Analysis of differentially expressed genes in individuals with noninfectious uveitis based on data in the gene expression omnibus database

Noninfectious uveitis (NIU), an intraocular inflammation caused by immune-mediated reactions to eye antigens, is associated with systemic rheumatism and several autoimmune diseases. However, the mechanisms underlying the pathogenesis of uveitis are poorly understood. Therefore, we aimed to identify differentially expressed genes (DEGs) in individuals with NIU and to explore its etiologies using bioinformatics tools.{"type":"entrez-geo","attrs":{"text":"GSE66936","term_id":"66936"}}GSE66936 and {"type":"entrez-geo","attrs":{"text":"GSE18781","term_id":"18781"}}GSE18781 datasets from the gene expression omnibus (GEO) database were merged and analyzed. Functional enrichment analysis was performed, and protein-protein interaction (PPI) networks were constructed.A total of 89 DEGs were identified. Gene ontology (GO) enrichment analysis identified 21 enriched gene sets. Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analysis identified four core enriched pathways: antigen processing and expression signaling, natural killer (NK) cell-mediated cytotoxicity signaling, glutathione metabolic signal transduction, and arachidonic acid metabolism pathways. PPI network analysis revealed an active component-target network with 40 nodes and 132 edges, as well as several hub genes, including CD27, LTF, NCR3, SLC4A1, CD69, KLRB1, KIR2DL3, KIR3DL1, and GZMK.The eight potential hub genes may be associated with the risk of developing NIU. NK cell-mediated cytotoxicity signaling might be the key molecular mechanism in the occurrence and development of NIU. Our study provided new insights on NIU, its genetics, molecular pathogenesis and new therapeutic targets.     

先兆子痫患者外周血潜在标志物及可能机制探索

目的基于GEO数据库挖掘先兆子痫(PE)患者外周血潜在标志物及可能机制。方法从GEO数据库中收集PE人群研究的外周血mRNA基因芯片GSE48424,共计36例,并根据是否发生PE将其分为两组,即PE组和对照组。在GEO2R平台内对各组的数据进行差异mRNA基因分析,剔除|Log2 Fold Change|<1、修正P值>0. 05以及信息不完整的基因数据,将筛选出的差异基因导入String在线数据库完成基因本体(GO)富集分析,并获得差异基因所编码的蛋白质之间的相互作用。结果筛选出差异基因65个,其中Toll样受体4 (TLR4)和GTP环化水解酶1 (GCH1)是处于网络核心的蛋白。差异基因主要参与的生物学过程包括对脂多糖的反应、对肿瘤坏死因子的反应、转化生长因子β生成的积极调节、Toll样受体信号通路的正调节和烟酰胺代谢过程;主要富集的细胞组分是神经元投射、突触小泡、高尔基体、质膜的整体成分和内质网;主要发挥的分子功能包括受体活性和蛋白质结合。结论 PE的发生可能与对脂多糖的受体活性调节有关,TLR4和GCH1可作为外周血中的潜在标志物。     

不同阶段阿尔茨海默病患者海马CA1区基因表达的生物信息学分析＊

目的 对不同阶段阿尔茨海默病海马CA1区差异表达的基因进行生物信息学分析以探究阿尔茨海默病（Alzheimer’s disease，AD）发生的分子机制。方法 从GEO数据库获取AD早期、中期、晚期基因芯片数据，筛选3个时期都具有的显著差异表达的基因，构建蛋白与蛋白相互作用（PPI）网络，利用cytoNCA获取关键基因并进行细胞实验验证，同时分析这些关键基因参与的主要生物学过程和信号通路富集程度，以探究其分子机制。结果 从AD不同阶段的基因芯片（GSE28146)中筛选出在不同时期均出现差异表达的基因412个，使用STRING构建PPI网络关系，cytoNCA构建并结合网络拓扑分析，共筛选出关键基因12个，qPCR验证了芯片结果的准确性；GO和Pathway富集分析显示与一氧化氮合酶活性的调节、细胞凋亡、缺氧反应、神经炎症等生物学过程密切相关，主要涉及的信号通路有Rap1、Ras、NF-κB、TNF、PI3K-Akt。结论 本研究发现TNF-α、白介素1-β（IL-1β）、白介素6（IL-6）等炎症相关基因的失调可能是导致AD发生的重要因素，它们可能是防治AD的潜在生物标志物或药物靶点。     

Screening and identification of key genes between liver hepatocellular carcinoma (LIHC) and cholangiocarcinoma (CHOL) by bioinformatic analysis

