Multiomics insight into disease trajectories of cardiometabolic diseases and cancer.

Abstract

Multimorbidity of cardiometabolic disease (CMD) and cancer is a growing but understudied global challenge in an aging world. Here, we perform multistate analysis in 429,555 UK Biobank participants to investigate transition patterns, identify multiomics signatures, and construct prediction models from baseline to single and multiple morbidities. During a median follow-up of 15 years, 105,903 participants develop single morbidity and 15,088 develop multimorbidity of CMD and cancer. Participants with multimorbidity have a 13%-33% higher mortality probability than those healthy or with single morbidity. In individuals living with multimorbidity, the development of CMD before cancer presents a higher mortality risk than the reverse order. Distinct and shared multiomics signatures are identified, with proteomics scores outperforming other omics in predicting disease trajectories (ΔC-statistic vs. base model: 0.03-0.14). This study reveals distinct transition patterns in CMD-cancer multimorbidity cluster and develops potentially useful prediction tools for supporting risk management if externally validated.