| Title: | Development of the predictive risk models for cardiovascular diseases using a multimodality approach |
| Lead Institution: | Second Hospital of Tianjin Medical University |
| Principal investigator: | Professor Gary Tse |
Application 79146
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About
The aim of our research is to improve predictive risk models for cardiovascular diseases by investigating genetic mutations as causes or drivers of heart diseases and mining data from different clinical and imaging tests to improve accurate risk predictions. We want to determine from our research the genetic and environmental factors that better allow us to understand risk factors associated with cardiovascular mortality and progression. On this end, we can better provide informative preventative strategies in cardiovascular outcomes on an individual and community level. Our research group has been extensively involved in cardiovascular health and understanding its association with co-morbidities such as metabolic syndrome. We believe that the genetic factors can attribute to cardiovascular death independent from environmental factors, with certain individuals at higher predispositions to adverse outcomes. By understanding the genetics of cardiology, better predictive risk models can improve overall health and add to the body of literature that guides clinical decision making in practices. We propose to use a special type of study method, Mendelian randomization, to investigate whether a risk factor causes cardiovascular disease. We also want to investigate whether a holistic approach of including different test results can enable doctors to make better predictions. The rationale is that there are many risk factors and risk markers, and that the more investigation findings we use, the more accurate predictions can be. For example, an electrical recording of the heart can reveal problems of aging-related changes in the heart's electrical system, whereas an ultrasound scan of the heart can tell us about how strongly a heart pumps, together with blood test results and genetic factors, we believe including all of these findings can improve our predictive models. We expect our project to take 36 months. The results of this project will be of benefit for the wider community and improve risk stratification on a case-by-case basis. Our team has previously developed a model for predicting severe disease in COVID-19. This was later adapted into a risk score calculator and made available on QxMD. It is our intention to make our risk models freely available for use by the medical and wider community. We hope to improve and expand on the body of literature that underpins cardiovascular outcomes from genetic and environmental factors that guide treatment for individuals and the wider community.1 Publication
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 13620 | Circulating ketone bodies, genetic susceptibility, with left atrial structure, function and atrial fibrillation: A prospective study from UK Biobank | Nan Zhang (+7) | 2024 | Heart Rhythm |
Enabling scientific discoveries that improve human health