Identification of Ferroptosis-Related Genes in Alzheimer's Disease Based on Bioinformatic Analysis.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35197821", "kind": "science-record", "revision": 5, "content_hash": "sha256:b3b467613a98a2ad992def105af5b0d04753eeb5a6685e7290ab507cdb899448", "created_at": "2026-11-01T17:36:57Z", "updated_at": "2026-11-01T22:05:57Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of Ferroptosis-Related Genes in Alzheimer's Disease Based on Bioinformatic Analysis.", "doi": "10.3389/fnins.2022.823741", "pmid": "35197821", "authors": ["Ying Wang", "Guohua Chen", "Wei Shao"], "journal": "Frontiers in neuroscience", "year": 2022, "abstract": "INTRODUCTION: Alzheimer's disease (AD) is the most prevalent cause of dementia, and emerging evidence suggests that ferroptosis is involved in the pathological process of AD.\nMATERIALS AND METHODS: Three microarray datasets (GSE122063, GSE37263, and GSE140829) about AD were collected from the GEO database. AD-related module genes were identified through a weighted gene co-expression network analysis (WGCNA). The ferroptosis-related genes were extracted from FerrDb. The apoptosis-related genes were downloaded from UniProt as a control to show the specificity of ferroptosis. The overlap was performed to obtain the module genes associated with ferroptosis and apoptosis. Then the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses and the protein-protein interaction (PPI) were conducted. Cytoscape with CytoHubba was used to identify the hub genes, and the Logistic regression was performed to distinguish the AD patients from controls.\nRESULTS: 53 ferroptosis-related module genes were obtained. The GO analysis revealed that response to oxidative stress and starvation, and multicellular organismal homeostasis were the most highly enriched terms. The KEGG analysis showed that these overlapped genes were enriched not only in renal cell carcinoma pathways and central carbon metabolism in cancer, but also in autophagy-related pathways and ferroptosis. Ferroptosis-related hub genes in AD (JUN, SLC2A1, TFRC, ALB, and NFE2L2) were finally identified, which could distinguish AD patients from controls (P < 0.05). The area under the ROC curve (AUC) was 0.643. Apoptosis-related hub genes in AD (STAT1, MCL1, and BCL2L11) were also identified and also could distinguish AD patients from controls (P < 0.05). The AUC was 0.608, which was less than the former AUC value, suggesting that ferroptosis was more special than apoptosis in AD.\nCONCLUSION: We identified five hub genes (JUN, SLC2A1, TFRC, ALB, and NFE2L2) that are closely associated with ferroptosis in AD and can differentiate AD patients from controls. Three hub genes of apoptosis-related genes in AD (STAT1, MCL1, and BCL2L11) were also identified as a control to show the specificity of ferroptosis. JUN, SLC2A1, TFRC, ALB, and NFE2L2 are thus potential ferroptosis-related biomarkers for disease diagnosis and therapeutic monitoring.", "claims": [{"id": "claim-method", "statement": "AD-related module genes were identified through a weighted gene co-expression network analysis (WGCNA).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35197821", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "AD-related module genes were identified through a weighted gene co-expression network analysis (WGCNA)."}], "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:35197821", "locator": "sections[19] \"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": "Five ferroptosis-related hub genes—JUN, SLC2A1, TFRC, ALB, and NFE2L2—were identified as potential biomarkers for differentiating AD patients from controls.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:35197821", "locator": "sections[18] \"Conclusion\" paragraph 2", "quote": "We identified five hub genes (JUN, SLC2A1, TFRC, ALB, and NFE2L2) that are closely associated with ferroptosis in AD and can differentiate AD patients from controls, and are thus potential ferroptosis-related biomarkers for disease diagnosis and therapeutic monitoring."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Five ferroptosis-related hub genes—JUN, SLC2A1, TFRC, ALB, and NFE2L2—were identified as potential biomarkers for differentiating AD patients from controls.", "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:35197821"], "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:GSE122063"], "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:GSE122063"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:35197821", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fnins.2022.823741", "sha256": "sha256:ae9fc50d1e5093df24fab8cb1b31579f2ecdb7100363f0f4c6c9fd2a99206823", "bytes": 22196, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3389/fnins.2022.823741", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC8858973", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE122063", "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=GSE122063", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE122063", "version": null, "note": "The datasets presented in this study can be found in online repositories. 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The names of the repository/repositories and accession number(s) can be found in the article/supplementary material.