Background: Stroke is a serious cardiovascular disease, a major cause of disability and death in both developed and developing countries. Superoxide dismutases (SODs) are enzymes that catalyze the breakdown of superoxide into oxygen and hydrogen peroxide and play a key role in the antioxidant response. This study explored the relationship between single-nucleotide polymorphisms (SNPs) in SOD genes and the risk of ischemic stroke (IS) in the Chinese Han population of Dali City. Methods: For this case-control study, the authors enrolled 144 patients who had an IS and 128 healthy controls. The SNPs rs17880487 and rs80265967 of the SOD1 gene, rs4880 and rs2842960 of the SOD2 gene, and rs2695232 and rs7655372 of the SOD3 gene were detected through TaqMan polymerase chain reaction. Genotypes and allele frequencies of the 2 groups were compared. Odds ratio and 95% confidence intervals were calculated by unconditional logistic regression, and environmental factors were corrected with multivariate logistic regression analysis. Results: Rs7655372 of SOD3 was associated with a significantly increased risk of IS. Moreover, the A and GA genotypes of SNP rs7655372 were associated with increased risk of IS, whereas the A and GA genotypes were risk factors for IS. Furthermore, multivariate logistic regression analysis showed that the rs7655372 GA genotype is the independent risk factor for IS. Conclusion: The SOD3 gene rs7655372 locus polymorphism is a risk factor for IS in the Dali region.

Stroke is a sudden cerebrovascular circulatory disorder with high morbidity, disability, mortality, and recurrence rate, but its pathogenesis and key genes are still unclear. In this study, bioinformatics was used to deeply analyze the pathogenesis of stroke and related key genes, so as to study the potential pathogenesis of stroke and provide guidance for clinical treatment. Gene Expression profiles of GSE58294 and GSE16561 were obtained from Gene Expression Omnibus (GEO), the differentially expressed genes (DEGs) were identified between IS and normal control group. The different expression genes (DEGs) between IS and normal control group were screened with the GEO2R online tool. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of the DEGs were performed. Using the Database for Annotation, Visualization and Integrated Discovery (DAVID) and gene set enrichment analysis (GSEA), the function and pathway enrichment analysis of DEGS were performed. Then, a protein–protein interaction (PPI) network was constructed via the Search Tool for the Retrieval of Interacting Genes (STRING) database. Cytoscape with CytoHubba were used to identify the hub genes. Finally, NetworkAnalyst was used to construct the targeted microRNAs (miRNAs) of the hub genes. A total of 85 DEGs were screened out in this study, including 65 upward genes and 20 downward genes. In addition, 3 KEGG pathways, cytokine − cytokine receptor interaction, hematopoietic cell lineage, B cell receptor signaling pathway, were significantly enriched using a database for labeling, visualization, and synthetic discovery. In combination with the results of the PPI network and CytoHubba, 10 hub genes including CEACAM8, CD19, MMP9, ARG1, CKAP4, CCR7, MGAM, CD79A, CD79B, and CLEC4D were selected. Combined with DEG-miRNAs visualization, 5 miRNAs, including hsa-mir-146a-5p, hsa-mir-7-5p, hsa-mir-335-5p, and hsa-mir-27a- 3p, were predicted as possibly the key miRNAs. Our findings will contribute to identification of potential biomarkers and novel strategies for the treatment of ischemic stroke, and provide a new strategy for clinical therapy.

