| Title: | Integrative Phenotypic and Multi-Omics Analysis of Life-Course Risk Factors for Chronic Diseases |
| Lead Institution: | Nanjing University |
| Principal investigator: |
Application 347405
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About
This proposed research project aims to utilize the multidimensional data from the UK Biobank to advance our understanding of biomarkers, interactions of multiple risk factors with chronic diseases, and disease-disease interactions within the context of various diseases. The project is designed in response to the substantial global burden posed by chronic diseases such as cancer, cardiovascular diseases, chronic respiratory diseases, and mental and neurological disorders. Integrating phenotypic and comprehensive multi-omics data analysis as a cutting-edge tool can help researchers decipher the complex network mechanisms underlying disease occurrence. However, most biomarkers and potential risk factors identified for chronic diseases have relied on traditional statistical methods using unidimensional data, which do not fully leverage omics data. Additionally, the impact of interactions between various factors on the development of chronic diseases remains underexplored. To address these gaps, we will employ advanced artificial intelligence technologies to integrate phenotypic and multi-omics data for an in-depth analysis of chronic diseases and their influencing factors. We plan to use the entire dataset of the UK Biobank over three years. This comprehensive analysis will elucidate the mechanisms and interactions underlying chronic diseases and clarify the relationships between risk factors and diseases, thereby identifying new therapeutic targets and preventive measures. Furthermore, this research will drive the development and application of multi-omics data integration methods, providing effective tools and approaches for future biomedical research.1 Publication
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 17960 | Metabolomic Atlas of Cardiovascular Diseases Mapping Shared and Specific Signatures | Jingjing Yang (+8) | 2026 | JACC Advances |
Enabling scientific discoveries that improve human health