Comprehensive Analysis of mRNA Expression Profiling and Identification of Potential Diagnostic Biomarkers in Coronary Artery Disease

Disparity of gene expression in coronary artery disease: insights from MEIS1, HIRA, and Myocardin

INTRODUCTION

Coronary artery disease (CAD) in young adults can have devastating consequences. The cardiac developmental gene MEIS1 plays important roles in vascular networks and heart development. This gene effects on the regeneration capacity of the heart. Considering role of MEIS1 in cardiac tissue development and the progression of myocardial infarction this study investigated the expression levels of the MEIS1, HIRA, and Myocardin genes in premature CAD patients compared to healthy subjects and evaluated the relationships between these genes and possible inflammatory factors.

METHODS AND RESULTS

The study conducted a case-control design involving 35 CAD patients and 35 healthy individuals. Peripheral blood mononuclear cells (PBMCs) were collected, and gene expression analysis was performed using real-time PCR. Compared with control group, the number of PBMCs in the CAD group exhibited greater MEIS1 and HIRA gene expression, with fold changes of 2.45 and 3.6. The expression of MEIS1 exhibited a negative correlation with IL-10 (r= -0.312) expression and positive correlation with Interleukin (IL)-6 (r = 0.415) and tumor necrosis factor (TNF)-α (r = 0.534) gene expression. Moreover, there was an inverse correlation between the gene expression of HIRA and that of IL-10 (r= -0.326), and a positive correlation was revealed between the expression of this gene and that of the IL-6 (r = 0.453) and TNF-α (r = 0.572) genes.

CONCLUSION

This research demonstrated a disparity in expression levels of MEIS1, HIRA, and Myocardin, between CAD and healthy subjects. The results showed that, MEIS1 and HIRA play significant roles in regulating the synthesis of proinflammatory cytokines, namely, TNF-α and IL-6.

Single-cell RNA sequencing atlas of peripheral blood mononuclear cells from subjects with coronary artery disease

BACKGROUND

The landscape of specific peripheral circulating immune cell subsets at the single-cell level in the occurrence and development of coronary artery disease (CAD) remains poorly understood.

METHODS

We conducted single-cell RNA sequencing (scRNA-seq) of peripheral blood mononuclear cells (PBMCs) from subjects with CAD (n = 3), and controls (n = 3), as well as downstream analysis including cell- and gene-level approaches. This explored the characteristics of peripheral circulating immune cells between CADs and controls by means of Uniform manifold approximation and projection (UMAP), Monocle3 package, CellPhoneDB, and single-cell regulatory network inference and clustering (SCENIC). PBMCs were used as clinical samples for validating our findings by qRT-PCR.

RESULTS

We identified 33 cell clusters among 67,447 cells, including monocytes, T cells, B cells, NK cells, and platelets. The significant difference in the abundance of the 33 clusters of cell type between CADs group and controls group was not found. The JUN was shared in cluster 0, 11,13, and 24 from differential expression genes analysis and SCENIC analysis in monocyte clusters between CAD and controls. Besides, JUN was validated to be significantly upregulated in the CAD group (p = 0.018) and may act as a potential diagnostic biomarker and independent predictor of CAD.

CONCLUSIONS

Our study offered a detailed profiling of single-cell RNA sequencing of PBMCs from subjects with CADs and controls. These data provide a line of evidence that the JUN signaling pathway may be a potential diagnostic and therapeutic molecule target for CAD.

RNA Sequencing of Whole Blood in Premature Coronary Artery Disease: Identification of Novel Biomarkers and Involvement of T Cell Imbalance

Serum biomarkers were explored based on the peripheral blood gene expression profiles of premature coronary artery disease (PCAD). RNA sequencing (RNA-Seq) was used to detect PCAD-specific differentially expressed genes (DEGs). Quantitative real-time polymerase chain reaction (RT-PCR) was used to validate the most significant DEGs, and enzyme-linked immunosorbent assay (ELISA) was utilized to quantify the effect on corresponding serum proteins. Fifty-nine PCAD-specific DEGs were identified. Functional analysis showed positive regulation of T cell-mediated cytotoxicity, regulation of T cell-mediated immunity, and the regulation of alpha-beta T cell proliferation which were enriched in PCAD. RT-PCR validated the significant difference in the expression of BAG6, MUC5B, and APOA2 between PCAD and late-onset coronary artery disease (LCAD) patients. ELISA validation showed serum MUC5B increased dramatically in PCAD when compared to LCAD. Our study found T cells contribute to the occurrence of PCAD, and the inflammatory factor MUC5B may be a novel serum marker in PCAD patients.

Interaction between the expression of hsa_circRPRD1A and hsa_circHERPUD2 and classical coronary risk factors promotes the development of coronary artery disease

BACKGROUND

Recent studies suggest that classical coronary risk factors play a significant role in the pathogenesis of coronary artery disease. Our study aims to explore the interaction of circRNA with classical coronary risk factors in coronary atherosclerotic disease.

