Single-cell RNA-sequencing reveals profound changes in circulating immune cells in patients with heart failure

Exploration of neuron heterogeneity in human heart failure with dilated cardiomyopathy through single-cell RNA sequencing analysis

OBJECTIVE

We aimed to explore the heterogeneity of neurons in heart failure with dilated cardiomyopathy (DCM).

METHODS

Single-cell RNA sequencing (scRNA-seq) data of patients with DCM and chronic heart failure and healthy samples from GSE183852 dataset were downloaded from NCBI Gene Expression Omnibus, in which neuron data were extracted for investigation. Cell clustering analysis, differential expression analysis, trajectory analysis, and cell communication analysis were performed, and highly expressed genes in neurons from patients were used to construct a protein-protein interaction (PPI) network and validated by GSE120895 dataset.

RESULTS

Neurons were divided into six subclusters involved in various biological processes and each subcluster owned its specific cell communication pathways. Neurons were differentiated into two branches along the pseudotime, one of which was differentiated into mature neurons, whereas another tended to be involved in the immune and inflammation response. Genes exhibited branch-specific differential expression patterns. FLNA, ITGA6, ITGA1, and MDK interacted more with other gene-product proteins in the PPI network. The differential expression of FLNA between DCM and control was validated.

CONCLUSION

Neurons have significant heterogeneity in heart failure with DCM, and may be involved in the immune and inflammation response to heart failure.

Identification and Validation of Hub Genes Related to Neutrophil Extracellular Traps-Mediated Cell Damage During Myocardial Infarction

Purpose

Studies have shown that neutrophil-mediated formation of neutrophil extracellular traps (NETs) leads to increased inflammatory response and cellular tissue damage during myocardial infarction (MI). We aimed to identify and validate possible hub genes in the process of NETs-mediated cell damage.

Methods

We performed an immune cell infiltration analysis of the MI transcriptome dataset based on CIBERSORT and ssGSEA algorithms. Gene expression profiles of NETs formation (GSE178883) were used to analyze the physiological processes of peripheral blood neutrophils after phorbol myristate acetate (PMA) stimulation. Bioinformatics and machine learning algorithms were utilized to find candidate hub genes based on NETs-related genes and transcriptome datasets (GSE66360 and GSE179828). We generated the receiver operating curve (ROC) to evaluate the diagnostic value of hub genes. Next, the correlation between hub genes and immune cells was analyzed using CIBERSORT, ssGSEA and xCell algorithms. Finally, we used quantitative real-time PCR (qRT-PCR) and immunohistochemistry to verify gene expression.

Results

Immune cell infiltration analysis revealed that inflammatory cells such as neutrophils were highly expressed in the peripheral blood of patients with MI. Functional analysis of differentially expressed genes (DEGs) in GSE178883 indicated that the potential pathogenesis lies in immune terms. Using weighted gene co-expression network analysis (WGCNA) and machine learning algorithms, we finally identified the seven hub genes (FCAR, IL1B, MMP9, NFIL3, CXCL2, ICAM1, and ZFP36). The qRT-PCR results showed that IL-1B, MMP9, and NFIL3 mRNA expression was up-regulated in the MI group compared to the control. Immunohistochemical results showed high MMP9, IL-1B, and NFIL3 expression in the infarcted area compared to the non-infarcted area and sham-operated groups.

Conclusion

We identified seven hub genes associated with NETs-mediated cellular damage during MI. Our results may provide insights into the mechanisms of neutrophil-mediated cell injury during MI.

Metabolism configures immune response across multi-systems: Lessons from COVID-19

Several studies over the last decade demonstrate the recruitment of immune cells, increased inflammatory cytokines, and chemokine in patients with metabolic diseases, including heart failure, parenchymal inflammation, obesity, tuberculosis, and diabetes mellitus. Metabolic rewiring of immune cells is associated with the severity and prevalence of these diseases. The risk of developing COVID-19/SARS-CoV-2 infection increases in patients with metabolic dysfunction (heart failure, diabetes mellitus, and obesity). Several etiologies, including fatigue, dyspnea, and dizziness, persist even months after COVID-19 infection, commonly known as Post-Acute Sequelae of CoV-2 (PASC) or long COVID. A chronic inflammatory state and metabolic dysfunction are the factors that contribute to long COVID. Here, this study explores the potential link between pathogenic metabolic and immune alterations across different organ systems that could underlie COVID-19 and PASC. These interactions could be utilized for targeted future therapeutic approaches.

Single-Cell RNA Sequencing of Coronary Perivascular Adipose Tissue From End-Stage Heart Failure Patients Identifies SPP1+ Macrophage Subpopulation as a Target for Alleviating Fibrosis

BACKGROUND

Perivascular adipose tissue (PVAT) is vital for vascular homeostasis, and PVAT dysfunction is associated with increased atherosclerotic plaque burden. But the mechanisms underlining coronary PVAT dysfunction in coronary atherosclerosis remain elusive.

METHODS

We performed single-cell RNA sequencing of the stromal vascular fraction of coronary PVAT from 3 groups of heart transplant recipients with end-stage heart failure, including 3 patients with nonobstructive coronary atherosclerosis, 3 patients with obstructive coronary artery atherosclerosis, and 4 nonatherosclerosis control subjects. Bioinformatics was used to annotate the cellular populations, depict the cellular developmental trajectories and interactions, and explore the differences among 3 groups of coronary PVAT at the cellular and molecular levels. Pathological staining, quantitative real-time polymerase chain reaction, and in vitro studies were performed to validate the key findings.

RESULTS

Ten cell types were identified among 67 936 cells from human coronary PVAT. Several cellular subpopulations, including SPP1+ (secreted phosphoprotein 1) macrophages and profibrotic fibroadipogenic progenitor cells, were accumulated in PVAT surrounding atherosclerotic coronary arteries compared with nonatherosclerosis coronary arteries. The fibrosis percentage was increased in PVAT surrounding atherosclerotic coronary arteries, and it was positively associated with the grade of coronary artery stenosis. Cellular interaction analysis suggested OPN (osteopontin) secreted by SPP1+ macrophages interacted with CD44 (cluster of differentiation 44)/integrin on fibroadipogenic progenitor cells. Strikingly, correlation analyses uncovered that higher level of SPP1 in PVAT correlates with a more severe fibrosis degree and a higher coronary stenosis grade. In vitro studies showed that conditioned medium from atherosclerotic coronary PVAT promoted the migration and proliferation of fibroadipogenic progenitor cells, while such effect was prevented by blocking CD44 or integrin.

