Decoding the transcriptome of calcified atherosclerotic plaque at single-cell resolution

scGAA: a general gated axial-attention model for accurate cell-type annotation of single-cell RNA-seq data

Single-cell RNA sequencing (scRNA-seq) is a key technology for investigating cell development and analysing cell diversity across various diseases. However, the high dimensionality and extreme sparsity of scRNA-seq data pose great challenges for accurate cell type annotation. To address this, we developed a new cell-type annotation model called scGAA (general gated axial-attention model for accurate cell-type annotation of scRNA-seq). Based on the transformer framework, the model decomposes the traditional self-attention mechanism into horizontal and vertical attention, considerably improving computational efficiency. This axial attention mechanism can process high-dimensional data more efficiently while maintaining reasonable model complexity. Additionally, the gated unit was integrated into the model to enhance the capture of relationships between genes, which is crucial for achieving an accurate cell type annotation. The results revealed that our improved transformer model is a promising tool for practical applications. This theoretical innovation increased the model performance and provided new insights into analytical tools for scRNA-seq data.

Breaking New Ground: Unraveling the USP1/ID3/E12/P21 Axis in Vascular Calcification

Vascular calcification (VC) poses significant challenges in cardiovascular health. This study employs single-cell transcriptome sequencing to dissect cellular dynamics in this process. We identify distinct cell subgroups, notably in vascular smooth muscle cells (VSMCs), and observe differences between calcified atherosclerotic cores and adjacent regions. Further exploration reveals ID3 as a key gene regulating VSMC function. In vitro experiments demonstrate ID3's interaction with USP1 and E12, modulating cell proliferation and osteogenic differentiation. Animal models confirm the critical role of the USP1/ID3/E12/P21 axis in VC. This study sheds light on a novel regulatory mechanism, offering potential therapeutic targets.

Integrated multi-omic high-throughput strategies across-species identified potential key diagnostic, prognostic, and therapeutic targets for atherosclerosis under high glucose conditions

Diabetes is a well-known risk factor for atherosclerosis (AS), but the underlying molecular mechanism remains unknown. The dysregulated immune response is an important reason. High glucose is proven to induce foam cell formation under lipidemia situations in clinical patients. Exploring the potential regulatory programs of accelerated foam cell formation stimulated by high glucose is meaningful. Macrophage-derived foam cells were induced in vitro, and high-throughput sequencing was performed. Coexpression gene modules were constructed using weighted gene co-expression network analysis (WGCNA). Highly related modules were identified. Hub genes were identified by multiple integrative strategies. The potential roles of selected genes were further validated in bulk-RNA and scRNA datasets of human plaques. By transfection of the siRNA, the role of the screened gene during foam cell formation was further explored. Two modules were found to be both positively related to high glucose and ox-LDL. Further enrichment analyses confirmed the association between the brown module and AS. The high correlation between the brown module and macrophages was identified and 4 hub genes (Aldoa, Creg1, Lgmn, and Pkm) were screened. Further validation in external bulk-RNA and scRNA revealed the potential diagnostic and therapeutic value of selected genes. In addition, the survival analysis confirmed the prognostic value of Aldoa while knocking down Aldoa expression alleviated the foam cell formation in vitro. We systematically investigated the synergetic effects of high glucose and ox-LDL during macrophage-derived foam cell formation and identified that ALDOA might be an important diagnostic, prognostic, and therapeutic target in these patients.

The pro-atherogenic enzyme PAPP-A is active in eluates from human carotid and femoral atherosclerotic plaques

Background

Pregnancy-associated plasma protein-A (PAPP-A) regulates bioavailability of insulin-like growth factor 1 (IGF1) in various tissues by proteolytic cleavage of a subset of IGF-binding proteins (IGFBPs). Pre-clinical studies have established a role of PAPP-A in atherosclerosis and proposed that targeting the proteolytic activity of PAPP-A has therapeutic value.This study aimed to investigate whether human atherosclerotic plaques contain proteolytically active PAPP-A, a prerequisite for further considering PAPP-A as a therapeutic target in patients.

Methods

We obtained carotid (n = 9) and femoral (n = 11) atherosclerotic plaques from patients undergoing vascular surgery and incubated freshly harvested plaque tissue in culture media for 24 h. Subsequently, conditioned media were assayed for PAPP-A, STC2, IGFBP4, and IGF1 using immunoassays. Enzymatic activity of PAPP-A was assessed by its ability to process recombinant IGFBP4-IGF1 complexes - a specific substrate of PAPP-A - by Western blotting.

Results

PAPP-A and STC2 were detectable in conditioned media from both carotid and femoral plaques, with higher STC2 concentrations in eluates from carotid plaque incubations (p = 0.02). IGFBP4 and IGF1 were undetectable. Conditioned media from all 20 plaques exhibited PAPP-A proteolytic activity. However, no correlation between PAPP-A concentration and its proteolytic activity was observed, whereas the PAPP-A: STC2 molar ratio correlated with PAPP-A activity (R2 = 0.25, p = 0.03).

Conclusion

This study provides evidence for the presence of enzymatically active PAPP-A in atherosclerotic plaques and underscores the need for further investigating potential beneficial effects associated with targeting PAPP-A in atherosclerotic cardiovascular disease.

scPriorGraph: constructing biosemantic cell-cell graphs with prior gene set selection for cell type identification from scRNA-seq data

Cell type identification is an indispensable analytical step in single-cell data analyses. To address the high noise stemming from gene expression data, existing computational methods often overlook the biologically meaningful relationships between genes, opting to reduce all genes to a unified data space. We assume that such relationships can aid in characterizing cell type features and improving cell type recognition accuracy. To this end, we introduce scPriorGraph, a dual-channel graph neural network that integrates multi-level gene biosemantics. Experimental results demonstrate that scPriorGraph effectively aggregates feature values of similar cells using high-quality graphs, achieving state-of-the-art performance in cell type identification.

Human atherosclerotic plaque transcriptomics reveals endothelial beta-2 spectrin as a potential regulator a leaky plaque microvasculature phenotype

The presence of atherosclerotic plaque vessels is a critical factor in plaque destabilization. This may be attributable to the leaky phenotype of these microvessels, although direct proof for this notion is lacking. In this study, we investigated molecular and cellular patterns of stable and hemorrhaged human plaque to identify novel drivers of intraplaque vessel dysfunction. From transcriptome data of a human atherosclerotic lesion cohort, we reconstructed a co-expression network, identifying a gene module strongly and selectively correlated with both plaque microvascular density and inflammation. Spectrin Beta Non-Erythrocytic 1 (sptbn1) was identified as one of the central hubs of this module (along with zeb1 and dock1) and was selected for further study based on its predominant endothelial expression. Silencing of sptbn1 enhanced leukocyte transmigration and vascular permeability in vitro, characterized by an increased number of focal adhesions and reduced junctional VE-cadherin. In vivo, sptbn1 knockdown in zebrafish impaired the development of the caudal vein plexus. Mechanistically, increased substrate stiffness was associated with sptbn1 downregulation in endothelial cells in vitro and in human vessels. Plaque SPTBN1 mRNA and protein expression were found to correlate with an enhanced presence of intraplaque hemorrhage and future cardiovascular disease (CVD) events during follow-up. In conclusion, we identify SPTBN1 as a central hub gene in a gene program correlating with plaque vascularisation. SPTBN1 was regulated by substrate stiffness in vitro while silencing blocked vascular development in vivo, and compromised barrier function in vitro. Together, SPTBN1 is identified as a new potential regulator of the leaky phenotype of atherosclerotic plaque microvessels.

Smooth muscle expression of RNA editing enzyme ADAR1 controls vascular integrity and progression of atherosclerosis

Mapping the genomic architecture of complex disease has been predicated on the understanding that genetic variants influence disease risk through modifying gene expression. However, recent discoveries have revealed that a significant burden of disease heritability in common autoinflammatory disorders and coronary artery disease is mediated through genetic variation modifying post-transcriptional modification of RNA through adenosine-to-inosine (A-to-I) RNA editing. This common RNA modification is catalyzed by ADAR enzymes, where ADAR1 edits specific immunogenic double stranded RNA (dsRNA) to prevent activation of the double strand RNA (dsRNA) sensor MDA5 ( IFIH1 ) and stimulation of an interferon stimulated gene (ISG) response. Multiple lines of human genetic data indicate impaired RNA editing and increased dsRNA sensing to be an important mechanism of coronary artery disease (CAD) risk. Here, we provide a crucial link between observations in human genetics and mechanistic cell biology leading to progression of CAD. Through analysis of human atherosclerotic plaque, we implicate the vascular smooth muscle cell (SMC) to have a unique requirement for RNA editing, and that ISG induction occurs in SMC phenotypic modulation, implicating MDA5 activation. Through culture of human coronary artery SMCs, generation of a conditional SMC specific Adar1 deletion mouse model on a pro-atherosclerosis background, and with incorporation of single cell RNA sequencing cellular profiling, we further show that Adar1 controls SMC phenotypic state, is required to maintain vascular integrity, and controls progression of atherosclerosis and vascular calcification. Through this work, we describe a fundamental mechanism of CAD, where cell type and context specific RNA editing and sensing of dsRNA mediates disease progression, bridging our understanding of human genetics and disease causality.

