Predicting biological age based on the BBMRI-NL 1H-NMR metabolomics repository
By
Erik Ben van den Akker,
S Trompet,
J.J.H. Barkey Wolf,
Marian Beekman,
H.E.D. Suchiman,
J Deelen,
F W Asselbergs,
BBMRI-NL,
E Boersma,
D Cats,
P.M. Elders,
J.M. Geleijnse,
M.A. Ikram,
M Kloppenburg,
H Mei,
I Meulenbelt,
S.P. Mooijaart,
R.G.H.H. Nelissen,
Mihai G. Netea,
BWJH Penninx,
M Slofstra,
C.D.A. Stehouwer,
M.A. Swertz,
C.E. Teunissen,
G.M. Terwindt,
L.M. ‘t Hart,
A.M.J.M. van den Maagdenberg,
P van der Harst,
I.C.C. van der Horst,
C.J.H. van der Kallen,
M.M.J. van Greevenbroek,
W.E. van Spil,
Cisca Wijmenga,
A Zhernakova,
A.H. Zwinderman,
N Sattar,
J.W. Jukema,
C.M. van Duijn,
Dorret I Boomsma,
M.J.T. Reinders,
P. Eline Slagboom
Posted 10 May 2019
bioRxiv DOI: 10.1101/632919
The blood metabolome incorporates cues from the environment as well as the host's genetic background, potentially offering a holistic view of an individual's health status. We have compiled a vast resource of 1H-NMR metabolomics and phenotypic data encompassing over 25,000 samples derived from 26 community and hospital-based cohorts. 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 to 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. 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 cardio-metabolic health.
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