Bryan Mowry

Naomi Wray and colleagues report an analysis of genome-wide association data sets from the Psychiatric Genomics Consortium for five psychiatric disorders. They find that common variation explains 17–29% of the variance in liability and provide further support for a shared genetic etiology for these related psychiatric disorders. 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.

Schizophrenia is a common disorder with high heritability and a 10-fold increase in risk to siblings of probands. Replication has been inconsistent for reports of significant genetic linkage. To assess evidence for linkage across studies, rank-based genome scan meta-analysis (GSMA) was applied to data from 20 schizophrenia genome scans. Each marker for each scan was assigned to 1 of 120 30-cM bins, with the bins ranked by linkage scores (1 = most significant) and the ranks averaged across studies (R(avg)) and then weighted for sample size (N(sqrt)[affected casess]). A permutation test was used to compute the probability of observing, by chance, each bin's average rank (P(AvgRnk)) or of observing it for a bin with the same place (first, second, etc.) in the order of average ranks in each permutation (P(ord)). The GSMA produced significant genomewide evidence for linkage on chromosome 2q (PAvgRnk<.000417). Two aggregate criteria for linkage were also met (clusters of nominally significant P values that did not occur in 1,000 replicates of the entire data set with no linkage present): 12 consecutive bins with both P(AvgRnk) and P(ord)<.05, including regions of chromosomes 5q, 3p, 11q, 6p, 1q, 22q, 8p, 20q, and 14p, and 19 consecutive bins with P(ord)<.05, additionally including regions of chromosomes 16q, 18q, 10p, 15q, 6q, and 17q. There is greater consistency of linkage results across studies than has been previously recognized. The results suggest that some or all of these regions contain loci that increase susceptibility to schizophrenia in diverse populations.

Schizophrenia, a devastating psychiatric disorder, has a prevalence of 0.5-1%, with high heritability (80-85%) and complex transmission. Recent studies implicate rare, large, high-penetrance copy number variants in some cases, but the genes or biological mechanisms that underlie susceptibility are not known. Here we show that schizophrenia is significantly associated with single nucleotide polymorphisms (SNPs) in the extended major histocompatibility complex region on chromosome 6. We carried out a genome-wide association study of common SNPs in the Molecular Genetics of Schizophrenia (MGS) case-control sample, and then a meta-analysis of data from the MGS, International Schizophrenia Consortium and SGENE data sets. No MGS finding achieved genome-wide statistical significance. In the meta-analysis of European-ancestry subjects (8,008 cases, 19,077 controls), significant association with schizophrenia was observed in a region of linkage disequilibrium on chromosome 6p22.1 (P = 9.54 x 10(-9)). This region includes a histone gene cluster and several immunity-related genes--possibly implicating aetiological mechanisms involving chromatin modification, transcriptional regulation, autoimmunity and/or infection. These results demonstrate that common schizophrenia susceptibility alleles can be detected. The characterization of these signals will suggest important directions for research on susceptibility mechanisms.

The regional distribution of white matter (WM) abnormalities in schizophrenia remains poorly understood, and reported disease effects on the brain vary widely between studies. In an effort to identify commonalities across studies, we perform what we believe is the first ever large-scale coordinated study of WM microstructural differences in schizophrenia. Our analysis consisted of 2359 healthy controls and 1963 schizophrenia patients from 29 independent international studies; we harmonized the processing and statistical analyses of diffusion tensor imaging (DTI) data across sites and meta-analyzed effects across studies. Significant reductions in fractional anisotropy (FA) in schizophrenia patients were widespread, and detected in 20 of 25 regions of interest within a WM skeleton representing all major WM fasciculi. Effect sizes varied by region, peaking at (d=0.42) for the entire WM skeleton, driven more by peripheral areas as opposed to the core WM where regions of interest were defined. The anterior corona radiata (d=0.40) and corpus callosum (d=0.39), specifically its body (d=0.39) and genu (d=0.37), showed greatest effects. Significant decreases, to lesser degrees, were observed in almost all regions analyzed. Larger effect sizes were observed for FA than diffusivity measures; significantly higher mean and radial diffusivity was observed for schizophrenia patients compared with controls. No significant effects of age at onset of schizophrenia or medication dosage were detected. As the largest coordinated analysis of WM differences in a psychiatric disorder to date, the present study provides a robust profile of widespread WM abnormalities in schizophrenia patients worldwide. Interactive three-dimensional visualization of the results is available at www.enigma-viewer.org.

Genome-wide association studies (GWASs) have focused primarily on populations of European descent, but it is essential that diverse populations become better represented. Increasing diversity among study participants will advance our understanding of genetic architecture in all populations and ensure that genetic research is broadly applicable. To facilitate and promote research in multi-ancestry and admixed cohorts, we outline key methodological considerations and highlight opportunities, challenges, solutions, and areas in need of development. Despite the perception that analyzing genetic data from diverse populations is difficult, it is scientifically and ethically imperative, and there is an expanding analytical toolbox to do it well.

Schizophrenia is a debilitating psychiatric disorder with approximately 1% lifetime risk globally. Large-scale schizophrenia genetic studies have reported primarily on European ancestry samples, potentially missing important biological insights. Here, we report the largest study to date of East Asian participants (22,778 schizophrenia cases and 35,362 controls), identifying 21 genome-wide-significant associations in 19 genetic loci. Common genetic variants that confer risk for schizophrenia have highly similar effects between East Asian and European ancestries (genetic correlation = 0.98 ± 0.03), indicating that the genetic basis of schizophrenia and its biology are broadly shared across populations. A fixed-effect meta-analysis including individuals from East Asian and European ancestries identified 208 significant associations in 176 genetic loci (53 novel). Trans-ancestry fine-mapping reduced the sets of candidate causal variants in 44 loci. Polygenic risk scores had reduced performance when transferred across ancestries, highlighting the importance of including sufficient samples of major ancestral groups to ensure their generalizability across populations.

Objective: To evaluate previously reported associations of copy number variants (CNVs) with schizophrenia and to identify additional associations, the authors analyzed CNVs in the Molecular Genetics of Schizophrenia study (MGS) and additional available data. Method: After quality control, MGS data for 3,945 subjects with schizophrenia or schizoaffective disorder and 3,611 screened comparison subjects were available for analysis of rare CNVs (<1% frequency). CNV detection thresholds were chosen that maximized concordance in 151 duplicate assays. Pointwise and genewise analyses were carried out, as well as analyses of previously reported regions. Selected regions were visually inspected and confirmed with quantitative polymerase chain reaction. Results: In analyses of MGS data combined with other available data sets, odds ratios of 7.5 or greater were observed for previously reported deletions in chromosomes 1q21.1, 15q13.3, and 22q11.21, duplications in 16p11.2, and exon-disrupting deletions in NRXN1. The most consistently supported candidate associations across data sets included a 1.6-Mb deletion in chromosome 3q29 (21 genes, TFRC to BDH1) that was previously described in a mild-moderate mental retardation syndrome, exonic duplications in the gene for vasoactive intestinal peptide receptor 2 (VIPR2), and exonic duplications in C16orf72. The case subjects had a modestly higher genome-wide number of gene-containing deletions (>100 kb and >1 Mb) but not duplications. Conclusions: The data strongly confirm the association of schizophrenia with 1q21.1, 15q13.3, and 22q11.21 deletions, 16p11.2 duplications, and exonic NRXN1 deletions. These CNVs, as well as 3q29 deletions, are also associated with mental retardation, autism spectrum disorders, and epilepsy. Additional candidate genes and regions, including VIPR2, were identified. Study of the mechanisms underlying these associations should shed light on the pathophysiology of schizophrenia.

The authors carried out a genetic association study of 14 schizophrenia candidate genes (RGS4, DISC1, DTNBP1, STX7, TAAR6, PPP3CC, NRG1, DRD2, HTR2A, DAOA, AKT1, CHRNA7, COMT, and ARVCF). This study tested the hypothesis of association of schizophrenia with common single nucleotide polymorphisms (SNPs) in these genes using the largest sample to date that has been collected with uniform clinical methods and the most comprehensive set of SNPs in each gene.The sample included 1,870 cases (schizophrenia and schizoaffective disorder) and 2,002 screened comparison subjects (i.e. controls), all of European ancestry, with ancestral outliers excluded based on analysis of ancestry-informative markers. The authors genotyped 789 SNPs, including tags for most common SNPs in each gene, SNPs previously reported as associated, and SNPs located in functional domains of genes such as promoters, coding exons (including nonsynonymous SNPs), 3' untranslated regions, and conserved noncoding sequences. After extensive data cleaning, 648 SNPs were analyzed for association of single SNPs and of haplotypes.Neither experiment-wide nor gene-wide statistical significance was observed in the primary single-SNP analyses or in secondary analyses of haplotypes or of imputed genotypes for additional common HapMap SNPs. Results in SNPs previously reported as associated with schizophrenia were consistent with chance expectation, and four functional polymorphisms in COMT, DRD2, and HTR2A did not produce nominally significant evidence to support previous evidence for association.It is unlikely that common SNPs in these genes account for a substantial proportion of the genetic risk for schizophrenia, although small effects cannot be ruled out.

The human cerebral cortex is a complex network of functionally specialized regions interconnected by axonal fibers, but the organizational principles underlying cortical connectivity remain unknown. Here, we report evidence that one such principle for functional cortical networks involves finding a balance between maximizing communication efficiency and minimizing connection cost, referred to as optimization of network cost-efficiency. We measured spontaneous fluctuations of the blood oxygenation level-dependent signal using functional magnetic resonance imaging in healthy monozygotic (16 pairs) and dizygotic (13 pairs) twins and characterized cost-efficient properties of brain network functional connectivity between 1041 distinct cortical regions. At the global network level, 60% of the interindividual variance in cost-efficiency of cortical functional networks was attributable to additive genetic effects. Regionally, significant genetic effects were observed throughout the cortex in a largely bilateral pattern, including bilateral posterior cingulate and medial prefrontal cortices, dorsolateral prefrontal and superior parietal cortices, and lateral temporal and inferomedial occipital regions. Genetic effects were stronger for cost-efficiency than for other metrics considered, and were more clearly significant in functional networks operating in the 0.09-0.18 Hz frequency interval than at higher or lower frequencies. These findings are consistent with the hypothesis that brain networks evolved to satisfy competitive selection criteria of maximizing efficiency and minimizing cost, and that optimization of network cost-efficiency represents an important principle for the brain's functional organization.

A genome scan meta-analysis (GSMA) was carried out on 32 independent genome-wide linkage scan analyses that included 3255 pedigrees with 7413 genotyped cases affected with schizophrenia (SCZ) or related disorders. The primary GSMA divided the autosomes into 120 bins, rank-ordered the bins within each study according to the most positive linkage result in each bin, summed these ranks (weighted for study size) for each bin across studies and determined the empirical probability of a given summed rank (P(SR)) by simulation. Suggestive evidence for linkage was observed in two single bins, on chromosomes 5q (142-168 Mb) and 2q (103-134 Mb). Genome-wide evidence for linkage was detected on chromosome 2q (119-152 Mb) when bin boundaries were shifted to the middle of the previous bins. The primary analysis met empirical criteria for 'aggregate' genome-wide significance, indicating that some or all of 10 bins are likely to contain loci linked to SCZ, including regions of chromosomes 1, 2q, 3q, 4q, 5q, 8p and 10q. In a secondary analysis of 22 studies of European-ancestry samples, suggestive evidence for linkage was observed on chromosome 8p (16-33 Mb). Although the newer genome-wide association methodology has greater power to detect weak associations to single common DNA sequence variants, linkage analysis can detect diverse genetic effects that segregate in families, including multiple rare variants within one locus or several weakly associated loci in the same region. Therefore, the regions supported by this meta-analysis deserve close attention in future studies.

A common limitation of neuroimaging studies is their small sample sizes. To overcome this hurdle, the Enhancing Neuro Imaging Genetics through Meta-Analysis (ENIGMA) Consortium combines neuroimaging data from many institutions worldwide. However, this introduces heterogeneity due to different scanning devices and sequences. ENIGMA projects commonly address this heterogeneity with random-effects meta-analysis or mixed-effects mega-analysis. Here we tested whether the batch adjustment method, ComBat, can further reduce site-related heterogeneity and thus increase statistical power. We conducted random-effects meta-analyses, mixed-effects mega-analyses and ComBat mega-analyses to compare cortical thickness, surface area and subcortical volumes between 2897 individuals with a diagnosis of schizophrenia and 3141 healthy controls from 33 sites. Specifically, we compared the imaging data between individuals with schizophrenia and healthy controls, covarying for age and sex. The use of ComBat substantially increased the statistical significance of the findings as compared to random-effects meta-analyses. The findings were more similar when comparing ComBat with mixed-effects mega-analysis, although ComBat still slightly increased the statistical significance. ComBat also showed increased statistical power when we repeated the analyses with fewer sites. Results were nearly identical when we applied the ComBat harmonization separately for cortical thickness, cortical surface area and subcortical volumes. Therefore, we recommend applying the ComBat function to attenuate potential effects of site in ENIGMA projects and other multi-site structural imaging work. We provide easy-to-use functions in R that work even if imaging data are partially missing in some brain regions, and they can be trained with one data set and then applied to another (a requirement for some analyses such as machine learning).

Background Sex differences in incidence and/or presentation of schizophrenia (SCZ), major depressive disorder (MDD), and bipolar disorder (BIP) are pervasive. Previous evidence for shared genetic risk and sex differences in brain abnormalities across disorders suggest possible shared sex-dependent genetic risk. Methods We conducted the largest to date genome-wide genotype-by-sex (G×S) interaction of risk for these disorders using 85,735 cases (33,403 SCZ, 19,924 BIP, and 32,408 MDD) and 109,946 controls from the PGC (Psychiatric Genomics Consortium) and iPSYCH. Results Across disorders, genome-wide significant single nucleotide polymorphism–by-sex interaction was detected for a locus encompassing NKAIN2 (rs117780815, p = 3.2 × 10−8), which interacts with sodium/potassium-transporting ATPase (adenosine triphosphatase) enzymes, implicating neuronal excitability. Three additional loci showed evidence (p < 1 × 10−6) for cross-disorder G×S interaction (rs7302529, p = 1.6 × 10−7; rs73033497, p = 8.8 × 10−7; rs7914279, p = 6.4 × 10−7), implicating various functions. Gene-based analyses identified G×S interaction across disorders (p = 8.97 × 10−7) with transcriptional inhibitor SLTM. Most significant in SCZ was a MOCOS gene locus (rs11665282, p = 1.5 × 10−7), implicating vascular endothelial cells. Secondary analysis of the PGC-SCZ dataset detected an interaction (rs13265509, p = 1.1 × 10−7) in a locus containing IDO2, a kynurenine pathway enzyme with immunoregulatory functions implicated in SCZ, BIP, and MDD. Pathway enrichment analysis detected significant G×S interaction of genes regulating vascular endothelial growth factor receptor signaling in MDD (false discovery rate-corrected p < .05). Conclusions In the largest genome-wide G×S analysis of mood and psychotic disorders to date, there was substantial genetic overlap between the sexes. However, significant sex-dependent effects were enriched for genes related to neuronal development and immune and vascular functions across and within SCZ, BIP, and MDD at the variant, gene, and pathway levels.

