Targeted Sequencing of 10,198 Samples Confirms Abnormalities in Neuronal Activity and Implicates Voltage-Gated Sodium Channels in Schizophrenia Pathogenesis

Genetic Implication of Specific Glutamatergic Neurons of the Prefrontal Cortex in the Pathophysiology of Schizophrenia

Background

The prefrontal cortex (PFC) has been strongly implicated in the pathophysiology of schizophrenia. Here, we combined high-resolution single-nuclei RNA sequencing data from the human PFC with large-scale genomic data for schizophrenia to identify constituent cell populations likely to mediate genetic liability to the disorder.

Methods

Gene expression specificity values were calculated from a single-nuclei RNA sequencing dataset comprising 84 cell populations from the human PFC, spanning gestation to adulthood. Enrichment of schizophrenia common variant liability and burden of rare protein-truncating coding variants were tested in genes with high expression specificity for each cell type. We also explored schizophrenia common variant associations in relation to gene expression across the developmental trajectory of implicated neurons.

Results

Common risk variation for schizophrenia was prominently enriched in genes with high expression specificity for a population of mature layer 4 glutamatergic neurons emerging in infancy. Common variant liability to schizophrenia increased along the developmental trajectory of this neuronal population. Fine-mapped genes at schizophrenia genome-wide association study risk loci had significantly higher expression specificity than other genes in these neurons and in a population of layer 5/6 glutamatergic neurons. People with schizophrenia had a higher rate of rare protein-truncating coding variants in genes expressed by cells of the PFC than control individuals, but no cell population was significantly enriched above this background rate.

Conclusions

We identified a population of layer 4 glutamatergic PFC neurons likely to be particularly affected by common variant genetic risk for schizophrenia, which may contribute to disturbances in thalamocortical connectivity in the condition.

When rare meets common: Treatable genetic diseases are enriched in the general psychiatric population

Mental illnesses are one of the biggest contributors to the global disease burden. Despite the increased recognition, diagnosis and ongoing research of mental health disorders, the etiology and underlying molecular mechanisms of these disorders are yet to be fully elucidated. Moreover, despite many treatment options available, a large subset of the psychiatric patient population is nonresponsive to standard medications and therapies. There has not been a comprehensive study to date examining the burden and impact of treatable genetic disorders (TGDs) that can present with neuropsychiatric features in psychiatric patient populations. In this study, we test the hypothesis that TGDs that present with psychiatric symptoms are more prevalent within psychiatric patient populations compared to the general population by performing targeted next-generation sequencing of 129 genes associated with 108 TGDs in a cohort of 2301 psychiatric patients. In total, 48 putative affected and 180 putative carriers for TGDs were identified, with known or likely pathogenic variants in 79 genes. Despite screening for only 108 genetic disorders, this study showed a two-fold (2.09%) enrichment for genetic disorders within the psychiatric population relative to the estimated 1% cumulative prevalence of all single gene disorders globally. This strongly suggests that the prevalence of these, and most likely all, genetic diseases is greatly underestimated in psychiatric populations. Increasing awareness and ensuring accurate diagnosis of TGDs will open new avenues to targeted treatment for a subset of psychiatric patients.

Anxiety and dysautonomia symptoms in patients with a NaV1.7 mutation and the potential benefits of low-dose short-acting guanfacine

PURPOSE

Guanfacine is an α2A-adrenergic receptor agonist, FDA-approved to treat attention-deficit hyperactivity disorder and high blood pressure, typically as an extended-release formulation up to 7 mg/day. In our dysautonomia clinic, we observed that off-label use of short-acting guanfacine at 1 mg/day facilitated symptom relief in two families with multiple members presenting with severe generalized anxiety. We also noted anecdotal improvements in associated dysautonomia symptoms such as hyperhidrosis, cognitive impairment, and palpitations. We postulated that a genetic deficit existed in these patients that might augment guanfacine susceptibility.

METHODS

We used whole-exome sequencing to identify mutations in patients with shared generalized anxiety and dysautonomia symptoms. Guanfacine-induced changes in the function of voltage-gated Na+ channels were investigated using voltage-clamp electrophysiology.

RESULTS

Whole-exome sequencing uncovered the p.I739V mutation in SCN9A in the proband of two nonrelated families. Moreover, guanfacine inhibited ionic currents evoked by wild-type and mutant NaV1.7 encoded by SCN9A, as well as other NaV channel subtypes to a varying degree.

CONCLUSION

Our study provides further evidence for a possible pathophysiological role of NaV1.7 in anxiety and dysautonomia. Combined with off-target effects on NaV channel function, daily administration of 1 mg short-acting guanfacine may be sufficient to normalize NaV channel mutation-induced changes in sympathetic activity, perhaps aided by partial inhibition of NaV1.7 or other channel subtypes. In a broader context, expanding genetic and functional data about ion channel aberrations may enable the prospect of stratifying patients in which mutation-induced increased sympathetic tone normalization by guanfacine can support treatment strategies for anxiety and dysautonomia symptoms.

