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Variants of the Ankyrin Repeat Domain 6 Gene (ANKRD6) and Muscle and Physical Activity Phenotypes Among European-Derived American Adults

Van Deveire, Katherine N.1; Scranton, Sarah K.1; Kostek, Mathew A.1; Angelopoulos, Theodore J.2; Clarkson, Priscilla M.3; Gordon, Paul M.4; Moyna, Niall M.5; Visich, Paul S.6; Zoeller, Robert F.7; Thompson, Paul D.8; Devaney, Joseph M.9; Gordish-Dressman, Heather9; Hoffman, Eric P.9; Maresh, Carl M.1; Pescatello, Linda S.1

The Journal of Strength & Conditioning Research: July 2012 - Volume 26 - Issue 7 - p 1740–1748
doi: 10.1519/JSC.0b013e31825c2bef
Original Research

Van Deveire, KN, Scranton, SK, Kostek, MA, Angelopoulos, TJ, Clarkson, PM, Gordon, PM, Moyna, NM, Visich, PS, Zoeller, RF, Thompson, PD, Devaney, JM, Gordish-Dressman, H, Hoffman, EP, Maresh, CM, and Pescatello, LS. Variants of the ankyrin repeat domain 6 gene (ANKRD6) and muscle and physical activity phenotypes among European-derived American adults. J Strength Cond Res 26(7): 1740–1748, 2012—Ankyrin repeat domain 6 (ANKRD6) is a ubiquitous protein that associates with early development in mammals and is highly expressed in the brain, spinal cord, and heart of humans. We examined the role of 8 ANKRD6 single-nucleotide polymorphisms (SNPs) on muscle performance and habitual physical activity (PA). Single-nucleotide polymorphisms were 545 T>A (rs9362667), 485 M>L (rs61736690), 233 T>M (rs2273238), 128 I>L (rs3748085), 631 P>L (rs61739327), 122 Q>E (rs16881983), 197805 G>A (rs9344950), and 710 L>X (NOVEL). This study consisted of 922 healthy, untrained, European-derived American men (n = 376, 23.6 ± 0.3 years, 25.0 ± 0.2 kg·m−2) and women (n = 546, 23.2 ± 0.2 years, 24.0 ± 0.2 kg·m−2). Muscle strength (maximum voluntary contraction [MVC] and 1 repetition maximum [1RM]) and size (cross-sectional area [CSA]) were assessed before and after 12 weeks of unilateral resistance training (RT). A subsample (n = 536, 23.4 ± 0.2 years, 24.6 ± 0.2 kg·m−2) completed the Paffenbarger Physical Activity Questionnaire. Associations among ANKRD6 genotypes and muscle phenotypes were tested with repeated measure analysis of covariance (ANCOVA) and PA phenotypes with multivariate ANCOVA, with age and body mass index as covariates. ANKRD6 122 Q>E was associated with increased baseline biceps CSA. ANKRD6 545 A>T and ANKRD6 710 L>X were associated with increased 1RM and MVC in response to RT, respectively. ANKRD6 631 P>L was associated with increased biceps CSA response to RT and time spent in moderate-intensity PA among the total sample and women. ANKRD6 genetic variants were associated with the muscle size and strength response to RT and habitual PA levels. Further research is needed to validate our results and explore mechanisms for the associations we observed.

1Department of Kinesiology, Human Performance Laboratory, School of Allied Health, University of Connecticut, Storrs, Connecticut

2Department of Health Professions, Center for Lifestyle Medicine, University of Central Florida, Orlando, Florida

3Department of Kinesiology, University of Massachusetts, Amherst, Massachusetts

4Laboratory for Physical Activity and Exercise Intervention Research, University of Michigan, Ann Arbor, Michigan

55Department of Sport Science and Health, Dublin City University, Dublin, Ireland

6Human Performance Laboratory, Central Michigan University, Mount Pleasant, Michigan

7Department of Exercise Science and Health Promotion, Florida Atlantic University, Davie, Florida

8Division of Cardiology, Henry Low Heart Center, Hartford Hospital, Hartford, Connecticut

9Department of Integrative Systems Biology, Research Center for Genetic Medicine, Children's National Medical Center, Washington, DC

