a 1 H-magnetic resonance spectroscopy study. J Clin Endocrinol Metab 2003; 88: 5638-43 88. Tarnopolsky MA, Rennie CD, Robertshaw HA, et al. Influence of endurance exercise training and sex on intramyocellular lipid and mitochondrial ultrastructure, substrate use, and mitochondrial enzyme activity. Am J Physiol 2007; 292 (3): R1271-8 89. Devries MC, Lowther SA, Glover AW, et al. IMCL area density, but not IMCL utilization, is higher in women during moderate-intensity endurance exercise, compared with men. Am J Physiol 2007; 293 (6): R2336-42 90. Zehnder M, Ith M, Kreis R, et al. Gender-specific usage of intramyocellular lipids and glycogen during exercise. Med Sci Sports Exerc 2005; 37 (9): 1517-24 91. Forsberg AM, Nilsson E, Werneman J, et al. Muscle composition in relation to age and sex. Clin Sci 1991; 81: 249-56 92. Roepstorff C, Steffensen CH, Madsen M, et al. Gender differences in substrate utilization during submaximal exercise in endurance-trained subjects. Am J Physiol 2002; 282: E435-47 93. Roepstorff C, Donsmark M, Thiele M, et al. Sex differences in hormone-sensitive lipase expression, activity, and phosphorylation in skeletal muscle at rest and during exercise. Am J Physiol 2006; 291: E1106-14
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Menstrual Cycle, Metabolism and Performance
94. Steffensen CH, Roepstorff C, Madsen M, et al. Myocellular triacylglycerol breakdown in females but not in males during exercise. Am J Physiol 2002; 282: E634-42 95. Jørgensen SB, Richter EA, Wojtaszewski JFP. Role of AMPK in skeletal muscle metabolism regulation and adaptation in relation to exercise. J Physiol 2006; 574 (1): 17-31 96. Steinberg GR, Macaulay SL, Febbraio MA, et al. AMPactivated protein kinase: the fat controller of the energy railroad. Can J Physiol Pharmacol 2006; 84: 655-65 97. Roepstorff C, Thiele M, Hillig T, et al. Higher skeletal muscle a2AMPK activation and lower energy charge and fat oxidation in men than in women during submaximal exercise. J Physiol 2006; 574 (1): 125-38 98. Wiik A, Gustafsson T, Esbjo¨rnsson M, et al. Expression of oestrogen receptor alpha and beta is higher in skeletal muscle of highly endurance-trained than of moderately active men. Acta Physiol Scand 2005; 184 (2): 105-12 99. Combs TP, Berg AH, Rajala MW, et al. Sexual differentiation, pregnancy, calorie restriction, and aging affect the adipocyte-specific secretory protein adiponectin. Diabetes 2003; 52: 268-76 100. Kleiblova P, Springer D, Haluzı´ k M. The influence of hormonal changes during menstrual cycle on serum adiponectin concentration in healthy women. Physiol Res 2006; 55: 661-6
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101. Kriengsinyos W, Wykes LJ, Goonewardene LA, et al. Phase of menstrual cycle affects lysine requirement in healthy women. Am J Physiol 2004; 287: E489-96 102. Lariviere F, Moussalli R, Garrel DR. Increased leucine flux and leucine oxidation during the luteal phase of the menstrual cycle in women. Am J Physiol 1994; 267: E422-8 103. Toth MJ, Sites CK, Matthews DE, et al. Ovarian suppression with gonadotropin-releasing hormone agonist reduces whole body protein turnover in women. Am J Physiol 2006; 291: E483-90 104. Hamadeh MJ, Devries MC, Tarnopolsky MA. Estrogen supplementation reduces whole body leucine and carbohydrate oxidation and increases lipid oxidation in men during endurance exercise. J Clin Endocrinol Metab 2005; 90 (6): 3592-9 105. Miller BF, Hansen M, Olesen JL, et al. No effect of menstrual cycle on myofibrillar and connective tissue protein synthesis in contracting skeletal muscle. Am J Physiol 2006; 290: E163-8
Correspondence: Dr Tanja Oosthuyse, School of Physiology, University of the Witwatersrand Medical School, Postnet Suite 19, Private Bag X8, Northriding 2162, South Africa. E-mail:
[email protected]
Sports Med 2010; 40 (3)
Sports Med 2010; 40 (3): 229-246 0112-1642/10/0003-0229/$49.95/0
REVIEW ARTICLE
ª 2010 Adis Data Information BV. All rights reserved.
Alterations in Central Fatigue by Pharmacological Manipulations of Neurotransmitters in Normal and High Ambient Temperature Bart Roelands and Romain Meeusen Department of Human Physiology and Sports Medicine, Faculty of Physical Education and Physiotherapy, Vrije Universiteit Brussel, Brussels, Belgium
Contents Abstract. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1. Fatigue: Periphery and the CNS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1 Peripheral Aspects of Fatigue . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2 Central Aspects of Fatigue . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2.1 The ‘Central Fatigue Hypothesis’ . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2.2 Biosynthesis and Metabolism of Serotonin, Dopamine and Noradrenaline. . . . . . . . . . . . . 2. Pharmacological Manipulations: Normal Environmental Temperature . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 Serotonin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Dopamine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3 Noradrenaline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3. Hyperthermia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4. Pharmacological Manipulations: High Environmental Temperature. . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 Effects of Catecholamines and Serotonin on Thermal Regulation . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 Effects on Performance. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2.1 Serotonin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2.2 Dopamine. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2.3 Noradrenaline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2.4 Combined Dopamine/Noradrenaline Reuptake Inhibition . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2.5 Caffeine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2.6 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5. Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Abstract
229 230 231 231 231 232 233 233 234 236 236 236 237 237 238 238 239 239 239 240 241 241
The scientific evidence is reviewed for the involvement of the brain monoamines serotonin, dopamine and noradrenaline (norepinephrine) in the onset of fatigue, in both normal and high ambient temperatures. The main focus is the pharmacological manipulations used to explore the central fatigue hypothesis. The original central fatigue hypothesis emphasizes that an exercise-induced increase in serotonin is responsible for the development of fatigue. However, several pharmacological studies attempted and failed to alter exercise capacity through changes in serotonergic neurotransmission in humans, indicating that the role of serotonin is often overrated. Recent
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studies, investigating the inhibition of the reuptake of both dopamine and noradrenaline, were capable of detecting changes in performance, specifically when ambient temperature was high. Dopamine and noradrenaline are prominent in innervated areas of the hypothalamus, therefore changes in the catecholaminergic concentrations may also be expected to be involved with the regulation of body core temperature during exercise in the heat. Evidence from different studies suggests that it is very unlikely that one neurotransmitter system is responsible for the appearance of central fatigue. The exact mechanism of fatigue is not known; presumably a complex interplay between both peripheral and central factors induces fatigue. Central fatigue will be determined by the collaboration of the different neurotransmitter systems, with the most important role possibly being for the catecholamines dopamine and noradrenaline.
Every athlete will experience fatigue on a regular basis. It may be fatigue because of a short term intensive exercise such as a 200 m sprint, an eight repetitions biceps curl set at 80% of one repetition maximum, or the fatigue experienced by a triathlete after an 11-hour race. Since there are many forms of fatigue, it is obvious that there are also several definitions available. In exercise physiology, fatigue has traditionally been defined as an acute impairment of exercise performance that leads to an inability to produce maximal force output possibly due to metabolite accumulation or substrate depletion.[1] However, fatigue will not only occur at the peripheral level, since there is ample evidence that mechanisms within the CNS are also implicated in the genesis of fatigue. The purpose of this article is to review the scientific evidence for the involvement of the brain monoamines serotonin, dopamine and noradrenaline (norepinephrine) in the onset of fatigue, in both normal and high ambient temperatures. Literature incorporated in this review was collected over 5 years, when the different studies were performed in our laboratory. A literature search of PubMed and ISI Web of Knowledge with the specific key words ‘dopamine’, ‘noradrenaline’, ‘serotonin’, ‘exercise’, ‘performance’, ‘heat’, ‘central fatigue’ and ‘thermoregulation’ was performed. These studies were further selected based on their purpose, the protocol applied, the number of subjects and the use of a control group. A number of excellent reviews ª 2010 Adis Data Information BV. All rights reserved.
were also included and provided even more interesting articles. 1. Fatigue: Periphery and the CNS Fatigue has many definitions. Be it a ‘failure to maintain the required force’,[2] or an ‘inability to continue working at a given exercise intensity’,[3] fatigue results in an acute impairment of exercise performance that includes both an increase in the perceived effort necessary to exert a desired force, and the eventual inability to produce that force.[4] It is obvious that fatigue not only occurs at the peripheral level, but that the ‘perception’ of fatigue is processed at the central level,[1] and that cerebral metabolism and neurohumoral or neurotransmitter responses during exercise can be disturbed, leading to fatigue.[5] It therefore appears that many parameters affect the capacity to ‘perform’ during exercise and each will depend on the type of exercise, the duration of exercise and on environmental factors. The processes that lead to decrements in performance can occur at every level of the brainmuscle pathway,[6] and although the literature makes a distinction between peripheral and central fatigue, we should be aware that both pathways are possibly integrated. Readers are directed to the work of St Clair Gibson et al.,[7] Marino,[8] Noakes et al.[9] and others on the perception of effort and possible integration of central and peripheral signals during exercise. This model describes a complex and intelligent Sports Med 2010; 40 (3)
Pharmacological Manipulation Effects on Performance
regulatory system that integrates peripheral and central elements of fatigue into a teleoanticipatory pacing system, which seeks to alter exercise intensity to maintain homeostasis at all times to prevent the catastrophic cessation of exercise. For the purpose of this review, central fatigue is defined as fatigue originating from the CNS. There is a strong link between alterations in neurotransmitters and neuromodulators and an individual’s mood; this implies that an increased sense of effort and a diminished drive to continue exercise result in centrally mediated fatigue. 1.1 Peripheral Aspects of Fatigue
Much research has focused on the peripheral aspects of fatigue, induced by the occurrence of a ‘metabolic end-point’.[10] An important cause of peripheral fatigue is depletion of energy stored in the working muscles. Studies have shown that during prolonged exercise, the rate of adenosine triphosphate (ATP) utilization exceeds the rate of ATP synthesis.[11] This might be due in part to decreased levels of creatine phosphate,[12] although Baldwin et al.[13] did not find these specific changes during prolonged exercise. As substrate availability is important, the depletion of muscle glycogen is often linked with muscle fatigue. At a certain point during prolonged exercise there will be an inability to maintain a sufficient rate of ATP resynthesis, secondary to reduced availability of pyruvate and key metabolic intermediates with the appearance of fatigue.[14] Besides depletion of energy sources, the accumulation of metabolic by-products – such as lactate and hydrogen ions after breakdown of glycogen, and glucose and ammonia after the breakdown of both ATP and amino acids[15] – have also been implicated in peripheral fatigue. During exercise without adequate fluid replacement, dehydration can occur. Even small decreases in body fluid can alter cardiovascular function and can consequently impair performance.[16] The magnitude of this effect will increase when exercise is performed in higher environmental temperatures.[17] If sweat loss during exercise is increased, the body has a smaller amount of blood volume to contribute to the ª 2010 Adis Data Information BV. All rights reserved.
231
sweat output; therefore, over time, blood flow to the skin is reduced, sweat output is decreased and the ability to dissipate heat is inhibited. This results in increased thermal strain, which may elicit fatigue by impairing voluntary activation of the muscle.[18,19] 1.2 Central Aspects of Fatigue
Much research has been focused on the involvement of the motor pathways in fatigue. Neuromuscular fatigue occurs when a progressive exercise-induced failure of voluntary activation of the muscle exists together with a gradual failure to drive motor neurons. Taylor and Gandevia[20] state that neuromuscular fatigue can be demonstrated by an increase in the increment of force evoked by nerve stimulation during a maximal voluntary contraction.[20] If extra force can be evoked by stimulating the motor neurons (superimposed twitch), central fatigue possibly takes place due to supraspinal mechanisms.[20] For an excellent review on this topic see the work by Taylor and Gandevia.[20,21] Brain neurotransmitter activity has not only been implicated in the regulation of cardiovascular[22,23] and endocrine[24,25] responses during exercise; neurotransmitters and especially the central monoamines are also strong candidates as neurochemical supports for central fatigueinducing effects of exercise. 1.2.1 The ‘Central Fatigue Hypothesis’
The monoamines serotonin, dopamine and noradrenaline play a key role in signal transduction between neurons, and exercise-induced changes in the concentrations of these neurotransmitters (especially serotonin and dopamine) have been linked to central fatigue. Romanowski and Grabiec[26] related serotonin, while Heyes[27] linked dopamine to a possible centrally mediated fatigue. Initiated by Acworth et al.,[28] Newsholme and his co-workers[29] developed the first hypothesis implicating changes in central neurotransmission to explain fatigue, i.e. the ‘central fatigue hypothesis’. This hypothesis is based on disturbances in brain serotonin concentrations, as this neurotransmitter is Sports Med 2010; 40 (3)
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involved in changes in sleep-wakefulness, emotion, sleep, appetite, the hypothalamic-pituitary axis and numerous physiological functions.[10] During exercise, the entry of tryptophan, a precursor of serotonin, into the CNS through the blood-brain barrier is favoured by increased muscle use of branched-chain amino acids and elevated plasma fatty acids, as this elevates the ratio of unbound tryptophan to branched-chain amino acids. This increases the amount of tryptophan crossing the blood-brain barrier, consequently leading to higher serotonin concentrations in the brain.[10,19] The hypothesis put forward by Newsholme et al.[29] has been challenged by several research groups who tried to manipulate performance and delay fatigue by different nutritional and pharmacological interventions, both in humans and in animals. The effects of the nutritional manipulations are not the main focus of this review and will not be discussed in detail (for a review on this topic see Meeusen et al.[10]). Table I (human, normal ambient temperature), table II (human, high ambient temperature) and table III (animal) give an overview of studies that ‘pharmacologically’ tried to manipulate brain neurotransmission in the search for mechanisms of fatigue induced by changes in the synthesis and metabolism of central monoamines. 1.2.2 Biosynthesis and Metabolism of Serotonin, Dopamine and Noradrenaline
This review focuses on pharmacological manipulations used to explore the central fatigue hypothesis. Most studies employing pharmacological substances aim at influencing different neurotransmitters and amino acids that have been related to central fatigue. The most important are serotonin, dopamine, noradrenaline, tryptophan, branched-chain amino acids, gaminobutyric-acid, glutamate, acetylcholine and adenosine. This review specifically focuses on three monoamines: serotonin, dopamine and noradrenaline. Serotonin-containing neurons are present in the cells located along the midline of the brainstem. They are mostly clustered in the raphe nuclei and their axons innervate nearly every region of the ª 2010 Adis Data Information BV. All rights reserved.
CNS.[65] The synthesis of serotonin requires two enzymatic steps. First, the amino acid precursor tryptophan is hydroxylized by tryptophan hydroxylase to L-5-hydroxytriptophan, and second, it is decarboxylated to serotonin. Metabolization occurs via aldehyde dehydrogenase and monoamine oxidase to 5-hydroxyindoleacetic acid.[66] Increases in serotonin are presumed to play an important role in various behavioural functions, such as increased feelings of tiredness, fatigue and pain, and decreases in the level of arousal.[33] Dopaminergic cells are primarily located in the mesencephalon, diencephalon and telencephalon. The main pathways include the nigrostriatal tractus, ventral mesostriatal pathway and tubero-infundibular system.[65] Neurons that synthesize noradrenaline are restricted to the pontine and medullary tegmental region, with the locus coeruleus being the most important noradrenaline nucleus.[67] Tyrosine hydroxylase is converted to L-3,4-dihydroxyphenylalanine (L-DOPA) by tyrosine hydroxylase. DOPA is then decarboxylated to dopamine by DOPA decarboxylase. Dopamine is implicated in increases of arousal, motivation, reinforcement, reward, the control of motor behaviour and mechanisms of addiction,[68] and can be reloaded in the synaptic vesicles for reuse. Dopamine is metabolized by monoamine oxidase to 3,4-dihydroxyphenylacetic acid, which is further destroyed by catechol-O-methyltransferase to homovanillic acid, or can be converted into noradrenaline by dopamine-b-hydroxylase. The catabolism of noradrenaline happens via monoamine oxidase and catechol-O-transferase. The main metabolite is 3-methoxy-4-hydroxyphenylethylene-glycol.[65] In their excellent review, Davis and Bailey[4] stated that not only increases in serotonin but an interaction between serotonin/dopamine would influence CNS fatigue, with a low ratio favouring improved performance and a high ratio decreasing motivation and augmenting lethargy, consequently decreasing performance.[4] The scientific evidence for the involvement of the brain monoamines serotonin, dopamine and noradrenaline in fatigue during prolonged exercise, in both normal and high ambient temperatures is reviewed in the following sections. Sports Med 2010; 40 (3)
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Table I. Pharmacological manipulations of central neurotransmission in humans in normal ambient temperature Study (year)
Subjects (no. of men)
Drug
Details
Exercise protocol . Cycling at 70% VO2max exh
Wilson and Maugan[30] (1992)
7
Paroxetine
SRI
Struder et al.[31] (1998)
10
Paroxetine
SRI
6
Fluoxetine
SRI
Davis et al.[32] (1993) Meeusen et al.[33] (2001)
Amb T (C)
Performance
18
fl
Cycling 2 mmol/L lactate exh . Cycling at 70% VO2max exh; incremental test to exh
8
Fluoxetine
SRI
Parise et al.[34] (2001)
11 12
Fluoxetine Fluoxetine
SRI SRI
Roelands et al.[35] (2009)
11
Citalopram
SRI
Pizotifen
Serotonin 5-HT2C antagonist
fl fl
90 min TT . Wingate + 80% VO2max exh . Wingate + 90% VO2max exh
18
Cycling 60 min 55 Wmax + 30 min TT . Running at 70% VO2max exh
18
2 2 2 2 2
Pannier et al.[36] (1995)
8
Marvin et al.[37] (1997)
13
Buspirone
5-HT1A agonist, dopamine D2 antagonist
Meeusen et al.[38] (1997)
7
Ritanserin
5-HT2A/2C antagonist
Piacentini et al.[39] (2002)
7
Venlafaxine
SNRI
Piacentini et al.[40] (2002)
7
Reboxetine
NRI
Roelands et al.[41] (2008)
9
Reboxetine
NRI
Cycling 60 min 55 Wmax + 30 min TT
Piacentini et al.[42] (2004)
8
Bupropion
Dopamine/NRI
90 min TT
18
2
Watson et al.[43] (2005)
8
Bupropion
Dopamine/NRI
18
2
Meeusen et al.[38] (1997)
7
L-Dopa
Dopamine precursor
Cycling 60 min 55 Wmax + 30 min TT . Cycling at 65% VO2max exh
18
2
16
Methylphenidate
Dopamine reuptake inhibitor
Cycling at fixed RPE of 16
Roelands et al.[45] (2008)
8
Methylphenidate
Dopamine reuptake inhibitor
Jacobs and Bell[46] (2004)
15
Modafinil
a1-Adrenergic agonist
Cycling 60 min 55 Wmax + 30 min TT . Cycling at 85% VO2max exh
Swart et al.[44] (2008)
. Cycling at 80% VO2max exh . Cycling at 65% VO2max exh
fl
18
2
90 min TT
18
2
90 min TT
18
2
18
fl
› 18
2 ›
5-HT = 5-hydroxytryptamine; Amb T = ambient temperature; exh = exhaustion; L-Dopa = L-3,4-dihydroxyphenylalanine; NRI = noradrenaline reuptake inhibitor; . RPE = ratings of perceived exertion; SNRI = serotonin/noradrenaline reuptake inhibitor; SRI = serotonin reuptake inhibitor; TT = time trial; VO2max = maximal oxygen uptake; Wmax = maximal wattage; › indicates significant increase; 2 indicates no difference; fl indicates significant decrease.