The Association of Hippocampal Long-Term Potentiation-Induced Gene Expression with Genetic Risk for Psychosis

Genomic studies focusing on the contribution of common and rare genetic variants of schizophrenia and bipolar disorder support the view that substantial risk is conferred through molecular pathways involved in synaptic plasticity in the neurons of cortical and subcortical brain regions, including the hippocampus. Synaptic long-term potentiation (LTP) is central to associative learning and memory and depends on a pattern of gene expression in response to neuronal stimulation. Genes related to the induction of LTP have been associated with psychiatric genetic risk, but the specific cell types and timepoints responsible for the association are unknown. Using published genomic and transcriptomic datasets, we studied the relationship between temporally defined gene expression in hippocampal pyramidal neurons following LTP and enrichment for common genetic risk for schizophrenia and bipolar disorder, and for copy number variants (CNVs) and de novo coding variants associated with schizophrenia. We observed that upregulated genes in hippocampal pyramidal neurons at 60 and 120 min following LTP induction were enriched for common variant association with schizophrenia and bipolar disorder subtype I. At 60 min, LTP-induced genes were enriched in duplications from patients with schizophrenia, but this association was not specific to pyramidal neurons, perhaps reflecting the combined effects of CNVs in excitatory and inhibitory neuron subtypes. Gene expression following LTP was not related to enrichment for de novo coding variants from schizophrenia cases. Our findings refine our understanding of the role LTP-related gene sets play in conferring risk to conditions causing psychosis and provide a focus for future studies looking to dissect the molecular mechanisms associated with this risk.

In vivo mapping of protein-protein interactions of schizophrenia risk factors generates an interconnected disease network

Genetic analyses of Schizophrenia (SCZ) patients have identified thousands of risk factors. In silico protein-protein interaction (PPI) network analysis has provided strong evidence that disrupted PPI networks underlie SCZ pathogenesis. In this study, we performed in vivo PPI analysis of several SCZ risk factors in the rodent brain. Using endogenous antibody immunoprecipitations coupled to mass spectrometry (MS) analysis, we constructed a SCZ network comprising 1612 unique PPI with a 5% FDR. Over 90% of the PPI were novel, reflecting the lack of previous PPI MS studies in brain tissue. Our SCZ PPI network was enriched with known SCZ risk factors, which supports the hypothesis that an accumulation of disturbances in selected PPI networks underlies SCZ. We used Stable Isotope Labeling in Mammals (SILAM) to quantitate phencyclidine (PCP) perturbations in the SCZ network and found that PCP weakened most PPI but also led to some enhanced or new PPI. These findings demonstrate that quantitating PPI in perturbed biological states can reveal alterations to network biology.

Mechanisms and Functions of Activity-Regulated Cytoskeleton-Associated Protein in Synaptic Plasticity

Activity-regulated cytoskeleton-associated protein (Arc) is one of the most important regulators of cognitive functions in the brain regions. As a hub protein, Arc plays different roles in modulating synaptic plasticity. Arc supports the maintenance of long-term potentiation (LTP) by regulating actin cytoskeletal dynamics, while it guides the endocytosis of AMPAR in long-term depression (LTD). Moreover, Arc can self-assemble into capsids, leading to a new way of communicating among neurons. The transcription and translation of the immediate early gene Arc are rigorous procedures guided by numerous factors, and RNA polymerase II (Pol II) is considered to regulate the precise timing dynamics of gene expression. Since astrocytes can secrete brain-derived neurotrophic factor (BDNF) and L-lactate, their unique roles in Arc expression are emphasized. Here, we review the entire process of Arc expression and summarize the factors that can affect Arc expression and function, including noncoding RNAs, transcription factors, and posttranscriptional regulations. We also attempt to review the functional states and mechanisms of Arc in modulating synaptic plasticity. Furthermore, we discuss the recent progress in understanding the roles of Arc in the occurrence of major neurological disorders and provide new thoughts for future research on Arc.

Dysfunction of cAMP-Protein Kinase A-Calcium Signaling Axis in Striatal Medium Spiny Neurons: A Role in Schizophrenia and Huntington's Disease Neuropathology

Background

Striatal medium spiny neurons (MSNs) are preferentially lost in Huntington's disease. Genomic studies also implicate a direct role for MSNs in schizophrenia, a psychiatric disorder known to involve cortical neuron dysfunction. It remains unknown whether the two diseases share similar MSN pathogenesis or if neuronal deficits can be attributed to cell type-dependent biological pathways. Transcription factor BCL11B, which is expressed by all MSNs and deep layer cortical neurons, was recently proposed to drive selective neurodegeneration in Huntington's disease and identified as a candidate risk gene in schizophrenia.

Methods

Using human stem cell-derived neurons lacking BCL11B as a model, we investigated cellular pathology in MSNs and cortical neurons in the context of these disorders. Integrative analyses between differentially expressed transcripts and published genome-wide association study datasets identified cell type-specific disease-related phenotypes.

