# Cell type-specific epigenetic regulatory circuitry of coronary artery disease loci

## TL;DR

This study identifies genes linked to coronary artery disease by combining genetic data with cell-specific epigenetic information, highlighting the role of non-coding RNA genes.

## Contribution

The study introduces a novel approach to prioritize candidate genes for coronary artery disease using cell type-specific epigenetic data and validates a non-coding RNA gene.

## Key findings

- 1580 candidate disease genes were identified, with 23.5% being non-coding RNA genes.
- The non-coding RNA gene IQCH-AS1 was biologically validated as a candidate gene for coronary artery disease.
- Candidate genes were linked to disease-specific pathways and risk factors through enrichment and association analyses.

## Abstract

Coronary artery disease is the leading cause of death worldwide. Recently, hundreds of genomic loci have been shown to increase risk for the disease, however, the molecular mechanisms underlying signals from risk loci remain largely unclear. Here, we integrate the latest statistics of coronary artery disease genetics from over one million individuals with epigenetic data from 45 cell types to identify genes and transcription factors whose regulation is affected by variants. Applying two statistical approaches, we identify 1580 candidate disease genes, including 23.5% non-coding RNA genes. Enrichment analysis and phenome-wide association studies link the candidate genes to disease-specific pathways and risk factors. We conduct a proof-of-concept biological validation for the non-coding RNA gene IQCH-AS1 via knockout in a human preadipocyte strain. Our study not only pinpoints CAD candidate genes in a cell type-specific manner but also highlights the roles of an understudied ncRNA gene in CAD genetics.

Many genetic loci that are associated with coronary artery disease lack understanding of how they contribute to the disease. Here, the authors combine summary genetic statistics with cell type-specific data of regulatory elements to prioritize candidate disease genes, including non-coding RNA genes.