From disease-free status to cardiometabolic multimorbidity: Metabolomic signatures associated with cardiometabolic...

Although research has focused on metabolomic profiles linked to individual cardiometabolic diseases, there is a lack of studies on metabolomic signatures associated with cardiometabolic multimorbidity.

We included 79,712 participants without cardiometabolic disease from the UK Biobank, randomly divided at a 70:30 training:testing ratio. Cox proportional hazards regression models were used to identify 249 metabolic biomarkers associated with cardiometabolic multimorbidity. Two-sample Mendelian randomization analyses were applied to explore the causal relationships between the identified metabolites and cardiometabolic outcomes. The association between the metabolic risk score and the risk of transitioning from disease-free status to cardiometabolic multimorbidity was evaluated using multi-state models.

Of the 249 metabolites, 183 were associated with cardiometabolic multimorbidity. Very low-density lipoprotein cholesterol levels were positively associated, whereas high-density lipoprotein cholesterol levels were inversely associated. Mendelian randomization identified the apolipoprotein B to A1 ratio as causally associated with ischemic heart disease, cardiometabolic multimorbidity, and stroke. Metabolite risk scores demonstrated a positive association with the risk of cardiometabolic multimorbidity (hazard ratio 2.67; 95% confidence interval 2.05-3.49) in the testing set. In multi-state models, those with a higher metabolite risk score had an increased risk of progressing from disease-free status to first cardiometabolic disease (hazard ratio 1.71, 95% confidence interval 1.51-1.93) and from first cardiometabolic disease to cardiometabolic multimorbidity (hazard ratio 1.89, 95% confidence interval 1.45-2.47) in the testing set.

Our findings indicate that metabolomic signatures can significantly aid risk stratification, underscoring the need to explore metabolic biomarkers in cardiometabolic multimorbidity to inform preventive strategies.