Results

We uncover a role for BCL11B in calcium homeostasis in both neuronal types, while deficits in mitochondrial function and PKA (protein kinase A)-dependent calcium transients are detected only in MSNs. Moreover, BCL11B-deficient MSNs display abnormal responses to glutamate and fail to integrate dopaminergic and glutamatergic stimulation, a key feature of striatal neurons in vivo. Gene enrichment analysis reveals overrepresentation of disorder risk genes among BCL11B-regulated pathways, primarily relating to cAMP-PKA-calcium signaling axis and synaptic signaling.

Conclusions

Our study indicates that Huntington's disease and schizophrenia are likely to share neuronal pathophysiology where dysregulation of intracellular calcium homeostasis is found in both striatal and cortical neurons. In contrast, reduction in PKA signaling and abnormal dopamine/glutamate receptor signaling is largely specific to MSNs.

Contribution of Axon Initial Segment Structure and Channels to Brain Pathology

Brain channelopathies are a group of neurological disorders that result from genetic mutations affecting ion channels in the brain. Ion channels are specialized proteins that play a crucial role in the electrical activity of nerve cells by controlling the flow of ions such as sodium, potassium, and calcium. When these channels are not functioning properly, they can cause a wide range of neurological symptoms such as seizures, movement disorders, and cognitive impairment. In this context, the axon initial segment (AIS) is the site of action potential initiation in most neurons. This region is characterized by a high density of voltage-gated sodium channels (VGSCs), which are responsible for the rapid depolarization that occurs when the neuron is stimulated. The AIS is also enriched in other ion channels, such as potassium channels, that play a role in shaping the action potential waveform and determining the firing frequency of the neuron. In addition to ion channels, the AIS contains a complex cytoskeletal structure that helps to anchor the channels in place and regulate their function. Therefore, alterations in this complex structure of ion channels, scaffold proteins, and specialized cytoskeleton may also cause brain channelopathies not necessarily associated with ion channel mutations. This review will focus on how the AISs structure, plasticity, and composition alterations may generate changes in action potentials and neuronal dysfunction leading to brain diseases. AIS function alterations may be the consequence of voltage-gated ion channel mutations, but also may be due to ligand-activated channels and receptors and AIS structural and membrane proteins that support the function of voltage-gated ion channels.

Resting-state brain functional alterations and their genetic mechanisms in drug-naive first-episode psychosis

Extensive research has established the presence of resting-state brain functional damage in psychosis. However, the genetic mechanisms of such disease phenotype are yet to be unveiled. We investigated resting-state brain functional alterations in patients with drug-naive first-episode psychosis (DFP) by performing a neuroimaging meta-analysis of 8 original studies comprising 500 patients and 469 controls. Combined with the Allen Human Brain Atlas, we further conducted transcriptome-neuroimaging spatial correlations to identify genes whose expression levels were linked to brain functional alterations in DFP, followed by a range of gene functional characteristic analyses. Meta-analysis revealed a mixture of increased and decreased brain function in widespread areas including the default-mode, visual, motor, striatal, and cerebellar systems in DFP. Moreover, these brain functional alterations were spatially associated with the expression of 1662 genes, which were enriched for molecular functions, cellular components, and biological processes of the cerebral cortex, as well as psychiatric disorders including schizophrenia. Specific expression analyses demonstrated that these genes were specifically expressed in the brain tissue, in cortical neurons and immune cells, and during nearly all developmental periods. Concurrently, the genes could construct a protein-protein interaction network supported by hub genes and were linked to multiple behavioral domains including emotion, attention, perception, and motor. Our findings provide empirical evidence for the notion that brain functional damage in DFP involves a complex interaction of polygenes with various functional characteristics.

Genetic mechanisms underlying gray matter volume changes in patients with drug-naive first-episode schizophrenia

Brain structural damage is a typical feature of schizophrenia. Investigating such disease phenotype in patients with drug-naive first-episode schizophrenia (DFSZ) may exclude the confounds of antipsychotics and illness chronicity. However, small sample sizes and marked clinical heterogeneity have precluded definitive identification of gray matter volume (GMV) changes in DFSZ as well as their underlying genetic mechanisms. Here, GMV changes in DFSZ were assessed using a neuroimaging meta-analysis of 19 original studies, including 605 patients and 637 controls. Gene expression data were derived from the Allen Human Brain Atlas and processed with a newly proposed standardized pipeline. Then, we used transcriptome-neuroimaging spatial correlations to identify genes associated with GMV changes in DFSZ, followed by a set of gene functional feature analyses. Meta-analysis revealed consistent GMV reduction in the right superior temporal gyrus, right insula and left inferior temporal gyrus in DFSZ. Moreover, we found that these GMV changes were spatially correlated with expression levels of 1,201 genes, which exhibited a wide range of functional features. Our findings may provide important insights into the genetic mechanisms underlying brain morphological abnormality in schizophrenia.

