Ferroptosis-related biomarkers for Alzheimer's disease: Identification by bioinformatic analysis in hippocampus.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:36467613", "kind": "science-record", "revision": 4, "content_hash": "sha256:d037c9bc372eb6cd08b4fde1b020ad3a273c55d728f69414b48c5481cb383649", "created_at": "2026-11-01T19:00:57Z", "updated_at": "2026-11-01T22:50:45Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Ferroptosis-related biomarkers for Alzheimer's disease: Identification by bioinformatic analysis in hippocampus.", "doi": "10.3389/fncel.2022.1023947", "pmid": "36467613", "authors": ["Binyang Wang", "Chenyang Fu", "Yuanyuan Wei", "Bonan Xu", "Rongxing Yang", "Chuanxiong Li", "Meihua Qiu", "Yong Yin", "Dongdong Qin"], "journal": "Frontiers in cellular neuroscience", "year": 2022, "abstract": "Background: Globally, Alzheimer's Disease (AD) accounts for the majority of dementia, making it a public health concern. AD treatment is limited due to the limited understanding of its pathogenesis. Recently, more and more evidence shows that ferroptosis lead to cell death in the brain, especially in the regions of the brain related to dementia.\nMaterials and methods: Three microarray datasets (GSE5281, GSE9770, GSE28146) related to AD were downloaded from Gene Expression Omnibus (GEO) datasets. Ferroptosis-related genes were extracted from FerrDb database. Data sets were separated into two groups. GSE5281 and GSE9770 were used to identify ferroptosis-related genes, and GSE28146 was used to verify results. During these processes, protein-protein interaction (PPI), the Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted. Finally, the differentiated values of ferroptosis-related genes were determined by receiver operator characteristic (ROC) monofactor analysis to judge their potential quality as biomarkers.\nResults: Twenty-four ferroptosis-related genes were obtained. Using STRING (https://cn.string-db.org/) and Cytoscape with CytoHubba, the top 10 genes (RB1, AGPAT3, SESN2, KLHL24, ALOX15B, CA9, GDF15, DPP4, PRDX1, UBC, FTH1, ASNS, GOT1, PGD, ATG16L1, SLC3A2, DDIT3, RPL8, VDAC2, GLS2, MTOR, HSF1, AKR1C3, NCF2) were identified as target genes. GO analysis revealed that response to carboxylic acid catabolic process, organic acid catabolic process, alpha-amino acid biosynthetic process and cellular amino acid biosynthetic process were the most highly enriched terms. KEGG analysis showed that these overlapped genes were enriched in p53 signaling pathways, longevity regulating pathway, mTOR signaling pathway, type 2 diabetes mellitus and ferroptosis. Box plots and violine plots were created and verified to confirm the significance of identified target genes. Moreover, ROC monofactor analysis was performed to determine the diagnostic value of identified genes. Two genes (ASNS, SESN2) were subsequently obtained. For the tow genes, STRING was used to obtain the five related genes and determined enriched GO terms and KEGG pathways for those genes.\nConclusion: Our results suggest that ASNS and SENS2 may serve as potential diagnostic biomarkers for AD and provide additional evidence regarding the essential role of ferroptosis in AD.", "claims": [{"id": "claim-method", "statement": "Finally, the LIMMA (Ritchie et al., 2015) package was used to identify DEGs (differentially expression genes) with a log fold change >1 and p-value <0.05.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36467613", "locator": "sections[3] \"Datasets and pre-processing\" paragraph 4", "quote": "Finally, the LIMMA (Ritchie et al., 2015) package was used to identify DEGs (differentially expression genes) with a log fold change >1 and p-value <0.05."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets presented in this study can be found in online repositories. The names of the repositories and accession numbers can be found in the article/supplementary material.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36467613", "locator": "sections[15] \"Data availability statement\" paragraph 2", "quote": "The datasets presented in this study can be found in online repositories. The names of the repositories and accession numbers can be found in the article/supplementary material."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Twenty-four ferroptosis-related genes were identified as biomarker candidates.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:36467613", "locator": "sections[8] \"Finding and identifying the ferroptosis-related genes\" paragraph 2", "quote": "Finally, 24 ferroptosis-related genes were identified as biomarker candidates."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Twenty-four ferroptosis-related genes were identified as biomarker candidates.", "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:36467613"], "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:GSE28146"], "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": {"fold_change": "LIMMA with a log fold change >1 and p-value <0"}, "inputs": ["data:geo:GSE28146"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:36467613", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fncel.2022.1023947", "sha256": "sha256:53eccbadf7b1c57e97c440983dc941a358d8691e1a6e15470a7533033fd17d93", "bytes": 25666, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3389/fncel.2022.1023947", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC9709107", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE28146", "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=GSE28146", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE28146", "version": null, "note": "The datasets presented in this study can be found in online repositories. The names of the repositories and accession numbers can be found in the article/supplementary material.