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pmid:35741729

Exploring the Core Genes of Schizophrenia Based on Bioinformatics Analysis.

Shunkang Feng · Ping Sun · Chunhui Qu · Xiaohui Wu · Lu Yang · Tao Yang · Shuo Wang · Yiru Fang · Jun Chen

Genes · 2022 doi:10.3390/genes13060967

Paper

complete

Experiment

complete

Data

partial

Analysis

partial

Execution

absent

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Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
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pmid:35741729
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science-record
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2026-11-01T18:14:45Z
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2026-11-01T22:06:51Z
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paper object · 10 fields
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title
Exploring the Core Genes of Schizophrenia Based on Bioinformatics Analysis.
doi
10.3390/genes13060967
pmid
35741729
authors array · 9 items
[0]
Shunkang Feng
[1]
Ping Sun
[2]
Chunhui Qu
[3]
Xiaohui Wu
[4]
Lu Yang
[5]
Tao Yang
[6]
Shuo Wang
[7]
Yiru Fang
[8]
Jun Chen
journal
Genes
year
2022
abstract
Schizophrenia is a clinical syndrome composed of a group of symptoms involving many obstacles such as perception, thinking, emotion, behavior, and the disharmony of mental activities. Schizophrenia is one of the top ten causes of disability globally, accounting for about 1% of the global population. Previous studies have shown that schizophrenia has solid genetic characteristics. However, the diagnosis of schizophrenia mainly depends on symptomatic manifestations, and no gene can be used as a clear diagnostic marker at present. This study explored the hub genes of schizophrenia by bioinformatics analysis. Three datasets were selected and downloaded from the GEO database (GSE53987, GSE21138, and GSE27383). GEO2R, NCBI's online analysis tool, is used to screen out significant gene expression differences. The genes were functionally enriched by GO and KEGG enrichment analysis. On this basis, the hub genes were explored through Cytoscape software, and the immune infiltration analysis and diagnostic value of the screened hub genes were judged. Finally, four hub genes (NFKBIA, CDKN1A, BTG2, GADD45B) were screened. There was a significant correlation between two hub genes (NFKBIA, BTG2) and resting memory CD4 T cells. The ROC curve results showed that all four hub genes had diagnostic value.
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An online receiver operating characteristic (ROC) curve drawing tool (https://www.xiantao.love/products, accessed on 24 May 2022) was used to help determine the diagnostic value of hub genes in schizophrenia.
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sections[9] "2.7. Diagnostic Value of Hub Genes" paragraph 2
quote
An online receiver operating characteristic (ROC) curve drawing tool (https://www.xiantao.love/products, accessed on 24 May 2022) was used to help determine the diagnostic value of hub genes in schizophrenia.
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All data are obtained from public data in the GEO database.
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The four hub genes NFKBIA, CDKN1A, BTG2, and GADD45B, as well as their combined use, showed potential diagnostic value for schizophrenia, with reported AUC values of 0.60–1.00 for individual genes.
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qualitative
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null
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sections[18] "3.8. Diagnostic Evaluation of Hub Genes" paragraph 6
quote
In conclusion, four hub genes may have significant diagnostic value in the diagnosis of schizophrenia (AUC: 0.60–1.00).
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The four hub genes NFKBIA, CDKN1A, BTG2, and GADD45B, as well as their combined use, showed potential diagnostic value for schizophrenia, with reported AUC values of 0.60–1.00 for individual genes.
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Gene Expression Profiles in BA46 of Subjects with Schizophrenia and Matched Controls
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570
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Homo sapiens
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Marked Reduction of AKT1 Expression and Deregulation of AKT1-associated Pathways in Peripheral Blood Mononuclear Cells of Schizophrenia Patients
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An online receiver operating characteristic (ROC) curve drawing tool (https://www.xiantao.love/products, accessed on 24 May 2022) was used to help determine the diagnostic value of hub genes in schizophrenia.
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capability object · 4 fields
