DISC1 exon 11 rare variants found more commonly in schizoaffective spectrum cases than controls

Dysregulated Signaling at Postsynaptic Density: A Systematic Review and Translational Appraisal for the Pathophysiology, Clinics, and Antipsychotics' Treatment of Schizophrenia

Emerging evidence from genomics, post-mortem, and preclinical studies point to a potential dysregulation of molecular signaling at postsynaptic density (PSD) in schizophrenia pathophysiology. The PSD that identifies the archetypal asymmetric synapse is a structure of approximately 300 nm in diameter, localized behind the neuronal membrane in the glutamatergic synapse, and constituted by more than 1000 proteins, including receptors, adaptors, kinases, and scaffold proteins. Furthermore, using FASS (fluorescence-activated synaptosome sorting) techniques, glutamatergic synaptosomes were isolated at around 70 nm, where the receptors anchored to the PSD proteins can diffuse laterally along the PSD and were stabilized by scaffold proteins in nanodomains of 50-80 nm at a distance of 20-40 nm creating "nanocolumns" within the synaptic button. In this context, PSD was envisioned as a multimodal hub integrating multiple signaling-related intracellular functions. Dysfunctions of glutamate signaling have been postulated in schizophrenia, starting from the glutamate receptor's interaction with scaffolding proteins involved in the N-methyl-D-aspartate receptor (NMDAR). Despite the emerging role of PSD proteins in behavioral disorders, there is currently no systematic review that integrates preclinical and clinical findings addressing dysregulated PSD signaling and translational implications for antipsychotic treatment in the aberrant postsynaptic function context. Here we reviewed a critical appraisal of the role of dysregulated PSD proteins signaling in the pathophysiology of schizophrenia, discussing how antipsychotics may affect PSD structures and synaptic plasticity in brain regions relevant to psychosis.

Mutations in DISC1 alter IP3R and voltage-gated Ca2+ channel functioning, implications for major mental illness

Disrupted in Schizophrenia 1 (DISC1) participates in a wide variety of developmental processes of central neurons. It also serves critical roles that underlie cognitive functioning in adult central neurons. Here we summarize DISC1’s general properties and discuss its use as a model system for understanding major mental illnesses (MMIs). We then discuss the cellular actions of DISC1 that involve or regulate Ca²⁺ signaling in adult central neurons. In particular, we focus on the tethering role DISC1 plays in transporting RNA particles containing Ca²⁺ channel subunit RNAs, including IP3R1, CACNA1C and CACNA2D1, and in transporting mitochondria into dendritic and axonal processes. We also review DISC1’s role in modulating IP₃R1 activity within mitochondria-associated ER membrane (MAM). Finally, we discuss DISC1-glycogen synthase kinase 3β (GSK3β) signaling that regulates functional expression of voltage-gated Ca²⁺ channels (VGCCs) at central synapses. In each case, DISC1 regulates the movement of molecules that impact Ca²⁺ signaling in neurons.

Genetic associations and expression of extra-short isoforms of disrupted-in-schizophrenia 1 in a neurocognitive subgroup of schizophrenia

Disrupted-in-schizophrenia 1 (DISC1) was reported to be associated with schizophrenia. In a previous study, we found significant association with schizophrenia patients with deficient sustained attention assessed by continuous performance test (CPT). This study aimed to identify risk polymorphisms in this specific neurocognitive subgroup and investigate the expression of different isoforms of DISC1. A total of 83 genetic variants were identified through direct sequencing in 50 controls and 100 schizophrenia patients. Fourteen variants were genotyped in 600 controls and 912 patients. Patients were subgrouped by familial loading (multiplex or simplex) and performance on CPT. The frequency of AA genotype of rs11122324 at the 3'-UTR of Es and Esv1 isoforms and of rs2793091 at intron 4 were significantly higher in multiplex schizophrenia patients than those in controls (corrected p < 0.05). In further subgrouping, the frequency of AA genotype of the two SNPs were significantly higher in multiplex schizophrenia patients with deficient sustained attention than those in controls (corrected p < 0.005). The mRNA expression levels of two extra-short isoforms (Es and Esv1) in the EBV-transformed lymphocytes of schizophrenia were significantly higher than those of controls. Luciferase reporter assays demonstrated that the A-allele of rs11122324 significantly upregulated DISC1 extra-short isoforms transcription compared with the G-allele. We found two SNPs (rs11122324 and rs2793091) of DISC1 may be specifically associated with multiplex schizophrenia patients with deficient sustained attention. The SNP rs11122324 may be a risk polymorphism, which may have functional influence on the transcription of Es and Esv1 through increasing their expression.