2. Pharmacological Manipulations: Normal Environmental Temperature In a previous paper we have already discussed several of the existing studies.[10] Therefore, in this review we only briefly present the most relevant papers and review new findings from research during the last 3 years, with special focus on the pharmacological manipulations used to unravel the mechanism of ‘central fatigue’. ª 2010 Adis Data Information BV. All rights reserved.
2.1 Serotonin
In rats, Bailey and co-workers[54-56] provided convincing evidence for a role of serotonin in the onset of fatigue. By using serotonin agonists, they showed that increased central serotonin activity decreased performance, while administration of a serotonin 5-HT1C/2 receptor antagonist (decreasing serotonin activity) led to performance improvement. Sports Med 2010; 40 (3)
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Table II. Pharmacological manipulations of central neurotransmission in humans in high ambient temperature Study (year)
Drug
Details
Exercise protocol
Amb T (C)
Performance
Strachan et al.[47] (2004)
8m
Paroxetine
SRI
Cycling at 60% . VO2max exh
32
2
Roelands et al.[35] (2009)
11 m
Citalopram
SRI
Cycling 60 min 55 Wmax + 30 min TT
30
2
Strachan et al.[48] (2005) Bridge et al.[49] (2003)
Subjects
6 m; 1 f 12 m
Pizotifen
5-HT2C antagonist
Cycling 40 km TT
35.5
2
Buspirone
5-HT1A receptor agonist; dopamine D2 antagonist
Cycling at 73% . VO2max exh
35
›
Roelands et al.[45] (2008)
8m
Methylphenidate
Dopamine reuptake inhibitor
Cycling 60 min 55 Wmax + 30 min TT
30
›
Watson et al.[43] (2005)
8m
Bupropion
Dopamine/NRI
Cycling 60 min 55 Wmax + 30 min TT
30
›
Roelands et al.[50] (2009)
8m
Chronic bupropion
Dopamine/NRI
Cycling 60 min 55 Wmax + 30 min TT
30
2
Roelands et al.[41] (2008)
9m
Reboxetine
NRI
Cycling 60 min 55 Wmax + 30 min TT
30
fl
5-HT = 5-hydroxytryptamine; Amb T = ambient temperature; exh = exhaustion; f = female; m = male; NRI = noradrenaline reuptake inhibitor; . SRI = serotonin reuptake inhibitor; TT = time trial; VO2max = maximal oxygen uptake; Wmax = maximal wattage; › indicates significant increase; 2 indicates no difference; fl indicates significant decrease.
From the literature it appears that results in humans are not that conclusive. Wilson and Maughan,[30] Marvin et al.[37] and Struder et al.[31] reported a shorter exercise time to exhaustion compared with placebo. Struder and Weicker[69] suggested, however, that the reduced exercise performance capacity might have been caused by differences in the regulatory function of serotonin rather than the increase in serotonin activity. The lack of response of prolactin after serotonin reuptake inhibition supported this statement.[69] Furthermore, endurance-trained athletes might also have developed mechanisms to compensate for excessive increases of brain serotonin.[69] Other studies were unable to detect any differences in performance after serotonin reuptake inhibition.[33,35,36] In a recently developed protocol, Roelands et al.[35] administered citalopram, a selective serotonin reuptake inhibitor, to subjects. In 18C ambient temperature, no differences in performances were observed for time-trial time. The contrasting findings in the literature probably result from the complexity of the serotonin neurotransmitter system, as many different receptors and receptor subtypes have been identified, each with different functions and interª 2010 Adis Data Information BV. All rights reserved.
actions (for a review see Zifa and Fillion[70]). However, this recent study and previous findings suggest that serotonin is not the key factor in the development of central fatigue but may play a role in combination with other neurotransmitter systems.[4] 2.2 Dopamine
Animal studies have shown that when rats stop exercising because of fatigue, dopamine concentrations are low due to an interaction with serotonin,[54] and the ratio between serotonin and dopamine has been hypothesized to influence central fatigue.[4] Gerald[57] administered amphetamines, potent catecholamine releasers to rats, and found significant increases in running time until exhaustion. Heyes et al.[27] infused rats with apomorphine (a dopamine agonist) and found a clear increase in the running time until exhaustion. After destruction of dopamine neurons, apomorphine was capable of restoring exercise capacity. In humans, Meeusen et al.[38] were not able to induce performance differences after supplementation with a dopamine precursor; L-3,4-dihydroxyphenylalanine (L-Dopa). Piacentini et al.[42] Sports Med 2010; 40 (3)
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influenced catecholaminergic transmission by administering a dual dopamine/noradrenaline reuptake inhibitor (bupropion). When bupropion or placebo were both administered, respectively, subjects finished a predetermined amount of work in the same amount of time (approximately
90 minutes). Animal studies showed that acute intraperitoneal bupropion injection produced increases in brain and core temperature and a decrease in tail temperature (heat loss mechanism) through an increase in noradrenaline and dopamine in the preoptic area and anterior hypothalamus
Table III. Pharmacological manipulations of central neurotransmission in animals in normal and high ambient temperature Study (year)
Subjects; no.
Drug
Details
Exercise protocol
Performance
Normal ambient temperature Jacobs and Eubanks[51] (1974)
SD rat; 64 males
Serotonin
NA
Crossing tilt cage: activity measured
fl
Hillegaart et al.[52] (1989)
Rats
8-OHDPAT
5-HT1A agonist
Open field activity + treadmill
2
Wilckens et al.[53] (1992)
Wistar rat males
m-chl-piperazine; DOI; quipazine
5-HT1C agonist; 5-HT2 agonist; serotonin agonist
Spontaneous running activity
fl
Bailey et al.[54] (1992)
Wistar rat; 8
m-chl-piperazine
5-HT1C agonist
RTTE (20 m/min; 5% incline)
fl
Bailey et al.[55] (1993)
Wistar rat; 36
Quipazine; LY 53857
Serotonin agonist; 5-HT1C and 5-HT2 antagonist
RTTE (20 m/min; 5% incline)
Quipazine: fl LY 53857: ›
Bailey et al.[56] (1993)
Wistar rat; 8 per group
Quipazine; LY 53857
Serotonin agonist; 5-HT1C and 5-HT2 antagonist
RTTE (20 m/min; 5% incline)
Quipazine: fl 32% LY 53857: › 26%
Gerald[57] (1978)
SD rat; 10 males
(+)-Amphetamine
Release catecholamine
RTTE (different speeds)
›
Heyes et al.[27] (1985)
SD rat; 57 males
6-OH dopamine lesion; apomorphine; clonidine
Dopamine agonist; a2 agonist
Treadmill running (36 m/min)
6-OH dopamine: fl apomorphine: clonidine: 2
Chaouloff et al.[58] (1987)
Wistar rat; 5 per group males
(+)-Amphetamine; pargyline; a-methylp-tyrosin; haloperidol
Release catecholamine monoamine oxidase B inhibitor; inhibitor catecholamine synthesis; dopamine antagonist
60 min treadmill (20 m/min; 5% incline)
2
Kalinski et al.[59] (2001)
Mice; 15 males
Methamphetamine
Dopamine reuptake inhibitor and neurotoxin
1 : 4 · increasing speed; 2 : RTTE (35 m/min)
fl
Connor et al.[60] (1999)
SD rat; 7–8
Reboxetine
NRI
Forced swim test
fl
Lima et al.[61] (1998)
Wistar rat; 27
Atropine
Antagonist central and peripheral muscarinic acetylcholine receptors
RTTE (15 m/min; 5% incline)
fl
Rodrigues et al.[62] (2004)
Wistar rat; 8
Physostigmine
Acetylcholinesterase inhibitor
RTTE (20 m/min; 5% incline)
2
Hasegawa et al.[63] (2005)
Wistar rat; 2
Tetrodotoxin
Sodium channel blocker
120 min running (10 m/min)
2
Bupropion
Dopamine/NRI
RTTE (26 m/min)
›
High ambient temperature Hasegawa et al.[64] (2008)
Wistar rat; 8
5-HT = 5-hydroxytryptamine; 5-HTTP = 5-hydroxytryptophan; 6-OH = 6-hydroxydopamine; 8-OHDPAT = 8-hydroxy-N,N-dipropyl-2-aminotetralin; DOI = 2,5-dimethoxy-4-iodoamphetamine; m-chl = m-chlorophenyl; NA = not available; NRI = Noradrenaline reuptake inhibitor; RTTE = running time to exhaustion; SD = Sprague-Dawley; › indicates significant increase; 2 indicates no difference; fl indicates significant decrease.
ª 2010 Adis Data Information BV. All rights reserved.
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(PO/AH),[71] and that neurotransmitter concentrations increased in the hippocampus.[72] A recent human study from our laboratory[43] used the same drug, bupropion. Catecholaminergic manipulation did not induce a difference in time-trial time at normal environmental temperature, but compared with placebo, core temperature was significantly elevated during the time trial without any changes in the subjects’ ratings of perceived exertion (RPE) and thermal stress scale.[43] In a recent study by Roelands et al.,[45] methylphenidate, an amphetamine-like stimulant widely administered to patients diagnosed with attention deficit hyperactivity disorder, was given to subjects. Treatment in normal ambient temperature did not induce any significant changes in performance and led to a nonsignificant rise in core temperature. The authors observed no change in RPE and thermal stress scale. As amphetamines are known for their performance-enhancing effects,[57,73] the reason for the lack of ergogenic effects in humans after dopamine manipulation in normal ambient temperature is not yet clear. Possibly, the influence of dopamine might not be strong enough in normal environmental temperatures.[45] However, the result found by Roelands et al.[45] is in contrast with findings by Swart et al.,[44] who observed subjects exercising at a fixed RPE after methylphenidate administration. Swart et al.[44] concluded that endurance performance is not only ‘limited’ by mechanical failure of the exercising muscles; rather, performance during prolonged endurance exercise under normal conditions is highly regulated by the CNS. 2.3 Noradrenaline
Less research has been performed on the role of noradrenaline in the onset of central fatigue. As noradrenaline is implicated in the control of level of arousal, consciousness and reward mechanisms in the brain, one would expect that noradrenaline reuptake inhibition leads to a delay in fatigue.[74] Results from Piacentini et al.,[39] administering a serotonin/ noradrenaline reuptake inhibitor (venlafaxine), show, however, no difference in performance, ª 2010 Adis Data Information BV. All rights reserved.
while Piacentini et al.[40] showed a trend towards a decrease in performance after acute administration of reboxetine (8 mg), a noradrenaline reuptake inhibitor. The authors found a ‘non-significant’ 5-minute difference in a 90-minute time trial when compared with placebo. Roelands et al.[41] administered reboxetine (16 mg) and found a 10% slower timetrial performance. This decrease in performance was unexpected; however, it is well known that noradrenaline neurons modulate the serotonin neurotransmitter system via excitatory a1receptors. The authors found a trend towards lower core temperatures, and subjects’ thermal stress scale scores were lower after reboxetine administration, indicating a hypothermic effect of noradrenaline reuptake inhibition. This effect was previously reported in animal studies[75-77] and is mediated by a2-noradrenergic receptors in the PO/AH.[78] 2.4 Summary
To summarize, animal studies that manipulated neurotransmitter systems through the administration of drugs, showed that fatigue can be elicited in normothermia, indicating an important role for serotonin and dopamine neurotransmission. However, in humans there is less clarity. Most evidence suggests that serotonin and dopamine are involved in central fatigue, but might not individually be able to alter fatigue. The noradrenaline neurotransmitter system has a negative influence on performance in normal ambient temperature. As it seems difficult to postpone fatigue in normothermia, in recent years there has been an increased interest in the role of hyperthermia and the link with pharmacological agents acting on the CNS during prolonged exercise. 3. Hyperthermia In both heat and cold, homeothermic animals utilize autonomic and behavioural responses to regulate their body temperature. These responses are better known as thermoregulation.[79] Mechanisms by which humans lose heat are well Sports Med 2010; 40 (3)
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described and include dilatation of the skin vessels, causing the warm blood from the body core to flow to the skin with sweating to facilitate evaporative heat loss. The hypothalamus is seen as the ‘thermoregulatory centre’ of the brain, and more specifically the PO/AH is thought to be the most important region, as it contains both coldsensitive and hot-sensitive neurons.[63] The PO/AH receives input from both peripheral and central thermoreceptors, and initiates appropriate heat loss or heat production responses.[64] During exercise we are no longer able to redistribute the same amount of blood from the body core to the skin, as the working muscles also demand an increased amount of blood.[79] The logical outcome is a rise in core temperature, inducing hyperthermia. The consequences are increases in the physiological strain on the body, and a severely impaired exercise capacity. Decreases in performance are specifically reported when exercise is undertaken in high ambient temperatures. Parkin et al.[80] and Galloway and Maughan[81] showed that exercise time to fatigue was significantly lower when exercise was undertaken in the heat, compared with normal and low ambient temperature. Mechanisms that cause this detrimental effect on performance were assumed to be associated with muscular and peripheral factors; however, these are not altered to such an extent that it would explain the diminished endurance during prolonged exercise in the heat.[5] Muscle glycogen stores are far from depleted, muscle and blood lactate concentrations are not elevated to levels normally associated with fatigue, and potassium release does not explain the hyperthermia-induced fatigue either.[82-85] Bru¨ck and Olschewski[86] suggested that performance in the heat is primarily regulated by a diminished drive from the CNS. This finding was later confirmed in studies by Nielsen et al.[83,84] An excellent review by Cheung[87] describes how over the past decade two major paradigms have been proposed for how hyperthermia may contribute to voluntary fatigue during prolonged exercise in the heat. The first paradigm suggests that exhaustion occurs upon the attainment of a critical core and brain temperature, serving as a protective mechanism and preventing poª 2010 Adis Data Information BV. All rights reserved.
