Cardiometabolic disorders, cancer, and musculoskeletal diseases (MSDs) frequently co-occur in aging populations, yet their interconnected pathophysiology is often studied in isolation. This research aims to bridge these gaps by investigating the shared genetic pleiotropy and biological pathways, such as systemic inflammation and cellular senescence, that link cardiovascular diseases with MSDs like osteoarthritis and sarcopenia, as well as various malignancies. A central focus will be the bone-vascular axis, specifically examining how the interplay between vascular calcification and bone loss influences both all-cause and cause-specific mortality. By integrating multi-modal data from MRI, Olink proteomics, and metabolomics, the study seeks to predict the emergence of complex multimorbidity clusters and their clinical trajectories.
The project objectives include deep phenotyping to identify clinical co-occurrence patterns across cardiac, metabolic, oncological, and skeletal domains. We will leverage high-throughput genomics and proteomics to uncover the shared upstream regulators driving cross-system degeneration. Furthermore, the study will employ Mendelian Randomization to establish causal links within the cardio-skeletal-cancer triad and develop AI-driven risk models that integrate cardiac and abdominal MRI with DXA data to predict adverse outcomes in multimorbid patients. Scientific evidence increasingly points to a tight regulation between bone metabolism, cardiovascular function, and oncological processes. The UK Biobank’s unprecedented scale and deep phenotyping provide a unique opportunity to systematically map the cardio-metabolic-skeletal network. Access to these diverse data domains is indispensable for disentangling the complex, multi-system etiology of multimorbidity in the elderly.
