Dissecting the phenotype in genome-wide association studies of psychiatric illness

Can we achieve pain stratification in musculoskeletal conditions? Implications for clinical practice

In the last few years there has been an increased appreciation that pain perception in rheumatic and musculoskeletal diseases (RMDs) has several mechanisms which include nociceptive, inflammatory, nociplastic and neuropathic components. Studies in specific patient groups have also demonstrated that the pain experienced by people with specific diagnoses can present with distinctive components over time. For example, the pain observed in rheumatoid arthritis has been widely accepted to be caused by the activation of nociceptors, potentiated by the release of inflammatory mediators, including prostaglandins, leukotrienes and cytokine networks in the joint environment. However, people with RA may also experience nociplastic and neuropathic pain components, particularly when treatments with disease modifying anti-rheumatic drugs (DMARDs) have been implemented and are insufficient to control pain symptoms. In other RMDs, the concept of pain sensitisation or nociplastic pain in driving ongoing pain symptoms e.g. osteoarthritis and fibromyalgia, is becoming increasingly recognised. In this review, we explore the hypothesis that pain has distinct modalities based on clinical, pathophysiological, imaging and genetic factors. The concept of pain stratification in RMD is explored and implications for future management are also discussed.

A Guide to Genome-Wide Association Study Design for Diabetic Retinopathy

Diabetic retinopathy (DR) is the most common microvascular complication related to diabetes. There is evidence that genetics play an important role in DR pathogenesis, but the complexity of the disease makes genetic studies a challenge. This chapter is a practical overview of the basic steps for genome-wide association studies with respect to DR and its associated traits. Also described are approaches that can be adopted in future DR studies. This is intended to serve as a guide for beginners and to provide a framework for further in-depth analysis.

Probing the molecular and cellular pathological mechanisms of schizophrenia using human induced pluripotent stem cell models

With recent advancements in psychiatric genomics, as a field, "stem cell-based disease modelers" were given the exciting yet daunting task of translating the extensive list of disease-associated risks into biologically and clinically relevant information in order to deliver therapeutically meaningful leads and insights. Despite their limitations, human induced pluripotent stem cell (iPSCs) based models have greatly aided our understanding of the molecular and cellular mechanisms underlying the complex etiology of brain disorders including schizophrenia (SCZ). In this review, we summarize the major findings from studies in the past decade which utilized iPSC models to investigate cell type-specific phenotypes relevant to idiopathic SCZ and disease penetrant alleles. Across cell type differences, several biological themes emerged, serving as potential neurodevelopmental mechanisms of SCZ, including oxidative stress and mitochondrial dysfunction, depletion of progenitor pools and insufficient differentiation potential of these progenitors, and structural and functional deficits of neurons and other supporting cells. Here, we discuss both the recent progress as well as challenges and improvements needed for future studies utilizing iPSCs as a model for SCZ and other neuropsychiatric disorders.

Genetics of eating disorders in the genome-wide era

Enabled by advances in high throughput genomic sequencing and an unprecedented level of global data sharing, molecular genetic research is beginning to unlock the biological basis of eating disorders. This invited review provides an overview of genetic discoveries in eating disorders in the genome-wide era. To date, five genome-wide association studies on eating disorders have been conducted - all on anorexia nervosa (AN). For AN, several risk loci have been detected, and ~11-17% of the heritability has been accounted for by common genetic variants. There is extensive genetic overlap between AN and psychological traits, especially obsessive-compulsive disorder, and intriguingly, with metabolic phenotypes even after adjusting for body mass index (BMI) risk variants. Furthermore, genetic risk variants predisposing to lower BMI may be causal risk factors for AN. Causal genes and biological pathways of eating disorders have yet to be elucidated and will require greater sample sizes and statistical power, and functional follow-up studies. Several studies are underway to recruit individuals with bulimia nervosa and binge-eating disorder to enable further genome-wide studies. Data collections and research labs focused on the genetics of eating disorders have joined together in a global effort with the Psychiatric Genomics Consortium. Molecular genetics research in the genome-wide era is improving knowledge about the biology behind the established heritability of eating disorders. This has the potential to offer new hope for understanding eating disorder etiology and for overcoming the therapeutic challenges that confront the eating disorder field.

Polygenic risk scores in the clinic: new perspectives needed on familiar ethical issues

Clinical use of polygenic risk scores (PRS) will look very different to the more familiar monogenic testing. Here we argue that despite these differences, most of the ethical, legal, and social issues (ELSI) raised in the monogenic setting, such as the relevance of results to family members, the approach to secondary and incidental findings, and the role of expert mediators, continue to be relevant in the polygenic context, albeit in modified form. In addition, PRS will reanimate other old debates. Their use has been proposed both in the practice of clinical medicine and of public health, two contexts with differing norms. In each of these domains, it is unclear what endpoints clinical use of PRS should aim to maximize and under what constraints. Reducing health disparities is a key value for public health, but clinical use of PRS could exacerbate race-based health disparities owing to differences in predictive power across ancestry groups. Finally, PRS will force a reckoning with pre-existing questions concerning biomarkers, namely the relevance of self-reported race, ethnicity and ancestry, and the relationship of risk factors to disease diagnoses. In this Opinion, we argue that despite the parallels to the monogenic setting, new work is urgently needed to gather data, consider normative implications, and develop best practices around this emerging branch of genomics.

A Systematic Review of Extreme Phenotype Strategies to Search for Rare Variants in Genetic Studies of Complex Disorders

Exome sequencing has been commonly used to characterize rare diseases by selecting multiplex families or singletons with an extreme phenotype (EP) and searching for rare variants in coding regions. The EP strategy covers both extreme ends of a disease spectrum and it has been also used to investigate the contribution of rare variants to the heritability of complex clinical traits. We conducted a systematic review to find evidence supporting the use of EP strategies in the search for rare variants in genetic studies of complex diseases and highlight the contribution of rare variations to the genetic structure of polygenic conditions. After assessing the quality of the retrieved records, we selected 19 genetic studies considering EPs to demonstrate genetic association. All studies successfully identified several rare or de novo variants, and many novel candidate genes were also identified by selecting an EP. There is enough evidence to support that the EP approach for patients with an early onset of a disease can contribute to the identification of rare variants in candidate genes or pathways involved in complex diseases. EP patients may contribute to a better understanding of the underlying genetic architecture of common heterogeneous disorders such as tinnitus or age-related hearing loss.

