Enriched expression of genes associated with autism spectrum disorders in human inhibitory neurons

Genetic advances in neurodevelopmental disorders

Neurodevelopmental disorders (NDDs) are a group of highly heterogeneous diseases that affect children's social, cognitive, and emotional functioning. The etiology is complicated with genetic factors playing an important role. During the past decade, large-scale whole exome sequencing (WES) and whole genome sequencing (WGS) have vastly advanced the genetic findings of NDDs. Various forms of variants have been reported to contribute to NDDs, such as de novo mutations (DNMs), copy number variations (CNVs), rare inherited variants (RIVs), and common variation. By far, over 200 high-risk NDD genes have been identified, which are involved in biological processes including synaptic function, transcriptional and epigenetic regulation. In addition, monogenic, oligogenic, polygenetic, and omnigenic models have been proposed to explain the genetic architecture of NDDs. However, the majority of NDD patients still do not have a definitive genetic diagnosis. In the future, more types of risk factors, as well as noncoding variants, are await to be identified, and including their interplay mechanisms are key to resolving the etiology and heterogeneity of NDDs.

Untangling the Molecular Mechanisms Contributing to Autism Spectrum Disorder Using Stem Cells

Autism spectrum disorder (ASD) is a complex neuro developmental condition characterized by significant genetic and phenotypic variability, making diagnosis and treatment challenging. The heterogeneity of ASD-associated genetic variants and the absence of clear causal factors in many cases complicate personalized care. Traditional models, such as postmortem brain tissue and animal studies, have provided valuable insights but are limited in capturing the dynamic processes and human-specific aspects of ASD pathology. Recent advances in human induced pluripotent stem cell (iPSC) technology have transformed ASD research by enabling the generation of patient-derived neural cells in both two-dimensional cultures and three-dimensional brain organoid models. These models retain the donor's genetic background, allowing researchers to investigate disease-specific cellular and molecular mechanisms while identifying potential therapeutic targets tailored to individual patients. This commentary highlights how stem cell-based approaches are advancing our understanding of ASD and paving the way for more personalized diagnostic and therapeutic strategies.

Mapping the regulatory effects of common and rare non-coding variants across cellular and developmental contexts in the brain and heart

Whole genome sequencing has identified over a billion non-coding variants in humans, while GWAS has revealed the non-coding genome as a significant contributor to disease. However, prioritizing causal common and rare non-coding variants in human disease, and understanding how selective pressures have shaped the non-coding genome, remains a significant challenge. Here, we predicted the effects of 15 million variants with deep learning models trained on single-cell ATAC-seq across 132 cellular contexts in adult and fetal brain and heart, producing nearly two billion context-specific predictions. Using these predictions, we distinguish candidate causal variants underlying human traits and diseases and their context-specific effects. While common variant effects are more cell-type-specific, rare variants exert more cell-type-shared regulatory effects, with selective pressures particularly targeting variants affecting fetal brain neurons. To prioritize de novo mutations with extreme regulatory effects, we developed FLARE, a context-specific functional genomic model of constraint. FLARE outperformed other methods in prioritizing case mutations from autism-affected families near syndromic autism-associated genes; for example, identifying mutation outliers near CNTNAP2 that would be missed by alternative approaches. Overall, our findings demonstrate the potential of integrating single-cell maps with population genetics and deep learning-based variant effect prediction to elucidate mechanisms of development and disease-ultimately, supporting the notion that genetic contributions to neurodevelopmental disorders are predominantly rare.

Decoding the genetic landscape of autism: A comprehensive review

BACKGROUND

Autism spectrum disorder (ASD) is a complex neurodevelopmental condition characterized by heterogeneous symptoms and genetic underpinnings. Recent advancements in genetic and epigenetic research have provided insights into the intricate mechanisms contributing to ASD, influencing both diagnosis and therapeutic strategies.

AIM

To explore the genetic architecture of ASD, elucidate mechanistic insights into genetic mutations, and examine gene-environment interactions.

METHODS

A comprehensive systematic review was conducted, integrating findings from studies on genetic variations, epigenetic mechanisms (such as DNA methylation and histone modifications), and emerging technologies [including Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-Cas9 and single-cell RNA sequencing]. Relevant articles were identified through systematic searches of databases such as PubMed and Google Scholar.

RESULTS

Genetic studies have identified numerous risk genes and mutations associated with ASD, yet many cases remain unexplained by known factors, suggesting undiscovered genetic components. Mechanistic insights into how these genetic mutations impact neural development and brain connectivity are still evolving. Epigenetic modifications, particularly DNA methylation and non-coding RNAs, also play significant roles in ASD pathogenesis. Emerging technologies like CRISPR-Cas9 and advanced bioinformatics are advancing our understanding by enabling precise genetic editing and analysis of complex genomic data.

CONCLUSION

Continued research into the genetic and epigenetic underpinnings of ASD is crucial for developing personalized and effective treatments. Collaborative efforts integrating multidisciplinary expertise and international collaborations are essential to address the complexity of ASD and translate genetic discoveries into clinical practice. Addressing unresolved questions and ethical considerations surrounding genetic research will pave the way for improved diagnostic tools and targeted therapies, ultimately enhancing outcomes for individuals affected by ASD.

Neural mechanism of non-adaptive cognitive emotion regulation in patients with non-suicidal self-injury

BACKGROUND

The incidence of non-suicidal self-injury (NSSI) has been on the rise in recent years. Studies have shown that people with NSSI have difficulties in emotion regulation and cognitive control. In addition, some studies have investigated the cognitive emotion regulation of people with NSSI which found that they have difficulties in cognitive emotion regulation, but there was a lack of research on cognitive emotion regulation strategies and related neural mechanisms.

METHODS

This study included 117 people with NSSI (age = 19.47 ± 5.13, male = 17) and 84 non-NSSI participants (age = 19.86 ± 4.14, male = 16). People with NSSI met the DSM-5 diagnostic criteria, and non-NSSI participants had no mental or physical disorders. The study collected all participants' data of Cognitive Emotion Regulation Questionnaire (CERQ) and functional magnetic resonance imaging (fMRI) to explore the differences in psychological performance and brain between two groups. Afterwards, Machine learning was used to select the found differential brain regions to obtain the highest correlation regions with NSSI. Then, Allen's Human Brain Atlas database was used to compare with the information on the abnormal brain regions of people with NSSI to find the genetic information related to NSSI. In addition, gene enrichment analysis was carried out to find the related pathways and specific cells that may have differences.

