Genomewide association for schizophrenia in the CATIE study: results of stage 1

Genome-wide association study of alcohol dependence

CONTEXT

Alcohol dependence is a serious and common public health problem. It is well established that genetic factors play a major role in the development of this disorder. Identification of genes that contribute to alcohol dependence will improve our understanding of the mechanisms that underlie this disorder.

OBJECTIVE

To identify susceptibility genes for alcohol dependence through a genome-wide association study (GWAS) and a follow-up study in a population of German male inpatients with an early age at onset.

DESIGN

The GWAS tested 524,396 single-nucleotide polymorphisms (SNPs). All SNPs with P < 10(-4) were subjected to the follow-up study. In addition, nominally significant SNPs from genes that had also shown expression changes in rat brains after long-term alcohol consumption were selected for the follow-up step.

SETTING

Five university hospitals in southern and central Germany.

PARTICIPANTS

The GWAS included 487 male inpatients with alcohol dependence as defined by the DSM-IV and an age at onset younger than 28 years and 1358 population-based control individuals. The follow-up study included 1024 male inpatients and 996 age-matched male controls. All the participants were of German descent.

MAIN OUTCOME MEASURES

Significant association findings in the GWAS and follow-up study with the same alleles.

RESULTS

The GWAS produced 121 SNPs with nominal P < 10(-4). These, together with 19 additional SNPs from homologues of rat genes showing differential expression, were genotyped in the follow-up sample. Fifteen SNPs showed significant association with the same allele as in the GWAS. In the combined analysis, 2 closely linked intergenic SNPs met genome-wide significance (rs7590720, P = 9.72 x 10(-9); rs1344694, P = 1.69 x 10(-8)). They are located on chromosome region 2q35, which has been implicated in linkage studies for alcohol phenotypes. Nine SNPs were located in genes, including the CDH13 and ADH1C genes, that have been reported to be associated with alcohol dependence.

CONCLUSIONS

This is the first GWAS and follow-up study to identify a genome-wide significant association in alcohol dependence. Further independent studies are required to confirm these findings.

A multi-dimensional evidence-based candidate gene prioritization approach for complex diseases-schizophrenia as a case

MOTIVATION

During the past decade, we have seen an exponential growth of vast amounts of genetic data generated for complex disease studies. Currently, across a variety of complex biological problems, there is a strong trend towards the integration of data from multiple sources. So far, candidate gene prioritization approaches have been designed for specific purposes, by utilizing only some of the available sources of genetic studies, or by using a simple weight scheme. Specifically to psychiatric disorders, there has been no prioritization approach that fully utilizes all major sources of experimental data.

RESULTS

Here we present a multi-dimensional evidence-based candidate gene prioritization approach for complex diseases and demonstrate it in schizophrenia. In this approach, we first collect and curate genetic studies for schizophrenia from four major categories: association studies, linkage analyses, gene expression and literature search. Genes in these data sets are initially scored by category-specific scoring methods. Then, an optimal weight matrix is searched by a two-step procedure (core genes and unbiased P-values in independent genome-wide association studies). Finally, genes are prioritized by their combined scores using the optimal weight matrix. Our evaluation suggests this approach generates prioritized candidate genes that are promising for further analysis or replication. The approach can be applied to other complex diseases.

AVAILABILITY

The collected data, prioritized candidate genes, and gene prioritization tools are freely available at http://bioinfo.mc.vanderbilt.edu/SZGR/.

Schizophrenia: from the brain to peripheral markers. A consensus paper of the WFSBP task force on biological markers

Objective. The phenotypic complexity, together with the multifarious nature of the so-called "schizophrenic psychoses", limits our ability to form a simple and logical biologically based hypothesis for the disease group. Biological markers are defined as biochemical, physiological or anatomical traits that are specific to particular conditions. An important aim of biomarker discovery is the detection of disease correlates that can be used as diagnostic tools. Method. A selective review of the WFSBP Task Force on Biological Markers in schizophrenia is provided from the central nervous system to phenotypes, functional brain systems, chromosomal loci with potential genetic markers to the peripheral systems. Results. A number of biological measures have been proposed to be correlated with schizophrenia. At present, not a single biological trait in schizophrenia is available which achieves sufficient specificity, selectivity and is based on causal pathology and predictive validity to be recommended as diagnostic marker. Conclusions. With the emergence of new technologies and rigorous phenotypic subclassification the identification of genetic bases and assessment of dynamic disease related alterations will hopefully come to a new stage in the complex field of psychiatric research.

Evidence for the association of the DAOA (G72) gene with schizophrenia and bipolar disorder but not for the association of the DAO gene with schizophrenia

BACKGROUND

Previous linkage and association studies have implicated the D-amino acid oxidase activator gene (DAOA)/G30 locus or neighbouring region of chromosome 13q33.2 in the genetic susceptibility to both schizophrenia and bipolar disorder. Four single nucleotide polymorphisms (SNPs) within the D-amino acid oxidase (DAO) gene located at 12q24.11 have also been found to show allelic association with schizophrenia.