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tential damage to body tissue by limiting further heat production.[17,83,88,89] This view has been supported by the observation that trained subjects, starting with different core temperatures, stop exercising at similar body core temperatures ~40C.[90] Brain temperature is a physiological parameter that is determined primarily by neural metabolism, and regulated by cerebral blood flow, which serves as a body-coupled heatexchanger system penetrating all brain structures.[64] Nybo and Secher[5] reported that cerebral blood flow is of utmost importance with regard to the cooling of the brain and is a safety mechanism to prevent a high level of heat storage and excessive hyperthermia, thus protecting the brain from thermal damage.[64] The second paradigm states that complex feed-forward and feedback mechanisms regulate fatigue. In this way, humans should be able to anticipate the intensity of heat stress that they will be or are exposed to, and would seek to regulate their workload accordingly to minimize heat storage.[19,91] This view has been supported by the finding that subjects reduce their workload early in a maximal 20 km time trial in the heat, prior to any increase in core temperature relative to normal ambient conditions. Serotonin, dopamine and noradrenaline have all been implicated in the control of thermoregulation and are thought to mediate thermoregulatory responses,[49] certainly since their neurons innervate areas of the hypothalamus, among which are also the PO/AH. It can be expected that a shift in the concentrations of these neurotransmitters contributes to changes in thermal regulation and consequently to fatigue, specifically when exercise is undertaken in hot environmental conditions. However, very little work has been reported on this potential mechanism (tables II and III). 4. Pharmacological Manipulations: High Environmental Temperature 4.1 Effects of Catecholamines and Serotonin on Thermal Regulation
The effects of brain catecholamines and serotonin on thermal regulation have been studied Sports Med 2010; 40 (3)
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in humans and animals. Noradrenaline microdialyzed in the PO/AH of different animal species evokes a fall in core temperature, a reaction mediated by a2-adrenoceptors.[75-78] On the other hand, studies that agonized a1-adrenoceptors found rapid rises in core temperature.[92,93] Local application of serotonin in the PO/AH was reported to alter thermosensitive neurons,[94] and studies reported both a rise[95] and a fall[96] of body temperature. Clark and Lipton[97] reviewed different responses of core temperature after micro-injection of serotonin into the PO/AH and concluded that the role of serotonin in the PO/AH in thermoregulation is obscure.[98] Hasegawa et al.[99] were able to show from a microdialysis study in rats that dopamine is important in the control of core temperature by modulating metabolic levels during exercise, while Ishiwata et al.[100] showed that g-aminobutyric acid is an important inhibitor of heat production in high environmental temperatures. Recently, perfusion of tetrodotoxin (a poison of the Japanese puffer fish that acts as a sodium channel blocker and is widely used for blockage of neurotransmission in specific brain regions) into the median raphe nucleus of rats induced considerable decreases in core temperature at 5C and 23C but not at 35C.[101] In contrast, when tetrodotoxin was microdialyzed in the PO/AH, it induced hyperthermia.[102] Hasegawa et al.[63] reported no change in the exercise behaviour of rats after injecting tetrodotoxin in the PO/AH via microdialysis. Tetrodotoxin did induce an increase in body core temperature, with a decrease in heat loss responses and an increase in heat production.[63] From these and previous animal studies[63,75-78,99-101] it seems fair to suggest that neurotransmission in the PO/AH region is involved in the regulation of body temperature during exercise and that both the catecholamines and serotonin can influence core temperature. Another key factor in the regulation of the internal body temperature is the environmental thermal condition. There have been interesting studies proving the effect of changes in environmental conditions to be imperative in the control of core temperature through the manipulation of neurotransmitter concentrations. Amphetaª 2010 Adis Data Information BV. All rights reserved.
mine has been shown to cause hyperthermia at temperatures of 20–37C but hypothermia at 4–14C.[103] Methamphetamine has shown the same effects.[104] Malberg and Seiden[105] showed that small changes in ambient temperature (2C) can produce changes in the thermal response to 3,4-methylene dioxymethamphetamine. At 20C, 3,4-methylene dioxymethamphetamine had a hypothermic effect, without significant changes in serotonin concentration, while at 30C there was a clear hyperthermic effect, coinciding with a decrease in serotonin. In a recent study, Myles et al.[106] reported that methamphetamine did not change core temperature at 24C, but there was a hypothermic effect at 20C and a hyperthermic effect at 28C. These results indicate that ambient conditions play an important role in the regulation of body core temperature. 4.2 Effects on Performance
Substrate availability in normothermia can, at least in part, account for the fatigue that occurs during prolonged exercise.[107] In the heat, it is clear that glycogen availability does not limit exercise capacity, and there is no clearly defined mechanism by which hyperthermia causes the decision to stop exercising.[108] Since serotonin, dopamine and noradrenaline have all been implicated in thermoregulation and central fatigue, researchers focused their attention towards the link between both by using pharmacological substances to disturb normal neurotransmission. 4.2.1 Serotonin
Strachan and co-workers[47] examined the effects of the serotonin reuptake inhibitor paroxetine at 32C in a time-to-exhaustion trial. The authors found no evidence for detrimental effects of serotonin on exercise capacity, nor were there any differences in the subjects’ RPE between the placebo and drug trial. Core temperature was very slightly increased by paroxetine, suggesting that it acts as a postsynaptic serotonin agonist.[109] This increase in core temperature might have been too small to evoke any negative effects on performance. The authors therefore concluded that the administration of paroxetine did Sports Med 2010; 40 (3)
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not significantly influence thermoregulatory factors that may limit performance.[47] In a follow-up study,[48] the role of serotonin was further explored during exercise in the heat. Pizotifen, a selective 5-HT2C receptor antagonist, was administered in order to examine whether blockade of 5-HT2C receptors exacerbates the thermal response and limits exercise performance in a 40 km time trial. Rectal temperature was increased by pizotifen, thereby confirming the results of a rodent study[110] that the 5-HT2 receptor family has a role in thermoregulation. However, the higher rectal temperatures did not induce any change in performance.[48] The lack of effect on performance confirms the results of Meeusen et al.,[38] who found no change in time to exhaustion after ritanserin (5-HT2A/2C antagonist) administration at normal ambient temperature. 4.2.2 Dopamine
Two studies provided evidence for an important role of dopamine in delaying fatigue and increasing core temperature combined with exercise in the heat. Bridge and co-workers[49] administered buspirone, a drug that acts on 5-HT1A and dopamine, to subjects exercising at 35C. The authors concluded that there is evidence that high levels of dopamine activity in the hypothalamus are associated with an increased tolerance to exercise in the heat. We studied the effects of acute dopamine reuptake inhibition in the heat.[45] The results of this study indicate a strong ergogenic effect of methylphenidate at 30C. A time trial was completed >7 minutes (16%) faster when dopamine reuptake was inhibited. Core temperature during the methylphenidate trial was significantly increased at rest, presumably due to the increased dopamine activity in combination with the heat, as also shown in other studies.[105,106] During time trials it is presumed that a significantly greater metabolic heat production in the methylphenidate trials results from the increased drive and motivation due to the dopamine reuptake inhibition. Interestingly, in the methylphenidate trial, average core temperature was 40C, while in the placebo trial only one subject reached this temperature. Despite reaching these high core temperatures there were no ª 2010 Adis Data Information BV. All rights reserved.
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changes in the thermal stress scale scores, and although the subjects’ heart rate and power output were higher, RPE was identical compared with placebo. Thus, it appears that mechanisms existing in the body to prevent harmful effects are dampened or overridden by the administration of a dopamine reuptake inhibitor, even at the low dose (20 mg, one-third of the maximal daily dose) administered. This prompted the authors to suggest there is a potential danger for the development of heat illness.[45] 4.2.3 Noradrenaline
A completely different effect was observed for noradrenaline reuptake inhibition (with reboxetine).[41] Performance during time trials at 30C with administration of reboxetine was 8 minutes (20%) slower compared with placebo trials conducted at this temperature. As noradrenaline is implicated in arousal and reward mechanisms, a better performance would have been expected rather than the 20% decrease. In fact, the present result is not that surprising, as Piacentini et al.[40] had already found a trend towards a decrease in performance with only half the dose administered. Core temperatures tended to be lower after reboxetine supplementation and subjects felt significantly colder. This confirms results from animal studies.[75-77] Quan et al.[78] showed that this effect is mediated by a2-noradrenergic receptors in the PO/AH. On the other hand, heart rates were higher after noradrenaline reuptake inhibition, which can be explained by a combination of both central and peripheral factors. Augmented noradrenaline concentrations are able to increase sympathomimetic activity, but it has also been hypothesized that the noradrenaline reuptake inhibition augments central noradrenaline inhibition in the parasympathetic nuclei, causing lower cardiac parasympathetic tone and an increase in heart rate.[41] 4.2.4 Combined Dopamine/Noradrenaline Reuptake Inhibition
Acute dopamine reuptake inhibition has a strong ergogenic effect, while acute noradrenaline reuptake inhibition has the opposite effect.[41,45] Results from these studies can be applied to the results of the acute bupropion Sports Med 2010; 40 (3)
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study. The literature suggests that bupropion shows a 2.5-fold selectivity for dopamine versus noradrenaline, while no changes in serotonin were reported.[64] The European Agency for the Evaluation of Medicinal Products[111] states that after bupropion administration, peak plasma concentrations are reached after 2–3 hours, while for the major metabolite, hydroxybupropion – which acts on the noradrenaline transporter – peak plasma concentrations are only reached after 6 hours. This means that bupropion first exerts its effects via dopamine pathways, while later there is a switch towards higher involvement of noradrenaline. As dopamine is known to have strong ergogenic effects when exercise is undertaken in high ambient temperature, this mechanism of action explains how bupropion improves performance and increases core temperature after acute administration. The results of the acute bupropion study in humans[43] were further explored in rats.[64] The authors examined the effect of bupropion in rats exercising in both normal and high ambient temperature. Microdialysis studies in rats have shown that acute administration of bupropion affects dopamine release in the striatum and nucleus accumbens,[112] and affects hippocampal dopamine, noradrenaline and serotonin release.[72] Running time until exhaustion was significantly influenced by ambient temperature, thereby confirming earlier studies in humans.[80,81] Brain and core temperature at exhaustion were significantly higher in the bupropion trial in the heat compared with the warm placebo trial. The higher core temperature was also observed after bupropion injection in freely moving rats,[71] while no differences in tail temperature were obvious between trials. These results are in line with those previously observed in humans[43] and indicate the potential performance-enhancing effects of this drug through its dopaminergic action. Bupropion is widely prescribed (40 million clinical-use exposures[113]) and is to be taken in a chronic manner. With regard to the impact of an acute dose, it was imperative to investigate the effects of chronic manipulation with the same drug.[50] Results from this study were less pronounced. Core temperature ª 2010 Adis Data Information BV. All rights reserved.
was significantly higher compared with a placebo, but only reached an average of 39.6C. Performance was not influenced by the chronic drug treatment (10 days). The reason for the diminished action after chronic bupropion administration will probably be linked to a central neurotransmitter homeostasis.[50] After approximately 7 days, bupropion and its metabolites reach steady-state levels.[113] Peak plasma levels with chronic administration are similar compared with levels reached after acute dosing, while for hydroxybupropion there is a 4-fold increase at steady-state compared with acute administration.[111] Logically, the concentration of hydroxybupropion gains importance as the ratio bupropion/hydroxybupropion is firmly decreased, indicating an increase in noradrenaline influence. Studies by Piacentini et al.[40] (5 minutes) and Roelands et al.[41] showed slower performances after increased noradrenaline neurotransmission (8 minutes), causing the different result when compared with acute bupropion administration.[43] Furthermore, Learned-Coughlin et al.[114] showed that after 11 days of bupropion there was only a low occupancy of the dopamine transporter. Serotonin, dopamine and noradrenaline are used in many therapeutic agents: sometimes combined, sometimes separately. Most antidepressants affect serotonin and/or noradrenaline and to a lesser extent dopamine, as there is evidence that drugs acting exclusively on dopamine do not appear to produce an appreciable antidepressant effect.[68] However, these neurotransmitter systems can also be influenced by different substances. Stimulant drugs, such as cocaine and amphetamines, exert their effects mainly through their effect on brain catecholamine concentrations;[115] alcohol, tobacco and caffeine also act via mechanisms including manipulation of neurotransmitter concentrations in the CNS. 4.2.5 Caffeine
Caffeine has been shown to exert ergogenic effects in normal ambient temperature,[116-121] probably related to the antagonism of adenosine receptors in the brain, resulting in increased dopamine neurotransmission. However, only one study has examined the effects of adenosine receptor antagonism in high environmental temperature.[122] Sports Med 2010; 40 (3)
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This study showed that caffeine did not alter exercise performance in a preloaded time trial. The authors found increased core temperatures during exercise – which was non-attributable to metabolic heat production, as subjects did not average higher power outputs – that were probably related to the influence of caffeine on the adenosine receptor and consequently dopamine. Very recently, we performed a study (Roelands et al., unpublished data) with caffeine manipulation in high temperature. Results were identical to the results obtained by Cheuvront et al.[122] From these two studies it became clear that environmental conditions play an important role in the effects mediated by caffeine. 4.2.6 Summary
In contrast to pharmacological manipulations in normal ambient temperature, manipulations of catecholamine levels via different reuptake inhibitors in the heat caused performance differences. Manipulation of the serotonin neurotransmitter level through reuptake inhibition did not influence performance, contradictory to the central fatigue hypothesis. Serotonin might be involved in the onset of fatigue, but in combination with other neurotransmitter systems. Dopamine has shown ergogenic effects and seems to override inhibitory signals from the CNS to stop exercising when core temperature becomes high. Core temperatures, increasing above 40C, are attained after dopamine reuptake inhibition, without any changes in the perception of effort and thermal strain. As the ‘safety brake’ seems to be eliminated, authors have suggested that there is a potential danger for the development of heat illness.[43] In contrast, noradrenaline reuptake inhibition led to slower performances and slightly lower core temperatures compared with a placebo. Taken together it appears that the catecholamines dopamine and noradrenaline have a much larger influence on fatigue, elicited via central neurotransmission, than does serotonin, indicating that the ‘original’ central fatigue hypothesis does not hold, especially when exercising in the heat. We have to take into account that in these trials there appears to be a complex regulatory system that integrates peripheral and central elements of fatigue into a teleoanticipatory pacing ª 2010 Adis Data Information BV. All rights reserved.
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system. Apparently, when pharmacological manipulations are made, the anticipatory system can be modified, as was shown in both human[41,43,45] and animal studies.[64,71] 5. Conclusions Originally, fatigue was attributed solely to peripheral factors, such as muscular and cardiovascular factors. In the last few decades there has been proof that fatigue can also occur at the level of the brain. This so-called central fatigue compromises specific alterations in the functioning of the CNS and can be divided into two major aspects: (i) neuromuscular fatigue, which is the change in voluntary activation of the muscle, originating from the CNS; and (ii) actions of different neurotransmitter systems that evoke central fatigue. Studies have tried to find the mechanisms by which central fatigue takes place, using indirect manipulations with different drugs known to evoke certain influences on central neurotransmission. There is convincing evidence in animals for the existence of central fatigue. Different animal studies in normothermia were able to show that increased serotonin activity in the CNS caused the onset of fatigue, especially when combined with a decrease in dopamine.[54-56] This result is not found in humans exercising in normal ambient temperature. It seems that serotonin is not the sole factor in the onset of fatigue. Dopamine has been shown to influence performance and increase core temperature when amphetamines were administered. Although the inhibition of the reuptake of dopamine increased core temperature, it did not induce any differences in performance in normothermia. Noradrenaline decreased performance and showed a small hypothermic effect. The above indicates that catecholaminergic neurotransmission will be implicated in the onset of fatigue and changes in thermal regulation in normal ambient temperature. Serotonin, dopamine and noradrenaline have been implicated in the control of thermoregulation and are thought to mediate thermoregulatory responses,[44] especially as their neurons innervate areas of the hypothalamus, the human thermoregulatory centre, which also includes the PO/AH. Sports Med 2010; 40 (3)
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Increases in core and brain temperature might be important factors in the onset of fatigue,[92] and it is known that a high ambient temperature is detrimental to exercise capacity. The combination of exercise and the manipulation of central neurotransmission in the heat may elucidate the mechanisms of fatigue. From these studies it was shown that dopamine significantly enhanced performance, coinciding with the attainment of high core temperatures and higher heart rates, without any change in thermosensation or the perception of effort. It seems that the safety mechanisms in the body are overridden due to increased dopaminergic activity. Increased brain concentration of noradrenaline strongly decreased performance in the heat and no negative effect of serotonin could be detected. Thermal regulation appears to be an important factor that will be influenced mainly by brain dopamine and noradrenaline in the PO/ AH, although the exact role of other neurotransmitter systems is not clear. It is very unlikely that one neurotransmitter system is responsible for the appearance of central fatigue. Most probably, central fatigue is caused by a complex interplay between the different neurotransmitters systems, with the most important role for the catecholamines dopamine and noradrenaline. Although work to date has given us clear observations on external behavioural changes after pharmacological interventions, the exact role of the different brain areas linked to exercise capacity and thermoregulation have yet to be elucidated. Acknowledgements We acknowledge the valuable work from Maria Francesca Piacentini, Hiroshi Hasegawa, Phil Watson, Luk Buyse, Guy De Schutter and Frank Pauwels. We also wish to acknowledge the help from funding from the Vrije Universiteit Brussel (OZR 607, 990, 1235). The authors have no conflicts of interest that are directly relevant to the content of this review.
