five

Table_2_Cellular Aspects of Muscle Specialization Demonstrate Genotype – Phenotype Interaction Effects in Athletes.docx

收藏
NIAID Data Ecosystem2026-03-11 收录
下载链接:
https://figshare.com/articles/dataset/Table_2_Cellular_Aspects_of_Muscle_Specialization_Demonstrate_Genotype_Phenotype_Interaction_Effects_in_Athletes_docx/8094605
下载链接
链接失效反馈
官方服务:
资源简介:
IntroductionGene polymorphisms are associated with athletic phenotypes relying on maximal or continued power production and affect the specialization of skeletal muscle composition with endurance or strength training of untrained subjects. We tested whether prominent polymorphisms in genes for angiotensin converting enzyme (ACE), tenascin-C (TNC), and actinin-3 (ACTN3) are associated with the differentiation of cellular hallmarks of muscle metabolism and contraction in high level athletes. MethodsMuscle biopsies were collected from m. vastus lateralis of three distinct phenotypes; endurance athletes (n = 29), power athletes (n = 17), and untrained non-athletes (n = 63). Metabolism-, and contraction-related cellular parameters (such as capillary-to-fiber ratio, capillary length density, volume densities of mitochondria and intramyocellular lipid, fiber mean cross sectional area (MCSA) and volume densities of myofibrils) and the volume densities of sarcoplasma were analyzed by quantitative electron microscopy of the biopsies. Gene polymorphisms of ACE (I/D (insertion/deletion), rs1799752), TNC (A/T, rs2104772), and ACTN3 (C/T, rs1815739) were determined using high-resolution melting polymerase chain reaction (HRM-PCR). Genotype distribution was assessed using Chi2 tests. Genotype and phenotype effects were analyzed by univariate or multivariate analysis of variance and post hoc test of Fisher. P-values below 0.05 were considered statistically significant. ResultsThe athletes demonstrated the specialization of metabolism- and contraction-related cellular parameters. Differences in cellular parameters could be identified for genotypes rs1799752 and rs2104772, and localized post hoc when taking the interaction with the phenotype into account. Between endurance and power athletes these concerned effects on capillary length density for rs1799752 and rs2104772, fiber type distribution and volume densities of myofibrils (rs1799752), and MSCA (rs2104772). Endurance athletes carrying the I-allele of rs1799752 demonstrated 50%-higher volume densities of mitochondria and sarcoplasma, when power athletes that carried only the D-allele showed the highest fiber MCSAs and a lower percentage of slow type muscle fibers. DiscussionACE and tenascin-C gene polymorphisms are associated with differences in cellular aspects of muscle metabolism and contraction in specifically-trained high level athletes. Quantitative differences in muscle fiber type distribution and composition, and capillarization in knee extensor muscle explain, in part, identified associations of the insertion/deletion genotypes of ACE (rs1799752) with endurance- and power-type Sports.

引言 基因多态性与依赖最大或持续功率输出的运动表型密切相关,同时可影响未经训练个体在接受耐力或力量训练后骨骼肌组成的特化过程。本研究旨在探讨血管紧张素转换酶(angiotensin converting enzyme, ACE)、肌腱蛋白-C(tenascin-C, TNC)以及辅肌动蛋白-3(actinin-3, ACTN3)基因的常见多态性,是否与高水平运动员肌肉代谢与收缩的细胞特征分化存在关联。 方法 本研究从3类不同表型个体的股外侧肌(m. vastus lateralis)获取肌肉活检样本:耐力运动员(n=29)、力量运动员(n=17)以及未经训练的非运动员(n=63)。通过对活检样本进行定量电子显微镜分析,检测与代谢及收缩相关的细胞参数,包括毛细血管-纤维比、毛细血管长度密度、线粒体和肌细胞内脂质的体密度、纤维平均横截面积(mean cross sectional area, MCSA)以及肌原纤维的体密度,同时检测肌浆的体密度。采用高分辨率熔解聚合酶链反应(high-resolution melting polymerase chain reaction, HRM-PCR)检测ACE基因的I/D(插入/缺失,rs1799752)多态性、TNC基因的A/T(rs2104772)多态性以及ACTN3基因的C/T(rs1815739)多态性。采用卡方检验(Chi2 tests)分析基因型分布情况;通过单因素或多因素方差分析以及Fisher事后检验分析基因型与表型的效应。将P值<0.05视为具有统计学显著性。 结果 运动员群体呈现出与代谢及收缩相关的细胞参数特化特征。rs1799752与rs2104772基因型的细胞参数存在显著差异,在纳入表型交互效应后,可通过事后检验明确差异的具体定位。在耐力运动员与力量运动员之间,rs1799752的差异主要涉及毛细血管长度密度、肌纤维类型分布以及肌原纤维体密度,rs2104772的差异则涉及毛细血管长度密度与MCSA。携带rs1799752的I等位基因的耐力运动员,其线粒体与肌浆的体密度较对照组高50%;而仅携带D等位基因的力量运动员则表现出最高的纤维MCSA,且慢肌纤维占比更低。 讨论 ACE与肌腱蛋白-C基因多态性与经过专项训练的高水平运动员肌肉代谢与收缩的细胞层面差异相关。膝伸肌中肌纤维类型分布与组成的量化差异,以及毛细血管化程度的差异,可部分解释ACE基因(rs1799752)的插入/缺失基因型与耐力型、力量型运动项目之间的关联。
创建时间:
2019-05-08
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作