TY - JOUR
T1 - Metabolic Age Based on the BBMRI-NL 1H-NMR Metabolomics Repository as Biomarker of Age-related Disease
AU - Van Den Akker, Erik B.
AU - Trompet, Stella
AU - Barkey Wolf, Jurriaan J.h.
AU - Beekman, Marian
AU - Suchiman, H. Eka D.
AU - Deelen, Joris
AU - Asselbergs, Folkert W.
AU - Boersma, Eric
AU - Cats, Davy
AU - Elders, Petra M.
AU - Geleijnse, J. Marianne
AU - Ikram, M. Arfan
AU - Kloppenburg, Margreet
AU - Mei, Haillang
AU - Meulenbelt, Ingrid
AU - Mooijaart, Simon P.
AU - Nelissen, Rob G.h.h.
AU - Netea, Mihai G.
AU - Penninx, Brenda W.J.H.
AU - Slofstra, Mariska
AU - Stehouwer, Coen D.a.
AU - Swertz, Morris A.
AU - Teunissen, Charlotte E.
AU - Terwindt, Gisela M.
AU - ‘t Hart, Leen M.
AU - Van Den Maagdenberg, Arn M.j.m.
AU - Van Der Harst, Pim
AU - Van Der Horst, Iwan C.c.
AU - Van Der Kallen, Carla J.h.
AU - Van Greevenbroek, Marleen M.j.
AU - Van Spil, W. Erwin
AU - Wijmenga, Cisca
AU - Zhernakova, Alexandra
AU - Zwinderman, Aeilko H.
AU - Sattar, Naveed
AU - Jukema, J. Wouter
AU - Van Duijn, Cornelia M.
AU - Boomsma, Dorret I.
AU - Reinders, Marcel J.t.
AU - Slagboom, P. Eline
PY - 2020/10
Y1 - 2020/10
N2 - BACKGROUND: The blood metabolome incorporates cues from the environment and the host's genetic background, potentially offering a holistic view of an individual's health status. METHODS: We have compiled a vast resource of proton nuclear magnetic resonance metabolomics and phenotypic data encompassing over 25 000 samples derived from 26 community and hospital-based cohorts. RESULTS: Using this resource, we constructed a metabolomics-based age predictor (metaboAge) to calculate an individual's biological age. Exploration in independent cohorts demonstrates that being judged older by one's metabolome, as compared with one's chronological age, confers an increased risk on future cardiovascular disease, mortality, and functionality in older individuals. A web-based tool for calculating metaboAge (metaboage.researchlumc.nl) allows easy incorporation in other epidemiological studies. Access to data can be requested at bbmri.nl/samples-images-data. CONCLUSIONS: In summary, we present a vast resource of metabolomics data and illustrate its merit by constructing a metabolomics-based score for biological age that captures aspects of current and future cardiometabolic health.
AB - BACKGROUND: The blood metabolome incorporates cues from the environment and the host's genetic background, potentially offering a holistic view of an individual's health status. METHODS: We have compiled a vast resource of proton nuclear magnetic resonance metabolomics and phenotypic data encompassing over 25 000 samples derived from 26 community and hospital-based cohorts. RESULTS: Using this resource, we constructed a metabolomics-based age predictor (metaboAge) to calculate an individual's biological age. Exploration in independent cohorts demonstrates that being judged older by one's metabolome, as compared with one's chronological age, confers an increased risk on future cardiovascular disease, mortality, and functionality in older individuals. A web-based tool for calculating metaboAge (metaboage.researchlumc.nl) allows easy incorporation in other epidemiological studies. Access to data can be requested at bbmri.nl/samples-images-data. CONCLUSIONS: In summary, we present a vast resource of metabolomics data and illustrate its merit by constructing a metabolomics-based score for biological age that captures aspects of current and future cardiometabolic health.
UR - https://www.scopus.com/pages/publications/85094176129
UR - https://www.scopus.com/pages/publications/85094176129#tab=citedBy
U2 - 10.1161/CIRCGEN.119.002610
DO - 10.1161/CIRCGEN.119.002610
M3 - Article
SN - 2574-8300
VL - 13
SP - 541
EP - 547
JO - Circulation: Genomic and Precision Medicine
JF - Circulation: Genomic and Precision Medicine
IS - 5
M1 - e002610
ER -
SDG 3 Good Health and Well-being