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Contains fulltext : 248656.pdf (Publisher’s version ) (Closed access) 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.

We generated cortical interneurons (cINs) from induced pluripotent stem cells derived from 14 healthy controls and 14 subjects with schizophrenia. Both healthy control cINs and schizophrenia cINs were authentic, fired spontaneously, received functional excitatory inputs from host neurons, and induced GABA-mediated inhibition in host neurons in vivo. However, schizophrenia cINs had dysregulated expression of protocadherin genes, which lie within documented schizophrenia loci. Mice lacking protocadherin-α showed defective arborization and synaptic density of prefrontal cortex cINs and behavioral abnormalities. Schizophrenia cINs similarly showed defects in synaptic density and arborization that were reversed by inhibitors of protein kinase C, a downstream kinase in the protocadherin pathway. These findings reveal an intrinsic abnormality in schizophrenia cINs in the absence of any circuit-driven pathology. They also demonstrate the utility of homogenous and functional populations of a relevant neuronal subtype for probing pathogenesis mechanisms during development.

Genome-wide association studies (GWAS) have identified many genomic loci associated with risk for schizophrenia, but unambiguous identification of the relationship between disease-associated variants and specific genes, and in particular their effect on risk conferring transcripts, has proven difficult. To better understand the specific molecular mechanism(s) at the schizophrenia locus in 11q25, we undertook cis expression quantitative trait loci (cis-eQTL) mapping for this 2 megabase genomic region using postmortem human brain samples. To comprehensively assess the effects of genetic risk upon local expression, we evaluated multiple transcript features: genes, exons, and exon-exon junctions in multiple brain regions-dorsolateral prefrontal cortex (DLPFC), hippocampus, and caudate. Genetic risk variants strongly associated with expression of SNX19 transcript features that tag multiple rare classes of SNX19 transcripts, whereas they only weakly affected expression of an exon-exon junction that tags the majority of abundant transcripts. The most prominent class of SNX19 risk-associated transcripts is predicted to be overexpressed, defined by an exon-exon splice junction between exons 8 and 10 (junc8.10) and that is predicted to encode proteins that lack the characteristic nexin C terminal domain. Risk alleles were also associated with either increased or decreased expression of multiple additional classes of transcripts. With RACE, molecular cloning, and long read sequencing, we found a number of novel SNX19 transcripts that further define the set of potential etiological transcripts. We explored epigenetic regulation of SNX19 expression and found that DNA methylation at CpG sites near the primary transcription start site and within exon 2 partially mediate the effects of risk variants on risk-associated expression. ATAC sequencing revealed that some of the most strongly risk-associated SNPs are located within a region of open chromatin, suggesting a nearby regulatory element is involved. These findings indicate a potentially complex molecular etiology, in which risk alleles for schizophrenia generate epigenetic alterations and dysregulation of multiple classes of SNX19 transcripts.

Post-zygotic mutations incurred during DNA replication, DNA repair, and other cellular processes lead to somatic mosaicism. Somatic mosaicism is an established cause of various diseases, including cancers. However, detecting mosaic variants in DNA from non-cancerous somatic tissues poses significant challenges, particularly if the variants only are present in a small fraction of cells. Here, the Brain Somatic Mosaicism Network conducted a coordinated, multi-institutional study to: (i) examine the ability of existing methods to detect simulated somatic single nucleotide variants (SNVs) in DNA mixing experiments; (ii) generate multiple replicates of whole genome sequencing data from the dorsolateral prefrontal cortex, other brain regions, dura mater, and dural fibroblasts of a single neurotypical individual; (iii) devise strategies to discover somatic SNVs; and (iv) apply various approaches to validate somatic SNVs. These efforts led to the identification of 43 bona fide somatic SNVs that ranged in variant allele fractions from ~0.005 to ~0.28. Guided by these results, we devised best practices for calling mosaic SNVs from 250X whole genome sequencing data in the accessible portion of the human genome that achieve 90% specificity and sensitivity. Finally, we demonstrated that analysis of multiple bulk DNA samples from a single individual allows the reconstruction of early developmental cell lineage trees. Thus, this study provides a unified set of best practices to detect somatic SNVs in non-cancerous tissues. The data and methods are freely available to the scientific community and should serve as a guide to assess the contributions of somatic SNVs to neuropsychiatric diseases.

Intelligence is highly heritable 1 and a major determinant of human health and well-being 2 . Recent genome-wide meta-analyses have identified 24 genomic loci linked to variation in intelligence 3-7 , but much about its genetic underpinnings remains to be discovered. Here, we present a large-scale genetic association study of intelligence (n = 269,867), identifying 205 associated genomic loci (190 new) and 1,016 genes (939 new) via positional mapping, expression quantitative trait locus (eQTL) mapping, chromatin interaction mapping, and gene-based association analysis. We find enrichment of genetic effects in conserved and coding regions and associations with 146 nonsynonymous exonic variants. Associated genes are strongly expressed in the brain, specifically in striatal medium spiny neurons and hippocampal pyramidal neurons. Gene set analyses implicate pathways related to nervous system development and synaptic structure. We confirm previous strong genetic correlations with multiple health-related outcomes, and Mendelian randomization analysis results suggest protective effects of intelligence for Alzheimer's disease and ADHD and bidirectional causation with pleiotropic effects for schizophrenia. These results are a major step forward in understanding the neurobiology of cognitive function as well as genetically related neurological and psychiatric disorders.

RNA sequencing (RNA-seq) is a powerful approach for measuring gene expression levels in cells and tissues, but it relies on high-quality RNA. We demonstrate here that statistical adjustment using existing quality measures largely fails to remove the effects of RNA degradation when RNA quality associates with the outcome of interest. Using RNA-seq data from molecular degradation experiments of human primary tissues, we introduce a method—quality surrogate variable analysis (qSVA)—as a framework for estimating and removing the confounding effect of RNA quality in differential expression analysis. We show that this approach results in greatly improved replication rates (>3×) across two large independent postmortem human brain studies of schizophrenia and also removes potential RNA quality biases in earlier published work that compared expression levels of different brain regions and other diagnostic groups. Our approach can therefore improve the interpretation of differential expression analysis of transcriptomic data from human tissue.

Summary The hippocampus formation, although prominently implicated in schizophrenia pathogenesis, has been overlooked in large-scale genomics efforts in the schizophrenic brain. We performed RNA-seq in hippocampi and dorsolateral prefrontal cortices (DLPFCs) from 551 individuals (286 with schizophrenia). We identified substantial regional differences in gene expression and found widespread developmental differences that were independent of cellular composition. We identified 48 and 245 differentially expressed genes (DEGs) associated with schizophrenia within the hippocampus and DLPFC, with little overlap between the brain regions. 124 of 163 (76.6%) of schizophrenia GWAS risk loci contained eQTLs in any region. Transcriptome-wide association studies in each region identified many novel schizophrenia risk features that were brain region-specific. Last, we identified potential molecular correlates of in vivo evidence of altered prefrontal-hippocampal functional coherence in schizophrenia. These results underscore the complexity and regional heterogeneity of the transcriptional correlates of schizophrenia and offer new insights into potentially causative biology.

Schizophrenia (SCZ) is a neurodevelopmental disorder. Thus, studying pathogenetic mechanisms underlying SCZ requires studying the development of brain cells. Cortical interneurons (cINs) are consistently observed to be abnormal in SCZ postmortem brains. These abnormalities may explain altered gamma oscillation and cognitive function in patients with SCZ. Of note, currently used antipsychotic drugs ameliorate psychosis, but they are not very effective in reversing cognitive deficits. Characterizing mechanisms of SCZ pathogenesis, especially related to cognitive deficits, may lead to improved treatments. We generated homogeneous populations of developing cINs from 15 healthy control (HC) iPSC lines and 15 SCZ iPSC lines. SCZ cINs, but not SCZ glutamatergic neurons, show dysregulated Oxidative Phosphorylation (OxPhos) related gene expression, accompanied by compromised mitochondrial function. The OxPhos deficit in cINs could be reversed by Alpha Lipoic Acid/Acetyl-L-Carnitine (ALA/ALC) but not by other chemicals previously identified as increasing mitochondrial function. The restoration of mitochondrial function by ALA/ALC was accompanied by a reversal of arborization deficits in SCZ cINs. OxPhos abnormality, even in the absence of any circuit environment with other neuronal subtypes, appears to be an intrinsic deficit in SCZ cINs.

