Integrative analysis of single-cell transcriptomics and genetic associations identify cell states associated with vascular disease.

Background: Vascular diseases are accompanied by alterations in cellular phenotypes which underlie disease pathogenesis, with single-cell technologies aiding in the discovery of cellular heterogeneity among endothelial cell (EC) and vascular smooth muscle cell (VSMC) populations. In atherosclerotic disease, VSMCs are hypothesized to transition between contractile and synthetic states; however, the specific vascular subpopulations and intermediate cell states responsible for early vascular dysfunction remain unclear.

Methods: We integrated newly generated and published single-nuclear RNA-sequencing (snRNA-seq) datasets to analyze normal (n = 7), aneurysmal (n = 9), and atherosclerotic (n = 2) flash-frozen human ascending thoracic aortas.

Interpreting MYH11 Copy Number Variation in Thoracic Aortic Aneurysm and Dissection: Insights From the Misannotation of Variants in Clinical Genetic Tests.

Thoracic aortic aneurysm and dissection (TAAD) is a rare but often fatal vascular disease. A family history of TAAD increases risk, and several genes are linked to risk of both aneurysm and dissection. The current AHA/ACC guidelines for management of TAAD include genetic testing for affected individuals with no other risk factors such as hypertension or bicuspid aortic valve.

Endothelial cell-related genetic variants identify LDL cholesterol-sensitive individuals who derive greater benefit from aggressive lipid lowering.

The role of endothelial cell (EC) dysfunction in contributing to an individual's susceptibility to coronary atherosclerosis and how low-density lipoprotein cholesterol (LDL-C) concentrations might modify this relationship have not been previously studied. Here, from an examination of genome-wide significant single nucleotide polymorphisms associated with coronary artery disease (CAD), we identified variants with effects on EC function and constructed a 35 single nucleotide polymorphism polygenic risk score comprising these EC-specific variants (EC PRS). The association of the EC PRS with the risk of incident cardiovascular disease was tested in 3 cohorts: a primary prevention population in the UK Biobank (UKBB; n = 348,967); a primary prevention cohort from a trial that tested a statin (JUPITER, n = 8,749); and a secondary prevention cohort that tested a PCSK9 inhibitor (FOURIER, n = 14,298).

Missing Regulation Between Genetic Association and Transcriptional Abundance for Hypercholesterolemia Genes.

Low-density lipoprotein cholesterol (LDL-C) is a well-established risk factor for cardiovascular disease, and it plays a causal role in the development of atherosclerosis. Genome-wide association studies (GWASs) have successfully identified hundreds of genetic variants associated with LDL-C. Most of these risk loci fall in non-coding regions of the genome, and it is unclear how these non-coding variants affect circulating lipid levels.

NERINE reveals rare variant associations in gene networks across multiple phenotypes and implicates an subnetwork in Parkinson's disease.

Gene networks encapsulate biological knowledge, often linked to polygenic diseases. While model system experiments generate many plausible gene networks, validating their role in human phenotypes requires evidence from human genetics. Rare variants provide the most straightforward path for such validation.

HiDDEN: a machine learning method for detection of disease-relevant populations in case-control single-cell transcriptomics data.

In case-control single-cell RNA-seq studies, sample-level labels are transferred onto individual cells, labeling all case cells as affected, when in reality only a small fraction of them may actually be perturbed. Here, using simulations, we demonstrate that the standard approach to single cell analysis fails to isolate the subset of affected case cells and their markers when either the affected subset is small, or when the strength of the perturbation is mild. To address this fundamental limitation, we introduce HiDDEN, a computational method that refines the case-control labels to accurately reflect the perturbation status of each cell.

Convergence of coronary artery disease genes onto endothelial cell programs.

Linking variants from genome-wide association studies (GWAS) to underlying mechanisms of disease remains a challenge. For some diseases, a successful strategy has been to look for cases in which multiple GWAS loci contain genes that act in the same biological pathway. However, our knowledge of which genes act in which pathways is incomplete, particularly for cell-type-specific pathways or understudied genes.