CONCLUSIONS

SPP1+ macrophages accumulated in the PVAT surrounding atherosclerotic coronary arteries, and they promoted the migration and proliferation of fibroadipogenic progenitor cells via OPN-CD44/integrin interaction and thus aggravated the fibrosis of coronary PVAT, which was positively correlated to the coronary stenosis burden. Therefore, SPP1+ macrophages in coronary PVAT may participate in the progression of coronary atherosclerosis.

Single-cell transcriptomics reveal a hyperacute cytokine and immune checkpoint axis after cardiac arrest in patients with poor neurological outcome

BACKGROUND

Most patients hospitalized after cardiac arrest (CA) die because of neurological injury. The systemic inflammatory response after CA is associated with neurological injury and mortality but remains poorly defined.

METHODS

We determine the innate immune network induced by clinical CA at single-cell resolution.

FINDINGS

Immune cell states diverge as early as 6 h post-CA between patients with good or poor neurological outcomes 30 days after CA. Nectin-2+ monocyte and Tim-3+ natural killer (NK) cell subpopulations are associated with poor outcomes, and interactome analysis highlights their crosstalk via cytokines and immune checkpoints. Ex vivo studies of peripheral blood cells from CA patients demonstrate that immune checkpoints are a compensatory mechanism against inflammation after CA. Interferon γ (IFNγ)/interleukin-10 (IL-10) induced Nectin-2 on monocytes; in a negative feedback loop, Nectin-2 suppresses IFNγ production by NK cells.

CONCLUSIONS

The initial hours after CA may represent a window for therapeutic intervention in the resolution of inflammation via immune checkpoints.

FUNDING

This work was supported by funding from the American Heart Association, Brigham and Women's Hospital Department of Medicine, the Evergreen Innovation Fund, and the National Institutes of Health.

The Molecular Role of Immune Cells in Dilated Cardiomyopathy

Dilated cardiomyopathy (DCM) is a rare and severe condition characterized by chamber dilation and impaired contraction of the left ventricle. It constitutes a fundamental etiology for profound heart failure and abrupt cardiac demise, rendering it a prominent clinical indication for heart transplantation (HTx) among both adult and pediatric populations. DCM arises from various etiologies, including genetic variants, epigenetic disorders, infectious insults, autoimmune diseases, and cardiac conduction abnormalities. The maintenance of cardiac function involves two distinct types of immune cells: resident immune cells and recruited immune cells. Resident immune cells play a crucial role in establishing a harmonious microenvironment within the cardiac tissue. Nevertheless, in response to injury, cardiomyocytes initiate a cytokine cascade that attracts peripheral immune cells, thus perturbing this intricate equilibrium and actively participating in the initiation and pathological remodeling of dilated cardiomyopathy (DCM), particularly during the progression of myocardial fibrosis. Additionally, immune cells assume a pivotal role in orchestrating the inflammatory processes, which are intimately linked to the prognosis of DCM. Consequently, understanding the molecular role of various immune cells and their regulation mechanisms would provide an emerging era for managing DCM. In this review, we provide a summary of the most recent advancements in our understanding of the molecular mechanisms of immune cells in DCM. Additionally, we evaluate the effectiveness and limitations of immunotherapy approaches for the treatment of DCM, with the aim of optimizing future immunotherapeutic strategies for this condition.

Gene regulatory network study of rheumatoid arthritis in single-cell chromatin landscapes of peripheral blood mononuclear cells

OBJECTIVES

Assays for transposase-accessible chromatin with single-cell sequencing (scATAC-seq) contribute to the progress in epigenetic studies. The purpose of our project was to discover the transcription factors (TFs) that were involved in the pathogenesis of rheumatoid arthritis (RA) at a single-cell resolution using epigenetic technology.

METHODS

Peripheral blood mononuclear cells of seven RA patients and seven natural controls were extracted nuclei suspensions for library construction. Subsequently, scATAC-seq was performed to generate a high-resolution map of active regulatory DNA for bioinformatics analysis.

RESULTS

We obtained 22 accessible chromatin patterns. Then, 10 key TFs were involved in RA pathogenesis by regulating the activity of mitogen-activated protein kinase. Consequently, two genes (PTPRC and SPAG9) regulated by 10 key TFs were found, which may be associated with RA disease pathogenesis, and these TFs were obviously enriched in RA patients (P < .05, fold change value > 1.2). With further quantitative polymerase chain reaction validation on PTPRC and SPAG9 in monocytes, we found differential expression of these two genes, which were regulated by eight TFs [ZNF384, HNF1B, DMRTA2, MEF2A, NFE2L1, CREB3L4 (var. 2), FOSL2::JUNB (var. 2), and MEF2B], showing highly accessible binding sites in RA patients.

CONCLUSIONS

These findings demonstrate the value of using scATAC-seq to reveal transcriptional regulatory variation in RA-derived peripheral blood mononuclear cells, providing insights into therapy from an epigenetic perspective.

Immune heterogeneity in cardiovascular diseases from a single-cell perspective

A variety of immune cell subsets occupy different niches in the cardiovascular system, causing changes in the structure and function of the heart and vascular system, and driving the progress of cardiovascular diseases (CVDs). The immune cells infiltrating the injury site are highly diverse and integrate into a broad dynamic immune network that controls the dynamic changes of CVDs. Due to technical limitations, the effects and molecular mechanisms of these dynamic immune networks on CVDs have not been fully revealed. With recent advances in single-cell technologies such as single-cell RNA sequencing, systematic interrogation of the immune cell subsets is feasible and will provide insights into the way we understand the integrative behavior of immune populations. We no longer lightly ignore the role of individual cells, especially certain highly heterogeneous or rare subpopulations. We summarize the phenotypic diversity of immune cell subsets and their significance in three CVDs of atherosclerosis, myocardial ischemia and heart failure. We believe that such a review could enhance our understanding of how immune heterogeneity drives the progression of CVDs, help to elucidate the regulatory roles of immune cell subsets in disease, and thus guide the development of new immunotherapies.

Identification of m7G regulator-mediated RNA methylation modification patterns and related immune microenvironment regulation characteristics in heart failure

BACKGROUND

N⁷-methylguanosine (m⁷G) modification has been reported to regulate RNA expression in multiple pathophysiological processes. However, little is known about its role and association with immune microenvironment in heart failure (HF).

