Metabolic age based on the BBMRI-NL 1H-NMR metabolomics repository as biomarker of age-related disease

Erik B. Van Den Akker*, Stella Trompet, Jurriaan J.H. Barkey Wolf, Marian Beekman, H.E.D. Suchiman, Joris Deelen, Folkert W. Asselbergs, Eric Boersma, Davy Cats, Petra M. Elders, J.M. Geleijnse, M.A. Ikram, Margreet Kloppenburg, Haillang Mei, Ingrid Meulenbelt, Simon P. Mooijaart, Rob G.H.H. Nelissen, Mihai G. Netea, Brenda W.J.H. Penninx, Mariska SlofstraCoen D.A. Stehouwer, Morris A. Swertz, Charlotte E. Teunissen, Gisela M. Terwindt, Leen M. T'Hart, Arn M.J.M. Van Den Maagdenberg, Pim Van Der Harst, Iwan C.C. Van Der Horst, Carla J.H. Van Der Kallen, Marleen M.J. Van Greevenbroek, W.E. Van Spil, Cisca Wijmenga, Alexandra Zhernakova, Aeilko H. Zwinderman, Naveed Sattar, J.W. Jukema, Cornelia M. Van Duijn, Dorret I. Boomsma, Marcel J.T. Reinders, P.E. Slagboom

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

1 Citation (Scopus)

Abstract

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.
Original languageEnglish
Article numbere002610
Pages (from-to)541-547
Number of pages7
JournalCirculation: Genomic and Precision Medicine
Volume13
DOIs
Publication statusPublished - 2020

Keywords

  • Aging
  • Cardiovascular disease
  • Data science
  • Metabolomics

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