Strategies beyond genome-wide association studies for atherosclerosis.

Atherosclerotic diseases, including coronary artery disease (CAD) and myocardial infarction (MI), are the leading causes of death in the world. The genetic basis of CAD and MI, which are caused by multiple interacting endogenous and exogenous factors, has gained considerable interest in the last years as genome-wide association studies (GWASs) have identified many new susceptibility loci for CAD and MI, and the underlying genes provide new insights into the genetic architecture of these diseases. Here we summarize the recent findings from GWASs of atherosclerosis and discuss their functional and biological implications. We also discuss the different post-GWAS strategies that are currently used for refining the location of causal variants, understanding their role, and shedding light on molecular mechanisms explaining their association to CAD. We finally discuss potential clinical translations of GWAS findings for individual risk prediction, advanced clinical strategies, and personalized treatments.

Long-range DNA looping and gene expression analyses identify DEXI as an autoimmune disease candidate gene.

The chromosome 16p13 region has been associated with several autoimmune diseases, including type 1 diabetes (T1D) and multiple sclerosis (MS). CLEC16A has been reported as the most likely candidate gene in the region, since it contains the most disease-associated single-nucleotide polymorphisms (SNPs), as well as an imunoreceptor tyrosine-based activation motif. However, here we report that intron 19 of CLEC16A, containing the most autoimmune disease-associated SNPs, appears to behave as a regulatory sequence, affecting the expression of a neighbouring gene, DEXI. The CLEC16A alleles that are protective from T1D and MS are associated with increased expression of DEXI, and no other genes in the region, in two independent monocyte gene expression data sets. Critically, using chromosome conformation capture (3C), we identified physical proximity between the DEXI promoter region and intron 19 of CLEC16A, separated by a loop of >150 kb. In reciprocal experiments, a 20 kb fragment of intron 19 of CLEC16A, containing SNPs associated with T1D and MS, as well as with DEXI expression, interacted with the promotor region of DEXI but not with candidate DNA fragments containing other potential causal genes in the region, including CLEC16A. Intron 19 of CLEC16A is highly enriched for transcription-factor-binding events and markers associated with enhancer activity. Taken together, these data indicate that although the causal variants in the 16p13 region lie within CLEC16A, DEXI is an unappreciated autoimmune disease candidate gene, and illustrate the power of the 3C approach in progressing from genome-wide association studies results to candidate causal genes.

Powerful identification of cis-regulatory SNPs in human primary monocytes using allele-specific gene expression.

A large number of genome-wide association studies have been performed during the past five years to identify associations between SNPs and human complex diseases and traits. The assignment of a functional role for the identified disease-associated SNP is not straight-forward. Genome-wide expression quantitative trait locus (eQTL) analysis is frequently used as the initial step to define a function while allele-specific gene expression (ASE) analysis has not yet gained a wide-spread use in disease mapping studies. We compared the power to identify cis-acting regulatory SNPs (cis-rSNPs) by genome-wide allele-specific gene expression (ASE) analysis with that of traditional expression quantitative trait locus (eQTL) mapping. Our study included 395 healthy blood donors for whom global gene expression profiles in circulating monocytes were determined by Illumina BeadArrays. ASE was assessed in a subset of these monocytes from 188 donors by quantitative genotyping of mRNA using a genome-wide panel of SNP markers. The performance of the two methods for detecting cis-rSNPs was evaluated by comparing associations between SNP genotypes and gene expression levels in sample sets of varying size. We found that up to 8-fold more samples are required for eQTL mapping to reach the same statistical power as that obtained by ASE analysis for the same rSNPs. The performance of ASE is insensitive to SNPs with low minor allele frequencies and detects a larger number of significantly associated rSNPs using the same sample size as eQTL mapping. An unequivocal conclusion from our comparison is that ASE analysis is more sensitive for detecting cis-rSNPs than standard eQTL mapping. Our study shows the potential of ASE mapping in tissue samples and primary cells which are difficult to obtain in large numbers.

Integrating genome-wide genetic variations and monocyte expression data reveals trans-regulated gene modules in humans.