RESULTS

The differences between NSSI participants and non-NSSI participants were as follows: positive refocusing (t = -4.74, p < 0.01); refocusing on plans (t = -4.11, p < 0.01); positive reappraisal (t = -9.22, p < 0.01); self-blame (t = 6.30, p < 0.01); rumination (t = 3.64, p < 0.01); catastrophizing (t = 9.10, p < 0.01), and blaming others (t = 2.52, p < 0.01), the precentral gyrus (t = 6.04, pFDR < 0.05) and the rolandic operculum (t = -4.57, pFDR < 0.05). Rolandic operculum activity was negatively correlated with blaming others (r = -0.20, p < 0.05). Epigenetic results showed that excitatory neurons (p < 0.01) and inhibitory neurons (p < 0.01) were significant differences in two pathways, "trans-synaptic signaling" (p < -log108) and "modulation of chemical synaptic transmission" (p < -log108) in both cells.

CONCLUSIONS

People with NSSI are more inclined to adopt non-adaptive cognitive emotion regulation strategies. Rolandic operculum is also abnormally active. Abnormal changes in the rolandic operculum of them are associated with non-adaptive cognitive emotion regulation strategies. Changes in the excitatory and inhibitory neurons provide hints to explore the abnormalities of the neurological mechanisms at the cellular level of them. Trial registration number NCT04094623.

The Variegation of Human Brain Vulnerability to Rare Genetic Disorders and Convergence With Behaviorally Defined Disorders

BACKGROUND

Diverse gene dosage disorders (GDDs) increase risk for psychiatric impairment, but characterization of GDD effects on the human brain has so far been piecemeal, with few simultaneous analyses of multiple brain features across different GDDs.

METHODS

Here, through multimodal neuroimaging of 3 aneuploidy syndromes (XXY [total n = 191, 92 control participants], XYY [total n = 81, 47 control participants], and trisomy 21 [total n = 69, 41 control participants]), we systematically mapped the effects of supernumerary X, Y, and chromosome 21 dosage across a breadth of 15 different macrostructural, microstructural, and functional imaging-derived phenotypes (IDPs).

RESULTS

The results revealed considerable diversity in cortical changes across GDDs and IDPs. This variegation of IDP change underlines the limitations of studying GDD effects unimodally. Integration across all IDP change maps revealed highly distinct architectures of cortical change in each GDD along with partial coalescence onto a common spatial axis of cortical vulnerability that is evident in all 3 GDDs. This common axis shows strong alignment with shared cortical changes in behaviorally defined psychiatric disorders and is enriched for specific molecular and cellular signatures.

CONCLUSIONS

Use of multimodal neuroimaging data in 3 aneuploidies indicates that different GDDs impose unique fingerprints of change in the human brain that differ widely depending on the imaging modality that is being considered. Embedded in this variegation is a spatial axis of shared multimodal change that aligns with shared brain changes across psychiatric disorders and therefore represents a major high-priority target for future translational research in neuroscience.

An overview of human single-cell RNA sequencing studies in neurobiological disease

Neurobiological disorders are highly prevalent medical conditions that contribute to significant morbidity and mortality. Single-cell RNA sequencing (scRNA-seq) is a technique that measures gene expression in individual cells. In this review, we survey scRNA-seq studies of tissues from patients suffering from neurobiological disease. This includes postmortem human brains and organoids derived from peripheral cells. We highlight a range of conditions, including epilepsy, cognitive disorders, substance use disorders, and mood disorders. These findings provide new insights into neurobiological disease in multiple ways, including discovering novel cell types or subtypes involved in disease, proposing new pathophysiological mechanisms, uncovering novel drug targets, or identifying potential biomarkers. We discuss the quality of these findings and suggest potential future directions and areas open for additional research, including studies of non-cortical brain regions and additional conditions such as anxiety disorders, mood disorders, and sleeping disorders. We argue that additional scRNA-seq of tissues from patients suffering from neurobiological disease could advance our understanding and treatment of these conditions.

Modeling Autism Spectrum Disorders with Induced Pluripotent Stem Cell-Derived Brain Organoids

Autism spectrum disorders (ASD) are a group of complex neurodevelopmental disorders that affect communication and social interactions and present with restricted interests and repetitive behavior patterns. The susceptibility to ASD is strongly influenced by genetic/heritable factors; however, there is still a large gap in understanding the cellular and molecular mechanisms underlying the neurobiology of ASD. Significant progress has been made in identifying ASD risk genes and the possible convergent pathways regulated by these gene networks during development. The breakthrough of cellular reprogramming technology has allowed the generation of induced pluripotent stem cells (iPSCs) from individuals with syndromic and idiopathic ASD, providing patient-specific cell models for mechanistic studies. In the past decade, protocols for developing brain organoids from these cells have been established, leading to significant advances in the in vitro reproducibility of the early steps of human brain development. Here, we reviewed the most relevant literature regarding the application of brain organoids to the study of ASD, providing the current state of the art, and discussing the impact of such models on the field, limitations, and opportunities for future development.

scHumanNet: a single-cell network analysis platform for the study of cell-type specificity of disease genes

A major challenge in single-cell biology is identifying cell-type-specific gene functions, which may substantially improve precision medicine. Differential expression analysis of genes is a popular, yet insufficient approach, and complementary methods that associate function with cell type are required. Here, we describe scHumanNet (https://github.com/netbiolab/scHumanNet), a single-cell network analysis platform for resolving cellular heterogeneity across gene functions in humans. Based on cell-type-specific gene networks (CGNs) constructed under the guidance of the HumanNet reference interactome, scHumanNet displayed higher functional relevance to the cellular context than CGNs built by other methods on single-cell transcriptome data. Cellular deconvolution of gene signatures based on network compactness across cell types revealed breast cancer prognostic markers associated with T cells. scHumanNet could also prioritize genes associated with particular cell types using CGN centrality and identified the differential hubness of CGNs between disease and healthy conditions. We demonstrated the usefulness of scHumanNet by uncovering T-cell-specific functional effects of GITR, a prognostic gene for breast cancer, and functional defects in autism spectrum disorder genes specific for inhibitory neurons. These results suggest that scHumanNet will advance our understanding of cell-type specificity across human disease genes.