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71. Hasegawa H, Meeusen R, Sarre S, et al. Acute dopamine/ noradrenaline reuptake inhibition increases brain and core temperature in rats. J Appl Physiol 2005; 99 (4): 1397-401 72. Piacentini MF, Clinckers R, Meeusen R, et al. Effect of bupropion on hippocampal neurotransmitters and on peripheral hormonal concentrations in the rat. J Appl Physiol 2003; 95 (2): 652-6 73. Borg G, Edstrom CG, Linderholm H, et al. Changes in physical performance induced by amphetamine and amobarbital. Psychopharmacologia 1972; 26 (1): 10-8 74. Meeusen R, Watson P, Dvorak J. The brain and fatigue: new opportunities for nutritional interventions? J Sports Sci 2006; 24: 773-82 75. Quan N, Xin L, Blatteis C. Microdialysis of norepinephrine into preoptic area of guinea pigs: characteristics of hypothermic effect. Am J Physiol 1991; 261: R378-85 76. Gisolfi C, Christman J. Thermal effects of injecting norepinephrine into hypothalamus of the rat during rest and exercise. J Appl Physiol 1980; 49: 937-41 77. Myers R, Beleslin D, Rezvani A. Hypothermia: role of alpha 1- and alpha 2-noradrenergic receptors in the hypothalamus of the cat. Pharmacol Biochem Behav 1987; 26: 373-9 78. Quan N, Xin L, Ungar A, et al. Preoptic norepinephrineinduced hypothermia is mediated by alpha 2-adrenoceptors. Am J Physiol 1992; 262: R407-11 79. Nagashima K. Central mechanisms for thermoregulation in a hot environment. Industrial Health 2006; 44: 359-67 80. Parkin JM, Carey MF, Zhao S, et al. Effect of ambient temperature on human skeletal muscle metabolism during fatiguing submaximal exercise. J Appl Physiol 1999; 86 (3): 902-8 81. Galloway SD, Maughan RJ. Effects of ambient temperature on the capacity to perform prolonged cycle exercise in man. Med Sci Sports Exerc 1997; 29 (9): 1240-9 82. Nielsen B, Savard G, Richter EA, et al. Muscle blood flow and metabolism during exercise and heat stress. J Appl Physiol 1990; 69: 1040-6 83. Nielsen B, Hales JR, Strange S, et al. Human circulatory and thermoregulatory adaptations with heat acclimation and exercise in a hot, dry environment. J Physiol 1993; 460: 467-85 84. Nielsen B, Strange S, Christensen NJ, et al. Acute and adaptive responses in human to exercise in a warm, humid environment. Pflu¨gers Arch 1997; 434: 49-56 85. Gonzalez-Alonso J, Calbet JA, Nielsen B. Metabolic and thermodynamic responses to hydration-induced reductions in muscle blood flow in exercising humans. J Physiol 1999; 520: 577-89 86. Bru¨ck K, Olschewski H. Body temperature related factors diminishing the drive to exercise. Can J Sports Sci 1987; 65: 1274-80 87. Cheung SS. Hyperthermia and voluntary exhaustion: integrating models and future challenges. Appl Physiol Nutr Metab 2007; 32: 808-17 88. MacDougall JD, Reddan WG, Layton CR, et al. Effects of metabolic hyperthermia on performance during heavy prolonged exercise. J Appl Physiol 1974; 36: 538-44
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formance in the heat. Am J Physiol Regul Integr Comp Physiol 2009 Feb; 296 (2): R394-401
Correspondence: Professor Dr Romain Meeusen, Department of Human Physiology and Sports Medicine, Pleinlaan 2, B-1050 Brussels, Belgium. E-mail:
[email protected]
Sports Med 2010; 40 (3)
Sports Med 2010; 40 (3): 247-263 0112-1642/10/0003-0247/$49.95/0
REVIEW ARTICLE
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Muscle Carnosine Metabolism and b-Alanine Supplementation in Relation to Exercise and Training Wim Derave, Inge Everaert, Sam Beeckman and Audrey Baguet Department of Movement and Sports Sciences, Ghent University, Ghent, Belgium
Contents Abstract. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1. Metabolic Pathways of Carnosine. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2. Proposed Role of Skeletal Muscle in Whole-Body Carnosine Metabolism . . . . . . . . . . . . . . . . . . . . . . . 3. Role of Carnosine in Myocellular Homeostasis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 pH Buffer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Anti-Oxidative Potential, Metal Chelation and Anti-Glycation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4. Determinants of Muscle Carnosine Content . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 Fibre Type. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 Age and Sex . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3 Training Status . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4 Nutrition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.5 b-Alanine Supplementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5. Ergogenic Effects of Elevated Muscle Carnosine Content. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1 Exercise Types that Benefit from b-Alanine Supplementation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2 Possible Mechanisms of Performance Improvement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3 b-Alanine as a Training Aid . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6. Practical Implications for Athletes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7. Conclusions and Future Directions for Research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Abstract
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Carnosine is a dipeptide with a high concentration in mammalian skeletal muscle. It is synthesized by carnosine synthase from the amino acids L-histidine and b-alanine, of which the latter is the rate-limiting precursor, and degraded by carnosinase. Recent studies have shown that the chronic oral ingestion of b-alanine can substantially elevate (up to 80%) the carnosine content of human skeletal muscle. Interestingly, muscle carnosine loading leads to improved performance in high-intensity exercise in both untrained and trained individuals. Although carnosine is not involved in the classic adenosine triphosphate-generating metabolic pathways, this suggests an important role of the dipeptide in the homeostasis of contracting muscle cells, especially during high rates of anaerobic energy delivery. Carnosine may attenuate acidosis by acting as a pH buffer, but improved contractile performance may also be obtained by improved excitation-contraction coupling and defence against reactive oxygen species. High carnosine concentrations
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are found in individuals with a high proportion of fast-twitch fibres, because these fibres are enriched with the dipeptide. Muscle carnosine content is lower in women, declines with age and is probably lower in vegetarians, whose diets are deprived of b-alanine. Sprint-trained athletes display markedly high muscular carnosine, but the acute effect of several weeks of training on muscle carnosine is limited. High carnosine levels in elite sprinters are therefore either an important genetically determined talent selection criterion or a result of slow adaptation to years of training. b-Alanine is rapidly developing as a popular ergogenic nutritional supplement for athletes worldwide, and the currently available scientific literature suggests that its use is evidence based. However, many aspects of the supplement, such as the potential side effects and the mechanism of action, require additional and thorough investigation by the sports science community.
Until recently, relatively little was known about the physiological role of carnosine in skeletal muscle, even though the molecule was discovered more than a century ago and it is one of the most abundant metabolites in muscle cells. The objective of this review is to provide a stateof-the-art overview of the science of carnosine’s role in muscle. The recent progress in this area originates from the discovery in 2006 by Roger Harris and co-workers[1,2] that oral b-alanine supplementation can increase the muscle carnosine content and thereby the performance during high-intensity exercise. This review aims to discuss the potential mechanisms, based on the known biochemical properties of the dipeptide, that may underlie the ergogenic effects of carnosine loading. Muscle carnosine concentration displays a high interindividual variation in humans and in this review we describe the possible determinants of this variability. The interaction between carnosine and training is discussed; both the effect of exercise training on the muscle carnosine content, as well as the value of b-alanine as a training aid, remain a matter of debate. We also present a number of practical implications for athletes who seek improved exercise performance by using b-alanine. In order to provide a comprehensive summary of the currently available knowledge on muscle carnosine and b-alanine supplementation with respect to exercise performance and training, a literature search was performed on PubMed and Web of Science using the search terms ‘carnosine’ ª 2010 Adis Data Information BV. All rights reserved.
or ‘b-alanine’ in combination with ‘muscle’, ‘exercise’ or ‘performance’. This literature overview is based on more than 100 published articles from 1950 to February 2010 on this topic. 1. Metabolic Pathways of Carnosine Carnosine (b-alynyl-L-histidine) is a dipeptide, combining the proteinogenic amino acid histidine with the non-proteinogenic b-amino acid b-alanine. Carnosine was first identified by the Russian biochemist Vladimir Gulevich in 1900 when he was looking for unidentified nitrogen-containing compounds in meat extract. Accordingly, he named the discovered molecule carnosine (‘carnis’ is Latin for meat/flesh). This name appeared to be accurately chosen, as carnosine is predominantly present in the skeletal muscle tissue of mammals and virtually absent from most other organs, except from its heterogeneous presence in brain regions. A concise review of carnosine’s discovery and identification was written by Alexander A. Boldyrev.[3] Carnosine is absent from plants (and therefore from vegetarian food) and invertebrates, whereas, in the animal kingdom, it appears in high but varying quantities in the muscles of different vertebrates.[4] In humans, the muscle concentration of carnosine is 5–8 mmol/L in wet weight (or 20–30 mmol/kg in dry weight), which is comparable to the concentrations of adenosine triphosphate (ATP), carnitine or taurine and lower than (phospho) creatine. Carnosine is the only Sports Med 2010; 40 (3)
Carnosine and b-Alanine in Exercise and Training
histidine-containing dipeptide (HCD) found in human muscle, whereas muscles of other animals/ mammals may also contain methylated analogues of carnosine, namely anserine (b-alanyl-N1methylhistidine) and balenine/ophidine (b-alanylN3-methylhistidine). When comparing the total HCD content in the muscles of different animals, humans are somewhere in the middle. Some endurance exercise-type animals like pigeons and migrating birds have lower concentrations (<5 mmol/L), while other animals that are involved in more burst-like and sprint exercise (chickens, greyhound dogs, thoroughbred horses) have markedly higher concentrations (20–50 mmol/L).[5] Some of the highest HCD concentrations, higher than the concentrations of ATP and phosphocreatine (PCr) combined, have been observed in whales, with an exercise profile characterized by extremely prolonged hypoxic dives and anaerobic energy delivery.[4] The specific evolutionary drive of high HCD content in the muscles of animals involved in anaerobic work may be of particular importance when trying to understand in what exercise conditions carnosine plays a pivotal role. The major pathways involved in carnosine metabolism are synthesis and hydrolysis, respectively from and to its constituent amino acids.[6] The enzymatic condensation of b-alanine and histidine is catalyzed by carnosine synthase (or synthetase). Recently, the responsible gene was identified by Drozak et al.[7] as the ATP-grasp domain containing protein-1 (ATP-GD1). High activities of carnosine synthase have been found in skeletal muscle tissue[4] and in specific regions of the brain, such as the olfactory bulb.[8] In humans and horses, b-alanine is considered to be the rate-limiting precursor of carnosine synthesis. b-Alanine can be obtained through the hydrolysis of dipeptides extracted from dietary meat or fish and through the degradation of uracil in the liver.[9] Bakardjiev and Bauer[10] have shown that the trans-sarcolemmal transport of one molecule of b-alanine requires two sodium ions and one chloride ion. The enzymatic hydrolysis of carnosine is catalyzed by carnosinase, of which two forms exist in the human body.[11] Serum carnosinase (CN1) is highly active in humans, resulting in the absence ª 2010 Adis Data Information BV. All rights reserved.
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of carnosine from human blood, in contrast to other mammals such as rodents who lack serum carnosinase and whose blood contains considerable amounts of carnosine.[12] Tissue carnosinase (CN2), also known as cytosolic nonspecific dipeptidase, is quantitatively less important for the degradation of carnosine in humans. 2. Proposed Role of Skeletal Muscle in Whole-Body Carnosine Metabolism The literature suggests that skeletal muscle is the major production and storage site for carnosine in the human body. With respect to its storage function, probably more than 99% of the body’s carnosine is present in the skeletal muscles, because of the size of the musculature (constituting 40–50% of total bodyweight) and the high muscle carnosine concentration (5–8 mmol/L) compared with its concentration in other carnosinecontaining tissues, such as the brain (0.1 mmol/L on average).[3] The support for the production function comes from several lines of evidence. First, the highest rates of carnosine synthase activity are found in skeletal muscle tissue, along with the olfactory bulb.[3,13] Second, there is reason to believe that very little of the synthesized carnosine in the muscle cells is subsequently hydrolyzed again, since carnosinase is virtually absent from muscle[13,14] and there is no nonenzymatic degradation process for carnosine. Instead, synthesized carnosine either remains present in the muscle cells for long periods, or it is secreted into the circulation through a regulated transport process. Evidence for the former was recently shown by Baguet et al.,[15] who showed that a highly increased concentration of carnosine in human calf muscles following b-alanine supplementation can remain present for >9 weeks following cessation of supplementation. Evidence for the regulated carnosine release from muscle into the circulation is fragmentary at present. Carnosine can be transported as an intact dipeptide across the plasma membrane through proton-coupled oligopeptide transporters (PEPT1, PEPT2, PHT).[16-18] Kamal et al.,[19] have recently shown that the genetic knockout of PEPT2 in mice results in a decreased tissue carnosine content in Sports Med 2010; 40 (3)
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the spleen, kidney and olfactory bulb. Interestingly, the muscle carnosine content was increased rather than decreased in PEPT2 knockout mice, suggesting that release of carnosine from muscle was inhibited by PEPT2 deficiency.[19] There is some evidence that carnosine metabolism (synthesis, degradation, release) increases upon muscle contractile activity and exercise. Nagai et al.,[20] observed elevated circulating carnosine levels and increased carnosine synthase activity in gastrocnemius muscle when rats were exercising on a running wheel. Also, in humans, carnosine concentration markedly increases in the skeletal muscle interstitium during leg extension exercise at 20 W, as determined by microdialysis.[21] Although some researchers believe that the contraction-induced release of carnosine by muscles is a measure of muscle damage and exertional rhabdomyolysis,[21-23] Nagai et al.[20] have proposed that carnosine release from muscle is a regulated process. The fact that proton accumulation (acidosis) can stimulate the protondriven PEPT2 provides one possible mechanism as to why muscles would release/secrete more carnosine during contractions than at rest. The observation that the histidine concentration increases in parallel with carnosine in human muscle interstitium[23] suggests that at least a portion of the contraction-induced release of carnosine from muscle is immediately hydrolyzed by the serum carnosinase present in the interstitium/ circulation in humans. In vitro animal experiments have suggested that the muscle carnosine concentration decreases following a period of contractions,[24] further supporting the hypothesis of contraction-induced carnosine release. Finally, it is suggested that exercise training increases the activity of serum carnosinase in rats[20] and humans,[25,26] although the latter studies are based on a limited number of subjects and were not well controlled. The physiological function and importance of exercise-induced carnosine release by skeletal muscle remains to be determined, but could be diverse. Hypothetically, released carnosine by muscle could have a paracrine or endocrine haemodynamic function, as carnosine is shown to have vasodilatory[27] and venoconstrictive potential.[28] ª 2010 Adis Data Information BV. All rights reserved.
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Carnosine has also been proposed to modulate the sympathetic nervous system, thereby affecting the autonomic control of the pancreas,[20] kidney,[29] adipose tissue[30] and of blood pressure.[29] Possibly, for some of these actions, carnosine can exert its effect by serving as a precursor of histamine through histidine.[31] The carnosinehistidine-histamine pathway may be involved in the therapeutic effects of carnosine.[32] However, it could also be that the rapid hydrolysis of circulating carnosine is a disadvantage, as certain tissues need intact carnosine for protective purposes. It is in this context that we should interpret the findings of Janssen et al.,[33] who observed that a short allelic form of the carnosinase gene CNDP1 is associated with a lower serum carnosinase activity and with a decreased risk of diabetic nephropathy. This suggests that the slower carnosine is hydrolyzed in the blood, the longer it can exert a protective effect in diabetes.[34] Carnosine is predominantly present in skeletal muscle. Its abundance probably serves two functions: (i) to contribute to homeostatic control in other organs through carnosine release; and (ii) to support local homeostasis in the muscle cells during contractions. The latter is discussed in the following section.
3. Role of Carnosine in Myocellular Homeostasis Since most metabolites (ATP, PCr, glycogen, glutamine, carnitine, etc.) that have a high abundance in skeletal muscle cells are directly involved in energy transport and delivery, initial searches for the role of carnosine in muscle were focused on its possible role as a phosphagen system. Goodall[35] proposed that monophosphocarnosine and diphosphocarnosine function as a phosphate donor for ATP resynthesis during contractions. However, neither the phosphorylated forms of carnosine[36] nor a ‘carnosine kinase’[37] have ever been detected in muscle tissue, and it is therefore unlikely that phosphocarnosine/ carnosine plays a similar role as the phosphocreatine/creatine kinase system in energy delivery and storage in skeletal muscle.[38] Instead, a Sports Med 2010; 40 (3)
Carnosine and b-Alanine in Exercise and Training
number of other biochemical properties of carnosine, mostly of the imidazole moiety of the histidine residue, have been described that can be of considerable value for contracting muscle cells. 3.1 pH Buffer
The total intramyocellular buffering capacity comprises the buffer actions of proteins, phosphates (inorganic phosphate, PCr), ammonia, bicarbonate and HCDs. Of all the amino acid side chains in proteins, only the imidazole ring of histidine (pKa 6.1) has a good pKa to function as a pH buffer in the physiological range. The pKa is the acid dissociation constant, which is ideal when it lies within the physiological pH range (6.5–7.1) of myocytes, so it can dynamically accept protons during contraction-induced acidosis. HCDs are thought to be a way to increase the concentration of histidine in muscle, as in proteins only one of 20 amino acids (on average) would be histidine, whereas in HCD this ratio is one of two. Moreover, when bound to b-alanine, the pKa of histidine increases slightly to 6.83, which is within the range of pH values that exist in contracting and fatigued myocytes. The role of carnosine as a physiologically relevant pH buffer was the first function of the dipeptide to be discovered.[39,40] Some fish species have no HCD in their muscles but instead display a very high concentration of free histidine (up to 100 mmol/L in pelamyd or ‘histidine fishes’[3]), which suggests that one reason why carnosine is so abundant in muscles is to increase the histidine and imidazole content. 3.2 Anti-Oxidative Potential, Metal Chelation and Anti-Glycation
Carnosine can contribute to the defence against oxidative stress of tissues by directly interacting with reactive oxygen species. At physiological concentrations in muscle, carnosine can interact with singlet oxygen and scavenge peroxyl radicals[41] and superoxide radicals.[42] Therefore, carnosine can reduce the products of lipid peroxidation (thiobarbituric acid reactive ª 2010 Adis Data Information BV. All rights reserved.
