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. Coronary artery disease (CAD) is the most prevalent cardiovascular disease, the major cause of mortality and morbidity in both developed and developing countries 1. This pathology is the manifestation of atherosclerosis in the coronary arteries. CAD can lead to a variety of complications, including chest pain, myocardial infarction (MI), arrhythmias and heart failure 2. The etiology of CAD is multifactorial and involves a genetic predisposition as well as dietary and other lifestyle risk factors 3. The genetic component to CAD has long been recognized. The Framingham Study demonstrated that positive family history is a strong risk factor for incident CAD 4-6. According to Swedish and Danish twin studies, the narrow-sense heritability of fatal CAD is about 40-60% 7,8. Today, it is widely accepted that much of the genetic component arises from the effect of many common alleles associated with modest increases in CAD risk 3,9. Genome-wide association studies demonstrated that the common variation accounts for 40-50% of heritability of MI/CAD 10,11. Genetic studies of CAD started from family-based linkage studies discovering monogenic drivers of CAD and small candidate-gene studies which often provided controversial results. Development of high-throughput genotyping technologies and new statistical methods opened the era of genome-wide association studies (GWAS) 12,13. MI was among the very first traits studied with use of genome-wide association strategy already in 2002 14 .

Intersecting single-cell transcriptomics and genome-wide association studies identifies crucial cell populations and candidate genes for atherosclerosis

“…Colocalization of tissue-specific eQTLs 10,32,33 with GWAS data provides another alternative that can be used to estimate if there are overlapping causal variants in both datasets. For example.…”

Mapping gene and gene pathways associated with coronary artery disease: a CARDIoGRAM exome and multi-ancestry UK biobank analysis

“…VEGAS2 GBA in CGEX identified multiple enriched genes (KIAA1462/JCAD, LIPA, FAM177B, PCSK9, ARHGEF26, ZC3HC1, LPL, FBF1) that met our significance threshold (p ≤ 3 × 10 –6 ) and further confirmed them in PUBB (Table 1 ). Many genes have been previously reported to be associated with CAD by a different GBA methods (Table 1 and Supplement 1, VII ) 23 , 24 . In addition, we further identified nine significant genes in PUBB (ADAMTS7, APOE, LPA, SH2B3, HNF1A, CELSR2, MYBPHL, ANGPTL4, EHBP1L1) that have been previously reported to be associated CAD by GBA (Table 1 ) 6 , 23 , 24 .…”

“…Many genes have been previously reported to be associated with CAD by a different GBA methods (Table 1 and Supplement 1, VII ) 23 , 24 . In addition, we further identified nine significant genes in PUBB (ADAMTS7, APOE, LPA, SH2B3, HNF1A, CELSR2, MYBPHL, ANGPTL4, EHBP1L1) that have been previously reported to be associated CAD by GBA (Table 1 ) 6 , 23 , 24 . The Manhattan plots (Fig.…”

The GWAS-MAP platform for aggregation of results of genome-wide association studies and the GWAS-MAP|homo database of 70 billion genetic associations of human traits

“…Se veral instruments implement these methods, for example, the SMR (Summary-level Mendelian Randomization) tool (Zhu et al, 2016). The same methods can often be used to study pleiotropic effects (Klarić et al, 2020;Shadrina et al, 2020). The results of studies of pleiotropy can be used for drug repositioning, for predicting…”