Currently, various age-related diseases, such as malignant tumors and their treatment-related adverse reactions, metabolic diseases, cardiovascular diseases, respiratory diseases, and autoimmune diseases, severely impact human health and social development. There exist complex comorbidity associations and molecular crosstalk mechanisms among these diseases. Despite the extensive research conducted so far, core issues including the etiological heterogeneity, pathophysiological regulatory networks, disease progression trajectories, and differences in treatment responses of most diseases remain unclear, leading to delays in the development of personalized diagnosis, treatment, and early intervention strategies.
Our project aims to leverage the multi-modal big data from the UK Biobank , including multi-omics, imaging, phenotypic, clinical diagnosis and treatment, lifestyle, environmental exposure, and follow-up outcome data. By integrating a variety of analytical methods, we will systematically decipher the complex biological mechanisms of multiple age-related diseases, identify specific biomarkers and potential therapeutic targets associated with disease susceptibility, progression, prognosis, and treatment response, and construct predictive models. This work will provide a scientific basis for early disease screening, precise classification, personalized intervention, and improved prognosis.
