Common schizophrenia alleles are enriched in mutation-intolerant genes and in regions under strong background selection

The effect of the DISC1 Ser704Cys polymorphism on striatal dopamine synthesis capacity: an [18F]-DOPA PET study

Whilst the role of the Disrupted-in-Schizophrenia 1 (DISC1) gene in the aetiology of major mental illnesses is debated, the characterization of its function lends it credibility as a candidate. A key aspect of this functional characterization is the determination of the role of common non-synonymous polymorphisms on normal variation within these functions. The common allele (A) of the DISC1 single-nucleotide polymorphism (SNP) rs821616 encodes a serine (ser) at the Ser704Cys polymorphism, and has been shown to increase the phosphorylation of extracellular signal-regulated protein Kinases 1 and 2 (ERK1/2) that stimulate the phosphorylation of tyrosine hydroxylase, the rate-limiting enzyme for dopamine biosynthesis. We therefore set out to test the hypothesis that human ser (A) homozygotes would show elevated dopamine synthesis capacity compared with cysteine (cys) homozygotes and heterozygotes (TT and AT) for rs821616. [18F]-DOPA positron emission tomography (PET) was used to index striatal dopamine synthesis capacity as the influx rate constant Kicer in healthy volunteers DISC1 rs821616 ser homozygotes (N = 46) and healthy volunteers DISC1 rs821616 cys homozygotes and heterozygotes (N = 56), matched for age, gender, ethnicity and using three scanners. We found DISC1 rs821616 ser homozygotes exhibited a significantly higher striatal Kicer compared with cys homozygotes and heterozygotes (P = 0.012) explaining 6.4% of the variance (partial η2 = 0.064). Our finding is consistent with its previous association with heightened activation of ERK1/2, which stimulates tyrosine hydroxylase activity for dopamine synthesis. This could be a potential mechanism mediating risk for psychosis, lending further credibility to the fact that DISC1 is of functional interest in the aetiology of major mental illness.

Common genetic variants contribute to risk of rare severe neurodevelopmental disorders

There are thousands of rare human disorders that are caused by single deleterious, protein-coding genetic variants¹. However, patients with the same genetic defect can have different clinical presentations^2-4, and some individuals who carry known disease-causing variants can appear unaffected⁵. Here, to understand what explains these differences, we study a cohort of 6,987 children assessed by clinical geneticists to have severe neurodevelopmental disorders such as global developmental delay and autism, often in combination with abnormalities of other organ systems. Although the genetic causes of these neurodevelopmental disorders are expected to be almost entirely monogenic, we show that 7.7% of variance in risk is attributable to inherited common genetic variation. We replicated this genome-wide common variant burden by showing, in an independent sample of 728 trios (comprising a child plus both parents) from the same cohort, that this burden is over-transmitted from parents to children with neurodevelopmental disorders. Our common-variant signal is significantly positively correlated with genetic predisposition to lower educational attainment, decreased intelligence and risk of schizophrenia. We found that common-variant risk was not significantly different between individuals with and without a known protein-coding diagnostic variant, which suggests that common-variant risk affects patients both with and without a monogenic diagnosis. In addition, previously published common-variant scores for autism, height, birth weight and intracranial volume were all correlated with these traits within our cohort, which suggests that phenotypic expression in individuals with monogenic disorders is affected by the same variants as in the general population. Our results demonstrate that common genetic variation affects both overall risk and clinical presentation in neurodevelopmental disorders that are typically considered to be monogenic.

Discovery of natural product inhibitors of phosphodiesterase 10A as novel therapeutic drug for schizophrenia using a multistep virtual screening

The major complaint that most of the schizophrenic patients' face is the cognitive impairment which affects the patient's quality of life. The current antipsychotic drugs treat only the positive symptoms without alleviating the negative or cognitive symptoms of the disease. In addition, the existing therapies are known to produce extrapyramidal side effects that affect the patient adherence to the treatment. PDE10A inhibitor is the new therapeutic approach which has been proven to be effective in alleviating the negative and cognitive symptoms of the disease. A number of PDE10A inhibitors have been developed, but no inhibitor has made it beyond the clinical trials so far. Thus, the present study has been conducted to identify a PDE10A inhibitor from natural sources to be used as a lead compound for the designing of novel selective PDE10A inhibitors. Ligand and structure-based pharmacophore models for PDE10A inhibitors were generated and employed for virtual screening of universal natural products database. From the virtual screening results, 37 compounds were docked into the active site of the PDE10A. Out of 37 compounds, three inhibitors showed the highest affinity for PDE10A where UNPD216549 showed the lowest binding energy and has been chosen as starting point for designing of novel PDE10A inhibitors. The structure-activity-relationship studies assisted in designing of selective PDE10A inhibitors. The optimization of the substituents on the phenyl ring resulted in 26 derivatives with lower binding energy with PDE10A as compared to the lead compound. Among these, MA 8 and MA 98 exhibited the highest affinity for PDE10A with binding energy (-10.90 Kcal/mol).

Tracing Early Neurodevelopment in Schizophrenia with Induced Pluripotent Stem Cells

Schizophrenia (SCZ) is a devastating mental disorder that is characterized by distortions in thinking, perception, emotion, language, sense of self, and behavior. Epidemiological evidence suggests that subtle perturbations in early neurodevelopment increase later susceptibility for disease, which typically manifests in adolescence to early adulthood. Early perturbations are thought to be significantly mediated through incompletely understood genetic risk factors. The advent of induced pluripotent stem cell (iPSC) technology allows for the in vitro analysis of disease-relevant neuronal cell types from the early stages of human brain development. Since iPSCs capture each donor's genotype, comparison between neuronal cells derived from healthy and diseased individuals can provide important insights into the molecular and cellular basis of SCZ. In this review, we discuss results from an increasing number of iPSC-based SCZ/control studies that highlight alterations in neuronal differentiation, maturation, and neurotransmission in addition to perturbed mitochondrial function and micro-RNA expression. In light of this remarkable progress, we consider also ongoing challenges from the field of iPSC-based disease modeling that call for further improvements on the generation and design of patient-specific iPSC studies to ultimately progress from basic studies on SCZ to tailored treatments.

