ArticleGenes2022
Exploring the Core Genes of Schizophrenia Based on Bioinformatics Analysis.
Article in Genes, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Research progress on BTG2 in non‑tumor diseases (Review).International journal of molecular medicine · 2026Review
- Identification of metabolism and inflammation-related biomarkers and potential drugs for schizophrenia based on comprehensive bioinformatics and machine learning.BMC psychiatry · 2026Article
- Bioinformatics-based identification of CTSS, DOK2, and ENTPD1 as potential blood biomarkers of schizophrenia.BMC psychiatry · 2025Article
- Exploring the relationship and shared mechanisms of major depressive disorder and diabetic kidney disease: a comprehensive clinical and genetic analysis.Frontiers in psychiatry · 2025Article
- Deciphering transcriptomic signatures in schizophrenia, bipolar disorder, and major depressive disorder.Frontiers in psychiatry · 2025Article
- Probing the Molecular Mechanisms of Kratom's Antipsychotic Effects through a Multi-modal Computational Approach.Current pharmaceutical design · 2025Article
- Identification of key genes and pathways in schizophrenia: a bioinformatics analysis based on GWAS and GEO.Frontiers in psychiatry · 2025Article
- Two hub genes of bipolar disorder, a bioinformatics study based on the GEO database.IBRO neuroscience reports · 2024Article
- Enhancing Transcriptomic Insights into Neurological Disorders Through the Comparative Analysis of Shapley Values.Current issues in molecular biology · 2024Article
- Identification of hub genes and construction of diagnostic nomogram model in schizophrenia.Frontiers in aging neuroscience · 2022Article
Corrections and comments
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
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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