Schizophrenia candidate regions 33–51 cM in length on chromosomes 5q, 6q, 10p, and 13q were investigated for genetic linkage with mapped markers with an average spacing of 5.64 cM. We studied 734 informative multiplex pedigrees (824 independent affected sibling pairs [ASPs], or 1,003 ASPs when all possible pairs are counted), which were collected in eight centers. Cases with diagnoses of schizophrenia or schizoaffective disorder (DSM-IIIR criteria) were considered affected (n=1,937). Data were analyzed with multipoint methods, including nonparametric linkage (NPL), ASP analysis using the possible-triangle method, and logistic-regression analysis of identity-by-descent (IBD) sharing in ASPs with sample as a covariate, in a test for intersample heterogeneity and for linkage with allowance for intersample heterogeneity. The data most supportive for linkage to schizophrenia were from chromosome 6q; logistic-regression analysis of linkage allowing for intersample heterogeneity produced an empirical P value < .0002 with, or P=.0004 without, inclusion of the sample that produced the first positive report in this region; the maximum NPL score in this region was 2.47 (P=.0046), the maximum LOD score (MLS) from ASP analysis was 3.10 (empirical P=.0036), and there was significant evidence for intersample heterogeneity (empirical P=.0038). More-modest support for linkage was observed for chromosome 10p, with logistic-regression analysis of linkage producing an empirical P=.045 and with significant evidence for intersample heterogeneity (empirical P=.0096). Schizophrenia candidate regions 33–51 cM in length on chromosomes 5q, 6q, 10p, and 13q were investigated for genetic linkage with mapped markers with an average spacing of 5.64 cM. We studied 734 informative multiplex pedigrees (824 independent affected sibling pairs [ASPs], or 1,003 ASPs when all possible pairs are counted), which were collected in eight centers. Cases with diagnoses of schizophrenia or schizoaffective disorder (DSM-IIIR criteria) were considered affected (n=1,937). Data were analyzed with multipoint methods, including nonparametric linkage (NPL), ASP analysis using the possible-triangle method, and logistic-regression analysis of identity-by-descent (IBD) sharing in ASPs with sample as a covariate, in a test for intersample heterogeneity and for linkage with allowance for intersample heterogeneity. The data most supportive for linkage to schizophrenia were from chromosome 6q; logistic-regression analysis of linkage allowing for intersample heterogeneity produced an empirical P value < .0002 with, or P=.0004 without, inclusion of the sample that produced the first positive report in this region; the maximum NPL score in this region was 2.47 (P=.0046), the maximum LOD score (MLS) from ASP analysis was 3.10 (empirical P=.0036), and there was significant evidence for intersample heterogeneity (empirical P=.0038). More-modest support for linkage was observed for chromosome 10p, with logistic-regression analysis of linkage producing an empirical P=.045 and with significant evidence for intersample heterogeneity (empirical P=.0096).

Although it is clear that errors in genotyping data can lead to severe errors in linkage analysis, there is as yet no consensus strategy for identification of genotyping errors. Strategies include comparison of duplicate samples, independent calling of alleles, and Mendelian-inheritance-error checking. This study aimed to develop a better understanding of error types associated with microsatellite genotyping, as a first step toward development of a rational error-detection strategy. Two microsatellite marker sets (a commercial genomewide set and a custom-designed fine-resolution mapping set) were used to generate 118,420 and 22,500 initial genotypes and 10,088 and 8,328 duplicates, respectively. Mendelian-inheritance errors were identified by PedManager software, and concordance was determined for the duplicate samples. Concordance checking identifies only human errors, whereas Mendelian-inheritance-error checking is capable of detection of additional errors, such as mutations and null alleles. Neither strategy is able to detect all errors. Inheritance checking of the commercial marker data identified that the results contained 0.13% human errors and 0.12% other errors (0.25% total error), whereas concordance checking found 0.16% human errors. Similarly, Mendelian-inheritance-error checking of the custom-set data identified 1.37% errors, compared with 2.38% human errors identified by concordance checking. A greater variety of error types were detected by Mendelian-inheritance-error checking than by duplication of samples or by independent reanalysis of gels. These data suggest that Mendelian-inheritance-error checking is a worthwhile strategy for both types of genotyping data, whereas fine-mapping studies benefit more from concordance checking than do studies using commercial marker data. Maximization of error identification increases the likelihood of linkage when complex diseases are analyzed.

Objective: Evidence from epidemiology suggests that low maternal vitamin D may be a risk factor for schizophrenia. Method: Based on sera taken during the third trimester, we compared the level of 25 hydroxyvitamin D3 in mothers of individuals with schizophrenia or schizoaffective disorders versus mothers of unaffected controls. For each case, we selected two controls matched on race, gender and date of birth of the offspring. Results: There was no significant difference in third trimester maternal vitamin D in the entire sample (cases=26, controls=51). Within the subgroup of black individuals (n=21), there was a trend level difference in the predicted direction. Conclusions: Maternal vitamin D does not operate as a continuous graded risk factor for schizophrenia, however, the results in the black subgroup raise the possibility that below a certain critical threshold, low levels of maternal vitamin D may be associated with an increased risk of schizophrenia.

The discovery of genetic factors that contribute to schizophrenia susceptibility is a key challenge in understanding the etiology of this disease. Here, we report the identification of a novel schizophrenia candidate gene on chromosome 1q32, plexin A2 (PLXNA2), in a genome-wide association study using 320 patients with schizophrenia of European descent and 325 matched controls. Over 25 000 single-nucleotide polymorphisms (SNPs) located within approximately 14 000 genes were tested. Out of 62 markers found to be associated with disease status, the most consistent finding was observed for a candidate locus on chromosome 1q32. The marker SNP rs752016 showed suggestive association with schizophrenia (odds ratio (OR)=1.49, P=0.006). This result was confirmed in an independent case–control sample of European Americans (combined OR=1.38, P=0.035) and similar genetic effects were observed in smaller subsets of Latin Americans (OR=1.26) and Asian Americans (OR=1.37). Supporting evidence was also obtained from two family-based collections, one of which reached statistical significance (OR=2.2, P=0.02). High-density SNP mapping showed that the region of association spans approximately 60 kb of the PLXNA2 gene. Eight out of 14 SNPs genotyped showed statistically significant differences between cases and controls. These results are in accordance with previous genetic findings that identified chromosome 1q32 as a candidate region for schizophrenia. PLXNA2 is a member of the transmembrane semaphorin receptor family that is involved in axonal guidance during development and may modulate neuronal plasticity and regeneration. The PLXNA2 ligand semaphorin 3A has been shown to be upregulated in the cerebellum of individuals with schizophrenia. These observations, together with the genetic results, make PLXNA2 a likely candidate for the 1q32 schizophrenia susceptibility locus.

Multiple sources of evidence suggest that genetic factors influence variation in clinical features of schizophrenia. The authors present the first genome-wide association study (GWAS) of dimensional symptom scores among individuals with schizophrenia.Based on the Lifetime Dimensions of Psychosis Scale ratings of 2,454 case subjects of European ancestry from the Molecular Genetics of Schizophrenia (MGS) sample, three symptom factors (positive, negative/disorganized, and mood) were identified with exploratory factor analysis. Quantitative scores for each factor from a confirmatory factor analysis were analyzed for association with 696,491 single-nucleotide polymorphisms (SNPs) using linear regression, with correction for age, sex, clinical site, and ancestry. Polygenic score analysis was carried out to determine whether case and comparison subjects in 16 Psychiatric GWAS Consortium (PGC) schizophrenia samples (excluding MGS samples) differed in scores computed by weighting their genotypes by MGS association test results for each symptom factor.No genome-wide significant associations were observed between SNPs and factor scores. Most of the SNPs producing the strongest evidence for association were in or near genes involved in neurodevelopment, neuroprotection, or neurotransmission, including genes playing a role in Mendelian CNS diseases, but no statistically significant effect was observed for any defined gene pathway. Finally, polygenic scores based on MGS GWAS results for the negative/disorganized factor were significantly different between case and comparison subjects in the PGC data set; for MGS subjects, negative/disorganized factor scores were correlated with polygenic scores generated using case-control GWAS results from the other PGC samples.The polygenic signal that has been observed in cross-sample analyses of schizophrenia GWAS data sets could be in part related to genetic effects on negative and disorganized symptoms (i.e., core features of chronic schizophrenia).

White matter abnormalities associated with schizophrenia have been widely reported, although the consistency of findings across studies is moderate. In this study, neuroimaging was used to investigate white matter pathology and its impact on whole-brain white matter connectivity in one of the largest samples of patients with schizophrenia. Fractional anisotropy (FA) and mean diffusivity (MD) were compared between patients with schizophrenia or schizoaffective disorder (n = 326) and age-matched healthy controls (n = 197). Between-group differences in FA and MD were assessed using voxel-based analysis and permutation testing. Automated whole-brain white matter fiber tracking and the network-based statistic were used to characterize the impact of white matter pathology on the connectome and its rich club. Significant reductions in FA associated with schizophrenia were widespread, encompassing more than 40% (234ml) of cerebral white matter by volume and involving all cerebral lobes. Significant increases in MD were also widespread and distributed similarly. The corpus callosum, cingulum, and thalamic radiations exhibited the most extensive pathology according to effect size. More than 50% of cortico-cortical and cortico-subcortical white matter fiber bundles comprising the connectome were disrupted in schizophrenia. Connections between hub regions comprising the rich club were disproportionately affected. Pathology did not differ between patients with schizophrenia and schizoaffective disorder and was not mediated by medication. In conclusion, although connectivity between cerebral hubs is most extensively disturbed in schizophrenia, white matter pathology is widespread, affecting all cerebral lobes and the cerebellum, leading to disruptions in the majority of the brain's fiber bundles.

Abstract Cross-ethnic genetic studies can leverage power from differences in disease epidemiology and population-specific genetic architecture. In particular, the differences in linkage disequilibrium and allele frequency patterns across ethnic groups may increase gene-mapping resolution. Here we use cross-ethnic genetic data in sporadic amyotrophic lateral sclerosis (ALS), an adult-onset, rapidly progressing neurodegenerative disease. We report analyses of novel genome-wide association study data of 1,234 ALS cases and 2,850 controls. We find a significant association of rs10463311 spanning GPX3-TNIP1 with ALS ( p = 1.3 × 10 −8 ), with replication support from two independent Australian samples (combined 576 cases and 683 controls, p = 1.7 × 10 −3 ). Both GPX3 and TNIP1 interact with other known ALS genes ( SOD1 and OPTN , respectively). In addition, GGNBP2 was identified using gene-based analysis and summary statistics-based Mendelian randomization analysis, although further replication is needed to confirm this result. Our results increase our understanding of genetic aetiology of ALS.

Mutations in the family of neurexins (NRXN1, NRXN2 and NRXN3) have been repeatedly identified in patients with autism spectrum disorder (ASD) and schizophrenia (SCZ). However, it remains unclear how these DNA variants affect neurexin functions and thereby predispose to these neurodevelopmental disorders. Understanding both the wild-type and pathologic roles of these genes in the brain could help unveil biological mechanisms underlying mental disorders. In this regard, numerous studies have focused on generating relevant loss-of-function (LOF) mammalian models. Although this has increased our knowledge about their normal functions, the potential pathologic role(s) of these human variants remains elusive. Indeed, after reviewing the literature, it seems apparent that a traditional LOF-genetic approach based on complete LOF might not be sufficient to unveil the role of these human mutations. First, these genes present a very complex transcriptome and total-LOF of all isoforms may not be the cause of toxicity in patients, particularly given evidence that causative variants act through haploinsufficiency. Moreover, human DNA variants may not all lead to LOF but potentially to intricate transcriptome changes that could also include the generation of aberrant isoforms acting as a gain-of-function (GOF). Furthermore, their transcriptomic complexity most likely renders them prone to genetic compensation when one tries to manipulate them using traditional site-directed mutagenesis approaches, and this could act differently from model to model leading to heterogeneous and conflicting phenotypes. This review compiles the relevant literature on variants identified in human studies and on the mouse models currently deployed, and offers suggestions for future research.

Abstract Schizophrenia (SZ) is associated with an increased risk of life-long cognitive impairments, age-related chronic disease, and premature mortality. We investigated evidence for advanced brain ageing in adult SZ patients, and whether this was associated with clinical characteristics in a prospective meta-analytic study conducted by the ENIGMA Schizophrenia Working Group. The study included data from 26 cohorts worldwide, with a total of 2803 SZ patients (mean age 34.2 years; range 18–72 years; 67% male) and 2598 healthy controls (mean age 33.8 years, range 18–73 years, 55% male). Brain-predicted age was individually estimated using a model trained on independent data based on 68 measures of cortical thickness and surface area, 7 subcortical volumes, lateral ventricular volumes and total intracranial volume, all derived from T1-weighted brain magnetic resonance imaging (MRI) scans. Deviations from a healthy brain ageing trajectory were assessed by the difference between brain-predicted age and chronological age (brain-predicted age difference [brain-PAD]). On average, SZ patients showed a higher brain-PAD of +3.55 years (95% CI: 2.91, 4.19; I 2 = 57.53%) compared to controls, after adjusting for age, sex and site (Cohen’s d = 0.48). Among SZ patients, brain-PAD was not associated with specific clinical characteristics (age of onset, duration of illness, symptom severity, or antipsychotic use and dose). This large-scale collaborative study suggests advanced structural brain ageing in SZ. Longitudinal studies of SZ and a range of mental and somatic health outcomes will help to further evaluate the clinical implications of increased brain-PAD and its ability to be influenced by interventions.

Abstract Schizophrenia is a prototypical network disorder with widespread brain-morphological alterations, yet it remains unclear whether these distributed alterations robustly reflect the underlying network layout. We tested whether large-scale structural alterations in schizophrenia relate to normative structural and functional connectome architecture, and systematically evaluated robustness and generalizability of these network-level alterations. Leveraging anatomical MRI scans from 2439 adults with schizophrenia and 2867 healthy controls from 26 ENIGMA sites and normative data from the Human Connectome Project ( n = 207), we evaluated structural alterations of schizophrenia against two network susceptibility models: (i) hub vulnerability, which examines associations between regional network centrality and magnitude of disease-related alterations; (ii) epicenter mapping, which identifies regions whose typical connectivity profile most closely resembles the disease-related morphological alterations. To assess generalizability and specificity, we contextualized the influence of site, disease stages, and individual clinical factors and compared network associations of schizophrenia with that found in affective disorders. Our findings show schizophrenia-related cortical thinning is spatially associated with functional and structural hubs, suggesting that highly interconnected regions are more vulnerable to morphological alterations. Predominantly temporo-paralimbic and frontal regions emerged as epicenters with connectivity profiles linked to schizophrenia’s alteration patterns. Findings were robust across sites, disease stages, and related to individual symptoms. Moreover, transdiagnostic comparisons revealed overlapping epicenters in schizophrenia and bipolar, but not major depressive disorder, suggestive of a pathophysiological continuity within the schizophrenia-bipolar-spectrum. In sum, cortical alterations over the course of schizophrenia robustly follow brain network architecture, emphasizing marked hub susceptibility and temporo-frontal epicenters at both the level of the group and the individual. Subtle variations of epicenters across disease stages suggest interacting pathological processes, while associations with patient-specific symptoms support additional inter-individual variability of hub vulnerability and epicenters in schizophrenia. Our work outlines potential pathways to better understand macroscale structural alterations, and inter- individual variability in schizophrenia.

Schizophrenia affects 1% of the world's population, but its cause remains obscure. Numerous theories have been proposed regarding the cause of schizophrenia, ranging from developmental or neurodegenerative processes or neurotransmitter abnormalities to infectious or autoimmune processes. In this review, findings suggestive of immune dysregulation and reactivity to self in patients with schizophrenia are examined with reference to criteria for defining whether or not a human disease is autoimmune in origin. Associations with other autoimmune diseases and particular MHC haplotypes, increased serum levels of autoantibodies, and in vivo and in vitro replication of some of the functional and ultrastructural abnormalities of schizophrenia by transfer of autoantibodies from the sera of patients with schizophrenia suggest that, in some patients at least, autoimmune mechanisms could play a role in the development of disease. Recent findings regarding specific autoimmune responses directed against neurotransmitter receptors in the brain in patients with schizophrenia will also be reviewed.