DISC1 regulates N-methyl-D-aspartate receptor dynamics: abnormalities induced by a Disc1 mutation modelling a translocation linked to major mental illness

The neuromodulatory gene DISC1 is disrupted by a t(1;11) translocation that is highly penetrant for schizophrenia and affective disorders, but how this translocation affects DISC1 function is incompletely understood. N-methyl-D-aspartate receptors (NMDAR) play a central role in synaptic plasticity and cognition, and are implicated in the pathophysiology of schizophrenia through genetic and functional studies. We show that the NMDAR subunit GluN2B complexes with DISC1-associated trafficking factor TRAK1, while DISC1 interacts with the GluN1 subunit and regulates dendritic NMDAR motility in cultured mouse neurons. Moreover, in the first mutant mouse that models DISC1 disruption by the translocation, the pool of NMDAR transport vesicles and surface/synaptic NMDAR expression are increased. Since NMDAR cell surface/synaptic expression is tightly regulated to ensure correct function, these changes in the mutant mouse are likely to affect NMDAR signalling and synaptic plasticity. Consistent with these observations, RNASeq analysis of the translocation carrier-derived human neurons indicates abnormalities of excitatory synapses and vesicle dynamics. RNASeq analysis of the human neurons also identifies many differentially expressed genes previously highlighted as putative schizophrenia and/or depression risk factors through large-scale genome-wide association and copy number variant studies, indicating that the translocation triggers common disease pathways that are shared with unrelated psychiatric patients. Altogether, our findings suggest that translocation-induced disease mechanisms are likely to be relevant to mental illness in general, and that such disease mechanisms include altered NMDAR dynamics and excitatory synapse function. This could contribute to the cognitive disorders displayed by translocation carriers.

Characterizing the Relation Between Expression QTLs and Complex Traits: Exploring the Role of Tissue Specificity

Measurement of gene expression levels and detection of eQTLs (expression quantitative trait loci) are difficult in tissues with limited sample availability, such as the brain. However, eQTL overlap between tissues might be high, which would allow for inference of eQTL functioning in the brain via eQTLs detected in readily accessible tissues, e.g. whole blood. Applying Stratified Linkage Disequilibrium Score Regression (SLDSR), we quantified the enrichment in polygenic signal of blood and brain eQTLs in genome-wide association studies (GWAS) of 11 complex traits. We looked at eQTLs discovered in 44 tissues by the Genotype-Tissue Expression (GTEx) consortium and two other large representative studies, and found no tissue-specific eQTL effects. Next, we integrated the GTEx eQTLs with regions associated with tissue-specific histone modifiers, and interrogated their effect on rheumatoid arthritis and schizophrenia. We observed substantially enriched effects of eQTLs located inside regions bearing modification H3K4me1 on schizophrenia, but not rheumatoid arthritis, and not tissue-specific. Finally, we extracted eQTLs associated with tissue-specific differentially expressed genes and determined their effects on rheumatoid arthritis and schizophrenia, these analysis revealed limited enrichment of eQTLs associated with gene specifically expressed in specific tissues. Our results pointed to strong enrichment of eQTLs in their effect on complex traits, without evidence for tissue-specific effects. Lack of tissue-specificity can be either due to a lack of statistical power or due to the true absence of tissue-specific effects. We conclude that eQTLs are strongly enriched in GWAS signal and that the enrichment is not specific to the eQTL discovery tissue. Until sample sizes for eQTL discovery grow sufficiently large, working with relatively accessible tissues as proxy for eQTL discovery is sensible and restricting lookups for GWAS hits to a specific tissue for which limited samples are available might not be advisable.

Polygenic risk score for schizophrenia and structural brain connectivity in older age: A longitudinal connectome and tractography study

Higher polygenic risk score for schizophrenia (szPGRS) has been associated with lower cognitive function and might be a predictor of decline in brain structure in apparently healthy populations. Age-related declines in structural brain connectivity-measured using white matter diffusion MRI -are evident from cross-sectional data. Yet, it remains unclear how graph theoretical metrics of the structural connectome change over time, and whether szPGRS is associated with differences in ageing-related changes in human brain connectivity. Here, we studied a large, relatively healthy, same-year-of-birth, older age cohort over a period of 3 years (age ∼ 73 years, N = 731; age ∼76 years, N = 488). From their brain scans we derived tract-averaged fractional anisotropy (FA) and mean diffusivity (MD), and network topology properties. We investigated the cross-sectional and longitudinal associations between these structural brain variables and szPGRS. Higher szPGRS showed significant associations with longitudinal increases in MD in the splenium (β = 0.132, pFDR = 0.040), arcuate (β = 0.291, pFDR = 0.040), anterior thalamic radiations (β = 0.215, pFDR = 0.040) and cingulum (β = 0.165, pFDR = 0.040). Significant declines over time were observed in graph theory metrics for FA-weighted networks, such as mean edge weight (β = -0.039, pFDR = 0.048) and strength (β = -0.027, pFDR = 0.048). No significant associations were found between szPGRS and graph theory metrics. These results are consistent with the hypothesis that szPGRS confers risk for ageing-related degradation of some aspects of structural connectivity.

