Autism Risk Genes Research Articles

Abstract 2459: Elucidating the role of autism risk gene TAOK2 in neurodevelopment and disease

Abstract 2459: Elucidating the role of autism risk gene TAOK2 in neurodevelopment and disease

CRISPR/Cas9-Induced Inactivation of the Autism-Risk Gene setd5 Leads to Social Impairments in Zebrafish.

Haploinsufficiency of the SETD5 gene, encoding a SET domain-containing histone methyltransferase, has been identified as a cause of intellectual disability and Autism Spectrum Disorder (ASD). Recently, the zebrafish has emerged as a valuable model to study neurodevelopmental disorders because of its genetic tractability, robust behavioral traits and amenability to high-throughput drug screening. To model human SETD5 haploinsufficiency, we generated zebrafish setd5 mutants using the CRISPR/Cas9 technology and characterized their morphological, behavioral and molecular phenotypes. According to our observation that setd5 is expressed in adult zebrafish brain, including those areas controlling social behavior, we found that setd5 heterozygous mutants exhibit defective aggregation and coordination abilities required for shoaling interactions, as well as indifference to social stimuli. Interestingly, impairment in social interest is rescued by risperidone, an antipsychotic drug used to treat behavioral traits in ASD individuals. The molecular analysis underscored the downregulation of genes encoding proteins involved in the synaptic structure and function in the adult brain, thus suggesting that brain hypo-connectivity could be responsible for the social impairments of setd5 mutant fishes. The zebrafish setd5 mutants display ASD-like features and are a promising setd5 haploinsufficiency model for drug screening aimed at reversing the behavioral phenotypes.

Neural Organoids Making Connections, Getting Real

Neural Organoids Making Connections, Getting Real

Neuron-specific protein network mapping of autism risk genes identifies shared biological mechanisms and disease-relevant pathologies.

There are hundreds of risk genes associated with autism spectrum disorder (ASD), but signaling networks at the protein level remain unexplored. We use neuron-specific proximity-labeling proteomics (BioID2) to identify protein-protein interaction (PPI) networks for 41 ASD risk genes. Neuron-specific PPI networks, including synaptic transmission proteins, are disrupted by de novo missense variants. The PPI network map reveals convergent pathways, including mitochondrial/metabolic processes, Wnt signaling, and MAPK signaling. CRISPR knockout displays an association between mitochondrial activity and ASD risk genes. The PPI network shows an enrichment of 112 additional ASD risk genes and differentially expressed genes from postmortem ASD patients. Clustering of risk genes based on PPI networks identifies gene groups corresponding to clinical behavior score severity. Our data report that cell type-specific PPI networks can identify individual and convergent ASD signaling networks, provide a method to assess patient variants, and highlight biological insight into disease mechanisms and sub-cohorts of ASD.

Elevated exposures to persistent endocrine disrupting compounds impact the sperm methylome in regions associated with autism spectrum disorder.

Environmental exposures to endocrine disrupting compounds (EDCs) such as the organochlorines have been linked with various diseases including neurodevelopmental disorders. Autism spectrum disorder (ASD) is a highly complex neurodevelopmental disorder that is considered strongly genetic in origin due to its high heritability. However, the rapidly rising prevalence of ASD suggests that environmental factors may also influence risk for ASD. In the present study, whole genome bisulfite sequencing was used to identify genome-wide differentially methylated regions (DMRs) in a total of 52 sperm samples from a cohort of men from the Faroe Islands (Denmark) who were equally divided into high and low exposure groups based on their serum levels of the long-lived organochlorine 1,1-dichloro-2,2-bis(p-chlorophenyl)ethylene (DDE), a primary breakdown product of the now banned insecticide dichlorodiphenyltrichloroethane (DDT). Aside from being considered a genetic isolate, inhabitants of the Faroe Islands have a native diet that potentially exposes them to a wide range of seafood neurotoxicants in the form of persistent organic pollutants (POPs). The DMRs were mapped to the human genome using Bismark, a 3-letter aligner used for methyl-seq analyses. Gene ontology, functional, and pathway analyses of the DMR-associated genes showed significant enrichment for genes involved in neurological functions and neurodevelopmental processes frequently impacted by ASD. Notably, these genes also significantly overlap with autism risk genes as well as those previously identified in sperm from fathers of children with ASD in comparison to that of fathers of neurotypical children. These results collectively suggest a possible mechanism involving altered methylation of a significant number of neurologically relevant ASD risk genes for introducing epigenetic changes associated with environmental exposures into the sperm methylome. Such changes may provide the potential for transgenerational inheritance of ASD as well as other disorders.

