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Background: Genome-wide association studies have identified hundreds of loci associated with common vascular diseases, such as coronary artery disease, myocardial infarction, and hypertension. However, the lack of mechanistic insights for many GWAS loci limits their translation into the clinic. Among these loci with unknown functions is UFL1 –four-and-a-half LIM (LIN-11, Isl-1, MEC-3) domain 5 ( FHL5 ; chr6q16.1), which reached genome-wide significance in a recent coronary artery disease/ myocardial infarction GWAS meta-analysis. UFL1-FHL5 is also associated with several vascular diseases, consistent with the widespread pleiotropy observed for GWAS loci. Methods: We apply a multimodal approach leveraging statistical fine-mapping, epigenomic profiling, and ex vivo analysis of human coronary artery tissues to implicate FHL5 as the top candidate causal gene. We unravel the molecular mechanisms of the cross-phenotype genetic associations through in vitro functional analyses and epigenomic profiling experiments in coronary artery smooth muscle cells. Results: We prioritized FHL5 as the top candidate causal gene at the UFL1-FHL5 locus through expression quantitative trait locus colocalization methods. FHL5 gene expression was enriched in the smooth muscle cells and pericyte population in human artery tissues with coexpression network analyses supporting a functional role in regulating smooth muscle cell contraction. Unexpectedly, under procalcifying conditions, FHL5 overexpression promoted vascular calcification and dysregulated processes related to extracellular matrix organization and calcium handling. Lastly, by mapping FHL5 binding sites and inferring FHL5 target gene function using artery tissue gene regulatory network analyses, we highlight regulatory interactions between FHL5 and downstream coronary artery disease/myocardial infarction loci, such as FOXL1 and FN1 that have roles in vascular remodeling. Conclusions: Taken together, these studies provide mechanistic insights into the pleiotropic genetic associations of UFL1-FHL5. We show that FHL5 mediates vascular disease risk through transcriptional regulation of downstream vascular remodeling gene programs. These transacting mechanisms may explain a portion of the heritable risk for complex vascular diseases.

Genome-wide association studies (GWAS) have identified hundreds of genetic risk loci for coronary artery disease (CAD). However, non-European populations are underrepresented in GWAS and the causal gene-regulatory mechanisms of these risk loci during atherosclerosis remain unclear. We incorporated local ancestry and haplotype information to identify quantitative trait loci (QTL) for gene expression and splicing in coronary arteries obtained from 138 ancestrally diverse Americans. Of 2,132 eQTL-associated genes (eGenes), 47% were previously unreported in coronary arteries and 19% exhibited cell-type-specific expression. Colocalization analysis with GWAS identified subgroups of eGenes unique to CAD and blood pressure. Fine-mapping highlighted additional eGenes of interest, includingTBX20andIL5. Splicing (s)QTLs for 1,690 genes were also identified, among whichTOR1AIP1andULK3sQTLs demonstrated the importance of evaluating splicing events to accurately identify disease-relevant gene expression. Our work provides the first human coronary artery eQTL resource from a patient sample and exemplifies the necessity of diverse study populations and multi-omic approaches to characterize gene regulation in critical disease processes.Study Design Overview

BACKGROUND: Activation of vascular smooth muscle cell (VSMC) inflammation is vital to initiate vascular disease. The role of human-specific long noncoding RNAs in VSMC inflammation is poorly understood. METHODS: Bulk RNA sequencing in differentiated human VSMCs revealed a novel human-specific long noncoding RNA called inflammatory MKL1 (megakaryoblastic leukemia 1) interacting long noncoding RNA ( INKILN ). INKILN expression was assessed in multiple in vitro and ex vivo models of VSMC phenotypic modulation as well as human atherosclerosis and abdominal aortic aneurysm. The transcriptional regulation of INKILN was verified through luciferase reporter and chromatin immunoprecipitation assays. Loss-of-function and gain-of-function studies and multiple RNA–protein and protein–protein interaction assays were used to uncover a mechanistic role of INKILN in the VSMC proinflammatory gene program. Bacterial artificial chromosome transgenic mice were used to study INKIL N expression and function in ligation injury–induced neointimal formation. RESULTS: INKILN expression is downregulated in contractile VSMCs and induced in human atherosclerosis and abdominal aortic aneurysm. INKILN is transcriptionally activated by the p65 pathway, partially through a predicted NF-κB (nuclear factor kappa B) site within its proximal promoter. INKILN activates proinflammatory gene expression in cultured human VSMCs and ex vivo cultured vessels. INKILN physically interacts with and stabilizes MKL1, a key activator of VSMC inflammation through the p65/NF-κB pathway. INKILN depletion blocks interleukin-1β–induced nuclear localization of both p65 and MKL1. Knockdown of INKILN abolishes the physical interaction between p65 and MKL1 and the luciferase activity of an NF-κB reporter. Furthermore, INKILN knockdown enhances MKL1 ubiquitination through reduced physical interaction with the deubiquitinating enzyme USP10 (ubiquitin-specific peptidase 10). INKILN is induced in injured carotid arteries and exacerbates ligation injury–induced neointimal formation in bacterial artificial chromosome transgenic mice. CONCLUSIONS: These findings elucidate an important pathway of VSMC inflammation involving an INKILN /MKL1/USP10 regulatory axis. Human bacterial artificial chromosome transgenic mice offer a novel and physiologically relevant approach for investigating human-specific long noncoding RNAs under vascular disease conditions.

