Network-Based Identification and Prioritization of Key Regulators of Coronary Artery Disease Loci

Abstract

Objective Recent 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 Results We 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. Conclusions Our 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.

Applications and Limitations of Mouse Models for Understanding Human Atherosclerosis

“…The extension of genes increases the probability of including false positive genes, but offers a better opportunity to infer biological mechanisms and pathways contributing to CAD (Zhao et al, 2016). …”

“…Three separate studies have modeled CAD pathways based on data of the Coronary Artery Disease Genome-Wide Replication and Meta-Analysis Consortium (CARDIoGRAM) (Ghosh et al, 2015b; Makinen et al, 2014; Zhao et al, 2016). Mäkinen et al utilized a SNP set enrichment analysis (SSEA) that first mapped CARDIoGRAM GWAS to genes based on expression quantitative trait loci (eQTLs), and then assessed the enrichment of CAD signals in tissue-specific co-expression networks and canonical pathways from Biocarta, KEGG and Reactome databases.…”

“…Gosh et al used an alternative gene mapping strategy which was based on chromosomal distance between SNPs and genes and an alternative gene set enrichment analysis to identify 32 significant CAD pathways derived from the Reactome database (Ghosh et al, 2015a). Zhao et al curated different candidate gene lists based on peak GWAS SNPs and implemented gene regulatory networks and expression patterns to identify 93 CAD relevant pathways based on canonical pathways from Biocarta, KEGG, and Reactome (Zhao et al, 2016). When combined, these three studies identified a total of 178 unique human CAD GWAS associated pathways (Table S4).…”

Genetics: Implications for Prevention and Management of Coronary Artery Disease

“…These new resources and techniques have already provided important mechanistic insights for several novel susceptibility loci for CAD, including those regions harboring the genes CDKN2B, SORT1, TCF21, ADAMTS7, SMAD3, and other loci (165)(166)(167)(168)(169)(170)(171)(172). Although this understanding has not yet been translated to therapeutic agents targeting these loci, the rapid path of translation for other susceptibility loci, such as PCSCK9, provides some reassurance that such developments are forthcoming and are likely to provide us with groundbreaking opportunities to further reduce, and possibility eliminate, the threat of CAD in the 21 st century.…”

The Brain–Skin Connection and the Pathogenesis of Psoriasis: A Review with a Focus on the Serotonergic System

“…The results that have been reported include in vitro assays, ex vivo assays, in vivo assays using animal models, in vivo assays in humans, clinical trials, cell biology, molecular biology and, more recently, genome-wide assays at the level of transcriptomics [131], proteomics [132], metabolomics [133], as well as their multi-omics integration and in silico predictions via modeling approaches [134]. This systems biology approach has been applied to help unravel the pathological mechanisms in human diseases, such as Alzheimer's [135], coronary artery disease [136], cardiovascular disease, type 2 diabetes [137] and cancer [138], among others. We believe that a similar approach will prove extremely useful to better understand the pathogenesis of psoriasis, making it easier to find new therapeutic strategies for this disease.…”