| Title: | Comprehensive identification of risk factors and biomarkers for musculoskeletal disorders (osteoporosis, osteoarthritis, and rheumatoid arthritis) |
| Lead Institution: | Shanghai University of Traditional Chinese Medicine |
| Principal investigator: |
Application 108866
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About
Stating the aims: This project aims to (1) investigate the relationship between genetics, behavior, diet structure, lifestyle, cognition, environmental factors, biomarkers and musculoskeletal diseases (osteoporosis, osteoarthritis, rheumatoid arthritis, etc.); (2) further identify potential pathways between various exposures and musculoskeletal diseases such as osteoporosis, osteoarthritis, and rheumatoid arthritis; (3) use genetic information, multi-omics sequencing, and anthropometry to predict the occurrence and progression of musculoskeletal-related diseases; (4) explore the internal biological mechanism of the interaction between common chronic diseases (hypertension, diabetes, psychiatric disorders, etc.) and musculoskeletal diseases. Method: Strict statistical analysis methods (Cox proportional hazard model, Logistics regression model, machine learning algorithm, etc.) will be used to identify valuable genetic, lifestyle and other factors. According to the results of multi-group sequencing, the potential targets and biomarkers of musculoskeletal diseases were explored, the targeted intervention measures were clarified, and the potential mechanism was further clarified. Project duration: The duration of this project is approximately 3 years. Scientific rationale: It is well known that musculoskeletal disorders are influenced by a combination of genetic factors, lifestyle, environmental factors and chronic co-morbidities. However, exposure affects different groups differently, depending on factors such as age, sex, or genetics. Based on genetic and acquired factors, early identification of high-risk individuals and accurate prevention and treatment of bone diseases are of great significance. Public health impact: A comprehensive understanding of risk factors for skeletal diseases will help identify high-risk groups, intervene early, effectively reduce the harm of skeletal diseases, reduce social and personal costs, and improve the quality of life of individuals.1 Publication
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 20943 | Graves' disease and bone mineral density: a meta-analysis and UK Biobank | Mengchu Wu (+17) | 2026 | Frontiers in Endocrinology |
Enabling scientific discoveries that improve human health