Metabolic Age Based on the BBMRI-NL 1 H-NMR Metabolomics Repository as Biomarker of Age-related Disease

Erik B. van den Akker; Stella Trompet; Jurriaan J. H. Barkey Wolf; Marian Beekman; H. Eka D. Suchiman; Joris Deelen; Folkert W. Asselbergs; Eric Boersma; Davy Cats; Petra M. Elders; J. Marianne Geleijnse; M. Arfan Ikram; Margreet Kloppenburg; Haillang Mei; Ingrid Meulenbelt; Simon P. Mooijaart; Rob G. H. H. Nelissen; Mihai G. Netea; Brenda W. J. H. Penninx; Mariska Slofstra; Coen 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. Erwin van Spil; Cisca Wijmenga; Alexandra Zhernakova; Aeilko H. Zwinderman; Naveed Sattar; J. Wouter Jukema; Cornelia M. van Duijn; Dorret I. Boomsma; Marcel J. T. Reinders; P. Eline Slagboom

doi:10.1161/CIRCGEN.119.002610

Metabolic Age Based on the BBMRI-NL 1 H-NMR Metabolomics Repository as Biomarker of Age-related Disease

Erik B. van den Akker^*, Stella Trompet, Jurriaan J. H. Barkey Wolf, Marian Beekman, H. Eka D. Suchiman, Joris Deelen, Folkert W. Asselbergs, Eric Boersma, Davy Cats, Petra M. Elders, J. Marianne Geleijnse, M. Arfan 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. Erwin van Spil, Cisca Wijmenga, Alexandra Zhernakova, Aeilko H. Zwinderman, Naveed Sattar, J. Wouter Jukema, Cornelia M. van Duijn, Dorret I. Boomsma, Marcel J. T. Reinders, P. Eline Slagboom

^*Corresponding author for this work

Research output: Contribution to journal › Article › Academic › peer-review

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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 bmri.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 language	English
Article number	002610
Pages (from-to)	541-547
Number of pages	7
Journal	Circulation: Genomic and Precision Medicine
Volume	13
Issue number	5
DOIs	https://doi.org/10.1161/CIRCGEN.119.002610
Publication status	Published - Oct 2020

Keywords

aging
cardiovascular disease
data science
metabolomics
DNA METHYLATION AGE
MORTALITY
REVEAL
RISK

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10.1161/CIRCGEN.119.002610

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Cite this

van den Akker, E. B., Trompet, S., Barkey Wolf, J. J. H., Beekman, M., Suchiman, H. E. D., Deelen, J., Asselbergs, F. W., Boersma, E., Cats, D., Elders, P. M., Geleijnse, J. M., Ikram, M. A., Kloppenburg, M., Mei, H., Meulenbelt, I., Mooijaart, S. P., Nelissen, R. G. H. H., Netea, M. G., Penninx, B. W. J. H., ... Slagboom, P. E. (2020). Metabolic Age Based on the BBMRI-NL 1 H-NMR Metabolomics Repository as Biomarker of Age-related Disease. Circulation: Genomic and Precision Medicine, 13(5), 541-547. Article 002610. https://doi.org/10.1161/CIRCGEN.119.002610

@article{3a492ca73dfd45179817dfc0cb9f69da,

title = "Metabolic Age Based on the BBMRI-NL 1 H-NMR Metabolomics Repository as Biomarker of Age-related Disease",

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 bmri.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.",

keywords = "aging, cardiovascular disease, data science, metabolomics, DNA METHYLATION AGE, MORTALITY, REVEAL, RISK",

author = "{van den Akker}, {Erik B.} and Stella Trompet and {Barkey Wolf}, {Jurriaan J. H.} and Marian Beekman and Suchiman, {H. Eka D.} and Joris Deelen and Asselbergs, {Folkert W.} and Eric Boersma and Davy Cats and Elders, {Petra M.} and Geleijnse, {J. Marianne} and Ikram, {M. Arfan} and Margreet Kloppenburg and Haillang Mei and Ingrid Meulenbelt and Mooijaart, {Simon P.} and Nelissen, {Rob G. H. H.} and Netea, {Mihai G.} and Penninx, {Brenda W. J. H.} and Mariska Slofstra and Stehouwer, {Coen D. A.} and Swertz, {Morris A.} and Teunissen, {Charlotte E.} and Terwindt, {Gisela M.} and {'t Hart}, {Leen M.} and {van den Maagdenberg}, {Arn M. J. M.} and {van der Harst}, Pim and {van der Horst}, {Iwan C. C.} and {van der Kallen}, {Carla J. H.} and {van Greevenbroek}, {Marleen M. J.} and {van Spil}, {W. Erwin} and Cisca Wijmenga and Alexandra Zhernakova and Zwinderman, {Aeilko H.} and Naveed Sattar and Jukema, {J. Wouter} and {van Duijn}, {Cornelia M.} and Boomsma, {Dorret I.} and Reinders, {Marcel J. T.} and Slagboom, {P. Eline}",

note = "Publisher Copyright: {\textcopyright} 2020 American Heart Association, Inc.",

year = "2020",

month = oct,

doi = "10.1161/CIRCGEN.119.002610",

language = "English",

volume = "13",

pages = "541--547",

journal = "Circulation: Genomic and Precision Medicine",

issn = "2574-8300",

publisher = "Lippincott Williams and Wilkins Ltd.",

number = "5",

}

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 2020, 'Metabolic Age Based on the BBMRI-NL 1 H-NMR Metabolomics Repository as Biomarker of Age-related Disease', Circulation: Genomic and Precision Medicine, vol. 13, no. 5, 002610, pp. 541-547. https://doi.org/10.1161/CIRCGEN.119.002610

TY - JOUR

T1 - Metabolic Age Based on the BBMRI-NL 1 H-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 bmri.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 bmri.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.

KW - aging

KW - cardiovascular disease

KW - data science

KW - metabolomics

KW - DNA METHYLATION AGE

KW - MORTALITY

KW - REVEAL

KW - RISK

U2 - 10.1161/CIRCGEN.119.002610

DO - 10.1161/CIRCGEN.119.002610

M3 - Article

C2 - 33079603

SN - 2574-8300

VL - 13

SP - 541

EP - 547

JO - Circulation: Genomic and Precision Medicine

JF - Circulation: Genomic and Precision Medicine

IS - 5

M1 - 002610

ER -