Early postnatal serotonin modulation prevents adult-stage deficits in Arid1b-deficient mice through synaptic transcriptional reprogramming

Autism spectrum disorder is characterized by early postnatal symptoms, although little is known about the mechanistic deviations that produce them and whether correcting them has long-lasting preventive effects on adult-stage deficits. ARID1B, a chromatin remodeler implicated in neurodevelopmental disorders, including autism spectrum disorder, exhibits strong embryonic- and early postnatal-stage expression. We report here that Arid1b-happloinsufficient (Arid1b+/-) mice display autistic-like behaviors at juvenile and adult stages accompanied by persistent decreases in excitatory synaptic density and transmission. Chronic treatment of Arid1b+/- mice with fluoxetine, a selective serotonin-reuptake inhibitor, during the first three postnatal weeks prevents synaptic and behavioral deficits in adults. Mechanistically, these rescues accompany transcriptomic changes, including upregulation of FMRP targets and normalization of HDAC4/MEF2A-related transcriptional regulation of the synaptic proteins, SynGAP1 and Arc. These results suggest that chronic modulation of serotonergic receptors during critical early postnatal periods prevents synaptic and behavioral deficits in adult Arid1b+/- mice through transcriptional reprogramming.

SFARI genes and where to find them; modelling Autism Spectrum Disorder specific gene expression dysregulation with RNA-seq data

Autism Spectrum Disorders (ASD) have a strong, yet heterogeneous, genetic component. Among the various methods that are being developed to help reveal the underlying molecular aetiology of the disease one approach that is gaining popularity is the combination of gene expression and clinical genetic data, often using the SFARI-gene database, which comprises lists of curated genes considered to have causative roles in ASD when mutated in patients. We build a gene co-expression network to study the relationship between ASD-specific transcriptomic data and SFARI genes and then analyse it at different levels of granularity. No significant evidence is found of association between SFARI genes and differential gene expression patterns when comparing ASD samples to a control group, nor statistical enrichment of SFARI genes in gene co-expression network modules that have a strong correlation with ASD diagnosis. However, classification models that incorporate topological information from the whole ASD-specific gene co-expression network can predict novel SFARI candidate genes that share features of existing SFARI genes and have support for roles in ASD in the literature. A statistically significant association is also found between the absolute level of gene expression and SFARI's genes and Scores, which can confound the analysis if uncorrected. We propose a novel approach to correct for this that is general enough to be applied to other problems affected by continuous sources of bias. It was found that only co-expression network analyses that integrate information from the whole network are able to reveal signatures linked to ASD diagnosis and novel candidate genes for the study of ASD, which individual gene or module analyses fail to do. It was also found that the influence of SFARI genes permeates not only other ASD scoring systems, but also lists of genes believed to be involved in other neurodevelopmental disorders.

Characterization of cell-cell communication in autistic brains with single-cell transcriptomes

BACKGROUND

Autism spectrum disorder is a neurodevelopmental disorder, affecting 1-2% of children. Studies have revealed genetic and cellular abnormalities in the brains of affected individuals, leading to both regional and distal cell communication deficits.

METHODS

Recent application of single-cell technologies, especially single-cell transcriptomics, has significantly expanded our understanding of brain cell heterogeneity and further demonstrated that multiple cell types and brain layers or regions are perturbed in autism. The underlying high-dimensional single-cell data provides opportunities for multilevel computational analysis that collectively can better deconvolute the molecular and cellular events altered in autism. Here, we apply advanced computation and pattern recognition approaches on single-cell RNA-seq data to infer and compare inter-cell-type signaling communications in autism brains and controls.

RESULTS

Our results indicate that at a global level, there are cell-cell communication differences in autism in comparison with controls, largely involving neurons as both signaling senders and receivers, but glia also contribute to the communication disruption. Although the magnitude of changes is moderate, we find that excitatory and inhibitor neurons are involved in multiple intercellular signaling that exhibits increased strengths in autism, such as NRXN and CNTN signaling. Not all genes in the intercellular signaling pathways show differential expression, but genes in the affected pathways are enriched for axon guidance, synapse organization, neuron migration, and other critical cellular functions. Furthermore, those genes are highly connected to and enriched for genes previously associated with autism risks.

CONCLUSIONS

Overall, our proof-of-principle computational study using single-cell data uncovers key intercellular signaling pathways that are potentially disrupted in the autism brains, suggesting that more studies examining cross-cell type effects can be valuable for understanding autism pathogenesis.

Mutant glucocerebrosidase impairs α-synuclein degradation by blockade of chaperone-mediated autophagy

The most common genetic risk factors for Parkinson's disease (PD) are a set of heterozygous mutant (MT) alleles of the GBA1 gene that encodes β-glucocerebrosidase (GCase), an enzyme normally trafficked through the ER/Golgi apparatus to the lysosomal lumen. We found that half of the GCase in lysosomes from postmortem human GBA-PD brains was present on the lysosomal surface and that this mislocalization depends on a pentapeptide motif in GCase used to target cytosolic protein for degradation by chaperone-mediated autophagy (CMA). MT GCase at the lysosomal surface inhibits CMA, causing accumulation of CMA substrates including α-synuclein. Single-cell transcriptional analysis and proteomics of brains from GBA-PD patients confirmed reduced CMA activity and proteome changes comparable to those in CMA-deficient mouse brain. Loss of the MT GCase CMA motif rescued primary substantia nigra dopaminergic neurons from MT GCase-induced neuronal death. We conclude that MT GBA1 alleles block CMA function and produce α-synuclein accumulation.

Cortical Cartography: Mapping Arealization Using Single-Cell Omics Technology

The cerebral cortex derives its cognitive power from a modular network of specialized areas processing a multitude of information. The assembly and organization of these regions is vital for human behavior and perception, as evidenced by the prevalence of area-specific phenotypes that manifest in neurodevelopmental and psychiatric disorders. Generations of scientists have examined the architecture of the human cortex, but efforts to capture the gene networks which drive arealization have been hampered by the lack of tractable models of human neurodevelopment. Advancements in "omics" technologies, imaging, and computational power have enabled exciting breakthroughs into the molecular and structural characteristics of cortical areas, including transcriptomic, epigenomic, metabolomic, and proteomic profiles of mammalian models. Here we review the single-omics atlases that have shaped our current understanding of cortical areas, and their potential to fuel a new era of multi-omic single-cell endeavors to interrogate both the developing and adult human cortex.

