Identification and validation of metabolism-related hub genes in idiopathic pulmonary fibrosis.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:36923791", "kind": "science-record", "revision": 4, "content_hash": "sha256:83a1553ee940144dfe6f10b30505a2f11ee7fc7113e968a2dcd3c8b586170829", "created_at": "2026-11-01T19:01:34Z", "updated_at": "2026-11-01T22:51:30Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification and validation of metabolism-related hub genes in idiopathic pulmonary fibrosis.", "doi": "10.3389/fgene.2023.1058582", "pmid": "36923791", "authors": ["Youjie Zeng", "Jun Huang", "Ren Guo", "Si Cao", "Heng Yang", "Wen Ouyang"], "journal": "Frontiers in genetics", "year": 2023, "abstract": "Background: Idiopathic pulmonary fibrosis (IPF) is a fatal and irreversible interstitial lung disease. The specific mechanisms involved in the pathogenesis of IPF are not fully understood, while metabolic dysregulation has recently been demonstrated to contribute to IPF. This study aims to identify key metabolism-related genes involved in the progression of IPF, providing new insights into the pathogenesis of IPF. Methods: We downloaded four datasets (GSE32537, GSE110147, GSE150910, and GSE92592) from the Gene Expression Omnibus (GEO) database and identified differentially expressed metabolism-related genes (DEMRGs) in lung tissues of IPF by comprehensive analysis. Then, we performed GO, KEGG, and Reactome enrichment analyses of the DEMRGs. Subsequently, key DEMRGs were identified by machine-learning algorithms. Next, miRNAs regulating these key DEMRGs were predicted by integrating the GSE32538 (IPF miRNA dataset) and the miRWalk database. The Cytoscape software was used to visualize miRNA-mRNA regulatory networks. In addition, the relative levels of immune cells were assessed by the CIBERSORT algorithm, and the correlation of key DEMRGs with immune cells was calculated. Finally, the mRNA expression of the key DEMRGs was validated in two external independent datasets and an in vivo experiment. Results: A total of 101 DEMRGs (51 upregulated and 50 downregulated) were identified. Six key DEMRGs (ENPP3, ENTPD1, GPX3, PDE7B, PNMT, and POLR3H) were further identified using two machine-learning algorithms (LASSO and SVM-RFE). In the lung tissue of IPF patients, the expression levels of ENPP3, ENTPD1, and PDE7B were upregulated, and the expression levels of GPX3, PNMT, and POLR3H were downregulated. In addition, the miRNA-mRNA regulatory network of key DEMRGs was constructed. Then, the expression levels of key DEMRGs were validated in two independent external datasets (GSE53845 and GSE213001). Finally, we verified the key DEMRGs in the lung tissue of bleomycin-induced pulmonary fibrosis mice by qRT-PCR. Conclusion: Our study identified key metabolism-related genes that are differentially expressed in the lung tissue of IPF patients. Our study emphasizes the critical role of metabolic dysregulation in IPF, offers potential therapeutic targets, and provides new insights for future studies.", "claims": [{"id": "claim-method", "statement": "To identify the most critical DEMRGs, we used two machine-learning algorithms: least absolute shrinkage and selection operator (LASSO) regression and support vector machine recursive feature elimination (SVM-RFE).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36923791", "locator": "sections[7] \"2.5 Screening of IPF key DEMRGs\" paragraph 2", "quote": "To identify the most critical DEMRGs, we used two machine-learning algorithms: least absolute shrinkage and selection operator (LASSO) regression and support vector machine recursive feature elimination (SVM-RFE)."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Publicly available datasets were analyzed in this study. This data can be found here: Gene Expression Omnibus (GEO) database (https://www.ncbi.nlm.nih.gov/geo/; accession number: GSE32537, GSE110147, GSE150910, GSE92592, GSE32538, GSE53845, GSE213001).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36923791", "locator": "sections[23] \"Data availability statement\" paragraph 2", "quote": "Publicly available datasets were analyzed in this study. This data can be found here: Gene Expression Omnibus (GEO) database (https://www.ncbi.nlm.nih.gov/geo/; accession number: GSE32537, GSE110147, GSE150910, GSE92592, GSE32538, GSE53845, GSE213001)."