Single-cell genomics identifies cell type-specific molecular changes in autism

Towards understanding sex differences in autism spectrum disorders

Autism Spectrum Disorder (ASD) is a neurodevelopmental condition characterized by social deficits, repetitive behaviours and lack of empathy. Its significant genetic heritability and potential comorbidities often lead to diagnostic and therapeutic challenges. This review addresses the biological basis of ASD, focusing on the sex differences in gene expression and hormonal influences. ASD is more commonly diagnosed in males at a ratio of 4:1, indicating a potential oversight in female-specific ASD research and a risk of underdiagnosis in females. We consider how ASD manifests differently across sexes by exploring differential gene expression in female and male brains and consider how variations in steroid hormones influence ASD characteristics. Synaptic function, including excitation/inhibition ratio imbalance, is influenced by gene mutations and this is explored as a key factor in the cognitive and behavioural manifestations of ASD. We also discuss the role of micro RNAs (miRNAs) and highlight a novel mutation in miRNA-873, which affects a suite of key synaptic genes, neurexin, neuroligin, SHANK and post-synaptic density proteins, implicated in the pathology of ASD. Our review suggests that genetic predisposition, sex differences in brain gene expression, and hormonal factors significantly contribute to the presentation, identification and severity of ASD, necessitating sex-specific considerations in diagnosis and treatments. These findings advocate for personalized interventions to improve the outcomes for individuals with ASD.

Propionic acid affects the synaptic architecture of rat hippocampus and prefrontal cortex

It is well documented that propionic acid (PPA) produces behavioral, morphological, molecular and immune responses in rats that are characteristic of autism spectrum disorder in humans. However, whether PPA affects the ultrastructure and synaptic architecture of regions of autistic brain has not been adequately addressed. Earlier we show that single intraperitoneal (IP) injection of PPA (175 mg/kg) produces superficial changes in the spatial memory and learning of adolescent male Wistar rats. However, in neurons, synapses and glial cells of hippocampal CA1 area and medial prefrontal cortex transient (mainly) or enduring alterations were detected. In this study, we used electron microscopic morphometric analysis to test the effect of PPA on different structural parameters of axodendritic synapses of the hippocampus and prefrontal cortex. The animals were treated with a single IP injection of PPA (175 mg/kg). The length and width of synaptic active zone, the area of presynaptic and postsynaptic mitochondria, the distance between presynaptic mitochondria and the synapse active zone, the distance between postsynaptic mitochondria and postsynaptic density and the depth and opening diameter of neuronal porosome complex were evaluated. Our results show that synaptic mitochondria of the hippocampus and prefrontal cortex are the most vulnerable to PPA treatment: in both regions, the area of postsynaptic mitochondria were increased. In general, our results show that even small dose of PPA, which produces only superficial effects on spatial memory and learning is able to alter the synapse architecture in brain regions involved in cognition and autism pathogenesis. Therefore, the microbiome may be involved in the control of neurotransmission in these regions.

Altered projection-specific synaptic remodeling and its modification by oxytocin in an idiopathic autism marmoset model

Alterations in the experience-dependent and autonomous elaboration of neural circuits are assumed to underlie autism spectrum disorder (ASD), though it is unclear what synaptic traits are responsible. Here, utilizing a valproic acid-induced ASD marmoset model, which shares common molecular features with idiopathic ASD, we investigate changes in the structural dynamics of tuft dendrites of upper-layer pyramidal neurons and adjacent axons in the dorsomedial prefrontal cortex through two-photon microscopy. In model marmosets, dendritic spine turnover is upregulated, and spines are generated in clusters and survived more often than in control marmosets. Presynaptic boutons in local axons, but not in commissural long-range axons, demonstrate hyperdynamic turnover in model marmosets, suggesting alterations in projection-specific plasticity. Intriguingly, nasal oxytocin administration attenuates clustered spine emergence in model marmosets. Enhanced clustered spine generation, possibly unique to certain presynaptic partners, may be associated with ASD and be a potential therapeutic target.

Single-cell multi-cohort dissection of the schizophrenia transcriptome

The complexity and heterogeneity of schizophrenia have hindered mechanistic elucidation and the development of more effective therapies. Here, we performed single-cell dissection of schizophrenia-associated transcriptomic changes in the human prefrontal cortex across 140 individuals in two independent cohorts. Excitatory neurons were the most affected cell group, with transcriptional changes converging on neurodevelopment and synapse-related molecular pathways. Transcriptional alterations included known genetic risk factors, suggesting convergence of rare and common genomic variants on neuronal population-specific alterations in schizophrenia. Based on the magnitude of schizophrenia-associated transcriptional change, we identified two populations of individuals with schizophrenia marked by expression of specific excitatory and inhibitory neuronal cell states. This single-cell atlas links transcriptomic changes to etiological genetic risk factors, contextualizing established knowledge within the human cortical cytoarchitecture and facilitating mechanistic understanding of schizophrenia pathophysiology and heterogeneity.

Single-cell genomics and regulatory networks for 388 human brains

Single-cell genomics is a powerful tool for studying heterogeneous tissues such as the brain. Yet little is understood about how genetic variants influence cell-level gene expression. Addressing this, we uniformly processed single-nuclei, multiomics datasets into a resource comprising >2.8 million nuclei from the prefrontal cortex across 388 individuals. For 28 cell types, we assessed population-level variation in expression and chromatin across gene families and drug targets. We identified >550,000 cell type-specific regulatory elements and >1.4 million single-cell expression quantitative trait loci, which we used to build cell-type regulatory and cell-to-cell communication networks. These networks manifest cellular changes in aging and neuropsychiatric disorders. We further constructed an integrative model accurately imputing single-cell expression and simulating perturbations; the model prioritized ~250 disease-risk genes and drug targets with associated cell types.

A data-driven single-cell and spatial transcriptomic map of the human prefrontal cortex

The molecular organization of the human neocortex historically has been studied in the context of its histological layers. However, emerging spatial transcriptomic technologies have enabled unbiased identification of transcriptionally defined spatial domains that move beyond classic cytoarchitecture. We used the Visium spatial gene expression platform to generate a data-driven molecular neuroanatomical atlas across the anterior-posterior axis of the human dorsolateral prefrontal cortex. Integration with paired single-nucleus RNA-sequencing data revealed distinct cell type compositions and cell-cell interactions across spatial domains. Using PsychENCODE and publicly available data, we mapped the enrichment of cell types and genes associated with neuropsychiatric disorders to discrete spatial domains.

Hippocampal astrocytes induce sex-dimorphic effects on memory

Astrocytic receptors influence cognitive function and can promote behavioral deficits in disease. These effects may vary based on variables such as biological sex, but it is not known if the effects of astrocytic receptors are dependent on sex. We leveraged in vivo gene editing and chemogenetics to examine the roles of astrocytic receptors in spatial memory and other processes. We show that reductions in metabotropic glutamate receptor 3 (mGluR3), the main astrocytic glutamate receptor in adults, impair memory in females but enhance memory in males. Similarly, increases in astrocytic mGluR3 levels have sex-dependent effects and enhance memory in females. mGluR3 manipulations also alter spatial search strategies during recall in a sex-specific manner. In addition, acute chemogenetic stimulation of Gi/o-coupled or Gs-coupled receptors in hippocampal astrocytes induces bidirectional and sex-dimorphic effects on memory. Thus, astrocytes are sex-dependent modulators of cognitive function and may promote sex differences in aging and disease.

Molecular cascades and cell type-specific signatures in ASD revealed by single-cell genomics

Genomic profiling in postmortem brain from autistic individuals has consistently revealed convergent molecular changes. What drives these changes and how they relate to genetic susceptibility in this complex condition are not well understood. We performed deep single-nucleus RNA sequencing (snRNA-seq) to examine cell composition and transcriptomics, identifying dysregulation of cell type-specific gene regulatory networks (GRNs) in autism spectrum disorder (ASD), which we corroborated using single-nucleus assay for transposase-accessible chromatin with sequencing (snATAC-seq) and spatial transcriptomics. Transcriptomic changes were primarily cell type specific, involving multiple cell types, most prominently interhemispheric and callosal-projecting neurons, interneurons within superficial laminae, and distinct glial reactive states involving oligodendrocytes, microglia, and astrocytes. Autism-associated GRN drivers and their targets were enriched in rare and common genetic risk variants, connecting autism genetic susceptibility and cellular and circuit alterations in the human brain.