Deep post-GWAS analysis identifies potential risk genes and risk variants for Alzheimer's disease, providing new insights into its disease mechanisms

Alzheimer's disease (AD) is a genetically complex, multifactorial neurodegenerative disease. It affects more than 45 million people worldwide and currently remains untreatable. Although genome-wide association studies (GWAS) have identified many AD-associated common variants, only about 25 genes are currently known to affect the risk of developing AD, despite its highly polygenic nature. Moreover, the risk variants underlying GWAS AD-association signals remain unknown. Here, we describe a deep post-GWAS analysis of AD-associated variants, using an integrated computational framework for predicting both disease genes and their risk variants. We identified 342 putative AD risk genes in 203 risk regions spanning 502 AD-associated common variants. 246 AD risk genes have not been identified as AD risk genes by previous GWAS collected in GWAS catalogs, and 115 of 342 AD risk genes are outside the risk regions, likely under the regulation of transcriptional regulatory elements contained therein. Even more significantly, for 109 AD risk genes, we predicted 150 risk variants, of both coding and regulatory (in promoters or enhancers) types, and 85 (57%) of them are supported by functional annotation. In-depth functional analyses showed that AD risk genes were overrepresented in AD-related pathways or GO terms-e.g., the complement and coagulation cascade and phosphorylation and activation of immune response-and their expression was relatively enriched in microglia, endothelia, and pericytes of the human brain. We found nine AD risk genes-e.g., IL1RAP, PMAIP1, LAMTOR4-as predictors for the prognosis of AD survival and genes such as ARL6IP5 with altered network connectivity between AD patients and normal individuals involved in AD progression. Our findings open new strategies for developing therapeutics targeting AD risk genes or risk variants to influence AD pathogenesis.

The effect of probiotic, prebiotic and gut microbiota on ASD: A review and future perspectives

Autism spectrum disorder is a serious neurodevelopmental disease that affects social communication and behavior, characterized by an increasingly common immune mechanism and various complications in the gastrointestinal system. Symptoms of autism can generally vary according to the genetic background of the individuals, the environment in which they live. The microbiota of individuals with autism is also different from healthy individuals. Recently, probiotics, prebiotic, fecal microbiota transplantation, diet therapy, etc. options have come to the fore. Cofactors are even more important at this stage. Since it is related to the gut microbiota, immune mechanism, gastrointestinal system, attention has been drawn to the relationship between dysbiosis, autism in the intestine. The component of the gut microbiota in individuals with autism has been linked with gastrointestinal symptoms that develop with autism severity. However, the role of the microbiota in diagnosis, follow-up, treatment is not clear yet, and its two-way relationship with the nervous system makes it difficult to establish a cause-effect relationship. Nutritional cofactors required in neurotransmitter synthesis and enzyme activation must be regularly and adequately taken to maximize brain functions in autistic individuals. Therefore, this study was conducted to investigate the cause-effect relationship of ASD with microbiota and brain-gut axis, probiotic-prebiotic use.

The phenomenal epigenome in neurodevelopmental disorders

Disruption of chromatin structure due to epimutations is a leading genetic etiology of neurodevelopmental disorders, collectively known as chromatinopathies. We show that there is an increasing level of convergence from the high diversity of genes that are affected by mutations to the molecular networks and pathways involving the respective proteins, the disrupted cellular and subcellular processes, and their consequence for higher order cellular network function. This convergence is ultimately reflected by specific phenotypic features shared across the various chromatinopathies. Based on these observations, we propose that the commonly disrupted molecular and cellular anomalies might provide a rational target for the development of symptomatic interventions for defined groups of genetically distinct neurodevelopmental disorders.

Convergent and distributed effects of the 3q29 deletion on the human neural transcriptome

The 3q29 deletion (3q29Del) confers high risk for schizophrenia and other neurodevelopmental and psychiatric disorders. However, no single gene in this interval is definitively associated with disease, prompting the hypothesis that neuropsychiatric sequelae emerge upon loss of multiple functionally-connected genes. 3q29 genes are unevenly annotated and the impact of 3q29Del on the human neural transcriptome is unknown. To systematically formulate unbiased hypotheses about molecular mechanisms linking 3q29Del to neuropsychiatric illness, we conducted a systems-level network analysis of the non-pathological adult human cortical transcriptome and generated evidence-based predictions that relate 3q29 genes to novel functions and disease associations. The 21 protein-coding genes located in the interval segregated into seven clusters of highly co-expressed genes, demonstrating both convergent and distributed effects of 3q29Del across the interrogated transcriptomic landscape. Pathway analysis of these clusters indicated involvement in nervous-system functions, including synaptic signaling and organization, as well as core cellular functions, including transcriptional regulation, posttranslational modifications, chromatin remodeling, and mitochondrial metabolism. Top network-neighbors of 3q29 genes showed significant overlap with known schizophrenia, autism, and intellectual disability-risk genes, suggesting that 3q29Del biology is relevant to idiopathic disease. Leveraging "guilt by association", we propose nine 3q29 genes, including one hub gene, as prioritized drivers of neuropsychiatric risk. These results provide testable hypotheses for experimental analysis on causal drivers and mechanisms of the largest known genetic risk factor for schizophrenia and highlight the study of normal function in non-pathological postmortem tissue to further our understanding of psychiatric genetics, especially for rare syndromes like 3q29Del, where access to neural tissue from carriers is unavailable or limited.

Reciprocal control of translation and transcription in autism spectrum disorder

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by deficits in social communication and the presence of restricted patterns of interest and repetitive behaviors. ASD is genetically heterogeneous and is believed to be caused by both inheritable and de novo gene variations. Studies have revealed an extremely complex genetic landscape of ASD, favoring the idea that mutations in different clusters of genes interfere with interconnected downstream signaling pathways and circuitry, resulting in aberrant behavior. In this review, we describe a select group of candidate genes that represent both syndromic and non-syndromic forms of ASD and encode proteins that are important in transcriptional and translational regulation. We focus on the interplay between dysregulated translation and transcription in ASD with the hypothesis that dysregulation of each synthetic process triggers a feedback loop to act on the other, which ultimately exacerbates ASD pathophysiology. Finally, we summarize findings from interdisciplinary studies that pave the way for the investigation of the cooperative impact of different genes and pathways underlying the development of ASD.