Deconstructing a Syndrome: Genomic Insights Into PCOS Causal Mechanisms and Classification

Polycystic ovary syndrome (PCOS) is among the most common disorders in women of reproductive age, affecting up to 15% worldwide, depending on the diagnostic criteria. PCOS is characterized by a constellation of interrelated reproductive abnormalities, including disordered gonadotropin secretion, increased androgen production, chronic anovulation, and polycystic ovarian morphology. It is frequently associated with insulin resistance and obesity. These reproductive and metabolic derangements cause major morbidities across the lifespan, including anovulatory infertility and type 2 diabetes (T2D). Despite decades of investigative effort, the etiology of PCOS remains unknown. Familial clustering of PCOS cases has indicated a genetic contribution to PCOS. There are rare Mendelian forms of PCOS associated with extreme phenotypes, but PCOS typically follows a non-Mendelian pattern of inheritance consistent with a complex genetic architecture, analogous to T2D and obesity, that reflects the interaction of susceptibility genes and environmental factors. Genomic studies of PCOS have provided important insights into disease pathways and have indicated that current diagnostic criteria do not capture underlying differences in biology associated with different forms of PCOS. We provide a state-of-the-science review of genetic analyses of PCOS, including an overview of genomic methodologies aimed at a general audience of non-geneticists and clinicians. Applications in PCOS will be discussed, including strengths and limitations of each study. The contributions of environmental factors, including developmental origins, will be reviewed. Insights into the pathogenesis and genetic architecture of PCOS will be summarized. Future directions for PCOS genetic studies will be outlined.

Developmental disruption to the cortical transcriptome and synaptosome in a model of SETD1A loss-of-function

Large-scale genomic studies of schizophrenia implicate genes involved in the epigenetic regulation of transcription by histone methylation and genes encoding components of the synapse. However, the interactions between these pathways in conferring risk to psychiatric illness are unknown. Loss-of-function (LoF) mutations in the gene encoding histone methyltransferase, SETD1A, confer substantial risk to schizophrenia. Among several roles, SETD1A is thought to be involved in the development and function of neuronal circuits. Here, we employed a multi-omics approach to study the effects of heterozygous Setd1a LoF on gene expression and synaptic composition in mouse cortex across five developmental timepoints from embryonic day 14 to postnatal day 70. Using RNA sequencing, we observed that Setd1a LoF resulted in the consistent downregulation of genes enriched for mitochondrial pathways. This effect extended to the synaptosome, in which we found age-specific disruption to both mitochondrial and synaptic proteins. Using large-scale patient genomics data, we observed no enrichment for genetic association with schizophrenia within differentially expressed transcripts or proteins, suggesting they derive from a distinct mechanism of risk from that implicated by genomic studies. This study highlights biological pathways through which SETD1A LOF may confer risk to schizophrenia. Further work is required to determine whether the effects observed in this model reflect human pathology.

Transcriptomic and Proteomic Analysis of CRISPR/Cas9-Mediated ARC-Knockout HEK293 Cells

Arc/Arg3.1 (activity-regulated cytoskeletal-associated protein (ARC)) is a critical regulator of long-term synaptic plasticity and is involved in the pathophysiology of schizophrenia. The functions and mechanisms of human ARC action are poorly understood and worthy of further investigation. To investigate the function of the ARC gene in vitro, we generated an ARC-knockout (KO) HEK293 cell line via CRISPR/Cas9-mediated gene editing and conducted RNA sequencing and label-free LC-MS/MS analysis to identify the differentially expressed genes and proteins in isogenic ARC-KO HEK293 cells. Furthermore, we used bioluminescence resonance energy transfer (BRET) assays to detect interactions between the ARC protein and differentially expressed proteins. Genetic deletion of ARC disturbed multiple genes involved in the extracellular matrix and synaptic membrane. Seven proteins (HSPA1A, ENO1, VCP, HMGCS1, ALDH1B1, FSCN1, and HINT2) were found to be differentially expressed between ARC-KO cells and ARC wild-type cells. BRET assay results showed that ARC interacted with PSD95 and HSPA1A. Overall, we found that ARC regulates the differential expression of genes involved in the extracellular matrix, synaptic membrane, and heat shock protein family. The transcriptomic and proteomic profiles of ARC-KO HEK293 cells presented here provide new evidence for the mechanisms underlying the effects of ARC and molecular pathways involved in schizophrenia pathophysiology.

Schizophrenia Genomics: Convergence on Synaptic Development, Adult Synaptic Plasticity, or Both?

Large-scale genomic studies of schizophrenia have identified hundreds of genetic loci conferring risk to the disorder. This progress offers an important route toward defining the biological basis of the condition and potentially developing new treatments. In this review, we discuss insights from recent genome-wide association study, copy number variant, and exome sequencing analyses of schizophrenia, together with functional genomics data from the pre- and postnatal brain, in relation to synaptic development and function. These data provide strong support for the view that synaptic dysfunction within glutamatergic and GABAergic (gamma-aminobutyric acidergic) neurons of the cerebral cortex, hippocampus, and other limbic structures is a central component of schizophrenia pathophysiology. Implicated genes and functional genomic data suggest that disturbances in synaptic connectivity associated with susceptibility to schizophrenia begin in utero but continue throughout development, with some alleles conferring risk to the disorder through direct effects on synaptic function in adulthood. This model implies that novel interventions for schizophrenia could include broad preventive approaches aimed at enhancing synaptic health during development as well as more targeted treatments aimed at correcting synaptic function in affected adults.

