Statistical and Functional Studies Identify Epistasis of Cardiovascular Risk Genomic Variants From Genome-Wide Association Studies

Genetics of posttraumatic stress disorder and cardiovascular conditions using Life's Essential 8, Electronic Health Records, and Heart Imaging

BACKGROUND

Patients with post-traumatic stress disorder (PTSD) experience higher risk of adverse cardiovascular (CV) outcomes. This study explores shared loci, and genes between PTSD and CV conditions from three major domains: CV diagnoses from electronic health records (CV-EHR), cardiac and aortic imaging, and CV health behaviors defined in Life's Essential 8 (LE8).

METHODS

We used genome-wide association study (GWAS) of PTSD (N=1,222,882), 246 CV diagnoses based on EHR data from Million Veteran Program (MVP; N=458,061), UK Biobank (UKBB; N=420,531), 82 cardiac and aortic imaging traits (N=26,893), and GWAS of traits defined in the LE8 (N = 282,271 ~ 1,320,016). Shared loci between PTSD and CV conditions were identified using local genetic correlations (rg), and colocalization (shared causal variants). Overlapping genes between PTSD and CV conditions were identified from genetically regulated proteome expression in brain and blood tissues, and subsequently tested to identify functional pathways and gene-drug targets. Epidemiological replication of EHR-CV diagnoses was performed in AllofUS cohort (AoU; N=249,906).

RESULTS

Among the 76 PTSD-susceptibility risk loci, 33 loci exhibited local rg with 45 CV-EHR traits (|rg|≥0.4), four loci with eight heart imaging traits(|rg|≥0.5), and 44 loci with LE8 factors (|rg|≥0.36) in MVP. Among significantly correlated loci, we found shared causal variants (colocalization probability > 80%) between PTSD and 17 CV-EHR (in MVP) at 11 loci in MVP, that also replicated in UKBB and/or other cohorts. Of the 17 traits, the observational analysis in the AoU showed PTSD was associated with 13 CV-EHR traits after accounting for socioeconomic factors and depression diagnosis. PTSD colocalized with eight heart imaging traits on 2 loci and with LE8 factors on 31 loci. Leveraging blood and brain proteome expression, we found 33 and 122 genes, respectively, shared between PTSD and CVD. Blood proteome genes were related to neuronal and immune processes, while the brain proteome genes converged on metabolic and calcium-modulating pathways (FDR p <0.05). Drug repurposing analysis highlighted DRD2, NOS1, GFAP, and POR as common targets of psychiatric and CV drugs.

CONCLUSION

PTSD-CV comorbidities exhibit shared risk loci, and genes involved in tissue-specific regulatory mechanisms.

Lysosomal membrane protein TMEM106B modulates hematopoietic stem and progenitor cell proliferation and differentiation by regulating LAMP2A stability

Hematopoietic stem and progenitor cells (HSPCs) are successfully employed for hematological transplantations, and impaired HSPC function causes hematological diseases and aging. HSPCs maintain the lifelong homeostasis of blood and immune cells through continuous self-renewal and maintenance of the multilineage differentiation potential. TMEM106B is a transmembrane protein localized on lysosomal membranes and associated with neurodegenerative and cardiovascular diseases; however, its roles in HSPCs and hematopoiesis are unknown. Here, we established tmem106bb-/- knockout (KO) zebrafish and showed that tmem106bb KO reduced the proliferation of HSPCs during definitive hematopoiesis. The differentiation potential of HSPCs to lymphoid lineage was reduced, whereas the myeloid and erythroid differentiation potentials of HPSCs were increased in tmem106bb-/- zebrafish. Similar results were obtained with morpholino knockdown of tmem106bb. Mechanistically, TMEM106B interacted with LAMP2A, the lysosomal associated membrane protein 2A, impaired LAMP2A-Cathepsin A interaction, and enhanced LAMP2A stability; tmem106bb KO or TMEM106B knockdown caused LAMP2A degradation and impairment of chaperone-mediated autophagy (CMA). Knockdown of lamp2a caused similar phenotypes to that in tmem106bb-/- zebrafish, and overexpression of lamp2a rescued the impaired phenotypes of HSPCs in tmem106bb-/- embryos. These results uncover a novel molecular mechanism for the maintenance of HSPC proliferation and differentiation through stabilizing LAMP2A via TMEM106B-LAMP2A interaction.

