A metabolic profile of all-cause mortality risk identified in an observational study of 44,168 individuals
- PMID: 31431621
- PMCID: PMC6702196
- DOI: 10.1038/s41467-019-11311-9
A metabolic profile of all-cause mortality risk identified in an observational study of 44,168 individuals
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.
Conflict of interest statement
P.W. is an employee and shareholder of Nightingale Health Ltd., the company offering the NMR-based metabolite profiling used in the current study. J.K. owns stock options for Nightingale Health Ltd. V.S. has participated in a conference trip sponsored by Novo Nordisk and received a honorarium for participating in an advisory board meeting. He also has an ongoing research collaboration with Bayer Ltd. (all unrelated to the present study). Remaining authors declare no competing interests.
Figures

Comment in
-
Predicting longevity using metabolomics: a novel tool for precision lifestyle medicine?Nat Rev Cardiol. 2020 Feb;17(2):67-68. doi: 10.1038/s41569-019-0310-2. Nat Rev Cardiol. 2020. PMID: 31754191 No abstract available.
-
Nuclear Magnetic Resonance Metabolomics-Enabled Biomarker Discovery for All-Cause Mortality.Clin Chem. 2020 Feb 1;66(2):400. doi: 10.1093/clinchem/hvz014. Clin Chem. 2020. PMID: 32040584 No abstract available.
References
Publication types
MeSH terms
Substances
Grants and funding
LinkOut - more resources
Full Text Sources
Other Literature Sources