Increased burden of ultra-rare protein-altering variants among 4,877 individuals with schizophrenia

The Path to New Therapies for Schizophrenia and Bipolar Illness

Schizophrenia and bipolar illness are two of the most serious forms of mental illness. Until relatively recently, almost nothing was known about the molecular pathogenesis of either illness. The single largest risk factor that predisposes people to schizophrenia or bipolar illness is genetic risk. Heritability is high, and the incidence is significantly higher in identical twins than in nonidentical twins. Despite decades of work aimed at identifying the genes involved in these two illnesses, virtually no progress had been made until the past decade. With the knowledge and technologies that have been gained from the Human Genome Project, it has been possible to begin to understand the underlying genetics and to use the new information to begin the effort to discover new and better medicines to treat these illnesses. This article will describe the past decade of work toward this goal and articulate both the promise that now exists and what is still needed to bring dramatic and tangible change to patients.-Scolnick, E. M. The path to new therapies for schizophrenia and bipolar illness.

The epigenomics of schizophrenia, in the mouse

Large-scale consortia including the Psychiatric Genomics Consortium, the Common Minds Consortium, BrainSeq and PsychENCODE, and many other studies taken together provide increasingly detailed insights into the genetic and epigenetic risk architectures of schizophrenia (SCZ) and offer vast amounts of molecular information, but with largely unexplored therapeutic potential. Here we discuss how epigenomic studies in human brain could guide animal work to test the impact of disease-associated alterations in chromatin structure and function on cognition and behavior. For example, transcription factors such as MYOCYTE-SPECIFIC ENHANCER FACTOR 2C (MEF2C), or multiple regulators of the open chromatin mark, methyl-histone H3-lysine 4, are associated with the genetic risk architectures of common psychiatric disease and alterations in chromatin structure and function in diseased brain tissue. Importantly, these molecules also affect cognition and behavior in genetically engineered mice, including virus-mediated expression changes in prefrontal cortex (PFC) and other key nodes in the circuitry underlying psychosis. Therefore, preclinical and small laboratory animal work could target genomic sequences affected by chromatin alterations in SCZ. To this end, in vivo editing of enhancer and other regulatory non-coding DNA by RNA-guided nucleases including CRISPR-Cas, and designer transcription factors, could be expected to deliver pipelines for novel therapeutic approaches aimed at improving cognitive dysfunction and other core symptoms of SCZ.

Genetics of Schizophrenia: Ready to Translate?

PURPOSE OF REVIEW

This is an era where we have significantly advanced the understanding of the genetic architecture of schizophrenia. In this review, we consider how this knowledge may translate into advances that will improve patient care.

RECENT FINDINGS

Large-scale genome-wide association studies (GWAS) have identified more than a hundred loci each making a small contribution to illness risk. Meta-analysis of copy number variants (CNVs) in the Psychiatric Genomics Consortium (PGC) dataset has confirmed that some variants have a moderate or large impact on risk, although these are rare in the population. Genome sequencing advances allow a much more comprehensive evaluation of genomic variation. We describe the key findings from whole exome studies to date. These studies are happening against a backdrop of growing understanding of the regulation and expression of genes and better functional tools to investigate molecular mechanisms in model systems. We provide an overview of how recent approaches in schizophrenia genetics are converging and consider how they could impact on diagnostics, the development of personalized medicine, and drug discovery.

Translating advances in the molecular basis of schizophrenia into novel cognitive treatment strategies

