The association between plasma metabolites and future risk of all-cause mortality

Abstract

Background: Metabolite profiles provide snapshots of the overall effect of numerous exposures accumulated over life courses, which may lead to health outcomes in the future.

Objective: We hypothesized that the risk of all-cause mortality is linked to alterations in metabolism earlier in life, which are reflected in plasma metabolite profiles. We aimed to identify plasma metabolites associated with future risk of all-cause mortality.

Methods: Through metabolomics, 110 metabolites were measured in 3833 individuals from the Malmö Diet and Cancer-Cardiovascular Cohort (MDC-CC). A total of 1574 deaths occurred within an average follow-up time of 22.2 years. Metabolites that were significantly associated with all-cause mortality in MDC-CC were replicated in 1500 individuals from Malmö Preventive Project re-examination (MPP), among whom 715 deaths occurred within an average follow-up time of 11.3 years.

Results: Twenty two metabolites were significantly associated with all-cause mortality in MDC-CC, of which 13 were replicated in MPP. Levels of trigonelline, glutamate, dimethylglycine, C18-1-carnitine, C16-1-carnitine, C14-1-carnitine, and 1-methyladenosine were associated with an increased risk, while levels of valine, tryptophan, lysine, leucine, histidine, and 2-aminoisobutyrate were associated with a decreased risk of all-cause mortality.

Conclusion: We used metabolomics in two Swedish prospective cohorts and identified replicable associations between 13 metabolites and future risk of all-cause mortality. Novel associations between five metabolites-C18-1-carnitine, C16-1-carnitine, C14-1-carnitine, trigonelline, and 2-aminoisobutyrate-and all-cause mortality were discovered. These findings suggest potential new biomarkers for the prediction of mortality and provide insights for understanding the biochemical pathways that lead to mortality.

Keywords: all-cause mortality; association; metabolite; metabolomics.

Fig. 1

Associations between the plasma levels of 110 metabolites at baseline and future risk of all‐cause mortality in participants from the Malmö Diet and Cancer–Cardiovascular Cohort (n = 3833). Using Cox regression model 1 (adjusted age and sex), logHR is the 10log of hazard ratio (per standard deviation increment of metabolite) and −log p is the negative 10log of false discovery rate (FDR)–adjusted p‐value. The association is considered significant when the FDR‐adjusted p‐value is <0.05.

Fig. 2

Associations between the plasma levels of the 13 identified metabolites at baseline and future risk of all‐cause mortality in the Malmö Diet and Cancer–Cardiovascular Cohort (MDC‐CC) (n = 3833) and Malmö Preventive Project (MPP) re‐examination (n = 1500). LogHR is the 10log of hazard ratio (per standard deviation increment of metabolite). The error bar denotes 95% standard deviation of the 10log of hazard ratio. The Cox regressions were adjusted for multivariate (age, sex, body mass index, fasting glucose, waist circumference, low‐density lipoprotein cholesterol, high‐density lipoprotein cholesterol, cholesterol, triglycerides, systolic blood pressure, diastolic blood pressure, having antihypertensive treatment or not, having lipid‐lowering treatment or not, smoking status, prevalence of baseline type 2 diabetes, and prevalence of baseline coronary artery disease).

Fig. 3

Associations between the plasma levels of the 13 identified metabolites at baseline and future risk of all‐cause mortality in males and females in (a) the Malmö Diet and Cancer–Cardiovascular Cohort (MDC‐CC) (n = 3833) and (b) Malmö Preventive Project (MPP) re‐examination (n = 1500). LogHR is the 10 log of hazard ratio (per standard deviation increment of metabolite). The error bar denotes 95% standard deviation of the 10 log of hazard ratio. The Cox regressions were adjusted for multivariate (age, body mass index, fasting glucose, waist circumference, low‐density lipoprotein cholesterol, high‐density lipoprotein cholesterol, cholesterol, triglycerides, systolic blood pressure, diastolic blood pressure, having antihypertensive treatment or not, having lipid‐lowering treatment or not, smoking status, prevalence of baseline type 2 diabetes, and prevalence of baseline coronary artery disease).