Family and twin studies suggest that liability for suicide attempts is heritable and distinct from mood disorder susceptibility. The authors therefore examined the association between common genomewide variation and lifetime suicide attempts.
The authors analyzed data on lifetime suicide attempts from genomewide association studies of bipolar I and II disorder as well as major depressive disorder. Bipolar disorder subjects were drawn from the Systematic Treatment Enhancement Program for Bipolar Disorder cohort, the Wellcome Trust Case Control Consortium bipolar cohort, and the University College London cohort. Replication was pursued in the NIMH Genetic Association Information Network bipolar disorder project and a German clinical cohort. Depression subjects were drawn from the Sequential Treatment Alternatives to Relieve Depression cohort, with replication in the Netherlands Study of Depression and Anxiety/Netherlands Twin Register depression cohort.
Strongest evidence of association for suicide attempt in bipolar disorder was observed in a region without identified genes (rs1466846); five loci also showed suggestive evidence of association. In major depression, strongest evidence of association was observed for a single nucleotide polymorphism in ABI3BP, with six loci also showing suggestive association. Replication cohorts did not provide further support for these loci. However, meta-analysis incorporating approximately 8,700 mood disorder subjects identified four additional regions that met the threshold for suggestive association, including the locus containing the gene coding for protein kinase C-epsilon, previously implicated in models of mood and anxiety.
The results suggest that inherited risk for suicide among mood disorder patients is unlikely to be the result of individual common variants of large effect. They nonetheless provide suggestive evidence for multiple loci, which merit further investigation.
Sponsored by the New York Academy of Sciences and with support from the National Institute of Mental Health, the Life Technologies Foundation, and the Josiah Macy Jr. Foundation, “Advancing Drug Discovery for Schizophrenia” was held March 9–11 at the New York Academy of Sciences in New York City. The meeting, comprising individual talks and panel discussions, highlighted basic, clinical, and translational research approaches, all of which contribute to the overarching goal of enhancing the pharmaceutical armamentarium for treating schizophrenia. This report surveys work by the vanguard of schizophrenia research in such topics as genetic and epigenetic approaches; small molecule therapeutics; and the relationships between target genes, neuronal function, and symptoms of schizophrenia.
schizophrenia; genetics; GWAS; neuronal function; small molecules; therapeutics
Exome sequencing is emerging as a popular approach to study the effect of rare coding variants on complex phenotypes. The promise of exome sequencing is grounded in theoretical population genetics and in empirical successes of candidate gene sequencing studies. Many projects aimed at common diseases are underway, and their results are eagerly anticipated. In this Perspective, using exome sequencing data from 438 individuals, we discuss several aspects of exome sequencing studies that we view as particularly important. We review processing and quality control of raw sequence data, evaluate the statistical properties of exome sequencing studies, discuss rare variant burden tests to detect association to phenotypes, and demonstrate the importance of accounting for population stratification in the analysis of rare variants. We conclude that enthusiasm for exome sequencing studies of complex traits should be combined with the caution that thousands of samples may be required to reach sufficient statistical power.
Research into the etiology of schizophrenia, particularly the possible genetic basis, has never been as interesting and as provocative as in the past three years. Sullivan looks critically at the key research.
To evaluate systematically in real clinical settings whether functional genetic variations in drug metabolizing enzymes influence optimized doses, efficacy, and safety of antipsychotic medications.
DNA was collected from 750 patients with chronic schizophrenia treated with five antipsychotic drugs (olanzapine, quetiapine, risperidone, ziprasidone and perphenazine) as part of the Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) study. Doses for each of the medicines were optimized to 1, 2, 3, or 4x units in identically-appearing capsules in a double blind design. We analyzed 25 known functional genetic variants in the major and minor metabolizing enzymes for each medication. These variants were tested for association with optimized dose and other relevant clinical outcomes.
None of the tested variants showed a nominally significant main effect in association with any of the tested phenotypes in European-Americans, African-Americans or all patients. Even after accounting for potential covariates no genetic variant was found to be associated with dosing, efficacy, overall tolerability, or tardive dyskinesia.
There are no strong associations between common functional genetic variants in drug metabolizing enzymes and dosing, safety or efficacy of leading antipsychotics, strongly suggesting merely modest effects on the use of these medicines in most patients in typical clinical settings.
Pharmacogenetics; CYP 450; Drug Metabolizing Enzymes; Antipsychotics; Personalized Medicine
Autism spectrum disorder (ASD) is a neurodevelopmental disorder of complex etiology. Whereas strong evidence supports the causal role of genetic factors, a number of environmental risk factors have also been implicated. This study employed a cotwin-control design to investigate low birth weight as a risk factor for ASD.