The presence and severity of cognitive symptoms, including working memory, executive dysfunction and attentional impairment, contributes materially to functional impairment in schizophrenia. Cognitive symptoms have proved to be resistant to both first- and second-generation antipsychotic drugs. Efforts to develop a consensus set of cognitive domains that are both disrupted in schizophrenia and are amenable to cross-species validation (e.g. the National Institute of Mental Health Cognitive Neuroscience Treatment Research to Improve Cognition in Schizophrenia and Research Domain Criteria initiatives) are an important step towards standardization of outcome measures that can be used in preclinical testing of new drugs. While causative genetic mutations have not been identified, new technologies have identified novel genes as well as hitherto candidate genes previously implicated in the pathophysiology of schizophrenia and/or mechanisms of antipsychotic efficacy. This review comprises a selective summary of these developments, particularly phenotypic data arising from preclinical genetic models for cognitive dysfunction in schizophrenia, with the aim of indicating potential new directions for pro-cognitive therapeutics. Linked Articles This article is part of a themed section on Pharmacology of Cognition: a Panacea for Neuropsychiatric Disease? To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v174.19/issuetoc.

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.

Rare FBXO18 variations and risk of schizophrenia: Whole-exome sequencing in two parent-affected offspring trios followed by resequencing and case-control studies

AIM

Rare variations are suggested to play a role in the genetic etiology of schizophrenia; to further investigate their role, we performed a three-stage study in a Japanese population.

METHODS

In the first stage, we performed whole-exome sequencing (WES) of two parent-affected offspring trios. In the second stage, we resequenced the FBXO18 coding region in 96 patients. In the third stage, we tested rare non-synonymous FBXO18 variations for association with schizophrenia in two independent populations comprising a total of 1376 patients and 1496 controls.

RESULTS

A rare frameshift variation (L116fsX) in the FBXO18 gene was recurrently identified by WES in both trios. Resequencing FBXO18 coding regions, we detected three rare non-synonymous variations (V15L, L116fsX, and V1006I). However, there were no significant associations between these rare FBXO18 variations and schizophrenia in the case-control study.

CONCLUSION

Our present study does not provide evidence for the contribution of rare non-synonymous FBXO18 variations to the genetic etiology of schizophrenia in the Japanese population. However, to draw a definitive conclusion, further studies should be performed using sufficiently large sample sizes.

Synaptic GAP and GEF Complexes Cluster Proteins Essential for GTP Signaling

GTPase-activating proteins (GAPs) and guanine exchange factors (GEFs) play essential roles in regulating the activity of small GTPases. Several GAPs and GEFs have been shown to be present at the postsynaptic density (PSD) within excitatory glutamatergic neurons and regulate the activity of glutamate receptors. However, it is not known how synaptic GAP and GEF proteins are organized within the PSD signaling machinery, if they have overlapping interaction networks, or if they associate with proteins implicated in contributing to psychiatric disease. Here, we determine the interactomes of three interacting GAP/GEF proteins at the PSD, including the RasGAP Syngap1, the ArfGAP Agap2, and the RhoGEF Kalirin, which includes a total of 280 interactions. We describe the functional properties of each interactome and show that these GAP/GEF proteins are highly associated with and cluster other proteins directly involved in GTPase signaling mechanisms. We also utilize Agap2 as an example of GAP/GEFs localized within multiple neuronal compartments and determine an additional 110 interactions involving Agap2 outside of the PSD. Functional analysis of PSD and non-PSD interactomes illustrates both common and unique functions of Agap2 determined by its subcellular location. Furthermore, we also show that these GAPs/GEFs associate with several proteins involved in psychiatric disease.

Spatiotemporal profile of postsynaptic interactomes integrates components of complex brain disorders

The postsynaptic density (PSD) contains a collection of scaffold proteins used for assembling synaptic signaling complexes. However, it is not known how the core-scaffold machinery associates in protein-interaction networks or how proteins encoded by genes involved in complex brain disorders are distributed through spatiotemporal protein complexes. Here using immunopurification, proteomics and bioinformatics, we isolated 2,876 proteins across 41 in vivo interactomes and determined their protein domain composition, correlation to gene expression levels and developmental integration to the PSD. We defined clusters for enrichment of schizophrenia, autism spectrum disorders, developmental delay and intellectual disability risk factors at embryonic day 14 and adult PSD in mice. Mutations in highly connected nodes alter protein-protein interactions modulating macromolecular complexes enriched in disease risk candidates. These results were integrated into a software platform, Synaptic Protein/Pathways Resource (SyPPRes), enabling the prioritization of disease risk factors and their placement within synaptic protein interaction networks.

