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Exercise and Health: Can Biotechnology Confer Similar Benefits?

Health Benefits of Physical Activity

Regular physical activity has been recognized to confer health benefits since antiquity [1]. However, for most of humankind, voluntary discretion over whether or not to exercise is a recent phenomenon limited to advanced industrialized societies.

A large body of epidemiological literature consistently documents greater longevity in persons who are physically active on a near-daily basis, and reveals inverse relationships between levels of daily exercise and incidence of major chronic disorders such as obesity [2], hypertension [3], diabetes [4], ischemic heart disease, and all causes of mortality [5,6,7,8,9,10,11,12]. From a public health perspective, there is little question that even modest increases in daily activities such as walking or stair climbing would have important positive consequences in reducing the burden of illness.

However, knowledge of the likely health benefits accruing to the physically active so far has not been a sufficient stimulus to promote sustained changes in behavior for most of the American population. If education and public policies are insufficient to promote behavioral changes to increase physical activity among most people, can advances in biotechnology confer such benefits to individuals unable or unwilling to perform the necessary physical effort?

Translating Knowledge of Exercise Biology to Novel Therapeutics

Greater knowledge of how cells and tissues are modified in response to recurring bouts of exercise provides a basis for more precise recommendations as to the mode, intensity, and amount of exercise required to produce specific health benefits (e.g., treatment of dyslipidemia [13], control of body weight [14], or prevention of diabetes [15]). In addition, an understanding of the molecular signaling events that drive the beneficial effects of exercise on human physiology could foster the development of novel drugs, devices, or biological agents designed to substitute for exercise.

Many individuals who otherwise would develop diabetes or cardiovascular disease would benefit if advances in exercise biology revealed novel measures to promote the favorable effects on insulin sensitivity, lipoprotein metabolism, and blood pressure that are known to accrue through regular physical activity.

Physiological Properties of Skeletal Muscle

What do we know about basic muscle and exercise biology? The cells that constitute our skeletal muscles are called myofibers—large multinucleated cells that may extend for the full length of individual muscles. There are different types of myofibers, which vary in size and with respect to metabolic and contractile capability [16] (Figure 1). Skeletal myofibers are innervated by motor neurons that contact each myofiber, and the intensity, duration, and timing of each muscle contraction are determined by the pattern of motor neuron firing. A pattern of occasional intense contractions separated by longer periods of rest is called “phasic,” while a pattern characterized by brief contractions occurring repeatedly over an extended period is called “tonic.” Endurance training regimens like running or cycling employ tonic patterns of contractile work, and it is this form of habitual activity that serves best to reduce risk for obesity, diabetes, hypertension, and heart disease.

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Figure 1. Specialized Myofibers in a Mammalian Skeletal Muscle

A cross-section of the gastrocnemius muscle of a mouse has been stained to detect myoglobin, which is found selectively in slow oxidative and fast oxidative myofibers (stained brown), but not in fast glycolytic myofibers (unstained). Human muscles exhibit a similar mosaic pattern. In response to sustained periods of motor nerve stimulation repeated daily for several weeks, the percentage of myofibers that contain myoglobin is increased, in synchrony with an increased abundance of mitochondria and a shift of myosin subtypes from fast glycolytic to slow or fast oxidative.

https://doi.org/10.1371/journal.pmed.0020068.g001

Dynamics of Muscle Mass

Maintenance of normal muscle mass requires some minimal level of ongoing work activity, and building and maintaining muscle mass is most effectively done through phasic contractions. A slow but inexorable loss of muscle mass is a feature of advancing age in human populations [17]. Loss of muscle mass and strength is an important determinant of injury and disability in the elderly, but even rigorous weight training programs cannot completely counteract this age-related decline that becomes particularly troublesome in the eighth and ninth decades of life. Efforts to develop effective countermeasures to maintain muscle mass in the elderly constitute an active and important area of current research [18,19,20].

Although the molecular signaling mechanisms that transduce the effects of phasic patterns of work activity to modify muscle mass are incompletely understood, recent evidence implicates pathways that include the signaling molecules PI3 kinase, Akt, mTOR, S6K, and ERK, the ubiquitin ligases MAFbx and MuRF1, and transcription factors of the FOX superfamily in the control of both catabolic and anabolic processes [21,22,23,24].