A population-based sample of 3,715 same-sex twin-pairs participating in the Child and Adolescent Twin Study of Sweden were studied. ASD was assessed using a structured parent interview for screening of ASD and related developmental disorders, based on DSM-IV criteria. Birth weight was obtained from medical birth records maintained by the Swedish Medical Birth Registry.
Lighter twins in birth weight and ASD discordant twin-pairs (n= 34) were over three times more likely to meet criteria for ASD than heavier twins (OR = 3.25). Analyses of birth weight as a continuous risk factor showed a 13% reduction in risk of ASD per 100 gram increase in birth weight (n=78). Analysis of the effect of birth weight on ASD symptoms in the entire population (most of whom did not have ASD) showed a modest association. That is, for every 100 gram increase in birth weight a 2% decrease in severity of ASD indexed by A-TAC scores would be expected in the sample as a whole.
Data are consistent with the hypothesis that low birth weight confers risk to ASD. Thus, even though genetic effects are of major importance, non-genetic influence associated with birth weight may contribute to the development of ASDs.
Autism; Twin; Birth weight
To investigate the prevalence and patterns of transitions between cigarette and snus use.
Cross-sectional study within the population-based Swedish Twin Registry.
Setting and participants
A total of 31 213 male and female twins 42–64 years old.
Age-adjusted prevalence odds ratios (POR) and 95% confidence intervals (CIs) described the association between gender and tobacco use, while Kaplan–Meier survival methods produced cumulative incidence curves of age at onset of tobacco use. Life-time tobacco use histories were constructed using ages at onset of tobacco use and current tobacco use status.
Although more males reported ever smoking (64.4%) than females (61.7%), more males were former smokers (POR: 1.33, 95% CI: 1.27–1.39). Males were far more likely to use snus than females (POR: 18.0, 95% CI: 16.17–20.04). Age at onset of cigarette smoking occurred almost entirely before age 25, while the age at onset of snus use among males occurred over a longer time period. Most men began using cigarettes first, nearly one-third of whom switched to using cigarettes and snus in combination. While 30.6% of these combined users quit tobacco completely, only 7.4% quit snus and currently use cigarettes, while 47.7% quit cigarettes and currently use snus.
Current cigarette smoking is more prevalent among Swedish women than men, while snus use is more prevalent among men. Among men who reported using both cigarettes and snus during their life-time, it was more common to quit cigarettes and currently use snus than to quit snus and currently use cigarettes. Once snus use was initiated, more men continued using snus rather than quit tobacco completely.
Cigarettes; prevalence; snus; Sweden; tobacco
In methylome-wide association studies (MWAS) there are many possible differences between cases and controls (e.g. related to life style, diet, and medication use) that may affect the methylome and produce false positive findings. An effective approach to control for these confounders is to first capture the major sources of variation in the methylation data and then regress out these components in the association analyses. This approach is, however, computationally very challenging due to the extremely large number of methylation sites in the human genome.
We introduce MethylPCA that is specifically designed to control for potential confounders in studies where the number of methylation sites is extremely large. MethylPCA offers a complete and flexible data analysis including 1) an adaptive method that performs data reduction prior to PCA by empirically combining methylation data of neighboring sites, 2) an efficient algorithm that performs a principal component analysis (PCA) on the ultra high-dimensional data matrix, and 3) association tests. To accomplish this MethylPCA allows for parallel execution of tasks, uses C++ for CPU and I/O intensive calculations, and stores intermediate results to avoid computing the same statistics multiple times or keeping results in memory. Through simulations and an analysis of a real whole methylome MBD-seq study of 1,500 subjects we show that MethylPCA effectively controls for potential confounders.
MethylPCA provides users a convenient tool to perform MWAS. The software effectively handles the challenge in memory and speed to perform tasks that would be impossible to accomplish using existing software when millions of sites are interrogated with the sample sizes required for MWAS.
Principal component analysis; Methylome-wide association studies; Eigen-decomposition; Association test; MBD-seq
antipsychotics; genome-wide association; neurotransmitters; pathways; prostaglandin; schizophrenia
schizophrenia; sequencing; SNV; genetic; association; mutation; DISC1
Chronic fatigue syndrome (CFS) has been found to be comorbid with various medical conditions in clinical samples, but little research has investigated CFS comorbidity in population-based samples.
