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pmid:33083497
Integrative Analyses of Genes Associated with Fulminant Type 1 Diabetes.
Xiaofeng Ye · Tianshu Zeng · Wen Kong · Lu-Lu Chen
Journal of immunology research · 2020 doi:10.1155/2020/1025857
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Complete file
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We intend to screen for crucial genes and potential molecular mechanisms in FT1D in this study.\nMETHOD: We downloaded GSE44314, which includes six healthy controls and five patients with FT1D, from the GEO database. Identification of differentially expressed genes (DEGs) was performed by NetworkAnalyst. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses of DEGs were screened by an online tool-Database for Annotation, Visualization, and Integration Discovery (DAVID). Protein-protein interaction (PPI) network and hub genes among DEGs were analyzed by NetworkAnalyst. And we also use NetworkAnalyst to find out the microRNAs (miRNAs) and transcription factors (TFs) which regulate the expression of DEGs.\nRESULT: We identified 130 DEGs (60 upregulated and 70 downregulated DEGs) between healthy controls and FT1D patients. GO analysis results revealed that DEGs were mostly enriched in generation of precursor metabolites and energy, neurohypophyseal hormone activity, and mitochondrial inner membrane. KEGG pathway analysis demonstrated that DEGs were mostly involved in nonalcoholic fatty liver disease. Results indicated that NCOA1, SRF, ERBB3, EST1, TOP1, UBE2S, INO80, COX7C, ITGAV, and COX6C were the top hub genes in the PPI network. Furthermore, we recognized that LDLR, POTEM, IFNAR2, BAZ2A, and SRF were the top hub genes in the miRNA-target gene network, and SRF, TSPAN4, CD59, ETS1, and SLC25A25 were the top hub genes in the TF-target gene network.\nCONCLUSION: Our study pinpoints key genes and pathways associated with FT1D by a sequence of bioinformatics analysis on DEGs. These identified genes and pathways provide more detailed molecular mechanisms of FT1D and may provide novel therapeutic targets.", "claims": [{"id": "claim-method", "statement": "NetworkAnalyst [16, 17] (https://www.networkanalyst.ca), a website for integrative statistical and visualizing tool, was used to determine the DEGs between healthy controls and FT1D patients. The cutoff of the P value was adjusted to 0.05, and ∣log fold change | (∣log FC∣) > 0.585 for the DEG discrimination, using the false discovery rate (FDR) found on the Benjamini-Hochberg program and moderated t-test based on the Limma algorithm.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:33083497", "locator": "sections[4] \"2.2. 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The cutoff of the P value was adjusted to 0.05, and ∣log fold change | (∣log FC∣) > 0.585 for the DEG discrimination, using the false discovery rate (FDR) found on the Benjamini-Hochberg program and moderated t-test based on the Limma algorithm."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The data used to support the findings of this study are included within the article.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:33083497", "locator": "sections[18] \"Data Availability\" paragraph 2", "quote": "The data used to support the findings of this study are included within the article."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": null, "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:33083497"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. 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The cutoff of the P value was adjusted to 0.05, and ∣log fold change | (∣log FC∣) > 0.585 for the DEG discrimination, using the false discovery rate (FDR) found on the Benjamini-Hochberg program and moderated t-test based on the Limma algorithm."], "order_basis": "analysis_only", "id": "assay:1"}]}