SummaryHuman induced pluripotent stem cells (hiPSCs) are a powerful model of neural differentiation and maturation. We present a hiPSC transcriptomics resource on corticogenesis from 5 iPSC donor and 13 subclonal lines across nine time points over 5 broad conditions: self-renewal, early neuronal differentiation, neural precursor cells (NPCs), assembled rosettes, and differentiated neuronal cells that were validated using electrophysiology. We identified widespread changes in the expression of individual transcript features and their splice variants, gene networks, and global patterns of transcription. We next demonstrated that co-culturing human NPCs with rodent astrocytes resulted in mutually synergistic maturation, and that cell type-specific expression data can be extracted using only sequencing read alignments without potentially disruptive cell sorting. We lastly developed and validated a computational tool to estimate the relative neuronal maturity of iPSC-derived neuronal cultures and human brain tissue, which were maturationally heterogeneous but contained subsets of cells most akin to adult human neurons.

Schizophrenia polygenic risk is plausibly manifested by complex transcriptional dysregulation in the brain, involving networks of co-expressed and functionally related genes. The main purpose of this study was to identify and prioritize co-expressed gene sets in a hierarchical manner, based on the strength of the relationships with clinical diagnosis and with polygenic risk for schizophrenia. Weighted Gene Co-expression Network Analysis (WGCNA) was applied to RNA-quality-adjusted DLPFC RNA-Seq data from the LIBD Postmortem Human Brain Repository (90 controls, 74 schizophrenia cases; all Caucasians) to construct co-expression networks and detect “modules” of co-expressed genes. After multiple internal and external validation procedures, modules of selected interest were tested for enrichment in biological ontologies, for association with schizophrenia polygenic risk scores (PRSs) and with diagnosis, and also for enrichment in genes within the significant GWAS loci reported by the Psychiatric Genomic Consortium (PGC2). The association between schizophrenia genetic signals and modules of co-expression converged on one module showing not only a significant association with both diagnosis and PRS but also significant overlap with 36 PGC2 loci genes, deemed the strongest candidates for drug targets. This module contained many genes involved in synaptic signaling and neuroplasticity. Fifty-three PGC2 genes were in modules associated only with diagnosis and 59 in modules unrelated to diagnosis or PRS. Our study highlights complex relationships between gene co-expression networks in the brain and clinical state and polygenic risk for SCZ and provides a strategy for using this information in selecting and prioritizing potentially targetable gene sets for therapeutic drug development.

Background Schizophrenia polygenic risk is plausibly manifested by complex transcriptional dysregulation in the brain, involving networks of co-expressed and functionally related genes. Methods 1. Samples: DLPFC gene expression (RNA-Seq) abundance was quantified (RPKM) in postmortem human brains from the LIBD Postmortem Human Brain Repository (90 controls- CTRL, 76 schizophrenia- SCZ, Caucasians, age: 16–80, RIN≥7). Common Mind Consortium (CMC) RNA-Seq postmortem DLPFC (125 CTRL, 109 SCZ, Caucasians, age, RIN as above) was used for replication of LIBD co-expression networks. 2. Expression measures/ quality control: only genes with median RPKM≥0.1 (N=23132 genes; LIBD samples) were used. Expression data was normalized by log2 transformation and adjusted for RNA quality measures (RIN, PMI, total gene assignment, proportion of mitochondrial RNA) by empirical Bayesian models. 3. Data analysis: WGCNA was applied to the adjusted expression data to construct co-expression networks, separately for LIBD- CTRL and LIBD- SCZ. Modules of co-expressed genes were detected by dynamic tree cutting method and summarized as “module eigengenes” for further analyses. 4. Modules of LIBD (CTRL; SCZ) were tested for enrichment in PGC2 genes within the 108 loci associated with the schizophrenia risk in the latest GWAS. 5. Composite module preservation statistics- median rank and Zsummary was used for assessing the preservation of LIBD SCZ modules in LIBD CTRL network and for replication of LIBD co-expression modules in the CMC independent data sets. Gene enrichment analyses for testing modules’ enrichment in Gene Ontology (GO) biological processes (BP) was performed with AmiGO/ PANTHER. Results 17 co-expression modules were identified in each LIBD group. Module preservation analysis showed a good preservation of co-expression modules between LIBD CTRL and SCZ networks, with all but one SCZ module showing evidence for strong preservation (Zsummary≥10). PGC2 genes were overrepresented in two CTRL modules (p=0.001973, p=0.028297) enriched for GO-BP such as translation, ATP synthesis, oxidative phosphorylation, homophilic cell adhesion via plasma membrane adhesion molecules, chemical synaptic transmission, axonogenesis, and in one SCZ module (p=0.000519) enriched for RNA processing, nervous system development and modulation of synaptic transmission. 58 PGC2 genes overlapped with the SCZ module (e.g., DRD2, FURIN, TSNARE1), whereas 48 + 17 PGC2 genes were overrepresented in the two CTRL modules (e.g., CACNA1C, CHRM4, CACNA1I, TCF20). Of note, only 9 overrepresented PGC2 genes were shared by CTRL and SCZ: AMBRA1, ANKRD63, HSPA9, LRP1, PRR12, PTPRF, RERE, TOM1L2, ZDHHC5. Replication of co-expression LIBD networks in CMC data set showed evidence of weak to strong preservation (Zsummary>2, respectively ≥10) for 16/ 17 modules for each LIBD group. Discussion Our results illustrate the complexity of SCZ risk distribution within the DLPFC co-expression networks in postmortem brains of affected and unaffected individuals. Importantly, not the same PGC2 genes are members of co-expression modules in CTRL and SCZ, nor do they aggregate in similar modules. These observations may be explained by differential transcriptional regulation due to pleiotropy, epistasis, epigenetic dysregulation, or even hidden RNA quality artifacts. Future studies are necessary to elucidate the participation of SCZ risk genes in brain co-expression networks.

Polygenic risk scores have shown great promise in predicting complex disease risk and will become more accurate as training sample sizes increase. The standard approach for calculating risk scores involves linkage disequilibrium (LD)-based marker pruning and applying a p value threshold to association statistics, but this discards information and can reduce predictive accuracy. We introduce LDpred, a method that infers the posterior mean effect size of each marker by using a prior on effect sizes and LD information from an external reference panel. Theory and simulations show that LDpred outperforms the approach of pruning followed by thresholding, particularly at large sample sizes. Accordingly, predicted R-2 increased from 20.1% to 25.3% in a large schizophrenia dataset and from 9.8% to 12.0% in a large multiple sclerosis dataset. A similar relative improvement in accuracy was observed for three additional large disease datasets and for non-European schizophrenia samples. The advantage of LDpred over existing methods will grow as sample sizes increase. Refereed/Peer-reviewed

Summary: GWAS have identified 108 schizophrenia risk loci, but risk mechanisms for individual loci are largely unknown. Using developmental, genetic, and illness-based RNA sequencing expression analysis in human brain, we characterized the human brain transcriptome around these loci and found enrichment for developmentally regulated genes with novel examples of shifting isoform usage across pre- and post-natal life. Across the genome, we found widespread expression quantitative trait loci (eQTLs), including many with transcript specificity and previously unannotated sequence that were independently replicated. We leveraged this general eQTL database to show that 48.1% of risk variants for schizophrenia associated with nearby expression. We lastly found 237 genes significantly differentially expressed between patients and controls which replicated in an independent dataset, implicated synaptic processes and were strongly regulated in early development. These findings together offer genetic- and diagnosis-related targets for better modeling schizophrenia risk. This publicly-available resource is available at: http://eqtl.brainseq.org/phase1

