Development, characterization, and replication of proteomic aging clocks: Analysis of 2 population-based cohorts.

IF 15.8 1区 医学 Q1 Medicine
PLoS Medicine Pub Date : 2024-09-24 eCollection Date: 2024-09-01 DOI:10.1371/journal.pmed.1004464
Shuo Wang, Zexi Rao, Rui Cao, Anne H Blaes, Josef Coresh, Rajat Deo, Ruth Dubin, Corinne E Joshu, Benoit Lehallier, Pamela L Lutsey, James S Pankow, Wendy S Post, Jerome I Rotter, Sanaz Sedaghat, Weihong Tang, Bharat Thyagarajan, Keenan A Walker, Peter Ganz, Elizabeth A Platz, Weihua Guan, Anna Prizment
{"title":"Development, characterization, and replication of proteomic aging clocks: Analysis of 2 population-based cohorts.","authors":"Shuo Wang, Zexi Rao, Rui Cao, Anne H Blaes, Josef Coresh, Rajat Deo, Ruth Dubin, Corinne E Joshu, Benoit Lehallier, Pamela L Lutsey, James S Pankow, Wendy S Post, Jerome I Rotter, Sanaz Sedaghat, Weihong Tang, Bharat Thyagarajan, Keenan A Walker, Peter Ganz, Elizabeth A Platz, Weihua Guan, Anna Prizment","doi":"10.1371/journal.pmed.1004464","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>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).</p><p><strong>Medthods and findings: </strong>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.</p><p><strong>Conclusions: </strong>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.</p>","PeriodicalId":49008,"journal":{"name":"PLoS Medicine","volume":null,"pages":null},"PeriodicalIF":15.8000,"publicationDate":"2024-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11460707/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"PLoS Medicine","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1371/journal.pmed.1004464","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/9/1 0:00:00","PubModel":"eCollection","JCR":"Q1","JCRName":"Medicine","Score":null,"Total":0}
引用次数: 0

Abstract

Background: 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).

Medthods and findings: 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.

Conclusions: 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.

蛋白质组老化时钟的开发、特征描述和复制:对两个基于人群的队列进行分析。
背景:生物年龄可通过蛋白质组老化时钟(PAC)来估算。以前发表的 PACs 都是在较小规模的研究中构建的,或者主要是在白人个体中构建的,而且它们只使用了一个时间点的蛋白质组测量值。在这项研究中,我们在社区动脉粥样硬化风险(ARIC)研究的白人和黑人参与者(约75%为白人,25%为黑人)中创建了全新的PACs,并在两个不同的时间点将其性能与已发表的PACs进行了比较:在 1990 年至 1992 年收集的 11,761 名中年参与者(年龄在 46 岁至 70 岁之间)的血样中,以及在 2011 年至 2013 年收集的 5,183 名晚年参与者(年龄在 66 岁至 90 岁之间)的血样中,共使用 SomaScan 测定了 4,712 种血浆蛋白。在三分之二的中年和晚年健康参与者中,我们使用弹性净回归法根据年代年龄对其进行了训练,从而构建了全新的 ARIC PACs,并在相应时间点对其余三分之一的健康参与者进行了验证。我们还计算了 3 个已发表的 PAC。我们将每个 PAC 与实际年龄回归后的残差作为年龄加速度的估计值。我们还计算了年龄加速度从中年到晚年的变化。在排除训练集后,我们使用 Cox 比例危险度回归法研究了年龄加速度和年龄加速度变化与到 2019 年的全因死亡率、心血管疾病(CVD)、癌症和下呼吸道疾病(LRD)之间的关系,参与者(无论健康状况如何)的年龄加速度和年龄加速度变化与全因死亡率、心血管疾病(CVD)、癌症和下呼吸道疾病(LRD)之间的关系。该模型对实际年龄、吸烟、体重指数(BMI)和其他混杂因素进行了调整。我们利用多种族动脉粥样硬化研究(MESA)第 1 次考试数据对中年 PAC 进行了外部验证。在每个时间点,ARIC PAC 与实际年龄的相关性略强于已发表的健康参与者的 PAC。ARIC PAC 与死亡率的相关性与已公布的 PAC 相似。就 ARIC PACs 的晚年和中年年龄加速度而言,全因死亡率每 1 个标准差的危险比(HRs)分别为 1.65 和 1.38(均 p <0.001),心血管疾病死亡率分别为 1.37 和 1.20(均 p <0.001),癌症死亡率分别为 1.21(p = 0.028)和 1.04(p = 0.280),低死亡率分别为 1.46 和 1.68(均 p <0.001)。就年龄加速度变化而言,全因、心血管疾病和 LRD 死亡率的 HR 值与晚年年龄加速度的 HR 值相当。年龄加速度变化与癌症死亡率之间的关系并不显著。在 MESA 中对中年 PAC 进行的外部验证显示,与 ARIC 中的中年参与者一样,中年 PAC 与死亡率有显著关联。主要的局限性在于,我们的 PAC 是在中年和晚年参与者中构建的。我们还不知道这些 PAC 是否适用于年轻人:在这项纵向研究中,我们发现 ARIC PACs 和已发表的 PACs 与死亡风险增加有相似的关联。这些发现表明,PACs有望成为生物年龄的生物标志物。PACs可作为预测死亡率和评估抗衰老生活方式及治疗干预效果的工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
PLoS Medicine
PLoS Medicine MEDICINE, GENERAL & INTERNAL-
CiteScore
17.60
自引率
0.60%
发文量
227
审稿时长
4-8 weeks
期刊介绍: PLOS Medicine is a prominent platform for discussing and researching global health challenges. The journal covers a wide range of topics, including biomedical, environmental, social, and political factors affecting health. It prioritizes articles that contribute to clinical practice, health policy, or a better understanding of pathophysiology, ultimately aiming to improve health outcomes across different settings. The journal is unwavering in its commitment to uphold the highest ethical standards in medical publishing. This includes actively managing and disclosing any conflicts of interest related to reporting, reviewing, and publishing. PLOS Medicine promotes transparency in the entire review and publication process. The journal also encourages data sharing and encourages the reuse of published work. Additionally, authors retain copyright for their work, and the publication is made accessible through Open Access with no restrictions on availability and dissemination. PLOS Medicine takes measures to avoid conflicts of interest associated with advertising drugs and medical devices or engaging in the exclusive sale of reprints.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信