scMeFormer: a transformer-based deep learning model for imputing DNA methylation states in single cells enhances the detection of epigenetic alterations in schizophrenia

DNA methylation (DNAm), a crucial epigenetic mark, plays a key role in gene regulation, mammalian development, and various human diseases. Single-cell technologies enable the profiling of DNAm states at cytosines within the DNA sequence of individual cells, but they often suffer from limited coverage of CpG sites. In this study, we introduce scMeFormer, a transformer-based deep learning model designed to impute DNAm states for each CpG site in single cells. Through comprehensive evaluations, we demonstrate the superior performance of scMeFormer compared to alternative models across four single-nucleus DNAm datasets generated by distinct technologies. Remarkably, scMeFormer exhibits high-fidelity imputation, even when dealing with significantly reduced coverage, as low as 10% of the original CpG sites. Furthermore, we applied scMeFormer to a single-nucleus DNAm dataset generated from the prefrontal cortex of four schizophrenia patients and four neurotypical controls. This enabled the identification of thousands of differentially methylated regions associated with schizophrenia that would have remained undetectable without imputation and added granularity to our understanding of epigenetic alterations in schizophrenia within specific cell types. Our study highlights the power of deep learning in imputing DNAm states in single cells, and we expect scMeFormer to be a valuable tool for single-cell DNAm studies.

Analysis of somatic mutations in 131 human brains reveals aging-associated hypermutability

We analyzed 131 human brains (44 neurotypical, 19 with Tourette syndrome, 9 with schizophrenia, and 59 with autism) for somatic mutations after whole genome sequencing to a depth of more than 200×. Typically, brains had 20 to 60 detectable single-nucleotide mutations, but ~6% of brains harbored hundreds of somatic mutations. Hypermutability was associated with age and damaging mutations in genes implicated in cancers and, in some brains, reflected in vivo clonal expansions. Somatic duplications, likely arising during development, were found in ~5% of normal and diseased brains, reflecting background mutagenesis. Brains with autism were associated with mutations creating putative transcription factor binding motifs in enhancer-like regions in the developing brain. The top-ranked affected motifs corresponded to MEIS (myeloid ectopic viral integration site) transcription factors, suggesting a potential link between their involvement in gene regulation and autism.

Mapping genomic loci implicates genes and synaptic biology in schizophrenia

Schizophrenia has a heritability of 60-80%1, much of which is attributable to common risk alleles. Here, in a two-stage genome-wide association study of up to 76,755 individuals with schizophrenia and 243,649 control individuals, we report common variant associations at 287 distinct genomic loci. Associations were concentrated in genes that are expressed in excitatory and inhibitory neurons of the central nervous system, but not in other tissues or cell types. Using fine-mapping and functional genomic data, we identify 120 genes (106 protein-coding) that are likely to underpin associations at some of these loci, including 16 genes with credible causal non-synonymous or untranslated region variation. We also implicate fundamental processes related to neuronal function, including synaptic organization, differentiation and transmission. Fine-mapped candidates were enriched for genes associated with rare disruptive coding variants in people with schizophrenia, including the glutamate receptor subunit GRIN2A and transcription factor SP4, and were also enriched for genes implicated by such variants in neurodevelopmental disorders. We identify biological processes relevant to schizophrenia pathophysiology; show convergence of common and rare variant associations in schizophrenia and neurodevelopmental disorders; and provide a resource of prioritized genes and variants to advance mechanistic studies.

Electrophysiological measures from human iPSC-derived neurons are associated with schizophrenia clinical status and predict individual cognitive performance

Neurons derived from human induced pluripotent stem cells (hiPSCs) have been used to model basic cellular aspects of neuropsychiatric disorders, but the relationship between the emergent phenotypes and the clinical characteristics of donor individuals has been unclear. We analyzed RNA expression and indices of cellular function in hiPSC-derived neural progenitors and cortical neurons generated from 13 individuals with high polygenic risk scores (PRSs) for schizophrenia (SCZ) and a clinical diagnosis of SCZ, along with 15 neurotypical individuals with low PRS. We identified electrophysiological measures in the patient-derived neurons that implicated altered Na+ channel function, action potential interspike interval, and gamma-aminobutyric acid-ergic neurotransmission. Importantly, electrophysiological measures predicted cardinal clinical and cognitive features found in these SCZ patients. The identification of basic neuronal physiological properties related to core clinical characteristics of illness is a potentially critical step in generating leads for novel therapeutics.

Identifying nootropic drug targets via large-scale cognitive GWAS and transcriptomics

Broad-based cognitive deficits are an enduring and disabling symptom for many patients with severe mental illness, and these impairments are inadequately addressed by current medications. While novel drug targets for schizophrenia and depression have emerged from recent large-scale genome-wide association studies (GWAS) of these psychiatric disorders, GWAS of general cognitive ability can suggest potential targets for nootropic drug repurposing. Here, we (1) meta-analyze results from two recent cognitive GWAS to further enhance power for locus discovery; (2) employ several complementary transcriptomic methods to identify genes in these loci that are credibly associated with cognition; and (3) further annotate the resulting genes using multiple chemoinformatic databases to identify "druggable" targets. Using our meta-analytic data set (N = 373,617), we identified 241 independent cognition-associated loci (29 novel), and 76 genes were identified by 2 or more methods of gene identification. Actin and chromatin binding gene sets were identified as novel pathways that could be targeted via drug repurposing. Leveraging our transcriptomic and chemoinformatic databases, we identified 16 putative genes targeted by existing drugs potentially available for cognitive repurposing.

Genome-wide analyses of smoking behaviors in schizophrenia: Findings from the Psychiatric Genomics Consortium

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.

Comprehensive identification of somatic nucleotide variants in human brain tissue

BACKGROUND

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.

RESULTS

Here, the Brain Somatic Mosaicism Network conducts a coordinated, multi-institutional study to examine the ability of existing methods to detect simulated somatic single-nucleotide variants (SNVs) in DNA mixing experiments, 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, devise strategies to discover somatic SNVs, and apply various approaches to validate somatic SNVs. These efforts lead to the identification of 43 bona fide somatic SNVs that range in variant allele fractions from ~ 0.005 to ~ 0.28. Guided by these results, we devise best practices for calling mosaic SNVs from 250× whole-genome sequencing data in the accessible portion of the human genome that achieve 90% specificity and sensitivity. Finally, we demonstrate that analysis of multiple bulk DNA samples from a single individual allows the reconstruction of early developmental cell lineage trees.

CONCLUSIONS

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.

Schizophrenia risk variants influence multiple classes of transcripts of sorting nexin 19 (SNX19)

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.