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substances [TBARS], malondialdehyde) and act as a natural hydrophilic antioxidant.[3,43,44] The mechanism for the antioxidative capacity may in part relate to the fact that carnosine can chelate ferrous ions and other transition metals.[41] Transition metals are known to promote the production of free radicals such as hydroxyl radical (OH ) formation through the Fenton reaction. Carnosine can also form complexes with other divalent cations like copper and zinc. The importance of this property in muscle homeostasis remains to be determined, whereas in the brain it has been shown that carnosine can protect against copper- and zinc-induced neurotoxicity.[45] Glycation or non-enzymatic glycosylation describes the reaction of sugar aldehydes with amino groups of proteins, which eventually leads to protein cross-linking and formation of advanced glycation end-products. The latter may be involved in the aetiology of aging and diabetic complications.[34] In vitro studies have shown that carnosine can inhibit glycation and protein cross-linking in a sacrificial process of aldehyde scavenging.[46] Carnosine has been implicated as a potential therapeutic adjuvant in a number of pathologies, such as cataract,[47] aging[48] and diabetic complications,[33] which may relate to carnosine’s biochemical properties of anti-glycation, antioxidation or metal chelation, or a combination of these. Several other chemical properties of carnosine have been described, among others as an activator of carbonic anhydrase[49] and an ACE inhibitor.[50] The physiological relevance of these effects is not intensively studied and lies beyond the scope of this review. More extensive reviews on the chemical properties and therapeutic benefit of carnosine have previously been published.[3,34,47,51,52]
4. Determinants of Muscle Carnosine Content The concentration of carnosine in human muscle follows a Gaussian distribution (figure 1) Sports Med 2010; 40 (3)
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and is characterized by a high variation coefficient in soleus (27.5%) and gastrocnemius (27.6%) muscle. The currently available methods for quantification include invasive procedures, where dipeptides in muscle biopsy homogenates or fibres are separated and quantified by highperformance liquid chromatography (HPLC),[54,55] and a non-invasive procedure based on proton magnetic resonance spectroscopy (proton MRS).[53,56,57] Both methods show similar effects of sex, b-alanine supplementation, etc. on muscle carnosine content. The currently identified determinants of muscle carnosine content are graphically summarized in figure 2, and are described in sections 4.1–4.5. 4.1 Fibre Type
In humans, fast-twitch muscle fibres have markedly higher carnosine content compared with slow-twitch fibres. The reported fast/slow concentration ratio, measured by HPLC-based single-fibre analysis, varies from 1.3 to 2.0.[2,58,59] As anaerobic energy delivery is quantitatively and qualitatively more important in glycolytic fibres, this pattern is in accordance with the supposed role of carnosine as a pH buffer. In most animal species the same fibre-type specificity of carnosine content in favour of fast-twitch fibres
is observed.[60,61] Human skeletal muscles with a known high proportion of fast-twitch muscle fibres, such as gastrocnemius, have a higher carnosine content than muscles with a typical slowtwitch profile, like the soleus (figure 3). The strong correlation in figure 3 indicates that subjects with high carnosine content in one muscle will also have high values in the other skeletal muscles. 4.2 Age and Sex
Mannion et al.[62] have compared the carnosine content of vastus lateralis muscles across both sexes and showed that men have approximately 20–25% higher muscle carnosine content than women, which is in line with their superior anaerobic performance capacity.[63] This could be caused partly by a higher proportion of fasttwitch fibres in male muscles,[64] although there is no consensus on this.[65] Sexual dimorphism with respect to muscle carnosine and HCD content is species dependent, as it appears more pronounced in rodents[66] but is absent in horses.[67] Rodent skeletal muscle carnosine content markedly declines with advancing age.[68,69] A similar pattern is expected in humans, although the current evidence is based mainly on cross-sectional comparisons of the elderly with a
b
a Mean 0.19 SD 0.052 n = 93
30
Frequency
Frequency
20
10
Mean 0.14 SD 0.039 n = 94
30
20
10
0
0 0
0.10
0.20 Carnosine
0.30
0.40
0
0.10
0.20 Carnosine
0.30
0.40
Fig. 1. Gaussian distribution of the carnosine content of the (a) gastrocnemius, and (b) soleus muscle, in an adult male population (age 19–49 years; n = 94). Data are compiled from subjects of previous studies from our laboratory. Carnosine concentration is measured by means of proton magnetic resonance spectroscopy, as previously described,[53] and expressed relative to the water signal.
ª 2010 Adis Data Information BV. All rights reserved.
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Type I Type II
Muscle fibre type composition
Aging
Sex
Vegetarian 0
10
20
β-alanine suppl. 30
Dietary β-alanine intake
40
50
Muscle carnosine content (mmol/kg dw) Fig. 2. Putative determinants of the human muscle carnosine content. dw = dry weight; suppl. = supplementation.
specific pathology, such as osteoarthritis,[70] neuromuscular disease[71] and glucose intolerance.[72] Advancing age is associated with a gradual transition towards a slower muscle type, which could relate to the lower carnosine levels in the elderly. However, a more slow-twitch fibre type profile in females and in the elderly can probably account for only a portion of the sex and age effects on muscle carnosine content. More likely, androgens have a stimulating effect on muscle carnosine synthesis. Indeed, experiments in mice show that males have a 3- to 4-fold higher carnosine content than females and in both sexes the carnosine content is reduced by ~40% following gonadectomy.[66] Interestingly, the female muscle carnosine content can be elevated up to the level of males by exogenous testosterone administration. Although the extragonadal sexual dimorphism in mice is more pronounced than in humans, there is indirect evidence supporting a role for androgens in carnosine synthesis. In a descriptive study on bodybuilders, where substance abuse with anabolic steroids is not unusual, very high muscle carnosine contents (approximately twice as high as in a control population) have been reported.[73] Also, the well-described decline in androgen concentration with advancing age may be a determinant of the lower carnosine content of muscle in elderly men. If indeed androgens play an important role in muscle carnosine content, then it could be expected that a substantial elevation takes place in the maturaª 2010 Adis Data Information BV. All rights reserved.
tion from boy to man. Data on humans are lacking, yet male but not female rodents show a doubling of muscle carnosine content during puberty.[66] 4.3 Training Status
Parkhouse et al.[74] have cross-sectionally compared the carnosine concentration of the vastus lateralis of sprinters and rowers with marathoners and untrained subjects. Sprinters (4.93 – 0.76 mmol/kg) and rowers (5.04 – 0.72) showed a markedly higher content than marathoners (2.80 – 0.74) and untrained participants (3.75 – 0.86) [p < 0.01]. Likewise, as shown in figure 4, trained 400 m runners display higher carnosine concentrations than physically active students. These differences probably relate to both selection/genetic factors (such as fibre-type distribution) and to training-induced alterations in muscle carnosine content. Training intervention studies show differing results, depending on the training mode, as shown in table I. Suzuki et al.[77] reported that the carnosine content of the vastus lateralis dramatically increased after 8 weeks of sprint training (one or two Wingate cycling sprints per session, two sessions per week) from 5.17 – 1.69 to 11.01 – 3.05 mmol/kg wet muscle. However, most other studies do not report an increase in muscle carnosine content following different types of training. According to Kendrick et al.,[75] 10 weeks (four sessions per week) of resistance training did Sports Med 2010; 40 (3)
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not change the carnosine content of the vastus lateralis. Also, in response to isokinetic knee extensor training,[59,76] no carnosine loading is observed. Although not intended as a training intervention study, Derave et al.[53] observed that the carnosine content in the gastrocnemius increased, with 16% (p < 0.05) in the placebo group, consisting of seven male trained 400 m runners during a 5-week period while in preparation for the indoor competition season. In summary, the limited amount of training intervention studies available to date is equivocal with respect to the effects of exercise training on muscle carnosine content, but the effect of short-term training is probably very small. The mechanism for the potential effects of chronic training on the carnosine content is yet to be elucidated. Hirakoba[78] proposes that the conditions of hypoxia and acidosis during high-intensity exercise can be responsible for increased carnosine concentration in skeletal muscle. This point of view is nevertheless inconsistent with the research of Edge et al.[79] Their high-intensity interval training (6–12, 2-minute intervals at 100% maximal oxygen uptake . (VO2max), with 1 minute of rest between sets)
Relative [carnosine] gastrocnemius
0.40 0.35 0.30 0.25 0.20 0.15 0.10 R2 = 0.68
0.05 0 0
0.05
0.10 0.15 0.20 0.25 0.30 Relative [carnosine] soleus
0.35
0.40
Fig. 3. Correlation between the carnosine content in the soleus and in the gastrocnemius in 93 male subjects as measured by proton magnetic resonance spectroscopy. Similar correlations were also found for tibialis anterior vs gastrocnemius and tibialis anterior vs soleus (data not shown). In almost all subjects, carnosine concentrations are higher in gastrocnemius than soleus. Data are the same as in figure 1.
ª 2010 Adis Data Information BV. All rights reserved.
performed during three sessions per week for 5 weeks, resulted in a decrease of buffering capacity despite large exercise-induced decreases in muscle pH (pH = 6.81). Moreover, the proposal of Hirakoba[78] cannot explain the differences in training effects, since both resistance training and isokinetic training can result in acidosis. 4.4 Nutrition
Carnosine can enter the circulation by intact absorption from the gut. The circulating carnosine concentrations are elevated for some time following the ingestion of HCD-containing meat,[25,80] but most of the dipeptide is hydrolyzed by serum carnosinase within minutes to hours. The synthesis of carnosine in skeletal muscle is limited by the availability of b-alanine rather than histidine.[1,81] Despite its designation as an essential amino acid, histidine occurs in sufficient concentrations in the circulation and will only limit carnosine synthesis in situations where a specific histidine-free diet is applied.[82] b-Alanine is not present in proteins, and its main endogenous source is from the irreversible degradation of the pyrimidines uracil and thymidine. Post-absorptive circulating b-alanine concentrations are therefore low. The trans-sarcolemmal transport of histidine and b-alanine provides the precursors for carnosine synthesis in skeletal muscle. The HCD content in the nutrition will have an impact on the availability of b-alanine and therefore possibly on the muscle carnosine content. A vegetarian diet is free of HCD and one abstract reported that vegetarians have low muscle carnosine content.[83] On the other hand, regular ingestion of chicken breast extract (CBEX), high in HCD content,[84] is thought to elevate muscle carnosine content.[85] Between these extremes (vegetarianism on the one hand and systematic large intakes of CBEX on the other), it remains to be determined to what degree variation in the amount and type of daily meat intake influences the variation in muscle carnosine content between individuals. It was recently demonstrated that 15 weeks of oral creatine supplementation can substantially Sports Med 2010; 40 (3)
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Muscle carnosine content (arbitrary units relative to water signal)
0.40 0.35 0.30 0.25 0.20 0.15 0.10 0.05 0 0 wk
5 wk
β-alanine
0 wk
5 wk
Placebo
Physically active students
0 wk
5 wk
β-alanine
0 wk
5 wk
Placebo
Trained 400 m runners
Fig. 4. Muscle carnosine content before (0 wk) and after 5 wk of oral supplementation (4.8 g/day) of b-alanine or placebo in physically active students or in trained 400 m runners. Data are extracted from previous studies from our laboratory.[15,53]
elevate muscle carnosine content in mice.[69] The mechanism for this phenomenon remains elusive at present. However, in humans, a carnosine loading effect of a short (1 week) period of oral creatine supplementation was not observed.[86] 4.5 b-Alanine Supplementation
b-Alanine supplementation is probably one of the most powerful means to elevate muscle carnosine content (figures 2 and 4). The development of b-alanine as a useful nutritional supplement has emerged from the elegant work of Roger Harris and co-workers, who demonstrated, first in horses[81] and later in humans,[1] that the ingestion of large daily amounts (~100 mg/kg bodyweight) of b-alanine is enough to elevate muscle carnosine content. Daily doses of b-alanine 4.8–6.4 g can elevate human muscle carnosine content by 60% in 4 weeks and 80% in 10 weeks.[1,2] Equimolar carnosine ingestion does not elevate muscle carnosine more than b-alanine alone. b-Alanine supplementation increases muscle carnosine content in both type I and type II fibres.[1] When comparing between individuals, high initial carnosine levels do not seem to impair the effectiveness of muscle carnosine loading.[53] Likewise, sprint-trained athletes who have high ª 2010 Adis Data Information BV. All rights reserved.
initial carnosine levels respond equally well to b-alanine supplementation (figure 4). Following cessation of b-alanine supplementation, carnosine washout occurs at a slow rate of 0.03 mmol/L/day. An increase of 55% in muscle carnosine content was calculated to require a washout period of 15 weeks.[15] Fasting circulating b-alanine concentrations are very low (<0.5 mmol/L). When ingested in pure form, peak concentrations of b-alanine appear in the blood within the first hour and rapidly decline within the second hour.[1] Doses >10 mg/kg of bodyweight are to be avoided, since circulating b-alanine concentrations >100 mmol/L give rise to paraesthesia symptoms, which probably relate to a sensitization of nociceptive neurons in the skin involved in neuropathic pain.[87] A daily dose of 4.8–6.4 g, therefore, requires six to eight servings, separated by at least 2 hours. However, new controlled-release formulations of b-alanine are currently being investigated, which display reduced peak concentrations and reduced paraesthesia.[88] Apart from paraesthesia, no other side effects of b-alanine have been described so far.[1] Unlike creatine supplementation, b-alanine does not induce bodyweight gain. Further research on the possible side effects and safety of b-alanine as a nutritional supplement is warranted. Sports Med 2010; 40 (3)
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5. Ergogenic Effects of Elevated Muscle Carnosine Content 5.1 Exercise Types that Benefit from b-Alanine Supplementation
Based on the observations that animals and humans who are performing well in sprint-type exercise have higher muscle carnosine content than those who excel in endurance exercise, it can be expected that high muscle carnosine content is ergogenic in anaerobic exercise, as first proposed by Parkhouse and McKenzie.[89] In 2002, Suzuki et al.[90] indicated that in a group of healthy men, high muscle carnosine content correlated positively with the mean power per body mass (r = 0.785; p < 0.01) during a 30-second all-out cycling sprint, and especially in the latter phase of the exercise bout. Several recent investigations have explored the potential ergogenic effect of chronic b-alanine supplementation on different types of exercise performance (summarized in table II). b-Alanine doses vary from 2 to 6.4 g/day and durations from 3 to 13 weeks. In one of the first studies, Hill et al.[2] supplemented men for 10 weeks with b-alanine 6.4 g/day. The total work done during a cycle capacity test at 110% of their maximal power (duration ~2.5 minutes) increased following 4 and 10 weeks of b-alanine supplementation (+13% and +16.2%, respectively). During an incremental cycling exercise test (starting at 40 W and increasing by 20 W every 3 minutes until exhaustion) in un-
trained women, Stout et al.[92] found that the ventilatory threshold (+13.9%) and the time to exhaustion (+2.5%) significantly increased after 28 days of b-alanine supplementation (6.4 g/day), . although the VO2max did not change. Also, the physical working capacity at the fatigue threshold, determined by EMG of the vastus lateralis during cycling, increased significantly with balanine supplementation in young[92] and aged[93] populations. These studies were all performed in untrained subjects. In trained 400 m runners, 4–5 weeks of b-alanine supplementation (4.8 g/day) did not improve 400 m running performance more than in a placebo group despite a marked increase in muscle carnosine content.[53] However, during repeated isokinetic knee extensions (5 · 30 contractions with 1-minute rest intervals) b-alanine reduced fatigue in the latter two bouts in this trained population. Whether b-alanine is ergogenic in aerobic endurance exercise remains to be established. However, b-alanine supplementation was shown to improve the 30-second sprint capacity by 11% at the end of a 2-hour simulated cycling race in moderately to well trained cyclists.[94] The effect of b-alanine supplementation on isometric knee extensor performance is equivocal. Ponte et al.[91] observed a 10–15% (8 seconds) improvement in isometric endurance at 45–50% of maximal voluntary contraction (MVC) of the knee extensors, whereas Derave et al.[53] could not identify an effect of oral b-alanine supplementation
Table I. Effect of a training intervention on the carnosine content in the vastus lateralis muscle Study (year)
Training type
Training duration (wk)
Subjects
Muscle carnosine content
Kendrick et al.[75] (2008)
Resistance training (4 days/wk)
10
13 male physical education students
Pre: 29.2 – 9.82 mmol/kg dm Post: 27.3 – 9.52 mmol/kg dm
Kendrick et al.[59] (2009)
One-legged isokinetic training (4 days/wk)
7 physical education students
Pre: 22.6 – 2.1 mmol/kg dm Post: 24.7 – 3.7 mmol/kg dm
Mannion et al.[76] (1994)
Isokinetic knee extensor training (3 days/wk)
8 physically active at two different velocities (4.19 and 1.05 rad/s) 7 physically active (1.05 rad/s)
Pre: 20.2 – 7.0 mmol/kg dm Post: 19.4 – 6.5 mmol/kg dm Pre: 18.9 – 3.0 mmol/kg dm Post: 20.9 – 3.3 mmol/kg dm
Suzuki et al.[77] (2004)
Wingate sprint training (2 days/wk)
6 untrained males
Pre: 5.17 – 1.69 mmol/L wm Post: 11.01 – 3.05* mmol/L wm
4 16
8
dm = dry muscle; rad/s = radians per second; wm = wet muscle; * p < 0.05.
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Table II. Ergogenic effects of b-alanine supplementation Study (year)
Exercise
Supplementation
Performance improved?
Subjects
Suzuki et al.[85] (2006)
10 · 5 sec maximal cycle ergometer sprints, with a recovery of 25 sec
CBEX (1.5 g carnosine and anserine) Acute: 30 min before exercise
Total/mean power: no
Untrained males
Ponte et al.[91] (2006)
Isometric knee extension at 45–50% MVC until exhaustion
6.4 g/day b-alanine, 4 wk
Isometric: yes
Untrained males
Derave et al.[53] (2007)
5 bouts of 30 maximal isokinetic knee extensions Isometric knee extension at 45% MVC until exhaustion 400 m race
4.8 g/day b-alanine, 4 wk
Isokinetic: yes Isometric: no 400 m race: no
Trained male 400 m runners
Hill et al.[2] (2007)
Cycle capacity test at 110% maximum power output
6.4 g/day b-alanine, 4–10 weeks
Total work done: yes
Untrained males
Stout et al.[92] (2007)
Continuous incremental cycle ergometry test to exhaustion Physical working capacity at fatigue threshold
6.4 g/day b-alanine, 4 wk
Time to exhaustion: yes Physical working capacity: yes
Untrained females
Stout et al.[93] (2008)
Physical working capacity at fatigue threshold
2.4 g/day b-alanine, 90 days
Physical working capacity: yes
Aged male and female (73 – 11 y)
Van Thienen et al.[94] (2009)
30 sec all-out cycling at the end of simulated cycling race
2–4 g/day b-alanine, 8 wk
Peak and mean power output: yes
Moderate to welltrained male cyclists
CBEX = chicken breast extract; MVC = maximal voluntary contraction.
on isometric endurance of the knee extensors at 45% MVC. A single acute pre-exercise administration of a CBEX soup (containing 1.5 g of carnosine and anserine) did not improve performance during intermittent exercise that consisted of 10 · 5second maximal cycle ergometer sprints with a 25-second recovery period between each sprint.[85] This finding supports the notion that the ergogenic effects of b-alanine supplementation result from an increase in muscle carnosine content, which cannot be achieved by a single dose, but only following several weeks of supplementation. It can be concluded that chronic b-alanine supplementation can have ergogenic effects during single or repeated bouts of high-intensity exercise or maximal contractions. Although the scientific evidence in untrained populations is substantial, more studies need to be conducted in trained populations and in various sport disciplines in order to fully understand the value of b-alanine supplementation for performance enhancement in elite sports. ª 2010 Adis Data Information BV. All rights reserved.
