CTLA4 and CD28 Gene Polymorphisms with Respect to Affective Symptom Domain in Schizophrenia

CTLA-4 expression and polymorphisms in Schizophrenia; a systematic review of literature

Schizophrenia constitutes a severe psychiatric disorder with detrimental impacts on individuals, their support systems, and the broader economy. Extensive research has revealed a notable association between variations in the Cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) gene and an increased susceptibility to schizophrenia.This study represents the first systematic review of the literature investigating the impact of CTLA-4 polymorphisms and expression on the development and progression of schizophrenia.Our investigation involved a comprehensive search strategy, using a combination of title, abstract, and MESH terms in four databases, including PubMed, Scopus, Web of Science, and Google Scholar, until August 29th, 2023. The complete texts of the identified records were obtained and rigorously assessed based on predefined exclusion and inclusion criteria. Out of the numerous records, a total of 88 were identified through the databases. 10 studies met the criteria; therefore, their quality was assessed and included in this systematic study. The records were then categorized into polymorphism and expression groups. Our investigation emphasizes an association between rs3087243, rs231779, rs231777, rs16840252, rs5742909, and rs231775 polymorphisms and the development of schizophrenia. The results demonstrate a correlation between CTLA-4 polymorphisms and schizophrenia, compelling the need for further research to thoroughly examine the role of CTLA-4 in schizophrenia and other psychiatric disorders.

Roles of inflammation in intrinsic pathophysiology and antipsychotic drug-induced metabolic disturbances of schizophrenia

Schizophrenia is a debilitating psychiatric illness that remains poorly understood. While the bulk of symptomatology has classically been associated with disrupted brain functioning, accumulating evidence demonstrates that schizophrenia is characterized by systemic inflammation and disturbances in metabolism. Indeed, metabolic disease is a major determinant of the high mortality rate associated with schizophrenia. Antipsychotic drugs (APDs) have revolutionized management of psychosis, making it possible to rapidly control psychotic symptoms. This has ultimately reduced relapse rates of psychotic episodes and improved overall quality of life for people with schizophrenia. However, long-term APD use has also been associated with significant metabolic disturbances including weight gain, dysglycemia, and worsening of the underlying cardiometabolic disease intrinsic to schizophrenia. While the mechanisms for these intrinsic and medication-induced metabolic effects remain unclear, inflammation appears to play a key role. Here, we review the evidence for roles of inflammatory mechanisms in the disease features of schizophrenia and how these mechanisms interact with APD treatment. We also discuss the effects of common inflammatory mediators on metabolic disease. Then, we review the evidence of intrinsic and APD-mediated effects on systemic inflammation in schizophrenia. Finally, we speculate about possible treatment strategies. Developing an improved understanding of inflammatory processes in schizophrenia may therefore introduce new, more effective options for treating not only schizophrenia but also primary metabolic disorders.

Integration of Imaging (epi)Genomics Data for the Study of Schizophrenia Using Group Sparse Joint Nonnegative Matrix Factorization

Schizophrenia (SZ) is a complex disease. Single nucleotide polymorphism (SNP), brain activity measured by functional magnetic resonance imaging (fMRI) and DNA methylation are all important biomarkers that can be used for the study of SZ. To our knowledge, there has been little effort to combine these three datasets together. In this study, we propose a group sparse joint nonnegative matrix factorization (GSJNMF) model to integrate SNP, fMRI, and DNA methylation for the identification of multi-dimensional modules associated with SZ, which can be used to study regulatory mechanisms underlying SZ at multiple levels. The proposed GSJNMF model projects multiple types of data onto a common feature space, in which heterogeneous variables with large coefficients on the same projected bases are used to identify multi-dimensional modules. We also incorporate group structure information available from each dataset. The genomic factors in such modules have significant correlations or functional associations with several brain activities. At the end, we have applied the method to the analysis of real data collected from the Mind Clinical Imaging Consortium (MCIC) for the study of SZ and identified significant biomarkers. These biomarkers were further used to discover genes and corresponding brain regions, which were confirmed to be significantly associated with SZ.

