| Title: | Multi-omics investigation of biological determinants, risk prediction and disease burden of cardiovascular disease in a large prospective cohort |
| Lead Institution: | Chinese Academy of Medical Sciences &Peking Union Medical College |
| Principal investigator: |
Application 1312325
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About
This project aims to investigate biological determinants, risk stratification, and disease burden of cardiovascular disease (CVD) using multi-omics data in a large prospective population cohort. Cardiovascular disease remains a leading cause of morbidity and mortality worldwide. Although traditional risk factors such as blood pressure, lipids, and lifestyle factors are well established, substantial residual risk remains unexplained. Advances in large-scale biobanks and multi-omics profiling provide an opportunity to examine cardiovascular disease from an integrated biological perspective. We will examine a wide range of biological measures, including hematological indices, biochemical and lipid biomarkers, inflammatory and metabolic markers, genetic variation, polygenic risk scores, and available proteomic data. In a subcohort, cardiovascular imaging-derived phenotypes will be analysed to explore structural and functional correlates of biological risk profiles. The objectives are: (1) to identify biomarkers and biological profiles associated with incident cardiovascular outcomes; (2) to construct composite biological risk indices integrating multi-layer data; (3) to evaluate their prospective associations with major cardiovascular events; (4) to assess incremental predictive value beyond established clinical risk factors; and (5) to explore potential causal relationships using genetic approaches. Population-level disease burden attributable to adverse biological profiles will also be quantified. This integrated framework will improve understanding of cardiovascular disease mechanisms and may enhance risk prediction and prevention strategies.1 Publication
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 21540 | A multidimensional proteomic framework of circulating inflammation identifies outcome-specific cardiovascular risk axes in 39,494 UK biobank participants | Xiangning Song (+3) | 2026 | Scientific Reports |
Enabling scientific discoveries that improve human health