The Psychiatric Cell Map Initiative: A Convergent Systems Biological Approach to Illuminating Key Molecular Pathways in Neuropsychiatric Disorders

Autism gene variants disrupt enteric neuron migration and cause gastrointestinal dysmotility

The comorbidity of autism spectrum disorders and severe gastrointestinal symptoms is well-established, yet the molecular underpinnings remain unknown. The identification of high-confidence large-effect autism risk genes offers the opportunity to identify convergent, underlying biology by studying these genes in the context of the gastrointestinal system. Here we show that the expression of these genes is enriched in human prenatal gut neurons as well as their migratory progenitors, suggesting that the development and/or function of these neurons may be disrupted by autism-associated pathogenic variants, leading to gastrointestinal dysfunction. Here we document the prevalence of gastrointestinal issues in patients with large-effect variants in sixteen of these genes, highlighting dysmotility, consistent with potential enteric neuron dysfunction. Using the high-throughput diploid frog Xenopus tropicalis , we individually target five of these genes ( SYNGAP1, CHD8, SCN2A, CHD2 , and DYRK1A ) and observe disrupted enteric neuronal progenitor migration for each. More extensive analysis of DYRK1A reveals that perturbation causes gut dysmotility in vivo , which can be ameliorated by treatment with a selective serotonin reuptake inhibitor (escitalopram) or a serotonin receptor 6 agonist, identified by in vivo drug screening. This work suggests that atypical development of enteric neurons contributes to the gastrointestinal distress commonly seen in individuals with autism and that increasing serotonin signaling may be a productive therapeutic avenue.

Modelling human genetic disorders in Xenopus tropicalis

Recent progress in human disease genetics is leading to rapid advances in understanding pathobiological mechanisms. However, the sheer number of risk-conveying genetic variants being identified demands in vivo model systems that are amenable to functional analyses at scale. Here we provide a practical guide for using the diploid frog species Xenopus tropicalis to study many genes and variants to uncover conserved mechanisms of pathobiology relevant to human disease. We discuss key considerations in modelling human genetic disorders: genetic architecture, conservation, phenotyping strategy and rigour, as well as more complex topics, such as penetrance, expressivity, sex differences and current challenges in the field. As the patient-driven gene discovery field expands significantly, the cost-effective, rapid and higher throughput nature of Xenopus make it an essential member of the model organism armamentarium for understanding gene function in development and in relation to disease.

A foundational atlas of autism protein interactions reveals molecular convergence

Translating high-confidence (hc) autism spectrum disorder (ASD) genes into viable treatment targets remains elusive. We constructed a foundational protein-protein interaction (PPI) network in HEK293T cells involving 100 hcASD risk genes, revealing over 1,800 PPIs (87% novel). Interactors, expressed in the human brain and enriched for ASD but not schizophrenia genetic risk, converged on protein complexes involved in neurogenesis, tubulin biology, transcriptional regulation, and chromatin modification. A PPI map of 54 patient-derived missense variants identified differential physical interactions, and we leveraged AlphaFold-Multimer predictions to prioritize direct PPIs and specific variants for interrogation in Xenopus tropicalis and human forebrain organoids. A mutation in the transcription factor FOXP1 led to reconfiguration of DNA binding sites and altered development of deep cortical layer neurons in forebrain organoids. This work offers new insights into molecular mechanisms underlying ASD and describes a powerful platform to develop and test therapeutic strategies for many genetically-defined conditions.

Nomo1 deficiency causes autism-like behavior in zebrafish

Patients with neuropsychiatric disorders often exhibit a combination of clinical symptoms such as autism, epilepsy, or schizophrenia, complicating diagnosis and development of therapeutic strategies. Functional studies of novel genes associated with co-morbidities can provide clues to understand the pathogenic mechanisms and interventions. NOMO1 is one of the candidate genes located at 16p13.11, a hotspot of neuropsychiatric diseases. Here, we generate nomo1-/- zebrafish to get further insight into the function of NOMO1. Nomo1 mutants show abnormal brain and neuronal development and activation of apoptosis and inflammation-related pathways in the brain. Adult Nomo1-deficient zebrafish exhibit multiple neuropsychiatric behaviors such as hyperactive locomotor activity, social deficits, and repetitive stereotypic behaviors. The Habenular nucleus and the pineal gland in the telencephalon are affected, and the melatonin level of nomo1-/- is reduced. Melatonin treatment restores locomotor activity, reduces repetitive stereotypic behaviors, and rescues the noninfectious brain inflammatory responses caused by nomo1 deficiency. These results suggest melatonin supplementation as a potential therapeutic regimen for neuropsychiatric disorders caused by NOMO1 deficiency.

Autism genes converge on microtubule biology and RNA-binding proteins during excitatory neurogenesis

Recent studies have identified over one hundred high-confidence (hc) autism spectrum disorder (ASD) genes. Systems biological and functional analyses on smaller subsets of these genes have consistently implicated excitatory neurogenesis. However, the extent to which the broader set of hcASD genes are involved in this process has not been explored systematically nor have the biological pathways underlying this convergence been identified. Here, we leveraged CROP-Seq to repress 87 hcASD genes in a human in vitro model of cortical neurogenesis. We identified 17 hcASD genes whose repression significantly alters developmental trajectory and results in a common cellular state characterized by disruptions in proliferation, differentiation, cell cycle, microtubule biology, and RNA-binding proteins (RBPs). We also characterized over 3,000 differentially expressed genes, 286 of which had expression profiles correlated with changes in developmental trajectory. Overall, we uncovered transcriptional disruptions downstream of hcASD gene perturbations, correlated these disruptions with distinct differentiation phenotypes, and reinforced neurogenesis, microtubule biology, and RBPs as convergent points of disruption in ASD.

Curation of causal interactions mediated by genes associated with autism accelerates the understanding of gene-phenotype relationships underlying neurodevelopmental disorders

Autism spectrum disorder (ASD) comprises a large group of neurodevelopmental conditions featuring, over a wide range of severity and combinations, a core set of manifestations (restricted sociality, stereotyped behavior and language impairment) alongside various comorbidities. Common and rare variants in several hundreds of genes and regulatory regions have been implicated in the molecular pathogenesis of ASD along a range of causation evidence strength. Despite significant progress in elucidating the impact of few paradigmatic individual loci, such sheer complexity in the genetic architecture underlying ASD as a whole has hampered the identification of convergent actionable hubs hypothesized to relay between the vastness of risk alleles and the core phenotypes. In turn this has limited the development of strategies that can revert or ameliorate this condition, calling for a systems-level approach to probe the cross-talk of cooperating genes in terms of causal interaction networks in order to make convergences experimentally tractable and reveal their clinical actionability. As a first step in this direction, we have captured from the scientific literature information on the causal links between the genes whose variants have been associated with ASD and the whole human proteome. This information has been annotated in a computer readable format in the SIGNOR database and is made freely available in the resource website. To link this information to cell functions and phenotypes, we have developed graph algorithms that estimate the functional distance of any protein in the SIGNOR causal interactome to phenotypes and pathways. The main novelty of our approach resides in the possibility to explore the mechanistic links connecting the suggested gene-phenotype relations.