Rare deleterious mutations are associated with disease in bipolar disorder families

Bipolar disorder (BD) is a common, complex and heritable psychiatric disorder characterized by episodes of severe mood swings. The identification of rare, damaging genomic mutations in families with BD could inform about disease mechanisms and lead to new therapeutic interventions. To determine whether rare, damaging mutations shared identity-by-descent in families with BD could be associated with disease, exome sequencing was performed in multigenerational families of the NIMH BD Family Study followed by in silico functional prediction. Disease association and disease specificity was determined using 5090 exomes from the Sweden-Schizophrenia (SZ) Population-Based Case-Control Exome Sequencing study. We identified 14 rare and likely deleterious mutations in 14 genes that were shared identity-by-descent among affected family members. The variants were associated with BD (P<0.05 after Bonferroni's correction) and disease specificity was supported by the absence of the mutations in patients with SZ. In addition, we found rare, functional mutations in known causal genes for neuropsychiatric disorders including holoprosencephaly and epilepsy. Our results demonstrate that exome sequencing in multigenerational families with BD is effective in identifying rare genomic variants of potential clinical relevance and also disease modifiers related to coexisting medical conditions. Replication of our results and experimental validation are required before disease causation could be assumed.

Missense mutation in DISC1 C-terminal coiled-coil has GSK3β signaling and sex-dependent behavioral effects in mice

Disrupted-in-Schizophrenia 1 (DISC1) is a risk factor for schizophrenia and affective disorders. The full-length DISC1 protein consists of an N-terminal 'head' domain and a C-terminal tail domain that contains several predicted coiled-coils, structural motifs involved in protein-protein interactions. To probe the in vivo effects of missense mutation of DISC1's C-terminal tail, we tested mice carrying mutation D453G within a predicted α-helical coiled-coil region. We report that, relative to wild-type littermates, female DISC1(D453G) mice exhibited novelty-induced hyperlocomotion, an anxiogenic profile in the elevated plus-maze and open field tests, and reduced social exploration of unfamiliar mice. Male DISC1(D453G) mice displayed a deficit in passive avoidance, while neither males nor females exhibited any impairment in startle reactivity or prepulse inhibition. Whole brain homogenates showed normal levels of DISC1 protein, but decreased binding of DISC1 to GSK3β, decreased phospho-inhibition of GSK3β at serine 9, and decreased levels of β-catenin in DISC1(D453G) mice of either sex. Interrupted GSK3β signaling may thus be part of the mechanism underlying the behavioral phenotype associated with D453G, in common with the previously described N-terminal domain mutations Q31L and L100P in mice, and the schizophrenia risk-conferring variant R264Q in humans.

Schizophrenia and Depression Co-Morbidity: What We have Learned from Animal Models

Patients with schizophrenia are at an increased risk for the development of depression. Overlap in the symptoms and genetic risk factors between the two disorders suggests a common etiological mechanism may underlie the presentation of comorbid depression in schizophrenia. Understanding these shared mechanisms will be important in informing the development of new treatments. Rodent models are powerful tools for understanding gene function as it relates to behavior. Examining rodent models relevant to both schizophrenia and depression reveals a number of common mechanisms. Current models which demonstrate endophenotypes of both schizophrenia and depression are reviewed here, including models of CUB and SUSHI multiple domains 1, PDZ and LIM domain 5, glutamate Delta 1 receptor, diabetic db/db mice, neuropeptide Y, disrupted in schizophrenia 1, and its interacting partners, reelin, maternal immune activation, and social isolation. Neurotransmission, brain connectivity, the immune system, the environment, and metabolism emerge as potential common mechanisms linking these models and potentially explaining comorbid depression in schizophrenia.

708 Common and 2010 rare DISC1 locus variants identified in 1542 subjects: analysis for association with psychiatric disorder and cognitive traits

A balanced t(1;11) translocation that transects the Disrupted in schizophrenia 1 (DISC1) gene shows genome-wide significant linkage for schizophrenia and recurrent major depressive disorder (rMDD) in a single large Scottish family, but genome-wide and exome sequencing-based association studies have not supported a role for DISC1 in psychiatric illness. To explore DISC1 in more detail, we sequenced 528 kb of the DISC1 locus in 653 cases and 889 controls. We report 2718 validated single-nucleotide polymorphisms (SNPs) of which 2010 have a minor allele frequency of <1%. Only 38% of these variants are reported in the 1000 Genomes Project European subset. This suggests that many DISC1 SNPs remain undiscovered and are essentially private. Rare coding variants identified exclusively in patients were found in likely functional protein domains. Significant region-wide association was observed between rs16856199 and rMDD (P=0.026, unadjusted P=6.3 × 10(-5), OR=3.48). This was not replicated in additional recurrent major depression samples (replication P=0.11). Combined analysis of both the original and replication set supported the original association (P=0.0058, OR=1.46). Evidence for segregation of this variant with disease in families was limited to those of rMDD individuals referred from primary care. Burden analysis for coding and non-coding variants gave nominal associations with diagnosis and measures of mood and cognition. Together, these observations are likely to generalise to other candidate genes for major mental illness and may thus provide guidelines for the design of future studies.

