molecular epidemiology of physical activity and …molecular epidemiology of physical activity and...

Molecular Epidemiology of Physical Activity and Cancer

Andrew Rundle

Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York

Abstract

As in other areas of epidemiology, researchers studyingphysical activity and cancer have begun to includelaboratory analyses of biological specimens in theirstudies. The incorporation of these ‘‘biomarkers’’ intoepidemiology has been termed molecular epidemiologyand is an approach primarily developed to study chemicalcarcinogens. Thus far, there has been no discussion in thefield on how the established molecular epidemiologicframework might be adapted for research into physicalactivity, what methodologic needs exist, what the goals ofsuch an approach might be, and what limitations exist.This article relates the literature on molecular epidemiol-ogy to the needs of physical activity research and tries toset research priorities for the field as it moves in this newdirection. Although this approach will be very useful forinvestigating the mechanisms through which physical

activity exerts effects, there are several challenges forphysical activity epidemiologists in adapting molecularepidemiologic approaches. Primarily, there are currently noavailable biomarkers that might be considered measures ofexposure or biologically effective dose. In addition, mostavailable biomarkers of intermediate effects have beentested in training studies at activity levels much higherthan those seen in population-based epidemiologic studies.Thus, it is not clear whether these biomarkers are valid atlower activity levels. Furthermore, the nature of therelationship between activity and many available biomar-kers depends very much on the context of the activity.Addressing these issues should be a priority if we are todevelop a molecular epidemiologic paradigm for studyingphysical activity. (Cancer Epidemiol Biomarkers Prev2005;14(1):227–36)

Introduction

Although there is consistent epidemiologic evidence showinga protective effect of physical activity for some cancers,surprisingly little is known about the mechanisms throughwhich activity exerts its effects. It has been suggested thatbiomarker studies would be very useful in evaluating the roleof physical activity in cancer prevention (1-4). Biomarkers referto the measurement of biological parameters that reflect eventsalong the causal chain between exposure and disease (5).Although these calls to action have been met with generalapproval, there has not yet been a discussion of what types ofbiomarkers and what strategies would be most useful. Suchstudies would fall under the rubric of molecular epidemiology,an analytic paradigm originally developed for the investiga-tion of chemical carcinogens (5). Thus far, there has been nodiscussion of how this framework might be adapted forresearch into physical activity and cancer. This article will (a)review the molecular epidemiologic framework developed forchemical carcinogens, (b) review the rationale for conductingbiomarker studies of physical activity, (c) discuss the role suchstudies would play in the investigation of various cancers, and(d) explore how such studies would relate to currentlydeveloped molecular epidemiologic paradigms.

The Traditional Molecular Epidemiologic Paradigm

A premise of molecular epidemiology is that examination ofbiological parameters reflecting events along the causal chaincan provide insight into exposure-disease relationships (5, 6).The measures of these intermediate steps are referred to asbiomarkers. The traditional molecular epidemiologic para-

digm for investigations of chemical carcinogens classifiesbiomarkers according to their theoretical position andfunction on causal pathways (5, 6). These categories arebiomarkers of exposure, of biologically effective dose, ofaltered function or effect, and of susceptibility (6). In thisparadigm, biomarkers of exposure provide a measure ofhow much of a xenobiotic carcinogen has entered the body.For example, blood levels of 1,1-dichloro-2,2-bis(p-chloro-phenyl) ethylene, the major metabolite of 2,2-bis(p-chloro-phenyl)-1,1,1-trichloroethane (DDT), serve as a biomarker ofexposure to DDT in the food chain (7). Biomarkers ofbioeffective dose indicate how much of the dose entering thebody has escaped detoxification and reacted with amacromolecule target, such as DNA (6). Measures ofcarcinogen-DNA adducts, for example, are commonly usedas biomarkers of bioeffective dose (5, 8). Biomarkers ofaltered function or effect are used to measure the extent towhich normal cellular processes have been impacted byexposures. Common biomarkers of effect include mutationsin reporter genes, such as HPRT , or in tumor suppressorgenes, such as p53 (9, 10). Finally, biomarkers of suscepti-bility are measures of factors believed to intervene in, ormodify, the causal chain from exposure to disease. Commonexamples of susceptibility markers are polymorphisms ingenes responsible for xenobiotic metabolism, such asGSTM1 , or in genes responsible for DNA repair, such asXPD (11-14).