Alternate approach to stroke phenotyping identifies a genetic risk locus for small vessel stroke

Ischemic stroke (IS), caused by obstruction of cerebral blood flow, is one of the leading causes of death. While neurologists agree on delineation of IS into three subtypes (cardioembolic stroke (CES), large artery stroke (LAS), and small vessel stroke (SVS)), several subtyping systems exist. The most commonly used systems are TOAST (Trial of Org 10172 in Acute Stroke Treatment) and CCS (Causative Classification System for Stroke), but agreement is only moderate. We have compared two approaches to combining the existing subtyping systems for a phenotype suited for a genome-wide association study (GWAS). We used the NINDS Stroke Genetics Network dataset (SiGN, 11,477 cases with CCS and TOAST subtypes and 28,026 controls). We defined two new phenotypes: the intersect, for which an individual must be assigned the same subtype by CCS and TOAST; and the union, for which an individual must be assigned a subtype by either CCS or TOAST. The union yields the largest sample size while the intersect yields a phenotype with less potential misclassification. We performed GWAS for all subtypes, using the original subtyping systems, the intersect, and the union as phenotypes. In each subtype, heritability was higher for the intersect compared with the other phenotypes. We observed stronger effects at known IS variants with the intersect compared with the other phenotypes. With the intersect, we identify rs10029218:G>A as an associated variant with SVS. We conclude that this approach increases the likelihood to detect genetic associations in ischemic stroke.

Identifying novel associations in GWAS by hierarchical Bayesian latent variable detection of differentially misclassified phenotypes

Background

Heterogeneity in the definition and measurement of complex diseases in Genome-Wide Association Studies (GWAS) may lead to misdiagnoses and misclassification errors that can significantly impact discovery of disease loci. While well appreciated, almost all analyses of GWAS data consider reported disease phenotype values as is without accounting for potential misclassification.

Results

Here, we introduce Phenotype Latent variable Extraction of disease misdiagnosis (PheLEx), a GWAS analysis framework that learns and corrects misclassified phenotypes using structured genotype associations within a dataset. PheLEx consists of a hierarchical Bayesian latent variable model, where inference of differential misclassification is accomplished using filtered genotypes while implementing a full mixed model to account for population structure and genetic relatedness in study populations. Through simulations, we show that the PheLEx framework dramatically improves recovery of the correct disease state when considering realistic allele effect sizes compared to existing methodologies designed for Bayesian recovery of disease phenotypes. We also demonstrate the potential of PheLEx for extracting new potential loci from existing GWAS data by analyzing bipolar disorder and epilepsy phenotypes available from the UK Biobank. From the PheLEx analysis of these data, we identified new candidate disease loci not previously reported for these datasets that have value for supplemental hypothesis generation.

Conclusion

PheLEx shows promise in reanalyzing GWAS datasets to provide supplemental candidate loci that are ignored by traditional GWAS analysis methodologies.

Alcohol misuse in bipolar disorder. A systematic review and meta-analysis of comorbidity rates

Aims:

To assess the comorbidity rates of alcohol use disorders (AUDs) in bipolar disorder (BD) and to explore possible sources of heterogeneity.

Methods:

Studies were identified through database searches. Meta-analytic techniques were employed to aggregate data on lifetime comorbidity and to explore possible sources of heterogeneity. Funnel plots were used to detect publication bias.

Results:

In clinical studies, AUDs affected more than one in three subjects with BD. Significant heterogeneity was found, which was largely explained by the geographical location of study populations and gender ratio of participants. AUDs affected more than one in five women and two in five men.

Conclusion:

AUDs are highly prevalent in BD. Our study revealed a substantial heterogeneity across studies. Further research including control groups is needed. Patients with BD should be assessed for current and previous AUDs.

Cross-Disorder Cognitive Impairments in Youth Referred for Neuropsychiatric Evaluation

OBJECTIVES

Studies suggest that impairments in some of the same domains of cognition occur in different neuropsychiatric conditions, including those known to share genetic liability. Yet, direct, multi-disorder cognitive comparisons are limited, and it remains unclear whether overlapping deficits are due to comorbidity. We aimed to extend the literature by examining cognition across different neuropsychiatric conditions and addressing comorbidity.

METHODS

Subjects were 486 youth consecutively referred for neuropsychiatric evaluation and enrolled in the Longitudinal Study of Genetic Influences on Cognition. First, we assessed general ability, reaction time variability (RTV), and aspects of executive functions (EFs) in youth with non-comorbid forms of attention-deficit/hyperactivity disorder (ADHD), mood disorders and autism spectrum disorder (ASD), as well as in youth with psychosis. Second, we determined the impact of comorbid ADHD on cognition in youth with ASD and mood disorders.

RESULTS

For EFs (working memory, inhibition, and shifting/ flexibility), we observed weaknesses in all diagnostic groups when participants' own ability was the referent. Decrements were subtle in relation to published normative data. For RTV, weaknesses emerged in youth with ADHD and mood disorders, but trend-level results could not rule out decrements in other conditions. Comorbidity with ADHD did not impact the pattern of weaknesses for youth with ASD or mood disorders but increased the magnitude of the decrement in those with mood disorders.

CONCLUSIONS

Youth with ADHD, mood disorders, ASD, and psychosis show EF weaknesses that are not due to comorbidity. Whether such cognitive difficulties reflect genetic liability shared among these conditions requires further study. (JINS, 2018, 24, 91-103).

Psychiatric Genomics: An Update and an Agenda

The Psychiatric Genomics Consortium (PGC) is the largest consortium in the history of psychiatry. This global effort is dedicated to rapid progress and open science, and in the past decade it has delivered an increasing flow of new knowledge about the fundamental basis of common psychiatric disorders. The PGC has recently commenced a program of research designed to deliver "actionable" findings-genomic results that 1) reveal fundamental biology, 2) inform clinical practice, and 3) deliver new therapeutic targets. The central idea of the PGC is to convert the family history risk factor into biologically, clinically, and therapeutically meaningful insights. The emerging findings suggest that we are entering a phase of accelerated genetic discovery for multiple psychiatric disorders. These findings are likely to elucidate the genetic portions of these truly complex traits, and this knowledge can then be mined for its relevance for improved therapeutics and its impact on psychiatric practice within a precision medicine framework. [AJP at 175: Remembering Our Past As We Envision Our Future November 1946: The Genetic Theory of Schizophrenia Franz Kallmann's influential twin study of schizophrenia in 691 twin pairs was the largest in the field for nearly four decades. (Am J Psychiatry 1946; 103:309-322 )].