Contractile and Metabolic Properties

With respect to variations in contractile and metabolic properties, myofibers are classified on a spectrum between two extremes on the basis of contractile (fast versus slow) and metabolic (glycolytic versus oxidative) properties. At one extreme, the fastest glycolytic fibers have high levels of enzymes that generate ATP via glycolysis but few mitochondria (approximately 1% of cell volume). At the other end of the spectrum, slow oxidative fibers generate force with slower kinetics but are capable of long periods of repeated contraction without fatigue. They are rich in mitochondria (3%–10% of cell volume). Other myofibers, called fast oxidative, are both relatively fast and resistant to fatigue, and are rich in mitochondria (like the slow oxidative fibers). Muscles composed primarily of fast glycolytic fibers are needed for rapid movements (e.g., escape from predators) but fatigue when sustained periods of activity are required (e.g., migration).

Most human muscles exhibit a mosaic pattern of different fiber types (Figure 1), with a great deal of variation among individuals, which is influenced at least in part by patterns of use. When we exercise daily, or at least several times weekly, we deliver a stimulus to the specific muscle groups involved in these activities that is sufficient to alter specialized properties of myofibers within these muscles. While habitual physical activity promotes a great variety of physiological adaptations that alter vascular reactivity, cardiac function, adipocyte function, and neurophysiology, adaptive responses of skeletal myofibers confer at least some of the health benefits.

Patterning of skeletal muscle fiber composition is initially determined during embryonic development, but can be partially or completely overturned by stimuli applied to fully mature adult myofibers: by hormonal influences (e.g., thyroid hormone), but most importantly by different patterns of motor nerve activity and contractile work. Myofibers that experience phasic patterns of contractile work—brief bursts of activity interspersed within long periods of inactivity—will assume the fast glycolytic phenotype. Myofibers subjected to tonic patterns of work activity—sustained periods of repetitive contraction on a habitual basis—will take on fast oxidative or slow oxidative properties. Under experimental conditions in laboratory animals, it is possible to transform muscles completely from one myofiber phenotype to another in a reversible manner, solely by altering the pattern of neural stimulation. We know that having a high proportion of oxidative muscle fibers conveys health benefits, and the possibility to control fiber composition through therapeutic intervention is promising.

Molecular Signaling Pathways

At a cellular and molecular level, how does a fast glycolytic myofiber sense a tonic pattern of contractile activity and transduce that information to transform itself into a cell with fast oxidative or slow oxidative properties? We know that such signals must be transduced to the nucleus, activating certain genes and suppressing others, for myofiber plasticity to occur. We know the identities of some of the nuclear transcription factors that carry these signals, and of other proteins that regulate the function of these transcription factors (Figure 2).

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Figure 2. Molecular Signaling Pathways Link Changes in Contractile Activity to Changes in Gene Expression That Establish Myofiber Diversity

A tonic pattern of motor nerve activity promotes changes in intracellular calcium that trigger a variety of intracellular events that modify the function of nuclear transcription factors. The pathway transduced by calcineurin and NFAT is highlighted in larger type. Other signals are received by cell surface receptors to activate similar or parallel signaling events. Signaling proteins that participate in transducing effects of contractile activity to specific genes include ion channels (TRP), scaffolding proteins (Homer), protein phosphatases and protein kinases (calcineurin, CAMK, p38MAPK), DNA-binding transcription factors (shown in red; NFAT, MEF2, PGC-1, ATF2), and endogenous inhibitors (shown in blue; GSK3, HDAC, and MCIP) (inhibitors antagonize gene activation via the pathways indicated, in some cases acting as negative feedback regulators).

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Quite a variety of intracellular messengers have been proposed to provide the proximate signals in exercising muscles to stimulate activity-dependent gene regulation. This discussion will focus on a signaling cascade mediated by calcineurin, a calcium-regulated protein phosphatase that signals to the nucleus via transcription factors of the nuclear factor of activated T cells (NFAT) family. Upon receipt of the appropriate calcium signal, calcineurin is activated and removes phosphate groups from NFAT, thereby permitting translocation of NFAT to the nucleus. Within the nucleus, NFAT binds DNA and activates transcription (in concert with other transcription factors) of relevant downstream target genes that encode proteins necessary for fast oxidative or slow oxidative myofiber phenotypes.

