The secretome of senescent monocytes predicts age-related clinical outcomes in humans.

Cellular senescence increases with age and contributes to age-related declines and pathologies. We identified circulating biomarkers of senescence and related them to clinical traits in humans to facilitate future noninvasive assessment of individual senescence burden, and efficacy testing of novel senotherapeutics. Using a nanoparticle-based proteomic workflow, we profiled the senescence-associated secretory phenotype (SASP) in THP-1 monocytes and examined these proteins in 1,060 plasma samples from the Baltimore Longitudinal Study of Aging. Machine-learning models trained on THP-1 monocyte SASP associated SASP signatures with several age-related phenotypes in a test cohort, including body fat composition, blood lipids, inflammatory markers and mobility-related traits, among others. Notably, a subset of SASP-based predictions, including a high-impact SASP panel, were validated in InCHIANTI, an independent aging cohort. These results demonstrate the clinical relevance of the circulating SASP and identify potential senescence biomarkers that could inform future clinical studies.