CellGO: a novel deep learning-based framework and webserver for cell-type-specific gene function interpretation

Interpreting the function of genes and gene sets identified from omics experiments remains a challenge, as current pathway analysis tools often fail to consider the critical biological context, such as tissue or cell-type specificity. To address this limitation, we introduced CellGO. CellGO tackles this challenge by leveraging the visible neural network (VNN) and single-cell gene expressions to mimic cell-type-specific signaling propagation along the Gene Ontology tree within a cell. This design enables a novel scoring system to calculate the cell-type-specific gene-pathway paired active scores, based on which, CellGO is able to identify cell-type-specific active pathways associated with single genes. In addition, by aggregating the activities of single genes, CellGO extends its capability to identify cell-type-specific active pathways for a given gene set. To enhance biological interpretation, CellGO offers additional features, including the identification of significantly active cell types and driver genes and community analysis of pathways. To validate its performance, CellGO was assessed using a gene set comprising mixed cell-type markers, confirming its ability to discern active pathways across distinct cell types. Subsequent benchmarking analyses demonstrated CellGO's superiority in effectively identifying cell types and their corresponding cell-type-specific pathways affected by gene knockouts, using either single genes or sets of genes differentially expressed between knockout and control samples. Moreover, CellGO demonstrated its ability to infer cell-type-specific pathogenesis for disease risk genes. Accessible as a Python package, CellGO also provides a user-friendly web interface, making it a versatile and accessible tool for researchers in the field.

Molecular programs of regional specification and neural stem cell fate progression in macaque telencephalon

During early telencephalic development, intricate processes of regional patterning and neural stem cell (NSC) fate specification take place. However, our understanding of these processes in primates, including both conserved and species-specific features, remains limited. Here, we profiled 761,529 single-cell transcriptomes from multiple regions of the prenatal macaque telencephalon. We deciphered the molecular programs of the early organizing centers and their cross-talk with NSCs, revealing primate-biased galanin-like peptide (GALP) signaling in the anteroventral telencephalon. Regional transcriptomic variations were observed along the frontotemporal axis during early stages of neocortical NSC progression and in neurons and astrocytes. Additionally, we found that genes associated with neuropsychiatric disorders and brain cancer risk might play critical roles in the early telencephalic organizers and during NSC progression.

Embryonic and adult synaptic proteome perturbations after maternal immune activation: Identification of persistent changes relevant for early intervention

Maternal infections during pregnancy pose an increased risk for neurodevelopmental psychiatric disorders (NPDs) in the offspring. Here, we examined age- and sex-dependent dynamic changes of the hippocampal synaptic proteome after maternal immune activation (MIA) in embryonic and adult mice. Adult male and female MIA offspring exhibited social deficits and sex-specific depression-like behaviours, among others, validating the model. Furthermore, we observed dose-, age-, and sex-dependent synaptic proteome differences. Analysis of the embryonic synaptic proteome implicates sphingolipid and ketoacid metabolism pathway disruptions during neurodevelopment for NPD-pertinent sequelae. In the embryonic hippocampus, prenatal immune activation also led to changes in neuronal guidance, glycosphingolipid metabolism important for signalling and myelination, and post-translational modification of proteins that regulate intercellular interaction and developmental timing. In adulthood, the observed changes in synaptoneurosomes revealed a dynamic shift toward transmembrane trafficking, intracellular signalling cascades, and hormone-mediated metabolism. Importantly, 68 of the proteins with differential abundance in the embryonic brains of MIA offspring were also altered in adulthood, 75% of which retained their directionality. These proteins are involved in synaptic organisation, neurotransmitter receptor regulation, and the vesicle cycle. A cluster of persistently upregulated proteins, including AKT3, PAK1/3, PPP3CA, formed a functional network enriched in the embryonic brain that is involved in cellular responses to environmental stimuli. To infer a link between the overlapping protein alterations and cognitive and psychiatric traits, we probed human phenome-wise association study data for cognitive and psychiatric phenotypes and all, but PORCN were significantly associated with the investigated domains. Our data provide insights into the dynamic effects of an early prenatal immune activation on developing and mature hippocampi and highlights targets for early intervention in individuals exposed to such immune challenges.

Cross-phenotype relationship between opioid use disorder and suicide attempts: new evidence from polygenic association and Mendelian randomization analyses

Clinical epidemiological studies have found high co-occurrence between suicide attempts (SA) and opioid use disorder (OUD). However, the patterns of correlation and causation between them are still not clear due to psychiatric confounding. To investigate their cross-phenotype relationship, we utilized raw phenotypes and genotypes from >150,000 UK Biobank samples, and genome-wide association summary statistics from >600,000 individuals with European ancestry. Pairwise association and a potential bidirectional relationship between OUD and SA were evaluated with and without controlling for major psychiatric disease status (e.g., schizophrenia, major depressive disorder, and alcohol use disorder). Multiple statistical and genetics tools were used to perform epidemiological association, genetic correlation, polygenic risk score prediction, and Mendelian randomizations (MR) analyses. Strong associations between OUD and SA were observed at both the phenotypic level (overall samples [OR = 2.94, P = 1.59 ×10-14]; non-psychiatric subgroup [OR = 2.15, P = 1.07 ×10-3]) and the genetic level (genetic correlation rg = 0.38 and 0.5 with or without conditioning on psychiatric traits, respectively). Consistently, increasing polygenic susceptibility to SA is associated with increasing risk of OUD (OR = 1.08, false discovery rate [FDR] =1.71 ×10-3), and similarly, increasing polygenic susceptibility to OUD is associated with increasing risk of SA (OR = 1.09, FDR = 1.73 ×10-6). However, these polygenic associations were much attenuated after controlling for comorbid psychiatric diseases. A combination of MR analyses suggested a possible causal association from genetic liability for SA to OUD risk (2-sample univariable MR: OR = 1.14, P = 0.001; multivariable MR: OR = 1.08, P = 0.001). This study provided new genetic evidence to explain the observed OUD-SA comorbidity. Future prevention strategies for each phenotype needs to take into consideration of screening for the other one.

Supplementary Pharmacotherapy for the Behavioral Abnormalities Caused by Stressors in Humans, Focused on Post-Traumatic Stress Disorder (PTSD)

Used as a supplement to psychotherapy, pharmacotherapy that addresses all of the known metabolic and genetic contributions to the pathogenesis of psychiatric conditions caused by stressors would require an inordinate number of drugs. Far simpler is to address the abnormalities caused by those metabolic and genetic changes in the cell types of the brain that mediate the behavioral abnormality. Relevant data regarding the changed brain cell types are described in this article and are derived from subjects with the paradigmatic behavioral abnormality of PTSD and from subjects with traumatic brain injury or chronic traumatic encephalopathy. If this analysis is correct, then therapy is required that benefits all of the affected brain cell types; those are astrocytes, oligodendrocytes, synapses and neurons, endothelial cells, and microglia (the pro-inflammatory (M1) subtype requires switching to the anti-inflammatory (M2) subtype). Combinations are advocated using several drugs, erythropoietin, fluoxetine, lithium, and pioglitazone, that benefit all of the five cell types, and that should be used to form a two-drug combination, suggested as pioglitazone with either fluoxetine or lithium. Clemastine, fingolimod, and memantine benefit four of the cell types, and one chosen from those could be added to the two-drug combination to form a three-drug combination. Using low doses of chosen drugs will limit both toxicity and drug-drug interactions. A clinical trial is required to validate both the advocated concept and the choice of drugs.

