Evidence map›Paper›PMID 39316596›Full record

ArticlePLoS medicine2024

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

Shuo Wang, Zexi Rao, Rui Cao, Anne H Blaes, Josef Coresh, Rajat Deo, Ruth Dubin, Corinne E Joshu, Benoit Lehallier, Pamela L Lutsey and 11 more

Abstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

21 authors.

Shuo WangDepartment of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, Minnesota, United States of America.ORCID https://orcid.org/0000-0003-4627-8625
Zexi RaoDivision of Biostatistics and Health Data Science, School of Public Health, University of Minnesota, Minneapolis, Minnesota, United States of America.ORCID https://orcid.org/0000-0001-9640-3725
Rui CaoDivision of Biostatistics and Health Data Science, School of Public Health, University of Minnesota, Minneapolis, Minnesota, United States of America.ORCID https://orcid.org/0009-0005-5157-2396
Anne H BlaesDivision of Hematology, Oncology and Transplantation, University of Minnesota, Minneapolis, Minnesota, United States of America.
Josef CoreshDepartments of Population Health and Medicine, New York University Glossman School of Medicine, New York, New York, United States of America.
Rajat DeoDivision of Cardiovascular Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.
Ruth DubinDivision of Nephrology, University of Texas Southwestern Medical Center, Dallas, Texas, United States of America.ORCID https://orcid.org/0000-0002-0498-1980
Corinne E JoshuDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America.ORCID https://orcid.org/0000-0002-5100-172X
Benoit LehallierAlkahest Inc, San Carlos, California, United States of America.
Pamela L LutseyDivision of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, Minnesota, United States of America.ORCID https://orcid.org/0000-0002-1572-1340
James S PankowDivision of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, Minnesota, United States of America.ORCID https://orcid.org/0000-0001-7076-483X
Wendy S PostDivision of Cardiology, Department of Medicine, Johns Hopkins University, Baltimore, Maryland, United States of America.ORCID https://orcid.org/0000-0002-8655-5204
Jerome I RotterInstitute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation; Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, California, United States of America.ORCID https://orcid.org/0000-0001-7191-1723
Sanaz SedaghatDivision of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, Minnesota, United States of America.
Weihong TangDivision of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, Minnesota, United States of America.
Bharat ThyagarajanDepartment of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, Minnesota, United States of America.
Keenan A WalkerLaboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, United States of America.ORCID https://orcid.org/0000-0002-5989-9853
Peter GanzDepartment of Medicine, University of California, San Francisco, California, United States of America.
Elizabeth A PlatzDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America.ORCID https://orcid.org/0000-0003-3676-8954
Weihua GuanDivision of Biostatistics and Health Data Science, School of Public Health, University of Minnesota, Minneapolis, Minnesota, United States of America.ORCID https://orcid.org/0000-0002-0956-9821
Anna PrizmentDepartment of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, Minnesota, United States of America.ORCID https://orcid.org/0000-0001-5924-6871