The schizophrenia risk gene Map2k7 regulates responding in a novel contingency-shifting rodent touchscreen gambling task

In schizophrenia, subjects show reduced ability to evaluate and update risk/reward contingencies, showing correspondingly suboptimal performance in the Iowa gambling task. JNK signalling gene variants are associated with schizophrenia risk, and JNK modulates aspects of cognition. We therefore studied the performance of mice hemizygous for genetic deletion of the JNK activator MKK7 (Map2k7+/- mice) in a touchscreen version of the Iowa gambling task, additionally incorporating a novel contingency-switching stage. Map2k7+/- mice performed slightly better than wild-type (WT) littermates in acquisition and performance of the task. Although Map2k7+/- mice adapted well to subtle changes in risk/reward contingencies, they were profoundly impaired when the positions of 'best' and 'worst' choice selections were switched, and still avoided the previous 'worst' choice location weeks after the switch. This demonstrates a precise role for MKK7-JNK signalling in flexibility of risk/reward assessment and suggests that genetic variants affecting this molecular pathway may underlie impairment in this cognitive domain in schizophrenia. Importantly, this new contingency shift adaptation of the rodent touchscreen gambling task has translational utility for characterising these cognitive subprocesses in models of neuropsychiatric disorders.

Evaluation of deep convolutional neural networks for in situ hybridization gene expression image representation

High resolution in situ hybridization (ISH) images of the brain capture spatial gene expression at cellular resolution. These spatial profiles are key to understanding brain organization at the molecular level. Previously, manual qualitative scoring and informatics pipelines have been applied to ISH images to determine expression intensity and pattern. To better capture the complex patterns of gene expression in the human cerebral cortex, we applied a machine learning approach. We propose gene re-identification as a contrastive learning task to compute representations of ISH images. We train our model on an ISH dataset of ~1,000 genes obtained from postmortem samples from 42 individuals. This model reaches a gene re-identification rate of 38.3%, a 13x improvement over random chance. We find that the learned embeddings predict expression intensity and pattern. To test generalization, we generated embeddings in a second dataset that assayed the expression of 78 genes in 53 individuals. In this set of images, 60.2% of genes are re-identified, suggesting the model is robust. Importantly, this dataset assayed expression in individuals diagnosed with schizophrenia. Gene and donor-specific embeddings from the model predict schizophrenia diagnosis at levels similar to that reached with demographic information. Mutations in the most discriminative gene, Sodium Voltage-Gated Channel Beta Subunit 4 (SCN4B), may help understand cardiovascular associations with schizophrenia and its treatment. We have publicly released our source code, embeddings, and models to spur further application to spatial transcriptomics. In summary, we propose and evaluate gene re-identification as a machine learning task to represent ISH gene expression images.

Developmental Profile of Psychiatric Risk Associated With Voltage-Gated Cation Channel Activity

BACKGROUND

Recent breakthroughs in psychiatric genetics have implicated biological pathways onto which genetic risk for psychiatric disorders converges. However, these studies do not reveal the developmental time point(s) at which these pathways are relevant.

METHODS

We aimed to determine the relationship between psychiatric risk and developmental gene expression relating to discrete biological pathways. We used postmortem RNA sequencing data (BrainSeq and BrainSpan) from brain tissue at multiple prenatal and postnatal time points, with summary statistics from recent genome-wide association studies of schizophrenia, bipolar disorder, and major depressive disorder. We prioritized gene sets for overall enrichment of association with each disorder and then tested the relationship between the association of their constituent genes with their relative expression at each developmental stage.

RESULTS

We observed relationships between the expression of genes involved in voltage-gated cation channel activity during early midfetal, adolescence, and early adulthood time points and association with schizophrenia and bipolar disorder, such that genes more strongly associated with these disorders had relatively low expression during early midfetal development and higher expression during adolescence and early adulthood. The relationship with schizophrenia was strongest for the subset of genes related to calcium channel activity, while for bipolar disorder, the relationship was distributed between calcium and potassium channel activity genes.

CONCLUSIONS

Our results indicate periods during development when biological pathways related to the activity of calcium and potassium channels may be most vulnerable to the effects of genetic variants conferring risk for psychiatric disorders. Furthermore, they indicate key time points and potential targets for disorder-specific therapeutic interventions.

Targeting synaptic plasticity in schizophrenia: insights from genomic studies

Patients with schizophrenia experience cognitive dysfunction and negative symptoms that do not respond to current drug treatments. Historical evidence is consistent with the hypothesis that these deficits are due, at least in part, to altered cortical synaptic plasticity (the ability of synapses to strengthen or weaken their activity), making this an attractive pathway for therapeutic intervention. However, while synaptic transmission and plasticity is well understood in model systems, it has been challenging to identify specific therapeutic targets for schizophrenia. New information is emerging from genomic findings, which converge on synaptic plasticity and provide a new window on the neurobiology of schizophrenia. Translating this information into therapeutic advances will require a multidisciplinary and collaborative approach.

