Suppr超能文献

多基因模型可部分预测老年女性的肌肉大小和力量,但不能预测低肌肉量。

Polygenic Models Partially Predict Muscle Size and Strength but Not Low Muscle Mass in Older Women.

机构信息

Musculoskeletal Science and Sports Medicine Research Centre, Department of Sport and Exercise Sciences, Manchester Metropolitan University Institute of Sport, Manchester Metropolitan University, Manchester M15 6BH, UK.

Physical Activity, Sports & Health Research Group, Department of Movement Sciences, KU Leuven, 3001 Leuven, Belgium.

出版信息

Genes (Basel). 2022 May 30;13(6):982. doi: 10.3390/genes13060982.

Abstract

Background: Heritability explains 45-82% of muscle mass and strength variation, yet polygenic models for muscle phenotypes in older women are scarce. Therefore, the objective of the present study was to (1) assess if total genotype predisposition score (GPSTOTAL) for a set of polymorphisms differed between older women with low and high muscle mass, and (2) utilise a data-driven GPS (GPSDD) to predict the variance in muscle size and strength-related phenotypes. Methods: In three-hundred 60- to 91-year-old Caucasian women (70.7 ± 5.7 years), skeletal muscle mass, biceps brachii thickness, vastus lateralis anatomical cross-sectional area (VLACSA), hand grip strength (HGS), and elbow flexion (MVCEF) and knee extension (MVCKE) maximum voluntary contraction were measured. Participants were classified as having low muscle mass if the skeletal muscle index (SMI) < 6.76 kg/m2 or relative skeletal muscle mass (%SMMr) < 22.1%. Genotyping was completed for 24 single-nucleotide polymorphisms (SNPs). GPSTOTAL was calculated from 23 SNPs and compared between the low and high muscle mass groups. A GPSDD was performed to identify the association of SNPs with other skeletal muscle phenotypes. Results: There was no significant difference in GPSTOTAL between low and high muscle mass groups, irrespective of classification based on SMI or %SMMr. The GPSDD model, using 23 selected SNPs, revealed that 13 SNPs were associated with at least one skeletal muscle phenotype: HIF1A rs11549465 was associated with four phenotypes and, in descending number of phenotype associations, ACE rs4341 with three; PTK2 rs7460 and CNTFR rs2070802 with two; and MTHFR rs17421511, ACVR1B rs10783485, CNTF rs1800169, MTHFR rs1801131, MTHFR rs1537516, TRHR rs7832552, MSTN rs1805086, COL1A1 rs1800012, and FTO rs9939609 with one phenotype. The GPSDD with age included as a predictor variable explained 1.7% variance of biceps brachii thickness, 12.5% of VLACSA, 19.0% of HGS, 8.2% of MVCEF, and 9.6% of MVCKE. Conclusions: In older women, GPSTOTAL did not differ between low and high muscle mass groups. However, GPSDD was associated with muscle size and strength phenotypes. Further advancement of polygenic models to understand skeletal muscle function during ageing might become useful in targeting interventions towards older adults most likely to lose physical independence.

摘要

背景

遗传因素可解释 45-82%的肌肉质量和力量变化,但老年人肌肉表型的多基因模型却很少。因此,本研究的目的是:(1) 评估一组多态性的总基因型倾向评分 (GPSTOTAL) 是否在肌肉质量低和高的老年女性之间存在差异;(2) 利用数据驱动的 GPS (GPSDD) 预测肌肉大小和与力量相关的表型的方差。

方法

在 300 名 60-91 岁的白种人女性(70.7 ± 5.7 岁)中,测量骨骼肌质量、肱二头肌厚度、股外侧肌解剖横截面积 (VLACSA)、手握力 (HGS)、肘屈肌 (MVCEF) 和膝伸肌 (MVCKE) 最大自主收缩。如果骨骼肌指数 (SMI) < 6.76 kg/m2 或相对骨骼肌质量 (%SMMr) < 22.1%,则将参与者归类为肌肉质量低。完成了 24 个单核苷酸多态性 (SNP) 的基因分型。从 23 个 SNP 中计算了 GPSTOTAL,并在低肌肉质量组和高肌肉质量组之间进行了比较。进行了 GPSDD 以确定 SNP 与其他骨骼肌表型的关联。

结果

无论基于 SMI 还是 %SMMr 进行分类,低肌肉质量组和高肌肉质量组之间的 GPSTOTAL 均无显著差异。使用 23 个选定 SNP 的 GPSDD 模型显示,13 个 SNP 与至少一种骨骼肌表型相关:HIF1A rs11549465 与四种表型相关,按表型关联数量递减,ACE rs4341 与三种相关;PTK2 rs7460 和 CNTFR rs2070802 与两种相关;MTHFR rs17421511、ACVR1B rs10783485、CNTF rs1800169、MTHFR rs1801131、MTHFR rs1537516、TRHR rs7832552、MSTN rs1805086、COL1A1 rs1800012 和 FTO rs9939609 与一种表型相关。将年龄作为预测变量纳入 GPSDD 可解释肱二头肌厚度的 1.7%、VLACSA 的 12.5%、HGS 的 19.0%、MVCEF 的 8.2%和 MVCKE 的 9.6%的方差。

结论

在老年女性中,低肌肉质量组和高肌肉质量组之间的 GPSTOTAL 没有差异。然而,GPSDD 与肌肉大小和力量表型相关。进一步推进多基因模型以了解衰老过程中的骨骼肌功能,可能有助于针对最有可能失去身体独立性的老年人进行干预。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd3f/9223182/dfd76837ffaa/genes-13-00982-g001.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验