This study investigated conditions concurrent with a CFS-like illness among twins in the population-based Mid-Atlantic Twin Registry (MATR), including chronic widespread pain (CWP), irritable bowel syndrome (IBS), and major depression (MD).
A survey was mailed to participants in the MATR in 1999. Generalized estimating equations were used to estimate odds ratios to assess associations between CFS-like illness and each comorbid condition.
A total of 4,590 completed surveys were collected. Most participants were female (86.3%); mean age was 44.7 years. Among participants with a CFS-like illness, lifetime prevalence of CWP was 41%, IBS was 16%, and MD was 57%. Participants reporting at least one of the three comorbid conditions were about 14 times more likely to have CFS-like illness than those without CWP, IBS, or MD (95% confidence interval 8.1–21.3%). Only MD showed a temporal pattern of presentation during the same year as diagnosis of CFS-like illness. Age, gender, body mass index, age at illness onset, exercise level, self-reported health status, fatigue symptoms, and personality measures did not differ between those reporting CFS-like illness with and without comorbidity.
These results support findings in clinically based samples that CFS-like illness is frequently cormorbid with CWP, IBS, and/or MD. We found no evidence that CFS-like illnesses with comorbidities are clinically distinct from those without comorbidities.
Structural variation is an important class of genetic variation in mammals. High-throughput sequencing (HTS) technologies promise to revolutionize copy-number variation (CNV) detection but present substantial analytic challenges. Converging evidence suggests that multiple types of CNV-informative data (e.g. read-depth, read-pair, split-read) need be considered, and that sophisticated methods are needed for more accurate CNV detection. We observed that various sources of experimental biases in HTS confound read-depth estimation, and note that bias correction has not been adequately addressed by existing methods. We present a novel read-depth–based method, GENSENG, which uses a hidden Markov model and negative binomial regression framework to identify regions of discrete copy-number changes while simultaneously accounting for the effects of multiple confounders. Based on extensive calibration using multiple HTS data sets, we conclude that our method outperforms existing read-depth–based CNV detection algorithms. The concept of simultaneous bias correction and CNV detection can serve as a basis for combining read-depth with other types of information such as read-pair or split-read in a single analysis. A user-friendly and computationally efficient implementation of our method is freely available.
Genome wide association studies (GWAS) have proven a powerful method to identify common genetic variants contributing to susceptibility to common diseases. Here we show that extremely low-coverage sequencing (0.1–0.5x) captures almost as much of the common (>5%) and low-frequency (1–5%) variation across the genome as SNP arrays. As an empirical demonstration, we show that genome-wide SNP genotypes can be inferred at a mean r2 of 0.71 using off-target data (0.24x average coverage) in a whole-exome study of 909 samples. Using both simulated and real exome sequencing datasets we show that association statistics obtained using ultra low-coverage sequencing data attain similar P-values at known associated variants as genotyping arrays, without an excess of false positives. Within the context of reductions in sample preparation and sequencing costs, funds invested in ultra low-coverage sequencing can yield several times the effective sample size of SNP-array GWAS, and a commensurate increase in statistical power.
QT prolongation is associated with increased risk of cardiac arrhythmias. Identifying the genetic variants that mediate antipsychotic induced prolongation may help to minimize this risk, which might prevent the removal of efficacious drugs from the market. We performed candidate gene analysis and five drug specific genome-wide association studies (GWAS) with 492K SNPs to search for genetic variation mediating antipsychotic induced QT prolongation in 738 schizophrenia patients from the Clinical Antipsychotic Trial of Intervention Effectiveness (CATIE) study.
Our candidate gene study suggests the involvement of NOS1AP and NUBPL (p-values =1.45×10−05 and 2.66×10−13, respectively). Furthermore, our top GWAS hit achieving genome-wide significance, defined as a q-value <0.10, (p-value =1.54×10−7, q-value =0.07), located in SLC22A23, mediated the effects of quetiapine on prolongation. SLC22A23 belongs to a family of organic ion transporters that shuttle a variety of compounds including drugs, environmental toxins, and endogenous metabolites across the cell membrane. This gene is expressed in the heart and is integral in mouse heart development. The genes mediating antipsychotic induced QT prolongation partially overlap with the genes affecting normal QT interval variation. However, some genes may also be unique for drug induced prolongation. This study demonstrates the potential of GWAS to discover genes and pathways that mediate antipsychotic induced QT prolongation.