Genetic contributors to risk of schizophrenia in the presence of a 22q11.2 deletion

Schizophrenia occurs in about one in four individuals with 22q11.2 deletion syndrome (22q11.2DS). The aim of this International Brain and Behavior 22q11.2DS Consortium (IBBC) study was to identify genetic factors that contribute to schizophrenia, in addition to the ~20-fold increased risk conveyed by the 22q11.2 deletion. Using whole-genome sequencing data from 519 unrelated individuals with 22q11.2DS, we conducted genome-wide comparisons of common and rare variants between those with schizophrenia and those with no psychotic disorder at age ≥25 years. Available microarray data enabled direct comparison of polygenic risk for schizophrenia between 22q11.2DS and independent population samples with no 22q11.2 deletion, with and without schizophrenia (total n = 35,182). Polygenic risk for schizophrenia within 22q11.2DS was significantly greater for those with schizophrenia (padj = 6.73 × 10-6). Novel reciprocal case-control comparisons between the 22q11.2DS and population-based cohorts showed that polygenic risk score was significantly greater in individuals with psychotic illness, regardless of the presence of the 22q11.2 deletion. Within the 22q11.2DS cohort, results of gene-set analyses showed some support for rare variants affecting synaptic genes. No common or rare variants within the 22q11.2 deletion region were significantly associated with schizophrenia. These findings suggest that in addition to the deletion conferring a greatly increased risk to schizophrenia, the risk is higher when the 22q11.2 deletion and common polygenic risk factors that contribute to schizophrenia in the general population are both present.

Genetic association of FMRP targets with psychiatric disorders

Genes encoding the mRNA targets of fragile X mental retardation protein (FMRP) are enriched for genetic association with psychiatric disorders. However, many FMRP targets possess functions that are themselves genetically associated with psychiatric disorders, including synaptic transmission and plasticity, making it unclear whether the genetic risk is truly related to binding by FMRP or is alternatively mediated by the sampling of genes better characterised by another trait or functional annotation. Using published common variant, rare coding variant and copy number variant data, we examined the relationship between FMRP binding and genetic association with schizophrenia, major depressive disorder and bipolar disorder. High-confidence targets of FMRP, derived from studies of multiple tissue types, were enriched for common schizophrenia risk alleles, as well as rare loss-of-function and de novo nonsynonymous variants in schizophrenia cases. Similarly, through common variation, FMRP targets were associated with major depressive disorder, and we present novel evidence of association with bipolar disorder. These relationships could not be explained by other functional annotations known to be associated with psychiatric disorders, including those related to synaptic structure and function. This study reinforces the evidence that targeting by FMRP captures a subpopulation of genes enriched for genetic association with a range of psychiatric disorders.

The Translational Machine: A novel machine-learning approach to illuminate complex genetic architectures

The Translational Machine (TM) is a machine learning (ML)-based analytic pipeline that translates genotypic/variant call data into biologically contextualized features that richly characterize complex variant architectures and permit greater interpretability and biological replication. It also reduces potentially confounding effects of population substructure on outcome prediction. The TM consists of three main components. First, replicable but flexible feature engineering procedures translate genome-scale data into biologically informative features that appropriately contextualize simple variant calls/genotypes within biological and functional contexts. Second, model-free, nonparametric ML-based feature filtering procedures empirically reduce dimensionality and noise of both original genotype calls and engineered features. Third, a powerful ML algorithm for feature selection is used to differentiate risk variant contributions across variant frequency and functional prediction spectra. The TM simultaneously evaluates potential contributions of variants operative under polygenic and heterogeneous models of genetic architecture. Our TM enables integration of biological information (e.g., genomic annotations) within conceptual frameworks akin to geneset-/pathways-based and collapsing methods, but overcomes some of these methods' limitations. The full TM pipeline is executed in R. Our approach and initial findings from its application to a whole-exome schizophrenia case-control data set are presented. These TM procedures extend the findings of the primary investigation and yield novel results.

Targeted sequencing and integrative analysis to prioritize candidate genes in neurodevelopmental disorders

Neurodevelopmental disorders (NDDs) are a group of diseases characterized by high heterogeneity and frequently co-occurring symptoms. The mutational spectrum in patients with NDDs is largely incomplete. Here, we sequenced 547 genes from 1102 patients with NDDs and validated 1271 potential functional variants, including 108 de novo variants (DNVs) in 78 autosomal genes and seven inherited hemizygous variants in six X chromosomal genes. Notably, 36 of these 78 genes are the first to be reported in Chinese patients with NDDs. By integrating our genetic data with public data, we prioritized 212 NDD candidate genes with FDR < 0.1, including 17 novel genes. The novel candidate genes interacted or were co-expressed with known candidate genes, forming a functional network involved in known pathways. We highlighted MSL2, which carried two de novo protein-truncating variants (p.L192Vfs*3 and p.S486Ifs*11) and was frequently connected with known candidate genes. This study provides the mutational spectrum of NDDs in China and prioritizes 212 NDD candidate genes for further functional validation and genetic counseling.