Dissecting transcriptomic signatures of neuronal differentiation and maturation using iPSCs

Human 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 9 time points over 5 broad conditions: self-renewal, early neuronal differentiation, neural precursor cells (NPCs), assembled rosettes, and differentiated neuronal cells. We identify widespread changes in the expression of both individual features and global patterns of transcription. We next demonstrate that co-culturing human NPCs with rodent astrocytes results in mutually synergistic maturation, and that cell type-specific expression data can be extracted using only sequencing read alignments without cell sorting. We lastly adapt a previously generated RNA deconvolution approach to single-cell expression data to estimate the relative neuronal maturity of iPSC-derived neuronal cultures and human brain tissue. Using many public datasets, we demonstrate neuronal cultures are maturationally heterogeneous but contain subsets of neurons more mature than previously observed.

Polygenic risk score increases schizophrenia liability through cognition-relevant pathways

Cognitive deficit is thought to represent, at least in part, genetic mechanisms of risk for schizophrenia, with recent evidence from statistical modelling of twin data suggesting direct causality from the former to the latter. However, earlier evidence was based on inferences from twin not molecular genetic data and it is unclear how much genetic influence 'passes through' cognition on the way to diagnosis. Thus, we included direct measurements of genetic risk (e.g. schizophrenia polygenic risk scores) in causation models to assess the extent to which cognitive deficit mediates some of the effect of polygenic risk scores on the disorder. Causal models of family data tested relationships among key variables and allowed parsing of genetic variance components. Polygenic risk scores were calculated from summary statistics from the current largest genome-wide association study of schizophrenia and were represented as a latent trait. Cognition was also modelled as a latent trait. Participants were 1313 members of 1078 families: 416 patients with schizophrenia, 290 unaffected siblings, and 607 controls. Modelling supported earlier findings that cognitive deficit has a putatively causal role in schizophrenia. In total, polygenic risk score explained 8.07% [confidence interval (CI) 5.45-10.74%] of schizophrenia risk in our sample. Of this, more than a third (2.71%, CI 2.41-3.85%) of the polygenic risk score influence was mediated through cognition paths, exceeding the direct influence of polygenic risk score on schizophrenia risk (1.43%, CI 0.46-3.08%). The remainder of the polygenic risk score influence (3.93%, CI 2.37-4.48%) reflected reciprocal causation between schizophrenia liability and cognition (e.g. mutual influences in a cyclical manner). Analysis of genetic variance components of schizophrenia liability indicated that 26.87% (CI 21.45-32.57%) was associated with cognition-related pathways not captured by polygenic risk score. The remaining variance in schizophrenia was through pathways other than cognition-related and polygenic risk score. Although our results are based on inference through statistical modelling and do not provide an absolute proof of causality, we find that cognition pathways mediate a significant part of the influence of cumulative genetic risk on schizophrenia. We estimate from our model that 33.51% (CI 27.34-43.82%) of overall genetic risk is mediated through influences on cognition, but this requires further studies and analyses as the genetics of schizophrenia becomes better characterized.

Pleiotropic Meta-Analysis of Cognition, Education, and Schizophrenia Differentiates Roles of Early Neurodevelopmental and Adult Synaptic Pathways

Susceptibility to schizophrenia is inversely correlated with general cognitive ability at both the phenotypic and the genetic level. Paradoxically, a modest but consistent positive genetic correlation has been reported between schizophrenia and educational attainment, despite the strong positive genetic correlation between cognitive ability and educational attainment. Here we leverage published genome-wide association studies (GWASs) in cognitive ability, education, and schizophrenia to parse biological mechanisms underlying these results. Association analysis based on subsets (ASSET), a pleiotropic meta-analytic technique, allowed jointly associated loci to be identified and characterized. Specifically, we identified subsets of variants associated in the expected ("concordant") direction across all three phenotypes (i.e., greater risk for schizophrenia, lower cognitive ability, and lower educational attainment); these were contrasted with variants that demonstrated the counterintuitive ("discordant") relationship between education and schizophrenia (i.e., greater risk for schizophrenia and higher educational attainment). ASSET analysis revealed 235 independent loci associated with cognitive ability, education, and/or schizophrenia at p < 5 × 10-8. Pleiotropic analysis successfully identified more than 100 loci that were not significant in the input GWASs. Many of these have been validated by larger, more recent single-phenotype GWASs. Leveraging the joint genetic correlations of cognitive ability, education, and schizophrenia, we were able to dissociate two distinct biological mechanisms-early neurodevelopmental pathways that characterize concordant allelic variation and adulthood synaptic pruning pathways-that were linked to the paradoxical positive genetic association between education and schizophrenia. Furthermore, genetic correlation analyses revealed that these mechanisms contribute not only to the etiopathogenesis of schizophrenia but also to the broader biological dimensions implicated in both general health outcomes and psychiatric illness.

Schizophrenia polygenic risk score predicts mnemonic hippocampal activity

The use of polygenic risk scores has become a practical translational approach to investigating the complex genetic architecture of schizophrenia, but the link between polygenic risk scores and pathophysiological components of this disorder has been the subject of limited research. We investigated in healthy volunteers whether schizophrenia polygenic risk score predicts hippocampal activity during simple memory encoding, which has been proposed as a risk-associated intermediate phenotype of schizophrenia. We analysed the relationship between polygenic risk scores and hippocampal activity in a discovery sample of 191 unrelated healthy volunteers from the USA and in two independent replication samples of 76 and 137 healthy unrelated participants from Europe and the USA, respectively. Polygenic risk scores for each individual were calculated as the sum of the imputation probability of reference alleles weighted by the natural log of odds ratio from the recent schizophrenia genome-wide association study. We examined hippocampal activity during simple memory encoding of novel visual stimuli assessed using blood oxygen level-dependent functional MRI. Polygenic risk scores were significantly associated with hippocampal activity in the discovery sample [P = 0.016, family-wise error (FWE) corrected within Anatomical Automatic Labeling (AAL) bilateral hippocampal-parahippocampal mask] and in both replication samples (P = 0.033, FWE corrected within AAL right posterior hippocampal-parahippocampal mask in Bari sample, and P = 0.002 uncorrected in the Duke Neurogenetics Study sample). The relationship between polygenic risk scores and hippocampal activity was consistently negative, i.e. lower hippocampal activity in individuals with higher polygenic risk scores, consistent with previous studies reporting decreased hippocampal-parahippocampal activity during declarative memory tasks in patients with schizophrenia and in their healthy siblings. Polygenic risk scores accounted for more than 8% of variance in hippocampal activity during memory encoding in discovery sample. We conclude that polygenic risk scores derived from the most recent schizophrenia genome-wide association study predict significant variability in hippocampal activity during memory encoding in healthy participants. Our findings validate mnemonic hippocampal activity as a genetic risk associated intermediate phenotype of schizophrenia, indicating that the aggregate neurobiological effect of schizophrenia risk alleles converges on this pattern of neural activity.awy004media15749593779001.

