Interaction between NOTCH4 and catechol-O-methyltransferase genotypes in schizophrenia patients with poor response to typical neuroleptics

Genetic Testing for Antipsychotic Pharmacotherapy: Bench to Bedside

There is growing research interest in learning the genetic basis of response and adverse effects with psychotropic medications, including antipsychotic drugs. However, the clinical utility of information from genetic studies is compromised by their controversial results, primarily due to relatively small effect and sample sizes. Clinical, demographic, and environmental differences in patient cohorts further explain the lack of consistent results from these genetic studies. Furthermore, the availability of psychopharmacological expertise in interpreting clinically meaningful results from genetic assays has been a challenge, one that often results in suboptimal use of genetic testing in clinical practice. These limitations explain the difficulties in the translation of psychopharmacological research in pharmacogenetics and pharmacogenomics from bench to bedside to manage increasingly treatment-refractory psychiatric disorders, especially schizophrenia. Although these shortcomings question the utility of genetic testing in the general population, the commercially available genetic assays are being increasingly utilized to optimize the effectiveness of psychotropic medications in the treatment-refractory patient population, including schizophrenia. In this context, patients with treatment-refractory schizophrenia are among of the most vulnerable patients to be exposed to the debilitating adverse effects from often irrational and high-dose antipsychotic polypharmacy without clinically meaningful benefits. The primary objective of this comprehensive review is to analyze and interpret replicated findings from the genetic studies to identify specific genetic biomarkers that could be utilized to enhance antipsychotic efficacy and tolerability in the treatment-refractory schizophrenia population.

Catechol-O-methyltransferase rs4680 and rs4818 haplotype association with treatment response to olanzapine in patients with schizophrenia

Antipsychotic drugs target primarily dopaminergic system which makes catechol-O-methyltransferase (COMT) an interesting target in studies searching for treatment response predictors in schizophrenia. The study assessed the association of the COMT rs4680 and rs4818 polymorphisms with therapeutic response to olanzapine, risperidone, clozapine or other antipsychotic medication after 8 weeks of monotherapy in patients with schizophrenia. 521 Caucasian patients with schizophrenia received a monotherapy with olanzapine (10–20 mg/day; N = 190), risperidone (3–6 mg/day; N = 99), or clozapine (100–500 mg/day; N = 102). The fourth group (N = 130) consisted of patients receiving haloperidol (3–15 mg/day), fluphenazine (4–25 mg/day) or quetiapine (50–800 mg/day). Treatment response was defined as a 50% reduction from the baseline positive and negative syndrome scale (PANSS) total and subscale scores, but also as an observed percentage reduction from the initial PANSS_0–6 total and subscale scores. Carriers of the COMT rs4680 A allele and carriers of the COMT rs4680–rs4818 C-A haplotype block had greater reduction in the PANSS total scores following olanzapine treatment, compared to carriers of the COMT rs4680 GG genotype and other COMT rs4680–rs4818 haplotypes. The COMT rs4680 A allele, and COMT rs4680–rs4818 C-A haplotype, were significantly associated with therapeutic response in patients treated with olanzapine, but not in patients treated with other antipsychotics.

Comprehensive functional annotation of susceptibility SNPs prioritized 10 genes for schizophrenia

Nearly 95% of susceptibility SNPs identified by genome-wide association studies (GWASs) are located in non-coding regions, which causes a lot of difficulty in deciphering their biological functions on disease pathogenesis. Here, we aimed to conduct a comprehensive functional annotation for all the schizophrenia susceptibility loci obtained from GWASs. Considering varieties of epigenomic regulatory elements, we annotated all 22,688 acquired susceptibility SNPs according to their genomic positions to obtain functional SNPs. The comprehensive annotation indicated that these functional SNPs are broadly involved in diverse biological processes. Histone modification enrichment showed that H3K27ac, H3K36me3, H3K4me1, and H3K4me3 were related to the development of schizophrenia. Transcription factors (TFs) prediction, methylation quantitative trait loci (meQTL) analyses, expression quantitative trait loci (eQTL) analyses, and proteomic quantitative trait loci analyses (pQTL) identified 447 target protein-coding genes. Subsequently, differential expression analyses between schizophrenia cases and controls, nervous system phenotypes from mouse models, and protein-protein interaction with known schizophrenia-related pathways and genes were carried out with our target genes. We finaly prioritized 10 target genes for schizophrenia (CACNA1C, CLU, CSNK2B, GABBR1, GRIN2A, MAPK3, NOTCH4, SRR, TNF, and SYNGAP1). Our results may serve as an encyclopedia of schizophrenia susceptibility SNPs and offer holistic guides for post-GWAS functional experiments.