Calcineurin and NFAT proteins are abundant in skeletal myofibers, and several lines of evidence support the viewpoint that the calcineurin–NFAT pathway plays a role in mediating activity-dependent gene regulation in muscle [25,26,27,28,29,30,31,32,33,34,35,36,37,38,39]. For example, in mice genetically engineered to distinguish the inactive (cytoplasmic) from active (nuclear) forms of NFAT by means of a sensor, it is evident that NFAT is inactive in resting muscles, but activated by tonic patterns of muscle contraction (running or electrical stimulation of the motor nerve) [40]. Using other genetic manipulations in mice to produce in muscle a form of calcineurin that remains active even in the absence of calcium signals, myofibers are converted from fast glycolytic to fast oxidative or slow oxidative forms [41]. And in muscles of mice genetically engineered to lack calcineurin, fiber type switching is impaired [42].

Cellular Memory

Muscle contractions are initiated under the influence of the motor nerve by release of calcium from the sarcoplasmic reticulum, which triggers actin–myosin crossbridge cycling (Figure 3). Calcium released via ryanodine receptors is completely sufficient to activate muscle contractions, and the effects are immediate (within milliseconds). It is also sufficient to initiate calcineurin–NFAT signaling to the nucleus, but cannot by itself sustain the signal in a manner necessary to promote myofiber remodeling [40]. Changes in gene expression evoked by neuromuscular activity are not immediate but require that the stimulus be sustained for an extended period (minutes to hours). Moreover, tonic stimulation of the motor nerve must be repeated daily, or nearly so, over several weeks for the changes in myofiber properties to become fully manifest. We have characterized this requirement for repetition of the activity stimulus over days as a form of “cellular memory.” The effects of the tenth or 20th day of exercise are not the same as the effects of the first day. The myofiber somehow “remembers” not only the pattern of activity it has experienced today, but what has gone on over the preceding days or weeks, such that the changes in abundance of proteins that control contractile function and metabolism accrue over time.

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Figure 3. Proposed Model for Cellular Memory, Based on Activity-Induced Changes in TRPC3—A Putative Store-Operated Calcium Channel

Neural activation triggers muscle contraction by releasing calcium stored within the sarcoplasmic reticulum (SR) through mechanisms that involve channel proteins called dihydropyridine receptors (DHPR) and ryanodine receptors (RYR). Inactive myofibers have a low abundance of TRPC3 channels, and calcium released from SR is not sufficient to maintain the calcium-regulated transcription factor NFAT in the nucleus. Under conditions of tonic activity (training stimulus), TRPC3 channels become more abundant, and are regulated by the scaffold protein Homer, which binds RYR. Under these conditions, the combined effect of calcium entering the cell via TRPC3 channels and exiting the SR via RYR channels maintains NFAT in the nucleus, where it promotes transcription of genes that establish the slow oxidative phenotype in myofibers. Once the slow oxidative phenotype is established (trained myofiber), the continued expression of TRPC3 allows this state to be maintained even with a less intensive tonic activity pattern of neural stimulation. (Figure adapted from [40].)

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To explain this cellular memory, we propose that, as the bursts of contractile activity are sustained over time (through a tonic pattern of neural stimulation), a second source of calcium is mobilized from outside of the cell and enters via a class of calcium channels that are called “store-operated” or “non-voltage-dependent.” This second source of calcium is not required for muscle contractions, but is required to sustain calcium-dependent signaling to the nucleus. Phasic patterns of contractile activity do not promote calcium entry via store-operated channels. Tonic patterns of activity, in contrast, would not only promote the mobilization of extracellular calcium but also increase the number of store-operated calcium channels with each bout of exercise. Myofibers would thereby grow progressively more responsive to tonic activity. Consistent with this model, we know that daily running increases the expression of a putative store-operated calcium channel called TRPC3. Moreover, increasing the abundance of TRPC3 in cultured myotubes prolongs the period in which intracellular calcium is elevated following a depolarizing stimulus, sustains the transcription factor NFAT within the nucleus, and augments expression of NFAT-dependent target genes [40].

