Evaluation of a susceptibility gene for schizophrenia: genotype based meta-analysis of RGS4 polymorphisms from thirteen independent samples.

Department of Human Genetics, University of Pittsburgh, Pittsburgh, Pennsylvania 15213, USA.
Biological Psychiatry (Impact Factor: 9.25). 08/2006; 60(2):152-62. DOI: 10.1016/j.biopsych.2006.02.015
Source: PubMed

ABSTRACT Associations between schizophrenia (SCZ) and polymorphisms at the regulator of G-protein signaling 4 (RGS4) gene have been reported (single nucleotide polymorphisms [SNPs] 1, 4, 7, and 18). Yet, similar to other SCZ candidate genes, studies have been inconsistent with respect to the associated alleles.
In an effort to resolve the role for RGS4 in SCZ susceptibility, we undertook a genotype-based meta-analysis using both published and unpublished family-based and case-control samples (total n = 13,807).
The family-based dataset consisted of 10 samples (2160 families). Significant associations with individual SNPs/haplotypes were not observed. In contrast, global analysis revealed significant transmission distortion (p = .0009). Specifically, analyses suggested overtransmission of two common haplotypes that account for the vast majority of all haplotypes. Separate analyses of 3486 cases and 3755 control samples (eight samples) detected a significant association with SNP 4 (p = .01). Individual haplotype analyses were not significant, but evaluation of test statistics from individual samples suggested significant associations.
Our collaborative meta-analysis represents one of the largest SCZ association studies to date. No individual risk factor arose from our analyses, but interpretation of these results is not straightforward. Our analyses suggest risk due to at least two common haplotypes in the presence of heterogeneity. Similar analysis for other putative susceptibility genes is warranted.

  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Meta-analysis is a popular methodology in several fields of medical research, including genetic association studies. However, the methods used for meta-analysis of association studies that report haplotypes have not been studied in detail. In this work, methods for performing meta-analysis of haplotype association studies are summarized, compared and presented in a unified framework along with an empirical evaluation of the literature. We present multivariate methods that use summary-based data as well as methods that use binary and count data in a generalized linear mixed model framework (logistic regression, multinomial regression and Poisson regression). The methods presented here avoid the inflation of the type I error rate that could be the result of the traditional approach of comparing a haplotype against the remaining ones, whereas, they can be fitted using standard software. Moreover, formal global tests are presented for assessing the statistical significance of the overall association. Although the methods presented here assume that the haplotypes are directly observed, they can be easily extended to allow for such an uncertainty by weighting the haplotypes by their probability. An empirical evaluation of the published literature and a comparison against the meta-analyses that use single nucleotide polymorphisms, suggests that the studies reporting meta-analysis of haplotypes contain approximately half of the included studies and produce significant results twice more often. We show that this excess of statistically significant results, stems from the sub-optimal method of analysis used and, in approximately half of the cases, the statistical significance is refuted if the data are properly re-analyzed. Illustrative examples of code are given in Stata and it is anticipated that the methods developed in this work will be widely applied in the meta-analysis of haplotype association studies.
    BMC Genetics 01/2011; 12:8. · 2.81 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: J. Neurochem. (2012) 10.1111/j.1471-4159.2012.07780.x ABSTRACT: Regulator of G-protein signaling-10 (RGS10) is a GTPase activating protein for Gα(i/q/z) subunits that is highly expressed in the immune system and in a broad range of brain regions including the hippocampus, striatum, dorsal raphe, and ventral midbrain. Previously, we reported that RGS10-null mice display increased vulnerability to chronic systemic inflammation-induced degeneration of nigral dopaminergic (DA) neurons. Given that RGS10 is expressed in DA neurons, we investigated the extent to which RGS10 regulates cell survival under conditions of inflammatory stress. Because of the inherent limitations associated with use of primary DA neurons for biochemical analyses, we employed a well-characterized ventral mesencephalon DA neuroblastoma cell line (MN9D) for our studies. We found that stable over-expression of RGS10 rendered them resistant to TNF-induced cytotoxicity; whereas MN9D cells expressing mutant RGS10-S168A (which is resistant to phosphorylation by protein kinase A at a serine residue that promotes its nuclear translocation) showed similar sensitivity to TNF as the parental MN9D cells. Using biochemical and pharmacologic approaches, we identified protein kinase A and the downstream phospho-cAMP response element-binding signaling pathway (and ruled out ERK 1/2, JNK, and NFkB) as key mediators of the neuroprotective effect of RGS10 against inflammatory stress.
    Journal of Neurochemistry 05/2012; · 3.97 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Schizophrenia is a complex disorder, where family, twin and adoption studies have been demonstrating a high heritability of the disease and that this disease is not simply defined by several major genes but rather evolves from addition or potentiation of a specific cluster of genes, which subsequently determines the genetic vulnerability of an individual. Linkage and association studies suggest that a genetic vulnerablility, is not forcefully leading to the disease since triggering factors and environmental influences, i.e. birth complications, drug abuse, urban background or time of birth have been identified. This has lead to the assumption that schizophrenia is not only a genetically defined static disorder but a dynamic process leading to dysregulation of multiple pathways. There are several different hypothesis based on several facets of the disease, some of them due to the relatively well-known mechanisms of therapeutic agents. The most widely considered neurodevelopmental hypothesis of schizophrenia integrates environmental influences and causative genes. The dopamine hypothesis of schizophrenia is based on the fact that all common treatments involve antidopaminergic mechanisms and genes such as DRD2, DRD3, DARPP-32, BDNF or COMT are closely related to dopaminergic system functioning. The glutamatergic hypothesis of schizophrenia lead recently to a first successful mGlu2/3 receptor agonistic drug and is underpinned by significant findings in genes regulating the glutamatergic system (SLC1A6, SLC1A2 GRIN1, GRIN2A, GRIA1, NRG1, ErbB4, DTNBP1, DAAO, G72/30, GRM3). Correspondingly, GABA has been proposed to modulate the pathophysiology of the disease which is represented by the involvement of genes like GABRA1, GABRP, GABRA6 and Reelin. Moreover, several genes implicating immune, signaling and networking deficits have been reported to be involved in the disease, i.e. DISC1, RGS4, PRODH, DGCR6, ZDHHC8, DGCR2, Akt, CREB, IL-1B, IL-1RN, IL-10, IL-1B. However, molecular findings suggest that a complex interplay between receptors, kinases, proteins and hormones is involved in schizophrenia. In a unifying hypothesis, different cascades merge into another that ultimately lead to the development of symptoms adherent to schizophrenic disorders.
    Cellular Physiology and Biochemistry 02/2007; 20(6):687-702. · 3.42 Impact Factor


Available from
Jun 4, 2014