Regional Heterogeneity in Gene Expression, Regulation, and Coherence in the Frontal Cortex and Hippocampus across Development and Schizophrenia

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.

Author Correction: Study of 300,486 individuals identifies 148 independent genetic loci influencing general cognitive function

Christina M. Lill, who contributed to analysis of data, was inadvertently omitted from the author list in the originally published version of this article. This has now been corrected in both the PDF and HTML versions of the article.

Developmental and genetic regulation of the human cortex transcriptome illuminate schizophrenia pathogenesis

Genome-wide association studies have identified 108 schizophrenia risk loci, but biological 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 postnatal 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 general eQTL database to show that 48.1% of risk variants for schizophrenia associate 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 genetics- and diagnosis-related targets for better modeling of schizophrenia risk. This resource is publicly available at http://eqtl.brainseq.org/phase1 .

Large-Scale Cognitive GWAS Meta-Analysis Reveals Tissue-Specific Neural Expression and Potential Nootropic Drug Targets

Here, we present a large (n = 107,207) genome-wide association study (GWAS) of general cognitive ability ("g"), further enhanced by combining results with a large-scale GWAS of educational attainment. We identified 70 independent genomic loci associated with general cognitive ability. Results showed significant enrichment for genes causing Mendelian disorders with an intellectual disability phenotype. Competitive pathway analysis implicated the biological processes of neurogenesis and synaptic regulation, as well as the gene targets of two pharmacologic agents: cinnarizine, a T-type calcium channel blocker, and LY97241, a potassium channel inhibitor. Transcriptome-wide and epigenome-wide analysis revealed that the implicated loci were enriched for genes expressed across all brain regions (most strongly in the cerebellum). Enrichment was exclusive to genes expressed in neurons but not oligodendrocytes or astrocytes. Finally, we report genetic correlations between cognitive ability and disparate phenotypes including psychiatric disorders, several autoimmune disorders, longevity, and maternal age at first birth.

Genome-wide association meta-analysis in 269,867 individuals identifies new genetic and functional links to intelligence

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 variation in intelligence3-7, 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.

Estimation of Genetic Correlation via Linkage Disequilibrium Score Regression and Genomic Restricted Maximum Likelihood

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 ∼150,000 individuals give a higher accuracy than LDSC estimates based on ∼400,000 individuals (from combined meta-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.

Study of 300,486 individuals identifies 148 independent genetic loci influencing general cognitive function

General cognitive function is a prominent and relatively stable human trait that is associated with many important life outcomes. We combine cognitive and genetic data from the CHARGE and COGENT consortia, and UK Biobank (total N = 300,486; age 16-102) and find 148 genome-wide significant independent loci (P < 5 × 10-8) associated with general cognitive function. Within the novel genetic loci are variants associated with neurodegenerative and neurodevelopmental disorders, physical and psychiatric illnesses, and brain structure. Gene-based analyses find 709 genes associated with general cognitive function. Expression levels across the cortex are associated with general cognitive function. Using polygenic scores, up to 4.3% of variance in general cognitive function is predicted in independent samples. We detect significant genetic overlap between general cognitive function, reaction time, and many health variables including eyesight, hypertension, and longevity. In conclusion we identify novel genetic loci and pathways contributing to the heritability of general cognitive function.

GWAS meta-analysis reveals novel loci and genetic correlates for general cognitive function: a report from the COGENT consortium

This corrects the article DOI: 10.1038/mp.2016.244.

Intersection of diverse neuronal genomes and neuropsychiatric disease: The Brain Somatic Mosaicism Network

Neuropsychiatric disorders have a complex genetic architecture. Human genetic population-based studies have identified numerous heritable sequence and structural genomic variants associated with susceptibility to neuropsychiatric disease. However, these germline variants do not fully account for disease risk. During brain development, progenitor cells undergo billions of cell divisions to generate the ~80 billion neurons in the brain. The failure to accurately repair DNA damage arising during replication, transcription, and cellular metabolism amid this dramatic cellular expansion can lead to somatic mutations. Somatic mutations that alter subsets of neuronal transcriptomes and proteomes can, in turn, affect cell proliferation and survival and lead to neurodevelopmental disorders. The long life span of individual neurons and the direct relationship between neural circuits and behavior suggest that somatic mutations in small populations of neurons can significantly affect individual neurodevelopment. The Brain Somatic Mosaicism Network has been founded to study somatic mosaicism both in neurotypical human brains and in the context of complex neuropsychiatric disorders.

GWAS meta-analysis reveals novel loci and genetic correlates for general cognitive function: a report from the COGENT consortium

The complex nature of human cognition has resulted in cognitive genomics lagging behind many other fields in terms of gene discovery using genome-wide association study (GWAS) methods. In an attempt to overcome these barriers, the current study utilized GWAS meta-analysis to examine the association of common genetic variation (~8M single-nucleotide polymorphisms (SNP) with minor allele frequency ⩾1%) to general cognitive function in a sample of 35 298 healthy individuals of European ancestry across 24 cohorts in the Cognitive Genomics Consortium (COGENT). In addition, we utilized individual SNP lookups and polygenic score analyses to identify genetic overlap with other relevant neurobehavioral phenotypes. Our primary GWAS meta-analysis identified two novel SNP loci (top SNPs: rs76114856 in the CENPO gene on chromosome 2 and rs6669072 near LOC105378853 on chromosome 1) associated with cognitive performance at the genome-wide significance level (P<5 × 10^-8). Gene-based analysis identified an additional three Bonferroni-corrected significant loci at chromosomes 17q21.31, 17p13.1 and 1p13.3. Altogether, common variation across the genome resulted in a conservatively estimated SNP heritability of 21.5% (s.e.=0.01%) for general cognitive function. Integration with prior GWAS of cognitive performance and educational attainment yielded several additional significant loci. Finally, we found robust polygenic correlations between cognitive performance and educational attainment, several psychiatric disorders, birth length/weight and smoking behavior, as well as a novel genetic association to the personality trait of openness. These data provide new insight into the genetics of neurocognitive function with relevance to understanding the pathophysiology of neuropsychiatric illness.

