Pathway-based association analysis of genome-wide screening data suggest that genes associated with the gamma-aminobutyric acid receptor signaling pathway are involved in neuroleptic-induced, treatment-resistant tardive dyskinesia

Association of two DRD2 gene polymorphisms with acute and tardive antipsychotic-induced movement disorders in young Caucasian patients

RATIONALE

Pharmacogenetic studies on antipsychotic-induced movement disorders (MD) in schizophrenia so far have focused mainly on tardive dyskinesia. Only a few examined the more acute antipsychotic-induced MD such as parkinsonism and akathisia. Notably, all MD relate to deregulation of the dopamine system.

OBJECTIVE

This study aimed to replicate previously reported associations in candidate genes for acute and tardive antipsychotic-induced MD in a young Caucasian sample.

METHODS

In 402 patients (median age 26 years), a total of 13 polymorphisms were genotyped in eight dopamine-related candidate genes selected a priori from the literature (regarding dopamine and serotonin receptors, dopamine degradation, and free radicals scavenging enzymes pathways).

RESULTS

Patients with MD used on average a higher haloperidol dose equivalent when compared to those without MD. The prevalence of MD was high and did not differ between first- and second-generation antipsychotics. Significant associations were found between (a) the TaqI_D polymorphism and akathisia (OR = 2.3, p = 0.001 for each extra C-allele) and (b) the -141C polymorphism and tardive dyskinesia (OR = 0.20, p = 0.001 for each extra Del allele). The other polymorphisms were not significantly associated with an MD.

CONCLUSIONS

Two associations were found between genetic variation TaqI_D and the -141C polymorphisms in the DRD2 gene and antipsychotic-induced MD; one with acute akathisia and one with tardive dyskinesia. These were previously reported to be associated with tardive dyskinesia and acute parkinsonism, respectively. These results suggest that the contribution of these DRD2 gene variants in the vulnerability of antipsychotic-induced MD takes place in a more general or pleiotropic way.

The pharmacogenetics of antipsychotic treatment

There is substantial interindividual variability in the effects of treatment with antipsychotic drugs not only in the emergence of adverse effects but also in symptom response. It is becoming increasingly clear that much of this variability is due to genetic factors; pharmacogenetics is the study of those factors, with the eventual goal of identifying genetic predictors of treatment effects. There have been many reported associations of single nucleotide polymorphisms (SNPs) in candidate genes with the consequences of antipsychotic drug treatment. Thus variations in dopaminergic and serotoninergic genes may influence positive and negative symptom outcome, respectively. Among the adverse effects, tardive dyskinesia and weight gain have been the most studied, with some consistent associations of functional SNPs in genes relating to pharmacological mechanisms. Technological advance has permitted large-scale genome-wide association studies (GWAS), but as yet there are few reports that replicate prior findings with candidate genes. Nevertheless, GWAS may identify associations which provide new clues relating to underlying mechanisms.

Pharmacogenetics of response to antipsychotics in patients with schizophrenia

This review presents the findings of pharmacogenetic studies exploring the influence of gene variants on antipsychotic treatment response, in terms of both symptom improvement and adverse effects, in patients with schizophrenia. Despite numerous studies in the field, replicating findings across different cohorts that include subjects of different ethnic groups has been challenging. It is clear that non-genetic factors have an important contribution to antipsychotic treatment response. Differing clinical, demographic and environmental characteristics of the cohorts studied have added substantial complexity to the interpretation of the positive and negative findings of many studies. Pharmacogenomic genome-wide investigations are beginning to yield interesting data although they have failed to replicate the most robust findings of candidate gene studies, and are limited by the sample size, especially given the need for studying homogeneous cohorts. Most of the studies conducted on cohorts treated with single antipsychotics have investigated clozapine, olanzapine or risperidone response. These studies have provided some of the most replicated associations with treatment efficacy. Serotonergic system gene variants are significantly associated with the efficacy of clozapine and risperidone, but may have less influence on the efficacy of olanzapine. Dopamine D3 receptor polymorphisms have been more strongly associated with the efficacy of clozapine and olanzapine, and D2 genetic variants with the efficacy of risperidone. Serotonin influences the control of feeding behaviour and has been hypothesized to have a role in the development of antipsychotic-induced weight gain. Numerous studies have linked the serotonin receptor 2C (5-HT2C) -759-C/T polymorphism with weight gain. The leptin gene variant, -2548-G/A, has also been associated with weight gain in several studies. Pharmacogenetic studies support the role of cytochrome P450 enzymes and dopamine receptor variants in the development of antipsychotic-induced movement disorders, with a contribution of serotonergic receptors and other gene variants implicated in the mechanism of action of antipsychotics. Clozapine-induced agranulocytosis has been associated with polymorphisms in the major histocompatibility complex gene (HLA).