Genome-scale metabolic network of human carotid plaque reveals the pivotal role of glutamine/glutamate metabolism in macrophage modulating plaque inflammation and vulnerability

BACKGROUND

Metabolism is increasingly recognized as a key regulator of the function and phenotype of the primary cellular constituents of the atherosclerotic vascular wall, including endothelial cells, smooth muscle cells, and inflammatory cells. However, a comprehensive analysis of metabolic changes associated with the transition of plaque from a stable to a hemorrhaged phenotype is lacking.

METHODS

In this study, we integrated two large mRNA expression and protein abundance datasets (BIKE, n = 126; MaasHPS, n = 43) from human atherosclerotic carotid artery plaque to reconstruct a genome-scale metabolic network (GEM). Next, the GEM findings were linked to metabolomics data from MaasHPS, providing a comprehensive overview of metabolic changes in human plaque.

RESULTS

Our study identified significant changes in lipid, cholesterol, and inositol metabolism, along with altered lysosomal lytic activity and increased inflammatory activity, in unstable plaques with intraplaque hemorrhage (IPH+) compared to non-hemorrhaged (IPH-) plaques. Moreover, topological analysis of this network model revealed that the conversion of glutamine to glutamate and their flux between the cytoplasm and mitochondria were notably compromised in hemorrhaged plaques, with a significant reduction in overall glutamate levels in IPH+ plaques. Additionally, reduced glutamate availability was associated with an increased presence of macrophages and a pro-inflammatory phenotype in IPH+ plaques, suggesting an inflammation-prone microenvironment.

CONCLUSIONS

This study is the first to establish a robust and comprehensive GEM for atherosclerotic plaque, providing a valuable resource for understanding plaque metabolism. The utility of this GEM was illustrated by its ability to reliably predict dysregulation in the cholesterol hydroxylation, inositol metabolism, and the glutamine/glutamate pathway in rupture-prone hemorrhaged plaques, a finding that may pave the way to new diagnostic or therapeutic measures.

A Novel Macrophage Subpopulation Conveys Increased Genetic Risk of Coronary Artery Disease

BACKGROUND

Coronary artery disease (CAD), the leading cause of death worldwide, is influenced by both environmental and genetic factors. Although over 250 genetic risk loci have been identified through genome-wide association studies, the specific causal variants and their regulatory mechanisms are still largely unknown, particularly in disease-relevant cell types such as macrophages.

METHODS

We utilized single-cell RNA-seq and single-cell multiomics approaches in primary human monocyte-derived macrophages to explore the transcriptional regulatory network involved in a critical pathogenic event of coronary atherosclerosis-the formation of lipid-laden foam cells. The relative genetic contribution to CAD was assessed by partitioning disease heritability across different macrophage subpopulations. Meta-analysis of single-cell RNA-seq data sets from 38 human atherosclerotic samples was conducted to provide high-resolution cross-referencing to macrophage subpopulations in vivo.

RESULTS

We identified 18 782 cis-regulatory elements by jointly profiling the gene expression and chromatin accessibility of >5000 macrophages. Integration with CAD genome-wide association study data prioritized 121 CAD-related genetic variants and 56 candidate causal genes. We showed that CAD heritability was not uniformly distributed and was particularly enriched in the gene programs of a novel CD52-hi lipid-handling macrophage subpopulation. These CD52-hi macrophages displayed significantly less lipoprotein accumulation and were also found in human atherosclerotic plaques. We investigated the cis-regulatory effect of a risk variant rs10488763 on FDX1, implicating the recruitment of AP-1 and C/EBP-β in the causal mechanisms at this locus.

CONCLUSIONS

Our results provide genetic evidence of the divergent roles of macrophage subsets in atherogenesis and highlight lipid-handling macrophages as a key subpopulation through which genetic variants operate to influence disease. These findings provide an unbiased framework for functional fine-mapping of genome-wide association study results using single-cell multiomics and offer new insights into the genotype-environment interactions underlying atherosclerotic disease.

Osteopontin/SPP1: a potential mediator between immune cells and vascular calcification

Vascular calcification (VC) is considered a common pathological process in various vascular diseases. Accumulating studies have confirmed that VC is involved in the inflammatory response in heart disease, and SPP1+ macrophages play an important role in this process. In VC, studies have focused on the physiological and pathological functions of macrophages, such as pro-inflammatory or anti-inflammatory cytokines and pro-fibrotic vesicles. Additionally, macrophages and activated lymphocytes highly express SPP1 in atherosclerotic plaques, which promote the formation of fatty streaks and plaque development, and SPP1 is also involved in the calcification process of atherosclerotic plaques that results in heart failure, but the crosstalk between SPP1-mediated immune cells and VC has not been adequately addressed. In this review, we summarize the regulatory effect of SPP1 on VC in T cells, macrophages, and dendritic cells in different organs' VC, which could be a potential therapeutic target for VC.

Deciphering smooth muscle cell heterogeneity in atherosclerotic plaques and constructing model: a multi-omics approach with focus on KLF15/IGFBP4 axis

BACKGROUND

Ruptured atherosclerotic plaques often precipitate severe ischemic events, such as stroke and myocardial infarction. Unraveling the intricate molecular mechanisms governing vascular smooth muscle cell (VSMC) behavior in plaque stabilization remains a formidable challenge.

METHODS

In this study, we leveraged single-cell and transcriptomic datasets from atherosclerotic plaques retrieved from the gene expression omnibus (GEO) database. Employing a combination of single-cell population differential analysis, weighted gene co-expression network analysis (WGCNA), and transcriptome differential analysis techniques, we identified specific genes steering the transformation of VSMCs in atherosclerotic plaques. Diagnostic models were developed and validated through gene intersection, utilizing the least absolute shrinkage and selection operator (LASSO) and random forest (RF) methods. Nomograms for plaque assessment were constructed. Tissue localization and expression validation were performed on specimens from animal models, utilizing immunofluorescence co-localization, western blot, and reverse-transcription quantitative-polymerase chain reaction (RT-qPCR). Various online databases were harnessed to predict transcription factors (TFs) and their interacting compounds, with determination of the cell-specific localization of TF expression using single-cell data.

RESULTS

Following rigorous quality control procedures, we obtained a total of 40,953 cells, with 6,261 representing VSMCs. The VSMC population was subsequently clustered into 5 distinct subpopulations. Analyzing inter-subpopulation cellular communication, we focused on the SMC2 and SMC5 subpopulations. Single-cell subpopulation and WGCNA analyses revealed significant module enrichments, notably in collagen-containing extracellular matrix and cell-substrate junctions. Insulin-like growth factor binding protein 4 (IGFBP4), apolipoprotein E (APOE), and cathepsin C (CTSC) were identified as potential diagnostic markers for early and advanced plaques. Notably, gene expression pattern analysis suggested that IGFBP4 might serve as a protective gene, a hypothesis validated through tissue localization and expression analysis. Finally, we predicted TFs capable of binding to IGFBP4, with Krüppel-like family 15 (KLF15) emerging as a prominent candidate showing relative specificity within smooth muscle cells. Predictions about compounds associated with affecting KLF15 expression were also made.

CONCLUSION

Our study established a plaque diagnostic and assessment model and analyzed the molecular interaction mechanisms of smooth muscle cells within plaques. Further analysis revealed that the transcription factor KLF15 may regulate the biological behaviors of smooth muscle cells through the KLF15/IGFBP4 axis, thereby influencing the stability of advanced plaques via modulation of the PI3K-AKT signaling pathway. This could potentially serve as a target for plaque stability assessment and therapy, thus driving advancements in the management and treatment of atherosclerotic plaques.