A human-specific AS3MT isoform and BORCS7 are molecular risk factors in the 10q24.32 schizophrenia-associated locus

Genome-wide association studies (GWASs) have reported many single nucleotide polymorphisms (SNPs) associated with psychiatric disorders, but knowledge is lacking regarding molecular mechanisms. Here we show that risk alleles spanning multiple genes across the 10q24.32 schizophrenia-related locus are associated in the human brain selectively with an increase in the expression of both BLOC-1 related complex subunit 7 (BORCS7) and a previously uncharacterized, human-specific arsenite methyltransferase (AS3MT) isoform (AS3MT(d2d3)), which lacks arsenite methyltransferase activity and is more abundant in individuals with schizophrenia than in controls. Conditional-expression analysis suggests that BORCS7 and AS3MT(d2d3) signals are largely independent. GWAS risk SNPs across this region are linked with a variable number tandem repeat (VNTR) polymorphism in the first exon of AS3MT that is associated with the expression of AS3MT(d2d3) in samples from both Caucasians and African Americans. The VNTR genotype predicts promoter activity in luciferase assays, as well as DNA methylation within the AS3MT gene. Both AS3MT(d2d3) and BORCS7 are expressed in adult human neurons and astrocytes, and they are upregulated during human stem cell differentiation toward neuronal fates. Our results provide a molecular explanation for the prominent 10q24.32 locus association, including a novel and evolutionarily recent protein that is involved in early brain development and confers risk for psychiatric illness.

Genomic structure and expression of the human serotonin 2A receptor gene (HTR2A) locus: identification of novel HTR2A and antisense (HTR2A-AS1) exons

Background

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.

Results

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.

Conclusions

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.

Electronic supplementary material

The online version of this article (doi:10.1186/s12863-015-0325-6) contains supplementary material, which is available to authorized users.

Independent evidence for an association between general cognitive ability and a genetic locus for educational attainment

Cognitive deficits and reduced educational achievement are common in psychiatric illness; understanding the genetic basis of cognitive and educational deficits may be informative about the etiology of psychiatric disorders. A recent, large genome-wide association study (GWAS) reported a genome-wide significant locus for years of education, which subsequently demonstrated association to general cognitive ability ("g") in overlapping cohorts. The current study was designed to test whether GWAS hits for educational attainment are involved in general cognitive ability in an independent, large-scale collection of cohorts. Using cohorts in the Cognitive Genomics Consortium (COGENT; up to 20,495 healthy individuals), we examined the relationship between g and variants associated with educational attainment. We next conducted meta-analyses with 24,189 individuals with neurocognitive data from the educational attainment studies, and then with 53,188 largely independent individuals from a recent GWAS of cognition. A SNP (rs1906252) located at chromosome 6q16.1, previously associated with years of schooling, was significantly associated with g (P = 1.47 × 10(-4) ) in COGENT. The first joint analysis of 43,381 non-overlapping individuals for this a priori-designated locus was strongly significant (P = 4.94 × 10(-7) ), and the second joint analysis of 68,159 non-overlapping individuals was even more robust (P = 1.65 × 10(-9) ). These results provide independent replication, in a large-scale dataset, of a genetic locus associated with cognitive function and education. As sample sizes grow, cognitive GWAS will identify increasing numbers of associated loci, as has been accomplished in other polygenic quantitative traits, which may be relevant to psychiatric illness.

Differential effects of common variants in SCN2A on general cognitive ability, brain physiology, and messenger RNA expression in schizophrenia cases and control individuals

IMPORTANCE

One approach to understanding the genetic complexity of schizophrenia is to study associated behavioral and biological phenotypes that may be more directly linked to genetic variation.

OBJECTIVE

To identify single-nucleotide polymorphisms associated with general cognitive ability (g) in people with schizophrenia and control individuals.

DESIGN, SETTING, AND PARTICIPANTS

Genomewide association study, followed by analyses in unaffected siblings and independent schizophrenia samples, functional magnetic resonance imaging studies of brain physiology in vivo, and RNA sequencing in postmortem brain samples. The discovery cohort and unaffected siblings were participants in the National Institute of Mental Health Clinical Brain Disorders Branch schizophrenia genetics studies. Additional schizophrenia cohorts were from psychiatric treatment settings in the United States, Japan, and Germany. The discovery cohort comprised 339 with schizophrenia and 363 community control participants. Follow-up analyses studied 147 unaffected siblings of the schizophrenia cases and independent schizophrenia samples including a total of an additional 668 participants. Imaging analyses included 87 schizophrenia cases and 397 control individuals. Brain tissue samples were available for 64 cases and 61 control individuals.

MAIN OUTCOMES AND MEASURES

We studied genomewide association with g, by group, in the discovery cohort. We used selected genotypes to test specific associations in unaffected siblings and independent schizophrenia samples. Imaging analyses focused on activation in the prefrontal cortex during working memory. Brain tissue studies yielded messenger RNA expression levels for RefSeq transcripts.

RESULTS

The schizophrenia discovery cohort showed genomewide-significant association of g with polymorphisms in sodium channel gene SCN2A, accounting for 10.4% of g variance (rs10174400, P = 9.27 × 10(-10)). Control individuals showed a trend for g/genotype association with reversed allelic directionality. The genotype-by-group interaction was also genomewide significant (P = 1.75 × 10(-9)). Siblings showed a genotype association with g parallel to the schizophrenia group and the same interaction pattern. Parallel, but weaker, associations with cognition were found in independent schizophrenia samples. Imaging analyses showed a similar pattern of genotype associations by group and genotype-by-group interaction. Sequencing of RNA in brain revealed reduced expression in 2 of 3 SCN2A alternative transcripts in the patient group, with genotype-by-group interaction, that again paralleled the cognition effects.

CONCLUSIONS AND RELEVANCE

The findings implicate SCN2A and sodium channel biology in cognitive impairment in schizophrenia cases and unaffected relatives and may facilitate development of cognition-enhancing treatments.

Incomplete penetrance of NRXN1 deletions in families with schizophrenia

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.

Variation in psychosis gene ZNF804A is associated with a refined schizotypy phenotype but not neurocognitive performance in a large young male population

Genetic variability within the ZNF804A gene has been recently found to be associated with schizophrenia and bipolar disorder, although the pathways by which this gene may confer risk remain largely unknown. We set out to investigate whether common ZNF804A variants affect psychosis-related intermediate phenotypes such as cognitive performance dependent on prefrontal and frontotemporal brain function, schizotypal traits, and attenuated psychotic experiences in a large young male population. Association analyses were performed using all 4 available self-rated schizotypy questionnaires and cognitive data retrospectively drawn from the Athens Study of Psychosis Proneness and Incidence of Schizophrenia (ASPIS). DNA samples from 1507 healthy young men undergoing induction to military training were genotyped for 4 previously studied polymorphic markers in the ZNF804A gene locus. Single-marker analysis revealed significant associations between 2 recently identified candidate schizophrenia susceptibility variants (rs1344706 and rs7597593) and a refined positive schizotypy phenotype characterized primarily by self-rated paranoia/ideas of reference. Nominal associations were noted with all positive, but not negative, schizotypy related factors. ZNF804A genotype effect on paranoia was confirmed at the haplotype level. No significant associations were noted with central indexes of sustained attention or working memory performance. In this study, ZNF804A variation was associated with a population-based self-rated schizotypy phenotype previously suggested to preferentially reflect genetic liability to psychosis and defined by a tendency to misinterpret otherwise neutral social cues and perceptual experiences in one's immediate environment, as personally relevant and significant information. This suggests a novel route by which schizophrenia-implicated ZNF804A genetic variation may confer risk to clinical psychosis at the general population level.

