Endothelial cell-specific deletion of a microRNA accelerates atherosclerosis

Background and aims: Chronic vascular endothelial inflammation predisposes to atherosclerosis; however, the cell-autonomous roles for endothelial-expressing microRNAs (miRNAs) are poorly understood in this process. MiR-181b is expressed in several cellular constituents relevant to lesion formation. The aim of this study is to examine the role of genetic deficiency of the miR-181b locus in endothelial cells during atherogenesis. Methods and Results: Using a proprotein convertase subtilisin/kexin type 9 (PCSK9)-induced atherosclerosis mouse model, we demonstrated that endothelial cell (EC)-specific deletion of miR-181a2b2 significantly promoted atherosclerotic lesion formation, cell adhesion molecule expression, and the influx of lesional macrophages in the vessel wall. Yet, endothelium deletion of miR-181a2b2 did not affect body weight, lipid metabolism, anti-inflammatory Ly6Clow or the pro-inflammatory Ly6Cinterm and Ly6Chigh fractions in circulating peripheral blood mononuclear cells (PBMCs), and pro-inflammatory or anti-inflammatory mediators in both bone marrow (BM) and PBMCs. Mechanistically, bulk RNA-seq and gene set enrichment analysis of ECs enriched from the aortic arch intima, as well as single cell RNA-seq from atherosclerotic lesions, revealed that endothelial miR-181a2b2 serves as a critical regulatory hub in controlling endothelial inflammation, cell adhesion, cell cycle, and immune response during atherosclerosis. Conclusions: Our study establishes that deficiency of a miRNA specifically in the vascular endothelium is sufficient to profoundly impact atherogenesis. Endothelial miR-181a2b2 deficiency regulates multiple key pathways related to endothelial inflammation, cell adhesion, cell cycle, and immune response involved in the development of atherosclerosis

Deep learning enables genetic analysis of the human thoracic aorta

Genome-wide association analyses identify variants associated with thoracic aortic diameter. A polygenic score for ascending aortic diameter was associated with a diagnosis of thoracic aortic aneurysm in independent samples. Enlargement or aneurysm of the aorta predisposes to dissection, an important cause of sudden death. We trained a deep learning model to evaluate the dimensions of the ascending and descending thoracic aorta in 4.6 million cardiac magnetic resonance images from the UK Biobank. We then conducted genome-wide association studies in 39,688 individuals, identifying 82 loci associated with ascending and 47 with descending thoracic aortic diameter, of which 14 loci overlapped. Transcriptome-wide analyses, rare-variant burden tests and human aortic single nucleus RNA sequencing prioritized genes including SVIL, which was strongly associated with descending aortic diameter. A polygenic score for ascending aortic diameter was associated with thoracic aortic aneurysm in 385,621 UK Biobank participants (hazard ratio = 1.43 per s.d., confidence interval 1.32-1.54, P = 3.3 x 10(-20)). Our results illustrate the potential for rapidly defining quantitative traits with deep learning, an approach that can be broadly applied to biomedical images

Single-Cell Analysis of the Normal Mouse Aorta Reveals Functionally Distinct Endothelial Cell Populations

Background: The cells that form the arterial wall contribute to multiple vascular diseases. The extent of cellular heterogeneity within these populations has not been fully characterized. Recent advances in single-cell RNA-sequencing make it possible to identify and characterize cellular subpopulations. Methods: We validate a method for generating a droplet-based single-cell atlas of gene expression in a normal blood vessel. Enzymatic dissociation of 4 whole mouse aortas was followed by single-cell sequencing of >10 000 cells. Results: Clustering analysis of gene expression from aortic cells identified 10 populations of cells representing each of the main arterial cell types: fibroblasts, vascular smooth muscle cells, endothelial cells (ECs), and immune cells, including monocytes, macrophages, and lymphocytes. The most significant cellular heterogeneity was seen in the 3 distinct EC populations. Gene set enrichment analysis of these EC subpopulations identified a lymphatic EC cluster and 2 other populations more specialized in lipoprotein handling, angiogenesis, and extracellular matrix production. These subpopulations persist and exhibit similar changes in gene expression in response to a Western diet. Immunofluorescence for Vcam1 and Cd36 demonstrates regional heterogeneity in EC populations throughout the aorta. Conclusions: We present a comprehensive single-cell atlas of all cells in the aorta. By integrating expression from >1900 genes per cell, we are better able to characterize cellular heterogeneity compared with conventional approaches. Gene expression signatures identify cell subpopulations with vascular disease-relevant functions

Application of whole exome sequencing in elucidating the phenotype and genotype spectrum of junctional epidermolysis bullosa: A preliminary experience of a tertiary care centre in India

•Junctional epidermolysis bullosa (JEB) is a clinically and genetically heterogenous group of genetic skin disorders.•We show the utility of WES in understanding the phenotype and genotype spectrum in four Indian JEB families.•Computational modeling studies have been used to understand the probable molecular consequence of a missense mutation on the structure-function relationship of lamininβ3 protein.•This is the first report documenting the phenotype-genotype correlations of JEB patients from India. Junctional epidermolysis bullosa (JEB) is a diverse group of genodermatoses associated with extreme skin fragility. Despite several well-characterized genetic studies, molecular diagnosis of this heterogeneous group is still challenging. Recent advances in the field of genomics have seen the successful implementation of whole exome sequencing (WES) as a fast and efficient diagnostic strategy in several genodermatoses. In view of the scarcity and need of molecular studies for JEB in India, we sought to explore the potential of WES in understanding the mutational spectrum of this rare, in certain subtypes lethal, sub-group of EB. WES was performed using genomic DNA from each case of EB, followed by massively parallel sequencing. Resulting reads were mapped to the human reference genome hg19. Sanger sequencing subsequently confirmed the potentially pathogenic mutations. Overall, four unrelated families (6 patients) of JEB with a highly variable clinical presentation including a rare case of LOC syndrome were studied. WES revealed 4 variations in 3 genes (LAMA3, LAMB3 and COL17A1) that are implicated in JEB. None of the variations were recurrent. In addition we proposed the probable molecular consequence of a missense mutation on the structure-function relationship of lamininβ3 protein through computational modeling studies. Being the first report documenting the phenotype-genotype correlations of JEB patients from India, our preliminary experience with WES is clearly encouraging and serves as a nidus for future large-scale molecular studies to actively identify and understand JEB patients in Indian population