New developments in non-exosomal and exosomal ncRNAs in coronary artery disease. Supplementary material.

Supplementary figures 1 and 2    Supplementary material Table S1. Findings of miRNAs in coronary artery disease    Supplementary material Table S2. Findings of lncRNAs in coronary artery disease    Supplementary material Table S3. Findings of circRNAs in coronary artery disease    Supplementary material Table S4. Findings of exosomal-derived ncRNAs in coronary artery disease</p

DataSheet1_Integrated bioinformatics analysis for novel miRNAs markers and ceRNA network in diabetic retinopathy.xlsx

In order to seek a more outstanding diagnosis and treatment of diabetic retinopathy (DR), we predicted the miRNA biomarkers of DR and explored the pathological mechanism of DR through bioinformatics analysis.Method: Based on public omics data and databases, we investigated ncRNA (non-coding RNA) functions based on the ceRNA hypothesis.Result: Among differentially expressed miRNAs (DE-miRNAs), hsa-miR-1179, -4797-3p and -665 may be diagnosis biomarkers of DR. Functional enrichment analysis revealed differentially expressed mRNAs (DE-mRNAs) enriched in mitochondrial transport, cellular respiration and energy derivation. 18 tissue/organ-specific expressed genes, 10 hub genes and gene cluster modules were identified. The ceRNA networks lncRNA FBXL19-AS1/miR-378f/MRPL39 and lncRNA UBL7-AS1/miR-378f/MRPL39 might be potential RNA regulatory pathways in DR.Conclusion: Differentially expressed hsa-miR-1179, -4797-3p and -665 can be used as powerful markers for DR diagnosis, and the ceRNA network: lncRNA FBXL19-AS1/UBL7-AS1-miR-378f-MRPL39 may represent an important regulatory role in DR progression.</p

DataSheet3_Integrated bioinformatics analysis for novel miRNAs markers and ceRNA network in diabetic retinopathy.xlsx

In order to seek a more outstanding diagnosis and treatment of diabetic retinopathy (DR), we predicted the miRNA biomarkers of DR and explored the pathological mechanism of DR through bioinformatics analysis.Method: Based on public omics data and databases, we investigated ncRNA (non-coding RNA) functions based on the ceRNA hypothesis.Result: Among differentially expressed miRNAs (DE-miRNAs), hsa-miR-1179, -4797-3p and -665 may be diagnosis biomarkers of DR. Functional enrichment analysis revealed differentially expressed mRNAs (DE-mRNAs) enriched in mitochondrial transport, cellular respiration and energy derivation. 18 tissue/organ-specific expressed genes, 10 hub genes and gene cluster modules were identified. The ceRNA networks lncRNA FBXL19-AS1/miR-378f/MRPL39 and lncRNA UBL7-AS1/miR-378f/MRPL39 might be potential RNA regulatory pathways in DR.Conclusion: Differentially expressed hsa-miR-1179, -4797-3p and -665 can be used as powerful markers for DR diagnosis, and the ceRNA network: lncRNA FBXL19-AS1/UBL7-AS1-miR-378f-MRPL39 may represent an important regulatory role in DR progression.</p

DataSheet2_Integrated bioinformatics analysis for novel miRNAs markers and ceRNA network in diabetic retinopathy.xlsx

In order to seek a more outstanding diagnosis and treatment of diabetic retinopathy (DR), we predicted the miRNA biomarkers of DR and explored the pathological mechanism of DR through bioinformatics analysis.Method: Based on public omics data and databases, we investigated ncRNA (non-coding RNA) functions based on the ceRNA hypothesis.Result: Among differentially expressed miRNAs (DE-miRNAs), hsa-miR-1179, -4797-3p and -665 may be diagnosis biomarkers of DR. Functional enrichment analysis revealed differentially expressed mRNAs (DE-mRNAs) enriched in mitochondrial transport, cellular respiration and energy derivation. 18 tissue/organ-specific expressed genes, 10 hub genes and gene cluster modules were identified. The ceRNA networks lncRNA FBXL19-AS1/miR-378f/MRPL39 and lncRNA UBL7-AS1/miR-378f/MRPL39 might be potential RNA regulatory pathways in DR.Conclusion: Differentially expressed hsa-miR-1179, -4797-3p and -665 can be used as powerful markers for DR diagnosis, and the ceRNA network: lncRNA FBXL19-AS1/UBL7-AS1-miR-378f-MRPL39 may represent an important regulatory role in DR progression.</p

DataSheet4_Integrated bioinformatics analysis for novel miRNAs markers and ceRNA network in diabetic retinopathy.xlsx

