Integrated bioinformatics analysis screened the key genes and pathways of idiopathic pulmonary fibrosis.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:40280949", "kind": "science-record", "revision": 4, "content_hash": "sha256:ea88c2eb9b42d8f32f51709c82706051ff8d348719c3d1aa05d953848c7a13d6", "created_at": "2026-11-01T20:30:26Z", "updated_at": "2026-11-01T22:56:25Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Integrated bioinformatics analysis screened the key genes and pathways of idiopathic pulmonary fibrosis.", "doi": "10.1038/s41598-025-97037-9", "pmid": "40280949", "authors": ["Juan Wu", "Yangyang Wei", "Hong Kang", "Xiao Yu", "Shuting Wei", "Ting Xue", "Xiaomei Kong"], "journal": "Scientific reports", "year": 2025, "abstract": "To investigate the molecular mechanisms underlying idiopathic pulmonary fibrosis (IPF), we analyzed the GSE173355 and GSE173356 datasets obtained from the NCBI-GEO database. We identified differentially expressed genes (DEGs) and differentially methylated sites. Functional enrichment analysis was conducted for both DEGs and differentially methylated sites. Functional enrichment analysis was performed for both DEGs and differentially methylated sites, alongside an examination of immune-related scores, proportions, and GSVA enrichment scores of immune cells in IPF versus control samples. An integrated gene-methylation association analysis revealed 8 genes with expression levels negatively influenced by methylation. The Rap1 pathway, Focal adhesion, and Axon guidance were significantly enriched among both DEGs and differentially methylated sites. Immune-related scores were notably lower in the IPF group compared to the control group, with marked differences in immune cell proportions and GSVA enrichment scores. Screening of DEGs identified 361 differentially expressed immune-related genes (IRGs). Protein-protein interaction (PPI) network analysis using the STRING database and Cytoscape software unveiled 10 key genes and 3 core subnetworks. RT-qPCR validation in bleomycin-induced IPF mouse model and A549 EMT model confirmed the reliability of most findings. These results provide new insights into IPF pathogenesis and potential therapeutic strategies, necessitating further functional validation.", "claims": [{"id": "claim-method", "statement": "DEGs analysis between IPF and control cohorts was conducted utilizing both the limma and edgeR packages in the R language. Furthermore, differentially methylated sites between IPF and control was performed employing the t-test methodology implemented in the limma package9. The ELMER package13 of R language was used to analyze the association between mRNA and methylation, and the genes whose expression levels were significantly affected by methylation were screened.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:40280949", "locator": "sections[4] \"Expression analysis of DEGs and differentially methylated sites\" paragraph 2", "quote": "DEGs analysis between IPF and control cohorts was conducted utilizing both the limma and edgeR packages in the R language."}, {"asset": "source:pmid:40280949", "locator": "sections[4] \"Expression analysis of DEGs and differentially methylated sites\" paragraph 2", "quote": "Furthermore, differentially methylated sites between IPF and control was performed employing the t-test methodology implemented in the limma package9."}, {"asset": "source:pmid:40280949", "locator": "sections[6] \"Association analysis of mRNA and methylation\" paragraph 2", "quote": "The ELMER package13 of R language was used to analyze the association between mRNA and methylation, and the genes whose expression levels were significantly affected by methylation were screened."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets generated during the current study are available in the GEO database (http://www.ncbi.nlm.nih.gov/geo/) with the accession number GSE173355 and GSE173356. All analysis scripts, including those for RNA-seq data preprocessing, differential expression analysis, and pathway enrichment, have been uploaded to GitHub and are available at the following link: https://github.com/wujuan948725/RNAseq-methylation-analysis-2025.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:40280949", "locator": "sections[24] \"Data availability\" paragraph 2", "quote": "The datasets generated during the current study are available in the GEO database (http://www.ncbi.nlm.nih.gov/geo/) with the accession number GSE173355 and GSE173356. All analysis scripts, including those for RNA-seq data preprocessing, differential expression analysis, and pathway enrichment, have been uploaded to GitHub and are available at the following link: https://github.com/wujuan948725/RNAseq-methylation-analysis-2025."}], "state": "complete"}, {"id": "claim-target-result", "statement": "An integrated gene-methylation association analysis revealed 8 genes with expression levels negatively influenced by methylation.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:40280949", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "An integrated gene-methylation association analysis revealed 8 genes with expression levels negatively influenced by methylation."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "An integrated gene-methylation association analysis revealed 8 genes with expression levels negatively influenced by methylation.", "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:40280949"], "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:GSE173355"], "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": {}, "inputs": ["data:geo:GSE173355"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:40280949", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1038/s41598-025-97037-9", "sha256": "sha256:0875ef065b0e0b4442b183cedeb9eb9cb871c650035ae0a94b716f819fd1b626", "bytes": 55853, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1038/s41598-025-97037-9", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC12032202", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE173355", "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=GSE173355", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE173355", "version": null, "note": "The datasets generated during the current study are available in the GEO database (http://www.ncbi.nlm.nih.gov/geo/) with the accession number GSE173355 and GSE173356. 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