Single-cell senescence identification reveals senescence heterogeneity, trajectory, and modulators

Cellular senescence underlies many aging-related pathologies, but its heterogeneity poses challenges for studying and targeting senescent cells. We present here a machine learning program senescent cell identification (SenCID), which accurately identifies senescent cells in both bulk and single-cell transcriptome. Trained on 602 samples from 52 senescence transcriptome datasets spanning 30 cell types, SenCID identifies six major senescence identities (SIDs). Different SIDs exhibit different senescence baselines, stemness, gene functions, and responses to senolytics. SenCID enables the reconstruction of senescent trajectories under normal aging, chronic diseases, and COVID-19. Additionally, when applied to single-cell Perturb-seq data, SenCID helps reveal a hierarchy of senescence modulators. Overall, SenCID is an essential tool for precise single-cell analysis of cellular senescence, enabling targeted interventions against senescent cells.

KLF13 promotes VSMCs phenotypic dedifferentiation by directly binding to the SM22α promoter

Krüppel-like factor 13 (KLF13), a zinc finger transcription factor, is considered as a potential regulator of cardiomyocyte differentiation and proliferation during heart morphogenesis. However, its precise role in the dedifferentiation of vascular smooth muscle cells (VSMCs) during atherosclerosis and neointimal formation after injury remains poorly understood. In this study, we investigated the relationship between KLF13 and SM22α expression in normal and atherosclerotic plaques by bioanalysis, and observed a significant increase in KLF13 levels in the atherosclerotic plaques of both human patients and ApoE-/- mice. Knockdown of KLF13 was found to ameliorate intimal hyperplasia following carotid artery injury. Furthermore, we discovered that KLF13 directly binds to the SM22α promoter, leading to the phenotypic dedifferentiation of VSMCs. Remarkably, we observed a significant inhibition of platelet-derived growth factor BB-induced VSMCs dedifferentiation, proliferation, and migration when knocked down KLF13 in VSMCs. This inhibitory effect of KLF13 knockdown on VCMC function was, at least in part, mediated by the inactivation of p-AKT signaling in VSMCs. Overall, our findings shed light on a potential therapeutic target for treating atherosclerotic lesions and restenosis after vascular injury.

Unveiling Atherosclerotic Plaque Heterogeneity and SPP1+/VCAN+ Macrophage Subtype Prognostic Significance Through Integrative Single-Cell and Bulk-Seq Analysis

Background

Dysregulated macrophages are important causes of Atherosclerosis (AS) formation and increased plaque instability, but the heterogeneity of these plaques and the role of macrophage subtypes in plaque instability have yet to be clarified.

Methods

This study integrates single-cell and bulk-seq data to analyze atherosclerotic plaques. Unsupervised clustering was used to reveal distinct plaque subtypes, while survival analysis and gene set variation analysis (GSVA) methods helped in understanding their clinical outcomes. Enrichment of differential expression of macrophage genes (DEMGs) score and pseudo-trajectory analysis were utilized to explore the biological functions and differentiation stages of macrophage subtypes in AS progression. Additionally, CellChat and the BayesPrism deconvolution method were used to elucidate macrophage subtype interaction and their prognostic significance at single-cell resolution. Finally, the expression of biomarkers was validated in mouse experiments.

Results

Three distinct AS plaque subtypes were identified, with cluster 3 plaque subtype being particularly associated with higher immune infiltration and poorer prognosis. The DEMGs score exhibited a significant elevation in three macrophage subtypes (SPP1+/VCAN+ macrophages, IL1B+ macrophages, and FLT3LG+ macrophages), associated with cluster 3 plaque subtype and highlighted the prognostic significance of these subtypes. Activation trajectory of the macrophage subtypes is divided into three states (Pre-branch, Cell fate 1, and Cell fate 2), and Cell fate 2 (SPP1+/VCAN+ macrophages, IL1B+ macrophages, and FLT3LG+ macrophages dominant) exhibiting the highest DEMGs score, distinct interactions with other cell components, and relating to poorer prognosis of ischemic events. This study also uncovered a unique SPP1+/VCAN+ macrophage subtype, rare in quantity but significant in influencing AS progression. Machine learning algorithms identified 10 biomarkers crucial for AS diagnosis. The validation of these biomarkers was performed using Mendelian Randomization analysis and in vitro methods, supporting their relevance in AS pathology.

Conclusion

Our study provides a comprehensive view of AS plaque heterogeneity and the prognostic significance of macrophage subtypes in plaque instability.

RSAD2 is abundant in atherosclerotic plaques and promotes interferon-induced CXCR3-chemokines in human smooth muscle cells

In atherosclerotic lesions, monocyte-derived macrophages are major source of interferon gamma (IFN-γ), a pleotropic cytokine known to regulate the expression of numerous genes, including the antiviral gene RSAD2. While RSAD2 was reported to be expressed in endothelial cells of human carotid lesions, its significance for the development of atherosclerosis remains utterly unknown. Here, we harnessed publicly available human carotid atherosclerotic data to explore RSAD2 in lesions and employed siRNA-mediated gene-knockdown to investigate its function in IFN-γ-stimulated human aortic smooth muscle cells (hAoSMCs). Silencing RSAD2 in IFN-γ-stimulated hAoSMCs resulted in reduced expression and secretion of key CXCR3-chemokines, CXCL9, CXCL10, and CXCL11. Conditioned medium from RSAD2-deficient hAoSMCs exhibited diminished monocyte attraction in vitro compared to conditioned medium from control cells. Furthermore, RSAD2 transcript was elevated in carotid lesions where it was expressed by several different cell types, including endothelial cells, macrophages and smooth muscle cells. Interestingly, RSAD2 displayed significant correlations with CXCL10 (r =  0.45, p = 0.010) and CXCL11 (r = 0.53, p = 0.002) in human carotid lesions. Combining our findings, we uncover a novel role for RSAD2 in hAoSMCs, which could potentially contribute to monocyte recruitment in the context of atherosclerosis.

Single-cell 'omic profiles of human aortic endothelial cells in vitro and human atherosclerotic lesions ex vivo reveal heterogeneity of endothelial subtype and response to activating perturbations

Heterogeneity in endothelial cell (EC) sub-phenotypes is becoming increasingly appreciated in atherosclerosis progression. Still, studies quantifying EC heterogeneity across whole transcriptomes and epigenomes in both in vitro and in vivo models are lacking. Multiomic profiling concurrently measuring transcriptomes and accessible chromatin in the same single cells was performed on six distinct primary cultures of human aortic ECs (HAECs) exposed to activating environments characteristic of the atherosclerotic microenvironment in vitro. Meta-analysis of single-cell transcriptomes across 17 human ex vivo arterial specimens was performed and two computational approaches quantitatively evaluated the similarity in molecular profiles between heterogeneous in vitro and ex vivo cell profiles. HAEC cultures were reproducibly populated by four major clusters with distinct pathway enrichment profiles and modest heterogeneous responses: EC1-angiogenic, EC2-proliferative, EC3-activated/mesenchymal-like, and EC4-mesenchymal. Quantitative comparisons between in vitro and ex vivo transcriptomes confirmed EC1 and EC2 as most canonically EC-like, and EC4 as most mesenchymal with minimal effects elicited by siERG and IL1B. Lastly, accessible chromatin regions unique to EC2 and EC4 were most enriched for coronary artery disease (CAD)-associated single-nucleotide polymorphisms from Genome Wide Association Studies (GWAS), suggesting that these cell phenotypes harbor CAD-modulating mechanisms. Primary EC cultures contain markedly heterogeneous cell subtypes defined by their molecular profiles. Surprisingly, the perturbations used here only modestly shifted cells between subpopulations, suggesting relatively stable molecular phenotypes in culture. Identifying consistently heterogeneous EC subpopulations between in vitro and ex vivo models should pave the way for improving in vitro systems while enabling the mechanisms governing heterogeneous cell state decisions.

Enrichment of type 1 innate lymphoid cells in the course of human atherosclerotic plaque development suggests contribution to atherogenesis

Introduction

Innate lymphoid cells (ILCs) have been implicated in multiple pathologic conditions, including atherogenesis, as documented in experimental mice studies, however, their role in atherosclerosis in humans remains unexplored.

Methods

Here, we identify ILCs and their dynamics in early, advanced, and complicated human carotid- and aortic atherosclerotic plaques, using a multiplex immunohistochemical quadruple-staining technique with prototypic transcription factors T-bet, GATA3, or RORgt for identification of the ILC1, ILC2 and ILC3 subsets, respectively, in combination with lineage markers CD3, CD20/ CD79a and CD56 to exclude other lymphoid cell types. ILC subsets were quantified, and to put this in perspective, their numbers were expressed as percentage of the total number of infiltrated lymphoid cells and related to the frequency of conventional T cells, B cells, NK cells, and NKT cells.

