Flow diagram for article selection.

<p>Flow diagram for article selection.</p

Role of Peripheral Inflammatory Markers in Postoperative Cognitive Dysfunction (POCD): A Meta-Analysis

<div><p>Background</p><p>Postoperative cognitive dysfunction (POCD) is common following cardiac and non-cardiac surgery, but the pathogenic mechanisms remain unknown. Many studies suggest that an inflammatory response is a key contributor to POCD. The current meta-analysis shows that the levels of peripheral inflammatory markers are associated with POCD.</p> <p>Methods</p><p>An online search was performed to identify peer-reviewed studies without language restriction that measured peripheral inflammatory markers of patients with and without POCD, using PubMed, ScienceDirect, SinoMed and the National Knowledge Infrastructure database. Extracted data were analyzed with STATA (version 12).The standardized mean difference (SMD) and the 95% confidence interval (95%CI) were calculated for each outcome using a random effect model. Tests of heterogeneity assessment of bias, and meta-regression were performed in the meta-analysis.</p> <p>Results</p><p>A total of 13 studies that measured the concentrations of peripheral inflammatory markers were included. The current meta-analysis found significantly higher concentrations of S-100β(SMD[95%CI]) (1.377 [0.423, 2.331], p-value < 0.001, N [POCD/non-POCD] =178/391, 7 studies), and interleukin(IL)-6 (SMD[95%CI]) (1.614 [0.603,2.624], p-value < 0.001, N[POCD/non-POCD] = 91/99, 5 studies), but not of neuron specific enolase, interleukin-1β, or tumor necrosis factor-α , in POCD compared with patients without POCD. In meta-regression analyses, a significant positive association was found between the SMD and the preoperative interleukin-6 peripheral blood concentration in patients with POCD (Coef.= 0.0587, p-value=0.038, 5 studies).</p> <p>Conclusions</p><p>This study shows that POCD is indeed correlated with the concentrations of peripheral inflammatory markers, particularly interleukin-6 and S-100β.</p> </div

Studies of peripheral blood IL-6.

<p>Forest plot for IL-6 displaying the results of the random-effects meta-analysis for the association between peripheral blood IL-6 concentrations and POCD. The standardized mean difference is presented on the horizontal axis; positive values denote higher serum levels in patients; negative values denote higher serum levels in control subjects. The dashed line is at the overall weighted mean difference. CI, confidence interval; SMD, standardized mean difference.</p

Association of preoperative IL-6 blood concentration in POCD patients with plasma IL-6 SMD using meta-regression.

<p>Plot of the preoperative IL-6 peripheral blood concentration vs. the peripheral blood IL-6 SMD in the 5 included studies showing a fitted random effects meta-regression line.( 5 studies, Coef.=0 .0587 ,p-value = 0.038 ) Coef., coefficient.</p

Association of preoperative S-100β blood concentration in all subjects with plasma S-100β SMD using meta-regression.

<p>Plot of the preoperative S-100β peripheral blood concentration vs. the peripheral blood S-100β SMD in the 6 included studies, showing a random effects meta-regression line. (6 studies, Coef.= 9.554,p-value = 0.290 ) Coef., coefficient.</p

Studies of peripheral blood S-100β.

<p>Forest plot for S-100β displaying the results of the random effects meta-analysis for the association between peripheral blood S-100β and postoperative cognitive dysfunction (POCD). The standardized mean difference is presented on the horizontal axis; positive values denote higher serum levels in POCD patients; negative values denote higher serum levels in control subjects. The dashed line is at the overall standardized mean difference. CI, confidence interval; SMD, standardized mean difference.</p

Table_1_Integrated Analysis of Immune-Related circRNA-miRNA-mRNA Regulatory Network in Ischemic Stroke.DOCX

