高强度间歇运动改善定量负荷运动心率效果的全基因组关联分析及预测模型构建  

Genome Wide Association Study of the Exercise Heart Rate Response to High Intensity Interval Training and the Predicting Model Construction

作　　者：杨晓琳[1] 李燕春[1] 包大鹏[1] 梅涛[1] 周多奇 乌云格日勒 聂晶[5] 夏小慧[6] 张之豪 顾壮壮 何子红[2] Yang Xiaolin;Li Yanchun;Bao Dapeng;Mei Tao;Zhou Duoqi;Wuyun Gerile;Nie Jing;Xia Xiaohui;Zhang Zhihao;Gu Zhuangzhuang;He Zihong(Beijing Sport University,Beijing 100084,China;China Institute of Sport Science,Beijing 100061,China;Anqing Normal University,Anqing 246133,China;Inner Mongolia Normal University,Hohhot 010022,China;Jiangxi Normal University,Nanchang 330022,China;Lanzhou City University,Lanzhou 730070,China)

机构地区：[1]北京体育大学,北京100084 [2]国家体育总局体育科学研究所,北京100061 [3]安庆师范大学,安庆246133 [4]内蒙古师范大学,呼和浩特010022 [5]江西师范大学,南昌330022 [6]兰州城市学院,兰州730070

出　　处：《中国运动医学杂志》2023年第7期505-517,共13页Chinese Journal of Sports Medicine

基　　金：国家重点研发计划(2018YFC2000602);中央高校基本科研业务费专项资金资助(2021TD003)。

摘　　要：目的:安静心率、运动中心率的增加以及运动后心率恢复是全因死亡率的预测因子,是运动健身中最常用的监控指标。本研究旨在分析高强度间歇运动(high intensity interval training,HIIT)改善定量负荷运动心率个体差异的表型和遗传因素,构建运动心率改善效果预测模型,为个体化运动健身方案的制定提供依据。方法:240名身体活动不足健康成年人完成12周HIIT,提取血液白细胞DNA进行全基因组解析,通过包括520多万个单核苷酸多态性位点(single nucleotide polymorphisms,SNPs)的全基因组关联分析(genome wide association study,GWAS)筛选影响运动心率改善效果的遗传标记,构建运动心率改善效果分子标记预测模型;计算权重后的多基因预测评分(polygenic predictor score,PPS),联合表型和遗传指标通过线性逐步回归构建运动心率改善效果预测模型。结果:(1)12周HIIT后,定量负荷运动心率显著下降(P<0.05),但效果存在个体差异,27%的受试者未有效降低运动心率(ΔHR≥0);(2)表型指标中初始运动心率、性别和年龄是HIIT改善运动心率效果的预测因子,可解释24.5%的效果差异;(3)基于GWAS筛选出12个效果相关SNPs(P<1×10^(-5)),去除冗余,由其中10个SNPs构建的分子标记预测模型可解释训练效果差异的37.7%,单个SNP的解释度在1.2%~8.1%;PPS高于11.45分时,HIIT对运动心率降低完全无效(ΔHR≥0),当PPS低于-7.728分时,HIIT改善运动心率效果最好(ES<-0.8)。(4)联合表型和遗传指标构建的综合预测模型中,PPS、初始运动心率、性别和年龄是HIIT改善运动心率效果的预测因子,可在62.5%的程度上共同解释HIIT改善运动心率效果个体差异。结论:多基因预测评分、初始运动心率、性别和年龄可有效预测HIIT改善定量负荷运动心率效果个体差异。受试者的PPS高于11.45分时无训练效果,低于-7.728分时效果最佳。基于遗传和表型因素构建的运动心率改善�Objective Resting heart rate(RHR),heart rate(HR)increase during exercise and the HR recovery are the predictors of all-cause mortality and are extensively monitored in exercise.This study aims to analyze the genomic and phenotypic factors contributing to the inter-individual variations in the exercise HR response following the 12-week high intensity interval training(HIIT),construct the predicting model for the exercise HR response,and provide recommendations on the tailored exer⁃cise protocols.Methods A total of 240 physically inactive healthy adults completed a 12-week HIIT and their leukocyte DNA was extracted from the whole blood sample for genome-wide analysis.A ge⁃nome wide association study(GWAS),which included 5.2 millions single nucleotide polymorphisms(SNPs),was performed on the exercise HR response of HIIT.The lead SNPs associated with the exer⁃cise HR response were identified and the genetic predicting model for the exercise HR response was constructed.A polygenic predictor score(PPS)derived from the leading variants was calculated and the multiple linear stepwise regression model was constructed to predict the HR response of 12-week HI⁃IT.Results(1)After 12-week HIIT,the exercise HR showed a significant reduction with inter-individ⁃ual variability(P<0.05),with approximately 27%of participants being non-responders(ΔHR≥0).(2)Baseline exercise HR,sex and age were the predictive factors for the exercise HR response after 12-week HIIT,and could explain 24.5%of the variance in inter-individual response.(3)A total of 12 lead SNPs were significantly associated with the exercise HR response according to GWAS(P<1×10^(-5)).Moreover,the PPS calculated from the ten lead SNPs could explain 37.7%of the variance in the exer⁃cise HR response,with each SNP explaining 1.2%to 8.1%.However,the individual with the PPS greater than 11.45 couldn’t decrease the exercise HR after 12-week HIIT(ΔHR≥0)whereas those with a PPS below-7.728 could reach the highest response in the exercise HR(ES<-0.8).(4)The PPS

关 键 词：全基因组关联分析 运动心率 高强度间歇运动 多基因预测评分 

分 类 号：R87[医药卫生—运动医学] G804.2[医药卫生—临床医学]