Protein interaction networks in the vasculature prioritize genes and pathways underlying coronary artery disease.

Population-based association studies have identified many genetic risk loci for coronary artery disease (CAD), but it is often unclear how genes within these loci are linked to CAD. Here, we perform interaction proteomics for 11 CAD-risk genes to map their protein-protein interactions (PPIs) in human vascular cells and elucidate their roles in CAD. The resulting PPI networks contain interactions that are outside of known biology in the vasculature and are enriched for genes involved in immunity-related and arterial-wall-specific mechanisms.

The Role of Endothelial Cells in Atherosclerosis: Insights from Genetic Association Studies.

Endothelial cells (ECs) mediate several biological functions that are relevant to atherosclerosis and coronary artery disease (CAD), regulating an array of vital processes including vascular tone, wound healing, reactive oxygen species, shear stress response, and inflammation. Although which of these functions is linked causally with CAD development and/or progression is not yet known, genome-wide association studies have implicated more than 400 loci associated with CAD risk, among which several have shown EC-relevant functions. Given the arduous process of mechanistically interrogating single loci to CAD, high-throughput variant characterization methods, including pooled Clustered Regularly Interspaced Short Palindromic Repeats screens, offer exciting potential to rapidly accelerate the discovery of bona fide EC-relevant genetic loci.

Leveraging polygenic enrichments of gene features to predict genes underlying complex traits and diseases.

Genome-wide association studies (GWASs) are a valuable tool for understanding the biology of complex human traits and diseases, but associated variants rarely point directly to causal genes. In the present study, we introduce a new method, polygenic priority score (PoPS), that learns trait-relevant gene features, such as cell-type-specific expression, to prioritize genes at GWAS loci. Using a large evaluation set of genes with fine-mapped coding variants, we show that PoPS and the closest gene individually outperform other gene prioritization methods, but observe the best overall performance by combining PoPS with orthogonal methods.

Polygenic prediction of preeclampsia and gestational hypertension.

Preeclampsia and gestational hypertension are common pregnancy complications associated with adverse maternal and child outcomes. Current tools for prediction, prevention and treatment are limited. Here we tested the association of maternal DNA sequence variants with preeclampsia in 20,064 cases and 703,117 control individuals and with gestational hypertension in 11,027 cases and 412,788 control individuals across discovery and follow-up cohorts using multi-ancestry meta-analysis.

Multiomic Analysis and CRISPR Perturbation Screens Identify Endothelial Cell Programs and Novel Therapeutic Targets for Coronary Artery Disease.

Endothelial cells (EC) are an important mediator of atherosclerosis and vascular disease. Their exposure to atherogenic risk factors such as hypertension and serum cholesterol leads to endothelial dysfunction and many disease-associated processes. Identifying which of these multiple EC functions is causally related to disease risk has been challenging.

Discovery and systematic characterization of risk variants and genes for coronary artery disease in over a million participants.

The discovery of genetic loci associated with complex diseases has outpaced the elucidation of mechanisms of disease pathogenesis. Here we conducted a genome-wide association study (GWAS) for coronary artery disease (CAD) comprising 181,522 cases among 1,165,690 participants of predominantly European ancestry. We detected 241 associations, including 30 new loci.

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.

Deep learning enables genetic analysis of the human thoracic aorta.

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.

Rare, Damaging DNA Variants in and Risk of Coronary Artery Disease: Insights From Functional Genomics and Large-Scale Sequencing Analyses.

Background: Corin is a protease expressed in cardiomyocytes that plays a key role in salt handling and intravascular volume homeostasis via activation of natriuretic peptides. It is unknown if Corin loss-of-function (LOF) is causally associated with risk of coronary artery disease (CAD).

Methods: We analyzed all coding variants in an Italian case-control study of CAD.