METHODS

We used the case control method to test for genetic association with variants at these loci in a sample of 431 patients with schizophrenia, 303 patients with bipolar disorder and 442 ancestrally matched supernormal controls all selected from the UK population.

RESULTS

Ten SNPs spanning the DAOA locus were genotyped in these samples. In addition three SNPs were genotyped at the DAO locus in the schizophrenia sample. Allelic association was detected between the marker rs3918342 (M23), 3' to the DAOA gene and both schizophrenia (chi2 = 5.824 p = 0.016) and bipolar disorder (chi2 = 4.293 p = 0.038). A trend towards association with schizophrenia was observed for two other DAOA markers rs3916967 (M14, chi2 = 3.675 p = 0.055) and rs1421292 (M24; chi2 = 3.499 p = 0.062). A test of association between a three marker haplotype comprising of the SNPs rs778293 (M22), rs3918342 (M23) and rs1421292 (M24) and schizophrenia gave a global empirical significance of p = 0.015. No evidence was found to confirm the association of genetic markers at the DAO gene with schizophrenia.

CONCLUSION

Our results provide some support for a role for DAOA in susceptibility to schizophrenia and bipolar disorder.

Accuracy of genome-wide imputation of untyped markers and impacts on statistical power for association studies

BACKGROUND

Although high-throughput genotyping arrays have made whole-genome association studies (WGAS) feasible, only a small proportion of SNPs in the human genome are actually surveyed in such studies. In addition, various SNP arrays assay different sets of SNPs, which leads to challenges in comparing results and merging data for meta-analyses. Genome-wide imputation of untyped markers allows us to address these issues in a direct fashion.

METHODS

384 Caucasian American liver donors were genotyped using Illumina 650Y (Ilmn650Y) arrays, from which we also derived genotypes from the Ilmn317K array. On these data, we compared two imputation methods: MACH and BEAGLE. We imputed 2.5 million HapMap Release22 SNPs, and conducted GWAS on approximately 40,000 liver mRNA expression traits (eQTL analysis). In addition, 200 Caucasian American and 200 African American subjects were genotyped using the Affymetrix 500 K array plus a custom 164 K fill-in chip. We then imputed the HapMap SNPs and quantified the accuracy by randomly masking observed SNPs.

RESULTS

MACH and BEAGLE perform similarly with respect to imputation accuracy. The Ilmn650Y results in excellent imputation performance, and it outperforms Affx500K or Ilmn317K sets. For Caucasian Americans, 90% of the HapMap SNPs were imputed at 98% accuracy. As expected, imputation of poorly tagged SNPs (untyped SNPs in weak LD with typed markers) was not as successful. It was more challenging to impute genotypes in the African American population, given (1) shorter LD blocks and (2) admixture with Caucasian populations in this population. To address issue (2), we pooled HapMap CEU and YRI data as an imputation reference set, which greatly improved overall performance. The approximate 40,000 phenotypes scored in these populations provide a path to determine empirically how the power to detect associations is affected by the imputation procedures. That is, at a fixed false discovery rate, the number of cis-eQTL discoveries detected by various methods can be interpreted as their relative statistical power in the GWAS. In this study, we find that imputation offer modest additional power (by 4%) on top of either Ilmn317K or Ilmn650Y, much less than the power gain from Ilmn317K to Ilmn650Y (13%).

CONCLUSION

Current algorithms can accurately impute genotypes for untyped markers, which enables researchers to pool data between studies conducted using different SNP sets. While genotyping itself results in a small error rate (e.g. 0.5%), imputing genotypes is surprisingly accurate. We found that dense marker sets (e.g. Ilmn650Y) outperform sparser ones (e.g. Ilmn317K) in terms of imputation yield and accuracy. We also noticed it was harder to impute genotypes for African American samples, partially due to population admixture, although using a pooled reference boosts performance. Interestingly, GWAS carried out using imputed genotypes only slightly increased power on top of assayed SNPs. The reason is likely due to adding more markers via imputation only results in modest gain in genetic coverage, but worsens the multiple testing penalties. Furthermore, cis-eQTL mapping using dense SNP set derived from imputation achieves great resolution, and locate associate peak closer to causal variants than conventional approach.