In order to seek a more outstanding diagnosis and treatment of diabetic retinopathy (DR), we predicted the miRNA biomarkers of DR and explored the pathological mechanism of DR through bioinformatics analysis.Method: Based on public omics data and databases, we investigated ncRNA (non-coding RNA) functions based on the ceRNA hypothesis.Result: Among differentially expressed miRNAs (DE-miRNAs), hsa-miR-1179, -4797-3p and -665 may be diagnosis biomarkers of DR. Functional enrichment analysis revealed differentially expressed mRNAs (DE-mRNAs) enriched in mitochondrial transport, cellular respiration and energy derivation. 18 tissue/organ-specific expressed genes, 10 hub genes and gene cluster modules were identified. The ceRNA networks lncRNA FBXL19-AS1/miR-378f/MRPL39 and lncRNA UBL7-AS1/miR-378f/MRPL39 might be potential RNA regulatory pathways in DR.Conclusion: Differentially expressed hsa-miR-1179, -4797-3p and -665 can be used as powerful markers for DR diagnosis, and the ceRNA network: lncRNA FBXL19-AS1/UBL7-AS1-miR-378f-MRPL39 may represent an important regulatory role in DR progression.</p

Table_4_Identification of immune-related hub genes and miRNA-mRNA pairs involved in immune infiltration in human septic cardiomyopathy by bioinformatics analysis.XLSX

AbstractSeptic cardiomyopathy (SCM) is a serious complication caused by sepsis that will further exacerbate the patient's prognosis. However, immune-related genes (IRGs) and their molecular mechanism during septic cardiomyopathy are largely unknown. Therefore, our study aims to explore the immune-related hub genes (IRHGs) and immune-related miRNA-mRNA pairs with potential biological regulation in SCM by means of bioinformatics analysis and experimental validation.MethodFirstly, screen differentially expressed mRNAs (DE-mRNAs) from the dataset GSE79962, and construct a PPI network of DE-mRNAs. Secondly, the hub genes of SCM were identified from the PPI network and the hub genes were overlapped with immune cell marker genes (ICMGs) to further obtain IRHGs in SCM. In addition, receiver operating characteristic (ROC) curve analysis was also performed in this process to determine the disease diagnostic capability of IRHGs. Finally, the crucial miRNA-IRHG regulatory network of IRHGs was predicted and constructed by bioinformatic methods. Real-time quantitative reverse transcription-PCR (qRT-PCR) and dataset GSE72380 were used to validate the expression of the key miRNA-IRHG axis.ResultThe results of immune infiltration showed that neutrophils, Th17 cells, Tfh cells, and central memory cells in SCM had more infiltration than the control group; A total of 2 IRHGs were obtained by crossing the hub gene with the ICMGs, and the IRHGs were validated by dataset and qRT-PCR. Ultimately, we obtained the IRHG in SCM: THBS1. The ROC curve results of THBS1 showed that the area under the curve (AUC) was 0.909. Finally, the miR-222-3p/THBS1 axis regulatory network was constructed.ConclusionIn summary, we propose that THBS1 may be a key IRHG, and can serve as a biomarker for the diagnosis of SCM; in addition, the immune-related regulatory network miR-222-3p/THBS1 may be involved in the regulation of the pathogenesis of SCM and may serve as a promising candidate for SCM therapy.</p

Additional file 1: Figure S1. of Thrombus leukocytes exhibit more endothelial cell-specific angiogenic markers than peripheral blood leukocytes do in acute coronary syndrome patients, suggesting a possibility of trans-differentiation: a comprehensive database mining study

Correlation of mRNA relative expression levels of specific genes with angiogenic potential in human tissues. Simple linear regression was applied to the mRNA relative expression levels (Y-axis) against angiogenic potentials (X-axis) in each group of angiogenic genes (transcription regulators, growth factors and receptors, cytokines and chemokines, and proteases, inhibitors, and others). Table S1. Summary of 163 genes related to angiogenesis

Table_1_Identification of immune-related hub genes and miRNA-mRNA pairs involved in immune infiltration in human septic cardiomyopathy by bioinformatics analysis.XLSX

AbstractSeptic cardiomyopathy (SCM) is a serious complication caused by sepsis that will further exacerbate the patient's prognosis. However, immune-related genes (IRGs) and their molecular mechanism during septic cardiomyopathy are largely unknown. Therefore, our study aims to explore the immune-related hub genes (IRHGs) and immune-related miRNA-mRNA pairs with potential biological regulation in SCM by means of bioinformatics analysis and experimental validation.MethodFirstly, screen differentially expressed mRNAs (DE-mRNAs) from the dataset GSE79962, and construct a PPI network of DE-mRNAs. Secondly, the hub genes of SCM were identified from the PPI network and the hub genes were overlapped with immune cell marker genes (ICMGs) to further obtain IRHGs in SCM. In addition, receiver operating characteristic (ROC) curve analysis was also performed in this process to determine the disease diagnostic capability of IRHGs. Finally, the crucial miRNA-IRHG regulatory network of IRHGs was predicted and constructed by bioinformatic methods. Real-time quantitative reverse transcription-PCR (qRT-PCR) and dataset GSE72380 were used to validate the expression of the key miRNA-IRHG axis.ResultThe results of immune infiltration showed that neutrophils, Th17 cells, Tfh cells, and central memory cells in SCM had more infiltration than the control group; A total of 2 IRHGs were obtained by crossing the hub gene with the ICMGs, and the IRHGs were validated by dataset and qRT-PCR. Ultimately, we obtained the IRHG in SCM: THBS1. The ROC curve results of THBS1 showed that the area under the curve (AUC) was 0.909. Finally, the miR-222-3p/THBS1 axis regulatory network was constructed.ConclusionIn summary, we propose that THBS1 may be a key IRHG, and can serve as a biomarker for the diagnosis of SCM; in addition, the immune-related regulatory network miR-222-3p/THBS1 may be involved in the regulation of the pathogenesis of SCM and may serve as a promising candidate for SCM therapy.</p