DRAGON-Data: a platform and protocol for integrating genomic and phenotypic data across large psychiatric cohorts

BACKGROUND

Current psychiatric diagnoses, although heritable, have not been clearly mapped onto distinct underlying pathogenic processes. The same symptoms often occur in multiple disorders, and a substantial proportion of both genetic and environmental risk factors are shared across disorders. However, the relationship between shared symptoms and shared genetic liability is still poorly understood.

AIMS

Well-characterised, cross-disorder samples are needed to investigate this matter, but few currently exist. Our aim is to develop procedures to purposely curate and aggregate genotypic and phenotypic data in psychiatric research.

METHOD

As part of the Cardiff MRC Mental Health Data Pathfinder initiative, we have curated and harmonised phenotypic and genetic information from 15 studies to create a new data repository, DRAGON-Data. To date, DRAGON-Data includes over 45 000 individuals: adults and children with neurodevelopmental or psychiatric diagnoses, affected probands within collected families and individuals who carry a known neurodevelopmental risk copy number variant.

RESULTS

We have processed the available phenotype information to derive core variables that can be reliably analysed across groups. In addition, all data-sets with genotype information have undergone rigorous quality control, imputation, copy number variant calling and polygenic score generation.

CONCLUSIONS

DRAGON-Data combines genetic and non-genetic information, and is available as a resource for research across traditional psychiatric diagnostic categories. Algorithms and pipelines used for data harmonisation are currently publicly available for the scientific community, and an appropriate data-sharing protocol will be developed as part of ongoing projects (DATAMIND) in partnership with Health Data Research UK.

miR-514a promotes neuronal development in human iPSC-derived neurons

Proper development and function of the central nervous system require precise regulation of gene expression. MicroRNAs (miRNAs), a group of small non-coding RNAs that can negatively regulate gene expression at the post-transcriptional level, are critical regulators of neuronal development, and dysregulation of microRNAs has been implicated in various neurological disorders. Changes in microRNA expression and repertoire are related to the emergence of social and behavioral variations in closely related primates, including humans, during evolution. MicroRNA-514a (miR-514a) is an X-linked miRNA that is conserved in species with higher social and cognitive functions, and frequent tandem duplications of miR-514a have been found in primate genomes. Here, we demonstrate that miR-514a plays a crucial role in neuronal development in neurons derived from human induced pluripotent stem cells (iPSCs). Overexpression of miR-514a increased dendritic length, soma size, and activity levels of mammalian target of rapamycin (mTOR) signaling in induced pluripotent stem cell-derived neurons, whereas blocking of endogenous miR-514a inhibited neuronal development. Furthermore, we performed a functional analysis of the miR-514a variation found during primate evolution, to investigate the impact of miR-514a sequence variation and associated changes in expression on brain development during evolution. We found that mutation in miR-514a significantly reduced the expression of the mature form and abolished the effects observed when native miR-514a was expressed. Our findings provide new insights into the functional role of miR-514a in the regulation of neuronal development and evolution of primate brain development.

Tourette syndrome: clinical features, pathophysiology, and treatment

Tourette syndrome is a chronic neurodevelopmental disorder characterised by motor and phonic tics that can substantially diminish the quality of life of affected individuals. Evaluating and treating Tourette syndrome is complex, in part due to the heterogeneity of symptoms and comorbidities between individuals. The underlying pathophysiology of Tourette syndrome is not fully understood, but recent research in the past 5 years has brought new insights into the genetic variations and the alterations in neurophysiology and brain networks contributing to its pathogenesis. Treatment options for Tourette syndrome are expanding with novel pharmacological therapies and increased use of deep brain stimulation for patients with symptoms that are refractory to pharmacological or behavioural treatments. Potential predictors of patient responses to therapies for Tourette syndrome, such as specific networks modulated during deep brain stimulation, can guide clinical decisions. Multicentre data sharing initiatives have enabled several advances in our understanding of the genetics and pathophysiology of Tourette syndrome and will be crucial for future large-scale research and in refining effective treatments.

Mapping the common gene networks that underlie related diseases

A longstanding goal of biomedicine is to understand how alterations in molecular and cellular networks give rise to the spectrum of human diseases. For diseases with shared etiology, understanding the common causes allows for improved diagnosis of each disease, development of new therapies and more comprehensive identification of disease genes. Accordingly, this protocol describes how to evaluate the extent to which two diseases, each characterized by a set of mapped genes, are colocalized in a reference gene interaction network. This procedure uses network propagation to measure the network 'distance' between gene sets. For colocalized diseases, the network can be further analyzed to extract common gene communities at progressive granularities. In particular, we show how to: (1) obtain input gene sets and a reference gene interaction network; (2) identify common subnetworks of genes that encompass or are in close proximity to all gene sets; (3) use multiscale community detection to identify systems and pathways represented by each common subnetwork to generate a network colocalized systems map; (4) validate identified genes and systems using a mouse variant database; and (5) visualize and further investigate select genes, interactions and systems for relevance to phenotype(s) of interest. We demonstrate the utility of this approach by identifying shared biological mechanisms underlying autism and congenital heart disease. However, this protocol is general and can be applied to any gene sets attributed to diseases or other phenotypes with suspected joint association. A typical NetColoc run takes less than an hour. Software and documentation are available at https://github.com/ucsd-ccbb/NetColoc .

In Search of Biomarkers to Guide Interventions in Autism Spectrum Disorder: A Systematic Review

OBJECTIVE

The aim of this study was to catalog and evaluate response biomarkers correlated with autism spectrum disorder (ASD) symptoms to improve clinical trials.

METHODS

A systematic review of MEDLINE, Embase, and Scopus was conducted in April 2020. Seven criteria were applied to focus on original research that includes quantifiable response biomarkers measured alongside ASD symptoms. Interventional studies or human studies that assessed the correlation between biomarkers and ASD-related behavioral measures were included.

RESULTS

A total of 5,799 independent records yielded 280 articles for review that reported on 940 biomarkers, 755 of which were unique to a single publication. Molecular biomarkers were the most frequently assayed, including cytokines, growth factors, measures of oxidative stress, neurotransmitters, and hormones, followed by neurophysiology (e.g., EEG and eye tracking), neuroimaging (e.g., functional MRI), and other physiological measures. Studies were highly heterogeneous, including in phenotypes, demographic characteristics, tissues assayed, and methods for biomarker detection. With a median total sample size of 64, almost all of the reviewed studies were only powered to identify biomarkers with large effect sizes. Reporting of individual-level values and summary statistics was inconsistent, hampering mega- and meta-analysis. Biomarkers assayed in multiple studies yielded mostly inconsistent results, revealing a "replication crisis."

CONCLUSIONS

There is currently no response biomarker with sufficient evidence to inform ASD clinical trials. This review highlights methodological imperatives for ASD biomarker research necessary to make definitive progress: consistent experimental design, correction for multiple comparisons, formal replication, sharing of sample-level data, and preregistration of study designs. Systematic "big data" analyses of multiple potential biomarkers could accelerate discovery.

From Genes to Therapy in Autism Spectrum Disorder

In recent years, findings from genetic and other biological studies are starting to reveal the role of various molecular mechanisms that contribute to the etiology of ASD [...]