Genetics of psychosis; insights from views across the genome

The major psychotic illnesses, schizophrenia and bipolar disorder (BD), are among the most heritable common disorders, but finding specific susceptibility genes for them has not been straightforward. The reasons are widely assumed to include lack of valid phenotypic definition, absence of good theories of pathophysiology for candidate gene studies, and the involvement of many genes, each making small contributions to population risk. Within the last year or so, a number of genome wide association (GWAS) of schizophrenia and BD have been published. These have produced stronger evidence for association to specific risk loci than have earlier studies, specifically for the zinc finger binding protein 804A (ZNF804A) locus in schizophrenia and for the calcium channel, voltage-dependent, L type, alpha 1C subunit (CACNA1C) and ankyrin 3, node of Ranvier (ANK3) loci in bipolar disorder. The ZNF804A and CACNA1C loci appear to influence risk for both disorders, a finding that supports the hypothesis that schizophrenia and BD are not aetiologically distinct. In the case of schizophrenia, a number of rare copy number variants have also been detected that have fairly large effect sizes on disease risk, and that additionally influence risk of autism, mental retardation, and other neurodevelopmental disorders. The existing findings point to some likely pathophysiological mechanisms but also challenge current concepts of disease classification. They also provide grounds for optimism that larger studies will reveal more about the origins of these disorders, although currently, very little of the genetic risk of either disorder is explained.

Genetics of Schizophrenia Spectrum Disorders: Looking Back and Peering Ahead

The genetics of schizophrenia spectrum disorders have come a long way since the early demonstration of a substantial genetic component by family, twin and adoption studies. After over a decade of intensive molecular genetic studies, initially by linkage scans and candidate gene association studies, and more recently genome-wide association studies, a picture is now emerging that susceptibility to schizophrenia spectrum disorders is determined by many genetic variants of different types, ranging from single nucleotide polymorphisms to copy number variants, including rare and de novo variants, of pleiotropic effects on multiple diagnoses and traits. Further large-scale genome-wide association studies, and the forthcoming availability of affordable whole-genome sequencing technology, will further characterise the genetic variants involved, which in turn will be translated to improved clinical practice. Key words: Copy number variation, Genome-wide association, Linkage

The DISC locus and schizophrenia: evidence from an association study in a central European sample and from a meta-analysis across different European populations

Association studies, as well as the initial translocation family study, identified the gene Disrupted-In-Schizophrenia-1 (DISC1) as a risk factor for schizophrenia. DISC1 encodes a multifunctional scaffold protein involved in neurodevelopmental processes implicated in the etiology of schizophrenia. The present study explores the contribution of the DISC locus to schizophrenia using three different approaches: (i) systematic association mapping aimed at detecting DISC risk variants in a schizophrenia sample from a central European population (556 SNPs, n = 1621 individuals). In this homogenous sample, a circumscribed DISC1 interval in intron 9 was significantly associated with schizophrenia in females (P = 4 x 10(-5)) and contributed most strongly to early-onset cases (P = 9 x 10(-5)). The odds ratios (ORs) were in the range of 1.46-1.88. (ii) The same sample was used to test for the locus-specific SNP-SNP interaction most recently associated with schizophrenia. Our results confirm the SNP interplay effect between rs1538979 and rs821633 that significantly conferred disease risk in male patients with schizophrenia (P = 0.016, OR 1.57). (iii) In order to detect additional schizophrenia variants, a meta-analysis was performed using nine schizophrenia samples from different European populations (50 SNPs, n = 10 064 individuals maximum, n = 3694 minimum). We found evidence for a common schizophrenia risk interval within DISC1 intron 4-6 (P = 0.002, OR 1.27). The findings point to a complex association between schizophrenia and DISC, including the presence of different risk loci and SNP interplay effects. Furthermore, our phenotype-genotype results--including the consideration of sex-specific effects--highlight the value of homogenous samples in mapping risk genes for schizophrenia in general, and at the DISC locus in particular.

A primate-specific, brain isoform of KCNH2 affects cortical physiology, cognition, neuronal repolarization and risk of schizophrenia

Organized neuronal firing is crucial for cortical processing and is disrupted in schizophrenia. Using rapid amplification of 5' complementary DNA ends in human brain, we identified a primate-specific isoform (3.1) of the ether-a-go-go-related K(+) channel KCNH2 that modulates neuronal firing. KCNH2-3.1 messenger RNA levels are comparable to full-length KCNH2 (1A) levels in brain but three orders of magnitude lower in heart. In hippocampus from individuals with schizophrenia, KCNH2-3.1 expression is 2.5-fold greater than KCNH2-1A expression. A meta-analysis of five clinical data sets (367 families, 1,158 unrelated cases and 1,704 controls) shows association of single nucleotide polymorphisms in KCNH2 with schizophrenia. Risk-associated alleles predict lower intelligence quotient scores and speed of cognitive processing, altered memory-linked functional magnetic resonance imaging signals and increased KCNH2-3.1 mRNA levels in postmortem hippocampus. KCNH2-3.1 lacks a domain that is crucial for slow channel deactivation. Overexpression of KCNH2-3.1 in primary cortical neurons induces a rapidly deactivating K(+) current and a high-frequency, nonadapting firing pattern. These results identify a previously undescribed KCNH2 channel isoform involved in cortical physiology, cognition and psychosis, providing a potential new therapeutic drug target.