One major expectation from the transcriptome in humans is to characterize the biological basis of associations identified by genome-wide association studies. So far, few cis expression quantitative trait loci (eQTLs) have been reliably related to disease susceptibility. Trans-regulating mechanisms may play a more prominent role in disease susceptibility. We analyzed 12,808 genes detected in at least 5% of circulating monocyte samples from a population-based sample of 1,490 European unrelated subjects. We applied a method of extraction of expression patterns-independent component analysis-to identify sets of co-regulated genes. These patterns were then related to 675,350 SNPs to identify major trans-acting regulators. We detected three genomic regions significantly associated with co-regulated gene modules. Association of these loci with multiple expression traits was replicated in Cardiogenics, an independent study in which expression profiles of monocytes were available in 758 subjects. The locus 12q13 (lead SNP rs11171739), previously identified as a type 1 diabetes locus, was associated with a pattern including two cis eQTLs, RPS26 and SUOX, and 5 trans eQTLs, one of which (MADCAM1) is a potential candidate for mediating T1D susceptibility. The locus 12q24 (lead SNP rs653178), which has demonstrated extensive disease pleiotropy, including type 1 diabetes, hypertension, and celiac disease, was associated to a pattern strongly correlating to blood pressure level. The strongest trans eQTL in this pattern was CRIP1, a known marker of cellular proliferation in cancer. The locus 12q15 (lead SNP rs11177644) was associated with a pattern driven by two cis eQTLs, LYZ and YEATS4, and including 34 trans eQTLs, several of them tumor-related genes. This study shows that a method exploiting the structure of co-expressions among genes can help identify genomic regions involved in trans regulation of sets of genes and can provide clues for understanding the mechanisms linking genome-wide association loci to disease.

Antagonistic regulation of macrophage phenotype by M-CSF and GM-CSF: implication in atherosclerosis.

OBJECTIVES: We characterized the transcriptional profiles of GM-CSF- (GM-MØ) and M-CSF-induced macrophages (M-MØ) and investigated in situ a subset of differentially expressed genes in human and mouse atherosclerotic lesions. METHODS AND RESULTS: Using microarrays we identified a number of genes and biological processes differentially regulated in M-MØ vs GM-MØ. By varying in culture the M-CSF/GM-CSF ratio (0-10), a spectrum of macrophage phenotypes was explored by RT-QPCR. M-CSF (10 ng/ml) stimulated expression of several genes, including selenoprotein-1 (SEPP1), stabilin-1 (STAB1) and CD163 molecule-like-1 (CD163L1) which was inhibited by a low dose of GM-CSF (1 ng/ml); M-CSF inhibited the expression of pro-platelet basic protein (PPBP) induced by GM-CSF. Combining tissue microarrays/quantitative immunohistochemistry of human aortic lesions with RT-QPCR expression data either from human carotids vs mammary non-atherosclerotic arteries or from the apoE null mice normal and atherosclerotic aortas showed that, STAB1, SEPP1 and CD163L1 (M-CSF-sensitive genes) and PPBP (GM-CSF-sensitive gene) were expressed in both human arterial and apoE null mice atherosclerotic tissues. CONCLUSION: A balance between M-CSF vs GM-CSF defines macrophage functional polarisation and may contribute to the progression of atherosclerosis.

A trans-acting locus regulates an anti-viral expression network and type 1 diabetes risk.

Combined analyses of gene networks and DNA sequence variation can provide new insights into the aetiology of common diseases that may not be apparent from genome-wide association studies alone. Recent advances in rat genomics are facilitating systems-genetics approaches. Here we report the use of integrated genome-wide approaches across seven rat tissues to identify gene networks and the loci underlying their regulation. We defined an interferon regulatory factor 7 (IRF7)-driven inflammatory network (IDIN) enriched for viral response genes, which represents a molecular biomarker for macrophages and which was regulated in multiple tissues by a locus on rat chromosome 15q25. We show that Epstein-Barr virus induced gene 2 (Ebi2, also known as Gpr183), which lies at this locus and controls B lymphocyte migration, is expressed in macrophages and regulates the IDIN. The human orthologous locus on chromosome 13q32 controlled the human equivalent of the IDIN, which was conserved in monocytes. IDIN genes were more likely to associate with susceptibility to type 1 diabetes (T1D)-a macrophage-associated autoimmune disease-than randomly selected immune response genes (P = 8.85 × 10(-6)). The human locus controlling the IDIN was associated with the risk of T1D at single nucleotide polymorphism rs9585056 (P = 7.0 × 10(-10); odds ratio, 1.15), which was one of five single nucleotide polymorphisms in this region associated with EBI2 (GPR183) expression. These data implicate IRF7 network genes and their regulatory locus in the pathogenesis of T1D.