Discovering non-additive heritability using additive GWAS summary statistics

LD score regression (LDSC) is a method to estimate narrow-sense heritability from genome-wide association study (GWAS) summary statistics alone, making it a fast and popular approach. In this work, we present interaction-LD score (i-LDSC) regression: an extension of the original LDSC framework that accounts for interactions between genetic variants. By studying a wide range of generative models in simulations, and by re-analyzing 25 well-studied quantitative phenotypes from 349,468 individuals in the UK Biobank and up to 159,095 individuals in BioBank Japan, we show that the inclusion of a cis-interaction score (i.e. interactions between a focal variant and proximal variants) recovers genetic variance that is not captured by LDSC. For each of the 25 traits analyzed in the UK Biobank and BioBank Japan, i-LDSC detects additional variation contributed by genetic interactions. The i-LDSC software and its application to these biobanks represent a step towards resolving further genetic contributions of sources of non-additive genetic effects to complex trait variation.

Epistasis regulates genetic control of cardiac hypertrophy

The combinatorial effect of genetic variants is often assumed to be additive. Although genetic variation can clearly interact non-additively, methods to uncover epistatic relationships remain in their infancy. We develop low-signal signed iterative random forests to elucidate the complex genetic architecture of cardiac hypertrophy. We derive deep learning-based estimates of left ventricular mass from the cardiac MRI scans of 29,661 individuals enrolled in the UK Biobank. We report epistatic genetic variation including variants close to CCDC141 , IGF1R , TTN , and TNKS. Several loci where variants were deemed insignificant in univariate genome-wide association analyses are identified. Functional genomic and integrative enrichment analyses reveal a complex gene regulatory network in which genes mapped from these loci share biological processes and myogenic regulatory factors. Through a network analysis of transcriptomic data from 313 explanted human hearts, we found strong gene co-expression correlations between these statistical epistasis contributors in healthy hearts and a significant connectivity decrease in failing hearts. We assess causality of epistatic effects via RNA silencing of gene-gene interactions in human induced pluripotent stem cell-derived cardiomyocytes. Finally, single-cell morphology analysis using a novel high-throughput microfluidic system shows that cardiomyocyte hypertrophy is non-additively modifiable by specific pairwise interactions between CCDC141 and both TTN and IGF1R . Our results expand the scope of genetic regulation of cardiac structure to epistasis.

Translational bioinformatics approach to combat cardiovascular disease and cancers

Bioinformatics is an interconnected subject of science dealing with diverse fields including biology, chemistry, physics, statistics, mathematics, and computer science as the key fields to answer complicated physiological problems. Key intention of bioinformatics is to store, analyze, organize, and retrieve essential information about genome, proteome, transcriptome, metabolome, as well as organisms to investigate the biological system along with its dynamics, if any. The outcome of bioinformatics depends on the type, quantity, and quality of the raw data provided and the algorithm employed to analyze the same. Despite several approved medicines available, cardiovascular disorders (CVDs) and cancers comprises of the two leading causes of human deaths. Understanding the unknown facts of both these non-communicable disorders is inevitable to discover new pathways, find new drug targets, and eventually newer drugs to combat them successfully. Since, all these goals involve complex investigation and handling of various types of macro- and small- molecules of the human body, bioinformatics plays a key role in such processes. Results from such investigation has direct human application and thus we call this filed as translational bioinformatics. Current book chapter thus deals with diverse scope and applications of this translational bioinformatics to find cure, diagnosis, and understanding the mechanisms of CVDs and cancers. Developing complex yet small or long algorithms to address such problems is very common in translational bioinformatics. Structure-based drug discovery or AI-guided invention of novel antibodies that too with super-high accuracy, speed, and involvement of considerably low amount of investment are some of the astonishing features of the translational bioinformatics and its applications in the fields of CVDs and cancers.

Association of epistatic effects of MTHFR, ACE, APOB, and APOE gene polymorphisms with the risk of myocardial infarction and unstable angina in Egyptian patients

