Evidence map›Paper›PMID 37732184›Full record

ArticlemedRxiv : the preprint server for health sciences2023

Development and Characterization of Proteomic Aging Clocks in the Atherosclerosis Risk in Communities (ARIC) Study.

Shuo Wang, Zexi Rao, Rui Cao, Anne H Blaes, Josef Coresh, Corinne E Joshu, Benoit Lehallier, Pamela L Lutsey, James S Pankow, Sanaz Sedaghat and 7 more

Open access · greenAbstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed, 6 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

17 authors at 6 institutions in 1 country.

Shuo WangDepartment of Laboratory Medicine and Pathology, Medical School, University of Minnesota, Minneapolis, MN.
Zexi RaoDivision of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN.
Rui CaoDivision of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN.
Anne H BlaesDivision of Hematology, Oncology and Transplantation, Medical School, University of Minnesota, Minneapolis, MN.
Josef CoreshDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD.
Corinne E JoshuDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD.
Benoit LehallierAlkahest Inc, San Carlos, CA, United States, Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA.
Pamela L LutseyDivision of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN.
James S PankowDivision of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN.
Sanaz SedaghatDivision of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN.
Weihong TangDivision of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN.
Bharat ThyagarajanDepartment of Laboratory Medicine and Pathology, Medical School, University of Minnesota, Minneapolis, MN.
Keenan A WalkerLaboratory of Behavioral Neuroscience, Intramural Research Program, National Institute on Aging, Baltimore, MD.
Peter GanzDivision of Cardiology, Zuckerberg San Francisco General Hospital and Department of Medicine, University of California, San Francisco, CA.
Elizabeth A PlatzDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD.
Weihua GuanDivision of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN.
Anna PrizmentDepartment of Laboratory Medicine and Pathology, Medical School, University of Minnesota, Minneapolis, MN.
University of Minnesota · USUniversity of Minnesota Medical Center · USJohns Hopkins University · USNational Institute on Aging · USSan Francisco General Hospital · USStanford University · US

Funding

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
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
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
THE ATHEROSCLEROSIS RISK IN COMMUNITIES (ARIC) STUDY - FIELD CENTER - TASK ORDER 01, TASK AREA A75N92022D00004 · NHLBI · UNIVERSITY OF MISSISSIPPI MED CTR · PI WINDHAM, BEVERLY GWEN · 2022 to 2025
$4.8M
THE ATHEROSCLEROSIS RISK IN COMMUNITIES (ARIC) STUDY - FIELD CENTER - TASK ORDER 01, TASK AREA A75N92022D00002 · NHLBI · JOHNS HOPKINS UNIVERSITY · PI CORESH, JOSEF · 2022 to 2025
$4.7M
Enhancing ARIC Infrastructure to Yield a New Cancer Epidemiology CohortU01CA164975 · NCI · JOHNS HOPKINS UNIVERSITY · PI PLATZ, ELIZABETH A. · 2012 to 2018
$3.8M
Profiling Cardiovascular Events and Biomarkers in the Very Old to Improve Personalized Approaches for the Prevention of Cardiac and Vascular DiseaseR01HL134320 · NHLBI · BAYLOR COLLEGE OF MEDICINE · PI BALLANTYNE, CHRISTIE MITCHELL, SELVIN, ELIZABETH · 2016 to 2019
$3.1M
Proteomic aging in adults before and after cancer diagnosisR01CA267977 · NCI · UNIVERSITY OF MINNESOTA · PI PRIZMENT, ANNA · 2022 to 2024
$1.0M
Mentoring and Research in Patient-Oriented Cardiovascular PharmacoepidemiologyK24HL159246 · NHLBI · UNIVERSITY OF MINNESOTA · PI PAMELA L. Lutsey · 2021 to 2026
$644k
Proteomic aging clock and brain structure, cognitive decline and the risk of Alzheimers Disease and related dementiasR21AG079242 · NIA · UNIVERSITY OF MINNESOTA · PI PRIZMENT, ANNA, SEDAGHAT, SANAZ · 2022 to 2022
$400k
NCI NIH HHS R01 CA267977NCI NIH HHS U01 CA164975NHLBI NIH HHS 75N92022D00001NHLBI NIH HHS 75N92022D00002NHLBI NIH HHS 75N92022D00003NHLBI NIH HHS 75N92022D00004NHLBI NIH HHS 75N92022D00005NHLBI NIH HHS K24 HL159246NHLBI NIH HHS R01 HL134320NIA NIH HHS R21 AG079242
6 · The paper itself

Abstract

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 the Atherosclerosis Risk in Communities (ARIC) study of about 12,000 persons followed for 30 years (around 75% White, 25% Black), we created de novo PACs and compared their performance to published PACs at two different time points. We measured 4,712 plasma proteins by SomaScan in 11,761 midlife participants, aged 46-70 years (1990-92), and 5,183 late-life pariticpants, aged 66-90 years (2011-13). All proteins were log2-transformed to correct for skewness. We created de novo PACs by training them against chronological age using elastic net regression in two-thirds of healthy participants in midlife and late life and compared their performance to three published PACs. We estimated age acceleration (by regressing each PAC on chronological age) and its change from midlife to late life. We examined their associations with mortality from all-cause, cardiovascular disease (CVD), cancer, and lower respiratory disease (LRD) using Cox proportional hazards regression in all remaining participants irrespective of health. The model was adjusted for chronological age, smoking, body mass index (BMI), and other confounders. 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 and published PACs. For late-life and midlife age acceleration for the ARIC PACs, respectively, hazard ratios (HRs) per one 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=0.03) and 1.04 (p=0.19) for cancer mortality, and 1.46 and 1.68 (both p<0.001) for LRD mortality. For the change in age acceleration, HRs for all-cause, CVD, and LRD mortality were comparable to those observed for late-life age acceleration. The association between the change in age acceleration and cancer mortality was insignificant. In this prospective study, the ARIC and published PACs were similarly associated with an increased risk of mortality and advanced testing in relation to various age-related conditions in future studies is suggested.

Identifiers

PMID37732184
PMCPMC10508816
OpenAlexW4386533510

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Registered trials

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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.