J. Lönnqvist on työryhmän Psychiat Genomics Consortium jäsen. Genetic correlation is a key population parameter that describes the shared genetic architecture of complex traits and diseases. It can be estimated by current state-of-art methods, i.e., linkage disequilibrium score regression (LDSC) and genomic restricted maximum likelihood (GREML). The massively reduced computing burden of LDSC compared to GREML makes it an attractive tool, although the accuracy (i.e., magnitude of standard errors) of LDSC estimates has not been thoroughly studied. In simulation, we show that the accuracy of GREML is generally higher than that of LDSC. When there is genetic heterogeneity between the actual sample and reference data from which LD scores are estimated, the accuracy of LDSC decreases further. In real data analyses estimating the genetic correlation between schizophrenia (SCZ) and body mass index, we show that GREML estimates based on similar to 150,000 individuals give a higher accuracy than LDSC estimates based on similar to 400,000 individuals (from combinedmeta-data). A GREML genomic partitioning analysis reveals that the genetic correlation between SCZ and height is significantly negative for regulatory regions, which whole genome or LDSC approach has less power to detect. We conclude that LDSC estimates should be carefully interpreted as there can be uncertainty about homogeneity among combined meta-datasets. We suggest that any interesting findings from massive LDSC analysis for a large number of complex traits should be followed up, where possible, with more detailed analyses with GREML methods, even if sample sizes are lesser.

Publisher's version (útgefin grein), Previous studies have shown an increased risk for mental health problems in children born to both younger and older parents compared to children of average-aged parents. We previously used a novel design to reveal a latent mechanism of genetic association between schizophrenia and age at first birth in women (AFB). Here, we use independent data from the UK Biobank (N = 38,892) to replicate the finding of an association between predicted genetic risk of schizophrenia and AFB in women, and to estimate the genetic correlation between schizophrenia and AFB in women stratified into younger and older groups. We find evidence for an association between predicted genetic risk of schizophrenia and AFB in women (P-value = 1.12E-05), and we show genetic heterogeneity between younger and older AFB groups (P-value = 3.45E-03). The genetic correlation between schizophrenia and AFB in the younger AFB group is −0.16 (SE = 0.04) while that between schizophrenia and AFB in the older AFB group is 0.14 (SE = 0.08). Our results suggest that early, and perhaps also late, age at first birth in women is associated with increased genetic risk for schizophrenia in the UK Biobank sample. These findings contribute new insights into factors contributing to the complex bio-social risk architecture underpinning the association between parental age and offspring mental health., This research is supported by the Australian National Health and Medical Research Council (1080157, 1087889, 1103418, 1127440), and the Australian Research Council (DP160102126, FT160100229). This research has been conducted using the UK Biobank Resource. UK Biobank (http://www.ukbiobank.ac.uk) Research Ethics Committee (REC) approval number is 11/NW/0382. Our reference number approved by UK Biobank is 14575.

Intelligence is highly heritable1 and a major determinant of human health and well-being2. Recent genome-wide meta-analyses have identified 24 genomic loci linked to intelligence3–7, but much about its genetic underpinnings remains to be discovered. Here, we present the largest genetic association study of intelligence to date (N=279,930), identifying 206 genomic loci (191 novel) and implicating 1,041 genes (963 novel) via positional mapping, expression quantitative trait locus (eQTL) mapping, chromatin interaction mapping, and gene-based association analysis. We find enrichment of genetic effects in conserved and coding regions and identify 89 nonsynonymous exonic variants. Associated genes are strongly expressed in the brain and specifically in striatal medium spiny neurons and cortical and hippocampal pyramidal neurons. Gene-set analyses implicate pathways related to neurogenesis, neuron differentiation and synaptic structure. We confirm previous strong genetic correlations with several neuropsychiatric disorders, and Mendelian Randomization results suggest protective effects of intelligence for Alzheimer’s dementia and ADHD, and bidirectional causation with strong pleiotropy for schizophrenia. These results are a major step forward in understanding the neurobiology of intelligence as well as genetically associated neuropsychiatric traits.

Defining the environmental context in which genes enhance disease susceptibility can provide insight into the pathogenesis of complex disorders. We report that the intra-uterine environment modulates the association of schizophrenia with genomic risk (in this study, genome-wide association study–derived polygenic risk scores (PRSs)). In independent samples from the United States, Italy, and Germany, the liability of schizophrenia explained by PRS is more than five times greater in the presence of early-life complications (ELCs) compared with their absence. Patients with ELC histories have significantly higher PRS than patients without ELC histories, which is confirmed in additional samples from Germany and Japan. The gene set composed of schizophrenia loci that interact with ELCs is highly expressed in placenta, is differentially expressed in placentae from complicated in comparison with normal pregnancies, and is differentially upregulated in placentae from male compared with female offspring. Pathway analyses reveal that genes driving the PRS-ELC interaction are involved in cellular stress response; genes that do not drive such interaction implicate orthogonal biological processes (for example, synaptic function). We conclude that a subset of the most significant genetic variants associated with schizophrenia converge on a developmental trajectory sensitive to events that affect the placental response to stress, which may offer insights into sex biases and primary prevention.

General cognitive function is a prominent human trait associated with many important life outcomes1,2, including longevity3. The substantial heritability of general cognitive function is known to be polygenic, but it has had little explication in terms of the contributing genetic variants4,5,6. Here, we combined cognitive and genetic data from the CHARGE and COGENT consortia, and UK Biobank (total N=280,360; age range = 16 to 102). We found 9,714 genome-wide significant SNPs (P−8) in 99 independent loci. Most showed clear evidence of functional importance. Among many novel genes associated with general cognitive function wereSGCZ,ATXN1,MAPT,AUTS2, andP2RY6. Within the novel genetic loci were variants associated with neurodegenerative disorders, neurodevelopmental disorders, physical and psychiatric illnesses, brain structure, and BMI. Gene-based analyses found 536 genes significantly associated with general cognitive function; many were highly expressed in the brain, and associated with neurogenesis and dendrite gene sets. Genetic association results predicted up to 4% of general cognitive function variance in independent samples. There was significant genetic overlap between general cognitive function and information processing speed, as well as many health variables including longevity.

Defining the environmental context in which genes enhance susceptibility can provide insight into the pathogenesis of complex disorders, like schizophrenia. Here we show that the intrauterine and perinatal environment modulates the association of schizophrenia with genomic risk, as measured with polygenic risk scores (PRS) based primarily on GWAS significant variants. Genomic risk interacts with intrauterine and perinatal complications (Early Life Complications, ELCs) in each of three independent samples from USA, Italy and Germany (overall n= 1693, p= 6e-05). In each sample, the liability of schizophrenia explained by PRS is nominally more than five times greater in the presence of a history of ELCs compared with its absence. In each sample, patients with positive ELC histories have higher PRS than patients without ELCs, which is further confirmed in two additional patient samples from Germany and Japan (overall n=2038, p= 1e-04). The gene set based on the schizophrenia loci interacting with ELCs is highly expressed in multiple placental compartments and dynamically regulated in placenta from complicated in comparison with normal pregnancies. The same genes are differentially up-regulated in placentae from male compared with female offspring. The interaction between genomic risk and ELCs is mainly driven by GWAS significant loci enriched for genes highly expressed in the various placenta samples. Molecular pathway analyses based on the genes not driving this interaction reflect previous analyses about schizophrenia risk-genes, while genes highly and differentially expressed in placentae implicate an orthogonal biology involving cellular stress. These results suggest that the most significant genetic variants detected by current schizophrenia GWAS contribute to risk in part by converging on a developmental trajectory sensitive to events affecting placentation, which may underlie the male preponderance of schizophrenia and offer new insights into primary prevention.

SummaryGWAS have identified 108 loci that confer risk for schizophrenia, but risk mechanisms for individual loci are largely unknown. Using developmental, genetic, and illness-based RNA sequencing expression analysis, we characterized the human brain transcriptome around these loci and found enrichment for developmentally regulated genes with novel examples of shifting isoform usage across pre- and post-natal life. We found widespread expression quantitative trait loci (eQTLs), including many with transcript specificity and previously unannotated sequence that were independently replicated. We leveraged this eQTL database to show that 48.1% of risk variants for schizophrenia associated with nearby expression. Within patients and controls, we implemented a novel algorithm for RNA quality adjustment, and identified 237 genes significantly associated with diagnosis that replicated in an independent case-control dataset. These genes implicated synaptic processes and were strongly regulated in early development (p < 10-20). These data offer new targets for modeling schizophrenia risk in cellular systems.