Integrating single cell expression quantitative trait loci summary statistics to understand complex trait risk genes

Transcriptome-wide association study (TWAS) is a popular approach to dissect the functional consequence of disease associated non-coding variants. Most existing TWAS use bulk tissues and may not have the resolution to reveal cell-type specific target genes. Single-cell expression quantitative trait loci (sc-eQTL) datasets are emerging. The largest bulk- and sc-eQTL datasets are most conveniently available as summary statistics, but have not been broadly utilized in TWAS. Here, we present a new method EXPRESSO (EXpression PREdiction with Summary Statistics Only), to analyze sc-eQTL summary statistics, which also integrates 3D genomic data and epigenomic annotation to prioritize causal variants. EXPRESSO substantially improves existing methods. We apply EXPRESSO to analyze multi-ancestry GWAS datasets for 14 autoimmune diseases. EXPRESSO uniquely identifies 958 novel gene x trait associations, which is 26% more than the second-best method. Among them, 492 are unique to cell type level analysis and missed by TWAS using whole blood. We also develop a cell type aware drug repurposing pipeline, which leverages EXPRESSO results to identify drug compounds that can reverse disease gene expressions in relevant cell types. Our results point to multiple drugs with therapeutic potentials, including metformin for type 1 diabetes, and vitamin K for ulcerative colitis.

Juvenile peripheral LPS exposure overrides female resilience to prenatal VPA effects on adult sociability in mice

Autism spectrum disorder (ASD) exhibits a gender bias, with boys more frequently affected than girls. Similarly, in mouse models induced by prenatal exposure to valproic acid (VPA), males typically display reduced sociability, while females are less affected. Although both males and females exhibit VPA effects on neuroinflammatory parameters, these effects are sex-specific. Notably, females exposed to VPA show increased microglia and astrocyte density during the juvenile period. We hypothesized that these distinct neuroinflammatory patterns contribute to the resilience of females to VPA. To investigate this hypothesis, we treated juvenile animals with intraperitoneal bacterial lipopolysaccharides (LPS), a treatment known to elicit brain neuroinflammation. We thus evaluated the impact of juvenile LPS-induced inflammation on adult sociability and neuroinflammation in female mice prenatally exposed to VPA. Our results demonstrate that VPA-LPS females exhibit social deficits in adulthood, overriding the resilience observed in VPA-saline littermates. Repetitive behavior and anxiety levels were not affected by either treatment. We also evaluated whether the effect on sociability was accompanied by heightened neuroinflammation in the cerebellum and hippocampus. Surprisingly, we observed reduced astrocyte and microglia density in the cerebellum of VPA-LPS animals. These findings shed light on the complex interactions between prenatal insults, juvenile inflammatory stimuli, and sex-specific vulnerability in ASD-related social deficits, providing insights into potential therapeutic interventions for ASD.

Mutant IDH inhibitors induce lineage differentiation in IDH-mutant oligodendroglioma

A subset of patients with IDH-mutant glioma respond to inhibitors of mutant IDH (IDHi), yet the molecular underpinnings of such responses are not understood. Here, we profiled by single-cell or single-nucleus RNA-sequencing three IDH-mutant oligodendrogliomas from patients who derived clinical benefit from IDHi. Importantly, the tissues were sampled on-drug, four weeks from treatment initiation. We further integrate our findings with analysis of single-cell and bulk transcriptomes from independent cohorts and experimental models. We find that IDHi treatment induces a robust differentiation toward the astrocytic lineage, accompanied by a depletion of stem-like cells and a reduction of cell proliferation. Furthermore, mutations in NOTCH1 are associated with decreased astrocytic differentiation and may limit the response to IDHi. Our study highlights the differentiating potential of IDHi on the cellular hierarchies that drive oligodendrogliomas and suggests a genetic modifier that may improve patient stratification.

Association of intestinal anti-inflammatory drug target genes with psychiatric Disorders: A Mendelian randomization study

INTRODUCTION

Psychiatric disorders present a substantial global public health burden with limited drug options. The gut-brain axis connects inflammatory bowel diseases and psychiatric disorders, which often have comorbidities. While some evidence hints at anti-inflammatory drugs aiding in treating psychiatric conditions, the specific effects of intestinal anti-inflammatory drugs remain unclear.

OBJECTIVES

This study investigates the causal effect of intestinal anti-inflammatory drug targets on psychiatric disorders. We hypothesize that these drug targets may offer new insights into the treatment and prevention of such disorders. Additionally, we explore gut microbiota's mediating role between drug target genes and psychiatric disorders.

METHODS

We performed two-sample Mendelian randomization (MR) using summary data from existing expression quantitative trait loci (eQTL) and protein QTL in the brain, along with public genome-wide association studies of disease. We also explored gut microbiota's mediating effect. The statistics encompassed six psychiatric disorders involving 9,725-500,199 individuals. Colocalization analysis enhanced the MR evidence.

RESULTS

We uncovered a causal link between TPMT (a target of olsalazine) expression in the amygdala and bipolar disorder (BD) risk (odds ratio [OR] = 1.08; P = 4.29 × 10-4). This association was observed even when the sigmoid colon and whole blood eQTL were considered as exposures. Colocalization analysis revealed a shared genetic variant (rs11751561) between TPMT expression and BD, with a posterior probability of 61.6 %. Interestingly, this causal effect was influenced by a decrease in the gut microbiota abundance of the genus Roseburia (effect proportion = 10.05 %). Moreover, elevated ACAT1 expression was associated with higher obsessive-compulsive disorder risk (OR = 1.62; P = 3.64 × 10-4; posterior probability = 3.1 %).

CONCLUSION

These findings provide novel targets for the treatment of psychiatric disorders, underscore the potential of repurposing olsalazine, and emphasize the importance of TPMT and ACAT1 in future drug development.

Integrative spatial analysis reveals a multi-layered organization of glioblastoma

Glioma contains malignant cells in diverse states. Here, we combine spatial transcriptomics, spatial proteomics, and computational approaches to define glioma cellular states and uncover their organization. We find three prominent modes of organization. First, gliomas are composed of small local environments, each typically enriched with one major cellular state. Second, specific pairs of states preferentially reside in proximity across multiple scales. This pairing of states is consistent across tumors. Third, these pairwise interactions collectively define a global architecture composed of five layers. Hypoxia appears to drive the layers, as it is associated with a long-range organization that includes all cancer cell states. Accordingly, tumor regions distant from any hypoxic/necrotic foci and tumors that lack hypoxia such as low-grade IDH-mutant glioma are less organized. In summary, we provide a conceptual framework for the organization of cellular states in glioma, highlighting hypoxia as a long-range tissue organizer.

Microglial Dysfunction in Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a highly heterogeneous neurodevelopmental disorder with onset in childhood. The molecular mechanisms underlying ASD have not yet been elucidated completely. Evidence has emerged to support a link between microglial dysfunction and the etiology of ASD. This review summarizes current research on microglial dysfunction in neuroinflammation and synaptic pruning, which are associated with altered transcriptomes and autophagy in ASD. Dysbiosis of gut microbiota in ASD and its correlation with microglial dysfunction are also addressed.

