Our research has led to the identification of hundreds of key genetic variants linked to CAD, many of which we successfully associated with causal genes. We found that most of these risk variants operate within specific cell types, and contrary to the current understanding, we identified several risk loci containing more than one functional variant, with the potential to influence the expression of multiple genes simultaneously.
A significant discovery was that while about one-third of the genetic risk factors for CAD are related to traditional risk factors, such as cholesterol metabolism in the liver, the majority function through alternative mechanisms involving the vascular wall—mechanisms that current treatments do not address. By pioneering the use of single-cell chromatin accessibility profiling (scATAC-Seq), we identified that specific cells within blood vessels, particularly smooth muscle cells (SMCs) and endothelial cells (ECs), are heavily impacted by these genetic changes. Our research further revealed twelve distinct disease-associated subtypes within atherosclerotic plaques, with a particular focus on the phenotypic changes in SMCs, which play a substantial role in CAD heritability.
In addition, we conducted a proof-of-concept study that demonstrated how a hybrid polygenic risk score (PRS), integrating this detailed functional genetic information, can significantly improve the accuracy of predicting individuals at high risk for CAD. This innovative approach not only advances our understanding of the genetic mechanisms driving CAD but also paves the way for more personalized and potentially more effective strategies for preventing and treating heart disease.
The results of this project have been extensively disseminated through nearly 30 conferences and multiple social media platforms, significantly enhancing the visibility of our findings within the scientific community and beyond. Additionally, we have expanded our collaboration networks, forming a robust research community focused on understanding the functional impact of each CAD locus and translating these findings into clinical practice. This collaborative effort is crucial in driving forward the application of our research to improve CAD diagnosis, prevention, and treatment on a global scale.