RESULTS

One hundred twenty-four HF patients and 135 nonfailing donors (NFDs) from six microarray datasets in the gene expression omnibus (GEO) database were included to evaluate the expression profiles of m⁷G regulators. Results revealed that 14 m⁷G regulators were differentially expressed in heart tissues from HF patients and NFDs. Furthermore, a five-gene m⁷G regulator diagnostic signature, NUDT16, NUDT4, CYFIP1, LARP1, and DCP2, which can easily distinguish HF patients and NFDs, was established by cross-combination of three machine learning methods, including best subset regression, regularization techniques, and random forest algorithm. The diagnostic value of five-gene m⁷G regulator signature was further validated in human samples through quantitative reverse-transcription polymerase chain reaction (qRT-PCR). In addition, consensus clustering algorithms were used to categorize HF patients into distinct molecular subtypes. We identified two distinct m⁷G subtypes of HF with unique m⁷G modification pattern, functional enrichment, and immune characteristics. Additionally, two gene subgroups based on m⁷G subtype-related genes were further discovered. Single-sample gene-set enrichment analysis (ssGSEA) was utilized to assess the alterations of immune microenvironment. Finally, utilizing protein-protein interaction network and weighted gene co-expression network analysis (WGCNA), we identified UQCRC1, NDUFB6, and NDUFA13 as m⁷G methylation-associated hub genes with significant clinical relevance to cardiac functions.

CONCLUSIONS

Our study discovered for the first time that m⁷G RNA modification and immune microenvironment are closely correlated in HF development. A five-gene m⁷G regulator diagnostic signature for HF (NUDT16, NUDT4, CYFIP1, LARP1, and DCP2) and three m⁷G methylation-associated hub genes (UQCRC1, NDUFB6, and NDUFA13) were identified, providing new insights into the underlying mechanisms and effective treatments of HF.

Wnt signaling pathway-derived score for predicting therapeutic resistance and tumor microenvironment in lung adenocarcinoma

Background: Lung adenocarcinoma (LUAD) is the most common subtype of lung cancer. Due to tumor heterogeneity, understanding the pathological mechanism of tumor progression helps to improve the diagnosis process and clinical treatment strategies of LUAD patients. Methods: The transcriptome pattern, mutant expression and complete clinical information were obtained from the cancer genome atlas (TCGA) database and microarray data from gene expression omnibus (GEO) database. Firstly, we used single sample Gene Set Enrichment Analysis (ssGSEA) to estimate the activation of Wnt signaling pathway in each sample. Consensus clustering algorithm was used to classify LUAD samples into different subgroups according to the transcription patterns of 152 Wnt signaling pathway related genes. Then, ESTIMATE, ssGSEA and Gene Set Variation Analysis (GSVA) algorithms were used to assess the biological pathways and immunocytes infiltration between different subtypes. LASSO-COX algorithm was conducted to construct prognostic model. Kaplan-Meier and multivariate Cox analysis were performed to evaluate the predictive performance of risk model. Gene features were further confirmed using external datasets. Finally, we conducted vitro assay for validating hub gene (LEF1). Results: Based on the transcription patterns of 152 Wnt signaling pathway related genes, four different subtypes of LUAD patients were screened out by consensus clustering algorithm. Subsequently, it was found that patients with cluster A and B had massive immunocytes infiltration, and the survival rate of patients with cluster B was better than that of other subgroups. According to the coefficients in the LASSO- Cox model and the transcriptome patterns of these 18 genes, the risk score was constructed for each sample. The degree of malignancy of LUAD patients with high-risk subgroup was remarkable higher than that of patients with low-risk subgroup (p < 0.001). Subsequently, five top prognostic genes (AXIN1, CTNNB1, LEF1, FZD2, FZD4.) were screened, and their expression values were different between cancer and normal tissues. FZD2 and LEF1 were negatively related to ImmunoScore, and AXIN1 was negatively related to ImmunoScore. The significant correlation between LUAD patient risk score and overall survival (OS) was verified in external datasets. In the A549 cell line, knockdown of LEF1 can reduce the invasive and proliferation ability of LUAD cells. Conclusion: A innovative 18 genes predictive feature based on transcriptome pattern was found in patients with lung adenocarcinoma. These investigations further promote the insight of the prognosis of lung adenocarcinoma and may contribute to disease management at risk stratification.

Single-cell and spatial transcriptomics: Advances in heart development and disease applications

Current transcriptomics technologies, including bulk RNA-seq, single-cell RNA sequencing (scRNA-seq), single-nucleus RNA-sequencing (snRNA-seq), and spatial transcriptomics (ST), provide novel insights into the spatial and temporal dynamics of gene expression during cardiac development and disease processes. Cardiac development is a highly sophisticated process involving the regulation of numerous key genes and signaling pathways at specific anatomical sites and developmental stages. Exploring the cell biological mechanisms involved in cardiogenesis also contributes to congenital heart disease research. Meanwhile, the severity of distinct heart diseases, such as coronary heart disease, valvular disease, cardiomyopathy, and heart failure, is associated with cellular transcriptional heterogeneity and phenotypic alteration. Integrating transcriptomic technologies in the clinical diagnosis and treatment of heart diseases will aid in advancing precision medicine. In this review, we summarize applications of scRNA-seq and ST in the cardiac field, including organogenesis and clinical diseases, and provide insights into the promise of single-cell and spatial transcriptomics in translational research and precision medicine.

Identification of biomarkers, pathways, and potential therapeutic targets for heart failure using next-generation sequencing data and bioinformatics analysis

BACKGROUND

Heart failure (HF) is the most common cardiovascular diseases and the leading cause of cardiovascular diseases related deaths. Increasing molecular targets have been discovered for HF prognosis and therapy. However, there is still an urgent need to identify novel biomarkers. Therefore, we evaluated biomarkers that might aid the diagnosis and treatment of HF.

METHODS

We searched next-generation sequencing (NGS) dataset (GSE161472) and identified differentially expressed genes (DEGs) by comparing 47 HF samples and 37 normal control samples using limma in R package. Gene ontology (GO) and pathway enrichment analyses of the DEGs were performed using the g: Profiler database. The protein-protein interaction (PPI) network was plotted with Human Integrated Protein-Protein Interaction rEference (HiPPIE) and visualized using Cytoscape. Module analysis of the PPI network was done using PEWCC1. Then, miRNA-hub gene regulatory network and TF-hub gene regulatory network were constructed by Cytoscape software. Finally, we performed receiver operating characteristic (ROC) curve analysis to predict the diagnostic effectiveness of the hub genes.

