Multi-omic signatures and trajectories of cardiometabolic diseases and depression

Cardiometabolic diseases (CMDs) and depression frequently co-occur and substantially increase mortality risk yet their multimorbidity trajectories and underlying biological mechanisms remain unclear. Here we analyzed 467,592 UK Biobank participants without baseline CMDs or depression, utilizing multistate models to characterize nine disease transition patterns and multi-omic approaches to identify predictive signatures. During a 14.6-year follow-up, 64,442 participants developed CMDs alone, 17,530 developed depression alone and 6,104 developed multimorbidity. Participants with either CMDs or depression exhibited higher risks of developing the other compared with healthy individuals. Multimorbidity increased mortality risk by 13–22% and reduced life expectancy by 3.6–3.8 years compared with disease-free individuals, although survival analysis revealed additive rather than synergistic effects. Multi-omic analysis identified distinct signatures across transitions, with proteomic models achieving 15-year area under the receiver-operating characteristic curve values of 0.70–0.91, significantly outperforming clinical models. These findings advance understanding of CMD–depression multimorbidity trajectories and offer potential for early risk stratification and targeted prevention.