candidate gene analysis; genome-wide association study; schizophrenia; adverse effects; CATIE
Schizophrenia is a complex disorder caused by both genetic and environmental factors. Using 9,087 cases, 12,171 controls and 915,354 imputed SNPs from the Psychiatric GWA Consortium for schizophrenia (PGC-SCZ) we estimate that 23% (s.e. 1%) of variation in liability to schizophrenia is captured by SNPs. We show that an important proportion of this variation must be due to common causal variants, that the variance explained by each chromosome is linearly related to its length (r = 0.89, p = 2.6 × 10−8), that the genetic basis of schizophrenia is the same in males and females, and that a disproportionate proportion of variation is attributable to a set of 2725 genes expressed in the central nervous system (CNS) (p = 7.6 ×10−8). These results are consistent with a polygenic genetic architecture and imply more individual SNP associations will be detected for this disease as sample size increases.
heritability; missing heritability; genomic variance; SNPs; GWAS
Understanding individual differences in the development of extra-pyramidal side effects (EPS) as a response to antipsychotic therapy is essential to individualize treatment.
We performed genome-wide association studies to search for genetic susceptibility to EPS. Our sample consists of 738 schizophrenia patients, genotyped for 492K SNPs. We studied three quantitative measures of antipsychotic adverse drug reactions, the Simpson-Angus scale (SAS) for parkinsonism, the Barnes akathisia rating scale, and the abnormal involuntary movement scale (AIMS) as well as a clinical diagnosis of probable tardive dyskinesia.
Two SNPs for SAS, rs17022444 and rs2126709 with p=1.2×10-10 and p=3.8×10-7, respectively, and one for AIMS, rs7669317 with p=7.7×10-8, reached genome-wide significance (q-value <0.1). Rs17022444 and rs7669317 were located in intergenic regions and rs2126709 was located in ZNF202 on 11q24. Fourteen additional signals were potentially interesting (q-value <0.5). The ZNF202 is a transcriptional repressor controlling, among other genes, PLP1 which is the major protein in myelin. Mutations in PLP1 cause Pelizaeus-Merzbacher disease, which has parkinsonism as an occurring symptom. Altered mRNA expression of PLP1 is associated with schizophrenia.
Although our findings require replication and validation, this study demonstrates the potential of GWAS to discover genes and pathways that mediate adverse effects of antipsychotics.
genome-wide association; antipsychotic; pharmacogenetics; personalized medicine; single nucleotide polymorphism; copy number variation; schizophrenia
Tardive dyskinesia (TD) is a debilitating, unpredictable and often irreversible side effect resulting from chronic treatment with typical antipsychotic agents such as haloperidol. TD is characterized by repetitive, involuntary, purposeless movements primarily of the orofacial region. In order to investigate genetic susceptibility to TD, we used a validated mouse model for a systems genetics analysis geared toward detecting genetic predictors of TD in human patients. Phenotypic data from 27 inbred strains chronically treated with haloperidol and phenotyped for vacuous chewing movements were subject to a comprehensive genomic analysis involving 426,493 SNPs, 4,047 CNVs, brain gene expression, along with gene network and bioinformatic analysis. Our results identified ~50 genes that we expect to have high prior probabilities for association with haloperidol-induced TD, most of which have never been tested for association with human TD. Among our top candidates were genes regulating the development of brain motor control regions (Zic4, Nkx6-1), glutamate receptors (Grin1, Grin2a), and an indirect target of haloperidol (Drd1a) that has not been as well studied as the direct target, Drd2.
pharmacogenetic; adverse drug reaction; QTL; haloperidol; mouse
The purpose of this invited review is to summarize the state of genetic research into the etiology of schizophrenia (SCZ) and to consider options for progress. The fundamental uncertainty in SCZ genetics has always been the nature of the beast, the underlying genetic architecture. If this were known, studies using the appropriate technologies and sample sizes could be designed with an excellent chance of producing high-confidence results. Until recently, few pertinent data were available, and the field necessarily relied on speculation. However, for the first time in the complex and frustrating history of inquiry into the genetics of SCZ, we now have empirical data about the genetic basis of SCZ that implicate specific loci and that can be used to plan the next steps forward.