We report the clinical characteristics of a schizophrenia sample of 409 pedigrees—263 of European ancestry (EA) and 146 of African American ancestry (AA)—together with the results of a genome scan (with a simple tandem repeat polymorphism interval of 9 cM) and follow-up fine mapping. A family was required to have a proband with schizophrenia (SZ) and one or more siblings of the proband with SZ or schizoaffective disorder. Linkage analyses included 403 independent full-sibling affected sibling pairs (ASPs) (279 EA and 124 AA) and 100 all-possible half-sibling ASPs (15 EA and 85 AA). Nonparametric multipoint linkage analysis of all families detected two regions with suggestive evidence of linkage at 8p23.3-q12 and 11p11.2-q22.3 (empirical <i>Z</i> likelihood-ratio score [<i>Z</i>_lr] threshold ⩾2.65) and, in exploratory analyses, two other regions at 4p16.1-p15.32 in AA families and at 5p14.3-q11.2 in EA families. The most significant linkage peak was in chromosome 8p; its signal was mainly driven by the EA families. <i>Z</i>_lr scores >2.0 in 8p were observed from 30.7 cM to 61.7 cM (Center for Inherited Disease Research map locations). The maximum evidence in the full sample was a multipoint <i>Z</i>_lr of 3.25 (equivalent Kong-Cox LOD of 2.30) near <i>D8S1771</i> (at 52 cM); there appeared to be two peaks, both telomeric to <i>neuregulin 1</i> (<i>NRG1</i>). There is a paracentric inversion common in EA individuals within this region, the effect of which on the linkage evidence remains unknown in this and in other previously analyzed samples. Fine mapping of 8p did not significantly alter the significance or length of the peak. We also performed fine mapping of 4p16.3-p15.2, 5p15.2-q13.3, 10p15.3-p14, 10q25.3-q26.3, and 11p13-q23.3. The highest increase in <i>Z</i>_lr scores was observed for 5p14.1-q12.1, where the maximum <i>Z</i>_lr increased from 2.77 initially to 3.80 after fine mapping in the EA families.

The aim of this study was to examine minor physical anomalies and quantitative measures of the head and face in patients with psychosis vs healthy controls.Based on a comprehensive prevalence study of psychosis, we recruited 310 individuals with psychosis and 303 controls. From this sample, we matched 180 case-control pairs for age and sex. Individual minor physical anomalies and quantitative measures related to head size and facial height and depth were compared within the matched pairs. Based on all subjects, we examined the specificity of the findings by comparing craniofacial summary scores in patients with nonaffective or affective psychosis and controls.The odds of having a psychotic disorder were increased in those with wider skull bases (odds ratio [OR], 1.40; 95% confidence interval [CI], 1.02-1.17), smaller lower-facial heights (glabella to subnasal) (OR, 0.57; 95% CI, 0.44-0.75), protruding ears (OR, 1.72; 95% CI, 1.05-2.82), and shorter (OR, 2.29; 95% CI, 1.37-3.82) and wider (OR, 2.28; 95% CI, 1.43-3.65) palates. Compared with controls, those with psychotic disorder had skulls that were more brachycephalic. These differences were found to distinguish patients with nonaffective and affective psychoses from controls.Several of the features that differentiate patients from controls relate to the development of the neuro-basicranial complex and the adjacent temporal and frontal lobes. Future research should examine both the temporal lobe and the middle cranial fossa to reconcile our anthropomorphic findings and the literature showing smaller temporal lobes in patients with schizophrenia. Closer attention to the skull base may provide clues to the nature and timing of altered brain development in patients with psychosis.

To identify genes dysregulated in bipolar disorder (BD1), we carried out global gene expression profiling using whole-genome microarrays. To minimize genetic variation in gene expression levels between cases and controls, we compared expression profiles in lymphoblastoid cell lines from monozygotic twin pairs discordant for the disease. We identified 82 genes that were differentially expressed by ⩾1.3-fold in three BD1 cases compared to their co-twins, and which were statistically (P⩽0.05) differentially expressed between the groups of BD1 cases and controls. Using quantitative reverse transcriptase-polymerase chain reaction, we confirmed the differential expression of some of these genes, including: KCNK1, MAL, PFN2, TCF7, PGK1 and PI4KCB, in at least two of the twin pairs. In contrast to the findings of a previous study by Kakiuchi and colleagues with similar discordant BD1 twin design, our data do not support the dysregulation of XBP1 and HSPA5. From pathway and gene ontology analysis, we identified upregulation of the WNT signalling pathway and the biological process of apoptosis. The differentially regulated genes and pathways identified in this study may provide insights into the biology of BD1.

We report an analysis of more than 240,000 loci genotyped using the Affymetrix SNP microarray in 554 individuals from 27 worldwide populations in Africa, Asia, and Europe. To provide a more extensive and complete sampling of human genetic variation, we have included caste and tribal samples from two states in South India, Daghestanis from eastern Europe, and the Iban from Malaysia. Consistent with observations made by Charles Darwin, our results highlight shared variation among human populations and demonstrate that much genetic variation is geographically continuous. At the same time, principal components analyses reveal discernible genetic differentiation among almost all identified populations in our sample, and in most cases, individuals can be clearly assigned to defined populations on the basis of SNP genotypes. All individuals are accurately classified into continental groups using a model-based clustering algorithm, but between closely related populations, genetic and self-classifications conflict for some individuals. The 250K data permitted high-level resolution of genetic variation among Indian caste and tribal populations and between highland and lowland Daghestani populations. In particular, upper-caste individuals from Tamil Nadu and Andhra Pradesh form one defined group, lower-caste individuals from these two states form another, and the tribal Irula samples form a third. Our results emphasize the correlation of genetic and geographic distances and highlight other elements, including social factors that have contributed to population structure.

This article describes the establishment of the Australian Schizophrenia Research Bank (ASRB), which operates to collect, store and distribute linked clinical, cognitive, neuroimaging and genetic data from a large sample of people with schizophrenia and healthy controls.Recruitment sources for the schizophrenia sample include a multi-media national advertising campaign, inpatient and community treatment services and non-government support agencies. Healthy controls have been recruited primarily through multi-media advertisements. All participants undergo an extensive diagnostic and family history assessment, neuropsychological evaluation, and blood sample donation for genetic studies. Selected individuals also complete structural MRI scans.Preliminary analyses of 493 schizophrenia cases and 293 healthy controls are reported. Mean age was 39.54 years (SD = 11.1) for the schizophrenia participants and 37.38 years (SD = 13.12) for healthy controls. Compared to the controls, features of the schizophrenia sample included a higher proportion of males (cases 65.9%; controls 46.8%), fewer living in married or de facto relationships (cases 16.1%; controls 53.6%) and fewer years of education (cases 13.05, SD = 2.84; controls 15.14, SD = 3.13), as well as lower current IQ (cases 102.68, SD = 15.51; controls 118.28, SD = 10.18). These and other sample characteristics are compared to those reported in another large Australian sample (i.e. the Low Prevalence Disorders Study), revealing some differences that reflect the different sampling methods of these two studies.The ASRB is a valuable and accessible schizophrenia research facility for use by approved scientific investigators. As recruitment continues, the approach to sampling for both cases and controls will need to be modified to ensure that the ASRB samples are as broadly representative as possible of all cases of schizophrenia and healthy controls.

To investigate the extent to which the proportion of schizophrenia's additive genetic variation tagged by SNPs is shared by populations of European and African descent, we analyzed the largest combined African descent (AD [n = 2,142]) and European descent (ED [n = 4,990]) schizophrenia case-control genome-wide association study (GWAS) data set available, the Molecular Genetics of Schizophrenia (MGS) data set. We show how a method that uses genomic similarities at measured SNPs to estimate the additive genetic correlation (SNP correlation [SNP-rg]) between traits can be extended to estimate SNP-rg for the same trait between ethnicities. We estimated SNP-rg for schizophrenia between the MGS ED and MGS AD samples to be 0.66 (SE = 0.23), which is significantly different from 0 (p(SNP-rg = 0) = 0.0003), but not 1 (p(SNP-rg = 1) = 0.26). We re-estimated SNP-rg between an independent ED data set (n = 6,665) and the MGS AD sample to be 0.61 (SE = 0.21, p(SNP-rg = 0) = 0.0003, p(SNP-rg = 1) = 0.16). These results suggest that many schizophrenia risk alleles are shared across ethnic groups and predate African-European divergence.

After decades of halting progress, recent large genome-wide association studies (GWAS) are finally shining light on the genetic architecture of schizophrenia. The picture emerging is one of sobering complexity, involving large numbers of risk alleles across the entire allelic spectrum. The aims of this article are to summarize the key genetic findings to date and to compare and contrast methods for identifying additional risk alleles, including GWAS, targeted genotyping and sequencing. A further aim is to consider the challenges and opportunities involved in determining the functional basis of genetic associations, for instance using functional genomics, cellular models, animal models and imaging genetics. We conclude that diverse approaches will be required to identify and functionally characterize the full spectrum of risk variants for schizophrenia. These efforts should adhere to the stringent standards of statistical association developed for GWAS and are likely to entail very large sample sizes. Nonetheless, now more than any previous time, there are reasons for optimism and the ultimate goal of personalized interventions and therapeutics, although still distant, no longer seems unattainable.

Excitement and controversy have followed neuregulin (NRG1) since its discovery as a putative schizophrenia susceptibility gene; however, the mechanism of action of the associated risk haplotype (HapICE) has not been identified, and specific genetic variations, which may increase risk to schizophrenia have remained elusive. Using a postmortem brain cohort from 37 schizophrenia cases and 37 controls, we resequenced upstream of the type I–IV promoters, and the HapICE repeat regions in intron 1. Relative abundance of seven NRG1 mRNA transcripts in the prefrontal cortex were determined and compared across diagnostic and genotypic groups. We identified 26 novel DNA variants and showed an increased novel variant load in cases compared with controls (χ2=7.815; P=0.05). The average nucleotide diversity (θ=10.0 × 10−4) was approximately twofold higher than that previously reported for BDNF, indicating that NRG1 may be particularly prone to genetic change. A greater nucleotide diversity was observed in the HapICE linkage disequilibrium block in schizophrenia cases (θ(case)=13.2 × 10−4; θ(control)=10.0 × 10−4). The specific HapICE risk haplotype was associated with increased type III mRNA (F=3.76, P=0.028), which in turn, was correlated with an earlier age of onset (r=−0.343, P=0.038). We found a novel intronic five-SNP haplotype ∼730 kb upstream of the type I promoter and determined that this region functions as transcriptional enhancer that is suppressed by SRY. We propose that the HapICE risk haplotype increases expression of the most brain-abundant form of NRG1, which in turn, elicits an earlier clinical presentation, thus providing a novel mechanism through which this genetic association may increase risk of schizophrenia.

Genome-wide association studies (GWASs) in European populations have identified more than 100 schizophrenia-associated loci. A schizophrenia GWAS in a unique Indian population offers novel findings.To discover and functionally evaluate genetic loci for schizophrenia in a GWAS of a unique Indian population.This GWAS included a sample of affected individuals, family members, and unrelated cases and controls. Three thousand ninety-two individuals were recruited and diagnostically ascertained via medical records, hospitals, clinics, and clinical networks in Chennai and surrounding regions. Affected participants fulfilled DSM-IV diagnostic criteria for schizophrenia. Unrelated control participants had no personal or family history of psychotic disorder. Recruitment, genotyping, and analysis occurred in consecutive phases beginning January 1, 2001. Recruitment was completed on February 28, 2018, and genotyping and analysis are ongoing.Associations of single-nucleotide polymorphisms and gene expression with schizophrenia.The study population included 1321 participants with schizophrenia, 885 family controls, and 886 unrelated controls. Among participants with schizophrenia, mean (SD) age was 39.1 (11.4) years, and 52.7% were male. This sample demonstrated uniform ethnicity, a degree of inbreeding, and negligible rates of substance abuse. A novel genome-wide significant association was observed between schizophrenia and a chromosome 8q24.3 locus (rs10866912, allele A; odds ratio [OR], 1.27 [95% CI, 1.17-1.38]; P = 4.35 × 10-8) that attracted support in the schizophrenia Psychiatric Genomics Consortium 2 data (rs10866912, allele A; OR, 1.04 [95% CI, 1.02-1.06]; P = 7.56 × 10-4). This locus has undergone natural selection, with the risk allele A declining in frequency from India (approximately 72%) to Europe (approximately 43%). rs10866912 directly modifies the abundance of the nicotinate phosphoribosyltransferase gene (NAPRT1) transcript in brain cortex (normalized effect size, 0.79; 95% CI, 0.6-1.0; P = 5.8 × 10-13). NAPRT1 encodes a key enzyme for niacin metabolism. In Indian lymphoblastoid cell lines, (risk) allele A of rs10866912 was associated with NAPRT1 downregulation (AA: 0.74, n = 21; CC: 1.56, n = 17; P = .004). Preliminary zebrafish data further suggest that partial loss of function of NAPRT1 leads to abnormal brain development.Bioinformatic analyses and cellular and zebrafish gene expression studies implicate NAPRT1 as a novel susceptibility gene. Given this gene's role in niacin metabolism and the evidence for niacin deficiency provoking schizophrenialike symptoms in neuropsychiatric diseases such as pellagra and Hartnup disease, these results suggest that the rs10866912 genotype and niacin status may have implications for schizophrenia susceptibility and treatment.

<h3>Importance</h3> A recently published study of national data by McGrath et al in 2014 showed increased risk of schizophrenia (SCZ) in offspring associated with both early and delayed parental age, consistent with a U-shaped relationship. However, it remains unclear if the risk to the child is due to psychosocial factors associated with parental age or if those at higher risk for SCZ tend to have children at an earlier or later age. <h3>Objective</h3> To determine if there is a genetic association between SCZ and age at first birth (AFB) using genetically informative but independently ascertained data sets. <h3>Design, Setting, and Participants</h3> This investigation used multiple independent genome-wide association study data sets. The SCZ sample comprised 18 957 SCZ cases and 22 673 controls in a genome-wide association study from the second phase of the Psychiatric Genomics Consortium, and the AFB sample comprised 12 247 genotyped women measured for AFB from the following 4 community cohorts: Estonia (Estonian Genome Center Biobank, University of Tartu), the Netherlands (LifeLines Cohort Study), Sweden (Swedish Twin Registry), and the United Kingdom (TwinsUK). Schizophrenia genetic risk for each woman in the AFB community sample was estimated using genetic effects inferred from the SCZ genome-wide association study. <h3>Main Outcomes and Measures</h3> We tested if SCZ genetic risk was a significant predictor of response variables based on published polynomial functions that described the relationship between maternal age and SCZ risk in offspring in Denmark. We substituted AFB for maternal age in these functions, one of which was corrected for the age of the father, and found that the fit was superior for the model without adjustment for the father's age. <h3>Results</h3> We observed a U-shaped relationship between SCZ risk and AFB in the community cohorts, consistent with the previously reported relationship between SCZ risk in offspring and maternal age when not adjusted for the age of the father. We confirmed that SCZ risk profile scores significantly predicted the response variables (coefficient of determination<i>R2</i> = 1.1E-03,<i>P</i> = 4.1E-04), reflecting the published relationship between maternal age and SCZ risk in offspring by McGrath et al in 2014. <h3>Conclusions and Relevance</h3> This study provides evidence for a significant overlap between genetic factors associated with risk of SCZ and genetic factors associated with AFB. It has been reported that SCZ risk associated with increased maternal age is explained by the age of the father and that de novo mutations that occur more frequently in the germline of older men are the underlying causal mechanism. This explanation may need to be revised if, as suggested herein and if replicated in future studies, there is also increased genetic risk of SCZ in older mothers.

