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

Posttranscriptional Control of Neural Progenitors Temporal Dynamics During Neocortical Development by Syncrip

The development of the mammalian neocortex is precisely regulated by temporal gene expression, yet the temporal regulatory mechanisms of cortical neurogenesis, particularly how radial glial cells (RGCs) sequentially generate deep to superficial neurons, remain unclear. Here, the hnRNP family member Syncrip (hnRNP Q) is identified as a key modulator of superficial neuronal differentiation in neocortical neurogenesis. Syncrip knockout in RGCs disrupts differentiation and abnormal neuronal localization, ultimately resulting in superficial cortical layer defects as well as learning and memory impairments in mice. Single-cell RNA sequencing analysis demonstrated that the knockout of Syncrip disrupts the late-stage neurogenesis, stalling transcriptional progression in RGCs. Mechanistically, Syncrip maintains the transcription of temporal process-related transcription factors by recruiting stabilization complexes through phase separation, crucially regulating the Notch signaling pathway that determines the fate of RGCs. Furthermore, pathogenic human mutations in Syncrip weaken its phase-separation capability, failing to form stable complexes normally. Thus, Syncrip acts as a mediator of posttranscriptional regulatory mechanisms, governing the fate progression of RGCs and the advancement of intrinsic temporal programs. This study establishes an intracellular mechanism for posttranscriptional regulation of progressive fate determination in cortical neurogenesis.

Inferring disease progression stages in single-cell transcriptomics using a weakly supervised deep learning approach

Application of single-cell/nucleus genomic sequencing to patient-derived tissues offers potential solutions to delineate disease mechanisms in humans. However, individual cells in patient-derived tissues are in different pathological stages, and hence, such cellular variability impedes subsequent differential gene expression analyses. To overcome such a heterogeneity issue, we present a novel deep learning approach, scIDST, that infers disease progression levels of individual cells with weak supervision framework. The disease progression-inferred cells display significant differential expression of disease-relevant genes, which cannot be detected by comparative analysis between patients and healthy donors. In addition, we demonstrate that pretrained models by scIDST are applicable to multiple independent data resources and are advantageous to infer cells related to certain disease risks and comorbidities. Taken together, scIDST offers a new strategy of single-cell sequencing analysis to identify bona fide disease-associated molecular features.

The chromatin remodeler ADNP regulates neurodevelopmental disorder risk genes and neocortical neurogenesis

Although chromatin remodelers are among the most important risk genes associated with neurodevelopmental disorders (NDDs), the roles of these complexes during brain development are in many cases unclear. Here, we focused on the recently discovered ChAHP chromatin remodeling complex. The zinc finger and homeodomain transcription factor ADNP is a core subunit of this complex, and de novo ADNP mutations lead to intellectual disability and autism spectrum disorder. However, germline Adnp knockout mice were previously shown to exhibit early embryonic lethality, obscuring subsequent roles for the ChAHP complex in neurogenesis. To circumvent this early developmental arrest, we generated a conditional Adnp mutant allele. Using single-cell transcriptomics, cut&run-seq, and histological approaches, we show that during neocortical development, Adnp orchestrates the production of late-born, upper-layer neurons through a two-step process. First, Adnp is required to sustain progenitor proliferation specifically during the developmental window for upper-layer cortical neurogenesis. Accordingly, we found that Adnp recruits the ChAHP subunit Chd4 to genes associated with progenitor proliferation. Second, in postmitotic differentiated neurons, we define a network of risk genes linked to NDDs that are regulated by Adnp and Chd4. Taken together, these data demonstrate that ChAHP is critical for driving the expansion of upper-layer cortical neurons and for regulating neuronal gene expression programs, suggesting that these processes may potentially contribute to NDD etiology.

