Department of Exercise Biochemistry, Exercise Science School, Beijing Sport University, Beijing 100084, China.
Exercise Biology Research Center, China Institute of Sport Science, Beijing 100084, China.
Genes (Basel). 2024 Sep 26;15(10):1251. doi: 10.3390/genes15101251.
The aim of this study was to assess the relationship between variant loci significantly associated with sports-related traits in the GWAS Catalog database and sprint/power athlete status, as well as to explore the polygenic profile of elite athletes. Next-generation sequencing and microarray technology were used to genotype samples from 211 elite athletes who had achieved success in national or international competitions in power-based sports and from 522 non-athletes, who were healthy university students with no history of professional sports training. Variant loci collected from databases were extracted after imputation. Subsequently, 80% of the samples were randomly selected as the training set, and the remaining 20% as the validation set. Association analysis of variant loci was conducted in the training set, and individual Total Genotype Score (TGS) were calculated using genotype dosage and lnOR, followed by the establishment of a logistic model, with predictive performance evaluated in the validation set. Association analysis was performed on 2075 variant loci, and after removing linked loci (r > 0.2), 118 Tag SNPs ( ≤ 0.05) were identified. A logistic model built using 30 Tag SNPs ( ≤ 0.01) showed better performance in the validation set (AUC = 0.707). Our study identified 30 new genetic molecular markers and demonstrated that elite sprint/power athlete status is polygenic.
本研究旨在评估 GWAS 目录数据库中与运动相关性状显著相关的变异位点与短跑/力量型运动员身份之间的关系，并探讨精英运动员的多基因特征。 我们使用下一代测序和微阵列技术对 211 名在力量型运动的国家级或国际比赛中取得成功的精英运动员样本和 522 名非运动员样本进行基因分型，这些非运动员是没有专业运动训练史的健康大学生。 在进行推断后，从数据库中提取变异位点。 随后，将 80%的样本随机选择为训练集，其余 20%为验证集。 在训练集中对变异位点进行关联分析，并使用基因型剂量和 lnOR 计算个体总基因型评分（TGS），然后建立逻辑模型，并在验证集中评估预测性能。 对 2075 个变异位点进行关联分析，在去除连锁位点（r > 0.2）后，确定了 118 个 Tag SNPs（ ≤ 0.05）。 使用 30 个 Tag SNPs（ ≤ 0.01）构建的逻辑模型在验证集（AUC = 0.707）中的表现更好。 我们的研究确定了 30 个新的遗传分子标记，并表明精英短跑/力量型运动员的身份是多基因的。
