ArticlePLoS medicine2024
Development, characterization, and replication of proteomic aging clocks: Analysis of 2 population-based cohorts.
Article in PLoS medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- Glycemic status-dependent proteomic signatures of biological aging for health risk prediction.GeroScience · 2026Article
- Associations of proteomic age clocks with lifestyle risk factors, incident chronic diseases and mortality in two European cohorts.Nature aging · 2026Article
- Proteomic aging clocks in epidemiological studies: advances, applications and prospects.Nature aging · 2026Review
- Longitudinal protein profiling of blood during childhood into early adulthood.Nature communications · 2026Article
- Proteomic Age Acceleration in Multiple Sclerosis Precedes Symptom Onset and Associates with Severity.medRxiv : the preprint server for health sciences · 2026Article
- Plasma Proteomic Profiling of Young and Older Adults Identifies Candidate Biomarkers of Biological Aging at the Intersection of Age and Disease.Aging cell · 2026Article
- Senescence protein signatures predict dementia risk with causal implication for TBCA: a two-cohort study.Research square · 2026Article
- Proteomics of aging: biomarkers for physiological systems and diseases.Frontiers in aging · 2026Review
- Proteomic aging clocks and the risk of mortality among long-term cancer survivors.Journal of the National Cancer Institute · 2026Article
- Proteomic landscape of multidimensional aging phenotypes.Genome medicine · 2025Article
- Associations of social network size and perceived level of social support with age acceleration estimated by a proteomic aging clock: the Atherosclerosis Risk in Communities Study.American journal of epidemiology · 2025Article
- Cerebrospinal fluid proteomic signatures in cognitively normal individuals identify distinct clusters linked to neurodegeneration.Nature aging · 2025Article
- Associations of proteomic age with mortality and incident chronic diseases in the European Prospective Investigation into Cancer and Nutrition (EPIC).Research square · 2025Article
- Exploring the impact of age, sex and life experiences on plasma inflammatory profiles through comparative proteomics.Frontiers in immunology · 2025Article
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Abstract
backgroundBiological 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
findingsA 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.
conclusionsIn 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.
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