Evaluation of inner retinal layers with optic coherence tomography in vigabatrin-exposed patients

In order to reveal the underlying retinal pathology leading to dysfunction in vigabatrin-exposed patients, we aimed to evaluate the inner retinal layers encompassing ganglion cell complex (GCC) layer and inner plexiform layer with new generation optic coherence tomography (OCT). Fourteen patients with epilepsy and exposure to vigabatrin and 12 clinically normal individuals, constituting the control group, were included. Retinal images were obtained using spectral-domain OCT (Optovue RTVue Fourier domain). Nasal and superior quadrants of retinal nerve fiber layer (RNFL) were found to be significantly lower in the patient group compared to the controls (p < 0.01). No significant difference was shown in the thickness of GCC layer (p > 0.05). Foveal thickness was significantly higher in the patient group (p: 0.006), but no significant difference was found in perifoveal and parafoveal regions between groups (p > 0.05). The thickness of RNFL was found to be lower in vigabatrin-exposed patients without any reduction in GCC layer in the macular region. However, foveal thickness was found to be significantly higher compared to perifoveal and parafoveal macular regions in vigabatrin-exposed patients. In conclusion, OCT revealed reduced thickness of RNFL without any reduction in ganglion cell layer in our study. The objective quantitative assessment of OCT is a practical noninvasive method and it can have role in future monitoring of these patients.

Cross-Disorder Psychiatric Genomics

PURPOSE OF REVIEW

The following review provides some description of the movement in cross-disorder psychiatric genomics toward addressing both comorbidity and polygenicity.

RECENT FINDINGS

We attempt to show how dimensional approaches to the phenotype have led to further addressing the problem of comorbidity of psychiatric diagnoses. And we also attempt to show how a dimensional approach to the genome, with different statistical methods from traditional genome-wide association analyses, has begun to resolve the problem of massive polygenicity.

SUMMARY

Cross-disorder research, of any area in psychiatry, arguably has the most potential to inform clinical diagnosis, early detection and prevention strategies, and pharmacological treatment research. Future research might leverage what we now know to inform developmental studies of risk and resilience.

Ethnicity and Psychiatric Disorders

Psychiatric disorders are one of the leading causes of disease-related disability in the world today. However, little is known about the ethnic variation of these disorders within populations. This is especially true in contexts outside of the United States and the European Diaspora. This study provides new evidence from South Asia on ethnic differences in Major Depressive Episode, Major Depressive Disorder, Panic Attack, Panic Disorder, Post-Traumatic Stress Disorder, and Intermittent Explosive Disorder. We use data from 400 adult interviews conducted in Nepal in a controlled comparison design as a case study. We use a series of multilevel logistic regression models to predict ethnic group differences in psychiatric disorders and episodes with measures from clinically validated World Mental Health survey instruments. Compared to the Brahmin/Chhetri group, we found historically excluded Dalits had statistically significantly higher odds of almost all psychiatric disorders and episodes. We also found that historically resilient Janajatis had statistically significantly lower odds of being diagnosed with PTSD than the majority Brahmin/Chhetri group. We also found no significant gender difference in MDD or MDE. Psychiatric disorders and episodes vary significantly by ethnicity within a rural Asian population, but gender differences are small.

An autism case history to review the systematic analysis of large-scale data to refine the diagnosis and treatment of neuropsychiatric disorders

Analysis of large-scale systems of biomedical data provides a perspective on neuropsychiatric disease that may be otherwise elusive. Described here is an analysis of three large-scale systems of data from autism spectrum disorder (ASD) and of ASD research as an exemplar of what might be achieved from study of such data. First is the biomedical literature that highlights the fact that there are two very successful but quite separate research communities and findings pertaining to genetics and the molecular biology of ASD. There are those studies positing ASD causes that are related to immunological dysregulation and those related to disorders of synaptic function and neuronal connectivity. Second is the emerging use of electronic health record systems and other large clinical databases that allow the data acquired during the course of care to be used to identify distinct subpopulations, clinical trajectories, and pathophysiological substructures of ASD. These systems reveal subsets of patients with distinct clinical trajectories, some of which are immunologically related and others which follow pathologies conventionally thought of as neurological. The third is genome-wide genomic and transcriptomic analyses which show molecular pathways that overlap neurological and immunological mechanisms. The convergence of these three large-scale data perspectives illustrates the scientific leverage that large-scale data analyses can provide in guiding researchers in an approach to the diagnosis of neuropsychiatric disease that is inclusive and comprehensive.

Molecular network analysis enhances understanding of the biology of mental disorders

We provide an introduction to network theory, evidence to support a connection between molecular network structure and neuropsychiatric disease, and examples of how network approaches can expand our knowledge of the molecular bases of these diseases. Without systematic methods to derive their biological meanings and inter-relatedness, the many molecular changes associated with neuropsychiatric disease, including genetic variants, gene expression changes, and protein differences, present an impenetrably complex set of findings. Network approaches can potentially help integrate and reconcile these findings, as well as provide new insights into the molecular architecture of neuropsychiatric diseases. Network approaches to neuropsychiatric disease are still in their infancy, and we discuss what might be done to improve their prospects.

Replication of bipolar disorder susceptibility alleles and identification of two novel genome-wide significant associations in a new bipolar disorder case-control sample

We have conducted a genotyping study using a custom Illumina Infinium HD genotyping array, the ImmunoChip, in a new UK sample of 1218 bipolar disorder (BD) cases and 2913 controls that have not been used in any studies previously reported independently or in meta-analyses. The ImmunoChip was designed before the publication of the Psychiatric Genome-Wide Association Study Consortium Bipolar Disorder Working Group (PGC-BD) meta-analysis data. As such 3106 single-nucleotide polymorphisms (SNPs) with a P-value <1 × 10(-3) from the BD meta-analysis by Ferreira et al. were genotyped. We report support for two of the three most strongly associated chromosomal regions in the Ferreira study, CACNA1C (rs1006737, P=4.09 × 10(-4)) and 15q14 (rs2172835, P=0.043) but not ANK3 (rs10994336, P=0.912). We have combined our ImmunoChip data (569 quasi-independent SNPs from the 3016 SNPs genotyped) with the recently published PGC-BD meta-analysis data, using either the PGC-BD combined discovery and replication data where available or just the discovery data where the SNP was not typed in a replication sample in PGC-BD. Our data provide support for two regions, at ODZ4 and CACNA1C, with prior evidence for genome-wide significant (GWS) association in PGC-BD meta-analysis. In addition, the combined analysis shows two novel GWS associations. First, rs7296288 (P=8.97 × 10(-9), odds ratio (OR)=0.9), an intergenic polymorphism on chromosome 12 located between RHEBL1 and DHH. Second, rs3818253 (P=3.88 × 10(-8), OR=1.16), an intronic SNP on chromosome 20q11.2 in the gene TRPC4AP, which lies in a high linkage disequilibrium region along with the genes GSS and MYH7B.

Shared polygenic contribution between childhood attention-deficit hyperactivity disorder and adult schizophrenia

BACKGROUND

There is recent evidence of some degree of shared genetic susceptibility between adult schizophrenia and childhood attention-deficit hyperactivity disorder (ADHD) for rare chromosomal variants.

AIMS

To determine whether there is overlap between common alleles conferring risk of schizophrenia in adults with those that do so for ADHD in children.