Evidence for suggestive linkage to schizophrenia with chromosome 6q markers was previously reported from a two-stage approach. Using nonparametric affected sib pairs (ASP) methods, nominal p-values of 0.00018 and 0.00095 were obtained in the screening (81 ASPs; 63 independent) and the replication (109 ASPs; 87 independent) data sets, respectively. Here, we report a follow-up study of this 50cM 6q region using 12 microsatellite markers to test for linkage to schizophrenia. We increased the replication sample size by adding an independent sample of 43 multiplex pedigrees (66 ASPs; 54 independent). Pairwise and multipoint nonparametric linkage analyses conducted in this third data set showed evidence consistent with excess sharing in this 6q region, though the statistical level is weaker (p=0.013). When combining both replication data sets (total of 141 independent ASPs), an overall nominal p-value=0.000014 (LOD=3.82) was obtained. The sibling recurrence risk (λs) attributed to this putative 6q susceptibility locus is estimated to be 1.92. The linkage region could not be narrowed down since LOD score values greater than three were observed within a 13cM region. The length of this region was only slightly reduced (12cM) when using the total sample of independent ASPs (204) obtained from all three data sets. This suggests that very large sample sizes may be needed to narrow down this region by ASP linkage methods. Study of the etiological candidate genes in this region is ongoing. Am. J. Med. Genet. (Neuropsychiatr. Genet.) 88:337–343, 1999. © 1999 Wiley-Liss, Inc.

Several linkage studies across multiple population groups provide convergent support for a susceptibility locus for schizophrenia—and, more recently, for bipolar disorder—on chromosome 6q13-q26. We genotyped 192 European-ancestry and African American (AA) pedigrees with schizophrenia from samples that previously showed linkage evidence to 6q13-q26, focusing on the <i>MOXD1</i>-<i>STX7</i>-<i>TRARs</i> gene cluster at 6q23.2, which contains a number of prime candidate genes for schizophrenia. Thirty-one screening single-nucleotide polymorphisms (SNPs) were selected, providing a minimum coverage of at least 1 SNP/20 kb. The association observed with rs4305745 (<i>P</i>=.0014) within the <i>TRAR4</i> (<i>trace amine receptor 4</i>) gene remained significant after correction for multiple testing. Evidence for association was proportionally stronger in the smaller AA sample. We performed database searches and sequenced genomic DNA in a 30-proband subsample to obtain a high-density map of 23 SNPs spanning 21.6 kb of this gene. Single-SNP analyses and also haplotype analyses revealed that rs4305745 and/or two other polymorphisms in perfect linkage disequilibrium (LD) with rs4305745 appear to be the most likely variants underlying the association of the <i>TRAR4</i> region with schizophrenia. Comparative genomic analyses further revealed that rs4305745 and/or the associated polymorphisms in complete LD with rs4305745 could potentially affect gene expression. Moreover, RT-PCR studies of various human tissues, including brain, confirm that <i>TRAR4</i> is preferentially expressed in those brain regions that have been implicated in the pathophysiology of schizophrenia. These data provide strong preliminary evidence that <i>TRAR4</i> is a candidate gene for schizophrenia; replication is currently being attempted in additional clinical samples.

We present evidence of complex balancing regulation of HTR1B transcription by common polymorphisms in its promoter. Computational analysis of the HTR1B gene predicted that a 5' segment, spanning common DNA sequence variations, T-261G, A-161T, and -182INS/DEL-181, contained a putative functional promoter. Using a secreted alkaline phosphatase (SEAP) reporter gene system, we found that the haplotype -261G_-182INS-181_A-161 enhanced transcriptional activity 2.3-fold compared with the haplotype T-261_-182INS-181_A-161. Conversely, -161T reversed this, and the net effect when -261G and -161T were in the same haplotype (-261G_-182INS-181_-161T) was equivalent to the major haplotype (T-261_-182INS-181_A-161). Electrophoretic mobility shift experiments showed that -261G and -161T modify the binding of transcription factors (TFs): -261G generates a new AP2 binding site, while alleles A-161 and -161T exhibit different binding characteristics to AP1. T-261G and A-161T were found to be in linkage disequilibrium (LD) with G861C in a European ancestry population. Interestingly, G861C has been reported to be associated with several psychiatric disorders. Our results indicate that HTR1B is the target of substantial transcriptional genetic regulation by common haplotypes, which are in LD with the HTR1B single-nucleotide polymorphism (SNP) most commonly used in association studies.

Abstract This article outlines a simple coding matrix for recording physical illness in a compact form suitable for computerization in research. It allows the recording of physical illness in a number of different ways: the particular organ system(s) involved; whether the illness is acute or chronic; the severity of illness; and the severity of interference with daily living. The application of the scheme is shown in a cohort of depressed elderly patients in hospital. Also included were three self‐assessment scales of physical illness and an OARS Physical Health Rating. It was concluded that the simplest and most parsimonious approach to assessing global physical illness for psychiatric research purposes on the elderly would be to (a) measure the number of body system affected by acute and chronic physical illness, and (b) ask each patient to assess his/her own physical health by one appropriate question.

A genomewide linkage scan was carried out in eight clinical samples of informative schizophrenia families. After all quality control checks, the analysis of 707 European-ancestry families included 1615 affected and 1602 unaffected genotyped individuals, and the analysis of all 807 families included 1900 affected and 1839 unaffected individuals. Multipoint linkage analysis with correction for marker–marker linkage disequilibrium was carried out with 5861 single nucleotide polymorphisms (SNPs; Illumina version 4.0 linkage map). Suggestive evidence for linkage (European families) was observed on chromosomes 8p21, 8q24.1, 9q34 and 12q24.1 in nonparametric and/or parametric analyses. In a logistic regression allele-sharing analysis of linkage allowing for intersite heterogeneity, genomewide significant evidence for linkage was observed on chromosome 10p12. Significant heterogeneity was also observed on chromosome 22q11.1. Evidence for linkage across family sets and analyses was most consistent on chromosome 8p21, with a one-LOD support interval that does not include the candidate gene NRG1, suggesting that one or more other susceptibility loci might exist in the region. In this era of genomewide association and deep resequencing studies, consensus linkage regions deserve continued attention, given that linkage signals can be produced by many types of genomic variation, including any combination of multiple common or rare SNPs or copy number variants in a region.

We previously identified a significant bipolar spectrum disorder linkage peak on 15q25-26 using 35 extended families with a broad clinical phenotype, including bipolar disorder (types I and II), recurrent unipolar depression and schizoaffective disorder. However, the specific gene(s) contributing to this signal had not been identified. By a fine mapping association study in an Australian case-control cohort (n = 385), we find that the sialyltransferase 8B (ST8SIA2) gene, coding for an enzyme that glycosylates proteins involved in neuronal plasticity which has previously shown association to both schizophrenia and autism, is associated with increased risk to bipolar spectrum disorder. Nominal single point association was observed with SNPs in ST8SIA2 (rs4586379, P = 0.0043; rs2168351, P = 0.0045), and a specific risk haplotype was identified (frequency: bipolar vs controls = 0.41 vs 0.31; χ2 = 6.46, P = 0.011, OR = 1.47). Over-representation of the specific risk haplotype was also observed in an Australian schizophrenia case-control cohort (n = 256) (χ2 = 8.41, P = 0.004, OR = 1.82). Using GWAS data from the NIMH bipolar disorder (n = 2055) and NIMH schizophrenia (n = 2550) cohorts, the equivalent haplotype was significantly over-represented in bipolar disorder (χ2 = 5.91, P = 0.015, OR = 1.29), with the same direction of effect in schizophrenia, albeit non-significant (χ2 = 2.3, P = 0.129, OR = 1.09). We demonstrate marked down-regulation of ST8SIA2 gene expression across human brain development and show a significant haplotype×diagnosis effect on ST8SIA2 mRNA levels in adult cortex (ANOVA: F(1,87) = 6.031, P = 0.016). These findings suggest that variation the ST8SIA2 gene is associated with increased risk to mental illness, acting to restrict neuronal plasticity and disrupt early neuronal network formation, rendering the developing and adult brain more vulnerable to secondary genetic or environmental insults.

The authors used a genome-wide association study (GWAS) of multiply affected families to investigate the association of schizophrenia to common single-nucleotide polymorphisms (SNPs) and rare copy number variants (CNVs).The family sample included 2,461 individuals from 631 pedigrees (581 in the primary European-ancestry analyses). Association was tested for single SNPs and genetic pathways. Polygenic scores based on family study results were used to predict case-control status in the Schizophrenia Psychiatric GWAS Consortium (PGC) data set, and consistency of direction of effect with the family study was determined for top SNPs in the PGC GWAS analysis. Within-family segregation was examined for schizophrenia-associated rare CNVs.No genome-wide significant associations were observed for single SNPs or for pathways. PGC case and control subjects had significantly different genome-wide polygenic scores (computed by weighting their genotypes by log-odds ratios from the family study) (best p=10(-17), explaining 0.4% of the variance). Family study and PGC analyses had consistent directions for 37 of the 58 independent best PGC SNPs (p=0.024). The overall frequency of CNVs in regions with reported associations with schizophrenia (chromosomes 1q21.1, 15q13.3, 16p11.2, and 22q11.2 and the neurexin-1 gene [NRXN1]) was similar to previous case-control studies. NRXN1 deletions and 16p11.2 duplications (both of which were transmitted from parents) and 22q11.2 deletions (de novo in four cases) did not segregate with schizophrenia in families.Many common SNPs are likely to contribute to schizophrenia risk, with substantial overlap in genetic risk factors between multiply affected families and cases in large case-control studies. Our findings are consistent with a role for specific CNVs in disease pathogenesis, but the partial segregation of some CNVs with schizophrenia suggests that researchers should exercise caution in using them for predictive genetic testing until their effects in diverse populations have been fully studied.

Background: A long-standing epidemiological puzzle is the reduced rate of rheumatoid arthritis (RA) in those with schizophrenia (SZ) and vice versa. Traditional epidemiological approaches to determine if this negative association is underpinned by genetic factors would test for reduced rates of one disorder in relatives of the other, but sufficiently powered data sets are difficult to achieve. The genomics era presents an alternative paradigm for investigating the genetic relationship between two uncommon disorders. Methods: We use genome-wide common single nucleotide polymorphism (SNP) data from independently collected SZ and RA case-control cohorts to estimate the SNP correlation between the disorders. We test a genotype X environment (GxE) hypothesis for SZ with environment defined as winter- vs summer-born. Results: We estimate a small but significant negative SNP-genetic correlation between SZ and RA (−0.046, s.e. 0.026, P = 0.036). The negative correlation was stronger for the SNP set attributed to coding or regulatory regions (−0.174, s.e. 0.071, P = 0.0075). Our analyses led us to hypothesize a gene-environment interaction for SZ in the form of immune challenge. We used month of birth as a proxy for environmental immune challenge and estimated the genetic correlation between winter-born and non-winter born SZ to be significantly less than 1 for coding/regulatory region SNPs (0.56, s.e. 0.14, P = 0.00090). Conclusions: Our results are consistent with epidemiological observations of a negative relationship between SZ and RA reflecting, at least in part, genetic factors. Results of the month of birth analysis are consistent with pleiotropic effects of genetic variants dependent on environmental context.

Family and twin studies suggest that genes play a role in male sexual orientation. We conducted a genome-wide association study (GWAS) of male sexual orientation on a primarily European ancestry sample of 1,077 homosexual men and 1,231 heterosexual men using Affymetrix single nucleotide polymorphism (SNP) arrays. We identified several SNPs with p < 10-5, including regions of multiple supporting SNPs on chromosomes 13 (minimum p = 7.5 × 10-7) and 14 (p = 4.7 × 10-7). The genes nearest to these peaks have functions plausibly relevant to the development of sexual orientation. On chromosome 13, SLITRK6 is a neurodevelopmental gene mostly expressed in the diencephalon, which contains a region previously reported as differing in size in men by sexual orientation. On chromosome 14, TSHR genetic variants in intron 1 could conceivably help explain past findings relating familial atypical thyroid function and male homosexuality. Furthermore, skewed X chromosome inactivation has been found in the thyroid condition, Graves' disease, as well as in mothers of homosexual men. On pericentromeric chromosome 8 within our previously reported linkage peak, we found support (p = 4.1 × 10-3) for a SNP association previously reported (rs77013977, p = 7.1 × 10-8), with the combined analysis yielding p = 6.7 × 10-9, i.e., a genome-wide significant association.

Reports of substantial evidence for genetic linkage of schizophrenia to chromosome 1q were evaluated by genotyping 16 DNA markers across 107 centimorgans of this chromosome in a multicenter sample of 779 informative schizophrenia pedigrees. No significant evidence was observed for such linkage, nor for heterogeneity in allele sharing among the eight individual samples. Separate analyses of European-origin families, recessive models of inheritance, and families with larger numbers of affected cases also failed to produce significant evidence for linkage. If schizophrenia susceptibility genes are present on chromosome 1q, their population-wide genetic effects are likely to be small.

In a previous genome scan of 43 schizophrenia pedigrees, nonparametric linkage (NPL) scores with empirically derived pointwise P-values less than 0.01 were observed in two regions (chromosomes 2q12-13 and 10q23) and less than 0.05 in three regions (4q22-23, 9q22, and 11q21). Markers with a mean spacing of about 5 cM were typed in these regions in an expanded sample of 71 pedigrees, and NPL analyses carried out. No region produced significant genomewide evidence for linkage. On chromosome 10q, the empirical P-value remained at less than 0.01 for the entire sample (D10S168), evidence in the original 43 pedigrees was slightly increased, and a broad peak of positive results was observed. P-values less than 0.05 were observed on chromosomes 2q (D2S436) and 4q (D4S2623), but not on chromosomes 9q or 11q. It is concluded that this sample is most supportive of linkage on chromosome 10q, with less consistent support on chromosomes 2q and 4q. Am. J. Med. Genet. (Neuropsychiatr. Genet.) 96:864–869, 2000. © 2000 Wiley-Liss, Inc.

Several lines of evidence have implicated the catechol-O-methyltransferase (COMT) gene as a candidate for schizophrenia (SZ) susceptibility, not only because it encodes a key dopamine catabolic enzyme but also because it maps to the velocardiofacial syndrome region of chromosome 22q11 which has long been associated with SZ predisposition. The interest in COMT as a candidate SZ risk factor has led to numerous case–control and family-based studies, with the majority placing emphasis on examining a functional Val/Met polymorphism within this enzyme. Unfortunately, these studies have continually produced conflicting results. To assess the genetic contribution of other COMT variants to SZ susceptibility, we investigated three single-nucleotide polymorphisms (SNPs) (rs737865, rs4633, rs165599) in addition to the Val/Met variant (rs4680) in a highly selected sample of Australian Caucasian families containing 107 patients with SZ. The Val/Met and rs4633 variants showed nominally significant associations with SZ (P<0.05), although neither of the individual SNPs remained significant after adjusting for multiple testing (most significant P=0.1174). However, haplotype analyses showed strong evidence of an association; the most significant being the three-marker haplotype rs737865-rs4680-rs165599 (global P=0.0022), which spans more than 26 kb. Importantly, conditional analyses indicated the presence of two separate and interacting effects within this haplotype, irrespective of gender. In addition, our results indicate the Val/Met polymorphism is not disease-causing and is simply in strong linkage disequilibrium with a causative effect, which interacts with another as yet unidentified variant ∼20 kb away. These results may help explain the inconsistent results reported on the Val/Met polymorphism and have important implications for future investigations into the role of COMT in SZ susceptibility.

