# Robust pleiotropy-decomposed polygenic scores identify distinct contributions to elevated coronary artery disease polygenic risk

## TL;DR

This study breaks down coronary artery disease genetic risk into nine subgroups, revealing distinct genetic and clinical features for better understanding and treatment.

## Contribution

A novel framework to decompose CAD PRS into nine pleiotropy-based subgroups using genome-wide variants.

## Key findings

- Each PD-PRS explained more of the global CAD-PRS within its subgroup than in others.
- Lipids-related subgroup showed significantly higher lipoprotein(a) and LDL-cholesterol levels.
- Interactions between PD-PRSs and lifestyle factors like smoking suggest potential clinical applications.

## Abstract

Polygenic risk score (PRS) have proved to offer robust risk prediction for coronary artery disease (CAD). However, the global CAD PRS summarizes the joint effects of all the markers in the genome, masking potential genetic heterogeneity that may be important for disease interpretation and targeted interventions.

Using summary-level data, we identified 43 significant CAD-related traits based on genetic correlations, and further classified them into eight pleiotropy clusters based on their biological functions. We then partitioned the genome into 2,353 near-independent regions. Variants in each region were assigned to the trait most genetically similar to CAD, and then were labeled with the corresponding pleiotropy cluster. We grouped variants without labels into a ninth, non-specific cluster. The Pleiotropy Decomposed (PD) PRSs for each of the nine clusters were calculated using variants assigned to each cluster for 407,903 samples of European ancestry from the UK Biobank (UKBB).

We decomposed the CAD PRS into nine PD-PRSs and further stratified individuals with high CAD-PRS into nine subgroups. Each PD-PRS accounted for a higher proportion of the global CAD-PRS within its corresponding subgroup than in the remaining subjects with high CAD-PRS (e.g., 25.2% (0.07) vs. 10.06% (0.07) for lipids-PD-PRS). Additionally, these subgroups showed distinct clinical features. For example, in the lipids-related subgroup, lipoprotein(a) and LDL-cholesterol levels were 67.5% and 18.3% higher, respectively, compared to the remaining high-risk individuals. Furthermore, significant interactions were observed between blood pressure and BP PD-PRS, and between current smoking and respiratory system PD-PRS.

Our findings suggest that PD-PRSs may reveal substantial genetic and phenotypic heterogeneity among individuals with high CAD-PRS. The unique PD-PRS compositions of each individual can highlight the relative importance of different pleiotropic regions.

Aggregating genetic variants into a polygenic risk score (PRS) can predict an individual’s risk for complex diseases such as coronary artery disease (CAD). However, people with high PRS for CAD show different symptoms and clinical outcomes. Understanding disease heterogeneity can help us better understand the genetic etiology of CAD and improve prevention and treatment. The existing methods to decompose CAD PRS into pathway-specific PRSs mainly consider a limited number of SNPs, limiting the overall utility of decompositions. In this study, we propose a framework to assign genome-wide genetic variants to eight relevant clusters and one non-specific cluster based on pleiotropy, where one variant is associated with two or more traits/disease. As a result, we decompose the overall CAD PRS into nine pleiotropy-decomposed PRSs (PD-PRSs) and use them to classify individuals with high CAD PRS into nine subgroups, which show both genetic and phenotypic heterogeneity among high-risk individuals. Additionally, interactions between current smoking and respiratory system-related subgroup indicate potential application of our PD-PRSs in offering clinical advice.