Antipsychotic Drug Responsiveness and Dopamine Receptor Signaling; Old Players and New Prospects

Antipsychotic drugs targeting dopamine neurotransmission are still the principal mean of therapeutic intervention for schizophrenia. However, about one third of people do not respond to dopaminergic antipsychotics. Genome wide association studies (GWAS), have shown that multiple genetic factors play a role in schizophrenia pathophysiology. Most of these schizophrenia risk variants are not related to dopamine or antipsychotic drugs mechanism of action. Genetic factors have also been implicated in defining response to antipsychotic medication. In contrast to disease risk, variation of genes coding for molecular targets of antipsychotics have been associated with treatment response. Among genes implicated, those involved in dopamine signaling mediated by D2-class dopamine receptor, including DRD2 itself and its molecular effectors, have been implicated as key genetic predictors of response to treatments. Studies have also reported that genetic variation in genes coding for proteins that cross-talk with DRD2 at the molecular level, such as AKT1, GSK3B, Beta-catenin, and PPP2R2B are associated with response to antipsychotics. In this review we discuss the relative contribution to antipsychotic drug responsiveness of candidate genes and GWAS identified genes encoding proteins involved in dopamine responses. We also suggest that in addition of these older players, a deeper investigation of new GWAS identified schizophrenia risk genes such as FXR1 can provide new prospects that are not clearly engaged in dopamine function while being targeted by dopamine-associated signaling molecules. Overall, further examination of genes proximally or distally related to signaling mechanisms engaged by medications and associated with disease risk and/or treatment responsiveness may uncover an interface between genes involved in disease causation with those affecting disease remediation. Such a nexus would provide realistic targets for therapy and further the development of genetically personalized approaches for schizophrenia.

Risperidone ameliorates cognitive deficits, promotes hippocampal proliferation, and enhances Notch signaling in a murine model of schizophrenia

Antipsychotic agents have been reported to promote hippocampal neurogenesis and improve cognitive deficits; yet, the molecular mechanisms underlying these actions remain unclear. In the present study, we used a murine model of schizophrenia induced by 5-day intraperitoneal injection with the non-competitive N-methyl-d-aspartate receptor antagonist MK801 (0.3mg/kg/day) to assess cognitive behavioral deficits, changes in Notch signaling, and cellular proliferation in the hippocampus of adult male C57BL/6 mice after 2-week administration of risperidone (Rip, 0.2mg/kg/day) or vehicle. We then utilized in vivo stereotaxic injections of a lentivirus expressing a short hairpin RNA (shRNA) for Notch1 into the dentate gyrus to examine the role of Notch1 in the observed actions of Rip. We found that Rip ameliorated cognitive deficits and restored cell proliferation in MK801-treated mice in a manner associated with the up-regulation of Notch signaling molecules, including Notch1, Hes1, and Hes5. Moreover, these effects were abolished by pretreatment with Notch1 shRNA. Our results suggest that the ability of Rip to improve cognitive function in schizophrenia is mediated in part by Notch signaling.

Catechol-O-Methyltransferase Val158Met Polymorphism and Clinical Response to Antipsychotic Treatment in Schizophrenia and Schizo-Affective Disorder Patients: a Meta-Analysis

BACKGROUND

The catechol-O-methyltransferase (COMT) enzyme plays a crucial role in dopamine degradation, and the COMT Val158Met polymorphism (rs4680) is associated with significant differences in enzymatic activity and consequently dopamine concentrations in the prefrontal cortex. Multiple studies have analyzed the COMT Val158Met variant in relation to antipsychotic response. Here, we conducted a meta-analysis examining the relationship between COMT Val158Met and antipsychotic response.