Address correspondence to Dr. Linda S. Pescatello,

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Ankyrin repeat domain 6 (ANKRD6) is a modular protein located on chromosome 6 (q14.2-q16.1). It is a member of the ankyrin repeat domain protein family that mediate physiologically important protein-protein interactions and act as adapters of signaling pathways (2). Tissir et al. (30) found that ANKRD6 is expressed prominently in zones of neuronal proliferation in the developing brain of mice. ANKRD6 also plays a role in signaling pathways that regulate crucial events in the development of vertebrates and invertebrates, including body axis formation in Xenopus and zebrafish embryos (24) and heart development in zebrafish embryogenesis (15). Thus, it appears biologically plausible that the ANKRD6 gene regulating function of the ANKRD6 protein would also have an important role in neural development, axis formation, and cardiogenesis of humans, and subsequently, muscle performance and habitual physical activity (PA) participation through centrally and peripherally mediated pathways (15,24,30). However, to our knowledge, the influence of ANKRD6 on neural, gastric, and heart development and its influence on muscle performance and habitual PA in humans have not been studied.

Our group (5) has documented considerable variability in the muscle strength and size response to a 12-week standardized resistance training (RT) program with muscle strength and size gains varying between 5–150% and 5–40%, respectively. In addition, it is estimated that 35–85% of RT strength gains are due to inheritance that appears to account for a significant portion of the variability in the muscle strength and size response to RT (19,27,28). Twin studies show habitual PA also have a significant genetic component, explaining 32–85% of the variation in adult PA levels (3,8,25). A recent advancement in the field of exercise genomics is the realization that the genetic basis of muscle performance and PA is accounted for by a large number of genes that play a small role rather than a small number of genes with large effects (3,25,26).

The purpose of our study was to explore the influence of ANKRD6 genetic variants on the muscle size and strength response to a RT program and habitual PA among a large homogenous sample of healthy, European-derived American adults undergoing a 12-week, standardized, unilateral upper arm RT regimen from the Functional Single-Nucleotide Polymorphisms (SNPs) Associate with Muscle Size and Strength Study (FAMuSS) (13,21,29). Given the known role of ANKRD6 on neural development, axis formation, and cardiogenesis, we hypothesized that ANKRD6 genetic variants would influence these muscle and PA phenotypes.

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Experimental Approach to the Problem

This study was a subset of a larger study designed to uncover novel nonsynonymous SNPs that associate with muscle size and strength phenotypes, that is, FAMuSS (13,21,29). The largest candidate gene association RT study conducted to date is FAMuSS. This multicenter study was conducted by the Exercise and Genetics Collaborative Research Group at 10 different institutions.

A detailed description of the experimental design of FAMuSS has been presented previously (9,13,21,29) and is described briefly for the reader here. Study volunteers were recruited from 8 of the 10 sites to complete a 12-week progressive RT program aimed at increasing strength and size of the elbow flexors and extensors of the nondominant arm only. Isometric (maximum voluntary contraction [MVC]) and dynamic (1 repetition maximum [1RM]) strength and cross-sectional area (CSA) by magnetic resonance imaging (MRI) were assessed pre- and post-RT. Blood samples for genotyping were taken before RT.

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Participants were European-derived American adults aged 18 to 40 years or younger from the FAMuSS cohort who were genotyped for 8 ANKRD6 genetic variants. FAMuSS exclusion criteria are described in detail elsewhere (9,29). The study protocol was approved by the institutional review board at each site, and all subjects gave written informed consent before the start of the study.

The FAMuSS subsample for the RT portion of this study consisted of 922 healthy, young (23.3 ± 0.2 years), normal weight (24.4 ± 0.2 kg·m−2) European-derived American men (n = 376) and women (n = 547). Age did not differ significantly by sex (p = 0.267), yet men had greater body mass than women (25.0 ± 0.2 vs. 24.0 ± 0.2 kg·m−2, p = 0.001). The FAMuSS subsample for the Paffenbarger Physical Activity Questionnaire (PPAQ) portion of this study (n = 536; 23.4 ± 0.2 years, 24.6 ± 0.2 kg·m−2) consisted of 242 men and 294 women. Although age did not differ by sex (p = 0.254), men were overweight and had greater body mass than women (25.3 ± 0.3 vs. 23.9 ± 0.3 kg·m−2, p = 0.001).

