Identification of key molecular markers of acute coronary syndrome using peripheral blood transcriptome sequencing analysis and mRNA-lncRNA co-expression network construction

Long non-coding RNA SNHG7 serves as a diagnostic biomarker for acute coronary syndrome and its predictive value for the clinical outcome after percutaneous coronary intervention

BACKGROUND

Acute coronary syndrome (ACS) is one of the common causes of cardiovascular death. The related lncRNAs were novel approaches for early diagnosis and intervention. This paper focused on the clinical function of SNHG7 for patients after PCI.

METHODS

The expression of SNHG7 was assessed in ACS patients. The predictive roles of SNHG7 were unveiled by the ROC curve. The relationship between SNHG7 and Gensini scores was judged by Pearson analysis. One-year follow-up was conducted and all patients were catalogued into different groups based on the prognosis. The qRT-PCR, K-M curve, and Cox regression analysis were performed to document the prognostic significance of SNHG7.

RESULTS

SNHG7 was highly expressed in ACS and its three subtypes. SNHG7 showed a certain value in predicting ACS, UA, NSTEMI, and STEMI. Gensini is a closely correlated indicator of SNHG7. The declined expression of SNHG7 was observed in the non-MACE and survival groups. The risk of MACE and death was increased in the group with high expression of SNHG7. SNHG7 was an independent biomarker in patients with ACS after PCI.

CONCLUSIONS

SNHG7 might be a diagnostic and prognostic tool for ACS patients.

Identification of biomarkers associated with diagnosis of acute lung injury based on bioinformatics and machine learning

BACKGROUND

Acute lung injury (ALI) is an acute inflammatory disease characterized by excess production of inflammatory factors in lung tissue and has a high mortality. This research was designed for the identification of novel diagnostic biomarkers for ALI and analyzing the possible association between critical genes and infiltrated immune cells.

METHODS

The study used 2 datasets (GSE2411 and GSE18341) to identify differentially expressed genes (DEGs) between 2 groups. Then we performed Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses to identify the functions of these DEGs. The study also used SVM-recursive feature elimination analysis and least absolute shrinkage and selection operator regression model to screen possible markers. The study further analyzed immune cell infiltration via CIBERSORT. Gene Set Enrichment Analysis was used to explore the molecular mechanism of the critical genes.

RESULTS

DEGs were identified between 2 groups. In total, 690 DEGs were obtained: 527 genes were upregulated and 163 genes were downregulated. We identified PDZK1IP1, CCKAR, and CXCL2 as critical genes. And we then found that these critical genes correlated with Mast Cells, Neutrophil Cells, M1 Macrophage, dendritic cell Actived, Eosinophil Cells, B Cells Naive, Mast Cells, and dendritic cell Immature. Furthermore, we investigated the specific signaling pathways involved in key genes and derived some potential molecular mechanisms by which key genes affect disease progression by use of Gene Set Enrichment Analysis. Moreover, we predict transcription factors. Also, we obtained critical gene-related microRNAs through the targetscan database, and visualized the microRNA network of the genes.

CONCLUSION

Our findings might provide some novel clue for the exploration of novel markers for ALI diagnosis. The critical genes and their associations with immune infiltration may offer new insight into understanding ALI developments.

Evaluation of lncRNA Expression Pattern and Potential Role in Heart Failure Pathology

During the last few decades, the morbidity and mortality of heart failure (HF) have remained on an upward trend. Despite the advances in therapeutic and diagnostic measures, there are still many aspects requiring further research. This study is aimed at finding potential long noncoding RNAs (lncRNAs) that could aid with the diagnosis and treatment of HF. We performed RNA sequencing on the peripheral blood of healthy controls as well as HF patients. The expression of lncRNAs was validated by RT-qPCR. Bioinformatic analysis was performed to investigate the possible mechanism of differentially expressed lncRNAs and mRNAs. The diagnostic value of lncRNAs was analysed by ROC analysis. Finally, a total of 207 mRNAs and 422 lncRNAs were identified. GO and KEGG pathway analyses revealed that biological pathways such as immune response, regulation of cell membrane, and transcriptional regulatory process were associated with the pathological progress of HF. The lncRNA-mRNA coexpression network was conducted, and several mRNAs were identified as key potential pathological targets, while lncRNA CHST11, MIR29B2CHG, CR381653.1, and FP236383.2 presented a potential diagnostic value for HF. These findings provide novel insights for the underlying mechanisms and possible therapeutic targets for HF.