METHODS

Searches using PubMed, Web of Science, and PsycInfo databases (03/01/2015) yielded 23 studies investigating COMT Val158Met variation and antipsychotic response in schizophrenia and schizo-affective disorder. Responders/nonresponders were defined using each study's original criteria. If no binary response definition was used, authors were asked to define response according to at least 30% Positive and Negative Syndrome Scale score reduction (or equivalent in other scales). Analysis was conducted under a fixed-effects model.

RESULTS

Ten studies met inclusion criteria for the meta-analysis. Five additional antipsychotic-treated samples were analyzed for Val158Met and response and included in the meta-analysis (ntotal=1416). Met/Met individuals were significantly more likely to respond than Val-carriers (P=.039, ORMet/Met=1.37, 95% CI: 1.02-1.85). Met/Met patients also experienced significantly greater improvement in positive symptoms relative to Val-carriers (P=.030, SMD=0.24, 95% CI: 0.024-0.46). Posthoc analyses on patients treated with atypical antipsychotics (n=1207) showed that Met/Met patients were significantly more likely to respond relative to Val-carriers (P=.0098, ORMet/Met=1.54, 95% CI: 1.11-2.14), while no difference was observed for typical-antipsychotic-treated patients (n=155) (P=.65).

CONCLUSIONS

Our findings suggest that the COMT Val158Met polymorphism is associated with response to antipsychotics in schizophrenia and schizo-affective disorder patients. This effect may be more pronounced for atypical antipsychotics.

COMT Val158Met and 5-HT1A-R -1019 C/G polymorphisms: effects on the negative symptom response to clozapine

Aim: Clozapine is still considered the gold standard for treatment-resistant schizophrenia patients; however, up to 40% of patients do not respond adequately. Identifying potential predictors of clinical response to this last-line antipsychotic could represent an important goal for treatment. Among these, functional polymorphisms involved in dopamine system modulation, known to be disrupted in schizophrenia, may play a role. We examined the COMT Val158Met polymorphism, which plays a key role in dopamine regulation at the prefrontal level, and the 5-HT1A-R -1019 C/G polymorphism, a target of clozapine activity involved in the interaction between the serotonin and dopamine systems. Materials & methods: 107 neuroleptic-refractory, biologically unrelated Italian patients (70 males and 37 females) with a DSM-IV diagnosis of schizophrenia who were being treated with clozapine were recruited. Psychopathology was assessed by the Positive and Negative Symptoms Scale (PANSS) at the beginning of treatment, and at weeks 8 and 12. Genomic DNA was extracted from venous blood samples. COMT rs4680 (Val158Met) and 5-HT1A-R rs6295 (-1019 C/G) polymorphisms were analyzed by PCR-based restriction fragment length and direct sequencing, respectively. Results: We found a significant effect of COMT and 5-HT1A-R on the PANSS Negative Subscale variation, with greater improvement among COMT Val/Val and 5-HT1A-R G/G subjects. Conclusion: The findings support the hypothesis that COMT rs4680 and 5-HT1A-R rs6295 polymorphisms could influence the negative symptom response to clozapine, probably through modulation of the dopaminergic system.

Original submitted 26 February 2014; Revision submitted 15 October 2014

Genetic variability testing of neurodevelopmental genes in schizophrenic patients

This study investigated the associations between single nucleotide polymorphisms in the neurodevelopmental Disrupted In Schizophrenia 1 (DISC1 ), neuregulin 1 (NRG1), brain-derived neurotrophic factor (BDNF) and NOTCH4 genes and the clinical symptoms and the occurrence of treatment-resistant schizophrenia in the Slovenian population. We included 138 schizophrenia patients, divided into treatment-responsive and treatment-resistant group and 94 healthy blood donors. All subjects were genotyped for eight polymorphisms (DISC1 rs6675281, DISC1 rs821616, NRG1 rs3735781, NRG1 rs3735782, NRG1 rs10503929, NRG1 rs3924999, BDNF rs6265, NOTCH rs367398) and investigated for associations with clinical variables. NOTCH4 rs367398 AA/AG was significantly associated with worse Positive and Negative Syndrome Scale (PANSS) and Clinical Global Impression (CGI) score. NOTCH4 rs367398 was not statistically significantly associated with the occurrence of treatment-resistant schizophrenia after the correction for multiple testing. Our data indicate that NOTCH4 polymorphism can influence clinical symptoms in Slovenian patients with schizophrenia.

