A Potential Endurance Algorithm Prediction in the Field of Sports Performance

Frontiers in Genetics

Gonzalo Colmenarejo¹  Rocio de la Iglesia²  J. Jose Ramos-Alvarez³  Guillermo Reglero⁴  Elena Aguilar-Aguilar⁶  Ana Ramirez-de Molina⁶  Helena Marcos-Pasero⁶  Elena Borregon-Rivilla⁶  Isabel Espinosa-Salinas⁶  Viviana Loria-Kohen⁶  F. Javier Lopez-Silvarrey⁷  J. Carlos Segovia⁷ 

[1] Biostatistics and Bioinformatics Unit, IMDEA Food CEI UAM + CSIC, Madrid, Spain;Departamento de Ciencias Farmacéuticas y de la Salud, Facultad de Farmacia, Universidad San Pablo-CEU, CEU Universities, Alcorcón, Spain;Departamento de Radiología, Rehabilitación y Fisioterapia, Universidad Complutense de Madrid, Madrid, Spain;Department of Production and Characterization of Novel Foods, Institute of Food Science Research (CIAL) CEI UAM + CSIC, Madrid, Spain;Facultad de Ciencias de la Salud, Universidad Camilo José Cela, Madrid, Spain;Nutrition and Clinical Trials Unit, GENYAL Platform IMDEA-Food Institute, CEI UAM + CSIC, Madrid, Spain;Sannus Clinic, Madrid, Spain;

关键词: SNP;    genetics;    exercise;    functional validation;    nutrition;   

DOI  :  10.3389/fgene.2020.00711

来源: DOAJ

【 摘 要 】

Sport performance is influenced by several factors, including genetic susceptibility. In the past years, specific single nucleotide polymorphisms have been associated to sport performance; however, these effects should be considered in multivariable prediction systems since they are related to a polygenic inheritance. The aim of this study was to design a genetic endurance prediction score (GES) of endurance performance and analyze its association with anthropometric, nutritional and sport efficiency variables in a cross-sectional study within fifteen male cyclists. A statistically significant positive relationship between GES and the VO2 maximum (P = 0.033), VO2 VT1 (P = 0.049) and VO2 VT2 (P < 0.001) was observed. Moreover, additional remarkable associations between genotype and the anthropometric, nutritional and sport performance variables, were achieved. In addition, an interesting link between the habit of consuming caffeinated beverages and the GES was observed. The outcomes of the present study indicate a potential use of this genetic prediction algorithm in the sports’ field, which may facilitate the finding of genetically talented athletes, improve their training and food habits, as well as help in the improvement of physical conditions of amateurs.

【 授权许可】

Unknown