Identification and validation of key biomarkers for the early diagnosis of diabetic kidney disease.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:36071835", "kind": "science-record", "revision": 5, "content_hash": "sha256:3473540af1196e2a375850f06dbb6c7d75149fcecc25e9e144a2aa331371c29a", "created_at": "2026-11-01T18:15:17Z", "updated_at": "2026-11-01T22:50:00Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification and validation of key biomarkers for the early diagnosis of diabetic kidney disease.", "doi": "10.3389/fphar.2022.931282", "pmid": "36071835", "authors": ["Wei Yu", "Ting Wang", "Feng Wu", "Yiding Zhang", "Jin Shang", "Zhanzheng Zhao"], "journal": "Frontiers in pharmacology", "year": 2022, "abstract": "Background: Diabetic kidney disease (DKD) is the leading cause of end-stage renal disease. This study explored the core genes and pathways associated with DKD to identify potential diagnostic and therapeutic targets. Methods: We downloaded microarray datasets GSE96804 and GSE104948 from the Gene Expression Omnibus (GEO) database. The dataset includes a total of 53 DKD samples and 41 normal samples. Differentially expressed genes (DEGs) were identified using the R package \"limma\". The Metascape database was subjected to Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses to identify the pathway and functional annotations of DEGs. A WGCAN network was constructed, the hub genes in the turquoise module were screened, and the core genes were selected using LASSO regression to construct a diagnostic model that was then validated in an independent dataset. The core genes were verified by in vitro and in vivo experiments. Results: A total of 430 DEGs were identified in the GSE96804 dataset, including 285 upregulated and 145 downregulated DEGs. WGCNA screened out 128 modeled candidate gene sets. A total of eight genes characteristic of DKD were identified by LASSO regression to build a prediction model. The results showed accuracies of 99.15% in the training set (GSE96804) and 94.44% and 100%, respectively, in the test (GSE104948-GPL22945 and GSE104948-GPL24120). Three core genes (OAS1, SECTM1, and SNW1) with high connectivity were selected among the modeled genes. In vitro and in vivo experiments confirmed the upregulation of these genes. Conclusion: Bioinformatics analysis combined with experimental validation identified three novel DKD-specific genes. These findings may advance our understanding of the molecular basis of DKD and provide potential therapeutic targets for its clinical management.", "claims": [{"id": "claim-method", "statement": "Differentially expressed genes (DEGs) were identified using the R package “limma”.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36071835", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "Differentially expressed genes (DEGs) were identified using the R package “limma”."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/Supplementary Material.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36071835", "locator": "sections[28] \"Data availability statement\" paragraph 2", "quote": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/Supplementary Material."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Limma-based differential-expression analysis of GSE96804 identified 430 differentially expressed genes, including 285 upregulated and 145 downregulated genes.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:36071835", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "A total of 430 DEGs were identified in the GSE96804 dataset, including 285 upregulated and 145 downregulated DEGs."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Limma-based differential-expression analysis of GSE96804 identified 430 differentially expressed genes, including 285 upregulated and 145 downregulated genes.", "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:36071835"], "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:GSE104948"], "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:GSE104948"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:36071835", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fphar.2022.931282", "sha256": "sha256:c2597ffd3cd0aed0a544b9f35f0c72a2d3c9794f2210fd0173e8c88507809dbd", "bytes": 37334, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3389/fphar.2022.931282", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC9441656", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE104948", "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=GSE104948", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE104948", "version": null, "note": "The datasets presented in this study can be found in online repositories. 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Results: A total of 430 DEGs we", "lected among the modeled genes. In vitro and in vivo experiments confirmed the upregulation of th", "five mice. The grouping was randomized. The mouse model of diabetes was induced by intraperitoneal i", "4.5) for five consecutive days (n = 5). All mice were euthanized at the 20th week, the fasting blo"], "order_basis": "paper_text_order:1017", "id": "assay:1"}, {"role": "data_generation", "definition_id": "cell_culture", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["American Type Culture Collection. Cells were cultured in DMEM medium (Gibco) containing 10% fetal bov", "o) at 37°C in a 5% CO2 atmosphere. 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