生物年龄可以通过蛋白质组衰老时钟（PAC）来估计。之前发表的 PAC 要么是在较小的研究中构建的，要么主要是在白人个体中构建的，并且它们仅从一个时间点使用蛋白质组学测量。在本研究中，我们创建了 de novo PAC，并将其与社区动脉粥样硬化风险 (ARIC) 研究中两个不同时间点的已发布 PAC 进行了比较，研究对象为白人和黑人参与者（约 75% 为白人，25% 为黑人）。使用 SomaScan 测量了 1990 年至 1992 年从 11,761 名中年参与者（年龄 46 至 70 岁）和 2011 至 2013 年从 5,183 名晚年参与者（年龄 66 至 90 岁）收集的血液样本中的 4,712 种血浆蛋白。 de novo ARIC PAC 是通过使用弹性网络回归对三分之二的中年和晚年健康参与者进行针对实际年龄的训练而构建的，并在相应时间点对剩余三分之一的健康参与者进行了验证。我们还计算了 3 个已发布的 PAC。我们将每个 PAC 按实际年龄进行回归后，将每个 PAC 的年龄加速估计为残差。我们还计算了从中年到晚年的年龄加速变化。我们在排除参与者（不考虑健康状况）后，使用 Cox 比例风险回归，研究了截至 2019 年，年龄加速和年龄加速变化与全因死亡率、心血管疾病 (CVD)、癌症和下呼吸道疾病 (LRD) 死亡率之间的关联。训练集。该模型根据实际年龄、吸烟、体重指数（BMI）和其他混杂因素进行了调整。我们使用动脉粥样硬化多种族研究 (MESA) 检查 1 数据对中年 PAC 进行外部验证。在每个时间点，ARIC PAC 与健康参与者的实际年龄的相关性比已发表的 PAC 稍强。 ARIC PAC 和已发布的 PAC 与死亡率的关联相似。对于 ARIC PAC 的晚年和中年年龄加速，全因死亡率每 1 个标准差的风险比 (HR) 分别为 1.65 和 1.38（均 p < 0.001），全因死亡率为 1.37 和 1.20（均 p < 0.001）。 CVD 死亡率，癌症死亡率为 1.21 (p = 0.028) 和 1.04 (p = 0.280)，LRD 死亡率为 1.68 和 1.36（均 p < 0.001）。对于年龄加速的变化，全因死亡率、CVD 死亡率和 LRD 死亡率的 HR 与晚年年龄加速的 HR 相当。年龄加速变化与癌症死亡率之间的关联并不显着。 MESA 中年 PAC 的外部验证显示与死亡率显着相关，正如 ARIC 中年参与者所观察到的那样。主要的限制是我们的 PAC 是在中年和晚年参与者中构建的。目前尚不清楚这些 PAC 是否可以应用于年轻人。在这项纵向研究中，我们发现 ARIC PAC 和已发表的 PAC 与死亡风险增加类似。这些发现表明 PAC 作为生物年龄的生物标志物具有前景。 PAC 可作为预测死亡率和评估抗衰老生活方式和治疗干预效果的工具。版权所有：© 2024 Wang 等人。这是一篇根据知识共享署名许可条款分发的开放获取文章，允许在任何媒体上不受限制地使用、分发和复制，前提是注明原始作者和来源。

Biological age may be estimated by proteomic aging clocks (PACs). Previous published PACs were constructed either in smaller studies or mainly in white individuals, and they used proteomic measures from only one-time point. In this study, we created de novo PACs and compared their performance to published PACs at 2 different time points in the Atherosclerosis Risk in Communities (ARIC) study of white and black participants (around 75% white and 25% black).A total of 4,712 plasma proteins were measured using SomaScan in blood samples collected in 1990 to 1992 from 11,761 midlife participants (aged 46 to 70 years) and in 2011 to 2013 from 5,183 late-life participants (aged 66 to 90 years). The de novo ARIC PACs were constructed by training them against chronological age using elastic net regression in two-thirds of healthy participants in midlife and late life and validated in the remaining one-third of healthy participants at the corresponding time point. We also computed 3 published PACs. We estimated age acceleration for each PAC as residuals after regressing each PAC on chronological age. We also calculated the change in age acceleration from midlife to late life. We examined the associations of age acceleration and change in age acceleration with mortality through 2019 from all-cause, cardiovascular disease (CVD), cancer, and lower respiratory disease (LRD) using Cox proportional hazards regression in participants (irrespective of health) after excluding the training set. The model was adjusted for chronological age, smoking, body mass index (BMI), and other confounders. We externally validated the midlife PAC using the Multi-Ethnic Study of Atherosclerosis (MESA) Exam 1 data. The ARIC PACs had a slightly stronger correlation with chronological age than published PACs in healthy participants at each time point. Associations with mortality were similar for the ARIC PACs and published PACs. For late-life and midlife age acceleration for the ARIC PACs, respectively, hazard ratios (HRs) per 1 standard deviation were 1.65 and 1.38 (both p < 0.001) for all-cause mortality, 1.37 and 1.20 (both p < 0.001) for CVD mortality, 1.21 (p = 0.028) and 1.04 (p = 0.280) for cancer mortality, and 1.68 and 1.36 (both p < 0.001) for LRD mortality. For the change in age acceleration, HRs for all-cause, CVD, and LRD mortality were comparable to the HRs for late-life age acceleration. The association between the change in age acceleration and cancer mortality was not significant. The external validation of the midlife PAC in MESA showed significant associations with mortality, as observed for midlife participants in ARIC. The main limitation is that our PACs were constructed in midlife and late-life participants. It is unknown whether these PACs could be applied to young individuals.In this longitudinal study, we found that the ARIC PACs and published PACs were similarly associated with an increased risk of mortality. These findings suggested that PACs show promise as biomarkers of biological age. PACs may be serve as tools to predict mortality and evaluate the effect of anti-aging lifestyle and therapeutic interventions.Copyright: © 2024 Wang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.