Chr21 protein-protein interactions: enrichment in proteins involved in intellectual disability, autism, and late-onset Alzheimer's disease

Down syndrome (DS) is caused by human chromosome 21 (HSA21) trisomy. It is characterized by a poorly understood intellectual disability (ID). We studied two mouse models of DS, one with an extra copy of the <i>Dyrk1A</i> gene (189N3) and the other with an extra copy of the mouse Chr16 syntenic region (Dp(16)1Yey). RNA-seq analysis of the transcripts deregulated in the embryonic hippocampus revealed an enrichment in genes associated with chromatin for the 189N3 model, and synapses for the Dp(16)1Yey model. A large-scale yeast two-hybrid screen (82 different screens, including 72 HSA21 baits and 10 rebounds) of a human brain library containing at least 10⁷ independent fragments identified 1,949 novel protein-protein interactions. The direct interactors of HSA21 baits and rebounds were significantly enriched in ID-related genes (<i>P</i>-value &lt; 2.29 × 10^-8). Proximity ligation assays showed that some of the proteins encoded by HSA21 were located at the dendritic spine postsynaptic density, in a protein network at the dendritic spine postsynapse. We located HSA21 DYRK1A and DSCAM, mutations of which increase the risk of autism spectrum disorder (ASD) 20-fold, in this postsynaptic network. We found that an intracellular domain of DSCAM bound either DLGs, which are multimeric scaffolds comprising receptors, ion channels and associated signaling proteins, or DYRK1A. The DYRK1A-DSCAM interaction domain is conserved in <i>Drosophila</i> and humans. The postsynaptic network was found to be enriched in proteins associated with ARC-related synaptic plasticity, ASD, and late-onset Alzheimer's disease. These results highlight links between DS and brain diseases with a complex genetic basis.

The Roles of Par3, Par6, and aPKC Polarity Proteins in Normal Neurodevelopment and in Neurodegenerative and Neuropsychiatric Disorders

Normal neural circuits and functions depend on proper neuronal differentiation, migration, synaptic plasticity, and maintenance. Abnormalities in these processes underlie various neurodevelopmental, neuropsychiatric, and neurodegenerative disorders. Neural development and maintenance are regulated by many proteins. Among them are Par3, Par6 (partitioning defective 3 and 6), and aPKC (atypical protein kinase C) families of evolutionarily conserved polarity proteins. These proteins perform versatile functions by forming tripartite or other combinations of protein complexes, which hereafter are collectively referred to as "Par complexes." In this review, we summarize the major findings on their biophysical and biochemical properties in cell polarization and signaling pathways. We next summarize their expression and localization in the nervous system as well as their versatile functions in various aspects of neurodevelopment, including neuroepithelial polarity, neurogenesis, neuronal migration, neurite differentiation, synaptic plasticity, and memory. These versatile functions rely on the fundamental roles of Par complexes in cell polarity in distinct cellular contexts. We also discuss how cell polarization may correlate with subcellular polarization in neurons. Finally, we review the involvement of Par complexes in neuropsychiatric and neurodegenerative disorders, such as schizophrenia and Alzheimer's disease. While emerging evidence indicates that Par complexes are essential for proper neural development and maintenance, many questions on their in vivo functions have yet to be answered. Thus, Par3, Par6, and aPKC continue to be important research topics to advance neuroscience.

How Variation in Risk Allele Output and Gene Interactions Shape the Genetic Architecture of Schizophrenia

Schizophrenia is a highly heritable polygenic psychiatric disorder. Characterization of its genetic architecture may lead to a better understanding of the overall burden of risk variants and how they determine susceptibility to disease. A major goal of this project is to develop a modeling approach to compare and quantify the relative effects of single nucleotide polymorphisms (SNPs), copy number variants (CNVs) and other factors. We derived a mathematical model for the various genetic contributions based on the probability of expressing a combination of risk variants at a frequency that matched disease prevalence. The model included estimated risk variant allele outputs (VAOs) adjusted for population allele frequency. We hypothesized that schizophrenia risk genes would be more interactive than random genes and we confirmed this relationship. Gene–gene interactions may cause network ripple effects that spread and amplify small individual effects of risk variants. The modeling revealed that the number of risk alleles required to achieve the threshold for susceptibility will be determined by the average functional locus output (FLO) associated with a risk allele, the risk allele frequency (RAF), the number of protective variants present and the extent of gene interactions within and between risk loci. The model can account for the quantitative impact of protective variants as well as CNVs on disease susceptibility. The fact that non-affected individuals must carry a non-trivial burden of risk alleles suggests that genetic susceptibility will inevitably reach the threshold for schizophrenia at a recurring frequency in the population.

Targeting NMDA receptors in neuropsychiatric disorders by drug screening on human neurons derived from pluripotent stem cells

NMDA receptors (NMDARs), a prominent subtype of glutamatergic receptors, are implicated in the pathogenesis and development of neuropsychiatric disorders such as epilepsy, intellectual disability, autism spectrum disorder, and schizophrenia, and are therefore a potential therapeutic target in treating these disorders. Neurons derived from induced pluripotent stem cells (iPSCs) have provided the opportunity to investigate human NMDARs in their native environment. In this review, we describe the expression, function, and regulation of NMDARs in human iPSC-derived neurons and discuss approaches for utilizing human neurons for identifying potential drugs that target NMDARs in the treatment of neuropsychiatric disorders. A challenge in studying NMDARs in human iPSC-derived neurons is a predominance of those receptors containing the GluN2B subunit and low synaptic expression, suggesting a relatively immature phenotype of these neurons and delayed development of functional NMDARs. We outline potential approaches for improving neuronal maturation of human iPSC-derived neurons and accelerating the functional expression of NMDARs. Acceleration of functional expression of NMDARs in human iPSC-derived neurons will improve the modeling of neuropsychiatric disorders and facilitate the discovery and development of novel therapeutics targeting NMDARs for the treatment of these disorders.

Quantifying concordant genetic effects of de novo mutations on multiple disorders

Exome sequencing on tens of thousands of parent-proband trios has identified numerous deleterious de novo mutations (DNMs) and implicated risk genes for many disorders. Recent studies have suggested shared genes and pathways are enriched for DNMs across multiple disorders. However, existing analytic strategies only focus on genes that reach statistical significance for multiple disorders and require large trio samples in each study. As a result, these methods are not able to characterize the full landscape of genetic sharing due to polygenicity and incomplete penetrance. In this work, we introduce EncoreDNM, a novel statistical framework to quantify shared genetic effects between two disorders characterized by concordant enrichment of DNMs in the exome. EncoreDNM makes use of exome-wide, summary-level DNM data, including genes that do not reach statistical significance in single-disorder analysis, to evaluate the overall and annotation-partitioned genetic sharing between two disorders. Applying EncoreDNM to DNM data of nine disorders, we identified abundant pairwise enrichment correlations, especially in genes intolerant to pathogenic mutations and genes highly expressed in fetal tissues. These results suggest that EncoreDNM improves current analytic approaches and may have broad applications in DNM studies.

Genomics, convergent neuroscience and progress in understanding autism spectrum disorder

More than a hundred genes have been identified that, when disrupted, impart large risk for autism spectrum disorder (ASD). Current knowledge about the encoded proteins - although incomplete - points to a very wide range of developmentally dynamic and diverse biological processes. Moreover, the core symptoms of ASD involve distinctly human characteristics, presenting challenges to interpreting evolutionarily distant model systems. Indeed, despite a decade of striking progress in gene discovery, an actionable understanding of pathobiology remains elusive. Increasingly, convergent neuroscience approaches have been recognized as an important complement to traditional uses of genetics to illuminate the biology of human disorders. These methods seek to identify intersection among molecular-level, cellular-level and circuit-level functions across multiple risk genes and have highlighted developing excitatory neurons in the human mid-gestational prefrontal cortex as an important pathobiological nexus in ASD. In addition, neurogenesis, chromatin modification and synaptic function have emerged as key potential mediators of genetic vulnerability. The continued expansion of foundational 'omics' data sets, the application of higher-throughput model systems and incorporating developmental trajectories and sex differences into future analyses will refine and extend these results. Ultimately, a systems-level understanding of ASD genetic risk holds promise for clarifying pathobiology and advancing therapeutics.

