Polygenic Risk of Disease in Populations of Diverse Ancestry

Mayo Clinic Rochester, Rochester MN

Investigators

Linked publications, trials & patents

Abstract

PROJECT SUMMARY In this application we propose to build on our prior work on polygenic risk scores (PRSs) to extend these to be applicable to all individuals. By improving risk stratification, PRSs for common diseases have the potential to transform clinical practice. However, such PRSs must be available for all individuals to ensure implementation of genomic medicine. Our application aims to address the critical need to develop PRSs for all individuals and will focus on coronary heart disease (CHD) and its risk factors: hypertension, diabetes, obesity and hypercholesterolemia, collectively an enormous health burden world-wide. CHD is the prototypical complex disease for the use of PRSs given available validated risk prediction equations that bin individuals into risk categories and substantial reclassification across these categories by a PRS with consequent therapeutic implications. We will develop methods to generate PRSs for ancestry using existing and new datasets with genomic and phenotype data for CHD and its risk factors. We will harmonize data elements across these data sets. The methods we develop will be applicable towards the generation of PRSs for a broad range of common diseases. The investigative team is part of the Mayo eMERGE IV application and will serve as a bridge to this effort. To generate PRSs, we will use data from the eMERGE consortium, Million Veteran’s Program (MVP), the All of US (AoU) program, dbGAP, , UK Biobank, and collaborations with several international groups representing the Middle Eastern, South Asian and East Asian cohorts. Our application includes several innovations to enable the use of PRSs for risk stratification and prevention of CHD in individuals. Our specific aims are: Specific aim 1. Integrate and harmonize phenotype data from heterogeneous sources to enable cross platform phenotyping and generation of PRSs for common diseases. Specific aim 2. Develop PRSs for CHD and its major risk factors (hypertension, diabetes, obesity, hypercholesterolemia) in populations that represent all individuals. Specific aim 3. Develop novel statistical and computational methods to account for heterogenous data for models of polygenic risk. Specific aim 4. Develop ‘clinic ready’ PRSs by creating reference distributions of a PRS for CHD and integrate it with clinical information to compute absolute risk estimates.