Identification of Genetic Biomarkers for Diagnosis of Myocardial Infarction Compared with Angina Patients

The single-cell atlas of short-chain fatty acid receptors in human and mice hearts

Introduction

The gut microbiota metabolite, short-chain fatty acids (SCFAs), can protect against multiple cardiovascular diseases, while the molecular targets and underlying mechanisms need to be elucidated. One of the primary mechanisms of SCFA benefits was the direct activation of a group of G-protein-coupled receptors (GPCRs), termed free fatty acid receptors (FFARs), the FFAR2 (GPR43), and FFAR3 (GPR41). At present, the distribution of FFAR2/3 in cardiac cells has not been entirely clarified.

Methods

Using 18 public single-cell RNA-seq and single-nuclear RNA-seq data of human and mouse hearts, we illustrate the entire atlas of FFAR2/3 distribution in different regions and cell types in normal and infarcted hearts.

Results and discussion

We present the atlas of FFAR2/3 in the whole human body, normal and infarcted hearts at single-cell resolution. We also illustrated the entire atlas of FFAR2/3 in normal/ischemic hearts of newborn and adult mice by combining public and newly built sc/snRNA-seq datasets. These findings provide valuable information on the possible effect of SCFAs via FFAR2/3 in the heart and valuable references for future studies.

ELF5-Regulated lncRNA-TTN-AS1 Alleviates Myocardial Cell Injury via Recruiting PCBP2 to Increase CDK6 Stability in Myocardial Infarction

Myocardial infarction (MI) seriously threatens the health of elderly people, and reducing myocardial injury is of great significance for the treatment of MI. LncRNA-TTN-AS1 shows protective effects on cardiomyocyte injury, while the role of TTN-AS1 in MI remains unknown. CCK8, flow cytometry, and JC-1 staining assessed cell viability, apoptosis and mitochondrial membrane potential (MMP), respectively. Cellular reactive oxygen species (ROS) and secreted lactate dehydrogenase (LDH) levels were measured. The interactions between ELF5, TTN-AS1, PCBP2 and CDK6 were explored using ChIP, luciferase reporter assay, RIP, and pull-down. The severity of MI in mice was evaluated using TTC, H&E, and TUNEL staining. The data revealed that OGD/R significantly induced ROS, mitochondrial injury and apoptosis in AC16 cells, while overexpression of ELF5 or TTN-AS1 reversed these phenomena. ELF5 transcriptionally activated TTN-AS1 through binding with its promoter. TTN-AS1 increased CDK6 stability via recruiting PCBP2. CDK6 knockdown abolished the inhibitory effects of TTN-AS1 overexpression on OGD/R-induced myocardial injury. Furthermore, overexpression of TTN-AS1 or ELF5 alleviated MI progression in mice by upregulating CDK6. Collectively, TTN-AS1 transcriptionally regulated by ELF5 alleviated myocardial apoptosis and injury during MI via recruiting PCBP2 to increase CDK6 stability, which shed new lights on exploring new strategies against MI.

Xinnaotongluo liquid protects H9c2 cells from H/R-induced damage by regulating MDM2/STEAP3

Xinnaotongluo liquid has been used to improve the clinical symptoms of patients with myocardial infarction. However, the molecular mechanism of Xinnaotongluo liquid is not completely understood. H9c2 cells exposed to hypoxia/reoxygenation (H/R) was used to simulate damage to cardiomyocytes in myocardial infarction in vitro. The biological indicators of H9c2 cells were measured by cell counting kit-8, enzyme linked immunoabsorbent assay, and western blot assay. In H/R-induced H9c2 cells, a markedly reduced murine double minute 2 (MDM2) was observed. However, the addition of Xinnaotongluo liquid increased MDM2 expression in H/R-induced H9c2 cells. And MDM2 overexpression strengthened the beneficial effects of Xinnaotongluo liquid on H9c2 cells from the perspective of alleviating oxidative damage, cellular inflammation, apoptosis and ferroptosis of H/R-induced H9c2 cells. Moreover, MDM2 overexpression reduced the protein expression of p53 and Six-Transmembrane Epithelial Antigen of Prostate 3 (STEAP3). Whereas, STEAP3 overexpression hindered the function of MDM2-overexpression in H/R-induced H9c2 cells. Our results insinuated that Xinnaotongluo liquid could protect H9c2 cells from H/R-induced damage by regulating MDM2/STEAP3, which provide a potential theoretical basis for further explaining the working mechanism of Xinnaotongluo liquid.