Figure 1 illustrates how these categories of biomarkersconceptually relate to each other and gives examples ofbiomarkers used in the study of aflatoxin exposure andhepatocellular carcinoma. These studies have includedmeasures of dietary aflatoxin intake (15, 16), aflatoxinmetabolites in urine samples (15), aflatoxin-albumin adducts(17), HPRT mutations in white blood cells (18), p53 mutationsin tumor sections (19), and GSTM1 genotype (16). Each of thebiomarker categories, except susceptibility, represents aconceptualized stage in the continuum from exposure todisease. Biomarkers of susceptibility are thought to act aseffect modifiers of exposure or as modifiers of the down-stream effects of exposure (20). To design valid molecular

Received 4/8/04; revised 6/30/04; accepted 7/20/04.

Grant support: National Cancer Institute Career Development AwardKO7-CA92348-01A1.

The costs of publication of this article were defrayed in part by the payment of page charges.This article must therefore be hereby marked advertisement in accordance with 18 U.S.C.Section 1734 solely to indicate this fact.

Requests for reprints: Andrew Rundle, Department of Epidemiology, Mailman School ofPublic Health, Columbia University, 722 West 168th Street, Room 730, New York NY 10032.Phone: 212-305-7619; Fax: 212-305-9413. E-mail:[email protected].

Copyright D 2005 American Association for Cancer Research.

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epidemiologic studies of physical activity, it must be decidedhow physical activity and related biomarkers fit into thisparadigm.

The Rationale for Biomarker Studies of PhysicalActivity

Molecular epidemiology was originally developed to crackopen the ‘‘black box’’ between exposures to xenobiotics andcancer. If anything, the relationship between physical activityand cancer represents a more opaque black box than therelationship between chemical exposures and cancer. Longbefore the advent of molecular epidemiology, it was under-stood that chemical carcinogens could form DNA adducts andcause mutations through various means (21-23). There is farless information on how physical activity exerts its effects andwhat type of intermediate events exist. Furthermore, physicalactivity patterns are likely to have complex associations withother determinants of cancer risk, such as diet, occupation, andsmoking. The lack of data on intermediate events and thelikely presence of confounding effects emphasize the need forbiomarker studies to generate mechanistic data to informcausal inference and guide future intervention studies.

For cancers for which traditional epidemiology has notprovided consistent data on the role of physical activity,biomarker studies could be used to test mechanistichypotheses and generate biological data useful in the processof causal inference. Furthermore, biomarker studies could beused to test and refine causal hypotheses, such asinvestigating associations with biomarker-defined subsets oftumors or by providing information on what components ofactivity may be important. For cancers for which traditionalepidemiology has already provided sufficient data todesignate causality, biomarkers studies could be used toelucidate the mechanisms through which activity exerts itsprotective effects. This would be useful in identifying newtargets for interventions. In addition, biomarkers would beuseful as surrogate outcomes in intervention trials to testvarious physical activity–based prevention programs.

Instances Where Traditional Epidemiologic Data AreInconclusive. For several cancers epidemiologic data are notconsistent or the observed effect is suspect because of thepresence of an overwhelming confounder. For example, thehypothesis that physical activity protects against prostatecancer has been investigated in over 30 studies. Fourteenstudies show a protective effect, 13 studies show no particulareffect, and 4 found an increased risk with activity (24-26).Clearly, the data assessing potential relationships betweenprostate cancer and physical activity are inconclusive.

Of 13 cohort analyses published on physical activity andlung cancer, 8 have found significant protective effects ofphysical activity (27-34), 4 observed protective effects that werenot statistically significant (35-37), and 1 observed a nonsig-

nificant increased risk of lung cancer with activity (35). Inaddition, two of four case-control studies on physical activityand lung cancer have found protective effects due to activity(38-41). In the two case-control studies that did not observeprotective effects, only occupational activity was studied,which was assessed by job title only (38, 39). However, theprimary concern with reports on lung cancer and physicalactivity is the overwhelming effect of cigarette smoking andthe likelihood that activity levels are associated with smokingbehavior. Most of the studies have had limited data onsmoking and activity levels, and so even after control forsmoking, residual confounding with smoking could stillexplain the observed protective effect of activity. Thus, thedata suggesting a protective effect of activity on lung cancerare considered inconclusive.

In instances in which traditional epidemiology is inconclu-sive or suspect, biomarkers downstream from physical activitycan be used to generate data relevant to causal inference.Mechanistic studies using biomarkers can examine whetherphysical activity acts as an antecedent to a known risk factor oras an effect modifier of a known disease process. An exampleof physical activity acting as an antecedent to a known riskfactor is the hypothesis that activity levels influence estrogenlevels, which in turn influence breast cancer risk (42, 43). As aneffect modifier, physical activity would modify the riskassociated with a known risk factor; that is, an exposurewould be hypothesized to be less harmful among activecompared with sedentary individuals. An example is thehypothesis that physically active smokers would have a lowerrisk of lung cancer than sedentary smokers because activityinduces protective antioxidant enzymes (43-45). Data demon-strating or refuting a hypothesized biological basis for aprotective effect would be useful in developing a causalunderstanding and addressing concerns regarding confound-ing. Likewise, such studies can determine whether activity islikely to be important at specific times in life or is onlyimportant for specific subtypes of the tumor in question. Suchdata could be then used to generate new or more refinedhypotheses that could be tested in population-based epidemi-ologic studies.

