{"title":"Senescence-related proteins in blood predict aging traits","authors":"","doi":"10.1038/s43587-025-00891-5","DOIUrl":null,"url":null,"abstract":"We used machine learning to identify senescence markers in the blood that are associated with signs of aging, such as frailty, high cholesterol levels, inflammation and increased body fat. These markers strongly reflected monocyte senescence in two independent human aging cohorts.","PeriodicalId":94150,"journal":{"name":"Nature aging","volume":"5 7","pages":"1191-1192"},"PeriodicalIF":19.4000,"publicationDate":"2025-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nature aging","FirstCategoryId":"1085","ListUrlMain":"https://www.nature.com/articles/s43587-025-00891-5","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
We used machine learning to identify senescence markers in the blood that are associated with signs of aging, such as frailty, high cholesterol levels, inflammation and increased body fat. These markers strongly reflected monocyte senescence in two independent human aging cohorts.