Improving power for robust trans-ethnic meta-analysis of rare and low-frequency variants with a partitioning approach

While genome-wide association studies have discovered numerous bona fide variants that are associated with common diseases and complex traits; these variants tend to be common in the population and explain only a small proportion of the phenotype variance. The search for the missing heritability has thus switched to rare and low-frequency variants, defined as <5% in the population, but which are expected to have a bigger impact on phenotypic outcomes. The rarer nature of these variants coupled with the curse of testing multiple variants across the genome meant that large sample sizes will still be required despite the assumption of bigger effect sizes. Combining data from multiple studies in a meta-analysis will continue to be the natural approach in boosting sample sizes. However, the population genetics of rare variants suggests that allelic and effect size heterogeneity across populations of different ancestries is likely to pose a greater challenge to trans-ethnic meta-analysis of rare variants than to similar analyses of common variants. Here, we introduce a novel method to perform trans-ethnic meta-analysis of rare and low-frequency variants. The approach is centered on partitioning the studies into distinct clusters using local inference of genomic similarity between population groups, with the aim to minimize both the number of clusters and between-study heterogeneity in each cluster. Through a series of simulations, we show that our approach either performs similarly to or outperforms conventional and recently introduced meta-analysis strategies, particularly in the presence of allelic heterogeneity.

Regularized rare variant enrichment analysis for case-control exome sequencing data

Rare variants have recently garnered an immense amount of attention in genetic association analysis. However, unlike methods traditionally used for single marker analysis in GWAS, rare variant analysis often requires some method of aggregation, since single marker approaches are poorly powered for typical sequencing study sample sizes. Advancements in sequencing technologies have rendered next-generation sequencing platforms a realistic alternative to traditional genotyping arrays. Exome sequencing in particular not only provides base-level resolution of genetic coding regions, but also a natural paradigm for aggregation via genes and exons. Here, we propose the use of penalized regression in combination with variant aggregation measures to identify rare variant enrichment in exome sequencing data. In contrast to marginal gene-level testing, we simultaneously evaluate the effects of rare variants in multiple genes, focusing on gene-based least absolute shrinkage and selection operator (LASSO) and exon-based sparse group LASSO models. By using gene membership as a grouping variable, the sparse group LASSO can be used as a gene-centric analysis of rare variants while also providing a penalized approach toward identifying specific regions of interest. We apply extensive simulations to evaluate the performance of these approaches with respect to specificity and sensitivity, comparing these results to multiple competing marginal testing methods. Finally, we discuss our findings and outline future research.

Disorders and borders: psychiatric genetics and nosology

Over the past century, the definition and classification of psychiatric disorders has evolved through a combination of historical trends, clinical observations, and empirical research. The current nosology, instantiated in the DSM-5 and ICD-10, rests on descriptive criteria agreed upon by a consensus of experts. While the development of explicit criteria has enhanced the reliability of diagnosis, the validity of the current diagnostic categories has been the subject of debate and controversy. Genetic studies have long been regarded as a key resource for validating the boundaries among diagnostic categories. Genetic epidemiologic studies have documented the familiality and heritability of clinically defined psychiatric disorders and molecular genetic studies have begun to identify specific susceptibility variants. At the same time, there is growing evidence from family, twin and genomic studies that genetic influences on psychiatric disorders transcend clinical boundaries. Here I review this evidence for cross-disorder genetic effects and discuss the implications of these findings for psychiatric nosology. Psychiatric genetic research can inform a bottom-up reappraisal of psychopathology that may help the field move beyond a purely descriptive classification and toward an etiology-based nosology.

Combined genotype and haplotype tests for region-based association studies

Background

Although single-SNP analysis has proven to be useful in identifying many disease-associated loci, region-based analysis has several advantages. Empirically, it has been shown that region-based genotype and haplotype approaches may possess much higher power than single-SNP statistical tests. Both high quality haplotypes and genotypes may be available for analysis given the development of next generation sequencing technologies and haplotype assembly algorithms.

Results

As generally it is unknown whether genotypes or haplotypes are more relevant for identifying an association, we propose to use both of them with the purpose of preserving high power under both genotype and haplotype disease scenarios. We suggest two approaches for a combined association test and investigate the performance of these two approaches based on a theoretical model, population genetics simulations and analysis of a real data set.

Conclusions

Based on a theoretical model, population genetics simulations and analysis of a central corneal thickness (CCT) Genome Wide Association Study (GWAS) data set we have shown that combined genotype and haplotype approach has a high potential utility for applications in association studies.