Characterizing cell type specific transcriptional differences between the living and postmortem human brain

Single-nucleus RNA sequencing (snRNA-seq) is often used to define gene expression patterns characteristic of brain cell types as well as to identify cell type specific gene expression signatures of neurological and mental illnesses in postmortem human brains. As methods to obtain brain tissue from living individuals emerge, it is essential to characterize gene expression differences associated with tissue originating from either living or postmortem subjects using snRNA-seq, and to assess whether and how such differences may impact snRNA-seq studies of brain tissue. To address this, human prefrontal cortex single nuclei gene expression was generated and compared between 31 samples from living individuals and 21 postmortem samples. The same cell types were consistently identified in living and postmortem nuclei, though for each cell type, a large proportion of genes were differentially expressed between samples from postmortem and living individuals. Notably, estimation of cell type proportions by cell type deconvolution of pseudo-bulk data was found to be more accurate in samples from living individuals. To allow for future integration of living and postmortem brain gene expression, a model was developed that quantifies from gene expression data the probability a human brain tissue sample was obtained postmortem. These probabilities are established as a means to statistically account for the gene expression differences between samples from living and postmortem individuals. Together, the results presented here provide a deep characterization of both differences between snRNA-seq derived from samples from living and postmortem individuals, as well as qualify and account for their effect on common analyses performed on this type of data.

Loss of Katnal2 leads to ependymal ciliary hyperfunction and autism-related phenotypes in mice

Autism spectrum disorders (ASD) frequently accompany macrocephaly, which often involves hydrocephalic enlargement of brain ventricles. Katnal2 is a microtubule-regulatory protein strongly linked to ASD, but it remains unclear whether Katnal2 knockout (KO) in mice leads to microtubule- and ASD-related molecular, synaptic, brain, and behavioral phenotypes. We found that Katnal2-KO mice display ASD-like social communication deficits and age-dependent progressive ventricular enlargements. The latter involves increased length and beating frequency of motile cilia on ependymal cells lining ventricles. Katnal2-KO hippocampal neurons surrounded by enlarged lateral ventricles show progressive synaptic deficits that correlate with ASD-like transcriptomic changes involving synaptic gene down-regulation. Importantly, early postnatal Katnal2 re-expression prevents ciliary, ventricular, and behavioral phenotypes in Katnal2-KO adults, suggesting a causal relationship and a potential treatment. Therefore, Katnal2 negatively regulates ependymal ciliary function and its deletion in mice leads to ependymal ciliary hyperfunction and hydrocephalus accompanying ASD-related behavioral, synaptic, and transcriptomic changes.

Single-Nucleus Transcriptome Profiling from the Hippocampus of a PTSD Mouse Model and CBD-Treated Cohorts

Post-traumatic stress disorder (PTSD) is the most common psychiatric disorder after a catastrophic event; however, the efficacious treatment options remain insufficient. Increasing evidence suggests that cannabidiol (CBD) exhibits optimal therapeutic effects for treating PTSD. To elucidate the cell-type-specific transcriptomic pathology of PTSD and the mechanisms of CBD against this disease, we conducted single-nucleus RNA sequencing (snRNA-seq) in the hippocampus of PTSD-modeled mice and CBD-treated cohorts. We constructed a mouse model by adding electric foot shocks following exposure to single prolonged stress (SPS+S) and tested the freezing time, anxiety-like behavior, and cognitive behavior. CBD was administrated before every behavioral test. The PTSD-modeled mice displayed behaviors resembling those of PTSD in all behavioral tests, and CBD treatment alleviated all of these PTSD-like behaviors (n = 8/group). Three mice with representative behavioral phenotypes were selected from each group for snRNA-seq 15 days after the SPS+S. We primarily focused on the excitatory neurons (ExNs) and inhibitory neurons (InNs), which accounted for 68.4% of the total cell annotations. A total of 88 differentially upregulated genes and 305 differentially downregulated genes were found in the PTSD mice, which were found to exhibit significant alterations in pathways and biological processes associated with fear response, synaptic communication, protein synthesis, oxidative phosphorylation, and oxidative stress response. A total of 63 overlapping genes in InNs were identified as key genes for CBD in the treatment of PTSD. Subsequent Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses revealed that the anti-PTSD effect of CBD was related to the regulation of protein synthesis, oxidative phosphorylation, oxidative stress response, and fear response. Furthermore, gene set enrichment analysis (GSEA) revealed that CBD also enhanced retrograde endocannabinoid signaling in ExNs, which was found to be suppressed in the PTSD group. Our research may provide a potential explanation for the pathogenesis of PTSD and facilitate the discovery of novel therapeutic targets for drug development. Moreover, it may shed light on the therapeutic mechanisms of CBD.

Precision and Accuracy of Single-Cell/Nuclei RNA Sequencing Data

Single-cell/nuclei RNA sequencing (sc/snRNA-Seq) is widely used for profiling cell-type gene expressions in biomedical research. An important but underappreciated issue is the quality of sc/snRNA-Seq data that would impact the reliability of downstream analyses. Here we evaluated the precision and accuracy in 18 sc/snRNA-Seq datasets. The precision was assessed on data from human brain studies with a total of 3,483,905 cells from 297 individuals, by utilizing technical replicates. The accuracy was evaluated with sample-matched scRNA-Seq and pooled-cell RNA-Seq data of cultured mononuclear phagocytes from four species. The results revealed low precision and accuracy at the single-cell level across all evaluated data. Cell number and RNA quality were highlighted as two key factors determining the expression precision, accuracy, and reproducibility of differential expression analysis in sc/snRNA-Seq. This study underscores the necessity of sequencing enough high-quality cells per cell type per individual, preferably in the hundreds, to mitigate noise in expression quantification.

Zmiz1 is a novel regulator of brain development associated with autism and intellectual disability

Neurodevelopmental disorders (NDDs) are a class of pathologies arising from perturbations in brain circuit formation and maturation with complex etiological triggers often classified as environmental and genetic. Neuropsychiatric conditions such as autism spectrum disorders (ASD), intellectual disability (ID), and attention deficit hyperactivity disorders (ADHD) are common NDDs characterized by their hereditary underpinnings and inherent heterogeneity. Genetic risk factors for NDDs are increasingly being identified in non-coding regions and proteins bound to them, including transcriptional regulators and chromatin remodelers. Importantly, de novo mutations are emerging as important contributors to NDDs and neuropsychiatric disorders. Recently, de novo mutations in transcriptional co-factor Zmiz1 or its regulatory regions have been identified in unrelated patients with syndromic ID and ASD. However, the role of Zmiz1 in brain development is unknown. Here, using publicly available databases and a Zmiz1 mutant mouse model, we reveal that Zmiz1 is highly expressed during embryonic brain development in mice and humans, and though broadly expressed across the brain, Zmiz1 is enriched in areas prominently impacted in ID and ASD such as cortex, hippocampus, and cerebellum. We investigated the relationship between Zmiz1 structure and pathogenicity of protein variants, the epigenetic marks associated with Zmiz1 regulation, and protein interactions and signaling pathways regulated by Zmiz1. Our analysis reveals that Zmiz1 regulates multiple developmental processes, including neurogenesis, neuron connectivity, and synaptic signaling. This work paves the way for future studies on the functions of Zmiz1 and highlights the importance of combining analysis of mouse models and human data.

Menin Deficiency Induces Autism-Like Behaviors by Regulating Foxg1 Transcription and Participates in Foxg1-Related Encephalopathy

FOXG1 syndrome is a developmental encephalopathy caused by FOXG1 (Forkhead box G1) mutations, resulting in high phenotypic variability. However, the upstream transcriptional regulation of Foxg1 expression remains unclear. This report demonstrates that both deficiency and overexpression of Men1 (protein: menin, a pathogenic gene of MEN1 syndrome known as multiple endocrine neoplasia type 1) lead to autism-like behaviors, such as social defects, increased repetitive behaviors, and cognitive impairments. Multifaceted transcriptome analyses revealed that Foxg1 signaling is predominantly altered in Men1 deficiency mice, through its regulation of the Alpha Thalassemia/Mental Retardation Syndrome X-Linked (Atrx) factor. Atrx recruits menin to bind to the transcriptional start region of Foxg1 and mediates the regulation of Foxg1 expression by H3K4me3 (Trimethylation of histone H3 lysine 4) modification. The deficits observed in menin deficient mice are rescued by the over-expression of Foxg1, leading to normalized spine growth and restoration of hippocampal synaptic plasticity. These findings suggest that menin may have a putative role in the maintenance of Foxg1 expression, highlighting menin signaling as a potential therapeutic target for Foxg1-related encephalopathy.