Background: Coronary artery disease (CAD) is the leading cause of death worldwide. Recent meta-analyses of genome-wide association studies have identified over 175 loci associated with CAD. The majority of these loci are in noncoding regions and are predicted to regulate gene expression. Given that vascular smooth muscle cells (SMCs) play critical roles in the development and progression of CAD, we aimed to identify the subset of the CAD loci associated with the regulation of transcription in distinct SMC phenotypes. Methods: We measured gene expression in SMCs isolated from the ascending aortas of 151 heart transplant donors of various genetic ancestries in quiescent or proliferative conditions and calculated the association of their expression and splicing with ~6.3 million imputed single-nucleotide polymorphism markers across the genome. Results: We identified 4910 expression and 4412 splicing quantitative trait loci (sQTLs) representing regions of the genome associated with transcript abundance and splicing. A total of 3660 expression quantitative trait loci (eQTLs) had not been observed in the publicly available Genotype-Tissue Expression dataset. Further, 29 and 880 eQTLs were SMC-specific and sex-biased, respectively. We made these results available for public query on a user-friendly website. To identify the effector transcript(s) regulated by CAD loci, we used 4 distinct colocalization approaches. We identified 84 eQTL and 164 sQTL that colocalized with CAD loci, highlighting the importance of genetic regulation of mRNA splicing as a molecular mechanism for CAD genetic risk. Notably, 20% and 35% of the eQTLs were unique to quiescent or proliferative SMCs, respectively. One CAD locus colocalized with a sex-specific eQTL ( TERF2IP ), and another locus colocalized with SMC-specific eQTL ( ALKBH8 ). The most significantly associated CAD locus, 9p21, was an sQTL for the long noncoding RNA CDKN2B-AS1 , also known as ANRIL , in proliferative SMCs. Conclusions: Collectively, our results provide evidence for the molecular mechanisms of genetic susceptibility to CAD in distinct SMC phenotypes.

Objective: Reported associations between kidney risk variants (G1 and G2) in APOL1 (apolipoprotein L1), encoding APOL1, and cardiovascular disease have been conflicting. We sought to explore associations of APOL1 risk variants with cause of sudden death using the CVPath Sudden Death Autopsy Registry. Approach and Results: APOL1 haplotypes and causes of sudden death, as determined through autopsy and histopathology, were obtained for 764 Black subjects. Genotyping revealed APOL1 risk alleles in 452 of 764 (59%) subjects with 347 (77%) subjects carrying one risk allele and 105 (23%) subjects harboring 2 risk alleles. APOL1 risk allele carrier status was associated with a significantly increased risk of coronary thrombosis due to plaque rupture, versus noncarriers (odds ratio for rupture, 1.655 [95% CI, 1.079–2.539]; P =0.021). Histological examinations showed coronary plaques in carriers of 2 APOL1 risk alleles had larger necrotic cores compared with noncarriers (necrotic core area/total plaque area: 46.79%±6.47% versus 20.57%±5.11%; P =0.0343 in ruptured plaques, and 41.48%±7.49% versus 18.93%±3.97%; P =0.0342 in nonruptured plaques), and immunohistochemical and immunofluorescent staining revealed APOL1-positive areas localized primarily to the necrotic core. Conclusions: APOL1 risk alleles were independently associated with an increased risk of thrombotic coronary death due to plaque rupture. Our results suggest that carriers of both 1 and 2 APOL1 risk alleles have greater accumulation of APOL1 protein within culprit plaques and greater necrotic core sizes than noncarriers. These findings suggest that APOL1 plays a role in determining plaque stability.