We have previously shown higher-than-expected rates of schizophrenia in relatives of patients with amyotrophic lateral sclerosis (ALS), suggesting an aetiological relationship between the diseases. Here, we investigate the genetic relationship between ALS and schizophrenia using genome-wide association study data from over 100,000 unique individuals. Using linkage disequilibrium score regression, we estimate the genetic correlation between ALS and schizophrenia to be 14.3% (7.05–21.6; P=1 × 10−4) with schizophrenia polygenic risk scores explaining up to 0.12% of the variance in ALS (P=8.4 × 10−7). A modest increase in comorbidity of ALS and schizophrenia is expected given these findings (odds ratio 1.08–1.26) but this would require very large studies to observe epidemiologically. We identify five potential novel ALS-associated loci using conditional false discovery rate analysis. It is likely that shared neurobiological mechanisms between these two disorders will engender novel hypotheses in future preclinical and clinical studies., Relatives of patients with amyotrophic lateral sclerosis have an unexpectedly high incidence of schizophrenia. Here, the authors show a genetic link between the two conditions, suggesting shared neurobiological mechanisms.

Neurexin 1 (NRXN1) is a presynaptic neuronal adhesion molecule that interacts with postsynaptic neuroligins in both glutamatergic and GABAergic synapses and is important in synaptic formation and function. NRXN1 deletions increase the risk of schizophrenia, so our aims were to explore this in our family sample, to distinguish de novo from inherited mutations, to examine transmission to affected and unaffected siblings and to estimate penetrance. We performed copy number analyses in NRXN1 using data from Illumina BeadArrays from 635 subjects with schizophrenia (276 in genotyped families), 487 of their unaffected parents and 309 unaffected siblings as well as 635 normal controls, all from the CBDB/NIMH Genetic Study of Schizophrenia. Deletions called by software were confirmed by quantitative PCR and comparative genome hybridization. There were deletions in 15 individuals in 11 families, including de novo exonic deletions in one case and one unaffected sibling. We observed no deletions in controls, 7 deletions in cases (1.10%), and an unexpectedly high deletion frequency in parents (n = 5, 1.02%) and siblings (n = 3, 0.97%). Three families showed inheritance from an unaffected parent, and in two families an unaffected parent did not transmit to the affected offspring. Thus we have added to the evidence that NRXN1 deletions are more frequent in patients with schizophrenia than in healthy individuals. However, the presence of de novo deletions in unaffected relatives and transmission from and to unaffected family members demonstrated that while the deletions may well have been necessary for some carriers to develop schizophrenia, they were not always sufficient.

Early in development, GABA, an inhibitory neurotransmitter in adults, is excitatory. NKCC1 (SLC12A2) encodes one of two cation chloride cotransporters mediating the conversion of GABA from excitatory to inhibitory. Using 3′ and 5′ RACE and PCR, we verified previously characterized alternative transcripts of NKCC1a (1–27) and NKCC1b (1–27(Δ21)), identified new NKCC1 transcripts, and explored their expression patterns during human prefrontal cortical development. A novel ultra-short transcript (1–2a) was expressed preferentially in the fetus. Expression of NKCC1b and 1–2a were decreased in schizophrenia compared with controls (NKCC1b: 0.8-fold decrease,p= 0.013; 1–2a: 0.8-fold decrease,p= 0.006). Furthermore, the expression of NKCC1b was associated with NKCC1 polymorphism rs3087889. The minor allele at rs3087889, associated with reduced NKCC1b expression (homozygous for major allele:N= 37; homozygous for minor allele:N= 15; 1.5-fold decrease;p< 0.01), was also associated with a modest increase in schizophrenia risk in a case-control sample (controls:N= 435; cases:N= 397, OR = 1.5). This same allele was then found associated with cognitive (n= 369) and fMRI (n= 313) intermediate phenotypes associated with schizophrenia—working memory (Cohen's d = 0.35), global cognition org(d = 0.18), and prefrontal inefficiency (d = 0.36) as measured by BOLD fMRI during a working memory task. Together, these preclinical and clinical results suggest that variation in NKCC1 may increase risk for schizophrenia via alterations of mRNA expression at the molecular level and impairment of optimal prefrontal function at the macro or systems level.

Background In recent years, Polygenic Risk Profile Scores (PRS's) are being increasingly used to indirectly measure the aggregate genetic effect of many weakly associated markers on the risk for a neuropsychiatric disorder. While the use of PRS's has supported the polygenic architecture of schizophrenia, a link between PRS's and the pathophysiology of this disorder is still missing. In this study, we analyze the association between PRS's for schizophrenia and hippocampal function during a simple declarative memory task in healthy volunteers. We then used regularized regression, a machine learning method, to further investigate the genetic structure that drives the association between schizophrenia PRS's and altered hippocampal engagement. Methods Two hundred and five healthy volunteers underwent BOLD fMRI (3 T) during a Simple Declarative Memory Task (SDMT), which included incidental encoding and retrieval of visual scenes. For both the encoding and retrieval sessions, the scenes were presented in a blocked fashion, with 4 blocks of neutral scenes and 4 blocks of visual scenes alternating with 9 blocks of resting state (fixation cross hair). In the current study, we focused on the encoding phase for neutral scenes only (Rasetti et al. 2014). PRS's were calculated for each individual as the weighted sum of the number of reference alleles on preselected markers based on PGC GWAS study (PGC 2014), with p-value threshold at 0.05 (24,670 SNPs). Imaging space association study was conducted using multiple regressions in SPM8. Region of interest (ROI) was defined as averaged signal within a 6 mm sphere around the peak of association between PRS and right hippocampus. Regularized regression was run using ROI in R using glmnet package (Zou et al. 2005). Results The PRS constructed with 24,670 SNPs (with association with schizophrenia at scoring threshold of p=0.05) is significantly associated with hippocampal activation (z=4.48, p=0.004, FWE corrected in bilateral hippocampal ROI), so that higher PRS corresponds to blunted hippocampal activation. Using the regularized regression with shrinkage factor lambda=0.001, we identified 255 SNPs driving this association, so that the association between the PRS based on these 255 SNPs (PRS255) and hippocampal activation increases dramatically (z=7.14, p Discussion Our results show that PRS's for schizophrenia are significantly associated with altered hippocampal function during a simple declarative memory task even in healthy volunteers. Using regularized regression, we are able to find a small subset of SNPs that drive the association and account for high percentage of variance in hippocampal activation. The use of machine learning techniques for dimension reduction allows disentangling the cumulative effect of risk genes on brain function.

RNA sequencing (RNA-seq) is a powerful approach for measuring gene expression levels in cells and tissues, but it relies on high-quality RNA. We demonstrate here that statistical adjustment employing existing quality measures largely fails to remove the effects of RNA degradation when RNA quality associates with the outcome of interest. Using RNA-seq data from a molecular degradation experiment of human brain tissue, we introduce the quality surrogate variable (qSVA) analysis framework for estimating and removing the confounding effect of RNA quality in differential expression analysis. We show this approach results in greatly improved replication rates (>3x) across two large independent postmortem human brain studies of schizophrenia. Finally, we explored public datasets to demonstrate potential RNA quality confounding when comparing expression levels of different brain regions and diagnostic groups beyond schizophrenia. Our approach can therefore improve the interpretation of differential expression analysis of transcriptomic data from the human brain.