Psychiatric GWAS Consortium Coordinating Committee, Cichon S, Craddock N, Daly M, Faraone SV, Gejman PV, Kelsoe J, Lehner T, Levinson DF, Moran A, Sklar P, Sullivan PF. Genomewide association studies: history, rationale, and prospects for psychiatric disorders

OBJECTIVE

The authors conducted a review of the history and empirical basis of genomewide association studies (GWAS), the rationale for GWAS of psychiatric disorders, results to date, limitations, and plans for GWAS meta-analyses.

METHOD

A literature review was carried out, power and other issues discussed, and planned studies assessed.

RESULTS

Most of the genomic DNA sequence differences between any two people are common (frequency >5%) single nucleotide polymorphisms (SNPs). Because of localized patterns of correlation (linkage disequilibrium), 500,000 to 1,000,000 of these SNPs can test the hypothesis that one or more common variants explain part of the genetic risk for a disease. GWAS technologies can also detect some of the copy number variants (deletions and duplications) in the genome. Systematic study of rare variants will require large-scale resequencing analyses. GWAS methods have detected a remarkable number of robust genetic associations for dozens of common diseases and traits, leading to new pathophysiological hypotheses, although only small proportions of genetic variance have been explained thus far and therapeutic applications will require substantial further effort. Study design issues, power, and limitations are discussed. For psychiatric disorders, there are initial significant findings for common SNPs and for rare copy number variants, and many other studies are in progress.

CONCLUSIONS

GWAS of large samples have detected associations of common SNPs and of rare copy number variants with psychiatric disorders. More findings are likely, since larger GWAS samples detect larger numbers of common susceptibility variants, with smaller effects. The Psychiatric GWAS Consortium is conducting GWAS meta-analyses for schizophrenia, bipolar disorder, major depressive disorder, autism, and attention deficit hyperactivity disorder. Based on results for other diseases, larger samples will be required. The contribution of GWAS will depend on the true genetic architecture of each disorder.

Genome-wide association studies in ADHD

Attention-deficit/hyperactivity disorder, ADHD, is a common and highly heritable neuropsychiatric disorder that is seen in children and adults. Although heritability is estimated at around 76%, it has been hard to find genes underlying the disorder. ADHD is a multifactorial disorder, in which many genes, all with a small effect, are thought to cause the disorder in the presence of unfavorable environmental conditions. Whole genome linkage analyses have not yet lead to the identification of genes for ADHD, and results of candidate gene-based association studies have been able to explain only a tiny part of the genetic contribution to disease, either. A novel way of performing hypothesis-free analysis of the genome suitable for the identification of disease risk genes of considerably smaller effect is the genome-wide association study (GWAS). So far, five GWAS have been performed on the diagnosis of ADHD and related phenotypes. Four of these are based on a sample set of 958 parent-child trio's collected as part of the International Multicentre ADHD Genetics (IMAGE) study and genotyped with funds from the Genetic Association Information Network (GAIN). The other is a pooled GWAS including adult patients with ADHD and controls. None of the papers reports any associations that are formally genome-wide significant after correction for multiple testing. There is also very limited overlap between studies, apart from an association with CDH13, which is reported in three of the studies. Little evidence supports an important role for the 'classic' ADHD genes, with possible exceptions for SLC9A9, NOS1 and CNR1. There is extensive overlap with findings from other psychiatric disorders. Though not genome-wide significant, findings from the individual studies converge to paint an interesting picture: whereas little evidence-as yet-points to a direct involvement of neurotransmitters (at least the classic dopaminergic, noradrenergic and serotonergic pathways) or regulators of neurotransmission, some suggestions are found for involvement of 'new' neurotransmission and cell-cell communication systems. A potential involvement of potassium channel subunits and regulators warrants further investigation. More basic processes also seem involved in ADHD, like cell division, adhesion (especially via cadherin and integrin systems), neuronal migration, and neuronal plasticity, as well as related transcription, cell polarity and extracellular matrix regulation, and cytoskeletal remodeling processes. In conclusion, the GWAS performed so far in ADHD, though far from conclusive, provide a first glimpse at genes for the disorder. Many more (much larger studies) will be needed. For this, collaboration between researchers as well as standardized protocols for phenotyping and DNA-collection will become increasingly important.

Schizophrenia genetics: advancing on two fronts

Recent studies have supported the hypothesis that the high heritability of schizophrenia reflects a combination of relatively common alleles of small effect and some rare alleles with relatively large effects. Genome-wide association studies have identified at least one common allele of small effect at ZNF804a, which encodes a putative zinc finger binding protein, as well as possible roles for other loci. The genome-wide studies of at least one class of relatively uncommon variant, submicroscopic chromosomal abnormalities often referred to as copy number variations (CNVs), suggest that these confer high risk of schizophrenia. There is evidence both for an increased burden of CNVs in schizophrenia and that risk is conferred by specific large deletions at 1q21.1 and at 15q13.2 and by deletions of NRXN1 which encodes the synaptic scaffolding protein neurexin 1.