Multimodal Nature of the Single-cell Primate Brain Atlas: Morphology, Transcriptome, Electrophysiology, and Connectivity

Primates exhibit complex brain structures that augment cognitive function. The neocortex fulfills high-cognitive functions through billions of connected neurons. These neurons have distinct transcriptomic, morphological, and electrophysiological properties, and their connectivity principles vary. These features endow the primate brain atlas with a multimodal nature. The recent integration of next-generation sequencing with modified patch-clamp techniques is revolutionizing the way to census the primate neocortex, enabling a multimodal neuronal atlas to be established in great detail: (1) single-cell/single-nucleus RNA-seq technology establishes high-throughput transcriptomic references, covering all major transcriptomic cell types; (2) patch-seq links the morphological and electrophysiological features to the transcriptomic reference; (3) multicell patch-clamp delineates the principles of local connectivity. Here, we review the applications of these technologies in the primate neocortex and discuss the current advances and tentative gaps for a comprehensive understanding of the primate neocortex.

Central neurocytoma exhibits radial glial cell signatures with FGFR3 hypomethylation and overexpression

We explored the genomic events underlying central neurocytoma (CN), a rare neoplasm of the central nervous system, via multiomics approaches, including whole-exome sequencing, bulk and single-nuclei RNA sequencing, and methylation sequencing. We identified FGFR3 hypomethylation leading to FGFR3 overexpression as a major event in the ontogeny of CN that affects crucial downstream events, such as aberrant PI3K-AKT activity and neuronal development pathways. Furthermore, we found similarities between CN and radial glial cells based on analyses of gene markers and CN tumor cells and postulate that CN tumorigenesis is due to dysregulation of radial glial cell differentiation into neurons. Our data demonstrate the potential role of FGFR3 as one of the leading drivers of tumorigenesis in CN.

Molecular mechanism analyses of post-traumatic epilepsy and hereditary epilepsy based on 10× single-cell transcriptome sequencing technology

BACKGROUND

Single-cell RNA sequencing analysis has been usually conducted on post-traumatic epilepsy (PET) and hereditary epilepsy (HE) patients; however, the transcriptome of patients with traumatic temporal lobe epilepsy has rarely been studied.

MATERIALS AND METHODS

Hippocampus tissues isolated from one patient with PTE and one patient with HE were used in the present study. Single cell isolates were prepared and captured using a 10× Genomics Chromium Single-Cell 3' kit (V3) according to the manufacturer's instructions. The libraries were sequenced on an Illumina NovaSeq 6000 sequencing system. Raw data were processed, and the cells were filtered and classified using the Seurat R package. Uniform Manifold Approximation and Projection was used for visualization. Differentially expressed genes (DEGs) were identified based on a p-value ≤0.01 and log fold change (FC) ≥0.25. Gene Ontology (GO, http://geneontology.org/) and KEGG (Kyoto Encyclopedia of Genes and Genomes, www.genome.jp/kegg) analyses were performed on the DEGs for enrichment analysis.

RESULTS

The reads obtained from the 10× genomic platform for PTE and HE were 39.56 M and 30.08 M, respectively. The Q30 score of the RNA reads was >91.6%. After filtering, 7479 PTE cells and 9357 HE cells remained for further study. More than 96.4% of the reads were mapped to GRCh38/GRCm38. The cells were differentially distributed in two groups, with higher numbers of oligodendrocytes (6522 vs. 2532) and astrocytes (133 vs. 52), and lower numbers of microglial cells (2242 vs. 3811), and neurons (3 vs. 203) present in the HE group than in the PTE group. The DEGs in four cell clusters were identified, with 25 being in oligodendrocytes (13 upregulated and 12 downregulated), 87 in microglia cells (42 upregulated and 45 downregulated), 222 in astrocytes (115 upregulated and 107 downregulated), and 393 in neurons (305 upregulated and 88 downregulated). The genes MTND1P23 (downregulated), XIST (downregulated), and RPS4Y1 (upregulated) were commonly expressed in all four cell clusters. The DEGs in microglial cells and astrocytes were enriched in the IL-17 signaling pathway.

CONCLUSION

Our study explored differences in cells found in a patient with PE compared to a patient with HE, and the transcriptome in the different cells was analyzed for the first time. Studying inflammatory and immune functions might be the best approach for investigating traumatic temporal lobe epilepsy in neurons.

Ranking of cell clusters in a single-cell RNA-sequencing analysis framework using prior knowledge

Prioritization or ranking of different cell types in a single-cell RNA sequencing (scRNA-seq) framework can be performed in a variety of ways, some of these include: i) obtaining an indication of the proportion of cell types between the different conditions under study, ii) counting the number of differentially expressed genes (DEGs) between cell types and conditions in the experiment or, iii) prioritizing cell types based on prior knowledge about the conditions under study (i.e., a specific disease). These methods have drawbacks and limitations thus novel methods for improving cell ranking are required. Here we present a novel methodology that exploits prior knowledge in combination with expert-user information to accentuate cell types from a scRNA-seq analysis that yield the most biologically meaningful results with respect to a disease under study. Our methodology allows for ranking and prioritization of cell types based on how well their expression profiles relate to the molecular mechanisms and drugs associated with a disease. Molecular mechanisms, as well as drugs, are incorporated as prior knowledge in a standardized, structured manner. Cell types are then ranked/prioritized based on how well results from data-driven analysis of scRNA-seq data match the predefined prior knowledge. In additional cell-cell communication perturbations between disease and control networks are used to further prioritize/rank cell types. Our methodology has substantial advantages to more traditional cell ranking techniques and provides an informative complementary methodology that utilizes prior knowledge in a rapid and automated manner, that has previously not been attempted by other studies. The current methodology is also implemented as an R package entitled Single Cell Ranking Analysis Toolkit (scRANK) and is available for download and installation via GitHub (https://github.com/aoulas/scRANK).

Single-cell genomics and regulatory networks for 388 human brains

Single-cell genomics is a powerful tool for studying heterogeneous tissues such as the brain. Yet, little is understood about how genetic variants influence cell-level gene expression. Addressing this, we uniformly processed single-nuclei, multi-omics datasets into a resource comprising >2.8M nuclei from the prefrontal cortex across 388 individuals. For 28 cell types, we assessed population-level variation in expression and chromatin across gene families and drug targets. We identified >550K cell-type-specific regulatory elements and >1.4M single-cell expression-quantitative-trait loci, which we used to build cell-type regulatory and cell-to-cell communication networks. These networks manifest cellular changes in aging and neuropsychiatric disorders. We further constructed an integrative model accurately imputing single-cell expression and simulating perturbations; the model prioritized ~250 disease-risk genes and drug targets with associated cell types.

