Metabolic Age Based on the BBMRI-NL 1H-NMR Metabolomics Repository as Biomarker of Age-related Disease.
van den Akker EB., Trompet S., Barkey Wolf JJH., Beekman M., Suchiman HED., Deelen J., Asselbergs FW., Boersma E., Cats D., Elders PM., Geleijnse JM., Ikram MA., Kloppenburg M., Mei H., Meulenbelt I., Mooijaart SP., Nelissen RGHH., Netea MG., Penninx BWJH., Slofstra M., Stehouwer CDA., Swertz MA., Teunissen CE., Terwindt GM., 't Hart LM., van den Maagdenberg AMJM., van der Harst P., van der Horst ICC., van der Kallen CJH., van Greevenbroek MMJ., van Spil WE., Wijmenga C., Zhernakova A., Zwinderman AH., Sattar N., Jukema JW., van Duijn CM., Boomsma DI., Reinders MJT., Slagboom PE.
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.