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Six key DEMRGs (ENPP3, ENTPD1, GPX3, PDE7B, PNMT, and POLR3H) were further identified using two machine-learning algorithms (LASSO and SVM-RFE).", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:36923791", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "Six key DEMRGs (ENPP3, ENTPD1, GPX3, PDE7B, PNMT, and POLR3H) were further identified using two machine-learning algorithms (LASSO and SVM-RFE)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Six key DEMRGs (ENPP3, ENTPD1, GPX3, PDE7B, PNMT, and POLR3H) were further identified using two machine-learning algorithms (LASSO and SVM-RFE).", "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:36923791"], "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:GSE110147"], "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:GSE110147"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:36923791", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fgene.2023.1058582", "sha256": "sha256:c2d162615b8903ccba3c3aa29d8ced4db4ee209a0e46e33881d41d0eb69b1125", "bytes": 34766, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3389/fgene.2023.1058582", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC10010493", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE110147", "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=GSE110147", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE110147", "version": null, "note": "Publicly available datasets were analyzed in this study. This data can be found here: Gene Expression Omnibus (GEO) database (https://www.ncbi.nlm.nih.gov/geo/; accession number: GSE32537, GSE110147, GSE150910, GSE92592, GSE32538, GSE53845, GSE213001).", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "Publicly available datasets were analyzed in this study. 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This data can be found here: Gene Expression Omnibus (GEO) database (https://www.ncbi.nlm.nih.gov/geo/; accession number: GSE32537, GSE110147, GSE150910, GSE92592, GSE32538, GSE53845, GSE213001).", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "Publicly available datasets were analyzed in this study. 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This data can be found here: Gene Expression Omnibus (GEO) database (https://www.ncbi.nlm.nih.gov/geo/; accession number: GSE32537, GSE110147, GSE150910, GSE92592, GSE32538, GSE53845, GSE213001).", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM2433098", "GSM2433099", "GSM2433100", "GSM2433101", "GSM2433102", "GSM2433103", "GSM2433104", "GSM2433105", "GSM2433106", "GSM2433107", "GSM2433108", "GSM2433109", "GSM2433110", "GSM2433111", "GSM2433112", "GSM2433113", "GSM2433114", "GSM2433115", "GSM2433116", "GSM2433117", "GSM2433118", "GSM2433119", "GSM2433120", "GSM2433121", "GSM2433122", "GSM2433123", "GSM2433124", "GSM2433125", "GSM2433126", "GSM2433127", "GSM2433128", "GSM2433129", "GSM2433130", "GSM2433131", "GSM2433132", "GSM2433133", "GSM2433134", "GSM2433135", "GSM2433136"], "sample_count": 39, "group_sizes": null, "group_sizes_basis": null, "platform": "11154", "taxon": "Homo sapiens", "title": "mRNA Sequencing of Ideopathic Pulmonary Fibrosis (IPF) and Control Samples from the Lung Tissue Research Consortium (LTRC)", "resolution_checked_at": "2026-11-01T18:46:34Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}], "gaps": ["asset:data:geo:GSE110147 not downloaded", "asset:data:geo:GSE110147 licence not read", "asset:data:geo:GSE150910 not downloaded", "asset:data:geo:GSE150910 licence not read", "asset:data:geo:GSE213001 not downloaded", "asset:data:geo:GSE213001 licence not read", "asset:data:geo:GSE32537 not downloaded", "asset:data:geo:GSE32537 licence not read", "asset:data:geo:GSE32538 not downloaded", "asset:data:geo:GSE32538 licence not read", "asset:data:geo:GSE53845 not downloaded", "asset:data:geo:GSE53845 licence not read", "asset:data:geo:GSE92592 not downloaded", "asset:data:geo:GSE92592 licence not read"]}, "analysis": {"state": "complete", "methods": [{"id": "method-1", "family": "machine_learning", "specific": "support_vector_machine", "label": "Machine learning", "dsl_operations": ["train_classifier", "cross_validate", "roc_auc"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["labelled_feature_matrix"], "evidence": {"score": 1.0, "band": "verbatim", "quote": "To identify the most critical DEMRGs, we used two machine-learning algorithms: least absolute shrinkage and selection operator (LASSO) regression and support vector machine recursive feature elimination (SVM-RFE)."}}, {"id": "method-2", "family": "network_analysis", "specific": "pathway_enrichment", "label": "Network / pathway analysis", "dsl_operations": ["pathway_enrich"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["edge_list"], "evidence": {"score": 0.8, "band": "high", "quote": "pathway enrichment"}}], "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": ["train_classifier", "cross_validate", "roc_auc"], "missing_operations": [], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: support_vector_machine."}, "capability": {"tier": "R1", "capability_id": "capability:computational_analysis", "availability_state": "owned", "basis": "The computational analysis is owned. The physical bench the paper used is not, so a physical validation cannot be run here."