Instances Where Associations with Physical Activity AreGenerally Accepted. Sufficient data have been generatedthrough traditional epidemiologic approaches such that aprotective effect of physical activity on breast and colon canceris generally accepted (43, 46-48). For breast and colon cancer,epidemiologic studies that incorporate biomarkers would beuseful for determining the mechanisms through whichphysical activity exerts its effects. These studies could usebiomarkers as the outcome or could be etiologic studies thattest whether a biomarker is a causal intermediate that mediatesthe effect of activity on disease risk. Such studies would helpanswer remaining questions related to the type and extent ofactivity needed to elicit a protective effect, whether there arecritical time periods in which activity is important, and

Figure 1. Biomarker categories along the continu-um from exposure to cancer with examples from theliterature on aflatoxin and hepatocellular carcinoma.

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whether the effect of activity is modified by other factors. Thisinformation would be very important for designing effectiveintervention trials and creating population-based preventionprograms. Furthermore, the identification of the mechanisticpathway may provide us with new targets for intervention thatcan be effectively modified by means other than activity or inways that increase the effect of activity. In much the same waythat the identification of estrogen-related risk factors for breastcancer helped provide the rationale for tamoxifen chemo-prevention, the biological pathways that respond to physicalactivity may be amenable to pharmaceutical or other inter-ventions. From a public health perspective, the promotion ofphysical activity is preferable to developing a pill that replacesphysical activity. However, the development of pharmaceut-icals that target activity responsive pathways may be useful forcertain segments of the population, for instance, individualswith conditions that prevent them from engaging in therequired level of activity.

The use of biomarkers as surrogate end points in interven-tion trials would also greatly aid physical activity research (3,49). The use of validated intermediate biomarkers rather thanclinical end points as outcomes would expedite interventiontrials allowing for the efficient testing of hypotheses (49).Furthermore, studies that incorporate repeated biomarkermeasures and cross-over designs could be used to determinethe time course over which exercise exerts its effects. Inaddition, there are questions that cannot easily be answered byobservational designs and are better addressed in interventiontrials. For instance, an important question is, if activeindividuals have a lower risk of cancer, will sedentaryindividuals who become active gain the same protective effect(3)? Because most people do not commonly change theiractivity patterns, observational studies are not a powerful toolfor observing the effects of change (50). Another important rolefor intervention trials is to determine whether efficaciousprevention programs are palatable and sustainable in thecommunity and thus likely to be adopted. Changes in cancer-related biomarkers could be used to determine whether thosewho have adopted an exercise program actually engage inenough activity to affect cancer risk.

Currently the best example of an exercise intervention trialusing intermediate end points as the outcome is the PhysicalActivity for Total Health study being conducted by McTiernanand colleagues (51). In this study, 173 overweight, sedentary,postmenopausal women were randomized to receive anactivity intervention or weekly stretching session for a year.The intervention arm engaged in 45 minutes a day of moderateexercise, five times a week. During the first 3 monthsintervention arm participants attended three supervisedsessions per week at a study facility and exercised 2 days aweek at home. For the rest of the study period the interventionarm participants attended one supervised session per weekand exercised at home or a facility four times a week. Thecontrol arm attended one supervised stretching session aweek. The intervention was shown to reduce body weight,body fat, serum estrone, estradiol, and free estradiol (42, 52).Overall, the effects on serum hormones were statisticallysignificant after 3 months of intervention but not after 12months (42). The effects on serum hormones were primarilyobserved among women who lost body fat during theintervention, and in this subgroup the effects on estradioland free estradiol were significant after both 3 and 12 monthsof intervention (42).

