Evidence map›Paper›PMID 40813726›Full record

ArticleCommunications medicine2025

Proteomics-based aging clocks in midlife or late-life and their associated risk of dementia.

Sanaz Sedaghat, Saeun Park, Rob F Walker, Shuo Wang, Jialing Liu, Timothy M Hughes, Behnam Sabayan, Weihong Tang, Josef Coresh, James S Pankow and 10 more

Abstract read
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Article in Communications medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

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0cells of the map it votes in
4citing 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.

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2 · The registry

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3 · Its place in the literature

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4 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

20 authors.

Sanaz SedaghatDivision of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA. sedaghat@umn.edu.ORCID http://orcid.org/0000-0002-8296-1811
Saeun ParkDivision of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA.
Rob F WalkerDivision of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA.ORCID http://orcid.org/0000-0002-1151-3675
Shuo WangDepartment of Laboratory Medicine and Pathology, Medical School, University of Minnesota, Minneapolis, MN, USA.
Jialing LiuDivision of Biostatistics and Health Data Science, School of Public Health, University of Minnesota, Minneapolis, MN, USA.
Timothy M HughesWake Forest University School of Medicine, Winston-Salem, NC, USA.
Behnam SabayanDivision of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA.
Weihong TangDivision of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA.
Josef CoreshDepartments of Population Health and Medicine, NYU Glossman School of Medicine, New York, NY, USA.ORCID http://orcid.org/0000-0002-4598-0669
James S PankowDivision of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA.ORCID http://orcid.org/0000-0001-7076-483X
Keenan A WalkerLaboratory of Behavioral Neuroscience, Intramural Research Program, National Institute on Aging, Baltimore, MD, USA.ORCID http://orcid.org/0000-0002-5989-9853
Ramon CasanovaDepartment of Biostatistics and Data Science, Wake Forest University School of Medicine, Medical Center Blvd., Winston-, Salem, NC, USA.
Ruth DubinDivision of Nephrology, University of Texas Southwestern Medical Center, Dallas, TX, USA.ORCID http://orcid.org/0000-0002-0498-1980
Rajat DeoDivision of Cardiovascular Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Jerome I RotterInstitute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation; Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, CA, USA.ORCID http://orcid.org/0000-0001-7191-1723
Alexis C WoodUS Department of Agriculture/Agricultural Research Service Children's Nutrition Research Center, Baylor College of Medicine, Houston, TX, USA.
Peter GanzDivision of Cardiology, Zuckerberg San Francisco General Hospital and Department of Medicine, University of California, San Francisco, CA, USA.ORCID http://orcid.org/0000-0002-0437-8882
Pamela L LutseyDivision of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA.ORCID http://orcid.org/0000-0002-1572-1340
Weihua GuanDivision of Biostatistics and Health Data Science, School of Public Health, University of Minnesota, Minneapolis, MN, USA.
Anna PrizmentDepartment of Laboratory Medicine and Pathology, Medical School, University of Minnesota, Minneapolis, MN, USA.ORCID http://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
ARIC Neurocognitive Study (ARIC-NCS) Renewal 2023-2028U01HL096812 · NHLBI · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI JOSEF CORESH, THOMAS H MOSLEY · 2010 to 2026
$65.7M
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
Subclinical Vascular Contributions to Alzheimer's Disease: The Multi-Ethnic Study of Atherosclerosis (MESA) Multisite Study of AD (Renewal)R01AG058969 · NIA · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI Timothy M. Hughes, YONGMEI LIU · 2018 to 2026
$33.4M
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
ARIC Neurocognitive Study (ARIC-NCS) Renewal 2 of 5U01HL096917 · NHLBI · UNIVERSITY OF MISSISSIPPI MED CTR · PI MOSLEY, THOMAS H · 2010 to 2018
$11.9M
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
NCATS NIH HHS UL1 TR000040NCATS NIH HHS UL1 TR001079NCATS NIH HHS UL1 TR001420NCATS NIH HHS UL1 TR001881NCATS NIH HHS UM1 TR004405NHLBI 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 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 HL159081NHLBI NIH HHS U01 HL096812NHLBI NIH HHS U01 HL096814NHLBI NIH HHS U01 HL096899NHLBI NIH HHS U01 HL096902NHLBI NIH HHS U01 HL096917NIA NIH HHS R01 AG058969NIA NIH HHS R21 AG079242NIDDK NIH HHS P30 DK063491NIH HHS 75N98025D00022NIH HHS 75N98025D00024NIH HHS 75N98025D00025NIH HHS 75N98025D00026NIH HHS 75N98025D00027NIH HHS 75N98025D00028U.S. Department of Health & Human Services | NIH | National Institute on Aging (U.S. National Institute on Aging) R01AG058969, R21AG079242, U01HL096812, U01HL096814, U01HL096899, U01HL096902, and U01HL096917
6 · The paper itself

Abstract

backgroundBiological age can be quantified by composite proteomic scores, called proteomics-based aging clocks (PACs). We investigated whether a discrepancy between chronological and biological age in midlife and late-life is associated with cognition and dementia risk.

methodsWe used two longitudinal population-based studies: the Atherosclerosis Risk in Communities (ARIC) Study and the Multi-Ethnic Study of Atherosclerosis (MESA). PACs were created in ARIC at midlife (mean age: 58 years, 57% female, n = 11,758) and late-life (mean age: 77 years, 56% female, n = 4934) using elastic net regression models in two-thirds of dementia-free participants and validated in the remaining one-third of participants. Proteomics-based age acceleration (PAA) was calculated as residuals after regressing PACs on chronological age. We validated the midlife PAC in the MESA cohort (mean age: 62 years, 52% female, n = 5829). We used multivariable linear and Cox proportional hazards regression to assess the association of PAA with cognitive function and dementia incidence, respectively.

resultsIn ARIC, every five years, PAA is associated with lower global cognition: difference: -0.11, 95% confidence interval[CI]: -0.16, -0.06) using midlife PAA and difference: -0.17, CI: -0.23, -0.12 using late-life PAA. Midlife PAA is associated with higher dementia risk (hazard ratio[HR]: 1.20 [CI: 1.04, 1.36]) and more prominently when using late-life PAA (HR: 2.14 [CI:1.67, 2.73]). Similar findings are observed in MESA: PAA is associated with lower global cognitive function (difference: -0.08 [CI: -0.14, -0.03]) and higher dementia risk (HR:1.23 [CI: 1.04, 1.46]).

conclusionsAccelerated biological age is associated with lower cognition and a higher risk of dementia in midlife and more prominently in late life.

Identifiers

PMID40813726
PMCPMC12354813

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