CTLA4 mRNA expression in blood is lower in schizophrenia, but not in affective disorders

CTL-associated antigen 4 (CTLA4) and its downstream signals compose an important mechanism that suppresses immune activity. Recent studies have shown that immune abnormalities are associated with the pathogenesis of schizophrenia (SCZ), but little research has been performed on the relevance of CTLA4 and SCZ. In the present study, we investigated the relationship between CTLA4 mRNA expression and SCZ. We examined the expression of CTLA4 mRNA in blood from patients with SCZ, bipolar disorder (BD), and major depressive disorder (MDD). We compared 50 SCZ subjects, 46 BD subjects, and 63 MDD subjects with age- and sex-matched healthy controls (HCs). Quantitative real-time PCR was performed to examine CTLA4 mRNA expression in peripheral blood using TaqMan probes. Levels of CTLA4 mRNA expression were significantly lower in patients with SCZ compared with HCs (p < 0.001), whereas no differences were found between affective disorder (BD and MDD) patients and HCs. We analyzed the correlation between CTLA4 mRNA expression and clinical parameters, but no significant correlation was found. The expression of CTLA4 mRNA was lower specifically in SCZ, suggesting that abnormal CTLA4 expression may be particularly related to the pathogenesis of SCZ. CTLA4 may be a useful diagnostic marker and a potential therapeutic target of SCZ.

Single-nucleotide Polymorphism of CTLA-4 (rs5742909) in Correlation with Schizophrenia Risk Factor

Background

Cytotoxic T protein lymphocyte antigen-4 (CTLA-4) plays a key role in regulating the T-cell system, where occurrence of disturbances in the system seen by imbalances in Th1 and Th2 levels is believed to be one of the etiologies of schizophrenia. Single-nucleotide polymorphisms (SNPs) at rs5742909 in the CTLA-4 gene (C→T) might affect the expression level of CTLA-4 protein.

Aims and Objectives

The aim of this study was to determine the genotype distribution of the CTLA-4 gene (rs5742909) in patients with schizophrenia at Rumah Sakit Jiwa Prof. Dr. Soerojo Magelang and identify the correlation of these genetic polymorphisms as the risk factors of schizophrenia.

Materials and Methods

This research was conducted through the stage of submitting ethical approval, primer design, chromosomal DNA isolation, optimization of polymerase chain reaction conditions, and data analysis.

Results

Based on the results of the study, the CC genotype was shown in 36 patients (78.26%), TT genotype in 10 patients (21.73%), and no TT genotypes. However, statistical analysis using Fisher's exact and binary logistic regression statistical test showed no significant relationship between genetic polymorphism of the CTLA-4 rs5742909 against risk factors for schizophrenia (P = 0.05; α = 5%).

Conclusion

SNP at rs5742909, C-to-T-allele transition, was not significant associated with the risk of schizophrenia.

Polymorphisms in immune-inflammatory response genes and the risk of deficit schizophrenia

Polymorphisms in immune-inflammatory response genes are believed to impact schizophrenia susceptibility. However, it remains unknown whether immunogenetic factors play a role in the etiology of deficit schizophrenia (D-SCZ). Therefore, we genotyped four polymorphisms in genes encoding two immune system regulatory proteins (CTLA-4 rs231775 and CD28 rs3116496), interleukin-6 (IL6 rs1800795) and transforming growth factor-β (TGFB1 rs1800470) in 513 schizophrenia patients and 374 controls. The CD28 rs3116496-CC genotype and C-allele were significantly more frequent in the whole group of patients and D-SCZ patients compared to controls. Our results indicate that the CD28 rs3116496 polymorphism might impact the risk of schizophrenia, especially D-SCZ.

Currently recognized genes for schizophrenia: High-resolution chromosome ideogram representation

A large body of genetic data from schizophrenia-related research has identified an assortment of genes and disturbed pathways supporting involvement of complex genetic components for schizophrenia spectrum and other psychotic disorders. Advances in genetic technology and expanding studies with searchable genomic databases have led to multiple published reports, allowing us to compile a master list of known, clinically relevant, or susceptibility genes contributing to schizophrenia. We searched key words related to schizophrenia and genetics from peer-reviewed medical literature sources, authoritative public access psychiatric websites and genomic databases dedicated to gene discovery and characterization of schizophrenia. Our list of 560 genes were arranged in alphabetical order in tabular form with gene symbols placed on high-resolution human chromosome ideograms. Genome wide pathway analysis using GeneAnalytics was carried out on the resulting list of genes to assess the underlying genetic architecture for schizophrenia. Recognized genes of clinical relevance, susceptibility or causation impact a broad range of biological pathways and mechanisms including ion channels (e.g., CACNA1B, CACNA1C, CACNA1H), metabolism (e.g., CYP1A2, CYP2C19, CYP2D6), multiple targets of neurotransmitter pathways impacting dopamine, GABA, glutamate, and serotonin function, brain development (e.g., NRG1, RELN), signaling peptides (e.g., PIK3CA, PIK4CA) and immune function (e.g., HLA-DRB1, HLA-DQA1) and interleukins (e.g., IL1A, IL10, IL6). This summary will enable clinical and laboratory geneticists, genetic counselors, and other clinicians to access convenient pictorial images of the distribution and location of contributing genes to inform diagnosis and gene-based treatment as well as provide risk estimates for genetic counseling of families with affected relatives.