The overall aims of the project include: 1) to use the UK Biobank data to systematically study human disease comorbidities, using the phenotypic disease networks (PDN) and traditional epidemiological study design and 2) to use systems biology approaches to study the underlying mechanisms of the identified disease comorbidities, incorporating rich data available in the UK Biobank including sociodemographic data, biomarkers (e.g., omics, imaging, and clinical chemistry), and self-reported questionnaire data. Specifically, we aim to address the following research questions: 1) Which diseases have a greater-than-expected comorbidity? 2) What are the common disease trajectories in the general population and among individuals with specific diseases (e.g., psychiatric disorders, cardiovascular disease, cancer, and neurodegenerative disease)? 3) Do the identified disease comorbidities and trajectories differ among people with different demographics, genetic background, lifestyle, and socioeconomic status? 4) What are the underlying mechanisms for the identified comorbidities and trajectories? This project includes a cohort of 500,000 participants aged between 40 to 69, recruited during 2006 and 2010 across the UK. UK Biobank has comprehensive information and biological samples collected at baseline (recruitment to the cohort) and during follow-up (through multiple follow-up assessments and data linkages), including self-reported questionnaire data and biomarker measurements (omics, clinical chemistry, imaging, etc.), as well as cross-linkages to multiple registers and other data sources including COVID-19 test results, primary care data, hospital inpatient data, death register data and cancer register data concerning different health-related outcomes such as disease diagnoses, surgical procedures, prescriptions, and other clinical events.