Bioinformatics and Quantitative Real-Time Polymerase Chain Reaction Analysis of SUCNR1 and GPR37L1 in Schizophrenia

Summary

This study evaluates SUCNR1 and GPR37L1 as candidate schizophrenia-associated molecular markers through integrated bioinformatics analysis of the GSE54913 dataset, quantitative real-time polymerase chain reaction (qRT-PCR) validation, and correlation analysis with verbal memory in an independent cohort.

Abstract

Schizophrenia is a severe, complex, and multifactorial mental disorder involving numerous genetic susceptibility elements, leading to substantial disability, morbidity, and mortality. Despite significant progress in understanding its pathophysiology and etiology, specific diagnostic biomarkers for schizophrenia remain elusive. This study aimed to identify candidate molecular markers associated with schizophrenia. An integrated bioinformatics analysis was performed on the public microarray dataset GSE54913. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses revealed that the most significantly enriched GO terms were related to channel activity, including passive transmembrane transporter activity, ion channel activity, gated channel activity, and substrate-specific channel activity. The top five enriched KEGG pathways were insulin secretion, cAMP signaling pathway, nucleotide excision repair, TNF signaling pathway, and glutathione metabolism. Validation was conducted using quantitative real-time polymerase chain reaction (qRT-PCR) on an independent sample set from Wuhan Rongjun Youfu Hospital. The qRT-PCR results were largely consistent with the microarray analysis (Pearson r = 0.89, 95% CI: 0.66–0.97). Protein-protein interaction (PPI) network analysis identified two hub genes, SUCNR1 and GPR37L1, which were significantly associated with the GO term ‘ion channel activity’ and enriched in the KEGG pathway ‘insulin secretion’. Furthermore, SUCNR1 expression showed a negative correlation with verbal memory scores (r = -0.54, P = 0.015), whereas GPR37L1 expression showed a positive correlation (r = 0.59, P = 0.0034). These findings suggest that altered SUCNR1 and GPR37L1 expression may be associated with schizophrenia and may represent candidate molecular markers for further investigation.

Introduction

Schizophrenia is a chronic and complex mental disorder of unidentified etiology, characterized by severe brain dysfunction, cognitive impairment, and psychosocial deficits¹. It poses a major global health burden, affecting over 21 million people worldwide². Although diagnostic and therapeutic approaches have evolved considerably over the past fifty years, the core pathogenesis remains unclear, and long-term outcomes associated with substantial disability, morbidity, and mortality have not markedly improved³. Therefore, identifying potential pivotal genes and regulatory targets is imperative.

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Protocol

This study was approved by the Ethics Committee of Wuhan Rongjun Youfu Hospital (project identification code, YF-IRB202310215) and conducted in accordance with the principles of the Declaration of Helsinki. All participants were Chinese community residents and provided written informed consent.

Study subjects and blood sampling
Ten adults diagnosed with schizophrenia and ten healthy control volunteers with no family history of mental illness within three generations were enrolled. Inclusion criteria for schizophrenia patients: (1) diagnosis of schizophrenia according to DSM-5 criteria confirmed by two independent seni....

Results

Identification of DEGs and hierarchical clustering
Analysis of the GSE54913 dataset identified 473 differentially expressed genes (DEGs), including 357 upregulated and 116 downregulated genes, between schizophrenia patients and controls (Figure 2A,B). Hierarchical clustering of these DEGs distinguished schizophrenia samples from controls (Figure 2C).

Functional enrichment analysis of DEGs<.......

Discussion

Schizophrenia is a severe, multifactorial disorder involving numerous genetic susceptibility factors^13,14. While progress has been made in understanding its pathophysiology, reliable diagnostic biomarkers are still lacking. In this study, an integrated bioinformatics approach identified 473 DEGs in blood samples from patients with schizophrenia. GO and KEGG analyses highlighted enrichment in channel activity-related terms and pathways, including insulin secretion.......

Materials

List of materials used in this article

Name	Company	Catalog Number	Comments
affy	Bioconductor	https://bioconductor.org/packages/affy/	microarray preprocessing software. Description: R package for microarray preprocessing
clusterProfiler	Bioconductor	https://bioconductor.org/packages/clusterProfiler/	functional enrichment analysis software. Description: R package for functional enrichment analysis
CytoHubba	National Institute of Bioinformatics	https://apps.cytoscape.org/apps/cytohubba	hub gene identification plugin. Description: Cytoscape plugin for hub gene identification
Cytoscape	Cytoscape Consortium	https://cytoscape.org/	network visualization software. Description: Software for network visualization and analysis
G*Power	Heinrich Heine University Düsseldorf	https://www.psychologie.hhu.de/arbeitsgruppen/allgemeine-psychologie-und-arbeitspsychologie/gpower	sample size calculation software. Description: Sample size calculation software
GraphPad Prism	GraphPad Software	https://www.graphpad.com/	statistical analysis and graphing software. Description: Statistical analysis and graphing software
Histopaque-1077	Sigma-Aldrich	10771	density gradient medium. Description: Density gradient medium for PBMC isolation
impute	Bioconductor	https://bioconductor.org/packages/impute/	missing-value imputation software. Description: R package for missing-value imputation
Limma	Bioconductor	https://bioconductor.org/packages/limma/	differential expression analysis software. Description: R package for differential expression analysis
MCODE	Cytoscape app	https://apps.cytoscape.org/apps/mcode	subnetwork extraction plugin. Description: Cytoscape plugin for subnetwork extraction
R/Bioconductor	R Foundation	https://www.r-project.org/	statistical computing environment. Description: Statistical computing environment
STRING	EMBL	https://string-db.org/	protein-protein interaction database. Description: Protein-protein interaction database
SYBR Green	Takara	RR820A	fluorescent dye for qRT-PCR. Description: Fluorescent dye for qRT-PCR
TRIzol	Takara	9109	RNA extraction reagent. Description: Reagent for RNA extraction