Schizophrenia candidate gene ERBB4: covert routes of vulnerability to psychosis detected at the population level

Prior genetic and functional evidence established ERBB4 as a probable schizophrenia susceptibility gene that may confer risk via modulating brain information processing dependent on the integrity of frontotemporal brain circuitry. Utilizing retrospective data drawn from the cross-sectional population-based Athens Study of Psychosis Proneness and Incidence of Schizophrenia (ASPIS) (n = 1127), we attempted to independently replicate and further extend previous findings by examining the effects of ERBB4 gene variants on 3 broad population-based psychosis-related phenotypes: verbal working memory (VWM), trait schizotypy, and stress-induced subclinical psychotic experiences (PE). Three common ERBB4 single nucleotide polymorphisms that were previously associated with schizophrenia and impaired frontotemporal-related information processing (rs7598440, rs839523, and rs707284), their haplotypes, and corresponding diplotypes were tested. VWM performance was significantly associated with rs839523 and rs707284 markers even after correction for multiple testing, thus validating reported findings that have implicated ERBB4 gene variation on working memory. No associations were detected between these ERBB4 variants and trait schizotypy. However, we were able to detect a significant effect of rs7598440 marker on PE expressed under stressful environmental conditions. Combined haplotype analysis of the above 3 markers, identified a "yin-yang" pattern of association, confirmed at the diplotype level. While GGG haplotype homozygotes were associated with "protective" effects on VWM performance and PE, AAA "risk" haplotype carriers were associated with worse VWM performance and simultaneously exhibited significantly elevated PE. This dual, possibly pleiotropic, impact on frontotemporal circuitry and increased sensitivity to psychosocial stress may represent subtle manifestations of ERBB4-related vulnerability to psychosis, expressed at the population level.

Effect of schizophrenia risk-associated alleles in SREB2 (GPR85) on functional MRI phenotypes in healthy volunteers

Genetic variants in GPR85 (SREB2: rs56080411 and rs56039557) have been associated with risk for schizophrenia. Here, we test the hypothesis that these variants impact on brain function in normal subjects, measured with functional magnetic resonance imaging (fMRI) paradigms that target regions with greatest SREB2 expression (hippocampal formation and amygdaloid complex). During a facial emotion recognition paradigm, a significant interaction of rs56080411 genotype by sex was found in the left amygdaloid complex (male risk allele carriers showed less activation than male homozygotes for the non-risk allele, while females showed the opposite pattern). During aversive encoding of an emotional memory paradigm, we found that risk allele carriers for rs56080411 had greater activation in the right inferior frontal gyrus. Trends in the same direction were present for rs56039557 in the right occipital cortex and right fusiform gyrus. During a working memory paradigm, a significant sex-by-genotype interaction was found with male risk allele carriers of rs56080411 having inefficient activation within the left dorsolateral prefrontal cortex (DLPFC), compared with same sex non-risk carriers, while females revealed an opposite pattern, despite similar levels of performance. These data suggest that risk-associated variants in SREB2 are associated with phenotypes similar to those found in patients with schizophrenia in the DLPFC and the amygdala of males, while the pattern is opposite in females. The findings in females and during the emotional memory paradigm are consistent with modulation by SREB2 of brain circuitries implicated in mood regulation and may be relevant to neuropsychiatric conditions other than schizophrenia.

Expression of GABA signaling molecules KCC2, NKCC1, and GAD1 in cortical development and schizophrenia

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.

Evidence of sex-modulated association of ZNF804A with schizophrenia

BACKGROUND

The single nucleotide polymorphism (SNP) rs1344706 in ZNF804A (2q32.1) has been associated with schizophrenia in a genome-wide association study (GWAS). A recent candidate gene study, which replicated the positive association with rs1344706, identified another positive SNP (rs7597593) in ZNF804A associated with schizophrenia.

METHODS

We performed an association study of rs7597593 in four GWAS cohorts of European ancestry. Postmortem human brain expression data of normal Caucasian individuals (n = 89) was also analyzed for examining the effect of rs7597593 on ZNF804A messenger RNA expression, using logistic regression and linear regression.

RESULTS

We found that rs7597593 was significantly associated with schizophrenia in the combined GWAS datasets (n = 5023, odds ratio [OR](combined) = 1.15, p = .0011). Analysis of stratification by sex showed that the association was driven by the female subjects (OR = 1.29, p = .0002) and was not significant in male subjects (OR = 1.08, p = .148) in the combined sample of four cohorts. A sex by genotype interaction was near significant in both the Genetic Association Information Network sample (p = .0532) and the combined sample of four cohorts (p(combined) = .0531). Gene expression analysis showed no main effects but a significant female-specific association (p(female) = .047, p(male) = .335) and sex by genotype interaction (p = .0166) for rs7597593.

CONCLUSIONS

Our data suggest a clinical and molecular modulation by sex of the association of ZNF804A SNP rs7597593 and risk of schizophrenia.

Biological validation of increased schizophrenia risk with NRG1, ERBB4, and AKT1 epistasis via functional neuroimaging in healthy controls

CONTEXT

NRG1 is a schizophrenia candidate gene and plays an important role in brain development and neural function. Schizophrenia is a complex disorder, with etiology likely due to epistasis.

OBJECTIVE

To examine epistasis between NRG1 and selected N-methyl-d-aspartate-glutamate pathway partners implicated in its effects, including ERBB4, AKT1, DLG4, NOS1, and NOS1AP.

DESIGN

Schizophrenia case-control sample analyzed using machine learning algorithms and logistic regression with follow-up using neuroimaging on an independent sample of healthy controls.

PARTICIPANTS

A referred sample of schizophrenic patients (n = 296) meeting DSM-IV criteria for schizophrenia spectrum disorder and a volunteer sample of controls for case-control comparison (n = 365) and a separate volunteer sample of controls for neuroimaging (n = 172).

MAIN OUTCOME MEASURES

Epistatic association between single-nucleotide polymorphisms (SNPs) and case-control status; epistatic association between SNPs and the blood oxygen level-dependent physiological response during working memory measured by functional magnetic resonance imaging.

