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Query: UMLS:C0021051 (immunodeficiency)
 71,517 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

One key step of human immunodeficiency virus type 1 (HIV-1) infection is the integration of its viral cDNA. This process is mediated through complex networks of host-virus interactions that alter several normal cell functions of the host. To study the complexity of disturbances in cell gene expression networks by HIV-1 integration, we constructed a network of human macrophage genes located close to chromatin regions rich in proviruses. To perform the network analysis, we selected 28 genes previously identified as the target of cDNA integration and their transcriptional profiles were obtained from GEO Profiles (NCBI). A total of 2770 interactions among the 28 genes located around the HIV-1 proviruses in human macrophages formed a highly dense main network connected to five sub-networks. The overall network was significantly enriched by genes associated with signal transduction, cellular communication and regulatory processes. To simulate the effects of HIV-1 integration in infected macrophages, five genes with the most number of interaction in the normal network were turned off by putting in zero the correspondent expression values. The HIV-1 infected network showed changes in its topology and alteration in the macrophage functions reflected in a re-programming of biosynthetic and general metabolic process. Understanding the complex virus-host interactions that occur during HIV-1 integration, may provided valuable genomic information to develop new antiviral treatments focusing on the management of some specific gene expression networks associated with viral integration. This is the first gene network which describes the human macrophages genes interactions related with HIV-1 integration.
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PMID:Changes in the topology of gene expression networks by human immunodeficiency virus type 1 (HIV-1) integration in macrophages. 2189 93

Immunodeficiency, centromeric instability and facial anomalies type I (ICF1) syndrome is a rare genetic disease caused by mutations in DNA methyltransferase (DNMT) 3B, a de novo DNA methyltransferase. However, the molecular basis of how DNMT3B deficiency leads to ICF1 pathogenesis is unclear. Induced pluripotent stem cell (iPSC) technology facilitates the study of early human developmental diseases via facile in vitro paradigms. Here, we generate iPSCs from ICF Type 1 syndrome patient fibroblasts followed by directed differentiation of ICF1-iPSCs to mesenchymal stem cells (MSCs). By performing genome-scale bisulfite sequencing, we find that DNMT3B-deficient iPSCs exhibit global loss of non-CG methylation and select CG hypomethylation at gene promoters and enhancers. Further unbiased scanning of ICF1-iPSC methylomes also identifies large megabase regions of CG hypomethylation typically localized in centromeric and subtelomeric regions. RNA sequencing of ICF1 and control iPSCs reveals abnormal gene expression in ICF1-iPSCs relevant to ICF syndrome phenotypes, some directly associated with promoter or enhancer hypomethylation. Upon differentiation of ICF1 iPSCs to MSCs, we find virtually all CG hypomethylated regions remained hypomethylated when compared with either wild-type iPSC-derived MSCs or primary bone-marrow MSCs. Collectively, our results show specific methylome and transcriptome defects in both ICF1-iPSCs and differentiated somatic cell lineages, providing a valuable stem cell system for further in vitro study of the molecular pathogenesis of ICF1 syndrome. GEO accession number: GSE46030.
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PMID:Selective demethylation and altered gene expression are associated with ICF syndrome in human-induced pluripotent stem cells and mesenchymal stem cells. 2502 25

Objective To analyze the differentially expressed genes in peripheral blood of human immunodeficiency(HIV)/tubercle bacilli co-infected patients and explore the biological regulatory mechanism and network of key proteins,so as to provide new evidence for early diagnosis and clinical treatment of HIV/TB co-infected patients. Methods Microarray gene chip data of HIV/TB co-infected patients were downloaded from public databases GEO and imported into the analysis software GEO,STRING,PANTHER,and GenClip. The gene expression profiles,protein interaction networks,processes of molecular biology,and gene functions were analyzed. Results The expression profiles of 15 529 genes between the two groups of patients were similar,and gene expression profiles from 44 subjects were highly correlated. The 251 differentially expressed genes had good diagnostic capabilities in the differential diagnosis of HIV/TB infection. RPLP1 might be a key gene in the diagnosis of HIV/TB infection. The differentially expressed genes and positive regulators showed certain functions such as external stimuli,signal transduction pathways in cells,migration of neutrophils,and immunological and other relevant functionalities. Meanwhile,they may also be involved in free radical-related apoptosis,inflammation,and activation pathways. Conclusions A total of 251 differentially expressed genes are found to be able to distinguish simple HIV infection from HIV/TB infection. Protein-protein interaction network of top 40 differential expression genes includes RPLP1 gene,which is possibly associated with HIV/TB co-infection and may be involved in and the positive regulation of external stimuli,signal transduction pathways in cells,migration of neutrophils,and immunological functions. These findings may provide certain evidence for the diagnosis and treatment of HIV/TB infection.
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PMID:Bioinformatic Analysis of Differentially Expressed Genes in Peripheral Blood of Human Immunodeficiency Virus/Tubercle Bacilli Co-infected Patients. 2869 3