5.2 Possible Mechanisms of Performance Improvement
The observed improvement in anaerobic exercise performance following b-alanine supplementation is most likely related to the increased muscle carnosine content, inducing an attenuation of peripheral (rather than central) fatigue. This is supported by studies with isolated muscle preparations of frogs and rodents, which showed reduced contractile fatigue when muscles were exposed to increased extracellular carnosine (a process termed ‘Severin’s phenomenon’[3,95,96]) or increased muscle carnosine content.[69] Increased availability of carnosine in myocytes can improve contractile behaviour and reduce fatigue in several possible ways. Carnosine is indisputably a functional pH buffer. This is supported in a recent study by Baguet et al.[97] on the effect of 4- to 5-week b-alanine supplementation on exercise-induced acidosis in physically active students. The decline in circulating pH was significantly attenuated during a 6-minute cycling Sports Med 2010; 40 (3)
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exercise bout at an intensity of 50% of the. difference between ventilatory threshold and VO2peak. The role of acidosis in muscular fatigue remains a matter of debate.[98] However, since both acute oral bicarbonate ingestion[99] and chronic b-alanine supplementation have been shown to improve performance in exercise modes of similar duration and intensity, it is probably correct to conclude that at least part of the ergogenic effect of b-alanine supplementation is related to improved physicochemical buffer capacity. However, the quantitative contribution of carnosine to total buffer capacity is limited, so it is likely that additional underlying mechanisms are at play. The initial estimates of carnosine’s contribution to total muscle buffer capacity were as high as 60%.[39] However, later studies[62,100] estimated the contribution of carnosine to the total buffering capacity to be only 7%. A second mechanism that is involved in muscle fatigue is the reduction in Ca2+ release from the sarcoplasmic reticulum (SR).[101] Russian studies[102,103] have proposed that the Severin’s phenomenon is explained by the modulation of SR Ca2+ release channel activity by carnosine. Specifically, carnosine could increase the sensitivity of Ca2+ release channels to their well-known activators (caffeine, adenosine monophosphate and Ca2+) and decrease the inhibitory effect of low concentrations of Mg+.[104] However, Dutka and Lamb[105] could not support these findings. They demonstrated that the positive effect of carnosine on the contractile fatigue is due to increased Ca2+ sensitivity of the contractile machinery and not to facilitated Ca2+ release. This effect was observed in the chemically skinned fibre preparations of frogs[106] as well as in mechanically skinned rat muscle fibres.[105] Thus, the increase of the Ca2+ sensitivity of the contractile apparatus by carnosine could aid in maintaining a higher level of force during the later stages of fatigue when Ca2+ release declines.[105] Mishima et al.,[107] examined whether this carnosineinduced increase in Ca2+ sensitivity has any ergogenic effect on high-intensity exercise in rats. Despite an attenuation of the exercise-induced reduction in SR Ca2+ handling following 5 weeks of dietary CBEX, the performance remained unchanged during high-intensity running for ª 2010 Adis Data Information BV. All rights reserved.
2.5 minutes. It has to be noted that the evidence for the carnosine-stimulated increase in Ca2+ sensitivity is based only on in vitro and rodent experiments, and that the physiological in vivo evidence in human myofibres remains to be determined. A third possible mechanism of performance improvement evoked by carnosine could be related to its antioxidative potential. Skeletal muscle fibres continually generate reactive oxygen species at a slow rate that increases during muscle contraction, which contributes to fatigue of skeletal muscle during intense and prolonged exercise.[108] Due to its antioxidative potential, an increased carnosine content could, theoretically, diminish this reactive oxygen species accumulation. Indeed, the acute oral ingestion of carnosine (450 mg) can, after 1 hour but not after 2 hours, elevate the serum total antioxidant capacity in humans with 11.6%.[109] Another mechanism by which carnosine could diminish this reactive oxygen species-induced fatigue could be related to its potential to increase the Ca2+ sensitivity, since reactive oxygen species can reduce the myofibrillar Ca2+ sensitivity in fatiguing mouse skeletal muscle.[110] However, it is clear that further research is recommended to verify the effects of prolonged ingestion of b-alanine on oxidative stress evoked by muscle contractions in humans. 5.3 b-Alanine as a Training Aid
Nutritional supplementation for athletes is not only useful in competition, but it can also be functional to optimize the training effects, e.g. by improving recovery, maintaining higher energy levels or by optimizing the training adaptations.[111] There is disagreement in the literature whether the training-induced adaptations could be stimulated by b-alanine supplementation. Several studies have investigated the effects of combined b-alanine supplementation and training on muscle and exercise performance, with conflicting results. According to Smith et al.,[112] the effects of 6 weeks of high-intensity interval training on EMG-based neuromuscular fatigue in recreationally active men were not different between a control and a b-alanine (3–6 g/day) Sports Med 2010; 40 (3)
Carnosine and b-Alanine in Exercise and Training
supplemented group. In physical education students, the supplementation of b-alanine 6.4 g/day (10 weeks) did not have any additive effect compared with training alone on whole body strength, isokinetic force production, muscular endurance and body composition after 10 weeks of resistance training.[75] On the other hand, Hoffman and colleagues[113] reported that collegiate football players, who are used to strength and power training, improved strength and body composition after 10 weeks of resistance training in a group consuming both b-alanine and creatine compared with the placebo and/or creatine group. Hofmann and colleagues[114] subsequently showed that the training volume of collegiate football players, during their preparation for the season, can be improved by the supplementation of b-alanine (30 days, 4.5 g/day). The experimental group reached a significantly higher training volume in the bench press exercise, a trend to significantly higher training volumes for all resistance exercise sessions and a better subjective feeling. In addition to the differences in initial training levels of the subjects, the higher volume and the possible synergistic effect of balanine with creatine in the study of Hoffman et al.[113] could explain the inconsistency between these two comparable studies.[75] However, it seems that the performance enhancement of combined b-alanine supplementation and training is smaller than the potential of creatine to stimulate training-induced muscle hypertrophy. Nevertheless, it should be mentioned that training can stimulate the responsiveness to creatine supplementation,[115,116] which is not the case with carnosine loading.[59] 6. Practical Implications for Athletes There is a relatively high interindividual variation in skeletal muscle carnosine content between humans, and carnosine is able to improve high-intensity exercise. Therefore, low muscle carnosine content in athletes may be disadvantageous for sprint performance. The carnosine content is determined by several factors, as depicted in figure 3. Oral b-alanine supplementation is probably the most efficient way to increase ª 2010 Adis Data Information BV. All rights reserved.
259
the skeletal muscle carnosine content. Still, it must be noted that the effects of b-alanine supplementation on the performance are small and probably only relevant to athletes who have already optimized the other training modalities and who are seeking a minor improvement in performance. The carnosine loading in muscle differs in several ways from the supplementation of creatine, which is widely used. First, the loading of carnosine takes at least several weeks, in contrast to the initial loading phase of 1 week for creatine. Conversely, the washout rate is also faster for creatine than for carnosine, indicating that the elevated muscle carnosine content is more stable.[15] A second difference with creatine supplementation is that individuals with a high initial muscle carnosine content, such as sprint-trained athletes, respond equally well to b-alanine supplementation as persons with a low initial content. In line with this apparent absence of a ceiling effect for carnosine, the highest reported supplementationinduced muscle loading is markedly higher for carnosine[2] than for creatine.[117] Finally, the supplementation of b-alanine, in contrast to creatine, does not result in increased body mass, which has important implications for athletes in weightbearing exercise types or weight class sports. Although both b-alanine and bicarbonate have been suggested to attenuate exerciseinduced acidosis, there are marked differences between both ergogenic supplements.[99,118] First, sodium bicarbonate or citrate should be taken as a single pre-exercise dose, inducing acute metabolic alkalosis,[119] whereas b-alanine requires chronic supplementation for weeks, but does not affect the blood pH at rest. Second, b-Alanine is thought to work as a first-line defence, as carnosine is elevated in the muscle cells where the protons are produced during contractions, whereas bicarbonate resides in the circulation and only buffers once protons have entered the blood (second-line buffer). Additionally, bicarbonate elicits a degree of gastrointestinal discomfort in many athletes, which does not occur with b-alanine. Currently, no health-related side effects from chronic oral supplementation of b-alanine have Sports Med 2010; 40 (3)
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been reported, except from the acute paraesthesia that occurs when the prescribed maximum dose of 1 g per 2-hour period is exceeded (see section 4.5). Standard supplementation advice is to supplement 4–6.4 g/day (divided over 0.8–1 g servings) for at least 4 weeks. However, the effects on health of continuous b-alanine supplementation beyond 10 weeks, as well as its combination with other supplements, remain to be established. 7. Conclusions and Future Directions for Research In summary, it seems that the high interindividual variation in muscle carnosine content between humans is related to several determinants such as muscle fibre type, age, sex, nutrition and possibly training status. The underlying physiological mechanisms for this variation need to be elucidated. Another important question to be clarified is whether the high muscle carnosine levels of sprint-trained athletes are the result of the chronic effect of years of training or of selection effects and genetic factors. There are a number of indications that elevated muscle carnosine content can delay fatigue during highintensity exercise. Even though there is a shortage of available literature concerning the underlying mechanisms, especially in humans, it seems reasonable to assume that the performance improvement from b-alanine supplementation is the result of the potential for carnosine to act as a pH buffer, as a stimulator of the Ca2+ sensitivity and/or as an antioxidant. Beside the ergogenic effects, carnosine probably contributes to homeostatic control in organs other than the muscle and to the susceptibility to certain diseases, but this research area is virtually unexplored at present. Acknowledgements This review and the mentioned studies from our laboratory are financially supported by grants from the Research Foundation – Flanders (FWO 1.5.149.08 and G0.0046.09). Audrey Baguet is a recipient of a PhD scholarship from the Research Foundation – Flanders. The authors have no conflicts of interest that are directly relevant to the content of this review.
ª 2010 Adis Data Information BV. All rights reserved.
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104. Batrukova MA, Rubtsov AM. Histidine-containing dipeptides as endogenous regulators of the activity of sarcoplasmic reticulum Ca-release channels. Biochim Biophys Acta 1997; 1324 (1): 142-50 105. Dutka TL, Lamb GD. Effect of carnosine on excitationcontraction coupling in mechanically-skinned rat skeletal muscle. J Muscle Res Cell Motil 2004; 25 (3): 203-13 106. Lamont C, Miller DJ. Calcium sensitizing action of carnosine and other endogenous imidazoles in chemically skinned striated muscle. J Physiol 1992; 454: 421-34 107. Mishima T, Yamada T, Sakamoto M, et al. Chicken breast attenuates high-intensity-exercise-induced decrease in rat sarcoplasmic reticulum Ca2+ handling. Int J Sport Nutr Exerc Metab 2008; 18 (4): 399-411 108. Reid MB. Free radicals and muscle fatigue: of ROS, canaries, and the IOC. Free Radic Biol Med 2008; 44 (2): 169-79 109. Antonini FM, Petruzzi E, Pinzani P, et al. The meat in the diet of aged subjects and the antioxidant effects of carnosine. Arch Gerontol Geriatr Suppl 2002; 8: 7-14 110. Moopanar TR, Allen DG. Reactive oxygen species reduce myofibrillar Ca2+ sensitivity in fatiguing mouse skeletal muscle at 37 degrees C. J Physiol 2005; 564 (Pt 1): 189-99 111. Tipton KD, Jeukendrup AE, Hespel P. Nutrition for the sprinter. J Sports Sci 2007; 25 Suppl. 1: 5-15 112. Smith AE, Walter AA, Graef JL, et al. Effects of beta-alanine supplementation and high-intensity interval training on endurance performance and body composition in men: a double-blind trial. J Int Soc Sports Nutr 2009; 6: 5 113. Hoffman J, Ratamess N, Kang J, et al. Effect of creatine and beta-alanine supplementation on performance and endocrine responses in strength/power athletes. Int J Sport Nutr Exerc Metab 2006; 16 (4): 430-46 114. Hoffman JR, Ratamess NA, Faigenbaum AD, et al. Shortduration beta-alanine supplementation increases training volume and reduces subjective feelings of fatigue in college football players. Nutr Res 2008; 28 (1): 31-5 115. Harris RC, So¨derlund K, Hultman E. Elevation of creatine in resting and exercised muscle of normal subjects by creatine supplementation. Clin Sci 1992; 83: 367-74 116. Robinson TM, Sewell DA, Hultman E, et al. Role of submaximal exercise in promoting creatine and glycogen accumulation in human skeletal muscle. J Appl Physiol 1999; 87 (2): 598-604 117. Derave W, Eijnde BO, Hespel P. Creatine supplementation in health and disease: what is the evidence for long-term efficacy? Mol Cell Biochem 2003; 244 (1-2): 49-55 118. Clarkson PM. Nutrition for improved sports performance: current issues on ergogenic aids. Sports Med 1996; 21 (6): 393-401 119. Bishop D, Edge J, Davis C, et al. Induced metabolic alkalosis affects muscle metabolism and repeated-sprint ability. Med Sci Sports Exerc 2004; 36 (5): 807-13
Correspondence: Dr Wim Derave, Department of Movement and Sports Sciences, Ghent University, Watersportlaan 2, B-9000 Ghent, Belgium. E-mail:
[email protected]
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Is it Time to Retire the ‘Central Governor’? A Philosophical and Evolutionary Perspective Any commentary on an author’s work is valuable as it prompts introspection and re-evaluation of the ideas posited by the work being critiqued. For this reason I am grateful to Prof. Shephard for the critical review of some of my writings that have contributed to the development of the Central Governor Model (CGM) of exercise physiology.[1] Prof. Shephard has provided some enticing and thoughtful points and therefore his critique invites comment. However, it would take several pages to rebut each of the points made by Prof. Shephard, so I will limit my arguments to a few philosophical points and the correction of factual errors and leave the interested reader and the fullness of time to evaluate the veracity for the arguments provided by Prof. Shephard’s critique of the CGM. I begin with the title of the article: Is it time to retire the ‘Central Governor’? This title begs the obvious counter question: what and who would benefit from the retirement of a new and revolutionary paradigm? Before addressing this question directly, it is worth being reminded about the true nature of scientific enquiry as written by renown paleoanthropologists Johanson and Streeve in responding to their opponents upon their discovery of the fossil, ‘Lucy’s child’:[2] ‘‘Frustrating as it is, the distantly tantalizing truths about our origins will probably not be revealed before we ourselves are buried under the earth. But that will not stop me from testing and retesting new hypotheses, exploring further possibilities. The point is not to be right. The point is to make progress. And you cannot make progress if you are afraid to be wrong.’’ Returning to the question of who and what would be the benefit of retiring the CGM, possible answers could be either that this allows us to continue with the previously held beliefs and assumptions and
therefore perpetuating the evidence that supports these assumptions or that proponents of the widely held classical view do not wish to embrace a new paradigm that might explain that which the classical view cannot. Either way there can be no significant progress towards the truth. In what is regarded as one of the hundred most influential books since WWII, Kuhn[3] has outlined why new revolutionary paradigms are seldom accepted immediately by the specialists in the field: ‘‘For these men the new theory implies a change in the rules governing the prior practice of normal science. Inevitably, therefore, it reflects upon much scientific work they have already successfully completed. That is why a new theory, however special its range of application, is seldom or never just an increment to what is already known. Its assimilation requires the reconstruction of prior theory and the re-evaluation of prior fact, an intrinsically revolutionary process that is seldom completed by a single man and never overnight.’’ It is thus not unusual that Prof. Shephard and those of his ilk might resist acknowledging a new paradigm that is better able to explain those observations that the classic teaching cannot. It is not entirely clear why opponents of the CGM do not take issue with the originators of the concepts leading to the CGM[4,5] in their attempt to explain the limitation of the cardiovascular model of exercise physiology. Rather, opponents of the CGM take issue with those who have provided further insights for its development.[6,7] At this point it is worth reiterating that the underpinning tenant of the CGM is the brain’s ability to recruit and de-recruit skeletal muscle to regulate exercise and avoid catastrophic failure of any organ system,[7] whereas the cardiovascular model holds that the heart and oxygen delivery are the factors limiting exercise.[8] It is notable that proponents of the cardiovascular model avoid the findings that clearly demonstrate the importance of the amount of skeletal muscle recruitment in the determination of peak oxygen uptake when improvements in central haemodynamics are not parallelled by increases in systemic exercise performance even in congestive heart failure.[9,10]
266
Prof. Shephard individually critiques what he calls ‘‘five correlates of the CGM,’’ one of which is the ‘‘potential for the evolution of a Central Governor.’’[1] A substantial discussion for the origins of an anticipatory mechanism in the evolution of hominids has been provided elsewhere, so the discerning reader will be able to evaluate the arguments presented on the matter to their satisfaction.[11] However, whether or not there has been an evolutionary process in the development of a centrally mediated mechanism for teleoanticipation is not a common area of research in the exercise sciences and the understanding of such an evolutionary process needs further elaboration. This section, like all other sections of Prof. Shephard’s critique, is littered with errors of fact and must be corrected as a matter of record. Prof. Shephard asserts that ‘‘Mosso noted that 3 years of learning was needed to perfect migration patterns in quails; he argued that the birds were then able to regulate the energy expenditures over prolonged flights in such a manner as to conserve a final store of metabolites against easy capture.’’[1] This interpretation is not only a distortion of Mosso’s findings, but it is also an error of fact as Mosso did not make this suggestion at all and he did not train quails. This is an important distinction as Mosso originally observed that energy expenditure may not have been crucial in the long-distance flight of quails from Africa to Rome but some other mechanism could explain the ability of the long-distance flight. In making this observation Mosso then attempted to elicit the same long-distance flying ability in carrier pigeons and it was then that he noted that this ability could only be attained after 3 years of specific training and education. In other words, a naturally occurring phenomenon (in quails) could be trained and indeed improved upon as training continued. Therefore, the issue is whether or not training provides the stimulus for the organism to better understand the task and plan a strategy to complete the task without catastrophic failure. I have previously provided a treatise on the development of anticipatory regulation through evolutionary forces and argued that this might be specific to the organisms’ conditions.[11] As ª 2010 Adis Data Information BV. All rights reserved.