BackgroundStroke is the leading cause of death and disability worldwide, with ischemic stroke (IS) being the most prevalent type. Circular RNAs (circRNAs) are involved in the pathological process of IS and are promising biomarkers for the diagnosis of IS. However, studies focusing on circRNAs acting as microRNAs (miRNAs) sponges in regulating mRNA expression are currently scarce.MethodsIn this study, expression profiles of circRNAs (GSE195442), miRNAs (GSE117064), and mRNAs (GSE58294) from the Gene Expression Omnibus (GEO) database were analyzed. Differentially expressed circRNAs (DEcircRNAs), differentially expressed miRNAs (DEmiRNAs), and differentially expressed mRNAs (DEmRNAs) were identified by R software. The target miRNAs and target genes were predicted by several bioinformatics methods. Then, we performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of the DEmRNAs. Subsequently, the protein-protein interaction (PPI) network and the competing endogenous RNA (ceRNA) regulatory network were visualized by Cytoscape software. Finally, we further constructed an immune-related circRNA-miRNA-mRNA regulatory sub-network in IS.ResultsA total of 35 DEcircRNAs, 141 DEmiRNAs, and 356 DEmRNAs were identified. By comprehensive analysis of bioinformatics methods, we constructed a circRNA-miRNA-mRNA regulatory network, including 15 DEcircRNAs, eight DEmiRNAs, and 39 DEmRNAs. FGF9 was identified as an immune-related hub gene. Immune cell analysis indicated a significantly higher level of neutrophils in IS, and the expression of FGF9 was significantly negatively correlated with the level of neutrophils. Eventually, miR-767-5p was predicted as the upstream molecules of FGF9, and circ_0127785 and circ_0075008 were predicted as the upstream circRNAs of miR-767-5p.ConclusionOur study provides novel insights into the molecular mechanisms governing the progression of IS from the perspective of immune-related ceRNA networks.</p

Data_Sheet_5_Integrated Analysis of Immune-Related circRNA-miRNA-mRNA Regulatory Network in Ischemic Stroke.ZIP

BackgroundStroke is the leading cause of death and disability worldwide, with ischemic stroke (IS) being the most prevalent type. Circular RNAs (circRNAs) are involved in the pathological process of IS and are promising biomarkers for the diagnosis of IS. However, studies focusing on circRNAs acting as microRNAs (miRNAs) sponges in regulating mRNA expression are currently scarce.MethodsIn this study, expression profiles of circRNAs (GSE195442), miRNAs (GSE117064), and mRNAs (GSE58294) from the Gene Expression Omnibus (GEO) database were analyzed. Differentially expressed circRNAs (DEcircRNAs), differentially expressed miRNAs (DEmiRNAs), and differentially expressed mRNAs (DEmRNAs) were identified by R software. The target miRNAs and target genes were predicted by several bioinformatics methods. Then, we performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of the DEmRNAs. Subsequently, the protein-protein interaction (PPI) network and the competing endogenous RNA (ceRNA) regulatory network were visualized by Cytoscape software. Finally, we further constructed an immune-related circRNA-miRNA-mRNA regulatory sub-network in IS.ResultsA total of 35 DEcircRNAs, 141 DEmiRNAs, and 356 DEmRNAs were identified. By comprehensive analysis of bioinformatics methods, we constructed a circRNA-miRNA-mRNA regulatory network, including 15 DEcircRNAs, eight DEmiRNAs, and 39 DEmRNAs. FGF9 was identified as an immune-related hub gene. Immune cell analysis indicated a significantly higher level of neutrophils in IS, and the expression of FGF9 was significantly negatively correlated with the level of neutrophils. Eventually, miR-767-5p was predicted as the upstream molecules of FGF9, and circ_0127785 and circ_0075008 were predicted as the upstream circRNAs of miR-767-5p.ConclusionOur study provides novel insights into the molecular mechanisms governing the progression of IS from the perspective of immune-related ceRNA networks.</p

Data_Sheet_1_Integrated Analysis of Immune-Related circRNA-miRNA-mRNA Regulatory Network in Ischemic Stroke.ZIP