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Physical Activity Determination

Habitual PA was determined through completion of the PPAQ, which has been validated in numerous studies as an accurate and reliable measure of adult leisure time PA (16). The PPAQ was completed by a subsample of FAMuSS subjects (n = 536) during their initial visit. Physical activities with a metabolic equivalent (MET) value of >6 were classified as vigorous intensity, 3 to ≤6 METs as moderate intensity, and <3 METs as low intensity (18). The following PA phenotypes were derived from the PPAQ: distance walked (miles per week), PA index (kilocalories per week), and energy expended in vigorous, moderate, light-intensity PA and sitting and sports and recreation (kilocalories per week) (16). Additional PA phenotypes included time (hours per week) spent in vigorous, moderate, and light-intensity PA and sitting (17).

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Anthropometric Measurements

Body weight (in pounds) and height (in inches) were assessed pre- and post-RT to calculate body mass index (BMI) (kilogram per square meter). Subjects were instructed to maintain their usual diet throughout the duration of the study. Body weight was measured every 3 weeks during the study to ensure weight stability (defined as ±5.0 lb pre-RT weight).

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Isometric Strength Testing (Maximum Voluntary Contraction)

Maximum voluntary contraction of the elbow flexors was assessed pre- and post-RT using a custom-made preacher curl bench and strain gauge (model 32628CTL; Lafayette Instrument Company, Lafayette, IN, USA). Each MVC attempt began with a verbal cue from the tester. Subjects gradually increased to a maximal effort sustained for 3 seconds with 1-minute rest between contractions. The test session was completed once 3 attempts were within 2.2 ft·kg−1 of each other or a maximum of 6 attempts had been made. The closest 3 measurements were averaged and recorded in kilograms. The investigator who administered the baseline MVC test also administered the post-RT MVC test.

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One Repetition Maximum Strength Testing

Dynamic strength of the elbow flexors of each arm was assessed pre- and post-RT. Participants were tested on a standard preacher curl bench (Yukon International, Inc., Cleveland, OH, USA) using Powerblock adjustable dumbbells (Intellbell, Inc., Owatonna, MN, USA) in increments of 1.1 and 2.2 kg. To start the assessment, the investigator verbally instructed the subject to perform one full repetition of full range of motion at 100% of estimated maximum weight. If the lift was unsuccessful, a 3-minute rest was given and the weight was decreased. If the lift was successful, a 3-minute rest was given and the weight was increased. This process was repeated until subjects failed to complete a full lift. Weights were used so that the 1RM could be completed in 3–5 attempts. The 1RM was recorded as the maximum weight lifted one time. The same investigator who administered the baseline 1RM test also administered the post-RT 1RM test.

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Muscle Cross-sectional Area Measurements

The MRI measurements to determine CSA have been described in detail elsewhere (29) and are briefly overviewed here. The CSA of each arm's biceps brachii muscle was determined using an MRI operated at 1.5 T. Measurements were taken before RT and within 48–96 hours of the final RT session. Subjects laid supine on the scanning bed with their arm aligned to the isocenter of the magnet and the point of measure centered to the alignment light of the MRI. Fifteen axial slices were taken over 24 cm beginning proximally and proceeding distally.

Images taken via MRI from each investigative site were saved via magnetic optical disk or CD-ROM in a DICOM format and sent to the central imaging facility for analysis. The same investigator analyzed the images using a custom-designed program created to function within MATLAB (The MathWorks, Inc., Natick, MA, USA). Cross-sectional area was determined by multiplying the number of pixels within the defined area by a preset CSA value of 0.01 cm2 determined from the MRI matrix and field of view.

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Resistance Training Program

A unilateral, 12-week upper arm RT program was chosen to minimize possible confounding effects of activities of daily living on the muscle size and strength response to RT (25). Subjects underwent 12 weeks of a gradually progressive supervised RT regimen of their nondominant arm only. Training sessions occurred twice weekly, with each session separated by a minimum of 48 hours. Exercises included biceps preacher curls, biceps concentration curls, standing biceps curls, overhead triceps extensions, and triceps kickbacks. Each RT session began with a warm-up consisting of 2 sets of 12 repetitions of the biceps preacher curls and overhead triceps extensions. A 3-minute rest followed each warm-up set. Subjects then performed 3 sets of 12 repetitions at 65–75% of their 1RM for each of the 5 exercises listed above. A 2-minute rest followed each set. At week 5, the number of repetitions was decreased to 8 and then to 6 at week 10. Thus, the exercise intensity at weeks 5 and 10 increased to 75–82% 1RM and 83–90% 1RM, respectively. All exercises were performed with Powerblocks, and some exercises also used the preacher curl bench. All training sessions were supervised and lasted approximately 45–60 minutes.

