| Title: | Investigating genetic, environmental, and clinical determinants and their interactions on non-communicable diseases risk, and developing prediction and prognosis models for common types |
| Lead Institution: | Zhejiang University |
| Principal investigator: |
Application 724597
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About
Research questions, objectives The proposed study aims to explore risk factors, prevention, prognosis management and prediction for non-communicable diseases (NCDs). (1) To identify key risk factors for NCDs, including genetic predisposition, lifestyle factors, diet, environmental exposures, and medical conditions. (2) To understand the molecular epidemiology of NCDs, focusing on chronic diseases such as digestive system diseases (inflammatory bowel disease, etc), metabolic diseases (polycystic ovary syndrome, etc), cancers (colorectal cancer, gynecological cancers, etc), mental health disorders, cardiovascular diseases, and respiratory conditions. (3) To develop risk prediction and prognosis models using machine learning and statistical tools to integrate data on key risk factors and disease outcomes. (4) To evaluate the effectiveness of prevention and treatment strategies, including lifestyle changes and pharmacological interventions, in reducing the burden of NCDs and improving patient outcomes across diverse populations. Scientific rationale for the research NCDs, including cardiovascular diseases, cancers, chronic respiratory conditions, and metabolic disorders, account for over 71% of global mortality, presenting a major public health challenge. Despite advances in understanding individual risk factors, the multifactorial etiology of NCDs, involving genetic, environmental, lifestyle, and psychosocial factors, remains poorly understood. Current research focuses on isolated risk factors or single diseases, limiting insights into shared mechanisms. Emerging evidence highlights gene-environment interactions, but the molecular pathways linking them to disease progression are unclear. This study aims to integrate genetic, clinical, and environmental data to develop predictive models, assess prevention strategies, and inform population-specific interventions. Ultimately, the research will bridge molecular epidemiology with public health to reduce NCD burden.1 Publication
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 17449 | Residential green space, air pollution, and related metabolites in association with depression among cancer survivors | Jianhui Zhao (+12) | 2026 | Nature Communications |
Enabling scientific discoveries that improve human health