Despite remarkable discoveries in the genetic susceptibility of coronary artery disease (CAD), a large part of heritability awaits identification. Epistasis or gene-gene interaction has a profound influence on CAD and might contribute to its missed genetic variability; however, this impact was largely unexplored. Here, we appraised the associations of gene-gene interactions and haplotypes of five polymorphisms, namely methylenetetrahydrofolate reductase (MTHFR) C677T and A1298C, angiotensin converting enzyme (ACE) insertion/deletion (I/D), apolipoprotein B (APOB) R3500Q, and apolipoprotein E (APOE) ε4 with the risk of myocardial infarction (MI) and unstable angina (UA). Gene-environment interactions with traditional risk factors and clinical data were also scrutinized. This study recruited 100 MI, 50 UA patients, and 100 apparently healthy controls. Logistic regression models were employed in association analyses. We remarked that the single locus effect of individual polymorphisms was relatively weak; however, a magnified effect of their combination via gene-gene interaction may predict MI risk after adjustment for multiple comparisons. Only MTHFR C677T, ACE I/D, and APOB R5300Q were associated with the risk of UA, and the ACE I/D-R3500Q interaction posed a decreased UA risk. APOB R3500Q was in strong linkage disequilibrium with MTHFR C677T, ACE I/D, and APE ε4 polymorphisms. The TCDGε3, CADGε4, and TADGε4-C677T-A1298C-ACE I/D-R3500Q-APOE haplotypes were associated with escalating MI risk, while the CDG or CIG-C677T-ACE I/D-R3500Q haplotype was highly protective against UA risk compared to controls. Interestingly, the CADGε4 and CAIGε3 haplotypes were strongly associated with the presence of diabetes and hypertension, respectively in MI patients; both haplotypes stratified patients according to the ECHO results. In UA, the CDG haplotype was negatively associated with the presence of diabetes or dilated heart. Conclusively, our results advocate that a stronger combined effect of polymorphisms in MTHFR, ACE, APOB, and APOE genes via gene-gene and gene-environment interactions might help in risk stratification of MI and UA patients.

LncRNA-mediated Modulation of Endothelial Cells: Novel Progress in the Pathogenesis of Coronary Atherosclerotic Disease

Coronary atherosclerotic disease (CAD) is a common cardiovascular disease and an important cause of death. Moreover, endothelial cells (ECs) injury is an early pathophysiological feature of CAD, and long noncoding RNAs (lncRNAs) can modulate gene expression. Recent studies have shown that lncRNAs are involved in the pathogenesis of CAD, especially by regulating ECs. In this review, we summarize the novel progress of lncRNA-modulated ECs in the pathogenesis of CAD, including ECs proliferation, migration, adhesion, angiogenesis, inflammation, apoptosis, autophagy, and pyroptosis. Thus, as lncRNAs regulate ECs in CAD, lncRNAs will provide ideal and novel targets for the diagnosis and drug therapy of CAD.

Gene Interactions in Human Disease Studies-Evidence Is Mounting

Despite monumental advances in molecular technology to generate genome sequence data at scale, there is still a considerable proportion of heritability in most complex diseases that remains unexplained. Because many of the discoveries have been single-nucleotide variants with small to moderate effects on disease, the functional implication of many of the variants is still unknown and, thus, we have limited new drug targets and therapeutics. We, and many others, posit that one primary factor that has limited our ability to identify novel drug targets from genome-wide association studies may be due to gene interactions (epistasis), gene-environment interactions, network/pathway effects, or multiomic relationships. We propose that many of these complex models explain much of the underlying genetic architecture of complex disease. In this review, we discuss the evidence from multiple research avenues, ranging from pairs of alleles to multiomic integration studies and pharmacogenomics, that supports the need for further investigation of gene interactions (or epistasis) in genetic and genomic studies of human disease. Our goal is to catalog the mounting evidence for epistasis in genetic studies and the connections between genetic interactions and human health and disease that could enable precision medicine of the future.

The Role of a Lung Vascular Endothelium Enriched Gene TMEM100

Transmembrane protein 100 (TMEM100) is a crucial factor in the development and maintenance of the vascular system. The protein is involved in several processes such as angiogenesis, vascular morphogenesis, and integrity. Furthermore, TMEM100 is a downstream target of the BMP9/10 and BMPR2/ALK1 signaling pathways, which are key regulators of vascular development. Our recent studies have shown that TMEM100 is a lung endothelium enriched gene and plays a significant role in lung vascular repair and regeneration. The importance of TMEM100 in endothelial cells' regeneration was demonstrated when Tmem100 was specifically deleted in endothelial cells, causing an impairment in their regenerative ability. However, the role of TMEM100 in various conditions and diseases is still largely unknown, making it an interesting area of research. This review summarizes the current knowledge of TMEM100, including its expression pattern, function, molecular signaling, and clinical implications, which could be valuable in the development of novel therapies for the treatment of cardiovascular and pulmonary diseases.

