Baseline metBMI and epigenomic signatures: a precision medicine framework for predicting cardiometabolic disease trajectories in aging populations

Project Summary

Traditional body mass index (BMI) poorly predicts who will develop diabetes and heart disease. We developed a superior measure, metabolic BMI (metBMI), based on blood metabolites that better identifies at-risk individuals. This study will use baseline metBMI and DNA modifications in over 9,000 aging Canadians to predict disease trajectories years before symptoms appear, tracking clinical outcomes over 6-9 years of follow-up. By integrating metabolic and epigenetic data, we will build personalized risk calculators for earlier intervention and compare performance with newly defined obesity subclusters across large populations. Results will be validated in three European cohorts. This precision medicine approach could transform prevention by identifying high-risk individuals earlier, potentially averting thousands of diabetes and cardiovascular disease cases through targeted, biology-based interventions rather than weight alone.