老化
健康老龄化
蛋白质组
队列
入射(几何)
医学
纵向研究
生物信息学
生物
老年学
内科学
病理
物理
光学
作者
Jun Tang,Yue Liang,Ying Xu,Fengzhe Xu,Xue Cai,Yuanqing Fu,Zelei Miao,Wanglong Gou,Wei Hu,Zhangzhi Xue,Kui Deng,Luqi Shen,Zengliang Jiang,Menglei Shuai,Xinxiu Liang,Congmei Xiao,Yuting Xie,Tiannan Guo,Yu‐Ming Chen,Ju‐Sheng Zheng
标识
DOI:10.1038/s42255-024-01185-7
摘要
The blood proteome contains biomarkers of ageing and age-associated diseases, but such markers are rarely validated longitudinally. Here we map the longitudinal proteome in 7,565 serum samples from a cohort of 3,796 middle-aged and elderly adults across three time points over a 9-year follow-up period. We pinpoint 86 ageing-related proteins that exhibit signatures associated with 32 clinical traits and the incidence of 14 major ageing-related chronic diseases. Leveraging a machine-learning model, we pick 22 of these proteins to generate a proteomic healthy ageing score (PHAS), capable of predicting the incidence of cardiometabolic diseases. We further identify the gut microbiota as a modifiable factor influencing the PHAS. Our data constitute a valuable resource and offer useful insights into the roles of serum proteins in ageing and age-associated cardiometabolic diseases, providing potential targets for intervention with therapeutics to promote healthy ageing. Tang, Yue, Xu and colleagues map the proteome of several thousand individuals over a 9-year period to identify potential biomarkers of ageing and of age-associated diseases.
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