Results

All ILC subsets were present in every different stage of atherogenesis. ILC1s were the most abundant ILC subset, and their numbers significantly increased in the course of plaque development, but paradoxically, their relative frequency was reduced because of a higher increment of T cells and B cells. The numbers of ILC2s and ILC3s also gradually increased, but this trend did not achieve significance. T cell subsets always significantly outnumbered their ILC counterparts, except for the early lesions where the proportion of ILC1s was markedly higher, albeit not significant.

Discussion

The high abundance of ILC1s in the early stages and further significant enrichment in later stages, suggest they may participate in the initiation and development of atherogenesis, and thus, may represent a novel target to prevent or treat atherosclerosis.

Omics Approaches Unveiling the Biology of Human Atherosclerotic Plaques

Atherosclerosis is a chronic inflammatory disease of the arterial wall, characterized by the buildup of plaques with the accumulation and transformation of lipids, immune cells, vascular smooth muscle cells, and necrotic cell debris. Plaques with collagen-poor thin fibrous caps infiltrated by macrophages and lymphocytes are considered unstable because they are at the greatest risk of rupture and clinical events. However, the current histologic definition of plaque types may not fully capture the complex molecular nature of atherosclerotic plaque biology and the underlying mechanisms contributing to plaque progression, rupture, and erosion. The advances in omics technologies have changed the understanding of atherosclerosis plaque biology, offering new possibilities to improve risk prediction and discover novel therapeutic targets. Genomic studies have shed light on the genetic predisposition to atherosclerosis, and integrative genomic analyses expedite the translation of genomic discoveries. Transcriptomic, proteomic, metabolomic, and lipidomic studies have refined the understanding of the molecular signature of atherosclerotic plaques, aiding in data-driven hypothesis generation for mechanistic studies and offering new prospects for biomarker discovery. Furthermore, advancements in single-cell technologies and emerging spatial analysis techniques have unveiled the heterogeneity and plasticity of plaque cells. This review discusses key omics-based discoveries that have advanced the understanding of human atherosclerotic plaque biology, focusing on insights derived from omics profiling of human atherosclerotic vascular specimens.

A systematic evaluation of state-of-the-art deconvolution methods in spatial transcriptomics: insights from cardiovascular disease and chronic kidney disease

A major challenge in sequencing-based spatial transcriptomics (ST) is resolution limitations. Tissue sections are divided into hundreds of thousands of spots, where each spot invariably contains a mixture of cell types. Methods have been developed to deconvolute the mixed transcriptional signal into its constituents. Although ST is becoming essential for drug discovery, especially in cardiometabolic diseases, to date, no deconvolution benchmark has been performed on these types of tissues and diseases. However, the three methods, Cell2location, RCTD, and spatialDWLS, have previously been shown to perform well in brain tissue and simulated data. Here, we compare these methods to assess the best performance when using human data from cardiovascular disease (CVD) and chronic kidney disease (CKD) from patients in different pathological states, evaluated using expert annotation. In this study, we found that all three methods performed comparably well in deconvoluting verifiable cell types, including smooth muscle cells and macrophages in vascular samples and podocytes in kidney samples. RCTD shows the best performance accuracy scores in CVD samples, while Cell2location, on average, achieved the highest performance across all test experiments. Although all three methods had similar accuracies, Cell2location needed less reference data to converge at the expense of higher computational intensity. Finally, we also report that RCTD has the fastest computational time and the simplest workflow, requiring fewer computational dependencies. In conclusion, we find that each method has particular advantages, and the optimal choice depends on the use case.

Comprehensive scRNA-seq Model Reveals Artery Endothelial Cell Heterogeneity and Metabolic Preference in Human Vascular Disease

Vascular disease is one of the major causes of death worldwide. Endothelial cells are important components of the vascular structure. A better understanding of the endothelial cell changes in the development of vascular disease may provide new targets for clinical treatment strategies. Single-cell RNA sequencing can serve as a powerful tool to explore transcription patterns, as well as cell type identity. Our current study is based on comprehensive scRNA-seq data of several types of human vascular disease datasets with deep-learning-based algorithm. A gene set scoring system, created based on cell clustering, may help to identify the relative stage of the development of vascular disease. Metabolic preference patterns were estimated using a graphic neural network model. Overall, our study may provide potential treatment targets for retaining normal endothelial function under pathological situations.

Macrophage profiling in atherosclerosis: understanding the unstable plaque

The development and rupture of atherosclerotic plaques is a major contributor to myocardial infarctions and ischemic strokes. The dynamic evolution of the plaque is largely attributed to monocyte/macrophage functions, which respond to various stimuli in the plaque microenvironment. To this end, macrophages play a central role in atherosclerotic lesions through the uptake of oxidized low-density lipoprotein that gets trapped in the artery wall, and the induction of an inflammatory response that can differentially affect the stability of the plaque in men and women. In this environment, macrophages can polarize towards pro-inflammatory M1 or anti-inflammatory M2 phenotypes, which represent the extremes of the polarization spectrum that include Mhem, M(Hb), Mox, and M4 populations. However, this traditional macrophage model paradigm has been redefined to include numerous immune and nonimmune cell clusters based on in-depth unbiased single-cell approaches. The goal of this review is to highlight (1) the phenotypic and functional properties of monocyte subsets in the circulation, and macrophage populations in atherosclerotic plaques, as well as their contribution towards stable or unstable phenotypes in men and women, and (2) single-cell RNA sequencing studies that have advanced our knowledge of immune, particularly macrophage signatures present in the atherosclerotic niche. We discuss the importance of performing high-dimensional approaches to facilitate the development of novel sex-specific immunotherapies that aim to reduce the risk of cardiovascular events.

Re-analysis of single-cell transcriptomics reveals a critical role of macrophage-like smooth muscle cells in advanced atherosclerotic plaque

Aims: Smooth muscle cell (SMC) remodeling poses a critical feature in the development and progression of atherosclerosis. Although fate mapping and in silicon approaches have expanded SMC phenotypes in atherosclerosis, it still remains elusive about the contributions of individual SMC phenotypes and molecular dynamics to advanced atherosclerotic plaque. Methods: Using single-cell transcriptome, we investigated cellular compositions of human carotid plaque laden with atherosclerotic core, followed by in vivo experiments utilizing SMC-lineage tracing technology, bulk RNA sequencing (RNA-seq) and both in vivo and in vitro validation of the underlying molecular mechanism. Results: 5 functionally distinct SMC subtypes were uncovered based on transcriptional features (described as contractile, fibroblast-like, osteogenic, synthetic and macrophage-like) within the niche. A proinflammatory, macrophage-like SMC subtype displaying an intermediary phenotype between SMC and macrophage, exhibits prominent potential in destabilizing plaque. At the molecular level, we explored cluster-specific master regulons by algorithm, and identified interferon regulatory factor-8 (IRF8) as a potential stimulator of SMC-to-macrophage transdifferentiation via activating nuclear factor-κB (NF-κB) signaling. Conclusions: Our study illustrates a comprehensive cell atlas and molecular landscape of advanced atherosclerotic lesion, which might renovate current understanding of SMC biology in atherosclerosis.

Spatial multi-omics: novel tools to study the complexity of cardiovascular diseases

Spatial multi-omic studies have emerged as a promising approach to comprehensively analyze cells in tissues, enabling the joint analysis of multiple data modalities like transcriptome, epigenome, proteome, and metabolome in parallel or even the same tissue section. This review focuses on the recent advancements in spatial multi-omics technologies, including novel data modalities and computational approaches. We discuss the advancements in low-resolution and high-resolution spatial multi-omics methods which can resolve up to 10,000 of individual molecules at subcellular level. By applying and integrating these techniques, researchers have recently gained valuable insights into the molecular circuits and mechanisms which govern cell biology along the cardiovascular disease spectrum. We provide an overview of current data analysis approaches, with a focus on data integration of multi-omic datasets, highlighting strengths and weaknesses of various computational pipelines. These tools play a crucial role in analyzing and interpreting spatial multi-omics datasets, facilitating the discovery of new findings, and enhancing translational cardiovascular research. Despite nontrivial challenges, such as the need for standardization of experimental setups, data analysis, and improved computational tools, the application of spatial multi-omics holds tremendous potential in revolutionizing our understanding of human disease processes and the identification of novel biomarkers and therapeutic targets. Exciting opportunities lie ahead for the spatial multi-omics field and will likely contribute to the advancement of personalized medicine for cardiovascular diseases.

