| Title: | Environmental factors, genetic information, and gene-environment interactions in the occurrence, progression, and prognosis of obesity-related diseases |
| Lead Institution: | Beijing Chao-Yang Hospital, Capital Medical University. |
| Principal investigator: |
Application 425612
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About
Obesity has been a global public health problem. Obesity is clearly linked to high blood pressure, diabetes, coronary heart disease, metabolic syndrome and other diseases, seriously affecting public health and placing a huge burden on society and economy. Genetic factors, environmental factors and gene-environment interaction play an important role in the occurrence and development of obesity-related diseases. There are many publications based on single risk factor. However, these resluts are inconsistent. Although genetic factors can affect the occurrence of obesity-related diseases, acquired environmental factors can also have a certain impact on the occurrence and development of diseases. Data on gene-environment interactions can provide new insights into the prediction and intervention of obesity-related diseases. However, there is a lack of research in this area. Previously, our research group conducted a series of studies on the relationship between environmental factors and diabetes and coronary heart disease based on clinical cohorts lacking genetic information. The UK Biobank's ample sample size and its extensive information on diet, lifestyle and genetics allow us to explore gene-environment interactions and the role of different risk factors in obesity-related diseases. Therefore we aim to use UK Biobank data to explore the role of gene-environment interactions in obesity-related diseases and to develop risk prediction models for obesity-related diseases. According to our expectations, the project will last 36 months. The research will ultimately help improve the prevention, diagnosis and treatment of obesity-related diseases, which is of great significance for public health.2 Publications
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 19023 | Data-driven cluster analysis identifies distinct types of cardiovascular-kidney-metabolic syndrome | Mengge Yang (+4) | 2025 | European Journal of Preventive Cardiology |
| 18914 | Long-term body mass index variability and the risk of cardiometabolic multimorbidity in middle-aged and older adults: Insights from two prospective cohorts | Xiaoying Ren (+5) | 2025 | International Journal of Cardiology Cardiovascular Risk and Prevention |
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