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pmid:38571583

Identification and validation of mutual hub genes in idiopathic pulmonary fibrosis and rheumatoid arthritis-associated usual interstitial pneumonia.

Liangyu Chen · Haobo Lin · Linmang Qin · Guangfeng Zhang · Donghui Huang · Peisheng Chen · Xiao Zhang

Heliyon · 2024 doi:10.1016/j.heliyon.2024.e28088

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Experiment

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title
Identification and validation of mutual hub genes in idiopathic pulmonary fibrosis and rheumatoid arthritis-associated usual interstitial pneumonia.
doi
10.1016/j.heliyon.2024.e28088
pmid
38571583
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Liangyu Chen
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Haobo Lin
[2]
Linmang Qin
[3]
Guangfeng Zhang
[4]
Donghui Huang
[5]
Peisheng Chen
[6]
Xiao Zhang
journal
Heliyon
year
2024
abstract
Objectives: The study aims at exploring common hub genes and pathways in idiopathic pulmonary fibrosis (IPF) and rheumatoid arthritis-associated usual interstitial pneumonia (RA-UIP) through integrated bioinformatics analyses. Methods: The GSE199152 dataset containing lung tissue samples from IPF and RA-UIP patients was acquired from the Gene Expression Omnibus (GEO) database. The identification of overlapping differentially expressed genes (DEGs) in IPF and RA-UIP was carried out through R language. Protein-protein interaction (PPI) network analysis and module analysis were applied to filter mutual hub genes in the two diseases. Enrichment analyses were also conducted to analyze the possible biological functions and pathways of the overlapped DEGs and hub genes. The diagnostic value of key genes was assessed with R language, and the expressions of these genes in pulmonary cells of IPF and rheumatoid arthritis-associated interstitial lung disease (RA-ILD) patients were analyzed with single cell RNA-sequencing (scRNA-seq) datasets. The expression levels of hub genes were validated in blood samples from patients, specimens of human lung fibroblasts, lung tissue samples from mice, as well as external GEO datasets. Results: Four common hub genes (THBS2, TIMP1, POSTN, and CD19) were screened. Enrichment analyses showed that the abnormal expressions of DEGs and hub genes may be connected with the onset of IPF and RA-UIP by regulating the progression of fibrosis. ScRNA-seq analyses illustrated that for both IPF and RA-ILD patients, THBS2, TIMP1, and POSTN were mainly expressed in lung fibroblasts, while CD19 was uniquely high-expressed in B cells. The qRT-PCR and immunohistochemistry (IHC) results verified that the expression levels of hub genes were mostly in accordance with the findings obtained from the bioinformatics analyses. Conclusion: Though IPF and RA-UIP are distinct diseases, they may to some extent have mutual pathogenesis in the development of fibrosis. THBS2, TIMP1, POSTN, and CD19 may be the potential biomarkers of IPF and RA-UIP, and intervention on related pathways of these genes could offer new strategies for the precision treatment of IPF and RA-UIP.
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Applying the "pROC" R package, a method for visualizing and analyzing the diagnostic performance through receiver operating characteristic (ROC) curves [22], the ROC analysis was executed to assess the ability of core genes to differentiate IPF or RA-UIP samples from normal samples.
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sections[8] "Diagnostic value of hub genes" paragraph 2
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Applying the "pROC" R package, a method for visualizing and analyzing the diagnostic performance through receiver operating characteristic (ROC) curves [22], the ROC analysis was executed to assess the ability of core genes to differentiate IPF or RA-UIP samples from normal samples.
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The datasets analyzed during the current study are available in the GEO database (https://www.ncbi.nlm.nih.gov/geo/). These accession numbers for the datasets are GSE199152, GSE213017, GSE180139, GSE150910, and GSE89408. Any additional information required to reanalyze the data are available from the corresponding author on request.
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The datasets analyzed during the current study are available in the GEO database (https://www.ncbi.nlm.nih.gov/geo/). These accession numbers for the datasets are GSE199152, GSE213017, GSE180139, GSE150910, and GSE89408. Any additional information required to reanalyze the data are available from the corresponding author on request.
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The AUC values of THBS2, TIMP1, POSTN, and CD19 in predicting the diagnostic value of IPF were 0.921 (95% confidence interval (CI), 0.816–1.000), 0.836 (95% CI, 0.658–1.000), 0.929 (95% CI, 0.829–1.000), and 0.779 (95% CI, 0.504–1.000).
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The AUC values of THBS2, TIMP1, POSTN, and CD19 in predicting the diagnostic value of IPF were 0.921 (95% confidence interval (CI), 0.816–1.000), 0.836 (95% CI, 0.658–1.000), 0.929 (95% CI, 0.829–1.000), and 0.779 (95% CI, 0.504–1.000).