Clinical response to antipsychotic drug treatment: association study of polymorphisms in six candidate genes

Pharmacogenetic studies have demonstrated significant associations between several candidate genes (DRD2, DRD3, 5HTR2A and 5HTR2C, COMT and MTHFR) and antipsychotic drug response. The present study investigates the effect of nine polymorphisms in these genes for an association with antipsychotic treatment response. 329 Caucasian patients with a non-affective psychotic disorder using antipsychotics were included. All patients participated in the longitudinal GROUP-study in The Netherlands. We genotyped 9 SNPs in 6 candidate genes (DRD2: TaqI_A, -141C; DRD3: Ser9Gly; HTR2A: 102-T/C, His452Tyr; HTR2C: Cys23Ser; COMT: Val158Met; MTHFR: 677-C/T) using standard protocols. Polymorphisms were based on previous studies showing associations with positive symptoms treatment response. The Clinical Global Impression - Improvement (CGI-I) scale was used to assess improvement in positive psychotic symptoms since the start of current antipsychotic treatment. Ordinal regression was used for association analyses. Ninety percent of the patients used second generation antipsychotics, with olanzapine (28%) and risperidone (29%) being the most prescribed drugs. Ser9Gly of the dopamine D3 receptor gene (P value 0.034) and 677-C/T of MTHFR (P value 0.019) were tested statistically significant. Gly-carriers and T-carriers, respectively, showed more clinical improvement on the CGI-I. The other polymorphisms did not show a statistically significant association (P values>0.10). In conclusion, we replicated two out of nine of the previously reported associations between polymorphisms and treatment response. The direction and magnitude of the associations presented here in DRD3 (Ser9Gly) and MTHFR (677-C/T) are in line with previous association studies in Caucasian patients. These polymorphisms may be of value for predicting clinical response.

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).

Gene-gene interaction analyses between NMDA receptor subunit and dopamine receptor gene variants and clozapine response

AIMS

To investigate the possible association and gene-gene interaction effects of polymorphisms in NMDA receptor subunit (GRIN1, GRIN2A and GRIN2B) and dopamine receptor (DRD1, DRD2 and DRD3) genes with clozapine response.

MATERIALS & METHODS

GRIN1 rs11146020 (G1001C), GRIN2A GT-repeat and GRIN2B rs10193895 (G-200T) polymorphisms were tested for association in a Caucasian (n = 183) and an African-American (n = 49) sample using χ(2) and ANOVA tests. Logistic regression and two-way ANOVA were used to explore gene-gene interaction effects with dopamine receptor gene variants.

RESULTS & CONCLUSION

This study does not support the involvement of the NMDA receptor subunit gene polymorphisms in clozapine response. All tests for an association were negative. Gene-gene interaction analyses however yielded promising leads, including an observed effect between DRD1 rs686 and DRD3 Ser9Gly polymorphisms on clozapine response (p = 0.002).

The promise and reality of pharmacogenetics in psychiatry

Existing psychotropic medications for the treatment of mental illnesses, including antidepressants, mood stabilizers, and antipsychotics, are clinically suboptimal. They are effective in only a subset of patients or produce partial responses, and they are often associated with debilitating side effects that discourage adherence. There is growing enthusiasm in the promise of pharmacogenetics to personalize the use of these treatments to maximize their efficacy and tolerability; however, there is still a long way to go before this promise becomes a reality. This article reviews the progress that has been made in research toward understanding how genetic factors influence psychotropic drug responses and the challenges that lie ahead in translating the research findings into clinical practices that yield tangible benefits for patients with mental illnesses.

