Identification of key cuproptosis-related genes and their targets in patients with IgAN.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:36329405", "kind": "science-record", "revision": 4, "content_hash": "sha256:18ea5ff7b2f7f55b846fb86b7edc7534fc3a5337a96a752c588b8b21d8e23674", "created_at": "2026-11-01T18:15:45Z", "updated_at": "2026-11-01T22:08:00Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of key cuproptosis-related genes and their targets in patients with IgAN.", "doi": "10.1186/s12882-022-02991-5", "pmid": "36329405", "authors": ["Huagang Lin", "Deping Wu", "Jing Xiao"], "journal": "BMC nephrology", "year": 2022, "abstract": "BACKGROUND: IgA nephropathy (IgAN) is one of the most common forms of chronic glomerulonephritis, but the aetiology and pathogenesis remain unclear. Cuproptosis is a newly identified form of cell death that plays an important role in many diseases. Researchers have not clearly determined whether the expression of cuproptosis-related genes (CRGs) is involved in the pathogenesis of IgAN.\nMETHODS: The GSE93798, GSE50469 and GSE37460 datasets containing microarray data from patients with IgAN (63) and healthy controls (31) were downloaded from the GEO database. Immune cells and immune-related functions were analysed in patients with IgAN and controls, and genes were identified that may be related to cuproptosis. A logistic regression model was established according to the results, and then GO and KEGG enrichment analyses were performed. Finally, possible drugs were selected using the DSigDB database.\nRESULTS: The subjects in the different groups showed significantly different fractions of immune cells and immune-related functions, and 11 genes related to cuproptosis may be involved in these processes. Based on these 11 genes, the ROC curve was plotted, and the AUC value was calculated (0.898, 95% CI: 0.839-0.958). The result revealed good predictability. Then, genes with P &lt; 0.05 (lipoyltransferase 1, LIPT1) were selected to plot an ROC curve, and the AUC value was calculated (0.729, 95% CI: 0.636-0.821). Enrichment analyses showed that the TCA cycle and multiple metabolic pathways may also be involved in the occurrence of IgAN. Finally, 293 potential drugs that may be used to treat IgAN were identified based on these genes.\nCONCLUSION: In this study, we identified some novel CRGs that may be involved in IgAN, among which LIPT1 was significantly differentially expressed. It may predict the risk of IgAN and provides a possible target for the treatment of IgAN. Further experimental studies are needed to explore how these CRGs mediate the occurrence and development of IgAN.", "claims": [{"id": "claim-method", "statement": "A 95% confidence interval (CI) was evaluated by performing univariable and multivariate logistic regression analyses.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36329405", "locator": "sections[9] \"Statistical analysis\" paragraph 2", "quote": "A 95% confidence interval (CI) was evaluated by performing univariable and multivariate logistic regression analyses."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Publicly available datasets were analyzed in this study. These data can be found here: https://www.ncbi.nlm.nih.gov/geo/, GSE93798, GSE50469 and GSE37460.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36329405", "locator": "sections[23] \"Availability of data and materials\" paragraph 2", "quote": "Publicly available datasets were analyzed in this study. These data can be found here: https://www.ncbi.nlm.nih.gov/geo/, GSE93798, GSE50469 and GSE37460."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The 11-gene logistic regression model showed good predictive ability for IgAN, with an AUC of 0.898, while LIPT1 alone had an AUC of 0.729.", "kind": "quantitative", "target": {"value": 95.0, "unit": "per cent", "tolerance": null, "source": "Based on these 11 genes, the ROC curve was plotted, and the AUC value was calculated (0.898, 95% CI: 0.839–0.958). The result revealed good predictability."}, "evidence": [{"asset": "source:pmid:36329405", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "Based on these 11 genes, the ROC curve was plotted, and the AUC value was calculated (0.898, 95% CI: 0.839–0.958). The result revealed good predictability."}, {"asset": "source:pmid:36329405", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "Then, genes with P < 0.05 (lipoyltransferase 1, LIPT1) were selected to plot an ROC curve, and the AUC value was calculated (0.729, 95% CI: 0.636–0.821)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The 11-gene logistic regression model showed good predictive ability for IgAN, with an AUC of 0.898, while LIPT1 alone had an AUC of 0.729.", "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:36329405"], "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:GSE37460"], "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:GSE37460"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:36329405", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1186/s12882-022-02991-5", "sha256": "sha256:e50af0c9b8d2a39e11173a67a59ddd17d8897a2b48341d30f46385a944df1cd5", "bytes": 31787, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1186/s12882-022-02991-5", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC9635123", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE37460", "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=GSE37460", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE37460", "version": null, "note": "Publicly available datasets were analyzed in this study. 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