METHOD

We used recently published Psychiatric Genome-wide Association Study (GWAS) Consortium (PGC) adult schizophrenia data to define alleles over-represented in people with schizophrenia and tested whether those alleles were more common in 727 children with ADHD than in 2067 controls.

RESULTS

Schizophrenia risk alleles discriminated ADHD cases from controls (P = 1.04 × 10(-4), R(2) = 0.45%); stronger discrimination was given by alleles that were risk alleles for both adult schizophrenia and adult bipolar disorder (also derived from a PGC data-set) (P = 9.98 × 10(-6), R(2) = 0.59%).

CONCLUSIONS

This increasing evidence for a small, but significant, shared genetic susceptibility between adult schizophrenia and childhood ADHD highlights the importance of research work across traditional diagnostic boundaries.

Genetics of bipolar disorder

Studies of families and twins show the importance of genetic factors affecting susceptibility to bipolar disorder and suggest substantial genetic and phenotypic complexity. Robust and replicable genome-wide significant associations have recently been reported in genome-wide association studies at several common polymorphisms, including variants within the genes CACNA1C, ODZ4, and NCAN. Strong evidence exists for a polygenic contribution to risk (ie, many risk alleles of small effect). A notable finding is the overlap of susceptibility between bipolar disorder and schizophrenia for several individual risk alleles and for the polygenic risk. By contrast, genomic structural variation seems to play a smaller part in bipolar disorder than it does in schizophrenia. Together, these genetic findings suggest directions for future studies to delineate the aetiology and pathogenesis of bipolar disorder, indicate the need to re-evaluate our diagnostic classifications, and might eventually pave the way for major improvements in clinical management.

Family history of schizophrenia and bipolar disorder as risk factors for autism

CONTEXT

The clinical and etiologic relation between autism spectrum disorders (ASDs) and schizophrenia is unclear. The degree to which these disorders share a basis in etiology has important implications for clinicians, researchers, and those affected by the disorders.

OBJECTIVE

To determine whether a family history of schizophrenia and/or bipolar disorder is a risk factor for ASD.

DESIGN, SETTING, AND PARTICIPANTS

We conducted a case-control evaluation of histories of schizophrenia or bipolar disorder in first-degree relatives of probands in 3 samples—population registers in Sweden, Stockholm County (in Sweden), and Israel. Probands met criteria for ASD, and affection status of parents and siblings for schizophrenia and bipolar disorder were established.

RESULTS

The presence of schizophrenia in parents was associated with an increased risk for ASD in a Swedish national cohort (odds ratio [OR], 2.9; 95% CI, 2.5-3.4) and a Stockholm County cohort (OR, 2.9; 95% CI, 2.0-4.1). Similarly, schizophrenia in a sibling was associated with an increased risk for ASD in a Swedish national cohort (OR, 2.6; 95% CI, 2.0-3.2) and an Israeli conscription cohort (OR, 12.1; 95% CI, 4.5-32.0). Bipolar disorder showed a similar pattern of associations but of lesser magnitude.

CONCLUSIONS

Findings from these 3 registers along with consistent findings from a similar study in Denmark suggest that ASD, schizophrenia, and bipolar disorder share common etiologic factors.

Genetic heterogeneity according to age at onset in bipolar disorder: a combined positional cloning and candidate gene approach

This study is the first that formally tests for genetic heterogeneity of bipolar disorder (BD) according to age at onset (AAO) sub-groups by combining positional cloning and candidate gene approaches. Our previous genome-wide linkage-scan identified five genomic regions linked to early-onset form of BD. The present study uses association analysis to test genetic heterogeneity of candidate genes located in these five regions in a sample of 443 unrelated bipolar patients and 1,731 controls. The study involved the following steps: (1) test of heterogeneity by comparing early-onset BD patients versus later-onset BD patients; and (2) for significant results in step 1, comparison of early-onset BD patients and later-onset BD patients separately to controls. Two types of analyses were used: the single SNP test and the gene-based association test. We provide evidence for genetic heterogeneity within the ADRB2 (beta-2adrenoreceptor) gene region that is specifically associated with the early onset form of BD with an OR of 1.8. Unfortunately, the genotyping coverage of ADRB2 in the Wellcome Trust Case Control Consortium sample meant undermined our efforts to undertake a replication. However, as the ADRB2 gene product directly interacts with the CACNA1C gene product, and is known to be implicated in BD susceptibility, we conclude that further exploration of the relationships between ADRB2 and BD needs to be undertaken.

Effects of a mis-sense DISC1 variant on brain activation in two cohorts at high risk of bipolar disorder or schizophrenia

Bipolar disorder and schizophrenia share a number of clinical features and genetic risk variants of small effect, suggesting overlapping pathogenic mechanisms. The effect of single genetic risk variants on brain function is likely to differ in people at high familial risk versus controls as these individuals have a higher overall genetic loading and are therefore closer to crossing a threshold of disease liability. Therefore, whilst the effects of genetic risk variants on brain function may be similar across individuals at risk of both disorders, they are hypothesized to differ compared to that seen in control subjects. We sought to examine the effects of the DISC1 Leu(607) Phe polymorphism on brain activation in young healthy individuals at familial risk of bipolar disorder (n = 84), in a group of controls (n = 78), and in a group at familial risk of schizophrenia (n = 47), performing a language task. We assessed whether genotype effects on brain activation differed according to risk status. There was a significant genotype × group interaction in a cluster centered on the left pre/postcentral gyrus, extending to the inferior frontal gyrus. The origin of this genotype × group effect originated from a significant effect of the presumed risk variant (Phe) on brain activation in the control group, which was absent in both high-risk groups. Differential effects of this polymorphism in controls compared to the two familial groups suggests a commonality of effect across individuals at high-risk of the disorders, which is likely to be dependant upon existing genetic background.

Association study of serotonin pathway genes in attempted suicide

Epidemiological studies, such as family, twin, and adoption studies, demonstrate the presence of a heritable component to both attempted and completed suicide. Some of this heritability is accounted for by the presence of comorbid psychiatric disorders, but the evidence also indicates that a portion of this heritability is specific to suicidality. The serotonergic system has been studied extensively in this phenotype, but findings have been inconsistent, possibly due to the presence of multiple susceptibility variants and/or gene-gene interactions. In this study, we genotyped 174 tag and coding single nucleotide polymorphisms (SNPs) from 17 genes within the serotonin pathway on 516 subjects with a major mood disorder and a history of a suicide attempt (cases) and 515 healthy controls, with the goal of capturing the common genetic variation across each of these candidate genes. We tested the 174 markers in single-SNP, haplotype, gene-based, and epistasis analyses. While these association analyses identified multiple marginally significant SNPs, haplotypes, genes, and interactions, none of them survived correction for multiple testing. Additional studies, including assessment in larger sample sets and deep resequencing to identify rare causal variants, may be required to fully understand the role that the serotonin pathway plays in suicidal behavior.