Integration of Pan-Cancer Single-Cell and Spatial Transcriptomics Reveals Stromal Cell Features and Therapeutic Targets in Tumor Microenvironment

Stromal cells are physiologically essential components of the tumor microenvironment (TME) that mediates tumor development and therapeutic resistance. Development of a logical and unified system for stromal cell type identification and characterization of corresponding functional properties could help design antitumor strategies that target stromal cells. Here, we performed a pan-cancer analysis of 214,972 nonimmune stromal cells using single-cell RNA sequencing from 258 patients across 16 cancer types and analyzed spatial transcriptomics from 16 patients across seven cancer types, including six patients receiving anti-PD-1 treatment. This analysis uncovered distinct features of 39 stromal subsets across cancer types, including various functional modules, spatial locations, and clinical and therapeutic relevance. Tumor-associated PGF+ endothelial tip cells with elevated epithelial-mesenchymal transition features were enriched in immune-depleted TME and associated with poor prognosis. Fibrogenic and vascular pericytes (PC) derived from FABP4+ progenitors were two distinct tumor-associated PC subpopulations that strongly interacted with PGF+ tips, resulting in excess extracellular matrix (ECM) abundance and dysfunctional vasculature. Importantly, ECM-related cancer-associated fibroblasts enriched at the tumor boundary acted as a barrier to exclude immune cells, interacted with malignant cells to promote tumor progression, and regulated exhausted CD8+ T cells via immune checkpoint ligand-receptors (e.g., LGALS9/TIM-3) to promote immune escape. In addition, an interactive web-based tool (http://www.scpanstroma.yelab.site/) was developed for accessing, visualizing, and analyzing stromal data. Taken together, this study provides a systematic view of the highly heterogeneous stromal populations across cancer types and suggests future avenues for designing therapies to overcome the tumor-promoting functions of stromal cells.

SIGNIFICANCE

Comprehensive characterization of tumor-associated nonimmune stromal cells provides a robust resource for dissecting tumor microenvironment complexity and guiding stroma-targeted therapy development across multiple human cancer types.

M6A plays a potential role in carotid atherosclerosis by modulating immune cell modification and regulating aging-related genes

RNA N6-methyladenosine (m6A) regulators play essential roles in diverse biological processes, including immune responses. Mounting evidence suggests that their dysregulation is intricately linked to numerous diseases. However, the role of m6A-associated genes in carotid atherosclerosis and their relationship with aging and immune cells remain unclear. Analyze the expression profiles of m6A-related genes in carotid atherosclerosis-related datasets. Based on the expression patterns of m6A-related genes, perform consistent clustering analysis of carotid atherosclerosis samples and investigate associated immune cell infiltration patterns and aging characteristics. Develop an m6A prediction model specific to carotid atherosclerosis and analyze the relationships between immune cells infiltration and aging features. The m6A methylation modification level exhibited a substantial decrease in early-stage carotid atherosclerosis samples compared to late-stage carotid atherosclerosis samples. Subsequently, two distinct m6A subtypes were defined through consensus clustering analysis, with the lower m6A modification level group showing associations with heightened immune cell infiltration and increased expression of aging-related genes. A model composed of five m6A-related genes was formulated, and the results indicated that this model possesses effective predictive and therapeutic capabilities for carotid atherosclerosis. Furthermore, the downregulation of YTHDC1 expression resulted in elevated expression of inflammatory factors and a decrease in the expression of the aging-related gene RGN. Single-cell data analysis suggests that the reduced expression of YTHDC1 may decrease the degradation of inflammation-related factors in macrophages, leading to a highly inflammatory state in the carotid artery wall. Furthermore, the sustained release of inflammatory factors may increase the expression of the aging-related gene RGN in vascular smooth muscle cells, further exacerbating the progression of atherosclerosis. A reduced level of m6A methylation modification could enhance inflammation and expedite cellular aging, thereby contributing to the development of carotid atherosclerosis.

Integrated systems biology approach identifies gene targets for endothelial dysfunction

Endothelial dysfunction (ED) is critical in the development and progression of cardiovascular (CV) disorders, yet effective therapeutic targets for ED remain elusive due to limited understanding of its underlying molecular mechanisms. To address this gap, we employed a systems biology approach to identify potential targets for ED. Our study combined multi omics data integration, with siRNA screening, high content imaging and network analysis to prioritise key ED genes and identify a pro- and anti-ED network. We found 26 genes that, upon silencing, exacerbated the ED phenotypes tested, and network propagation identified a pro-ED network enriched in functions associated with inflammatory responses. Conversely, 31 genes ameliorated ED phenotypes, pointing to potential ED targets, and the respective anti-ED network was enriched in hypoxia, angiogenesis and cancer-related processes. An independent screen with 17 drugs found general agreement with the trends from our siRNA screen and further highlighted DUSP1, IL6 and CCL2 as potential candidates for targeting ED. Overall, our results demonstrate the potential of integrated system biology approaches in discovering disease-specific candidate drug targets for endothelial dysfunction.

Unveiling the Hidden Landscape of Arterial Diseases at Single-Cell Resolution

High-resolution single-cell technologies have shed light on the pathogenesis of cardiovascular diseases by enabling the discovery of novel cellular and transcriptomic signatures associated with various conditions, and uncovering new contributions of inflammatory processes, immunity, metabolic stress, and risk factors. We review the information obtained from studies using single-cell technologies in tissues with atherosclerosis and aortic aneurysms. Insights are provided on the biology of endothelial, smooth muscle, and immune cells in the arterial intima and media. In addition to cellular diversity, numerous examples of plasticity and phenotype switching are highlighted and presented in the context of normal cell functions.

Endothelial heterogeneity and their relevance in cardiac development and coronary artery disease

Micro- and macrovascular endothelial cells (ECs) are characterized by structural and functional heterogeneity, which is also reflected in their secretory activity. The root of this heterogeneity and related regulatory mechanisms are still poorly understood. During embryogenesis, microvascular ECs participate in organogenesis prior to the development of the fetal circulation, suggesting that ECs are capable of releasing paracrine trophogens, termed angiocrine factors (AFs). These are angiocrine growth factors, adhesion molecules, and chemokines, which are intended to promote morphogenesis and repair of the adjacent parenchyma/stroma where the vessels are located. There is a tissue and organ-specificity of AFs that traces the heterogeneity of ECs. This AF heterogeneity also traces how ECs respond to pathological conditions or exposure to cardiovascular risk factors. The study of the mechanisms that regulate endothelial and paracrine heterogeneity and that contribute to endotheliopathy represents a broad and as yet understudied area of research. A better understanding of the cellular and molecular mechanisms that regulate this heterogeneity, leading to endotheliopathy is an exciting challenge. In this brief review we will discuss experimental advances in the heterogeneity of ECs and their AF, with a focus on their involvement in the pathogenesis of coronary artery disease.

Integrative single-cell meta-analysis reveals disease-relevant vascular cell states and markers in human atherosclerosis

Coronary artery disease (CAD) is characterized by atherosclerotic plaque formation in the arterial wall. CAD progression involves complex interactions and phenotypic plasticity among vascular and immune cell lineages. Single-cell RNA-seq (scRNA-seq) studies have highlighted lineage-specific transcriptomic signatures, but human cell phenotypes remain controversial. Here, we perform an integrated meta-analysis of 22 scRNA-seq libraries to generate a comprehensive map of human atherosclerosis with 118,578 cells. Besides characterizing granular cell-type diversity and communication, we leverage this atlas to provide insights into smooth muscle cell (SMC) modulation. We integrate genome-wide association study data and uncover a critical role for modulated SMC phenotypes in CAD, myocardial infarction, and coronary calcification. Finally, we identify fibromyocyte/fibrochondrogenic SMC markers (LTBP1 and CRTAC1) as proxies of atherosclerosis progression and validate these through omics and spatial imaging analyses. Altogether, we create a unified atlas of human atherosclerosis informing cell state-specific mechanistic and translational studies of cardiovascular diseases.

Sex differences in the genetic and molecular mechanisms of coronary artery disease

Sex differences in coronary artery disease (CAD) presentation, risk factors and prognosis have been widely studied. Similarly, studies on atherosclerosis have shown prominent sex differences in plaque biology. Our understanding of the underlying genetic and molecular mechanisms that drive these differences remains fragmented and largely understudied. Through reviewing genetic and epigenetic studies, we identified more than 40 sex-differential candidate genes (13 within known CAD loci) that may explain, at least in part, sex differences in vascular remodeling, lipid metabolism and endothelial dysfunction. Studies with transcriptomic and single-cell RNA sequencing data from atherosclerotic plaques highlight potential sex differences in smooth muscle cell and endothelial cell biology. Especially, phenotypic switching of smooth muscle cells seems to play a crucial role in female atherosclerosis. This matches the known sex differences in atherosclerotic phenotypes, with men being more prone to lipid-rich plaques, while women are more likely to develop fibrous plaques with endothelial dysfunction. To unravel the complex mechanisms that drive sex differences in CAD, increased statistical power and adjustments to study designs and analysis strategies are required. This entails increasing inclusion rates of women, performing well-defined sex-stratified analyses and the integration of multi-omics data.

