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  • 1.
    Mattsson, C. Mikael
    et al.
    Swedish School of Sport and Health Sciences, GIH, Department of Sport and Health Sciences.
    Wheeler, Matthew
    Stanford University.
    Waggott, Daryl
    Stanford University.
    Caleshu, Colleen
    Stanford University.
    Ashley, Euan A.
    Stanford University.
    Sports genetics moving forward - lessons learned from medical research2016In: Physiological Genomics, ISSN 1094-8341, E-ISSN 1531-2267, Vol. 48, no 3, p. 175-182Article in journal (Refereed)
    Abstract [en]

    Sports genetics can take advantage of lessons learned from human disease genetics. By righting past mistakes and increasing scientific rigor, the breadth and depth of knowledge in the field can be magnified. We present an outline of challenges facing sports genetics in the light of experiences from medical research.

    Sports performance is complex, resulting from a combination of a wide variety of different traits and attributes.  Improving sports genetics will foremost require analyses based on detailed phenotyping. In order to find widely valid, reproducible common variants associated with athletic phenotypes, study sample sizes must be dramatically increased. One paradox is that in order to confirm relevance, replications in specific populations must be undertaken. Family studies of athletes may facilitate the discovery of rare variants with large effects on athletic phenotypes. The complexity of the human genome, combined with the complexity of athletic phenotypes, will require additional metadata and biological validation to identify a comprehensive set of genes involved.

    Analysis of personal genetic and multiomic profiles contribute to our conceptualization of precision medicine; the same will be the case in precision sports science. In the refinement of sports genetics it is essential to evaluate similarities and differences between genders and among ethnicities. Sports genetics to date have been hampered by small sample sizes and biased methodology which can lead to erroneous associations and overestimation of effect sizes. Consequently, currently available genetic tests based on these inherently limited data cannot predict athletic performance with any accuracy.

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