Modeling Human Genetic Disorders with CRISPR Technologies in Xenopus

Combining the power of Xenopus developmental biology with CRISPR-based technologies promises great discoveries in understanding and treating human genetic disorders. Here we provide a practical pipeline for how to go from known disease gene(s) or risk gene(s) of interest to methods for gaining functional insight into the contribution of these genes to disorder etiology in humans.

A matter of space and time: Emerging roles of disease-associated proteins in neural development

Recent genetic studies of neurodevelopmental disorders point to synaptic proteins and ion channels as key contributors to disease pathogenesis. Although many of these proteins, such as the L-type calcium channel Cav1.2 or the postsynaptic scaffolding protein SHANK3, have well-studied functions in mature neurons, new evidence indicates that they may subserve novel, distinct roles in immature cells as the nervous system is assembled in prenatal development. Emerging tools and technologies, including single-cell sequencing and human cellular models of disease, are illuminating differential isoform utilization, spatiotemporal expression, and subcellular localization of ion channels and synaptic proteins in the developing brain compared with the adult, providing new insights into the regulation of developmental processes. We propose that it is essential to consider the temporally distinct and cell-specific roles of these proteins during development and maturity in our framework for understanding neuropsychiatric disorders.

Current Understanding of the Genetics of Tourette Syndrome

Gilles de la Tourette syndrome (TS) is a common, childhood-onset psychiatric disorder characterized by persistent motor and vocal tics. It is a heterogeneous disorder in which the phenotypic expression may be affected by environmental factors, such as immune responses. Furthermore, several studies have shown that genetic factors play a vital role in the etiology of TS, as well as its comorbidity with other disorders, including attention deficit hyperactivity disorder, obsessive-compulsive disorder, and autism spectrum disorder. TS has a complex inheritance pattern and, according to various genetic studies, several genes and loci have been correlated with TS. Genome-wide linkage studies have identified Slit and Trk-like 1 (SLITRK1) and histidine decarboxylase (HDC) genes, and candidate gene association studies have extensively investigated the dopamine and serotonin system genes, but there have been no consistent results. Moreover, genome-wide association studies have implicated several genetic loci; however, larger study cohorts are needed to confirm this. Copy number variations, which are polymorphisms in the number of gene copies due to chromosomal deletions or duplications, are considered another significant source of mutations in TS. In the last decade, whole genome/exome sequencing has identified several novel genetic mutations in patients with TS. In conclusion, more studies are needed to reveal the exact mechanisms of underlying TS, which may help to provide more information on the prognosis and therapeutic plans for TS.

A convergent molecular network underlying autism and congenital heart disease

Patients with neurodevelopmental disorders, including autism, have an elevated incidence of congenital heart disease, but the extent to which these conditions share molecular mechanisms remains unknown. Here, we use network genetics to identify a convergent molecular network underlying autism and congenital heart disease. This network is impacted by damaging genetic variants from both disorders in multiple independent cohorts of patients, pinpointing 101 genes with shared genetic risk. Network analysis also implicates risk genes for each disorder separately, including 27 previously unidentified genes for autism and 46 for congenital heart disease. For 7 genes with shared risk, we create engineered disruptions in Xenopus tropicalis, confirming both heart and brain developmental abnormalities. The network includes a family of ion channels, such as the sodium transporter SCN2A, linking these functions to early heart and brain development. This study provides a road map for identifying risk genes and pathways involved in co-morbid conditions.

M-DATA: A statistical approach to jointly analyzing de novo mutations for multiple traits

Recent studies have demonstrated that multiple early-onset diseases have shared risk genes, based on findings from de novo mutations (DNMs). Therefore, we may leverage information from one trait to improve statistical power to identify genes for another trait. However, there are few methods that can jointly analyze DNMs from multiple traits. In this study, we develop a framework called M-DATA (Multi-trait framework for De novo mutation Association Test with Annotations) to increase the statistical power of association analysis by integrating data from multiple correlated traits and their functional annotations. Using the number of DNMs from multiple diseases, we develop a method based on an Expectation-Maximization algorithm to both infer the degree of association between two diseases as well as to estimate the gene association probability for each disease. We apply our method to a case study of jointly analyzing data from congenital heart disease (CHD) and autism. Our method was able to identify 23 genes for CHD from joint analysis, including 12 novel genes, which is substantially more than single-trait analysis, leading to novel insights into CHD disease etiology.

Molecular signatures from multi-omics of autism spectrum disorders and schizophrenia

The genetic and phenotypic heterogeneity of autism spectrum disorder (ASD) impedes the unification of multiple biological hypotheses in an attempt to explain the complex features of ASD, such as impaired social communication, social interaction deficits, and restricted and repetitive patterns of behavior. However, recent psychiatric genetic studies have identified numerous risk genes and chromosome loci (copy number variation: CNV) which enable us to analyze at the single gene level and utilize system-level approaches. In this review, we focus on ASD as a major neurodevelopmental disorder and review recent findings mainly from the bioinformatics of omics studies. Additionally, by comparing these data with other major psychiatric disorders, including schizophrenia (SCZ), we identify unique characteristics of both diseases from multiple enrichment, pathway, and protein-protein interaction networks (PPIs) analyses using susceptible genes found in recent large-scale genetic studies. These unified, systematic approaches highlight unique characteristics of both disorders from multiple aspects and demonstrate how convergent pathways can contribute to an understanding of the complex etiology of such neurodevelopmental and neuropsychiatric disorders.

Bayesian metamodeling of complex biological systems across varying representations

Comprehensive modeling of a whole cell requires an integration of vast amounts of information on various aspects of the cell and its parts. To divide and conquer this task, we introduce Bayesian metamodeling, a general approach to modeling complex systems by integrating a collection of heterogeneous input models. Each input model can in principle be based on any type of data and can describe a different aspect of the modeled system using any mathematical representation, scale, and level of granularity. These input models are 1) converted to a standardized statistical representation relying on probabilistic graphical models, 2) coupled by modeling their mutual relations with the physical world, and 3) finally harmonized with respect to each other. To illustrate Bayesian metamodeling, we provide a proof-of-principle metamodel of glucose-stimulated insulin secretion by human pancreatic β-cells. The input models include a coarse-grained spatiotemporal simulation of insulin vesicle trafficking, docking, and exocytosis; a molecular network model of glucose-stimulated insulin secretion signaling; a network model of insulin metabolism; a structural model of glucagon-like peptide-1 receptor activation; a linear model of a pancreatic cell population; and ordinary differential equations for systemic postprandial insulin response. Metamodeling benefits from decentralized computing, while often producing a more accurate, precise, and complete model that contextualizes input models as well as resolves conflicting information. We anticipate Bayesian metamodeling will facilitate collaborative science by providing a framework for sharing expertise, resources, data, and models, as exemplified by the Pancreatic β-Cell Consortium.