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Fasting venous blood samples were collected from all subjects at the start of the study. Samples were sent in EDTA-containing vacutainer tubes to the coordinating site (Children's National Medical Center, Washington, DC, USA) with all subject identification information removed. DNA was isolated from each blood sample using the Gentra Puregene Blood DNA Purification Kit (Qiagen, Valencia, CA, USA). Genotyping was performed using Applied Biosystem's TaqMan allele discrimination assay using standard thermal cycling conditions, with genotypes called by the 7900HT Real-Time PCR System (Applied Biosystems, Foster City, CA, USA). If available, the Applied Biosystem Assay ID for each SNPs is listed in Table 1.

Table 1

Table 1

Subjects were genotyped for each SNP listed in Table 2 using 2 separate polymerase chain reaction–based methods to assure accuracy with the novel TaqMan allelic discrimination and restriction enzyme assays (Table 3). A complete description of the genotyping methods used in this study can be found in previously published literature (13,21,29).

Table 2

Table 2

Table 3

Table 3

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Statistical Analyses

All analyses included only subjects who completed the study and were genotyped for ANKRD6 genetic variants. Descriptive statistics and frequencies were calculated for study variables. The χ2 test was used to determine whether the ANKRD6 genotype was in Hardy-Weinberg equilibrium for white populations (Table 4). All ANKRD6 SNPs except ANKRD6 710 L>X were in linkage disequilibrium (r 2 > 0.8); thus, data for all SNPs are presented individually. Dependent variables included baseline and change in muscle strength and size (post- to pre-RT) for MVC, 1RM, and CSA in the trained (T) arm. Values are presented in absolute (no correction for MVC, 1RM, and CSA) and relative percent (post-RT − pre-RT/pre-RT × 100% for MVC, 1RM, and CSA). For the PA analysis, dependent variables included the Paffenbarger PA phenotypes listed previously.

Table 4

Table 4

Associations among the ANKRD6 genetic variants and muscle phenotypes were tested with repeated measure analysis of covariance (ANCOVA), with age and BMI as covariates and ANKRD6 genotype and gender as between-genotype factors. Associations among the ANKRD6 genetic variants and PA phenotypes were tested with multivariate ANCOVA by gender with age and BMI as covariates. No gender × ANKRD6 genotype interactions were found for any of the muscle phenotypes examined. However, a gender × ANKRD6 genotype interaction was found for one of the PA phenotypes examined, and thus results are presented for the total sample and by gender.

When significant main effects were found for the linear multivariate tests above (repeated measure ANCOVA and multivariate ANCOVA), post hoc analyses were performed, with Bonferroni adjustments applied for multiple comparisons. Significant findings for individual SNP cohorts are presented by genotype group (Tables 5 and 6). Statistical significance was set at p < 0.05, and all data were reported as mean ± SEM. Analyses were performed using SPSS 14.0 for Windows.

Table 5

Table 5

Table 6

Table 6

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Muscle Performance Phenotypes and ANKRD6 Genotype Associations

Muscle size and strength associations by ANKRD6 genotypes among the total sample are presented in Table 5 for the ANKRD6 SNPs that were found to have significant genotype main effects (p < 0.05). The Bonferroni post hoc genotype comparisons revealed that, for ANKRD6 122Q>E, subjects with the QE genotype tended to have higher baseline biceps CSA in the T arm than those with the QQ genotype (p = 0.076). For ANKRD6 631P>L, subjects with the PP genotype had a higher absolute increase in biceps CSA in the T arm post-RT than subjects with the PL genotype (p = 0.062). For ANKRD6 710L>X, subjects with the LL genotype tended to have higher absolute and relative gains in biceps MVC in the T arm post-RT than those with the LX genotype (p = 0.074). For ANKRD6 545A>T, subjects with the TA genotype tended to have greater absolute increases in biceps 1RM in the T arm post-RT than those with the TT genotype (n = 454) (p = 0.069). No significant associations among the muscle phenotypes and remaining 4 ANKRD6 genetic variants were found among the total sample and by sex (p > 0.05) (data not shown).