Background:Liver hepatocellular carcinoma (LIHC) and cholangiocarcinoma (CHOL) are common primary liver cancers worldwide. Liver stem cells have biopotential to differentiate into either hepatocytes and cholangiocytes, the phenotypic overlap between LIHC and CHOL has been acceptable as a continuous liver cancer spectrum. However, few studies directly investigated the underlying molecular mechanisms between LIHC and CHOL.Method:To identify the candidate genes between LIHC and CHOL, three data series including {"type":"entrez-geo","attrs":{"text":"GSE31370","term_id":"31370"}}GSE31370, {"type":"entrez-geo","attrs":{"text":"GSE15765","term_id":"15765"}}GSE15765 and {"type":"entrez-geo","attrs":{"text":"GSE40367","term_id":"40367"}}GSE40367 were downloaded from Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were identified, and function enrichment analyses were performed. The protein-protein interaction network (PPI) was constructed and the module analysis was performed using STRING and Cytoscape.Results:A total of 171 DEGs were identified, consisting of 49 downregulated genes and 122 upregulated genes. Compared with CHOL, the enriched functions of the DEGs mainly included steroid metabolic process, acute inflammatory response, coagulation. Meanwhile, the pathway of KEGG enrichment analyses showed that the upregulated gene(s) were mainly enriched complement and coagulation cascades, cholesterol metabolism and PPAR signaling pathway, while the downregulated gene(s) were mainly enriched in ECM-receptor interaction, focal adhesion, bile secretion. Similarly, the most significant module was identified and biological process analysis revealed that these genes were mainly enriched in regulation of blood coagulation, acute inflammatory response, complement and coagulation cascades. Finally, two (ITIH2 and APOA2) of 10 hub genes had been screened out to help differential diagnosis.Conclusion:171 DEGs and two (ITIH2 and APOA2) of 10 hub genes identified in the present study help us understand the different molecular mechanisms between LIHC and CHOL, and provide candidate targets for differential diagnosis.     

TTLL12在鼻咽癌中的表达及临床意义

目的 探讨鼻咽癌患者中微管蛋白酪氨酸连接酶类似物12（tubulin tyrosine ligase like 12，TTLL12）的表达及临床意义。方法 利用免疫组织化学法研究TTLL12在鼻咽慢性炎症组织和鼻咽癌组织中的表达，分析其在不同鼻咽组织中的表达差异及与鼻咽癌患者临床特征之间的相关性。从GEO数据库中筛选合适的鼻咽癌基因芯片数据集GSE102349，分析不同临床分期中TTLL12基因在转录水平上的表达差异、TTLL12与鼻咽癌患者无进展生存的相关性及可能参与的通路。结果 免疫组织化学结果显示，与鼻咽慢性炎症组织相比，TTLL12蛋白在鼻咽癌组织中表达明显上调（P<0.001）。TTLL12高表达鼻咽癌患者的T3～T4、N2～N3、Ⅲ～Ⅳ期的占比显著高于TTLL12低表达患者（P<0.05）。TTLL12高表达患者的总生存显著低于低表达患者（P=0.027）。TTLL12高表达和N分期均是影响鼻咽癌患者预后的独立危险因素（P<0.05）。在基因芯片数据集中，TTLL12 mRNA在鼻咽癌组织中的表达与临床分期呈正相关（P=0.033），TTLL12高表达的鼻咽癌患者无进展生存率显著低于TTLL12低表达患者（P=0.041）。KEGG富集分析显示TTLL12高表达基因样本主要富集在趋化因子信号通路，与人类T细胞白血病病毒1型感染及EB病毒感染密切相关。结论 TTLL12表达上调作为不利因素可促进鼻咽癌的发生发展。     