}, "data": {"tier": "R1", "reachable": true, "accessions": ["GSE32537", "GSE110147", "GSE150910", "GSE92592", "GSE32538", "GSE53845", "GSE213001"], "resolved_accessions": ["GSE32537", "GSE110147", "GSE150910", "GSE92592", "GSE32538", "GSE53845", "GSE213001"], "statements": ["Publicly available datasets were analyzed in this study. This data can be found here: Gene Expression Omnibus (GEO) database (https://www.ncbi.nlm.nih.gov/geo/; accession number: GSE32537, GSE110147, GSE150910, GSE92592, GSE32538, GSE53845, GSE213001)."], "basis": "The paper names GSE32537, GSE110147, GSE150910, GSE92592, GSE32538, GSE53845, GSE213001 in Gene Expression Omnibus (GEO) and the accession resolves in the repository. No dataset was downloaded and no licence was read."}}, "can_run": {"dsl_operations": ["train_classifier", "cross_validate", "roc_auc"], "assets": ["source:pmid:36923791", "data:geo:GSE110147"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE110147"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-11-01T18:34:17Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": "verbatim"}, "calls": 5, "usage": {"prompt_tokens": 10486, "completion_tokens": 3684, "cached_tokens": 256}}, "human_critique": null, "stages": [{"id": "extraction", "state": "complete", "reader": "MiniMax-M3.1-Flash", "provider": "minimax"}], "gaps": ["review.independent_reader", "review.machine_critique", "review.human_critique"]}, "execution": {"state": "absent", "status": "not_run", "mode": null, "runs": [], "gaps": ["execution.not_run"]}, "provenance": {"entities": [{"id": "pmid:36923791", "type": "paper", "label": "pmid:36923791"}, {"id": "source:pmid:36923791", "type": "manuscript", "label": "PMID 36923791 full text"}, {"id": "data:geo:GSE110147", "type": "dataset", "label": "GEO GSE110147"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:36923791", "type": "paper", "label": "pmid:36923791"}, {"id": "source:pmid:36923791", "type": "manuscript", "label": "PMID 36923791 full text"}, {"id": "data:geo:GSE110147", "type": "dataset", "label": "GEO GSE110147"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-36923791", "type": "extraction", "used": ["source:pmid:36923791"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE110147", "type": "accession_resolution", "used": ["data:geo:GSE110147"], "agent": "agent:corpus-assay-engine"}], "agents": [{"id": "agent:corpus-assay-engine", "type": "software", "label": "Corpus assay engine"}, {"id": "agent:minimax-reader", "type": "software", "label": "MiniMax literature reader"}], "source_run_id": "reading-sci-2026-11-01", "dsl_catalogue_fingerprint": "343fb30756ba6ec3", "capability_table_fingerprint": "2cb3e42f047d2ecf", "snapshot_id": "ba34b49490d9bfaf"}, "lineage": {"parent_id": "pmid:36923791", "parent_hash": "sha256:8f954cfa13d68772607739689e7a9b467895884b1d6f72b02cc81b8c83b60464", "fork_of": null, "generation": 3}, "gaps": ["asset:data:geo:GSE110147 licence not read", "asset:data:geo:GSE110147 not downloaded", "asset:data:geo:GSE150910 licence not read", "asset:data:geo:GSE150910 not downloaded", "asset:data:geo:GSE213001 licence not read", "asset:data:geo:GSE213001 not downloaded", "asset:data:geo:GSE32537 licence not read", "asset:data:geo:GSE32537 not downloaded", "asset:data:geo:GSE32538 licence not read", "asset:data:geo:GSE32538 not downloaded", "asset:data:geo:GSE53845 licence not read", "asset:data:geo:GSE53845 not downloaded", "asset:data:geo:GSE92592 licence not read", "asset:data:geo:GSE92592 not downloaded", "execution.not_run", "review.human_critique", "review.independent_reader", "review.machine_critique"], "assays": [{"role": "data_generation", "definition_id": "animal_model", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["in two external independent datasets and an in vivo experiment. Results: A total of 101 DEMRGs (", "Laboratory Animal Co., Ltd. (Hunan, China). Mice were housed in pathogen-free conditions with a 12", "onary fibrosis model (Moeller et al., 2008). Mice were randomly divided into two groups: 1) Sham gr", "ne containing BLM (5 mg/kg). Before surgery, mice were anesthetized by intraperitoneal injection of"], "order_basis": "paper_text_order:1347", "id": "assay:1"}, {"role": "analysis", "definition_id": "machine_learning", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["train_classifier", "cross_validate", "roc_auc"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["To identify the most critical DEMRGs, we used two machine-learning algorithms: least absolute shrinkage and selection operator (LASSO) regression and support vector machine recursive feature elimination (SVM-RFE)."], "order_basis": "consumes_earlier_output", "id": "assay:2"}]}