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.

Prioritization of microRNA biomarkers for a prospective evaluation in a cohort of myocardial infarction patients based on their mechanistic role using public datasets

Background

MicroRNAs (miR) have proven to be promising biomarkers for several diseases due to their diverse functions, stability and tissue/organ-specific nature. Identification of new markers with high sensitivity and specificity will help in risk reduction in acute myocardial infarction (AMI) patients with chest pain and also prevent future adverse outcomes. Hence the aim of this study was to perform a detailed in silico analysis for identifying the mechanistic role of miRs involved in the pathogenesis/prognosis of AMI for prospective evaluation in AMI patients.

Methods

miR profiling data was extracted from GSE148153 and GSE24591 datasets using the GEO2R gene expression omnibus repository and analyzed using limma algorithm. Differentially expressed miRs were obtained by comparing MI patients with corresponding controls after multiple testing corrections. Data mining for identifying candidate miRs from published literature was also performed. Target prediction and gene enrichment was done using standard bioinformatics tools. Disease specific analysis was performed to identify target genes specific for AMI using open targets platform. Protein-protein interaction and pathway analysis was done using STRING database and Cytoscape platform.

Results and conclusion

The analysis revealed significant miRs like let-7b-5p, let-7c-5p, miR-4505, and miR-342-3p in important functions/pathways including phosphatidylinositol-3-kinase/AKT and the mammalian target of rapamycin, advanced glycation end products and its receptor and renin–angiotensin–aldosterone system by directly targeting angiotensin II receptor type 1, forkhead box protein O1, etc. With this approach we were able to prioritize the miR candidates for a prospective clinical association study in AMI patients of south Indian origin.

Transcriptome Sequencing Data Reveal LncRNA-miRNA-mRNA Regulatory Network in Calcified Aortic Valve Disease

Background

Calcified aortic valve disease (CAVD) is one of the most common valvular heart diseases in the elderly population. However, no effective medical treatments have been found to interfere with the progression of CAVD, and specific molecular mechanisms of CAVD remain unclear.

Materials and Methods

Transcriptome sequencing data of GSE55492 and GSE148219 were downloaded from the European Nucleotide Archive, and the microarray dataset, GSE12644 was acquired from the Gene Expression Omnibus database. Software, including FastQC, HISAT2, samtools, and featureCounts was applied to generate the read count matrix. The “Limma” package in R was utilized to analyze differentially expressed genes (DEGs). Thereafter, weighted gene co-expression network analysis, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, and the protein-protein interaction (PPI) network were used to identify hub genes associated with CAVD, which were further validated by receiver operating characteristic curve (ROC) analysis using GSE12644. The long non-coding RNA (LncRNA)-mediated regulatory network was established based on the differentially expressed LncRNAs and hub genes, which were detected using quantitative real-time PCR (qRT-PCR) in clinical samples and valve interstitial cells. Moreover, CIBERSORT was used to calculate the expression distribution of immune cell infiltration in CAVD.

Results

A total of 126 DEGs were included in the PPI network. PI3K-Akt signaling pathway, ECM-receptor interaction, hematopoietic cell lineage, cell adhesion molecules, and focal adhesion were the most enriched pathways revealed by KEGG. Four LncRNAs, including TRHDE-AS1, LINC00092, LINC01094, and LINC00702 were considered the differentially expressed LncRNA. SPP1, TREM1, GPM6A, CCL19, CR1, NCAM1, CNTN1, TLR8, SDC1, and COL6A6 were the 10 hub genes identified to be associated with CAVD. Moreover, the calcified aortic valve samples had a greater level of Tregs, naïve B cells, and M0 macrophages than the noncalcified ones, whereas CAVD samples had a lower M2 macrophage expression compared to the noncalcified valve tissues.

Conclusion

The current study identified SPP1, TREM1, TLR8, SDC1, GPM6A, and CNTN1 as hub genes that could potentially be associated with CAVD. The LINC00702–miR-181b-5p–SPP1 axis might participate in the development of CAVD. Additionally, M2 macrophages, Tregs, naïve B cells, and M0 macrophages might possibly play a role in the initiation of CAVD.

