Metabolic Age Based on the BBMRI-NL 1 H-NMR Metabolomics Repository as Biomarker of Age-related Disease-Reference-Cited by-同舟云学术

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

Published:2020-10 Issue:5 Volume:13 Page:541-547
ISSN:2574-8300
Container-title:Circulation: Genomic and Precision Medicine
language:en
Short-container-title:Circ: Genomic and Precision Medicine

Author:

van den Akker Erik B.¹²³^ORCID,Trompet Stella¹⁴^ORCID,Barkey Wolf Jurriaan J.H.¹,Beekman Marian¹^ORCID,Suchiman H. Eka D.¹^ORCID,Deelen Joris¹⁵^ORCID,Asselbergs Folkert W.⁶⁷⁸⁹^ORCID,Boersma Eric¹⁰^ORCID,Cats Davy¹^ORCID,Elders Petra M.¹¹¹²^ORCID,Geleijnse J. Marianne¹³^ORCID,Ikram M. Arfan¹⁴¹⁵¹⁶^ORCID,Kloppenburg Margreet¹⁷¹⁸,Mei Haillang¹¹⁹^ORCID,Meulenbelt Ingrid¹^ORCID,Mooijaart Simon P.²^ORCID,Nelissen Rob G.H.H.²⁰,Netea Mihai G.²¹,Penninx Brenda W.J.H.¹²²²^ORCID,Slofstra Mariska²³,Stehouwer Coen D.A.²⁴²⁵^ORCID,Swertz Morris A.²³^ORCID,Teunissen Charlotte E.²⁶^ORCID,Terwindt Gisela M.²⁷^ORCID,‘t Hart Leen M.¹²⁸¹²²⁹³⁰^ORCID,van den Maagdenberg Arn M.J.M.³¹,van der Harst Pim³²^ORCID,van der Horst Iwan C.C.³³^ORCID,van der Kallen Carla J.H.²⁴²⁵^ORCID,van Greevenbroek Marleen M.J.²⁴²⁵,van Spil W. Erwin³⁴^ORCID,Wijmenga Cisca²³,Zhernakova Alexandra²³^ORCID,Zwinderman Aeilko H.³⁵^ORCID,Sattar Naveed³⁶^ORCID,Jukema J. Wouter³⁷^ORCID,van Duijn Cornelia M.¹⁴^ORCID,Boomsma Dorret I.³⁷³⁸^ORCID,Reinders Marcel J.T.²³^ORCID,Slagboom P. Eline¹⁵^ORCID

Affiliation:

1. Department of Molecular Epidemiology (E.B.v.d.A., J.J.H.B.W., M.B., H.E.D.S., J.D., D.C., H.M., I.M., L.M.‘t.H., P.E.S.)

2. Department of Biomedical Data Sciences, Leiden Computational Biology Center (E.B.v.d.A., M.J.T.R.), Leiden University Medical Center, the Netherlands.

3. Department of Pattern Recognition and Bioinformatics, Delft University of Technology, the Netherlands (E.B.v.d.A., M.J.T.R.).

4. Department of Internal Medicine, Division of Gerontology and Geriatrics (S.T., S.P.M.), Leiden University Medical Center, the Netherlands.

5. Max Planck Institute for Biology of Ageing, Cologne, Germany (J.D., P.E.S.).

6. Department of Cardiology, Division of Heart and Lungs (F.W.A.), University Medical Center Utrecht, the Netherlands.

7. Durrer Center for Cardiovascular Research, Netherlands Heart Institute, Utrecht (F.W.A.).

8. Faculty of Population Health Sciences, Institute of Cardiovascular Science (F.W.A.), Institute of Health Informatics, UCL, London, United Kingdom.

9. Farr Institute of Health Informatics Research (F.W.A.), Institute of Health Informatics, UCL, London, United Kingdom.

10. Thorax Center (E.B.), Erasmus Medical Center, Rotterdam, the Netherlands.

11. Department of General Practice and Elderly Care Medicine (P.M.E.), VU University Medical Center, the Netherlands.

12. Amsterdam Public Health Research Institute (P.M.E., B.W.J.H.P., L.M.‘t.H., D.I.B.), VU University Medical Center, the Netherlands.

13. Division of Human Nutrition and Health, Wageningen University, the Netherlands (J.M.G.).

14. Department of Epidemiology (M.A.I., C.M.v.D.), Erasmus Medical Center, Rotterdam, the Netherlands.

15. Department of Radiology (M.A.I.), Erasmus Medical Center, Rotterdam, the Netherlands.

16. Department of Neurology (M.A.I.), Erasmus Medical Center, Rotterdam, the Netherlands.

17. Department of Rheumatology (M.K.), Leiden University Medical Center, the Netherlands.

18. Department of Clinical Epidemiology (M.K.), Leiden University Medical Center, the Netherlands.

19. Department of Biomedical Data Sciences, Sequencing Analysis Support Core (H.M.), Leiden University Medical Center, the Netherlands.

20. Department of Orthopaedics (R.G.H.H.N.), Leiden University Medical Center, the Netherlands.

21. Department for Genomics and Immunoregulation, Life and Medical Sciences Institute, University of Bonn, Germany (M.G.N.).

22. Department of Psychiatry (B.W.J.H.P.), VU University Medical Center, the Netherlands.

23. Department of Genetics, University of Groningen, the Netherlands (M.S., M.A.S., C.W., A.Z.).

24. Department of Internal Medicine, Maastricht University Medical Center, the Netherlands (C.D.A.S., C.J.H.v.d.K., M.M.J.v.G.).

25. School for Cardiovascular Diseases (Cardiovascular Research Institute Maastricht [CARIM]), Maastricht University, Maastricht, the Netherlands (C.D.A.S., C.J.H.v.d.K., M.M.J.v.G.).

26. Neurochemistry Laboratory, Clinical Chemistry Department (C.E.T.), Amsterdam University Medical Center, the Netherlands.

27. Department of Neurology (G.M.T.), Leiden University Medical Center, the Netherlands.

28. Department of Cell and Chemical Biology (L.M.‘t.H.), Leiden University Medical Center, the Netherlands.

29. Department of Epidemiology and Biostatistics (L.M.‘t.H.), Amsterdam University Medical Center, the Netherlands.

30. Department of General Practice (L.M.‘t.H.), Amsterdam University Medical Center, the Netherlands.

31. Department of Human Genetics (A.M.J.M.v.d.M.), Leiden University Medical Center, the Netherlands.

32. Department of Cardiology (P.v.d.H.), University Medical Center Groningen, the Netherlands.

33. Department of Critical Care (I.C.C.v.d.H.), University Medical Center Groningen, the Netherlands.

34. Department of Rheumatology and Clinical Immunology (W.E.v.S.), University Medical Center Utrecht, the Netherlands.

35. Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Center, University of Amsterdam, the Netherlands (A.H.Z.).

36. Institute of Cardiovascular and Medical Sciences, Cardiovascular Research Center, University of Glasgow, United Kingdom (N.S.).

37. Department of Cardiology (S.T., J.W.J.), Leiden University Medical Center, the Netherlands.

38. Netherlands Twin Register, Department of Biological Psychology, Vrije University, Amsterdam (D.I.B.).

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.

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

General Medicine

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