Genes for Elite Power and Sprint Performance: ACTN3 Leads the Way

Abstract

The ability of skeletal muscles to produce force at a high velocity, which is crucial for success in power and sprint performance, is strongly influenced by genetics and without the appropriate genetic make-up, an individual reduces his/her chances of becoming an exceptional power or sprinter athlete. Several genetic variants (i.e. polymorphisms) have been associated with elite power and sprint performance in the last few years and the current paradigm is that elite performance is a polygenic trait, with minor contributions of each variant to the unique athletic phenotype. The purpose of this review is to summarize the specific knowledge in the field of genetics and elite power performance, and to provide some future directions for research in this field. Of the polymorphisms associated with elite power and sprint performance, the α-actinin-3 R577X polymorphism provides the most consistent results. ACTN3 is the only gene that shows a genotype and performance association across multiple cohorts of elite power athletes, and this association is strongly supported by mechanistic data from an Actn3 knockout mouse model. The angiotensin-1 converting enzyme insertion/deletion polymorphism (ACE I/D, registered single nucleotide polymorphism [rs]4646994), angiotensinogen (AGT Met235Thr rs699), skeletal adenosine monophosphate deaminase (AMPD1) Gln(Q)12Ter(X) [also termed C34T, rs17602729], interleukin-6 (IL-6 -174 G/C, rs1800795), endothelial nitric oxide synthase 3 (NOS3 -786 T/C, rs2070744; and Glu298Asp, rs1799983), peroxisome proliferator-activated receptor-α (PPARA Intron 7 G/C, rs4253778), and mitochondrial uncoupling protein 2 (UCP2 Ala55Val, rs660339) polymorphisms have also been associated with elite power performance, but the findings are less consistent. In general, research into the genetics of athletic performance is limited by a small sample size in individual studies and the heterogeneity of study samples, often including athletes from multiple-difference sporting disciplines. In the future, large, homogeneous, strictly defined elite power athlete cohorts need to be established though multinational collaboration, so that meaningful genome-wide association studies can be performed. Such an approach would provide unbiased identification of potential genes that influence elite athletic performance.

Investigation of the Relationship Between a Genetic Polymorphism in ACTN3 and Elite Sport Performance Among Iranian Soccer Players

“…After digestion with DdeI enzyme, 577X allele shows two fragments with 205 and 85 bp, whereas 557R allele presents three fragments with 105, 97, and 85 bp athletes [9,12,13] or is associated with inferior performance [19]. Two recent meta analyses [20,21] and a revision [22] of the literature with regards to the effect of ACTN3 on athletic performance indicate that the 577RR genotype is affiliated with sprint-power athletes among Caucasians. A large cohort study of about 300 elite Japanese athletes indicated that the ACTN3 577RX genotype was associated with sprint-power performance among track and field contestants [23].…”

Can we optimise the exercise training prescription to maximise improvements in mitochondria function and content?

“…However, the research focus has now shifted to continuously-developing, molecular-based, laboratory methods (e.g., candidate genetic variations analysis, direct sequencing) designed to directly test the interaction between genetic and environmental factors, not only in family or twin studies, but also in studies involving populations of interest [80]. The hypothesis, shared by many scientists, is that common genetic variants (i.e., polymorphisms), which are present throughout the human genome, may cause biological changes that influence mitochondrial adaptations [81,82].…”

Performance trade-offs and individual quality in decathletes

“…And, both found that the expected negative correlations emerged only after this adjustment. Importantly, both Van Damme et al (2002) and Wilson et al (2014b) are cited in the evolutionary and human performance literature as evidence of performance trade-offs without acknowledging that the measured correlations were positive (MacArthur and North, 2005;Flueck, 2009;Ruiz et al, 2010;Eynon et al, 2013;Lailvaux and Husak, 2014;Wilson et al, 2014a;Servedio et al, 2014). We emphasize this because all four methods used to infer trade-offs in Van Damme et al (2002) and Wilson et al (2014b) are poor estimators of qualityfree correlations.…”