The Emergence of Network Activity Patterns in the Somatosensory Cortex - An Early Window to Autism Spectrum Disorders

Across mammalian species, patterned activity in neural populations is a prominent feature of developing sensory cortices. Numerous studies have long appreciated the diversity of these patterns, characterizing their differences in spatial and temporal dynamics. In the murine somatosensory cortex, neuronal co-activation is thought to guide the formation of sensory maps and prepare the cortex for sensory processing after birth. While pioneering studies deftly utilized slice electrophysiology and unit recordings to characterize correlated activity, a detailed understanding of the underlying circuits remains poorly understood. More recently, advances in in vivo calcium imaging in awake mouse pups and increasing genetic tractability of neuronal types have allowed unprecedented manipulation of circuit components at select developmental timepoints. These novel approaches have proven fundamental in uncovering the identity of neurons engaged in correlated activity during development. In particular, recent studies have highlighted interneurons as key in refining the spatial extent and temporal progression of patterned activity. Here, we discuss how emergent synchronous activity across the first postnatal weeks is shaped by underlying gamma aminobutyric acid (GABA)ergic contributors in the somatosensory cortex. Further, the importance of participation in specific activity patterns per se for neuronal maturation and perdurance will be of particular highlight in this survey of recent literature. Finally, we underscore how aberrant neuronal synchrony and disrupted inhibitory interneuron activity underlie sensory perturbations in neurodevelopmental disorders, particularly Autism Spectrum Disorders (ASDs), emphasizing the importance of future investigative approaches that incorporate the spatiotemporal features of patterned activity alongside the cellular components to probe disordered circuit assembly.

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.

Multiplex gene and phenotype network to characterize shared genetic pathways of epilepsy and autism

It is well established that epilepsy and autism spectrum disorder (ASD) commonly co-occur; however, the underlying biological mechanisms of the co-occurence from their genetic susceptibility are not well understood. Our aim in this study is to characterize genetic modules of subgroups of epilepsy and autism genes that have similar phenotypic manifestations and biological functions. We first integrate a large number of expert-compiled and well-established epilepsy- and ASD-associated genes in a multiplex network, where one layer is connected through protein-protein interaction (PPI) and the other layer through gene-phenotype associations. We identify two modules in the multiplex network, which are significantly enriched in genes associated with both epilepsy and autism as well as genes highly expressed in brain tissues. We find that the first module, which represents the Gene Ontology category of ion transmembrane transport, is more epilepsy-focused, while the second module, representing synaptic signaling, is more ASD-focused. However, because of their enrichment in common genes and association with both epilepsy and ASD phenotypes, these modules point to genetic etiologies and biological processes shared between specific subtypes of epilepsy and ASD. Finally, we use our analysis to prioritize new candidate genes for epilepsy (i.e. ANK2, CACNA1E, CACNA2D3, GRIA2, DLG4) for further validation. The analytical approaches in our study can be applied to similar studies in the future to investigate the genetic connections between different human diseases.

An analytical method for the identification of cell type-specific disease gene modules

Background

Genome-wide association studies have identified genetic variants associated with the risk of brain-related diseases, such as neurological and psychiatric disorders, while the causal variants and the specific vulnerable cell types are often needed to be studied. Many disease-associated genes are expressed in multiple cell types of human brains, while the pathologic variants affect primarily specific cell types. We hypothesize a model in which what determines the manifestation of a disease in a cell type is the presence of disease module comprised of disease-associated genes, instead of individual genes. Therefore, it is essential to identify the presence/absence of disease gene modules in cells.

Methods

To characterize the cell type-specificity of brain-related diseases, we construct human brain cell type-specific gene interaction networks integrating human brain nucleus gene expression data with a referenced tissue-specific gene interaction network. Then from the cell type-specific gene interaction networks, we identify significant cell type-specific disease gene modules by performing statistical tests.

Results

Between neurons and glia cells, the constructed cell type-specific gene networks and their gene functions are distinct. Then we identify cell type-specific disease gene modules associated with autism spectrum disorder and find that different gene modules are formed and distinct gene functions may be dysregulated in different cells. We also study the similarity and dissimilarity in cell type-specific disease gene modules among autism spectrum disorder, schizophrenia and bipolar disorder. The functions of neurons-specific disease gene modules are associated with synapse for all three diseases, while those in glia cells are different. To facilitate the use of our method, we develop an R package, CtsDGM, for the identification of cell type-specific disease gene modules.

Conclusions

The results support our hypothesis that a disease manifests itself in a cell type through forming a statistically significant disease gene module. The identification of cell type-specific disease gene modules can promote the development of more targeted biomarkers and treatments for the disease. Our method can be applied for depicting the cell type heterogeneity of a given disease, and also for studying the similarity and dissimilarity between different disorders, providing new insights into the molecular mechanisms underlying the pathogenesis and progression of diseases.

Brief Report: Genetic Links Between Autism and Suicidal Behavior-A Preliminary Investigation

Evidence suggests there may be increased risk for suicidal behavior among individuals with autism spectrum disorder (ASD). An emerging body of research explores social factors that may contribute to increased risk, however little is known about the potential role of biological factors. The current project addresses this knowledge gap through a preliminary study of genes associated with both ASD and suicidal behavior. Gene set enrichment tests of eight genes strongly associated with both ASD and suicidal behavior revealed overrepresentation of nine biological processes, including cognition and synapse function, and 14 cellular components, including the neuron, the synapse, and the synaptic and postsynaptic membrane. These results can be used to inform future investigations of the biological underpinnings of suicidal behavior and ASD.

Genetic origins of suicidality? A synopsis of genes in suicidal behaviours, with regard to evidence diversity, disorder specificity and neurodevelopmental brain transcriptomics

With regard to suicidal behavior (SB) genetics, many novel genes have been implicated over the years, in particular by a variety of hypothesis-free genomic methods (e.g. GWAS and exome sequencing). In addition, many novel SB gene findings appear enigmatic in their biological relevance and have weak statistical support, e.g. lack direct replications. Adding to this is the comorbidity between psychiatric disorders and SB. Here we provide a synopsis of SB genes, by prioritization of 106 (out of ~2500) genes based on their highest level of evidence diversity across mainly five genetic evidence types (candidate/GWAS SNP, CNV, linkage and whole exome sequencing), supplemented by three functional categories. This is a representative set of both old and new SB gene candidates, implicated by all kinds of evidence. Furthermore, we define a subset of 40 SB "specific" genes, which are not found among ~3900 genes implicated in other neuropsychiatric disorders, e.g. Autism spectrum disorders (ASD) or Schizophrenia. Biological research of suicidality contains a major developmental focus, e.g. with regard to the gene-environment interactions and epigenetic effects during childhood. Less is known about early (fetal) development and SB genes. Inspired by huge efforts to understand the role early (fetal) neurodevelopment in e.g. ASD by using brain transcriptomic data, we here also characterize the 106 SB genes. We find interesting spatiotemporal expression differences and similarities between SB specific and non-specific genes during brain neurodevelopment. These aspects are of interest to investigate further, to better understand and counteract the genetic origins suicidality.