The Association of Redox Regulatory Drug Target Genes with Psychiatric Disorders: A Mendelian Randomization Study

Redox regulatory drug (RRD) targets may be considered potential novel drug targets of psychosis due to the fact that the brain is highly susceptible to oxidative stress imbalance. The aim of the present study is to identify potential associations between RRD targets' perturbation and the risk of psychoses; to achieve this, Mendelian randomization analyses were conducted. The expression quantitative trait loci (eQTL) and protein QTL data were used to derive the genetic instrumental variables. We obtained the latest summary data of genome-wide association studies on seven psychoses as outcomes, including schizophrenia (SCZ), bipolar disorder (BD), major depressive disorder (MDD), attention-deficit/hyperactivity disorder, autism, obsessive-compulsive disorder and anorexia nervosa. In total, 95 unique targets were included in the eQTL panel, and 48 targets in the pQTL one. Genetic variations in the vitamin C target (OGFOD2, OR = 0.784, p = 2.14 × 10-7) and melatonin target (RORB, OR = 1.263, p = 8.80 × 10-9) were significantly related to the risk of SCZ. Genetic variation in the vitamin E (PRKCB, OR = 0.248, p = 1.24 × 10-5) target was related to an increased risk of BD. Genetic variation in the vitamin C target (P4HTM: cerebellum, OR = 1.071, p = 4.64 × 10-7; cerebellar hemisphere, OR = 1.092, p = 1.98 × 10-6) was related to an increased risk of MDD. Cognitive function mediated the effects on causal associations. In conclusion, this study provides supportive evidence for a causal association between RRD targets and risk of SCZ, BD or MDD, which were partially mediated by cognition.

scNovel: a scalable deep learning-based network for novel rare cell discovery in single-cell transcriptomics

Single-cell RNA sequencing has achieved massive success in biological research fields. Discovering novel cell types from single-cell transcriptomics has been demonstrated to be essential in the field of biomedicine, yet is time-consuming and needs prior knowledge. With the unprecedented boom in cell atlases, auto-annotation tools have become more prevalent due to their speed, accuracy and user-friendly features. However, existing tools have mostly focused on general cell-type annotation and have not adequately addressed the challenge of discovering novel rare cell types. In this work, we introduce scNovel, a powerful deep learning-based neural network that specifically focuses on novel rare cell discovery. By testing our model on diverse datasets with different scales, protocols and degrees of imbalance, we demonstrate that scNovel significantly outperforms previous state-of-the-art novel cell detection models, reaching the most AUROC performance(the only one method whose averaged AUROC results are above 94%, up to 16.26% more comparing to the second-best method). We validate scNovel's performance on a million-scale dataset to illustrate the scalability of scNovel further. Applying scNovel on a clinical COVID-19 dataset, three potential novel subtypes of Macrophages are identified, where the COVID-related differential genes are also detected to have consistent expression patterns through deeper analysis. We believe that our proposed pipeline will be an important tool for high-throughput clinical data in a wide range of applications.

Maternal dietary fat during lactation shapes single nucleus transcriptomic profile of postnatal offspring hypothalamus in a sexually dimorphic manner in mice

Maternal overnutrition during lactation predisposes offspring to develop metabolic diseases and exacerbates the relevant syndromes in males more than females in later life. The hypothalamus is a heterogenous brain region that regulates energy balance. Here we combined metabolic trait quantification of mother and offspring mice under low and high fat diet (HFD) feeding during lactation, with single nucleus transcriptomic profiling of their offspring hypothalamus at peak lacation to understand the cellular and molecular alterations in response to maternal dietary pertubation. We found significant expansion in neuronal subpopulations including histaminergic (Hdc), arginine vasopressin/retinoic acid receptor-related orphan receptor β (Avp/Rorb) and agouti-related peptide/neuropeptide Y (AgRP/Npy) in male offspring when their mothers were fed HFD, and increased Npy-astrocyte interactions in offspring responding to maternal overnutrition. Our study provides a comprehensive offspring hypothalamus map at the peak lactation and reveals how the cellular subpopulations respond to maternal dietary fat in a sex-specific manner during development.

eSVD-DE: cohort-wide differential expression in single-cell RNA-seq data using exponential-family embeddings

BACKGROUND

Single-cell RNA-sequencing (scRNA) datasets are becoming increasingly popular in clinical and cohort studies, but there is a lack of methods to investigate differentially expressed (DE) genes among such datasets with numerous individuals. While numerous methods exist to find DE genes for scRNA data from limited individuals, differential-expression testing for large cohorts of case and control individuals using scRNA data poses unique challenges due to substantial effects of human variation, i.e., individual-level confounding covariates that are difficult to account for in the presence of sparsely-observed genes.

RESULTS

We develop the eSVD-DE, a matrix factorization that pools information across genes and removes confounding covariate effects, followed by a novel two-sample test in mean expression between case and control individuals. In general, differential testing after dimension reduction yields an inflation of Type-1 errors. However, we overcome this by testing for differences between the case and control individuals' posterior mean distributions via a hierarchical model. In previously published datasets of various biological systems, eSVD-DE has more accuracy and power compared to other DE methods typically repurposed for analyzing cohort-wide differential expression.

CONCLUSIONS

eSVD-DE proposes a novel and powerful way to test for DE genes among cohorts after performing a dimension reduction. Accurate identification of differential expression on the individual level, instead of the cell level, is important for linking scRNA-seq studies to our understanding of the human population.

CD8+ T cell infiltration and proliferation in the brainstem during experimental cerebral malaria

INTRODUCTION

Cerebral malaria (CM) is a lethal neuroinflammatory disease caused by Plasmodium infection. Immune cells and brain parenchyma cells contribute to the pathogenesis of CM. However, a systematic examination of the changes that occur in the brain parenchyma region during CM at the single-cell resolution is still poorly studied.

AIMS

To explore cell composition and CD8+ T cell infiltration, single-cell RNA sequencing (scRNA-seq) was performed on the brainstems of healthy and experimental cerebral malaria (ECM) mice. Then CD8+ T cell infiltration was confirmed by flow cytometry and immunofluorescence assays. Subsequently, the characteristics of the brain-infiltrated CD8+ T cells were analyzed. Finally, the interactions between parenchyma cells and brain-infiltrated CD8+ T cells were studied with an astrocytes-CD8+ T cell cocultured model.

RESULTS

The brainstem is the most severely damaged site during ECM. ScRNA-seq revealed a large number of CD8+ T cells infiltrating into the brainstem in ECM mice. Brain-infiltrated CD8+ T cells were highly activated according to scRNA-seq, immunofluorescence, and flow cytometry assays. Further analysis found a subset of ki-67+ CD8+ T cells that have a higher transcriptional level of genes related to T cell function, activation, and proliferation, suggesting that they were exposed to specific antigens presented by brain parenchyma cells. Brain-infiltrated CD8+ T cells were the only prominent source of IFN-γ in this single-cell analysis. Astrocytes, which have a high interferon response, act as cross-presenting cells to recruit and re-activate brain-infiltrated CD8+ T cells. We also found that brain-infiltrated CD8+ T cells were highly expressed immune checkpoint molecule PD-1, while parenchyma cells showed up-regulation of PD-L1 after infection.

CONCLUSIONS

These findings reveal a novel interaction between brain-infiltrated CD8+ T cells and parenchyma cells in the ECM brainstem, suggesting that the PD-1/PD-L1 signal pathway is a promising adjunctive therapeutic strategy for ECM targeting over-activated CD8+ T cells.

Key roles of glial cells in the encephalopathy of prematurity

Across the globe, approximately one in 10 babies are born preterm, that is, before 37 weeks of a typical 40 weeks of gestation. Up to 50% of preterm born infants develop brain injury, encephalopathy of prematurity (EoP), that substantially increases their risk for developing lifelong defects in motor skills and domains of learning, memory, emotional regulation, and cognition. We are still severely limited in our abilities to prevent or predict preterm birth. No longer just the "support cells," we now clearly understand that during development glia are key for building a healthy brain. Glial dysfunction is a hallmark of EoP, notably, microgliosis, astrogliosis, and oligodendrocyte injury. Our knowledge of glial biology during development is exponentially expanding but hasn't developed sufficiently for development of effective neuroregenerative therapies. This review summarizes the current state of knowledge for the roles of glia in infants with EoP and its animal models, and a description of known glial-cell interactions in the context of EoP, such as the roles for border-associated macrophages. The field of perinatal medicine is relatively small but has worked passionately to improve our understanding of the etiology of EoP coupled with detailed mechanistic studies of pre-clinical and human cohorts. A primary finding from this review is that expanding our collaborations with computational biologists, working together to understand the complexity of glial subtypes, glial maturation, and the impacts of EoP in the short and long term will be key to the design of therapies that improve outcomes.

eSVD-DE: Cohort-wide differential expression in single-cell RNA-seq data using exponential-family embeddings

Background

Single-cell RNA-sequencing (scRNA) datasets are becoming increasingly popular in clinical and cohort studies, but there is a lack of methods to investigate differentially expressed (DE) genes among such datasets with numerous individuals. While numerous methods exist to find DE genes for scRNA data from limited individuals, differential-expression testing for large cohorts of case and control individuals using scRNA data poses unique challenges due to substantial effects of human variation, i.e., individual-level confounding covariates that are difficult to account for in the presence of sparsely-observed genes.