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The datasets presented in this study can be found in online repositories. The names of the repositories and accession numbers can be found in the article/supplementary material.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM697308", "GSM697309", "GSM697310", "GSM697311", "GSM697312", "GSM697313", "GSM697314", "GSM697315", "GSM697316", "GSM697317", "GSM697318", "GSM697319", "GSM697320", "GSM697321", "GSM697322", "GSM697323", "GSM697324", "GSM697325", "GSM697326", "GSM697327", "GSM697328", "GSM697329", "GSM697330", "GSM697331", "GSM697332", "GSM697333", "GSM697334", "GSM697335", "GSM697336", "GSM697337"], "sample_count": 30, "group_sizes": null, "group_sizes_basis": null, "platform": "570", "taxon": "Homo sapiens", "title": "Microarray analyses of laser-captured hippocampus reveal distinct gray and white matter signatures associated with incipient Alzheimer’s disease", "resolution_checked_at": "2026-11-01T17:30:42Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "data:geo:GSE5281", "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=GSE5281", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE5281", "version": null, "note": "The datasets presented in this study can be found in online repositories. 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The names of the repositories and accession numbers can be found in the article/supplementary material.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The datasets presented in this study can be found in online repositories. The names of the repositories and accession numbers can be found in the article/supplementary material.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM242043", "GSM242044", "GSM242045", "GSM242046", "GSM242047", "GSM242048", "GSM242049", "GSM242050", "GSM242051", "GSM242052", "GSM242053", "GSM242054", "GSM242055", "GSM242056", "GSM242057", "GSM242058", "GSM242059", "GSM242060", "GSM242061", "GSM242062", "GSM242063", "GSM242064", "GSM242065", "GSM242066", "GSM242067", "GSM242068", "GSM242069", "GSM242083", "GSM242084", "GSM242085", "GSM242086", "GSM242087", "GSM242088", "GSM242089"], "sample_count": 34, "group_sizes": null, "group_sizes_basis": null, "platform": "570", "taxon": "Homo sapiens", "title": "Non-demented individuals with intermediate Alzheimer's neuropathologies - neuronal expression (6 regions)", "resolution_checked_at": "2026-11-01T18:46:34Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}], "gaps": ["asset:data:geo:GSE28146 not downloaded", "asset:data:geo:GSE28146 licence not read", "asset:data:geo:GSE5281 not downloaded", "asset:data:geo:GSE5281 licence not read", "asset:data:geo:GSE9770 not downloaded", "asset:data:geo:GSE9770 licence not read"]}, "analysis": {"state": "complete", "methods": [{"id": "method-1", "family": "differential_expression", "specific": "limma_voom", "label": "Differential expression analysis", "dsl_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "missing_operations": [], "expressible": true, "parameters": {"fold_change": "LIMMA with a log fold change >1 and p-value <0"}, "data_shapes": ["count_matrix_with_condition"], "evidence": {"score": 1.0, "band": "verbatim", "quote": "Finally, the LIMMA (Ritchie et al., 2015) package was used to identify DEGs (differentially expression genes) with a log fold change >1 and p-value <0.05."}}, {"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"}}], "targets": [], "gaps": []}, "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": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "missing_operations": [], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: limma_voom."}, "capability": {"tier": "R1", "capability_id": "capability:computational_analysis", "availability_state": "owned", "basis": "The computational analysis is owned. 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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:36467613", "data:geo:GSE28146"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE28146"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-11-01T18:18:07Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": "verbatim"}, "calls": 5, "usage": {"prompt_tokens": 7812, "completion_tokens": 1447, "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:36467613", "type": "paper", "label": "pmid:36467613"}, {"id": "source:pmid:36467613", "type": "manuscript", "label": "PMID 36467613 full text"}, {"id": "data:geo:GSE28146", "type": "dataset", "label": "GEO GSE28146"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:36467613", "type": "paper", "label": "pmid:36467613"}, {"id": "source:pmid:36467613", "type": "manuscript", "label": "PMID 36467613 full text"}, {"id": "data:geo:GSE28146", "type": "dataset", "label": "GEO GSE28146"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-36467613", "type": "extraction", "used": ["source:pmid:36467613"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE28146", "type": "accession_resolution", "used": ["data:geo:GSE28146"], "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:36467613", "parent_hash": "sha256:3aea0031e182f54903da836e9973b8aa9e40f2d630e74775f5e1b12321da9313", "fork_of": null, "generation": 3}, "gaps": ["asset:data:geo:GSE28146 licence not read", "asset:data:geo:GSE28146 not downloaded", "asset:data:geo:GSE5281 licence not read", "asset:data:geo:GSE5281 not downloaded", "asset:data:geo:GSE9770 licence not read", "asset:data:geo:GSE9770 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": 0.93, "evidence": ["ed to dementia. 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