Does the presenilin 2 gene predispose to schizophrenia?

Presenilins are a group of proteins playing an important role in the Notch, ErbB4 and Wnt signaling pathways possibly associated with schizophrenia. The gene coding for presenilin 2 (PSEN2) is located on 1q42 and adjacent to a balanced translocation t (1; 11) (q42; q14.3) that was found to co-segregate within family members of patients with schizophrenia. We thus hypothesized that PSEN2 may contribute to the pathogenesis of schizophrenia. Five functional SNPs (rs1295645, rs11405, rs6759, rs1046240 and rs8383) present in the coding regions of the PSEN2 gene were tested in 410 patients with schizophrenia and 355 controls in a Chinese Han population. Association analysis showed a weak association for rs1295645 and the rs1295645-T allele was involved in increased risk of schizophrenia (corrected p=0.045, OR=1.32, 95% CI 1.04-1.68). The T-C-T-T-T haplotype also showed association with increased risk of the illness (p=1.8x10(-5), OR=3.37, 95% CI 1.33-8.51). Analysis of gene expression demonstrated that PSEN2 mRNA levels in peripheral leukocytes were significantly lower in the patient group than in the control group and that expression levels of the PSEN2 gene were significantly correlated to its genotypes. Analysis of clinical profiles showed an association between the PSEN2 gene and some clinical phenotypes scored using the PANSS. The present results suggest that the PSEN2 gene may be a novel candidate involved in the development of certain psychotic symptoms of schizophrenia although the initial finding needs further replication in a large sample size.

Gene discovery through imaging genetics: identification of two novel genes associated with schizophrenia

We have discovered two genes, RSRC1 and ARHGAP18, associated with schizophrenia and in an independent study provided additional support for this association. We have both discovered and verified the association of two genes, RSRC1 and ARHGAP18, with schizophrenia. We combined a genome-wide screening strategy with neuroimaging measures as the quantitative phenotype and identified the single nucleotide polymorphisms (SNPs) related to these genes as consistently associated with the phenotypic variation. To control for the risk of false positives, the empirical P-value for association significance was calculated using permutation testing. The quantitative phenotype was Blood-Oxygen-Level Dependent (BOLD) Contrast activation in the left dorsal lateral prefrontal cortex measured during a working memory task. The differential distribution of SNPs associated with these two genes in cases and controls was then corroborated in a larger, independent sample of patients with schizophrenia (n=82) and healthy controls (n=91), thus suggesting a putative etiological function for both genes in schizophrenia. Up until now these genes have not been linked to any neuropsychiatric illness, although both genes have a function in prenatal brain development. We introduce the use of functional magnetic resonance imaging activation as a quantitative phenotype in conjunction with genome-wide association as a gene discovery tool.

Genome-wide association for major depressive disorder: a possible role for the presynaptic protein piccolo

Major depressive disorder (MDD) is a common complex trait with enormous public health significance. As part of the Genetic Association Information Network initiative of the US Foundation for the National Institutes of Health, we conducted a genome-wide association study of 435 291 single nucleotide polymorphisms (SNPs) genotyped in 1738 MDD cases and 1802 controls selected to be at low liability for MDD. Of the top 200, 11 signals localized to a 167 kb region overlapping the gene piccolo (PCLO, whose protein product localizes to the cytomatrix of the presynaptic active zone and is important in monoaminergic neurotransmission in the brain) with P-values of 7.7 x 10(-7) for rs2715148 and 1.2 x 10(-6) for rs2522833. We undertook replication of SNPs in this region in five independent samples (6079 MDD independent cases and 5893 controls) but no SNP exceeded the replication significance threshold when all replication samples were analyzed together. However, there was heterogeneity in the replication samples, and secondary analysis of the original sample with the sample of greatest similarity yielded P=6.4 x 10(-8) for the nonsynonymous SNP rs2522833 that gives rise to a serine to alanine substitution near a C2 calcium-binding domain of the PCLO protein. With the integrated replication effort, we present a specific hypothesis for further studies.

GABAergic promoter hypermethylation as a model to study the neurochemistry of schizophrenia vulnerability

The neuronal GABAergic mechanisms that mediate the symptomatic beneficial effects elicited by a combination of antipsychotics with valproate (a histone deacetylase inhibitor) in the treatment of psychosis (expressed by schizophrenia or bipolar disorder patients) are unknown. This prompted us to investigate whether the beneficial action of this combination results from a modification of histone tail covalent esterification or is secondary to specific chromatin remodeling. The results suggest that clozapine, or sulpiride associated with valproate, by increasing DNA demethylation with an unknown mechanism, causes a chromatin remodeling that brings about a beneficial change in the epigenetic GABAergic dysfunction typical of schizophrenia and bipolar disorder patients.