Influence of variability in the cyclooxygenase pathway on cardiovascular outcomes of nephrosclerosis patients

Nephrosclerosis patients are at an exceptionally high cardiovascular (CV) risk. We aimed to determine whether genetic variability represented by 38 tag-SNPs in genes of the cyclooxygenase pathway (PTGS1, PTGS2, PTGES, PTGES2 and PTGES3) leading to prostaglandin E2 (PGE2) synthesis, modified CV traits and events in 493 nephrosclerosis patients. Additionally, we genotyped 716 controls to identify nephrosclerosis risk associations. The addition of three variants, namely PTGS2 rs4648268, PTGES3 rs2958155 and PTGES3 rs11300958, to a predictive model for CV events containing classic risk factors in nephrosclerosis patients, significantly enhanced its statistical power (AUC value increased from 78.6 to 87.4%, p = 0.0003). Such increase remained significant after correcting for multiple testing. In addition, two tag-SNPs (rs11790782 and rs2241270) in PTGES were linked to higher systolic and diastolic pressure [carriers vs. non-carriers = 5.23 (1.87-9.93), p = 0.03 and 5.9 (1.87-9.93), p = 0.004]. PTGS1(COX1) rs10306194 was associated with higher common carotid intima media thickness (ccIMT) progression [OR 1.90 (1.07-3.36), p = 0.029], presence of carotid plaque [OR 1.79 (1.06-3.01), p = 0.026] and atherosclerosis severity (p = 0.041). These associations, however, did not survive Bonferroni correction of the data. Our findings highlight the importance of the route leading to PGE2 synthesis in the CV risk experienced by nephrosclerosis patients and add to the growing body of evidence pointing out the PGE2 synthesis/activity axis as a promising therapeutic target in this field.

Limited Effect of Y Chromosome Variation on Coronary Artery Disease and Mortality in UK Biobank-Brief Report

BACKGROUND

The effect of genetic variation in the male-specific region of the Y chromosome (MSY) on coronary artery disease and cardiovascular risk factors has been disputed. In this study, we systematically assessed the association of MSY genetic variation on these traits using a kin-cohort analysis of family disease history in the largest sample to date.

METHODS

We tested 90 MSY haplogroups against coronary artery disease, hypertension, blood pressure, classical lipid levels, and all-cause mortality in up to 152 186 unrelated, genomically British individuals from UK Biobank. Unlike previous studies, we did not adjust for heritable lifestyle factors (to avoid collider bias) and instead adjusted for geographic variables and socioeconomic deprivation, given the link between MSY haplogroups and geography. For family history traits, subject MSY haplogroups were tested against father and mother disease as validation and negative control, respectively.

RESULTS

Our models find little evidence for an effect of any MSY haplogroup on cardiovascular risk in participants. Parental models confirm these findings.

CONCLUSIONS

Kin-cohort analysis of the Y chromosome uniquely allows for discoveries in subjects to be validated using family history data. Despite our large sample size, improved models, and parental validation, there is little evidence to suggest cardiovascular risk in UK Biobank is influenced by genetic variation in MSY.

Omnibus testing approach for gene-based gene-gene interaction

Genetic interaction is considered as one of the main heritable component of complex traits. With the emergence of genome-wide association studies (GWAS), a collection of statistical methods dedicated to the identification of interaction at the SNP level have been proposed. More recently, gene-based gene-gene interaction testing has emerged as an attractive alternative as they confer advantage in both statistical power and biological interpretation. Most of the gene-based interaction methods rely on a multidimensional modeling of the interaction, thus facing a lack of robustness against the huge space of interaction patterns. In this paper, we study a global testing approaches to address the issue of gene-based gene-gene interaction. Based on a logistic regression modeling framework, all SNP-SNP interaction tests are combined to produce a gene-level test for interaction. We propose an omnibus test that takes advantage of (1) the heterogeneity between existing global tests and (2) the complementarity between allele-based and genotype-based coding of SNPs. Through an extensive simulation study, it is demonstrated that the proposed omnibus test has the ability to detect with high power the most common interaction genetic models with one causal pair as well as more complex genetic models where more than one causal pair is involved. On the other hand, the flexibility of the proposed approach is shown to be robust and improves power compared to single global tests in replication studies. Furthermore, the application of our procedure to real datasets confirms the adaptability of our approach to replicate various gene-gene interactions.

