Geriatric diseases such as aging, frailty, Alzheimer’s disease and sarcopenia are rapidly becoming major risk factors for cardiovascular disease (CVDs). However, the mechanisms connecting geriatric diseases and CVDs are not fully understood, with most research being limited to observational studies. This study aims to utilize the UK Biobank’s extensive dataset, which includes genetic, clinical, proteomic, and metabolomic data, to explore the complex relationships between geriatric diseases and CVDs. The primary objectives are to identify novel biomarkers and risk factors for geriatric diseases or cardiovascular diseases, investigate causal relationships between aging, frailty, Alzheimer’s, sarcopenia, and cardiovascular diseases using multi-omics data (such as proteomics, metabolomics, and imaging), and develop predictive models to better identify individuals at high risk for CVDs based on clinical and multi-omics data. Previous studies have established a link between these conditions and cardiovascular disease, but the biological mechanisms behind these links have been unclear. Current studies often focus on isolated clinical, genetic, or imaging data. A more integrated approach is needed to understand these mechanisms. By combining multi-omics techniques, including proteomics and metabolomics, with UK Biobank’s clinical data, this study offers a unique opportunity to uncover new biomarkers and causal pathways, enhancing our understanding of how frailty, Alzheimer’s, and sarcopenia increase cardiovascular disease risk. The proteomic and metabolomic data will provide insights into the complex interactions between genetics, environmental factors, and disease progression. Advanced analytical techniques will help identify previously unknown factors contributing to frailty and cardiovascular diseases. By leveraging the UK Biobank’s database, this research aims to confirm existing associations and discover new therapeutic targets and prevention strategies for the elderly
