Association between RGS4 gene polymorphisms and schizophrenia

Abstract Background: Schizophrenia is a complex brain disorder, the pathogenesis of which remains unclear. Regulator of G-protein signaling 4 is regarded as a candidate gene for schizophrenia risk. The association between the regulator of G-protein signaling 4 gene and the risk of schizophrenia is complicated and controversial, thus, an updated meta-analysis is needed. Methods: A search strategy using Medical Subject Headings was developed in English (PubMed, SZGene) and Chinese (CNKI, Wanfang, and Weipu) databases. Inclusion and exclusion criteria were used to screen for eligible studies. Parameters, such as P value of Hardy–Weinberg equilibrium, odds ratios, 95% confidence intervals, P values of association, heterogeneity (Ph), and publication bias, were analyzed by the Stata software using a random effects model. Subgroup analyses were performed to detect heterogeneity. Results: There were 15 articles regarding rs10917670 (8046 cases and 8837 controls), 16 regarding rs951436 (8990 cases and 10,568 controls), 15 regarding rs951439 (7995 cases and 8646 controls), 15 regarding rs2661319 (8320 cases and 9440 controls), and 4 regarding rs10759 (2752 cases and 2866 controls). The frequencies of rs10917670 and rs951439 were not significantly different between the case and control groups (P > .05). As shown by the East Asian and hospital-based subgroup analyses, the genotype TT of rs951436 might be related to the risk of schizophrenia. The genotypes CC + CT of rs2661319 and CC + CA of rs10759 were statistically different between the 2 groups, and the East Asian population contributed to these differences. Conclusion: The genotypes CC + CT of rs2661319 and CC + CA of rs10759 might be associated with the risk of schizophrenia.


Introduction
Schizophrenia is a complex brain disorder, the pathogenesis of which remains unclear. [1] It has been shown that schizophrenia is caused by both genetic and environmental factors, [2] and genetic factors play an important role to the etiology of schizophrenia. [3,4] Regulator of G-protein signaling proteins control the duration and timing of intracellular signaling of many G-protein coupled receptors. The major mechanism by which regulator of G-protein signaling proteins negatively regulate G proteins is via their GTPase accelerating activity. [5] Regulator of G-protein signaling 4 (RGS4) is known to play a fundamental role in neurotransmission and neuronal differentiation, in addition to axonogenesis during embryogenesis. [6] RGS4 regulation of G-protein activity, may inhibit the interaction between neurotransmitters and their receptors, leading to dysfunction of glutamatergic neurotransmission, [7] which is classically related to the etiology of psychotic disorders. [8] Schwarz et al [6] suggested that the RGS4 gene, localized to chromosome 1q23, might be an important part of a larger biological system contributing to schizophrenia risk. Mirnics et al [9] showed that RGS4 expression was down regulated in schizophrenia. [10,11] However, the association between RGS4 and the risk of schizophrenia remains controversial. [12][13][14][15] Meta-analysis is a useful tool for the detection of disease-gene relationships. [16] In the Chinese Han population, 1 meta-analysis showed no association between the RGS4 gene and the risk of schizophrenia [15] ; however, in another meta-analysis, the SNP, rs951436, was found to be associated with the risk of schizophrenia. [17] Therefore, the association between RGS4 and the risk of schizophrenia remains complicated and Ethics approval was not necessary. It was because that the study was a metaanalysis and date in it was collected from other published articles.
controversial. [17][18][19] Additional articles have since been published; thus, an updated meta-analysis is needed. Here, we conducted an updated meta-analysis to detect the association between RGS4 gene polymorphisms and the risk of schizophrenia.

Literature search
The systematic review and meta-analysis were conducted in adherence to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. [20] A search was performed in English (PubMed, SZGene) and Chinese (CNKI, Wanfang, and Weipu) databases with the following keywords: "the regulator of G-protein signaling 4" or "RGS4", and "schizophrenia". References to related articles were also reviewed for further data.

Identification and eligibility of relevant studies
The inclusion criteria were: studies with a case-control design; involvement of patients with schizophrenia; available allele or genotype frequencies; and published before May 12, 2020. The authors were emailed if there was no genotype frequency mentioned in the article. The exclusion criteria were: familybased studies; no control group data; no detailed genotype frequency data after emailing the authors; and duplicate samples. [21] Information regarding the author, year, country, ethnicity, controls source, mean age of the control group, number of samples, diagnostic criteria, gender index the of cases and controls, and genotypes of the cases and controls were collected.

Statistical analysis
The meta-analysis was conducted using Stata version 10.0 (Stata Corp., College Station, TX). In the control group, the P value of Hardy-Weinberg equilibrium was calculated. Parameters, such as the odds ratios (ORs), 95% confidence intervals (CIs), and P values of association (P z ), were calculated to detect the association in 5 genetic models, [22] using the random effects model. [21,23] The heterogeneity of the studies (P h ) was determined by Cochran chi-square-based Q-statistic test. To assess the heterogeneity, subgroup analyses by ethnicity and control source were performed. [24] The studies were classified by control source into community-based (participants from the general population) and hospital-based (participants from a hospital) groups. [25] The Egger test was conducted to detect the publication bias, which could be visualized using a funnel plot. To assess the impact of each study on the pooled results, sensitivity analysis was performed by removing single studies in turn. The power was calculated using the PS program. [26] The threshold for statistical significance was P < .05 in all tests.