Lessons from single cell sequencing in CNS cell specification and function

Modern RNA sequencing methods have greatly increased our understanding of the molecular fingerprint of neurons, astrocytes and oligodendrocytes throughout the central nervous system (CNS). Technical approaches with greater sensitivity and throughput have uncovered new connections between gene expression, cell biology, and ultimately CNS function. In recent years, single cell RNA-sequencing (scRNA-seq) has made a large impact on the neurosciences by enhancing the resolution of types of cells that make up the CNS and shedding light on their developmental trajectories and how their diversity is modified across species. Here we will review the advantages, innovations, and challenges of the single cell genomics era and highlight how it has impacted our understanding of neurodevelopment and neurological function.

DNA Methylation Associated with Mitochondrial Dysfunction in a South African Autism Spectrum Disorder Cohort

Autism spectrum disorder (ASD) is characterized by phenotypic heterogeneity and a complex genetic architecture which includes distinctive epigenetic patterns. We report differential DNA methylation patterns associated with ASD in South African children. An exploratory whole‐epigenome methylation screen using the Illumina 450 K MethylationArray identified differentially methylated CpG sites between ASD and controls that mapped to 898 genes (P ≤ 0.05) which were enriched for nine canonical pathways converging on mitochondrial metabolism and protein ubiquitination. Targeted Next Generation Bisulfite Sequencing of 27 genes confirmed differential methylation between ASD and control in our cohort. DNA pyrosequencing of two of these genes, the mitochondrial enzyme Propionyl‐CoA Carboxylase subunit Beta (PCCB) and Protocadherin Alpha 12 (PCDHA12), revealed a wide range of methylation levels (9–49% and 0–54%, respectively) in both ASD and controls. Three CpG loci were differentially methylated in PCCB (P ≤ 0.05), while PCDHA12, previously linked to ASD, had two significantly different CpG sites (P ≤ 0.001) between ASD and control. Differentially methylated CpGs were hypomethylated in ASD. Metabolomic analysis of urinary organic acids revealed that three metabolites, 3‐hydroxy‐3‐methylglutaric acid (P = 0.008), 3‐methyglutaconic acid (P = 0.018), and ethylmalonic acid (P = 0.043) were significantly elevated in individuals with ASD. These metabolites are directly linked to mitochondrial respiratory chain disorders, with a putative link to PCCB, consistent with impaired mitochondrial function. Our data support an association between DNA methylation and mitochondrial dysfunction in the etiology of ASD. Autism Res 2020, 13: 1079‐1093. © 2020 The Authors. Autism Research published by International Society for Autism Research published by Wiley Periodicals, Inc.

Lay Summary

Epigenetic changes are chemical modifications of DNA which can change gene function. DNA methylation, a type of epigenetic modification, is linked to autism. We examined DNA methylation in South African children with autism and identified mitochondrial genes associated with autism. Mitochondria are power‐suppliers in cells and mitochondrial genes are essential to metabolism and energy production, which are important for brain cells during development. Our findings suggest that some individuals with ASD also have mitochondrial dysfunction.

Identification of amygdala-expressed genes associated with autism spectrum disorder

BACKGROUND

Studies of individuals with autism spectrum disorder (ASD) have revealed a strong multigenic basis with the identification of hundreds of ASD susceptibility genes. ASD is characterized by social deficits and a range of other phenotypes, implicating complex genetics and involvement of a variety of brain regions. However, how mutations and mis-expression of select gene sets are associated with the behavioral components of ASD remains unknown. We reasoned that for genes to be associated with ASD core behaviors they must be: (1) expressed in brain regions relevant to ASD social behaviors and (2) expressed during the ASD susceptible window of brain development.

METHODS

Focusing on the amygdala, a brain region whose dysfunction has been highly implicated in the social component of ASD, we mined publicly available gene expression databases to identify ASD-susceptibility genes expressed during human and mouse amygdala development. We found that a large cohort of known ASD susceptibility genes is expressed in the developing human and mouse amygdala. We further performed analysis of single-nucleus RNA-seq (snRNA-seq) data from microdissected amygdala tissue from five ASD and five control human postmortem brains ranging in age from 4 to 20 years to elucidate cell type specificity of amygdala-expressed genes and their dysregulation in ASD.

RESULTS

Our analyses revealed that of the high-ranking ASD susceptibility genes, 80 are expressed in both human and mouse amygdala during fetal to early postnatal stages of development. Our human snRNA-seq analyses revealed cohorts of genes with altered expression in the ASD amygdala postnatally, especially within excitatory neurons, with dysregulated expression of seven genes predicted from our datamining pipeline.

LIMITATIONS

We were limited by the ages for which we were able to obtain human tissue; therefore, the results from our datamining pipeline approach will require validation, to the extent possible, in human tissue from earlier developmental stages.

CONCLUSIONS

Our pipeline narrows down the number of amygdala-expressed genes possibly involved in the social pathophysiology of ASD. Our human single-nucleus gene expression analyses revealed that ASD is characterized by changes in gene expression in specific cell types in the early postnatal amygdala.

Cell Type-Specific Gene Network-Based Analysis Depicts the Heterogeneity of Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a complex neuropsychiatric disorder characterized by substantial heterogeneity. To identify the convergence of disease pathology on common pathways, it is essential to understand the correlations among ASD candidate genes and study shared molecular pathways between them. Investigating functional interactions between ASD candidate genes in different cell types of normal human brains may shed new light on the genetic heterogeneity of ASD. Here we apply cell type-specific gene network-based analysis to analyze human brain nucleus gene expression data and identify cell type-specific ASD-associated gene modules. ASD-associated modules specific to different cell types are relevant to different gene functions, for instance, the astrocytes-specific module is involved in functions of axon and neuron projection guidance, GABAergic interneuron-specific modules are involved in functions of postsynaptic membrane, extracellular matrix structural constituent, and ion transmembrane transporter activity. Our findings can promote the study of cell type heterogeneity of ASD, providing new insights into the pathogenesis of ASD. Our method has been shown to be effective in discovering cell type-specific disease-associated gene expression patterns and can be applied to other complex diseases.

