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A metabolic profile of all-cause mortality risk identified in an observational study of 44,168 individuals
- Source :
- ISSN: 2041-1723
- Publication Year :
- 2019
-
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.
Details
- Database :
- OAIster
- Journal :
- ISSN: 2041-1723
- Notes :
- application/pdf, Nature Communications 10 (2019), ISSN: 2041-1723, ISSN: 2041-1723, English
- Publication Type :
- Electronic Resource
- Accession number :
- edsoai.on1200318961
- Document Type :
- Electronic Resource