Dissecting the polygenic basis of atherosclerosis via disease-associated cell state signatures.

Coronary artery disease (CAD) is a pandemic disease where up to half of the risk is explained by genetic factors. Advanced insights into the genetic basis of CAD require deeper understanding of the contributions of different cell types, molecular pathways, and genes to disease heritability. Here, we investigate the biological diversity of atherosclerosis-associated cell states and interrogate their contribution to the genetic risk of CAD by using single-cell and bulk RNA sequencing (RNA-seq) of mouse and human lesions. We identified 12 disease-associated cell states that we characterized further by gene set functional profiling, ligand-receptor prediction, and transcription factor inference. Importantly, Vcam1+ smooth muscle cell state genes contributed most to SNP-based heritability of CAD. In line with this, genetic variants near smooth muscle cell state genes and regulatory elements explained the largest fraction of CAD-risk variance between individuals. Using this information for variant prioritization, we derived a hybrid polygenic risk score (PRS) that demonstrated improved performance over a classical PRS. Our results provide insights into the biological mechanisms associated with CAD risk, which could make a promising contribution to precision medicine and tailored therapeutic interventions in the future.

Coronary Artery Disease Risk Variant Dampens the Expression of CALCRL by Reducing HSF Binding to Shear Stress Responsive Enhancer in Endothelial Cells In Vitro.

BACKGROUND: CALCRL (calcitonin receptor-like) protein is an important mediator of the endothelial fluid shear stress response, which is associated with the genetic risk of coronary artery disease. In this study, we functionally characterized the noncoding regulatory elements carrying coronary artery disease that risks single-nucleotide polymorphisms and studied their role in the regulation of CALCRL expression in endothelial cells. METHODS: To functionally characterize the coronary artery disease single-nucleotide polymorphisms harbored around the gene CALCRL, we applied an integrative approach encompassing statistical, transcriptional (RNA-seq), and epigenetic (ATAC-seq [transposase-accessible chromatin with sequencing], chromatin immunoprecipitation assay-quantitative polymerase chain reaction, and electromobility shift assay) analyses, alongside luciferase reporter assays, and targeted gene and enhancer perturbations (siRNA and clustered regularly interspaced short palindromic repeats/clustered regularly interspaced short palindromic repeat-associated 9) in human aortic endothelial cells. RESULTS: We demonstrate that the regulatory element harboring rs880890 exhibits high enhancer activity and shows significant allelic bias. The A allele was favored over the G allele, particularly under shear stress conditions, mediated through alterations in the HSF1 (heat shock factor 1) motif and binding. CRISPR deletion of rs880890 enhancer resulted in downregulation of CALCRL expression, whereas HSF1 knockdown resulted in a significant decrease in rs880890-enhancer activity and CALCRL expression. A significant decrease in HSF1 binding to the enhancer region in endothelial cells was observed under disturbed flow compared with unidirectional flow. CALCRL knockdown and variant perturbation experiments indicated the role of CALCRL in mediating eNOS (endothelial nitric oxide synthase), APLN (apelin), angiopoietin, prostaglandins, and EDN1 (endothelin-1) signaling pathways leading to a decrease in cell proliferation, tube formation, and NO production. CONCLUSIONS: Overall, our results demonstrate the existence of an endothelial-specific HSF (heat shock factor)-regulated transcriptional enhancer that mediates CALCRL expression. A better understanding of CALCRL gene regulation and the role of single-nucleotide polymorphisms in the modulation of CALCRL expression could provide important steps toward understanding the genetic regulation of shear stress signaling responses.

Integrative analysis of liver-specific non-coding regulatory SNPs associated with the risk of coronary artery disease.

Genetic factors underlying coronary artery disease (CAD) have been widely studied using genome-wide association studies (GWASs). However, the functional understanding of the CAD loci has been limited by the fact that a majority of GWAS variants are located within non-coding regions with no functional role. High cholesterol and dysregulation of the liver metabolism such as non-alcoholic fatty liver disease confer an increased risk of CAD. Here, we studied the function of non-coding single-nucleotide polymorphisms in CAD GWAS loci located within liver-specific enhancer elements by identifying their potential target genes using liver cis-eQTL analysis and promoter Capture Hi-C in HepG2 cells. Altogether, 734 target genes were identified of which 121 exhibited correlations to liver-related traits. To identify potentially causal regulatory SNPs, the allele-specific enhancer activity was analyzed by (1) sequence-based computational predictions, (2) quantification of allele-specific transcription factor binding, and (3) STARR-seq massively parallel reporter assay. Altogether, our analysis identified 1,277 unique SNPs that display allele-specific regulatory activity. Among these, susceptibility enhancers near important cholesterol homeostasis genes (APOB, APOC1, APOE, and LIPA) were identified, suggesting that altered gene regulatory activity could represent another way by which genetic variation regulates serum lipoprotein levels. Using CRISPR-based perturbation, we demonstrate how the deletion/activation of a single enhancer leads to changes in the expression of many target genes located in a shared chromatin interaction domain. Our integrative genomics approach represents a comprehensive effort in identifying putative causal regulatory regions and target genes that could predispose to clinical manifestation of CAD by affecting liver function.

DNA methylation profiling reveals the presence of population-specific signatures correlating with phenotypic characteristics.

