| Title: | Exploiting modifiable risk factors and multi-omics mechanisms of common chronic diseases |
| Lead Institution: | Beijing Normal University |
| Principal investigator: |
Application 784650
WARNING: the interactive features of this website use CSS3, which your browser does not support. To use the full features of this website, please update your browser.
About
Research question and scientific rationale: There has been accumulating evidence suggesting a role of common risk factors in chronic diseases. However, these existing studies were either limited by small samples or a cross-sectional design. The availability of over half a million participants in the UK Biobank would provide ample statistical power to achieve accurate estimations of effect sizes and control for multiple confounds. Identifying modifiable risk factors has become a public health priority. This is of particular importance for diseases like depression and dementia, which lack effective treatments and have irreversible progression. The potential biological mechanisms linking these modifiable risk factors with chronic diseases also remain unknown. Neuroimaging measures serve as a cornerstone in both brain disorders and other chronic diseases research, facilitating early disease detection, accurate diagnosis, and in-depth exploration of pathological mechanisms. Moreover, emerging multi-omics measures-metabolome and proteome-also carry dynamic biological signals reflecting homeostatic processes and health status. However, studies regarding whether risk factor-associated metabolic/proteomic/neuroimaging signatures mediate the increased risk of chronic diseases are scarce. Understanding the molecular mechanism holds promise in informing potential prevention strategies. Objectives: 1) investigate the longitudinal association between multiple risk factors and some common chronic diseases, especially depression, 2) investigate the neurobiological and molecular basis. We will disseminate findings via peer-reviewed publications, conference presentations, and engagement with clinical societies. Analytic code and summary data will be shared openly, and results will be communicated through press releases and lay summaries to reach both scientific and public audiences.1 Publication
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 20054 | The metabolomic signatures mediate associations between physical frailty and metabolic dysfunction-associated steatotic liver disease | Rongtao Jiang (+8) | 2026 | Science Advances |
Enabling scientific discoveries that improve human health