Prenatal inflammation impairs early CD11c-positive microglia induction and delays myelination in neurodevelopmental disorders

Histological chorioamnionitis (HCA) is a form of maternal immune activation (MIA) linked to an increased risk of neurodevelopmental disorders in offspring. Our previous study identified neurodevelopmental impairments in an MIA mouse model mimicking HCA. Thus, this study investigated the role of CD11c+ microglia, key contributors to myelination through IGF-1 production, in this pathology. In the mouse model, the CD11c+ microglial population was significantly lower in the MIA group than in the control group on postnatal day 3 (PN3d). Furthermore, myelination-related protein levels significantly decreased in the MIA group at PN8d. In humans, preterm infants with HCA exhibited higher IL-6 and IL-17A cord-serum levels and lower IGF-1 levels than those without HCA, followed by a higher incidence of delayed myelination on magnetic resonance imaging at the term-equivalent age. In silico analysis revealed that the transient induction of CD11c+ microglia during early development occurred similarly in mice and humans. Notably, a lack of high CD11c+ microglial population has been observed in children with neurodevelopmental disorders. This study reports impaired induction of CD11c+ microglia during postnatal development in a mouse model of MIA associated with delayed myelination. Our findings may inform strategies for improving outcomes in infants with HCA.

An atlas of neuropathic pain-associated molecular pathological characteristics in the mouse spinal cord

Peripheral nerve injury (PNI)-induced neuropathic pain (NP) is a severe disease with high prevalence in clinics. Gene reprogramming and tissue remodeling in the dorsal root ganglia (DRG) and spinal cord (SC) drive the development and maintenance of neuropathic pain (NP). However, our understanding of the NP-associated spatial molecular processing landscape of SC and the non-synaptic interactions between DRG neurons and SC cells remains limited. We here integrate spatial transcriptomics (ST) with single-nucleus RNA-sequencing (snRNA-seq) and bulk RNA-sequencing (bulk RNA-seq) to characterize regional pathological heterogeneity of the SC under NP conditions. First, the SC of NP mice manifests unique spatial atlases of genes, cell populations, cell-cell cross-talks, signaling pathways, and transcriptional regulatory networks compared to sham mice. We further report that injured DRG sensory neurons and the corresponding ventral horn of the SC show similar expression patterns after PNI. In addition, for the first time, we systematically exhibit "cross-talk omics" between the DRG neurons and SC dorsal horn neurons and glial cells, indicating an altered communication profile under NP conditions. Together, our findings decode the spatial and cellular heterogeneity of molecular pathological mechanisms underlying NP, providing a foundation for designing therapeutic targets for this disorder.

The Human Microglia Atlas (HuMicA) unravels changes in disease-associated microglia subsets across neurodegenerative conditions

Dysregulated microglia activation, leading to neuroinflammation, is crucial in neurodegenerative disease development and progression. We constructed an atlas of human brain immune cells by integrating nineteen single-nucleus RNA-seq and single-cell RNA-seq datasets from multiple neurodegenerative conditions, comprising 241 samples from patients with Alzheimer's disease, autism spectrum disorder, epilepsy, multiple sclerosis, Lewy body diseases, COVID-19, and healthy controls. The integrated Human Microglia Atlas (HuMicA) included 90,716 nuclei/cells and revealed nine populations distributed across all conditions. We identified four subtypes of disease-associated microglia and disease-inflammatory macrophages, recently described in mice, and shown here to be prevalent in human tissue. The high versatility of microglia is evident through changes in subset distribution across various pathologies, suggesting their contribution in shaping pathological phenotypes. A GPNMB-high subpopulation was expanded in AD and MS. In situ hybridization corroborated this increase in AD, opening the question on the relevance of this population in other pathologies.

Synaptic signatures and disease vulnerabilities of layer 5 pyramidal neurons

Cortical layer 5 (L5) intratelencephalic (IT) and pyramidal tract (PT) neurons are embedded in distinct information processing pathways. Their morphology, connectivity, electrophysiological properties, and role in behavior have been extensively analyzed. However, the molecular composition of their synapses remains largely uncharacterized. Here, we dissect the protein composition of the excitatory postsynaptic compartment of mouse L5 neurons in intact somatosensory circuits, using an optimized proximity biotinylation workflow with high spatial accuracy. We find distinct synaptic signatures of L5 IT and PT neurons that are defined by proteins regulating synaptic organization and transmission, including cell-surface proteins (CSPs), neurotransmitter receptors and ion channels. In addition, we find a differential vulnerability to disease, with a marked enrichment of autism risk genes in the synaptic signature of L5 IT neurons compared to PT neurons. These results align with human studies and suggest that the excitatory postsynaptic compartment of L5 IT neurons is susceptible in autism. Our approach is versatile and can be broadly applied to other neuron types to create a protein-based, synaptic atlas of cortical circuits.