BackgroundGenome-wide association studies (GWAS) have identified hundreds of loci associated with common vascular diseases such as coronary artery disease (CAD), myocardial infarction (MI), and hypertension. However, the lack of mechanistic insights for a majority of these loci limits translation of these findings into the clinic. Among these loci with unknown functions is UFL1-FHL5 (chr6q16.1), a locus that reached genome-wide significance in a recent CAD/MI GWAS meta-analysis. In addition to CAD/MI, UFL1-FHL5 is also implicated to coronary calcium, intracranial aneurysm, and migraine risk, consistent with the widespread pleiotropy observed among other GWAS loci.MethodsWe apply a multimodal approach leveraging statistical fine-mapping, epigenomic profiling, and imaging of human coronary artery tissues to implicate Four-and-a-half LIM domain 5 (FHL5) as the top candidate causal gene. We unravel the molecular mechanisms of the cross-phenotype genetic associations through in vitro functional analyses and epigenomic profiling experiments.ResultsWe prioritized FHL5 as the top candidate causal gene at the UFL1-FHL5 locus through eQTL colocalization methods. FHL5 gene expression was enriched in the SMC and pericyte population in human artery tissues with coexpression network analyses supporting a functional role in regulating SMC contraction. Unexpectedly, under procalcifying conditions, FHL5 overexpression promoted vascular calcification and dysregulated processes related to extracellular matrix organization and calcium handling. Lastly, by mapping FHL5 binding sites and inferring FHL5 target gene function using artery tissue gene regulatory network analyses, we highlight regulatory interactions between FHL5 and downstream CAD/MI loci, such as FOXL1 and FN1 that have roles in vascular remodeling.ConclusionTaken together, these studies provide mechanistic insights into the pleiotropic genetic associations of UFL1-FHL5. We show that FHL5 mediates vascular disease risk through transcriptional regulation of downstream vascular remodeling loci. These trans-acting mechanisms may account for a portion of the heritable risk for complex vascular diseases.

In this second of a 5-part Focus Seminar series, we focus on precision medicine in the context of vascular disease. The most common vascular disease worldwide is atherosclerosis, which is the primary cause of coronary artery disease, peripheral vascular disease, and a large proportion of strokes and other disorders. Atherosclerosis is a complex genetic disease that likely involves many hundreds to thousands of single nucleotide polymorphisms, each with a relatively modest effect for causing disease. Conversely, although less prevalent, there are many vascular disorders that typically involve only a single genetic change, but these changes can often have a profound effect that is sufficient to cause disease. These are termed "Mendelian vascular diseases," which include Marfan and Loeys-Dietz syndromes. Given the very different genetic basis of atherosclerosis versus Mendelian vascular diseases, this article was divided into 2 parts to cover the most promising precision medicine approaches for these disease types.

Coronary artery calcification (CAC), a measure of subclinical atherosclerosis, predicts symptomatic coronary artery disease. Identifying genetic risk factors for CAC may point to new therapeutic avenues for preventing clinical disease. Here, we conducted a multi-ancestry genome-wide association study in 26,909 individuals of European ancestry and 8,867 individuals of African American ancestry. We identified 11 independent risk loci, of which 8 are novel for CAC. Some novel loci harbor candidate causal genes supported by multiple lines of functional evidence. Together, these findings help refine the genetic architecture of CAC, extend our understanding of the biological pathways underlying CAC formation, as well as identify druggable targets for CAC.

Background: Hundreds of candidate genes have been associated with coronary artery disease (CAD) through genome-wide association studies. However, a systematic way to understand the causal mechanism(s) of these genes, and a means to prioritize them for further study, has been lacking. This represents a major roadblock for developing novel disease- and gene-specific therapies for patients with CAD. Recently, powerful integrative genomics analyses pipelines have emerged to identify and prioritize candidate causal genes by integrating tissue/cell-specific gene expression data with genome-wide association study data sets. Methods: We aimed to develop a comprehensive integrative genomics analyses pipeline for CAD and to provide a prioritized list of causal CAD genes. To this end, we leveraged several complimentary informatics approaches to integrate summary statistics from CAD genome-wide association studies (from UK Biobank and CARDIoGRAMplusC4D) with transcriptomic and expression quantitative trait loci data from 9 cardiometabolic tissue/cell types in the STARNET study (Stockholm-Tartu Atherosclerosis Reverse Network Engineering Task). Results: We identified 162 unique candidate causal CAD genes, which exerted their effect from between one and up to 7 disease-relevant tissues/cell types, including the arterial wall, blood, liver, skeletal muscle, adipose, foam cells, and macrophages. When their causal effect was ranked, the top candidate causal CAD genes were CDKN2B (associated with the 9p21.3 risk locus) and PHACTR1 ; both exerting their causal effect in the arterial wall. A majority of candidate causal genes were represented in cross-tissue gene regulatory co-expression networks that are involved with CAD, with 22/162 being key drivers in those networks. Conclusions: We identified and prioritized candidate causal CAD genes, also localizing their tissue(s) of causal effect. These results should serve as a resource and facilitate targeted studies to identify the functional impact of top causal CAD genes.