Neuregulin 1 (NRG1) and ErbB4, critical neurodevelopmental genes, are implicated in schizophrenia, but the mediating mechanisms are unknown. Here we identify a genetically regulated, pharmacologically targetable, risk pathway associated with schizophrenia and with ErbB4 genetic variation involving increased expression of a PI3K-linked ErbB4 receptor (CYT-1) and the phosphoinositide 3-kinase subunit, p110δ (PIK3CD). In human lymphoblasts, NRG1-mediated phosphatidyl-inositol,3,4,5 triphosphate [PI(3,4,5)P3] signaling is predicted by schizophrenia-associated ErbB4 genotype and PIK3CD levels and is impaired in patients with schizophrenia. In human brain, the same ErbB4 genotype again predicts increased PIK3CD expression. Pharmacological inhibition of p110δ using the small molecule inhibitor, IC87114, blocks the effects of amphetamine in a mouse pharmacological model of psychosis and reverses schizophrenia-related phenotypes in a rat neonatal ventral hippocampal lesion model. Consistent with these antipsychotic-like properties, IC87114 increases AKT phosphorylation in brains of treated mice, implicating a mechanism of action. Finally, in two family-based genetic studies, PIK3CD shows evidence of association with schizophrenia. Our data provide insight into a mechanism of ErbB4 association with schizophrenia; reveal a previously unidentified biological and disease link between NRG1-ErbB4, p110δ, and AKT; and suggest that p110δ is a previously undescribed therapeutic target for the treatment of psychiatric disorders.

Background Clinical studies have identified several regions of the genome with copy number variations (CNVs) associated with diverse neurodevelopmental behavioral disorders. Methods We analyzed 1 million (M) single nucleotide polymorphism genotype arrays for evidence of previously reported recurrent CNVs and enriched genome-wide CNV burden in DNA from 600 brains, including 441 individuals with various psychiatric diagnoses. We explored gene expression in the dorsolateral prefrontal cortex in selected cases with CNVs and in other subjects with Illumina BeadArrays (568 subjects in total) and additionally in 66–92 subjects with quantitative real-time polymerase chain reaction. Results The CNVs in previously reported genomic regions were identified in 4 of 193 patients with the diagnosis of schizophrenia (1q21.1, 11q25, 15q11.2, 22q11), 4 of 238 patients with mood disorders (11q25, 15q11.2, 22q11), and 1 of 10 patients with autism (2p16.3). No evidence of increased genome-wide CNV burden was observed in cases with schizophrenia or mood disorders, although the study is underpowered to observe rare events. Messenger RNA expression patterns suggested incomplete molecular penetrance of observed CNVs. Conclusions Our data confirm in brain DNA the presence of certain recurrent CNVs in a small percentage of patients with psychiatric diagnoses.

GABA signaling molecules are critical for both human brain development and the pathophysiology of schizophrenia. We examined the expression of transcripts derived from three genes related to GABA signaling [GAD1 (GAD67 and GAD25), SLC12A2 (NKCC1), and SLC12A5 (KCC2)] in the prefrontal cortex (PFC) and hippocampal formation of a large cohort of nonpsychiatric control human brains (n = 240) across the lifespan (from fetal week 14 to 80 years) and in patients with schizophrenia (n = 30–31), using quantitative RT-PCR. We also examined whether a schizophrenia risk-associated promoter SNP in GAD1 (rs3749034) is related to expression of these transcripts. Our studies revealed that development and maturation of both the PFC and hippocampal formation are characterized by progressive switches in expression from GAD25 to GAD67 and from NKCC1 to KCC2. Previous studies have demonstrated that the former leads to GABA synthesis, and the latter leads to switching from excitatory to inhibitory neurotransmission. In the hippocampal formation, GAD25/GAD67 and NKCC1/KCC2 ratios are increased in patients with schizophrenia, reflecting a potentially immature GABA physiology. Remarkably, GAD25/GAD67 and NKCC1/KCC2 expression ratios are associated with rs3749034 genotype, with risk alleles again predicting a relatively less mature pattern. These findings suggest that abnormalities in GABA signaling critical to brain development contribute to genetic risk for schizophrenia.

Genetic and molecular studies indicate that dysbindin-1 plays a role in the pathophysiology of schizophrenia. We examined dysbindin-1 mRNA in the hippocampal formation of patients with schizophrenia and found reduced expression in dentate granule and polymorph cells and in hippocampal field CA3, but not in CA1. Furthermore, there were positive correlations between dysbindin-1 mRNA and expression of synaptic markers known to be reduced in schizophrenia. Our results indicate that previously reported dysbindin-1 protein reductions may be due in part to decreased dysbindin-1 mRNA and that reduced dysbindin-1 may contribute to hippocampal formation synaptic pathology in schizophrenia.

The schizophrenia susceptibility gene dystrobrevin-binding protein 1 (DTNBP1) encodes dysbindin, which along with its binding partner Muted is an essential component of the biogenesis of lysosome-related organelles complex 1 (BLOC-1). Dysbindin expression is reduced in schizophrenic brain tissue, but the molecular mechanisms by which this contributes to pathogenesis and symptomatology are unknown. We studied the effects of transfection of DTNBP1 siRNA on cell surface levels of dopamine D2receptor (DRD2) in human SH-SY5Y neuroblastoma cells and in rat primary cortical neurons. DTNBP1 siRNA decreased dysbindin protein, increased cell surface DRD2 and blocked dopamine-induced DRD2 internalization. MUTED siRNA produced similar effects. In contrast, decreased dysbindin did not change dopamine D1receptor (DRD1) levels, or its basal or dopamine-induced internalization. The DRD2 agonist quinpirole reduced phosphorylation of CREB (cAMP response element-binding protein) in dysbindin downregulated cells, demonstrating enhanced intracellular signaling caused by the upregulation of DRD2. This is the first demonstration of a schizophrenia susceptibility gene exerting a functional effect on DRD2 signaling, a pathway that has long been implicated in the illness. We propose a molecular mechanism for pathogenesis in which risk alleles inDTNBP1, or other factors that also downregulate dysbindin, compromise the ability of BLOC-1 to traffic DRD2 toward degradation, but has little effect on DRD1 trafficking. Impaired trafficking of DRD2 decreases dopamine-induced internalization, and with more receptors retained on the cell surface, dopamine stimulation produces excess intracellular signaling. Such an increase in DRD2 signaling relative to DRD1 would contribute to the imbalances in dopaminergic neurotransmission characteristic of schizophrenia.

Background Premenstrual dysphoric disorder (PMDD) is a heritable mood disorder that is triggered by gonadal steroids during the luteal phase in susceptible women. Methods We performed haplotype analyses of estrogen receptors alpha and beta (ESR1 and ESR2) in 91 women with prospectively confirmed PMDD and 56 control subjects to investigate possible sources of the genetic susceptibility to affective dysregulation induced by normal levels of gonadal steroids. We also examined associations with the valine (Val)158methionine (Met) single nucleotide polymorphism (SNP) of the gene for catechol-O-methyltransferase (COMT), an enzyme involved in estrogen metabolism and prefrontal cortical activation. Results Four SNPs in intron 4 of ESR1 showed significantly different genotype and allele distributions between patients and control subjects. Significant case-control differences were seen in sliding-window analyses of two-, three-, and four-marker haplotypes but only in those haplotypes containing SNPs in intron 4 that were positive in the single-locus analysis. No significant associations were observed with ESR2 or with the COMT Val158Met polymorphism, although the significant associations with ESR1 were observed only in those with the Val/Val genotype. Conclusions These are the first positive (albeit preliminary) genetic findings in this reproductive endocrine-related mood disorder and involve the receptor for a hormone that is pathogenically relevant.

Regulator of G-protein signaling 4 (RGS4) modulates postsynaptic signal transduction by affecting the kinetics of Gα-GTP binding. Linkage, association, and postmortem studies have implicated the gene encoding RGS4 (RGS4) as a schizophrenia susceptibility factor. Using a multimodal neuroimaging approach, we demonstrate that genetic variation inRGS4is associated with functional activation and connectivity during working memory in the absence of overt behavioral differences, with regional gray and white matter volume and with gray matter structural connectivity in healthy human subjects. Specifically, variation at oneRGS4single nucleotide polymorphism that has been associated previously with psychosis (rs951436) impacts frontoparietal and frontotemporal blood oxygenation level-dependent response and network coupling during working memory and results in regionally specific reductions in gray and white matter structural volume in individuals carrying the A allele. These findings suggest mechanisms in brain for the association ofRGS4with risk for psychiatric illness.