Systems biology in cardiovascular disease: a multiomics approach

Omics techniques generate large, multidimensional data that are amenable to analysis by new informatics approaches alongside conventional statistical methods. Systems theories, including network analysis and machine learning, are well placed for analysing these data but must be applied with an understanding of the relevant biological and computational theories. Through applying these techniques to omics data, systems biology addresses the problems posed by the complex organization of biological processes. In this Review, we describe the techniques and sources of omics data, outline network theory, and highlight exemplars of novel approaches that combine gene regulatory and co-expression networks, proteomics, metabolomics, lipidomics and phenomics with informatics techniques to provide new insights into cardiovascular disease. The use of systems approaches will become necessary to integrate data from more than one omic technique. Although understanding the interactions between different omics data requires increasingly complex concepts and methods, we argue that hypothesis-driven investigations and independent validation must still accompany these novel systems biology approaches to realize their full potential.

Feedback regulation of coronary artery disease susceptibility gene ADTRP and LDL receptors LDLR/CD36/LOX-1 in endothelia cell functions involved in atherosclerosis

A high level of low-density lipoprotein cholesterol (LDL) is one of the most important risk factors for coronary artery disease (CAD), the leading cause of death worldwide. However, a low concentration of LDL may be protective. Genome-wide association studies revealed that variation in ADTRP gene increased the risk of CAD. In this study, we found that a low concentration of oxidized-LDL induced the expression of ADTRP. Further analyses showed that knockdown of the expression of LDL receptor genes LDLR, CD36, or LOX-1 significantly downregulated ADTRP expression, whereas overexpression of LDLR/CD36/LOX-1 markedly increased ADTRP expression through the NF-κB pathway. Like ADTRP, LDLR, CD36 and LOX-1 were all involved in endothelial cell (EC) functions relevant to the initiation of atherosclerosis. Downregulation of LDLR/CD36/LOX-1 promoted monocyte adhesion to ECs and transendothelial migration of monocytes by increasing expression of ICAM-1, VCAM-1, E-selectin and P-selectin, decreased EC proliferation and migration, and increased EC apoptosis, thereby promoting the initiation of atherosclerosis. Opposite effects were observed with the overexpression of ADTRP and LDLR/CD36/LOX-1 in ECs. Interestingly, through the NF-κB and AKT pathways, overexpression of ADTRP significantly upregulated the expression of LDLR, CD36, and LOX-1, and knockdown of ADTRP expression significantly downregulated the expression of LDLR, CD36, and LOX-1. These data suggest that ADTRP and LDL receptors LDLR/CD36/LOX-1 positively regulate each other, and form a positive regulatory loop that regulates endothelial cell functions, thereby providing a potential protective mechanism against atherosclerosis. Our findings provide a new molecular mechanism by which deregulation of ADTRP and LDLR/CD36/LOX-1 promote the development of atherosclerosis and CAD.

A comprehensive understanding about the pharmacological effect of diallyl disulfide other than its anti-carcinogenic activities

Diallyl disulfide (DADS), an oil-soluble sulfur compound that is responsible for the biological effects of garlic, displays numerous biological activities, among which its anti-cancer activities are the most famous ones. In recent years, the pharmacological effects of DADS other than its anti-carcinogenic activities have attracted numerous attentions. For example, it has been reported that DADS can prevent the microglia-mediated neuroinflammatory response and depression-like behaviors in mice. In the cardiovascular system, DADS administration was found to ameliorate the isoproterenol- or streptozotocin-induced cardiac dysfunction via the activation of the nuclear factor E2-related factor 2 (Nrf2) and insulin-like growth factor (IGF)-phosphatidylinositol-3-kinase (PI3K)-protein kinase B (Akt) signaling. DADS administration can also produce neuroprotective effects in animal models of Alzheimer's disease and protect the heart, endothelium, liver, lung, and kidney against cellular or tissue damages induced by various toxic factors, such as the oxidized-low density lipoprotein (ox-LDL), carbon tetrachloride (CCl₄), ethanol, acetaminophen, Cis-Diammine Dichloroplatinum (CisPt), and gentamicin. The major mechanisms of action of DADS in disease prevention and/or treatment include inhibition of inflammation, oxidative stress, and cellular apoptosis. Mechanisms, including the activation of Akt, extracellular signal-regulated kinase 1/2 (ERK1/2), protein kinase A (PKA), and cyclic adenosine monophosphate-response element binding protein (CREB) and the inhibition of histone deacetylases (HDACs), can also mediate the cellular protective effects of DADS in different tissues and organs. In this review, we summarize and discuss the pharmacological effects of DADS other than its anti-carcinogenic activities, aiming to reveal more possibilities for DADS in disease prevention and/or treatment.

