Predicting longer-term mortality risk requires collection of clinical data, which is often cumbersome. Therefore, we use a well-standardized metabolomics platform to identify metabolic predictors of long-term mortality in the circulation of 44,168 individuals (age at baseline 18–109), of whom 5512 died during follow-up. We apply a stepwise (forward-backward) procedure based on meta-analysis results and identify 14 circulating biomarkers independently associating with all-cause mortality. Overall, these associations are similar in men and women and across different age strata. We subsequently show that the prediction accuracy of 5- and 10-year mortality based on a model containing the identified biomarkers and sex (C-statistic = 0.837 and 0.830, respectively) is better than that of a model containing conventional risk factors for mortality (C-statistic = 0.772 and 0.790, respectively). The use of the identified metabolic profile as a predictor of mortality or surrogate endpoint in clinical studies needs further investigation.

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Persistent URL dx.doi.org/10.1038/s41467-019-11311-9, hdl.handle.net/1765/119081
Journal Nature Communications
Citation
Deelen, J, Kettunen, J. (Johannes), Fischer, K, van der Spek, A, Trompet, S, Kastenmuller, G, … Slagboom, P.E. (2019). A metabolic profile of all-cause mortality risk identified in an observational study of 44,168 individuals. Nature Communications, 10(1). doi:10.1038/s41467-019-11311-9