Potential Cross Talk between Autism Risk Genes and Neurovascular Molecules: A Pilot Study on Impact of Blood Brain Barrier Integrity.

Autism Spectrum Disorder (ASD) is a common pediatric neurobiological disorder with up to 80% of genetic etiologies. Systems biology approaches may make it possible to test novel therapeutic strategies targeting molecular pathways to alleviate ASD symptoms. A clinical database of autism subjects was queried for individuals with a copy number variation (CNV) on microarray, Vineland, and Parent Concern Questionnaire scores. Pathway analyses of genes from pathogenic CNVs yielded 659 genes whose protein–protein interactions and mRNA expression mapped 121 genes with maximal antenatal expression in 12 brain regions. A Research Domain Criteria (RDoC)-derived neural circuits map revealed significant differences in anxiety, motor, and activities of daily living skills scores between altered CNV genes and normal microarrays subjects, involving Positive Valence (reward), Cognition (IQ), and Social Processes. Vascular signaling was identified as a biological process that may influence these neural circuits. Neuroinflammation, microglial activation, iNOS and 3-nitrotyrosine increase in the brain of Semaphorin 3F- Neuropilin 2 (Sema 3F-NRP2) KO, an ASD mouse model, agree with previous reports in the brain of ASD individuals. Signs of platelet deposition, activation, release of serotonin, and albumin leakage in ASD-relevant brain regions suggest possible blood brain barrier (BBB) deficits. Disruption of neurovascular signaling and BBB with neuroinflammation may mediate causative pathophysiology in some ASD subgroups. Although preliminary, these data demonstrate the potential for developing novel therapeutic strategies based on clinically derived data, genomics, cognitive neuroscience, and basic neuroscience methods.

Autism-Risk Gene necab2 Regulates Psychomotor and Social Behavior as a Neuronal Modulator of mGluR1 Signaling.

BackgroundDe novo deletion of the neuronal calcium-binding protein 2 (NECAB2) locus is associated with idiopathic autism spectrum disorders (ASDs). The in vivo function of NECAB2 in the brain remains largely elusive.MethodsWe investigated the morphological and behavioral profiles of both necab2 knock-out and overexpression zebrafish models. The expression pattern and molecular role of necab2 were probed through a combination of in vitro and in vivo assays.ResultsWe show that Necab2 is a neuronal specific, cytoplasmic, and membrane-associated protein, abundantly expressed in the telencephalon, habenula, and cerebellum. Necab2 is distributed peri-synaptically in subsets of glutamatergic and GABAergic neurons. CRISPR/Cas9-generated necab2 knock-out zebrafish display normal morphology but exhibit a decrease in locomotor activity and thigmotaxis with impaired social interaction only in males. Conversely, necab2 overexpression yields behavioral phenotypes opposite to the loss-of-function. Proteomic profiling uncovers a role of Necab2 in modulating signal transduction of G-protein coupled receptors. Specifically, co-immunoprecipitation, immunofluorescence, and confocal live-cell imaging suggest a complex containing NECAB2 and the metabotropic glutamate receptor 1 (mGluR1). In vivo measurement of phosphatidylinositol 4,5-bisphosphate further substantiates that Necab2 promotes mGluR1 signaling.ConclusionsNecab2 regulates psychomotor and social behavior via modulating a signaling cascade downstream of mGluR1.