Myeloid BAF60a deficiency alters metabolic homeostasis and exacerbates atherosclerosis

Atherosclerosis, a leading health concern, stems from the dynamic involvement of immune cells in vascular plaques. Despite its significance, the interplay between chromatin remodeling and transcriptional regulation in plaque macrophages is understudied. We discovered the reduced expression of Baf60a, a component of the switch/sucrose non-fermentable (SWI/SNF) chromatin remodeling complex, in macrophages from advanced plaques. Myeloid-specific Baf60a deletion compromised mitochondrial integrity and heightened adhesion, apoptosis, and plaque development. BAF60a preserves mitochondrial energy homeostasis under pro-atherogenic stimuli by retaining nuclear respiratory factor 1 (NRF1) accessibility at critical genes. Overexpression of BAF60a rescued mitochondrial dysfunction in an NRF1-dependent manner. This study illuminates the BAF60a-NRF1 axis as a mitochondrial function modulator in atherosclerosis, proposing the rejuvenation of perturbed chromatin remodeling machinery as a potential therapeutic target.

Multi-ancestry genome-wide study identifies effector genes and druggable pathways for coronary artery calcification

Coronary artery calcification (CAC), a measure of subclinical atherosclerosis, predicts future symptomatic coronary artery disease (CAD). Identifying genetic risk factors for CAC may point to new therapeutic avenues for prevention. Currently, there are only four known risk loci for CAC identified from genome-wide association studies (GWAS) in the general population. Here we conducted the largest multi-ancestry GWAS meta-analysis of CAC to date, which comprised 26,909 individuals of European ancestry and 8,867 individuals of African ancestry. We identified 11 independent risk loci, of which eight were new for CAC and five had not been reported for CAD. These new CAC loci are related to bone mineralization, phosphate catabolism and hormone metabolic pathways. Several new loci harbor candidate causal genes supported by multiple lines of functional evidence and are regulators of smooth muscle cell-mediated calcification ex vivo and in vitro. Together, these findings help refine the genetic architecture of CAC and extend our understanding of the biological and potential druggable pathways underlying CAC.

Atherosclerotic plaque vulnerability quantification system for clinical and biological interpretability

Acute myocardial infarction dominates coronary artery disease mortality. Identifying bio-signatures for plaque destabilization and rupture is important for preventing the transition from coronary stability to instability and the occurrence of thrombosis events. This computational systems biology study enrolled 2,235 samples from 22 independent bulks cohorts and 14 samples from two single-cell cohorts. A machine-learning integrative program containing nine learners was developed to generate a warning classifier linked to atherosclerotic plaque vulnerability signature (APVS). The classifier displays the reliable performance and robustness for distinguishing ST-elevation myocardial infarction from chronic coronary syndrome at presentation, and revealed higher accuracy to 33 pathogenic biomarkers. We also developed an APVS-based quantification system (APVSLevel) for comprehensively quantifying atherosclerotic plaque vulnerability, empowering early-warning capabilities, and accurate assessment of atherosclerosis severity. It unraveled the multidimensional dysregulated mechanisms at high resolution. This study provides a potential tool for macro-level differential diagnosis and evaluation of subtle genetic pathological changes in atherosclerosis.

Proteomic Atlas of Atherosclerosis: The Contribution of Proteoglycans to Sex Differences, Plaque Phenotypes, and Outcomes

BACKGROUND

Using proteomics, we aimed to reveal molecular types of human atherosclerotic lesions and study their associations with histology, imaging, and cardiovascular outcomes.

METHODS

Two hundred nineteen carotid endarterectomy samples were procured from 120 patients. A sequential protein extraction protocol was employed in conjunction with multiplexed, discovery proteomics. To focus on extracellular proteins, parallel reaction monitoring was employed for targeted proteomics. Proteomic signatures were integrated with bulk, single-cell, and spatial RNA-sequencing data, and validated in 200 patients from the Athero-Express Biobank study.

RESULTS

This extensive proteomics analysis identified plaque inflammation and calcification signatures, which were inversely correlated and validated using targeted proteomics. The inflammation signature was characterized by the presence of neutrophil-derived proteins, such as S100A8/9 (calprotectin) and myeloperoxidase, whereas the calcification signature included fetuin-A, osteopontin, and gamma-carboxylated proteins. The proteomics data also revealed sex differences in atherosclerosis, with large-aggregating proteoglycans versican and aggrecan being more abundant in females and exhibiting an inverse correlation with estradiol levels. The integration of RNA-sequencing data attributed the inflammation signature predominantly to neutrophils and macrophages, and the calcification and sex signatures to smooth muscle cells, except for certain plasma proteins that were not expressed but retained in plaques, such as fetuin-A. Dimensionality reduction and machine learning techniques were applied to identify 4 distinct plaque phenotypes based on proteomics data. A protein signature of 4 key proteins (calponin, protein C, serpin H1, and versican) predicted future cardiovascular mortality with an area under the curve of 75% and 67.5% in the discovery and validation cohort, respectively, surpassing the prognostic performance of imaging and histology.

CONCLUSIONS

Plaque proteomics redefined clinically relevant patient groups with distinct outcomes, identifying subgroups of male and female patients with elevated risk of future cardiovascular events.

Oxidized Low-density Lipoproteins and Lipopolysaccharides Augment Carotid Artery Plaque Vulnerability in Hypercholesterolemic Microswine

Atherosclerosis is a chronic inflammatory disease and hypercholesterolemia is a risk factor. This study aims to compare the potency of lipopolysaccharide (LPS) and oxidized low-density lipoproteins (oxLDL) to induce plaque formation and increase plaque vulnerability in the carotid artery of hypercholesterolemic Yucatan microswine. Atherosclerotic lesions at the common carotid artery junction and ascending pharyngeal artery were induced in hypercholesterolemic Yucatan microswine at 5-6 months of age with balloon angioplasty. LPS or oxLDL were administered intraluminally at the site of injury after occluding the arterial flow temporarily. Pre-intervention ultrasound (US), angiography, and optical coherence tomography (OCT) were done at baseline and just before euthanasia to assess post-op parameters. The images from the US, OCT, and angiography in the LPS and the oxLDL-treated group showed increased plaque formation with features suggestive of unstable plaque, including necrotic core, thin fibrous caps, and a signal poor region more with oxLDL compared to LPS. Histomorphology of the carotid artery tissue near the injury corroborated the presence of severe lesions in both LPS and oxLDL-treated pigs but more in the oxLDL group. Vascular smooth muscle and endothelial cells treated with LPS and oxLDL showed increased folds changes in mRNA transcripts of the biomarkers of inflammation and plaque vulnerability compared to untreated cells. Collectively, the results suggest that angioplasty-mediated intimal injury of the carotid arteries in atherosclerotic swine with local administration of LPS or ox-LDL induces vulnerable plaques compared to angioplasty alone and oxLDL is relatively more potent than LPS in inducing vulnerable plaque.

Tissue Inhibitor of Metalloproteinases-1 Interacts with CD74 to Promote AKT Signaling, Monocyte Recruitment Responses, and Vascular Smooth Muscle Cell Proliferation

Tissue inhibitor of metalloproteinases-1 (TIMP-1), an important regulator of matrix metalloproteinases (MMPs), has recently been shown to interact with CD74, a receptor for macrophage migration inhibitory factor (MIF). However, the biological effects mediated by TIMP-1 through CD74 remain largely unexplored. Using sequence alignment and in silico protein-protein docking analysis, we demonstrated that TIMP-1 shares residues with both MIF and MIF-2, crucial for CD74 binding, but not for CXCR4. Subcellular colocalization, immunoprecipitation, and internalization experiments supported these findings, demonstrating that TIMP-1 interacts with surface-expressed CD74, resulting in its internalization in a dose-dependent manner, as well as with a soluble CD74 ectodomain fragment (sCD74). This prompted us to study the effects of the TIMP-1-CD74 axis on monocytes and vascular smooth muscle cells (VSCMs) to assess its impact on vascular inflammation. A phospho-kinase array revealed the activation of serine/threonine kinases by TIMP-1 in THP-1 pre-monocytes, in particular AKT. Similarly, TIMP-1 dose-dependently triggered the phosphorylation of AKT and ERK1/2 in primary human monocytes. Importantly, Transwell migration, 3D-based Chemotaxis, and flow adhesion assays demonstrated that TIMP-1 engagement of CD74 strongly promotes the recruitment response of primary human monocytes, while live cell imaging studies revealed a profound activating effect on VSMC proliferation. Finally, re-analysis of scRNA-seq data highlighted the expression patterns of TIMP-1 and CD74 in human atherosclerotic lesions, thus, together with our experimental data, indicating a role for the TIMP-1-CD74 axis in vascular inflammation and atherosclerosis.