RESULTS

We observed interaction between NRG1 5' and 3' SNPs rs4560751 and rs3802160 (likelihood ratio test P = .00020) and schizophrenia, which was validated using functional magnetic resonance imaging of working memory in healthy controls; carriers of risk-associated genotypes showed inefficient processing in the dorsolateral prefrontal cortex (P = .015, familywise error corrected). We observed epistasis between NRG1 (rs10503929; Thr286/289/294Met) and its receptor ERBB4 (rs1026882; likelihood ratio test P = .035); a 3-way interaction with these 2 SNPs and AKT1 (rs2494734) was also observed (odds ratio, 27.13; 95% confidence interval, 3.30-223.03; likelihood ratio test P = .042). These same 2- and 3-way interactions were further biologically validated via functional magnetic resonance imaging: healthy individuals carrying risk genotypes for NRG1 and ERBB4, or these 2 together with AKT1, were disproportionately less efficient in dorsolateral prefrontal cortex processing. Lower-level interactions were not observed between NRG1 /ERBB4 and AKT1 in association or neuroimaging, consistent with biological evidence that NRG1 × ERBB4 interaction modulates downstream AKT1 signaling.

CONCLUSION

Our data suggest complex epistatic effects implicating an NRG1 molecular pathway in cognitive brain function and the pathogenesis of schizophrenia.

Genetic variation in CACNA1C affects brain circuitries related to mental illness

CONTEXT

The CACNA1C gene (alpha-1C subunit of the L-type voltage-gated calcium channel) has been identified as a risk gene for bipolar disorder and schizophrenia, but the mechanism of association has not been explored.

OBJECTIVE

To identify the neural system mechanism that explains the genetic association between the CACNA1C gene and psychiatric illness using neuroimaging and human brain expression.

DESIGN

We used blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging (fMRI) to measure brain activation in circuitries related to bipolar disorder and schizophrenia by comparing CACNA1C genotype groups among healthy subjects. We tested the effect of genotype on messenger RNA (mRNA) levels of CACNA1C in postmortem human brain. A case-control analysis was used to determine the association of CACNA1C genotype with schizophrenia.

SETTING

National Institutes of Health Clinical Center.

PATIENTS

Healthy men and women of white race/ethnicity participated in the fMRI study. Postmortem samples from normal human brains were used for the brain expression study. Patients with schizophrenia and healthy subjects were used in the case-control analysis.

MAIN OUTCOME MEASURES

BOLD fMRI, mRNA levels in postmortem brain samples, and genetic association with schizophrenia.

RESULTS

The risk-associated single-nucleotide polymorphism (SNP rs1006737) in CACNA1C predicted increased hippocampal activity during emotional processing (P = .001 uncorrected, P((false recovery rate [FDR])) = .05, z = 3.20) and increased prefrontal activity during executive cognition (P = 2.8e-05 uncorrected, P(FDR) = .01, z = 4.03). The risk-associated SNP also predicted increased expression of CACNA1C mRNA in human brain (P = .002). CACNA1C was associated with schizophrenia in our case-control sample (odds ratio, 1.77; P = .03).

CONCLUSIONS

The risk-associated SNP in CACNA1C maps to circuitries implicated in genetic risk for bipolar disorder and schizophrenia. Its effects in human brain expression implicate a molecular and neural system mechanism for the clinical genetic association.

Genetic modulation of GABA levels in the anterior cingulate cortex by GAD1 and COMT

Gamma-aminobutyric acid (GABA)-ergic transmission is critical for normal cortical function and is likely abnormal in a variety of neuropsychiatric disorders. We tested the in vivo effects of variations in two genes implicated in GABA function on GABA concentrations in prefrontal cortex of living subjects: glutamic acid decarboxylase 1 (GAD1), which encodes GAD67, and catechol-o-methyltransferase (COMT), which regulates synaptic dopamine in the cortex. We studied six single nucleotide polymorphisms (SNPs) in GAD1 previously associated with risk for schizophrenia or cognitive dysfunction and the val158met polymorphism in COMT in 116 healthy volunteers using proton magnetic resonance spectroscopy. Two of the GAD1 SNPs (rs1978340 (p=0.005) and rs769390 (p=0.004)) showed effects on GABA levels as did COMT val158met (p=0.04). We then tested three SNPs in GAD1 (rs1978340, rs11542313, and rs769390) for interaction with COMT val158met based on previous clinical results. In this model, rs11542313 and COMT val158met showed significant main effects (p=0.001 and 0.003, respectively) and a trend toward a significant interaction (p=0.05). Interestingly, GAD1 risk alleles for schizophrenia were associated with higher GABA/Cre, and Val-Val homozygotes had high GABA/Cre levels when on a GAD1 risk genotype background (N=6). These results support the importance of genetic variation in GAD1 and COMT in regulating prefrontal cortical GABA function. The directionality of the effects, however, is inconsistent with earlier evidence of decreased GABA activity in schizophrenia.

Progranulin (GRN) in two siblings of a Latino family and in other patients with schizophrenia

Schizophrenia has been linked to a region on chromosome 17q21 in Latino populations (Escamilla et al., 2009). Mutations of a gene at this location (GRN) are associated with frontotemporal dementia. A recent study demonstrated that patients with frontotemporal dementia who presented with symptoms of schizophrenia show neuropathological findings consistent with GRN mutations, but were not tested for GRN mutations (Velakoulis, Walterfang, Mocellin, Pantelis, & McLean, 2009). The current study describes a Latino family in which two siblings have schizophrenia and one has frontotemporal dementia. We sequenced GRN in one of the siblings with frontotemporal dementia and one of the siblings with schizophrenia. The siblings both have a loss-of-function GRN mutation. This finding, in conjunction with other studies (Escamilla et al., 2009; Velakoulis et al., 2009), suggests that there may be an association between schizophrenia, frontotemporal dementia, and GRN mutations in Latino populations that should be investigated further.

Serious obstetric complications interact with hypoxia-regulated/vascular-expression genes to influence schizophrenia risk

The etiology of schizophrenia is thought to include both epistasis and gene-environment interactions. We sought to test whether a set of schizophrenia candidate genes regulated by hypoxia or involved in vascular function in the brain (AKT1, BDNF, CAPON, CHRNA7, COMT, DTNBP1, GAD1, GRM3, NOTCH4, NRG1, PRODH, RGS4, TNF-alpha) interacted with serious obstetric complications to influence risk for schizophrenia. A family-based study of transmission disequilibrium was conducted in 116 trios. Twenty-nine probands had at least one serious obstetric complication (OC) using the McNeil-Sjostrom Scale, and many of the OCs reported were associated with the potential for fetal hypoxia. Analyses were conducted using conditional logistic regression and a likelihood ratio test (LRT) between nested models was performed to assess significance. Of the 13 genes examined, four (AKT1 (three SNPs), BDNF (two SNPs), DTNBP1 (one SNP) and GRM3 (one SNP)) showed significant evidence for gene-by-environment interaction (LRT P-values ranged from 0.011 to 0.037). Although our sample size was modest and the power to detect interactions was limited, we report significant evidence for genes involved in neurovascular function or regulated by hypoxia interacting with the presence of serious obstetric complications to increase risk for schizophrenia.

