Most psychiatric disorders are moderately to highly heritable. The degree to which genetic variation is unique to individual disorders or shared across disorders is unclear. To examine shared genetic etiology, we use genome-wide genotype data from the Psychiatric Genomics Consortium (PGC) for cases and controls in schizophrenia, bipolar disorder, major depressive disorder, autism spectrum disorders (ASD) and attention-deficit/hyperactivity disorder (ADHD). We apply univariate and bivariate methods for the estimation of genetic variation within and covariation between disorders. SNPs explained 17–29% of the variance in liability. The genetic correlation calculated using common SNPs was high between schizophrenia and bipolar disorder (0.68 ± 0.04 s.e.), moderate between schizophrenia and major depressive disorder (0.43 ± 0.06 s.e.), bipolar disorder and major depressive disorder (0.47 ± 0.06 s.e.), and ADHD and major depressive disorder (0.32 ± 0.07 s.e.), low between schizophrenia and ASD (0.16 ± 0.06 s.e.) and non-significant for other pairs of disorders as well as between psychiatric disorders and the negative control of Crohn’s disease. This empirical evidence of shared genetic etiology for psychiatric disorders can inform nosology and encourages the investigation of common pathophysiologies for related disorders.

We conducted a combined genome-wide association (GWAS) analysis of 7,481 individuals affected with bipolar disorder and 9,250 control individuals within the Psychiatric Genomewide Association Study Consortium Bipolar Disorder group (PGC-BD). We performed a replication study in which we tested 34 independent SNPs in 4,493 independent bipolar disorder cases and 42,542 independent controls and found strong evidence for replication. In the replication sample, 18 of 34 SNPs had P value < 0.05, and 31 of 34 SNPs had signals with the same direction of effect (P = 3.8 × 10−7). In the combined analysis of all 63,766 subjects (11,974 cases and 51,792 controls), genome-wide significant evidence for association was confirmed for CACNA1C and found for a novel gene ODZ4. In a combined analysis of non-overlapping schizophrenia and bipolar GWAS samples we observed strong evidence for association with SNPs in CACNA1C and in the region of NEK4/ITIH1,3,4. Pathway analysis identified a pathway comprised of subunits of calcium channels enriched in the bipolar disorder association intervals. The strength of the replication data implies that increasing samples sizes in bipolar disorder will confirm many additional loci.

Smoking is a leading global cause of disease and mortality1. We performed a genomewide meta-analytic association study of smoking-related behavioral traits in a total sample of 41,150 individuals drawn from 20 disease, population, and control cohorts. Our analysis confirmed an effect on smoking quantity (SQ) at a locus on 15q25 (P=9.45e-19) that includes three genes encoding neuronal nicotinic acetylcholine receptor subunits (CHRNA5, CHRNA3, CHRNB4). We used data from the 1000 Genomes project to investigate the region using imputation, which allowed analysis of virtually all common variants in the region and offered a five-fold increase in coverage over the HapMap. This increased the spectrum of potentially causal single nucleotide polymorphisms (SNPs), which included a novel SNP that showed the highest significance, rs55853698, located within the promoter region of CHRNA5. Conditional analysis also identified a secondary locus (rs6495308) in CHRNA3.

Genome-wide association studies (GWAS) of psychiatric disorders have identified multiple genetic associations with such disorders, but better methods are needed to derive the underlying biological mechanisms that these signals indicate. We sought to identify biological pathways in GWAS data from over 60,000 participants from the Psychiatric Genomics Consortium. We developed an analysis framework to rank pathways that requires only summary statistics. We combined this score across disorders to find common pathways across three adult psychiatric disorders: schizophrenia, major depression and bipolar disorder. Histone methylation processes showed the strongest association, and we also found statistically significant evidence for associations with multiple immune and neuronal signaling pathways and with the postsynaptic density. Our study indicates that risk variants for psychiatric disorders aggregate in particular biological pathways and that these pathways are frequently shared between disorders. Our results confirm known mechanisms and suggest several novel insights into the etiology of psychiatric disorders.

