HSPB1 Gene Variants and Schizophrenia: A Case-Control Study in a Polish Population

Kowalczyk, Małgorzata; Kucia, Krzysztof; Owczarek, Aleksander; Suchanek-Raif, Renata; Paul-Samojedny, Monika; Choręża, Piotr; Kowalski, Jan

doi:10.1155/2022/4933011

Cited by 5 publications

(2 citation statements)

References 52 publications

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“…Pathogenic mutations of HSPB1 are associated with neurodegenerative diseases (Geuens et al., 2017). In addition, polymorphism of HSPB1 is associated with schizophrenia (Kowalczyk & Kucia, 2022). TAOK1 is associated with neurodevelopmental disorder.…”

Section: Discussionmentioning

confidence: 99%

Identification of key mRNAs and signaling pathways in obsessive compulsive disorder based on weighted gene co‐expression network analysis and cytoHubba plugin

Zhang,

Liu,

Guo

et al. 2024

Brain and Behavior

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PurposeObsessive‐compulsive disorder (OCD) is a complex psychiatric disorder. Genetic and broad environmental factors are common risk factors for OCD. The purpose of this study is to explore the molecular mechanism of OCD and to find new molecular targets for the diagnosis and management of OCD.MethodsAll data were downloaded from public dataset. Key modules and candidate key mRNAs were identified based on weighted gene co‐expression network analysis (WGCNA). The “limma” R package was used for differential expression analysis of mRNAs. Subsequently, functional enrichment analysis of differentially expressed mRNAs (DEmRNAs) was also carried out. In addition, a diagnostic model was constructed. Finally, the infiltration level of immune cells in OCD and its correlation with multicentric key DEmRNAs were analyzed.ResultsGreen and red modules were selected as the hub modules. A total of 447 mRNAs were considered candidate key mRNAs according to GS > 0.2 and MM > 0.3. A total of 26 DEmRNAs in the same direction were identified in the GSE60190 and GSE78104 datasets. A total of 26 DEmRNAs were intersected with candidate key mRNAs in WGCNA to obtain 10 intersection DEmRNAs (HSPB1, ITPK1, CBX7, PPP1R10, TAOK1, PISD, MKNK2, RWDD1, PPA1, and RELN). However, only four DEmRNAs (HSPB1, TAOK1, MKNK2, and PPA1) predicted related drugs. Subsequently, receiver operating characteristic analysis shows that the diagnostic model has high diagnostic value. Moreover, six multicentric key DEmRNAs (SNRPF, SNRNP70, PRPF8, NOP56, EPRS, and CCT2) were screened by UpSet package. Finally, six multicentric key DEmRNAs were found to be associated with immune cells.ConclusionThe key molecules obtained in this study lay a foundation for further research on the molecular mechanism of OCD.

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Section: Discussionmentioning

confidence: 99%

Identification of key mRNAs and signaling pathways in obsessive compulsive disorder based on weighted gene co‐expression network analysis and cytoHubba plugin

Zhang,

Liu,

Guo

et al. 2024

Brain and Behavior

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show abstract

“…The overexpression of HSPB1 directly inhibits apoptotic pathways to increase neuronal survival, 13 Behavioural Neurology thereby protecting against injury-induced nerve death [34]. Changes in HSPB1 expression levels were observed in patients with schizophrenia, and HSPB1 polymorphisms were associated with an increased risk of schizophrenia [35]. TNFRSF1A is downregulated in elderly schizophrenia subjects, which may be related to cognitive decline [36].…”

Section: Discussionmentioning

confidence: 99%

Construction of a Diagnostic Model and a lncRNA-Associated ceRNA Network Based on Apoptosis-Related Genes for Schizophrenia