RESULTS

A total of 930 DEGs, 464 upregulated genes and 466 downregulated genes, were identified in HF. GO and REACTOME pathway enrichment results showed that DEGs mainly enriched in localization, small molecule metabolic process, SARS-CoV infections, and the citric acid tricarboxylic acid (TCA) cycle and respiratory electron transport. After combining the results of the PPI network miRNA-hub gene regulatory network and TF-hub gene regulatory network, 10 hub genes were selected, including heat shock protein 90 alpha family class A member 1 (HSP90AA1), arrestin beta 2 (ARRB2), myosin heavy chain 9 (MYH9), heat shock protein 90 alpha family class B member 1 (HSP90AB1), filamin A (FLNA), epidermal growth factor receptor (EGFR), phosphoinositide-3-kinase regulatory subunit 1 (PIK3R1), cullin 4A (CUL4A), YEATS domain containing 4 (YEATS4), and lysine acetyltransferase 2B (KAT2B).

CONCLUSIONS

This discovery-driven study might be useful to provide a novel insight into the diagnosis and treatment of HF. However, more experiments are needed in the future to investigate the functional roles of these genes in HF.

Single-cell transcriptomics reveals cell type-specific immune regulation associated with anti-NMDA receptor encephalitis in humans

Introduction

Anti-N-methyl-D-aspartate receptor encephalitis (anti-NMDARE) is a rare autoimmune disease, and the peripheral immune characteristics associated with anti-NMDARE antibodies remain unclear.

Methods

Herein, we characterized peripheral blood mononuclear cells from patients with anti-NMDARE and healthy individuals by single-cell RNA sequencing (scRNA-seq).

Results

The transcriptional profiles of 129,217 cells were assessed, and 21 major cell clusters were identified. B-cell activation and differentiation, plasma cell expansion, and excessive inflammatory responses in innate immunity were all identified. Patients with anti-NMDARE showed higher expression levels of CXCL8, IL1B, IL6, TNF, TNFSF13, TNFSF13B, and NLRP3. We observed that anti-NMDARE patients in the acute phase expressed high levels of DC_CCR7 in human myeloid cells. Moreover, we observed that anti-NMDARE effects include oligoclonal expansions in response to immunizing agents. Strong humoral immunity and positive regulation of lymphocyte activation were observed in acute stage anti-NMDARE patients.

Discussion

This high-dimensional single-cell profiling of the peripheral immune microenvironment suggests that potential mechanisms are involved in the pathogenesis and recovery of anti-NMDAREs.

Cellular Landscapes of Nondiseased Human Cardiac Valves From End-Stage Heart Failure-Explanted Heart

BACKGROUND

Exploring the mechanisms of valvular heart disease at the cellular level may be useful to identify new therapeutic targets; however, the comprehensive cellular landscape of nondiseased human cardiac valve leaflets remains unclear.

METHODS

The cellular landscapes of nondiseased human cardiac valve leaflets (5 aortic valves, 5 pulmonary valves, 5 tricuspid valves, and 3 mitral valves) from end-stage heart failure patients undergoing heart transplantation were explored using single-cell RNA sequencing. Bioinformatics was used to identify the cell types, describe the cell functions, and investigate cellular developmental trajectories and interactions. Differences among the 4 types of cardiac valves at the cellular level were summarized. Pathological staining was performed to validate the key findings of single-cell RNA sequencing. An integrative analysis of our single-cell data and published genome-wide association study-based and bulk RNA sequencing-based data provided insights into the cell-specific contributions to calcific aortic valve diseases.

RESULTS

Six cell types were identified among 128 412 cells from nondiseased human cardiac valve leaflets. Valvular interstitial cells were the largest population, followed by myeloid cells, lymphocytes, valvular endothelial cells, mast cells, and myofibroblasts. The 4 types of cardiac valve had distinct cellular compositions. The intercellular communication analysis revealed that valvular interstitial cells were at the center of the communication network. The integrative analysis of our single-cell RNA sequencing data revealed key cellular subpopulations involved in the pathogenesis of calcific aortic valve diseases.

CONCLUSIONS

The cellular landscape differed among the 4 types of nondiseased cardiac valve, which might explain their differences in susceptibility to pathological remodeling and valvular heart disease.

Identification and verification of immune-related biomarkers and immune infiltration in diabetic heart failure

PURPOSE

Diabetic heart failure (DHF) or cardiomyopathy is a common complication of diabetes; however, the underlying mechanism is not clear. In the present study, the authors searched for differentially expressed genes associated with DHF and the molecular types of immune cells based on bioinformatics.

METHODS

The RNA expression dataset of DHF was obtained from the NCBI Gene Expression Omnibus (GEO) database. After preprocessing the data, the differentially expressed genes (DEGs) between the DHF group and the non-diabetic heart failure (NHF) group were screened and intersected with immune-related genes (IRGs) in the ImmPort database. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed using the DAVID tool. The ssGSEA algorithm was used to evaluate immune infiltration of the heart tissue in each group. In addition, the protein-protein interaction (PPI) network and miRNA-mRNA network were constructed using the STRING online website and Cytoscape program. Finally, validation analysis was performed using animal models.

RESULTS

Eight immune-related core genes were identified. GO and KEGG showed that core genes were mainly enriched in angiogenesis and cytokine-cytokine receptor interaction. Immune infiltration results showed that activated dendritic cells, central memory CD4 T cells, central memory CD8 T cells, myeloid-derived suppressor cells (MDSCs), neutrophils, and regulatory T cells may be involved in DHF. Neutrophils may play a key role in the pathogenesis of HF in diabetes.

CONCLUSION

Immune-related core genes and immune infiltrating cells provide a new perspective on the pathogenesis of DHF.

From novel discovery tools and biomarkers to precision medicine-basic cardiovascular science highlights of 2021/22

Here, we review the highlights of cardiovascular basic science published in 2021 and early 2022 on behalf of the European Society of Cardiology Council for Basic Cardiovascular Science. We begin with non-coding RNAs which have emerged as central regulators cardiovascular biology, and then discuss how technological developments in single-cell 'omics are providing new insights into cardiovascular development, inflammation, and disease. We also review recent discoveries on the biology of extracellular vesicles in driving either protective or pathogenic responses. The Nobel Prize in Physiology or Medicine 2021 recognized the importance of the molecular basis of mechanosensing and here we review breakthroughs in cardiovascular sensing of mechanical force. We also summarize discoveries in the field of atherosclerosis including the role of clonal haematopoiesis of indeterminate potential, and new mechanisms of crosstalk between hyperglycaemia, lipid mediators, and inflammation. The past 12 months also witnessed major advances in the field of cardiac arrhythmia including new mechanisms of fibrillation. We also focus on inducible pluripotent stem cell technology which has demonstrated disease causality for several genetic polymorphisms in long-QT syndrome and aortic valve disease, paving the way for personalized medicine approaches. Finally, the cardiovascular community has continued to better understand COVID-19 with significant advancement in our knowledge of cardiovascular tropism, molecular markers, the mechanism of vaccine-induced thrombotic complications and new anti-viral therapies that protect the cardiovascular system.