Association of Disrupted in Schizophrenia 1 (DISC1) missense variants with ultra-resistant schizophrenia

Three common missense variants of the Disrupted in Schizophrenia 1 (DISC1) gene, rs3738401 (Q264R), rs6675281 (L607F) and rs821616 (S704C), have been variably associated with the risk of schizophrenia. In a case-control study, we examine whether these gene variants are associated with schizophrenia and ultra-resistant schizophrenia (URS) in a population of French Caucasian patients. The URS phenotype is characterized according to stringent criteria as patients who experience no clinical, social and/or occupational remission in spite of treatment with clozapine and at least two periods of treatment with distinct conventional or atypical antipsychotic drugs. We find a significant association between DISC1 missense variants and URS. The association with rs3738401 remains significant after appropriate correction for multiple testing. These results suggest that the DISC1 rs3738401 missense variant is statistically linked with ultra-resistance to antipsychotic treatment.

The promise and reality of pharmacogenetics in psychiatry

Existing psychotropic medications for the treatment of mental illnesses, including antidepressants, mood stabilizers, and antipsychotics, are clinically suboptimal. They are effective in only a subset of patients or produce partial responses, and they are often associated with debilitating side effects that discourage adherence. There is growing enthusiasm in the promise of pharmacogenetics to personalize the use of these treatments to maximize their efficacy and tolerability; however, there is still a long way to go before this promise becomes a reality. This article reviews the progress that has been made in research toward understanding how genetic factors influence psychotropic drug responses and the challenges that lie ahead in translating the research findings into clinical practices that yield tangible benefits for patients with mental illnesses.

Pharmacogenetic of response efficacy to antipsychotics in schizophrenia: pharmacodynamic aspects. Review and implications for clinical research

Pharmacogenetics constitutes a new and growing therapeutic approach in the identification of the predictive factors of the response to antipsychotic treatment. This review aims to summarize recent finding into pharmacodynamic approach of pharmacogenetics of antipsychotics and particularly second generation. Studies were identified in the MEDLINE database from 1993 to July 2008 by combining the following Medical Subject Heading search terms: genetic, polymorphism, single nucleotide polymorphism, pharmacogenetics, antipsychotics, and response to treatment as well as individual antipsychotics names. Only pharmacodynamics studies were analyzed and we focused on efficacy studies. We also reviewed the references of ll identified articles. Most studies follow a polymorphism-by-polymorphism approach, and concern polymorphisms of genes coding for dopamine and serotonin receptors. Haplotypic approach has been considered in some studies. Few have studied the combinations of polymorphisms of several genes as a predictive factor of the response to antipsychotics. We present this gene-by-gene approach while detailing the features of the polymorphisms being studied (functionality, linkage disequilibrium) and the features of the studies (studied treatment(s), prospective/retrospective study, pharmacological dosage). We discuss the heterogeneity of the results and their potential clinical implications and extract methodological suggestions for the future concerning phenotype characterization, genotypes variants studied and methodological and statistical approach.

Pharmacogenetics of antipsychotic response in the CATIE trial: a candidate gene analysis

The Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) Phase 1 Schizophrenia trial compared the effectiveness of one typical and four atypical antipsychotic medications. Although trials such as CATIE present important opportunities for pharmacogenetics research, the very richness of the clinical data presents challenges for statistical interpretation, and in particular the risk that data mining will lead to false-positive discoveries. For this reason, it is both misleading and unhelpful to perpetuate the current practice of reporting association results for these trials one gene at a time, ignoring the fact that multiple gene-by-phenotype tests are being carried out on the same data set. On the other hand, suggestive associations in such trials may lead to new hypotheses that can be tested through both replication efforts and biological experimentation. The appropriate handling of these forms of data therefore requires dissemination of association statistics without undue emphasis on select findings. Here we attempt to illustrate this approach by presenting association statistics for 2769 polymorphisms in 118 candidate genes evaluated for 21 pharmacogenetic phenotypes. On current evidence it is impossible to know which of these associations may be real, although in total they form a valuable resource that is immediately available to the scientific community.

Pharmacogenomic Biomarkers in Neuropsychiatry: The Path to Personalized Medicine in Mental Disorders

Neuropsychiatric disorders and dementia represent a major cause of disability and high cost in developed societies. Most disorders of the central nervous system (CNS) share some common features, such as a genomic background in which hundreds of genes might be involved, genome-environment interactions, complex pathogenic pathways, poor therapeutic outcomes, and chronic disability.