Comprehensive gene-based association study of a chromosome 20 linked region implicates novel risk loci for depressive symptoms in psychotic illness

BACKGROUND

Prior genomewide scans of schizophrenia support evidence of linkage to regions of chromosome 20. However, association analyses have yet to provide support for any etiologically relevant variants.

METHODS

We analyzed 2988 LD-tagging single nucleotide polymorphisms (SNPs) in 327 genes on chromosome 20, to test for association with schizophrenia in 270 Irish high-density families (ISHDSF, N = 270 families, 1408 subjects). These SNPs were genotyped using an Illumina iSelect genotyping array which employs the Infinium assay. Given a previous report of novel linkage with chromosome 20p using latent classes of psychotic illness in this sample, association analysis was also conducted for each of five factor-derived scores based on the Operational Criteria Checklist for Psychotic Illness (delusions, hallucinations, mania, depression, and negative symptoms). Tests of association were conducted using the PDTPHASE and QPDTPHASE packages of UNPHASED. Empirical estimates of gene-wise significance were obtained by adaptive permutation of a) the smallest observed P-value and b) the threshold-truncated product of P-values for each locus.

RESULTS

While no single variant was significant after LD-corrected Bonferroni-correction, our gene-dropping analyses identified loci which exceeded empirical significance criteria for both gene-based tests. Namely, R3HDML and C20orf39 are significantly associated with depressive symptoms of schizophrenia (P(emp)<2×10⁻⁵) based on the minimum P-value and truncated-product methods, respectively.

CONCLUSIONS

Using a gene-based approach to family-based association, R3HDML and C20orf39 were found to be significantly associated with clinical dimensions of schizophrenia. These findings demonstrate the efficacy of gene-based analysis and support previous evidence that chromosome 20 may harbor schizophrenia susceptibility or modifier loci.

Validity of bipolar disorder hospital discharge diagnoses: file review and multiple register linkage in Sweden

OBJECTIVE

Hospital discharge registers (HDRs) are frequently used in epidemiological research. However, the validity of several important psychiatric diagnostic entities, including bipolar disorder, remains uncertain. Hence, we aimed to develop an optimal algorithm for register-based identification of DSM-IV-TR bipolar disorder.

METHOD

We identified potential cases in the Swedish national HDR using two separate discharge diagnoses of bipolar disorder according to ICD versions 8-10 during January 1, 1973 to December 31, 2004. In a randomly selected subsample of 135 cases from the county of Sörmland, two senior psychiatrists reassessed the diagnostic status based on patients' medical records. We scrutinized false-positive cases and modified the initial algorithm to improve positive predictive value while minimizing false negatives. Finally, we externally validated resulting caseness algorithms by linking HDR diagnostic data with best-estimate clinical diagnoses from the National Quality Assurance Register for Bipolar Disorder (BipoläR), dispensed lithium prescriptions from the National Prescribed Drug Register, and the ICD-10 diagnoses from the National Outpatient Register respectively.

RESULTS

The algorithm with two discharge diagnoses of bipolar disorder yielded a positive predictive value of 0.81. Modification by excluding individuals diagnosed with ICD-8 296.20 (manic-depressive psychosis, depressed type), and/or ICD-9 296.B (unipolar affective psychosis, melancholic form), gave a positive positive predictive value of 0.92. The modified algorithm also had statistically superior external validity compared with the original algorithm.

CONCLUSION

Our findings suggest that DSM-IV-TR bipolar disorder caseness based on two inpatient episodes with a bipolar disorder diagnosis is sufficiently sensitive and specific to be used in further epidemiological study of bipolar disorder.

Research review: gene-environment interaction research in youth depression - a systematic review with recommendations for future research

BACKGROUND

Depression is a major public health problem among youth, currently estimated to affect as many as 9% of US children and adolescents. The recognition that both genes (nature) and environments (nurture) are important for understanding the etiology of depression has led to a rapid growth in research exploring gene-environment interactions (GxE). However, there has been no systematic review of GxE in youth depression to date.

METHODS

The goal of this article was to systematically review evidence on the contribution of GxE to the risk of child and adolescent depression. Through a search of PubMed and PsycINFO databases to 1 April 2010, we identified 20 candidate gene-environment interaction studies focused on depression in youth (up to age 26) and compared each study in terms of the following characteristics: research design and sample studied; measure of depression and environment used; genes explored; and GxE findings in relation to these factors.

RESULTS

In total, 80% of studies (n = 16) found at least one significant GxE association. However, there was wide variation in methods and analyses adopted across studies, especially with respect to environmental measures used and tests conducted to estimate GxE. This heterogeneity made it difficult to compare findings and evaluate the strength of the evidence for GxE.

CONCLUSIONS

The existing body of GxE research on depression in youth contains studies that are conceptually and methodologically quite different, which contributes to mixed findings and makes it difficult to assess the current state of the evidence. To decrease this heterogeneity, we offer 20 recommendations that are focused on: (a) reporting GxE research; (b) testing and reporting GxE effects; (c) conceptualizing, measuring and analyzing depression; (d) conceptualizing, measuring and analyzing environment; (e) increasing power to test for GxE; and (f) improving the quality of genetic data used. Although targeted to GxE research on depression, these recommendations can be adopted by GxE researchers focusing on other mental health outcomes.

Genome wide association studies (GWAS) and copy number variation (CNV) studies of the major psychoses: what have we learnt?

Schizophrenia (SZ) and bipolar disorder (BPD) have high heritabilities and are clinically and genetically complex. Genome wide association studies (GWAS) and studies of copy number variations (CNV) in SZ and BPD have allowed probing of their underlying genetic risks. In this systematic review, we assess extant genetic signals from published GWAS and CNV studies of SZ and BPD up till March 2011. Risk genes associated with SZ at genome wide significance level (p value<7.2 × 10(-8)) include zinc finger binding protein 804A (ZNF804A), major histocompatibility (MHC) region on chromosome 6, neurogranin (NRGN) and transcription factor 4 (TCF4). Risk genes associated with BPD include ankyrin 3, node of Ranvier (ANK3), calcium channel, voltage dependent, L type, alpha 1C subunit (CACNA1C), diacylglycerol kinase eta (DGKH), gene locus on chromosome 16p12, and polybromo-1 (PBRM1) and very recently neurocan gene (NCAN). Possible common genes underlying psychosis include ZNF804A, CACNA1C, NRGN and PBRM1. The CNV studies suggest that whilst CNVs are found in both SZ and BPD, the large deletions and duplications are more likely found in SZ rather than BPD. The validation of any genetic signal is likely confounded by genetic and phenotypic heterogeneities which are influenced by epistatic, epigenetic and gene-environment interactions. There is a pressing need to better integrate the multiple research platforms including systems biology computational models, genomics, cross disorder phenotyping studies, transcriptomics, proteomics, metabolomics, neuroimaging and clinical correlations in order to get us closer to a more enlightened understanding of the genetic and biological basis underlying these potentially crippling conditions.

