Research objective: To investigate the influence of genetic, lifestyle, environmental and metabolic factors on metabolic diseases and their clinical outcomes
Research scientific rationale: Metabolic diseases, such as obesity, diabetes, coronary heart disease, hypertension, hyperlipidemia, fatty liver related to metabolic dysfunction, cardiovascular-kidney-metabolic diseases, etc., pose a huge threat to health. Metabolic diseases and the multi-system complications they cause are a major health burden worldwide. Their causes involve complex interactions among genetics, environment, lifestyle and metabolic processes within the body. Therefore, we plan to utilize the prospective cohort data from the UK Biobank, integrate multi-omics data with clinical information, and employ a series of analytical methods, including but not limited to: multivariate Cox regression, machine learning, path analysis, structural equation models, and Mendelian randomization, to handle high-dimensional data and infer causal relationships. The system explores the etiology, early diagnosis, disease progression and prognosis of metabolic diseases, aiming to provide a scientific basis for precise prevention and clinical practice, and ultimately offer feasible risk prediction tools and intervention targets for precise public health and individualized medicine.
We plan to explore the following issues: 1. How do genetic, lifestyle, environmental and metabolic factors independently or in combination affect the risk of metabolic diseases and their complications? 2. Can new biomarkers or indices be found to diagnose metabolic diseases? 3. Whether there is a connection between metabolic diseases and other systemic diseases. 4. Whether the gut microbiota and its related metabolites have an impact on metabolic diseases and their complications.
This project is expected to last for 36 months and is anticipated to publish multiple research papers in high-level academic journals.