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Physical Activity Phenotype and ANKRD6 Genotype Associations

Physical activity associations by ANKRD6 631 P>L genotype among the total sample are presented in Table 6 because this was the only ANKRD6 SNP displaying a significant genotype main effect with the PA phenotypes obtained from the PPAQ (p = 0.03). Bonferroni post hoc genotype comparisons revealed that adults with the ANKRD6 631 LL genotype reported more time spent in moderate-intensity PA than those who were carriers of the P allele (p = 0.030). We further examined ANKRD6 631 P>L for the sex interactions we found (Table 6). Women with the ANKRD6 631 LL genotype reported more time spent in moderate-intensity PA than women who were carriers of the P allele (p = 0.05). There was no significant associations among PA phenotypes and ANKRD6 631 P>L for men (p > 0.05). No other significant associations among PA phenotypes and the remaining 7 ANKRD6 genetic variants were found among the total sample and by sex (p > 0.05) (data not shown).

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We examined whether ANKRD6 SNPs were associated with muscle performance in response to a 12-week, unilateral progressive RT intervention and habitual PA phenotypes in a large sample of healthy, untrained European-derived American adults from FAMuSS (29). The major findings were (a) ANKRD6 122 Q>E tended to be associated with baseline muscle size and ANKRD6 631 P>L with the muscle size response to RT (Table 5); (b) ANKRD6 710 L>X and ANKRD6 545 T>A tended to be associated with muscle strength response to RT (Table 5); and (c) ANKRD6 631 P>L was associated with moderate-intensity PA levels, and this association was sex dependent (Table 6).

The results of this exploratory study suggest that the ANKRD6 gene appears to associate with the muscle size and strength response to RT and habitual PA levels, and these genotype differences may have important public health considerations. For example: (a) subjects with the ANKRD6 631 PP genotype gained approximately 10% more muscle size (i.e., CSA) in response to RT than those with the PL genotype; (b) subjects with the ANKRD6 710 LL genotype gained approximately 50% more isometric muscle strength (i.e., MVC) in response to RT than those with the LX genotype; and (c) subjects with ANKRD6 545 TA genotype gained approximately 15% more muscle strength (i.e., 1RM) in response to RT than those with the TT genotype. In addition, subjects with the ANKRD6 631 LL genotype spent approximately 60% more hours per week in moderate-intensity PA than those who were carriers of the P allele, whereas it appears that they spent approximately 50% less hours per week in vigorous-intensity PA, although these latter findings did not reach statistical significance. These findings suggest that ANKRD6 genetic predispositions may be important to consider along with a growing number of genetic variants that have been reported to be associated with muscle performance (6,13,21,32) and habitual PA (7,8,14) when an individualized approach to PA prescription for health benefit based on genotype becomes more of a reality (22). For example, when recommending PA to adults for its overall health benefits, the ANKRD6 631 P>L and PA intensity-dependent genotype differences we found could be considered when encouraging people to become more physically active due to what appears to be genetic dispositions to prefer moderate over vigorous-intensity PA among those with the LL genotype. However, an individualized approach to PA prescription such as this remains a vision of the future rather than a reality of the present (20).

At this time, biological mechanisms by which ANKRD6 SNPs would influence muscle performance and habitual PA levels remains unclear. To our knowledge, this is the first article investigating ANKRD6 in humans and the first to report ANKRD6 genotype associations with muscle performance and habitual PA phenotypes. Previous research in mice has shown that the ANKRD6 protein is expressed predominantly in the developing brain from embryonic day 12 (E12) to maturity, suggesting a role during brain development. Tissir et al. (30) found that the ANKRD6 signal was prominent in the embryonic central nervous system and in dorsal root ganglia at E12. Within the central nervous system, expression was highest in ventricular zones of neuronal proliferation, particularly around the rhombencephalic and mesencephalic ventricles. At E15, ANKRD6 RNA concentration was also elevated in the spinal cord, dorsal root ganglia, and cranial ganglia. These findings provide evidence that ANKRD6 is highly expressed in the brain in a developmentally regulated manner, suggesting important functions that remain to be studied further.