Coronary artery disease (CAD) is the leading cause of death worldwide. Recent meta-analyses of genome-wide association studies (GWAS) have identified over 175 loci associated with CAD. The majority of these loci are in non-coding regions and are predicted to regulate gene expression. Given that vascular smooth muscle cells (SMCs) play critical roles in the development and progression of CAD, we hypothesized that a subset of the CAD GWAS risk loci are associated with the regulation of transcription in distinct SMC phenotypes. Here, we measured gene expression in SMCs isolated from the ascending aortas of 151 ethnically diverse heart transplant donors in quiescent or proliferative conditions and calculated the association of their expression and splicing with ∼6.3 million imputed single nucleotide polymorphism (SNP) markers across the genome. We identified 4,910 expression and 4,412 splice quantitative trait loci (sQTL) that represent regions of the genome associated with transcript abundance and splicing. 3,660 of the eQTLs had not been observed in the publicly available Genotype-Tissue Expression dataset. Further, 29 and 880 of the eQTLs were SMC- and sex-specific, respectively. To identify the effector transcript(s) regulated by CAD GWAS loci, we used four distinct colocalization approaches and identified 84 eQTL and 164 sQTLs that colocalized with CAD loci, highlighting the importance of genetic regulation of mRNA splicing as a molecular mechanism for CAD genetic risk. Notably, 20% and 35% of the eQTLs were unique to quiescent or proliferative SMCs, respectively. Two CAD loci colocalized with a SMC sex-specific eQTL (AL160313.1 and TERF2IP) and another locus colocalized with SMC-specific eQTL (ALKBH8). Also, 27% and 37% of the sQTLs were unique to quiescent or proliferative SMCs, respectively. The most significantly associated CAD locus, 9p21, was an sQTL for the long non-coding RNA CDKN2B-AS1, also known as ANRIL, in proliferative SMCs. Collectively, these results provide evidence for the molecular mechanisms of genetic susceptibility to CAD in distinct SMC phenotypes.

BackgroundGenome-wide association studies have discovered hundreds of common genetic variants for atherosclerotic disease and cardiovascular risk factors. The translation of susceptibility loci into biological mechanisms and targets for drug discovery remains challenging. Intersecting genetic and gene expression data has led to the identification of candidate genes. However, previously studied tissues are often non-diseased and heterogeneous in cell composition, hindering accurate candidate prioritization. Therefore, we analyzed single-cell transcriptomics from atherosclerotic plaques for cell-type-specific expression to identify atherosclerosis-associated candidate gene-cell pairs.Methods and ResultsTo identify disease-associated genes, we applied gene-based analyses using GWAS summary statistics from 46 atherosclerotic and cardiovascular disease, risk factors, and other traits. We then intersected these candidates with scRNA-seq data to identify genes specific for individual cell (sub)populations in atherosclerotic plaques. The coronary artery disease loci demonstrated a prominent signal in plaque smooth muscle cells (SKI, KANK2, SORT1) p-adj. = 0.0012, and endothelial cells (SLC44A1, ATP2B1) p-adj. = 0.0011. Further sub clustering revealed genes in risk loci for coronary calcification specifically enriched in a synthetic smooth muscle cell population. Finally, we used liver-derived scRNA-seq data and showed hepatocyte-specific enrichment of genes involved in serum lipid levels.ConclusionWe discovered novel gene-cell pairs, on top of known pairs, pointing to new biological mechanisms of atherosclerotic disease. We highlight that loci associated with coronary artery disease reveal prominent association levels in mainly plaque smooth muscle and endothelial cell populations. We present an intuitive single-cell transcriptomics-driven workflow rooted in human large-scale genetic studies to identify putative candidate genes and affected cells associated with cardiovascular traits. Collectively, our workflow allows for the identification of cell-specific targets relevant for atherosclerosis and can be universally applied to other complex genetic diseases and traits.Translational perspectiveGWAS identified a large number of genomic loci associated with atherosclerotic disease. The translation of these results into drug development and faster diagnostics remains challenging. With our approach, we cross-reference the GWAS findings for atherosclerotic disease with scRNA-seq data of disease-relevant tissue and bring the GWAS findings closer to the functional and mechanistic studies.Abstract Figure

Histopathological studies have revealed key processes of atherosclerotic plaque thrombosis. However, the diversity and complexity of lesion types highlight the need for improved sub- phenotyping. We hypothesized that unbiased clustering of plaques based on gene expression results in an alternative categorization of late-stage atherosclerotic lesions.We analyzed the gene expression profiles of 654 advanced human carotid plaques. The unsupervised, transcriptome-driven clustering revealed five dominant plaque types. These novel plaque phenotypes associated with clinical presentation (pIn conclusion, the definition of the plaque at risk for a thrombotic event can be fine-tuned by in- depth transcriptomic based phenotyping. These differential plaque phenotypes prove clinically relevant for both carotid and coronary artery plaques and point to differential underlying biology of symptomatic lesions.

