The Integrated Landscape of Biological Candidate Causal Genes in Coronary Artery Disease

Abstract

Background: Genome-wide association studies (GWASs) have identified more than 150 genetic loci that demonstrate robust association with coronary artery disease (CAD). In contrast to the success of GWAS, the translation from statistical signals to biological mechanism and exploration of causal genes for drug development remain difficult, owing to the complexity of gene regulatory and linkage disequilibrium patterns. We aim to prioritize the plausible causal genes for CAD at a genome-wide level.Methods: We integrated the latest GWAS summary statistics with other omics data from different layers and utilized eight different computational methods to predict CAD potential causal genes. The prioritized candidate genes were further characterized by pathway enrichment analysis, tissue-specific expression analysis, and pathway crosstalk analysis.Results: Our analysis identified 55 high-confidence causal genes for CAD, among which 15 genes (LPL, COL4A2, PLG, CDKN2B, COL4A1, FES, FLT1, FN1, IL6R, LPA, PCSK9, PSRC1, SMAD3, SWAP70, and VAMP8) ranked the highest priority because of consistent evidence from different data-driven approaches. GO analysis showed that these plausible causal genes were enriched in lipid metabolic and extracellular regions. Tissue-specific enrichment analysis revealed that these genes were significantly overexpressed in adipose and liver tissues. Further, KEGG and crosstalk analysis also revealed several key pathways involved in the pathogenesis of CAD. Conclusion:Our study delineated the landscape of CAD potential causal genes and highlighted several biological processes involved in CAD pathogenesis. Further studies and experimental validations of these genes may shed light on mechanistic insights into CAD development and provide potential drug targets for future therapeutics. HIGHLIGHTS-Conducted an integrative analysis to prioritize the CAD potential causal genes by using eight computational methods. -Identified 55 high-confidence causal genes for CAD, among which 15 genes ranked the highest priority. -Plausible causal genes were enriched in lipid metabolic and extracellular region.

A Workflow for Selection of Single Nucleotide Polymorphic Markers for Studying of Genetics of Ischemic Stroke Outcomes

“…Like other studies pointed to establish genomic landscape of complex traits, our approach is also based on exploration of data of different types (mRNA transcription, population genetic variations, eQTLs) [33,34]. However, it does not rely on GWAS data which are known to be not good in identifying real causative variants and genes as well [35] and thus it is initially more confident.…”

Altered function and differentiation of age-associated B cells contribute to the female bias in lupus mice

“…The CORO1A-DEF6 blood transcription module correlates with responses to flu vaccination and malaria 25 , 26 . Furthermore, SWAP70 is a susceptibility locus for RA 27 and CVD 28 while DEF6 is a risk factor for human SLE 29 , 30 . Mutations in DEF6 moreover result in early-onset autoimmune manifestations, often associated with viral infections, which include autoantibody production and upregulation of an ISG signature 31 , 32 .…”

Examination of Genetic Variants Revealed from a Rat Model of Brain Ischemia in Patients with Ischemic Stroke: A Pilot Study

“…Ultimately, this deficiency highlights the need for the development of new approaches that can delineate causal genetic variants and biological mechanisms underlying the associations observed with IS. They can be realized in enhanced downstream characterization of identified loci through the involvement of different ‘omics’ data and advanced analytic techniques, or in direct functional dissection of particular variants and genes [ 8 , 9 , 10 ].…”