The serotonin 2A receptor is widely implicated in genetic association studies and remains an important drug target for psychiatric, neurological, and cardiovascular conditions. RNA sequencing redefined the architecture of the serotonin 2A receptor gene (HTR2A), revealing novel mRNA transcript isoforms utilizing unannotated untranslated regions of the gene. Expression of these untranslated regions is modulated by common single nucleotide polymorphisms (SNPs), namely rs6311. Previous studies did not fully capture the complexity of the sense- and antisense-encoded transcripts with respect to novel exons in the HTR2A gene locus. Here, we comprehensively catalogued exons and RNA isoforms for both HTR2A and HTR2A-AS1 using RNA-Seq from human prefrontal cortex and multiple mouse tissues. We subsequently tested associations between expression of newfound gene features and common SNPs in humans. We find that the human HTR2A gene spans ~66 kilobases and consists of 7, rather than 4 exons. Furthermore, the revised human HTR2A-AS1 gene spans ~474 kilobases and consists of 18, rather than 3 exons. Three HTR2A exons directly overlap with HTR2A-AS1 exons, suggesting potential for complementary nucleotide interactions. The repertoire of possible mouse Htr2a splice isoforms is remarkably similar to humans and we also find evidence for overlapping sense-antisense transcripts in the same relative positions as the human transcripts. rs6311 and SNPs in high linkage disequilibrium are associated with HTR2A-AS1 expression, in addition to previously described associations with expression of the extended 5’ untranslated region of HTR2A. Our proposed HTR2A and HTR2A-AS1 gene structures dramatically differ from current annotations, now including overlapping exons on the sense and anti-sense strands. We also find orthologous transcript isoforms expressed in mice, providing opportunities to elucidate the biological roles of the human isoforms using a model system. Associations between rs6311 and expression of HTR2A and HTR2A-AS1 suggest this polymorphism is capable of modulating the expression of the sense or antisense transcripts. Still unclear is whether these SNPs act directly on the expression of the sense or antisense transcripts and whether overlapping exons are capable of interacting through complimentary base-pairing. Additional studies are necessary to determine the extent and nature of interactions between the SNPs and the transcripts prior to interpreting these findings in the context of phenotypes associated with HTR2A.

Disrupted-in-schizophrenia 1 (DISC1) is a promising schizophrenia candidate gene expressed predominantly within the hippocampus. We typed 12 single-nucleotide polymorphisms (SNPs) that covered the DISC1 gene. A three-SNP haplotype [hCV219779 (C)-rs821597 (G)-rs821616 (A)] spanning 83 kb of the gene was associated with schizophrenia in a family-based sample ( P = 0.002). A common nonconservative SNP (Ser704Cys) (rs821616) within this haplotype was associated with schizophrenia ( P = 0.004). Based on primary expression of DISC1 in hippocampus, we hypothesized that allelic variation at Ser704Cys would have a measurable impact on hippocampal structure and function as assayed via specific hippocampus-related intermediate phenotypes. In addition to overtransmission in schizophrenia, the Ser allele was associated with altered hippocampal structure and function in healthy subjects, including reduced hippocampal gray matter volume and altered engagement of the hippocampus during several cognitive tasks assayed with functional magnetic resonance imaging. These convergent data suggest that allelic variation within DISC1, either at Ser704Cys or haplotypes monitored by it, increases the risk for schizophrenia and that the mechanism of this effect involves structural and functional alterations in the hippocampal formation.

A variation in theBDNFgene (val66met) affects the function of BDNF in neurons, predicts variation in human memory, and is associated with several neurological and psychiatric disorders. Here, we show that, in magnetic resonance imaging scans of a large sample of normal individuals, this polymorphism affects the anatomy of the hippocampus and prefrontal cortex, identifying a genetic mechanism of variation in brain morphology related to learning and memory.

Postmortem brain studies have shown deficits in the cortical gamma-aminobutyric acid (GABA) system in schizophrenic individuals. Expression studies have shown a decrease in the major GABA-synthesizing enzyme (glutamic acid decarboxylase (GAD67) mRNA levels in neurons in dorsolateral prefrontal cortex in schizophrenics relative to controls. In the present study, SNPs in and around the GAD1 gene, which encodes the protein GAD67, were tested on a rare, severely ill group of children and adolescents with childhood-onset schizophrenia (COS) (n=72), in a family-based association analysis. Compared to adult-onset samples, the COS sample has evidence for more salient familial, and perhaps genetic, risk factors for schizophrenia, as well as evidence for frontal cortical hypofunction, and greater decline in cortical gray matter volume on anatomic brain MRI scans during adolescence. We performed family-based TDT and haplotype association analyses of the clinical phenotype, as well as association analyses with endophenotypes using the QTDT program. Three adjacent SNPs in the 5' upstream region of GAD1 showed a positive pairwise association with illness in these families (P=0.022-0.057). Significant transmission distortion of 4-SNP haplotypes was also observed (P=0.003-0.008). Quantitative trait TDT analyses showed an intriguing association between several SNPs and increased rate of frontal gray matter loss. These observations, when taken together with the positive results reported recently in two independent adult-onset schizophrenia pedigree samples, suggest that the gene encoding GAD67 may be a common risk factor for schizophrenia.

Many smoking-related phenotypes are substantially heritable. One genome scan of nicotine dependence (ND) has been published and several others are in progress and should be completed in the next 5 years. The goal of this hypothesis-generating study was two-fold. First, we present further analyses of our genome scan data for ND published by Straub et al. [1999: Mol Psychiatry 4:129-144] (PMID: 10208445). Second, we used the method described by Cox et al. [1999: Nat Genet 21:213-215] (PMID: 9988276) to search for epistatic loci across the markers used in the genome scan. The overall results of the genome scan nearly reached the rigorous Lander and Kruglyak [1995: Nat Genet 11:241-247] criteria for "significant" linkage with the best findings on chromosomes 10 and 2. We then looked for correspondence between genes located in the 10 regions implicated in affected sibling pair (ASP) and epistatic linkage analyses with a list of genes suggested by microarray studies of experimental nicotine exposure and candidate genes from the literature. We found correspondence between linkage and microarray/candidate gene studies for genes involved with the mitogen-activated protein kinase (MAPK) signaling system, nuclear factor kappa B (NFKB) complex, neuropeptide Y (NPY) neurotransmission, a nicotinic receptor subunit (CHRNA2), the vesicular monoamine transporter (SLC18A2), genes in pathways implicated in human anxiety (HTR7, TDO2, and the endozepine-related protein precursor, DKFZP434A2417), and the micro 1-opioid receptor (OPRM1). Although the hypotheses resulting from these linkage and bioinformatic analyses are plausible and intriguing, their ultimate worth depends on replication in additional linkage samples and in future experimental studies.

From our linkage study of Irish families with a high density of schizophrenia, we have previously reported evidence for susceptibility genes in regions 5q21-31, 6p24-21, 8p22-21, and 10p15-p11. In this report, we describe the cumulative results from independent genome scans of three a priori random subsets of 90 families each, and from multipoint analysis of all 270 families in ten regions. Of these ten regions, three (13q32, 18p11-q11, and 18q22-23) did not generate scores above the empirical baseline pairwise scan results, and one (6q13-26) generated a weak signal. Six other regions produced more positive pairwise and multipoint results. They showed the following maximum multipoint H-LOD (heterogeneity LOD) and NPL scores: 2p14-13: 0.89 (P = 0.06) and 2.08 (P = 0.02), 4q24-32: 1.84 (P = 0.007) and 1.67 (P = 0.03), 5q21-31: 2.88 (P= 0.0007), and 2.65 (P = 0.002), 6p25-24: 2.13 (P = 0.005) and 3.59 (P = 0.0005), 6p23: 2.42 (P = 0.001) and 3.07 (P = 0.001), 8p22-21: 1.57 (P = 0.01) and 2.56 (P = 0.005), 10p15-11: 2.04 (P = 0.005) and 1.78 (P = 0.03). The degree of 'internal replication' across subsets differed, with 5q, 6p, and 8p being most consistent and 2p and 10p being least consistent. On 6p, the data suggested the presence of two susceptibility genes, in 6p25-24 and 6p23-22. Very few families were positive on more than one region, and little correlation between regions was evident, suggesting substantial locus heterogeneity. The levels of statistical significance were modest, as expected from loci contributing to complex traits. However, our internal replications, when considered along with the positive results obtained in multiple other samples, suggests that most of these six regions are likely to contain genes that influence liability to schizophrenia.

