This study aims to investigate the associations between lifestyle, genetic, environmental, and other factors with the onset, progression, and prognosis of musculoskeletal diseases. Although previous research has identified some risk factors, how these factors collectively influence disease onset, progression, and prognosis remains unclear. This study will utilize multidimensional data from the UK Biobank (including lifestyle, genetic information, environmental data, clinical records, Imaging and etc.) and employ methods such as multivariate regression, machine learning, and interaction analysis to uncover key risk and protective factors, as well as to construct disease progression and prognosis prediction models. The research objectives include: (1) elucidating the mechanisms by which genetic, lifestyle, and environmental factors influence disease; (2) identifying novel biomarkers to provide a basis for early diagnosis; and (3) developing precision prediction tools to improve patient outcomes and quality of life. The findings will provide a scientific foundation for early intervention, personalized treatment, and public health policy formulation for musculoskeletal diseases.