MRI diffusion tensor imaging (DTI), optimized for measuring the trace of the diffusion tensor, was used to investigate microstructural changes in the brains of 12 individuals with schizophrenia compared with 12 matched control subjects. To control for the effects of anatomic variation between subject groups, all participants' diffusion images were nonlinearly registered to standard anatomical space. Significant statistical differences in mean diffusivity (MD) measures between the two groups were determined on a pixel-by-pixel basis, using Gaussian random field theory. We found significantly elevated MD measures within temporal, parietal and prefrontal cortical regions in the schizophrenia group (P > 0.001), especially within the medial frontal gyrus and anterior cingulate. The dorsal medial and anterior nucleus of the thalamus, including the caudate, also exhibited significantly increased MD in the schizophrenia group (P > 0.001). This study has shown for the first time that MD measures offer an alternative strategy for investigating altered prefrontal–thalamic circuitry in schizophrenia.

Treatment of schizophrenia with olanzapine and other atypical antipsychotic agents is associated with insulin resistance and diabetes mellitus. The mechanism for this is not understood. Adiponectin is an insulin-sensitizing cytokine secreted by adipocytes. It is present in serum in multimers of varying size. Trimers and hexamers are referred to as low molecular weight (LMW) adiponectin. Larger multimers (12-, 18-, and 24-mers) have been designated high molecular weight (HMW) adiponectin and seem responsible for the insulin-sensitizing action of this adipokine. The aim of this study was to examine total adiponectin and LMW and HMW multimers in serum from patients with schizophrenia treated with either olanzapine (n = 9) or other typical antipsychotics (n = 9) and compare results with 16 healthy sex-, body mass index-, and age-matched controls. The effects of olanzapine on adiponectin protein expression and secretion in in vitro-differentiated primary human adipocytes were also examined. Patients receiving olanzapine had significantly lower total serum adiponectin as compared with those on conventional treatment and controls (5.23 +/- 1.53 ng/mL vs. 8.20 +/- 3.77 ng/mL and 8.78 +/- 3.8 ng/mL; P < 0.05 and P < 0.01, respectively). The HMW adiponectin was also reduced in patients on olanzapine as compared with the disease and healthy control groups (1.67 +/- 0.96 ng/mL vs. 3.87 +/- 2.69 ng/mL and 4.07 +/- 3.2 ng/mL; P < 0.05 for both). The LMW adiponectin was not different between patient groups (P = 0.15) but lower in patients on olanzapine as compared with controls (3.56 +/- 0.85 ng/mL vs. 4.70 +/- 1.4 ng/mL; P < 0.05). In vitro, short duration (up to 7 days) olanzapine exposure had no effect on total adiponectin expression or multimer composition of secreted protein. In summary, this study demonstrates a correlation between olanzapine treatment and reduced serum adiponectin, particularly HMW multimers. This may not be a direct effect of olanzapine on adipocyte expression or secretion of adiponectin. These observations provide insights into possible mechanisms for the association between olanzapine treatment and insulin resistance.

The Molecular Genetics of Schizophrenia (MGS2) project recruited an adult control sample of non-Hispanic European-ancestry (N=3,364) and African American (N=1,301) subjects.Subjects gave consent to deposit phenotypic data and blood samples into a repository for general research use, with full anonymization of the sample. The authors compared the control sample with population census data for demographic data and with previous population surveys for anthropometrics and prevalences of psychiatric disorders as estimated by an Internet-administered questionnaire.The full MGS2 control sample includes 4,665 subjects (European-ancestry: N=3,364; African American: N=1,301), of whom 3,626 were included in the MGS2 genome-wide association study (GWAS). The sample is generally demographically representative of the U.S. population, except for being older and more female, educated, and affluent, although all strata are represented. Self-reported ancestry was consistent with genotypic and census data. Lifetime prevalences for depressive, anxiety, and substance use diagnoses were higher than in previous population-based surveys, probably due to use of an abbreviated self-report instrument. However, patterns such as sex ratios, comorbidity, and demographic associations were consistent with previous reports. DNA quality for the Internet collected/evaluated control sample was comparable to that of the face-to-face case sample.The Internet-based methods facilitated the rapid collection of large and anonymized non-Hispanic European-ancestry and African American control samples that have been validated as being generally representative for many aspects of demography, ancestry, and morbidity. Utilization of clinical screening data shared with the scientific community may permit investigators to select appropriate controls for some studies.

Background Schizophrenia is associated with lower pre-morbid intelligence (IQ) in addition to (pre-morbid) cognitive decline. Both schizophrenia and IQ are highly heritable traits. Therefore, we hypothesized that genetic variants associated with schizophrenia, including copy number variants (CNVs) and a polygenic schizophrenia (risk) score (PSS), may influence intelligence. Method IQ was estimated with the Wechsler Adult Intelligence Scale (WAIS). CNVs were determined from single nucleotide polymorphism (SNP) data using the QuantiSNP and PennCNV algorithms. For the PSS, odds ratios for genome-wide SNP data were calculated in a sample collected by the Psychiatric Genome-Wide Association Study (GWAS) Consortium (8690 schizophrenia patients and 11 831 controls). These were used to calculate individual PSSs in our independent sample of 350 schizophrenia patients and 322 healthy controls. Results Although significantly more genes were disrupted by deletions in schizophrenia patients compared to controls ( p = 0.009), there was no effect of CNV measures on IQ. The PSS was associated with disease status ( R 2 = 0.055, p = 2.1 × 10 −7 ) and with IQ in the entire sample ( R 2 = 0.018, p = 0.0008) but the effect on IQ disappeared after correction for disease status. Conclusions Our data suggest that rare and common schizophrenia-associated variants do not explain the variation in IQ in healthy subjects or in schizophrenia patients. Thus, reductions in IQ in schizophrenia patients may be secondary to other processes related to schizophrenia risk.

A sex chromosome locus for psychosis has been considered on the basis of some sex differences in genetic risk and expression of illness, and an association with X-chromosome anomalies. Previous molecular genetic studies produced weak evidence for linkage of schizophrenia to the proximal short arm of the X-chromosome, while some other regions were not ruled out. Here we report an attempt to expand the Xp findings in: (i) a multicenter collaboration focusing on 92 families with a maternal pattern of inheritance (Study I.); and (ii) an independent sample of 34 families unselected for parental mode of transmission (Study II.). In the multicenter study, a parametric analysis resulted in positive lod scores (highest of 1.97 for dominant and 1.19 for recessive inheritance at a theta of 0.20) for locus DXS7, with scores below 0.50 for other markers in this region (MAOB, DXS228, and ARAF1). Significant allele sharing among affected sibling pairs was present at DXS7. In the second study, positive lod scores were observed at MAOB (highest of 2.16 at a theta of 0.05 for dominant and 1.64 at a theta of 0.00 for recessive models) and ALAS2 (the highest of 1.36 at a theta of 0.05 for a recessive model), with significant allele sharing (P=0.003 and 0.01, respectively) at these two loci. These five markers are mapped within a small region of Xp11. Thus, although substantial regions of the X-chromosome have been investigated without evidence for linkage being found, a locus predisposing to schizophrenia in the proximal short arm of the X-chromosome is not excluded. © 1997 Elsevier Science Ireland Ltd.

1. Schizophrenia is a chronic, disabling brain disease that affects approximately 1% of the world's population. It is characterized by delusions, hallucinations and formal thought disorder, together with a decline in socio-occupational functioning. While the causes for schizophrenia remain unknown, evidence from family, twin and adoption studies clearly demonstrates that it aggregates in families, with this clustering largely attributable to genetic rather than cultural or environmental factors. Identifying the genes involved, however, has proven to be a difficult task because schizophrenia is a complex trait characterized by an imprecise phenotype, the existence of phenocopies and the presence of low disease penetrance. 2. The current working hypothesis for schizophrenia causation is that multiple genes of small to moderate effect confer compounding risk through interactions with each other and with non-genetic risk factors. The same genes may be commonly involved in conferring risk across populations or they may vary in number and strength between different populations. To search for evidence of such genetic loci, both candidate gene and genome-wide linkage studies have been used in clinical cohorts collected from a variety of populations. Collectively, these works provide some evidence for the involvement of a number of specific genes (e.g. the 5-hydroxytryptamine (5-HT) type 2a receptor (5-HT2a) gene and the dopamine D3 receptor gene) and as yet unidentified factors localized to specific chromosomal regions, including 6p, 6q, 8p, 13q and 22q. These data provide suggestive, but no conclusive, evidence for causative genes. 3. To enable further progress there is a need to: (i) collect fine-grained clinical datasets while searching the schizophrenia phenotype for subgroups or dimensions that may provide a more direct route to causative genes; and (ii) integrate recent refinements in molecular genetic technology, including modern composite marker maps, DNA expression assays and relevant animal models, while using the latest analytical techniques to extract maximum information in order to help distinguish a true result from a false-positive finding.

Genetic linkage studies of schizophrenia depend on accurate psychiatric diagnosis of relatives within multiply affected families. Each investigator makes a series of explicit or implicit decisions to define which relatives will be assumed to share a schizophrenia-related genotype, that is, who is an "affected relative." In this article we delineate issues that we believe should be considered in such studies and review the relevant literature. Issues include criteria for selecting probands; whether broader criteria should be used to select affected relatives; approaches to including or excluding diagnoses for which family study data suggest a relationship to schizophrenia or to affective disorders or other psychiatric disorders; clarification of diagnostic hierarchy; and issues related to substance abuse and neurological disorders. Also discussed are whether relatives without spectrum diagnoses should be considered unaffected or undiagnosed in linkage analyses, how bilateral familial affectedness should be defined, and provision for independent review of study diagnoses. As an illustration, the clinical model for the authors' schizophrenia linkage study is described.

The result of, and difficulties in, applying a range of existing criteria for mild dementia to a random sample of community elderly aged 70 years and over is examined. By one or more criteria, 25% had mild dementia, and almost 30% of these had additional psychiatric disorders, mostly depression. Prevalence rates for mild dementia varied widely according to the different criteria. Rates of mild dementia increased with age. Poor specification of diagnostic criteria was a major problem. These criteria should be standardised and detailed, and prospective longitudinal studies conducted to elicit the natural history of this condition.

Lymphoblastoid cell lines (LCLs) and fibroblasts provide conveniently derived non-neuronal samples in which to investigate the aetiology of schizophrenia (SZ) using gene expression profiling. This assumes that heritable mechanisms associated with risk of SZ have systemic effects and result in changes to gene expression in all tissues. The broad aim of this and other similar studies is that comparison of the transcriptomes of non-neuronal tissues from SZ patients and healthy controls may identify gene/pathway dysregulation underpinning the neurobiological defects associated with SZ. Using microarrays consisting of 18,664 probes we compared gene expression profiles of LCLs from SZ cases and healthy controls. To identify robust associations with SZ that were not patient or tissue specific, we also examined fibroblasts from an independent series of SZ cases and controls using the same microarrays. In both tissue types ANOVA analysis returned approximately the number of differentially expressed genes expected by chance. No genes were significantly differentially expressed in either tissue when corrected for multiple testing. Even using relaxed parameters (p < or = 0.05, without multiple testing correction) there were still no differentially expressed genes that also displayed > or = 2-fold change between the groups of SZ cases and controls common to both LCLs and fibroblasts. We conclude that despite encouraging data from previous microarray studies assessing non-neural tissues, the lack of a convergent set of differentially expressed genes associated with SZ using fibroblasts and LCLs indicates the utility of non-neuronal tissues for detection of gene expression differences and/or pathways associated with SZ remains to be demonstrated.

Genome‐wide association studies in schizophrenia have recently made significant progress in our understanding of the complex genetic architecture of this disorder. Many genetic loci have been identified and now require functional investigation. One approach involves studying their correlation with neuroimaging and neurocognitive endophenotypes. Theory of Mind ( ToM ) deficits are well established in schizophrenia and they appear to fulfill criteria for being considered an endophenotype. We aim to review the behavioral and neuroimaging‐based studies of ToM in schizophrenia, assess its suitability as an endophenotype, discuss current findings, and propose future research directions. Suitable research articles were sourced from a comprehensive literature search and from references identified through other studies. ToM deficits are repeatable, stable, and heritable: First‐episode patients, those in remission and unaffected relatives all show deficits. Activation and structural differences in brain regions believed important for ToM are also consistently reported in schizophrenia patients at all stages of illness, although no research to date has examined unaffected relatives. Studies using ToM as an endophenotype are providing interesting genetic associations with both single nucleotide polymorphisms ( SNPs ) and specific copy number variations ( CNVs ) such as the 22q11.2 deletion syndrome. We conclude that ToM is an important cognitive endophenotype for consideration in future studies addressing the complex genetic architecture of schizophrenia, and may help identify more homogeneous clinical sub‐types for further study

A significant number of patients with schizophrenia fail to respond to antipsychotic medication. Although several studies have investigated associated patient characteristics, the emerging findings from genetic studies offer further scope for study.In 612 schizophrenia patients with detailed clinical information, common genetic variants indexed by polygenic risk scores, and rare variants indexed by deletion and duplication burden genomewide, we explored potential genetic predictors alongside other established risk factors for treatment resistance. Clinical outcomes of treatment resistance were also calculated using lifetime measures of positive, negative/disorganized and mood symptoms as well as number of hospitalizations and suicide attempts.Logistic regression models identified a significant relationship between treatment resistance and total duplication burden genomewide, years of formal schooling and age at onset. Clinically, treatment-resistant patients were characterized by greater negative/disorganized and positive symptoms and greater number of hospitalizations.Taken together, these findings suggest genetic information, specifically the genomewide burden of rare copy number variants, may increase our understanding and clinical management of patients with treatment-resistant schizophrenia.

There is significant variation in the expression of schizophrenia across ethnically different populations, and the optimal structural and diagnostic representation of schizophrenia are contested. We contrasted both lifetime frequencies of DSM-IV criterion A (the core symptom criterion of the internationally recognized DSM classification system) symptoms and types/content of delusions and hallucinations in transethnic schizophrenia populations from Australia (n = 776), India (n = 504) and Sarawak, Malaysia (n = 259), to elucidate clinical heterogeneity. Differences in both criterion A symptom composition and symptom content were apparent. Indian individuals with schizophrenia reported negative symptoms more frequently than other sites, whereas individuals from Sarawak reported disorganized symptoms more frequently. Delusions of control and thought broadcast, insertion, or withdrawal were less frequent in Sarawak than Australia. Curiously, a subgroup of 20 Indian individuals with schizophrenia reported no lifetime delusions or hallucinations. These findings potentially challenge the long-held view in psychiatry that schizophrenia is fundamentally similar across cultural groups, with differences in only the content of psychotic symptoms, but equivalence in structural form.

