Prediction and Identification of Power Performance Using Polygenic Models of Three Single-Nucleotide Polymorphisms in Chinese Elite Athletes

• DOI: 10.3389/fgene.2021.726552
• Publication Date: 2021-10-10T20:24:37Z
• Authors: Ruoyu Yang; Feng Jin; Liyan Wang; Xunzhang Shen; Qi Guo; Haihan Song; Jingyun Hu; Qiang Zhao; Jian Wan; Ming Cai
• Keywords: Nomogram; Elite Athletes

Objective: The manuscript aims to explore the relationship between power performance and SNPs of Chinese elite athletes create polygenic models. Methods: One hundred three were divided into group ( n = 60) endurance 43) by their sports event. Best standing long jump (SLJ) vertical (SVJ) collected. Twenty genotyped SNaPshot. Genotype distribution allele frequency compared groups. Additional genotype data 125 used verify screened SNPs. Predictive identifying models established multivariate logistic regression analysis. Results: ACTN3 (rs1815739), ADRB3 (rs4994), CNTFR (rs2070802), PPARGC1A (rs8192678) significantly different in or groups p < 0.05). predictive model consisted (rs8192678), area under curve (AUC) which was 0.736. body mass index (BMI), (SVJ), ACTN3, ADRB3, PPARGC1A, 0.854. Based on two models, nomograms created visualize results. Conclusion: Two can be for talent identification athletes, among adolescent predict development potential one evaluate athletic status. These applied quickly visually using nomograms. When score is more than 130 148 cutoff, it suggests that athlete has a good high level performance.