Novel linkage to chromosome 20p using latent classes of psychotic illness in 270 Irish high-density families

BACKGROUND

Several lines of evidence suggest that the clinical heterogeneity of schizophrenia is due to genetic heterogeneity. Genetic heterogeneity may decrease the signal-to-noise ratio in linkage and association studies. Therefore, linkage studies of clinically homogeneous classes of psychotic illness may result in greater power to detect at least some loci.

METHODS

Latent class analysis was used to divide psychotic subjects from 270 Irish high-density families (N = 755) into six classes based on the Operational Criteria Checklist for Psychotic Illness. We heuristically call them Bipolar, Schizoaffective, Mania, Schizomania, Deficit Syndrome, and Core Schizophrenia. The latter four had prevalences of greater than .08 and were individually tested for linkage in a 10-cM nonparametric autosomal genomewide scan. Empirical significance was determined using 200 simulated genome scans.

RESULTS

Seven regions achieved empirical criteria for suggestive significance for at least one latent class: 5q23.2-q35.3, 8q13.1-q23.1, 10q23.33-q26.3, 12q21.2-q24.32, 19q13.32-q13.43, 20p13-q22.3, and 21q11.2-q22.3. Five of 200 simulated scans resulted in seven suggestively significant loci (experiment-wide p = .03). Furthermore, at 20p13-p12.2, the Mania and Schizomania classes individually achieved criteria, whereas Deficit Syndrome had a suggestive logarithm of the odds peak 28 cM centromeric to this locus.

CONCLUSIONS

Using empirically derived, clinically homogeneous phenotypes, four chromosomal regions were suggestively linked but provided little evidence of linkage using traditional operationalized criteria. This approach was particularly fruitful on chromosome 20, which had previously yielded little evidence of linkage. Future studies of psychiatric illness may increase their ability to detect linkage or association by using clinically homogeneous phenotypes.

Genetic variation in AKT1 is linked to dopamine-associated prefrontal cortical structure and function in humans

AKT1-dependent molecular pathways control diverse aspects of cellular development and adaptation, including interactions with neuronal dopaminergic signaling. If AKT1 has an impact on dopaminergic signaling, then genetic variation in AKT1 would be associated with brain phenotypes related to cortical dopaminergic function. Here, we provide evidence that a coding variation in AKT1 that affects protein expression in human B lymphoblasts influenced several brain measures related to dopaminergic function. Cognitive performance linked to frontostriatal circuitry, prefrontal physiology during executive function, and frontostriatal gray-matter volume on MRI were altered in subjects with the AKT1 variation. Moreover, on neuroimaging measures with a main effect of the AKT1 genotype, there was significant epistasis with a functional polymorphism (Val158Met) in catechol-O-methyltransferase [COMT], a gene that indexes cortical synaptic dopamine. This genetic interaction was consistent with the putative role of AKT1 in dopaminergic signaling. Supportive of an earlier tentative association of AKT1 with schizophrenia, we also found that this AKT1 variant was associated with risk for schizophrenia. These data implicate AKT1 in modulating human prefrontal-striatal structure and function and suggest that the mechanism of this effect may be coupled to dopaminergic signaling and relevant to the expression of psychosis.

Variants in the estrogen receptor alpha gene and its mRNA contribute to risk for schizophrenia

Estrogen modifies human emotion and cognition and impacts symptoms of schizophrenia. We hypothesized that the variation in the estrogen receptor alpha (ESR1) gene and cortical ESR1 mRNA is associated with schizophrenia. In a small case–control genetic association analysis of postmortem brain tissue, genotype CC (rs2234693) and haplotypes containing the C allele of a single-nucleotide polymorphism (SNP) in intron1 (PvuII) were more frequent in African American schizophrenics (P = 0.01–0.001). In a follow-up family-based association analysis, we found overtransmission of PvuII allele C and a PvuII C-containing haplotype (P = 0.01–0.03) to African American and Caucasian patients with schizophrenia. Schizophrenics with the ‘at risk’ PvuII genotype had lower ESR1 mRNA levels in the frontal cortex. Eighteen ESR1 splice variants and decreased frequencies of the wild-type ESR1 mRNA were detected in schizophrenia. In one patient, a unique ESR1 transcript with a genomic insert encoding a premature stop codon and a truncated ESR1 protein lacking most of the estrogen binding domain was the only transcript detected. Using a luciferase assay, we found that mRNA encoding a truncated ESR1 significantly attenuates gene expression at estrogen-response elements demonstrating a dominant negative function. An intron 6 SNP [rs2273207(G)] was associated with an ESR1 splice variant missing exon seven. The T allele of another intron 6 SNP was part of a 3′ haplotype less common in schizophrenia [rs2273206(T), rs2273207(G), rs2228480(G)]. Thus, the variation in the ESR1 gene is associated with schizophrenia and the mechanism of this association may involve alternative gene regulation and transcript processing.

Reduced DTNBP1 (dysbindin-1) mRNA in the hippocampal formation of schizophrenia patients

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.

Genetic variation in catechol-O-methyltransferase: effects on working memory in schizophrenic patients, their siblings, and healthy controls

BACKGROUND

Catechol-O-methyltransferase (COMT) val(108/158)met (rs4680) is thought to affect dopamine regulated prefrontal cortical activity during working memory (WM) tasks, and to weakly increase risk for developing schizophrenia. Recently, other single nucleotide polymorphisms (SNPs) across the gene have emerged as additional risk factors for schizophrenia: namely rs737865, rs165599, and rs2097603. In a large sample, we examined whether these SNPs affect WM.

METHODS

Schizophrenic probands (n = 325), their nonpsychotic siblings (n = 359), and normal control subjects (n = 330) completed tests of WM function. Data were analyzed with a series of mixed model analyses of variance (ANOVAs).

RESULTS

Val homozygotes performed most poorly on all conditions of the n-back, irrespective of diagnosis. Additionally, there was a trend towards a disease-only val(108/158)met effect on a test of attentional set-shifting; val homozygote probands performed most poorly. Significant or near-significant effects of rs737865 were found on all conditions of the n-back, with G homozygotes performing worst. There also was a disease-only COMT rs737865 effect on the 0-back. None of the other SNPs showed main effects by themselves. A haplotype constructed from promoter and val(108/158)met SNPs showed main effects on WM parameters, consistent with inverted U models of dopamine signaling.