Biomarkers of Exposure and Physical Fitness

In principle, physical activity can be conceptualized as anexposure existing outside of the black box. In the same way thatdata can be gathered on occupational, dietary, or tobacco-

related exposures, data on an individual’s activity levels can begathered. However, it is difficult to identify or even conceptu-alize appropriate biomarkers of exposure or biologicallyeffective dose for physical activity. In the realm of physicalactivity, there is no currently known biomarker akin to aflatoxinB1-albumin adducts, which serve as a biomarker of biologicallyeffective dose in studies of aflatoxin exposure (53, 54). Withinthe traditional molecular epidemiologic framework, bio-markers of exposure and biologically effective dose measure,respectively, the amount of an external exposure that hasentered the body and the amount of the exposure that interactedwith a macromolecular target (5, 6). The use of these biomarkersis thought to increase the validity of exposure assessment (6).These concepts do not translate well to the realm of physicalactivity. Physical activity does not represent an ambientexternal exposure, like a chemical component of air pollution,in which only a portion of the external dose is absorbed into thebody. For physical activity there is no conceptual discrepancybetween the external ambient concentrations and the dose thatenters the body. Thus, this rationale for using biomarkers ofexposure or biologically effective dose does not apply to studiesof physical activity. However, exposure-related biomarkers ofphysical activity would be useful in addressing other difficul-ties in measuring physical activity.

In instances in which exposures are ambient and unnoticed,or exposure assessment relies on a subject’s memory, the use ofbiomarkers of exposure or biologically effective dose isexpected to improve exposure assessment (6). In many ways,the measurement of physical activity fits this description. Forlarge-scale epidemiologic studies, the assessment of physicalactivity relies on questionnaires and thus on a study subject’smemory and subjective recall of the duration and intensity ofhis or her activity. In addition, although regular patterns oftraining or gym usage may be readily recalled, there areunnoticed and ambient types of activity that may haveimportant effects on health. For many people, activities ofdaily living, such as cleaning the house, transportation, ortaking care of children, may compose a large portion of theiractivity and differentiate them from truly sedentary individu-als. Thus, it is generally acknowledged that physical activity isoften poorly measured (43, 55). The current lack of suit-able exposure-related biomarkers means that one of the oftencited advantages of molecular epidemiology, improved mea-surement of exposure, will not be realized by adapting thisapproach to the study of physical activity.

Although not biomarkers in the traditional sense, it is worthconsidering the use of measures of physical fitness, such asaerobic capacity or resting pulse, as markers of activity.Although they certainly complement measures of activity,using measures of physical fitness to improve measurement ofphysical activity suffers from several drawbacks. Fitness andphysical activity represent different constructs that are notinterchangeable and one is not a more refined measure of theother. Fitness is a performance characteristic defined as ‘‘theability to carry out daily tasks with vigor and alertness, withoutundue fatigue, and with ample energy to enjoy leisure-timepursuits and to meet unforeseen emergencies’’ (56). Fitnessincludes health-related aspects, such as cardiorespiratoryendurance and body composition, and skill-related aspects,such as balance and speed (56). Physical activity is a behaviordefined as ‘‘bodily movement produced by skeletal musclesthat results in energy expenditure’’ (56). Thus, the use of fitnessas a biomarker of activity may negatively affect the constructvalidity of studies seeking to understand the role of physicalactivity. Activity among nonfit subjects can have importanthealth benefits potentially relevant to cancer. For example, inrelation to obesity and type II diabetes, overweight/obeseindividuals who increase physical activity can reduce insulinresistance even in the absence of concurrent weight loss (57-60).

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Similarly among the nonobese, physical activity done at levelsinsufficient to influence body mass or maximal oxygen uptakecan still improve insulin action (61). It has been hypothesizedthat insulin resistance plays a role in the development ofpancreatic cancer and underlies observed associations betweenphysical activity, obesity, and pancreatic cancer (62-64). Astudy of pancreatic cancer that solely uses measures of fitnessas a marker of activity may yield inappropriate conclusionsabout activity.

Clearly, the current lack of biomarkers that can beconceptualized as measures of exposure or the biologicallyeffective dose of physical activity means that the use ofmolecular epidemiologic approaches will not improve themeasurement of physical activity. If the benefits of bringingmolecular epidemiologic techniques to the study of physicalactivity are to be fully realized, the development of suchbiomarkers should be a research priority.

Biomarkers of Effect, Altered Function, andSusceptibility

Due to the lack of biomarkers of exposure to physical activity,most of the biomarkers suggested for use in molecularepidemiologic studies of physical activity are best conceptual-ized as biomarkers of effect, altered function, or susceptibility.Biomarkers of effect and altered function are defined as‘‘processes that are intermediate between exposure anddisease’’ or as ‘‘early biological or biochemical changes in thetarget tissue that result from the action of the carcinogen and arethought to be either a step in the carcinogenic process orcorrelate closely with that process’’ (5, 6). Biomarkers ofsusceptibility represent processes that are thought to modifythe effects of an exposure that causes cancer. Table 1 showsexamples from the literature of proposed mechanisms throughwhich physical activity might exert its effects and relevantbiomarkers that could be incorporated into studies. Figure 2shows how these proposed mechanisms are thought to relate tothe stages of carcinogenesis. For studies of physical activity,

these biomarkers either represent a hypothesized risk factor fordisease or factors that modify the effects of other risk factors orexposures. That is, physical activity may represent an anteced-ent exposure that influences a previously identified risk factoror represents an antecedent to a susceptibility factor thatinteracts with a disease pathway. The correct specification of abiomarker influenced by physical activity as a risk factor on thedisease path or as an effect modifier of the disease process iscritically important. In the molecular epidemiologic literatureon chemical carcinogens, confusion regarding the relationshipof antecedent and effect modifying biomarkers has led to themisinterpretation of several important data sets (20).