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The AUC values of THBS2, TIMP1, POSTN, and CD19 in predicting the diagnostic value of IPF were 0.921 (95% confidence interval (CI), 0.816–1.000), 0.836 (95% CI, 0.658–1.000), 0.929 (95% CI, 0.829–1.000), and 0.779 (95% CI, 0.504–1.000).
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The AUC values of THBS2, TIMP1, POSTN, and CD19 in predicting the diagnostic value of IPF were 0.921 (95% confidence interval (CI), 0.816–1.000), 0.836 (95% CI, 0.658–1.000), 0.929 (95% CI, 0.829–1.000), and 0.779 (95% CI, 0.504–1.000).
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{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:38571583", "kind": "science-record", "revision": 4, "content_hash": "sha256:b7bd890ebae0373dc007437ac00d0644400ea3a4539cfd9333a7ee06890b5513", "created_at": "2026-11-01T19:20:32Z", "updated_at": "2026-11-01T22:11:36Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification and validation of mutual hub genes in idiopathic pulmonary fibrosis and rheumatoid arthritis-associated usual interstitial pneumonia.", "doi": "10.1016/j.heliyon.2024.e28088", "pmid": "38571583", "authors": ["Liangyu Chen", "Haobo Lin", "Linmang Qin", "Guangfeng Zhang", "Donghui Huang", "Peisheng Chen", "Xiao Zhang"], "journal": "Heliyon", "year": 2024, "abstract": "Objectives: The study aims at exploring common hub genes and pathways in idiopathic pulmonary fibrosis (IPF) and rheumatoid arthritis-associated usual interstitial pneumonia (RA-UIP) through integrated bioinformatics analyses.\nMethods: The GSE199152 dataset containing lung tissue samples from IPF and RA-UIP patients was acquired from the Gene Expression Omnibus (GEO) database. The identification of overlapping differentially expressed genes (DEGs) in IPF and RA-UIP was carried out through R language. Protein-protein interaction (PPI) network analysis and module analysis were applied to filter mutual hub genes in the two diseases. Enrichment analyses were also conducted to analyze the possible biological functions and pathways of the overlapped DEGs and hub genes. The diagnostic value of key genes was assessed with R language, and the expressions of these genes in pulmonary cells of IPF and rheumatoid arthritis-associated interstitial lung disease (RA-ILD) patients were analyzed with single cell RNA-sequencing (scRNA-seq) datasets. The expression levels of hub genes were validated in blood samples from patients, specimens of human lung fibroblasts, lung tissue samples from mice, as well as external GEO datasets.\nResults: Four common hub genes (THBS2, TIMP1, POSTN, and CD19) were screened. Enrichment analyses showed that the abnormal expressions of DEGs and hub genes may be connected with the onset of IPF and RA-UIP by regulating the progression of fibrosis. ScRNA-seq analyses illustrated that for both IPF and RA-ILD patients, THBS2, TIMP1, and POSTN were mainly expressed in lung fibroblasts, while CD19 was uniquely high-expressed in B cells. The qRT-PCR and immunohistochemistry (IHC) results verified that the expression levels of hub genes were mostly in accordance with the findings obtained from the bioinformatics analyses.\nConclusion: Though IPF and RA-UIP are distinct diseases, they may to some extent have mutual pathogenesis in the development of fibrosis. THBS2, TIMP1, POSTN, and CD19 may be the potential biomarkers of IPF and RA-UIP, and intervention on related pathways of these genes could offer new strategies for the precision treatment of IPF and RA-UIP.", "claims": [{"id": "claim-method", "statement": "Applying the \"pROC\" R package, a method for visualizing and analyzing the diagnostic performance through receiver operating characteristic (ROC) curves [22], the ROC analysis was executed to assess the ability of core genes to differentiate IPF or RA-UIP samples from normal samples.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38571583", "locator": "sections[8] \"Diagnostic value of hub genes\" paragraph 2", "quote": "Applying the \"pROC\" R package, a method for visualizing and analyzing the diagnostic performance through receiver operating characteristic (ROC) curves [22], the ROC analysis was executed to assess the ability of core genes to differentiate IPF or RA-UIP samples from normal samples."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets analyzed during the current study are available in the GEO database (https://www.ncbi.nlm.nih.gov/geo/). These accession numbers for the datasets are GSE199152, GSE213017, GSE180139, GSE150910, and GSE89408. Any additional information required to reanalyze the data are available from the corresponding author on request.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38571583", "locator": "sections[25] \"Data availability statement\" paragraph 2", "quote": "The datasets analyzed during the current study are available in the GEO database (https://www.ncbi.nlm.nih.gov/geo/). These accession numbers for the datasets are GSE199152, GSE213017, GSE180139, GSE150910, and GSE89408. Any additional information required to reanalyze the data are available from the corresponding author on request."