Transcriptomic profile analysis of the left atrium in spontaneously hypertensive rats in the early stage

Left atrial remodeling, characterized by enlargement and hypertrophy of the left atrium and increased fibrosis, was accompanied by an increased incidence of atrial fibrillation. While before morphological changes at the early stage of hypertension, how overloaded hypertension influences the transcriptomic profile of the left atrium remains unclear. Therefore, RNA-sequencing was performed to define the RNA expressing profiles of left atrium in spontaneously hypertensive rats (SHRs) and normotensive Wistar-Kyoto (WKY) rats as a control group. We also compared the changes in the RNA expression profiles in SHRs treated with an angiotensin receptor blocker (ARB) and angiotensin receptor-neprilysin inhibitor (ARNI) to assess the distinct effects on the left atrium. In total, 1,558 differentially expressed genes were found in the left atrium between WKY rats and SHRs. Bioinformatics analysis showed that these mRNAs could regulate upstream pathways in atrial remodeling through atrial fibrosis, inflammation, electrical remodeling, and cardiac metabolism. The regulated transcripts detected in the left atrial tissue in both the ARB-treated and ARNI-treated groups were related to metabolism. In contrast to the ARB-treated rates, the transcripts in ARNI-treated rats were mapped to the cyclic guanosine monophosphate-protein kinase G signaling pathway.

Pro-Inflammatory Derangement of the Immuno-Interactome in Heart Failure

Chronic heart failure (HF) is a syndrome of heterogeneous etiology associated with multiple co-morbidities. Inflammation is increasingly recognized as a key contributor to the pathophysiology of HF. Heterogeneity and lack of data on the immune mechanism(s) contributing to HF may partially underlie the failure of clinical trials targeting inflammatory mediators. We studied the Immunome in HF cohort using mass cytometry and used data-driven systems immunology approach to discover and characterize modulated immune cell subsets from peripheral blood. We showed cytotoxic and inflammatory innate lymphoid and myeloid cells were expanded in HF patients compared to healthy controls. Network analysis showed highly modular and centralized immune cell architecture in healthy control immune cell network. In contrast, the HF immune cell network showed greater inter-cellular communication and less modular structure. Furthermore, we found, as an immune mechanism specific to HF with preserved ejection fraction (HFpEF), an increase in inflammatory MAIT and CD4 T cell subsets.

The Biological Functions and Regulatory Mechanisms of Fatty Acid Binding Protein 5 in Various Diseases

In recent years, fatty acid binding protein 5 (FABP5), also known as fatty acid transporter, has been widely researched with the help of modern genetic technology. Emerging evidence suggests its critical role in regulating lipid transport, homeostasis, and metabolism. Its involvement in the pathogenesis of various diseases such as metabolic syndrome, skin diseases, cancer, and neurological diseases is the key to understanding the true nature of the protein. This makes FABP5 be a promising component for numerous clinical applications. This review has summarized the most recent advances in the research of FABP5 in modulating cellular processes, providing an in-depth analysis of the protein’s biological properties, biological functions, and mechanisms involved in various diseases. In addition, we have discussed the possibility of using FABP5 as a new diagnostic biomarker and therapeutic target for human diseases, shedding light on challenges facing future research.

Single-cell technologies to decipher cardiovascular diseases

Cardiovascular disease remains the leading cause of death worldwide. A deeper understanding of the multicellular composition and molecular processes may help to identify novel therapeutic strategies. Single-cell technologies such as single-cell or single-nuclei RNA sequencing provide expression profiles of individual cells and allow for dissection of heterogeneity in tissue during health and disease. This review will summarize (i) how these novel technologies have become critical for delineating mechanistic drivers of cardiovascular disease, particularly, in humans and (ii) how they might serve as diagnostic tools for risk stratification or individualized therapy. The review will further discuss technical pitfalls and provide an overview of publicly available human and mouse data sets that can be used as a resource for research.

Single-Cell RNA Sequencing Reveals the Temporal Diversity and Dynamics of Cardiac Immunity after Myocardial Infarction

Myocardial infarction (MI) is strongly associated with the temporal regulation of cardiac immunity. However, a variety of current clinical trials have failed because of the lack of post-MI immunomodulating/anti-inflammatory targets. Single-cell RNA sequencing analysis of the cardiac Cd45⁺ immune cell at 0, 3, 7, and 14 d after injury in a mouse left anterior descending coronary artery ligation model is performed. Major immune cell populations, distinct subsets, and dynamic changes are identified. Macrophages (Mø) are most abundant, peaking at 3 d after infarction. Mø-5 and Mø-6 are the predominant infiltrated subsets at this time point, with strong expression of inflammatory factors. Further analysis demonstrates that suppressing these sets attenuated pathological MI progression by preventing subsequent leukocyte extravasation and adverse remodeling. Abundant apoptotic neutrophils and a profibrotic macrophage subset on days 7 and 14, respectively, are also detected. These results provide a basis for developing cell type- and time-specific interventions in MI.

Progress of Single-Cell RNA Sequencing Technology in Myocardial Infarction Research

After myocardial infarction, the heart enters a remodeling and repair phase that involves myocardial cell damage, inflammatory response, fibroblast activation, and, ultimately, angiogenesis. In this process, the proportions and functions of cardiomyocytes, immune cells, fibroblasts, endothelial cells, and other cells change. Identification of the potential differences in gene expression among cell types and/or transcriptome heterogeneity among cells of the same type greatly contribute to understanding the cellular changes that occur in heart and disease conditions. Recent advent of the single-cell transcriptome sequencing technology has facilitated the exploration of single cell diversity as well as comprehensive elucidation of the natural history and molecular mechanisms of myocardial infarction. In this manner, novel putative therapeutic targets for myocardial infarction treatment may be detected and clinically applied.

Identification of Diagnostic Biomarkers Associated with Stromal and Immune Cell Infiltration in Fatty Infiltration After Rotator Cuff Tear by Integrating Bioinformatic Analysis and Machine-Learning

Purpose

The present study aimed to explore potential diagnostic biomarkers for fatty infiltration (FI) of the rotator cuff muscles after rotator cuff tear (RCT) and investigate the influence of stromal and immune cell infiltration on this pathology.

Methods

The GSE130447 and GSE103266 datasets were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were identified, and gene set enrichment analyses were performed by R software. Two machine learning algorithms, random forest and multiple support vector machine recursive feature elimination (mSVM-RFE), were used to screen candidate biomarkers. The diagnostic value of the screened biomarkers was further validated by the area under the ROC curve (AUC) in the GSE103266 dataset. Murine microenvironment cell population counter (mMCP-counter) method was employed to estimate stromal and immune cell infiltration of FI. The correlation between biomarkers and infiltrated immune and stromal cell subsets was further analyzed.