Results

We develop the eSVD-DE, a matrix factorization that pools information across genes and removes confounding covariate effects, followed by a novel two-sample test in mean expression between case and control individuals. In general, differential testing after dimension reduction yields an inflation of Type-1 errors. However, we overcome this by testing for differences between the case and control individuals' posterior mean distributions via a hierarchical model. In previously published datasets of various biological systems, eSVD-DE has more accuracy and power compared to other DE methods typically repurposed for analyzing cohort-wide differential expression.

Conclusions

eSVD-DE proposes a novel and powerful way to test for DE genes among cohorts after performing a dimension reduction. Accurate identification of differential expression on the individual level, instead of the cell level, is important for linking scRNA-seq studies to our understanding of the human population.

Proteomic and transcriptomic profiling of brainstem, cerebellum and olfactory tissues in early- and late-phase COVID-19

Neurological symptoms, including cognitive impairment and fatigue, can occur in both the acute infection phase of coronavirus disease 2019 (COVID-19) and at later stages, yet the mechanisms that contribute to this remain unclear. Here we profiled single-nucleus transcriptomes and proteomes of brainstem tissue from deceased individuals at various stages of COVID-19. We detected an inflammatory type I interferon response in acute COVID-19 cases, which resolves in the late disease phase. Integrating single-nucleus RNA sequencing and spatial transcriptomics, we could localize two patterns of reaction to severe systemic inflammation, one neuronal with a direct focus on cranial nerve nuclei and a separate diffuse pattern affecting the whole brainstem. The latter reflects a bystander effect of the respiratory infection that spreads throughout the vascular unit and alters the transcriptional state of mainly oligodendrocytes, microglia and astrocytes, while alterations of the brainstem nuclei could reflect the connection of the immune system and the central nervous system via, for example, the vagus nerve. Our results indicate that even without persistence of severe acute respiratory syndrome coronavirus 2 in the central nervous system, local immune reactions are prevailing, potentially causing functional disturbances that contribute to neurological complications of COVID-19.

Autism spectrum disorder: pathogenesis, biomarker, and intervention therapy

Autism spectrum disorder (ASD) has become a common neurodevelopmental disorder. The heterogeneity of ASD poses great challenges for its research and clinical translation. On the basis of reviewing the heterogeneity of ASD, this review systematically summarized the current status and progress of pathogenesis, diagnostic markers, and interventions for ASD. We provided an overview of the ASD molecular mechanisms identified by multi-omics studies and convergent mechanism in different genetic backgrounds. The comorbidities, mechanisms associated with important physiological and metabolic abnormalities (i.e., inflammation, immunity, oxidative stress, and mitochondrial dysfunction), and gut microbial disorder in ASD were reviewed. The non-targeted omics and targeting studies of diagnostic markers for ASD were also reviewed. Moreover, we summarized the progress and methods of behavioral and educational interventions, intervention methods related to technological devices, and research on medical interventions and potential drug targets. This review highlighted the application of high-throughput omics methods in ASD research and emphasized the importance of seeking homogeneity from heterogeneity and exploring the convergence of disease mechanisms, biomarkers, and intervention approaches, and proposes that taking into account individuality and commonality may be the key to achieve accurate diagnosis and treatment of ASD.

Sex-biased single-cell genetic landscape in mice with autism spectrum disorder

Autistic spectrum disorder (ASD) is a male-biased, heterogeneous neurodevelopmental disorder that affects approximately 1%-2% of the population. Prenatal exposure to valproic acid (VPA) is a recognized risk factor for ASD, but the cellular and molecular basis of VPA-induced ASD at the single-cell resolution is unclear. Here, we aim to compare the cellular and molecular differences in the hippocampus between male and female prenatal mice with ASD at the single-cell transcriptomic level. The transcriptomes of more than 45,000 cells are assigned to 12 major cell types, including neurons, glial cells, vascular cells, and immune cells. Cell type-specific genes with altered expression after prenatal VPA exposure are analyzed, and the largest number of differentially expressed genes (DEGs) are found in neurons, choroid plexus epithelial cells, and microglia. In microglia, several pathways related to inflammation are found in both males and females, including the tumor necrosis factor (TNF), nuclear factor kappa B (NF-κB), toll-like receptor (TLR), and mitogen-activated protein kinase (MAPK) signaling pathways, which are important for the induction of autistic-like behavior. Additionally, we note that several X-linked genes, including Bex1, Bex3, and Gria3, were among the male-specific DEGs of neurons. This pioneering study describes the landscape of the transcriptome in the hippocampus of autistic mice. The elucidation of sexual differences could provide innovative strategies for the prevention and treatment of ASD.

Variable expression of MECP2, CDKL5, and FMR1 in the human brain: Implications for gene restorative therapies

MECP2, CDKL5, and FMR1 are three X-linked neurodevelopmental genes associated with Rett, CDKL5-, and fragile-X syndrome, respectively. These syndromes are characterized by distinct constellations of severe cognitive and neurobehavioral anomalies, reflecting the broad but unique expression patterns of each of the genes in the brain. As these disorders are not thought to be neurodegenerative and may be reversible, a major goal has been to restore expression of the functional proteins in the patient's brain. Strategies have included gene therapy, gene editing, and selective Xi-reactivation methodologies. However, tissue penetration and overall delivery to various regions of the brain remain challenging for each strategy. Thus, gaining insights into how much restoration would be required and what regions/cell types in the brain must be targeted for meaningful physiological improvement would be valuable. As a step toward addressing these questions, here we perform a meta-analysis of single-cell transcriptomics data from the human brain across multiple developmental stages, in various brain regions, and in multiple donors. We observe a substantial degree of expression variability for MECP2, CDKL5, and FMR1 not only across cell types but also between donors. The wide range of expression may help define a therapeutic window, with the low end delineating a minimum level required to restore physiological function and the high end informing toxicology margin. Finally, the inter-cellular and inter-individual variability enable identification of co-varying genes and will facilitate future identification of biomarkers.

Granulocyte macrophage colony-stimulating factor-induced macrophages of individuals with autism spectrum disorder adversely affect neuronal dendrites through the secretion of pro-inflammatory cytokines

BACKGROUND

A growing body of evidence suggests that immune dysfunction and inflammation in the peripheral tissues as well as the central nervous system are associated with the neurodevelopmental deficits observed in autism spectrum disorder (ASD). Elevated expression of pro-inflammatory cytokines in the plasma, serum, and peripheral blood mononuclear cells of ASD has been reported. These cytokine expression levels are associated with the severity of behavioral impairments and symptoms in ASD. In a prior study, our group reported that tumor necrosis factor-α (TNF-α) expression in granulocyte-macrophage colony-stimulating factor-induced macrophages (GM-CSF MΦ) and the TNF-α expression ratio in GM-CSF MΦ/M-CSF MΦ (macrophage colony-stimulating factor-induced macrophages) was markedly higher in individuals with ASD than in typically developed (TD) individuals. However, the mechanisms of how the macrophages and the highly expressed cytokines affect neurons remain to be addressed.

METHODS

To elucidate the effect of macrophages on human neurons, we used a co-culture system of control human-induced pluripotent stem cell-derived neurons and differentiated macrophages obtained from the peripheral blood mononuclear cells of five TD individuals and five individuals with ASD. All participants were male and ethnically Japanese.

RESULTS

Our results of co-culture experiments showed that GM-CSF MΦ affect the dendritic outgrowth of neurons through the secretion of pro-inflammatory cytokines, interleukin-1α and TNF-α. Macrophages derived from individuals with ASD exerted more severe effects than those derived from TD individuals.