Letter to the Editor
further examples, two extremes were used to illustrate the difference between endurance and sprint capacity in the African hunting dog and the cheetah, respectively.[12] I suggested that evolutionary pressures led to the development of a central regulatory mechanism. However, in a sleight-of-hand Prof. Shephard suggests that the evolutionary scenario could be argued in several different ways as given by Hopkins,[13] whereby predators might risk a loss of homeostasis in order to avoid death from starvation or predators risking a loss of homeostasis to avoid capture. In this scenario the most widely accepted scientific theory, that of natural selection, has been ruled out simply by suggesting that the Central Governor could work in two opposing directions. But natural selection does not provide for either/or in survival; that is, individuals within a species that were caught or could not catch prey were either respectively killed or starved and did not produce offspring. The very basis of natural selection predicts that any trait favouring a species will carry on in their offspring; in this case those individuals with the most advanced teleoanticipatory system or Central Governor will have survived. To defend the view that the Central Governor could not have evolved, Prof. Shephard defers to an obscure one-sided editorial by Hopkins who suggests ‘‘y that the governor makes little sense from an evolutionary perspective. Only an unintelligent designer would endow animals with capacities they cannot use.’’[13] There are two fallacies with this argument. First, how can one argue for unintelligent design in relation to evolution? These are mutually exclusive views of reality; evolution being a scientific paradigm open to refutation and intelligent design (or as Hopkins prefers, unintelligent design) being a creationist perspective that does not fulfil the criteria of a scientific paradigm. Second, to suggest that evolution, and by extension nature, does not endow organisms with capacities they cannot use is false. This view of natural selection is known as hyper-selectionism and denies the obvious that many species have vestigial features.[14] For example, in mammals the recurrent laryngeal nerve does not extend directly from the brain to Sports Med 2010; 40 (3)
Letter to the Editor
the larynx, but upon reaching the neck bypasses the larynx and drops into the chest where it loops and only then retraces up to the larynx in the neck;[15,16] those of us who have had wisdom teeth extracted can attest to the futility of these structures. Although Prof. Shephard should be applauded for a valiant attempt at dissecting the CGM and in particular the evolutionary basis for a teleo-anticipatory mechanism, such critiques should be carried out with the inclusion of the accepted scientific theories rather than attempting to distort the facts by excluding such theories; this line of reasoning is usually labelled as ‘spin’. Finally, in an attempt to refute the hypothesis that the Central Governor evolved during persistent hunting under heat stress, Prof. Shephard cites the conclusions drawn by the International Biological Program (IBP)[17] on the ability of various isolated populations to undertake fatiguing work of various durations. The IBP apparently found little evidence that humans have developed unusual physiological characteristics in response to prolonged residence in extreme environments as ‘‘y field studies of traditional Neolithic populations suggest that their success in hunting trips, and thus any selective pressures, depends much more on intellect than brute force, running ability or tolerance of physical fatigue.’’[1] The logic here does not follow as the assumption is that intellect preceded human bipedal locomotion. In this instance Prof. Shephard ignores completely the current wisdom, which holds that the ‘‘y big brain arose from the big baby, and the big baby arose first from challenges in walking, and then enlarged hips in females. The proposal thoroughly contradicts the alternative assumption, that selection pressures for intelligence drove the evolution of big brains. Tool use didn’t prompt brain expansion. Rather walking expanded brain size, and the bigger brain was able to conceive of tool construction and use.’’[18-20] Therefore, any observation in contemporary ‘primitive’ peoples assumes that the large brain and, therefore, the intellect spontaneously occurred. In addition to this broken logic, a case is made for the unlikely genetic transmission of hunting skills into the 21st century simply because the planet is now a genetic melting ª 2010 Adis Data Information BV. All rights reserved.
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pot. Assuming that a mechanism for anticipatory regulation evolved over millions of years, Prof. Shephard would now wish us to accept that this characteristic along with many other genetic traits would disappear within only a few generations. It is also notable that the relationship between phenotype and genotype is used as evidence against the selection pressures for the evolution of a thermally protective ‘Central Governor’ as exercise tolerance and thermoregulation seem to be phenotypic.[21] However, Prof. Shephard is guilty of removing the contextual basis for this statement as given by the authors who state that ‘‘y for future studies to make an impact in identifying genotypic differences, the phenotypical changes arising from diversity in environmental conditions will need to be controlled before there is any intervention (exposure to hot or cold conditions).’’[21] Therefore, it is not the case that there is no genotype for thermotolerance but rather these data are difficult to acquire due to the lack of control arising from the diverse environmental conditions. In summary, it is clear that many exercise scientists do not regard the CGM as an alternative hypothesis to the more traditional view or that it can predict the way in which human performance is regulated under all conditions. Therefore, the challenge issued by Prof. Shephard should not be taken lightly. However, to continue to assert that ‘‘Over the past 13 years a small group of investigators has argued repeatedly for the existence of a Central Governor y’’[1] reduces this debate to nothing more than an us-or-them approach to science. Rather, the fact that the CGM provides an uncomplicated solution to the understanding of the regulation of exercise and that it puts the brain back in focus is to be celebrated rather than maligned. When T.H. Huxley first read Darwin’s The Origin of Species[22] it is said that his reaction was ‘‘How extremely stupid not to have thought of that.’’ Perhaps it is this sentiment that the opponents of the CGM lament? Frank E. Marino Prof. and Chair of Exercise Physiology, Head of School of Human Movement Studies, Charles Sturt University, Bathurst, New South Wales, Australia
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Letter to the Editor
References 1. Shephard RJ. Is it time to retire the ‘Central Governor?’ Sports Med 2009; 39: 709-21 2. Johanson D, Streeve J. Lucy’s child: the discovery of a human ancestor. London: Viking, 1989 3. Kuhn TS. The structure of scientific revolutions. 3rd ed. Chicago (IL): The University of Chicago Press, 1996 4. Hill AV, Long CHN, Lupton H. Muscular exercise, lactic acid and the supply and utilisation of oxygen: parts VIIVIII. Proceed Roy Soc Britain 1924; 97: 155-76 5. Ulmer HV. Concept of extracellular regulation of muscular metabolic rate during heavy exercise in humans by psychophysiological feedback. Experentia 1996; 52: 416-20 6. Noakes TD, Marino FE. Point/counterpoint: maximal oxygen uptake is limited by a central nervous system governor. J Appl Physiol 2008; 106: 338-48 7. Noakes TD, St Clair Gibson A, Lambert VA. From catastrophe to complexity: a novel model of integrative central neural regulation of effort and fatigue during exercise in humans. Br J Sports Med 2004; 38: 511-4 8. Brink-Elfegoun T, Kaijser L, Gustafsson T, et al. Maximal oxygen uptake is not limited by a central nervous system governor. J Appl Physiol 2007; 102: 781-6 9. Jondeau G, Katz SD, Zohman L, et al. Active skeletal mass and cardiopulmonary reserve. Circulation 1992; 86: 1351-6 10. Minotti JR, Christoph I, Oka R, et al. Impaired skeletal muscle function in patients with congestive heart failure. J Clin Investig 1991; 88: 2077-82 11. Marino FE. The evolutionary basis of thermoregulation and exercise performance. In: Marino FE, editor. Thermoregulation and human performance: physiological and biological aspects. Basel: Karger, 2008: 1-13 12. Marino FE. Comparative thermoregulation and the quest for athletic supremacy. In: Marino FE, editor. Thermoregulation and human performance: physiological and biological aspects. Basel: Karger, 2008: 14-25 13. Hopkins WG. The improbable Central Governor of maximal endurance performance. Sportsci 2009; 13: 9-12 14. Gould SJ. The Panda’s thumb: more reflections in natural history. New York: WW Norton & Company, 1980 15. Pennock RT, editor. Intelligent design creationism and its critics. Cambridge (MA): MIT Press, 2001 16. Dawkins R. The greatest show on Earth: the evidence for evolution. London: Bantam Press, 2009 17. Shephard RJ. Human physiological work capacity. London: Cambridge University Press, 1978 18. Lynch G, Granger R. Big brain: the origins and future of human intelligence. New York: Macmillan, 2008 19. Fia"kowski KR. A mechanism for the origin of the human brain: a hypothesis. Curr Anthropol 1986; 27: 288-9 20. Fia"kowski KR. Early hominid brain evolution and heat stress: a hypothesis. Stud Phys Anthropol 1978; 4: 87-92 21. Lambert MI, Mann T, Dugas JP. Ethnicity and temperature regulation. In: Marino FE, editor. Thermoregulation and human performance: physiological and biological aspects. Basel: Karger, 2008: 104-20 22. Darwin C. The origin of species. New York: Random House, 1998
ª 2010 Adis Data Information BV. All rights reserved.
The Author’s Reply I would like to thank Prof. Frank Marino for his interest in and spirited comments on my recent article ‘Is it time to retire the Central Governor’?[1] However, I must admit to difficulty with blanket assertions such as ‘‘Prof. Shephard’s critique is littered with errors of fact,’’ particularly when the specifics raised in a lengthy letter are light on substance. The first issue is an appropriate time to retire the ‘Central Governor’. Age is a common criterion for retirement. Prof. Marino quotes Kuhn[2] implying that he is discussing ‘‘a new paradigm,’’ although at the same time he traces the origins of this hypothesis back to A.V. Hill, in the early part of the 20th century. He cites Johanson and Streeve[3] on the need for ‘‘testing and retesting new hypotheses.’’ If proponents of the ‘Central Governor’ were busily engaged in such activity, most scientists would be glad to allocate precious journal space to what might be exciting test results. However, repeated assertions that this hypothesis is a fact (e.g. the concluding paragraph of Prof. Marino’s letter) in the absence of convincing evidence have evoked more negative reactions. To quote again from Johanson and Streeve ‘‘The point is to make progress.’’[3] Most scientists of my ‘ilk’ would welcome consignment of the ‘Central Governor’ hypothesis to a bottom drawer, at least until patient testing and retesting has elicited some tangible proof of its truth. Prof. Marino makes the bold assertion that ‘‘proponents of the cardiovascular model avoid the findings that clearly demonstrate the importance of the amount of skeletal muscle recruitment ...’’ I am not sure which, if any, proponents of the ‘cardiovascular model’ are guilty of such neglect. Certainly, the International Biological Program (IBP) working group on the measurement of maximal oxygen intake recognized the importance of active muscle mass when determining an individual’s peak aerobic performance.[4] In collaboration with colleagues at the Centre National de la Recherche Scientifique (CNRS) in Paris, I later carried out extensive Sports Med 2010; 40 (3)
Letter to the Editor
research on this very issue,[5] highlighting the limitation of peak effort by negative feedback from a rising blood pressure and a peripheral accumulation of metabolites when the active muscle mass was small. Further research with investigators at the Toronto Rehabilitation Centre addressed the rather special case of oxygen transport in congestive heart failure, where (contrary to the assertion of Prof. Marino) the functional gains from 12 months of aerobic training proved largely attributable to an increase of peak cardiac output; any muscular limitation of effort in this class of patients reflected a loss of lean tissue loss and a decrease of oxidative metabolism in the leg muscles.[6,7] Moreover, none of this experimental evidence pointed to the existence of a ‘Central Governor’. We next move to the possible evolutionary history of any ‘Central Governor’. Prof. Marino is quite correct in asserting that Mosso’s actual experiments were on carrier pigeons; it was for this reason that I noted Mosso had argued rather than observed the phenomenon of migration training in quails. Bird migration is an interesting topic, although it seems a far cry from an athlete who is running a marathon. Many bald eagles migrate to the area where I am currently living, and at this time of the year I can observe that their success in energy conservation depends not on some ‘Central Governor’, but rather on an ability to exploit updrafts and strong prevailing winds. The necessary talents may be partly inherited, but much of the necessary expertise is acquired through parental training. Furthermore, most bird species do not rely on a Central Governor rationing out initial food reserves over their entire migratory journey; rather, they select their migration routes to allow feeding at various stop-over points. Thus, when quail migrate between Europe and Africa, they typically enjoy a rest stop in the southern Sinai, a point noted many years ago in the Hebrew Bible. I am accused of a ‘‘sleight of hand’’ for stressing an inconvenient truth previously pointed out by Prof. Will Hopkins.[8] When an animal is hunting or being hunted, a selective pressure could arise from an inadequate rather than an ª 2010 Adis Data Information BV. All rights reserved.
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excessive intensity of exercise. I am not clear why Prof. Marino thinks that the statement of these alternative possibilities implies a rejection of natural selection. But the several potential interpretations of a hunting scenario illustrate the difficulty in drawing any firm inferences from hypothesized patterns of evolution. Prof. Marino also states: ‘‘a case is made for the unlikely genetic transmission of hunting skills into the 21st century.’’ In fact, no such case is made. Indeed, during the mid-part of the 20th century a major objective of the International Biological Programme was to document the characteristics of isolated populations as quickly as possible, recognizing that within a very few years the peoples concerned would have become a part of a planetary genetic melting pot.[9,10] As I indicated in my article,[1] the dependence of human hunting success upon brain rather than brawn does not exclude the possibility that the physical demands of hunting may have influenced natural selection in other species. But, as Hopkins and I have both pointed out, any such selective pressures would not necessarily favour evolution of a Central Controller, even in lower animals. In conclusion, it is stimulating to engage in further discussion of evolutionary phenomena that may have influenced exercise performance. With the possible exception of International Biological Programme participants, physiologists have rarely visited this topic. Unfortunately, I cannot presently agree ‘‘that the [Central Governor Model] provides an uncomplicated solution to the understanding of exercise.’’ However, I do not think Prof. Marion should retreat into an ‘us or them’ stance. If the ‘Central Governor’ hypothesis is established by years of patient research matching that of Charles Darwin, I shall be the first to congratulate Profs. Frank Marino and Tim Noakes, and I shall urge the publication of an equally well documented treatise on The Origin of Species with a Central Controller. Roy J. Shephard Prof. Emeritus of Applied Physiology, Faculty of Physical Education and Health, University of Toronto, Toronto, Ontario, Canada
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Acknowledgements The author has no conflicts of interest that are directly relevant to the content of this letter.
References 1. Shephard RJ. Is it time to retire the ‘Central Governor’? Sports Med 2009; 39: 707-21 2. Kuhn TS. The structure of scientific revolutions. 3rd ed. Chicago (IL): University of Chicago Press, 1996 3. Johanson D, Streeve J. Lucy’s child: the discovery of a human ancestor. London: Viking, 1989 4. Shephard RJ, Allen C, Benade AJS, et al. The maximum oxygen intake: an international reference standard of cardio-respiratory fitness. Bull WHO 1968; 38: 757-64
ª 2010 Adis Data Information BV. All rights reserved.
5. Shephard RJ, Bouhlel E, Vandewalle H, et al. Muscle mass as a factor limiting physical work. Eur J Appl Physiol 1988; 64: 1472-9 6. Kavanagh T, Myerds MG, Baigrie MS, et al. Quality of life and cardiorespiratory function in chronic heart failure: effects of 12 months’ aerobic training. Heart 1996; 76: 42-9 7. Shephard RJ. Exercise for patients with congestive heart failure. Sports Med 1997; 23: 75-92 8. Hopkins WG. The implausible governor. Sportsci 2009; 13: 9-11 9. Shephard RJ. Human physiological work capacity. London: Cambridge University Press, 1978 10. Weiner JS. Proposals for international research. Human adaptability project: document 5. London: Royal Anthropological Institute, 1964
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Is it Time to Retire the ‘Central Governor’? A Philosophical and Evolutionary Perspective Any commentary on an author’s work is valuable as it prompts introspection and re-evaluation of the ideas posited by the work being critiqued. For this reason I am grateful to Prof. Shephard for the critical review of some of my writings that have contributed to the development of the Central Governor Model (CGM) of exercise physiology.[1] Prof. Shephard has provided some enticing and thoughtful points and therefore his critique invites comment. However, it would take several pages to rebut each of the points made by Prof. Shephard, so I will limit my arguments to a few philosophical points and the correction of factual errors and leave the interested reader and the fullness of time to evaluate the veracity for the arguments provided by Prof. Shephard’s critique of the CGM. I begin with the title of the article: Is it time to retire the ‘Central Governor’? This title begs the obvious counter question: what and who would benefit from the retirement of a new and revolutionary paradigm? Before addressing this question directly, it is worth being reminded about the true nature of scientific enquiry as written by renown paleoanthropologists Johanson and Streeve in responding to their opponents upon their discovery of the fossil, ‘Lucy’s child’:[2] ‘‘Frustrating as it is, the distantly tantalizing truths about our origins will probably not be revealed before we ourselves are buried under the earth. But that will not stop me from testing and retesting new hypotheses, exploring further possibilities. The point is not to be right. The point is to make progress. And you cannot make progress if you are afraid to be wrong.’’ Returning to the question of who and what would be the benefit of retiring the CGM, possible answers could be either that this allows us to continue with the previously held beliefs and assumptions and
therefore perpetuating the evidence that supports these assumptions or that proponents of the widely held classical view do not wish to embrace a new paradigm that might explain that which the classical view cannot. Either way there can be no significant progress towards the truth. In what is regarded as one of the hundred most influential books since WWII, Kuhn[3] has outlined why new revolutionary paradigms are seldom accepted immediately by the specialists in the field: ‘‘For these men the new theory implies a change in the rules governing the prior practice of normal science. Inevitably, therefore, it reflects upon much scientific work they have already successfully completed. That is why a new theory, however special its range of application, is seldom or never just an increment to what is already known. Its assimilation requires the reconstruction of prior theory and the re-evaluation of prior fact, an intrinsically revolutionary process that is seldom completed by a single man and never overnight.’’ It is thus not unusual that Prof. Shephard and those of his ilk might resist acknowledging a new paradigm that is better able to explain those observations that the classic teaching cannot. It is not entirely clear why opponents of the CGM do not take issue with the originators of the concepts leading to the CGM[4,5] in their attempt to explain the limitation of the cardiovascular model of exercise physiology. Rather, opponents of the CGM take issue with those who have provided further insights for its development.[6,7] At this point it is worth reiterating that the underpinning tenant of the CGM is the brain’s ability to recruit and de-recruit skeletal muscle to regulate exercise and avoid catastrophic failure of any organ system,[7] whereas the cardiovascular model holds that the heart and oxygen delivery are the factors limiting exercise.[8] It is notable that proponents of the cardiovascular model avoid the findings that clearly demonstrate the importance of the amount of skeletal muscle recruitment in the determination of peak oxygen uptake when improvements in central haemodynamics are not parallelled by increases in systemic exercise performance even in congestive heart failure.[9,10]
266
Prof. Shephard individually critiques what he calls ‘‘five correlates of the CGM,’’ one of which is the ‘‘potential for the evolution of a Central Governor.’’[1] A substantial discussion for the origins of an anticipatory mechanism in the evolution of hominids has been provided elsewhere, so the discerning reader will be able to evaluate the arguments presented on the matter to their satisfaction.[11] However, whether or not there has been an evolutionary process in the development of a centrally mediated mechanism for teleoanticipation is not a common area of research in the exercise sciences and the understanding of such an evolutionary process needs further elaboration. This section, like all other sections of Prof. Shephard’s critique, is littered with errors of fact and must be corrected as a matter of record. Prof. Shephard asserts that ‘‘Mosso noted that 3 years of learning was needed to perfect migration patterns in quails; he argued that the birds were then able to regulate the energy expenditures over prolonged flights in such a manner as to conserve a final store of metabolites against easy capture.’’[1] This interpretation is not only a distortion of Mosso’s findings, but it is also an error of fact as Mosso did not make this suggestion at all and he did not train quails. This is an important distinction as Mosso originally observed that energy expenditure may not have been crucial in the long-distance flight of quails from Africa to Rome but some other mechanism could explain the ability of the long-distance flight. In making this observation Mosso then attempted to elicit the same long-distance flying ability in carrier pigeons and it was then that he noted that this ability could only be attained after 3 years of specific training and education. In other words, a naturally occurring phenomenon (in quails) could be trained and indeed improved upon as training continued. Therefore, the issue is whether or not training provides the stimulus for the organism to better understand the task and plan a strategy to complete the task without catastrophic failure. I have previously provided a treatise on the development of anticipatory regulation through evolutionary forces and argued that this might be specific to the organisms’ conditions.[11] As ª 2010 Adis Data Information BV. All rights reserved.
