Exploring the pathogenesis of diabetic kidney disease by microarray data analysis.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:36059966", "kind": "science-record", "revision": 5, "content_hash": "sha256:261e69f0212d18e0e52521180231446c907784561c4a8f09a511ec36110dcdba", "created_at": "2026-11-01T18:15:15Z", "updated_at": "2026-11-01T22:49:59Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Exploring the pathogenesis of diabetic kidney disease by microarray data analysis.", "doi": "10.3389/fphar.2022.932205", "pmid": "36059966", "authors": ["Haiyan Cao", "Xiaosheng Rao", "Junya Jia", "Tiekun Yan", "Dong Li"], "journal": "Frontiers in pharmacology", "year": 2022, "abstract": "Diabetic kidney disease (DKD) is a major complication of diabetes mellitus, and the leading contributor of end-stage renal disease. Hence, insights into the molecular pathogenesis of DKD are urgently needed. The purpose of this article is to reveal the molecular mechanisms underlying the pathogenesis of DKD. The microarray datasets of GSE30528 and GSE30529 were downloaded from the NCBI Gene Expression Omnibus (GEO) database to identify the common differentially expressed genes (DEGs) between the glomerular DKD (GDKD) and tubular DKD (TDKD), respectively. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed to analyze the function and pathways of the common DEGs. After constructing the protein-protein interaction (PPI) network and subnetwork analysis, three types of analyses were performed, namely, identification of hub genes, analysis of the coexpressed network, and exploration of transcription factors (TFs). Totally, 348 and 463 DEGs were identified in GDKD and TDKD, respectively. Then, 66 common DEGs (63 upregulated DEGs and three downregulated DEGs) were obtained in DKD patients. GO and KEGG pathway analyses revealed the importance of inflammation response, immune-related pathways, and extracellular matrix-related pathways, especially chemokines and cytokines, in DKD. Fifteen hub genes from the 66 common DEGs, namely, IL10RA, IRF8, LY86, C1QA, C1QB, CD53, CD1C, CTSS, CCR2, CD163, CCL5, CD48, RNASE6, CD52, and CD2 were identified. In summary, through the microarray data analysis, the common functions and hub genes greatly contribute to the elucidation of the molecular pathogenesis associated with DKD.", "claims": [{"id": "claim-method", "statement": "Based on the GEOquery package and Limma package of R software, GEO2R enables the users to analyze and visualize the DEGs (Diboun et al., 2006).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36059966", "locator": "sections[4] \"Identification of differentially expressed genes\" paragraph 2", "quote": "Based on the GEOquery package and Limma package of R software, GEO2R enables the users to analyze and visualize the DEGs (Diboun et al., 2006)."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets presented in this study can be found in online repositories. 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No dataset was downloaded and no licence was read."}}, "can_run": {"dsl_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "assets": ["source:pmid:36059966", "data:geo:GSE30122"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE30122"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-11-01T18:03:25Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": "verbatim"}, "calls": 5, "usage": {"prompt_tokens": 15332, "completion_tokens": 1684, "cached_tokens": 264}}, "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:36059966", "type": "paper", "label": "pmid:36059966"}, {"id": "source:pmid:36059966", "type": "manuscript", "label": "PMID 36059966 full text"}, {"id": "data:geo:GSE30122", "type": "dataset", "label": "GEO GSE30122"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:36059966", "type": "paper", "label": "pmid:36059966"}, {"id": "source:pmid:36059966", "type": "manuscript", "label": "PMID 36059966 full text"}, {"id": "data:geo:GSE30122", "type": "dataset", "label": "GEO GSE30122"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-36059966", "type": "extraction", "used": ["source:pmid:36059966"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE30122", "type": "accession_resolution", "used": ["data:geo:GSE30122"], "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:36059966", "parent_hash": "sha256:59c668c9055754bf398a534501565260e920dd3642faf761c96b3a7f6828e9b9", "fork_of": null, "generation": 4}, "gaps": ["asset:data:geo:GSE30122 licence not read", "asset:data:geo:GSE30122 not downloaded", "asset:data:geo:GSE30528 licence not read", "asset:data:geo:GSE30528 not downloaded", "asset:data:geo:GSE30529 licence not read", "asset:data:geo:GSE30529 not downloaded", "asset:data:geo:GSE47183 licence not read", "asset:data:geo:GSE47183 not downloaded", "asset:data:geo:GSE47184 licence not read", "asset:data:geo:GSE47184 not downloaded", "execution.not_run", "review.human_critique", "review.independent_reader", "review.machine_critique"], "assays": [{"role": "data_generation", "definition_id": "microarray", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["e pathogenesis of diabetic kidney disease by microarray data analysis.", "isms underlying the pathogenesis of DKD. The microarray datasets of GSE30528 and GSE30529 were downl", "CD2 were identified. In summary, through the microarray data analysis, the common functions and hub"], "order_basis": "paper_text_order:12", "id": "assay:1"}, {"role": "analysis", "definition_id": "differential_expression", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["Based on the GEOquery package and Limma package of R software, GEO2R enables the users to analyze and visualize the DEGs (Diboun et al., 2006)."], "order_basis": "consumes_earlier_output", "id": "assay:2"}]}