Antipsychotic-induced weight gain (AIWG) is a serious concern in therapy with antipsychotic medications. To identify single nucleotide polymorphisms (SNPs) associated with AIWG, we conducted a genome-wide association study (GWAS) for antipsychotic treatment. The discovery cohort consisted of 534 patients with schizophrenia, who underwent 8-week treatment with antipsychotics and were genotyped using the Illumina Human 610-Quad BeadChip. The independent replication cohort consisted of 547 patients with schizophrenia, treated with similar antipsychotics, and genotyped using the Sequenom MassARRAY platform. Two hundred and thirty-six drug-naive patients treated with risperidone or quetiapine were analyzed independently. Additionally, we conducted pathway and expression analyses using several public bioinformatics databases. After correction for age and gender, the top 2 genome-wide significant SNPs with AIWG were located in the PTPRD gene (protein tyrosine phosphatase, receptor type D, 9p24-p23; rs10977144, PGWAS = 9.26E-09; rs10977154, PGWAS = 4.53E-08). The third most significant SNP was in the GFPT2 gene (glutamine-fructose-6-phosphate amidotransferase 2, 5q35.3; rs12386481, PGWAS = 1.98E-07). These results were validated in the replication cohort (rs10977144, PReplication = 4.30E-03; rs10977154, PReplication = 6.33E-03; rs12386481, PReplication =7.65E-03). These results were also verified in those patients initially exposed to risperidone and quetiapine (rs10977144, P = 1.97E-05; rs10977154, P = 2.04E-05; rs12386481, P = 1.97E-04). Pathway analyses showed that AIWG may involve in multiple pathways related to metabolic processes. Moreover, PTPRD mRNA might be highly expressed in brain regions, and the SNPs (rs10977144, rs1097154) also showed significant expression quantitative trait locus effects. Our findings indicate that PTPRD polymorphisms might modulate AIWG.

Major population movements, social structure, and caste endogamy have influenced the genetic structure of Indian populations. An understanding of these influences is increasingly important as gene mapping and case-control studies are initiated in South Indian populations.We report new data on 155 individuals from four Tamil caste populations of South India and perform comparative analyses with caste populations from the neighboring state of Andhra Pradesh. Genetic differentiation among Tamil castes is low (RST = 0.96% for 45 autosomal short tandem repeat (STR) markers), reflecting a largely common origin. Nonetheless, caste- and continent-specific patterns are evident. For 32 lineage-defining Y-chromosome SNPs, Tamil castes show higher affinity to Europeans than to eastern Asians, and genetic distance estimates to the Europeans are ordered by caste rank. For 32 lineage-defining mitochondrial SNPs and hypervariable sequence (HVS) 1, Tamil castes have higher affinity to eastern Asians than to Europeans. For 45 autosomal STRs, upper and middle rank castes show higher affinity to Europeans than do lower rank castes from either Tamil Nadu or Andhra Pradesh. Local between-caste variation (Tamil Nadu RST = 0.96%, Andhra Pradesh RST = 0.77%) exceeds the estimate of variation between these geographically separated groups (RST = 0.12%). Low, but statistically significant, correlations between caste rank distance and genetic distance are demonstrated for Tamil castes using Y-chromosome, mtDNA, and autosomal data.Genetic data from Y-chromosome, mtDNA, and autosomal STRs are in accord with historical accounts of northwest to southeast population movements in India. The influence of ancient and historical population movements and caste social structure can be detected and replicated in South Indian caste populations from two different geographic regions.

Objectives: Social and economic marginalization are significant problems for many people living with mental illness. Clinicians and policy-makers have increased their focus on these aspects of recovery. Current outcome measures, however, do not support this focus, and detailed functional measures are not suitable for routine clinical use. This report describes the development and test–retest reliability of the Activity and Participation Questionnaire (APQ6); a self-report measure of vocational activity and social participation for routine use in community mental health services. Method: The APQ6 was developed from concepts of the Australian Bureau of Statistics Labour Force Surveys and Census. Field testing and consumer consultation were undertaken in New South Wales (NSW) mental health rehabilitation services. Test–retest reliability trials were conducted simultaneously by research teams in NSW and Queensland. Results: Pairs of short-cycle test–retest reliability interviews were obtained from 129 mental health service consumers. Consumer feedback and test–retest reliability results at question and item levels indicate good construct validity. The measure has utility as both a telephone and a personal interview in community mental health settings. Conclusions: The reported psychometric properties support the proposed use of the APQ6 as a recovery-orientated measure focusing on vocational activity and community participation. The APQ6 is being introduced for routine use by NSW mental health services.

There are divergent findings about the level of employment interest among community residents with schizophrenia. In addition, little is known about interest in other socially valued roles, such as formal education and training, self-development, living independently, and other forms of rehabilitation. Interest in employment is important as an indicator of demand for effective supported employment services. Data for this analysis were provided by a large and well-defined community sample of 255 persons with a DSM-IV diagnosis of schizophrenia or schizoaffective disorder. Role functioning was investigated with the Socially-Valued Role Classification Scale. Interest in employment was high, with 85% of the participants being either employed or interested in employment as a future goal. In addition, 95% of participants were either performing, or interested in performing, two other socially valued roles (education and training or rehabilitation). This is more encouraging than some previous studies suggest and indicates that 95% of all community residents with schizophrenia and schizoaffective disorder are candidates for effective rehabilitation programs. Further research is needed to understand the importance of interest in socially valued roles and how appropriate assistance can develop both interest and lack of interest into motivation and action within each role domain.

Patients with schizophrenia often display deficits on tasks thought to measure "executive" processes. Recently, it has been suggested that reductions in fluid intelligence test performance entirely explain deficits reported for patients with focal frontal lesions on classical executive tasks. For patients with schizophrenia, it is unclear whether deficits on executive tasks are entirely accountable by fluid intelligence and representative of a common general process or best accounted for by distinct contributions to the cognitive profile of schizophrenia.In the current study, 50 patients with schizophrenia and 50 age, sex and premorbid intelligence matched controls were assessed using a broad neuropsychological battery, including tasks considered sensitive to executive abilities, namely the Hayling Sentence Completion Test (HSCT), word fluency, Stroop test, digit-span backwards, and spatial working memory. Fluid intelligence was measured using both the Matrix reasoning subtest from the Weschler Abbreviated Scale of Intelligence (WASI) and a composite score derived from a number of cognitive tests.Patients with schizophrenia were impaired on all cognitive measures compared with controls, except smell identification and the optimal betting and risk-taking measures from the Cambridge Gambling Task. After introducing fluid intelligence as a covariate, significant differences remained for HSCT suppression errors, and classical executive function tests such as the Stroop test and semantic/phonemic word fluency, regardless of which fluid intelligence measure was included.Fluid intelligence does not entirely explain impaired performance on all tests considered as reflecting "executive" processes. For schizophrenia, these measures should remain part of a comprehensive neuropsychological assessment alongside a measure of fluid intelligence.

Amyotrophic lateral sclerosis (ALS) is a progressive neurological disease characterised by the degeneration of motor neurons, which are responsible for voluntary movement. There remains limited understanding of disease aetiology, with median survival of ALS of three years and no effective treatment. Identifying genes that contribute to ALS susceptibility is an important step towards understanding aetiology. The vast majority of published human genetic studies, including for ALS, have used samples of European ancestry. The importance of trans-ethnic studies in human genetic studies is widely recognised, yet a dearth of studies of non-European ancestries remains. Here, we report analyses of novel whole-exome sequencing (WES) data from Chinese ALS and control individuals.WES data were generated for 610 ALS cases and 460 controls drawn from Chinese populations. We assessed evidence for an excess of rare damaging mutations at the gene level and the gene set level, considering only singleton variants filtered to have allele frequency less than 5 × 10-5 in reference databases. To meta-analyse our results with a published study of European ancestry, we used a Cochran-Mantel-Haenszel test to compare gene-level variant counts in cases vs controls.No gene passed the genome-wide significance threshold with ALS in Chinese samples alone. Combining rare variant counts in Chinese with those from the largest WES study of European ancestry resulted in three genes surpassing genome-wide significance: TBK1 (p = 8.3 × 10-12), SOD1 (p = 8.9 × 10-9) and NEK1 (p = 1.1 × 10-9). In the Chinese data alone, SOD1 and NEK1 were nominally significantly associated with ALS (p = 0.04 and p = 7 × 10-3, respectively) and the case/control frequencies of rare coding variants in these genes were similar in Chinese and Europeans (SOD1: 1.5%/0.2% vs 0.9%/0.1%, NEK1 1.8%/0.4% vs 1.9%/0.8%). This was also true for TBK1 (1.2%/0.2% vs 1.4%/0.4%), but the association with ALS in Chinese was not significant (p = 0.14).While SOD1 is already recognised as an ALS-associated gene in Chinese, we provide novel evidence for association of NEK1 with ALS in Chinese, reporting variants in these genes not previously found in Europeans.

It is well known that inbreeding increases the risk of recessive monogenic diseases, but it is less certain whether it contributes to the etiology of complex diseases such as schizophrenia. One way to estimate the effects of inbreeding is to examine the association between disease diagnosis and genome-wide autozygosity estimated using runs of homozygosity (ROH) in genome-wide single nucleotide polymorphism arrays. Using data for schizophrenia from the Psychiatric Genomics Consortium (n = 21,868), Keller et al. (2012) estimated that the odds of developing schizophrenia increased by approximately 17% for every additional percent of the genome that is autozygous (β = 16.1, CI(β) = [6.93, 25.7], Z = 3.44, p = 0.0006). Here we describe replication results from 22 independent schizophrenia case-control datasets from the Psychiatric Genomics Consortium (n = 39,830). Using the same ROH calling thresholds and procedures as Keller et al. (2012), we were unable to replicate the significant association between ROH burden and schizophrenia in the independent PGC phase II data, although the effect was in the predicted direction, and the combined (original + replication) dataset yielded an attenuated but significant relationship between Froh and schizophrenia (β = 4.86,CI(β) = [0.90,8.83],Z = 2.40,p = 0.02). Since Keller et al. (2012), several studies reported inconsistent association of ROH burden with complex traits, particularly in case-control data. These conflicting results might suggest that the effects of autozygosity are confounded by various factors, such as socioeconomic status, education, urbanicity, and religiosity, which may be associated with both real inbreeding and the outcome measures of interest.

A new rating scale, the Lifetime Dimensions of Psychosis Scale (LDPS), is described. The LDPS creates a profile of the lifetime characteristics of each case based on retrospective ratings, encompassing the positive, bizarre, negative, and disorganized symptom factors identified by previous studies of psychotic disorders, plus mood-related symptomatology, degree of deterioration, and complicating factors over the course of illness. A preliminary 39-item scale and instruction manual were developed. Intraclass correlation coefficients (ICCs) for positive symptom and mood item total scores were 0.76 to 0.87 (mean of 0.70 for all items). Highly intercorrelated (tau-b coefficients) or unreliable items were eliminated to create the final 20-item version 2. Good-excellent reliability was observed in a second study using different raters. The LDPS is designed for use by experienced clinicians or researchers who have access to comprehensive clinical information, including semistructured diagnostic interviews, psychiatric records, and family history reports. Dimensional scores and multidimensional patterns might prove useful in studying the relationship of clinical phenotype to genotypes, treatment response, and other variables. They may also be useful in clinical practice.

<h3>Context</h3> Identifying susceptibility genes for schizophrenia may be complicated by phenotypic heterogeneity, with some evidence suggesting that phenotypic heterogeneity reflects genetic heterogeneity. <h3>Objective</h3> To evaluate the heritability and conduct genetic linkage analyses of empirically derived, clinically homogeneous schizophrenia subtypes. <h3>Design</h3> Latent class and linkage analysis. <h3>Setting</h3> Taiwanese field research centers. <h3>Participants</h3> The latent class analysis included 1236 Han Chinese individuals with<i>DSM-IV</i>schizophrenia. These individuals were members of a large affected-sibling-pair sample of schizophrenia (606 ascertained families), original linkage analyses of which detected a maximum logarithm of odds (LOD) of 1.8 (<i>z</i> = 2.88) on chromosome 10q22.3. <h3>Main Outcome Measures</h3> Multipoint exponential LOD scores by latent class assignment and parametric heterogeneity LOD scores. <h3>Results</h3> Latent class analyses identified 4 classes, with 2 demonstrating familial aggregation. The first (LC2) described a group with severe negative symptoms, disorganization, and pronounced functional impairment, resembling “deficit schizophrenia.” The second (LC3) described a group with minimal functional impairment, mild or absent negative symptoms, and low disorganization. Using the negative/deficit subtype, we detected genome-wide significant linkage to 1q23-25 (LOD = 3.78, empiric genome-wide<i>P</i> = .01). This region was not detected using the<i>DSM-IV</i>schizophrenia diagnosis, but has been strongly implicated in schizophrenia pathogenesis by previous linkage and association studies.Variants in the 1q region may specifically increase risk for a negative/deficit schizophrenia subtype. Alternatively, these results may reflect increased familiality/heritability of the negative class, the presence of multiple 1q schizophrenia risk genes, or a pleiotropic 1q risk locus or loci, with stronger genotype-phenotype correlation with negative/deficit symptoms. Using the second familial latent class, we identified nominally significant linkage to the original 10q peak region. <h3>Conclusion</h3> Genetic analyses of heritable, homogeneous phenotypes may improve the power of linkage and association studies of schizophrenia and thus have relevance to the design and analysis of genome-wide association studies.

Objective: Suicide and attempted suicide are common in individuals with schizophrenia, and evidence exists for a link between substance use disorders and suicidality in this disorder. However, alcohol has not been consistently implicated. We examined the relationship between substance use disorders and suicide attempts in schizophrenia. Methods: We recruited a schizophrenia sample in Australia ( n = 821) for genetic analyses. We analysed demographic and clinical variables, including substance use disorders, and their relationship to suicide attempts using generalised equation modelling. Results: A significant association was identified between lifetime alcohol abuse/dependence and suicide attempts (OR = 1.66; 95% CI, 1.23 to 2.24; p= 0.001) after adjustment for potential confounders, but not between cannabis abuse/dependence and suicide attempts, nor between other illicit drug abuse/dependence and suicide attempts. Polysubstance abuse/dependence was also not implicated. Conclusions: These results suggest that the presence of alcohol abuse/dependence may be a risk factor for suicide attempts in individuals with schizophrenia, independent of comorbid substance abuse/dependence.

The neurodevelopmentally regulated microRNA miR-137 was strongly implicated as risk locus for schizophrenia in the most recent genome wide association study coordinated by the Psychiatric Genome Consortium (PGC). This molecule is highly conserved in vertebrates enabling the investigation of its function in the developing zebrafish. We utilized this model system to achieve overexpression and suppression of miR-137, both transiently and stably through transgenesis. While miR-137 overexpression was not associated with an observable specific phenotype, downregulation by antisense morpholino and/or transgenic expression of miR-sponge RNA induced significant impairment of both embryonic and larval touch-sensitivity without compromising overall anatomical development. We observed miR-137 expression and activity in sensory neurons including Rohon-Beard neurons and dorsal root ganglia, two neuronal cell types that confer touch-sensitivity in normal zebrafish, suggesting a role of these cell types in the observed phenotype. The lack of obvious anatomical or histological pathology in these cells, however, suggested that subtle axonal network defects or a change in synaptic function and neural connectivity might be responsible for the behavioral phenotype rather than a change in the cellular morphology or neuroanatomy.

We systematically and comprehensively investigated polymorphisms of the HTR1B gene as well as their linkage disequilibrium and ancestral relationships. We have detected the following polymorphisms in our sample via denaturing gradient gel electrophoresis, database comparisons, and/or previously published assays: G-511T, T-261G, -182INS/DEL-181, A-161T, C129T, T371G, T655C, C705T, G861C, A1099G, G1120A, and A1180G. The results of the intermarker analyses showed strong linkage disequilibrium between the C129T and the G861C polymorphisms and revealed four common haplotypes: ancestral (via chimpanzee comparisons), 129T/861C, -161T, and -182DEL-181. The results of association tests with schizophrenia were negative, although A-161T had a nominal P = 0.04 via ASPEX/sib_tdt. The expressed missense substitutions, Phe124Cys, Phe219Leu, Ile367Val, and Glu374Lys, could potentially affect ligand binding or interaction with G proteins and thus modify drug response in carriers of these variants. On average, the human cSNPs and differences among other primates clustered in the more thermodynamically unstable regions of the mRNA, which suggests that the evolutionary survival of nucleotide sequence variation may be influenced by the mRNA structure of this gene.