3.2.3.
There was no association between rs951439 and the risk of schizophrenia. To evaluate the relationship between rs951439 and the risk of schizophrenia, 7995 cases and 8646 controls were included in the pooled and subgroup analyses (see Table S3, Supplemental Digital Content, http://links.lww.com/ MD2/A638, which illustrated genotype distribution and allele frequency of rs951439). Detailed genotype frequencies were not available in [43] ; thus, these data were only included in the allele contrast. No relationship between rs951439 and the risk of schizophrenia was detected in the pooled analysis (P z = .414, OR = 1.036, 95% CI = 0.952-1.128) using the dominant model ( Fig. 4) or in the subgroup analyses by ethnicity and control source. No significant heterogeneity was observed in the pooled or subgroup analyses.

Rs2661319 might be a risk factor for schizophrenia.
Pooled and subgroup analyses of 8320 cases and 9440 controls were performed (see Table S4, Supplemental Digital Content, http://links.lww.com/MD2/A639, which illustrated genotype distribution and allele frequency of rs2661319). Of the 5 genetic models, significant differences were detected when using allele contrast (C vs T, P z = .023), homozygous codominant (CC vs TT, P z = .034), dominant (CC + CT vs TT, P z = .016), and recessive (CC vs CT + TT, P z = .046). According to the dominant model (Fig. 5), the genotype CC + CT might be a risk factor for schizophrenia (P z = .016, OR = 1.087, 95% CI = 1.016-1.164). An association was detected in the East Asian subgroup analysis (P z = .035, OR = 1.13, 95% CI = 1.009-1.266), with a power of 0.694. No significant heterogeneity was observed in the pooled or subgroup analyses.
3.2.5. Genotype CC + CA of rs10759 might be a risk factor for schizophrenia. A total of 2752 cases and 2866 controls were analyzed in pooled and subgroup analyses (see Table S5, Supplemental Digital Content, http://links.lww.com/MD2/ A640, which illustrated genotype distribution and allele frequency of rs10759). Significant differences were observed in 2 of the genetic models, allele contrast (C vs A, P z = .046) and dominant (CC + CA vs AA, P z = .016). Using the random effects model, the dominant model was selected (Fig. 6). The genotype CC + CA of rs10759 was a risk factor for schizophrenia (P z = .016, OR = 1.226, 95% CI = 1.038-1.448), with a power of 0.694. An association was found in the East Asian population (P z = .012, OR = 1.482, 95% CI = 1.092-2.011). No significant heterogeneity was observed in the pooled or subgroup analyses.

Discussion
No association between rs10917670 and rs951439 and the risk of schizophrenia was detected in the present study, which was consistent with previous meta-analyses. [17][18][19] In the East Asian and hospital-based subgroup analyses, an association between the genotype TT of rs951436 and the risk of schizophrenia was found; however, this relationship was not detected in the pooled analysis. Therefore, the geographical environment, culture, lifestyle, and genetic background might affect polymorphisms. [28,31,33] It was studied that rs951436 was associated with magnetic resonance imaging measurements of functional activation and connectivity related to working memory, an intermediate phenotype of schizophrenia. [44] Moreover, Prasad et al [36] reported that rs951436 was related the volume of dorsolateral prefrontal cortex (DLPFC). But the mechanism remained unclear. Rs2661319 and rs10759 were found to be associated with the risk of schizophrenia in the present study, which was inconsistent with previous meta-analyses. It was detected by subgroup analyses that the East Asian population contributed to this association. It was previously reported that rs2661319 was related to RGS4-1 mRNA level, which was decreased in the postmortem DLPFC of schizophrenic patients. [11] Moreover, rs2661319 was demonstrated to be associated with a more severe baseline total PANSS score and the treatment effect of perphenazine. [45] The rs10759 polymorphism was suggested to increase the risk of schizophrenia by altering the binding of miRNA-124 to its target. [46] MiRNA-124 might bind to the 3 0 UTR of mRNAs containing target sites, resulting in miRNA-mediated gene silencing, translational inhibition, and induction of mRNA de-adenylation or decay. [47] The level of RGS4 might be decreased, leading to dysfunction of neurotransmission.
More relevant data were included in our meta-analysis than those in previous meta-analyses, for instance, an increased number of more SNPs (5), and databases ((PubMed and SZGene, CNKI, Wanfang, and Weipu). However, the results described herein should be interpreted with caution. First, in the present study, the East Asian population contributed to the association between the RGS4 gene and the risk of schizophrenia; however, the sample size was relatively small, and the power was low. Further articles are needed to form a representative and comprehensive conclusion. Second, family-based and functional studies were not included in the present meta-analysis. In addition, it was reported that there was an association between DLPFC volume and RGS4 genotype interacting with COMT rs4818 [48] ; thus, this association warrants further gene-gene interaction [49,50] and functional studies.

Conclusion
No association between rs10917670 and the risk of schizophrenia was found. In the East Asian and hospital-based subgroup analyses, an association between rs951436 and the risk of schizophrenia was demonstrated. No association between rs951439 and the risk of schizophrenia was detected. The genotypes CC + CT of rs2661319 and CC + CA of rs10759 might be risk factors for schizophrenia, and the East Asian population contributed to this association. Further updated gene-gene interaction and functional studies are needed.