An Ancestry-Informed Approach to Improve Genetic Testing for Cardiovascular Disease

Baylor College Of Medicine, Houston TX

Investigators

Abstract

Project Summary/Abstract Cardiovascular disease (CVD) is the leading cause of death in the United States, making it a promising disease for genetic testing to predict those at risk and prevent problems before they start. Indeed, genetic testing for CVD is now being implemented in clinic, however its benefits are not evenly shared and non-European ancestry individuals are less likely to receive meaningful information from these tests. This is because many genetic tests are developed using data from European-ancestry individuals, posing a problem when these methods are applied to a broader population. Further, many tools to study human genomes are geared towards European- ancestry data and not optimized for diverse genomes. To overcome these challenges and improve genetic testing for CVD, I propose to study the genetics of CVD across diverse and mixed-ancestry populations using novel and precise tools that evaluate ancestry appropriately. Specifically, I aim to improve genetic testing for CVD and lipoprotein a (Lp(a)), a lipoprotein that is resistant to commonly used CVD medications and can increased someone’s risk for CVD by 2-4X. For Lp(a) in particular, I will evaluate the role of linkage disequilibrium and genetic structure in the key gene regulating this lipoprotein. I take this approach as there is poor predictive transferability of currently used genetic tests to Hispanic individuals that may be explained by different patterns of genetic variation and linkage across ancestries. I will pair these analyses with phenotypic analyses of Lp(a) and CVD through Genome-Wide Association Studies, and the development of a novel polygenic scoring model accounting for both a single locus of large effect with polygenic variation. Doing so will provide me with the critical information needed to improve prevision medicine approaches for CVD and narrow the disparities that are already being seen in clinic. To succeed in my goal to improve genetic testing for CVD and Lp(a), I will be developing skills across disciplines and advocating for the communities most impacted by the disparities that exist in this domain. Through this F31, I aim to strengthen my knowledge of CVD phenotypes, computational techniques, and science advocacy. The fellowship will advance my skills to address existing inequities in precision medicine approaches to CVD and help me further develop my role as an advocate, scientist, and leader in the field of CVD and genetics in the future.