Muscular strength and power are important fitness components, essential for the execution of a variety of daily activities and sport activities throughout the life span. Various indicators of strength and power are available, but in the context of epidemiological studies the following indicators of strength and power are generally considered: static or isometric strength, explosive strength or power, and dynamic (sometimes called functional) strength. Factor analyses of a variety of muscular fitness indicators observed in both sexes demonstrate that the above muscular fitness components are identified as separate factors, and these factors are fairly independent components of the motor ability domain.
Analyses of the genetic determinants of strength provide insight not only into the importance of the contribution of genes, but also into the contribution of environmental factors. With regard to strength, physical activity and weight training are probably the most important environmental factors. It is beyond the scope of this review to provide an overview of the effects of strength training. Furthermore, interaction effects between genes and environment can be studied. One interaction effect of interest is the gene-by-training interaction; i.e., is the training effect—the strength gain during a weight training program—under genetic control? Finally, how far are we in the identification of genes or coding variants in relation to strength characteristics?
Most characteristics of human performance and contributing human body dimensions are evaluated on a continuous scale of measurement. The distributions in the normal population show a Gaussian, or skewed, distribution—typical for quantitative, multifactorial phenotypes, which are influenced by multiple genes (polygenic) as well as environmental factors. The search for the genetic basis of muscular strength and power can be studied by two basic approaches: the unmeasured genotype approach (top-down), and the measured genotype approach (bottom-up) (3) (Fig. 1).
When the measured genotype is not available, inferences about genetic influences on a phenotype are based on statistical analyses of the distributions of strength measures in related individuals and families based on the theoretical framework of biometrical genetics (Chapter 3 in (8)). Two major strategies are used to identify genetic and environmental contributions to muscular strength phenotypes: twin studies and family studies. In twin studies, both monozygotic (MZ) and dizygotic (DZ) twins are used. Since monozygotic twins have an identical genetic background, they will be more similar (higher intra-pair correlation) in a trait that is under genetic control than dizygotic twins, who share, on average, half of their genes. When using twin data, genetic as well as environmental factors unique to the individual and shared within families can be identified. Under certain assumptions, dominant genetic effects also can be identified. In family studies, the similarities among parents and offspring and between sisters and brothers are studied. This approach allows the identification of genetic plus cultural transmission of traits and estimates of maximum transmissibility. If data from more extended or combined pedigrees (e.g., twins and their parents) are included, more sophisticated models can be tested.
Analyses of different familial or twin covariances can be done using path analysis, in which several of the contributing sources of variation mentioned above can be quantified by testing a hypothetical model to the observed familial (or twin) variation/covariation matrices (8). Assessment of heritability is based on the basic genetic model that the total variation (Vtot) in traits such as muscular strength is partitioned into genetic (VG), common environmental (VC) and individual-specific environmental (VE) variation components (Vtot = VG+VC+VE). Heritability (h2) refers to the proportion of the total variation that can be attributed to genetic effects (VG/Vtot). In most studies it is assumed that the effects of different genes are additive (a2), meaning that the genotypic effect of the heterozygote genotype on the phenotype falls between the genotypic effects of both homozygote genotypes. Dominance genetic effects refer to the interaction between alleles at the same locus (heterozygote effect is not intermediate between the two homozygote genotype effects), and epistasis describes the interaction between alleles at different loci. The contribution of environmental factors shared by family members (common environmental factors, c2 = VC/Vtot) and the proportion of environmental factors that act on an individual level can also be estimated (e2 = VE/Vtot). When using this additive model of sources of variation, several assumptions should be met: no interaction between gene action and environment (different genotypes all react equally to similar environmental factors), no gene–environment correlation (similar exposure of environments for different genotypes), no gene–gene interaction, and no assortative mating for the trait (one assumes people mate randomly for the phenotype in question). In all likelihood, influences on muscular strength do not follow all of these assumptions. The heritability coefficient is specific for the studied population, and can be estimated using ANOVA or genetic modeling techniques.
All of these methods provide only a measure of the importance of genetics for a particular trait; more sophisticated genetic models (e.g., complex segregation analysis) can provide indications of the actions of major genes, modes of inheritance, etc. To identify specific genes that contribute to a multifactorial phenotype, one needs to deal with the measured genotype methods.
Two major complementary strategies are available in humans to identify genes that explain variability in human muscular strength and power using the measured genotype approach (Figs. 1 and 2). First, attempts to localize and identify individual loci that make up the genetic component of muscle strength phenotype by Quantitative Trait Loci linkage analysis are briefly discussed. Second, methodology for allelic association studies is described. Within the scope of the present review, only general descriptions of both approaches can be presented. More detailed and theoretical background on statistical genetics can be found elsewhere (10).