A network-based approach to prioritize results from genome-wide association studies

Genome-wide association studies (GWAS) are a valuable approach to understanding the genetic basis of complex traits. One of the challenges of GWAS is the translation of genetic association results into biological hypotheses suitable for further investigation in the laboratory. To address this challenge, we introduce Network Interface Miner for Multigenic Interactions (NIMMI), a network-based method that combines GWAS data with human protein-protein interaction data (PPI). NIMMI builds biological networks weighted by connectivity, which is estimated by use of a modification of the Google PageRank algorithm. These weights are then combined with genetic association p-values derived from GWAS, producing what we call ‘trait prioritized sub-networks.’ As a proof of principle, NIMMI was tested on three GWAS datasets previously analyzed for height, a classical polygenic trait. Despite differences in sample size and ancestry, NIMMI captured 95% of the known height associated genes within the top 20% of ranked sub-networks, far better than what could be achieved by a single-locus approach. The top 2% of NIMMI height-prioritized sub-networks were significantly enriched for genes involved in transcription, signal transduction, transport, and gene expression, as well as nucleic acid, phosphate, protein, and zinc metabolism. All of these sub-networks were ranked near the top across all three height GWAS datasets we tested. We also tested NIMMI on a categorical phenotype, Crohn’s disease. NIMMI prioritized sub-networks involved in B- and T-cell receptor, chemokine, interleukin, and other pathways consistent with the known autoimmune nature of Crohn’s disease. NIMMI is a simple, user-friendly, open-source software tool that efficiently combines genetic association data with biological networks, translating GWAS findings into biological hypotheses.

Gene set analysis and network analysis for genome-wide association studies

The application of high-throughput genotyping in humans has yielded numerous insights into the genetic basis of human phenotypes and an unprecedented amount of genetic data. Genome-wide association studies (GWAS) have increased in number in recent years, but the variants that have been found have generally explained only a tiny proportion of the estimated genetic contribution to phenotypic variation. This article summarizes the progress made in the development of gene set analysis (GSA) and network analysis for GWAS was a way to identify the underlying molecular processes of human phenotypes. It also highlights some promising findings and indicates future directions that may greatly enhance the analysis and interpretation of GWAS.

DPP6 as a candidate gene for neuroleptic-induced tardive dyskinesia

We implemented a two-step approach to detect potential predictor gene variants for neuroleptic-induced tardive dyskinesia (TD) in schizophrenic subjects. First, we screened associations by using a genome-wide (Illumina HumanHapCNV370) SNP array in 61 Japanese schizophrenia patients with treatment-resistant TD and 61 Japanese schizophrenia patients without TD. Next, we performed a replication analysis in 36 treatment-resistant TD and 138 non-TD subjects. An association of an SNP in the DPP6 (dipeptidyl peptidase-like protein-6) gene, rs6977820, the most promising association identified by the screen, was significant in the replication sample (allelic P=0.008 in the replication sample, allelic P=4.6 × 10(-6), odds ratio 2.32 in the combined sample). The SNP is located in intron-1 of the DPP6 gene and the risk allele was associated with decreased DPP6 gene expression in the human postmortem prefrontal cortex. Chronic administration of haloperidol increased Dpp6 expression in mouse brains. DPP6 is an auxiliary subunit of Kv4 and regulates the properties of Kv4, which regulates the activity of dopaminergic neurons. The findings of this study indicate that an altered response of Kv4/DPP6 to long-term neuroleptic administration is involved in neuroleptic-induced TD.

Support for association of HSPG2 with tardive dyskinesia in Caucasian populations

Tardive dyskinesia (TD) is a severe adverse effect of chronic antipsychotic drug treatment. In addition to clinical risk factors, TD susceptibility is influenced by genetic predisposition. Recently, Syu et al. (2010) reported a genome-wide association screening of TD in Japanese schizophrenia patients. The best result was association of single-nucleotide polymorphism (SNP) rs2445142 in the HSPG2 (heparan sulfate proteoglycan 2) gene with TD. In the present study, we report a replication study of the five top Japanese TD-associated SNPs in two Caucasian TD samples. Applying logistic regression and controlling for relevant clinical risk factors, we were able to replicate the association of HSPG2 SNP rs2445142 with TD in a prospective study sample of 179 Americans of European origin by performing a secondary analysis of the CATIE (Clinical Antipsychotic Trials of Intervention Effectiveness) genome-wide association study data set, and using a perfect proxy surrogate marker (rs878949; P = 0.039). An association of the 'G' risk allele of HSPG2 SNP rs2445142 with TD was also shown in a sample of Jewish Israeli schizophrenia patients (retrospective, cross-sectional design; P = 0.03). Although the associations were only nominally significant, the findings provide further support for the possible involvement of HSPG2 in susceptibility to TD.