Background and aims The atherosclerotic plaque microenvironment is highly complex, and selective agents that modulate plaque stability are not yet available. We sought to develop a scRNA-seq analysis workflow to investigate this environment and uncover potential therapeutic approaches. We designed a user-friendly, reproducible workflow that will be applicable to other disease-specific scRNA-seq datasets. Methods Here we incorporated automated cell labeling, pseudotemporal ordering, ligand-receptor evaluation, and drug-gene interaction analysis into a ready-to-deploy workflow. We applied this pipeline to further investigate a previously published human coronary single-cell dataset by Wirka et al. Notably, we developed an interactive web application to enable further exploration and analysis of this and other cardiovascular single-cell datasets. Results We revealed distinct derivations of fibroblast-like cells from smooth muscle cells (SMCs), and showed the key changes in gene expression along their de-differentiation path. We highlighted several key ligand-receptor interactions within the atherosclerotic environment through functional expression profiling and revealed several avenues for future pharmacological development for precision medicine. Further, our interactive web application, PlaqView ( www.plaqview.com ), allows lay scientists to explore this and other datasets and compare scRNA-seq tools without prior coding knowledge. Conclusions This publicly available workflow and application will allow for more systematic and user-friendly analysis of scRNA datasets in other disease and developmental systems. Our analysis pipeline provides many hypothesis-generating tools to unravel the etiology of coronary artery disease. We also highlight potential mechanisms for several drugs in the atherosclerotic cellular environment. Future releases of PlaqView will feature more scRNA-seq and scATAC-seq atherosclerosis-related datasets to provide a critical resource for the field, and to promote data harmonization and biological interpretation.

Significance Here, we present unequivocal evidence of physical association of AMPK holoenzymes with mitochondrial reticulum (mitoAMPK) across multiple mouse tissues with evidence of conservation in human skeletal muscle and heart. We demonstrate that mitoAMPK is activated heterogeneously across the mitochondrial reticulum by mitochondrial energetic stress. Finally, we present evidence that suggests activation of mitoAMPK in skeletal muscle is required for mitophagy. We propose that mitoAMPK responds to mitochondrial microenvironment cues to maintain energetic homeostasis through mitochondrial quality control., Mitochondria form a complex, interconnected reticulum that is maintained through coordination among biogenesis, dynamic fission, and fusion and mitophagy, which are initiated in response to various cues to maintain energetic homeostasis. These cellular events, which make up mitochondrial quality control, act with remarkable spatial precision, but what governs such spatial specificity is poorly understood. Herein, we demonstrate that specific isoforms of the cellular bioenergetic sensor, 5′ AMP-activated protein kinase (AMPKα1/α2/β2/γ1), are localized on the outer mitochondrial membrane, referred to as mitoAMPK, in various tissues in mice and humans. Activation of mitoAMPK varies across the reticulum in response to energetic stress, and inhibition of mitoAMPK activity attenuates exercise-induced mitophagy in skeletal muscle in vivo. Discovery of a mitochondrial pool of AMPK and its local importance for mitochondrial quality control underscores the complexity of sensing cellular energetics in vivo that has implications for targeting mitochondrial energetics for disease treatment.

Coronary artery disease (CAD) is a complex inflammatory disease involving genetic influences across several cell types. Genome-wide association studies (GWAS) have identified over 170 loci associated with CAD, where the majority of risk variants reside in noncoding DNA sequences impacting cis -regulatory elements (CREs). Here, we applied single-cell ATAC-seq to profile 28,316 cells across coronary artery segments from 41 patients with varying stages of CAD, which revealed 14 distinct cellular clusters. We mapped over 320,000 accessible sites across all cells, identified cell type-specific elements, transcription factors, and prioritized functional CAD risk variants via quantitative trait locus and sequence-based predictive modeling. Using differential peak analyses we identified a number of candidate mechanisms for smooth muscle cell transition states (e.g. fibromyocytes). By integrating these profiles with GWAS meta-analysis summary data we resolved cell type-specific putative binding sites for the majority of CAD risk variants. In particular, we prioritized functional variants predicted to alter MEF2 binding in smooth muscle cells at the MRAS locus. We also identify variants predicted to alter macrophage-specific regulation of LIPA. We further employed DNA to gene linkage to nominate disease-associated key driver transcription factors such as PRDM16 and TBX2. Together, this single cell atlas provides a critical step towards interpreting cis -regulatory mechanisms in the vessel wall across the continuum of CAD risk.

Introduction: Coronary artery disease (CAD) is the leading cause of death worldwide with an estimated heritability of ~50%. The most recent genome wide association study (GWAS) for CAD and myocardial infarction (MI) identified over 200 loci. One such novel CAD/MI locus, UFL1-FHL5 (P = 1.1E-8), is associated with additional vascular pathologies, including hypertension, migraines, and coronary calcification. We previously showed through statistical fine-mapping that FHL5 is the top candidate causal gene underlying each of these vascular trait associations and highly enriched in the contractile mural cell populations in the artery. These preliminary studies motivate our hypothesis that FHL5 functions as a transcriptional regulator of SMC contractility to affect vascular disease risk. Methods and Results: Given the reported role of FHL5 as a cofactor, we mapped 17,201 candidate FHL5 binding sites in coronary artery SMCs using the Cleavage Under Targets and Release Using Nuclease (CUT&RUN) method. Binding sites were enriched for AP-1 family motifs and strongly overlapped CREB binding sites and H3K27ac enhancer marks. FHL5 target genes were functionally enriched in well characterized CAD pathways, such as extracellular matrix organization (P=5.2E-15, OR=2.1) and TGF-beta signaling (P=8.0E-5, OR=2.0). Interestingly, FHL5 binding sites were also enriched for CAD (P=1.8E-7, OR=2.3) and blood pressure (BP) risk variants (P=0.04, OR=1.2), thereby linking FHL5 with the regulation of multiple downstream CAD/BP loci. Weighted gene co-expression network and key driver analyses of human coronary artery transcriptomic data further support this regulatory role. Lastly, we validated these findings by performing confocal based calcium imaging and collagen gel contraction assays. Consistent with our functional genomic analyses, overexpression of FHL5 elevated intracellular calcium levels 2.5X and increased SMC contractility by ~45%. Conclusion: Taken together, our results provide evidence that FHL5 may impact CAD risk by regulating a network of disease-associated genes mediating SMC functions. These findings further contribute to our understanding of the heritable risk for multiple vascular diseases.

