| Title: | Predicting risk and understanding mechanisms of cardiovascular disease with high-dimensional multiomics, hemodynamic and imaging data |
| Lead Institution: | Klinikum der Universität München |
| Principal investigator: |
Application 151281
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About
Aims: We aim to use high-dimensional data from the UKB including multiomics and imaging in order to Develop biomarkers of established cardiovascular pathologies, detect prediction signatures of future cardiovascular events, and discover disease-causing mechanisms with high potential of therapeutic targeting Scientific rationale: Every year more than 19 million people worldwide lose their lives to cardiovascular diseases like heart attacks and strokes. To tackle this growing health crisis, we need new prevention strategies. Our research uses advanced technology to analyze large-scale data in order better understand the unique biological factors and early signs of cardiovascular diseases, offering hope for more accurate risk assessments and innovative treatments to reduce their burden. Project duration: 3 years Public health impact: By using advanced technology that combines different kinds of healthcare data, including genetics, blood assessments and imaging techniques, and applying artificial intelligence methods, we hope to create better ways of predicting cardiovascular diseases and finding new clues that can help us treat them. This could make our approach for treating cardiovascular diseases more accurate and personalized and could help us live longer with a lower burden of heart disease and stroke.1 Publication
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 16252 | A Beneficial Role for Gluteofemoral Adipose Tissue in Cerebrovascular Disease | Evangelos Pavlos Myserlis (+7) | 2025 | Neurology |
Enabling scientific discoveries that improve human health