NMR metabolomics-guided DNA methylation mortality predictors

Daniele Bizzarri; Marcel J.T. Reinders; J. van Dongen; René Pool; Dorret I. Boomsma; A. H.M. Willemsen; Pieternella E. Slagboom; Erik B. van den Akker; BBMRI Consortium

doi:10.1016/j.ebiom.2024.105279

NMR metabolomics-guided DNA methylation mortality predictors

Daniele Bizzarri, Marcel J.T. Reinders, J. van Dongen, René Pool, Dorret I. Boomsma, A. H.M. Willemsen, Pieternella E. Slagboom, Erik B. van den Akker^*, BBMRI Consortium

^*Corresponding author for this work

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

Abstract

Background: ¹H-NMR metabolomics and DNA methylation in blood are widely known biomarkers predicting age-related physiological decline and mortality yet exert mutually independent mortality and frailty signals. Methods: Leveraging multi-omics data in four Dutch population studies (N = 5238, ∼40% of which male) we investigated whether the mortality signal captured by ¹H-NMR metabolomics could guide the construction of DNA methylation-based mortality predictors. Findings: We trained DNA methylation-based surrogates for 64 metabolomic analytes and found that analytes marking inflammation, fluid balance, or HDL/VLDL metabolism could be accurately reconstructed using DNA-methylation assays. Interestingly, a previously reported multi-analyte score indicating mortality risk (MetaboHealth) could also be accurately reconstructed. Sixteen of our derived surrogates, including the MetaboHealth surrogate, showed significant associations with mortality, independent of relevant covariates. Interpretation: The addition of our metabolic analyte-derived surrogates to the well-established epigenetic clock GrimAge demonstrates that our surrogates potentially represent valuable mortality signal. Funding: BBMRI-NL, X-omics, VOILA, Medical Delta, NWO, ERC.

Original language	English
Article number	105279
Pages (from-to)	1-17
Number of pages	17
Journal	Ebiomedicine
Volume	107
Early online date	17 Aug 2024
DOIs	https://doi.org/10.1016/j.ebiom.2024.105279
Publication status	Published - Sept 2024

Bibliographical note

Publisher Copyright:
© 2024 The Authors

Funding

EBvdA, DB, MJTR and PES conceived and wrote the manuscript. DB performed the analyses. EBvdA and MJTR verified and supervised the analyses. PES, MB, JBJvM, JvD, DIB, RP, MG, LF were involved in data acquisition of the cohort data. All authors (DB, MJTR, LMK, MB, JD, JBJvM, JvD, RP, DIB, MG, LF, PES, EBvdA) discussed the results read, and approved the final version of the manuscript. Data used in this manuscript was mostly funded by the BBMRI-NL Metabolomics Consortium. This work was performed within the BBMRI Metabolomics Consortium funded by: BBMRI-NL (financed by NWO 184.021.007 and 184.033.111), X-omics (NWO 184.034.019), VOILA (ZonMW 457001001) and Medical Delta (METABODELTA: Metabolomics for clinical advances in the Medical Delta). EBvdA is funded by a personal grant of the Dutch Research Council (NWO; VENI:09150161810095). Acknowledgements for all contributing studies can be found in the Supplementary Material-BIOS Consortium. Additional NTR samples were funded by the European Research Council (ERC-230374) project Genetics of Mental Illness (DIB).

Funders	Funder number
BBMRI-NL Metabolomics Consortium
BBMRI-NL
Nederlandse Organisatie voor Wetenschappelijk Onderzoek	184.034.019, 184.033.111, 09150161810095, 184.021.007
European Research Council	ERC-230374
VOILA	ZonMW 457001001

Keywords

Ageing biomarkers
DNA methylation predictors
Epidemiology
Epigenetic clock
Metabolic risk score
NMR metabolomics

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10.1016/j.ebiom.2024.105279

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Cite this

@article{4d3b5f8b10f04fd8975922a2d45edc76,

title = "NMR metabolomics-guided DNA methylation mortality predictors",

abstract = "Background: 1H-NMR metabolomics and DNA methylation in blood are widely known biomarkers predicting age-related physiological decline and mortality yet exert mutually independent mortality and frailty signals. Methods: Leveraging multi-omics data in four Dutch population studies (N = 5238, ∼40\% of which male) we investigated whether the mortality signal captured by 1H-NMR metabolomics could guide the construction of DNA methylation-based mortality predictors. Findings: We trained DNA methylation-based surrogates for 64 metabolomic analytes and found that analytes marking inflammation, fluid balance, or HDL/VLDL metabolism could be accurately reconstructed using DNA-methylation assays. Interestingly, a previously reported multi-analyte score indicating mortality risk (MetaboHealth) could also be accurately reconstructed. Sixteen of our derived surrogates, including the MetaboHealth surrogate, showed significant associations with mortality, independent of relevant covariates. Interpretation: The addition of our metabolic analyte-derived surrogates to the well-established epigenetic clock GrimAge demonstrates that our surrogates potentially represent valuable mortality signal. Funding: BBMRI-NL, X-omics, VOILA, Medical Delta, NWO, ERC.",

