Mechanism of ferroptosis in hypertensive nephropathy.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35693711", "kind": "science-record", "revision": 5, "content_hash": "sha256:8bc1935545b8b3dc05893b178f4954b8415041de092006788e6375e7976ac90c", "created_at": "2026-11-01T18:14:39Z", "updated_at": "2026-11-01T22:49:17Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Mechanism of ferroptosis in hypertensive nephropathy.", "doi": "10.21037/tau-22-276", "pmid": "35693711", "authors": ["Yongzhi Chen", "Kun Wang", "Jie Yang", "Aixia Zhang", "Xiayun Dong", "Zhaocheng Zhou", "Tianshu Li", "Ruixia Fan"], "journal": "Translational andrology and urology", "year": 2022, "abstract": "Background: In recent years, it has been demonstrated that ferroptosis can be involved in a variety of kidney injury processes, but the role played by ferroptosis in hypertensive kidney injury is still unclear. The aim was to explore the mechanism of ferroptosis playing a role in hypertensive kidney disease and related signalling pathways.\nMethods: GSE37455 microarray data was downloaded from the Gene Expression Omnibus (GEO) database and preprocessed. Batch correction and differential analysis were performed on the normal population and the hypertensive nephropathy samples using the \"sva\" and \"limma\" packages in R software. Ferroptosis-related genes were obtained from the FerrDb database and normalized and processed using UniProt. Ferroptosis-related differentially expressed genes were obtained using Venny 2.1. and imported into the Search Tool for the Retrieval of Interacting Genes (STRING) to obtain protein-protein interactions (PPIs). The data were imported into Cytoscape 3.7.2 for processing to identify the core differential genes of ferroptosis based on nodes. Gene set enrichment analysis (GSEA) was performed on the core differential genes of ferroptosis to infer the pathway of ferroptosis action in hypertensive nephropathy.\nResults: The R software processing yielded 37 differential genes, including 13 upregulated genes and 24 downregulated genes. 202 ferroptosis-related genes were obtained by screening, and 3 ferroptosis-related differentially expressed genes were obtained after taking the intersection. The ferroptosis-related core differentially expressed gene albumin (ALB) was obtained by PPI network analysis and Cytoscape processing. GSEA analysis revealed that ferroptosis may act in hypertensive nephropathy through pathways such as drug metabolism-cytochrome P450, branched-chain amino acid (BCAA) metabolism, retinol metabolism, and biological processes (BPs) such as organic and amino acid metabolism and humoral immunity.\nConclusions: Ferroptosis may act in the development of hypertensive nephropathy through pathways such as BCAA metabolism and retinol metabolism and BPs such as organic and amino acid metabolism and humoral immunity.", "claims": [{"id": "claim-method", "statement": "All genes were analyzed by classical Bayesian analysis with the support of the R “limma” package to obtain the corresponding P and logFC values and the Benjamini-Hochberg (BH) adjusted P values.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35693711", "locator": "sections[4] \"Analysis of variances\" paragraph 2", "quote": "All genes were analyzed by classical Bayesian analysis with the support of the R “limma” package to obtain the corresponding P and logFC values and the Benjamini-Hochberg (BH) adjusted P values."}], "state": "complete"}, {"id": "claim-data-access", "statement": "GSE37455 microarray data were downloaded from the publicly available Gene Expression Omnibus (GEO) database (http://www.ncbi.nlm.nih.gov/geo/), along with data from the GPL11670 platform (18 normal population samples and 0 hypertensive nephropathy samples) and the GPL14663 platform (3 normal population samples and 20 hypertensive nephropathy samples).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35693711", "locator": "sections[3] \"Data collection and preprocessing\" paragraph 2", "quote": "GSE37455 microarray data were downloaded from the publicly available Gene Expression Omnibus (GEO) database (http://www.ncbi.nlm.nih.gov/geo/), along with data from the GPL11670 platform (18 normal population samples and 0 hypertensive nephropathy samples) and the GPL14663 platform (3 normal population samples and 20 hypertensive nephropathy samples)."}], "state": "complete"}, {"id": "claim-target-result", "statement": "A correlation analysis was performed with the R “limma” package, and 37 genes were obtained, including 13 upregulated genes and 24 downregulated genes.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:35693711", "locator": "sections[10] \"Results of differentially expressed gene acquisition\" paragraph 2", "quote": "A correlation analysis was performed with the R “limma” package, and 37 genes were obtained, including 13 upregulated genes and 24 downregulated genes."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "A correlation analysis was performed with the R “limma” package, and 37 genes were obtained, including 13 upregulated genes and 24 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:35693711"], "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. 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