Modifiers and subtype-specific analyses in whole-genome association studies: a likelihood framework

OBJECTIVE

We propose new statistical methods for analyzing genetic case/control association data in which cases can be further classified into subtypes, for example, based on clinical features. The primary utility of our work is the ability to distinguish between subtype-specific and modifier effects of genetic variants within a single testing framework.

METHODS

A range of disease/subtype causal models are defined for genetic variants involving subtype-specific and modifier effects. We present a log-linear modeling framework enabling comparison between these causal models and selection of the best-fit model.

RESULTS

We evaluate and compare the analytic power and model selection performance of the proposed work with standard two-group-based association tests. Simulation studies demonstrate that our approach has similar or greater power than the traditional approach over a range of causal models. We also report empirical findings about the impact of misspecification of subtype frequency during model selection, and extend the application of the proposed work to the cross-disorder association studies of multiple diseases.

CONCLUSION

Whether a variant is a disease risk factor, is subtype specific, or modifies disease features has important consequences for the interpretation and follow-up of genetic associations. Our framework provides a simple, systematic way to evaluate and describe associations involving such subtype-specific or modifier effects.

Cognitive manic symptoms associated with the P2RX7 gene in bipolar disorder

OBJECTIVE

  Several genetic loci have been suggested to be associated with bipolar disorder but results have been inconsistent. Studying associations between bipolar symptoms and candidate genes may better expose this relationship. Here we investigate the association between bipolar key symptoms and the P2RX7 gene.

METHODS

  Key symptoms of mania were rated in two sets of medicated bipolar disorder patients (n=171 and n=475) at two specialized outpatient clinics for affective disorders and three regular psychiatric outpatient units in Sweden. The relationships between all manic symptoms according to DSM-IV were entered in a principal component analysis. We used a case-case model to reduce the genetic heterogeneity and tested associations between four factors related to manic symptoms and their association to four single nucleotide polymorphisms in the P2RX7 gene.

RESULTS

  The combination of the cognitive symptoms, distractibility, talkativeness, and thought disorder was significantly associated with rs1718119 in the P2RX7 gene in Set 1 [odds ratio (OR) = 1.78; p=0.011]. The association was re-tested in the second set (OR = 1.42; p=0.009). In the total sample, the association was even stronger (OR = 1.49; p<0.001). None of the other factors was associated with the P2RX7 gene. Within the first factor, the distractibility symptom accounted for a significant portion of the association to rs1718119 (p=0.016).

CONCLUSION

  There is an association between specific symptoms of bipolar disorder and the P2RX7 gene. This finding may open up new approaches to elucidating the neurobiology behind bipolar symptoms.

A common genetic variant in the neurexin superfamily member CNTNAP2 is associated with increased risk for selective mutism and social anxiety-related traits

BACKGROUND

Selective mutism (SM), considered an early-onset variant of social anxiety disorder, shares features of impaired social interaction and communication with autism spectrum disorders (ASDs) suggesting a possible shared pathophysiology. We examined association of a susceptibility gene, contactin-associated protein-like 2 (CNTNAP2), for ASDs and specific language impairment with SM and social anxiety-related traits.

METHODS

Sample 1 subjects were 99 nuclear families including 106 children with SM. Sample 2 subjects were young adults who completed measures of social interactional anxiety (n = 1028) and childhood behavioral inhibition (n = 920). Five single nucleotide polymorphisms in CNTNAP2 (including rs7794745 and rs2710102, previously associated with ASDs) were genotyped.

RESULTS

Analyses revealed nominal significance (p = .018) for association of SM with rs2710102, which, with rs6944808, was part of a common haplotype associated with SM (permutation p = .022). Adjusting for sex and ancestral proportion, each copy of the rs2710102*a risk allele in the young adults was associated with increased odds of being >1 SD above the mean on the Social Interactional Anxiety Scale (odds ratio = 1.33, p = .015) and Retrospective Self-Report of Inhibition (odds ratio = 1.40, p = .010).

CONCLUSIONS

Although association was found with rs2710102, the risk allele (a) for the traits studied here is the nonrisk allele for ASD and specific language impairment. These findings suggest a partially shared etiology between ASDs and SM and raise questions about which aspects of these syndromes are potentially influenced by CNTNAP2 and mechanism(s) by which these influences may be conveyed.

Polygenic dissection of the bipolar phenotype

BACKGROUND

Recent data provide strong support for a substantial common polygenic contribution (i.e. many alleles each of small effect) to genetic susceptibility for schizophrenia and overlapping susceptibility for bipolar disorder.

AIMS

To test hypotheses about the relationship between schizophrenia and psychotic types of bipolar disorder.

METHOD

Using a polygenic score analysis to test whether schizophrenia polygenic risk alleles, en masse, significantly discriminate between individuals with bipolar disorder with and without psychotic features. The primary sample included 1829 participants with bipolar disorder and the replication sample comprised 506 people with bipolar disorder.

RESULTS

The subset of participants with Research Diagnostic Criteria schizoaffective bipolar disorder (n = 277) were significantly discriminated from the remaining participants with bipolar disorder (n = 1552) in both the primary (P = 0.00059) and the replication data-sets (P = 0.0070). In contrast, those with psychotic bipolar disorder as a whole were not significantly different from those with non-psychotic bipolar disorder in either data-set.

CONCLUSIONS

Genetic susceptibility influences at least two major domains of psychopathological variation in the schizophrenia-bipolar disorder clinical spectrum: one that relates to expression of a 'bipolar disorder-like' phenotype and one that is associated with expression of 'schizophrenia-like' psychotic symptoms.

Pharmacogenetics of antidepressants

Up to 60% of depressed patients do not respond completely to antidepressants (ADs) and up to 30% do not respond at all. Genetic factors contribute for about 50% of the AD response. During the recent years the possible influence of a set of candidate genes as genetic predictors of AD response efficacy was investigated by us and others. They include the cytochrome P450 superfamily, the P-glycoprotein (ABCB1), the tryptophan hydroxylase, the catechol-O-methyltransferase, the monoamine oxidase A, the serotonin transporter (5-HTTLPR), the norepinephrine transporter, the dopamine transporter, variants in the 5-hydroxytryptamine receptors (5-HT1A, 5-HT2A, 5-HT3A, 5-HT3B, and 5-HT6), adrenoreceptor beta-1 and alpha-2, the dopamine receptors (D2), the G protein beta 3 subunit, the corticotropin releasing hormone receptors (CRHR1 and CRHR2), the glucocorticoid receptors, the c-AMP response-element binding, and the brain-derived neurotrophic factor. Marginal associations were reported for angiotensin I converting enzyme, circadian locomotor output cycles kaput protein, glutamatergic system, nitric oxide synthase, and interleukin 1-beta gene. In conclusion, gene variants seem to influence human behavior, liability to disorders and treatment response. Nonetheless, gene × environment interactions have been hypothesized to modulate several of these effects.