keywords = "Ageing biomarkers, DNA methylation predictors, Epidemiology, Epigenetic clock, Metabolic risk score, NMR metabolomics",

author = "Daniele Bizzarri and Reinders, \{Marcel J.T.\} and Lieke Kuiper and Marian Beekman and J. Deelen and \{van Meurs\}, \{Joyce B.J.\} and \{van Dongen\}, J. and Ren{\'e} Pool and Boomsma, \{Dorret I.\} and M. Ghanbari and Lude Franke and Geleijnse, \{J. M.\} and E. Boersma and \{van Spil\}, \{W. E.\} and \{van Greevenbroek\}, \{M. M.J.\} and Stehouwer, \{C. D.A.\} and \{van der Kallen\}, \{C. J.H.\} and Arts, \{I. C.W.\} and F. Rutters and Beulens, \{J. W.J.\} and M. Muilwijk and Elders, \{P. J.M.\} and \{'t Hart\}, \{L. M.\} and M. Ghanbari and Ikram, \{M. A.\} and Netea, \{M. G.\} and M. Kloppenburg and Ramos, \{Y. F.M.\} and N. Bomer and I. Meulenbelt and K. Stronks and Snijder, \{M. B.\} and Zwinderman, \{A. H.\} and Heijmans, \{B. T.\} and Lumey, \{L. H.\} and C. Wijmenga and J. Fu and A. Zhernakova and J. Deelen and Mooijaart, \{S. P.\} and M. Beekman and Slagboom, \{P. E.\} and Onderwater, \{G. L.J.\} and \{van den Maagdenberg\}, \{A. M.J.M.\} and Terwindt, \{G. M.\} and C. Thesing and M. Bot and Penninx, \{B. W.J.H.\} and S. Trompet and Jukema, \{J. W.\} and N. Sattar and \{van der Horst\}, \{I. C.C.\} and \{van der Harst\}, P. and C. So-Osman and \{van Hilten\}, \{J. A.\} and Nelissen, \{R. G.H.H.\} and H{\"o}fer, \{I. E.\} and Asselbergs, \{F. W.\} and P. Scheltens and Teunissen, \{C. E.\} and \{van der Flier\}, \{W. M.\} and \{van Dongen\}, J. and R. Pool and Willemsen, \{A. H.M.\} and Boomsma, \{D. I.\} and Suchiman, \{H. E.D.\} and \{Barkey Wolf\}, \{J. J.H.\} and D. Cats and H. Mei and M. Slofstra and M. Swertz and Reinders, \{M. J.T.\} and \{van den Akker\}, \{Erik B.\} and Slagboom, \{Pieternella E.\} and \{van den Akker\}, \{Erik B.\} and \{BBMRI Consortium\}",

note = "Publisher Copyright: {\textcopyright} 2024 The Authors",

year = "2024",

month = sep,

doi = "10.1016/j.ebiom.2024.105279",

language = "English",

volume = "107",

pages = "1--17",

journal = "Ebiomedicine",

issn = "2352-3964",

publisher = "Elsevier BV",

}

TY - JOUR

T1 - NMR metabolomics-guided DNA methylation mortality predictors

AU - Bizzarri, Daniele

AU - Reinders, Marcel J.T.

AU - Kuiper, Lieke

AU - Beekman, Marian

AU - Deelen, J.

AU - van Meurs, Joyce B.J.

AU - van Dongen, J.

AU - Pool, René

AU - Boomsma, Dorret I.

AU - Ghanbari, M.

AU - Franke, Lude

AU - Geleijnse, J. M.

AU - Boersma, E.

AU - van Spil, W. E.

AU - van Greevenbroek, M. M.J.

AU - Stehouwer, C. D.A.

AU - van der Kallen, C. J.H.

AU - Arts, I. C.W.

AU - Rutters, F.

AU - Beulens, J. W.J.

AU - Muilwijk, M.

AU - Elders, P. J.M.

AU - 't Hart, L. M.

AU - Ghanbari, M.

AU - Ikram, M. A.

AU - Netea, M. G.

AU - Kloppenburg, M.

AU - Ramos, Y. F.M.

AU - Bomer, N.

AU - Meulenbelt, I.