Recent advances in genomic medicine can contribute to accelerate our understanding on the pathogenesis of CNS disorders, improve diagnostic accuracy with the introduction of novel biomarkers, and personalize therapeutics with the incorporation of pharmacogenetic and pharmacogenomic procedures to drug development and clinical practice.

The pharmacological treatment of CNS disorders, in general, accounts for 10–20% of direct costs, and less than 30–40% of the patients are moderate responders to conventional drugs, some of which may cause important adverse drugs reactions (ADRs). Pharmacogenetic and pharmacogenomic factors may account for 60–90% of drug variability in drug disposition and pharmacodynamics. Approximately 60–80% of CNS drugs are metabolized via enzymes of the CYP gene superfamily; 18% of neuroleptics are major substrates of CYP1A2 enzymes, 40% of CYP2D6, and 23% of CYP3A4; 24% of antidepressants are major substrates of CYP1A2 enzymes, 5% of CYP2B6, 38% of CYP2C19, 85% of CYP2D6, and 38% of CYP3A4; 7% of benzodiazepines are major substrates of CYP2C19 enzymes, 20% of CYP2D6, and 95% of

CYP3A4. About 10–20% of Caucasians are carriers of defective CYP2D6 polymorphic variants that alter the metabolism of many psychotropic agents. Other 100 genes participate in the efficacy and safety of psychotropic drugs. The incorporation of pharmacogenetic/ pharmacogenomic protocols to CNS research and clinical practice can foster therapeutics optimization by helping to develop cost-effective pharmaceuticals and improving drug efficacy and safety. To achieve this goal several measures have to be taken, including: (a) educate physicians and the public on the use of genetic/ genomic screening in the daily clinical practice; (b) standardize genetic testing for major categories of drugs; (c) validate pharmacogenetic and pharmacogenomic procedures according to drug category and pathology; (d) regulate ethical, social, and economic issues; and (e) incorporate pharmacogenetic and pharmacogenomic procedures to both drugs in development and drugs in the market to optimize therapeutics.

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.

Polymorphisms in catechol-O-methyltransferase and methylenetetrahydrofolate reductase in relation to the risk of schizophrenia

BACKGROUND

Evidence is emerging for the association of aberrant homocysteine-methylation cycle and increased risk of schizophrenia.

METHODS

We examined the prevalence of the catechol-O-methyltransferase (COMT) 324G>A (Val108/158Met) and methylenetetrahydrofolate reductase (MTHFR) 677C>T polymorphisms in 252 patients with schizophrenia and 405 control subjects. All subjects were of Dutch ancestry.

RESULTS

The COMT 324AA genotype was not associated with an increased risk of schizophrenia (odds ratio (OR)=1.38 [95% CI: 0.88-2.16], P=0.162), and the MTHFR 677TT genotype showed a nearly significant increased risk for schizophrenia (OR=1.65 [95% CI: 0.97-2.82], P=0.067). The odds ratio for schizophrenia associated with joint occurrence of the COMT 324AA and MTHFR 677TT genotype was 3.08 (95% CI: 1.08-8.76) (P=0.035). Increasing number of low enzyme activity alleles in the COMT and MTHFR genotype combinations were associated with an increased risk of schizophrenia (test for trend, P=0.017).

CONCLUSIONS

Our findings do not support a major role for the COMT 324AA and MTHFR 677TT genotype alone, but the combination of both genotypes might increase schizophrenia susceptibility.

