Xinrong Zuo, Rui Zhao, Minming Wu, Yanyan Wang, Shisheng Wang, Kuo Tang, Yang Wang, Jie Chen, Xiaoxiang Yan, Yang Cao, Tao Li
{"title":"Multi-omic profiling of sarcopenia identifies disrupted branched-chain amino acid catabolism as a causal mechanism and therapeutic target.","authors":"Xinrong Zuo, Rui Zhao, Minming Wu, Yanyan Wang, Shisheng Wang, Kuo Tang, Yang Wang, Jie Chen, Xiaoxiang Yan, Yang Cao, Tao Li","doi":"10.1038/s43587-024-00797-8","DOIUrl":null,"url":null,"abstract":"<p><p>Sarcopenia is a geriatric disorder characterized by a gradual loss of muscle mass and function. Despite its prevalence, the underlying mechanisms remain unclear, and there are currently no approved treatments. In this study, we conducted a comprehensive analysis of the molecular and metabolic signatures of skeletal muscle in patients with impaired muscle strength and sarcopenia using multi-omics approaches. Across discovery and replication cohorts, we found that disrupted branched-chain amino acid (BCAA) catabolism is a prominent pathway in sarcopenia, which leads to BCAA accumulation and decreased muscle health. Machine learning analysis further supported the causal role of BCAA catabolic dysfunction in sarcopenia. Using mouse models, we validated that defective BCAA catabolism impairs muscle mass and strength through dysregulated mTOR signaling, and enhancing BCAA catabolism by BT2 protects against sarcopenia in aged mice and in mice lacking Ppm1k, a positive regulator of BCAA catabolism in skeletal muscle. This study highlights improving BCAA catabolism as a potential treatment of sarcopenia.</p>","PeriodicalId":94150,"journal":{"name":"Nature aging","volume":" ","pages":""},"PeriodicalIF":17.0000,"publicationDate":"2025-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nature aging","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1038/s43587-024-00797-8","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CELL BIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Sarcopenia is a geriatric disorder characterized by a gradual loss of muscle mass and function. Despite its prevalence, the underlying mechanisms remain unclear, and there are currently no approved treatments. In this study, we conducted a comprehensive analysis of the molecular and metabolic signatures of skeletal muscle in patients with impaired muscle strength and sarcopenia using multi-omics approaches. Across discovery and replication cohorts, we found that disrupted branched-chain amino acid (BCAA) catabolism is a prominent pathway in sarcopenia, which leads to BCAA accumulation and decreased muscle health. Machine learning analysis further supported the causal role of BCAA catabolic dysfunction in sarcopenia. Using mouse models, we validated that defective BCAA catabolism impairs muscle mass and strength through dysregulated mTOR signaling, and enhancing BCAA catabolism by BT2 protects against sarcopenia in aged mice and in mice lacking Ppm1k, a positive regulator of BCAA catabolism in skeletal muscle. This study highlights improving BCAA catabolism as a potential treatment of sarcopenia.