CACNA1C: Association With Psychiatric Disorders, Behavior, and Neurogenesis

Large-scale genome-wide association studies have consistently shown that genetic variation in CACNA1C, a gene that encodes calcium voltage-gated channel subunit alpha1C, increases risk for psychiatric disorders. CACNA1C encodes the Cav1.2 subunit of voltage-gated calcium channels, which themselves have been functionally implicated in a broad spectrum of neuropsychiatric syndromes. Research has concentrated on uncovering the underlying biological mechanisms that could be responsible for this increased risk. This review presents an overview of recent findings regarding Cacna1c variation in animal models, particularly focusing on behavioral phenotypes associated with neurodevelopmental disorders such as cognition, anxiety and depressive phenotypes, and fear conditioning. The impact of reduced gene dosage of Cacna1c on adult hippocampal neurogenesis is also assessed, including new data from a novel Cacna1c+/- rat model.

Genes associated with anhedonia: a new analysis in a large clinical trial (GENDEP)

A key feature of major depressive disorder (MDD) is anhedonia, which is a predictor of response to antidepressant treatment. In order to shed light on its genetic underpinnings, we conducted a genome-wide association study (GWAS) followed by investigation of biological pathway enrichment using an anhedonia dimension for 759 patients with MDD in the GENDEP study. The GWAS identified 18 SNPs associated at genome-wide significance with the top one being an intronic SNP (rs9392549) in PRPF4B (pre-mRNA processing factor 4B) located on chromosome 6 (P = 2.07 × 10-9) while gene-set enrichment analysis returned one gene ontology term, axon cargo transport (GO: 0008088) with a nominally significant P value (1.15 × 10-5). Furthermore, our exploratory analysis yielded some interesting, albeit not statistically significant genetic correlation with Parkinson's Disease and nucleus accumbens gray matter. In addition, polygenic risk scores (PRSs) generated from our association analysis were found to be able to predict treatment efficacy of the antidepressants in this study. In conclusion, we found some markers significantly associated with anhedonia, and some suggestive findings of related pathways and biological functions, which could be further investigated in other studies.

Genetic Evidence for the Association between Schizophrenia and Breast Cancer

OBJECTIVE

To estimate the potential effect of schizophrenia on breast cancer risk in women, we performed a two-sample Mendelian randomization (MR) study.

METHODS

The instrumental variables comprised 170 uncorrelated and non-pleiotropic single nucleotide polymorphisms (SNPs) that are significantly associated with schizophrenia risk in genome-wide association studies in 105,000 European descent individuals of the Psychiatric Genomics Consortium (http://www.med.unc.edu/pgc/) and the United Kingdom Clozapine Clinic. The association between these SNPs determined schizophrenia and breast cancer risk was estimated in approximately 229,000 European descent females from the Breast Cancer Association Consortium using the inverse-variance weighted and the weighted median MR methods.

RESULTS

We found that the genetically-predicted risk of schizophrenia was associated with increased breast cancer risk (under a random-effects model: odds ratio per 1 unit increase in log odds of schizophrenia = 1.04, 95% confidence interval: 1.02-1.06, p = 5.6 × 10-5). Similar significant associations were observed in analyses using a weighted median model and sensitivity analysis excluding six SNPs with genotype imputation score of less than 0.8, as well as analyses stratified by estrogen receptor status of breast cancer.

CONCLUSION

Our findings implicate a modest increased risk for breast cancer in genetically determined schizophrenic females.

Evaluation of chromatin accessibility in prefrontal cortex of individuals with schizophrenia

Schizophrenia genome-wide association studies have identified >150 regions of the genome associated with disease risk, yet there is little evidence that coding mutations contribute to this disorder. To explore the mechanism of non-coding regulatory elements in schizophrenia, we performed ATAC-seq on adult prefrontal cortex brain samples from 135 individuals with schizophrenia and 137 controls, and identified 118,152 ATAC-seq peaks. These accessible chromatin regions in the brain are highly enriched for schizophrenia SNP heritability. Accessible chromatin regions that overlap evolutionarily conserved regions exhibit an even higher heritability enrichment, indicating that sequence conservation can further refine functional risk variants. We identify few differences in chromatin accessibility between cases and controls, in contrast to thousands of age-related differential accessible chromatin regions. Altogether, we characterize chromatin accessibility in the human prefrontal cortex, the effect of schizophrenia and age on chromatin accessibility, and provide evidence that our dataset will allow for fine mapping of risk variants.

Genome-wide association study results for educational attainment aid in identifying genetic heterogeneity of schizophrenia

Higher educational attainment (EA) is negatively associated with schizophrenia (SZ). However, recent studies found a positive genetic correlation between EA and SZ. We investigate possible causes of this counterintuitive finding using genome-wide association study results for EA and SZ (N = 443,581) and a replication cohort (1169 controls; 1067 cases) with deeply phenotyped SZ patients. We find strong genetic dependence between EA and SZ that cannot be explained by chance, linkage disequilibrium, or assortative mating. Instead, several genes seem to have pleiotropic effects on EA and SZ, but without a clear pattern of sign concordance. Using EA as a proxy phenotype, we isolate FOXO6 and SLITRK1 as novel candidate genes for SZ. Our results reveal that current SZ diagnoses aggregate over at least two disease subtypes: one part resembles high intelligence and bipolar disorder (BIP), while the other part is a cognitive disorder that is independent of BIP.

Genome wide analysis of rare copy number variations in alcohol abuse or dependence

Genetics plays an important role in alcohol abuse/dependence. Its heritability has been estimated as 45-65%. Rare copy number variations (CNVs) have been confirmed as relevant genetic factors in other neuropsychiatric disorders, such as autism spectrum disorders, schizophrenia, epilepsy, or Tourette syndrome. In the present study, we analyzed the role of rare CNVs affecting exons of coding genes in a sample from Northwest Spain genotyped using the Illumina Infinium PsychArray Beadchip. After rigorous genotyping quality control procedure, 712 patients with alcohol abuse or dependence and 804 controls were used for CNV detection. CNV calling was performed using PennCNV and cnvPartition, and analyses were restricted to CNVs of at least 100 kb and including at least 10 single nucleotide polymorphisms. Logistic regression was used to test for the effect of CNV as well as number of genes affected by CNVs on case/control status, after adjustment for demographic and experimental covariates. We have found an excess of deletions (p = 0.008) and genes affected by deletions (p = 0.017) in cases. This effect was restricted to the 14.8% of affected genes that are intolerant to loss-of-function mutations (gene count p = 0.009). The importance of this subset of genes is emerging in other psychiatric disorders of neurodevelopmental origin, suggesting that disturbance in neurodevelopment mediated by genetic alterations may be a risk factor for alcohol use disorder.

