Genomics and Sports: Building a Bridge Towards a Rational and Personalized Training Framework

It is now widely acknowledged that several genes influence the athletic performance and it is increasingly being highlighted that a major integration between genetic and environmental factors might contribute towards unveiling the most important determinants of physiology and pathology in humans, allowing the construction of a rational personalized framework that would be applied in both clinical and sport settings [[7], [9]]. The alpha-actinin 3 (ACTN3) gene, which encodes for a protein of the Z disk of myofibers, has been found to be associated with performance in elite athletes, in whom the R allele was more common in sprint and power athletes and the X allele more common in endurance athletes [[15]]. Data in a large sample size have also shown that women with the nonsense allele in ACTN3 are at a disadvantage in the ability to produce high-force isometric strength, but they are at an advantage in developing dynamic muscular strength in response to a progressive resistance training program. Up to 2 % of the variability in the absolute and relative difference in 1-repetition maximum strength and in the baseline elbow flexor isometric strength are attributable to the ACTN3 genotype [[2]]. Turley et al. further confirmed the presence of a substantial genetic influence on acute submaximal exercise and regular endurance training, as maximal oxygen uptake and training response are influenced by multigenetic effects, which account for nearly 40 % and 20 % of the variance, respectively [[13]].

In an article which recently appeared in this journal, Cayla et al. demonstrated that in skeletal muscles from adult rats, massive erythropoietin injections and endurance training have both similar effects, i.e., a shift from a fast glycolitic to a slow oxidative phenotype, concluding that the effects of erythropoietin and training might be additive. In particular, they observed that the expression of slow twitch myosin light chains and oxidative myosin heavy chains both increase in erythropoietin-treated muscles [[1]]. This is a rather intriguing finding, in that it adds further insight into the challenging scenario of genes-performances interaction. Basically, most of the studies on this topic could identify a significant association between genotype and elite power performance [[8], [10]], though such influence rarely explained more than 20 - 50 % of the variability (e.g., Clarkson et al. observed a relationship between ACTN3 genotype and performances in women but not in men, while Turley et al. reported that genetic variation accounts for only 27 % of variation in the training response [[2], [13]]). The discovery of a family of proteins called hypoxia inducible factors (HIFs) has further contributed to enhance comprehension of the intricate mechanisms of response to hypoxia, as occurs in tissues that in some circumstances have to deal with increased oxygen demand, such as hard working muscles [[6]]. Basically, the genes controlled by the HIFs include those coding for proteins that stimulate red cell production (mainly erythropoietin), as well as those encoding glycolytic enzymes, both of which are pivotal mechanisms in the attempt to achieve improved aerobic performances. Since both erythropoietin production and expression of glycolytic enzymes are genetically regulated [[6]], and erythropoietin administration produces effects on the muscle which might be independent from the training regimen [[1]], it is conceivable that construction of genetic maps based on a variety of polymorphisms, including those of the HIFs and erythropoietin genes, might help to clarify the genetic background lying beyond the athletic performances, especially those of top-class athletes, where genetic endowment is developed by an intensive training program. Sport performances are indeed a polygenic trait and the adoption of a “single-gene-as-magic-bullet” philosophy would be inconclusive and even misleading in the athletic field [[3]], as the 2005 human gene map for physical performance and health-related phenotypes already includes 165 autosomal gene entries and quantitative trait loci, plus five others on the X chromosome. Additionally, 17 mitochondrial genes with sequence variants have been shown to influence relevant fitness and performance phenotypes [[12]]. Genetic testing was initially developed nearly 20 years ago, and its original applications were limited to counselling and prenatal diagnosis of a few hereditary diseases. Technological advances and continuous identification of a variety of genes responsible for many hereditary diseases have enormously amplified its development and diffusion from basic research to clinical laboratories. The recently developed multiplex allele-specific amplification (ASA‐PCR) technology represents a valid alternative to standard protocols such as restriction fragment length polymorphism-PCR, allele-specific oligonucleotide hybridization, non-PCR oligonucleotide cleavage technology, and real-time PCR, especially when a simultaneous determination of the multiple genetic mutations is required [[4]]. DNA microchips, taking advantage of colorimetric or fluorescence detection (including energy transfer), are currently under development. These promising devices allow qualitative and quantitative interpretation of results, providing a reliable solution to the predictable increase of requests for genetic testing by high throughput and walkaway performance. Although genetic testing is never going to replace the findings on the athletic field, in an ideal situation it might be less invasive, less expensive, and more accurate than conventional in vivo or in vitro analyses. Although genetic testing should be discretionary and regulated in athletes [[7]], it does represent a great opportunity to build a solid bridge towards a rational and personalized training framework, one of the future challenges of physiology and sports medicine. It should also be mentioned that gene arrays and, probably, proteomics would also be useful in the antidoping context, in that they would help identification of drug-induced long-lasting changes of gene expression following doping exposure [[11]], and, especially, they would enable the recognization of genetic variations due to gene transfer technology, in a practice termed “gene doping” [[5]]. Promising results confirm the enormous potential of the proteomic approach to investigate a broad series of physiological adaptations to exercise and detection of distinctive functional features in athletes, i.e., the differential expressions of several proteins and enzymes [[14]]. In the very near future, integration of gene- and protein-screening technologies might drive a paradox shift in the way sport performance is assessed and monitored, enabling a much broader view of the complex physiological responses that finally contribute to differentiate individual performances.

References

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