| Title: | Identification of Etiologic and Predictive Genetic and Non-genetic factors involved in Risk of Cardiovascular Diseases |
| Lead Institution: | Brunel University London |
| Principal investigator: | Dr Raha Pazoki |
Application 60549
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About
Each year, Cardiovascular diseases cause 17 million deaths around the world. Many of these deaths occur without any previous knowledge of the existing cardiovascular problem. An important way to predict and prevent these deaths is to identify risk factors and predictors that help us identify one's risk of cardiovascular disease years before these events occur. We can then target preventive strategies in these high risk groups and decrease burden of cardiovascular diseases. Here we use data on genetics, biomarkers, lifestyle and metabolic factors using various traditional and novel methods such as machine learning approaches in order to help prediction and prevention of cardiovascular disease.5 Publications
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 14115 | Molecular Alterations Caused by Alcohol Consumption in the UK Biobank: A Mendelian Randomisation Study | Felix O'Farrell (+3) | 2022 | Nutrients |
| 9800 | Physical activity alters the effect of genetic determinants of adiposity on hypertension among individuals of European ancestry in the UKB | Chukwueloka Hezekiah (+3) | 2024 | Scandinavian Journal of Medicine and Science in Sports |
| 14936 | The Association Between Metabolic Syndrome and the Risk of Endometrial Cancer in Pre- and Post-Menopausal Women: A UK Biobank Study | Rebecca Karkia (+5) | 2025 | Journal of Clinical Medicine |
| 14083 | Urinary Sodium Excretion Enhances the Effect of Alcohol on Blood Pressure | Xiyun Jiang (+4) | 2022 | Healthcare |
| 12053 | Using Machine Learning to Evaluate the Value of Genetic Liabilities in the Classification of Hypertension within the UK Biobank | Gideon MacCarthy (+1) | 2024 | Journal of Clinical Medicine |
Enabling scientific discoveries that improve human health