Using protein turnover to expand the applications of transcriptomics

RNA expression and protein abundance are often at odds when measured in parallel, raising questions about the functional implications of transcriptomics data. Here, we present the concept of persistence, which attempts to address this challenge by combining protein half-life data with RNA expression into a single metric that approximates protein abundance. The longer a protein's half-life, the more influence it can have on its surroundings. This data offers a valuable opportunity to gain deeper insight into the functional meaning of transcriptome changes. We demonstrate the application of persistence using schizophrenia (SCZ) datasets, where it greatly improved our ability to predict protein abundance from RNA expression. Furthermore, this approach successfully identified persistent genes and pathways known to have impactful changes in SCZ. These results suggest that persistence is a valuable metric for improving the functional insight offered by transcriptomics data, and extended application of this concept could advance numerous research fields.

Correlation between cortical gene expression and resting-state functional network centrality in healthy young adults

Resting‐state functional connectivity in the human brain is heritable, and previous studies have investigated the genetic basis underlying functional connectivity. However, at present, the molecular mechanisms associated with functional network centrality are still largely unknown. In this study, functional networks were constructed, and the graph‐theory method was employed to calculate network centrality in 100 healthy young adults from the Human Connectome Project. Specifically, functional connectivity strength (FCS), also known as the “degree centrality” of weighted networks, is calculated to measure functional network centrality. A multivariate technique of partial least squares regression (PLSR) was then conducted to identify genes whose spatial expression profiles best predicted the FCS distribution. We found that FCS spatial distribution was significantly positively correlated with the expression of genes defined by the first PLSR component. The FCS‐related genes we identified were significantly enriched for ion channels, axon guidance, and synaptic transmission. Moreover, FCS‐related genes were preferentially expressed in cortical neurons and young adulthood and were enriched in numerous neurodegenerative and neuropsychiatric disorders. Furthermore, a series of validation and robustness analyses demonstrated the reliability of the results. Overall, our results suggest that the spatial distribution of FCS is modulated by the expression of a set of genes associated with ion channels, axon guidance, and synaptic transmission.

GSK-3β Disrupts Neuronal Oscillatory Function to Inhibit Learning and Memory in Male Rats

Alterations in glycogen synthase kinase-3β (GSK-3β) activity have been implicated in disorders of cognitive impairment, including Alzheimer's disease and schizophrenia. Cognitive dysfunction is also characterized by the dysregulation of neuronal oscillatory activity, macroscopic electrical rhythms in brain that are critical to systems communication. A direct functional relationship between GSK-3β and neuronal oscillations has not been elucidated. Therefore, in the present study, using an adeno-associated viral vector containing a persistently active mutant form of GSK-3β, GSK-3β(S9A), the impact of elevated kinase activity in prefrontal cortex (PFC) or ventral hippocampus (vHIP) of rats on neuronal oscillatory activity was evaluated. GSK-3β(S9A)-induced changes in learning and memory were also assessed and the phosphorylation status of tau protein, a substrate of GSK-3β, examined. It was demonstrated that increasing GSK-3β(S9A) activity in either the PFC or vHIP had similar effects on neuronal oscillatory activity, enhancing theta and/or gamma spectral power in one or both regions. Increasing PFC GSK-3β(S9A) activity additionally suppressed high gamma PFC-vHIP coherence. These changes were accompanied by deficits in recognition memory, spatial learning, and/or reversal learning. Elevated pathogenic tau phosphorylation was also evident in regions where GSK-3β(S9A) activity was upregulated. The neurophysiological and learning and memory deficits induced by GSK-3β(S9A) suggest that aberrant GSK-3β signalling may not only play an early role in cognitive decline in Alzheimer's disease but may also have a more central involvement in disorders of cognitive dysfunction through the regulation of neurophysiological network function.

Multiple Rare Risk Coding Variants in Postsynaptic Density-Related Genes Associated With Schizophrenia Susceptibility

Objective

Schizophrenia is a chronic debilitating neurobiological disorder of aberrant synaptic connectivity and synaptogenesis. Postsynaptic density (PSD)–related proteins in N-methyl-D-aspartate receptor–postsynaptic signaling complexes are crucial to regulating the synaptic transmission and functions of various synaptic receptors. This study examined the role of PSD-related genes in susceptibility to schizophrenia.

Methods

We resequenced 18 genes encoding the disks large-associated protein (DLGAP), HOMER, neuroligin (NLGN), neurexin, and SH3 and multiple ankyrin repeat domains (SHANK) protein families in 98 schizophrenic patients with family psychiatric history using semiconductor sequencing. We analyzed the protein function of the identified rare schizophrenia-associated mutants via immunoblotting and immunocytochemistry.

Results

We identified 50 missense heterozygous mutations in 98 schizophrenic patients with family psychiatric history, and in silico analysis revealed some as damaging or pathological to the protein function. Ten missense mutations were absent from the dbSNP database, the gnomAD (non-neuro) dataset, and 1,517 healthy controls from Taiwan BioBank. Immunoblotting revealed eight missense mutants with altered protein expressions in cultured cells compared with the wild type.

