1. The Athlome Project Consortium: A Concerted Effort to Discover Genomic and other 'OMIC' Markers of Athletic Performance
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Pitsiladis, Y. P., Tanaka, M., Eynon, N., Bouchard, C., North, K. N., Williams, A. G., Collins, M., Moran, C. N., Britton, S. L., Fuku, N., Ashley, E. A., Klissouras, V., Lucia, A., Ahmetov, I. I., De Geus, E., Alsayrafi, M., Webborn, N., Wang, G., Bishop, D. J., Papadimitriou, I., Yan, X., Tirosh, O., Kuang, J., Rankinen, T., Sarzinsky, M., Mikael Mattsson, C., Wheeler, M., Waggott, D., Byrne, N. M., Artioli, G. G., September, A., Posthumus, M., Van der Merwe, W., Cieszczyk, P., Leonska-Duniec, A., Ficek, K., Maciejewska-Karlowska, A., Sawczuk, M., Stepien-Slodkowska, M., Feller, J., Dijkstra, P., Chmutov, A. M., Dyatlov, D. A., Orekhov, E. F., Pushkareva, Y. E., Shvedkaya, I. A., Massidda, M., Calo, C. M., Day, S. H., Stebbings, G. K., Erskine, R. M., Montgomery, H. E., Garton, F. C., Houweling, P., Derave, W., Baguet, A., Muniesa, C. A., Sessa, F., Petito, A., Sale, C., Hughes, D. C., Varley, I., Boomsma, D., Bartels, M., Davies, G. E., Gineviciene, V., Jakaitiene, A., Kucinskas, V., Tubelis, L., Utkus, A., Milasius, K., Venckunas, T., Skurvydas, A., Stasiulis, A., Malkova, D., Wilson, R., Koch, L. G., Zempo, H., Naito, H., Kikuchi, N., Miyamoto-Mikami, E., Murakami, H., Miyachi, M., Takahashi, H., Ohiwa, N., Kawahara, T., Tsuchie, H., Tobina, T., Ichinoseki-Sekine, N., Tanaka, H., Kaneoka, K., Nakazato, K., Egorova, E. S., Gabdrakhmanova, L. J., Arkhipova, A. A., Borisova, A. V., Gabbasov, R. T., Stepanova, A. A., Kashapov, R. I., Rogozkin, V. A., Astratenkova, I. V., Druzhevskaya, A. M., Fedotovskaya, O. N., Golberg, N. D., Hakimullina, A. M., Kostryukova, E. S., Alexeev, D. G., Generozov, E. V., Ischenko, D. S., Kulemin, N. A., Larin, A. K., Ospanova, E. A., Pavlenko, A. V., Govorun, V. M., Gilep, A. A., Gilep, I. L., Haidukevich, I. V., Rybina, I. L., Drozdovska, S. B., Docenko, V. E., Ilyin, V. N., Lekontsev, E., Akimov, E. B., El-Rayess, M., Georgakopoulos, C., Botre, F., Suhre, K., Hubank, M., Wolfarth, B., Greeves, J. P., Stellingwerff, T., Ranson, C., Fraser, W. D., Grealy, R., Griffiths, L., Scott, R., Pushkarev, V. P., Biological Psychology, EMGO+ - Lifestyle, Overweight and Diabetes, and Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep
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0301 basic medicine ,Candidate gene ,Physiology ,Sports genomics ,Performance ,Declaration ,Genomics ,Tissue Banks ,Athletic Performance ,Genética humana ,Epigenesis, Genetic ,RC1200 ,03 medical and health sciences ,0302 clinical medicine ,SDG 17 - Partnerships for the Goals ,Genetic ,Atleta ,Genetics ,Animals ,Humans ,QH426 ,Biomedicine ,Genetic association ,Atletismo ,biology ,Athletes ,business.industry ,Call for Papers: Systems Biology and Polygenic Traits ,030229 sport sciences ,Atletas ,Deporte ,biology.organism_classification ,QP ,Data science ,Biobank ,Europe ,030104 developmental biology ,Elite ,business ,Biomarkers ,Epigenesis - Abstract
Despite 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 (SNPs) or the insertion/deletion variants in small, often heterogeneous cohorts 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 associations is often smaller than initially anticipated and, as such, large sample sizes are required to identify them robustly. Thus, alternative approaches involving large-scale, collaborative efforts, within which high-resolution genome-wide data is generated and interrogated using advanced bioinformatics approaches, are likely necessary for meaningful progress to be made. Accordingly, a symposium was held on the Greek island of Santorini from 14-17th May 2015 to review the main findings in exercise genetics and genomics and to explore promising trends and possibilities. The symposium offered a forum for the development of a position stand. Among the participants, many were involved in ongoing collaborative studies. 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. Sin financiación 3.044 JCR (2016) Q2, 26/84 Physiology, 68/167 Genetics and Heredity; Q3, 104/190 Cell Biology 1.448 SJR (2016) Q2, 106/351 Genetics, 47/191 Physiology No data IDR 2016 UEM
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- 2016