A dimension reduction approach for modeling multi-locus interaction in case-control studies

Studying one locus or one single nucleotide polymorphism (SNP) at a time may not be sufficient to understand complex diseases because they are unlikely to result from the effect of only one SNP. Each SNP alone may have little or no effect on the risk of the disease, but together they may increase the risk substantially. Analyses focusing on individual SNPs ignore the possibility of interaction among SNPs. In this paper, we propose a parsimonious model to assess the joint effect of a group of SNPs in a case-control study. The model implements a data reduction strategy within a likelihood framework and uses a test to assess the statistical significance of the effect of the group of SNPs on the binary trait. The primary advantage of the proposed approach is that the dimension reduction technique produces a test statistic with degrees of freedom significantly lower than a multiple logistic regression with only main effects of the SNPs, and our parsimonious model can incorporate the possibility of interaction among the SNPs. Moreover, the proposed approach estimates the direction of association of each SNP with the disease and provides an estimate of the average effect of the group of SNPs positively and negatively associated with the disease in the given SNP set. We illustrate the proposed model on simulated and real data, and compare its performance with a few other existing approaches. Our proposed approach appeared to outperform the other approaches for independent SNPs in our simulation studies.

Genome-wide association studies in pharmacogenomics

Genome-wide association (GWA) studies for pharmacogenomics-related traits are increasingly being performed to identify loci that affect either drug response or susceptibility to adverse drug reactions. Until now, only the largest effects have been detected, partly because of the challenges of obtaining large numbers of cases for pharmacogenomic studies. Since 2007, a range of pharmacogenomics GWA studies have been published that have identified several interesting and novel associations between drug responses or reactions and clinically relevant loci, showing the value of this approach.

Genetics of tardive dyskinesia

Tardive dyskinesia (TD) is one of the most serious adverse side effects of antipsychotic drugs and is an important topic of pharmacogenetic studies. Since there is a genetic susceptibility for developing this adverse reaction, and given that it is hard to predict its development prior to or during the early period of medication, the genetic study of TD is a promising research topic that has a direct clinical application. Moreover, such studies would improve our understanding of the genetic mechanism(s) underlying abnormal dyskinetic movement. A substantial number of case-control association studies of TD have been performed, with numbers of studies focusing on the genes involved in antipsychotic drug metabolism, such as those for cytochrome P450 (CYP) and oxidative stress related genes as well as various neurotransmitter related genes. These studies have produced relatively consistent though controversial findings for certain polymorphisms such as CYP2D6*10, DRD2 Taq1A, DRD3 Ser9Gly, HTR2A T102C, and MnSOD Ala9Val. Moreover, the application of the genome-wide association study (GWAS) to the susceptibility of TD has revealed certain associated genes that previously were never considered to be associated with TD, such as the rs7669317 on 4q24, GLI2 gene, GABA pathway genes, and HSPG2 gene. Although a substantial number of genetic studies have investigated TD, many of the positive findings have not been replicated or are inconsistent, which could be due to differences in study design, sample size, and/or subject ethnicity. We expect that more refined research will be performed in the future to resolve these issues, which will then enable the genetic prediction of TD and clinical application thereof.

An integrative method for scoring candidate genes from association studies: application to warfarin dosing

Background

A key challenge in pharmacogenomics is the identification of genes whose variants contribute to drug response phenotypes, which can include severe adverse effects. Pharmacogenomics GWAS attempt to elucidate genotypes predictive of drug response. However, the size of these studies has severely limited their power and potential application. We propose a novel knowledge integration and SNP aggregation approach for identifying genes impacting drug response. Our SNP aggregation method characterizes the degree to which uncommon alleles of a gene are associated with drug response. We first use pre-existing knowledge sources to rank pharmacogenes by their likelihood to affect drug response. We then define a summary score for each gene based on allele frequencies and train linear and logistic regression classifiers to predict drug response phenotypes.

Results

We applied our method to a published warfarin GWAS data set comprising 181 individuals. We find that our method can increase the power of the GWAS to identify both VKORC1 and CYP2C9 as warfarin pharmacogenes, where the original analysis had only identified VKORC1. Additionally, we find that our method can be used to discriminate between low-dose (AUROC=0.886) and high-dose (AUROC=0.764) responders.