Targeting S100A9 attenuates social dysfunction by modulating neuroinflammation and myelination in a mouse model of autism

Growing evidence supports a role for dysregulated neuroinflammation in autism. However, the underlying mechanisms of microglia-evoked neuroinflammation in the development of autistic phenotypes have not been elucidated. This study aimed to investigate the role and underlying mechanisms of microglial S100 calcium-binding protein A9 (S100A9) in autistic phenotypes. We utilized the BTBR T + tf/J (BTBR) mouse, a reliable preclinical model for autism that displays core behavioral features of autism as well as persistent immune dysregulation. A combination of behavioral, pharmacological, immunological, genetic, molecular, and transcriptomics approaches were used to uncover the potential role of S100A9 in autism. Significant overexpression of microglial S100A9 was observed in the hippocampus of BTBR mice. BTBR mice displayed decreased social communication and increased repetitive behaviors compared to C57BL/6 mice. Interestingly, the above social dysfunction was attenuated by a pharmacological inhibitor of S100A9, accompanied by a significant reduction in the activated microglia morphological phenotype, inflammatory receptors, and proinflammatory cytokines. Notably, S100A9 inhibition decreased c-Fos+ cells and promoted myelination in the cornu ammonis 3 of BTBR mice. Furthermore, the promyelinating compound administration ameliorated the autism-relevant behaviors in BTBR mice. Our findings indicate that microglia-derived S100A9 triggers the neuroinflammation cascade, myelination deficits, and social dysfunction. Targeting S100A9 could, therefore, be a promising therapeutic strategy for neuroinflammation-related neurodevelopmental disorders.

Transcriptomic analysis of EGFR co-expression and activation in glioblastoma reveals associations with its ligands

Background

Approximately half of the isocitrate dehydrogenase (IDH)-wildtype glioblastomas (GBMs) exhibit EGFR amplification. Additionally, genomic changes that occur in the extracellular domain of EGFR can lead to ligand-hypersensitivity (R108K/A289V/G598V) or ligand-independence (EGFRvIII). Unlike in lung adenocarcinoma (LUAD), clinical trials with epidermal growth factor receptor (EGFR) inhibitors showed no survival benefit for GBM and it remains unclear why. We aimed to elucidate differences in molecular mechanisms of EGFR activation and regulation between GBM and LUAD.

Methods

We used RNA-sequencing (RNA-seq) data to find EGFR co-regulated genes and pathways in GBM and compare EGFR signaling patterns between GBM and LUAD. Cellular origins of expression signals were determined by analyzing single-cell RNA-seq data.

Results

We identified 2 ligands (BTC/EREG) among the significant EGFR predictor genes (TCGA-GBM: n = 169, Intellance-2: n = 166). Their expression was inversely correlated with EGFR amplification and incidence of ligand-sensitive mutations. Ligands were expressed by nonmalignant cells and differed in their primary source of expression (BTC: neurons, EREG: myeloid). High expression of MDM2 and CDK4 was less common in EGFR-amplified GBMs with ligand-sensitive mutations compared with those without these mutations. Our analyses revealed distinct transcriptional profiles between GBM and LUAD when comparing tumors carrying activating mutations.

Conclusions

BTC and EREG are negatively associated with EGFR expression in GBM. These findings emphasize the role of ligands in regulating EGFR, where EGFR activation seems to be modulated by the highly varying levels of EGFR amplification, the sensitivity of the receptor toward ligands, and ligand expression levels. Ligand expression levels and EGFR mutations could refine patient stratification for EGFR-targeted therapies in GBM.