Hepatitis B virus (HBV) infection remains a severe health burden worldwide. Emerging long noncoding RNAs (lncRNAs) are hijacked to enhance virus replication or employed by the host to stimulate immune responses to clear the virus. LncRNA growth arrest-specific transcript 5 (GAS5) can regulate RNA virus by suppressing the replication of both hepatitis C virus and human immunodeficiency virus. In this study, we explored the changes of HBV replication by overexpressing or knocking down GAS5 in HepAD38 cell and HepG2 cell transfected with pHBV1.2. We found HBV can induce the expression of GAS5. However, GAS5 had no effect on extracellular HBsAg and HBeAg, nor intracellular HBV RNA and HBV DNA. In addition, GAS5 possessed similar expression levels between stable HBV-producing cell lines and hepatoma cell lines. Furthermore, GAS5 showed no difference between healthy subjects and patients with chronic HBV in multiple GEO microarray data sets by GEO2R analysis. Taken together these results, GAS5 does not modulate the replication of HBV but it inhibits cell proliferation in HepAD38. This provides insights into the possible roles of GAS5 in HBV infection.
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PMID:Long noncoding RNA GAS5 does not regulate HBV replication. 3130 Nov 49

Renal cell carcinoma (RCC) is one of the most common malignancies in the urinary system, among which the proportion of clear cell RCC (ccRCC) is over 80%. This study aims to explore potential signaling pathways and key biomarkers that drive RCC progression. The RCC GEO Datasets GSE15641 was featured to screen differentially expressed genes (DEGs). The pathway enrichment and functional annotation of differentially expressed genes were analyzed using the Kyoto Encyclopedia of Genes and Genomes (KEGG) and the Gene Ontology (GO). We screened Hub genes from DEGs using protein-protein interaction (PPI) networks and Cytoscape software. The survival and diagnostic analysis of these hub genes was performed to evaluate their potential prognostic and diagnostic value for ccRCC. In GSE15641 dataset, 598 DEGs were captured according to screening criteria (406 up-regulated genes and 192 down-regulated genes). Meanwhile, 15 hub genes were screened out from DEGs using PPI and Cytoscape. Kaplan Meier and ROC curve analysis identified three potential prognostic and diagnostic biomarkers (TGFB1, TIMP1 and VIM) for ccRCC from 15 hub genes. Gene set enrichment analysis (GSEA) revealed that these three dysregulated genes are mainly enriched in primary immunodeficiency, ECM receptor interaction, cytokine receptor interaction and natural killer cell-mediated cytotoxicity pathway. In summary, our findings discovered pivotal gene expression signatures and signaling pathways in the progression of ccRCC. TGFB1, TIMP1 and VIM might contribute to the progression of ccRCC, which could have potential as biomarkers or therapeutic targets for ccRCC.
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PMID:The screening of pivotal gene expression signatures and biomarkers in renal carcinoma. 3177 71

Objective: The present study was designed to identify potential diagnostic markers for acute myocardial infarction (AMI) and determine the significance of immune cell infiltration in this pathology. Methods: Two publicly available gene expression profiles (GSE66360 and GSE48060 datasets) from human AMI and control samples were downloaded from the GEO database. Differentially expressed genes (DEGs) were screened between 80 AMI and 71 control samples. The LASSO regression model and support vector machine recursive feature elimination (SVM-RFE) analysis were performed to identify candidate biomarkers. The area under the receiver operating characteristic curve (AUC) value was obtained and used to evaluate discriminatory ability. The expression level and diagnostic value of the biomarkers in AMI were further validated in the GSE60993 dataset (17 AMI patients and 7 controls). The compositional patterns of the 22 types of immune cell fraction in AMI were estimated based on the merged cohorts using CIBERSORT. Results: A total of 27 genes were identified. The identified DEGs were mainly involved in carbohydrate binding, Kawasaki disease, atherosclerosis, and arteriosclerotic cardiovascular disease. Gene sets related to atherosclerosis signaling, primary immunodeficiency, IL-17, and TNF signaling pathways were differentially activated in AMI compared with the control. IL1R2, IRAK3, and THBD were identified as diagnostic markers of AMI (AUC = 0.877) and validated in the GSE60993 dataset (AUC = 0.941). Immune cell infiltration analysis revealed that IL1R2, IRAK3, and THBD were correlated with M2 macrophages, neutrophils, monocytes, CD4+ resting memory T cells, activated natural killer (NK) cells, and gamma delta T cells. Conclusion: IL1R2, IRAK3, and THBD can be used as diagnostic markers of AMI, and can provide new insights for future studies on the occurrence and the molecular mechanisms of AMI.
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PMID:Predicting Diagnostic Gene Biomarkers Associated With Immune Infiltration in Patients With Acute Myocardial Infarction. 3319 75