LIMITATIONS

The main limitations of our study were the small sample size with a gender bias toward males, the use of artificially polarized macrophages, and the inability to directly observe the interaction between neurons and macrophages from the same individuals.

CONCLUSIONS

Our co-culture system revealed the non-cell autonomous adverse effects of GM-CSF MΦ in individuals with ASD on neurons, mediated by interleukin-1α and TNF-α. These results may support the immune dysfunction hypothesis of ASD, providing new insights into its pathology.

Molecular profiling of the hippocampus of children with autism spectrum disorder

Several lines of evidence point to a key role of the hippocampus in Autism Spectrum Disorders (ASD). Altered hippocampal volume and deficits in memory for person and emotion related stimuli have been reported, along with enhanced ability for declarative memories. Mouse models have demonstrated a critical role of the hippocampus in social memory dysfunction, associated with ASD, together with decreased synaptic plasticity. Chondroitin sulfate proteoglycans (CSPGs), a family of extracellular matrix molecules, represent a potential key link between neurodevelopment, synaptic plasticity, and immune system signaling. There is a lack of information regarding the molecular pathology of the hippocampus in ASD. We conducted RNAseq profiling on postmortem human brain samples containing the hippocampus from male children with ASD (n = 7) and normal male children (3-14 yrs old), (n = 6) from the NIH NeuroBioBank. Gene expression profiling analysis implicated molecular pathways involved in extracellular matrix organization, neurodevelopment, synaptic regulation, and immune system signaling. qRT-PCR and Western blotting were used to confirm several of the top markers identified. The CSPG protein BCAN was examined with multiplex immunofluorescence to analyze cell-type specific expression of BCAN and astrocyte morphology. We observed decreased expression of synaptic proteins PSD95 (p < 0.02) and SYN1 (p < 0.02), increased expression of the extracellular matrix (ECM) protease MMP9 (p < 0.03), and decreased expression of MEF2C (p < 0.03). We also observed increased BCAN expression with astrocytes in children with ASD, together with altered astrocyte morphology. Our results point to alterations in immune system signaling, glia cell differentiation, and synaptic signaling in the hippocampus of children with ASD, together with alterations in extracellular matrix molecules. Furthermore, our results demonstrate altered expression of genes implicated in genetic studies of ASD including SYN1 and MEF2C.

Transcriptional cartography integrates multiscale biology of the human cortex

The cerebral cortex underlies many of our unique strengths and vulnerabilities, but efforts to understand human cortical organization are challenged by reliance on incompatible measurement methods at different spatial scales. Macroscale features such as cortical folding and functional activation are accessed through spatially dense neuroimaging maps, whereas microscale cellular and molecular features are typically measured with sparse postmortem sampling. Here, we integrate these distinct windows on brain organization by building upon existing postmortem data to impute, validate, and analyze a library of spatially dense neuroimaging-like maps of human cortical gene expression. These maps allow spatially unbiased discovery of cortical zones with extreme transcriptional profiles or unusually rapid transcriptional change which index distinct microstructure and predict neuroimaging measures of cortical folding and functional activation. Modules of spatially coexpressed genes define a family of canonical expression maps that integrate diverse spatial scales and temporal epochs of human brain organization - ranging from protein-protein interactions to large-scale systems for cognitive processing. These module maps also parse neuropsychiatric risk genes into subsets which tag distinct cyto-laminar features and differentially predict the location of altered cortical anatomy and gene expression in patients. Taken together, the methods, resources, and findings described here advance our understanding of human cortical organization and offer flexible bridges to connect scientific fields operating at different spatial scales of human brain research.

2dGBH: Two-dimensional group Benjamini-Hochberg procedure for false discovery rate control in two-way multiple testing of genomic data

MOTIVATION

Emerging omics technologies have introduced a two-way grouping structure in multiple testing, as seen in single-cell omics data, where the features can be grouped by either genes or cell types. Traditional multiple testing methods have limited ability to exploit such two-way grouping structure, leading to potential power loss.

RESULTS

We propose a new 2D Group Benjamini-Hochberg (2dGBH) procedure to harness the two-way grouping structure in omics data, extending the traditional one-way adaptive GBH procedure. Using both simulated and real datasets, we show that 2dGBH effectively controls the false discovery rate across biologically relevant settings, and it is more powerful than the BH or q-value procedure and more robust than the one-way adaptive GBH procedure.

AVAILABILITY AND IMPLEMENTATION

2dGBH is available as an R package at: https://github.com/chloelulu/tdGBH. The analysis code and data are available at: https://github.com/chloelulu/tdGBH-paper.

ATM-deficiency-induced microglial activation promotes neurodegeneration in ataxia-telangiectasia

While ATM loss of function has long been identified as the genetic cause of ataxia-telangiectasia (A-T), how it leads to selective and progressive degeneration of cerebellar Purkinje and granule neurons remains unclear. ATM expression is enriched in microglia throughout cerebellar development and adulthood. Here, we find evidence of microglial inflammation in the cerebellum of patients with A-T using single-nucleus RNA sequencing. Pseudotime analysis revealed that activation of A-T microglia preceded upregulation of apoptosis-related genes in granule and Purkinje neurons and that microglia exhibited increased neurotoxic cytokine signaling to granule and Purkinje neurons in A-T. To confirm these findings experimentally, we performed transcriptomic profiling of A-T induced pluripotent stem cell (iPSC)-derived microglia, which revealed cell-intrinsic microglial activation of cytokine production and innate immune response pathways compared to controls. Furthermore, A-T microglia co-culture with either control or A-T iPSC-derived neurons was sufficient to induce cytotoxicity. Taken together, these studies reveal that cell-intrinsic microglial activation may promote neurodegeneration in A-T.

Leveraging single-cell ATAC-seq and RNA-seq to identify disease-critical fetal and adult brain cell types

Prioritizing disease-critical cell types by integrating genome-wide association studies (GWAS) with functional data is a fundamental goal. Single-cell chromatin accessibility (scATAC-seq) and gene expression (scRNA-seq) have characterized cell types at high resolution, and studies integrating GWAS with scRNA-seq have shown promise, but studies integrating GWAS with scATAC-seq have been limited. Here, we identify disease-critical fetal and adult brain cell types by integrating GWAS summary statistics from 28 brain-related diseases/traits (average N = 298 K) with 3.2 million scATAC-seq and scRNA-seq profiles from 83 cell types. We identified disease-critical fetal (respectively adult) brain cell types for 22 (respectively 23) of 28 traits using scATAC-seq, and for 8 (respectively 17) of 28 traits using scRNA-seq. Significant scATAC-seq enrichments included fetal photoreceptor cells for major depressive disorder, fetal ganglion cells for BMI, fetal astrocytes for ADHD, and adult VGLUT2 excitatory neurons for schizophrenia. Our findings improve our understanding of brain-related diseases/traits and inform future analyses.

Transcriptome Analysis Identifies An ASD-Like Phenotype In Oligodendrocytes And Microglia From C58/J Amygdala That Is Dependent On Sex and Sociability

Background

Autism Spectrum Disorder (ASD) is a group of neurodevelopmental disorders with higher incidence in males and is characterized by atypical verbal/nonverbal communication, restricted interests that can be accompanied by repetitive behavior, and disturbances in social behavior. This study investigated brain mechanisms that contribute to sociability deficits and sex differences in an ASD animal model.

Methods

Sociability was measured in C58/J and C57BL/6J mice using the 3-chamber social choice test. Bulk RNA-Seq and snRNA-Seq identified transcriptional changes in C58/J and C57BL/6J amygdala within which DMRseq was used to measure differentially methylated regions in amygdala.

