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NMR metabolomics-guided DNA methylation mortality predictors.
Bizzarri, Daniele; Reinders, Marcel J T; Kuiper, Lieke; Beekman, Marian; Deelen, Joris; van Meurs, Joyce B J; van Dongen, Jenny; Pool, René; Boomsma, Dorret I; Ghanbari, Mohsen; Franke, Lude; Slagboom, Pieternella E; van den Akker, Erik B.
Afiliação
  • Bizzarri D; Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands; Leiden Computational Biology Center, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands; Delft Bioinformatics Lab, TU Delft, Delft
  • Reinders MJT; Leiden Computational Biology Center, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands; Delft Bioinformatics Lab, TU Delft, Delft, the Netherlands.
  • Kuiper L; Department of Internal Medicine, Erasmus MC, Rotterdam, the Netherlands; Center for Nutrition, Prevention and Health Services, National Institute for Public Health and Environment (RIVM), Bilthoven, the Netherlands.
  • Beekman M; Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands.
  • Deelen J; Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands; Max Planck Institute for the Biology of Ageing, Cologne, Germany; Cologne Excellence Cluster on Cellular Stress Responses in Aging Associated Diseases, University of Cologne, Co
  • van Meurs JBJ; Department of Internal Medicine, Erasmus MC, Rotterdam, the Netherlands; Department of Orthopaedics & Sports, Erasmus Medical Center, Rotterdam, the Netherlands.
  • van Dongen J; Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands; Amsterdam Reproduction and Development (AR&D) Research Institute, Amsterdam, the Netherlands; Amsterdam Public Health Research Institute, Amsterdam, the Netherlands.
  • Pool R; Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands; Amsterdam Public Health Research Institute, Amsterdam, the Netherlands.
  • Boomsma DI; Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands; Amsterdam Reproduction and Development (AR&D) Research Institute, Amsterdam, the Netherlands; Amsterdam Public Health Research Institute, Amsterdam, the Netherlands.
  • Ghanbari M; Department of Epidemiology, Erasmus MC, Rotterdam, the Netherlands.
  • Franke L; Department of Genetics, University Medical Center Groningen, Groningen, the Netherlands.
  • Slagboom PE; Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands; Max Planck Institute for the Biology of Ageing, Cologne, Germany.
  • van den Akker EB; Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands; Leiden Computational Biology Center, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands; Delft Bioinformatics Lab, TU Delft, Delft
EBioMedicine ; 107: 105279, 2024 Aug 17.
Article em En | MEDLINE | ID: mdl-39154540
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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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article