Linkage analysis is an important initial tool for mapping genetic loci. One of its advantages is that it requires no knowledge of physiological mechanisms. A total genome linkage study uses several hundreds of highly variant DNA markers, regularly spaced (e.g., each 10 cM) throughout the human genome. Both parametric and nonparametric methods are now available to test whether a marker at a specific location is in linkage (cotransmitted) with a gene causing the phenotype under study. In a quantitative trait like muscular strength, such a gene or locus is called a Quantitative Trait Locus (QTL). In the parametric method one tests whether the recombination fraction between a marker and a causal gene is significantly <0.5. This can be tested by a Lod score, with a value of 3 (1000-to-1 odds in favor of linkage) indicating significant linkage between a marker locus and a locus causing the phenotype. Amongst other parameters, the mode of inheritance is needed to perform this type of model-based analysis on family data.
Since muscular strength characteristics are determined by environmental factors and a large set of genes of which the mode of inheritance is unknown, several model-free (or nonparametric) methods have been developed, mostly applied in sibling pair or nuclear family datasets. All available methods are based on the relationship of the number of alleles shared by descent (identical by descent: IBD)—alleles from the same ancestral chromosome—in pairs of relatives, and observed differences in the phenotypes between these relatives. Several methods have been proposed to determine the expected proportion of alleles IBD from marker genotype data of which the Lander-Green algorithm is often applied. Figure 2B schematically presents the Haseman-Elston regression method (reviewed in (10)), which provides evidence for linkage when the squared sibling-pair trait differences decrease with an increase in the proportion of alleles shared IBD at the marker locus. This method has been updated (11), and variance-component methods have been developed (10). Multipoint linkage mapping refers to the fact that genotypic data of flanking markers is used together with the marker of interest to better estimate the number of alleles shared by individuals at the marker of interest.
A second set of strategies concerns allelic association studies, in which one studies the effect of a specific (polymorphic) marker allele, mostly within a candidate gene, with the mean strength performance level in groups of different genotypes for this polymorphism (ANOVA) (Fig. 2D). One can also test for significant differences in allele frequencies in a case-control design, meaning that the occurrence of one specific allele is counted in a group of strength athletes and compared to the frequency of this allele in a control group (χ2 test, Fig. 2C). Single nucleotide polymorphisms (SNPs), with two different chromosomes having a change in one nucleotide at a certain position, insertion/deletion polymorphisms, or multi-allelic variants can be used in allelic association studies. When a positive association is found, the “strength increasing” allele under study might be the true functional variant, or might be in tight linkage (in linkage disequilibrium) with the true functional allele. Often, multiple polymorphisms within one or more genes—or even genome-wide—are studied. Instead of testing for association with each polymorphism separately, one can analyze haplotypes—a set of SNPs along a region of a chromosome—and test whether a specific haplotype is associated with increased or decreased strength. Association studies do not need genetically related subjects; however, family data can be included in the analyses to overcome problems of hidden population stratification, an effect that could induce false-positive association findings (10). The success of association analysis depends largely on the choice of the candidate gene under study. Figure 1 presents several possible “guiding” sources of information to select good candidate genes. These could be: 1) the Quantitative Trait Loci, or genes under the highest linkage peaks from a genome-wide or designed-linkage analysis; 2) animal models (e.g., Mstn−/− or “mighty” mouse) related to muscle characteristics or strength; 3) knowledge of genes involved in human neuromuscular diseases; 4) human muscle physiology; and 5) differences in gene expression (mRNA levels) of a large set of genes between muscle of “strength athletes” versus control individuals.
Linkage and association studies complement each other, and could be seen as two ends of a continuum in the search to find genes for muscular strength phenotypes. Linkage studies need the cooperation of genetically related individuals that, through a limited number of meioses, have large segments of chromosomes in common. The outcome of the analysis gives a large chromosomal region which might harbor many Quantitative Trait Loci for the measure of interest. Linkage analysis might only find loci with rather large effects on the phenotype (explaining more than 10% of the phenotypic variation). Association studies can be interpreted as a form of identity-by-state analysis between distant relatives who only share very small chromosomal regions. Because they allow for unrelated individuals to be studied, and can detect much smaller gene effects (1–3% of phenotypic variation), these studies are often more feasible to perform.