Deciphering crucial genes in coeliac disease by bioinformatics analysis

Abstract

Coeliac disease (CD) is a chronic autoimmune disease that is characterized by malabsorption in sensitive individuals. CD is triggered by the ingestion of grains containing gluten. CD is concomitant with several other disorders, including dermatitis herpetiformis, selective IgA deficiency, thyroid disorders, diabetes mellitus, various connective tissue disorders, inflammatory bowel disease, and rheumatoid arthritis. The advent of high throughput technologies has provided a massive wealth of data which are processed in various omics scale fields. These approaches have revolutionized the medical research and monitoring of the biological systems. In this regard, omics scaled analyses of CD by Comparative Toxicogenomics Database (CTD), DISEASES, and GeneCards databases have retrieved 2656?CD associated genes. Amongst, 54 genes were assigned by Venn Diagram of the intersection to be shared by these 3 databases for CD. These common genes were subjected to further analysis and screening. The Enrich database, GeneMANIA, Cytoscape, and WebGestalt (WEB-based GEne SeT AnaLysis Toolkit) were employed for functional analysis. These analyses indicated that the obtained genes are mainly involved in the immune system and signalling pathways related to autoimmune diseases. The STAT1, ALB, IL10, IL2, IL4, IL17A, TGFB1, IL1B, IL6, TNF, IFNG hub genes were particularly indicated to have significant roles in CD. Functional analyses of these hub genes by GeneMANIA indicated that they are involved in immune systems regulation. Moreover, 25 out of 54 genes were identified to be seed genes by the WebGestalt database. Gene set analysis with GEO2R tool from Gene Expression Omnibus (GEO) showed that there were 15 significant genes in GSE76168, 29 significant genes in GSE87460, 12 significant genes in GSE87458, 9 significant genes in GSE87457, 3753 significant genes in GSE112102 and 1043 significant genes in GSE102991 with differential expression in coeliac patients compared to controls. The IRF1and STAT1 genes were common between the significant genes from GEO and the 54?CD related genes from three public databases. In the light these results, nine key genes, including IRF1, STAT1, IL17A, TGFB1, ALB, IL10, IL2, IL4, and IL1B, were identified to be associated with CD. These findings could be used to find novel diagnostic biomarkers, understand the pathology of disease, and devise more efficient treatments.     

The nuclear receptors pregnane X receptor and constitutive androstane receptor contribute to the impact of fipronil on hepatic gene expression linked to thyroid hormone metabolism

Fipronil is described as a thyroid disruptor in rat. Based on the hypothesis that this results from a perturbation of hepatic thyroid hormone metabolism, our goal was to investigate the pathways involved in fipronil-induced liver gene expression regulations. First, we performed a microarray screening in the liver of rats treated with fipronil or vehicle. Fipronil treatment led to the upregulation of several genes involved in the metabolism of xenobiotics, including the cytochrome P450 Cyp2b1, Cyp2b2 and Cyp3a1, the carboxylesterases Ces2 and Ces6, the phase II enzymes Ugt1a1, Sult1b1 and Gsta2, and the membrane transporters Abcc2, Abcc3, Abcg5, Abcg8, Slco1a1 and Slco1a4. Based on a large overlap with the target genes of constitutive androstane receptor (CAR) and pregnane X receptor (PXR), we postulated that these two nuclear receptors are involved in mediating the effects of fipronil on liver gene expression in rodents. We controlled that liver gene expression changes induced by fipronil were generally reproduced in mice, and then studied the effects of fipronil in wild-type, CAR- and PXR-deficient mice. For most of the genes studied, the gene expression modulations were abolished in the liver of PXR-deficient mice and were reduced in the liver of CAR-deficient mice. However, CAR and PXR activation in mouse liver was not associated with a marked increase of thyroid hormone clearance, as observed in rat. Nevertheless, our data clearly indicate that PXR and CAR are key modulators of the hepatic gene expression profile following fipronil treatment which, in rats, may contribute to increase thyroid hormone clearance.     

FKBP5 expression in human adipose tissue increases following dexamethasone exposure and is associated with insulin resistance

Objective

To study effects of dexamethasone on gene expression in human adipose tissue aiming to identify potential novel mechanisms for glucocorticoid-induced insulin resistance.

Materials/methods

Subcutaneous and omental adipose tissue, obtained from non-diabetic donors (10 M/15 F; age: 28–60 years; BMI: 20.7–30.6 kg/m²), was incubated with or without dexamethasone (0.003–3 μmol/L) for 24 h. Gene expression was assessed by microarray and real time-PCR and protein expression by immunoblotting.

Results

FKBP5 (FK506-binding protein 5) and CNR1 (cannabinoid receptor 1) were the most responsive genes to dexamethasone in both subcutaneous and omental adipose tissue (~ 7-fold). Dexamethasone increased FKBP5 gene and protein expression in a dose-dependent manner in both depots. The gene product, FKBP51 protein, was 10-fold higher in the omental than in the subcutaneous depot, whereas the mRNA levels were similar. Higher FKBP5 gene expression in omental adipose tissue was associated with reduced insulin effects on glucose uptake in both depots. Furthermore, FKBP5 gene expression in subcutaneous adipose tissue was positively correlated with serum insulin, HOMA-IR and subcutaneous adipocyte diameter and negatively with plasma HDL-cholesterol. FKBP5 SNPs were found to be associated with type 2 diabetes and diabetes-related phenotypes in large population-based samples.

Conclusions

Dexamethasone exposure promotes expression of FKBP5 in adipose tissue, a gene that may be implicated in glucocorticoid-induced insulin resistance.