Truncating mutations in RBM12 are associated with psychosis

Thus far, a handful of highly penetrant mutations conferring risk of psychosis have been discovered. Here we used whole-genome sequencing and long-range phasing to investigate an Icelandic kindred containing ten individuals with psychosis (schizophrenia, schizoaffective disorder or psychotic bipolar disorder). We found that all affected individuals carry RBM12 (RNA-binding-motif protein 12) c.2377G>T (P = 2.2 × 10^-4), a nonsense mutation that results in the production of a truncated protein lacking a predicted RNA-recognition motif. We replicated the association in a Finnish family in which a second RBM12 truncating mutation (c.2532delT) segregates with psychosis (P = 0.020). c.2377G>T is not fully penetrant for psychosis; however, we found that carriers unaffected by psychosis resemble patients with schizophrenia in their non-psychotic psychiatric disorder and neuropsychological test profile (P = 0.0043) as well as in their life outcomes (including an increased chance of receiving disability benefits, P = 0.011). As RBM12 has not previously been linked to psychosis, this work provides new insight into psychiatric disease.

The impact of genetics on future drug discovery in schizophrenia

INTRODUCTION

Failures of investigational new drugs (INDs) for schizophrenia have left huge unmet medical needs for patients. Given the recent lackluster results, it is imperative that new drug discovery approaches (and resultant drug candidates) target pathophysiological alterations that are shared in specific, stratified patient populations that are selected based on pre-identified biological signatures. One path to implementing this paradigm is achievable by leveraging recent advances in genetic information and technologies. Genome-wide exome sequencing and meta-analysis of single nucleotide polymorphism (SNP)-based association studies have already revealed rare deleterious variants and SNPs in patient populations. Areas covered: Herein, the authors review the impact that genetics have on the future of schizophrenia drug discovery. The high polygenicity of schizophrenia strongly indicates that this disease is biologically heterogeneous so the identification of unique subgroups (by patient stratification) is becoming increasingly necessary for future investigational new drugs. Expert opinion: The authors propose a pathophysiology-based stratification of genetically-defined subgroups that share deficits in particular biological pathways. Existing tools, including lower-cost genomic sequencing and advanced gene-editing technology render this strategy ever more feasible. Genetically complex psychiatric disorders such as schizophrenia may also benefit from synergistic research with simpler monogenic disorders that share perturbations in similar biological pathways.

DNA Sequence Analysis in Clinical Medicine, Proceeding Cautiously

Delineation of underlying genomic and genetic factors in a specific disease may be valuable in establishing a definitive diagnosis and may guide patient management and counseling. In addition, genetic information may be useful in identification of at risk family members. Gene mapping and initial genome sequencing data enabled the development of microarrays to analyze genomic variants. The goal of this review is to consider different generations of sequencing techniques and their application to exome sequencing and whole genome sequencing and their clinical applications. In recent decades, exome sequencing has primarily been used in patient studies. Discussed in some detail, are important measures that have been developed to standardize variant calling and to assess pathogenicity of variants. Examples of cases where exome sequencing has facilitated diagnosis and led to improved medical management are presented. Whole genome sequencing and its clinical relevance are presented particularly in the context of analysis of nucleotide and structural genomic variants in large population studies and in certain patient cohorts. Applications involving analysis of cell free DNA in maternal blood for prenatal diagnosis of specific autosomal trisomies are reviewed. Applications of DNA sequencing to diagnosis and therapeutics of cancer are presented. Also discussed are important recent diagnostic applications of DNA sequencing in cancer, including analysis of tumor derived cell free DNA and exosomes that are present in body fluids. Insights gained into underlying pathogenetic mechanisms of certain complex common diseases, including schizophrenia, macular degeneration, neurodegenerative disease are presented. The relevance of different types of variants, rare, uncommon, and common to disease pathogenesis, and the continuum of causality, are addressed. Pharmogenetic variants detected by DNA sequence analysis are gaining in importance and are particularly relevant to personalized and precision medicine.