Genome-wide, integrative analysis of circular RNA dysregulation and the corresponding circular RNA-microRNA-mRNA regulatory axes in autism

Circular RNAs (circRNAs), a class of long noncoding RNAs, are known to be enriched in mammalian neural tissues. Although a wide range of dysregulation of gene expression in autism spectrum disorder (ASD) have been reported, the role of circRNAs in ASD remains largely unknown. Here, we performed genome-wide circRNA expression profiling in postmortem brains from individuals with ASD and controls and identified 60 circRNAs and three coregulated modules that were perturbed in ASD. By integrating circRNA, microRNA, and mRNA dysregulation data derived from the same cortex samples, we identified 8170 ASD-associated circRNA-microRNA-mRNA interactions. Putative targets of the axes were enriched for ASD risk genes and genes encoding inhibitory postsynaptic density (PSD) proteins, but not for genes implicated in monogenetic forms of other brain disorders or genes encoding excitatory PSD proteins. This reflects the previous observation that ASD-derived organoids show overproduction of inhibitory neurons. We further confirmed that some ASD risk genes (NLGN1, STAG1, HSD11B1, VIP, and UBA6) were regulated by an up-regulated circRNA (circARID1A) via sponging a down-regulated microRNA (miR-204-3p) in human neuronal cells. Particularly, alteration of NLGN1 expression is known to affect the dynamic processes of memory consolidation and strengthening. To the best of our knowledge, this is the first systems-level view of circRNA regulatory networks in ASD cortex samples. We provided a rich set of ASD-associated circRNA candidates and the corresponding circRNA-microRNA-mRNA axes, particularly those involving ASD risk genes. Our findings thus support a role for circRNA dysregulation and the corresponding circRNA-microRNA-mRNA axes in ASD pathophysiology.

Cellular and molecular characterization of multiplex autism in human induced pluripotent stem cell-derived neurons

Background

Autism spectrum disorder (ASD) is a neurodevelopmental disorder with pronounced heritability in the general population. This is largely attributable to the effects of polygenic susceptibility, with inherited liability exhibiting distinct sex differences in phenotypic expression. Attempts to model ASD in human cellular systems have principally involved rare de novo mutations associated with ASD phenocopies. However, by definition, these models are not representative of polygenic liability, which accounts for the vast share of population-attributable risk.

Methods

Here, we performed what is, to our knowledge, the first attempt to model multiplex autism using patient-derived induced pluripotent stem cells (iPSCs) in a family manifesting incremental degrees of phenotypic expression of inherited liability (absent, intermediate, severe). The family members share an inherited variant of uncertain significance (VUS) in GPD2, a gene that was previously associated with developmental disability but here is insufficient by itself to cause ASD. iPSCs from three first-degree relatives and an unrelated control were differentiated into both cortical excitatory (cExN) and cortical inhibitory (cIN) neurons, and cellular phenotyping and transcriptomic analysis were conducted.

Results

cExN neurospheres from the two affected individuals were reduced in size, compared to those derived from unaffected related and unrelated individuals. This reduction was, at least in part, due to increased apoptosis of cells from affected individuals upon initiation of cExN neural induction. Likewise, cIN neural progenitor cells from affected individuals exhibited increased apoptosis, compared to both unaffected individuals. Transcriptomic analysis of both cExN and cIN neural progenitor cells revealed distinct molecular signatures associated with affectation, including the misregulation of suites of genes associated with neural development, neuronal function, and behavior, as well as altered expression of ASD risk-associated genes.

Conclusions

We have provided evidence of morphological, physiological, and transcriptomic signatures of polygenic liability to ASD from an analysis of cellular models derived from a multiplex autism family. ASD is commonly inherited on the basis of additive genetic liability. Therefore, identifying convergent cellular and molecular phenotypes resulting from polygenic and monogenic susceptibility may provide a critical bridge for determining which of the disparate effects of rare highly deleterious mutations might also apply to common autistic syndromes.

Pathogenetical and Neurophysiological Features of Patients with Autism Spectrum Disorder: Phenomena and Diagnoses

Autism spectrum disorder (ASD) is a neurodevelopmental disorder that is accompanied by social deficits, repetitive and restricted interests, and altered brain development. The majority of ASD patients suffer not only from ASD itself but also from its neuropsychiatric comorbidities. Alterations in brain structure, synaptic development, and misregulation of neuroinflammation are considered risk factors for ASD and neuropsychiatric comorbidities. Electroencephalography has been developed to quantitatively explore effects of these neuronal changes of the brain in ASD. The pineal neurohormone melatonin is able to contribute to neural development. Also, this hormone has an inflammation-regulatory role and acts as a circadian key regulator to normalize sleep. These functions of melatonin may play crucial roles in the alleviation of ASD and its neuropsychiatric comorbidities. In this context, this article focuses on the presumable role of melatonin and suggests that this hormone could be a therapeutic agent for ASD and its related neuropsychiatric disorders.

Multiscale Neuroscience of Psychiatric Disorders

The human brain comprises a multiscale network with multiple levels of organization. Neurons with dendritic and axonal connections form the microscale fabric of brain circuitry, and macroscale brain regions and white matter connections form the infrastructure for system-level brain communication and information integration. In this review, we discuss the emerging trend of multiscale neuroscience, the multidisciplinary field that brings together data from these different levels of nervous system organization to form a better understanding of between-scale relationships of brain structure, function, and behavior in health and disease. We provide a broad overview of this developing field and discuss recent findings of exemplary multiscale neuroscience studies that illustrate the importance of studying cross-scale interactions among the genetic, molecular, cellular, and macroscale levels of brain circuitry and connectivity and behavior. We particularly consider a central, overarching goal of these multiscale neuroscience studies of human brain connectivity: to obtain insight into how disease-related alterations at one level of organization may underlie alterations observed at other scales of brain network organization in mental disorders. We conclude by discussing the current limitations, challenges, and future directions of the field.