Pharmacogenetics and pharmacogenomics of schizophrenia: a review of last decade of research

The last decade of research into the pharmacogenetics of antipsychotics has seen the development of genetic tests to determine the patients' metabolic status and the first attempts at personalization of antipsychotic treatment. The most significant results are the association between drug metabolic polymorphisms, mainly in cytochrome P450 genes, with variations in drug metabolic rates and side effects. Patients with genetically determined CYP2D6 poor metabolizer (PMs) status may require lower doses of antipsychotic. Alternatively, CYP2D6 ultrarapid matabolizers (UMs) will need increased drug dosage to obtain therapeutic response. Additionally, polymorphisms in dopamine and serotonin receptor genes are repeatedly found associated with response phenotypes, probably reflecting the strong affinities that most antipsychotics display for these receptors. In particular, there is important evidence suggesting association between dopamine 2 receptor (D2) polymorphisms (Taq I and -141-C Ins/Del) and a dopamine 3 receptor (D3) polymorphism (Ser9Gly) with antipsychotic response and drug-induced tardive dyskinesia. Additionally, there is accumulating evidence indicating the influence of a 5-HT2C polymorphism (-759-T/C) in antipsychotic-induced weight gain. Application of this knowledge to clinical practice is slowly gathering pace, with pretreatment determination of individual's drug metabolic rates, via CYP genotyping, leading the field. Genetic determination of patients' metabolic status is expected to bring clinical benefits by helping to adjust therapeutic doses and reduce adverse reactions. Genetic tests for the pretreatment prediction of antipsychotic response, although still in its infancy, have obvious implications for the selection and improvement of antipsychotic treatment. These developments can be considered as successes, but the objectives of bringing pharmacogenetic and pharmacogenomic research in psychiatric clinical practice are far from being realized. Further development of genetic tests is required before the concept of tailored treatment can be applied to psychopharmatherapy. This review aims to summarize the key findings from the last decade of research in the field. Current knowledge on genetic prediction of drug metabolic status, general response and drug-induced side effects will be reviewed and future pharmacogenomic and epigenetic research will be discussed.

PharmGED: Pharmacogenetic Effect Database

Prediction and elucidation of pharmacogenetic effects is important for facilitating the development of personalized medicines. Knowledge of polymorphism-induced and other types of drug-response variations is needed for facilitating such studies. Although databases of pharmacogenetic knowledge, polymorphism and toxicogenomic information have appeared, some of the relevant data are provided in separate web-pages and in terms of relatively long descriptions quoted from literatures. To facilitate easy and quick assessment of the relevant information, it is helpful to develop databases that provide all of the information related to a pharmacogenetic effect in the same web-page and in brief descriptions. We developed a database, Pharmacogenetic Effect Database (PharmGED), for providing sequence, function, polymorphism, affected drugs and pharmacogenetic effects. PharmGED can be accessed at free of charge for academic use. It currently contains 1825 entries covering 108 disease conditions, 266 distinct proteins, 693 polymorphisms, 414 drugs/ligands cited from 856 references.

A review and re-evaluation of an association between the NOTCH4 locus and schizophrenia

This work reviewed all the reports on the NOTCH4 gene in schizophrenia, which have been published since the gene was found to be associated with illness among a British population in 2000. The results from independent studies were inconsistent. Allelic heterogeneity, clinical diagnosis, ethnical backgrounds, and linkage disequilibrium (LD) structures in the human genome may be major reasons for poor replication. A couple of studies suggested that the NOTCH4 gene could play a role in a subgroup of the disease, such as early-onset schizophrenia and negative symptoms. A single study revealed a weak association of the NOTCH4 gene with frontal lobe brain volumes and a strong association with frontal lobe cognitive performance. A meta-analysis showed stronger evidence of the NOTCH4 association in family-based studies than in case-control studies. In a previous study, we found that rs520692, a single nucleotide polymorphism (SNP) at the NOTCH4 locus, was associated with schizophrenia in a Chinese population. In the present study, we applied a large sample size to re-evaluate our initial findings and then confirmed the rs520692 association with illness. The pairwise measures did not show strong LD between paired SNPs although the SNPs tested are located within a 34-kb region, suggesting that LD within the NOTCH4 gene has been broken rapidly by historical recombination in the Chinese population. Taken together, the NOTCH4 gene may be associated with schizophrenia but how the gene contributes to the etiology of the illness needs a further investigation.

