Olinger Bradley, Banarjee Reema, Dey Amit, Tsitsipatis Dimitrios, Tanaka Toshiko, Ram Anjana, Nyunt Thedoe, Daya Gulzar N, Peng Zhongsheng, Shrivastava Mansi, Cui Linna, Candia Julian, Simonsick Eleanor M, Gorospe Myriam, Walker Keenan A, Ferrucci Luigi, Basisty Nathan
Translational Gerontology Branch, National Institute on Aging, NIH, Baltimore, MD, USA.
Department of Biology, Johns Hopkins University, Baltimore, MD, USA.
Nat Aging. 2025 Jun 3. doi: 10.1038/s43587-025-00877-3.
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.
细胞衰老随年龄增长而增加，并导致与年龄相关的机能衰退和病理变化。我们鉴定了衰老的循环生物标志物，并将其与人类的临床特征相关联，以促进未来对个体衰老负担的无创评估以及新型衰老治疗药物的疗效测试。使用基于纳米颗粒的蛋白质组学工作流程，我们分析了THP-1单核细胞中衰老相关分泌表型（SASP），并在来自巴尔的摩纵向衰老研究的1060份血浆样本中检测了这些蛋白质。在一个测试队列中，基于THP-1单核细胞SASP训练的机器学习模型将SASP特征与几种与年龄相关的表型相关联，包括身体脂肪组成、血脂、炎症标志物和与活动能力相关的特征等。值得注意的是，包括一个高影响力SASP组合在内的一部分基于SASP的预测在独立的衰老队列InCHIANTI中得到了验证。这些结果证明了循环SASP的临床相关性，并确定了可能为未来临床研究提供信息的潜在衰老生物标志物。