Previously, a combined analysis by the Chromosome 22 Collaborative Linkage Group (1996; Am. J. Med Genet. 67, 40–45) used an affected sib-pair analysis of a single marker (D22S278) in 574 families multiply affected by schizophrenia and found some evidence for linkage (χ2 =9.35, 1 df, p = 0.001), suggesting the presence of a disease locus nearby on chromosome 22q12. In order to further investigate the importance of this result, we have performed the transmission disequilibrium test (TDT) and additional parametric and non-parametric linkage analysis of the same data. The most positive result obtained was an admixture lod score of 0.9 under the assumption of locus heterogeneity and dominant transmission. The result of the TDT analysis was significant at p = 0.015 (allele-wise; χ2 = 22, 10 df) and p = 0.00016 (genotype-wise; χ2 = 66.2, 30 df, empirical p value = 0.0009). Overall, these results further strengthen the notion that there is a susceptibility locus for schizophrenia close to D22S278.

Several studies have reported alterations in finger and a-b ridge counts, and their derived measures of asymmetry, in schizophrenia compared to controls. Because ridges are fully formed by the end of the second trimester, they may provide clues to disturbed early development. The aim of this study was to assess these measures in a sample of patients with psychosis and normal controls.Individuals with psychosis (n = 240), and normal controls (n = 228) were drawn from a catchment-area case-control study. Differences in finger and a-b ridge count and Fluctuating Asymmetry were assessed in three group comparisons (non-affective psychosis versus controls; affective psychosis versus controls; non-affective psychosis versus affective psychosis). The analyses were performed separately for males and females.There were no significant group differences for finger nor a-b ridge counts. While there were no group difference for Directional Asymmetry, for Fluctuating Asymmetry measures men with non-affective psychosis had significantly higher fluctuating asymmetry of the index finger ridge count (a) when compared to controls (FA-correlation score, p = 0.02), and (b) when compared to affective psychosis (adjusted FA-difference score, p = 0.04).Overall, measures of finger and a-b ridge counts, and their derived measures of directional and fluctuating asymmetry were not prominent features of psychosis in this sample. While directional asymmetry in cerebral morphology is reduced in schizophrenia, this is not reflected in dermatoglyphic variables.

Schizophrenia is a severe debilitating brain disorder with a poorly understood aetiology. Among the diverse aetiological clues lies evidence for immune abnormalities in some individuals. The aim of this study was to investigate the frequency and specificity of autoantibodies directed against the brain in people with schizophrenia. Sera were screened for reactivity against human brain tissue (hippocampus and prefrontal cortex). Neuronal cell body and filamentous patterns of brain tissue staining were observed significantly more frequently in sera from schizophrenia patients (n=30) compared to controls (n=24). Sera that showed a neuronal cell body pattern of staining on hippocampus reacted strongly to an extracellular epitope of the M1 muscarinic acetylcholine receptor (m1AChR) in ELISA. Both cell body staining and elevated m1AChR reactivity correlated with higher symptom scores for poverty of speech. Sera showing a filamentous staining pattern predominantly targeted microfilaments, intermediate filaments or neurofilaments, particularly neurofilament medium (NFM), which is a dopamine receptor interacting protein. By ELISA, there was strongly elevated reactivity against NFM in a subset (15%) of schizophrenia patients (n=101) compared to healthy controls (n=55) or patients with multiple sclerosis (n=32). These results support the hypothesis that neurotransmitter receptors or molecules involved in regulation of neurotransmission are targets of autoantibodies in some people with schizophrenia.

MicroRNAs (miRNAs) are known to regulate the expression of genes that are important for brain development and function, but the roles of other classes of small non-coding RNAs (sncRNAs) are less well understood. Additionally, although miRNA expression studies have been conducted in post-mortem brain samples from schizophrenia (SCZ) patients, other classes of sncRNAs are yet to be investigated in SCZ. We profiled the expression of miRNAs, piwi-interacting RNAs (piRNAs), small nucleolar RNAs (snoRNAs) and small nuclear RNAs (snRNAs) in SCZ by applying small RNA sequencing (RNA-Seq) to sncRNA isolated from post-mortem anterior cingulate cortex (ACC) of SCZ-affected individuals (n = 22) and matched controls (n = 22). We identified about one-third of annotated miRNAs, one-quarter of snoRNAs and a small proportion of piRNAs and snRNAs. No sncRNAs were significantly differentially expressed between SCZ and controls, but there was evidence for an interaction between disease status and sex on the expression level of a number of miRNAs and snoRNAs. Many of these transcripts exhibited differential expression between male and female cases, and/or between female cases and controls, suggesting sex based dysregulation in ACC of SCZ. These findings require replication in an independent sample, but our study provides further insights into the potential involvement of sncRNAs in brain function and SCZ.

Polygenic risk score (PRS) methods based on genome-wide association studies (GWAS) have a potential for predicting the risk of developing complex diseases and are expected to become more accurate with larger training datasets and innovative statistical methods. The area under the ROC curve (AUC) is often used to evaluate the performance of PRSs, which requires individual genotypic and phenotypic data in an independent GWAS validation dataset. We are motivated to develop methods for approximating AUC of PRSs based on the summary level data of the validation dataset, which will greatly facilitate the development of PRS models for complex diseases.We develop statistical methods and an R package SummaryAUC for approximating the AUC and its variance of a PRS when only the summary level data of the validation dataset are available. SummaryAUC can be applied to PRSs with SNPs either genotyped or imputed in the validation dataset. We examined the performance of SummaryAUC using a large-scale GWAS of schizophrenia. SummaryAUC provides accurate approximations to AUCs and their variances. The bias of AUC is typically <0.5% in most analyses. SummaryAUC cannot be applied to PRSs that use all SNPs in the genome because it is computationally prohibitive.https://github.com/lsncibb/SummaryAUC.Supplementary data are available at Bioinformatics online.

Rapid emotion processing is an ecologically essential ability for survival in social environments in which threatening or advantageous encounters dynamically and rapidly occur. Efficient emotion recognition is subserved by different processes, depending on one's expectations; however, the underlying functional and structural circuitry is still poorly understood. In this study, we delineate brain networks that subserve fast recognition of emotion in situations either congruent or incongruent with prior expectations. For this purpose, we used multimodal neuroimaging and investigated performance on a dynamic emotion perception task. We show that the extended amygdala structural and functional networks relate to speed of emotion processing under threatening conditions. Specifically, increased microstructure of the right stria terminalis, an amygdala white-matter pathway, was related to faster detection of emotion during actual presentation of anger or after cueing anger. Moreover, functional connectivity of right amygdala with limbic regions was related to faster detection of anger congruent with cue, suggesting selective attention to threat. On the contrary, we found that faster detection of anger incongruent with cue engaged the ventral attention "reorienting" network. Faster detection of happiness, in either expectancy context, engaged a widespread frontotemporal-subcortical functional network. These findings shed light on the functional and structural circuitries that facilitate speed of emotion recognition and, for the first time, elucidate a role for the stria terminalis in human emotion processing.

Schizophrenia is associated with mentalizing deficits that impact on social functioning and quality of life. Recently, schizophrenia has been conceptualized as a disorder of neural dysconnectivity and network level analyses offers a means of understanding the underlying deficits leading to mentalizing difficulty. Using an established mentalizing task (The Triangles Task), functional magnetic resonance images (fMRI) were acquired from 19 patients with schizophrenia and 17 age- and sex-matched healthy controls (HCs). Participants were required to watch short animations of two triangles interacting with each other with the interactions either random (no interaction), physical (patterned movement), or mental (intentional movement). Task-based Partial Least Squares (PLS) was used to analyze activation differences and commonalities between the three conditions and the two groups. Seed-based PLS was used to assess functional connectivity with peaks identified in the task-based PLS. Behavioural PLS was then performed using the accuracy from the mental conditions. Patients with schizophrenia performed worse on the mentalizing condition compared to HCs. Task-based PLS revealed one significant latent variable (LV) that explained 42.9% of the variance in the task, with theLV separating the mental condition from the physical and random conditions in patients with schizophrenia, but only the mental from physical in healthy controls. The mental animations were associated with increased modulation of the inferior frontal gyri bilaterally, left superior temporal gyrus, right postcentral gyrus, and left caudate nucleus. The physical/random animations were associated with increased modulation of the right medial frontal gyrus and left superior frontal gyrus. Seed-based PLS identified increased functional connectivity with the left inferior frontal gyrus (liFG) and caudate nucleus in patients with schizophrenia, during the mental and physical interactions, with functional connectivity with the liFG associated with increased performance on the mental animations. The results suggest that mentalizing deficits in schizophrenia may arise due to inefficient social brain networks.

Abstract Schizophrenia (SZ) is associated with an increased risk of life-long cognitive impairments, age-related chronic disease, and premature mortality. We investigated evidence for advanced brain ageing in adult SZ patients, and whether this was associated with clinical characteristics in a prospective meta-analytic study conducted by the ENIGMA Schizophrenia Working Group. The study included data from 26 cohorts worldwide, with a total of 2803 SZ patients (mean age 34.2 years; range 18-72 years; 67% male) and 2598 healthy controls (mean age 33.8 years, range 18-73 years, 55% male). Brain-predicted age was individually estimated using a model trained on independent data based on 68 measures of cortical thickness and surface area, 7 subcortical volumes, lateral ventricular volumes and total intracranial volume, all derived from T1-weighted brain magnetic resonance imaging (MRI) scans. Deviations from a healthy brain ageing trajectory were assessed by the difference between brain-predicted age and chronological age (brain-predicted age difference [brain-PAD]). On average, SZ patients showed a higher brain-PAD of +3.64 years (95% CI: 3.01, 4.26; I 2 = 55.28%) compared to controls, after adjusting for age and sex (Cohen’s d = 0.50). Among SZ patients, brain-PAD was not associated with specific clinical characteristics (age of onset, duration of illness, symptom severity, or antipsychotic use and dose). This large-scale collaborative study suggests advanced structural brain ageing in SZ. Longitudinal studies of SZ and a range of mental and somatic health outcomes will help to further evaluate the clinical implications of increased brain-PAD and its ability to be influenced by interventions.

We recently introduced the Cre/Lox technology in our laboratory for both transient (mRNA injections) and stable/transgenic experiments. We experienced significant issues such as silencing, mosaicism, and partial recombination using both approaches. Reviewing the literature gave us the impression that these issues are common among the zebrafish community using the Cre/Lox system. While some researchers took advantage of these problems for specific applications, such as cell and lineage tracing using the Zebrabow construct, we tried here to improve the efficiency and reliability of this system by constituting and testing a new set of tools for zebrafish genetics. First, we implemented a codon-improved Cre version (iCre) designed for rodent studies to counteract some of the aforementioned problems. This eukaryotic-like iCre version was engineered to i) reduce silencing, ii) increase mRNA stability, iii) enhance translational efficiency, and iv) improve nuclear translocation. Second, we established a new set of tol2-kit compatible vectors to facilitate the generation of either iCre-mRNA or iCre-transgenes for transient and transgenic experiments, respectively. We then validated the use of this material and are providing tips for users. Interestingly, during the validation steps, we found that maternal iCRE-mRNA and/or protein deposition from female transgenics systematically led to complete/homogeneous conversion of all tested Lox-responder-transgenes, as opposed to some residual imperfect conversion when using males-drivers or mRNA injections. Considering that we did not find any evidence of Cre-protein soaking and injections in the literature as it is usually conducted with cells, we tested these approaches. While soaking of cell-permeant CRE-protein did not lead to any detectable Lox-conversion, 1ng-10 ng protein injections led to robust and homogeneous Lox-recombination, suggesting that the use of protein could be a robust option for exogenous delivery. This approach may be particularly useful to manipulate housekeeping genes involved in development, sex determination and reproduction which are difficult to investigate with traditional knockout approaches. All in all, we are providing here a new set of tools that should be useful in the field.

Background: The relationship between genotype and phenotype is governed by numerous genetic interactions (GIs), and the mapping of GI networks is of interest for two main reasons: 1) By modelling biological robustness, GIs provide a powerful opportunity to infer compensatory biological mechanisms via the identification of functional relationships between genes, which is of interest for biological discovery and translational research. Biological systems have evolved to compensate for genetic (i.e., variations and mutations) and environmental (i.e., drug efficacy) perturbations by exploiting compensatory relationships between genes, pathways and biological processes; 2) GI facilitates the identification of the direction (alleviating or aggravating interactions) and magnitude of epistatic interactions that influence the phenotypic outcome. The generation of GIs for human diseases is impossible using experimental biology approaches such as systematic deletion analysis. Moreover, the generation of disease-specific GIs has never been undertaken in humans. Methods: We used our Indian schizophrenia case-control (case-816, controls-900) genetic dataset to implement the workflow. Standard GWAS sample quality control procedure was followed. We used the imputed genetic data to increase the SNP coverage to analyse epistatic interactions across the genome comprehensively. Using the odds ratio (OR), we identified the GIs that increase or decrease the risk of a disease phenotype. The SNP-based epistatic results were transformed into gene-based epistatic results. Results: We have developed a novel approach by conducting gene-based statistical epistatic analysis using an Indian schizophrenia case-control genetic dataset and transforming these results to infer GIs that increase the risk of schizophrenia. There were ∼9.5 million GIs with a p-value ≤ 1 × 10-5. Approximately 4.8 million GIs showed an increased risk (OR > 1.0), while ∼4.75 million GIs had a decreased risk (OR <1.0) for schizophrenia. Conclusion: Unlike model organisms, this approach is specifically viable in humans due to the availability of abundant disease-specific genome-wide genotype datasets. The study exclusively identified brain/nervous system-related processes, affirming the findings. This computational approach fills a critical gap by generating practically non-existent heritable disease-specific human GIs from human genetic data. These novel datasets can train innovative deep-learning models, potentially surpassing the limitations of conventional GWAS.

Bipolar disorder (BD) is a heritable mental illness with complex etiology. While the largest published genome-wide association study identified 64 BD risk loci, the causal SNPs and genes within these loci remain unknown. We applied a suite of statistical and functional fine-mapping methods to these loci, and prioritized 22 likely causal SNPs for BD. We mapped these SNPs to genes, and investigated their likely functional consequences by integrating variant annotations, brain cell-type epigenomic annotations, brain quantitative trait loci, and results from rare variant exome sequencing in BD. Convergent lines of evidence supported the roles of SCN2A, TRANK1, DCLK3, INSYN2B, SYNE1, THSD7A, CACNA1B, TUBBP5, PLCB3, PRDX5, KCNK4, AP001453.3, TRPT1, FKBP2, DNAJC4, RASGRP1, FURIN, FES, YWHAE, DPH1, GSDMB, MED24, THRA, EEF1A2, and KCNQ2 in BD. These represent promising candidates for functional experiments to understand biological mechanisms and therapeutic potential. Additionally, we demonstrated that fine-mapping effect sizes can improve performance and transferability of BD polygenic risk scores across ancestrally diverse populations, and present a high-throughput fine-mapping pipeline (https://github.com/mkoromina/SAFFARI).