Background: Early life events influence susceptibility to adult diseases and, as such, represent an environmental context in which genes enhance risk for complex disorders. Here we analyze the role of the intrauterine and perinatal environment in modulating genomic risk for schizophrenia, a neurodevelopmental disorder often associated with obstetrical complications. Methods: We evaluated the relationship between genomic risk, intrauterine and perinatal complications (Early Life Complications, ELCs) and schizophrenia in samples from USA, Europe and Eastern Asia (total N = 946). Genomic risk was measured with risk profile scores (RPS) based on GWAS-significant alleles, while ELCs exposure was assessed with the McNeil-Sjostrom Scale. We tested whether genes overlapping the RPS loci interacting with ELCs are enriched in placenta and differentially expressed in placental samples from complicated pregnancies, in 8 independent placental datasets. Finally, we evaluated whether GWAS SNPs marking loci containing genes highly expressed and dynamically modulated in placenta (PlacRPS genes) drive the interaction between RPS and ELCs, and performed pathway analyses on PlacRPS genes. Results: In the USA sample, genetic risk score was associated with schizophrenia only in the context of exposure to ELCs (P = 6.62e-09); similar results were found in the Italian sample (P = .0005), and the relationship between RPS and ELCs was further replicated in the sample of Japanese patients (P < .05). The gene-set based on RPS loci interacting with ELCs is highly expressed in multiple placental tissues (P < .001) and dynamically regulated in placental samples from complicated, in comparison with normal, pregnancies (P < .05). These differences are significantly greater in placentae from male compared with female offspring (P

Schizophrenia is a highly heritable disorder. Genetic risk is conferred by a large number of alleles, including common alleles of small effect that might be detected by genome-wide association studies. Here we report a multi-stage schizophrenia genome-wide association study of up to 36,989 cases and 113,075 controls. We identify 128 independent associations spanning 108 conservatively defined loci that meet genome-wide significance, 83 of which have not been previously reported. Associations were enriched among genes expressed in brain, providing biological plausibility for the findings. Many findings have the potential to provide entirely new insights into aetiology, but associations at DRD2 and several genes involved in glutamatergic neurotransmission highlight molecules of known and potential therapeutic relevance to schizophrenia, and are consistent with leading pathophysiological hypotheses. Independent of genes expressed in brain, associations were enriched among genes expressed in tissues that have important roles in immunity, providing support for the speculated link between the immune system and schizophrenia. ispartof: Nature vol:511 issue:7510 pages:421-7 ispartof: location:England status: published

We investigated the association between two markers in the seventh intron of the tryptophan hydroxylase gene (TPH C218A and C779A) in a population-based case control study of 780 genotyped subjects. As in prior studies, the two markers were in strong linkage disequilibrium. The phenotypes we studied were smoking initiation and progression to nicotine dependence. Allele, genotype, and estimated haplotype frequencies for each marker were highly significantly different for smoking initiation (P < 0.0004 for each comparison) and were nonsignificant for progression to nicotine dependence. An empirical test suggested that the positive results were unlikely to have resulted from population stratification. Our results are similar to those of Lerman et al. [2001: Am J Med Genet (Neuropsychiatr Genet) 105:000-000] in associating these TPH markers with a construct related to smoking initiation but dissimilar in the variable implicated. If these results replicate in other samples, the serotonergic system may be involved in the etiology of smoking initiation given the rate-limiting role of TPH in the biosynthesis of serotonin.

Epistasis may be important in the etiology of schizophrenia. Analysis of epistasis has been important in the positional cloning of a gene involved in the etiology of type II diabetes mellitus. We investigated the importance of epistasis among six linked regions in 268 multiplex pedigrees in the Irish Study of High-Density Schizophrenia Families (ISHDSF) by computing pairwise correlations between nonparametric linkage scores for narrow, intermediate, and broad diagnostic definitions. The linked regions were on chromosomes 2, 4, 5, 6, 8, and 10. No correlation reached our a priori level of statistical significance. Using this statistical approach, we did not find evidence of important epistatic effects among these six regions in the ISHDSF.

Several types of evidence, including experiments with mice that lack the nicotinic acetylcholine receptor beta2-subunit gene (CHRNB2), have suggested that a beta2-containing nicotinic receptor is necessary for at least some of the reinforcing properties of nicotine. However, sequence variations in CHRNB2 have not been reported, and its role in influencing human smoking behavior and nicotine dependence is not known. We screened most of the introns and exons and found five novel single nucleotide polymorphisms (SNPs). We tested four of these SNPs in three large, carefully selected samples: nonsmokers (n = 317) and regular smokers low levels of nicotine dependence (ND, n = 238), or smokers with high-ND (n = 317). None of the four polymorphisms we tested, nor their estimated haplotypes, were associated with smoking initiation or progression to nicotine dependence.