Hormone levels are an example of a biomarker of effect thatare thought to be influenced by physical activity and arethemselves a hypothesized causal factor of disease (43). It isthought that high androgen levels cause prostate cancer andhigh estrogen levels cause breast cancer (1, 43). Physicalactivity has been hypothesized to protect against these twocancers by influencing the levels of these hormones (1, 43). In acohort study that has stored blood samples, one could assessthe extent to which lower hormone levels mediate anyassociation between physical activity and breast cancer.Physical activity can thus be integrated into molecu-lar epidemiologic models for these cancers, as shown in Fig. 3.

If indeed causal, the observed protective effect of physicalactivity on lung cancer is likely to occur because physicalactivity in some manner reduces the effect of cigarette smokecarcinogens. In this case, physical activity would be concep-tualized as a susceptibility factor that acts as an effect modifier.Causal models representing effect modification could bediagrammed as shown in Fig. 4. For instance, it has beenhypothesized that physical activity increases the body’sdefenses against oxidative stress and carcinogens (43, 44, 82,83) and thus may protect the lung against reactive oxygenspecies and carcinogens in cigarette smoke (see Fig. 5). Such acausal model could be tested by assessing the impact ofphysical activity on glutathione peroxidase or catalase activity(biomarkers of endogenous oxidative defenses) and levels of 8-oxodeoxyguanosine, a biomarker of oxidative DNA damage.

Table 1. Physical activity responsive pathways and related biomarkers

Potential physical activity responsive pathways Potential biomarkers

Immune function Number and activity of natural killer cells (65, 66)Lymphocyte cytolytic activity (67)Interleukin 1 (67)Tumor necrosis factor a

Growth factors and growth factor binding proteins Insulin-like growth factor I (2)Insulin-like growth factor binding protein I and III (2)Platelet-derived growth factor (2)

Sex hormones and binding proteins Estradiol (2, 42)Estrone (2, 42)Testosterone (2)Sex hormone– binding globulin (2, 42)

Endogenous antioxidant enzyme systems Glutathione system: glutathione peroxidase,glutathione reductase, glutathione (68-75)

Catalase (70, 71, 73)Superoxide dismutase (69-71,73)Glutathione S-transferase (72)

Oxidative stress Plasma thiobarbituric acid reactive substances (69, 70, 76)8-Hydroxydeoxyguanosine (77, 78)Single-cell gel electrophoresis assay (79)

DNA repair Human 8-oxoguanine DNA glycosylase (80)Human MutT homologue (81)

Phase II xenobiotic enzyme Systems UDP-glucuronosyl transferase (45)Glutathione S-transferase (45, 72)




In the case of colon cancer, physical activity has beenhypothesized to decrease the transit time of food through thecolon, reducing mucosal exposure to dietary carcinogens (43).This mechanism could be investigated by testing whetherphysical activity is associated with lower levels of heterocyclicamine adducts in individuals with diets high in broiled meats(84). Again, in this example, physical activity is conceptualizedas a susceptibility factor that induces a process that lowers therisk associated with a presumed causal exposure. In epidemi-ologic terms, physical activity is hypothesized to be an effectmodifier that reduces the main effects of an exposure.

The relationship between many of these proposed bio-markers and activity can be complex. Several of these markersseem to have U- or J-shaped dose-response curves in relationto activity (85, 86). Furthermore, differential effects have beennoted that seem to depend on whether the activity is acute orchronic, is done by trained or untrained individuals, and is ofmoderate or exhaustive intensity (2, 85, 87, 88). For instance,single bouts of intense exercise lead to the generation of

reactive oxygen species and DNA damage (79, 89, 90).However, regular exercise seems to cause an adaptiveresponse that induces endogenous antioxidant enzyme sys-tems and lowers oxidative stress (70, 77-81). Miyazaki andcolleagues showed that bouts of exhaustive exercise causedincreased lipid peroxidation, indicative of increased oxidativestress (70). However, training increased glutathione peroxidaseand superoxide dismutase activity and reduced the levels oflipid peroxidation caused by bouts of exhaustive exercise (70).In regard to immune function, strenuous bouts of activity havebeen associated with immune suppression as measured byincreased upper respiratory infections and by reductions innatural killer cell counts and activity (86, 91). However,moderate exercise training seems to reduce the risk of upperrespiratory tract infections (66, 86), and this effect may be dueto increases in salivary IgA levels seen with training (92).Likewise several studies have found increases in natural killercell count and activity associated with programs of exercisetraining (65, 66, 93-95). Similarly cross-sectional analyses of