Genetics and beyond--the transcriptome of human monocytes and disease susceptibility.

BACKGROUND: Variability of gene expression in human may link gene sequence variability and phenotypes; however, non-genetic variations, alone or in combination with genetics, may also influence expression traits and have a critical role in physiological and disease processes. METHODOLOGY/PRINCIPAL FINDINGS: To get better insight into the overall variability of gene expression, we assessed the transcriptome of circulating monocytes, a key cell involved in immunity-related diseases and atherosclerosis, in 1,490 unrelated individuals and investigated its association with >675,000 SNPs and 10 common cardiovascular risk factors. Out of 12,808 expressed genes, 2,745 expression quantitative trait loci were detected (P<5.78x10(-12)), most of them (90%) being cis-modulated. Extensive analyses showed that associations identified by genome-wide association studies of lipids, body mass index or blood pressure were rarely compatible with a mediation by monocyte expression level at the locus. At a study-wide level (P<3.9x10(-7)), 1,662 expression traits (13.0%) were significantly associated with at least one risk factor. Genome-wide interaction analyses suggested that genetic variability and risk factors mostly acted additively on gene expression. Because of the structure of correlation among expression traits, the variability of risk factors could be characterized by a limited set of independent gene expressions which may have biological and clinical relevance. For example expression traits associated with cigarette smoking were more strongly associated with carotid atherosclerosis than smoking itself. CONCLUSIONS/SIGNIFICANCE: This study demonstrates that the monocyte transcriptome is a potent integrator of genetic and non-genetic influences of relevance for disease pathophysiology and risk assessment.

Phospholipolyzed LDL induces an inflammatory response in endothelial cells through endoplasmic reticulum stress signaling.

Secreted phospholipases A2 (sPLA2s) are present in atherosclerotic plaques and are now considered novel attractive therapeutic targets and potential biomarkers as they contribute to the development of atherosclerosis through lipoprotein-dependent and independent mechanisms. We have previously shown that hGX-sPLA2-phospholipolyzed LDL (LDL-X) induces proinflammatory responses in human umbilical endothelial cells (HUVECs); here we explore the molecular mechanisms involved. Global transcriptional gene expression profiling of the response of endothelial cells exposed to either LDL or LDL-X revealed that LDL-X activates multiple distinct cellular pathways including the unfolded protein response (UPR). Mechanistic insight showed that LDL-X activates UPR through calcium depletion of intracellular stores, which in turn disturbs cytoskeleton organization. Treatment of HUVECs and aortic endothelial cells (HAECs) with LDL-X led to activation of all 3 proximal initiators of UPR: eIF-2alpha, IRE1alpha, and ATF6. In parallel, we observed a sustained phosphorylation of the p38 pathway resulting in the phosphorylation of AP-1 downstream targets. This was accompanied by significant production of the proinflammatory cytokines IL-6 and IL-8. Our study demonstrates that phospholipolyzed LDL uses a range of molecular pathways including UPR to initiate endothelial cell perturbation and thus provides an LDL oxidation-independent mechanism for the initiation of vascular inflammation in atherosclerosis.

Performance comparison of two microarray platforms to assess differential gene expression in human monocyte and macrophage cells.

BACKGROUND: In this study we assessed the respective ability of Affymetrix and Illumina microarray methodologies to answer a relevant biological question, namely the change in gene expression between resting monocytes and macrophages derived from these monocytes. Five RNA samples for each type of cell were hybridized to the two platforms in parallel. In addition, a reference list of differentially expressed genes (DEG) was generated from a larger number of hybridizations (mRNA from 86 individuals) using the RNG/MRC two-color platform. RESULTS: Our results show an important overlap of the Illumina and Affymetrix DEG lists. In addition, more than 70% of the genes in these lists were also present in the reference list. Overall the two platforms had very similar performance in terms of biological significance, evaluated by the presence in the DEG lists of an excess of genes belonging to Gene Ontology (GO) categories relevant for the biology of monocytes and macrophages. Our results support the conclusion of the MicroArray Quality Control (MAQC) project that the criteria used to constitute the DEG lists strongly influence the degree of concordance among platforms. However the importance of prioritizing genes by magnitude of effect (fold change) rather than statistical significance (p-value) to enhance cross-platform reproducibility recommended by the MAQC authors was not supported by our data. CONCLUSION: Functional analysis based on GO enrichment demonstrates that the 2 compared technologies delivered very similar results and identified most of the relevant GO categories enriched in the reference list.