Metabolome-Wide Mendelian Randomization Assessing the Causal Relationship Between Blood Metabolites and Sarcopenia-Related Traits.

Simin Chen, Yiran Dong, Nuerbiyamu Aiheti, Jie Wang, Shikang Yan, Kaidiriyan Kuribanjiang, Huilong Li, Xing Peng, Abudunaibi Wupuer, Yihan Li, Lei Yang, Jianping Zhao
{"title":"Metabolome-Wide Mendelian Randomization Assessing the Causal Relationship Between Blood Metabolites and Sarcopenia-Related Traits.","authors":"Simin Chen, Yiran Dong, Nuerbiyamu Aiheti, Jie Wang, Shikang Yan, Kaidiriyan Kuribanjiang, Huilong Li, Xing Peng, Abudunaibi Wupuer, Yihan Li, Lei Yang, Jianping Zhao","doi":"10.1093/gerona/glae051","DOIUrl":null,"url":null,"abstract":"<p><p>Sarcopenia is among the most common musculoskeletal illnesses, yet its underlying biochemical mechanisms remain incompletely understood. In this study, we used Mendelian randomization (MR) to investigate the causal relationship between the genetically determined blood metabolites and sarcopenia, with the overall objective of identifying likely molecular pathways for sarcopenia. We used 2-sample MR to investigate the effects of blood metabolites on sarcopenia-related traits. 452 metabolites were exposure, and 3 sarcopenia-related traits as the outcomes: handgrip strength, appendicular lean mass, and walking pace. The inverse-variance weighted (IVW) causal estimates were determined. For sensitivity analysis, methods such as MR-Egger regression, the weighted median, the weighted mode, and the heterogeneity test were used. Additionally, for complementation, we performed replication, meta-analysis, and metabolic pathway analyses. Candidate biomarkers were defined by meeting one of the following criteria: (1) significant metabolites are defined as pIVW < pBonferroni [1.11 × 10-4 (.05/452)]; (2) strong metabolites are defined as 4 MR methods p < .05; and (3) suggestive metabolites are defined as passing sensitivity analysis. Three metabolites (creatine, 1-arachidonoylglycerophosphocholine, and pentadecanoate [15:0]) with significant causality, 3 metabolites (glycine, 1-arachidonoylglycerophosphocholine, and epiandrosterone sulfate) with strong causality, and 25 metabolites (including leucylleucin, pyruvic acid, etc.) with suggestive causality were associated with sarcopenia-related traits. After further replication analyses and meta-analysis, these metabolites maintained substantial effects on sarcopenia-related traits. We additionally identified 14 important sarcopenia-related trait metabolic pathways. By combining metabolomics with genomics, these candidate metabolites and metabolic pathways identified in our study may provide new clues regarding the mechanisms underlying sarcopenia.</p>","PeriodicalId":94243,"journal":{"name":"The journals of gerontology. Series A, Biological sciences and medical sciences","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The journals of gerontology. Series A, Biological sciences and medical sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/gerona/glae051","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Sarcopenia is among the most common musculoskeletal illnesses, yet its underlying biochemical mechanisms remain incompletely understood. In this study, we used Mendelian randomization (MR) to investigate the causal relationship between the genetically determined blood metabolites and sarcopenia, with the overall objective of identifying likely molecular pathways for sarcopenia. We used 2-sample MR to investigate the effects of blood metabolites on sarcopenia-related traits. 452 metabolites were exposure, and 3 sarcopenia-related traits as the outcomes: handgrip strength, appendicular lean mass, and walking pace. The inverse-variance weighted (IVW) causal estimates were determined. For sensitivity analysis, methods such as MR-Egger regression, the weighted median, the weighted mode, and the heterogeneity test were used. Additionally, for complementation, we performed replication, meta-analysis, and metabolic pathway analyses. Candidate biomarkers were defined by meeting one of the following criteria: (1) significant metabolites are defined as pIVW < pBonferroni [1.11 × 10-4 (.05/452)]; (2) strong metabolites are defined as 4 MR methods p < .05; and (3) suggestive metabolites are defined as passing sensitivity analysis. Three metabolites (creatine, 1-arachidonoylglycerophosphocholine, and pentadecanoate [15:0]) with significant causality, 3 metabolites (glycine, 1-arachidonoylglycerophosphocholine, and epiandrosterone sulfate) with strong causality, and 25 metabolites (including leucylleucin, pyruvic acid, etc.) with suggestive causality were associated with sarcopenia-related traits. After further replication analyses and meta-analysis, these metabolites maintained substantial effects on sarcopenia-related traits. We additionally identified 14 important sarcopenia-related trait metabolic pathways. By combining metabolomics with genomics, these candidate metabolites and metabolic pathways identified in our study may provide new clues regarding the mechanisms underlying sarcopenia.

全代谢组孟德尔随机化评估血液代谢物与肌肉疏松症相关特征之间的因果关系。
肌肉疏松症是最常见的肌肉骨骼疾病之一,但人们对其潜在的生化机制仍知之甚少。在这项研究中,我们采用孟德尔随机化方法(MR)来研究由基因决定的血液代谢物与肌肉疏松症之间的因果关系,总体目标是找出可能导致肌肉疏松症的分子途径。我们采用双样本 MR 方法研究血液代谢物对肌肉疏松症相关性状的影响。我们暴露了 452 种代谢物,并以三种与肌肉疏松症相关的性状为结果:手握强度、关节瘦体重和步行速度。确定了反方差加权(IVW)因果估计值。在敏感性分析中,使用了 MR-Egger 回归、加权中位数、加权模式和异质性检验等方法。此外,为了进行补充,我们还进行了复制、荟萃分析和代谢通路分析。候选生物标志物的定义需满足以下标准之一:(1) 重要的代谢物定义为 Pivw
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信