Figure 2. Points at which proposed mechanism for the effects of physical activity interact with the stages of carcinogenesis. A number ofmechanisms have been proposed to explain the protective effect of physical activity. The figure diagrams how these mechanisms may impactthe stages of carcinogenesis. It has been suggested that physical activity can increase detoxification of chemical carcinogens and reactiveoxygen species, theoretically reducing exposure-induced DNA damage. There is also evidence that physical activity can increase DNA repairactivity, which in turn would reduce DNA damage and prevent initiation. Physical activity has also been suggested to reduce some growthfactor levels, which would reduce proliferation-induced replication errors and thus reduce initiation. In addition, lower levels of growth factorswould be expected to reduce the promotion of otherwise initiated cells. Likewise, increased hormone levels are thought to influence cancerrisk through a number of effects: (a) metabolic redox cycling of catecholestrogens leads to oxidative stress and DNA damage, (b) estrogen-quinones can form DNA adducts, (c) hormone-induced proliferation can lead to replication errors and initiation, and (d) hormone-inducedproliferation can promote otherwise initiated cells. Lastly, physical activity is thought to improve immune function, which can combat tumorgrowth.

Figure 3. Examples of physical activity as an antecedentto know or hypothesize risk factors for cancer.




sedentary elderly adults and regularly exercising elderlyadults have found higher natural killer cell counts amongexercisers (96). A firm understanding of the nature of the dose-response curve and its modification by the context of exerciseis important for modeling the effect of activity on intermediatebiomarkers and on disease outcome.

As with other areas of research in carcinogenesis, physicalactivity researchers are starting to study gene and proteinexpression with microarray technology, and such data mayuseful for identifying biomarkers of effect (97-99). At thistime, the literature on human studies is quite limited. In astudy of muscle aging, Roth and colleagues used musclebiopsies to assess the expression of f4,000 genes in responseto strength training (98). In total, 69 genes showed alteredexpression in response to a 9-week strength-training program,and the majority of changes represented down-regulation.Connolly and colleagues have studied circulating peripheralblood mononuclear cells and shown alterations in expressionfor 311 genes after a single bout of heavy exercise (99). Up-regulated genes included those related to stress, inflamma-tion, growth and repair (99). At this time, however, it isunclear how an individual’s global patterns of gene expres-sion might be incorporated into traditional epidemiologicdesigns. But work such as those of Roth and colleagues andConnoly and colleagues could identify new candidate geneswhose expression might serve as useful biomarkers of effect.As with other biomarkers, the dose response between activityand gene expression is unknown, and it is unclear how other

methodologic issues such as multiple comparisons, individualvariability, and measurement error affect microarray results(99, 100). Still, gene and protein expression studies are likelyto be useful for understanding the effects of physical activity.

Strategies for the Use of Biomarkers in Studies ofPhysical Activity

The molecular epidemiologic literature regarding chemicalcarcinogens has made the distinction between etiologicinvestigations and transitional studies (101). This distinctionis also useful for developing a molecular epidemiologicapproach to the investigation of physical activity.

Transitional Studies. Transitional studies are defined asstudies that ‘‘bridge the gap between laboratory experimenta-tion and population-based epidemiology’’ (101). Such studieshave one of several goals: to validate biomarkers so that theycan be used in population-based studies; to determine sourcesof intersubject variability, thus identifying potential confound-ers, antecedents, or effect modifiers; to evaluate the feasibilityof using the marker in the field; to investigate proposedmechanistic pathways; and to define exposure-effect relations(101). In general, transitional studies treat the biomarker ofinterest as the outcome. The majority of molecular epidemio-logic studies of chemical carcinogens that utilize intermediatebiomarkers, such as carcinogen-DNA adducts, are transitionalin nature. There are, in contrast, relatively few studies that

Figure 4. Physical activity as an antecedent to asusceptibility factor that modifies a disease process.

Figure 5. Theoretical model for the role of physicalactivity as a susceptibility factor in smoking-relatedcancers.




have assessed the association between intermediate bio-markers and disease (15, 17, 102, 103).