Genes regulated by SATB2 during neurodevelopment contribute to schizophrenia and educational attainment

SATB2 is associated with schizophrenia and is an important transcription factor regulating neocortical organization and circuitry. Rare mutations in SATB2 cause a syndrome that includes developmental delay, and mouse studies identify an important role for SATB2 in learning and memory. Interacting partners BCL11B and GATAD2A are also schizophrenia risk genes indicating that other genes interacting with or are regulated by SATB2 are making a contribution to schizophrenia and cognition. We used data from Satb2 mouse models to generate three gene-sets that contain genes either functionally related to SATB2 or targeted by SATB2 at different stages of development. Each was tested for enrichment using the largest available genome-wide association studies (GWAS) datasets for schizophrenia and educational attainment (EA) and enrichment analysis was also performed for schizophrenia and other neurodevelopmental disorders using data from rare variant sequencing studies. These SATB2 gene-sets were enriched for genes containing common variants associated with schizophrenia and EA, and were enriched for genes containing rare variants reported in studies of schizophrenia, autism and intellectual disability. In the developing cortex, genes targeted by SATB2 based on ChIP-seq data, and functionally affected when SATB2 is not expressed based on differential expression analysis using RNA-seq data, show strong enrichment for genes associated with EA. For genes expressed in the hippocampus or at the synapse, those targeted by SATB2 are more strongly enriched for genes associated EA than gene-sets not targeted by SATB2. This study demonstrates that single gene findings from GWAS can provide important insights to pathobiological processes. In this case we find evidence that genes influenced by SATB2 and involved in synaptic transmission, axon guidance and formation of the corpus callosum are contributing to schizophrenia and cognition.

Schizophrenia is a complex disorder caused by many genes. Using new gene discoveries to understand pathobiology is a foundation for development of new treatments. Current drugs for schizophrenia are only partially effective and do not treat cognitive deficits, which are key factors for explaining disability, leading to unemployment, homelessness and social isolation. Genome-wide association studies (GWAS) of schizophrenia have been effective at identifying individual SNPs and genes that contribute to risk but have struggled to immediately uncover the bigger picture of the underlying biology of the disorder. Here we take an individual gene identified in a schizophrenia GWAS called SATB2, which on its own is a very important regulator of brain development. We use functional genomics data from mouse studies to identify sets of others genes that are influenced by SATB2 during development. We show that these gene sets are enriched for common variants associated with schizophrenia and educational attainment (used as a proxy for cognition), and for rare variants that increase risk of various neurodevelopmental disorders. This study provides evidence that the molecular mechanisms that underpin schizophrenia and cognitive function include disruption of biological processes influenced by SATB2 as the brain is being organized and wired during development.

Estimating SNP-Based Heritability and Genetic Correlation in Case-Control Studies Directly and with Summary Statistics

Methods that estimate SNP-based heritability and genetic correlations from genome-wide association studies have proven to be powerful tools for investigating the genetic architecture of common diseases and exposing unexpected relationships between disorders. Many relevant studies employ a case-control design, yet most methods are primarily geared toward analyzing quantitative traits. Here we investigate the validity of three common methods for estimating SNP-based heritability and genetic correlation between diseases. We find that the phenotype-correlation-genotype-correlation (PCGC) approach is the only method that can estimate both quantities accurately in the presence of important non-genetic risk factors, such as age and sex. We extend PCGC to work with arbitrary genetic architectures and with summary statistics that take the case-control sampling into account, and we demonstrate that our new method, PCGC-s, accurately estimates both SNP-based heritability and genetic correlations and can be applied to large datasets without requiring individual-level genotypic or phenotypic information. Finally, we use PCGC-s to estimate the genetic correlation between schizophrenia and bipolar disorder and demonstrate that previous estimates are biased, partially due to incorrect handling of sex as a strong risk factor.

A Novel Ultrasensitive In Situ Hybridization Approach to Detect Short Sequences and Splice Variants with Cellular Resolution

Investigating the expression of RNAs that differ by short or single nucleotide sequences at a single-cell level in tissue has been limited by the sensitivity and specificity of in situ hybridization (ISH) techniques. Detection of short isoform-specific sequences requires RNA isolation for PCR analysis-an approach that loses the regional and cell-type-specific distribution of isoforms. Having the capability to distinguish the differential expression of RNA variants in tissue is critical because alterations in mRNA splicing and editing, as well as coding single nucleotide polymorphisms, have been associated with numerous cancers, neurological and psychiatric disorders. Here we introduce a novel highly sensitive single-probe colorimetric/fluorescent ISH approach that targets short exon/exon RNA splice junctions using single-pair oligonucleotide probes (~ 50 bp). We use this approach to investigate, with single-cell resolution, the expression of four transcripts encoding the neuregulin (NRG) receptor ErbB4 that differ by alternative splicing of exons encoding two juxtamembrane (JMa/JMb) and two cytoplasmic (CYT-1/CYT-2) domains that alter receptor stability and signaling modes, respectively. By comparing ErbB4 hybridization on sections from wild-type and ErbB4 knockout mice (missing exon 2), we initially demonstrate that single-pair probes provide the sensitivity and specificity to visualize and quantify the differential expression of ErbB4 isoforms. Using cell-type-specific GFP reporter mice, we go on to demonstrate that expression of ErbB4 isoforms differs between neurons and oligodendrocytes, and that this differential expression of ErbB4 isoforms is evolutionarily conserved to humans. This single-pair probe ISH approach, known as BaseScope, could serve as an invaluable diagnostic tool to detect alternative spliced isoforms, and potentially single base polymorphisms, associated with disease.

