循环血浆蛋白在人类健康中发挥着关键作用，可用于测量生物年龄，从而预测与年龄相关的疾病、多种发病率和死亡率。在这里，我们使用包含 2,897 个血浆蛋白的蛋白质组平台在英国生物库 (n = 45,441) 中开发了一个蛋白质组年龄时钟，并探索了其在预测不同人群中主要疾病发病率和死亡率方面的实用性。我们鉴定了 204 个能够准确预测实际年龄的蛋白质（Pearson r = 0.94），并发现蛋白质组衰老与 18 种主要慢性疾病（包括心脏、肝脏、肾脏和肺部疾病、糖尿病、神经退行性疾病和癌症）的发病率相关，以及多发病和全因死亡风险。蛋白质组衰老还与生物、身体和认知功能的年龄相关指标相关，包括端粒长度、衰弱指数和反应时间。对蛋白质组年龄时钟贡献最大的蛋白质涉及许多生物功能，包括细胞外基质相互作用、免疫反应和炎症、激素调节和繁殖、神经元结构和功能以及发育和分化。在一项涉及中国（n = 3,977）和芬兰（n = 1,990）生物样本库的验证研究中，与英国生物样本库中的表现相比，蛋白质组年龄时钟显示出相似的年龄预测准确性（分别为 Pearson r = 0.92 和 r = 0.94） 。我们的结果表明，蛋白质组衰老涉及跨越多个功能类别的蛋白质，可用于预测地理和遗传不同人群中与年龄相关的功能状态、多发病和死亡风险。© 2024。作者。

Circulating plasma proteins play key roles in human health and can potentially be used to measure biological age, allowing risk prediction for age-related diseases, multimorbidity and mortality. Here we developed a proteomic age clock in the UK Biobank (n = 45,441) using a proteomic platform comprising 2,897 plasma proteins and explored its utility to predict major disease morbidity and mortality in diverse populations. We identified 204 proteins that accurately predict chronological age (Pearson r = 0.94) and found that proteomic aging was associated with the incidence of 18 major chronic diseases (including diseases of the heart, liver, kidney and lung, diabetes, neurodegeneration and cancer), as well as with multimorbidity and all-cause mortality risk. Proteomic aging was also associated with age-related measures of biological, physical and cognitive function, including telomere length, frailty index and reaction time. Proteins contributing most substantially to the proteomic age clock are involved in numerous biological functions, including extracellular matrix interactions, immune response and inflammation, hormone regulation and reproduction, neuronal structure and function and development and differentiation. In a validation study involving biobanks in China (n = 3,977) and Finland (n = 1,990), the proteomic age clock showed similar age prediction accuracy (Pearson r = 0.92 and r = 0.94, respectively) compared to its performance in the UK Biobank. Our results demonstrate that proteomic aging involves proteins spanning multiple functional categories and can be used to predict age-related functional status, multimorbidity and mortality risk across geographically and genetically diverse populations.© 2024. The Author(s).