Deciphering the molecular regulatory of RAB32/GPRC5A axis in chronic obstructive pulmonary disease.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:38448858", "kind": "science-record", "revision": 3, "content_hash": "sha256:a298e04c6f684513b16aeeae7e5d982fe55a619d65aa12bd332ce101bdfc5ed5", "created_at": "2026-11-01T19:20:23Z", "updated_at": "2026-11-01T21:32:38Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Deciphering the molecular regulatory of RAB32/GPRC5A axis in chronic obstructive pulmonary disease.", "doi": "10.1186/s12931-024-02724-2", "pmid": "38448858", "authors": ["Yixing Wu", "Binfeng He", "Jianlan Hua", "Weiping Hu", "Yaopin Han", "Jing Zhang"], "journal": "Respiratory research", "year": 2024, "abstract": "BACKGROUND: Chronic obstructive pulmonary disease (COPD) is a significant public health problem characterized by persistent airflow limitation. Despite previous research into the pathogenesis of COPD, a comprehensive understanding of the cell-type-specific mechanisms in COPD remains lacking. Recent studies have implicated Rab GTPases in regulating chronic immune response and inflammation via multiple pathways. In this study, the molecular regulating mechanism of RAB32 in COPD was investigated by multiple bioinformatics mining and experimental verification.\nMETHODS: We collected lung tissue surgical specimens from Zhongshan Hospital, Fudan University, and RT-qPCR and western blotting were used to detect the expression of Rabs in COPD lung tissues. Four COPD microarray datasets from the Gene Expression Omnibus (GEO) were analyzed. COPD-related epithelial cell scRNA-seq data was obtained from the GSE173896 dataset. Weighted gene co-expression network analysis (WGCNA), mfuzz cluster, and Spearman correlation analysis were combined to obtain the regulatory network of RAB32 in COPD. The slingshot algorithm was used to identify the regulatory molecule, and the co-localization of RAB32 and GPRC5A was observed with immunofluorescence.\nRESULTS: WGCNA identified 771 key module genes significantly associated with the occurrence of COPD, including five Rab genes. RAB32 was up-regulated in lung tissues from subjects with COPD as contrast to those without COPD on both mRNA and protein levels. Integrating the results of WGCNA, Mfuzz clusters, and Spearman analysis, nine potential interacting genes with RAB32 were identified. Among these genes, GPRC5A exhibited a similar molecular expression pattern to RAB32. Co-expression density analysis at the cell level demonstrated that the co-expression density of RAB32 and GPRC5A was higher in type I alveolar epithelial cells (AT1s) than in type II alveolar epithelial cells (AT2s). The immunofluorescence also confirmed the co-localization of RAB32 and GPRC5A, and the Pearson correlation analysis found the relationship between RAB32 and GPRC5A was significantly stronger in the COPD lungs (r = 0.65) compared to the non-COPD lungs (r = 0.33).\nCONCLUSIONS: Our study marked endeavor to delineate the molecular regulatory axis of RAB32 in COPD by employing diverse methods and identifying GPRC5A as a potential interacting molecule with RAB32. These findings offered novel perspectives on the mechanism of COPD.", "claims": [{"id": "claim-method", "statement": "We used the WGCNA package [26] to perform weighted gene co-expression network analysis to identify genes associated with COPD development.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38448858", "locator": "sections[9] \"Weighted gene co-expression network construction\" paragraph 2", "quote": "We used the WGCNA package [26] to perform weighted gene co-expression network analysis to identify genes associated with COPD development."}], "state": "complete"}, {"id": "claim-data-access", "statement": "All the data utilized for analysis and processing was described in the method section. On reasonable request, the corresponding author will provide the data and code supporting the conclusions of this work.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38448858", "locator": "sections[30] \"Data availability\" paragraph 2", "quote": "All the data utilized for analysis and processing was described in the method section. On reasonable request, the corresponding author will provide the data and code supporting the conclusions of this work."}], "state": "complete"}, {"id": "claim-target-result", "statement": "RAB32 was up-regulated in lung tissues from subjects with COPD as contrast to those without COPD on both mRNA and protein levels.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:38448858", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "RAB32 was up-regulated in lung tissues from subjects with COPD as contrast to those without COPD on both mRNA and protein levels."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "RAB32 was up-regulated in lung tissues from subjects with COPD as contrast to those without COPD on both mRNA and protein levels.", "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:38448858"], "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:GSE10006"], "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:GSE10006"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:38448858", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1186/s12931-024-02724-2", "sha256": "sha256:6057e16cb3eee4ee7be6b334e65801cbc5cd14cbbca5e497b63f2795cb991991", "bytes": 52434, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1186/s12931-024-02724-2", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC10919015", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE10006", "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=GSE10006", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE10006", "version": null, "note": "All the data utilized for analysis and processing was described in the method section. 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