Mei Tao, Li Yanchun, Bao Dapeng, Yang Xiangang, Yang Xiaolin, Li Liang, He Zihong
China Institute of Sport and Health Science, Beijing Sport University, Beijing, China.
Beijing Key Laboratory of Sports Performance and Skill Assessment, Beijing Sport University, Beijing, China.
Biol Sport. 2025 Jan 14;42(3):3-15. doi: 10.5114/biolsport.2025.145918. eCollection 2025 Jul.
This study aimed to identify genetic variations associated with changes in isometric strength following resistance training and develop a predictive model for understanding training effects, providing insights for tailored fitness guidance. A 12-week resistance training program, consisting of traditional squats and bench press exercises, was completed by 193 healthy Chinese adults, with isometric strength assessed before and after the intervention. DNA was extracted for whole-genome genotyping, followed by genomewide association analysis using PLINK 1.9. Lasso regression was used to screen variables, and predictive models for training effectiveness were established using logistic regression, Nomogram, and stepwise linear regression. Following the training, participants showed an increased isometric strength (Δ = 8.69%, p = 0.08, ES = 0.07), ranging from -55.78% to 133.47%. Nineteen lead SNPs were significantly associated with improvements in lower limb isometric strength (p < 1 × 10), with 8 SNPs showing nominal associations (p < 1 × 10), and rs4623258 was the only SNP with genome-wide significance (p < 5 × 10). Stepwise linear regression identified several factors that impact training effects: baseline isometric strength, lower limb muscle mass, right rectus femoris length, rs4623258, rs344843, rs112298078, rs200507975, rs559077, rs8008364, rs6837485, rs4712860, rs76521421, rs1965365, and rs2746086 (adjusted R = 0.704). Logistic regression identified isometric strength, lean body mass, trunk fat, right rectus femoris length, rs139338397, rs76521421, rs8008364, and rs6579275 as significant factors influencing the outcome. (AUC = 0.875, p < 0.001). These findings show that predictive models can accurately predict changes in lower limb isometric strength after resistance training in Chinese subjects. However, applicability is primarily confined to East Asians, necessitating further studies in diverse populations to validate broader relevance.
本研究旨在确定与抗阻训练后等长肌力变化相关的基因变异,并开发一种预测模型以理解训练效果,为个性化健身指导提供见解。193名健康的中国成年人完成了一项为期12周的抗阻训练计划,该计划包括传统深蹲和卧推练习,并在干预前后评估了等长肌力。提取DNA进行全基因组基因分型,随后使用PLINK 1.9进行全基因组关联分析。使用套索回归筛选变量,并使用逻辑回归、列线图和逐步线性回归建立训练效果的预测模型。训练后,参与者的等长肌力有所增加(Δ = 8.69%,p = 0.08,ES = 0.07),范围从 -55.78% 到133.47%。19个领先单核苷酸多态性(SNPs)与下肢等长肌力的改善显著相关(p < 1×10),8个SNPs显示出名义上的关联(p < 1×10),而rs4623258是唯一具有全基因组显著性的SNP(p < 5×10)。逐步线性回归确定了几个影响训练效果的因素:基线等长肌力、下肢肌肉质量、右股直肌长度、rs4623258、rs344843、rs112298078、rs200507975、rs559077、rs8008364、rs6837485、rs4712860、rs76521421、rs1965365和rs2746086(调整后R = 0.704)。逻辑回归确定等长肌力、瘦体重、躯干脂肪、右股直肌长度、rs139338397、rs76521421、rs8008364和rs6579275是影响结果的显著因素(AUC = 0.875,p < 0.001)。这些发现表明,预测模型可以准确预测中国受试者抗阻训练后下肢等长肌力的变化。然而,其适用性主要局限于东亚人群,需要在不同人群中进行进一步研究以验证更广泛的相关性。