Conclusion

Our findings suggest that PSD-related genes, especially the NLGN, SHANK, and DLGAP families, harbor rare functional mutations that might alter protein expression in some patients with schizophrenia, supporting contributing rare coding variants into the genetic architecture of schizophrenia.

Disrupted Sleep and Circadian Rhythms in Schizophrenia and Their Interaction With Dopamine Signaling

Sleep and circadian rhythm disruption (SCRD) is a common feature of schizophrenia, and is associated with symptom severity and patient quality of life. It is commonly manifested as disturbances to the sleep/wake cycle, with sleep abnormalities occurring in up to 80% of patients, making it one of the most common symptoms of this disorder. Severe circadian misalignment has also been reported, including non-24 h periods and phase advances and delays. In parallel, there are alterations to physiological circadian parameters such as body temperature and rhythmic hormone production. At the molecular level, alterations in the rhythmic expression of core clock genes indicate a dysfunctional circadian clock. Furthermore, genetic association studies have demonstrated that mutations in several clock genes are associated with a higher risk of schizophrenia. Collectively, the evidence strongly suggests that sleep and circadian disruption is not only a symptom of schizophrenia but also plays an important causal role in this disorder. The alterations in dopamine signaling that occur in schizophrenia are likely to be central to this role. Dopamine is well-documented to be involved in the regulation of the sleep/wake cycle, in which it acts to promote wakefulness, such that elevated dopamine levels can disturb sleep. There is also evidence for the influence of dopamine on the circadian clock, such as through entrainment of the master clock in the suprachiasmatic nuclei (SCN), and dopamine signaling itself is under circadian control. Therefore dopamine is closely linked with sleep and the circadian system; it appears that they have a complex, bidirectional relationship in the pathogenesis of schizophrenia, such that disturbances to one exacerbate abnormalities in the other. This review will provide an overview of the evidence for a role of SCRD in schizophrenia, and examine the interplay of this with altered dopamine signaling. We will assess the evidence to suggest common underlying mechanisms in the regulation of sleep/circadian rhythms and the pathophysiology of schizophrenia. Improvements in sleep are associated with improvements in symptoms, along with quality of life measures such as cognitive ability and employability. Therefore the circadian system holds valuable potential as a new therapeutic target for this disorder.

Translating insights from neuropsychiatric genetics and genomics for precision psychiatry

The primary aim of precision medicine is to tailor healthcare more closely to the needs of individual patients. This requires progress in two areas: the development of more precise treatments and the ability to identify patients or groups of patients in the clinic for whom such treatments are likely to be the most effective. There is widespread optimism that advances in genomics will facilitate both of these endeavors. It can be argued that of all medical specialties psychiatry has most to gain in these respects, given its current reliance on syndromic diagnoses, the minimal foundation of existing mechanistic knowledge, and the substantial heritability of psychiatric phenotypes. Here, we review recent advances in psychiatric genomics and assess the likely impact of these findings on attempts to develop precision psychiatry. Emerging findings indicate a high degree of polygenicity and that genetic risk maps poorly onto the diagnostic categories used in the clinic. The highly polygenic and pleiotropic nature of psychiatric genetics will impact attempts to use genomic data for prediction and risk stratification, and also poses substantial challenges for conventional approaches to gaining biological insights from genetic findings. While there are many challenges to overcome, genomics is building an empirical platform upon which psychiatry can now progress towards better understanding of disease mechanisms, better treatments, and better ways of targeting treatments to the patients most likely to benefit, thus paving the way for precision psychiatry.

Pathogenesis and management of Brugada syndrome in schizophrenia: A scoping review

CONTEXT

Excess cardiovascular morbidity and an increased prevalence of sudden cardiac death (SCD) contributes to premature mortality in schizophrenia. Brugada syndrome (BrS) is an important but underrecognized cause of SCD. It is more commonly seen in schizophrenia than in general population controls.

METHODS

We conducted a scoping review to describe the pathogenesis of BrS in schizophrenia and to identify the psychotropic medications that increase the risk of unmasking BrS and associated ventricular arrhythmias resulting in SCD.

FINDINGS

Schizophrenia and BrS share similar calcium channel abnormalities, which may result in aberrant myocardial conductivity. It remains uncertain if there is a genetic pre-disposition for BrS in a subset of patients with schizophrenia. However, the unmasking of Brugada ECG patterns with the use of certain antipsychotics and antidepressants increases the risk of precipitating SCD, independent of QT prolongation.

CONCLUSIONS AND FUTURE DIRECTIONS

Specific cardiology assessment and interventions may be required for the congenital or unmasked Brugada ECG pattern in schizophrenia. The current long-term standard of care for BrS is an implantable cardioverter defibrillator (ICD), but post-implantation psychological effects must be considered. Careful use of antipsychotic and other psychotropic medications is necessary to minimize proarrhythmic effects due to impact on cardiac sodium and calcium ion channels. When prescribing such drugs to patients with schizophrenia, clinicians should be mindful of the potentially fatal unmasking of Brugada ECG patterns and how to manage it. We present recommendations for psychiatrists managing this patient population.