Putative contributions of the sex chromosome proteins SOX3 and SRY to neurodevelopmental disorders

The male-biased prevalence of certain neurodevelopmental disorders and the sex-biased outcomes associated with stress exposure during gestation have been previously described. Here, we hypothesized that genes distinctively targeted by only one or both homologous proteins highly conserved across therian mammals, SOX3 and SRY, could induce sexual adaptive changes that result in a differential risk for neurodevelopmental disorders. ChIP-seq/chip data showed that SOX3/SRY gene targets were expressed in different brain cell types in mice. We used orthologous human genes in rodent genomes to extend the number of SOX3/SRY set (1,721). These genes were later found to be enriched in five modules of coexpressed genes during the early and mid-gestation periods (FDR < 0.05), independent of sexual hormones. Genes with differential expression (24, p < 0.0001) and methylation (40, p < 0.047) between sexes were overrepresented in this set. Exclusive SOX3 or SRY target genes were more associated with the late gestational and postnatal periods. Using autism as a model sex-biased disorder, the SOX3/SRY set was enriched in autism gene databases (FDR ≤ 0.05), and there were more de novo variations from the male autism spectrum disorder (ASD) samples under the SRY peaks compared to the random peaks (p < 0.024). The comparison of coexpressed networks of SOX3/SRY target genes between male autism and control samples revealed low preservation in gene modules related to stress response (99 genes) and neurogenesis (78 genes). This study provides evidence that while SOX3 is a regulatory mechanism for both sexes, the male-exclusive SRY also plays a role in gene regulation, suggesting a potential mechanism for sex bias in ASD.

Regulatory genes and pathways disrupted in autism spectrum disorders

Autism spectrum disorder (ASD) is a highly prevalent and complex genetic disorder. The complex genetic make-up of ASD has been extensively studied and both common and rare genetic variants in up to 1000 genes have been linked to increased ASD risk. While these studies highlight the genetic complexity and begin to provide a window for delineating pathways at risk in ASD, the pathogenicity and specific contribution of many mutations to the disorder are poorly understood. Defining the convergent pathways disrupted by this large number of ASD-associated genetic variants will help to understand disease pathogenesis and direct future therapeutic efforts for the groups of patients with distinct etiologies. Here, we review some of the common regulatory pathways including chromatin remodeling, transcription, and alternative splicing that have emerged as common features from genetic and transcriptomic profiling of ASD. For each category, we focus on one gene (CHD8, FOXP1, and RBFOX1) that is significantly linked to ASD and functionally characterized in recent years. Finally, we discuss genetic and transcriptomic overlap between ASD and other neurodevelopmental disorders.

The Human Cell Atlas: making 'cell space' for disease

A single change in DNA, RNA, proteins or cellular images can be useful as a biomarker of disease onset or progression. With high-throughput molecular phenotyping of single cells, it is now conceivable that the molecular changes occurring across thousands, or tens of thousands, of individual cells could additionally be considered as a disease biomarker. Transition to a disease state would then be reflected by the shifts in cell numbers and locations across a multidimensional space that is defined by the molecular content of cells. Realising this ambition requires a robust formulation of such a multidimensional 'cell space'. This is one of the goals of the recently launched Human Cell Atlas project. A second goal is to populate this 'cell space' with all cell types in the human body. Here, I consider the potential of the Human Cell Atlas project for improving our description and understanding of the cell-type specificity of disease.

Cortical interneuron function in autism spectrum condition

Cortical interneurons (INs) are a diverse group of neurons that project locally and shape the function of neural networks throughout the brain. Multiple lines of evidence suggest that a proper balance of glutamate and GABA signaling is essential for both the proper function and development of the brain. Dysregulation of this system may lead to neurodevelopmental disorders, including autism spectrum condition (ASC). We evaluate the development and function of INs in rodent and human models and examine how neurodevelopmental dysfunction may produce core symptoms of ASC. Finding common physiological mechanisms that underlie neurodevelopmental disorders may lead to novel pharmacological targets and candidates that could improve the cognitive and emotional symptoms associated with ASC.

Animal models of PTSD: a challenge to be met

Recent years have seen increased interest in psychopathologies related to trauma exposure. Specifically, there has been a growing awareness to posttraumatic stress disorder (PTSD) in part due to terrorism, climate change-associated natural disasters, the global refugee crisis, and increased violence in overpopulated urban areas. However, notwithstanding the increased awareness to the disorder, the increasing number of patients, and the devastating impact on the lives of patients and their families, the efficacy of available treatments remains limited and highly unsatisfactory. A major scientific effort is therefore devoted to unravel the neural mechanisms underlying PTSD with the aim of paving the way to developing novel or improved treatment approaches and drugs to treat PTSD. One of the major scientific tools used to gain insight into understanding physiological and neuronal mechanisms underlying diseases and for treatment development is the use of animal models of human diseases. While much progress has been made using these models in understanding mechanisms of conditioned fear and fear memory, the gained knowledge has not yet led to better treatment options for PTSD patients. This poor translational outcome has already led some scientists and pharmaceutical companies, who do not in general hold opinions against animal models, to propose that those models should be abandoned. Here, we critically examine aspects of animal models of PTSD that may have contributed to the relative lack of translatability, including the focus on the exposure to trauma, overlooking individual and sex differences, and the contribution of risk factors. Based on findings from recent years, we propose research-based modifications that we believe are required in order to overcome some of the shortcomings of previous practice. These modifications include the usage of animal models of PTSD which incorporate risk factors and of the behavioral profiling analysis of individuals in a sample. These modifications are aimed to address factors such as individual predisposition and resilience, thus taking into consideration the fact that only a fraction of individuals exposed to trauma develop PTSD. We suggest that with an appropriate shift of practice, animal models are not only a valuable tool to enhance our understanding of fear and memory processes, but could serve as effective platforms for understanding PTSD, for PTSD drug development and drug testing.

Enriched expression of genes associated with autism spectrum disorders in human inhibitory neurons

Autism spectrum disorder (ASD) is highly heritable but genetically heterogeneous. The affected neural circuits and cell types remain unclear and may vary at different developmental stages. By analyzing multiple sets of human single cell transcriptome profiles, we found that ASD candidates showed relatively enriched gene expression in neurons, especially in inhibitory neurons. ASD candidates were also more likely to be the hubs of the co-expression gene module that is highly expressed in inhibitory neurons, a feature not detected for excitatory neurons. In addition, we found that upregulated genes in multiple ASD cortex samples were enriched with genes highly expressed in inhibitory neurons, suggesting a potential increase of inhibitory neurons and an imbalance in the ratio between excitatory and inhibitory neurons in ASD brains. Furthermore, the downstream targets of several ASD candidates, such as CHD8, EHMT1 and SATB2, also displayed enriched expression in inhibitory neurons. Taken together, our analyses of single cell transcriptomic data suggest that inhibitory neurons may be a major neuron subtype affected by the disruption of ASD gene networks, providing single cell functional evidence to support the excitatory/inhibitory (E/I) imbalance hypothesis.