A panoramic view of proteomics and multiomics in precision health

Health is often qualitatively defined as a status free from disease and its quantitative definition requires finding the boundary separating health from pathological conditions. Since many complex diseases have a strong genetic component, substantial efforts have been made to sequence large-scale personal genomes; however, we are not yet able to effectively quantify health status from personal genomes. Since mutational impacts are ultimately manifested at the protein level, we envision that introducing a panoramic proteomic view of complex diseases will allow us to mechanistically understand the molecular etiologies of human diseases. In this perspective article, we will highlight key proteomic approaches to identify pathogenic mutations and map their convergent pathways underlying disease pathogenesis and the integration of omics data at multiple levels to define the borderline between health and disease.

Next-generation gene panel testing in adolescents and adults in a medical neuropsychiatric genetics clinic

Intellectual disability (ID) encompasses a clinically and genetically heterogeneous group of neurodevelopmental disorders that may present with psychiatric illness in up to 40% of cases. Despite the evidence for clinical utility of genetic panels in pediatrics, there are no published studies in adolescents/adults with ID or autism spectrum disorder (ASD). This study was approved by our institutional research ethics board. We retrospectively reviewed the medical charts of all patients evaluated between January 2017 and December 2019 in our adult neuropsychiatric genetics clinic at the McGill University Health Centre (MUHC), who had undergone a comprehensive ID/ASD gene panel. Thirty-four patients aged > 16 years, affected by ID/ASD and/or other neuropsychiatric/behavioral disorders, were identified. Pathogenic or likely pathogenic variants were identified in one-third of our cohort (32%): 8 single-nucleotide variants in 8 genes (CASK, SHANK3, IQSEC2, CHD2, ZBTB20, TREX1, SON, and TUBB2A) and 3 copy number variants (17p13.3, 16p13.12p13.11, and 9p24.3p24.1). The presence of psychiatric/behavioral disorders, regardless of the co-occurrence of ID, and, at a borderline level, the presence of ID alone were associated with positive genetic findings (p = 0.024 and p = 0.054, respectively). Moreover, seizures were associated with positive genetic results (p = 0.024). One-third of individuals presenting with psychiatric illness who met our red flags for Mendelian diseases have pathogenic or likely pathogenic variants which can be identified using a comprehensive ID/ASD gene panel (~ 2500 genes) performed on an exome backbone.

Spatial and cell type transcriptional landscape of human cerebellar development

The human neonatal cerebellum is one-fourth of its adult size yet contains the blueprint required to integrate environmental cues with developing motor, cognitive and emotional skills into adulthood. Although mature cerebellar neuroanatomy is well studied, understanding of its developmental origins is limited. In this study, we systematically mapped the molecular, cellular and spatial composition of human fetal cerebellum by combining laser capture microscopy and SPLiT-seq single-nucleus transcriptomics. We profiled functionally distinct regions and gene expression dynamics within cell types and across development. The resulting cell atlas demonstrates that the molecular organization of the cerebellar anlage recapitulates cytoarchitecturally distinct regions and developmentally transient cell types that are distinct from the mouse cerebellum. By mapping genes dominant for pediatric and adult neurological disorders onto our dataset, we identify relevant cell types underlying disease mechanisms. These data provide a resource for probing the cellular basis of human cerebellar development and disease.

A white paper on a neurodevelopmental framework for drug discovery in autism and other neurodevelopmental disorders

In the last decade there has been a revolution in terms of genetic findings in neurodevelopmental disorders (NDDs), with many discoveries critical for understanding their aetiology and pathophysiology. Clinical trials in single-gene disorders such as fragile X syndrome highlight the challenges of investigating new drug targets in NDDs. Incorporating a developmental perspective into the process of drug development for NDDs could help to overcome some of the current difficulties in identifying and testing new treatments. This paper provides a summary of the proceedings of the 'New Frontiers Meeting' on neurodevelopmental disorders organised by the European College of Neuropsychopharmacology in conjunction with the Innovative Medicines Initiative-sponsored AIMS-2-TRIALS consortium. It brought together experts in developmental genetics, autism, NDDs, and clinical trials from academia and industry, regulators, patient and family associations, and other stakeholders. The meeting sought to provide a platform for focused communication on scientific insights, challenges, and methodologies that might be applicable to the development of CNS treatments from a neurodevelopmental perspective. Multidisciplinary translational consortia to develop basic and clinical research in parallel could be pivotal to advance knowledge in the field. Although implementation of clinical trials for NDDs in paediatric populations is widely acknowledged as essential, safety concerns should guide each aspect of their design. Industry and academia should join forces to improve knowledge of the biology of brain development, identify the optimal timing of interventions, and translate these findings into new drugs, allowing for the needs of users and families, with support from regulatory agencies.

High-resolution transcriptional landscape of xeno-free human induced pluripotent stem cell-derived cerebellar organoids

Current protocols for producing cerebellar neurons from human pluripotent stem cells (hPSCs) often rely on animal co-culture and mostly exist as monolayers, limiting their capability to recapitulate the complex processes in the developing cerebellum. Here, we employed a robust method, without the need for mouse co-culture to generate three-dimensional cerebellar organoids from hPSCs that display hallmarks of in vivo cerebellar development. Single-cell profiling followed by comparison to human and mouse cerebellar atlases revealed the presence and maturity of transcriptionally distinct populations encompassing major cerebellar cell types. Encapsulation with Matrigel aimed to provide more physiologically-relevant conditions through recapitulation of basement-membrane signalling, influenced both growth dynamics and cellular composition of the organoids, altering developmentally relevant gene expression programmes. We identified enrichment of cerebellar disease genes in distinct cell populations in the hPSC-derived cerebellar organoids. These findings ascertain xeno-free human cerebellar organoids as a unique model to gain insight into cerebellar development and its associated disorders.

An Epilepsy-Associated GRIN2A Rare Variant Disrupts CaMKIIα Phosphorylation of GluN2A and NMDA Receptor Trafficking

Rare variants in GRIN genes, which encode NMDAR subunits, are strongly associated with neurodevelopmental disorders. Among these, GRIN2A, which encodes the GluN2A subunit of NMDARs, is widely accepted as an epilepsy-causative gene. Here, we functionally characterize the de novo GluN2A-S1459G mutation identified in an epilepsy patient. We show that S1459 is a CaMKIIα phosphorylation site, and that endogenous phosphorylation is regulated during development and in response to synaptic activity in a dark rearing model. GluN2A-S1459 phosphorylation results in preferential binding of NMDARs to SNX27 and a corresponding decrease in PSD-95 binding, which consequently regulates NMDAR trafficking. Furthermore, the epilepsy-associated GluN2A-S1459G variant displays defects in interactions with both SNX27 and PSD-95, resulting in trafficking deficits, reduced spine density, and decreased excitatory synaptic transmission. These data demonstrate a role for CaMKIIα phosphorylation of GluN2A in receptor targeting and implicate NMDAR trafficking defects as a link to epilepsy.