Funding

UCLA Clinical Translational Science InstituteUL1TR001881 · NCATS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI ARLEEN F. BROWN, ARASH NAEIM · 2016 to 2026
$118.1M
Institute for Clinical and Translational ResearchUL1TR001079 · NCATS · JOHNS HOPKINS UNIVERSITY · PI FORD, DANIEL ERNEST · 2013 to 2017
$60.1M
Transgenic & Knock-out MouseP30DK063491 · NIDDK · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI MILES Frome WILKINSON · 2003 to 2026
$40.4M
Wake Forest Clinical and Translational Science AwardUL1TR001420 · NCATS · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI ARD, JAMY D, FOLEY, KRISTIE L · 2015 to 2023
$32.3M
University of Minnesota Clinical and Translational Science Institute (UMN CTSI)UM1TR004405 · NCATS · UNIVERSITY OF MINNESOTA · PI Bruce R Blazar, Damien A Fair · 2023 to 2026
$30.8M
Clinical and Translational Science AwardUL1TR000040 · NCATS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI GINSBERG, HENRY N · 2012 to 2015
$26.2M
Task Area A Core Study Operations.Task Area A shall encompass annual follow-up of cohort members, clinical endpoints ascertainment, study coordination activities, maintenance of the database and biosp75N92020D00001 · NHLBI · UNIVERSITY OF WASHINGTON · PI MCCLELLAND, ROBYN LEAGH · 2020 to 2025
$17.2M
THE ATHEROSCLEROSIS RISK IN COMMUNITIES (ARIC) STUDY - COORDINATING CENTER - TASK AREA B.2 AND B.375N92022D00001 · NHLBI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI COUPER, DAVID · 2022 to 2025
$13.7M
CHARGE Consortium: Omics Discovery for CVD and Aging PhenotypesR01HL105756 · NHLBI · UNIVERSITY OF WASHINGTON · PI Bruce M Psaty, NICHOLAS L SMITH · 2011 to 2026
$9.5M
THE ATHEROSCLEROSIS RISK IN COMMUNITIES (ARIC) STUDY - FIELD CENTER - TASK ORDER 01, TASK AREA A75N92022D00003 · NHLBI · UNIVERSITY OF MINNESOTA · PI LUTSEY, PAMELA L. · 2022 to 2025
$5.1M
Task Area A shall encompass annual follow-up of cohort members, clinical events investigations, study operations, and data analysis and manuscript writing. If implemented, Task A.1 will provide fundin75N92020D00005 · NHLBI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI WATSON, KAROL E · 2020 to 2025
$5.1M
THE ATHEROSCLEROSIS RISK IN COMMUNITIES (ARIC) STUDY - FIELD CENTER - TASK ORDER 01, TASK AREA A75N92022D00005 · NHLBI · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI WAGENKNECHT, LYNNE E · 2022 to 2025
$5.0M
NCATS NIH HHS UL1 TR000040NCATS NIH HHS UL1 TR001079NCATS NIH HHS UL1 TR001420NCATS NIH HHS UL1 TR001881NCATS NIH HHS UM1 TR004405NCI NIH HHS R01 CA267977NCI NIH HHS U01 CA164975NHLBI NIH HHS 75N92020D00001NHLBI NIH HHS 75N92020D00002NHLBI NIH HHS 75N92020D00003NHLBI NIH HHS 75N92020D00004NHLBI NIH HHS 75N92020D00005NHLBI NIH HHS 75N92020D00006NHLBI NIH HHS 75N92020D00007NHLBI NIH HHS 75N92022D00001NHLBI NIH HHS 75N92022D00002NHLBI NIH HHS 75N92022D00003NHLBI NIH HHS 75N92022D00004NHLBI NIH HHS 75N92022D00005NHLBI NIH HHS HHSN268201500003CNHLBI NIH HHS HHSN268201500003INHLBI NIH HHS K24 HL159246NHLBI NIH HHS N01 HC095159NHLBI NIH HHS N01 HC095160NHLBI NIH HHS N01 HC095161NHLBI NIH HHS N01 HC095162NHLBI NIH HHS N01 HC095163NHLBI NIH HHS N01 HC095164NHLBI NIH HHS N01 HC095165NHLBI NIH HHS N01 HC095166NHLBI NIH HHS N01 HC095167NHLBI NIH HHS N01 HC095168NHLBI NIH HHS N01 HC095169NHLBI NIH HHS R01 HL105756NHLBI NIH HHS R01 HL134320NHLBI NIH HHS R01 HL159081NIA NIH HHS R21 AG079242NIDDK NIH HHS P30 DK063491
6 · The paper itself

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.

Indexed as

AgingProteomicsAgedAged, 80 and overAtherosclerosisCardiovascular DiseasesCohort StudiesFemaleHumansMaleMiddle AgedRisk Factors

Identifiers

PMID39316596
PMCPMC11460707

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.