The interaction of several genetic and traditional (non-genetic) factors modulates the clinical occurrence of the common cardiovascular diseases (CVDs), such as coronary artery disease (CAD), atrial fibrillation, heart failure and cerebrovascular disease. Substantial efforts have been made to treat these CVDs and manage their complications, but the underlying pathophysiology still deserve more attention.
In our study, we aim to utilize the individual-level data to combining the genetic and non-genetic risk for CVDs to establish new strategies for detection and prevention.
We believe that our data can be of high public health importance, since CVDs are the most common causes of death and disability in the world. Moreover, our study gives important indication regarding the weight of both genetic and non-genetic factors to promote the accuracy of identification of CVDs.
We estimate that we will complete the majority of data analysis and finish the publication of the relevant results in 36 months.