Other research has demonstrated that ANKRD6 likely plays a role in human cardiogenesis. In zebrafish, ANKRD6 was found to control fusion of heart precursors, influence gastrulation movements during embryogenesis, and play a critical role in normal heart development. Additionally, ANKRD6 functions in Wnt signaling pathways, which regulate many developmental processes including cell proliferation, cell-fate specification, and morphogenesis in embryos (5). Within the Wnt pathway, ANKRD6 specifically binds with Dishevelled in the planar cell polarity pathway, creating a functional interaction essential for cardiogenesis and gastrulation in vertebrates (15).

Based on its physiology and function in developmental biology, ANKRD6 would appear to play an important role in human neural development, axis formation, and cardiogenesis. Additionally, according to Table 2, all SNPs we found phenotype associations with were located in exons, suggesting that these SNPs may influence the function of the protein. Thus, it is biologically plausible that this gene could influence muscle performance and habitual PA participation through centrally and peripherally mediated mechanisms, which may alter neural and cardiac tissue development, growth, and function. A centrally mediated mechanism for PA regulation has been suggested by studies that involve the candidate gene dopamine receptor 1 (Drd1) (14). Of note, Knab et al. (12) found that the brains of high physically active animals presented with down-regulated Drd1 compared with low physically active animals for 7 different dopamine genes. Furthermore, Rhodes and Garland (23) showed that PA was altered through pharmacological manipulation of Drd1. Although mechanisms explaining how Drd1 regulates PA are not yet known, the existent research suggests that the Drd1 associations with PA in animals are centrally mediated. Thus, it is possible that the ANKRD6 genetic variants may also associate with PA through central mechanisms. Our discussion regarding central and peripheral mechanistic explanations of how ANKRD6 may influence PA and muscle performance are purely speculative, and further prospective studies are necessary to validate our preliminary findings and, if validated, investigate mechanisms for the associations we observed.

Strengths of our study include a large homogenous sample and a highly standardized training intervention. Additionally, although FAMuSS was a multicenter trial and measurements of muscle performance and habitual PA were taken at multiple sites by a variety of different investigators, a manual with standardized measurement techniques and investigator certification was required at each site to minimize measurement variability, and all sites used the same equipment.

One limitation of this study is that FAMuSS was not originally designed to assess habitual PA levels, which were determined using a self-reported questionnaire. However, the PPAQ has been validated in similar subject populations and is considered to provide an accurate estimation of habitual PA in adults (1). Another limitation is that the study involved a young self-selected sample from university communities that may not represent the general population as a whole. However, the sample was an accurate representation of the general college-aged population from which it was studied. Similar to most candidate gene association studies, the significance we found in this study is limited by very low minor allele frequency values of the SNPs examined. However, cell sizes of the individual SNPs will never approach equality in this case because of the low prevalence of the minor allele in the general population. Despite such limitations, Urso (31) recently cited FAMuSS as one of the few initial studies in the field of exercise genomics that followed the model for a quality exercise genomics research study including a large sample size, rigorous exercise intervention, and diverse population. A final limitation of this study is that one of the SNPs, ANKRD6 710 L>X, was not in Hardy-Weinberg equilibrium.

In conclusion, the findings of this study support our hypothesis that ANKRD6 genetic variants associate with muscle size and strength in response to RT and habitual PA. Literature identifying specific gene associations with habitual PA is scarce, and current data are preliminary. Furthermore, the ANKRD6 protein has never been investigated in humans. Additional research is needed to validate the results of this preliminary candidate gene association study and to explore the pathways through which ANKRD6 genetic variants influence muscle performance and habitual PA.

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Practical Applications

Despite the many potential benefits of regular exercise, current PA levels do not measure up to the alarming increases in obesity and sedentary lifestyles across the nation. Findings such as ours regarding ANKRD6 associations with muscle size and strength response to RT and PA may contribute to a better understanding of the significant role that genetics and individual physiological variability plays in muscle performance and participation in PA (4,11,22). Eventually, this may lead to the use of genetic information in developing individualized weight loss and training goals and personalized prescription to enhance PA participation and desired health outcomes. From a disease prevention perspective, improving PA levels in sedentary individuals has enormous potential for preventing cardiovascular disease and decreasing morbidity and mortality rates.

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This research was supported by National Institutes of Health-National Institute Neurological Disorder and Stroke Grant R01 NS40606-02 and the University of Connecticut Center for Health, Intervention, and Prevention.