NRG1 is a schizophrenia candidate gene which regulates brain development and neural function. The minor allele of rs7014762 in the NRG1 5′ core promoter was associated with schizophrenia (p=0.031) and significant predicted reduced NRG1 Type III isoform expression in postmortem human brain of schizophrenia cases (p=0.001). Our results provide additional evidence for transcriptional dysregulation as a biological mechanism implicating NRG1 in schizophrenia risk. Association between NRG1 and schizophrenia was originally discovered via haplotype analysis in an Icelandic sample (HAPICE) at the 5′ end of the gene1, further replicated in a Scottish population2. In the present report, we examined association between schizophrenia and the NRG1 SNP rs7014762 because it is situated within a core promoter region3 and is physically proximal (87bp) to a functional SNP which has been shown to influence NRG1 type IV isoform expression4. In addition to clinical association analyses, we validated the functional effects of rs7014762 by testing for effects on mRNA expression in postmortem human brain. Cases (N=296) and controls (N=365) were ascertained as part of the Clinical Brain Disorders Branch Sibling Study. Probands met DSM-IV criteria for a broad diagnosis category including schizophrenia, schizoaffective disorder, psychosis NOS, delusional disorder, schizotypal, schizoid, or paranoid personality disorder. Control individuals were screened to exclude individuals with psychiatric diagnoses. All participants gave informed consent and self-identified as Caucasian. Blood was collected and DNA was extracted using standard methods. Genotypes were obtained using the Taqman 5′-exonuclease allelic discrimination assay. Postmortem brain tissue was collected with informed consent from the legal next-of-kin. The sample was previously described in detail along with the NRG1 primer and probe sets3,4. Briefly, hippocampi from 84 normal controls (22 females/62 males, 53 African American/25 American Caucasian/5 Hispanic and 1 Asian individual, mean age 40.5 ±(SD) 15.4 years, post mortem interval (PMI) 30.7 ± 13.9 hrs, pH 6.59 ± 0.32); and 44 schizophrenic patients (15 females/29 males, 24 African Americans/20 Caucasians, mean age 49.7 ± 17.2 years, PMI, 36.3 ± 17.7 hrs, pH 6.48 ± 0.28) were available for study. Diagnoses were determined by independent reviews of clinical records and family interviews by two psychiatrists using DSM-IV criteria. Macro- and microscopic neuropathological examinations and toxicology screening were performed prior to inclusion. No differences were observed on variables that potentially affect gene expression in human postmortem brain (i.e. age, PMI, pH and RIN) by rs7014762 genotype group. NRG1 (types I-IV) mRNA splice isoform expression was measured by real-time quantitative RT-PCR using an ABI Prism 7900 sequence detection system with 384-well format (Applied Biosystems, Foster City, CA, USA). Case-control analyses used unconditional logistic regression. Effects of rs7014762 on NRG1 isoform mRNA expression were examined using ANOVA with genotype and diagnosis as independent factors, controlling for race. Where there was a significant genotype bydiagnosis interaction, individual group post hoc tests were examined. P-values were not adjusted for multiple testing. rs7014762 was in Hardy Weinberg equilibrium in cases and controls (p > 0.05). The minor allele of rs7014762 showed significant association with schizophrenia case status (minor allele (T) carrier OR = 1.49 (1.04, 2.15), p-value = 0.031). mRNA expression analysis revealed a significant diagnosis by genotype interaction on type III isoform expression in the hippocampus (F (5, 106) = 5.98; p-value = 0.003). Post hoc analysis showed the effect of rs7014762 was significant only in patients, whereby individuals heterozygous (LSD; p-value = 0.001) or homozygous (LSD p-value = 0.002) for the minor allele exhibited significantly lower levels of NRG1 type III expression compared to major allele homozygotes (Figure 1). No effects of race or race by genotype interactions were observed. No effects of genotype were observed for any other NRG1 isoform. Figure 1 Normalized NRG1 Type III Expression by rs7014762 Genotype in Schizophrenia Cases and Healthy Controls We report association between schizophrenia and rs7014762 in a case-control sample and show that the same allele of rs7014762 in the NRG1 5′ promoter region significantly predicts lower type III isoform expression levels in patients. NRG1 is expressed throughout the human brain, including the hippocampus and prefrontal cortex5, two areas implicated in schizophrenia, and individuals with schizophrenia show abnormalities in ErbB4–NRG1 signaling in the brain versus healthy controls6. In animal models, NRG1 type III isoform has been associated with axonal myelination7, lateral ventricle enlargement, and reduced function in the prefrontal cortex and hippocampus8. Disturbances in myelination/oligodendroglial density in individuals with schizophrenia have been observed9 and suggest reduced structural connectivity may be part of the neurobiology of schizophrenia. The same allele at this SNP has been shown to be associated with increased risk for bipolar disorder10. In addition, rs7014752 is 87 bp from rs6994992 (HAPICE SNP8NRG1243177) and is in moderate LD with this HAPICE SNP (D′ = 0.96, r2 = 0.21). SNP rs6994992 has previously been reported to be a functional promoter variant associated with schizophrenia and the regulated expression of a novel brain-specific isoform of NRG1, type IV, in humans3,4 and was associated with alterations in activation in frontal/temporal lobes, higher risk of psychotic symptomology and reduction in premorbid IQ in schizophrenia patients11. Together these observations suggest that variation in the HAPICE region may impact risk for schizophrenia via transcriptional regulation of multiple NRG1 isoforms.

The aim of this study was to test previous hypotheses of association between schizophrenia and human leukocyte antigen (HLA) specificities A9 (A23/24), DR4, and allele DQbeta1*0602. Using sequence-specific oligonucleotide probes, 256 familial schizophrenic patients and 261 unrelated controls were genotyped at polymorphisms for HLA-A, DRbeta1, and DQbeta1 loci. No significant (p < 0.05) differences in the allele frequencies between schizophrenics and controls were found, either when examining the sample as a whole or when subdivided by clinical subtype or gender. The present data do not support association between these HLA specificities and schizophrenia, and our review of previous studies suggests that reported associations may well be false positive results.

Susceptibility to autoimmunity is strongly influence by genes clustered in the MHC region, particularly class I and class II antigens. It has been proposed that there is an immune component in the aetiology of schizophrenia, and the distribution of human leukocyte antigens (HLA) in schizophrenic patients and controls has been investigated in numerous studies. Positive associations have been reported between schizophrenia and the HLA-A1, A2, A9, B5, Cw4, and DR8 and negative associations with HLA-DR4 and HLA-DQbeta*0602. Small sample size, variable diagnostic methodology, unreliable laboratory and statistical procedures, and possible mismatching of cases and controls may have contributed to a lack of consistency of results to date. Therefore, in this investigation we used a large and carefully diagnosed homogeneous Irish familial schizophrenic sample compared with ethnically matched controls. All alleles were determined using polymerase chain reaction amplification followed by short specific oligoprobes. We found no evidence of association with 80 HLA alleles (some previously not examined) from 4 genes. Our data therefore do not support the involvement of these classical HLA loci in the aetiology of schizophrenia at least in these Irish families. The remaining classical HLA loci (HLA-B and HLA-C) should be typed when reliable DNA-based methods become available.

Cigarette smoking is associated with considerable morbidity, mortality, and public health costs. Genetic factors influence both smoking initiation and nicotine dependence, but none of the genes involved have been identified. A genome scan using 451 markers was conducted to identify chromosomal regions linked to nicotine dependence in a collection of 130 families containing 343 genotyped individuals (308 nicotine-dependent) from Christchurch, New Zealand. By pairwise analysis, the best result was with marker D2S1326 which gave a lod score under heterogeneity (H-LOD) of 2.63 (P=0.0012) and a nonparametric linkage (NPL, Zall) score of 2.65 (P=0.0011). To identify regions that warranted further study, rather than comparing the pairwise scores from the scan to theoretical thresholds, we compared them to an empirical baseline, found here to be H-LOD scores of 0.5 and Zall scores of 1.0. We also found a number of large (31-88 cM) regions where many (8-16) consecutive markers yielded small but positive Zall scores. Selected regions of chromosomes 2, 4, 10, 16, 17 and 18 were investigated further by additional genotyping of the Christchurch sample and an independent sample from Richmond, Virginia (91 families with 264 genotyped individuals, 211 nicotine-dependent). Multipoint nonparametric analysis showed the following maximums for the Christchurch sample: Chr. 2 (Zlr=2.61, P=0.005), Chr. 4 (Zlr=1.36, P=0.09), Chr. 10 (Zlr=2.43, P=0.008), Chr. 16 (Zlr=0.85, P=0.19), Chr. 17 (Zlr=1.64, P=0.05), Chr. 18 (Zlr=1.54, P=0.06). Analysis of the Richmond sample showed the following maximums: Chr. 2 (Zlr=1.00, P=0.15), Chr. 4 (Zlr=0.39, P=0.34), Chr. 10 (Zlr=1.21, P=0.11), Chr. 16 (Zlr=1.11, P=0.13), Chr. 17 (Zlr=1.60, P=0.05), Chr. 18 (Zlr=1.33, P=0.09). It is probable that the small samples used here provided only limited power to detect linkage. It may have been difficult therefore to detect genes of small effect, or those that are influencing risk in only a small proportion of the families. When simply judged against the usual standards of linkage significance, none of the individual regions yielded strong evidence in either sample. Some or all of the most positive results in the genome scan of the Christchurch sample, therefore, could be due to chance. However, the presence in the Christchurch scan of multiple large regions containing many consecutive positive markers, coupled with the relatively positive results in these same regions in the Richmond sample, suggests that some of these regions may contain genes influencing nicotine dependence and therefore deserve further study.

Linkage disequilibrium (LD) is a potentially powerful tool for the localization of disease genes for complex disorders. Most prior studies of the relationship between genetic distance and LD have examined only very short distances, focusing on the role of LD in fine-mapping and positional cloning. We examine here the relationship between marker-to-marker (M-M) LD and somewhat greater genetic distances. We analyzed 622 M-M pairings on chromosomes 6p, 8p, and 5q in 265 native Irish pedigrees ascertained for a high density of schizophrenia. LD, significant at the 5% level, was found for 96% of all M-M pairings within 0.5 cM, for 67% within 0.5–1 cM, for 35% within 1–2 cM, for 15% within 2–4 cM, for 8% within 5–10 cM, and for 7% above 10 cM. Thus, in Irish families selected for a high density of schizophrenia, M-M LD may be very common within 0.5 cM and frequent up to distances of 2 cM. Am J. Med. Genet. (Neuropsychiatr. Genet.) 88:29–33, 1999. © 1999 Wiley-Liss, Inc.