WDFY3 mutation alters laminar position and morphology of cortical neurons

BackgroundProper cerebral cortical development depends on the tightly orchestrated migration of newly born neurons from the inner ventricular and subventricular zones to the outer cortical plate. Any disturbance in this process during prenatal stages may lead to neuronal migration disorders (NMDs), which can vary in extent from focal to global. Furthermore, NMDs show a substantial comorbidity with other neurodevelopmental disorders, notably autism spectrum disorders (ASDs). Our previous work demonstrated focal neuronal migration defects in mice carrying loss-of-function alleles of the recognized autism risk gene WDFY3. However, the cellular origins of these defects in Wdfy3 mutant mice remain elusive and uncovering it will provide critical insight into WDFY3-dependent disease pathology.MethodsHere, in an effort to untangle the origins of NMDs in Wdfy3lacZ mice, we employed mosaic analysis with double markers (MADM). MADM technology enabled us to genetically distinctly track and phenotypically analyze mutant and wild-type cells concomitantly in vivo using immunofluorescent techniques.ResultsWe revealed a cell autonomous requirement of WDFY3 for accurate laminar positioning of cortical projection neurons and elimination of mispositioned cells during early postnatal life. In addition, we identified significant deviations in dendritic arborization, as well as synaptic density and morphology between wild type, heterozygous, and homozygous Wdfy3 mutant neurons in Wdfy3-MADM reporter mice at postnatal stages.LimitationsWhile Wdfy3 mutant mice have provided valuable insight into prenatal aspects of ASD pathology that remain inaccessible to investigation in humans, like most animal models, they do not a perfectly replicate all aspects of human ASD biology. The lack of human data makes it indeterminate whether morphological deviations described here apply to ASD patients or some of the other neurodevelopmental conditions associated with WDFY3 mutation.ConclusionsOur genetic approach revealed several cell autonomous requirements of WDFY3 in neuronal development that could underlie the pathogenic mechanisms of WDFY3-related neurodevelopmental conditions. The results are also consistent with findings in other ASD animal models and patients and suggest an important role for WDFY3 in regulating neuronal function and interconnectivity in postnatal life.

A Bayesian framework to integrate multi-level genome-scale data for Autism risk gene prioritization

BackgroundAutism spectrum disorder (ASD) is a group of complex neurodevelopment disorders with a strong genetic basis. Large scale sequencing studies have identified over one hundred ASD risk genes. Nevertheless, the vast majority of ASD risk genes remain to be discovered, as it is estimated that more than 1000 genes are likely to be involved in ASD risk. Prioritization of risk genes is an effective strategy to increase the power of identifying novel risk genes in genetics studies of ASD. As ASD risk genes are likely to exhibit distinct properties from multiple angles, we reason that integrating multiple levels of genomic data is a powerful approach to pinpoint genuine ASD risk genes.ResultsWe present BNScore, a Bayesian model selection framework to probabilistically prioritize ASD risk genes through explicitly integrating evidence from sequencing-identified ASD genes, biological annotations, and gene functional network. We demonstrate the validity of our approach and its improved performance over existing methods by examining the resulting top candidate ASD risk genes against sets of high-confidence benchmark genes and large-scale ASD genome-wide association studies. We assess the tissue-, cell type- and development stage-specific expression properties of top prioritized genes, and find strong expression specificity in brain tissues, striatal medium spiny neurons, and fetal developmental stages.ConclusionsIn summary, we show that by integrating sequencing findings, functional annotation profiles, and gene-gene functional network, our proposed BNScore provides competitive performance compared to current state-of-the-art methods in prioritizing ASD genes. Our method offers a general and flexible strategy to risk gene prioritization that can potentially be applied to other complex traits as well.

Neural Hyperactivity Is a Core Pathophysiological Change Induced by Deletion of a High Autism Risk Gene Ash1L in the Mouse Brain.

ASH1L is one of the highest risk genes associated with autism spectrum disorder (ASD) and intellectual disability (ID). Our recent studies demonstrate that loss of Ash1l in the mouse brain is sufficient to induce ASD/ID-like behavioral and cognitive deficits, suggesting that disruptive ASH1L mutations are likely to have a positive correlation with ASD/ID genesis. However, the core pathophysiological changes in the Ash1l-deficient brain remain largely unknown. Here we show that loss of Ash1l in the mouse brain causes locomotor hyperactivity, high metabolic activity, and hyperactivity-related disturbed sleep and lipid metabolic changes. In addition, the mutant mice display lower thresholds for the convulsant reagent-induced epilepsy and increased neuronal activities in multiple brain regions. Thus, our current study reveals that neural hyperactivity is a core pathophysiological change in the Ash1l-deficient mouse brain, which may function as a brain-level mechanism leading to the Ash1l-deletion-induced brain functional abnormalities and autistic-like behavioral deficits.

SeGMM: A New Tool for Gender Determination From Massively Parallel Sequencing Data.