There is a particular need for transitional studies of physicalactivity and biomarkers. Most studies linking physical activityto a biomarker, usually of biological effect, have occurredwithin the realm of sports physiology or clinical experimentsand have been in the context of high activity levels. Forinstance, Evelo and colleagues trained 23 men and 18 womento run a half-marathon and observed training-related increasesin glutathione reductase levels, glutathione, and glutathione S-transferase activity (72). Likewise, increases in immunefunction have been noted in comparisons between sedentaryand actively training individuals (104).

It is important to recognize that epidemiologic studies linkingphysical activity and reduced cancer risk have noted effects atactivity levels far lower than typically used in exercisephysiology experiments. It is not clear whether biomarkerresponses seen at high activity levels are relevant to associationsseen in the epidemiologic literature. Furthermore, the smallsample sizes common in these studies prevent consideration ofpotential confounders and effect modifiers that may beimportant to consider in large epidemiologic studies. Anexample of the discrepancies that can arise between smallclinical studies conducted at high training levels and largepopulation-based studies can be seen in the cardiovascularliterature. Several small, clinical training studies haveobserved associations between training and blood lipidprofiles (105-108). However, a large population-based studyonly observed strong associations between activity levels andblood lipid levels when an interaction with the ApoE4genotype was taken into consideration (109).

A greater focus on large-scale cross-sectional studies ofphysical activity and biomarkers of effect are warranted toconfirm that biological effects seen in training studies arerelevant to the lower activity levels typical of population-basedepidemiologic studies. Such studies will be useful in identify-ing potential confounders and effect modifiers that should beconsidered in etiologic studies. For instance, some of the effectsof training on the antioxidant glutathione system seen in smallclinical studies have been verified in larger scale studies of thegeneral population (110-112). These larger studies have alsoidentified other important correlates of improved antioxidantglutathione status, such as cigarette smoking, body massindex, and gender, factors likely to be associated with activity(110-112). Also of interest are multitiered studies in whichmultiple markers along a proposed causal chain are assessed.Taking the example of physical activity and antioxidantenzymes a step further, it would be of interest to assesswhether physical activity levels and increased antioxidantenzyme activity were associated with lower levels of oxidativeDNA damage. Statistical analyses could determine whethervariation in antioxidant enzyme activity mediated any inverseassociation between physical activity levels and oxidativeDNA damage.

One perceived weakness of larger scale studies of thegeneral population is that activity levels are likely to beassessed using questionnaires (55), whereas more objectivemeasures, such as accelerometers or pedometers, may only befeasible for smaller studies (113, 114). Generally, question-naires are hampered by measurement error, and, furthermore,older questionnaires lacked content validity, focusing only onselected recreational activities and not considering occupa-tional or home activities (43, 55). Poor questionnaire reliabilityreduces the ability of a study to identify relationships (55, 115).However, despite these issues, questionnaire-based studieshave revealed important relationships between activity andcertain cancers (2, 30, 43). Because the relationship betweenquestionnaire data and a causal intermediate is likely to bestronger than the relationship between questionnaire data anddisease, questionnaire data are likely to provide sufficient

information for larger scale transitional studies that usebiomarkers as the outcome (20).

Etiologic studies. Etiologic studies include measures ofdisease outcome, and optimally would assess measures ofactivity and activity-related biomarkers of effect representinghypothesized mechanisms through which physical activityexerts its effects. In light of the large number of proposedmechanisms through which physical activity might exert itseffects, it is important that these biomarkers have previouslybeen validated and tested in transitional studies. The optimaldesign would be a case-cohort or nested case-control studyconducted within a cohort study that collected baseline bloodsamples. Population or hospital-based case-control studies areproblematic because in these designs blood samples arecollected from cases at the time of or after diagnosis. Diseasestatus may influence biomarker levels and/or may influencerecent activity patterns that, in turn, could influence biomarkerlevels (116).

The European Prospective Investigation of Cancer andNutrition (EPIC) is an excellent example of a study in whichmolecular epidemiologic studies of physical activity can benested (117). Baseline blood samples are available forbiomarker analyses, as are data on physical activity andimportant potential confounding factors, such as dietarypractices and smoking (117, 118). An appropriate strategywould be to conduct a nested case-control study of a particularcancer within the EPIC cohort and to analyze stored samplesfor a biomarker of interest. Given the lack of exposure-relatedbiomarkers, biomarkers of effect would be the most likelycandidates for such a study. The biomarker should be wellcharacterized as being activity responsive and should repre-sent a mechanism through which activity is hypothesized toexert its effect. The data would then be analyzed to determinewhether the biomarker mediates the association betweenactivity and disease. In this example, sedentary behavior isthought of as the primary ‘‘exposure’’ of interest and as anantecedent to a biological mechanism that causes cancer.Alternatively, physical activity could be hypothesized to be asusceptibility factor that modifies the effect of anotherexposure. Under this hypothesis, an appropriate strategywould be to test for an interaction between the activity-relatedbiomarker and the primary exposure of interest. For instance,one could test for an interaction between smoking history andan immune function marker that is thought to be positivelyinfluenced by physical activity.