Phenotypic characteristics are known to vary substantially among different ethnicities around the globe. These variations are mediated by number of stochastic events and cannot be attributed to genetic architecture alone. DNA methylation is a well-established mechanism that sculpts our epigenome influencing phenotypic variation including disease manifestation. Since DNA methylation is an important determinant for health issues of a population, it demands a thorough investigation of the natural differences in genome wide DNA methylation patterns across different ethnic groups. This study is based on comparative analyses of methylome from five different ethnicities with major focus on Indian subjects. The current study uses hierarchical clustering approaches, principal component analysis and locus specific differential methylation analysis on Illumina 450K methylation data to compare methylome of different ethnic subjects. Our data indicates that the variations in DNA methylation patterns of Indians are less among themselves compared to other global population. It empirically correlated with dietary, cultural and demographical divergences across different ethnic groups. Our work further suggests that Indians included in this study, despite their genetic similarity with the Caucasian population, are in close proximity with Japanese in terms of their methylation signatures.

Translatome profiling reveals Itih4 as a novel smooth muscle cell-specific gene in atherosclerosis.

AIMS: Vascular smooth muscle cells (SMCs) and their derivatives are key contributors to the development of atherosclerosis. However, studying changes in SMC gene expression in heterogeneous vascular tissues is challenging due to the technical limitations and high cost associated with current approaches. In this paper, we apply translating ribosome affinity purification sequencing to profile SMC-specific gene expression directly from tissue. METHODS AND RESULTS: To facilitate SMC-specific translatome analysis, we generated SMCTRAP mice, a transgenic mouse line expressing enhanced green fluorescent protein (EGFP)-tagged ribosomal protein L10a (EGFP-L10a) under the control of the SMC-specific αSMA promoter. These mice were further crossed with the atherosclerosis model Ldlr-/-, ApoB100/100 to generate SMCTRAP-AS mice and used to profile atherosclerosis-associated SMCs in thoracic aorta samples of 15-month-old SMCTRAP and SMCTRAP-AS mice. Our analysis of SMCTRAP-AS mice showed that EGFP-L10a expression was localized to SMCs in various tissues, including the aortic wall and plaque. The TRAP fraction demonstrated high enrichment of known SMC-specific genes, confirming the specificity of our approach. We identified several genes, including Cemip, Lum, Mfge8, Spp1, and Serpina3, which are known to be involved in atherosclerosis-induced gene expression. Moreover, we identified several novel genes not previously linked to SMCs in atherosclerosis, such as Anxa4, Cd276, inter-alpha-trypsin inhibitor-4 (Itih4), Myof, Pcdh11x, Rab31, Serpinb6b, Slc35e4, Slc8a3, and Spink5. Among them, we confirmed the SMC-specific expression of Itih4 in atherosclerotic lesions using immunofluorescence staining of mouse aortic roots and spatial transcriptomics of human carotid arteries. Furthermore, our more detailed analysis of Itih4 showed its link to coronary artery disease through the colocalization of genome-wide association studies, splice quantitative trait loci (QTL), and protein QTL signals. CONCLUSION: We generated a SMC-specific TRAP mouse line to study atherosclerosis and identified Itih4 as a novel SMC-expressed gene in atherosclerotic plaques, warranting further investigation of its putative function in extracellular matrix stability and genetic evidence of causality.

Exploiting Glutamine Consumption in Atherosclerotic Lesions by Positron Emission Tomography Tracer (2S,4R)-4-18F-Fluoroglutamine.

Increased glutamine metabolism by macrophages is associated with development of atherosclerotic lesions. Positron emission tomography/computed tomography (PET/CT) with a glutamine analog (2S,4R)-4-18F-fluoroglutamine (18F-FGln) allows quantification of glutamine consumption in vivo. Here, we investigated uptake of 18F-FGln by atherosclerotic lesions in mice and compared the results with those obtained using the glucose analog 2-deoxy-2-18F-fluoro-D-glucose (18F-FDG). Uptake of 18F-FGln and 18F-FDG by healthy control mice (C57BL/6JRj) and atherosclerotic low-density lipoprotein receptor-deficient mice expressing only apolipoprotein B100 (LDLR-/-ApoB100/100) was investigated. The mice were injected intravenously with 18F-FGln or 18F-FDG for in vivo PET/CT imaging. After sacrifice at 70 minutes post-injection, tracer uptake was analyzed by gamma counting of excised tissues and by autoradiography of aorta cryosections, together with histological and immunohistochemical analyses. We found that myocardial uptake of 18F-FGln was low. PET/CT detected lesions in the aortic arch, with a target-to-background ratio (SUVmax, aortic arch/SUVmean, blood) of 1.95 ± 0.42 (mean ± standard deviation). Gamma counting revealed that aortic uptake of 18F-FGln by LDLR-/-ApoB100/100 mice (standardized uptake value [SUV], 0.35 ± 0.06) was significantly higher than that by healthy controls (0.20 ± 0.08, P = 0.03). More detailed analysis by autoradiography revealed that the plaque-to-healthy vessel wall ratio of 18F-FGln (2.90 ± 0.42) was significantly higher than that of 18F-FDG (1.93 ± 0.22, P = 0.004). Immunohistochemical staining confirmed that 18F-FGln uptake in plaques co-localized with glutamine transporter SLC7A7-positive macrophages. Collectively these data show that the 18F-FGln PET tracer detects inflamed atherosclerotic lesions. Thus, exploiting glutamine consumption using 18F-FGln PET may have translational relevance for studying atherosclerotic inflammation.

Corrigendum: Exploiting Glutamine Consumption in Atherosclerotic Lesions by Positron Emission Tomography Tracer (2S,4R)-4-18F-Fluoroglutamine.

[This corrects the article DOI: 10.3389/fimmu.2022.821423.].