Results

C58/J mice displayed divergent social strata in the 3-chamber test. Transcriptional and pathway signatures revealed immune-related biological processes differ between C58/J and C57BL/6J amygdala. Hypermethylated and hypomethylated genes were identified in C58/J versus C57BL/6J amygdala. snRNA-Seq data in C58/J amygdala identified differential transcriptional signatures within oligodendrocytes and microglia characterized by increased ASD risk gene expression and predicted impaired myelination that was dependent on sex and sociability. RNA velocity, gene regulatory network, and cell communication analysis showed diminished oligodendrocyte/microglia differentiation. Findings were verified using bulk RNA-Seq and demonstrated oxytocin's beneficial effects on myelin gene expression.

Limitations

Our findings are significant. However, limitations can be noted. The cellular mechanisms linking reduced oligodendrocyte differentiation and reduced myelination to an ASD phenotype in C58/J mice need further investigation. Additional snRNA-Seq and spatial studies would determine if effects in oligodendrocytes/microglia are unique to amygdala or if this occurs in other brain regions. Oxytocin's effects need further examination to understand its potential as an ASD therapeutic.

Conclusions

Our work demonstrates the C58/J mouse model's utility in evaluating the influence of sex and sociability on the transcriptome in concomitant brain regions involved in ASD. Our single-nucleus transcriptome analysis elucidates potential pathological roles of oligodendrocytes and microglia in ASD. This investigation provides details regarding regulatory features disrupted in these cell types, including transcriptional gene dysregulation, aberrant cell differentiation, altered gene regulatory networks, and changes to key pathways that promote microglia/oligodendrocyte differentiation. Our studies provide insight into interactions between genetic risk and epigenetic processes associated with divergent affiliative behavior and lack of positive sociability.

Differences in Intrinsic Gray Matter Connectivity and Their Genomic Underpinnings in Autism Spectrum Disorder

BACKGROUND

Autism is a heterogeneous neurodevelopmental condition accompanied by differences in brain connectivity. Structural connectivity in autism has mainly been investigated within the white matter. However, many genetic variants associated with autism highlight genes related to synaptogenesis and axonal guidance, thus also implicating differences in intrinsic (i.e., gray matter) connections in autism. Intrinsic connections may be assessed in vivo via so-called intrinsic global and local wiring costs.

METHODS

Here, we examined intrinsic global and local wiring costs in the brain of 359 individuals with autism and 279 healthy control participants ages 6 to 30 years from the EU-AIMS LEAP (Longitudinal European Autism Project). FreeSurfer was used to derive surface mesh representations to compute the estimated length of connections required to wire the brain within the gray matter. Vertexwise between-group differences were assessed using a general linear model. A gene expression decoding analysis based on the Allen Human Brain Atlas was performed to link neuroanatomical differences to putative underpinnings.

RESULTS

Group differences in global and local wiring costs were predominantly observed in medial and lateral prefrontal brain regions, in inferior temporal regions, and at the left temporoparietal junction. The resulting neuroanatomical patterns were enriched for genes that had been previously implicated in the etiology of autism at genetic and transcriptomic levels.

CONCLUSIONS

Based on intrinsic gray matter connectivity, the current study investigated the complex neuroanatomy of autism and linked between-group differences to putative genomic and/or molecular mechanisms to parse the heterogeneity of autism and provide targets for future subgrouping approaches.

Epigenetic reprogramming shapes the cellular landscape of schwannoma

Mechanisms specifying cancer cell states and response to therapy are incompletely understood. Here we show epigenetic reprogramming shapes the cellular landscape of schwannomas, the most common tumors of the peripheral nervous system. We find schwannomas are comprised of 2 molecular groups that are distinguished by activation of neural crest or nerve injury pathways that specify tumor cell states and the architecture of the tumor immune microenvironment. Moreover, we find radiotherapy is sufficient for interconversion of neural crest schwannomas to immune-enriched schwannomas through epigenetic and metabolic reprogramming. To define mechanisms underlying schwannoma groups, we develop a technique for simultaneous interrogation of chromatin accessibility and gene expression coupled with genetic and therapeutic perturbations in single-nuclei. Our results elucidate a framework for understanding epigenetic drivers of tumor evolution and establish a paradigm of epigenetic and metabolic reprograming of cancer cells that shapes the immune microenvironment in response to radiotherapy.

ZEBRA: a hierarchically integrated gene expression atlas of the murine and human brain at single-cell resolution

The molecular causes and mechanisms of neurodegenerative diseases remain poorly understood. A growing number of single-cell studies have implicated various neural, glial, and immune cell subtypes to affect the mammalian central nervous system in many age-related disorders. Integrating this body of transcriptomic evidence into a comprehensive and reproducible framework poses several computational challenges. Here, we introduce ZEBRA, a large single-cell and single-nucleus RNA-seq database. ZEBRA integrates and normalizes gene expression and metadata from 33 studies, encompassing 4.2 million human and mouse brain cells sampled from 39 brain regions. It incorporates samples from patients with neurodegenerative diseases like Alzheimer's disease, Parkinson's disease, and Multiple sclerosis, as well as samples from relevant mouse models. We employed scVI, a deep probabilistic auto-encoder model, to integrate the samples and curated both cell and sample metadata for downstream analysis. ZEBRA allows for cell-type and disease-specific markers to be explored and compared between sample conditions and brain regions, a cell composition analysis, and gene-wise feature mappings. Our comprehensive molecular database facilitates the generation of data-driven hypotheses, enhancing our understanding of mammalian brain function during aging and disease. The data sets, along with an interactive database are freely available at https://www.ccb.uni-saarland.de/zebra.

STAB2: an updated spatio-temporal cell atlas of the human and mouse brain

The brain is constituted of heterogeneous types of neuronal and non-neuronal cells, which are organized into distinct anatomical regions, and show precise regulation of gene expression during development, aging and function. In the current database release, STAB2 provides a systematic cellular map of the human and mouse brain by integrating recently published large-scale single-cell and single-nucleus RNA-sequencing datasets from diverse regions and across lifespan. We applied a hierarchical strategy of unsupervised clustering on the integrated single-cell transcriptomic datasets to precisely annotate the cell types and subtypes in the human and mouse brain. Currently, STAB2 includes 71 and 61 different cell subtypes defined in the human and mouse brain, respectively. It covers 63 subregions and 15 developmental stages of human brain, and 38 subregions and 30 developmental stages of mouse brain, generating a comprehensive atlas for exploring spatiotemporal transcriptomic dynamics in the mammalian brain. We also augmented web interfaces for querying and visualizing the gene expression in specific cell types. STAB2 is freely available at https://mai.fudan.edu.cn/stab2.

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.

Changes in neuroinflammatory markers and microglial density in the hippocampus and prefrontal cortex of the C58/J mouse model of autism

Autism spectrum disorder (ASD) is a diverse group of neurodevelopmental conditions with complex origins. Individuals with ASD present various neurobiological abnormalities, including an altered immune response in the central nervous system and other tissues. Animal models like the C58/J inbred mouse strain are used to study biological characteristics of ASD. This strain is considered an idiopathic autism model because of its demonstrated reduced social preference and repetitive behaviours. Notably, C58/J mice exhibit alterations in dendritic arbour complexity, density and dendritic spines maturation in the hippocampus and prefrontal cortex (PFC), but inflammatory-related changes have not been explored in these mice. In this study, we investigated proinflammatory markers in the hippocampus and PFC of adult male C58/J mice. We discovered elevated levels of interferon gamma (IFN-γ) and monocyte chemoattractant protein 1 (MCP-1) in the hippocampus, suggesting increased inflammation, alongside a reduction in the anti-inflammatory enzyme arginase 1 (ARG1). Conversely, the PFC displayed reduced levels of TNF-α and MCP-1. Microglial analysis revealed higher levels of transmembrane protein 119 (TMEM119) and increased microglial density in a region-specific manner of the autistic-like mice, particularly in the PFC and hippocampus. Additionally, an augmented expression of the fractalkine receptor CX3CR1 was observed in the hippocampus and PFC of C58/J mice. Microglial morphological analysis shows no evident changes in the hippocampus of mice with autistic-like behaviours versus wild-type strain. These region-specific changes can contribute to modulate processes like inflammation or synaptic pruning in the C58/J mouse model of idiopathic autism.