Analyses of the associations between the genes of 22q11 deletion syndrome and schizophrenia

Schizophrenia is a severe, debilitating mental disorder characterized by profound disturbances of cognition, emotion and social functioning. The lifetime morbid risk is surprisingly uniform at slightly less than 1% across different populations and different cultures. The evidence of genetic risk factors is our strongest clue to the cause of schizophrenia. Linkage and association analyses have identified genes associated with the development of schizophrenia. However, most of the alleles or haplotypes identified thus far have only a weak association or are reported to be population specific. A deletion of 22q11.2 that causes the most common microdeletion syndrome (22q11DS) with an estimated prevalence of 1:2,500-1:4,000 live births may represent one of the greatest known genetic risk factors for schizophrenia. Schizophrenia is a late manifestation in approximately 30% of patients with 22q11.2 deletion, comparable to the risk to offspring of two parents with schizophrenia. Clinical and neuroimaging assessments indicate that 22q11DS-schizophrenia is a neurodevelopmental model of schizophrenia. Recent studies have provided evidence that haploinsufficiency of TBX1 is likely to be responsible for many of the physical features associated with the deletion. Most of the genes in the 22q11 deletion region are conserved together on mouse chromosome 16, enabling the generation of mouse models. Similarities in the cardiovascular and other phenotypes between 22q11DS patients and mouse models can provide important insights into roles of genes in neurobehavioral phenotypes. Because more than one gene in the 22q11DS region is likely to contribute to the marked risk for schizophrenia, further extensive studies are necessary. Analyses of 22q11DS will help clarify the molecular pathogenesis of schizophrenia.

Tumor necrosis factor-alpha −G308A polymorphism in schizophrenia in a Finnish population

Tumor necrosis factor-alpha (TNF-alpha) is a proinflammatory cytokine with functions in nerve cell growth, differentiation, and apoptosis. There are several studies showing that a TNF-alpha--G308A promoter polymorphism, which possibly affects TNF-alpha transcription, is associated with schizophrenia, although negative results also exist. Our aim was to investigate the relationship between the TNF-alpha --G308A promoter polymorphism, the risk of schizophrenia, and the age of onset of schizophrenia, and the TNF-alpha -G308A polymorphism was therefore studied in 149 southern Finnish patients with a DSM-IV diagnosis of schizophrenia and in 393 healthy controls. The allele and genotype frequencies did not differ significantly between the patient and control groups (P=0.10 and 0.12, respectively), but the frequency of G/G homozygotes was statistically significantly higher in male patients than in male controls (chi(2)=5.03, d.f.=1, P=0.025) with an odds ratio of 2.00 (95% confidence interval: 1.08--3.70). No such difference was seen in female patients (P=0.79) or in the whole study group (P=0.064). The age of onset of schizophrenia did not differ significantly between the different TNF-alpha genotypes (ANOVA: F=0.45, P=0.64). In conclusion, we did not find a clear association between the TNF-alpha --G308A polymorphism and schizophrenia in the whole study group. However, TNF-alpha --G308A G/G homozygosity was modestly associated with schizophrenia in male patients.

Psychiatric genetics--the new era: genetic research and some clinical implications

Impressive advances in the last decade have been made in the genetics and neuroscience of neuropsychiatric illness. Synergies between complex genetics, elaboration of intermediate phenotypes (Egan et al. (2004) Schizophrenia. London: Blackwell) and novel applications in neuroimaging (Bookheimer et al. (2000) N Engl J Med, 343, 450-456) are revealing the effects of positively associated disease alleles on aspects of neurological function. Genes such as NRG-1, DISC1, RGS4, COMT, PRODH, DTNBP1, G72, DAAO, GRM3 (Harrison and Weinberger (2005) Mol Psychiatry, 10, 40-68) and others have been implicated in schizophrenia along with 5-HTTPR (Ogilvie et al. (1996) Lancet, 347, 731-733; Caspi et al. (2003) Science, 301, 386-389) and BDNF (Geller et al. (2004) Am J Psychiatry, 161, 1698-1700) in affective disorders. As the genetics and complex neurocircuits of these and disorders are being untangled, parallel applications in pharmacogenomics and gene-based drug metabolism are shaping a drive for personalized medicine. Genetic research and pharmacogenomics suggest that the subcategorization of individuals based on various sets of susceptibility alleles will make the treatment of neuropsychiatric and other illnesses more predictable and effective.