Further evidence of biallelic NAV3 variants associated with recessive neurodevelopmental disorder with dysmorphism, developmental delay, intellectual disability, and behavioral abnormalities

Neuron navigators (NAVs) are cytoskeleton-associated proteins well known for their role in axonal guidance, neuronal migration, and neurite growth necessary for neurodevelopment. Neuron navigator 3 (NAV3) is one of the three NAV proteins highly expressed in the embryonic and adult brain. However, the role of the NAV3 gene in human disease is not well-studied. Recently, five bi-allelic and three mono-allelic variants in NAV3 were reported in 12 individuals from eight unrelated families with neurodevelopmental disorder (NDD). Here, we report five patients from three unrelated consanguineous families segregating autosomal recessive NDD. Patients have symptoms of dysmorphism, intellectual disability, developmental delay, and behavioral abnormalities. Exome sequencing (ES) was performed on two affected individuals from one large family, and one affected individual from each of the other two families. ES revealed two homozygous nonsense c.6325C > T; p.(Gln2109Ter) and c.6577C > T; p.(Arg2193Ter) and a homozygous splice site (c.243 + 1G > T) variants in the NAV3 (NM_001024383.2). Analysis of single-cell sequencing datasets from embryonic and young adult human brains revealed that NAV3 is highly expressed in the excitatory neurons, inhibitory neurons, and microglia, consistent with its role in neurodevelopment. In conclusion, in this study, we further validate biallelic protein truncating variants in NAV3 as a cause of NDD, expanding the spectrum of pathogenic variants in this newly discovered NDD gene.

Transcriptomic Evidence Reveals the Dysfunctional Mechanism of Synaptic Plasticity Control in ASD

BACKGROUND/OBJECTIVES

A prominent endophenotype in Autism Spectrum Disorder (ASD) is the synaptic plasticity dysfunction, yet the molecular mechanism remains elusive. As a prototype, we investigate the postsynaptic signal transduction network in glutamatergic neurons and integrate single-cell nucleus transcriptomics data from the Prefrontal Cortex (PFC) to unveil the malfunction of translation control.

METHODS

We devise an innovative and highly dependable pipeline to transform our acquired signal transduction network into an mRNA Signaling-Regulatory Network (mSiReN) and analyze it at the RNA level. We employ Cell-Specific Network Inference via Integer Value Programming and Causal Reasoning (CS-NIVaCaR) to identify core modules and Cell-Specific Probabilistic Contextualization for mRNA Regulatory Networks (CS-ProComReN) to quantitatively reveal activated sub-pathways involving MAPK1, MKNK1, RPS6KA5, and MTOR across different cell types in ASD.

RESULTS

The results indicate that specific pivotal molecules, such as EIF4EBP1 and EIF4E, lacking Differential Expression (DE) characteristics and responsible for protein translation with long-term potentiation (LTP) or long-term depression (LTD), are dysregulated. We further uncover distinct activation patterns causally linked to the EIF4EBP1-EIF4E module in excitatory and inhibitory neurons.

CONCLUSIONS

Importantly, our work introduces a methodology for leveraging extensive transcriptomics data to parse the signal transduction network, transforming it into mSiReN, and mapping it back to the protein level. These algorithms can serve as potent tools in systems biology to analyze other omics and regulatory networks. Furthermore, the biomarkers within the activated sub-pathways, revealed by identifying convergent dysregulation, illuminate potential diagnostic and prognostic factors in ASD.

Decomposing the Brain in Autism: Linking Behavioral Domains to Neuroanatomical Variation and Genomic Underpinnings

BACKGROUND

Autism is accompanied by highly individualized patterns of neurodevelopmental differences in brain anatomy. This variability makes the neuroanatomy of autism inherently difficult to describe at the group level. Here, we examined interindividual neuroanatomical differences using a dimensional approach that decomposed the domains of social communication and interaction (SCI), restricted and repetitive behaviors (RRBs), and atypical sensory processing (ASP) within a neurodiverse study population. Moreover, we aimed to link the resulting neuroanatomical patterns to specific molecular underpinnings.

METHODS

Neurodevelopmental differences in cortical thickness (CT) and surface area (SA) were correlated with SCI, RRB, and ASP domain scores by regression of a general linear model in a large neurodiverse sample of 288 autistic individuals and 140 nonautistic individuals, ages 6 to 30 years, recruited within the European Autism Interventions Longitudinal European Autism Project (EU-AIMS LEAP). The domain-specific patterns of neuroanatomical variability were subsequently correlated with cortical gene expression profiles via the Allen Human Brain Atlas.