Polymethoxylated flavones (PMFs) from citrus inhibit production of TNF-alpha and other pro-inflammatory cytokines. As TNF-alpha also modulates NK cell activity, the current studies were conducted to assess the potential for a standardized citrus PMF mixture to suppress humoral and innate immune functions. PMFs were isolated from orange peel oil using a procedure that obtained a consistent mixture of PMFs both in identity and proportion. The mixture consisted of nobiletin (30.7%), 3,3',4',5,6,7,8-heptamethoxyflavone (27.9%), trimethylscutellarein (14.5%), tangeretin (10.4%), sinensetin (5.8%), 5-demethyl-nobiletin (2.0%), hexa-O-methylquercetagetin (1.3%), 5-demethyl-tetramethylscutellarein (0.6%), and other flavonoids (2.7%). To assess the effect of the PMF mixture on humoral immune responses, female B(6)C(3)F(1) mice (n=8) were exposed to the PMF by gavage at 5, 50, 150 and 500 mg/kg/day for 28 days. On day 25, mice were sensitized to sRBC by tail vein injection and AFC response determined 4 days later. Humoral immunity was insensitive to suppression following exposure to all concentrations of the PMF mixture. Suppression of NK cell activity was observed only following 500 mg/kg/day for 28 days. Body weights were not affected by exposure to any concentration of the PMF mixture in sRBC immunized or non-immunized mice. However, in sRBC-immunized mice, higher concentrations of PMF were associated with a statistically insignificant increase in spleen weight (P>0.05). No change in spleen weight was observed in non-immunized mice. As anticipated, based on previously published in vitro observations, long-term, high-dose exposure to a standardized mixture of citrus PMFs caused a mild suppression of NK cell activity; however, humoral immunity was not sensitive to suppression at the same exposure levels.

Seasonal variation has been reported for both affective disorders and schizophrenia. The current study examines seasonal variation in admissions in schizophrenia, depression and bipolar disorder in Tasmania, the southernmost state of Australia.All admissions with a diagnosis of schizophrenia, bipolar disorder and depression in Tasmania between 1983 and 1989 were examined for evidence of seasonal variation in admission patterns.Using the modified Kolmogorov-Smirnov statistic defined by Freedman no significant seasonal variation was found in admissions with diagnoses of mania, depression or schizophrenia. There was a significant seasonal variation in admissions with schizoaffective disorder (winter peak).There is no significant seasonal variation in admissions with schizophrenia, depression or bipolar disorder in Tasmania. This may be due to a combination of geographical location and the stringent test of seasonal variation used in the current study.

A single nucleotide polymorphism (TNF(-308A)) within the promoter region of the gene encoding tumor necrosis factor (TNF), has been significantly associated with schizophrenia in a study of Italian patients and control subjects Boin et al. [2001: Mol Psychiatry 6:79-82]. We have applied case-control analyses to examine TNF promoter haplotypes (containing TNF(-308) and two additional promoter variants: TNF(-376) and TNF(-238)) in four schizophrenia cohorts drawn from Australian, Indian Fijian, Indigenous Fijian, and Brahmin populations. In addition, we have applied the sibling transmission disequilibrium (STD) test to promoter haplotypes within 81 trios drawn from Australian Caucasian pedigrees with multiple schizophrenia cases, and 86 trios drawn from the Brahmin population of Tamil Nadu province in Southern India. Within each of these cohorts, we found no evidence of recombination between these tightly linked promoter variants, supporting previous studies which demonstrated that only a subset of the eight possible haplotypes exist. Of the four observed haplotypes, we and others have observed only one carries the TNF(-308A) variant allele. We report no significant differences in TNF promoter haplotype frequencies between the patient and control groups within each population, although the Indian Fijian cohort showed a trend towards reduced TNF(-308A) alleles amongst schizophrenia cases (P = 0.07). We found no evidence of bias in TNF promoter haplotype transmission to schizophrenia probands. Very similar results were obtained when only the TNF(-308) polymorphism was considered. Taken together, these data provide no support for the involvement of TNF promoter variants TNF(-308), TNF(-376), and TNF(-238) in schizophrenia susceptibility within four ethnically distinct cohorts.

Genes contain the codes for the growth, development, and function of all living organisms. In the study of animal behavior, genetics has come to the forefront because much of behavior is shaped by the interaction between genetic and environmental information. Genes are the products of natural selection and students of animal behavior must consider how the adaptive value of behavior affected past evolutionary events as well as how evolution might shape behavior in the future. Humans have, through the process of domestication, manipulated the behavior of numerous animal species; the study of the effects of artificial selection on behavior is a key element of behavioral genetics. The search for the precise genetic basis for behavior that involves hypotheses for single-gene control over a specific behavior may be futile, as quantitative genetic approaches teach us that many genes can contribute to a given behavior. Identifying candidate genes—those which may influence a behavior—helps us to isolate specific genes within the network of genes and to understand the role of each gene in the network. Behavioral genetics is a rapidly expanding area in the study of animal behavior.

The association between vitamin D levels and skeletal growth has long been recognized. However, exposure to low levels of vitamin D during early life is also known to alter brain development, and is a candidate risk factor for schizophrenia. This study examines the association between four polymorphisms in the vitamin D receptor (VDR) and 1) risk of schizophrenia, and 2) three anthropometric variables (height, head size, and head shape). Four single-nucleotide polymorphisms (SNPs; rs10735810/FokI, rs1544410/BsmI, rs7975232/ApaI, and rs731236/TaqI) in the VDR gene were genotyped in 179 individuals with schizophrenia and 189 healthy controls. No significant associations were detected between any of the four VDR SNPs and risk of schizophrenia. Patients were slightly but significantly shorter compared to controls. Of the four SNPs, only rs10735810/FokI was associated with any of the anthropometric measures: the M4 isoform of this SNP was significantly associated with larger head size (P = 0.002). In light of the evidence demonstrating a role for vitamin D during brain development, the association between polymorphisms in VDR and brain development warrants closer scrutiny.

The study of ethnically homogeneous populations may help to identify schizophrenia risk loci. The authors conducted a genomewide linkage scan for schizophrenia in an Indian population.Participants were 441 individuals (262 affected probands and siblings) who were recruited primarily from one ethnically homogeneous group, the Tamil Brahmin caste, although individuals from other geographically proximal castes also participated. Genotyping of 124 affected sibling pair pedigrees was performed with 402 short tandem repeat polymorphisms. Linkage analyses were conducted using nonparametric exponential LOD (logarithm of the odds ratio for linkage) scores and parametric heterogeneity LOD scores. Parametric heterogeneity scores were calculated using simple dominant and recessive models, correcting for multiple statistics. The data were examined for evidence of consanguinity. Genomewide significance levels were determined using 10,000 gene dropping simulations.These findings revealed genomewide significant linkage to chromosome 1p31.1, through the use of both exponential and heterogeneity LOD scores, incorporating correction for multiple statistics and mild consanguinity. The estimated sibling recurrence risk associated with this putative locus was 1.95. Analysis for heterogeneity LOD scores also detected suggestive linkage to chromosomes 13q22.1 and 16q12.2. Using 117 tag single nucleotide polymorphisms (SNPs), family-based association analyses of phosphodiesterase 4B (PDE4B), the closest schizophrenia candidate gene, detected no convincing evidence of association, suggesting that the chromosome 1 peak represents a novel risk locus.This is the first study-to the authors' knowledge-to report significant linkage of schizophrenia to chromosome 1p31.1. Further investigation of this chromosome region in diverse populations is warranted to identify underlying sequence variants.

Large deletions are found to a greater extent in patients with schizophrenia compared with healthy controls. This study aims to investigate clinical symptomatology and substance abuse rates in patients with large (>500kb), rare (<1% of cohort) deletions and duplications compared with schizophrenia patients in general.633 schizophrenia patients, including 60 with large (>500kb), rare (<1% of cohort) deletions and 74 with large, rare duplications, who formed part of a large genome-wide association study, were assessed for alcohol and cannabis abuse rates as well as a range of symptom measures using the Diagnostic Interview for Genetic Studies (DIGS), Family Interview for Genetic Studies (FIGS), and medical records.Patients with large, rare deletions had significantly less cannabis abuse rates but comparable alcohol abuse rates, with an age at onset later than those without large, rare deletions. There was no significant difference in any substance abuse or clinical symptom rates between patients with and without large, rare duplications, but an interaction did exist between cannabis abuse, duplication status, and age at onset, with cannabis abuse resulting in an earlier age at onset only in those without a large, rare duplication. Similarly, patients with a large, rare duplication had a later onset age for cannabis abuse/dependence.Schizophrenia patients with large, rare deletions were less likely to have comorbid cannabis abuse over their lifetime. This provides support for a threshold model of risk with those carrying a schizophrenia-associated copy number variation less reliant on environmental insults. Patients with large, rare duplications were protected against earlier onset of schizophrenia in the presence of comorbid cannabis abuse in addition to later onset of cannabis abuse itself.

While 17% of US adults use tobacco regularly, smoking rates among persons with schizophrenia are upwards of 60%. Research supports a shared etiological basis for smoking and schizophrenia, including findings from genome-wide association studies (GWAS). However, few studies have directly tested whether the same or distinct genetic variants also influence smoking behavior among schizophrenia cases. Using data from the Psychiatric Genomics Consortium (PGC) study of schizophrenia (35476 cases, 46839 controls), we estimated genetic correlations between these traits and tested whether polygenic risk scores (PRS) constructed from the results of smoking behaviors GWAS were associated with schizophrenia risk or smoking behaviors among schizophrenia cases. Results indicated significant genetic correlations of schizophrenia with smoking initiation (rg = 0.159; P = 5.05 × 10−10), cigarettes-smoked-per-day (rg = 0.094; P = 0.006), and age-of-onset of smoking (rg = 0.10; P = 0.009). Comparing smoking behaviors among schizophrenia cases to the general population, we observe positive genetic correlations for smoking initiation (rg = 0.624, P = 0.002) and cigarettes-smoked-per-day (rg = 0.689, P = 0.120). Similarly, TAG-based PRS for smoking initiation and cigarettes-smoked-per-day were significantly associated with smoking initiation (P = 3.49 × 10−5) and cigarettes-smoked-per-day (P = 0.007) among schizophrenia cases. We performed the first GWAS of smoking behavior among schizophrenia cases and identified a novel association with cigarettes-smoked-per-day upstream of the TMEM106B gene on chromosome 7p21.3 (rs148253479, P = 3.18 × 10−8, n = 3520). Results provide evidence of a partially shared genetic basis for schizophrenia and smoking behaviors. Additionally, genetic risk factors for smoking behaviors were largely shared across schizophrenia and non-schizophrenia populations. Future research should address mechanisms underlying these associations to aid both schizophrenia and smoking treatment and prevention efforts.

The aim of this study was to examine the rate of rehospitalisation for schizophrenia, bipolar disorder and depression over a 5-year period in Tasmania, and to identify predictors of the number and duration of readmissions.The Tasmanian Mental Health Register was used to study the 5-year pattern of rehospitalisation for all patients admitted to a Tasmanian public psychiatric inpatient facility with a primary diagnosis of schizophrenia, bipolar disorder or depression, in 1983 or 1984.Seventy-one percent of patients receiving a diagnosis of schizophrenia were readmitted in the 5-year period, compared to 59% for bipolar disorder and 48% for depression. For all three diagnoses, the number of prior admissions was a predictor of the number of readmissions and the total number of days spent in hospital in the follow-up period. Age and sex also had significant effects, which varied across diagnostic groups.A substantial proportion of patients hospitalised for schizophrenia, bipolar disorder or schizophrenia were rehospitalised during the next 5 years. Patients with more previous admissions had more readmissions than those with fewer previous admissions.

The expression level for 15 887 transcripts in lymphoblastoid cell lines from 19 monozygotic twin pairs (10 male, 9 female) were analysed for the effects of genotype and sex. On an average, the effect of twin pairs explained 31% of the variance in normalized gene expression levels, consistent with previous broad sense heritability estimates. The effect of sex on gene expression levels was most noticeable on the X chromosome, which contained 15 of the 20 significantly differentially expressed genes. A high concordance was observed between the sex difference test statistics and surveys of genes escaping X chromosome inactivation. Notably, several autosomal genes showed significant differences in gene expression between the sexes despite much of the cellular environment differences being effectively removed in the cell lines. A publicly available gene expression data set from the CEPH families was used to validate the results. The heritability of gene expression levels as estimated from the two data sets showed a highly significant positive correlation, particularly when both estimates were close to one and thus had the smallest standard error. There was a large concordance between the genes significantly differentially expressed between the sexes in the two data sets. Analysis of the variability of probe binding intensities within a probe set indicated that results are robust to the possible presence of polymorphisms in the target sequences.

Humans reached present-day Island Southeast Asia (ISEA) in one of the first major human migrations out of Africa. Population movements in the millennia following this initial settlement are thought to have greatly influenced the genetic makeup of current inhabitants, yet the extent attributed to different events is not clear. Recent studies suggest that south-to-north gene flow largely influenced present-day patterns of genetic variation in Southeast Asian populations and that late Pleistocene and early Holocene migrations from Southeast Asia are responsible for a substantial proportion of ISEA ancestry. Archaeological and linguistic evidence suggests that the ancestors of present-day inhabitants came mainly from north-to-south migrations from Taiwan and throughout ISEA approximately 4,000 years ago. We report a large-scale genetic analysis of human variation in the Iban population from the Malaysian state of Sarawak in northwestern Borneo, located in the center of ISEA. Genome-wide single-nucleotide polymorphism (SNP) markers analyzed here suggest that the Iban exhibit greatest genetic similarity to Indonesian and mainland Southeast Asian populations. The most common non-recombining Y (NRY) and mitochondrial (mt) DNA haplogroups present in the Iban are associated with populations of Southeast Asia. We conclude that migrations from Southeast Asia made a large contribution to Iban ancestry, although evidence of potential gene flow from Taiwan is also seen in uniparentally inherited marker data.

Total burden of copy number deletions has been implicated in schizophrenia risk and has been associated with reduced cognitive functioning. The current study aims to replicate the cognitive findings and investigate regional grey and white matter volumes. Moreover, it will explore resting-state networks for correlations between functional connectivity and total deletion burden. All imaging differences will be investigated for correlations with cognitive differences. Seventy-eight patients with chronic schizophrenia, who formed a subset of a large genome-wide association study (GWAS), were assessed for intelligence, 34 had structural magnetic resonance imaging, 33 had resting-state functional magnetic resonance imaging, and 32 had diffusion tensor imaging (DTI). Total deletion burden was negatively associated with IQ performance and positively associated with regional volumes in the striatum bilaterally and in the right superior temporal gyrus and white-matter in the corpus callosum. Correlations were identified between deletion burden and both hyper and hypoconnectivity within the default-mode network and hypoconnectivity within the cognitive control network. The functional connectivity correlations with deletion burden were also correlated with the IQ differences identified. Total deletion burden affects regional volumes and resting-state functional connectivity in key brain networks in patients with schizophrenia. Moreover, effects of deletions on cognitive functioning in may be due to inefficiency of key brain networks as identified by dysconnectivity in resting-state networks.

Social interactions require the ability to rapidly perceive emotion from various incoming dynamic, multisensory cues. Prior expectations reduce incoming emotional information and direct attention to cues that are aligned with what is expected. Studies to date have investigated the prior expectancy effect using static emotional images, despite the fact that dynamic stimuli would represent greater ecological validity. The objective of the study was to create a novel functional magnetic resonance imaging (fMRI) paradigm to examine the influence of prior expectations on naturalistic emotion perception. For this purpose, we developed a dynamic emotion perception task, which consisted of audio-visual videos that carry emotional information congruent or incongruent with prior expectations. The results show that emotional congruency was associated with activity in prefrontal regions, amygdala, and putamen, whereas emotional incongruency was associated with activity in temporoparietal junction and mid-cingulate gyrus. Supported by the behavioural results, our findings suggest that prior expectations are reinforced after repeated experience and learning, whereas unexpected emotions may rely on fast change detection processes. The results from the current study are compatible with the notion that the ability to automatically detect unexpected changes in complex dynamic environments allows for adaptive behaviours in potentially advantageous or threatening situations.