In clinical genetic testing, checking the concordance between self-reported gender and genotype-inferred gender from genomic data is a significant quality control measure because mismatched gender due to sex chromosomal abnormalities or misregistration of clinical information can significantly affect molecular diagnosis and treatment decisions. Targeted gene sequencing (TGS) is widely recommended as a first-tier diagnostic step in clinical genetic testing. However, the existing gender-inference tools are optimized for whole genome and whole exome data and are not adequate and accurate for analyzing TGS data. In this study, we validated a new gender-inference tool, seGMM, which uses unsupervised clustering (Gaussian mixture model) to determine the gender of a sample. The seGMM tool can also identify sex chromosomal abnormalities in samples by aligning the sequencing reads from the genotype data. The seGMM tool consistently demonstrated >99% gender-inference accuracy in a publicly available 1,000-gene panel dataset from the 1,000 Genomes project, an in-house 785 hearing loss gene panel dataset of 16,387 samples, and a 187 autism risk gene panel dataset from the Autism Clinical and Genetic Resources in China (ACGC) database. The performance and accuracy of seGMM was significantly higher for the targeted gene sequencing (TGS), whole exome sequencing (WES), and whole genome sequencing (WGS) datasets compared to the other existing gender-inference tools such as PLINK, seXY, and XYalign. The results of seGMM were confirmed by the short tandem repeat analysis of the sex chromosome marker gene, amelogenin. Furthermore, our data showed that seGMM accurately identified sex chromosomal abnormalities in the samples. In conclusion, the seGMM tool shows great potential in clinical genetics by determining the sex chromosomal karyotypes of samples from massively parallel sequencing data with high accuracy.

Astrocytic Gap Junctions Contribute to Aberrant Neuronal Synchronization in a Mouse Model of MeCP2 Duplication Syndrome.

Abnormal synchronous neuronal activity has been widely detected by brain imaging of autistic patients, but its underlying neural mechanism remains unclear. Compared with wild-type mice, our in vivo two-photon imaging showed that transgenic (Tg1) mice over-expressing human autism risk gene MeCP2 exhibited higher neuronal synchrony in the young but lower synchrony in the adult stage. Whole-cell recording of neuronal pairs in brain slices revealed that higher neuronal synchrony in young postnatal Tg1 mice was attributed mainly to more prevalent giant slow inward currents (SICs). Both in vivo and slice imaging further demonstrated more dynamic activity and higher synchrony in astrocytes from young Tg1 mice. Blocking astrocytic gap junctions markedly decreased the generation of SICs and overall cell synchrony in the Tg1 brain. Furthermore, the expression level of Cx43 protein and the coupling efficiency of astrocyte gap junctions remained unchanged in Tg1 mice. Thus, astrocytic gap junctions facilitate but do not act as a direct trigger for the abnormal neuronal synchrony in young Tg1 mice, revealing the potential role of the astrocyte network in the pathogenesis of MeCP2 duplication syndrome.

Autism risk gene POGZ promotes chromatin accessibility and expression of clustered synaptic genes.

SUMMARYDeleterious genetic variants in POGZ, which encodes the chromatin regulator Pogo Transposable Element with ZNF Domain protein, are strongly associated with autism spectrum disorder (ASD). Although it is a high-confidence ASD risk gene, the neurodevelopmental functions of POGZ remain unclear. Here we reveal the genomic binding of POGZ in the developing forebrain at euchromatic loci and gene regulatory elements (REs).We profile chromatin accessibility and gene expression in Pogz−/− mice and show that POGZ promotes the active chromatin state and transcription of clustered synaptic genes. We further demonstrate that POGZ forms a nuclear complex and co-occupies loci with ADNP, another high-confidence ASD risk gene, and provide evidence that POGZ regulates other neurodevelopmental disorder risk genes as well. Our results reveal a neurodevelopmental function of an ASD risk gene and identify molecular targets that may elucidate its function in ASD.

DSCAM Deficiency Leads to Premature Spine Maturation and Autism-like Behaviors.