Results

A total of 2123 DEGs were identified. The identified DEGs were predominantly linked to immune system process, extracellular matrix organization and PPAR signalling pathway. FABP5 (AUC = 0.958) and MGP (AUC = 1) were screened as diagnostic biomarkers of FI. Stromal and immune cell infiltration analysis showed that monocytes, mast cells, vessels, endothelial cells and fibroblasts may be related to the process of FI. FABP5 and MGP were positively correlated with vessels whereas negatively correlated with monocytes and mast cells.

Conclusion

FABP5 and MGP can serve as diagnostic biomarkers of FI after RCT, and stromal and immune cell infiltration may play a crucial role in this pathology.

Pathophysiology of Heart Failure: A Role for Peripheral Blood Mononuclear Cells Mitochondrial Dysfunction?

Heart failure (HF) is a leading cause of hospitalization in patients aged more than 65 years and is associated with high mortality rates. A better comprehension of its physiopathology is still needed, and, in addition to neurohormonal systems and sodium glucose co-transporter 2 modulations, recent studies focus on the mitochondrial respiration of peripheral blood circulating cells (PBMCs). Thus, cardiovascular metabolic risk factors and cellular switch with an increased neutrophil/lymphocytes ratio might favor the decreased PBMC mitochondrial respiration observed in relation with HF severity. PBMCs are implicated in the immune system function and mitochondrial dysfunction of PBMC, potentially induced by their passage through a damaged heart and by circulating mitoDAMPs, which can lead to a vicious circle, thus sustaining negative cardiac remodeling during HF. This new approach of HF complex pathophysiology appears to be a promising field of research, and further studies on acute and chronic HF with reduced or preserved LVEF are warranted to better understand whether circulating PBMC mitochondrial function and mitoDAMPs follow-ups in HF patients might show diagnosis, prognosis or therapeutic usefulness.

Comparative analysis of common alignment tools for single-cell RNA sequencing

BACKGROUND

With the rise of single-cell RNA sequencing new bioinformatic tools have been developed to handle specific demands, such as quantifying unique molecular identifiers and correcting cell barcodes. Here, we benchmarked several datasets with the most common alignment tools for single-cell RNA sequencing data. We evaluated differences in the whitelisting, gene quantification, overall performance, and potential variations in clustering or detection of differentially expressed genes. We compared the tools Cell Ranger version 6, STARsolo, Kallisto, Alevin, and Alevin-fry on 3 published datasets for human and mouse, sequenced with different versions of the 10X sequencing protocol.

RESULTS

Striking differences were observed in the overall runtime of the mappers. Besides that, Kallisto and Alevin showed variances in the number of valid cells and detected genes per cell. Kallisto reported the highest number of cells; however, we observed an overrepresentation of cells with low gene content and unknown cell type. Conversely, Alevin rarely reported such low-content cells. Further variations were detected in the set of expressed genes. While STARsolo, Cell Ranger 6, Alevin-fry, and Alevin produced similar gene sets, Kallisto detected additional genes from the Vmn and Olfr gene family, which are likely mapping artefacts. We also observed differences in the mitochondrial content of the resulting cells when comparing a prefiltered annotation set to the full annotation set that includes pseudogenes and other biotypes.

CONCLUSION

Overall, this study provides a detailed comparison of common single-cell RNA sequencing mappers and shows their specific properties on 10X Genomics data.

Integrative Analysis of Bulk and Single-Cell RNA Sequencing Data Reveals Cell Types Involved in Heart Failure

Owing to the high mortality rates of heart failure (HF), a more detailed description of the HF becomes extremely urgent. Since the pathogenesis of HF remain elusive, a thorough identification of the genetic factors will provide novel insights into the molecular basis of this cardiac dysfunction. In our research, we performed publicly available transcriptome profiling datasets, including non-failure (NF), dilated cardiomyopathy (DCM) and ischemic cardiomyopathy (ICM) hearts tissues. Through principal component analysis (PCA), gene differential expression analysis, gene set enrichment analysis (GSEA), and gene Set Variation Analysis (GSVA), we figured out the candidate genes noticeably altered in HF, the specific biomarkers of endothelial cell (EC) and cardiac fibrosis, then validated the differences of the inflammation-related cell adhesion molecules (CAMs), extracellular matrix (ECM) genes, and immune responses. Taken together, our results suggested the EC and fibroblast could be activated in response to HF. DCM and ICM had both commonality and specificity in the pathogenesis of HF. Higher inflammation in ICM might related to autocrine CCL3/CCL4-CCR5 interaction induced chemokine signaling activation. Furthermore, the activities of neutrophil and macrophage were higher in ICM than DCM. These findings identified features of the landscape of previously underestimated cellular, transcriptomic heterogeneity between ICM and DCM.

N6-Methyladenosine-Related Gene Signature Associated With Monocyte Infiltration Is Clinically Significant in Gestational Diabetes Mellitus

OBJECTIVE

The objective of this study was to reveal the potential crosstalk between immune infiltration and N⁶- methyladenosine (m⁶A) modification in the placentas of patients with gestational diabetes mellitus (GDM), and to construct a model for the diagnosis of GDM.

METHODS

We analyzed imbalanced immune infiltration and differentially expressed m⁶A-related genes (DMRGs) in the placentas of patients with GDM, based on the GSE70493 dataset. An immune-related DMRG signature, with significant classifying power and diagnostic value, was identified using a least absolute shrinkage and selection operator (LASSO) regression. Based on the selected DMRGs, we developed and validated a nomogram model using GSE70493 and GSE92772 as the training and validation sets, respectively.

RESULTS

Infiltration of monocytes was higher in GDM placentas than in control samples, while the infiltration of macrophages (M1 and M2) in GDM placentas was lower than in controls. A total of 14 DMRGs were strongly associated with monocyte infiltration, seven of which were significant in distinguishing patients with GDM from normal controls. These genes were CD81, CFH, FABP5, GBP1, GNG11, IL1RL1, and SLAMF6. The calibration curve, decision curve, clinical impact curve, and receiver operating characteristic curve showed that the nomogram recognized GDM with high accuracy in both the training and validation sets.

CONCLUSIONS

Our results provide clues that crosstalk between m⁶A modification and immune infiltration may have implications in terms of novel biomarkers and therapeutic targets for GDM.