A great deal of additional research remains to be done before we have a comprehensive understanding of how habitual physical activity promotes changes in gene expression in skeletal muscles, and in turn improves fitness and reduces risk for diabetes, hypertension, dyslipidemia, and coronary artery disease. However, studies of the relationships between the proteins of calcium metabolism and calcium-regulated signaling pathways—as described here in a simplified manner with respect to TRPC3, calcineurin, and NFAT proteins—are illustrative of progress in this field. Other notable findings point to additional signaling proteins (CAMK, p38MAPK, and AMPK) and transcription factors (PGC-1, MEF2, ATF2, PPARs) active in pathways that intersect with calcineurin–NFAT signaling [31,43,44,45,46,47,48] (see Figure 2). It is encouraging that some of these proteins are attractive targets for drug discovery.

Summary and Conclusions

Long the province of physiologists who have contributed valuable insights in past decades, exercise science more recently has attracted the attention of molecular biologists, who have recognized the biological interest and medical importance of this field. Biotechnology and pharmaceutical companies also are beginning to take interest.

This review has focused on adaptive responses of skeletal muscle to changing patterns of physical activity, and on the role of the calcium–calcineurin–NFAT signaling cascade in controlling gene expression in skeletal myofibers. Further advances in our understanding of signaling mechanisms that govern activity-dependent gene regulation in skeletal muscle could lead to drugs, gene therapy, or devices that can, at least in part, substitute for daily exercise. Although it is unlikely that such technologies would fully recapitulate exercise-induced adaptations that affect other tissues of the body, beneficial effects on work performance and whole-body metabolism have been demonstrated using gene transfer techniques to alter skeletal muscles in animal models. If it proves possible to drive similar effects in skeletal muscles in humans, the interventions capable of providing such effects would almost certainly find broad clinical application.