Genetic identification of brain cell types underlying schizophrenia

With few exceptions, the marked advances in knowledge about the genetic basis of schizophrenia have not converged on findings that can be confidently used for precise experimental modeling. By applying knowledge of the cellular taxonomy of the brain from single-cell RNA sequencing, we evaluated whether the genomic loci implicated in schizophrenia map onto specific brain cell types. We found that the common-variant genomic results consistently mapped to pyramidal cells, medium spiny neurons (MSNs) and certain interneurons, but far less consistently to embryonic, progenitor or glial cells. These enrichments were due to sets of genes that were specifically expressed in each of these cell types. We also found that many of the diverse gene sets previously associated with schizophrenia (genes involved in synaptic function, those encoding mRNAs that interact with FMRP, antipsychotic targets, etc.) generally implicated the same brain cell types. Our results suggest a parsimonious explanation: the common-variant genetic results for schizophrenia point at a limited set of neurons, and the gene sets point to the same cells. The genetic risk associated with MSNs did not overlap with that of glutamatergic pyramidal cells and interneurons, suggesting that different cell types have biologically distinct roles in schizophrenia.

A data-driven investigation of relationships between bipolar psychotic symptoms and schizophrenia genome-wide significant genetic loci

The etiologies of bipolar disorder (BD) and schizophrenia include a large number of common risk alleles, many of which are shared across the disorders. BD is clinically heterogeneous and it has been postulated that the pattern of symptoms is in part determined by the particular risk alleles carried, and in particular, that risk alleles also confer liability to schizophrenia influence psychotic symptoms in those with BD. To investigate links between psychotic symptoms in BD and schizophrenia risk alleles we employed a data-driven approach in a genotyped and deeply phenotyped sample of subjects with BD. We used sparse canonical correlation analysis (sCCA) (Witten, Tibshirani, & Hastie, ) to analyze 30 psychotic symptoms, assessed with the OPerational CRITeria checklist, and 82 independent genome-wide significant single nucleotide polymorphisms (SNPs) identified by the Schizophrenia Working group of the Psychiatric Genomics Consortium for which we had data in our BD sample (3,903 subjects). As a secondary analysis, we applied sCCA to larger groups of SNPs, and also to groups of symptoms defined according to a published factor analyses of schizophrenia. sCCA analysis based on individual psychotic symptoms revealed a significant association (p = .033), with the largest weights attributed to a variant on chromosome 3 (rs11411529), chr3:180594593, build 37) and delusions of influence, bizarre behavior and grandiose delusions. sCCA analysis using the same set of SNPs supported association with the same SNP and the group of symptoms defined "factor 3" (p = .012). A significant association was also observed to the "factor 3" phenotype group when we included a greater number of SNPs that were less stringently associated with schizophrenia; although other SNPs contributed to the significant multivariate association result, the greatest weight remained assigned to rs11411529. Our results suggest that the canonical correlation is a useful tool to explore phenotype-genotype relationships. To the best of our knowledge, this is the first study to apply this approach to complex, polygenic psychiatric traits. The sparse canonical correlation approach offers the potential to include a larger number of fine-grained systematic descriptors, and to include genetic markers associated with other disorders that are genetically correlated with BD.

Rare-Variant Studies to Complement Genome-Wide Association Studies

Genome-wide association studies (GWASs) have revolutionized human disease genetics by discovering tens of thousands of associations between common variants and complex diseases. In parallel, huge technological advances in DNA sequencing have made it possible to measure and analyze rare variation in populations. This review considers these two stories and how they have come together. We first review the history of GWASs and sequencing. We then consider how to understand the biological mechanisms that drive signals of strong association in the absence of rare-variant studies. We describe how rare-variant studies complement these approaches and highlight both data generation and statistical challenges in their interpretation. Finally, we consider how certain special study designs, such as those for families and isolated populations, fit in this paradigm.

Rare disruptive variants in the DISC1 Interactome and Regulome: association with cognitive ability and schizophrenia

Schizophrenia (SCZ), bipolar disorder (BD) and recurrent major depressive disorder (rMDD) are common psychiatric illnesses. All have been associated with lower cognitive ability, and show evidence of genetic overlap and substantial evidence of pleiotropy with cognitive function and neuroticism. Disrupted in schizophrenia 1 (DISC1) protein directly interacts with a large set of proteins (DISC1 Interactome) that are involved in brain development and signaling. Modulation of DISC1 expression alters the expression of a circumscribed set of genes (DISC1 Regulome) that are also implicated in brain biology and disorder. Here we report targeted sequencing of 59 DISC1 Interactome genes and 154 Regulome genes in 654 psychiatric patients and 889 cognitively-phenotyped control subjects, on whom we previously reported evidence for trait association from complete sequencing of the DISC1 locus. Burden analyses of rare and singleton variants predicted to be damaging were performed for psychiatric disorders, cognitive variables and personality traits. The DISC1 Interactome and Regulome showed differential association across the phenotypes tested. After family-wise error correction across all traits (FWERacross), an increased burden of singleton disruptive variants in the Regulome was associated with SCZ (FWERacross P=0.0339). The burden of singleton disruptive variants in the DISC1 Interactome was associated with low cognitive ability at age 11 (FWERacross P=0.0043). These results identify altered regulation of schizophrenia candidate genes by DISC1 and its core Interactome as an alternate pathway for schizophrenia risk, consistent with the emerging effects of rare copy number variants associated with intellectual disability.