Coronary artery disease (CAD) is a complex inflammatory disease involving genetic influences across several cell types. Genome-wide association studies (GWAS) have identified over 170 loci associated with CAD, where the majority of risk variants reside in noncoding DNA sequences impacting cis-regulatory elements (CREs). Here, we applied single-cell ATAC-seq to profile 28,316 cells across coronary artery segments from 41 patients with varying stages of CAD, which revealed 14 distinct cellular clusters. We mapped ~320,000 accessible sites across all cells, identified cell type-specific elements, transcription factors, and prioritized functional CAD risk variants via quantitative trait locus and sequence-based predictive modeling. We identified a number of candidate mechanisms for smooth muscle cell transition states and identified putative binding sites for risk variants. We further employed CRE to gene linkage to nominate disease-associated key driver transcription factors such as PRDM16 and TBX2. This single cell atlas provides a critical step towards interpreting cis-regulatory mechanisms in the vessel wall across the continuum of CAD risk.

Coronary artery disease (CAD) is a complex inflammatory disease involving genetic influences across cell types. Genome-wide association studies have identified over 200 loci associated with CAD, where the majority of risk variants reside in noncoding DNA sequences impacting cis-regulatory elements. Here, we applied single-nucleus assay for transposase-accessible chromatin with sequencing to profile 28,316 nuclei across coronary artery segments from 41 patients with varying stages of CAD, which revealed 14 distinct cellular clusters. We mapped ~320,000 accessible sites across all cells, identified cell-type-specific elements and transcription factors, and prioritized functional CAD risk variants. We identified elements in smooth muscle cell transition states (for example, fibromyocytes) and functional variants predicted to alter smooth muscle cell- and macrophage-specific regulation of MRAS (3q22) and LIPA (10q23), respectively. We further nominated key driver transcription factors such as PRDM16 and TBX2. Together, this single-nucleus atlas provides a critical step towards interpreting regulatory mechanisms across the continuum of CAD risk.

Aims De-differentiation and activation of pro-inflammatory pathways are key transitions vascular smooth muscle cells (SMCs) make during atherogenesis. Here, we explored the upstream regulators of this 'atherogenic transition'. Methods and results Genome-wide sequencing studies, including ATAC-seq (Assay for Transposase-Accessible Chromatin using sequencing) and RNA-seq, were performed on cells isolated from both murine SMC-lineage tracing models of atherosclerosis and human atherosclerotic lesions. At the bulk level, alterations in chromatin accessibility were associated with the atherogenic transitioning of lesional SMCs, especially in relation to genes that govern differentiation status and complement-dependent inflammation. Using computational biology, we observed that a transcription factor previously related to coronary artery disease, ATF3 (Activating transcription factor 3), was predicted to be an upstream regulator of genes altered during the transition. At the single-cell level, our results indicated that ATF3 is a key repressor of SMC transitioning towards the subset of cells that promote vascular inflammation by activating the complement cascade. The expression of ATF3 and complement component C3 were negatively correlated in SMCs from human atherosclerotic lesions, suggesting translational relevance. Phenome-wide association studies indicated that genetic variation that results in reduced expression of ATF3 is correlated with an increased risk for atherosclerosis, and the expression of ATF3 was significantly downregulated in humans with advanced vascular disease. Conclusion Our study indicates that the plasticity of atherosclerotic SMCs may in part be explained by dynamic changes in their chromatin architecture, which in turn may contribute to their maladaptive response to inflammation-induced stress. Translational perspective The recent CANTOS and COLCOT trials have shown that targeting inflammatory pathways lowers the risk of major adverse cardiovascular events. However, more specific targets are needed to avoid immunosuppressive side effects. Our data identify an upstream regulator of pro-inflammatory SMCs, ATF3, which is involved in the initial atherogenic transitioning of lesional SMCs. Restoring ATF3 activity may prevent the de-differentiation of SMCs and offer a novel translational approach for the suppression of complement-dependent inflammation in atherosclerotic lesions.