The Drosophila ortholog of the schizophrenia-associated CACNA1A and CACNA1B voltage-gated calcium channels regulate memory, sleep and circadian rhythms

Schizophrenia exhibits up to 80% heritability. A number of genome wide association studies (GWAS) have repeatedly shown common variants in voltage-gated calcium (Ca_v) channel genes CACNA1C, CACNA1I and CACNA1G have a major contribution to the risk of the disease. More recently, studies using whole exome sequencing have also found that CACNA1B (Ca_v2.2 N-type) deletions and rare disruptive variants in CACNA1A (Ca_v2.1 P/Q-type) are associated with schizophrenia. The negative symptoms of schizophrenia include behavioural defects such as impaired memory, sleep and circadian rhythms. It is not known how variants in schizophrenia-associated genes contribute to cognitive and behavioural symptoms, thus hampering the development of treatment for schizophrenia symptoms. In order to address this knowledge gap, we studied behavioural phenotypes in a number of loss of function mutants for the Drosophila ortholog of the Ca_v2 gene family called cacophony (cac). cac mutants showed several behavioural features including decreased night-time sleep and hyperactivity similar to those reported in human patients. The change in timing of sleep-wake cycles suggested disrupted circadian rhythms, with the loss of night-time sleep being caused by loss of cac just in the circadian clock neurons. These animals also showed a reduction in rhythmic circadian behaviour a phenotype that also could be mapped to the central clock. Furthermore, reduction of cac just in the clock resulted in a lengthening of the 24 h period. In order to understand how loss of Ca_v2 function may lead to cognitive deficits and underlying cellular pathophysiology we targeted loss of function of cac to the memory centre of the fly, called the mushroom bodies (MB). This manipulation was sufficient to cause reduction in both short- and intermediate-term associative memory. Memory impairment was accompanied by a decrease in Ca²⁺ transients in response to a depolarizing stimulus, imaged in the MB presynaptic terminals. This work shows loss of cac Ca_v2 channel function alone causes a number of cognitive and behavioural deficits and underlying reduced neuronal Ca²⁺ transients, establishing Drosophila as a high-throughput in vivo genetic model to study the Ca_v channel pathophysiology related to schizophrenia.

Cross-Disorder Analysis of De Novo Mutations in Neuropsychiatric Disorders

The clinical similarity among different neuropsychiatric disorders (NPDs) suggested a shared genetic basis. We catalogued 23,109 coding de novo mutations (DNMs) from 6511 patients with autism spectrum disorder (ASD), 4,293 undiagnosed developmental disorder (UDD), 933 epileptic encephalopathy (EE), 1022 intellectual disability (ID), 1094 schizophrenia (SCZ), and 3391 controls. We evaluated that putative functional DNMs contribute to 38.11%, 34.40%, 33.31%, 10.98% and 6.91% of patients with ID, EE, UDD, ASD and SCZ, respectively. Consistent with phenotype similarity and heterogeneity in different NPDs, they show different degree of genetic association. Cross-disorder analysis of DNMs prioritized 321 candidate genes (FDR < 0.05) and showed that genes shared in more disorders were more likely to exhibited specific expression pattern, functional pathway, genetic convergence, and genetic intolerance.

Novel Compound Heterozygous Mutation in TRAPPC9 Gene: The Relevance of Whole Genome Sequencing

Advances in high-throughput technologies and its implementation worldwide have had a considerable impact on the elucidation of the molecular causes underlying neurodevelopmental psychiatric disorders, especially for autism spectrum disorder and intellectual disability (ID). Nevertheless, etiology remains elusive in close to 50% of cases, even in those families with multiple affected individuals, strongly hinting at a genetic cause. Here we present a case report of two siblings affected with severe ID and other comorbidities, who embarked on a genetic testing odyssey until diagnosis was reached by using whole genome sequencing (WGS). WGS identified a maternally inherited novel missense variant (NM_031466.7:c.1037G > A; p.Gly346Glu) and a paternally inherited 90 kb intragenic deletion in TRAPPC9 gene. This report demonstrates the clinical utility of WGS in patients who remain undiagnosed after whole exome sequencing.

Cross-Disorder Analysis of De Novo Variants Increases the Power of Prioritising Candidate Genes

De novo variants (DNVs) are critical to the treatment of neurodevelopmental disorders (NDDs). However, effectively identifying candidate genes in small cohorts is challenging in most NDDs because of high genetic heterogeneity. We hypothesised that integrating DNVs from multiple NDDs with genetic similarity can significantly increase the possibility of prioritising the candidate gene. We catalogued 66,186 coding DNVs in 50,028 individuals with nine types of NDDs in cohorts with sizes spanning from 118 to 31,260 from Gene4Denovo database to validate this hypothesis. Interestingly, we found that integrated DNVs can effectively increase the number of prioritised candidate genes for each disorder. We identified 654 candidate genes including 481 shared candidate genes carrying putative functional variants in at least two disorders. Notably, 13.51% (65/481) of shared candidate genes were prioritised only via integrated analysis including 44.62% (29/65) genes validated in recent large cohort studies. Moreover, we estimated that more novel candidate genes will be prioritised with the increase in cohort size, in particular for some disorders with high putative functional DNVs per individual. In conclusion, integrated DNVs may increase the power of prioritising candidate genes, which is important for NDDs with small cohort size.

The region-selective regulation of endothelial claudin-5 expression and signaling in brain health and disorders

The neurovascular unit (NVU) consists of neurons, glial cells, microvascular cells, and extracellular matrix, and is involved in a variety of physiological and pathological processes in the central nervous system (CNS). Within the NVU, the microvascular endothelial cells and pericytes principally contribute to maintaining the integrity of the blood-brain barrier (BBB). Various types of cells are connected to each other in the NVU by diverse cell adhesion molecules, of which claudin-5 (CLDN5) is by far the most abundantly expressed tight-junction protein in brain microvascular endothelial cells and absolutely required for the maintenance of the BBB. This review highlights recent progress in understanding the region-specific regulation and dysregulation of CLDN5 expression in CNS health and disorders. We also discuss how CLDN5 expression is regionally disrupted within the NVU. In addition, we focus on the link between cell adhesion and transcription factor signalings and describe the possible involvement of CLDN5-adhesion signaling in brain health and disorders.

Core transcriptional networks in Williams syndrome: IGF1-PI3K-AKT-mTOR, MAPK and actin signaling at the synapse echo autism

Gene networks for disorders of social behavior provide the mechanisms critical for identifying therapeutic targets and biomarkers. Large behavioral phenotypic effects of small human deletions make the positive sociality of Williams syndrome (WS) ideal for determining transcriptional networks for social dysfunction currently based on DNA variations for disorders such as autistic spectrum disorder (ASD) and schizophrenia (SCHZ). Consensus on WS networks has been elusive due to the need for larger cohort size, sensitive genome-wide detection and analytic tools. We report a core set of WS network perturbations in a cohort of 58 individuals (34 with typical, 6 atypical deletions and 18 controls). Genome-wide exon-level expression arrays robustly detected changes in differentially expressed gene (DEG) transcripts from WS deleted genes that ranked in the top 11 of 12 122 transcripts, validated by quantitative reverse transcription PCR, RNASeq and western blots. WS DEG's were strictly dosed in the full but not the atypical deletions that revealed a breakpoint position effect on non-deleted CLIP2, a caveat for current phenotypic mapping based on copy number variants. Network analyses tested the top WS DEG's role in the dendritic spine, employing GeneMANIA to harmonize WS DEGs with comparable query gene-sets. The results indicate perturbed actin cytoskeletal signaling analogous to the excitatory dendritic spines. Independent protein-protein interaction analyses of top WS DEGs generated a 100-node graph annotated topologically revealing three interacting pathways, MAPK, IGF1-PI3K-AKT-mTOR/insulin and actin signaling at the synapse. The results indicate striking similarity of WS transcriptional networks to genome-wide association study-based ASD and SCHZ risk suggesting common network dysfunction for these disorders of divergent sociality.