Jean PL, Giegling I, Hartmann AM, Möller HJ, Ruppert A, Fraser G, Crombie C, Middleton LT, St. Clair D, Roses AD, Muglia P, Francks C, Rujescu D, Meltzer HY, Goldstein DB. A genome-wide investigation of SNPs and CNVs in schizophrenia

We report a genome-wide assessment of single nucleotide polymorphisms (SNPs) and copy number variants (CNVs) in schizophrenia. We investigated SNPs using 871 patients and 863 controls, following up the top hits in four independent cohorts comprising 1,460 patients and 12,995 controls, all of European origin. We found no genome-wide significant associations, nor could we provide support for any previously reported candidate gene or genome-wide associations. We went on to examine CNVs using a subset of 1,013 cases and 1,084 controls of European ancestry, and a further set of 60 cases and 64 controls of African ancestry. We found that eight cases and zero controls carried deletions greater than 2 Mb, of which two, at 8p22 and 16p13.11-p12.4, are newly reported here. A further evaluation of 1,378 controls identified no deletions greater than 2 Mb, suggesting a high prior probability of disease involvement when such deletions are observed in cases. We also provide further evidence for some smaller, previously reported, schizophrenia-associated CNVs, such as those in NRXN1 and APBA2. We could not provide strong support for the hypothesis that schizophrenia patients have a significantly greater "load" of large (>100 kb), rare CNVs, nor could we find common CNVs that associate with schizophrenia. Finally, we did not provide support for the suggestion that schizophrenia-associated CNVs may preferentially disrupt genes in neurodevelopmental pathways. Collectively, these analyses provide the first integrated study of SNPs and CNVs in schizophrenia and support the emerging view that rare deleterious variants may be more important in schizophrenia predisposition than common polymorphisms. While our analyses do not suggest that implicated CNVs impinge on particular key pathways, we do support the contribution of specific genomic regions in schizophrenia, presumably due to recurrent mutation. On balance, these data suggest that very few schizophrenia patients share identical genomic causation, potentially complicating efforts to personalize treatment regimens.

The trace amine associated receptor (TAAR6) gene is not associated with schizophrenia in the Irish Case-Control Study of Schizophrenia (ICCSS) sample

To replicate previous association between TAAR6 and schizophrenia, including our own finding in the Irish Study of High Density Schizophrenia Families (ISHDSF) sample, we genotyped 12 single nucleotide polymorphisms (SNPs) in the Irish Case-Control Study of Schizophrenia (ICCSS) sample. Only rs9389020 provided nominal evidence for association (p<0.0228), which did not withstand the permutation testing (p<0.2196). The combined odds ratio from ISHDSF and ICCSS samples [OR (95%CI)=1.0564 (1.0078-1.1074); p=0.02], while nominally significant, did not survive correction for multiple testing. Here we demonstrate that TAAR6 is not associated with schizophrenia in the ICCSS sample.

Chromosome 13q13-q14 locus overlaps mood and psychotic disorders: the relevance for redefining phenotype

The nosology of major psychoses is challenged by the findings that schizophrenia (SZ) and bipolar disorder (BP) share several neurobiological, neuropsychological and clinical phenotypic characteristics. Moreover, several vulnerability loci or genes may be common to the two DSM disorders. We previously reported, in a sample of 21 kindreds (sample 1), a genome-wide suggestive linkage in 13q13-q14 with a common locus (CL) phenotype that crossed the diagnostic boundaries by combining SZ, BP and schizoaffective disorders. Our objectives were to test phenotype specificity in a separate sample (sample 2) of 27 kindreds from Eastern Quebec and to also analyze the combined sample of 48 kindreds (1274 family members). We performed nonparametric and parametric analyses and tested as phenotypes: SZ alone, BP alone, and a CL phenotype. We replicated in sample 2 our initial finding with CL with a maximum NPL(pair) score of 3.36 at D13S1272 (44 Mb), only 2.1 Mb telomeric to our previous maximum result. In the combined sample, the peak with CL was at marker D13S1297 (42.1 Mb) with a NPL(pair) score reaching 5.21, exceeding that obtained in each sample and indicating consistency across the two samples. Our data suggest a susceptibility locus in 13q13-q14 that is shared by schizophrenia and mood disorder. That locus would be additional to another well documented and more distal 13q locus where the G72/G30 gene is mapped.

A genome-wide association study of schizophrenia using brain activation as a quantitative phenotype

BACKGROUND

Genome-wide association studies (GWASs) are increasingly used to identify risk genes for complex illnesses including schizophrenia. These studies may require thousands of subjects to obtain sufficient power. We present an alternative strategy with increased statistical power over a case-control study that uses brain imaging as a quantitative trait (QT) in the context of a GWAS in schizophrenia.

METHODS

Sixty-four subjects with chronic schizophrenia and 74 matched controls were recruited from the Functional Biomedical Informatics Research Network (FBIRN) consortium. Subjects were genotyped using the Illumina HumanHap300 BeadArray and were scanned while performing a Sternberg Item Recognition Paradigm in which they learned and then recognized target sets of digits in an functional magnetic resonance imaging protocol. The QT was the mean blood oxygen level-dependent signal in the dorsolateral prefrontal cortex during the probe condition for a memory load of 3 items.

