Numerous efforts have been made over the past two decades to uncover the genetic basis of elite athletic performance. As of 2008, over 200 autosomal gene entries and quantitative trait loci have been reported to be associated with performance and health-related fitness phenotypes. Nevertheless, most genetic findings to date have been inconclusive due primarily to the reliance on the hypothesis-driven candidate gene approach applied to relatively small samples. Genome-wide association study (GWAS) utilises linkage disequilibrium between a common single nucleotide polymorphism (SNP) and a causal variant, and involves genotyping cases and controls at a large number of tagSNPs spread throughout the genome. GWAS requires no prior assumptions made on the location or function of a causal variant but rather GWAS is regarded as hypothesis generation. Elite athletic performance is a complex trait that requires different genetically driven components of human biological systems to coordinate effectively with the environment. It is undoubtedly that multiple genetic loci are associated with the performance trait and/or its components. The genetic architecture underlying elite human performance is unknown. Genotype imputation can effectively predict genotypes that have not been directly typed in a GWAS array owing to the creation of the 1000 Genomes reference panels, which contain the largest human variation and genotype data. Consequently, imputation increases the chance of detecting a causal variant or a better tagSNP. There are no published GWASs of elite sprint performance. We conducted an imputation-driven meta-analysis of three GWASs of elite Jamaican, African-American and Japanese sprint athletes in an attempt to identify and understand genes and their functions in elite sprint performance. The initial exploratory data offers further insights into genetic influence on elite human sprint performance. Independent replications and functional analyses on the identified loci are necessary. Future efforts in genetic/genomic research should focus on establishing international multi-centre interdisciplinary research consortia in order to overcome the many limitations typical of single-centre studies such as the reliance on candidate gene analysis of poorly phenotyped and underpowered cohorts. The Athlome Project Consortium (www.athlomeconsortium.org) and the 1000 Athlomes component (using next generation sequencing in a top slice of the endurance ability spectrum) are recent examples of such initiatives and signal a new era in the field of sports and exercise genomics.
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