Conclusions

Our method offers a new route for candidate pharmacogene discovery from pharmacogenomics GWAS, and serves as a foundation for future work in methods for predictive pharmacogenomics.

mRNA and protein levels for GABAAalpha4, alpha5, beta1 and GABABR1 receptors are altered in brains from subjects with autism

We have shown altered expression of gamma-aminobutyric acid A (GABA(A)) and gamma-aminobutyric acid B (GABA(B)) receptors in the brains of subjects with autism. In the current study, we sought to verify our western blotting data for GABBR1 via qRT-PCR and to expand our previous work to measure mRNA and protein levels of 3 GABA(A) subunits previously associated with autism (GABRalpha4; GABRalpha5; GABRbeta1). Three GABA receptor subunits demonstrated mRNA and protein level concordance in superior frontal cortex (GABRalpha4, GABRalpha5, GABRbeta1) and one demonstrated concordance in cerebellum (GABBetaR1). These results provide further evidence of impairment of GABAergic signaling in autism.

Association of the HSPG2 gene with neuroleptic-induced tardive dyskinesia

Tardive dyskinesia (TD) is characterized by repetitive, involuntary, and purposeless movements that develop in patients treated with long-term dopaminergic antagonists, usually antipsychotics. By a genome-wide association screening of TD in 50 Japanese schizophrenia patients with treatment-resistant TD and 50 Japanese schizophrenia patients without TD (non-TD group) and subsequent confirmation in independent samples of 36 treatment-resistant TD and 136 non-TD subjects, we identified association of a single nucleotide polymorphism, rs2445142, (allelic p=2 x 10(-5)) in the HSPG2 (heparan sulfate proteoglycan 2, perlecan) gene with TD. The risk allele was significantly associated with higher expression of HSPG2 in postmortem human prefrontal brain (p<0.01). Administration of daily injection of haloperidol (HDL) for 50 weeks significantly reduced Hspg2 expression in mouse brains (p<0.001). Vacuous chewing movements (VCMs) induced by 7-week injection of haloperidol-reserpine were significantly infrequent in adult Hspg2 hetero-knockout mice compared with wild-type littermates (p<0.001). Treatment by the acetylcholinesterase inhibitor, physostigmine, was significantly effective for reduction of VCMs in wild-type mice but not in Hspg2 hetero-knockout mice. These findings suggest that the HSPG2 gene is involved in neuroleptic-induced TD and higher expression of HSPG2, probably even after antipsychotic treatment, and may be associated with TD susceptibility.

Expectations, validity, and reality in pharmacogenetics

In this review, we discuss the potential expectations, validity, predictive ability, and reality of pharmacogenetics in (1) titration of medication dose, (2) prediction of intended (efficacy) drug response, and (3) dose prediction of unintended (adverse) drug response. We expound on what these potential genetic predictors tell us and, more importantly, what they cannot tell us. Although pharmacogenetic markers have been hailed as promising tools, these proclamations are based mainly on associations rather than their evaluation as predictors. To put the expectations of the promise of pharmacogenetics in a realistic perspective, we review three examples. First, warfarin pharmacogenetics, wherein although the validity of the genetic variant dose is established and there is a validity of genetic variant-hemorrhage association, the clinical utility of testing is not clear. Second, the strong and clinically relevant HLA-Stevens-Johnson syndrome/toxic epidermal necrolysis association highlights the role of ethnicity. Third, the influence of CYP2D6 on tamoxifen efficacy, a model candidate with potential clinical utility but unclear validity. These examples highlight both the challenges and opportunities of pharmacogenomics. First, establishing a valid association between a genetic variation and drug response; second, doing so for a clinically meaningful outcome; and third, providing solid evidence or rationale for improvement in patient outcomes compared with current standard of care.

Genetic study of BDNF, DRD3, and their interaction in tardive dyskinesia

Tardive dyskinesia (TD) is a neuroleptic-induced movement disorder. Its pathophysiology is unclear. The most consistent genetic findings have shown an association with the Ser9Gly polymorphism of the DRD3 gene. However, only few polymorphisms within DRD3 has been tested, and a comprehensive examination of DRD3 in TD is still lacking. Further, brain-derived neurotrophic factor (BDNF), a neuronal growth and survival peptide, regulates DRD3 expression and may be involved in the neuronal degeneration observed in TD. In the present study, we investigated 15 tag DRD3 polymorphisms and four tag BDNF polymorphisms for association with TD in our sample of Caucasian schizophrenia patients (N=171). While BDNF markers showed no association, a haplotype containing rs3732782, rs905568, and rs7620754 in the 5' region of DRD3 was associated with TD diagnosis (p[10,000 permutations]=0.007). We also found evidence of interaction between BDNF and DRD3 polymorphisms. Further studies are needed to confirm these findings.