Neuropsychiatric disease-associated genetic variants of the dopamine transporter display heterogeneous molecular phenotypes

Genetic factors are known to significantly contribute to the etiology of psychiatric diseases such as attention deficit hyperactivity disorder (ADHD) and autism spectrum and bipolar disorders, but the underlying molecular processes remain largely elusive. The dopamine transporter (DAT) has received continuous attention as a potential risk factor for psychiatric disease, as it is critical for dopamine homeostasis and serves as principal target for ADHD medications. Constrain metrics for the DAT-encoding gene, solute carrier family 6 member 3 (SLC6A3), indicate that missense mutations are under strong negative selection, pointing to pathophysiological outcomes when DAT function is compromised. Here, we systematically characterized six rare genetic variants of DAT (I312F, T356M, D421N, A559V, E602G, and R615C) identified in patients with neuropsychiatric disorders. We evaluated dopamine uptake and ligand interactions, along with ion coordination and electrophysiological properties, to elucidate functional phenotypes, and applied Zn²⁺ exposure and a substituted cysteine-accessibility approach to identify shared structural changes. Three variants (I312F, T356M, and D421N) exhibited impaired dopamine uptake associated with changes in ligand binding, ion coordination, and distinct conformational disturbances. Remarkably, we found that all three variants displayed gain-of-function electrophysiological phenotypes. I312F mediated an increased uncoupled anion conductance previously suggested to modulate neuronal excitability. T356M and D421N both mediated a cocaine-sensitive leakage of cations, which for T356M was potentiated by Zn²⁺, concurrent with partial functional rescue. Collectively, our findings support that gain of disruptive functions due to missense mutations in SLC6A3 may be key to understanding how dopaminergic dyshomeostasis arises in heterozygous carriers.

Altered DNA methylation associated with a translocation linked to major mental illness

Recent work has highlighted a possible role for altered epigenetic modifications, including differential DNA methylation, in susceptibility to psychiatric illness. Here, we investigate blood-based DNA methylation in a large family where a balanced translocation between chromosomes 1 and 11 shows genome-wide significant linkage to psychiatric illness. Genome-wide DNA methylation was profiled in whole-blood-derived DNA from 41 individuals using the Infinium HumanMethylation450 BeadChip (Illumina Inc., San Diego, CA). We found significant differences in DNA methylation when translocation carriers (n = 17) were compared to related non-carriers (n = 24) at 13 loci. All but one of the 13 significant differentially methylated positions (DMPs) mapped to the regions surrounding the translocation breakpoints. Methylation levels of five DMPs were associated with genotype at SNPs in linkage disequilibrium with the translocation. Two of the five genes harbouring significant DMPs, DISC1 and DUSP10, have been previously shown to be differentially methylated in schizophrenia. Gene Ontology analysis revealed enrichment for terms relating to neuronal function and neurodevelopment among the genes harbouring the most significant DMPs. Differentially methylated region (DMR) analysis highlighted a number of genes from the MHC region, which has been implicated in psychiatric illness previously through genetic studies. We show that inheritance of a translocation linked to major mental illness is associated with differential DNA methylation at loci implicated in neuronal development/function and in psychiatric illness. As genomic rearrangements are over-represented in individuals with psychiatric illness, such analyses may be valuable more widely in the study of these conditions.

Association Between Schizophrenia-Related Polygenic Liability and the Occurrence and Level of Mood-Incongruent Psychotic Symptoms in Bipolar Disorder

Importance

Bipolar disorder (BD) overlaps schizophrenia in its clinical presentation and genetic liability. Alternative approaches to patient stratification beyond current diagnostic categories are needed to understand the underlying disease processes and mechanisms.

Objective

To investigate the association between common-variant liability for schizophrenia, indexed by polygenic risk scores (PRSs), and psychotic presentations of BD.

Design, Setting, and Participants

This case-control study in the United Kingdom used multinomial logistic regression to estimate differential PRS associations across categories of cases and controls. Participants included in the final analyses were 4436 cases of BD from the Bipolar Disorder Research Network. These cases were compared with the genotypic data for 4976 cases of schizophrenia and 9012 controls from the Type 1 Diabetes Genetics Consortium study and the Generation Scotland study. Data were collected between January 1, 2000, and December 31, 2013. Data analysis was conducted from March 1, 2016, to February 28, 2017.

Exposures

Standardized PRSs, calculated using alleles with an association threshold of P < .05 in the second Psychiatric Genomics Consortium genome-wide association study of schizophrenia, were adjusted for the first 10 population principal components and genotyping platforms.

Main Outcomes and Measures

Multinomial logit models estimated PRS associations with BD stratified by Research Diagnostic Criteria subtypes of BD, by lifetime occurrence of psychosis, and by lifetime mood-incongruent psychotic features. Ordinal logistic regression examined PRS associations across levels of mood incongruence. Ratings were derived from the Schedules for Clinical Assessment in Neuropsychiatry interview and the Bipolar Affective Disorder Dimension Scale.

Results

Of the 4436 cases of BD, 2966 (67%) were female patients, and the mean (SD) age at interview was 46 [12] years. Across clinical phenotypes, there was an exposure-response gradient, with the strongest PRS association for schizophrenia (risk ratio [RR] = 1.94; 95% CI, 1.86-2.01), followed by schizoaffective BD (RR = 1.37; 95% CI, 1.22-1.54), bipolar I disorder subtype (RR = 1.30; 95% CI, 1.24-1.36), and bipolar II disorder subtype (RR = 1.04; 95% CI, 0.97-1.11). Within BD cases, there was an effect gradient, indexed by the nature of psychosis. Prominent mood-incongruent psychotic features had the strongest association (RR = 1.46; 95% CI, 1.36-1.57), followed by mood-congruent psychosis (RR = 1.24; 95% CI, 1.17-1.33) and BD with no history of psychosis (RR = 1.09; 95% CI, 1.04-1.15).