Mutations in some cell adhesion molecules (CAMs) cause abnormal synapse formation and maturation, and serve as one of the potential mechanisms of autism spectrum disorders (ASDs). Recently, DSCAM (Down syndrome cell adhesion molecule) was found to be a high-risk gene for autism. However, it is still unclear how DSCAM contributes to ASD. Here, we show that DSCAM expression was downregulated following synapse maturation, and that DSCAM deficiency caused accelerated dendritic spine maturation during early postnatal development. Mechanistically, the extracellular domain of DSCAM interacts with neuroligin1 (NLGN1) to block the NLGN1-neurexin1β (NRXN1β) interaction. DSCAM extracellular domain was able to rescue spine overmaturation in DSCAM knockdown neurons. Precocious spines in DSCAM-deficient mice showed increased glutamatergic transmission in the developing cortex and induced autism-like behaviors, such as social novelty deficits and repetitive behaviors. Thus, DSCAM might be a repressor that prevents premature spine maturation and excessive glutamatergic transmission, and its deficiency could lead to autism-like behaviors. Our study provides new insight into the potential pathophysiological mechanisms of ASDs.SIGNIFICANCE STATEMENT DSCAM is not only associated with Down syndrome but is also a strong autism risk gene based on large-scale sequencing analysis. However, it remains unknown exactly how DSCAM contributes to autism. In mice, either neuron- and astrocyte-specific or pyramidal neuron-specific DSCAM deficiencies resulted in autism-like behaviors and enhanced spatial memory. In addition, DSCAM knockout or knockdown in pyramidal neurons led to increased dendritic spine maturation. Mechanistically, the extracellular domain of DSCAM binds to NLGN1 and inhibits NLGN1-NRXN1β interaction, which can rescue abnormal spine maturation induced by DSCAM deficiency. Our research demonstrates that DSCAM negatively modulates spine maturation, and that DSCAM deficiency leads to excessive spine maturation and autism-like behaviors, thus providing new insight into a potential pathophysiological mechanism of autism.

SHANK3 conformation regulates direct actin binding and crosstalk with Rap1 signaling

Actin-rich cellular protrusions direct versatile biological processes from cancer cell invasion to dendritic spine development. The stability, morphology, and specific biological functions of these protrusions are regulated by crosstalk between three main signaling axes: integrins, actin regulators, and small guanosine triphosphatases (GTPases). SHANK3 is a multifunctional scaffold protein, interacting with several actin-binding proteins and a well-established autism risk gene. Recently, SHANK3 was demonstrated to sequester integrin-activating small GTPases Rap1 and R-Ras to inhibit integrin activity via its Shank/ProSAP N-terminal (SPN) domain. Here, we demonstrate that, in addition to scaffolding actin regulators and actin-binding proteins, SHANK3 interacts directly with actin through its SPN domain. Molecular simulations and targeted mutagenesis of the SPN-ankyrin repeat region (ARR) interface reveal that actin binding is inhibited by an intramolecular closed conformation of SHANK3, where the adjacent ARR domain covers the actin-binding interface of the SPN domain. Actin and Rap1 compete with each other for binding to SHANK3, and mutation of SHANK3, resulting in reduced actin binding, augments inhibition of Rap1-mediated integrin activity. This dynamic crosstalk has functional implications for cell morphology and integrin activity in cancer cells. In addition, SHANK3-actin interaction regulates dendritic spine morphology in neurons and autism-linked phenotypes invivo.

Atypical genomic cortical patterning in autism with poor early language outcome.

Cortical regionalization develops via genomic patterning along anterior-posterior (A-P) and dorsal-ventral (D-V) gradients. Here, we find that normative A-P and D-V genomic patterning of cortical surface area (SA) and thickness (CT), present in typically developing and autistic toddlers with good early language outcome, is absent in autistic toddlers with poor early language outcome. Autistic toddlers with poor early language outcome are instead specifically characterized by a secondary and independent genomic patterning effect on CT. Genes involved in these effects can be traced back to midgestational A-P and D-V gene expression gradients and different prenatal cell types (e.g., progenitor cells and excitatory neurons), are functionally important for vocal learning and human-specific evolution, and are prominent in prenatal coexpression networks enriched for high-penetrance autism risk genes. Autism with poor early language outcome may be explained by atypical genomic cortical patterning starting in prenatal development, which may detrimentally affect later regional functional specialization and circuit formation.