Ma¹,

Wang²,

Meng³

2023

Behavioural Neurology

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Background and Aim. Schizophrenia is a complex psychiatric disorder with an unknown etiology. Previous studies suggest that apoptosis is potentially involved in the pathophysiology of schizophrenia, but whether apoptotic markers can help diagnosis of schizophrenia has not been reported. This study aimed to establish a potential diagnostic model based on apoptosis-related gene expression in blood samples and to construct a competing endogenous RNA (ceRNA) network that could provide mechanistic insight of schizophrenia. Methods. Gene expression profiles and apoptosis-related data were downloaded from the Gene Expression Omnibus and Molecular Signature databases, respectively. Apoptosis-related differentially expressed mRNAs (DEGs) and miRNAs (DEMs) from blood samples between the schizophrenia and healthy control individuals were screened. A diagnostic model was developed using the data from univariate and least absolute shrinkage and selection operator (LASSO) regression analyses, followed by validation using the GSE38485 dataset. Cases were divided into low-risk (LR) and high-risk (HR) groups based on the risk score of the model, and differences in immune gene sets and pathways between these two groups were compared. Finally, a ceRNA network was constructed by integrating long non-coding RNAs (lncRNAs), DEMs, and DEGs. Results. A diagnostic model containing 15 apoptosis-related genes was developed and its diagnostic efficiency was found to be robust. The HR group was correlated with higher immune scores of chemokines, cytokines, and interleukins; it was also significantly involved in pathways such as pancreatic beta cells and early estrogen response. A ceRNA network composed of 2 lncRNAs, 14 miRNAs, and 5 mRNAs was established. Conclusions. The established model is a potential tool to improve the diagnostic efficiency of patients with schizophrenia, and the nodes included in the ceRNA network might serve as biomarkers and therapeutic targets for schizophrenia.

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The Identification of Key Genes and Biological Pathways in Polycystic Ovary Syndrome and its Complications by Next Generation Squancing (NGS) and Bioinformatics Analysis

Vastrad¹,

Vastrad²

2023

Preprint

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Polycystic ovary syndrome (PCOS) is is associated with infertility, obesity, insulin resistance, hyperinsulinemia, type 2 diabetes mellitus, hypertension, cardiovascular problems, neurological and psychological problems and cancer. The specific mechanism of PCOS and its complications remains unclear. The aim of this study was to apply a bioinformatics approach to reveal related pathways or genes involved in the development of PCOS and its complications. The next generation squancing (NGS) datset GSE199225 was downloaded from the gene expression omnibus (GEO) database. Differentially expressed gene (DEG) analysis was performed using DESeq2. The g:Profiler was utilized to analyze the functional enrichment, gene ontology (GO) and REACTOME pathway of the differentially expressed genes. A protein-protein interaction (PPI) network was constructed and module analysis was performed using HiPPIE and cytoscape. The miRNA-hub gene regulatory network and TF-hub gene regulatory network were also constructed for research. The expression of the hub genes was validated using receiver operating characteristic (ROC) curve analysis. We have identified 957 DEGs in total, including 478 up regulated genes and 479 down regulated gene. GO and REACTOME illustrated that DEGs in PCOS were significantly enriched in regulation of molecular function, developmental process, interferon signaling and platelet activation, signaling and aggregation. Finally, through analyzing the PPI network, modules, miRNA-hub gene regulatory network and TF-hub gene regulatory network, we screened hub genes HSPA5, PLK1, RIN3, DBN1, CCDC85B, DISC1, AR, MTUS2, LYN and TCF4 by the Cytoscape software. This study uses a series of bioinformatics technologies to obtain hug genes and key pathways related to PCOS and its complications. These analysis results provide us with novel ideas for finding biomarkers and treatment methods for PCOS and its complications.

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HSPB1 Gene Variants and Schizophrenia: A Case-Control Study in a Polish Population

Cited by 5 publications

References 52 publications

Identification of key mRNAs and signaling pathways in obsessive compulsive disorder based on weighted gene co‐expression network analysis and cytoHubba plugin

Identification of key mRNAs and signaling pathways in obsessive compulsive disorder based on weighted gene co‐expression network analysis and cytoHubba plugin

Construction of a Diagnostic Model and a lncRNA-Associated ceRNA Network Based on Apoptosis-Related Genes for Schizophrenia

The Identification of Key Genes and Biological Pathways in Polycystic Ovary Syndrome and its Complications by Next Generation Squancing (NGS) and Bioinformatics Analysis

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