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Simultaneous prediction of risk for multiple common diseases using metabolomics

Early identification of at-risk people is critical in disease prevention, but current screening approaches are resource intensive and are often restricted to one disease at a time. We show how nuclear magnetic resonance (NMR) spectroscopy–derived metabolomics profiles can be used to predict multi-disease risk for the onset of 24 common conditions.

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Fig. 1: Study overview.

References

  1. Deelen, J. et al. A metabolic profile of all-cause mortality risk identified in an observational study of 44,168 individuals. Nat. Commun. 10, 3346 (2019). A landmark study linking NMR metabolomics profiles to mortality risk.

    Article  Google Scholar 

  2. Pietzner, M. et al. Plasma metabolites to profile pathways in noncommunicable disease multimorbidity. Nat. Med. 27, 471–479 (2021). An important article that presents the broad metabolic basis across the human disease landscape.

    CAS  Article  Google Scholar 

  3. Würtz, P. et al. Quantitative serum nuclear magnetic resonance metabolomics in large-scale epidemiology: a primer on -omic technologies. Am. J. Epidemiol. 186, 1084–1096 (2017). A comprehensive review of the potential utility of broad biomarker platforms.

    Article  Google Scholar 

  4. Sudlow, C. et al. UK Biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age. PLoS Med. 12, e1001779 (2015). A detailed description of the UK Biobank resource.

    Article  Google Scholar 

  5. Fry, A. et al. Comparison of sociodemographic and health-related characteristics of UK Biobank participants with those of the general population. Am. J. Epidemiol. 186, 1026–1034 (2017). An important study on differences between the UK Biobank and the UK general population.

    Article  Google Scholar 

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This is a summary of: Buergel, T. et al. Metabolomic profiles predict individual multidisease outcomes. Nat. Med. https://doi.org/10.1038/s41591-022-01980-3 (2022).

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Simultaneous prediction of risk for multiple common diseases using metabolomics. Nat Med (2022). https://doi.org/10.1038/s41591-022-01992-z

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