Syngap1 regulates experience-dependent cortical ensemble plasticity by promoting in vivo excitatory synapse strengthening

A significant proportion of autism risk genes regulate synapse function, including plasticity, which is believed to contribute to behavioral abnormalities. However, it remains unclear how impaired synapse plasticity contributes to network-level processes linked to adaptive behaviors, such as experience-dependent ensemble plasticity. We found that Syngap1, a major autism risk gene, promoted measures of experience-dependent excitatory synapse strengthening in the mouse cortex, including spike-timing-dependent glutamatergic synaptic potentiation and presynaptic bouton formation. Synaptic depression and bouton elimination were normal in Syngap1 mice. Within cortical networks, Syngap1 promoted experience-dependent increases in somatic neural activity in weakly active neurons. In contrast, plastic changes to highly active neurons from the same ensemble that paradoxically weaken with experience were unaffected. Thus, experience-dependent excitatory synapse strengthening mediated by Syngap1 shapes neuron-specific plasticity within cortical ensembles. We propose that other genes regulate neuron-specific weakening within ensembles, and together, these processes function to redistribute activity within cortical networks during experience.

\u201cGuilt by association\u201d is not competitive with genetic association for identifying autism risk genes

Discovering genes involved in complex human genetic disorders is a major challenge. Many have suggested that machine learning (ML) algorithms using gene networks can be used to supplement traditional genetic association-based approaches to predict or prioritize disease genes. However, questions have been raised about the utility of ML methods for this type of task due to biases within the data, and poor real-world performance. Using autism spectrum disorder (ASD) as a test case, we sought to investigate the question: can machine learning aid in the discovery of disease genes? We collected 13 published ASD gene prioritization studies and evaluated their performance using known and novel high-confidence ASD genes. We also investigated their biases towards generic gene annotations, like number of association publications. We found that ML methods which do not incorporate genetics information have limited utility for prioritization of ASD risk genes. These studies perform at a comparable level to generic measures of likelihood for the involvement of genes in any condition, and do not out-perform genetic association studies. Future efforts to discover disease genes should be focused on developing and validating statistical models for genetic association, specifically for association between rare variants and disease, rather than developing complex machine learning methods using complex heterogeneous biological data with unknown reliability.

Prioritizing Autism Risk Genes Using Personalized Graphical Models Estimated From Single-Cell RNA-seq Data

Hundreds of autism risk genes have been reported recently, mainly based on genetic studies where these risk genes have more de novo mutations in autism subjects than healthy controls. However, as a complex disease, autism is likely associated with more risk genes and many of them may not be identifiable through de novo mutations. We hypothesize that more autism risk genes can be identified through their connections with known autism risk genes in personalized gene–gene interaction graphs. We estimate such personalized graphs using single-cell RNA sequencing (scRNA-seq) while appropriately modeling the cell dependence and possible zero-inflation in the scRNA-seq data. The sample size, which is the number of cells per individual, ranges from 891 to 1241 in our case study using scRNA-seq data in autism subjects and controls. We consider 1500 genes in our analysis. Since the number of genes is larger or comparable to the sample size, we perform penalized estimation. We score each gene’s relevance by applying a simple graph kernel smoothing method to each personalized graph. The molecular functions of the top-scored genes are related to autism diseases. For example, a candidate gene RYR2 that encodes protein ryanodine receptor 2 is involved in neurotransmission, a process that is impaired in ASD patients. While our method provides a systemic and unbiased approach to prioritize autism risk genes, the relevance of these genes needs to be further validated in functional studies. Supplementary materials for this article, including a standardized description of the materials available for reproducing the work, are available as an online supplement.

Anterior thalamic dysfunction underlies cognitive deficits in a subset of neuropsychiatric disease models

Neuropsychiatric disorders are often accompanied by cognitive impairments/intellectual disability (ID). It is not clear whether there are converging mechanisms underlying these debilitating impairments. We found that many autism and schizophrenia risk genes are expressed in the anterodorsal subdivision (AD) of anterior thalamic nuclei, which has reciprocal connectivity with learning and memory structures. CRISPR-Cas9 knockdown of multiple risk genes selectively in AD thalamus led to memory deficits. While the AD is necessary for contextual memory encoding, the neighboring anteroventral subdivision (AV) regulates memory specificity. These distinct functions of AD and AV are mediated through their projections to retrosplenial cortex, using differential mechanisms. Furthermore, knockdown of autism and schizophrenia risk genes PTCHD1, YWHAG, or HERC1 from AD led to neuronal hyperexcitability, and normalization of hyperexcitability rescued memory deficits in these models. This study identifies converging cellular to circuit mechanisms underlying cognitive deficits in a subset of neuropsychiatric disease models.