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1. Ainsworth BE, Leon AS, Richardson MT, Jacobs DR, Paffenbarger RS Jr. Accuracy of the college alumnus physical activity questionnaire. J Clin Epidemiol 46: 1403–1411, 1993.
2. Bennett V, Baines AJ. Spectrin and ankyrin-based pathways: Metazoan inventions for integrating cells into tissues. Physiol Rev 81: 1353–1392, 2001.
3. Bouchard C, Dionne FT, Simoneau JA, Boulay MR. Genetics of aerobic and anaerobic performances. Exerc Sport Sci Rev 20: 27–58, 1992.
4. Carlsson S, Andersson T, Lichtenstein P, Michaelsson K, Ahlbom A. Genetic effects on physical activity: Results from the Swedish Twin Registry. Med Sci Sports Exer 38: 1396–1401, 2006.
5. Clevers H. Wnt/beta-catenin signaling in development and disease. Cell 127: 469–480, 2006.
6. De Mars G, Windelinckx A, Beunen G, Delecluse C, Lefevre J, Thomis MA. Polymorphisms in the CNTF and CNTF receptor genes are associated with muscle strength in men and women. J Appl Physiol 102: 1824–1831, 2007.
7. De Moor MH, Liu YJ, Boomsma DI, Li J, Hamilton JJ, Hottenga JJ, Levy S, Liu XG, Pei YF, Posthuma D, Recker RR, Sullivan PF, Wang L, Willemsen G, Yan H, De Geus EJC, Deng HW. Genome-wide association study of exercise behavior in Dutch and American adults. Med Sci Sports Exerc 41: 1887–1895, 2009.
8. De Moor MH, Posthuma D, Hottenga JJ, Willemsen G, Boomsma DI, De Geus EJ. Genome-wide linkage scan for exercise participation in Dutch sibling pairs. Eur J Hum Genet 15: 1252–1259, 2007.
9. Hubal MJ, Gordish-Dressman H, Thompson PD, Hoffman EP, Angelopoulos TJ, Gordon PM, Moyna NM, Pescatello LS, Visich PS, Zoeller RF, Seip RL, Clarkson PM. Variability in muscle size and strength gain after unilateral resistance training. Med Sci Sports Exerc 37: 964–972, 2005.
10. International HapMap Consortium, Frazer KA, Ballinger DG, et al.. A second generation human haplotype map of over 3.1 million SNPs. Nature 449: 851–861, 2007.
    11. Joosen AM, Gielen M, Vlietinck R, Westerterp KR. Genetic analysis of physical activity in twins. Am J Clin Nutr 82: 1253–1259, 2005.
    12. Knab AM, Bowen RS, Hamilton AT, Gulledge AA, Lightfoot JT. Altered dopaminergic profiles: Implications for the regulation of voluntary physical activity. Behav Brain Res 204: 147–152, 2009.
    13. Kostek MA, Angelopoulos TJ, Clarkson PM, Gordon PM, Moyna NM, Visich PS, Zoeller RF, Price TB, Seip RL, Thompson PD, Devaney JM, Gordish-Dressman H, Hoffman EP, Pescatello LS. Myostatin and follistatin polymorphisms interact with muscle phenotypes and ethnicity. Med Sci Sports Exerc 41: 1063–1071, 2009.
    14. Lightfoot JT. Current understanding of the genetic basis for physical activity. J Nutr 141; 526–530, 2011.
    15. Moeller H, Jenny A, Schaeffer HJ, Schwarz-Romond T, Mlodzik M, Hammerschmidt M, Birchmeier W. Diversin regulates heart formation and gastrulation movements in development. Pro Natl Acad Sci U S A 103: 15900–15905, 2006.
    16. Paffenbarger RS Jr, Wing AL, Hyde RT. Physical activity as an index of heart attack risk in college alumni. Am J Epidemiol 108: 161–175, 1978.
    17. Paffenbarger RS Jr, Blair SN, Lee IM, Hyde RT. Measurement of physical activity to assess health effects in free-living populations. Med Sci Sports Exerc 25: 60–70, 1993.
    18. Pate RR, Pratt M, Blair SN, Haskell WL, Macera CA, Bouchard C, Buchner D, Ettinger W, Heath GW, King AC, Kriska A, Leon AS, Marcus BH, Morris J, Paffenbarger RS Jr, Patrick K, Pollock ML, Rippe JM, Sallis J, Wilmore JH. Physical activity and public health: A recommendation from the Centers for Disease Control and Prevention and the American College of Sports Medicine. JAMA 273: 402–407, 1995.