CONCLUSIONS

We extended earlier findings of a val(108/158)met effect on WM function, and suggest that combinations of alleles within COMT may modulate the val(108/158)met effect in a nonlinear manner.

Risk for premenstrual dysphoric disorder is associated with genetic variation in ESR1, the estrogen receptor alpha gene

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.

Significant correlation in linkage signals from genome-wide scans of schizophrenia and schizotypy

Prior family and adoption studies have suggested a genetic relationship between schizophrenia and schizotypy. However, this has never been verified using linkage methods. We therefore attempted to test for a correlation in linkage signals from genome-wide scans of schizophrenia and schizotypy. The Irish study of high-density schizophrenia families comprises 270 families with at least two members with schizophrenia or poor-outcome schizoaffective disorder (n=637). Non-psychotic relatives were assessed using the structured interview for schizotypy (n=746). A 10-cM multipoint, non-parametric, autosomal genome-wide scan of schizophrenia was performed in Merlin. A scan of a quantitative trait comprising ratings of DSM-III-R criteria for schizotypal personality disorder in non-psychotic relatives was also performed. Schizotypy logarithm of the odds (LOD) scores were regressed onto schizophrenia LOD scores at all loci, with adjustment for spatial autocorrelation. To assess empirical significance, this was also carried out using 1000 null scans of schizotypy. The number of jointly linked loci in the real data was compared to distribution of jointly linked loci in the null scans. No markers were suggestively linked to schizotypy based on strict Lander-Kruglyak criteria. Schizotypy LODs predicted schizophrenia LODs above chance expectation genome wide (empirical P=0.04). Two and four loci yielded nonparametric LOD (NPLs) >1.0 and >0.75, respectively, for both schizophrenia and schizotypy (genome-wide empirical P=0.04 and 0.02, respectively). These results suggest that at least a subset of schizophrenia susceptibility genes also affects schizotypy in non-psychotic relatives. Power may therefore be increased in molecular genetic studies of schizophrenia if they incorporate measures of schizotypy in non-psychotic relatives.

Alpha7 nicotinic acetylcholine receptor mRNA expression and binding in postmortem human brain are associated with genetic variation in neuregulin 1

Studies in cell culture and in animals suggest that neuregulin 1 (NRG1), a probable schizophrenia susceptibility gene, regulates the expression of the alpha7 nicotinic acetylcholine receptors (nAChRs). We hypothesized that schizophrenia-associated allelic variations within the NRG1 gene, via their effects on NRG1 isoform expression, would be associated with alterations in nAChR alpha7 receptor levels. We examined the effects of four disease-associated single-nucleotide polymorphisms (SNPs) in the 5' region of the NRG1 gene on nAChR alpha7 mRNA transcript expression in both the dorsolateral prefrontal cortex (DLPFC) and hippocampus of normal controls and patients with schizophrenia using quantitative real-time PCR. NRG1 risk alleles at SNPs SNP8NRG221132 and rs6994992 predicted significantly lower nAChR alpha7 mRNA expression in the DLPFC. Haplotypes containing the risk alleles at the above SNPs were also associated with lower expression of nAChR alpha7 in the DLPFC. The genotype effect for rs6994992 and the haplotype effect were more pronounced within the schizophrenic patient group. To determine whether receptor levels follow that of mRNA expression, we performed receptor binding and autoradiography using [(125)I] alpha-bungarotoxin in the DLPFC. Consistent with the mRNA findings, we found a decrease in binding in risk allele carriers of SNP8NRG221132 as compared with heterozygous individuals. Together, these results suggest that the molecular mechanism of the association between NRG1 risk alleles and schizophrenia may include down-regulation of nAChR alpha7 expression.

Allelic variation in GAD1 (GAD67) is associated with schizophrenia and influences cortical function and gene expression

Cortical GABAergic dysfunction has been implicated as a key component of the pathophysiology of schizophrenia and decreased expression of the gamma-aminobutyric acid (GABA) synthetic enzyme glutamic acid decarboxylase 67 (GAD(67)), encoded by GAD1, is found in schizophrenic post-mortem brain. We report evidence of distorted transmission of single-nucleotide polymorphism (SNP) alleles in two independent schizophrenia family-based samples. In both samples, allelic association was dependent on the gender of the affected offspring, and in the Clinical Brain Disorders Branch/National Institute of Mental Health (CBDB/NIMH) sample it was also dependent on catechol-O-methyltransferase (COMT) Val158Met genotype. Quantitative transmission disequilibrium test analyses revealed that variation in GAD1 influenced multiple domains of cognition, including declarative memory, attention and working memory. A 5' flanking SNP affecting cognition in the families was also associated in unrelated healthy individuals with inefficient BOLD functional magnetic resonance imaging activation of dorsal prefrontal cortex (PFC) during a working memory task, a physiologic phenotype associated with schizophrenia and altered cortical inhibition. In addition, a SNP in the 5' untranslated (and predicted promoter) region that also influenced cognition was associated with decreased expression of GAD1 mRNA in the PFC of schizophrenic brain. Finally, we observed evidence of statistical epistasis between two SNPs in COMT and SNPs in GAD1, suggesting a potential biological synergism leading to increased risk. These coincident results implicate GAD1 in the etiology of schizophrenia and suggest that the mechanism involves altered cortical GABA inhibitory activity, perhaps modulated by dopaminergic function.

A genome-wide scan for modifier loci in schizophrenia

The purpose of this study was to detect genetic loci that influence clinical features of, but not necessarily susceptibility to, psychotic illness. In the Irish Study of High-Density Schizophrenia Families (n = 270 families, n = 1,408 individuals), subjects with non-affective psychosis were rated using the Operational Criteria Checklist for Psychotic Illness. Factor analysis identified hallucinations, delusions, and negative, manic, and depressive symptom factors. We performed autosomal genome-wide multipoint non-parametric quantitative trait locus linkage analysis, in affected individuals only, using these five factors, as well as age at onset, and course of illness. Determination of empirical significance and correction for multiple testing was implemented using 200 simulated genome scans. We also tested for pleiotropic loci by examining the sums of -log(10)'s of the empirical P values of multiple traits in selected regions. LODs of 2.42 and 2.35 were obtained near D9S934 (9q33.1) and D14S587 (14q24.2), respectively, for course of illness, and of 2.26 between D6S1040-D6S2420 (6q23.1-25.1) and age at onset. No other regions met criteria for suggestive linkage to any one trait. No loci were significant after correction for multiple testing. On 6q, however, the joint linkage of age of onset, course, delusions, and depressive symptoms resulted in a genome-wide P = 0.06. We conclude that genes located near 9q33.1 and 14q24.2 may modify the clinical course and severity of schizophrenia. A gene in 6q may affect several clinical features of illness.