METHOD

Combined analysis of RNA sequencing results from coronary segments and peripheral blood mononuclear cells of patients with coronary atherosclerotic disease was employed to identify critical circRNAs. Competing endogenous RNA networks were constructed by miRanda-3.3a and TargetScan7.0. The relative expression quantity of circRNA in peripheral blood mononuclear cells was determined by qRT-PCR in a large cohort including 256 patients and 49 controls. Spearman's correlation test, receiver operating characteristic curve analysis, multivariable logistic regression analysis, one-way analysis of variance, and crossover analysis were performed.

RESULTS

A total of 34 circRNAs were entered into our study, hsa_circRPRD1A, hsa_circHERPUD2, hsa_circLMBR1, and hsa_circDHTKD1 were selected for further investigation. A circRNA-miRNA-mRNA network is composed of 20 microRNAs and 66 mRNAs. The expression of hsa_circRPRD1A (P = 0.004) and hsa_circHERPUD2 (P = 0.003) were significantly down-regulated in patients with coronary artery disease compared to controls. The area under the curve of hsa_circRPRD1A and hsa_circHERPUD2 is 0.689 and 0.662, respectively. Univariate and multivariable logistic regression analyses identified hsa_circRPRD1A (OR = 0.613, 95%CI:0.380-0.987, P = 0.044) as a protective factor for coronary artery disease. Based on the additive model, crossover analysis demonstrated that there was an antagonistic interaction between the expression of hsa_circHERPUD2 and alcohol consumption in subjects with coronary artery disease.

CONCLUSION

Our findings imply that hsa_circRPRD1A and hsa_circHERPUD2 could be used as biomarkers for the diagnosis of coronary artery disease and provide epidemiological support for the interactions between circRNAs and classical coronary risk factors.

Detailed profiling of m6A modified circRNAs and synergistic effects of circRNA and environmental risk factors for coronary artery disease

The modification of N6-methyladenosine (m6A) modification is implicated in human diseases. However, considerable uncertainty is associated with the regulatory mechanisms of m6A circRNAs in coronary artery disease (CAD), which require further clarification. In this study, m6A-modified RNA immunoprecipitation sequencing (MeRIP-seq) was conducted to investigate m6A-modified circRNAs in human coronary artery smooth muscle cells (HCASMCs) and to identify potential biomarkers for CAD. A total of 830 and 331 up- and down-regulated m6A peaks, (corresponding to 463 and 243 up- and down-regulated circRNAs, respectively), were identified in HCASMCs in a pathological condition. Functional analysis suggested that these circRNAs appeared to participate in intracellular protein, histone deacetylase complex, ATP-dependent activity, autophagy, and AMPK signaling pathway. Four candidate circRNAs were selected for further evaluation in HCASMCs and human samples. The results suggested that hsa_circHECTD1 and hsa_circZBTB46 were significantly increased in patients with CAD (p-value = 0.039 and p-value = 0.014) and may act as potential diagnostic biomarkers of CAD. Furthermore, statistical results showed that hsa_circHECTD1 and hsa_circSEC62 were positively correlated with triglyceride (TG) (r = 0.213, p-value = 0.014) and Gensini Score (used to quantify the severity of CAD) (r = 0.349, p-value <0.001), respectively. Logistic regression revealed that hsa_circZBTB46 was strongly correlated with the incidence of CAD, and the synergistic effects of circRNAs and hypertension enhanced the risk of CAD. These results show that hsa_circHECTD1 and hsa_circZBTB46 may be new targets for further studies, and this study enhances our understanding of the effects of m6A-circRNAs on the pathogenesis of CAD.

Whole-Blood Transcriptional Profiles Enable Early Prediction of the Presence of Coronary Atherosclerosis and High-Risk Plaque Features at Coronary CT Angiography

Existing tools to estimate cardiovascular (CV) risk have sub-optimal predictive capacities. In this setting, non-invasive imaging techniques and omics biomarkers could improve risk-prediction models for CV events. This study aimed to identify gene expression patterns in whole blood that could differentiate patients with severe coronary atherosclerosis from subjects with a complete absence of detectable coronary artery disease and to assess associations of gene expression patterns with plaque features in coronary CT angiography (CCTA). Patients undergoing CCTA for suspected coronary artery disease (CAD) were enrolled. Coronary stenosis was quantified and CCTA plaque features were assessed. The whole-blood transcriptome was analyzed with RNA sequencing. We detected highly significant differences in the circulating transcriptome between patients with high-degree coronary stenosis (≥70%) in the CCTA and subjects with an absence of coronary plaque. Notably, regression analysis revealed expression signatures associated with the Leaman score, the segment involved score, the segment stenosis score, and plaque volume with density <150 HU at CCTA. This pilot study shows that patients with significant coronary stenosis are characterized by whole-blood transcriptome profiles that may discriminate them from patients without CAD. Furthermore, our results suggest that whole-blood transcriptional profiles may predict plaque characteristics.