AU - Stronks, K.

AU - Snijder, M. B.

AU - Zwinderman, A. H.

AU - Heijmans, B. T.

AU - Lumey, L. H.

AU - Wijmenga, C.

AU - Fu, J.

AU - Zhernakova, A.

AU - Deelen, J.

AU - Mooijaart, S. P.

AU - Beekman, M.

AU - Slagboom, P. E.

AU - Onderwater, G. L.J.

AU - van den Maagdenberg, A. M.J.M.

AU - Terwindt, G. M.

AU - Thesing, C.

AU - Bot, M.

AU - Penninx, B. W.J.H.

AU - Trompet, S.

AU - Jukema, J. W.

AU - Sattar, N.

AU - van der Horst, I. C.C.

AU - van der Harst, P.

AU - So-Osman, C.

AU - van Hilten, J. A.

AU - Nelissen, R. G.H.H.

AU - Höfer, I. E.

AU - Asselbergs, F. W.

AU - Scheltens, P.

AU - Teunissen, C. E.

AU - van der Flier, W. M.

AU - van Dongen, J.

AU - Pool, R.

AU - Willemsen, A. H.M.

AU - Boomsma, D. I.

AU - Suchiman, H. E.D.

AU - Barkey Wolf, J. J.H.

AU - Cats, D.

AU - Mei, H.

AU - Slofstra, M.

AU - Swertz, M.

AU - Reinders, M. J.T.

AU - van den Akker, Erik B.

AU - Slagboom, Pieternella E.

AU - van den Akker, Erik B.

AU - BBMRI Consortium

PY - 2024/9

Y1 - 2024/9

N2 - Background: 1H-NMR metabolomics and DNA methylation in blood are widely known biomarkers predicting age-related physiological decline and mortality yet exert mutually independent mortality and frailty signals. Methods: Leveraging multi-omics data in four Dutch population studies (N = 5238, ∼40% of which male) we investigated whether the mortality signal captured by 1H-NMR metabolomics could guide the construction of DNA methylation-based mortality predictors. Findings: We trained DNA methylation-based surrogates for 64 metabolomic analytes and found that analytes marking inflammation, fluid balance, or HDL/VLDL metabolism could be accurately reconstructed using DNA-methylation assays. Interestingly, a previously reported multi-analyte score indicating mortality risk (MetaboHealth) could also be accurately reconstructed. Sixteen of our derived surrogates, including the MetaboHealth surrogate, showed significant associations with mortality, independent of relevant covariates. Interpretation: The addition of our metabolic analyte-derived surrogates to the well-established epigenetic clock GrimAge demonstrates that our surrogates potentially represent valuable mortality signal. Funding: BBMRI-NL, X-omics, VOILA, Medical Delta, NWO, ERC.

AB - Background: 1H-NMR metabolomics and DNA methylation in blood are widely known biomarkers predicting age-related physiological decline and mortality yet exert mutually independent mortality and frailty signals. Methods: Leveraging multi-omics data in four Dutch population studies (N = 5238, ∼40% of which male) we investigated whether the mortality signal captured by 1H-NMR metabolomics could guide the construction of DNA methylation-based mortality predictors. Findings: We trained DNA methylation-based surrogates for 64 metabolomic analytes and found that analytes marking inflammation, fluid balance, or HDL/VLDL metabolism could be accurately reconstructed using DNA-methylation assays. Interestingly, a previously reported multi-analyte score indicating mortality risk (MetaboHealth) could also be accurately reconstructed. Sixteen of our derived surrogates, including the MetaboHealth surrogate, showed significant associations with mortality, independent of relevant covariates. Interpretation: The addition of our metabolic analyte-derived surrogates to the well-established epigenetic clock GrimAge demonstrates that our surrogates potentially represent valuable mortality signal. Funding: BBMRI-NL, X-omics, VOILA, Medical Delta, NWO, ERC.

KW - Ageing biomarkers

KW - DNA methylation predictors

KW - Epidemiology

KW - Epigenetic clock

KW - Metabolic risk score

KW - NMR metabolomics

UR - https://www.scopus.com/pages/publications/85201444255

UR - https://www.scopus.com/inward/citedby.url?scp=85201444255&partnerID=8YFLogxK

U2 - 10.1016/j.ebiom.2024.105279

DO - 10.1016/j.ebiom.2024.105279

M3 - Article

AN - SCOPUS:85201444255

SN - 2352-3964

VL - 107

SP - 1

EP - 17

JO - Ebiomedicine

JF - Ebiomedicine

M1 - 105279

ER -

NMR metabolomics-guided DNA methylation mortality predictors

Abstract

Bibliographical note

Funding

Keywords

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