Identification of crucial extracellular genes as potential biomarkers in newly diagnosed Type 1 diabetes via integrated bioinformatics analysis.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:39802181", "kind": "science-record", "revision": 4, "content_hash": "sha256:eb52006315173a631f0774ea33a0ba670d49ad83633f5896a0edc7bbe6f0fbd0", "created_at": "2026-11-01T20:30:06Z", "updated_at": "2026-11-01T22:55:59Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of crucial extracellular genes as potential biomarkers in newly diagnosed Type 1 diabetes via integrated bioinformatics analysis.", "doi": "10.7717/peerj.18660", "pmid": "39802181", "authors": ["Ming Gao", "Qing Liu", "Lingyu Zhang", "Fatema Tabak", "Yifei Hua", "Wei Shao", "Yangyang Li", "Li Qian", "Yu Liu"], "journal": "PeerJ", "year": 2025, "abstract": "Purpose: In this study, we aimed to study the role of extracellular proteins as biomarkers associated with newly diagnosed Type 1 diabetes (NT1D) diagnosis and prognosis.\nPatients and Methods: We retrieved and analyzed the GSE55098 microarray dataset from the Gene Expression Omnibus (GEO) database. Using R software, we screened out the extracellular protein-differentially expressed genes (EP-DEGs) through several protein-related databases. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were applied to describe the role and function of these EP-DEGs. We used the STRING database to construct the interaction of proteins, Cytoscape software to visualize the protein-protein interaction (PPI) networks, and its plugin CytoHubba to identify the crucial genes between PPI networks. Finally, we used the comparative toxicogenomics database (CTD) to evaluate the connection between NT1D with the potential crucial genes and we validated our conclusions with another dataset (GSE33440) and some clinical samples.\nResults: We identified 422 DEGs and 122 EP-DEGs from a dataset that includes (12) NT1D patients compared with (10) healthy people. Protein digestion and absorption, toll-like receptor signaling, and T cell receptor signaling were the most meaningful pathways defined by KEGG enrichment analyses. We recognized nine important extracellular genes: GZMB, CCL4, TNF, MMP9, CCL5, IFNG, CXCL1, GNLY, and LCN2. CTD analyses showed that LCN2, IFNG, and TNF had higher levels in NT1D and hypoglycemia; while TNF, IFNG and MMP9 increased in hyperglycemia. Further verification showed that LCN2, MMP9, TNF and IFNG were elevated in NT1D patients.\nConclusion: The nine identified key extracellular genes, particularly LCN2, IFNG, TNF, and MMP9, may be potential diagnostic biomarkers for NT1D. Our findings provide new insights into the molecular mechanisms and novel therapeutic targets of NT1D.", "claims": [{"id": "claim-method", "statement": "Specifically, the Benjamini-Hochberg procedure was used to adjust the p-values from the differential expression analysis.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39802181", "locator": "sections[5] \"Identification of DEGs and EP-DEGs\" paragraph 2", "quote": "Specifically, the Benjamini-Hochberg procedure was used to adjust the p-values from the differential expression analysis."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The raw measurements are available in the Supplemental Files.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39802181", "locator": "sections[25] \"Data Availability\" paragraph 2", "quote": "The raw measurements are available in the Supplemental Files."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The study identified 422 DEGs and 122 EP-DEGs in GSE55098.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:39802181", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "We identified 422 DEGs and 122 EP-DEGs from a dataset that includes (12) NT1D patients compared with (10) healthy people."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The study identified 422 DEGs and 122 EP-DEGs in GSE55098.", "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:39802181"], "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:GSE33440"], "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": "with Benjamini-Hochberg false discovery rate correction"}, "inputs": ["data:geo:GSE33440"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:39802181", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": 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