In response to various stimuli, vascular smooth muscle cells (SMCs) can de-differentiate, proliferate and migrate in a process known as phenotypic modulation. However, the phenotype of modulated SMCs in vivo during atherosclerosis and the influence of this process on coronary artery disease (CAD) risk have not been clearly established. Using single-cell RNA sequencing, we comprehensively characterized the transcriptomic phenotype of modulated SMCs in vivo in atherosclerotic lesions of both mouse and human arteries and found that these cells transform into unique fibroblast-like cells, termed 'fibromyocytes', rather than into a classical macrophage phenotype. SMC-specific knockout of TCF21-a causal CAD gene-markedly inhibited SMC phenotypic modulation in mice, leading to the presence of fewer fibromyocytes within lesions as well as within the protective fibrous cap of the lesions. Moreover, TCF21 expression was strongly associated with SMC phenotypic modulation in diseased human coronary arteries, and higher levels of TCF21 expression were associated with decreased CAD risk in human CAD-relevant tissues. These results establish a protective role for both TCF21 and SMC phenotypic modulation in this disease.

Background: More than 90% of individuals with Noonan syndrome (NS) with mutations clustered in the CR2 domain of RAF1 present with severe and often lethal hypertrophic cardiomyopathy (HCM). The signaling pathways by which NS RAF1 mutations promote HCM remain elusive, and so far, there is no known treatment for NS-associated HCM. Methods: We used patient-derived RAF1 S257L/+ and CRISPR-Cas9–generated isogenic control inducible pluripotent stem cell (iPSC)–derived cardiomyocytes to model NS RAF1 -associated HCM and to further delineate the molecular mechanisms underlying the disease. Results: We show that mutant iPSC–derived cardiomyocytes phenocopy the pathology seen in hearts of patients with NS by exhibiting hypertrophy and structural defects. Through pharmacological and genetic targeting, we identify 2 perturbed concomitant pathways that, together, mediate HCM in RAF1 mutant iPSC–derived cardiomyocytes. Hyperactivation of mitogen-activated protein kinase kinase 1/2 (MEK1/2), but not extracellular regulated kinase 1/2, causes myofibrillar disarray, whereas the enlarged cardiomyocyte phenotype is a direct consequence of increased extracellular regulated kinase 5 (ERK5) signaling, a pathway not previously known to be involved in NS. RNA-sequencing reveals genes with abnormal expression in RAF1 mutant iPSC–derived cardiomyocytes and identifies subsets of genes dysregulated by aberrant MEK1/2 or ERK5 pathways that could contribute to the NS-associated HCM. Conclusions: Taken together, the results of our study identify the molecular mechanisms by which NS RAF1 mutations cause HCM and reveal downstream effectors that could serve as therapeutic targets for treatment of NS and perhaps other, more common, congenital HCM disorders.

Aims While most patients with myocardial infarction (MI) have underlying coronary atherosclerosis, not all patients with coronary artery disease (CAD) develop MI. We sought to address the hypothesis that some of the genetic factors which establish atherosclerosis may be distinct from those that predispose to vulnerable plaques and thrombus formation. Methods and results We carried out a genome-wide association study for MI in the UK Biobank (n∼472 000), followed by a meta-analysis with summary statistics from the CARDIoGRAMplusC4D Consortium (n∼167 000). Multiple independent replication analyses and functional approaches were used to prioritize loci and evaluate positional candidate genes. Eight novel regions were identified for MI at the genome wide significance level, of which effect sizes at six loci were more robust for MI than for CAD without the presence of MI. Confirmatory evidence for association of a locus on chromosome 1p21.3 harbouring choline-like transporter 3 (SLC44A3) with MI in the context of CAD, but not with coronary atherosclerosis itself, was obtained in Biobank Japan (n∼165 000) and 16 independent angiography-based cohorts (n∼27 000). Follow-up analyses did not reveal association of the SLC44A3 locus with CAD risk factors, biomarkers of coagulation, other thrombotic diseases, or plasma levels of a broad array of metabolites, including choline, trimethylamine N-oxide, and betaine. However, aortic expression of SLC44A3 was increased in carriers of the MI risk allele at chromosome 1p21.3, increased in ischaemic (vs. non-diseased) coronary arteries, up-regulated in human aortic endothelial cells treated with interleukin-1β (vs. vehicle), and associated with smooth muscle cell migration in vitro. Conclusions A large-scale analysis comprising ∼831 000 subjects revealed novel genetic determinants of MI and implicated SLC44A3 in the pathophysiology of vulnerable plaques.