Conclusions and Relevance

For the first time to date, a study shows a polygenic-risk gradient across schizophrenia and BD, indexed by the occurrence and level of mood-incongruent psychotic symptoms.

Genomic and Imaging Biomarkers in Schizophrenia

Recent large-scale genomic studies have confirmed that schizophrenia is a polygenic syndrome and have implicated a number of biological pathways in its aetiology. Both common variants individually of small effect and rarer but more penetrant genetic variants have been shown to play a role in the pathogenesis of the disorder. No simple Mendelian forms of the condition have been identified, but progress has been made in stratifying risk on the basis of the polygenic burden of common variants individually of small effect, and the contribution of rarer variants of larger effect such as Copy Number Variants (CNVs). Pathway analysis of risk-associated variants has begun to identify specific biological processes implicated in risk for the disorder, including elements of the glutamatergic NMDA receptor complex and post synaptic density, voltage-gated calcium channels, targets of the Fragile X Mental Retardation Protein (FMRP targets) and immune pathways. Genetic studies have also been used to drive genomic imaging approaches to the investigation of brain markers associated with risk for the disorder. Genomic imaging approaches have been applied both to investigate the effect of polygenic risk and to study the impact of individual higher-penetrance variants such as CNVs. Both genomic and genomic imaging approaches offer potential for the stratification of patients and at-risk groups and the development of better biomarkers of risk and treatment response; however, further research is needed to integrate this work and realise the full potential of these approaches.

Is It Possible to Predict the Future in First-Episode Psychosis?

The outcome of first-episode psychosis (FEP) is highly variable, ranging from early sustained recovery to antipsychotic treatment resistance from the onset of illness. For clinicians, a possibility to predict patient outcomes would be highly valuable for the selection of antipsychotic treatment and in tailoring psychosocial treatments and psychoeducation. This selective review summarizes current knowledge of prognostic markers in FEP. We sought potential outcome predictors from clinical and sociodemographic factors, cognition, brain imaging, genetics, and blood-based biomarkers, and we considered different outcomes, like remission, recovery, physical comorbidities, and suicide risk. Based on the review, it is currently possible to predict the future for FEP patients to some extent. Some clinical features-like the longer duration of untreated psychosis (DUP), poor premorbid adjustment, the insidious mode of onset, the greater severity of negative symptoms, comorbid substance use disorders (SUDs), a history of suicide attempts and suicidal ideation and having non-affective psychosis-are associated with a worse outcome. Of the social and demographic factors, male gender, social disadvantage, neighborhood deprivation, dysfunctional family environment, and ethnicity may be relevant. Treatment non-adherence is a substantial risk factor for relapse, but a small minority of patients with acute onset of FEP and early remission may benefit from antipsychotic discontinuation. Cognitive functioning is associated with functional outcomes. Brain imaging currently has limited utility as an outcome predictor, but this may change with methodological advancements. Polygenic risk scores (PRSs) might be useful as one component of a predictive tool, and pharmacogenetic testing is already available and valuable for patients who have problems in treatment response or with side effects. Most blood-based biomarkers need further validation. None of the currently available predictive markers has adequate sensitivity or specificity used alone. However, personalized treatment of FEP will need predictive tools. We discuss some methodologies, such as machine learning (ML), and tools that could lead to the improved prediction and clinical utility of different prognostic markers in FEP. Combination of different markers in ML models with a user friendly interface, or novel findings from e.g., molecular genetics or neuroimaging, may result in computer-assisted clinical applications in the near future.

DNA sequence-level analyses reveal potential phenotypic modifiers in a large family with psychiatric disorders

Psychiatric disorders are a group of genetically related diseases with highly polygenic architectures. Genome-wide association analyses have made substantial progress towards understanding the genetic architecture of these disorders. More recently, exome- and whole-genome sequencing of cases and families have identified rare, high penetrant variants that provide direct functional insight. There remains, however, a gap in the heritability explained by these complementary approaches. To understand how multiple genetic variants combine to modify both severity and penetrance of a highly penetrant variant, we sequenced 48 whole genomes from a family with a high loading of psychiatric disorder linked to a balanced chromosomal translocation. The (1;11)(q42;q14.3) translocation directly disrupts three genes: DISC1, DISC2, DISC1FP and has been linked to multiple brain imaging and neurocognitive outcomes in the family. Using DNA sequence-level linkage analysis, functional annotation and population-based association, we identified common and rare variants in GRM5 (minor allele frequency (MAF) > 0.05), PDE4D (MAF > 0.2) and CNTN5 (MAF < 0.01) that may help explain the individual differences in phenotypic expression in the family. We suggest that whole-genome sequencing in large families will improve the understanding of the combined effects of the rare and common sequence variation underlying psychiatric phenotypes.

Integrated Bayesian analysis of rare exonic variants to identify risk genes for schizophrenia and neurodevelopmental disorders

BACKGROUND

Integrating rare variation from trio family and case-control studies has successfully implicated specific genes contributing to risk of neurodevelopmental disorders (NDDs) including autism spectrum disorders (ASD), intellectual disability (ID), developmental disorders (DDs), and epilepsy (EPI). For schizophrenia (SCZ), however, while sets of genes have been implicated through the study of rare variation, only two risk genes have been identified.

METHODS

We used hierarchical Bayesian modeling of rare-variant genetic architecture to estimate mean effect sizes and risk-gene proportions, analyzing the largest available collection of whole exome sequence data for SCZ (1,077 trios, 6,699 cases, and 13,028 controls), and data for four NDDs (ASD, ID, DD, and EPI; total 10,792 trios, and 4,058 cases and controls).