schizophrenia; genetics; review; genome-wide association; genome-wide linkage; next-generation sequencing
Neurocognitive deficits are a core feature of schizophrenia and, therefore, represent potentially critical outcome variables for assessing antipsychotic treatment response. We performed genome-wide association studies (GWAS) with 492K single nucleotide polymorphisms (SNPs) in a sample of 738 patients with schizophrenia from the Clinical Antipsychotic Trials of Intervention Effectiveness study. Outcome variables consisted of a neurocognitive battery administered at multiple time points over an 18-month period, measuring processing speed, verbal memory, vigilance, reasoning, and working memory domains. Genetic mediation of improvements in each of these five domains plus a composite neurocognitive measure was assessed for each of five antipsychotics (olanzapine, perphenazine, quetiapine, risperidone, and ziprasidone). Six SNPs achieved genome-wide significance using a pre-specified threshold that ensures, on average, only 1 in 10 findings is a false discovery. These six SNPs were located within, or in close proximity to, genes EHF, SLC26A9, DRD2, GPR137B, CHST8, and IL1A. The more robust findings, that is those significant across multiple neurocognitive domains and having adjacent SNPs showing evidence for association, were rs286913 at the EHF gene (p-value 6.99 × 10−8, q-value 0.034, mediating the effects of ziprasidone on vigilance), rs11240594 at SLC26A9 (p-value 1.4 × 10−7, q-value 0.068, mediating the effects of olanzapine on processing speed), and rs11677416 at IL1A (p-value 6.67 × 10−7, q-value 0.081, mediating the effects of olanzapine on working memory). This study has generated several novel candidate genes for antipsychotic response. However, our findings will require replication and functional validation. To facilitate replication efforts, we provide all GWAS p-values for download.
genome-wide association; schizophrenia; pharmacogenomics; personalized medicine; single nucleotide polymorphisms; biological psychiatry; cognition; schizophrenia; antipsychotics; pharmacogenetics; pharmacogenomics; genome-wide association; single nucleotide polymorphism
Mouse models play a crucial role in the study of human behavioral traits and diseases. Variation of gene expression in brain may play a critical role in behavioral phenotypes, and thus it is of great importance to understand regulation of transcription in mouse brain. In this study, we analyzed the role of two important factors influencing steady-state transcriptional variation in mouse brain. First we considered the effect of assessing whole brain vs. discrete regions of the brain. Second, we investigated the genetic basis of strain effects on gene expression. We examined the transcriptome of three brain regions using Affymetrix expression arrays: whole brain, forebrain, and hindbrain in adult mice from two common inbred strains (C57BL/6J vs. NOD/ShiLtJ) with eight replicates for each brain region and strain combination. We observed significant differences between the transcriptomes of forebrain and hindbrain. In contrast, the transcriptomes of whole brain and forebrain were very similar. Using 4.3 million single-nucleotide polymorphisms identified through whole-genome sequencing of C57BL/6J and NOD/ShiLtJ strains, we investigated the relationship between strain effect in gene expression and DNA sequence similarity. We found that cis-regulatory effects play an important role in gene expression differences between strains and that the cis-regulatory elements are more often located in 5′ and/or 3′ transcript boundaries, with no apparent preference on either 5′ or 3′ ends.
Mouse Genetic Resource; Mouse Collaborative Cross; mouse; gene expression; whole brain; forebrain; hindbrain; sequence variation
Summary: seeQTL is a comprehensive and versatile eQTL database, including various eQTL studies and a meta-analysis of HapMap eQTL information. The database presents eQTL association results in a convenient browser, using both segmented local-association plots and genome-wide Manhattan plots.
Availability and implementation: seeQTL is freely available for non-commercial use at http://www.bios.unc.edu/research/genomic_software/seeQTL/.
Contact: email@example.com; firstname.lastname@example.org
Supplementary information: Supplementary data are available at Bioinformatics online.
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.
Variation in personality traits is 30% to 60% attributed to genetic influences. Attempts to unravel these genetic influences at the molecular level have, so far, been inconclusive. We performed the first genome-wide association study of Cloninger’s temperament scales in a sample of 5117 individuals, in order to identify common genetic variants underlying variation in personality. Participants’ scores on Harm Avoidance, Novelty Seeking, Reward Dependence, and Persistence were tested for association with 1,252,387 genetic markers. We also performed gene-based association tests and biological pathway analyses. No genetic variants that significantly contribute to personality variation were identified, while our sample provides over 90% power to detect variants that explain only 1% of the trait variance. This indicates that individual common genetic variants of this size or greater do not contribute to personality trait variation, which has important implications regarding the genetic architecture of personality and the evolutionary mechanisms by which heritable variation is maintained.
genome-wide association; genes; personality; temperament; mutation; selection; maintenance of genetic variation; evolution
schizophrenia; 5-HTTLPR; rs25531; neurocognition; association study
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.
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.
Current results have few implications for clinical practice or research, and it is possible that this recommendation could be dramatically different in a year.
schizophrenia; genetics; genomewide association; genomewide linkage