Genetic underpinnings of tardive dyskinesia: passing the baton to pharmacogenetics

Manifestation of tardive dyskinesia (TD) among schizophrenia subjects on long-term antipsychotic treatment with typical drugs has been a clinical concern. Despite its association with extrapyramidal symptoms, typical drugs are still routinely prescribed globally though marginally superior atypical drugs have long been available. The genetic component in the etiology of TD is well documented. Search for these determinants has led to a few consensus associations of CYP2D6 *10, CYP1A2*1F, DRD2 Taq1A (rs1800497), DRD3 Ser9Gly (rs6280) and MnSOD Ala9Val (rs4880) variants with TD. However, translation of these observations into the clinic has not been achieved so far. This review discusses the salient features of TD etiopathology, current status of TD genetics, interactions between genetic and nongenetic factors, some major drawbacks, challenges and expected focus in TD research over the next decade, with emphasis on pharmacogenetics.

Pathways-based analyses of whole-genome association study data in bipolar disorder reveal genes mediating ion channel activity and synaptic neurotransmission

Despite known heritability, the complex genetic architecture of bipolar disorder (likely including trait, locus and allelic heterogeneity, as well as genetic interactions) has confounded genetic discovery for many years. Even modern day whole genome association studies (WGAS) using over half a million common SNPs have implicated only a handful of genes at the genomewide level. Temporally coincident with this series of WGAS, a host of pathways-based analyses (PBAs) have emerged as novel computational approaches in the examination of large-scale datasets, but thus far rarely have been applied to WGAS data in psychiatric disorders. Here, we report a series of PBAs conducted using exploratory visual analysis, an analytic and visualization software tool for examining genomic data, to examine results from the National Institutes of Mental Health and Wellcome-Trust Case Control Consortium WGAS in bipolar disorder. Consistent with a host of prior linkage findings, some candidate gene association studies, and recent WGAS, our strongest findings suggest involvement of ion channel structural and regulatory genes, including voltage-gated ion channels and the broader ion channel group that comprises both voltage- and ligand-gated channels. Moreover, we found only modest overlap in the particular genes driving the significance of these gene sets across the analyses. This observation strongly suggests that variation in ion channel genes, as a class of genes, may contribute to the susceptibility of bipolar disorder and that heterogeneity may figure prominently in the genetic architecture of this susceptibility.

Pharmacogenetics in psychiatry: are we ready for widespread clinical use?

There are high expectations about the capabilities of pharmacogenetics to tailor psychotropic treatment and "personalize" treatment. While a large number of associations, with generally small effect size, have been discovered, a "test" with widespread use and adoption is still missing. A more realistic picture, recognizing the important contribution of clinical and environmental factors toward overall clinical outcome has emerged. In this emerging view, genetic findings, if considered individually, may have limited clinical applications. Thus, in recent years, combinations of information in several genes have been used for the selection of appropriate therapeutic doses and for the prediction of agranulocytosis, hyperlipidemia, and response to antipsychotic and antidepressant medications. While these tests based on multiple genes show greater predictive ability than individual allele tests, their net impact on clinical consequence and costs is limited, thus leading to limited penetration into widespread clinical use. As one looks at other branches of medicine, there are successful examples of pharmacogenetic tests guiding treatment, and thus, it is reasonable to hope that with the incorporation of clinical and environmental information and the identification of new genes drawn from genome-wide analysis, will improve the predictive utility of these tests leading to their increased use by clinicians.

GABA(A) receptor downregulation in brains of subjects with autism

Gamma-aminobutyric acid A (GABA(A)) receptors are ligand-gated ion channels responsible for mediation of fast inhibitory action of GABA in the brain. Preliminary reports have demonstrated altered expression of GABA receptors in the brains of subjects with autism suggesting GABA/glutamate system dysregulation. We investigated the expression of four GABA(A) receptor subunits and observed significant reductions in GABRA1, GABRA2, GABRA3, and GABRB3 in parietal cortex (Brodmann's Area 40 (BA40)), while GABRA1 and GABRB3 were significantly altered in cerebellum, and GABRA1 was significantly altered in superior frontal cortex (BA9). The presence of seizure disorder did not have a significant impact on GABA(A) receptor subunit expression in the three brain areas. Our results demonstrate that GABA(A) receptors are reduced in three brain regions that have previously been implicated in the pathogenesis of autism, suggesting widespread GABAergic dysfunction in the brains of subjects with autism.