NMR metabolomics-guided DNA methylation mortality predictors
Daniele Bizzarri (TU Delft - Pattern Recognition and Bioinformatics, Leiden University Medical Center)
Marcel J.T. Reinders (TU Delft - Pattern Recognition and Bioinformatics, Leiden University Medical Center)
Lieke Kuiper (Rijksinstituut voor Volksgezondheid en Milieu (RIVM), Erasmus MC)
Marian Beekman (Leiden University Medical Center)
Joris Deelen (Max Planck Institute for Biology of Ageing, Universität zu Köln, Leiden University Medical Center)
Joyce B.J. van Meurs (Erasmus MC)
Jenny van Dongen (Vrije Universiteit Amsterdam, Amsterdam Reproduction and Development Research Institute, Amsterdam, Amsterdam Public Health Research Institute)
René Pool (Vrije Universiteit Amsterdam, Amsterdam Public Health Research Institute)
Erik B. van den Akker (Leiden University Medical Center, TU Delft - Pattern Recognition and Bioinformatics)
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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.
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