RESULTS

Three genes or chromosomal regions were identified by having 2 single-nucleotide polymorphisms (SNPs) each significant at P < 10(-6) for the interaction between the imaging QT and the diagnosis (ROBO1-ROBO2, TNIK, and CTXN3-SLC12A2). Three other genes had a significant SNP at <10(-6) (POU3F2, TRAF, and GPC1). Together, these 6 genes/regions identified pathways involved in neurodevelopment and response to stress.

CONCLUSION

Combining imaging and genetic data from a GWAS identified genes related to forebrain development and stress response, already implicated in schizophrenic dysfunction, as affecting prefrontal efficiency. Although the identified genes require confirmation in an independent sample, our approach is a screening method over the whole genome to identify novel SNPs related to risk for schizophrenia.

Schizophrenia genetics: new insights from new approaches

INTRODUCTION

Schizophrenia is a debilitating psychiatric disorder that imposes a considerable burden on sufferers, their families and society. The prominent involvement of genes, combined with the complexity and relative inaccessibility of the brain has led many to suggest that the identification of specific risk loci offers the best chance of understanding pathogenesis.

SOURCES OF DATA

Recent genome-wide association studies (GWAS) and copy number variation (CNV) publications have been included in this review along with key papers from the fields of schizophrenia, functional psychoses and complex disease mapping.

AREAS OF AGREEMENT

Recent GWAS have now shown that both common alleles of small effect and rare alleles of moderate to large effect contribute to the high heritability of schizophrenia.

AREAS OF CONTROVERSY

It is well known that many schizophrenic patients suffer symptoms seen in patients with bipolar disease and vice versa. There is now considerable interest in using aetiologically relevant risk factors, including genes, to explore the validity of the contemporary system of classification.

GROWING POINTS

Rare CNVs have been shown to play a role in at least some cases of schizophrenia and it is highly predictable that this figure will rise with the use of technologies with higher resolution or that are better designed to assay common CNVs reliably.

AREAS TIMELY FOR DEVELOPING RESEARCH

The findings with common alleles thus far point to overlap in the genetic risk for schizophrenia and bipolar disorder, while the specific CNVs implicated in schizophrenia also increase susceptibility to a range of developmental disorders, including autism, mental retardation, attention deficit-hyperactivity disorder (ADHD) and epilepsy.

New findings from genetic association studies of schizophrenia

In the past 20 years, association studies of schizophrenia have evolved from analyses in lesser than 100 subjects of one or two markers in candidate genes to systematic analyses of association at a genome-wide level in samples of thousands of subjects. During this process, much of the emergent literature has been difficult to interpret and definitive findings that have met with universal acceptance have been elusive, largely because studies have been underpowered for such conclusions to be drawn. Nevertheless, in the course of the past few years, a few promising candidate genes have been reported for which the evidence is positive across multiple studies, and more recently, genome-wide association studies have yielded findings of a compelling nature. It is clear that genetic studies in schizophrenia have borne fruit, a process that can be expected to accelerate in the next few years, and that these findings are providing new avenues for research into the pathophysiology of this poorly understood disorder.

A systematic method for estimating individual responses to treatment with antipsychotics in CATIE

OBJECTIVE

In addition to comparing drug treatment groups, the wealth of genetic and clinical data collected in the Clinical Antipsychotic Trials of Intervention Effectiveness study offers tremendous opportunities to study individual differences in response to treatment with antipsychotics. A major challenge, however, is how to estimate the individual responses to treatments. For this purpose, we propose a systematic method that condenses all information collected during the trials in an optimal, empirical fashion.

METHODS

Our method comprises three steps. First, we test how to best model treatment effects over time. Next, we screen many covariates to select those that will further improve the precision of the individual treatment effect estimates which, for example, improves power to detect predictors of individual treatment response. Third, Best Linear Unbiased Predictors (BLUPs) of the random effects are used to estimate for each individual a treatment effect based on the model empirically indicated to best fit the data. We illustrate our method for the Positive and Negative Syndrome Scale (PANSS).

RESULTS

A model assuming it takes on average about 30 days for a treatment to exert an effect that will then remain about the same for the rest of the trial showed the best fit to the data. Of all screened covariates, only two improved the precision of the individual treatment effect estimates. Finally, correlations between drug effects and PANSS scales suggested that in CATIE it cannot be recommended to simply combine treatment effects across drugs (e.g. to study common drug mechanisms), but it is sensible to study how a given drug affects multiple symptom dimensions.

CONCLUSIONS

We demonstrate that treatment effects can be estimated in a way that condenses all information collected in an optimal, empirical fashion. We expect the proposed method to be valuable for other clinical outcomes in CATIE and potentially other clinical trials.

