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


Journal

medRxiv : the preprint server for health sciences
Titre abrégé: medRxiv
Pays: United States
ID NLM: 101767986

Informations de publication

Date de publication:
08 Sep 2023
Historique:
pubmed: 21 9 2023
medline: 21 9 2023
entrez: 21 9 2023
Statut: epublish

Résumé

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.

Identifiants

pubmed: 37732184
doi: 10.1101/2023.09.06.23295174
pmc: PMC10508816
pii:
doi:

Types de publication

Preprint

Langues

eng

Subventions

Organisme : NHLBI NIH HHS
ID : 75N92022D00002
Pays : United States
Organisme : NCI NIH HHS
ID : R01 CA267977
Pays : United States
Organisme : NHLBI NIH HHS
ID : 75N92022D00004
Pays : United States
Organisme : NHLBI NIH HHS
ID : K24 HL159246
Pays : United States
Organisme : NHLBI NIH HHS
ID : 75N92022D00003
Pays : United States
Organisme : NHLBI NIH HHS
ID : 75N92022D00005
Pays : United States
Organisme : NIA NIH HHS
ID : R21 AG079242
Pays : United States
Organisme : NHLBI NIH HHS
ID : 75N92022D00001
Pays : United States
Organisme : NCI NIH HHS
ID : U01 CA164975
Pays : United States
Organisme : NHLBI NIH HHS
ID : R01 HL134320
Pays : United States

Auteurs

Shuo Wang (S)

Department of Laboratory Medicine and Pathology, Medical School, University of Minnesota, Minneapolis, MN.

Zexi Rao (Z)

Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN.

Rui Cao (R)

Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN.

Anne H Blaes (AH)

Division of Hematology, Oncology and Transplantation, Medical School, University of Minnesota, Minneapolis, MN.

Josef Coresh (J)

Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD.

Corinne E Joshu (CE)

Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD.
Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins, Baltimore, MD.

Benoit Lehallier (B)

Alkahest Inc, San Carlos, CA, United States, Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA.

Pamela L Lutsey (PL)

Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN.

James S Pankow (JS)

Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN.

Sanaz Sedaghat (S)

Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN.

Weihong Tang (W)

Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN.

Bharat Thyagarajan (B)

Department of Laboratory Medicine and Pathology, Medical School, University of Minnesota, Minneapolis, MN.

Keenan A Walker (KA)

Laboratory of Behavioral Neuroscience, Intramural Research Program, National Institute on Aging, Baltimore, MD.

Peter Ganz (P)

Division of Cardiology, Zuckerberg San Francisco General Hospital and Department of Medicine, University of California, San Francisco, CA.

Elizabeth A Platz (EA)

Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD.
Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins, Baltimore, MD.

Weihua Guan (W)

Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN.

Anna Prizment (A)

Department of Laboratory Medicine and Pathology, Medical School, University of Minnesota, Minneapolis, MN.

Classifications MeSH