| Title: | Pathway analysis and Prediction of Cardiovascular Disease |
| Lead Institution: | Capital Medical University |
| Principal investigator: |
Application 446734
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About
Cardiovascular diseases, such as calcified aortic valve disease (CAVD) and familial hypercholesterolemia (FH), are still not fully diagnosed and treated. We aim to evaluate the performance of these indexes in cardiovascular risk prediction. At present, we have established some cohorts of related studies, and combined with other cohorts for verification. It's very important to early diagnosis calcific aortic valve disease (CAVD), familial hypercholesterolemia(FH), and other cardiovascular diseases, in population is key to disease prevention and control. Many studies have reported that Mendelian disorders and polygenic traits that have a large effect on the propensity for developing a certain disease or characteristic. However, the practical applications of polygenic risk information for screening or for guiding lifestyle and medical interventions in the clinical setting remain further analysis. We will use plink and R to analyze the data to obtain the polygenic risk score associated with our population, and verify it in the UK Biobank population. At the same time, we will combine the transcriptome data, protein data, etc. in our organization to build the model and verify the model in UKbiobank. Genotype and genome information for the Whole cohort and corresponding clinical information(clinical outcome and diseases). We hope that the investigation of genetic characteristics that can predict the cardiovascular risk determined by our method will help understand the biological basis of the corresponding disease and provide an improved method for risk stratification, thereby providing a basis for the best treatment. At the same time, genomics is combined with other different omics to improve the effectiveness of the model.1 Publication
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 21078 | Proteomics assisted improvement prediction of risk for adverse cardiovascular events in individuals with metabolic syndrome | Yanlin Chen (+7) | 2026 | BMC Cardiovascular Disorders |
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