A metabolic profile of all-cause mortality risk identified in an observational 
study of 44,168 individuals

Deelen, J.; Kettunen, J.; Fischer, K.; van der Spek, A.; Trompet, S.; Kastenmuller, G.; Boyd, A.; Zierer, J.; van den Akker, E. B.; Ala-Korpela, M.; Amin, N.; Demirkan, A.; Ghanbari, M.; van Heemst, D.; Ikram, M. A.; van Klinken, J. B.; Mooijaart, S. P.; Peters, A.; Salomaa, V.; Sattar, N.; Spector, T. D.; Tiemeier, H.; Verhoeven, A.; Waldenberger, M.; Wurtz, P.; Davey Smith, G.; Metspalu, A.; Perola, M.; Menni, C.; Geleijnse, J. M.; Drenos, F.; Beekman, M.; Jukema, J. W.; van Duijn, C. M.; Slagboom, P. E.

doi:10.1038/s41467-019-11311-9

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A metabolic profile of all-cause mortality risk identified in an observational study of 44,168 individuals

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Deelen, J.
Deelen – Genetics and Biomarkers of Human Ageing, Research Groups, Max Planck Institute for Biology of Ageing, Max Planck Society;

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https://www.ncbi.nlm.nih.gov/pubmed/31431621
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Citation

Deelen, J., Kettunen, J., Fischer, K., van der Spek, A., Trompet, S., Kastenmuller, G., et al. (2019). A metabolic profile of all-cause mortality risk identified in an observational study of 44,168 individuals. Nat Commun, 10(1), 3346. doi:10.1038/s41467-019-11311-9.

Cite as: https://hdl.handle.net/21.11116/0000-000B-2B95-D

Abstract

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.