References

  1. 1. United States Department of Health and Human Services (1996) Surgeon General's report on physical activity and health. Centers for Disease Control and Prevention, The President's Council on Physical Fitness and Sports, National Center for Chronic Disease Prevention and Health Promotion. Atlanta: United States Department of Health and Human Services. Available: http://www.cdc.gov/nccdphp/sgr/contents.htm. Accessed 4 February 2005.
  2. 2. Kriska AM, Saremi A, Hanson RL, Bennett PH, Kobes S, et al. (2003) Physical activity, obesity, and the incidence of type 2 diabetes in a high-risk population. Am J Epidemiol 158: 669–675.
  3. 3. Paffenbarger RS, Wing AL, Hyde RT, Jung DL (1983) Physical activity and incidence of hypertension in college alumni. Am J Epidemiol 117: 245–257.
  4. 4. Church TS, Cheng YJ, Earnest CP, Barlow CE, Gibbons LW, et al. (2004) Exercise capacity and body composition as predictors of mortality among men with diabetes. Diabetes Care 27: 83–88.
  5. 5. Schnohr P, Scharling H, Jensen JS (2003) Changes in leisure-time physical activity and risk of death: An observational study of 7,000 men and women. Am J Epidemiol 158: 639–644.
  6. 6. Lee IM, Hsieh CC, Paffenbarger RS (1995) Exercise intensity and longevity in men: The Harvard Alumni Study. JAMA 273: 1179–1184.
  7. 7. Blair SN, Kohl HW, Barlow CE, Paffenbarger RS, Gibbons LW, et al. (1995) Changes in physical fitness and all-cause mortality: A prospective study of healthy and unhealthy men. JAMA 273: 1093–1098.
  8. 8. Paffenbarger RS, Hyde RT, Wing AL, Hsieh CC (1993) Physical activity, all-cause mortality, and longevity of college alumni. N Engl J Med 314: 605–613.
  9. 9. Paffenbarger RS, Hyde RT, Wing AL, Lee IM, Jung DL, et al. (1993) The association of changes in physical-activity level and other lifestyle characteristics with mortality among men. N Engl J Med 328: 538–545.
  10. 10. Blair SN, Kohl HW, Paffenbarger RS, Clark DG, Cooper KH, et al. (1989) Physical fitness and all-cause mortality: A prospective study of healthy men and women. JAMA 262: 2395–2401.
  11. 11. Batty GD, Lee IM (2004) Physical activity and coronary heart disease. BMJ 328: 1089–1090.
  12. 12. Mokdad AH, Marks JS, Stroup DF, Gerberding JL (2004) Actual causes of death in the United States, 2000. JAMA 291: 1238–1245.
  13. 13. Kraus WE, Houmard JA, Duscha BD, Knetzger KJ, Wharton MB, et al. (2002) Effects of the amount and intensity of exercise on plasma lipoproteins. N Engl J Med 347: 1483–1492.
  14. 14. Slentz CA, Duscha BD, Johnson JL, Ketchum K, Aiken LB, et al. (2004) Effects of the amount of exercise on body weight, body composition, and measures of central obesity: STRRIDE—A randomized controlled study. Archiv Int Med 164: 31–39.
  15. 15. Houmard JA, Tanner CJ, Slentz CA, Duscha BD, McCartney JS, et al. (2004) The effect of the amount and intensity of exercise training on insulin sensitivity. J Appl Physiol 96: 101–106.
  16. 16. Kraus WE, Torgan CE, Taylor DA (1994) Skeletal muscle adaptation to chronic low-frequency motor nerve stimulation. In: Holloszy JO, editor. Exercise and sports sciences reviews. Baltimore: Williams and Wilkins. pp. 313–360.
  17. 17. Hadley EC, Dutta C (1995) The significance of sarcopenia in old age. J Gerontol 50A: 1–4.
  18. 18. Barton ER, Morris L, Musaro A, Rosenthal N, Sweeney HL (2002) Muscle-specific expression of insulin-like growth factor I counters muscle decline in mdx mice. J Cell Biol 157: 137–148.
  19. 19. Musaro A, McCullagh K, Paul A, Houghton L, Dobrowolny G, et al. (2001) Localized Igf-1 transgene expression sustains hypertrophy and regeneration in senescent skeletal muscle. Nat Genet 27: 195–200.
  20. 20. Musaro A, McCullagh KJ, Naya FJ, Olson EN, Rosenthal N (1999) IGF-1 induces skeletal myocyte hypertrophy through calcineurin in association with GATA-2 and NF-ATc1. Nature 400: 581–585.
  21. 21. Stitt TN, Drujan D, Clarke BA, Panaro F, Timofeyva Y, et al. (2004) The IGF-1/PI3K/Akt pathway prevents expression of muscle atrophy-induced ubiquitin ligases by inhibiting FOXO transcription factors. Mol Cell 14: 395–403.
  22. 22. Rennie MJ, Wackerhage H, Spangenburg EE, Booth FW (2004) Control of the size of the human muscle mass. Annu Rev Physiol 66: 799–828.
  23. 23. McNally EM (2004) Powerful genes—Myostatin regulation of human muscle mass. N Engl J Med 350: 2642–2644.
  24. 24. Kamei Y, Miura S, Suzuki M, Kai Y, Mizukami J, et al. (2004) Skeletal muscle FOXO1 (FKHR)-transgenic mice have less skeletal muscle mass, down-regulated type I (slow twitch / red muscle) fiber genes, and impaired glycemic control. J Biol Chem 279: 41114–41123.