Retinal nerve fiber layer thickness in vigabatrin-exposed patients

OBJECTIVE

Vigabatrin-associated visual field loss (VAVFL) occurs in 25 to 50% of exposed patients and is routinely monitored using perimetry, which has inherent limitations. Using optical coherence tomography (OCT), retinal nerve fiber layer (RNFL) thinning has been described in a small number of vigabatrin-exposed patients. We explored the relationship between RNFL thickness and visual field size, to determine whether OCT is a suitable tool to use in patients exposed to vigabatrin.

METHODS

Two hundred one vigabatrin-exposed subjects with epilepsy, divided into 2 groups, and 90 healthy controls participated. Visual fields were obtained using Goldmann kinetic perimetry and quantified using mean radial degrees (MRD). RNFL imaging was performed using either spectral-domain (Group 1) or time-domain (Group 2) OCT.

RESULTS

Thirty-nine of 201 (19.4%) patients were unable to perform perimetry. Thirteen (6.5%) patients were unable to perform OCT. A total of 51.6% of patients showed VAVFL. Average RNFL thickness was significantly thinner in patients (77.9 μm) compared to healthy controls (93.6 μm) (p < 0.001). There was a strong correlation between MRD and average RNFL thickness for Group 1 (r = 0.768, p < 0.001) and Group 2 (r = 0.814, p < 0.001). OCT RNFL imaging showed high repeatability.

INTERPRETATION

OCT provides a useful tool to assess people exposed to vigabatrin, and can provide an accurate estimate of the extent of visual field loss in the absence of a reliable direct measure of the visual field. The strong linear relationship found between RNFL thickness and visual field size provides some evidence that irreversible VAVFL may be related to loss of retinal ganglion cell axons.

L-type calcium channels and psychiatric disorders: A brief review

Emerging evidence from genome-wide association studies (GWAS) support the association of polymorphisms in the alpha 1C subunit of the L-type voltage-gated calcium channel gene (CACNA1C) with bipolar disorder. These studies extend a rich prior literature implicating dysfunction of L-type calcium channels (LTCCs) in the pathophysiology of neuropsychiatric disorders. Moreover, calcium channel blockers reduce Ca(2+) flux by binding to the α1 subunit of the LTCC and are used extensively for treating hypertension, preventing angina, cardiac arrhythmias and stroke. Calcium channel blockers have also been studied clinically in psychiatric conditions such as mood disorders and substance abuse/dependence, yielding conflicting results. In this review, we begin with a summary of LTCC pharmacology. For each category of disorder, this article then provides a review of animal and human data. In particular, we extensively focus on animal models of depression and clinical trials in mood disorders and substance abuse/dependence. Through examining rationale and study design of published clinical trials, we provide some of the possible reasons why we still do not have definitive evidence of efficacy of calcium-channel antagonists for mood disorders. Refinement of genetic results and target phenotypes, enrollment of adequate sample sizes in clinical trials and progress in physiologic and pharmacologic studies to synthesize tissue and isoform specific calcium channel antagonists, are all future challenges of research in this promising field. © 2010 Wiley-Liss, Inc.

Schizophrenia risk genes: Implications for future drug development and discovery

Present-day development of improved treatments for schizophrenia is hindered by uncertain models of disease, inter-individual response variability in clinical trials and a paucity of sensitive measures of treatment effects. Findings from genetic research emphasize the potential for schizophrenia risk genes to help develop focused treatments, discover new drug targets and provide markers of clinical subtypes. Advances in genetic technologies also provide novel modes of drug discovery in schizophrenia such as transcriptomics, epigenetics and transgenic animal models. In this review, we discuss proven and proposed ways risk genes can be used to enhance the development and discovery of treatments for schizophrenia and highlight key studies in these approaches.

Phenotypic complexity, measurement bias, and poor phenotypic resolution contribute to the missing heritability problem in genetic association studies

BACKGROUND

The variance explained by genetic variants as identified in (genome-wide) genetic association studies is typically small compared to family-based heritability estimates. Explanations of this 'missing heritability' have been mainly genetic, such as genetic heterogeneity and complex (epi-)genetic mechanisms.

METHODOLOGY

We used comprehensive simulation studies to show that three phenotypic measurement issues also provide viable explanations of the missing heritability: phenotypic complexity, measurement bias, and phenotypic resolution. We identify the circumstances in which the use of phenotypic sum-scores and the presence of measurement bias lower the power to detect genetic variants. In addition, we show how the differential resolution of psychometric instruments (i.e., whether the instrument includes items that resolve individual differences in the normal range or in the clinical range of a phenotype) affects the power to detect genetic variants.

CONCLUSION

We conclude that careful phenotypic data modelling can improve the genetic signal, and thus the statistical power to identify genetic variants by 20-99%.

The psychiatric GWAS consortium: big science comes to psychiatry

The Psychiatric GWAS Consortium was founded with the aim of conducting statistically rigorous and comprehensive GWAS meta-analyses for five major psychiatric disorders: ADHD, autism, bipolar disorder, major depressive disorder, and schizophrenia. In the era of GWAS and high-throughput genomics, a major trend has been the emergence of collaborative, consortia approaches. Taking advantage of the scale that collaborative consortia approaches can bring to a problem, the PGC has been a major driver in psychiatric genetics and provides a model for how similar approaches may be applied to other disease communities.

The bipolar disorder risk allele at CACNA1C also confers risk of recurrent major depression and of schizophrenia

Molecular genetic analysis offers opportunities to advance our understanding of the nosological relationship between psychiatric diagnostic categories in general, and the mood and psychotic disorders in particular. Strong evidence (P=7.0 × 10(-7)) of association at the polymorphism rs1006737 (within CACNA1C, the gene encoding the α-1C subunit of the L-type voltage-gated calcium channel) with the risk of bipolar disorder (BD) has recently been reported in a meta-analysis of three genome-wide association studies of BD, including our BD sample (N=1868) studied within the Wellcome Trust Case Control Consortium. Here, we have used our UK case samples of recurrent major depression (N=1196) and schizophrenia (N=479) and UK non-psychiatric comparison groups (N=15316) to examine the spectrum of phenotypic effect of the bipolar risk allele at rs1006737. We found that the risk allele conferred increased risk for schizophrenia (P=0.034) and recurrent major depression (P=0.013) with similar effect sizes to those previously observed in BD (allelic odds ratio ∼1.15). Our findings are evidence of some degree of overlap in the biological underpinnings of susceptibility to mental illness across the clinical spectrum of mood and psychotic disorders, and show that at least some loci can have a relatively general effect on susceptibility to diagnostic categories, as currently defined. Our findings will contribute to a better understanding of the pathogenesis of major psychiatric illness, and such knowledge should be useful in providing an etiological rationale for shaping psychiatric nosology, which is currently reliant entirely on descriptive clinical data.