    19. Perusse L, Lortie G, Leblanc C, Tremblay A, Theriault G, Bouchard C. Genetic and environmental sources of variation in physical fitness. Ann Hum Biol 14: 425–434, 1987.
    20. Pescatello LS. The promises and challenges of the use of genomics in the prescription of exercise for hypertension. Curr Hypertens Rev 6: 32–34, 2010.
    21. Pescatello LS, Kostek MA, Gordish-Dressman H, Thompson PD, Seip RL, Price TB, Angelopoulos TJ, Clarkson PM, Gordon PM, Moyna NM, Visich PS, Zoeller RF, Devaney JM, Hoffman EP. ACE ID genotype and the muscle strength and size response to unilateral resistance training. Med Sci Sports Exerc 38: 1074–1081, 2006.
    22. Pescatello LS, Roth SM. Molecular and Translational Medicine Series Volume: Exercise Genomics. New York, NY: Humana Press, 2011. ISBN 978-1-60761-354-1.
    23. Rhodes JS, Garland T Jr. Differential sensitivity to acute administration of Ritalin, apomorphine, SCH 23390, but not raclopride in mice selectively bred for hyperactive wheel-running behavior. Psychopharmacology (Berl) 167: 242–250, 2003.
    24. Schwarz-Romond T, Asbrand C, Bakkers J, Kuhl M, Schaeffer HJ, Huelsken J, Behrens J, Hammerschmidt M, Birchmeier W. The ankyrin repeat protein diversin recruits casein kinase iepsilon to the beta-catenin degradation complex and acts in both canonical wnt and Wnt/JNK signaling. Genes Dev 16: 2073–2084, 2002.
    25. Simonen R, Levalahti E, Kaprio J, Videman T, Battie MC. Multivariate genetic analysis of lifetime exercise and environmental factors. Med Sci Sports Exerc 36: 1559–1566, 2004.
    26. Stubbe JH, Boomsma DI, Vink JM, Cornes BK, Martin NG, Skytthe A, Kyvik KO, Rose RJ, Kujala UM, Kaprio J, Harris JR, Pederson NL, Hunkin J, Spector TD, de Geus EJC. Genetic influences on exercise participation in 37,051 twin pairs from seven countries. PLoS One 1: e22, 2006.
    27. Thomis MA, Beunen GP, Van Leemputte M, Maes HH, Blimkie CJ, Claessens AL, Marchal G, Willems E, Vlietinck RF. Inheritance of static and dynamic arm strength and some of its determinants. Acta Physiol Scand 163: 59–71, 1998.
    28. Thomis MA, Beunen GP, Maes HH, Blimkie CJ, Van Leemputte M, Claessens AL, Marchal G, Willems E, Vlietinck RF. Strength training: Importance of genetic factors. Med Sci Sports Exerc 30: 724–731, 1998.
    29. Thompson PD, Moyna N, Seip R, Price T, Clarkson P, Angelopoulos T, Gordon P, Pescatello LS, Visich P, Zoeller R, Devaney JM, Gordish H, Bilbie S, Hoffman EP. Functional polymorphisms associated with human muscle size and strength. Med Sci Sports Exerc 36: 1132–1139, 2004.
    30. Tissir F, Bar I, Goffinet AM, Lambert De Rouvroit C. Expression of the ankyrin repeat domain 6 gene (ANKRD6) during mouse brain development. Dev Dyn 224: 465–469, 2002.
    31. Urso ML. Is it time to change the ground rules of exercise-related genomics research? Med Sci Sports Exerc 43: 753–754, 2011.
    32. Walsh S, Kelsey BK, Angelopoulos TJ, Clarkson PM, Gordon PM, Moyna NM, Visich PS, Zoeller RF, Seip RL, Bilbie S, Thompson PD, Hoffman EP, Price TB, Devaney JM, Pescatello LS. CNTF 1357 G > A polymorphism and the muscle strength response to resistance training. J Appl Physiol 107: 1235–1240, 2009.

    diversin; exercise; resistance training; genetics

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