Qijun Wang, Xuan Zhao, Wei Wang, Xiaolong Chen, Shibao Lu
{"title":"Identification of novel biomarkers and drug targets for frailty-related skeletal muscle aging: a multi-omics study.","authors":"Qijun Wang, Xuan Zhao, Wei Wang, Xiaolong Chen, Shibao Lu","doi":"10.1093/qjmed/hcaf108","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Skeletal muscle aging is the major cause and hallmark of frailty, which poses a significant challenge to the healthcare system.</p><p><strong>Aim: </strong>This study aimed to identify the potential biomarkers for the early detection and therapeutic intervention of this age-related condition.</p><p><strong>Methods: </strong>A transcriptomics-based methodology using machine learning algorithms was performed to select the biomarker genes. A predictive machine learning model for (pre-)frailty based on the transcriptomic profile of the biomarker genes was constructed and validated. The cell-type specific changes of the biomarkers during muscle aging were investigated in a single-cell RNA sequencing dataset of human skeletal muscle. Summary data-based Mendelian randomization (SMR) and Bayesian colocalization analyses were performed to identify biomarker genes with therapeutic effects on frailty-related skeletal muscle aging, and drug candidates were explored in the DSigDB database.</p><p><strong>Results: </strong>We identified 24 biomarker genes, most of which were discovered for the first time. The optimal predictive model showed excellent performance in the external test set. Differential expression of the biomarkers in the single-cell dataset indicated a critical role of endothelial cells modulated by the marker genes MGP and ID1 in muscle degeneration. The SMR and colocalization analyses showed causal relationships between 2 marker genes (MGP and WAC) and frailty-related muscle aging. Potential therapeutics for MGP modulation were identified in the DSigDB database.</p><p><strong>Conclusions: </strong>This multi-omics study identified biomarkers associated with frailty-related muscle aging and provided new insights into the etiology and therapeutic targets for this age-related condition.</p>","PeriodicalId":20806,"journal":{"name":"QJM: An International Journal of Medicine","volume":" ","pages":""},"PeriodicalIF":7.3000,"publicationDate":"2025-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"QJM: An International Journal of Medicine","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1093/qjmed/hcaf108","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MEDICINE, GENERAL & INTERNAL","Score":null,"Total":0}
引用次数: 0
Abstract
Background: Skeletal muscle aging is the major cause and hallmark of frailty, which poses a significant challenge to the healthcare system.
Aim: This study aimed to identify the potential biomarkers for the early detection and therapeutic intervention of this age-related condition.
Methods: A transcriptomics-based methodology using machine learning algorithms was performed to select the biomarker genes. A predictive machine learning model for (pre-)frailty based on the transcriptomic profile of the biomarker genes was constructed and validated. The cell-type specific changes of the biomarkers during muscle aging were investigated in a single-cell RNA sequencing dataset of human skeletal muscle. Summary data-based Mendelian randomization (SMR) and Bayesian colocalization analyses were performed to identify biomarker genes with therapeutic effects on frailty-related skeletal muscle aging, and drug candidates were explored in the DSigDB database.
Results: We identified 24 biomarker genes, most of which were discovered for the first time. The optimal predictive model showed excellent performance in the external test set. Differential expression of the biomarkers in the single-cell dataset indicated a critical role of endothelial cells modulated by the marker genes MGP and ID1 in muscle degeneration. The SMR and colocalization analyses showed causal relationships between 2 marker genes (MGP and WAC) and frailty-related muscle aging. Potential therapeutics for MGP modulation were identified in the DSigDB database.
Conclusions: This multi-omics study identified biomarkers associated with frailty-related muscle aging and provided new insights into the etiology and therapeutic targets for this age-related condition.
期刊介绍：
QJM, a renowned and reputable general medical journal, has been a prominent source of knowledge in the field of internal medicine. With a steadfast commitment to advancing medical science and practice, it features a selection of rigorously reviewed articles.
Released on a monthly basis, QJM encompasses a wide range of article types. These include original papers that contribute innovative research, editorials that offer expert opinions, and reviews that provide comprehensive analyses of specific topics. The journal also presents commentary papers aimed at initiating discussions on controversial subjects and allocates a dedicated section for reader correspondence.
In summary, QJM's reputable standing stems from its enduring presence in the medical community, consistent publication schedule, and diverse range of content designed to inform and engage readers.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