Identification of CALU and PALLD as Potential Biomarkers Associated With Immune Infiltration in Heart Failure

Background: Inflammatory activation and immune infiltration play important roles in the pathologic process of heart failure (HF). The current study is designed to investigate the immune infiltration and identify related biomarkers in heart failure patients due to ischemic cardiomyopathy. Methods: Expression data of HF due to ischemic cardiomyopathy (CM) samples and non-heart failure (NF) samples were downloaded from gene expression omnibus (GEO) database. Differentially expressed genes (DEGs) between CM and NF samples were identified. Single sample gene set enrichment analysis (ssGSEA) was performed to explore the landscape of immune infiltration. Weighted gene co-expression network analysis (WGCNA) was applied to screen the most relevant module associated with immune infiltration. The diagnostic values of candidate genes were evaluated by receiver operating curves (ROC) curves. The mRNA levels of potential biomarkers in the peripheral blood mononuclear cells (PBMCs) isolated from 10 CM patients and 10 NF patients were analyzed to further assess their diagnostic values. Results: A total of 224 DEGs were identified between CM and NF samples in GSE5406, which are mainly enriched in the protein processing and extracellular matrix related biological processes and pathways. The result of ssGSEA showed that the abundance of dendritic cells (DC), mast cells, natural killer (NK) CD56dim cells, T cells, T follicular helper cells (Tfh), gammadelta T cells (Tgd) and T helper 2 (Th2) cells were significantly higher, while the infiltration of eosinophils and central memory T cells (Tcm) were lower in CM samples compared to NF ones. Correlation analysis revealed that Calumenin (CALU) and palladin (PALLD) were negatively correlated with the abundance of DC, NK CD56dim cells, T cells, Tfh, Tgd and Th2 cells, but positively correlated with the level of Tcm. More importantly, CALU and PALLD were significantly lower in PBMCs from CM patients compared to NF ones. Conclusion: Our study revealed that CALU and PALLD are potential biomarkers associated with immune infiltration in heart failure due to ischemic cardiomyopathy.

Reciprocal organ interactions during heart failure: a position paper from the ESC Working Group on Myocardial Function

Heart failure-either with reduced or preserved ejection fraction (HFrEF/HFpEF)-is a clinical syndrome of multifactorial and gender-dependent aetiology, indicating the insufficiency of the heart to pump blood adequately to maintain blood flow to meet the body's needs. Typical symptoms commonly include shortness of breath, excessive fatigue with impaired exercise capacity, and peripheral oedema, thereby alluding to the fact that heart failure is a syndrome that affects multiple organ systems. Patients suffering from progressed heart failure have a very limited life expectancy, lower than that of numerous cancer types. In this position paper, we provide an overview regarding interactions between the heart and other organ systems, the clinical evidence, underlying mechanisms, potential available or yet-to-establish animal models to study such interactions and finally discuss potential new drug interventions to be developed in the future. Our working group suggests that more experimental research is required to understand the individual molecular mechanisms underlying heart failure and reinforces the urgency for tailored therapeutic interventions that target not only the heart but also other related affected organ systems to effectively treat heart failure as a clinical syndrome that affects and involves multiple organs.

FABP5 Deficiency Impairs Mitochondrial Function and Aggravates Pathological Cardiac Remodeling and Dysfunction

Fatty acid-binding protein 5 (FABP5) is an important member of the FABP family and plays a vital role in the metabolism of fatty acids. However, few studies have examined the role of FABP5 in pathological cardiac remodeling and heart failure. The aim of this study was to explore the role of FABP5 in transverse aortic constriction (TAC)-induced pathological cardiac remodeling and dysfunction in mice. Quantitative RT-PCR (qRT-PCR) and western blotting (WB) analysis showed that the levels of FABP5 mRNA and protein, respectively, were upregulated in hearts of the TAC model. Ten weeks after TAC in FABP5 knockout and wild type control mice, echocardiography, histopathology, qRT-PCR, and WB demonstrated that FABP5 deficiency aggravated cardiac injury (both cardiac hypertrophy and fibrosis) and dysfunction. In addition, transmission electron microscopy, ATP detection, and WB revealed that TAC caused severe impairment to mitochondria in the hearts of FABP5-deficient mice compared with that in control mice. When FABP5 was downregulated by siRNA in primary mouse cardiac fibroblasts, FABP5 silencing increased oxidative stress, reduced mitochondrial respiration, and increased the expression of myofibroblast activation marker genes in response to treatment with transforming growth factor-β. Our findings demonstrate that FABP5 deficiency aggravates cardiac pathological remodeling and dysfunction by damaging cardiac mitochondrial function.

Association of Clonal Hematopoiesis of Indeterminate Potential With Inflammatory Gene Expression in Patients With Severe Degenerative Aortic Valve Stenosis or Chronic Postischemic Heart Failure

Importance

Cytokine release syndrome is a complication of coronavirus disease 2019. Clinically, advanced age and cardiovascular comorbidities are the most important risk factors.

Objective

To determine whether clonal hematopoiesis of indeterminate potential (CHIP), an age-associated condition with excess cardiovascular risk defined as the presence of an expanded, mutated somatic blood cell clone in persons without other hematological abnormalities, may be associated with an inflammatory gene expression sensitizing monocytes to aggravated immune responses.

Design, Setting, and Participants

This hypothesis-generating diagnostic study examined a cohort of patients with severe degenerative aortic valve stenosis or chronic postinfarction heart failure, as well as age-matched healthy control participants. Single-cell RNA sequencing and analyses of circulating peripheral monocytes was done between 2017 and 2019 to assess the transcriptome of circulating monocytes.

Exposures

Severe degenerative aortic valve stenosis or chronic postinfarction heart failure.

Main Outcomes and Measures

CHIP-driver sequence variations in monocytes with a proinflammatory signature of genes involved in cytokine release syndrome.