DISC1 genetics, biology and psychiatric illness

Psychiatric disorders are highly heritable, and in many individuals likely arise from the combined effects of genes and the environment. A substantial body of evidence points towards DISC1 being one of the genes that influence risk of schizophrenia, bipolar disorder and depression, and functional studies of DISC1 consequently have the potential to reveal much about the pathways that lead to major mental illness. Here, we review the evidence that DISC1 influences disease risk through effects upon multiple critical pathways in the developing and adult brain.

Comparison of similarity-based tests and pooling strategies for rare variants

Background

As several rare genomic variants have been shown to affect common phenotypes, rare variants association analysis has received considerable attention. Several efficient association tests using genotype and phenotype similarity measures have been proposed in the literature. The major advantages of similarity-based tests are their ability to accommodate multiple types of DNA variations within one association test, and to account for the possible interaction within a region. However, not much work has been done to compare the performance of similarity-based tests on rare variants association scenarios, especially when applied with different rare variants pooling strategies.

Results

Based on the population genetics simulations and analysis of a publicly-available sequencing data set, we compared the performance of four similarity-based tests and two rare variants pooling strategies. We showed that weighting approach outperforms collapsing under the presence of strong effect from rare variants and under the presence of moderate effect from common variants, whereas collapsing of rare variants is preferable when common variants possess a strong effect. We also demonstrated that the difference in statistical power between the two pooling strategies may be substantial. The results also highlighted consistently high power of two similarity-based approaches when applied with an appropriate pooling strategy.

Conclusions

Population genetics simulations and sequencing data set analysis showed high power of two similarity-based tests and a substantial difference in power between the two pooling strategies.

Convergent functional genomics of schizophrenia: from comprehensive understanding to genetic risk prediction

We have used a translational convergent functional genomics (CFG) approach to identify and prioritize genes involved in schizophrenia, by gene-level integration of genome-wide association study data with other genetic and gene expression studies in humans and animal models. Using this polyevidence scoring and pathway analyses, we identify top genes (DISC1, TCF4, MBP, MOBP, NCAM1, NRCAM, NDUFV2, RAB18, as well as ADCYAP1, BDNF, CNR1, COMT, DRD2, DTNBP1, GAD1, GRIA1, GRIN2B, HTR2A, NRG1, RELN, SNAP-25, TNIK), brain development, myelination, cell adhesion, glutamate receptor signaling, G-protein-coupled receptor signaling and cAMP-mediated signaling as key to pathophysiology and as targets for therapeutic intervention. Overall, the data are consistent with a model of disrupted connectivity in schizophrenia, resulting from the effects of neurodevelopmental environmental stress on a background of genetic vulnerability. In addition, we show how the top candidate genes identified by CFG can be used to generate a genetic risk prediction score (GRPS) to aid schizophrenia diagnostics, with predictive ability in independent cohorts. The GRPS also differentiates classic age of onset schizophrenia from early onset and late-onset disease. We also show, in three independent cohorts, two European American and one African American, increasing overlap, reproducibility and consistency of findings from single-nucleotide polymorphisms to genes, then genes prioritized by CFG, and ultimately at the level of biological pathways and mechanisms. Finally, we compared our top candidate genes for schizophrenia from this analysis with top candidate genes for bipolar disorder and anxiety disorders from previous CFG analyses conducted by us, as well as findings from the fields of autism and Alzheimer. Overall, our work maps the genomic and biological landscape for schizophrenia, providing leads towards a better understanding of illness, diagnostics and therapeutics. It also reveals the significant genetic overlap with other major psychiatric disorder domains, suggesting the need for improved nosology.

DISC1: Structure, Function, and Therapeutic Potential for Major Mental Illness

Disrupted in schizophrenia 1 (DISC1) is well established as a genetic risk factor across a spectrum of psychiatric disorders, a role supported by a growing body of biological studies, making the DISC1 protein interaction network an attractive therapeutic target. By contrast, there is a relative deficit of structural information to relate to the myriad biological functions of DISC1. Here, we critically appraise the available bioinformatics and biochemical analyses on DISC1 and key interacting proteins, and integrate this with the genetic and biological data. We review, analyze, and make predictions regarding the secondary structure and propensity for disordered regions within DISC1, its protein-interaction domains, subcellular localization motifs, and the structural and functional implications of common and ultrarare DISC1 variants associated with major mental illness. We discuss signaling pathways of high pharmacological potential wherein DISC1 participates, including those involving phosphodiesterase 4 (PDE4) and glycogen synthase kinase 3 (GSK3). These predictions and priority areas can inform future research in the translational and potentially guide the therapeutic processes.