Bipolar disorder (BP) is a disabling and often life-threatening disorder that affects Ϸ1% of the population worldwide. To identify genetic variants that increase the risk of BP, we genotyped on the Illumina HumanHap550 Beadchip 2,076 bipolar cases and 1,676 controls of European ancestry from the National Institute of Mental Health Human Genetics Initiative Repository, and the Prechter Repository and samples collected in London, Toronto, and Dundee. We imputed SNP genotypes and tested for SNP-BP association in each sample and then performed meta-analysis across samples. The strongest association P value for this 2-study metaanalysis was 2.4 ؋ 10 ؊6 . We next imputed SNP genotypes and tested for SNP-BP association based on the publicly available Affymetrix 500K genotype data from the Wellcome Trust Case Control Consortium for 1,868 BP cases and a reference set of 12,831 individuals. A 3-study meta-analysis of 3,683 nonoverlapping cases and 14,507 extended controls on >2.3 M genotyped and imputed SNPs resulted in 3 chromosomal regions with association P Ϸ 10 ؊7 : 1p31.1 (no known genes), 3p21 (>25 known genes), and 5q15 (MCTP1). The most strongly associated nonsynonymous SNP rs1042779 (OR ‫؍‬ 1.19, P ‫؍‬ 1.8 ؋ 10 ؊7 ) is in the ITIH1 gene on chromosome 3, with other strongly associated nonsynonymous SNPs in GNL3, NEK4, and ITIH3. Thus, these chromosomal regions harbor genes implicated in cell cycle, neurogenesis, neuroplasticity, and neurosignaling. In addition, we replicated the reported ANK3 association results for SNP rs10994336 in the nonoverlapping GSK sample (OR ‫؍‬ 1.37, P ‫؍‬ 0.042). Although these results are promising, analysis of additional samples will be required to confirm that variant(s) in these regions influence BP risk.genetics ͉ genome-wide association study B ipolar disorder (BP) is characterized by dramatic mood changes, with individuals experiencing alternating episodes of depression and mania interspersed with periods of normal function. BP is chronic, severely disabling, and life-threatening, with increased risk of suicide and estimated lifetime prevalence of Ϸ1% (1).BP has a substantial genetic component. Monozygotic twin concordance rate estimates range from 45 to 70% and sibling recurrence risk estimates from 5 to 10 (2). Nonetheless, the underlying genetic and neurobiological triggers of BP remain elusive. Numerous linkage and candidate gene studies have sought to identify BP linked regions and associated genes, but no loci have been convincingly identified. Several groups have recently reported results of BP genome-wide association studies (GWAS), using pooled (3) or individually genotyped (4-6) samples; these studies identified SNPs in CACNA1C (alpha 1C subunit of the L-type voltage-gated calcium channel), ANK3 (ankyrin 3), and DGKH (diacylglycerol kinase, eta) as potentially associated with BP.To test for SNP-BP association in additional well-characterized samples, we analyzed data for Ͼ2.3 million genotyped and imputed SNPs on Ͼ3,700 individuals in 2 sample sets: (i) 1,177 bipolar I ...

The majority of antidepressant drugs act by increasing synaptic serotonin levels in the brain. Genetic variation in serotonin-related genes may therefore influence antidepressant efficacy. In this study, nine polymorphisms in four serotonin receptor genes (HTR1B, HTR2A, HTR5A and HTR6) and the serotonin transporter gene (SLC6A4) were analysed to investigate their influence on antidepressant response in a well-characterized unipolar depressive population (n ¼ 166) following a protocolized treatment regimen. 5-HTTLPR short-allele homozygotes were significantly associated with both remission (odds ratios (OR) ¼ 4.00, P ¼ 0.04) and response (OR ¼ 5.06, P ¼ 0.02) following second switch treatment, with a similar trend observed following initial treatment and paroxetine therapy. Following initial treatment, unipolar patients homozygous for the SLC6A4 intron 2 repeat polymorphism were significantly associated with lack of remission (OR ¼ 0.38, P ¼ 0.02) and lack of response (OR ¼ 0.42, P ¼ 0.01). Additionally, the HTR2A C 1354 T polymorphism showed an association with remission (OR ¼ 7.50, P ¼ 0.002) and response (OR ¼ 5.25, P ¼ 0.01) following paroxetine therapy. These results suggest that genetically determined variation in serotonin receptor genes makes a significant contribution to the efficacy of commonly prescribed antidepressant drugs.

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Smoking influences body weight such that smokers weigh less than non-smokers and smoking cessation often leads to weight increase. The relationship between body weight and smoking is partly explained by the effect of nicotine on appetite and metabolism. However, the brain reward system is involved in the control of the intake of both food and tobacco. We evaluated the effect of single-nucleotide polymorphisms (SNPs) affecting body mass index (BMI) on smoking behavior, and tested the 32 SNPs identified in a meta-analysis for association with two smoking phenotypes, smoking initiation (SI) and the number of cigarettes smoked per day (CPD) in an Icelandic sample (N=34 216 smokers). Combined according to their effect on BMI, the SNPs correlate with both SI (r=0.019, P=0.00054) and CPD (r=0.032, P=8.0 × 10−7). These findings replicate in a second large data set (N=127 274, thereof 76 242 smokers) for both SI (P=1.2 × 10−5) and CPD (P=9.3 × 10−5). Notably, the variant most strongly associated with BMI (rs1558902-A in FTO) did not associate with smoking behavior. The association with smoking behavior is not due to the effect of the SNPs on BMI. Our results strongly point to a common biological basis of the regulation of our appetite for tobacco and food, and thus the vulnerability to nicotine addiction and obesity.