Splice variants of lncRNA RNA ANRIL exert opposing effects on endothelial cell activities associated with coronary artery disease

Each gene typically has multiple alternatively spliced transcripts. Different transcripts are assumed to play a similar biological role; however, some transcripts may simply lose their function due to loss of important functional domains. Here, we show that two different transcripts of lncRNA gene ANRIL associated with coronary artery disease (CAD) play antagonizing roles against each other. We previously reported that DQ485454, the short transcript, is downregulated in coronary arteries from CAD patients, and reduces monocyte adhesion to endothelial cells (ECs) and transendothelial monocyte migration (TEM). Interestingly, the longest transcript NR_003529 is significantly upregulated in coronary arteries from CAD patients. Overexpression of ANRIL transcript NR_003529 increases monocyte adhesion to ECs and TEM, whereas knockdown of NR_003529 expression reduces monocyte adhesion to ECs and TEM. Much more dramatic effects were observed for the combination of overexpression of NR_003529 and knockdown of DQ485454 or the combination of knockdown of NR_003529 and overexpression of DQ485454. The antagonizing effects of ANRIL transcripts NR_003529 and DQ485454 were associated with their opposite effects on expression of downstream target genes EZR, CXCL11 or TMEM106B. Our results demonstrate that different transcripts of lncRNA can exert antagonizing effects on biological functions, thereby providing important insights into the biology of lncRNA. The data further support the hypothesis that ANRIL is the causative gene at the 9p21 CAD susceptibility locus.

Genetic control of non-genetic inheritance in mammals: state-of-the-art and perspectives

Thought to be directly and uniquely dependent from genotypes, the ontogeny of individual phenotypes is much more complicated. Individual genetics, environmental exposures, and their interaction are the three main determinants of individual's phenotype. This picture has been further complicated a decade ago when the Lamarckian theory of acquired inheritance has been rekindled with the discovery of epigenetic inheritance, according to which acquired phenotypes can be transmitted through fertilization and affect phenotypes across generations. The results of Genome-Wide Association Studies have also highlighted a big degree of missing heritability in genetics and have provided hints that not only acquired phenotypes, but also individual's genotypes affect phenotypes intergenerationally through indirect genetic effects. Here, we review available examples of indirect genetic effects in mammals, what is known of the underlying molecular mechanisms and their potential impact for our understanding of missing heritability, phenotypic variation. and individual disease risk.

Statistical and Functional Studies Identify Epistasis of Cardiovascular Risk Genomic Variants From Genome-Wide Association Studies

Background

Epistasis describes how gene‐gene interactions affect phenotypes, and could have a profound impact on human diseases such as coronary artery disease (CAD). The goal of this study was to identify gene‐gene interactions in CAD using an easily generalizable multi‐stage approach.

Methods and Results

Our forward genetic approach consists of multiple steps that combine statistical and functional approaches, and analyze information from global gene expression profiling, functional interactions, and genetic interactions to robustly identify gene‐gene interactions. Global gene expression profiling shows that knockdown of ANRIL (DQ485454) at 9p21.3 GWAS (genome‐wide association studies) CAD locus upregulates TMEM100 and TMEM106B. Functional studies indicate that the increased monocyte adhesion to endothelial cells and transendothelial migration of monocytes, 2 critical processes in the initiation of CAD, by ANRIL knockdown are reversed by knockdown of TMEM106B, but not of TMEM100. Furthermore, the decreased monocyte adhesion to endothelial cells and transendothelial migration of monocytes induced by ANRIL overexpression was reversed by overexpressing TMEM106B. TMEM106B expression was upregulated by >2‐fold in CAD coronary arteries. A significant association was found between variants in TMEM106B (but not in TMEM100) and CAD (P=1.9×10⁻⁸). Significant gene‐gene interaction was detected between ANRIL variant rs2383207 and TMEM106B variant rs3807865 (P=0.009). A similar approach also identifies significant interaction between rs6903956 in ADTRP and rs17465637 in MIA3 (P=0.005).

Conclusions

We demonstrate 2 pairs of epistatic interactions between GWAS loci for CAD and offer important insights into the genetic architecture and molecular mechanisms for the pathogenesis of CAD. Our strategy has broad applicability to the identification of epistasis in other human diseases.