Post-Transcriptional Regulation of Molecular Determinants during Cardiogenesis

Cardiovascular development is initiated soon after gastrulation as bilateral precardiac mesoderm is progressively symmetrically determined at both sides of the developing embryo. The precardiac mesoderm subsequently fused at the embryonic midline constituting an embryonic linear heart tube. As development progress, the embryonic heart displays the first sign of left-right asymmetric morphology by the invariably rightward looping of the initial heart tube and prospective embryonic ventricular and atrial chambers emerged. As cardiac development progresses, the atrial and ventricular chambers enlarged and distinct left and right compartments emerge as consequence of the formation of the interatrial and interventricular septa, respectively. The last steps of cardiac morphogenesis are represented by the completion of atrial and ventricular septation, resulting in the configuration of a double circuitry with distinct systemic and pulmonary chambers, each of them with distinct inlets and outlets connections. Over the last decade, our understanding of the contribution of multiple growth factor signaling cascades such as Tgf-beta, Bmp and Wnt signaling as well as of transcriptional regulators to cardiac morphogenesis have greatly enlarged. Recently, a novel layer of complexity has emerged with the discovery of non-coding RNAs, particularly microRNAs and lncRNAs. Herein, we provide a state-of-the-art review of the contribution of non-coding RNAs during cardiac development. microRNAs and lncRNAs have been reported to functional modulate all stages of cardiac morphogenesis, spanning from lateral plate mesoderm formation to outflow tract septation, by modulating major growth factor signaling pathways as well as those transcriptional regulators involved in cardiac development.

Construction of miRNA-mRNA network reveals crucial miRNAs and genes in acute myocardial infarction

Acute myocardial infarction (AMI) is a severe cardiovascular disease. This study aimed to identify crucial microRNAs (miRNAs) and mRNAs in AMI by establishing a miRNA-mRNA network. The microarray datasets GSE31568, GSE148153, and GSE66360 were downloaded from the Gene Expression Omnibus (GEO) database. We identified differentially expressed miRNAs (DE-miRNAs) and mRNAs (DE-mRNAs) in AMI samples compared with normal control samples. The consistently changing miRNAs in both GSE31568 and GSE148153 datasets were selected as candidate DE-miRNAs. The interactions between the candidate DE-miRNAs and DE-mRNAs were analyzed, and a miRNA-mRNA network and a protein-protein interaction network were constructed, along with functional enrichment and pathway analyses. A total of 209 DE-miRNAs in the GSE31568 dataset, 857 DE-miRNAs in the GSE148153 dataset, and 351 DE-mRNAs in the GSE66360 dataset were identified. Eighteen candidate DE-miRNAs were selected from both the GSE31568 and GSE148153 datasets. Furthermore, miR-646, miR-127-5p, miR-509-5p, miR-509-3-5p, and miR-767-5p were shown to have a higher degree in the miRNA-mRNA network.THBS-1 as well as FOS was a hub gene in the miRNA-mRNA network and the protein-protein interaction (PPI) network, respectively. CDKN1A was important in both miRNA-mRNA network and PPI network. We established a miRNA-mRNA network in AMI and identified five miRNAs and three genes, which might be used as biomarkers and potential therapeutic targets for patients with AMI.

Transporters, TBC1D4, and ARID5B Variants to Explain Glycated Hemoglobin Variability in Patients with Type 2 Diabetes

INTRODUCTION

Genetic variants could aid in predicting antidiabetic drug response by associating them with markers of glucose control, such as glycated hemoglobin (HbA1c). However, pharmacogenetic implementation for antidiabetics is still under development, as the list of actionable markers is being populated and validated. This study explores potential associations between genetic variants and plasma levels of HbA1c in 100 patients under treatment with metformin.

METHODS

HbA1c was measured in a clinical chemistry analyzer (Roche), genotyping was performed in an Illumina-GSA array and data were analyzed using PLINK. Association and prediction models were developed using R and a 10-fold cross-validation approach.

RESULTS

We identified genetic variants on SLC47A1, SLC28A1, ABCG2, TBC1D4, and ARID5B that can explain up to 55% of the interindividual variability of HbA1c plasma levels in diabetic patients under treatment. Variants on SLC47A1, SLC28A1, and ABCG2 likely impact the pharmacokinetics (PK) of metformin, while the role of the two latter can be related to insulin resistance and regulation of adipogenesis.

CONCLUSIONS

Our results confirm previous genetic associations and point to previously unassociated gene variants for metformin PK and glucose control.