Lifestyle-associated metabolite signatures and the risk of late-onset asthma.

BACKGROUND Unhealthy lifestyle behaviors, leading to systemic metabolic disturbances, are significantly linked to the risk of late-onset asthma. However, the underlying metabolism-related mechanisms remain unclear. OBJECTIVE This study aims to identify lifestyle-related metabolites and assess their predictive value for incident asthma. METHODS Using NMR metabolomics data from the UK Biobank population (aged 40-69), plasma metabolites associated with healthy lifestyle scores were identified through multiple linear regression. Cox proportional hazards regression was used to further screen metabolites linked to late-onset asthma risk. Elastic net regularization selected critical metabolites for developing an asthma risk prediction model, incorporating conventional clinical characteristics and lifestyle factors. A metabolic score based on non-zero regularization coefficients was derived, and its association with asthma risk was evaluated through survival analysis. Models and metabolic score performance were validated in unused internal UK Biobank participants and an external China Kadoorie Biobank cohort. RESULTS Among 198,607 participants (mean age 56.4 years), 159 plasma metabolites were significantly related to healthy lifestyle scores, 103 of which were associated with incident asthma risk. Nine metabolites were selected and incorporated into the asthma risk prediction model, significantly improving its predictive performance (Area under the curve: 0.812 vs. 0.758). Individuals with an unfavorable metabolic signature exhibited a 77.0% increased risk (hazard ratio [HR] 1.770, 95% confidence interval [CI] 1.634-1.918) of developing asthma compared to those with a favorable metabolic signature, with a stronger effect observed in females (HR 1.914, 95% CI 1.729-2.118). The results for the predictive model and metabolic score were confirmed in both internal and external validations. CONCLUSION Multiple lifestyle-related metabolites are associated with late-onset asthma risk and can help stratify asthma risk, particularly among females.