Department of Public Health Sciences, University of Connecticut Health Center, Farmington, Connecticut, USA.
The Cato T. Laurencin Institute for Regenerative Engineering, University of Connecticut Health Center, Farmington, Connecticut, USA.
Aging Cell. 2024 Aug;23(8):e14195. doi: 10.1111/acel.14195. Epub 2024 May 15.
Beyond mere prognostication, optimal biomarkers of aging provide insights into qualitative and quantitative features of biological aging and might, therefore, offer useful information for the testing and, ultimately, clinical use of gerotherapeutics. We aimed to develop a proteomic aging clock (PAC) for all-cause mortality risk as a proxy of biological age. Data were from the UK Biobank Pharma Proteomics Project, including 53,021 participants aged between 39 and 70 years and 2923 plasma proteins assessed using the Olink Explore 3072 assay®. 10.9% of the participants died during a mean follow-up of 13.3 years, with the mean age at death of 70.1 years. The Spearman correlation between PAC proteomic age and chronological age was 0.77. PAC showed robust age-adjusted associations and predictions for all-cause mortality and the onset of various diseases in general and disease-free participants. The proteins associated with PAC proteomic age deviation were enriched in several processes related to the hallmarks of biological aging. Our results expand previous findings by showing that biological age acceleration, based on PAC, strongly predicts all-cause mortality and several incident disease outcomes. Particularly, it facilitates the evaluation of risk for multiple conditions in a disease-free population, thereby, contributing to the prevention of initial diseases, which vary among individuals and may subsequently lead to additional comorbidities.
除了简单的预测,最佳的衰老生物标志物提供了对生物衰老的定性和定量特征的深入了解,因此可能为衰老治疗的测试和最终临床应用提供有用的信息。我们旨在开发一种用于全因死亡率风险的蛋白质组学衰老时钟 (PAC),作为生物年龄的替代指标。数据来自英国生物银行制药蛋白质组学项目,包括 53021 名年龄在 39 至 70 岁之间的参与者和使用 Olink Explore 3072 assay®评估的 2923 种血浆蛋白。在平均 13.3 年的随访中,有 10.9%的参与者死亡,死亡时的平均年龄为 70.1 岁。PAC 蛋白质组年龄与实际年龄之间的斯皮尔曼相关性为 0.77。PAC 显示出与全因死亡率和各种疾病(包括无疾病参与者)的发生呈稳健的年龄调整关联和预测。与 PAC 蛋白质组年龄偏差相关的蛋白质在几个与生物衰老标志相关的过程中富集。我们的结果扩展了之前的发现,表明基于 PAC 的生物年龄加速强烈预测全因死亡率和几种疾病的发生。特别是,它促进了在无疾病人群中评估多种疾病的风险,从而有助于预防个体之间存在差异的初始疾病,这些疾病可能随后导致其他合并症。