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Prioritization of causal genes for coronary artery disease based on cumulative evidence from experimental and in silico studies.

ABSTRACT: Genome-wide association studies have led to a significant progress in identification of genomic loci affecting coronary artery disease (CAD) risk. However, revealing the causal genes responsible for the observed associations is challenging. In the present study, we aimed to prioritize CAD-relevant genes based on cumulative evidence from the published studies and our own study of colocalization between eQTLs and loci associated with CAD using SMR/HEIDI approach. Prior knowledge of candidate genes was extracted from both experimental and in silico studies, employing different prioritization algorithms. Our review systematized information for a total of 51 CAD-associated loci. We pinpointed 37 genes in 36 loci. For 27 genes we infer they are causal for CAD, and for 10 further genes we judge them most likely causal. Colocalization analysis showed that for 18 out of these loci, association with CAD can be explained by changes in gene expression in one or more CAD-relevant tissues. Furthermore, for 8 out of 36 loci, existing evidence suggested additional CAD-associated genes. For the remaining 15 loci, we concluded that evidence for gene prioritization remains inconsistent, insufficient, or absent. Our results provide deeper insights into the genetic etiology of CAD and demonstrate knowledge gaps where further research is warranted.

SUBMITTER: Shadrina AS

PROVIDER: S-EPMC7320185 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

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Prioritization of causal genes for coronary artery disease based on cumulative evidence from experimental and in silico studies.

Shadrina Alexandra S AS Shashkova Tatiana I TI Torgasheva Anna A AA Sharapov Sodbo Z SZ Klarić Lucija L Pakhomov Eugene D ED Alexeev Dmitry G DG Wilson James F JF Tsepilov Yakov A YA Joshi Peter K PK Aulchenko Yurii S YS

Scientific reports 20200626 1

Genome-wide association studies have led to a significant progress in identification of genomic loci affecting coronary artery disease (CAD) risk. However, revealing the causal genes responsible for the observed associations is challenging. In the present study, we aimed to prioritize CAD-relevant genes based on cumulative evidence from the published studies and our own study of colocalization between eQTLs and loci associated with CAD using SMR/HEIDI approach. Prior knowledge of candidate genes ...[more]

PMID: 32591598

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Project description:BackgroundHundreds 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.MethodsWe 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).ResultsWe 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.ConclusionsWe 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.

Project description:ObjectiveRecent genome-wide association studies of coronary artery disease (CAD) have revealed 58 genome-wide significant and 148 suggestive genetic loci. However, the molecular mechanisms through which they contribute to CAD and the clinical implications of these findings remain largely unknown. We aim to retrieve gene subnetworks of the 206 CAD loci and identify and prioritize candidate regulators to better understand the biological mechanisms underlying the genetic associations.Approach and resultsWe devised a new integrative genomics approach that incorporated (1) candidate genes from the top CAD loci, (2) the complete genetic association results from the 1000 genomes-based CAD genome-wide association studies from the Coronary Artery Disease Genome Wide Replication and Meta-Analysis Plus the Coronary Artery Disease consortium, (3) tissue-specific gene regulatory networks that depict the potential relationship and interactions between genes, and (4) tissue-specific gene expression patterns between CAD patients and controls. The networks and top-ranked regulators according to these data-driven criteria were further queried against literature, experimental evidence, and drug information to evaluate their disease relevance and potential as drug targets. Our analysis uncovered several potential novel regulators of CAD such as LUM and STAT3, which possess properties suitable as drug targets. We also revealed molecular relations and potential mechanisms through which the top CAD loci operate. Furthermore, we found that multiple CAD-relevant biological processes such as extracellular matrix, inflammatory and immune pathways, complement and coagulation cascades, and lipid metabolism interact in the CAD networks.ConclusionsOur data-driven integrative genomics framework unraveled tissue-specific relations among the candidate genes of the CAD genome-wide association studies loci and prioritized novel network regulatory genes orchestrating biological processes relevant to CAD.

Dataset Information

Prioritization of causal genes for coronary artery disease based on cumulative evidence from experimental and in silico studies.

Publications

Prioritization of causal genes for coronary artery disease based on cumulative evidence from experimental and in silico studies.

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