Hepatocellular carcinoma (HCC) is a common malignant tumour with high rates of morbidity and mortality worldwide. Therefore, it is of great significance to find new molecular markers for HCC diagnosis and treatment. G6PD is known to be dysregulated in a variety of tumours. In addition, the ceRNA network plays a crucial role in the occurrence and development of HCC. However, the mechanism by which the ceRNA network regulates G6PD in HCC remains unclear. We used TCGA-LIHC data to analyse the possibility of using G6PD as an independent prognostic marker. UCR, MCR, and ROC analysis were used to analyse the influence of G6PD overexpression on the prognosis of HCC patients. We also analysed the biological function of G6PD, its effect on the immune microenvironment, and drug sensitivity. Finally, we constructed a ceRNA network of lncRNAs/miR-22-5p/G6PD to explore the regulatory mechanism of G6PD. G6PD was highly expressed in HCC, was related to pathological stage and poor prognosis, and could be used as an independent prognostic indicator of HCC. The expression of G6PD was closely related to the immune microenvironment of HCC. In addition, the expression of G6PD in HCC could be regulated by the ceRNA network. Therefore, G6PD can be used as an immunotherapy target to improve the survival and prognosis of HCC patients, and the ceRNA regulatory network of G6PD has potential diagnostic and therapeutic value for HCC.

Objective : The present study aimed to identify the function of ischemic stroke (IS) patients’ peripheral blood and its role in IS, explore the pathogenesis, and provide direction for clinical research progress by comprehensive bioinformatics analysis.Methods : Two datasets, including GSE58294 and GSE22255, were downloaded from Gene Expression Omnibus database. GEO2R was utilized to obtain differentially expressed genes (DEGs). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of DEGs were performed using the database annotation, visualization and integrated discovery database. The protein-protein interaction (PPI) network of DEGs was constructed by search tool of searching interactive gene and visualized by Cytoscape software, and then the Hub gene was identified by degree analysis. The microRNA (miRNA) and miRNA target genes closely related to the onset of stroke were obtained through the miRNA gene regulatory network.Results : In total, 36 DEGs, containing 27 up-regulated and nine down-regulated DEGs, were identified. GO functional analysis showed that these DEGs were involved in regulation of apoptotic process, cytoplasm, protein binding and other biological processes. KEGG enrichment analysis showed that these DEGs mediated signaling pathways, including HTLV-I infection and microRNAs in cancer. The results of PPI network and cytohubba showed that there was a relationship between DEGs, and five hub genes related to stroke were obtained : SOCS3, KRAS, PTGS2, EGR1, and DUSP1. Combined with the visualization of DEG-miRNAs, hsa-mir-16-5p, hsa-mir-181a-5p and hsa-mir-124-3p were predicted to be the key miRNAs in stroke, and three miRNAs were related to hub gene.Conclusion : Thirty-six DEGs, five Hub genes, and three miRNA were obtained from bioinformatics analysis of IS microarray data, which might provide potential targets for diagnosis and treatment of IS.

To perform a systematic review of the data collected from case-control studies conducted earlier to investigate the correlation between E-selectin S128R polymorphism and ischemic stroke (IS) risk among the Chinese population. The PubMed, Web of Science, Chinese biomedical literature database (CBM), Chinese databases China National Knowledge Infrastructure (CNKI), WanfangData knowledge service platform (Wanfang Data), and information resource integration service platform (VIP) Databases were searched to retrieve case-control studies on the correlation between E-selectin gene S128R polymorphism and IS from the inception of the database till June 2019. The literature was screened, data were extracted, the risk of bias was reviewed, and the studies included were assessed independently by two reviewers. Stata ver. 12.0 software (Stata Corp LLC, College Station, TX, USA) was used to perform the meta-analysis. A total of 2907 cases from eight case-control studies involving 1478 IS patients and 1429 controls were included in this study. The R allele and RS genotype in E-selectin were found to be associated with the risk of IS as per the results of the meta-analysis (R vs. S : odds ratio [OR], 2.75; 95% confidence interval [CI], 2.15-3.51; p<0.00001; RS vs. SS : OR, 2.50; 95% CI, 1.95-3.19; p<0.00001; RR+RS vs. SS : OR, 2.85, 95% CI, 2.21-3.67; p<0.00001). The E-selectin gene S128R polymorphism is likely related to IS based on the results of a meta-analysis in the Chinese population, and the R allele and RS genotype of E-selectin may be IS risk factors. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.