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.
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.
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.
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.
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.
Abstract 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.
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-2α, IRE1α, 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.--Gora, S., Maouche, S., Atout, R., Wanherdrick, K., Lambeau, G., Cambien, F., Ninio, E., Karabina, S.-A. Phospholipolyzed LDL induces an inflammatory response in endothelial cells through endoplasmic reticulum stress signaling.
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.
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.
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.
Emerging technologies (ET) are novel and relatively fast-growing technologies that can have massive socio-economic impact and bring new ethical and regulatory challenges. Although they cannot be ...considered as new technologies, artificial intelligence (AI) and related data driven technologies are examples of ET. AI is advancing at a rapid pace, in both public and private sectors, and being more widely deployed in different domains, including healthcare and education.
In today's digital age, our societies are facing rapid and massive technological transformations. It is important to ensure that the behavior of AI systems is beneficial to humanity. Policymakers and the research community need to identify the greatest barriers to AI adoption and related risks. In recent years, Google's plans and visions to use ET gained serious and intense criticism. This situation pushed Google in March 2019 to announce an AI ethics panel which is supposed to offer guidance on ethical issues relating to AI, machine learning, and related technologies. This AI ethics panel was shut down just days after it was launched. The episode illustrates how ethical debates relating to ET are often characterized by ambiguity, dishonesty, and demagoguery. In this paper, I discuss the ethics of ET, focusing on Google and its AI platform.
Coronary artery disease (CAD) is the commonest cause of death. Here, we report an association analysis in 63,746 CAD cases and 130,681 controls identifying 15 loci reaching genome-wide significance, ...taking the number of susceptibility loci for CAD to 46, and a further 104 independent variants (r(2) < 0.2) strongly associated with CAD at a 5% false discovery rate (FDR). Together, these variants explain approximately 10.6% of CAD heritability. Of the 46 genome-wide significant lead SNPs, 12 show a significant association with a lipid trait, and 5 show a significant association with blood pressure, but none is significantly associated with diabetes. Network analysis with 233 candidate genes (loci at 10% FDR) generated 5 interaction networks comprising 85% of these putative genes involved in CAD. The four most significant pathways mapping to these networks are linked to lipid metabolism and inflammation, underscoring the causal role of these activities in the genetic etiology of CAD. Our study provides insights into the genetic basis of CAD and identifies key biological pathways.
We performed a meta-analysis of 14 genome-wide association studies of coronary artery disease (CAD) comprising 22,233 individuals with CAD (cases) and 64,762 controls of European descent followed by ...genotyping of top association signals in 56,682 additional individuals. This analysis identified 13 loci newly associated with CAD at P < 5 × 10⁻⁸ and confirmed the association of 10 of 12 previously reported CAD loci. The 13 new loci showed risk allele frequencies ranging from 0.13 to 0.91 and were associated with a 6% to 17% increase in the risk of CAD per allele. Notably, only three of the new loci showed significant association with traditional CAD risk factors and the majority lie in gene regions not previously implicated in the pathogenesis of CAD. Finally, five of the new CAD risk loci appear to have pleiotropic effects, showing strong association with various other human diseases or traits.
Proinsulin is a precursor of mature insulin and C-peptide. Higher circulating proinsulin levels are associated with impaired β-cell function, raised glucose levels, insulin resistance, and type 2 ...diabetes (T2D). Studies of the insulin processing pathway could provide new insights about T2D pathophysiology.
We have conducted a meta-analysis of genome-wide association tests of ∼2.5 million genotyped or imputed single nucleotide polymorphisms (SNPs) and fasting proinsulin levels in 10,701 nondiabetic adults of European ancestry, with follow-up of 23 loci in up to 16,378 individuals, using additive genetic models adjusted for age, sex, fasting insulin, and study-specific covariates.
Nine SNPs at eight loci were associated with proinsulin levels (P < 5 × 10(-8)). Two loci (LARP6 and SGSM2) have not been previously related to metabolic traits, one (MADD) has been associated with fasting glucose, one (PCSK1) has been implicated in obesity, and four (TCF7L2, SLC30A8, VPS13C/C2CD4A/B, and ARAP1, formerly CENTD2) increase T2D risk. The proinsulin-raising allele of ARAP1 was associated with a lower fasting glucose (P = 1.7 × 10(-4)), improved β-cell function (P = 1.1 × 10(-5)), and lower risk of T2D (odds ratio 0.88; P = 7.8 × 10(-6)). Notably, PCSK1 encodes the protein prohormone convertase 1/3, the first enzyme in the insulin processing pathway. A genotype score composed of the nine proinsulin-raising alleles was not associated with coronary disease in two large case-control datasets.
We have identified nine genetic variants associated with fasting proinsulin. Our findings illuminate the biology underlying glucose homeostasis and T2D development in humans and argue against a direct role of proinsulin in coronary artery disease pathogenesis.
PDF