Summary Despite the emerging evidence implying early vascular contributions to neurodegenerative syndromes, the role of vascular smooth muscle cells (VSMCs) in the pathogenesis of Alzheimer disease (AD) is still not well understood. Herein, we show that VSMCs in brains of patients with AD and animal models of the disease are deficient in multiple VSMC contractile markers which correlated with Tau accumulation in brain arterioles. Ex vivo and in vitro experiments demonstrated that VSMCs undergo dramatic phenotypic transitions under AD-like conditions, adopting pro-inflammatory phenotypes. Notably, these changes coincided with Tau hyperphosphorylation at residues Y18, T205, and S262. We also observed that VSMC dysfunction occurred in an age-dependent manner and that expression of Sm22α protein was inversely correlated with CD68 and Tau expression in brain arterioles of the 3xTg-AD and 5xFAD mice. Together, these findings further support the contribution of dysfunctional VSMCs in AD pathogenesis and nominate VSMCs as a potential therapeutic target in AD., Graphical abstract, Highlights • Loss of VSMC contractile phenotypes correlates with Tau accumulation in brain arterioles • VSMC dysfunction promotes the hyperphosphorylation of Tau protein at multiple residues • VSMC dysfunction occurs in an age-dependent manner in brain arterioles of patients with AD • Vascular smooth muscle cell is a promising therapeutic target in AD, Molecular neuroscience; Immunology; Omics

Viruses such as SARS-CoV-2 infect the human body by forming interactions between virus proteins and human proteins. However, experimental methods to find protein interactions are inadequate: large scale experiments are noisy, and small scale experiments are slow and expensive. Inspired by the recent successes of deep neural networks, we hypothesize that deep learning methods are well-positioned to aid and augment biological experiments, hoping to help identify more accurate virus-host protein interaction maps. Moreover, computational methods can quickly adapt to predict how virus mutations change protein interactions with the host proteins.We propose DeepVHPPI, a novel deep learning framework combining a self-attention-based transformer architecture and a transfer learning training strategy to predict interactions between human proteins and virus proteins that have novel sequence patterns. We show that our approach outperforms the state-of-the-art methods significantly in predicting Virus–Human protein interactions for SARS-CoV-2, H1N1, and Ebola. In addition, we demonstrate how our framework can be used to predict and interpret the interactions of mutated SARS-CoV-2 Spike protein sequences.AvailabilityWe make all of our data and code available on GitHub https://github.com/QData/DeepVHPPI.ACM Reference FormatJack Lanchantin, Tom Weingarten, Arshdeep Sekhon, Clint Miller, and Yanjun Qi. 2021. Transfer Learning for Predicting Virus-Host Protein Interactions for Novel Virus Sequences. In Proceedings of ACM Conference (ACM-BCB). ACM, New York, NY, USA, 10 pages. https://doi.org/??

In this second of a 5-part Focus Seminar series, we focus on precision medicine in the context of vascular disease. The most common vascular disease worldwide is atherosclerosis, which is the primary cause of coronary artery disease, peripheral vascular disease, and a large proportion of strokes and other disorders. Atherosclerosis is a complex genetic disease that likely involves many hundreds to thousands of single nucleotide polymorphisms, each with a relatively modest effect for causing disease. Conversely, although less prevalent, there are many vascular disorders that typically involve only a single genetic change, but these changes can often have a profound effect that is sufficient to cause disease. These are termed “Mendelian vascular diseases,” which include Marfan and Loeys-Dietz syndromes. Given the very different genetic basis of atherosclerosis versus Mendelian vascular diseases, this article was divided into 2 parts to cover the most promising precision medicine approaches for these disease types.

Background and AimsThe atherosclerotic plaque microenvironment is highly complex, and selective agents that modulate plaque stability or other plaque phenotypes are not yet available. We sought to investigate the human atherosclerotic cellular environment using scRNA-seq to uncover potential therapeutic approaches. We aimed to make our workflow user-friendly, reproducible, and applicable to other disease-specific scRNA-seq datasets.MethodsHere we incorporate automated cell labeling, pseudotemporal ordering, ligand-receptor evaluation, and drug-gene interaction analysis into an enhanced and reproducible scRNA-seq analysis workflow. Notably, we also developed an R Shiny based interactive web application to enable further exploration and analysis of the scRNA dataset.ResultsWe applied this analysis workflow to a human coronary artery scRNA dataset and revealed distinct derivations of chondrocyte-like and fibroblast-like cells from smooth muscle cells (SMCs), and show the key changes in gene expression along their de-differentiation path. We highlighted several key ligand-receptor interactions within the atherosclerotic environment through functional expression profiling and revealed several attractive avenues for future pharmacological repurposing in precision medicine. Further, our interactive web application, PlaqView (www.plaqview.com), allows other researchers to easily explore this dataset and benchmark applicable scRNA-seq analysis tools without prior coding knowledge.ConclusionsThese results suggest novel effects of chemotherapeutics on the atherosclerotic cellular environment and provide future avenues of studies in precision medicine. This publicly available workflow will also allow for more systematic and user-friendly analysis of scRNA datasets in other disease and developmental systems. PlaqView allows for rapid visualization and analysis of atherosclerosis scRNA-seq datasets without the need of prior coding experience. Future releases of PlaqView will feature additional larger scRNA-seq and scATAC-seq atherosclerosis-related datasets, thus providing a critical resource for the field by promoting data harmonization and biological interpretation.