The Weighting is the Hardest Part: On the Behavior of the Likelihood Ratio Test and the Score Test Under a Data-Driven Weighting Scheme in Sequenced Samples

Sequence-based association studies are at a critical inflexion point with the increasing availability of exome-sequencing data. A popular test of association is the sequence kernel association test (SKAT). Weights are embedded within SKAT to reflect the hypothesized contribution of the variants to the trait variance. Because the true weights are generally unknown, and so are subject to misspecification, we examined the efficiency of a data-driven weighting scheme. We propose the use of a set of theoretically defensible weighting schemes, of which, we assume, the one that gives the largest test statistic is likely to capture best the allele frequency-functional effect relationship. We show that the use of alternative weights obviates the need to impose arbitrary frequency thresholds. As both the score test and the likelihood ratio test (LRT) may be used in this context, and may differ in power, we characterize the behavior of both tests. The two tests have equal power, if the weights in the set included weights resembling the correct ones. However, if the weights are badly specified, the LRT shows superior power (due to its robustness to misspecification). With this data-driven weighting procedure the LRT detected significant signal in genes located in regions already confirmed as associated with schizophrenia - the PRRC2A (p = 1.020e-06) and the VARS2 (p = 2.383e-06) - in the Swedish schizophrenia case-control cohort of 11,040 individuals with exome-sequencing data. The score test is currently preferred for its computational efficiency and power. Indeed, assuming correct specification, in some circumstances, the score test is the most powerful test. However, LRT has the advantageous properties of being generally more robust and more powerful under weight misspecification. This is an important result given that, arguably, misspecified models are likely to be the rule rather than the exception in weighting-based approaches.

Exploring the genetic architecture of inflammatory bowel disease by whole-genome sequencing identifies association at ADCY7

To further resolve the genetic architecture of the inflammatory bowel diseases ulcerative colitis and Crohn's disease, we sequenced the whole genomes of 4,280 patients at low coverage and compared them to 3,652 previously sequenced population controls across 73.5 million variants. We then imputed from these sequences into new and existing genome-wide association study cohorts and tested for association at ∼12 million variants in a total of 16,432 cases and 18,843 controls. We discovered a 0.6% frequency missense variant in ADCY7 that doubles the risk of ulcerative colitis. Despite good statistical power, we did not identify any other new low-frequency risk variants and found that such variants explained little heritability. We detected a burden of very rare, damaging missense variants in known Crohn's disease risk genes, suggesting that more comprehensive sequencing studies will continue to improve understanding of the biology of complex diseases.

DNA Methylation in Schizophrenia

Schizophrenia is a highly heritable psychiatric condition that displays a complex phenotype. A multitude of genetic susceptibility loci have now been identified, but these fail to explain the high heritability estimates of schizophrenia. In addition, epidemiologically relevant environmental risk factors for schizophrenia may lead to permanent changes in brain function. In conjunction with genetic liability, these environmental risk factors-likely through epigenetic mechanisms-may give rise to schizophrenia, a clinical syndrome characterized by florid psychotic symptoms and moderate to severe cognitive impairment. These pathophysiological features point to the involvement of epigenetic processes. Recently, a wave of studies examining aberrant DNA modifications in schizophrenia was published. This chapter aims to comprehensively review the current findings, from both candidate gene studies and genome-wide approaches, on DNA methylation changes in schizophrenia.

Ultra-rare disruptive and damaging mutations influence educational attainment in the general population

Disruptive, damaging ultra-rare variants in highly constrained genes are enriched in individuals with neurodevelopmental disorders. In the general population, this class of variants was associated with a decrease in years of education (YOE). This effect was stronger among highly brain-expressed genes and explained more YOE variance than pathogenic copy number variation but less than common variants. Disruptive, damaging ultra-rare variants in highly constrained genes influence the determinants of YOE in the general population.