Related Experiment Video
Updated: Oct 8, 2025
Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation
Published on: January 16, 2019
Integrative Prioritization of Causal Genes for Coronary Artery Disease
Ke Hao1,2, Raili Ermel3, Katyayani Sukhavasi3
1Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, NY (K.H., H.C., L.M., L.A., J.L.M.B.).
Background:
Hundreds of candidate genes have been associated with coronary artery disease (CAD) through genome-wide association studies. However, a systematic way to understand the causal mechanism(s) of these genes, and a means to prioritize them for further study, has been lacking. This represents a major roadblock for developing novel disease- and gene-specific therapies for patients with CAD. Recently, powerful integrative genomics analyses pipelines have emerged to identify and prioritize candidate causal genes by integrating tissue/cell-specific gene expression data with genome-wide association study data sets.
Methods:
We aimed to develop a comprehensive integrative genomics analyses pipeline for CAD and to provide a prioritized list of causal CAD genes. To this end, we leveraged several complimentary informatics approaches to integrate summary statistics from CAD genome-wide association studies (from UK Biobank and CARDIoGRAMplusC4D) with transcriptomic and expression quantitative trait loci data from 9 cardiometabolic tissue/cell types in the STARNET study (Stockholm-Tartu Atherosclerosis Reverse Network Engineering Task).
Results:
We identified 162 unique candidate causal CAD genes, which exerted their effect from between one and up to 7 disease-relevant tissues/cell types, including the arterial wall, blood, liver, skeletal muscle, adipose, foam cells, and macrophages. When their causal effect was ranked, the top candidate causal CAD genes were CDKN2B (associated with the 9p21.3 risk locus) and PHACTR1; both exerting their causal effect in the arterial wall. A majority of candidate causal genes were represented in cross-tissue gene regulatory co-expression networks that are involved with CAD, with 22/162 being key drivers in those networks.
Conclusions:
We identified and prioritized candidate causal CAD genes, also localizing their tissue(s) of causal effect. These results should serve as a resource and facilitate targeted studies to identify the functional impact of top causal CAD genes.
Insights
Researchers identified 162 candidate causal genes for coronary artery disease (CAD) by integrating genome-wide association studies with gene expression data. Top genes like CDKN2B and PHACTR1 show effects in the arterial wall, aiding targeted therapy development.
Area of Science:
- Genomics
- Cardiovascular Research
- Systems Biology
Background:
- Genome-wide association studies (GWAS) have identified numerous coronary artery disease (CAD) candidate genes.
- A lack of systematic methods hinders understanding causal mechanisms and prioritizing genes for CAD therapies.
- Integrative genomics pipelines offer a powerful approach to identify and prioritize causal genes by combining GWAS with gene expression data.
Purpose of the Study:
- To develop a comprehensive integrative genomics pipeline for CAD.
- To identify and prioritize causal genes for coronary artery disease.
- To localize the tissue-specific effects of these causal genes.
Main Methods:
- Integrated GWAS summary statistics (UK Biobank, CARDIoGRAMplusC4D) with transcriptomic and expression quantitative trait loci (eQTL) data.
- Utilized data from the STARNET study across 9 cardiometabolic tissue/cell types.
- Employed complementary informatics approaches for comprehensive analysis.
Main Results:
- Identified 162 unique candidate causal genes for CAD.
- These genes exert effects in 1–7 disease-relevant tissues, including arterial wall, blood, liver, and immune cells.
- Top prioritized genes include CDKN2B and PHACTR1, primarily acting in the arterial wall; 22 genes were key drivers in CAD-associated networks.
Conclusions:
- Successfully identified and prioritized candidate causal CAD genes.
- Localized the tissue(s) of causal effect for these genes.
- Provides a valuable resource to facilitate targeted studies on the functional impact of top CAD genes.
More Related Videos
08:51Author Spotlight: Integrated Multi-Omics Analysis for Unveiling Multicellular Immune Signatures in Clinical Heart Attack Cohorts
Published on: September 20, 2024
06:16Signal Acquisition, Score Interpretation, and Economics of a Non-Invasive Point-of-Care Test for Coronary Artery Disease
Published on: August 9, 2024
Related Concept Videos
01:30Coronary Artery Disease I: Introduction
01:26Coronary Artery Disease II: Pathophysiology
01:26Coronary Artery Disease IV: Preventive Measures
01:27Coronary Artery Disease V: Interprofessional Care
01:30Acute Coronary Syndrome III: Diagnostic Studies
01:33Pleiotropy