RESULTS

Across groups, behavioral variations in SCI, RRBs, and ASP were associated with interindividual differences in CT and SA in partially non-overlapping frontoparietal, temporal, and occipital networks. These domain-specific imaging patterns were enriched for genes that 1) are differentially expressed in autism, 2) mediate typical brain development, and 3) are associated with specific cortical cell types. Many of these genes were implicated in pathways governing synaptic structure and function.

CONCLUSIONS

Our study corroborates the close relationship between neuroanatomical variation and interindividual differences in autism-related symptoms and traits within the general framework of neurodiversity and links domain-specific patterns of neuroanatomical differences to putative molecular underpinnings.

The intersection of inflammation and DNA damage as a novel axis underlying the pathogenesis of autism spectrum disorders

Autism spectrum disorders (ASD) affects 1 in 36 children and is characterized by repetitive behaviors and difficulties in social interactions and social communication. The etiology of ASD is extremely heterogeneous, with a large number of ASD cases that are of unknown or complex etiology, which suggests the potential contribution of epigenetic risk factors. In particular, epidemiological and animal model studies suggest that inflammation during pregnancy could lead to an increased risk of ASD in the offspring. However, the molecular mechanisms that contribute to ASD pathogenesis in relation to maternal inflammation during pregnancy in humans are underexplored. Several pro-inflammatory cytokines have been associated with increased autistic-like behaviors in animal models of maternal immune activation, including IL-17A. Using a combination of ASD patient lymphocytes and stem cell-derived human neurons exposed to IL-17A we discovered a shared molecular signature that highlights a metabolic and translational node that could lead to altered neuronal excitability. Further, our work on human neurons brings forward the possibility that defects in the DNA damage response could be underlying the effect of IL-17A on human excitatory neurons, linking exacerbated unrepaired DNA damage to the pathogenicity of maternal inflammation in connection to ASD.

Single-nucleus multi-omics analyses reveal cellular and molecular innovations in the anterior cingulate cortex during primate evolution

The anterior cingulate cortex (ACC) of the human brain is involved in higher-level cognitive functions such as emotion and self-awareness. We generated profiles of human and macaque ACC gene expression and chromatin accessibility at single-nucleus resolution. We characterized the conserved patterns of gene expression, chromatin accessibility, and transcription factor binding in different cell types. Combining the published mouse data, we discovered the molecular identities and cell-lineage origin of the primate von Economo neurons (VENs). Our in vitro and in vivo experiments identified a group of primate-shared and human-specific VEN marker genes, such as PCSK6, ADAMTSL3, and CDHR3, potentially contributing to VEN morphogenesis. We demonstrated that the human-specific sequence changes account for the cellular and functional innovations in the ACC during primate evolution and human origin. These findings provide new insights into understanding the cellular composition and molecular regulation of ACC and its evolutionary role in shaping human-owned higher cognitive skills.

Rapid effects of valproic acid on the fetal brain transcriptome: implications for brain development and autism

There is an increased incidence of autism among the children of women who take the anti-epileptic, mood-stabilizing drug, valproic acid (VPA) during pregnancy; moreover, exposure to VPA in utero causes autistic-like symptoms in rodents and non-human primates. Analysis of RNA-seq data obtained from E12.5 fetal mouse brains 3 hours after VPA administration to the pregnant dam revealed that VPA rapidly and significantly increased or decreased the expression of approximately 7,300 genes. No significant sex differences in VPA-induced gene expression were observed. Expression of 399 autism risk genes was significantly altered by VPA as was expression of 258 genes that have been reported to modulate fetal brain development but are not otherwise linked to autism. Expression of genes associated with intracellular signaling pathways, neurogenesis, and excitation-inhibition balance as well as synaptogenesis, neuronal fate determination, axon and dendritic development, neuroinflammation, circadian rhythms, and epigenetic modulation of gene expression was dysregulated by VPA. Notably, at least 40 genes that are known to regulate embryonic neurogenesis were dysregulated by VPA. The goal of this study was to identify mouse genes that are: (a) significantly up- or downregulated by VPA in the fetal brain and (b) associated with autism and/or known to play a role in embryonic neurodevelopmental processes, perturbation of which has the potential to alter brain connectivity and, consequently behavior, in the adult. The genes meeting these criteria provide potential targets for future hypothesis-driven studies to elucidate the proximal causes of errors in brain connectivity underlying neurodevelopmental disorders such as autism.