  25. 25. Chin ER, Olson EN, Richardson JA, Yang Q, Humphries C, et al. (1998) A calcineurin-dependent transcriptional pathway controls skeletal muscle fiber type. Genes Dev 12: 2499–2509.
  26. 26. Schulz RA, Yutzey KE (2004) Calcineurin signaling and NFAT activation in cardiovascular and skeletal muscle development. Dev Biol 266: 1–16.
  27. 27. McCullagh KJ, Calabria E, Pallafacchina G, Ciciliot S, Serrano AL, et al. (2004) NFAT is a nerve activity sensor in skeletal muscle and controls activity-dependent myosin switching. Proc Natl Acad Sci U S A 101: 10590–10595.
  28. 28. Fenyvesi R, Racz G, Wuytack F, Zador E (2004) The calcineurin activity and MCIP1.4 mRNA levels are increased by innervation in regenerating soleus muscle. Biochem Biophys Res Commun 320: 599–605.
  29. 29. Ryder JW, Bassel-Duby R, Olson EN, Zierath JR (2001) Skeletal muscle reprogramming by activation of calcineurin improves insulin action on metabolic pathways. J Biol Chem 278: 44298–44304.
  30. 30. Wu H, Rothermel B, Kanatous S, Rosenberg P, Naya FJ, et al. (2001) Activation of MEF2 by muscle activity is mediated through a calcineurin-dependent pathway. EMBO J 20: 6414–6423.
  31. 31. Yan Z, Serrano AL, Schiaffino S, Bassel-Duby R, Williams RS (2001) Regulatory elements governing transcription in specialized myofiber subtypes. J Biol Chem 276: 17361–17366.
  32. 32. Serrano AL, Murgia M, Pallafacchina G, Calabria E, Coniglio P, et al. (2001) Calcineurin controls nerve activity-dependent specification of slow skeletal muscle fibers but not muscle growth. Proc Natl Acad Sci U S A 98: 13108–13113.
  33. 33. Meissner JD, Gros G, Scheibe RJ, Scholz M, Kubis HP (2001) Calcineurin regulates slow myosin, but not fast myosin or metabolic enzymes, during fast-to-slow transformation in rabbit skeletal muscle cell culture. J Physiol 533: 215–226.
  34. 34. Wu H, Naya FJ, McKinsey TA, Mercer B, Shelton JM, et al. (2000) MEF2 responds to multiple calcium-regulated signals in the control of skeletal muscle fiber type. EMBO J 19: 1963–1973.
  35. 35. Olson EN, Williams RA (2000) Calcineurin signaling and muscle remodeling. Cell 101: 689–692.
  36. 36. Delling U, Tureckova J, Lim HW, De Windt LJ, Rotwein P, et al. (2000) A calcineurin-NFATc3-dependent pathway regulates skeletal muscle differentiation and slow myosin heavy-chain expression. Mol Cell Biol 20: 6600–6611.
  37. 37. Bigard X, Sanchez H, Zoll J, Mateo P, Rousseau V, et al. (2000) Calcineurin co-regulates contractile and metabolic components of slow muscle phenotype. J Biol Chem 275: 19653–19660.
  38. 38. Ojuka EO, Jones TE, Han DH, Chen M, Holloszy JO (2003) Raising Ca2+ in L6 myotubes mimics effects of exercise on mitochondrial biogenesis in muscle. FASEB J 17: 675–681.
  39. 39. Bassel-Duby R, Olson EN (2003) Role of calcineurin in striated muscle: Development, adaptation, and disease. Biochem Biophys Res Commun 311: 1133–1141.
  40. 40. Rosenberg P, Hawkins A, Stiber J, Shelton JM, Hutcheson K, et al. (2004) TRPC3 channels confer cellular memory of recent neuromuscular activity. Proc Natl Acad Sci U S A 101: 9387–9392.
  41. 41. Naya FJ, Mercer B, Shelton J, Richardson JA, Williams RS, et al. (2000) Stimulation of slow skeletal muscle fiber gene expression by calcineurin in vivo. J Biol Chem 275: 4545–4548.
  42. 42. Parsons SA, Wilkins BJ, Bueno OF, Molkentin JD (2003) Altered skeletal muscle phenotypes in calcineurin Aalpha and Abeta gene-targeted mice. Mol Cell Biol 23: 4331–4343.
  43. 43. Baar K, Wende AR, Jones TE, Marison M, Nolte LA, et al. (2002) Adaptations of skeletal muscle to exercise: Rapid increase in the transcriptional coactivator PGC-1. FASEB J 16: 1879–1886.
  44. 44. Lin J, Wu H, Tarr PT, Zhang CY, Wu Z, et al. (2002) Transcriptional co-activator PGC-1 alpha drives the formation of slow-twitch muscle fibres. Nature 418: 797–801.
  45. 45. Zong H, Ren JM, Young LH, Pypaert M, Mu J, et al. (2002) AMP kinase is required for mitochondrial biogenesis in skeletal muscle in response to chronic energy deprivation. Proc Natl Acad Sci U S A 99: 15983–15987.
  46. 46. Russell AP, Feilchenfeldt J, Schreiber S, Praz M, Crettenand A, et al. (2003) Endurance training in humans leads to fiber type-specific increases in levels of peroxisome proliferator-activated receptor-gamma coactivator-1 and peroxisome proliferator-activated receptor-alpha in skeletal muscle. Diabetes 52: 2874–2881.
  47. 47. Wang YX, Lee CH, Tiep S, Yu RT, Ham J, et al. (2003) Peroxisome-proliferator-activated receptor delta activates fat metabolism to prevent obesity. Cell 113: 159–170.
  48. 48. McGee SL, Hargreaves M (2004) Exercise and myocyte enhancer factor 2 regulation in human skeletal muscle. Diabetes 53: 1208–1214.