BackgroundStroke is the leading cause of death and disability worldwide, with ischemic stroke (IS) being the most prevalent type. Circular RNAs (circRNAs) are involved in the pathological process of IS and are promising biomarkers for the diagnosis of IS. However, studies focusing on circRNAs acting as microRNAs (miRNAs) sponges in regulating mRNA expression are currently scarce.MethodsIn this study, expression profiles of circRNAs (GSE195442), miRNAs (GSE117064), and mRNAs (GSE58294) from the Gene Expression Omnibus (GEO) database were analyzed. Differentially expressed circRNAs (DEcircRNAs), differentially expressed miRNAs (DEmiRNAs), and differentially expressed mRNAs (DEmRNAs) were identified by R software. The target miRNAs and target genes were predicted by several bioinformatics methods. Then, we performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of the DEmRNAs. Subsequently, the protein-protein interaction (PPI) network and the competing endogenous RNA (ceRNA) regulatory network were visualized by Cytoscape software. Finally, we further constructed an immune-related circRNA-miRNA-mRNA regulatory sub-network in IS.ResultsA total of 35 DEcircRNAs, 141 DEmiRNAs, and 356 DEmRNAs were identified. By comprehensive analysis of bioinformatics methods, we constructed a circRNA-miRNA-mRNA regulatory network, including 15 DEcircRNAs, eight DEmiRNAs, and 39 DEmRNAs. FGF9 was identified as an immune-related hub gene. Immune cell analysis indicated a significantly higher level of neutrophils in IS, and the expression of FGF9 was significantly negatively correlated with the level of neutrophils. Eventually, miR-767-5p was predicted as the upstream molecules of FGF9, and circ_0127785 and circ_0075008 were predicted as the upstream circRNAs of miR-767-5p.ConclusionOur study provides novel insights into the molecular mechanisms governing the progression of IS from the perspective of immune-related ceRNA networks.</p

Data_Sheet_3_Integrated Analysis of Immune-Related circRNA-miRNA-mRNA Regulatory Network in Ischemic Stroke.ZIP

BackgroundStroke is the leading cause of death and disability worldwide, with ischemic stroke (IS) being the most prevalent type. Circular RNAs (circRNAs) are involved in the pathological process of IS and are promising biomarkers for the diagnosis of IS. However, studies focusing on circRNAs acting as microRNAs (miRNAs) sponges in regulating mRNA expression are currently scarce.MethodsIn this study, expression profiles of circRNAs (GSE195442), miRNAs (GSE117064), and mRNAs (GSE58294) from the Gene Expression Omnibus (GEO) database were analyzed. Differentially expressed circRNAs (DEcircRNAs), differentially expressed miRNAs (DEmiRNAs), and differentially expressed mRNAs (DEmRNAs) were identified by R software. The target miRNAs and target genes were predicted by several bioinformatics methods. Then, we performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of the DEmRNAs. Subsequently, the protein-protein interaction (PPI) network and the competing endogenous RNA (ceRNA) regulatory network were visualized by Cytoscape software. Finally, we further constructed an immune-related circRNA-miRNA-mRNA regulatory sub-network in IS.ResultsA total of 35 DEcircRNAs, 141 DEmiRNAs, and 356 DEmRNAs were identified. By comprehensive analysis of bioinformatics methods, we constructed a circRNA-miRNA-mRNA regulatory network, including 15 DEcircRNAs, eight DEmiRNAs, and 39 DEmRNAs. FGF9 was identified as an immune-related hub gene. Immune cell analysis indicated a significantly higher level of neutrophils in IS, and the expression of FGF9 was significantly negatively correlated with the level of neutrophils. Eventually, miR-767-5p was predicted as the upstream molecules of FGF9, and circ_0127785 and circ_0075008 were predicted as the upstream circRNAs of miR-767-5p.ConclusionOur study provides novel insights into the molecular mechanisms governing the progression of IS from the perspective of immune-related ceRNA networks.</p