临床试验
蛋白质组
计算生物学
生物信息学
蛋白质组学
药物试验
生物
疾病
衰老
效应器
表观遗传学
医学
药物开发
生物标志物
精密医学
药物发现
系统生物学
生物途径
机制(生物学)
临床研究阶段
生物年龄
作者
Alex A. Zhavoronkov,Fedor Galkin,Shan Chen,Feng Ren,Alex Aliper,Mikhail O. Durymanov,Denis Sidorenko,Hui Cui,Jing‐Dong J. Han,Hao Xu,Xiaodong Liu,Zuojun Xu,Christoph Kuppe,M. Austin Argentieri,Kejun Ying,Ludger J.E. Goeminne,Mahdi Moqri,Alexander Tyshkovskiy,Vadim N. Gladyshev
标识
DOI:10.1038/s41587-026-03286-y
摘要
Abstract Drugs for aging-related diseases may modulate aging itself, but standard clinical trial designs cannot detect such effects. Aging clocks could close this gap, but epigenetic models often yield inconsistent, hard-to-interpret results. In contrast, proteomic clocks, by tracking the immediate effectors of biological change, may excel in providing aging biomarkers or mechanistic insight. Here we compare six proteomic clocks (ProtAge, OrganAge mortality , OrganAge chrono , PAC, ipfP3GPT and PAOPAC) on serum proteomes from a published 12-week phase 2a trial of the candidate anti-fibrotic drug rentosertib in idiopathic pulmonary fibrosis. We measure the variance between the clocks and find that all six clocks consistently predicted lower biological age in treated arms. However, proteomic clocks alone cannot deconvolute aging- and disease-specific effects. We addressed this issue indirectly through pathway analyses that identified potential anti-aging shifts in senescence and metabolic processes alongside the anti-fibrotic activity of rentosertib. This work supports the goal of dual-purpose clinical trial designs that integrate aging endpoints into studies for specific disease indications.
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