GENETICS OF STRENGTH
Family and Twin Studies
Bouchard, Malina and Pérusse (3) and Beunen and Thomis (1) recently reviewed the genetic and environmental influences in different strength characteristics. Heritability estimates (based on sibling correlations for grip strength, pull and push) vary from 0.44 to 0.58. Correction for body mass reduced the estimates, but corrections for the reliability of the measurements increased the heritabilities. Results from 15 twin studies, sometimes with small sample sizes, and often covering an extended age period, provide heritabilities ranging from 0.14 to 0.83. Data on explosive strength or power, often measured with standing broad jump or vertical jump, are less extensive, but indicate significant genetic contributions for jumping performances. Functional strength or muscular endurance is mostly evaluated by tests like bent-arm hang, chin-ups, sit-ups or leg lifts. Both family and twin data demonstrate a genetic component in the explanation of inter-individual differences for these performance characteristics. In general, heritability estimates from sibling or family studies are lower than those from twin studies. Static strength and power tend to have higher heritabilities than muscular endurance. Gender differences are not always clear, but genes seem to play a more prominent role in male than in female strength determination (1,2). For a summary of these studies, see Table 1.
Most of the studies reviewed use one type of study, twins or family data, and often span a large age period; therefore, no information is readily available on time-specific effects and/or gender effects. Based on recently published twin studies on older adults (15) and on data of the Leuven Longitudinal Twin Study (2), age trends in the heritability estimates of isometric strength have been documented. Between 10 and 18 yr heritability estimates for isometric strength (arm pull) vary between a2 = .67 and a2 = .83, with four exceptions (a2 = .52/.44 in boys aged 13 and 18 yr, and a2 = .52/.50 in girls aged 13 and 15 yr) out of 16 heritability coefficients. There is no clear age trend over this period, although boys in particular experience a dramatic growth spurt in static strength between 12 and 14.5 yr. Heritability estimates for grip strength in men and women in the second half of life (45 yr and older) vary between a2 = .14 and a2 = .52 (4,15). The sample sizes in all these studies provide sufficient power to detect a significant genetic contribution. Allowing for the difference in phenotype (arm pull and grip strength), it seems reasonable to conclude that with the aging process and decline in muscle function, the genetic component of isometric strength is lower in older adults than it is during the growth process. From all the studies thus far reported, no clear gender difference can be detected. For the other strength characteristics there is much too little published information to verify age and gender effects on heritability estimates. There is also evidence that different genes are acting in adults, children and adolescents (7).
Univariate and multivariate genetic modeling of sources of variation in angle-specific maximal static torques in elbow flexion and in eccentric and concentric torques in the Leuven Twin & Training Study showed trends for angle-specificity in the heritabilities for elbow flexor strength (h2 66–78 %), except at a small angle (13). Furthermore, striking similarities were found comparing the average phenotypic strength values in the strength-velocity (and contraction type) curve and the estimated heritabilities, being higher for eccentric strength than concentric strength (13). These findings might relate to the different contributions of genetic variation in contractile (concentric) elements and contractile and passive elastic components (eccentric) in the specific types of contraction. Similarly higher transmissibility estimates were found for static elbow, knee and trunk contractions, compared to concentric muscle actions in the Leuven Genes for Muscular Strength Study (5).
Genetic Factors in Trainability of Strength
Physical activity and specific, high-resistance strength training are “environmental factors” that contribute or add to the observed differences in muscular strength and power between individuals, both at young ages and in adult life. The question of whether responses to strength training are variable in the population and whether this observed heterogeneity in trainability is related to the genotype is referred to as genotype–training interaction. This genotype–training interaction effect has only been studied in young adult populations for aerobic and anaerobic performances (3) and for muscular strength in two studies (3, 12). In a 10-wk knee flexion/extension isokinetic strength training protocol, 5 monozygotic twins (17–26 yr) were tested for responses in maximal strength and muscle fiber metabolites. Despite significant increases in strength and considerable variation in training responses (24% ± 12%), evidence for genotype-dependent changes were found only in muscle oxoglutarate-dehydrogenase concentrations—not for strength increases in peak torque output or other muscle enzymes. In a 10-wk high-resistance strength training study of arm flexors in 25 MZ and 16 DZ male twins (22.4 yr ± 3.7 yr), responses in static and dynamic arm flexor strength and arm cross-sectional area were analyzed by bivariate genetic models (12). The increase in one-maximal repetition load (1RM) was high: 45.8% of the pretraining value, with large interindividual differences (CV = 34%). Also, isometric and concentric arm flexor strength increased by about 20% of pretraining values, and small hypertrophic effects were found as arm cross-sectional area increased on average by 4.4%. Evidence for genotype-environment interaction was found for the increase in 1RM (see Fig. 3), static strength and concentric flexion at 120°·s−1. In the ANOVA approach, 3.5 times more variation was found between MZ pairs than within MZ pairs. From bivariate pre- and posttraining analysis of both MZ and DZ twin data, it was observed that about 20% of the variation in strength (1MR, static and concentric flexor strength) at posttraining evaluation was explained by genetic factors that did not contribute to the genetic variability in strength before strength training. Trainability in muscular strength is therefore found to be highly variable in young adults, with some evidence for the importance of training-specific genes coming into action by impulse of the imposed training load. However, variation in strength outcome attained after strength training is largely explained by the same genetic factors that act before strength training.