Results

The study included 8 patients with severe degenerative aortic valve stenosis, 6 with chronic postinfarction heart failure, and 3 healthy control participants. Their mean age was 75.7 (range, 54-89) years, and 6 were women. Mean CHIP-driver gene variant allele frequency was 4.2% (range, 2.5%-6.9%) for DNMT3A and 14.3% (range, 2.6%-37.4%) for TET2. Participants with DNMT3A or TET2 CHIP-driver sequence variations displayed increased expression of interleukin 1β (no CHIP-driver sequence variations, 1.6217 normalized Unique Molecular Identifiers [nUMI]; DNMT3A, 5.3956 nUMI; P < .001; TET2, 10.8216 nUMI; P < .001), the interleukin 6 receptor (no CHIP-driver sequence variations, 0.5386 nUMI; DNMT3A, 0.9162 nUMI; P < .001;TET2, 0.5738 nUMI; P < .001), as well as the NLRP3 inflammasome complex (no CHIP-driver sequence variations, 0.4797 nUMI; DNMT3A, 0.9961 nUMI; P < .001; TET2, 1.2189 nUMI; P < .001), plus upregulation of CD163 (no CHIP-driver sequence variations, 0.5239 nUMI; DNMT3A, 1.4722 nUMI; P < .001; TET2, 1.0684 nUMI; P < .001), a cellular receptor capable of mediating infection, macrophage activation syndrome, and other genes involved in cytokine response syndrome. Gene ontology term analyses of regulated genes revealed that the most significantly upregulated genes encode for leukocyte-activation and interleukin-signaling pathways in monocytes of individuals with DNMT3A (myeloid leukocyte activation: log[Q value], -50.1986; log P value, -54.5177; regulation of cytokine production: log[Q value], -21.0264; log P value, -24.1993; signaling by interleukins: log[Q value], -18.0710: log P value, -21.1597) or TET2 CHIP-driver sequence variations (immune response: log[Q value], -36.3673; log P value, -40.6864; regulation of cytokine production: log[Q value], -13.1733; log P value, -16.3463; signaling by interleukins: log[Q value], -12.6547: log P value, -15.7977).

Conclusions and Relevance

Monocytes of individuals who carry CHIP-driver sequence variations and have cardiovascular disease appear to be primed for excessive inflammatory responses. Further studies are warranted to address potential adverse outcomes of coronavirus disease 2019 in patients with CHIP-driver sequence variations.

Understanding the Adult Mammalian Heart at Single-Cell RNA-Seq Resolution

During the last decade, extensive efforts have been made to comprehend cardiac cell genetic and functional diversity. Such knowledge allows for the definition of the cardiac cellular interactome as a reasonable strategy to increase our understanding of the normal and pathologic heart. Previous experimental approaches including cell lineage tracing, flow cytometry, and bulk RNA-Seq have often tackled the analysis of cardiac cell diversity as based on the assumption that cell types can be identified by the expression of a single gene. More recently, however, the emergence of single-cell RNA-Seq technology has led us to explore the diversity of individual cells, enabling the cardiovascular research community to redefine cardiac cell subpopulations and identify relevant ones, and even novel cell types, through their cell-specific transcriptomic signatures in an unbiased manner. These findings are changing our understanding of cell composition and in consequence the identification of potential therapeutic targets for different cardiac diseases. In this review, we provide an overview of the continuously changing cardiac cellular landscape, traveling from the pre-single-cell RNA-Seq times to the single cell-RNA-Seq revolution, and discuss the utilities and limitations of this technology.

Plasma Metabolites Alert Patients With Chest Pain to Occurrence of Myocardial Infarction

Myocardial infarction (MI) is one of the leading causes of death worldwide, and knowing the early warning signs of MI is lifesaving. To expand our knowledge of MI, we analyzed plasma metabolites in MI and non-MI chest pain cases to identify markers for alerting about MI occurrence based on metabolomics. A total of 230 volunteers were recruited, consisting of 146 chest pain patients admitted with suspected MI (85 MIs and 61 non-MI chest pain cases) and 84 control individuals. Non-MI cardiac chest pain cases include unstable angina (UA), myocarditis, valvular heart diseases, etc. The blood samples of all suspected MI cases were collected not longer than 6 h since the onset of chest pain. Gas chromatography-mass spectrometry and liquid chromatography-mass spectrometry were applied to identify and quantify the plasma metabolites. Multivariate statistical analysis was utilized to analyze the data, and principal component analysis showed MI could be clearly distinguished from non-MI chest pain cases (including UA and other cases) in the scores plot of metabolomic data, better than that based on the data constructed with medical history and clinical biochemical parameters. Pathway analysis highlighted an upregulated methionine metabolism and downregulated arginine biosynthesis in MI cases. Receiver operating characteristic curve (ROC) and adjusted odds ratio (OR) were calculated to evaluate potential markers for the diagnosis and prediction ability of MI (MI vs. non-MI cases). Finally, gene expression profiles from the Gene Expression Omnibus (GEO) database were briefly discussed to study differential metabolites' connection with plasma transcriptomics. Deoxyuridine (dU), homoserine, and methionine scored highly in ROC analysis (AUC > 0.91), sensitivity (>80%), and specificity (>94%), and they were correlated to LDH and AST (p < 0.05). OR values suggested, after adjusting for gender, age, lipid levels, smoking, type II diabetes, and hypertension history, that high levels of dU of positive logOR = 3.01, methionine of logOR = 3.48, and homoserine of logOR = 1.61 and low levels of isopentenyl diphosphate (IDP) of negative logOR = -5.15, uracil of logOR = -2.38, and arginine of logOR = -0.82 were independent risk factors of MI. Our study highlighted that metabolites belonging to pyrimidine, methionine, and arginine metabolism are deeply influenced in MI plasma samples. dU, homoserine, and methionine are potential markers to recognize MI cases from other cardiac chest pain cases after the onset of chest pains. Individuals with high plasma abundance of dU, homoserine, or methionine have increased risk of MI, too.

Ex uno, plures-From One Tissue to Many Cells: A Review of Single-Cell Transcriptomics in Cardiovascular Biology

Recent technological advances have revolutionized the study of tissue biology and garnered a greater appreciation for tissue complexity. In order to understand cardiac development, heart tissue homeostasis, and the effects of stress and injury on the cardiovascular system, it is essential to characterize the heart at high cellular resolution. Single-cell profiling provides a more precise definition of tissue composition, cell differentiation trajectories, and intercellular communication, compared to classical bulk approaches. Here, we aim to review how recent single-cell multi-omic studies have changed our understanding of cell dynamics during cardiac development, and in the healthy and diseased adult myocardium.

Biological and Medical Importance of Cellular Heterogeneity Deciphered by Single-Cell RNA Sequencing

The present review discusses recent progress in single-cell RNA sequencing (scRNA-seq), which can describe cellular heterogeneity in various organs, bodily fluids, and pathologies (e.g., cancer and Alzheimer's disease). We outline scRNA-seq techniques that are suitable for investigating cellular heterogeneity that is present in cell populations with very high resolution of the transcriptomic landscape. We summarize scRNA-seq findings and applications of this technology to identify cell types, activity, and other features that are important for the function of different bodily organs. We discuss future directions for scRNA-seq techniques that can link gene expression, protein expression, cellular function, and their roles in pathology. We speculate on how the field could develop beyond its present limitations (e.g., performing scRNA-seq in situ and in vivo). Finally, we discuss the integration of machine learning and artificial intelligence with cutting-edge scRNA-seq technology, which could provide a strong basis for designing precision medicine and targeted therapy in the future.