Table_3_Identification of immune-related hub genes and miRNA-mRNA pairs involved in immune infiltration in human septic cardiomyopathy by bioinformatics analysis.XLSX

AbstractSeptic cardiomyopathy (SCM) is a serious complication caused by sepsis that will further exacerbate the patient's prognosis. However, immune-related genes (IRGs) and their molecular mechanism during septic cardiomyopathy are largely unknown. Therefore, our study aims to explore the immune-related hub genes (IRHGs) and immune-related miRNA-mRNA pairs with potential biological regulation in SCM by means of bioinformatics analysis and experimental validation.MethodFirstly, screen differentially expressed mRNAs (DE-mRNAs) from the dataset GSE79962, and construct a PPI network of DE-mRNAs. Secondly, the hub genes of SCM were identified from the PPI network and the hub genes were overlapped with immune cell marker genes (ICMGs) to further obtain IRHGs in SCM. In addition, receiver operating characteristic (ROC) curve analysis was also performed in this process to determine the disease diagnostic capability of IRHGs. Finally, the crucial miRNA-IRHG regulatory network of IRHGs was predicted and constructed by bioinformatic methods. Real-time quantitative reverse transcription-PCR (qRT-PCR) and dataset GSE72380 were used to validate the expression of the key miRNA-IRHG axis.ResultThe results of immune infiltration showed that neutrophils, Th17 cells, Tfh cells, and central memory cells in SCM had more infiltration than the control group; A total of 2 IRHGs were obtained by crossing the hub gene with the ICMGs, and the IRHGs were validated by dataset and qRT-PCR. Ultimately, we obtained the IRHG in SCM: THBS1. The ROC curve results of THBS1 showed that the area under the curve (AUC) was 0.909. Finally, the miR-222-3p/THBS1 axis regulatory network was constructed.ConclusionIn summary, we propose that THBS1 may be a key IRHG, and can serve as a biomarker for the diagnosis of SCM; in addition, the immune-related regulatory network miR-222-3p/THBS1 may be involved in the regulation of the pathogenesis of SCM and may serve as a promising candidate for SCM therapy.</p

Table_2_Identification of immune-related hub genes and miRNA-mRNA pairs involved in immune infiltration in human septic cardiomyopathy by bioinformatics analysis.XLSX

AbstractSeptic cardiomyopathy (SCM) is a serious complication caused by sepsis that will further exacerbate the patient's prognosis. However, immune-related genes (IRGs) and their molecular mechanism during septic cardiomyopathy are largely unknown. Therefore, our study aims to explore the immune-related hub genes (IRHGs) and immune-related miRNA-mRNA pairs with potential biological regulation in SCM by means of bioinformatics analysis and experimental validation.MethodFirstly, screen differentially expressed mRNAs (DE-mRNAs) from the dataset GSE79962, and construct a PPI network of DE-mRNAs. Secondly, the hub genes of SCM were identified from the PPI network and the hub genes were overlapped with immune cell marker genes (ICMGs) to further obtain IRHGs in SCM. In addition, receiver operating characteristic (ROC) curve analysis was also performed in this process to determine the disease diagnostic capability of IRHGs. Finally, the crucial miRNA-IRHG regulatory network of IRHGs was predicted and constructed by bioinformatic methods. Real-time quantitative reverse transcription-PCR (qRT-PCR) and dataset GSE72380 were used to validate the expression of the key miRNA-IRHG axis.ResultThe results of immune infiltration showed that neutrophils, Th17 cells, Tfh cells, and central memory cells in SCM had more infiltration than the control group; A total of 2 IRHGs were obtained by crossing the hub gene with the ICMGs, and the IRHGs were validated by dataset and qRT-PCR. Ultimately, we obtained the IRHG in SCM: THBS1. The ROC curve results of THBS1 showed that the area under the curve (AUC) was 0.909. Finally, the miR-222-3p/THBS1 axis regulatory network was constructed.ConclusionIn summary, we propose that THBS1 may be a key IRHG, and can serve as a biomarker for the diagnosis of SCM; in addition, the immune-related regulatory network miR-222-3p/THBS1 may be involved in the regulation of the pathogenesis of SCM and may serve as a promising candidate for SCM therapy.</p