Identification of lipid metabolism-related biomarkers for diagnosis and molecular classification of atherosclerosis

BACKGROUND

Atherosclerosis is now the main cause of cardiac-cerebral vascular diseases around the world. Disturbances in lipid metabolism have an essential role in the development and progression of atherosclerosis. Thus, we aimed to investigate lipid metabolism-related molecular clusters and develop a diagnostic model for atherosclerosis.

METHODS

First, we used the GSE100927 and GSE43292 datasets to screen differentially expressed lipid metabolism-related genes (LMRGs). Subsequent enrichment analysis of these key genes was performed using the Metascape database. Using 101 atherosclerosis samples, we investigated the LMRG-based molecular clusters and the corresponding immune cell infiltration. After that, a diagnostic model for atherosclerosis was constructed using the least absolute shrinkage and selection operator (LASSO) and multivariate logistic regression. Finally, a series of bioinformatics techniques, including CIBERSORT, gene set variation analysis, and single-cell data analysis, were used to analyze the potential mechanisms of the model genes in atherosclerosis.

RESULTS

A total of 29 LMRGs were found to be differentially expressed between atherosclerosis and normal samples. Functional and DisGeNET enrichment analyses indicated that 29 LMRGs are primarily engaged in cholesterol and lipid metabolism, the PPAR signaling pathway, and regulation of the inflammatory response and are also closely associated with atherosclerotic lesions. Two LMRG-related molecular clusters with significant biological functional differences are defined in atherosclerosis. A three-gene diagnostic model containing ADCY7, SCD, and CD36 was subsequently constructed. Receiver operating characteristic curves, decision curves, and an external validation dataset showed that our model exhibits good predictive performance. In addition, three model genes were found to be closely associated with immune cell infiltration, especially macrophage infiltration.

CONCLUSIONS

Our study comprehensively highlighted the intricate association between lipid metabolism and atherosclerosis and created a three-gene model for future clinical diagnosis.

Pyruvate dehydrogenase kinase regulates vascular inflammation in atherosclerosis and increases cardiovascular risk

AIMS

Recent studies have revealed a close connection between cellular metabolism and the chronic inflammatory process of atherosclerosis. While the link between systemic metabolism and atherosclerosis is well established, the implications of altered metabolism in the artery wall are less understood. Pyruvate dehydrogenase kinase (PDK)-dependent inhibition of pyruvate dehydrogenase (PDH) has been identified as a major metabolic step regulating inflammation. Whether the PDK/PDH axis plays a role in vascular inflammation and atherosclerotic cardiovascular disease remains unclear.

METHODS AND RESULTS

Gene profiling of human atherosclerotic plaques revealed a strong correlation between PDK1 and PDK4 transcript levels and the expression of pro-inflammatory and destabilizing genes. Remarkably, the PDK1 and PDK4 expression correlated with a more vulnerable plaque phenotype, and PDK1 expression was found to predict future major adverse cardiovascular events. Using the small-molecule PDK inhibitor dichloroacetate (DCA) that restores arterial PDH activity, we demonstrated that the PDK/PDH axis is a major immunometabolic pathway, regulating immune cell polarization, plaque development, and fibrous cap formation in Apoe-/- mice. Surprisingly, we discovered that DCA regulates succinate release and mitigates its GPR91-dependent signals promoting NLRP3 inflammasome activation and IL-1β secretion by macrophages in the plaque.

CONCLUSIONS

We have demonstrated for the first time that the PDK/PDH axis is associated with vascular inflammation in humans and particularly that the PDK1 isozyme is associated with more severe disease and could predict secondary cardiovascular events. Moreover, we demonstrate that targeting the PDK/PDH axis with DCA skews the immune system, inhibits vascular inflammation and atherogenesis, and promotes plaque stability features in Apoe-/- mice. These results point toward a promising treatment to combat atherosclerosis.

Lipid-associated macrophages transition to an inflammatory state in human atherosclerosis increasing the risk of cerebrovascular complications

The immune system is integral to cardiovascular health and disease. Targeting inflammation ameliorates adverse cardiovascular outcomes. Atherosclerosis, a major underlying cause of cardiovascular disease (CVD), is conceptualised as a lipid-driven inflammation where macrophages play a non-redundant role. However, evidence emerging so far from single cell atlases suggests a dichotomy between lipid associated and inflammatory macrophage states. Here, we present an inclusive reference atlas of human intraplaque immune cell communities. Combining scRNASeq of human surgical carotid endarterectomies in a discovery cohort with bulk RNASeq and immunohistochemistry in a validation cohort (the Carotid Plaque Imaging Project-CPIP), we reveal the existence of PLIN2hi/TREM1hi macrophages as a toll-like receptor-dependent inflammatory lipid-associated macrophage state linked to cerebrovascular events. Our study shifts the current paradigm of lipid-driven inflammation by providing biological evidence for a pathogenic macrophage transition to an inflammatory lipid-associated phenotype and for its targeting as a new treatment strategy for CVD.

Analysis of immunogenic cell death in atherosclerosis based on scRNA-seq and bulk RNA-seq data

BACKGROUND

Regulated cell death plays a very important role in atherosclerosis (AS). Despite a large number of studies, there is a lack of literature on immunogenic cell death (ICD) in AS.

METHOD

Carotid atherosclerotic plaque single-cell RNA (scRNA) sequencing data were analyzed to define involved cells and determine their transcriptomic characteristics. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, CIBERSORT, ESTIMATE and ssGSEA (Gene Set Enrichment Analysis), consensus clustering analysis, random forest (RF), Decision Curve Analysis (DCA), and the Drug-Gene Interaction and DrugBank databases were applied for bulk sequencing data. All data were downloaded from Gene Expression Omnibus (GEO).

RESULT

mDCs and CTLs correlated obviously with AS occurrence and development (k2(mDCs) = 48.333, P < 0.001; k2(CTL) = 130.56, P < 0.001). In total, 21 differentially expressed genes were obtained for the bulk transcriptome; KEGG enrichment analysis results were similar to those for differentially expressed genes in endothelial cells. Eleven genes with a gene importance score > 1.5 were obtained in the training set and validated in the test set, resulting in 8 differentially expressed genes for ICD. A model to predict occurrence of AS and 56 drugs that may be used to treat AS were obtained with these 8 genes.

CONCLUSION

Immunogenic cell death occurs mainly in endothelial cells in AS. ICD maintains chronic inflammation in AS and plays a crucial role in its occurrence and development. ICD related genes may become drug-targeted genes for AS treatment.

Comprehensive analysis of the diagnostic and therapeutic value of the hypoxia-related gene PLAUR in the progression of atherosclerosis

Atherosclerosis (AS) is a major contributor to a variety of negative clinical outcomes, including stroke and myocardial infarction. However, the role and therapeutic value of hypoxia-related genes in AS development has been less discussed. In this study, Plasminogen activator, urokinase receptor (PLAUR) was identified as an effective diagnostic marker for AS lesion progression by combining WGCNA and random forest algorithm. We validated the stability of the diagnostic value on multiple external datasets including humans and mice. We identified a significant correlation between PLAUR expression and lesion progression. We mined multiple single cell-RNA sequencing (sc-RNA seq) data to nominate macrophage as the key cell cluster for PLAUR mediated lesion progression. We combined cross-validation results from multiple databases to predict that HCG17-hsa-miR-424-5p-HIF1A, a competitive endogenous RNA (ceRNA) network, may regulate hypoxia inducible factor 1 subunit alpha (HIF1A) expression. The DrugMatrix database was used to predict alprazolam, valsartan, biotin A, lignocaine, and curcumin as potential drugs to delay lesion progression by antagonizing PLAUR, and AutoDock was used to verify the binding ability of drugs and PLAUR. Overall, this study provides the first systematic identification of the diagnostic and therapeutic value of PLAUR in AS and offers multiple treatment options with potential applications.