Biomarkers would also be useful in etiologic studies todefine more etiologically homogeneous subgroups of cancersthat may be more strongly associated with physical activity(119). That is, specific molecular characteristics of tumors,such as p53 mutation or estrogen receptor expression, maydefine a subset of cancers linked to a specific exposure byvirtue of the exposure having caused the mutation orexpression of that marker (119-121). Alternatively, tumorsnot expressing the marker in question may have been causedby other exposures. If indeed an exposure is associated onlywith a particular subset of a cancer diagnosis, for instance,estrogen receptor–positive breast cancer, studies that includeall breast cancers would underestimate the effect of theexposure or even fail to find the association. Biomarkersmeasured in tumors can be used to test hypotheses regardingetiologic heterogeneity in either the case-only study design orin a case-control or cohort study using a polytomous outcomevariable (119).

Enger and colleagues have used this strategy to studyphysical activity, body size, and breast cancer (121). Both ofthese risk factors have been hypothesized to act through ahormone-related pathway. Thus, it was hypothesized thatobesity and a lack of physical activity would be associatedwith increased risk of estrogen receptor (ER) and progesteronereceptor (PR) positive tumors, but not ER�/PR� tumors (121).




For postmenopausal breast cancer they found increasing bodymass index to be associated with case-control status onlywhen ER+/PR+ cases were compared with controls. However,they found the protective effect of physical activity did notvary by ER/PR status. Thus, ER/PR status defined etiologicheterogeneity with respect to body mass index, but not withrespect to physical activity, suggesting a sex hormone–relatedcausal pathway for body mass index only. Similarly, Gammonand colleagues have used polytomous logistic regression toassess whether the protective effect of physical activity differsby p53 status in tumor tissue (120). Again in this example thebiomarker did not define tumor subgroups that wereetiologically heterogeneous with regard to activity levels.

Conclusion

Molecular epidemiology was developed to address thechallenges of linking xenobiotic exposures to cancer devel-opment. There is a great hope that adapting these approachesto the study of physical activity and cancer will aid inelucidating new associations, identifying mechanistic path-ways, and validating prevention programs. A primary utilityof biomarker studies will be to illuminate the mechanismsthrough which activity exerts its effects. The elucidation ofthese mechanisms will hopefully provide new targets for life-style or pharmaceutical interventions that may more effi-ciently modulate these pathways, producing a greaterpreventive effect than physical activity. This is analogous tohow the identification of reproductive risk factors for breastcancer led to investigations of the role of reproductivehormones, which then helped provide a rationale for theuse of chemopreventive agents that target reproductivehormone–related pathways. Another utility will be the useof biomarkers to refine causal hypotheses and potentiallyuncover relationships between physical activity and cancerthat have thus far been hidden. Of particular interest is thepossibility that sedentary life-styles might only be associatedwith particular subtypes of cancers and that these subtypesmay be identifiable by biomarkers measured in tumorsamples. Biomarkers may also be very useful as intermediateoutcomes in intervention trials, increasing the rate at whichintervention strategies can be tested.

However, there are several challenges to applyingmolecular epidemiologic approaches to the study of physicalactivity and cancer that must be surmounted before thesehopes can be fulfilled. A primary challenge is the currentlack of biomarkers of exposure or biologically effective dosefor physical activity. Without major developments in thisarea, the application of molecular epidemiologic approacheswill not solve the difficult measurement issues inherent inphysical activity research. An additional challenge isdefining the relationship between physical activity andbiomarkers of effect, altered function, and susceptibility.Many of the dose-response curves do not appear to belinear, and for many biomarkers, the effects of acute bouts ofexhaustive activity differ from the effects of trainingor an overall active life-style. An understanding ofthese issues is critical for statistical analyses of whether aparticular biomarker acts as a mediating factor be-tween physical activity and cancer development. A greatdeal of work is also required to show that biomarkers re-sponsive to activity in intense exercise physiology studiesare also responsive to lower levels of activity actuallyachievable by the general population. This process mustalso consider the wide range of possible confounding andeffect-modifying factors that might impact the biomarker butwhich are rarely considered in small exercise physiologystudies. Addressing these issues should be a prominentcomponent of the physical activity and cancer researchagenda for the coming years.

AcknowledgmentsI thank Drs. Neugut, Vineis, Ahsan, and Halim and Ms. Campbell fortheir thoughtful comments on the manuscript.

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