Targeting Circulating lncRNA ENST00000538705.1 Relieves Acute Coronary Syndrome via Modulating ALOX15

Objective

Acute coronary syndrome (ACS) is the most dangerous and deadly form of coronary heart disease. Herein, we aimed to explore ACS-specific circulating lncRNAs and their regulatory mechanisms.

Methods

This study collected serum samples from ACS patients and healthy controls for microarray analysis. Dysregulated circulating lncRNAs and mRNAs were determined with |log2fold − change| > 1 and p < 0.05. lncRNA-mRNA coexpression analysis was carried out. ENST00000538705.1 and ALOX15 expression was further verified in serum specimens. In human coronary artery endothelial cells (HCAECs), ENST00000538705.1 and ALOX15 were knocked out through transfecting specific siRNAs. Thereafter, proliferation and migration were investigated with CCK-8 and wound-healing assays. Myocardial infarction rat models were established and administrated with siRNAs against ENST00000538705.1 or ALOX15. Myocardial damage was investigated with H&E staining, and serum TC, LDL, and HDL levels were measured.

Results

Microarray analysis identified 353 dysregulated circulating lncRNAs and 441 dysregulated circulating mRNAs in ACS. Coexpression analysis indicated the interaction between ENST00000538705.1 and ALOX15. RT-qPCR confirmed the remarkable upregulation of circulating ENST00000538705.1 and ALOX15 in ACS patients. In HCAECs, ENST00000538705.1 knockdown lowered the expression of ALOX15 but ALOX15 did not alter the expression of ENST00000538705.1. Silencing ENST00000538705.1 or ALOX15 weakened the proliferation and migration of HCAECs. Additionally, knockdown of ENST00000538705.1 or ALOX15 relieved myocardial damage, decreased serum TC and LDL levels, and elevated HDL levels in myocardial infarction rats.

Conclusion

Collectively, our findings demonstrate that circulating ENST00000538705.1 facilitates ACS progression through modulating ALOX15, which provide potential targets for ACS treatment.

Transcriptome sequencing and lncRNA-miRNA-mRNA network construction in cardiac fibrosis and heart failure

Cardiac fibrosis (CF) and heart failure (HF) are common heart diseases, and severe CF can lead to HF. In this study, we tried to find their common potential molecular markers, which may help the diagnosis and treatment of CF and HF. RNA library construction and high-throughput sequencing were performed. The DESeq2 package in R was used to screen differentially expressed mRNAs (DEmRNAs), differentially expressed lncRNA (DElncRNAs) and differentially expressed miRNA (DEmiRNAs) between different samples. The common DEmRNAs, DElncRNAs and DEmiRNAs for the two diseases were obtained. The ConsensusPathDB (CPDB) was used to perform biological function enrichment for common DEmRNAs. Gene interaction network was constructed to screen out key genes. Subsequently, real-time polymerase chain reaction (RT-PCR) verification was performed. Lastly, GSE104150 and GSE21125 data sets were utilized for expression validation and diagnostic analysis. There were 1477 DEmRNAs, 502 DElncRNAs and 36 DEmiRNAs between CF and healthy control group. There were 607 DEmRNAs, 379DElncRNAs,s and 42 DEmiRNAs between HF and healthy control group. CH and FH shared 146 DEmRNAs, 80 DElncRNAs, and 6 DEmiRNAs. Hsa-miR-144-3p, CCNE2, C9orf72, MAP3K20-AS1, LEF1-AS1, AC243772.2, FLJ46284, and AC239798.2 were key molecules in lncRNA-miRNA-mRNA network. In addition, hsa-miR-144-3p and CCNE2 may be considered as potential diagnostic gene biomarkers in HF. In this study, the identification of common biomarkers of CF and HF may help prevent CF to HF transition as early as possible.