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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

Paper

complete

Experiment

complete

Data

partial

Analysis

complete

Execution

absent

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Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
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pmid:33083497
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2026-11-01T15:41:13Z
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2026-11-01T22:45:29Z
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title
Integrative Analyses of Genes Associated with Fulminant Type 1 Diabetes.
doi
10.1155/2020/1025857
pmid
33083497
authors array · 4 items
[0]
Xiaofeng Ye
[1]
Tianshu Zeng
[2]
Wen Kong
[3]
Lu-Lu Chen
journal
Journal of immunology research
year
2020
abstract
OBJECTIVE: Fulminant type 1 diabetes (FT1D) is a type of type 1 diabetes, which is characterized by rapid onset of disease and severe metabolic disorders. We intend to screen for crucial genes and potential molecular mechanisms in FT1D in this study. METHOD: 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. RESULT: 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. CONCLUSION: 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.
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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.
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sections[4] "2.2. Identification of Differentially Expressed Genes" paragraph 2
quote
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.
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sections[18] "Data Availability" paragraph 2
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The data used to support the findings of this study are included within the article.
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gene expression Fulminant type 1 diabetes vs classical type 1A diabetes vs healthy controls
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3.2. Functional Enrichment Analysis
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The results of Kyoto Encyclopedia of Genes and Genomes (KEGG) of DEGs ranked by P value.
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Sixteen genes with degrees < 10 in the protein-protein interaction network of the differentially expressed genes.
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3.3. PPI Network and Hub Gene Identification
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Sixteen genes with degrees < 10 in the protein-protein interaction network of the differentially expressed genes.
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quote
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.
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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.
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:33083497", "kind": "science-record", "revision": 8, "content_hash": "sha256:ac9fa8d6407237899f45d560928bfde7563028faa195905920e9ec7c1549b362", "created_at": "2026-11-01T15:41:13Z", "updated_at": "2026-11-01T22:45:29Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Integrative Analyses of Genes Associated with Fulminant Type 1 Diabetes.", "doi": "10.1155/2020/1025857", "pmid": "33083497", "authors": ["Xiaofeng Ye", "Tianshu Zeng", "Wen Kong", "Lu-Lu Chen"], "journal": "Journal of immunology research", "year": 2020, "abstract": "OBJECTIVE: Fulminant type 1 diabetes (FT1D) is a type of type 1 diabetes, which is characterized by rapid onset of disease and severe metabolic disorders. 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. Identification of Differentially Expressed Genes\" paragraph 2", "quote": "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."}], "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. This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE44314"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "complete", "blocked_on": null, "description": "Apply the paper's statistical method to the resolved series and compare the result with the published target.", "duration_hours": null, "parameters": {"fdr_threshold": "the Benjamini-Hochberg false discovery rate"}, "inputs": ["data:geo:GSE44314"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:33083497", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1155/2020/1025857", "sha256": "sha256:d484863f932eed9e08b27467e5fd64e21ee87191edf8ef29e95f8a8eba8a556c", "bytes": 35223, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1155/2020/1025857", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC7559223", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE44314", "role": "raw", "format": "geo-series", "media_type": "application/vnd.ncbi.geo-series+json", "uri": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE44314", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE44314", "version": null, "note": "The data used to support the findings of this study are included within the article.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The data used to support the findings of this study are included within the article.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM1082964", "GSM1082965", "GSM1082966", "GSM1082967", "GSM1082968", "GSM1082969", "GSM1082970", "GSM1082971", "GSM1082972", "GSM1082973", "GSM1082974", "GSM1082975", "GSM1082976", "GSM1082977", "GSM1082978", "GSM1082979"], "sample_count": 16, "group_sizes": null, "group_sizes_basis": null, "platform": "6480", "taxon": "Homo sapiens", "title": "gene expression Fulminant type 1 diabetes vs classical type 1A diabetes vs healthy controls", "resolution_checked_at": "2026-11-01T15:39:54Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "asset:table:pmid:33083497:1", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:0f11ac463dadb8778f441ce5bc4713ed1c5122f3c04c5cacbc1dcee85bd1fd81", "bytes": 1951, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[11]/table-wrap[1]#tab1", "version": null, "note": "The results of Gene Ontology (GO) of DEGs ranked by P value.", "structure": {"pmcid": "PMC7559223", "section_index": 11, "section_title": "3.2. 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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."}}, {"id": "method-2", "family": "network_analysis", "specific": "ppi_network", "label": "Network / pathway analysis", "dsl_operations": ["build_graph", "centrality_scores", "pathway_enrich"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["edge_list"], "evidence": {"score": 0.7, "band": "medium", "quote": "Protein-protein interaction"}}], "targets": [], "gaps": []}, "capability": {"state": "complete", "requirements": [{"capability_id": "capability:computational_analysis", "label": "Computational analysis platform", "assay_families": ["meta_analysis", "machine_learning", "survival_analysis", "statistical_regression", "pca", "molecular_docking", "network_analysis", "differential_expression", "gwas"], "availability_state": "owned", "tier_unlocked": "R1", "candidate": "Automated Assays Laravel application and simulated adapters"}], "gaps": []}, "readiness": {"state": "complete", "tier": "R1", "blocking_axis": "none", "blocked_on": "nothing:replicable_now", "axes": {"method": {"tier": "R1", "expressible": true, "required_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "missing_operations": [], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: limma_voom."}, "capability": {"tier": "R1", "capability_id": "capability:computational_analysis", "availability_state": "owned", "basis": "The computational analysis is owned. 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