Screening of the key genes and signaling pathways for schizophrenia using bioinformatics and next generation sequencing data analysis

Schizophrenia is thought to be the most prevalent chronic psychiatric disorder. Researchers have identified numerous proteins associated with the occurrence and development of schizophrenia. This study aimed to identify potential core genes and pathways involved in schizophrenia through exhaustive bioinformatics and next generation sequencing (NGS) data analyses using GSE106589 NGS data of neural progenitor cells and neurons obtained from healthy controls and patients with schizophrenia. The NGS data were downloaded from the Gene Expression Omnibus database. NGS data was processed by the DESeq2 package in R software, and the differentially expressed genes (DEGs) were identified. Gene ontology (GO) enrichment analysis and REACTOME pathway enrichment analysis were carried out to identify potential biological functions and pathways of the DEGs. Protein-protein interaction network, module, micro-RNA (miRNA)-hub gene regulatory network, transcription factor (TF)-hub gene regulatory network, and drug-hub gene interaction network analysis were performed to identify the hub genes, miRNA, TFs, and drug molecules. Potential hub genes were analyzed using receiver operating characteristic curves in the R package. In this investigation, an overall 955 DEGs were identified: 478 genes were remarkably upregulated and 477 genes were distinctly downregulated. These genes were enriched for GO terms and pathways mainly involved in the multicellular organismal process, G protein-coupled receptor ligand binding, regulation of cellular processes, and amine ligand-binding receptors. MYC, FN1, CDKN2A, EEF1G, CAV1, ONECUT1, SYK, MAPK13, TFAP2A, and BTK were considered the potential hub genes. The MiRNA-hub gene regulatory network, TF-hub gene regulatory network, and drug-hub gene interaction network were constructed successfully and predicted key miRNAs, TFs, and drug molecules for schizophrenia diagnosis and treatment. On the whole, the findings of this investigation enhance our understanding of the potential molecular mechanisms of schizophrenia and provide potential targets for further investigation.

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Journal
Italian Journal of Medicine
Published
2024-12-18
DOI
https://doi.org/10.4081/itjm.2024.1830
Primary Topic
Genetic Associations and Epidemiology
Type
article
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article

Screening of the key genes and signaling pathways for schizophrenia using bioinformatics and next generation sequencing data analysis

Chanabasayya Vastrad, Iranna Kotturshetti, Basavaraj Vastrad, Shivakumar Kotrashetti et al.
Italian Journal of Medicine
Genetic Associations and Epidemiology
article

Screening of the key genes and signaling pathways for schizophrenia using bioinformatics and next generation sequencing data analysis

Chanabasayya Vastrad, Iranna Kotturshetti, Basavaraj Vastrad, Shivakumar Kotrashetti, Veena Kori
article en

Abstract

Schizophrenia is thought to be the most prevalent chronic psychiatric disorder. Researchers have identified numerous proteins associated with the occurrence and development of schizophrenia. This study aimed to identify potential core genes and pathways involved in schizophrenia through exhaustive bioinformatics and next generation sequencing (NGS) data analyses using GSE106589 NGS data of neural progenitor cells and neurons obtained from healthy controls and patients with schizophrenia. The NGS data were downloaded from the Gene Expression Omnibus database. NGS data was processed by the DESeq2 package in R software, and the differentially expressed genes (DEGs) were identified. Gene ontology (GO) enrichment analysis and REACTOME pathway enrichment analysis were carried out to identify potential biological functions and pathways of the DEGs. Protein-protein interaction network, module, micro-RNA (miRNA)-hub gene regulatory network, transcription factor (TF)-hub gene regulatory network, and drug-hub gene interaction network analysis were performed to identify the hub genes, miRNA, TFs, and drug molecules. Potential hub genes were analyzed using receiver operating characteristic curves in the R package. In this investigation, an overall 955 DEGs were identified: 478 genes were remarkably upregulated and 477 genes were distinctly downregulated. These genes were enriched for GO terms and pathways mainly involved in the multicellular organismal process, G protein-coupled receptor ligand binding, regulation of cellular processes, and amine ligand-binding receptors. MYC, FN1, CDKN2A, EEF1G, CAV1, ONECUT1, SYK, MAPK13, TFAP2A, and BTK were considered the potential hub genes. The MiRNA-hub gene regulatory network, TF-hub gene regulatory network, and drug-hub gene interaction network were constructed successfully and predicted key miRNAs, TFs, and drug molecules for schizophrenia diagnosis and treatment. On the whole, the findings of this investigation enhance our understanding of the potential molecular mechanisms of schizophrenia and provide potential targets for further investigation.

Italian Journal of MedicineVol. 18(4)
Government Ayurvedic College and Hospital (IN), Desh Bhagat Ayurvedic College and Hospital (IN)
Openalex Percentile: Top 74%
Genetic Associations and Epidemiology
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