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Get Free AccessDespite numerous attempts to discover genetic variants associated with elite athletic performance, injury predisposition, and elite/world-class athletic status, there has been limited progress to date. Past reliance on candidate gene studies predominantly focusing on genotyping a limited number of single nucleotide polymorphisms or the insertion/deletion variants in small, often heterogeneous cohorts (i.e., made up of athletes of quite different sport specialties) have not generated the kind of results that could offer solid opportunities to bridge the gap between basic research in exercise sciences and deliverables in biomedicine. A retrospective view of genetic association studies with complex disease traits indicates that transition to hypothesis-free genome-wide approaches will be more fruitful. In studies of complex disease, it is well recognized that the magnitude of genetic association is often smaller than initially anticipated, and, as such, large sample sizes are required to identify the gene effects robustly. A symposium was held in Athens and on the Greek island of Santorini from 14–17 May 2015 to review the main findings in exercise genetics and genomics and to explore promising trends and possibilities. The symposium also offered a forum for the development of a position stand (the Santorini Declaration). Among the participants, many were involved in ongoing collaborative studies (e.g., ELITE, GAMES, Gene SMART, GENESIS, and POWERGENE). A consensus emerged among participants that it would be advantageous to bring together all current studies and those recently launched into one new large collaborative initiative, which was subsequently named the Athlome Project Consortium.
Yannis Pitsiladis, Masashi Tanaka, Nir Eynon, Claude Bouchard, Kathryn N. North, Alun G. Williams, Malcolm Collins, Colin N. Moran, Steven L. Britton, Noriyuki Fuku, Euan A. Ashley, Vassilis Klissouras, Alejandro Lucía, Ildus I. Ahmetov, Eco J. C. de Geus, Mohammed Alsayrafi (2015). Athlome Project Consortium: a concerted effort to discover genomic and other “omic” markers of athletic performance. Physiological Genomics, 48(3), pp. 183-190, DOI: 10.1152/physiolgenomics.00105.2015.
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Type
Article
Year
2015
Authors
16
Datasets
0
Total Files
0
Language
English
Journal
Physiological Genomics
DOI
10.1152/physiolgenomics.00105.2015
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