Dataset Information

Identification of primary genes in glomeruli compartment of immunoglobulin A nephropathy by bioinformatic analysis.

ABSTRACT: The current study is aimed to explore the specific genes which are responsible for the manifestation of Immunoglobulin A nephropathy (IgAN). Gene expression profiles GSE37460, GSE93798 and GSE104948 were analyzed using biological informatics methods to identify differentially expressed genes (DEGs) in IgAN glomeruli samples which were then compared to normal control samples. Subsequently, the DEGs were overlapped to explore genes with significant expression in at least two profiles. Finally, the enrichment analysis was conducted and the protein-protein interaction (PPI) network was constructed for the overlapping DEGs. A total of 28 genes were up-regulated and 10 genes were down-regulated. The up-regulated genes including CD44 and FN1 were chiefly involved in extracellular matrix receptors interaction pathway. In addition, CX3CR1 and CCL4 were associated with chemokine signaling pathway. ITGB2, PTPRC, FN1, and FCER1G were hub genes with a high degree of interaction in the PPI network. Therefore, this study identified many significant genes associated with extracellular matrix expansion and inflammatory mechanism which may be the novel biomarker and target candidates in IgAN.

SUBMITTER: Miraji MK

PROVIDER: S-EPMC6645034 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Identification of primary genes in glomeruli compartment of immunoglobulin A nephropathy by bioinformatic analysis.

Miraji Mohammed Khamis MK Cheng Yichun Y Ge Shuwang S Xu Gang G

PeerJ 20190719

The current study is aimed to explore the specific genes which are responsible for the manifestation of Immunoglobulin A nephropathy (IgAN). Gene expression profiles GSE37460, GSE93798 and GSE104948 were analyzed using biological informatics methods to identify differentially expressed genes (DEGs) in IgAN glomeruli samples which were then compared to normal control samples. Subsequently, the DEGs were overlapped to explore genes with significant expression in at least two profiles. Finally, the ...[more]

PMID: 31355054

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Project description:BackgroundIgAV, the most common systemic vasculitis in childhood, is an immunoglobulin A-associated immune complex-mediated disease and its underlying molecular mechanisms are not fully understood. This study attempted to identify differentially expressed genes (DEGs) and find dysregulated immune cell types in IgAV to find the underlying pathogenesis for IgAVN.MethodsGSE102114 datasets were obtained from the Gene Expression Omnibus (GEO) database to identify DEGs. Then, the protein-protein interaction (PPI) network of the DEGs was constructed using the STRING database. And key hub genes were identified by cytoHubba plug-in, performed functional enrichment analyses and followed by verification using PCR based on patient samples. Finally, the abundance of 24 immune cells were detected by Immune Cell Abundance Identifier (ImmuCellAI) to estimate the proportions and dysregulation of immune cell types within IgAVN.ResultA total of 4200 DEGs were screened in IgAVN patients compared to Health Donor, including 2004 upregulated and 2196 downregulated genes. Of the top 10 hub genes from PPI network, STAT1, TLR4, PTEN, UBB, HSPA8, ATP5B, UBA52, and CDC42 were verified significantly upregulated in more patients. Enrichment analyses indicated that hub genes were primarily enriched in Toll-like receptor (TLR) signaling pathway, nucleotide oligomerization domain (NOD)-like receptor signaling pathway, and Th17 signaling pathways. Moreover, we found a diversity of immune cells in IgAVN, consisting mainly of T cells. Finally, this study suggests that the overdifferentiation of Th2 cells, Th17 cells and Tfh cells may be involved in the occurrence and development of IgAVN.ConclusionWe screened out the key genes, pathways and maladjusted immune cells and associated with the pathogenesis of IgAVN. The unique characteristics of IgAV-infiltrating immune cell subsets were confirmed, providing new insights for future molecular targeted therapy and a direction for immunological research on IgAVN.

Project description:Lung cancer is the world's most common malignancies and ranks first among all cancer-related deaths. Lung adenocarcinoma (LUAD) is the most frequent histological type in lung cancer. Its pathogenesis has not yet been fully elucidated, so it is of great significance to explore related genes for elucidating the molecular mechanism involved in occurrence and development of LUAD.To explore the crucial genes associated with LUAD development and progression, microarray datasets GSE7670, GSE10072, and GSE31547 were acquired from the Gene Expression Omnibus (GEO) database. R language Limma package was adopted to screen the differentially expressed genes (DEGs). The clusterProfiler package was used for enrichment analysis and annotation of the Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genome (KEGG) pathways for DEGs. The Search Tool for the Retrieval of Interacting Genes database (STRING) was used to construct the protein interaction network for DEGs, while Cytoscape was adopted to visualize it. The functional module was screened with Cytoscape's MCODE (The Molecular Complex Detection) plugin. The crucial genes associated with LUAD were identified by cytoHubba plugin. Kaplan-Meier plotter online tool was used to perform survival analysis of the hub gene.Three hundred twenty-one DEGs in total were screened, of which 105 were upregulated and 216 were downregulated. It was found that some GO terms and pathways (e.g., collagen trimer, extracellular structure organization, heparin binding, complement and coagulation cascades, malaria, protein digestion and absorption, and PPAR signaling pathway) were considerably enriched in DEGs. UBE2C, TOP2A, RRM2, CDC20, CCNB2, KIAA0101, BUB1B, TPX2, PRC1, and CDK1 were identified as crucial genes. Survival analysis showed that the overexpression of UBE2C, TOP2A, RRM2, CDC20, CCNB2, KIAA0101, BUB1B, TPX2, and PRC1 significantly reduced the overall survival of LUAD patients. One of the crucial genes: UBE2C was validated by immunohistochemistry to be upregulated in LUAD tissues.This study screened out potential biomarkers of LUAD, providing a theoretical basis for elucidating the pathogenesis and evaluating the prognosis of LUAD.

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Identification of primary genes in glomeruli compartment of immunoglobulin A nephropathy by bioinformatic analysis.

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Identification of primary genes in glomeruli compartment of immunoglobulin A nephropathy by bioinformatic analysis.

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