Letter to the Editor
further examples, two extremes were used to illustrate the difference between endurance and sprint capacity in the African hunting dog and the cheetah, respectively.[12] I suggested that evolutionary pressures led to the development of a central regulatory mechanism. However, in a sleight-of-hand Prof. Shephard suggests that the evolutionary scenario could be argued in several different ways as given by Hopkins,[13] whereby predators might risk a loss of homeostasis in order to avoid death from starvation or predators risking a loss of homeostasis to avoid capture. In this scenario the most widely accepted scientific theory, that of natural selection, has been ruled out simply by suggesting that the Central Governor could work in two opposing directions. But natural selection does not provide for either/or in survival; that is, individuals within a species that were caught or could not catch prey were either respectively killed or starved and did not produce offspring. The very basis of natural selection predicts that any trait favouring a species will carry on in their offspring; in this case those individuals with the most advanced teleoanticipatory system or Central Governor will have survived. To defend the view that the Central Governor could not have evolved, Prof. Shephard defers to an obscure one-sided editorial by Hopkins who suggests ‘‘y that the governor makes little sense from an evolutionary perspective. Only an unintelligent designer would endow animals with capacities they cannot use.’’[13] There are two fallacies with this argument. First, how can one argue for unintelligent design in relation to evolution? These are mutually exclusive views of reality; evolution being a scientific paradigm open to refutation and intelligent design (or as Hopkins prefers, unintelligent design) being a creationist perspective that does not fulfil the criteria of a scientific paradigm. Second, to suggest that evolution, and by extension nature, does not endow organisms with capacities they cannot use is false. This view of natural selection is known as hyper-selectionism and denies the obvious that many species have vestigial features.[14] For example, in mammals the recurrent laryngeal nerve does not extend directly from the brain to Sports Med 2010; 40 (3)
Letter to the Editor
the larynx, but upon reaching the neck bypasses the larynx and drops into the chest where it loops and only then retraces up to the larynx in the neck;[15,16] those of us who have had wisdom teeth extracted can attest to the futility of these structures. Although Prof. Shephard should be applauded for a valiant attempt at dissecting the CGM and in particular the evolutionary basis for a teleo-anticipatory mechanism, such critiques should be carried out with the inclusion of the accepted scientific theories rather than attempting to distort the facts by excluding such theories; this line of reasoning is usually labelled as ‘spin’. Finally, in an attempt to refute the hypothesis that the Central Governor evolved during persistent hunting under heat stress, Prof. Shephard cites the conclusions drawn by the International Biological Program (IBP)[17] on the ability of various isolated populations to undertake fatiguing work of various durations. The IBP apparently found little evidence that humans have developed unusual physiological characteristics in response to prolonged residence in extreme environments as ‘‘y field studies of traditional Neolithic populations suggest that their success in hunting trips, and thus any selective pressures, depends much more on intellect than brute force, running ability or tolerance of physical fatigue.’’[1] The logic here does not follow as the assumption is that intellect preceded human bipedal locomotion. In this instance Prof. Shephard ignores completely the current wisdom, which holds that the ‘‘y big brain arose from the big baby, and the big baby arose first from challenges in walking, and then enlarged hips in females. The proposal thoroughly contradicts the alternative assumption, that selection pressures for intelligence drove the evolution of big brains. Tool use didn’t prompt brain expansion. Rather walking expanded brain size, and the bigger brain was able to conceive of tool construction and use.’’[18-20] Therefore, any observation in contemporary ‘primitive’ peoples assumes that the large brain and, therefore, the intellect spontaneously occurred. In addition to this broken logic, a case is made for the unlikely genetic transmission of hunting skills into the 21st century simply because the planet is now a genetic melting ª 2010 Adis Data Information BV. All rights reserved.
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pot. Assuming that a mechanism for anticipatory regulation evolved over millions of years, Prof. Shephard would now wish us to accept that this characteristic along with many other genetic traits would disappear within only a few generations. It is also notable that the relationship between phenotype and genotype is used as evidence against the selection pressures for the evolution of a thermally protective ‘Central Governor’ as exercise tolerance and thermoregulation seem to be phenotypic.[21] However, Prof. Shephard is guilty of removing the contextual basis for this statement as given by the authors who state that ‘‘y for future studies to make an impact in identifying genotypic differences, the phenotypical changes arising from diversity in environmental conditions will need to be controlled before there is any intervention (exposure to hot or cold conditions).’’[21] Therefore, it is not the case that there is no genotype for thermotolerance but rather these data are difficult to acquire due to the lack of control arising from the diverse environmental conditions. In summary, it is clear that many exercise scientists do not regard the CGM as an alternative hypothesis to the more traditional view or that it can predict the way in which human performance is regulated under all conditions. Therefore, the challenge issued by Prof. Shephard should not be taken lightly. However, to continue to assert that ‘‘Over the past 13 years a small group of investigators has argued repeatedly for the existence of a Central Governor y’’[1] reduces this debate to nothing more than an us-or-them approach to science. Rather, the fact that the CGM provides an uncomplicated solution to the understanding of the regulation of exercise and that it puts the brain back in focus is to be celebrated rather than maligned. When T.H. Huxley first read Darwin’s The Origin of Species[22] it is said that his reaction was ‘‘How extremely stupid not to have thought of that.’’ Perhaps it is this sentiment that the opponents of the CGM lament? Frank E. Marino Prof. and Chair of Exercise Physiology, Head of School of Human Movement Studies, Charles Sturt University, Bathurst, New South Wales, Australia
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References 1. Shephard RJ. Is it time to retire the ‘Central Governor?’ Sports Med 2009; 39: 709-21 2. Johanson D, Streeve J. Lucy’s child: the discovery of a human ancestor. London: Viking, 1989 3. Kuhn TS. The structure of scientific revolutions. 3rd ed. Chicago (IL): The University of Chicago Press, 1996 4. Hill AV, Long CHN, Lupton H. Muscular exercise, lactic acid and the supply and utilisation of oxygen: parts VIIVIII. Proceed Roy Soc Britain 1924; 97: 155-76 5. Ulmer HV. Concept of extracellular regulation of muscular metabolic rate during heavy exercise in humans by psychophysiological feedback. Experentia 1996; 52: 416-20 6. Noakes TD, Marino FE. Point/counterpoint: maximal oxygen uptake is limited by a central nervous system governor. J Appl Physiol 2008; 106: 338-48 7. Noakes TD, St Clair Gibson A, Lambert VA. From catastrophe to complexity: a novel model of integrative central neural regulation of effort and fatigue during exercise in humans. Br J Sports Med 2004; 38: 511-4 8. Brink-Elfegoun T, Kaijser L, Gustafsson T, et al. Maximal oxygen uptake is not limited by a central nervous system governor. J Appl Physiol 2007; 102: 781-6 9. Jondeau G, Katz SD, Zohman L, et al. Active skeletal mass and cardiopulmonary reserve. Circulation 1992; 86: 1351-6 10. Minotti JR, Christoph I, Oka R, et al. Impaired skeletal muscle function in patients with congestive heart failure. J Clin Investig 1991; 88: 2077-82 11. Marino FE. The evolutionary basis of thermoregulation and exercise performance. In: Marino FE, editor. Thermoregulation and human performance: physiological and biological aspects. Basel: Karger, 2008: 1-13 12. Marino FE. Comparative thermoregulation and the quest for athletic supremacy. In: Marino FE, editor. Thermoregulation and human performance: physiological and biological aspects. Basel: Karger, 2008: 14-25 13. Hopkins WG. The improbable Central Governor of maximal endurance performance. Sportsci 2009; 13: 9-12 14. Gould SJ. The Panda’s thumb: more reflections in natural history. New York: WW Norton & Company, 1980 15. Pennock RT, editor. Intelligent design creationism and its critics. Cambridge (MA): MIT Press, 2001 16. Dawkins R. The greatest show on Earth: the evidence for evolution. London: Bantam Press, 2009 17. Shephard RJ. Human physiological work capacity. London: Cambridge University Press, 1978 18. Lynch G, Granger R. Big brain: the origins and future of human intelligence. New York: Macmillan, 2008 19. Fia"kowski KR. A mechanism for the origin of the human brain: a hypothesis. Curr Anthropol 1986; 27: 288-9 20. Fia"kowski KR. Early hominid brain evolution and heat stress: a hypothesis. Stud Phys Anthropol 1978; 4: 87-92 21. Lambert MI, Mann T, Dugas JP. Ethnicity and temperature regulation. In: Marino FE, editor. Thermoregulation and human performance: physiological and biological aspects. Basel: Karger, 2008: 104-20 22. Darwin C. The origin of species. New York: Random House, 1998
ª 2010 Adis Data Information BV. All rights reserved.
The Author’s Reply I would like to thank Prof. Frank Marino for his interest in and spirited comments on my recent article ‘Is it time to retire the Central Governor’?[1] However, I must admit to difficulty with blanket assertions such as ‘‘Prof. Shephard’s critique is littered with errors of fact,’’ particularly when the specifics raised in a lengthy letter are light on substance. The first issue is an appropriate time to retire the ‘Central Governor’. Age is a common criterion for retirement. Prof. Marino quotes Kuhn[2] implying that he is discussing ‘‘a new paradigm,’’ although at the same time he traces the origins of this hypothesis back to A.V. Hill, in the early part of the 20th century. He cites Johanson and Streeve[3] on the need for ‘‘testing and retesting new hypotheses.’’ If proponents of the ‘Central Governor’ were busily engaged in such activity, most scientists would be glad to allocate precious journal space to what might be exciting test results. However, repeated assertions that this hypothesis is a fact (e.g. the concluding paragraph of Prof. Marino’s letter) in the absence of convincing evidence have evoked more negative reactions. To quote again from Johanson and Streeve ‘‘The point is to make progress.’’[3] Most scientists of my ‘ilk’ would welcome consignment of the ‘Central Governor’ hypothesis to a bottom drawer, at least until patient testing and retesting has elicited some tangible proof of its truth. Prof. Marino makes the bold assertion that ‘‘proponents of the cardiovascular model avoid the findings that clearly demonstrate the importance of the amount of skeletal muscle recruitment ...’’ I am not sure which, if any, proponents of the ‘cardiovascular model’ are guilty of such neglect. Certainly, the International Biological Program (IBP) working group on the measurement of maximal oxygen intake recognized the importance of active muscle mass when determining an individual’s peak aerobic performance.[4] In collaboration with colleagues at the Centre National de la Recherche Scientifique (CNRS) in Paris, I later carried out extensive Sports Med 2010; 40 (3)
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research on this very issue,[5] highlighting the limitation of peak effort by negative feedback from a rising blood pressure and a peripheral accumulation of metabolites when the active muscle mass was small. Further research with investigators at the Toronto Rehabilitation Centre addressed the rather special case of oxygen transport in congestive heart failure, where (contrary to the assertion of Prof. Marino) the functional gains from 12 months of aerobic training proved largely attributable to an increase of peak cardiac output; any muscular limitation of effort in this class of patients reflected a loss of lean tissue loss and a decrease of oxidative metabolism in the leg muscles.[6,7] Moreover, none of this experimental evidence pointed to the existence of a ‘Central Governor’. We next move to the possible evolutionary history of any ‘Central Governor’. Prof. Marino is quite correct in asserting that Mosso’s actual experiments were on carrier pigeons; it was for this reason that I noted Mosso had argued rather than observed the phenomenon of migration training in quails. Bird migration is an interesting topic, although it seems a far cry from an athlete who is running a marathon. Many bald eagles migrate to the area where I am currently living, and at this time of the year I can observe that their success in energy conservation depends not on some ‘Central Governor’, but rather on an ability to exploit updrafts and strong prevailing winds. The necessary talents may be partly inherited, but much of the necessary expertise is acquired through parental training. Furthermore, most bird species do not rely on a Central Governor rationing out initial food reserves over their entire migratory journey; rather, they select their migration routes to allow feeding at various stop-over points. Thus, when quail migrate between Europe and Africa, they typically enjoy a rest stop in the southern Sinai, a point noted many years ago in the Hebrew Bible. I am accused of a ‘‘sleight of hand’’ for stressing an inconvenient truth previously pointed out by Prof. Will Hopkins.[8] When an animal is hunting or being hunted, a selective pressure could arise from an inadequate rather than an ª 2010 Adis Data Information BV. All rights reserved.
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excessive intensity of exercise. I am not clear why Prof. Marino thinks that the statement of these alternative possibilities implies a rejection of natural selection. But the several potential interpretations of a hunting scenario illustrate the difficulty in drawing any firm inferences from hypothesized patterns of evolution. Prof. Marino also states: ‘‘a case is made for the unlikely genetic transmission of hunting skills into the 21st century.’’ In fact, no such case is made. Indeed, during the mid-part of the 20th century a major objective of the International Biological Programme was to document the characteristics of isolated populations as quickly as possible, recognizing that within a very few years the peoples concerned would have become a part of a planetary genetic melting pot.[9,10] As I indicated in my article,[1] the dependence of human hunting success upon brain rather than brawn does not exclude the possibility that the physical demands of hunting may have influenced natural selection in other species. But, as Hopkins and I have both pointed out, any such selective pressures would not necessarily favour evolution of a Central Controller, even in lower animals. In conclusion, it is stimulating to engage in further discussion of evolutionary phenomena that may have influenced exercise performance. With the possible exception of International Biological Programme participants, physiologists have rarely visited this topic. Unfortunately, I cannot presently agree ‘‘that the [Central Governor Model] provides an uncomplicated solution to the understanding of exercise.’’ However, I do not think Prof. Marion should retreat into an ‘us or them’ stance. If the ‘Central Governor’ hypothesis is established by years of patient research matching that of Charles Darwin, I shall be the first to congratulate Profs. Frank Marino and Tim Noakes, and I shall urge the publication of an equally well documented treatise on The Origin of Species with a Central Controller. Roy J. Shephard Prof. Emeritus of Applied Physiology, Faculty of Physical Education and Health, University of Toronto, Toronto, Ontario, Canada
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Acknowledgements The author has no conflicts of interest that are directly relevant to the content of this letter.
References 1. Shephard RJ. Is it time to retire the ‘Central Governor’? Sports Med 2009; 39: 707-21 2. Kuhn TS. The structure of scientific revolutions. 3rd ed. Chicago (IL): University of Chicago Press, 1996 3. Johanson D, Streeve J. Lucy’s child: the discovery of a human ancestor. London: Viking, 1989 4. Shephard RJ, Allen C, Benade AJS, et al. The maximum oxygen intake: an international reference standard of cardio-respiratory fitness. Bull WHO 1968; 38: 757-64
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5. Shephard RJ, Bouhlel E, Vandewalle H, et al. Muscle mass as a factor limiting physical work. Eur J Appl Physiol 1988; 64: 1472-9 6. Kavanagh T, Myerds MG, Baigrie MS, et al. Quality of life and cardiorespiratory function in chronic heart failure: effects of 12 months’ aerobic training. Heart 1996; 76: 42-9 7. Shephard RJ. Exercise for patients with congestive heart failure. Sports Med 1997; 23: 75-92 8. Hopkins WG. The implausible governor. Sportsci 2009; 13: 9-11 9. Shephard RJ. Human physiological work capacity. London: Cambridge University Press, 1978 10. Weiner JS. Proposals for international research. Human adaptability project: document 5. London: Royal Anthropological Institute, 1964
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