Selected summaries from the XVII World Congress of Psychiatric Genetics, San Diego, California, USA, 4-8 November 2009

The XVII World Congress of Psychiatric Genetics, sponsored by The International Society of Psychiatric Genetics (ISPG) took place in San Diego, California from 4 to 8 November 2009. Approximately 550 participants gathered to discuss the latest molecular genetic findings relevant to serious mental illness, including schizophrenia, mood disorders, substance abuse, autism, and attention deficit disorder. Recent advances in the field were discussed, including the genome-wide association studies results, copy number variation (CNV) in the genome, genomic imaging, and large multicenter collaborations. The following report, written by junior travel awardees who were assigned sessions as rapporteurs represents some of the areas covered in oral presentation during the conference, and reports on some of the notable major new findings described at this 2009 World Congress of Psychiatric Genetics.

Genome variation and complexity in the autism spectrum

A large international consortium reports in Nature on the diversity of genomic changes in families with autism spectrum disorders. Inherited and de novo mutations affecting many genes were discovered implicating disruption to postsynaptic and cellular signaling processes.

Genetics of post-traumatic stress disorder: review and recommendations for genome-wide association studies

Post-traumatic stress disorder (PTSD) is a prevalent, disabling anxiety disorder that constitutes a major health care burden. Despite evidence supporting a genetic predisposition to PTSD, the precise genetic loci remain unclear. Herein we review the current state and limitations of genetic research on PTSD. Although recent years have seen an exponential increase in the number of studies examining the influence of candidate genes on PTSD diagnosis and symptomatology, most studies have been characterized by relatively low rates of PTSD, with apparent inconsistencies in gene associations linked to marked differences in methodology. We further discuss how current advances in the genetics field can be applied to studies of PTSD, emphasizing the need to adapt a genome-wide approach that facilitates discovery rather than hypothesis testing. Genome-wide association studies offer the best opportunity to identify novel "true" risk variants for the disorder that in turn has the potential to inform our understanding of PTSD etiology.

Genome-wide association studies: a primer

There have been nearly 400 genome-wide association studies (GWAS) published since 2005. The GWAS approach has been exceptionally successful in identifying common genetic variants that predispose to a variety of complex human diseases and biochemical and anthropometric traits. Although this approach is relatively new, there are many excellent reviews of different aspects of the GWAS method. Here, we provide a primer, an annotated overview of the GWAS method with particular reference to psychiatric genetics. We dissect the GWAS methodology into its components and provide a brief description with citations and links to reviews that cover the topic in detail.

The Kraepelinian dichotomy - going, going... but still not gone

Recent genetic studies reinforce the view that current approaches to the diagnosis and classification of major psychiatric illness are inadequate. These findings challenge the distinction between schizophrenia and bipolar disorder, and suggest that more attention should be given to the relationship between the functional psychoses and neurodevelopmental disorders such as autism. We are entering a transitional period of several years during which psychiatry will need to move from using traditional descriptive diagnoses to clinical entities (categories and/or dimensions) that relate more closely to the underlying workings of the brain.

Prioritizing GWAS results: A review of statistical methods and recommendations for their application

Genome-wide association studies (GWAS) have rapidly become a standard method for disease gene discovery. A substantial number of recent GWAS indicate that for most disorders, only a few common variants are implicated and the associated SNPs explain only a small fraction of the genetic risk. This review is written from the viewpoint that findings from the GWAS provide preliminary genetic information that is available for additional analysis by statistical procedures that accumulate evidence, and that these secondary analyses are very likely to provide valuable information that will help prioritize the strongest constellations of results. We review and discuss three analytic methods to combine preliminary GWAS statistics to identify genes, alleles, and pathways for deeper investigations. Meta-analysis seeks to pool information from multiple GWAS to increase the chances of finding true positives among the false positives and provides a way to combine associations across GWAS, even when the original data are unavailable. Testing for epistasis within a single GWAS study can identify the stronger results that are revealed when genes interact. Pathway analysis of GWAS results is used to prioritize genes and pathways within a biological context. Following a GWAS, association results can be assigned to pathways and tested in aggregate with computational tools and pathway databases. Reviews of published methods with recommendations for their application are provided within the framework for each approach.

Common polygenic variation contributes to risk of schizophrenia and bipolar disorder

Schizophrenia is a severe mental disorder with a lifetime risk of about 1%, characterized by hallucinations, delusions and cognitive deficits, with heritability estimated at up to 80%. We performed a genome-wide association study of 3,322 European individuals with schizophrenia and 3,587 controls. Here we show, using two analytic approaches, the extent to which common genetic variation underlies the risk of schizophrenia. First, we implicate the major histocompatibility complex. Second, we provide molecular genetic evidence for a substantial polygenic component to the risk of schizophrenia involving thousands of common alleles of very small effect. We show that this component also contributes to the risk of bipolar disorder, but not to several non-psychiatric diseases.

Psychosis genetics: modeling the relationship between schizophrenia, bipolar disorder, and mixed (or "schizoaffective") psychoses

As a result of improving technologies and greatly increased sample sizes, the last 2 years has seen unprecedented advances in identification of specific genetic risk factors for psychiatric phenotypes. Strong genetic associations have been reported at common polymorphisms within ANK3 and CACNA1C in bipolar disorder and ZNF804A in schizophrenia and a relatively specific association between common variation in GABA(A) receptor genes and cases with features of both bipolar disorder and schizophrenia. Further, the occurrence of rare copy number variants (CNVs) has been shown to be increased in schizophrenia compared with controls. These emerging data provide a powerful resource for exploring the relationship between psychiatric phenotypes and can, and should, be used to inform conceptualization, classification, and diagnosis in psychiatry. It is already clear that, in general, genetic associations are not specific to one of the traditional diagnostic categories. For example, variation at ZNF804A is associated with risk of both bipolar disorder and schizophrenia, and some rare CNVs are associated with risk of autism and epilepsy as well as schizophrenia. These data are not consistent with a simple dichotomous model of functional psychosis and indicate the urgent need for moves toward approaches that (a) better represent the range of phenotypic variation seen in the clinical population and (b) reflect the underlying biological variation that gives rise to the phenotypes. We consider the implications for models of psychosis and the importance of recognizing and studying illness that has prominent affective and psychotic features. We conclude that if psychiatry is to translate the opportunities offered by new research methodologies, we must finally abandon a 19th-century dichotomy and move to a classificatory approach that is worthy of the 21st century.