Mind the translational gap: using iPS cell models to bridge from genetic discoveries to perturbed pathways and therapeutic targets

Autism spectrum disorder (ASD) comprises a group of neurodevelopmental disorders characterized by impaired social interactions as well as the presentation of restrictive and repetitive behaviors. ASD is highly heritable but genetically heterogenous with both common and rare genetic variants collaborating to predispose individuals to the disorder. In this review, we synthesize recent efforts to develop human induced pluripotent stem cell (iPSC)-derived models of ASD-related phenotypes. We firstly address concerns regarding the relevance and validity of available neuronal iPSC-derived models. We then critically evaluate the robustness of various differentiation and cell culture protocols used for producing cell types of relevance to ASD. By exploring iPSC models of ASD reported thus far, we examine to what extent cellular and neuronal phenotypes with potential relevance to ASD can be linked to genetic variants found to underlie it. Lastly, we outline promising strategies by which iPSC technology can both enhance the power of genetic studies to identify ASD risk factors and nominate pathways that are disrupted across groups of ASD patients that might serve as common points for therapeutic intervention.

Xenopus leads the way: Frogs as a pioneering model to understand the human brain

From its long history in the field of embryology to its recent advances in genetics, Xenopus has been an indispensable model for understanding the human brain. Foundational studies that gave us our first insights into major embryonic patterning events serve as a crucial backdrop for newer avenues of investigation into organogenesis and organ function. The vast array of tools available in Xenopus laevis and Xenopus tropicalis allows interrogation of developmental phenomena at all levels, from the molecular to the behavioral, and the application of CRISPR technology has enabled the investigation of human disorder risk genes in a higher-throughput manner. As the only major tetrapod model in which all developmental stages are easily manipulated and observed, frogs provide the unique opportunity to study organ development from the earliest stages. All of these features make Xenopus a premier model for studying the development of the brain, a notoriously complex process that demands an understanding of all stages from fertilization to organogenesis and beyond. Importantly, core processes of brain development are conserved between Xenopus and human, underlining the advantages of this model. This review begins by summarizing discoveries made in amphibians that form the cornerstones of vertebrate neurodevelopmental biology and goes on to discuss recent advances that have catapulted our understanding of brain development in Xenopus and in relation to human development and disease. As we engage in a new era of patient-driven gene discovery, Xenopus offers exceptional potential to uncover conserved biology underlying human brain disorders and move towards rational drug design.

Parallel in vivo analysis of large-effect autism genes implicates cortical neurogenesis and estrogen in risk and resilience

Gene Ontology analyses of autism spectrum disorders (ASD) risk genes have repeatedly highlighted synaptic function and transcriptional regulation as key points of convergence. However, these analyses rely on incomplete knowledge of gene function across brain development. Here we leverage Xenopus tropicalis to study in vivo ten genes with the strongest statistical evidence for association with ASD. All genes are expressed in developing telencephalon at time points mapping to human mid-prenatal development, and mutations lead to an increase in the ratio of neural progenitor cells to maturing neurons, supporting previous in silico systems biological findings implicating cortical neurons in ASD vulnerability, but expanding the range of convergent functions to include neurogenesis. Systematic chemical screening identifies that estrogen, via Sonic hedgehog signaling, rescues this convergent phenotype in Xenopus and human models of brain development, suggesting a resilience factor that may mitigate a range of ASD genetic risks.

Leveraging large genomic datasets to illuminate the pathobiology of autism spectrum disorders

"Big data" approaches in the form of large-scale human genomic studies have led to striking advances in autism spectrum disorder (ASD) genetics. Similar to many other psychiatric syndromes, advances in genotyping technology, allowing for inexpensive genome-wide assays, has confirmed the contribution of polygenic inheritance involving common alleles of small effect, a handful of which have now been definitively identified. However, the past decade of gene discovery in ASD has been most notable for the application, in large family-based cohorts, of high-density microarray studies of submicroscopic chromosomal structure as well as high-throughput DNA sequencing-leading to the identification of an increasingly long list of risk regions and genes disrupted by rare, de novo germline mutations of large effect. This genomic architecture offers particular advantages for the illumination of biological mechanisms but also presents distinctive challenges. While the tremendous locus heterogeneity and functional pleiotropy associated with the more than 100 identified ASD-risk genes and regions is daunting, a growing armamentarium of comprehensive, large, foundational -omics databases, across species and capturing developmental trajectories, are increasingly contributing to a deeper understanding of ASD pathology.

Mass spectrometry-based protein-protein interaction networks for the study of human diseases

A better understanding of the molecular mechanisms underlying disease is key for expediting the development of novel therapeutic interventions. Disease mechanisms are often mediated by interactions between proteins. Insights into the physical rewiring of protein-protein interactions in response to mutations, pathological conditions, or pathogen infection can advance our understanding of disease etiology, progression, and pathogenesis and can lead to the identification of potential druggable targets. Advances in quantitative mass spectrometry (MS)-based approaches have allowed unbiased mapping of these disease-mediated changes in protein-protein interactions on a global scale. Here, we review MS techniques that have been instrumental for the identification of protein-protein interactions at a system-level, and we discuss the challenges associated with these methodologies as well as novel MS advancements that aim to address these challenges. An overview of examples from diverse disease contexts illustrates the potential of MS-based protein-protein interaction mapping approaches for revealing disease mechanisms, pinpointing new therapeutic targets, and eventually moving toward personalized applications.

Autism Spectrum Disorder Genetics and the Search for Pathological Mechanisms

Recent progress in the identification of genes and genomic regions contributing to autism spectrum disorder (ASD) has had a broad impact on our understanding of the nature of genetic risk for a range of psychiatric disorders, on our understanding of ASD biology, and on defining the key challenges now facing the field in efforts to translate gene discovery into an actionable understanding of pathology. While these advances have not yet had a transformative impact on clinical practice, there is nonetheless cause for real optimism: reliable lists of risk genes are large and growing rapidly; the identified encoded proteins have already begun to point to a relatively small number of areas of biology, where parallel advances in neuroscience and functional genomics are yielding profound insights; there is strong evidence pointing to mid-fetal prefrontal cortical development as one nexus of vulnerability for some of the largest-effect ASD risk genes; and there are multiple plausible paths forward toward rational therapeutics development that, while admittedly challenging, constitute fundamental departures from what was possible prior to the era of successful gene discovery.

Proteomic Approaches to Investigate Regulated Trafficking and Signaling of G Protein-Coupled Receptors

Advances in proteomic methodologies based on quantitative mass spectrometry are now transforming pharmacology and experimental biology more broadly. The present review will discuss several examples based on work in the author's laboratory, which focuses on delineating relationships between G protein-coupled receptor signaling and trafficking in the endocytic network. The examples highlighted correspond to those discussed in a talk presented at the 2019 EB/ASPET meeting, which was organized by Professor Joe Beavo to commemorate his receipt of the Julius Axelrod Award. SIGNIFICANCE STATEMENT: GPCRs are allosteric machines that signal by interacting with other cellular proteins, and this, in turn, is determined by a complex interplay between the biochemical, subcellular localization, and membrane trafficking properties of receptors relative to transducer and regulatory proteins. The present minireview highlights recent advances and challenges in elucidating this dynamic cell biology and toward delineating the cellular basis of drug action at the level of defined GPCR interaction networks using proteomic approaches enabled by quantitative mass spectrometry.