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GSE21138
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GSE27383
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GSE53987
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GSE27383
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All data are obtained from public data in the GEO database.
basis
The paper names GSE53987, GSE21138, GSE27383 in GEO (Gene Expression Omnibus) and the accession resolves in the repository. No dataset was downloaded and no licence was read.
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PMID 35741729 full text
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35741729", "kind": "science-record", "revision": 4, "content_hash": "sha256:5e0303d474b6d15b001bc08fc6b421dc4a97f1837a63d5864a5bca80fd597438", "created_at": "2026-11-01T18:14:45Z", "updated_at": "2026-11-01T22:06:51Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Exploring the Core Genes of Schizophrenia Based on Bioinformatics Analysis.", "doi": "10.3390/genes13060967", "pmid": "35741729", "authors": ["Shunkang Feng", "Ping Sun", "Chunhui Qu", "Xiaohui Wu", "Lu Yang", "Tao Yang", "Shuo Wang", "Yiru Fang", "Jun Chen"], "journal": "Genes", "year": 2022, "abstract": "Schizophrenia is a clinical syndrome composed of a group of symptoms involving many obstacles such as perception, thinking, emotion, behavior, and the disharmony of mental activities. Schizophrenia is one of the top ten causes of disability globally, accounting for about 1% of the global population. Previous studies have shown that schizophrenia has solid genetic characteristics. However, the diagnosis of schizophrenia mainly depends on symptomatic manifestations, and no gene can be used as a clear diagnostic marker at present. This study explored the hub genes of schizophrenia by bioinformatics analysis. Three datasets were selected and downloaded from the GEO database (GSE53987, GSE21138, and GSE27383). GEO2R, NCBI's online analysis tool, is used to screen out significant gene expression differences. The genes were functionally enriched by GO and KEGG enrichment analysis. On this basis, the hub genes were explored through Cytoscape software, and the immune infiltration analysis and diagnostic value of the screened hub genes were judged. Finally, four hub genes (NFKBIA, CDKN1A, BTG2, GADD45B) were screened. 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No dataset was downloaded and no licence was read."}}, "can_run": {"dsl_operations": ["build_graph", "centrality_scores", "pathway_enrich"], "assets": ["source:pmid:35741729", "data:geo:GSE21138"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE21138"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-11-01T17:52:00Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": "verbatim"}, "calls": 5, "usage": {"prompt_tokens": 7903, "completion_tokens": 1514, "cached_tokens": 128}}, "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:35741729", "type": "paper", "label": "pmid:35741729"}, {"id": "source:pmid:35741729", "type": "manuscript", "label": "PMID 35741729 full text"}, {"id": "data:geo:GSE21138", "type": "dataset", "label": "GEO GSE21138"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:35741729", "type": "paper", "label": "pmid:35741729"}, {"id": "source:pmid:35741729", "type": "manuscript", "label": "PMID 35741729 full text"}, {"id": "data:geo:GSE21138", "type": "dataset", "label": "GEO GSE21138"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-35741729", "type": "extraction", "used": ["source:pmid:35741729"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE21138", "type": "accession_resolution", "used": ["data:geo:GSE21138"], "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:35741729", "parent_hash": "sha256:4c8097a76d9b1a5540f7c4eda98d6f51ec5f01bbfe9e7fcef1ffd27242b5989a", "fork_of": null, "generation": 3}, "gaps": ["asset:data:geo:GSE21138 licence not read", "asset:data:geo:GSE21138 not downloaded", "asset:data:geo:GSE27383 licence not read", "asset:data:geo:GSE27383 not downloaded", "asset:data:geo:GSE53987 licence not read", "asset:data:geo:GSE53987 not downloaded", "execution.not_run", "method.reader_named_unmapped", "review.human_critique", "review.independent_reader", "review.machine_critique"], "assays": [{"role": "data_generation", "definition_id": "apoptosis_assay", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.69, "evidence": ["mall cell lung cancer, endocrine resistance, apoptosis, breast cancer, hepatitis B, NOD-like recept"], "order_basis": "paper_text_order:2908", "id": "assay:1"}, {"role": "analysis", "definition_id": "network_analysis", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["build_graph", "centrality_scores", "pathway_enrich"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 0.8, "evidence": ["PPI"], "order_basis": "consumes_earlier_output", "id": "assay:2"}]}