Genetic or therapeutic neutralization of ALK1 reduces LDL transcytosis and atherosclerosis in mice

Low-density lipoprotein (LDL) accumulation in the arterial wall contributes to atherosclerosis initiation and progression1. Activin A receptor-like type 1 (ACVRL1, called activin-like kinase receptor (ALK1)) is a recently identified receptor that mediates LDL entry and transcytosis in endothelial cells (ECs)2,3. However, the role of this pathway in vivo is not yet known. In the present study, we show that genetic deletion of ALK1 in arterial ECs of mice substantially limits LDL accumulation, macrophage infiltration and atherosclerosis without affecting cholesterol or triglyceride levels. Moreover, a selective monoclonal antibody binding ALK1 efficiently blocked LDL transcytosis, but not bone morphogenetic protein-9 (BMP9) signaling, dramatically reducing plaque formation in LDL receptor knockout mice fed a high-fat diet. Thus, our results demonstrate that blocking LDL transcytosis into the endothelium may be a promising therapeutic strategy that targets the initiating event of atherosclerotic cardiovascular disease.

FHL5 Controls Vascular Disease-Associated Gene Programs in Smooth Muscle Cells

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.

Porphyromonas gingivalis regulates atherosclerosis through an immune pathway

Atherosclerosis (AS) is a chronic inflammatory disease, involving a pathological process of endothelial dysfunction, lipid deposition, plaque rupture, and arterial occlusion, and is one of the leading causes of death in the world population. The progression of AS is closely associated with several inflammatory diseases, among which periodontitis has been shown to increase the risk of AS. Porphyromonas gingivalis (P. gingivalis), presenting in large numbers in subgingival plaque biofilms, is the “dominant flora” in periodontitis, and its multiple virulence factors are important in stimulating host immunity. Therefore, it is significant to elucidate the potential mechanism and association between P. gingivalis and AS to prevent and treat AS. By summarizing the existing studies, we found that P. gingivalis promotes the progression of AS through multiple immune pathways. P. gingivalis can escape host immune clearance and, in various forms, circulate with blood and lymph and colonize arterial vessel walls, directly inducing local inflammation in blood vessels. It also induces the production of systemic inflammatory mediators and autoimmune antibodies, disrupts the serum lipid profile, and thus promotes the progression of AS. In this paper, we summarize the recent evidence (including clinical studies and animal studies) on the correlation between P. gingivalis and AS, and describe the specific immune mechanisms by which P. gingivalis promotes AS progression from three aspects (immune escape, blood circulation, and lymphatic circulation), providing new insights into the prevention and treatment of AS by suppressing periodontal pathogenic bacteria.

The angiopoietin receptor Tie2 is atheroprotective in arterial endothelium

Leukocytes and resident cells in the arterial wall contribute to atherosclerosis, especially at sites of disturbed blood flow. Expression of endothelial Tie1 receptor tyrosine kinase is enhanced at these sites, and attenuation of its expression reduces atherosclerotic burden and decreases inflammation. However, Tie2 tyrosine kinase function in atherosclerosis is unknown. Here we provide genetic evidence from humans and from an atherosclerotic mouse model to show that TIE2 is associated with protection from coronary artery disease. We show that deletion of Tie2, or both Tie2 and Tie1, in the arterial endothelium promotes atherosclerosis by increasing Foxo1 nuclear localization, endothelial adhesion molecule expression and accumulation of immune cells. We also show that Tie2 is expressed in a subset of aortic fibroblasts, and its silencing in these cells increases expression of inflammation-related genes. Our findings indicate that unlike Tie1, the Tie2 receptor functions as the dominant endothelial angiopoietin receptor that protects from atherosclerosis.

Heterogeneity of macrophages in atherosclerosis revealed by single-cell RNA sequencing

Technology at the single-cell level has advanced dramatically in characterizing molecular heterogeneity. These technologies have enabled cell subtype diversity to be seen in all tissues, including atherosclerotic plaques. Critical in atherosclerosis pathogenesis and progression are macrophages. Previous studies have only determined macrophage phenotypes within the plaque, mainly by bulk analysis. However, recent progress in single-cell technologies now enables the comprehensive mapping of macrophage subsets and phenotypes present in plaques. In this review, we have updated and discussed the definition and classification of macrophage subsets in mice and humans using single-cell RNA sequencing. We summarized the different classification methods and perspectives: traditional classification with an updated scoring system, inflammatory macrophages, foamy macrophages, and atherosclerotic-resident macrophages. In addition, some special types of macrophages were identified by specific markers, including IFN-inducible and cavity macrophages. Furthermore, we discussed macrophage subset-specific markers and their functions. In the future, these novel insights into the characteristics and phenotypes of these macrophage subsets within atherosclerotic plaques can provide additional therapeutic targets for cardiovascular diseases.

Bulk and single-cell characterisation of the immune heterogeneity of atherosclerosis identifies novel targets for immunotherapy

BACKGROUND

Immune cells that infiltrate lesions are important for atherosclerosis progression and immunotherapies. This study was aimed at gaining important new insights into the heterogeneity of these cells by integrating the sequencing results of multiple samples and using an enhanced single-cell sequencing workflow to overcome the limitations of a single study.

RESULTS

Integrative analyses identified 28 distinct subpopulations based on gene expression profiles. Further analysis demonstrated that these cells manifested high heterogeneity at the levels of tissue preferences, genetic perturbations, functional variations, immune dynamics, transcriptional regulators, metabolic changes, and communication patterns. Of the T cells, interferon-induced CD8⁺ T cells were involved in the progression of atherosclerosis. In contrast, proinflammatory CD4⁺ CD28^null T cells predicted a poor outcome in atherosclerosis. Notably, we identified two subpopulations of foamy macrophages that exhibit contrasting phenotypes. Among them, TREM2^- SPP1⁺ foamy macrophages were preferentially distributed in the hypoxic core of plaques. These glycolytic metabolism-enriched cells, with impaired cholesterol metabolism and robust pro-angiogenic capacity, were phenotypically regulated by CSF1 secreted by co-localised mast cells. Moreover, combined with deconvolution of the bulk datasets, we revealed that these dysfunctional cells had a higher proportion of ruptured and haemorrhagic lesions and were significantly associated with poor atherosclerosis prognoses.

CONCLUSIONS

We systematically explored atherosclerotic immune heterogeneity and identified cell populations underlying atherosclerosis progression and poor prognosis, which may be valuable for developing new and precise immunotherapies.

Transformer for one stop interpretable cell type annotation

Consistent annotation transfer from reference dataset to query dataset is fundamental to the development and reproducibility of single-cell research. Compared with traditional annotation methods, deep learning based methods are faster and more automated. A series of useful single cell analysis tools based on autoencoder architecture have been developed but these struggle to strike a balance between depth and interpretability. Here, we present TOSICA, a multi-head self-attention deep learning model based on Transformer that enables interpretable cell type annotation using biologically understandable entities, such as pathways or regulons. We show that TOSICA achieves fast and accurate one-stop annotation and batch-insensitive integration while providing biologically interpretable insights for understanding cellular behavior during development and disease progressions. We demonstrate TOSICA's advantages by applying it to scRNA-seq data of tumor-infiltrating immune cells, and CD14+ monocytes in COVID-19 to reveal rare cell types, heterogeneity and dynamic trajectories associated with disease progression and severity.

Exploring Shared Biomarkers of Myocardial Infarction and Alzheimer's Disease via Single-Cell/Nucleus Sequencing and Bioinformatics Analysis

BACKGROUND

Patients are at increased risk of dementia, including Alzheimer's disease (AD), after myocardial infarction (MI), but the biological link between MI and AD is unclear.

OBJECTIVE

To understand the association between the pathogenesis of MI and AD and identify common biomarkers of both diseases.

METHODS

Using public databases, we identified common biomarkers of MI and AD. Least absolute shrinkage and selection operator (LASSO) regression and protein-protein interaction (PPI) network were performed to further screen hub biomarkers. Functional enrichment analyses were performed on the hub biomarkers. Single-cell/nucleus analysis was utilized to further analyze the hub biomarkers at the cellular level in carotid atherosclerosis and AD datasets. Motif enrichment analysis was used to screen key transcription factors.

RESULTS

26 common differentially expressed genes were screened between MI and AD. Function enrichment analyses showed that these differentially expressed genes were mainly associated with inflammatory pathways. A key gene, Regulator of G-protein Signaling 1 (RGS1), was obtained by LASSO regression and PPI network. RGS1 was confirmed to mainly express in macrophages and microglia according to single-cell/nucleus analysis. The difference in expression of RGS1 in macrophages and microglia between disease groups and controls was statistically significant (p < 0.0001). The expression of RGS1 in the disease groups was upregulated with the differentiation of macrophages and microglia. RelA was a key transcription factor regulating RGS1.

CONCLUSION

Macrophages and microglia are involved in the inflammatory response of MI and AD. RGS1 may be a key biomarker in this process.