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The AUC values of THBS2, TIMP1, POSTN, and CD19 in predicting the diagnostic value of IPF were 0.921 (95% confidence interval (CI), 0.816–1.000), 0.836 (95% CI, 0.658–1.000), 0.929 (95% CI, 0.829–1.000), and 0.779 (95% CI, 0.504–1.000).", "kind": "quantitative", "target": {"value": 95.0, "unit": "per cent", "tolerance": null, "source": "The AUC values of THBS2, TIMP1, POSTN, and CD19 in predicting the diagnostic value of IPF were 0.921 (95% confidence interval (CI), 0.816–1.000), 0.836 (95% CI, 0.658–1.000), 0.929 (95% CI, 0.829–1.000), and 0.779 (95% CI, 0.504–1.000)."}, "evidence": [{"asset": "source:pmid:38571583", "locator": "sections[19] \"Diagnostic evaluation of hub genes\" paragraph 2", "quote": "The AUC values of THBS2, TIMP1, POSTN, and CD19 in predicting the diagnostic value of IPF were 0.921 (95% confidence interval (CI), 0.816–1.000), 0.836 (95% CI, 0.658–1.000), 0.929 (95% CI, 0.829–1.000), and 0.779 (95% CI, 0.504–1.000)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The AUC values of THBS2, TIMP1, POSTN, and CD19 in predicting the diagnostic value of IPF were 0.921 (95% confidence interval (CI), 0.816–1.000), 0.836 (95% CI, 0.658–1.000), 0.929 (95% CI, 0.829–1.000), and 0.779 (95% CI, 0.504–1.000).", "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:38571583"], "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:GSE199152"], "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:GSE199152"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:38571583", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1016/j.heliyon.2024.e28088", "sha256": "sha256:21606c0bf8cce2466e8c715193efddaf5182365f3860020180c8d600f07335cc", "bytes": 54633, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1016/j.heliyon.2024.e28088", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC10987927", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE199152", "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=GSE199152", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE199152", "version": null, "note": "The datasets analyzed during the current study are available in the GEO database (https://www.ncbi.nlm.nih.gov/geo/). These accession numbers for the datasets are GSE199152, GSE213017, GSE180139, GSE150910, and GSE89408. Any additional information required to reanalyze the data are available from the corresponding author on request.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The datasets analyzed during the current study are available in the GEO database (https://www.ncbi.nlm.nih.gov/geo/). These accession numbers for the datasets are GSE199152, GSE213017, GSE180139, GSE150910, and GSE89408. 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No tolerance is published because the paper states none."}], "gaps": ["method.reader_named_unmapped"]}, "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": ["group_summary", "welch_t", "bootstrap_mean_difference", "group_comparison_anova"], "missing_operations": [], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: anova."}, "capability": {"tier": "R1", "capability_id": "capability:computational_analysis", "availability_state": "owned", "basis": "The computational analysis is owned. 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The expression levels", "aterials and methods Analysis of single cell RNA-sequencing (scRNA-seq) data To further comprehend the r", "for they respectively contained single cell RNA-sequencing data of pulmonary cells of an IPF patient an"], "order_basis": "paper_text_order:1114", "id": "assay:1"}, {"role": "data_generation", "definition_id": "scrna_seq", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "unsupported", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["re analyzed with single cell RNA-sequencing (scRNA-seq) datasets. The expression levels of hub gene", "P by regulating the progression of fibrosis. ScRNA-seq analyses illustrated that for both IPF and R", "hods Analysis of single cell RNA-sequencing (scRNA-seq) data To further comprehend the roles of hub", "lls in IPF and RA-UIP patients, we performed scRNA-seq analyses on datasets GSE213017 and GSE180139"], "order_basis": "paper_text_order:1130", "id": "assay:2"}, {"role": "data_generation", "definition_id": "ihc", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["y high-expressed in B cells. The qRT-PCR and immunohistochemistry (IHC) results verified that the expression l", "cells. The qRT-PCR and immunohistochemistry (IHC) results verified that the expression levels"], "order_basis": "paper_text_order:1789", "id": "assay:3"}, {"role": "analysis", "definition_id": "group_comparison", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["group_summary", "welch_t", "bootstrap_mean_difference", "group_comparison_anova"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 0.8, "evidence": ["Analysis of Variance"], "order_basis": "consumes_earlier_output", "id": "assay:4"}]}