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

Joris Deelen*, Johannes Kettunen, Krista Fischer, Ashley van der Spek, Stella Trompet, Andy Boyd, Jonas Zierer, Erik B. van den Akker, Mika Ala-Korpela, More Authors

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

79 Citations (Scopus)
58 Downloads (Pure)

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.
Original languageEnglish
Article number3346
Pages (from-to)1-8
Number of pages8
JournalNature Communications
Volume10
Issue number1
DOIs
Publication statusPublished - 2019

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