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM915094", "GSM915095", "GSM915096", "GSM915097", "GSM915098", "GSM915099", "GSM915100", "GSM915101", "GSM915102", "GSM915103", "GSM915104", "GSM915105", "GSM915106", "GSM915107", "GSM915108", "GSM915109"], "sample_count": 16, "group_sizes": null, "group_sizes_basis": null, "platform": "5175", "taxon": "Homo sapiens", "title": "Genome-wide profiling of altered gene expression in the neocortex of Alzheimer's disease (gene level)", "resolution_checked_at": "2026-11-01T17:30:42Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}], "gaps": ["asset:data:geo:GSE122063 not downloaded", "asset:data:geo:GSE122063 licence not read", "asset:data:geo:GSE140829 not downloaded", "asset:data:geo:GSE140829 licence not read", "asset:data:geo:GSE37263 not downloaded", "asset:data:geo:GSE37263 licence not read"]}, "analysis": {"state": "partial", "methods": [{"id": "method-1", "family": "regression_modelling", "specific": "logistic", "label": "Regression modelling", "dsl_operations": ["glm_logit_fit"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["predictors_and_outcome"], "evidence": {"score": 0.7, "band": "medium", "quote": "Logistic regression"}}, {"id": "method-2", "family": "network_analysis", "specific": "ppi_network", "label": "Network / pathway analysis", "dsl_operations": ["build_graph", "centrality_scores", "pathway_enrich"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["edge_list"], "evidence": {"score": 0.7, "band": "medium", "quote": "protein-protein interaction"}}, {"id": "method-3", "family": "network_analysis", "specific": "pathway_enrichment", "label": "Network / pathway analysis", "dsl_operations": ["pathway_enrich"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["edge_list"], "evidence": {"score": 0.7, "band": "medium", "quote": "pathway enrichment"}}, {"id": "method-4", "family": "diagnostic_evaluation", "specific": "roc", "label": "Diagnostic test evaluation", "dsl_operations": ["confusion_counts", "roc_curve", "sensitivity_specificity", "solve_confusion_matrix", "classification_metrics", "published_precision_envelope"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["reference_standard_and_test"], "evidence": {"score": 0.7, "band": "medium", "quote": "ROC curve"}}, {"id": "method-5", "family": null, "specific": null, "label": "Weighted gene co-expression network analysis (WGCNA)", "dsl_operations": [], "missing_operations": [], "expressible": null, "parameters": {}, "data_shapes": [], "evidence": {"score": 1.0, "band": "verbatim", "quote": "AD-related module genes were identified through a weighted gene co-expression network analysis (WGCNA)."}}], "targets": [], "gaps": ["method.reader_named_unmapped"]}, "capability": {"state": "complete", "requirements": [{"capability_id": "capability:computational_analysis", "label": "Computational analysis platform", "assay_families": ["meta_analysis", "machine_learning", "survival_analysis", "statistical_regression", "pca", "molecular_docking", "network_analysis", "differential_expression", "gwas"], "availability_state": "owned", "tier_unlocked": "R1", "candidate": "Automated Assays Laravel application and simulated adapters"}], "gaps": []}, "readiness": {"state": "complete", "tier": "R1", "blocking_axis": "none", "blocked_on": "nothing:replicable_now", "axes": {"method": {"tier": "R1", "expressible": true, "required_operations": ["glm_logit_fit"], "missing_operations": [], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: logistic."}, "capability": {"tier": "R1", "capability_id": "capability:computational_analysis", "availability_state": "owned", "basis": "The computational analysis is owned. The physical bench the paper used is not, so a physical validation cannot be run here."}, "data": {"tier": "R1", "reachable": true, "accessions": ["GSE122063", "GSE37263", "GSE140829"], "resolved_accessions": ["GSE122063", "GSE37263", "GSE140829"], "statements": ["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."], "basis": "The paper names GSE122063, GSE37263, GSE140829 in GEO and the accession resolves in the repository. 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MATERIALS AND METHODS: Three microarray datasets (GSE122063, GSE37263, and GSE140829", "Materials and Methods Microarray Data Processing Three microarray datasets (G", "and Methods Microarray Data Processing Three microarray datasets (GSE122063, GSE37263, and GSE140829"], "order_basis": "paper_text_order:260", "id": "assay:1"}, {"role": "data_generation", "definition_id": "apoptosis_assay", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["elated genes were extracted from FerrDb. The apoptosis-related genes were downloaded from UniProt a", "module genes associated with ferroptosis and apoptosis. Then the Gene Ontology (GO) and Kyoto Encyc", "he area under the ROC curve (AUC) was 0.643. Apoptosis-related hub genes in AD (STAT1, MCL1, and BC", "sting that ferroptosis was more special than apoptosis in AD. CONCLUSION: We identified five hub ge"], "order_basis": "paper_text_order:529", "id": "assay:2"}, {"role": "analysis", "definition_id": "regression_modelling", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["glm_logit_fit"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 0.7, "evidence": ["Logistic regression"], "order_basis": "consumes_earlier_output", "id": "assay:3"}]}