RESULTS

For SCZ, we estimate there are 1,551 risk genes. There are more risk genes and they have weaker effects than for NDDs. We provide power analyses to predict the number of risk-gene discoveries as more data become available. We confirm and augment prior risk gene and gene set enrichment results for SCZ and NDDs. In particular, we detected 98 new DD risk genes at FDR < 0.05. Correlations of risk-gene posterior probabilities are high across four NDDs (ρ>0.55), but low between SCZ and the NDDs (ρ<0.3). An in-depth analysis of 288 NDD genes shows there is highly significant protein-protein interaction (PPI) network connectivity, and functionally distinct PPI subnetworks based on pathway enrichment, single-cell RNA-seq cell types, and multi-region developmental brain RNA-seq.

CONCLUSIONS

We have extended a pipeline used in ASD studies and applied it to infer rare genetic parameters for SCZ and four NDDs ( https://github.com/hoangtn/extTADA ). We find many new DD risk genes, supported by gene set enrichment and PPI network connectivity analyses. We find greater similarity among NDDs than between NDDs and SCZ. NDD gene subnetworks are implicated in postnatally expressed presynaptic and postsynaptic genes, and for transcriptional and post-transcriptional gene regulation in prenatal neural progenitor and stem cells.

Mutation intolerant genes and targets of FMRP are enriched for nonsynonymous alleles in schizophrenia

Risk of schizophrenia is conferred by alleles occurring across the full spectrum of frequencies from common SNPs of weak effect through to ultra rare alleles, some of which may be moderately to highly penetrant. Previous studies have suggested that some of the risk of schizophrenia is attributable to uncommon alleles represented on Illumina exome arrays. Here, we present the largest study of exomic variation in schizophrenia to date, using samples from the United Kingdom and Sweden (10,011 schizophrenia cases and 13,791 controls). Single variants, genes, and gene sets were analyzed for association with schizophrenia. No single variant or gene reached genome-wide significance. Among candidate gene sets, we found significant enrichment for rare alleles (minor allele frequency [MAF] < 0.001) in genes intolerant of loss-of-function (LoF) variation and in genes whose messenger RNAs bind to fragile X mental retardation protein (FMRP). We further delineate the genetic architecture of schizophrenia by excluding a role for uncommon exomic variants (0.01 ≤ MAF ≥ 0.001) that confer a relatively large effect (odds ratio [OR] > 4). We also show risk alleles within this frequency range exist, but confer smaller effects and should be identified by larger studies.

Schizophrenia and the neurodevelopmental continuum:evidence from genomics

The idea that disturbances occurring early in brain development contribute to the pathogenesis of schizophrenia, often referred to as the neurodevelopmental hypothesis, has become widely accepted. Despite this, the disorder is viewed as being distinct nosologically, and by implication pathophysiologically and clinically, from syndromes such as autism spectrum disorders, attention-deficit/hyperactivity disorder (ADHD) and intellectual disability, which typically present in childhood and are grouped together as "neurodevelopmental disorders". An alternative view is that neurodevelopmental disorders, including schizophrenia, rather than being etiologically discrete entities, are better conceptualized as lying on an etiological and neurodevelopmental continuum, with the major clinical syndromes reflecting the severity, timing and predominant pattern of abnormal brain development and resulting functional abnormalities. It has also been suggested that, within the neurodevelopmental continuum, severe mental illnesses occupy a gradient of decreasing neurodevelopmental impairment as follows: intellectual disability, autism spectrum disorders, ADHD, schizophrenia and bipolar disorder. Recent genomic studies have identified large numbers of specific risk DNA changes and offer a direct and robust test of the predictions of the neurodevelopmental continuum model and gradient hypothesis. These findings are reviewed in detail. They not only support the view that schizophrenia is a disorder whose origins lie in disturbances of brain development, but also that it shares genetic risk and pathogenic mechanisms with the early onset neurodevelopmental disorders (intellectual disability, autism spectrum disorders and ADHD). They also support the idea that these disorders lie on a gradient of severity, implying that they differ to some extent quantitatively as well as qualitatively. These findings have important implications for nosology, clinical practice and research.

Developmental Dysfunction of VIP Interneurons Impairs Cortical Circuits

GABAergic interneurons play important roles in cortical circuit development. However, there are multiple populations of interneurons and their respective developmental contributions remain poorly explored. Neuregulin 1 (NRG1) and its interneuron-specific receptor ERBB4 are critical genes for interneuron maturation. Using a conditional ErbB4 deletion, we tested the role of vasoactive intestinal peptide (VIP)-expressing interneurons in the postnatal maturation of cortical circuits in vivo. ErbB4 removal from VIP interneurons during development leads to changes in their activity, along with severe dysregulation of cortical temporal organization and state dependence. These alterations emerge during adolescence, and mature animals in which VIP interneurons lack ErbB4 exhibit reduced cortical responses to sensory stimuli and impaired sensory learning. Our data support a key role for VIP interneurons in cortical circuit development and suggest a possible contribution to pathophysiology in neurodevelopmental disorders. These findings provide a new perspective on the role of GABAergic interneuron diversity in cortical development. VIDEO ABSTRACT.

The contribution of rare variants to risk of schizophrenia in individuals with and without intellectual disability

By performing a meta-analysis of rare coding variants in whole-exome sequences from 4,133 schizophrenia cases and 9,274 controls, de novo mutations in 1,077 family trios, and copy number variants from 6,882 cases and 11,255 controls, we show that individuals with schizophrenia carry a significant burden of rare, damaging variants in 3,488 genes previously identified as having a near-complete depletion of loss-of-function variants. In patients with schizophrenia who also have intellectual disability, this burden is concentrated in risk genes associated with neurodevelopmental disorders. After excluding known risk genes for neurodevelopmental disorders, a significant rare variant burden persists in other genes intolerant of loss-of-function variants; although this effect is notably stronger in patients with both schizophrenia and intellectual disability, it is also seen in patients with schizophrenia who do not have intellectual disability. Together, our results show that rare, damaging variants contribute to the risk of schizophrenia both with and without intellectual disability and support an overlap of genetic risk between schizophrenia and other neurodevelopmental disorders.