Gene Powered? Gene-Hunting for Muscular Strength
A generous and useful service is provided by Medicine and Science in Sports and Exercise®, an official journal of the American College of Sports Medicine, to inform exercise scientists with a yearly update on the “Human Gene Map for Performance and Health-Related Fitness Phenotypes”. In the 2002 update (9), allelic variations are reported to have significant associations with static or dynamic strength in 6 candidate genes: myostatin; GDF8 K153R, insulin-like growth factor 2; IGF2 ApaI, cyliary neurotrophic factor; CNTF null, vitamin D Receptor; VDR BsmI, type-I Collagen alpha1; COLIA1 Sp1, Angiotensin Converting Enzyme; ACE – Insertion/deletion polymorphism. More recently, a stop-codon polymorphism in the ACTN3 gene has been associated with power-related sports, and a C174T variant in the ciliary neurotrophic factor receptor (CNTFR) gene has been significantly related to concentric and eccentric isokinetic quadriceps strength, through its association with lower limb fat free mass. No linkage study investigating polymorphic markers throughout the whole genome has yet been published. At present, linkage analysis is performed with polymorphic markers in genes of the myostatin pathway in the Leuven Genes for Muscular Strength Study, with (suggestive) linkage for knee flexor and extensor strength with markers D2S118, D6S1051 and D11S4138 (6). Most of these reported findings have not yet been replicated in independent samples. Furthermore, the association of the ACE deletion allele (D) with favorable strength training gains has not been confirmed by training studies in young (Fig. 3) (14) or aging populations (4). Therefore, it can be concluded that allelic association studies for muscular strength phenotypes are limited, and not yet conclusive.
Hints for Gene-Hunting
The search for genes related to muscular strength and power is a daunting task. Below are some hints to aid in the hunt for genes regulating muscular strength in humans:
- 1) Have correct heritability estimates, phenotype-, gender- and age-specific. Heritability estimates are sometimes used directly in linkage analysis methods, but can also direct association type analyses to the phenotypes with the highest genetic background.
- 2) Measure “strength-characteristics” in as much detail as possible, with “sub phenotypes”—muscle biopsies if possible.
- 3) Aim for large samples with enough statistical power (extremely different in phenotype or within normal variation) and well-designed for both association and linkage analysis approaches.
- 4) Think about many genes, major and minor contributing genes, regulatory elements, etc. Muscle strength and power are probably determined by many genes each explaining small amounts of the overall variability. Allelic variants might be located within coding, noncoding or regulatory elements of the candidate genes under study.
- 5) Use all available information to focus on the best selection of specific candidate genes. Candidate gene regions can be identified based on genome-wide linkage studies. Animal models, muscle physiology pathways, human muscle diseases and human muscle gene expression studies are all useful for identifying sets of candidate genes. Single nucleotide polymorphism databases are available to select sequence variations within the candidate gene, or de novo SNP detection can be performed.
- 6) Joint efforts are probably needed, especially when muscle strength responses to training are the main phenotypes of interest. The study of human DNA sequence variation involved in muscular strength and power, both at baseline and in response to training requires sample sizes large enough to identify genes and detect functional variation, and also requires samples to replicate these findings independently. Joint efforts of different research groups might add to the probability of identifying several contributing QTLs.
Present studies focus on variations in the DNA sequence from nuclear or mitochondrial DNA at coding (exon), noncoding (intron), or untranslated regions of candidate genes. However, more insight into the complexity of our species is emerging, with a greater focus on alternative splicing, and other ribotypic modifications of gene transcripts and proteins.
Studies have shown the importance of genetic and environmental factors in individual differences in muscular strength and power. For isometric strength, heritabilities are higher during growth than during the second half of life, without clear gender differences. For the other strength components, there is a paucity of data on gender- and age-specific estimates of heritabilities. Association and linkage studies for muscular strength phenotypes are limited and not yet conclusive. Large, well-phenotyped samples will induce both linkage-driven (genetically-related individuals) evidence of genomic regions harboring quantitative trait loci for human muscle strength and power, and association-driven evidence of strength-increasing alleles or haplotypes.
The authors thank all investigators of the Leuven Longitudinal Twin Study, the Twin & Training Study, and the Leuven Genes for Muscular Strength Study, upon whose original research this article is largely based. The authors apologize to any investigator whose work was not cited because of a limit on references. Original research and references concerning studies on heritabilities of strength and responses to training before 1995 were referred by reviews of Bouchard et al. (3) and Beunen et al. (1,2). The authors are thankful to the Associate Editor, P. Katzmarzyk, for editorial assistance.
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