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de la Iglesia R, Espinosa-Salinas I, Lopez-Silvarrey FJ, Ramos-Alvarez JJ, Segovia JC, Colmenarejo G, Borregon-Rivilla E, Marcos-Pasero H, Aguilar-Aguilar E, Loria-Kohen V, Reglero G, Ramirez-de Molina A. A Potential Endurance Algorithm Prediction in the Field of Sports Performance. Front Genet 2020; 11:711. [PMID: 32849773 PMCID: PMC7431952 DOI: 10.3389/fgene.2020.00711] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2020] [Accepted: 06/11/2020] [Indexed: 11/13/2022] Open
Abstract
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.
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Affiliation(s)
- Rocio de la Iglesia
- Departamento de Ciencias Farmacéuticas y de la Salud, Facultad de Farmacia, Universidad San Pablo-CEU, CEU Universities, Alcorcón, Spain
| | - Isabel Espinosa-Salinas
- Nutrition and Clinical Trials Unit, GENYAL Platform IMDEA-Food Institute, CEI UAM + CSIC, Madrid, Spain
| | - F Javier Lopez-Silvarrey
- Facultad de Ciencias de la Salud, Universidad Camilo José Cela, Madrid, Spain.,Sannus Clinic, Madrid, Spain
| | - J Jose Ramos-Alvarez
- Departamento de Radiología, Rehabilitación y Fisioterapia, Universidad Complutense de Madrid, Madrid, Spain
| | - J Carlos Segovia
- Facultad de Ciencias de la Salud, Universidad Camilo José Cela, Madrid, Spain.,Sannus Clinic, Madrid, Spain
| | - Gonzalo Colmenarejo
- Biostatistics and Bioinformatics Unit, IMDEA Food CEI UAM + CSIC, Madrid, Spain
| | - Elena Borregon-Rivilla
- Nutrition and Clinical Trials Unit, GENYAL Platform IMDEA-Food Institute, CEI UAM + CSIC, Madrid, Spain
| | - Helena Marcos-Pasero
- Nutrition and Clinical Trials Unit, GENYAL Platform IMDEA-Food Institute, CEI UAM + CSIC, Madrid, Spain
| | - Elena Aguilar-Aguilar
- Nutrition and Clinical Trials Unit, GENYAL Platform IMDEA-Food Institute, CEI UAM + CSIC, Madrid, Spain
| | - Viviana Loria-Kohen
- Nutrition and Clinical Trials Unit, GENYAL Platform IMDEA-Food Institute, CEI UAM + CSIC, Madrid, Spain
| | - Guillermo Reglero
- Nutrition and Clinical Trials Unit, GENYAL Platform IMDEA-Food Institute, CEI UAM + CSIC, Madrid, Spain.,Department of Production and Characterization of Novel Foods, Institute of Food Science Research (CIAL) CEI UAM + CSIC, Madrid, Spain
| | - Ana Ramirez-de Molina
- Nutrition and Clinical Trials Unit, GENYAL Platform IMDEA-Food Institute, CEI UAM + CSIC, Madrid, Spain
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