Functional polymorphisms in PRODH are associated with risk and protection for schizophrenia and fronto-striatal structure and function

PRODH, encoding proline oxidase (POX), has been associated with schizophrenia through linkage, association, and the 22q11 deletion syndrome (Velo-Cardio-Facial syndrome). Here, we show in a family-based sample that functional polymorphisms in PRODH are associated with schizophrenia, with protective and risk alleles having opposite effects on POX activity. Using a multimodal imaging genetics approach, we demonstrate that haplotypes constructed from these risk and protective functional polymorphisms have dissociable correlations with structure, function, and connectivity of striatum and prefrontal cortex, impacting critical circuitry implicated in the pathophysiology of schizophrenia. Specifically, the schizophrenia risk haplotype was associated with decreased striatal volume and increased striatal-frontal functional connectivity, while the protective haplotype was associated with decreased striatal-frontal functional connectivity. Our findings suggest a role for functional genetic variation in POX on neostriatal-frontal circuits mediating risk and protection for schizophrenia.

Schizophrenia is a major mental illness affecting 1% of the population. It is known that genetics plays a role in the disease susceptibility, and it is thought that the illness is a complex disorder involving multiple genes. We show that the schizophrenia susceptibility gene, PRODH, conveys its risk through a variation that increases its enzyme activity. We further show that protection is associated with variations that decrease enzyme activity and these protective variations are enriched in their unaffected siblings. We then used brain imaging of structure and memory function to dissect the risk and protective haplotypes differential effects, and found that the schizophrenia risk haplotype was associated with decreased striatal gray matter volume and increased subcortical to frontal lobe functional connectivity, while the schizophrenia protective haplotype was associated with trend-level increase of frontal lobe volume and decreased subcortical to frontal lobe connectivity. These findings indicate a new target for treating schizophrenia and characterize associated structural and functional deficits.

Genetic research in schizophrenia: new tools and future perspectives

Genetically, schizophrenia is a complex disease whose pathogenesis is likely governed by a number of different risk factors. While substantial efforts have been made to identify the underlying susceptibility alleles over the past 2 decades, they have been of only limited success. Each year, the field is enriched with nearly 150 additional genetic association studies, each of which either proposes or refutes the existence of certain schizophrenia genes. To facilitate the evaluation and interpretation of these findings, we have recently created a database for genetic association studies in schizophrenia ("SzGene"; available at http://www.szgene.org). In addition to systematically screening the scientific literature for eligible studies, SzGene also reports the results of allele-based meta-analyses for polymorphisms with sufficient genotype data. Currently, these meta-analyses highlight not only over 20 different potential schizophrenia genes, many of which represent the "usual suspects" (eg, various dopamine receptors and neuregulin 1), but also several that were never meta-analyzed previously. All the highlighted loci contain at least one variant showing modest (summary odds ratios approximately 1.20 [range 1.06-1.45]) but nominally significant risk effects. This review discusses some of the strengths and limitations of the SzGene database, which could become a useful bioinformatics tool within the schizophrenia research community.

Psychiatric genetics: progress amid controversy

Several psychiatric disorders--such as bipolar disorder, schizophrenia and autism--are highly heritable, yet identifying their genetic basis has been challenging, with most discoveries failing to be replicated. However, inroads have been made by the incorporation of intermediate traits (endophenotypes) and of environmental factors into genetic analyses, and through the identification of rare inherited variants and novel structural mutations. Current efforts aim to increase sample sizes by gathering larger samples for case-control studies or through meta-analyses of such studies. More attention on unique families, rare variants, and on incorporating environment and the emerging knowledge of biological function and pathways into genetic analysis is warranted.

Genetic causality in schizophrenia and bipolar disorder: out with the old and in with the new

Schizophrenia (SZ) and bipolar disorder are highly heritable forms of major mental illness. Great hopes were held out for a major breakthrough with the advent of genome wide association studies, but to date there have been no obvious low hanging fruit. A richer harvest of strong candidates has however emerged from molecular cytogenetics and copy number variant mapping strategies promise to add more. Both strategies identify gene mutations, paving a direct path to biological studies and tests of causality. Risk genes and convergent biological pathways common to both disorders are being revealed, offering hope for a better understanding of aetiological factors and for the development of biomarkers to aid in diagnosis and prognosis.

Schizophrenia genetics: the search for a hard lead

PURPOSE OF REVIEW

To describe the rationale for searching for genes for schizophrenia, prior efforts via candidate gene association and genomewide linkage studies, and to set the stage for the numerous genomewide association studies that will emerge by the end of 2008.

RECENT FINDINGS

Genomewide association studies have identified dozens of new and previously unsuspected candidate genes for many biomedical disorders. At least seven new studies of approximately 20,000 cases plus controls are expected to be completed by the end of 2008.

SUMMARY

Current results have few implications for clinical practice or research, and it is possible that this recommendation could be dramatically different in a year.