Astrocyte-neuron crosstalk in neurodevelopmental disorders

A fundamental feature shared across neurodevelopmental disorders (NDDs) is the disruption of synaptic circuit formation and homeostasis. During early life, non-neuronal cells called astrocytes tightly regulate the establishment of circuits by controlling formation, remodeling, stabilization, and maturation of synapses. Concurrently, astrocytes mature to meet the evolving needs of the developing brain. Bidirectional astrocyte-neuron communication synchronizes astrocyte maturation with synapse development. An emerging body of evidence supports the hypothesis that in NDDs, deficits in astrocyte-neuron communication underlie errors in synaptic circuit development. Here we will review and discuss these findings, with the aim of inspiring future research and guiding translational studies.

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.

The single-cell opioid responses in the context of HIV (SCORCH) consortium

Substance use disorders (SUD) and drug addiction are major threats to public health, impacting not only the millions of individuals struggling with SUD, but also surrounding families and communities. One of the seminal challenges in treating and studying addiction in human populations is the high prevalence of co-morbid conditions, including an increased risk of contracting a human immunodeficiency virus (HIV) infection. Of the ~15 million people who inject drugs globally, 17% are persons with HIV. Conversely, HIV is a risk factor for SUD because chronic pain syndromes, often encountered in persons with HIV, can lead to an increased use of opioid pain medications that in turn can increase the risk for opioid addiction. We hypothesize that SUD and HIV exert shared effects on brain cell types, including adaptations related to neuroplasticity, neurodegeneration, and neuroinflammation. Basic research is needed to refine our understanding of these affected cell types and adaptations. Studying the effects of SUD in the context of HIV at the single-cell level represents a compelling strategy to understand the reciprocal interactions among both conditions, made feasible by the availability of large, extensively-phenotyped human brain tissue collections that have been amassed by the Neuro-HIV research community. In addition, sophisticated animal models that have been developed for both conditions provide a means to precisely evaluate specific exposures and stages of disease. We propose that single-cell genomics is a uniquely powerful technology to characterize the effects of SUD and HIV in the brain, integrating data from human cohorts and animal models. We have formed the Single-Cell Opioid Responses in the Context of HIV (SCORCH) consortium to carry out this strategy.

Patterns of Brain Maturation in Autism and Their Molecular Associations

Importance

In the neurotypical brain, regions develop in coordinated patterns, providing a fundamental scaffold for brain function and behavior. Whether altered patterns contribute to clinical profiles in neurodevelopmental conditions, including autism, remains unclear.

Objectives

To examine if, in autism, brain regions develop differently in relation to each other and how these differences are associated with molecular/genomic mechanisms and symptomatology.

Design, Setting, and Participants

This study was an analysis of one the largest deep-phenotyped, case-control, longitudinal (2 assessments separated by approximately 12-24 months) structural magnetic resonance imaging and cognitive-behavioral autism datasets (EU-AIMS Longitudinal European Autism Project [LEAP]; study dates, February 2014-November 2017) and an out-of-sample validation in the Brain Development Imaging Study (BrainMapASD) independent cohort. Analyses were performed during the 2022 to 2023 period. This multicenter study included autistic and neurotypical children, adolescents, and adults. Autistic participants were included if they had an existing autism diagnosis (DSM-IV/International Statistical Classification of Diseases and Related Health Problems, Tenth Revision or DSM-5 criteria). Autistic participants with co-occurring psychiatric conditions (except psychosis/bipolar disorder) and those taking regular medications were included.

Exposures

Neuroanatomy of neurotypical and autistic participants.

Main Outcomes and Measures

Intraindividual changes in surface area and cortical thickness over time, analyzed via surface-based morphometrics.

Results

A total of 386 individuals in the LEAP cohort (6-31 years at first visit; 214 autistic individuals, mean [SD] age, 17.3 [5.4] years; 154 male [72.0%] and 172 neurotypical individuals, mean [SD] age, 16.35 [5.7] years; 108 male [62.8%]) and 146 individuals in the BrainMapASD cohort (11-18 years at first visit; 49 autistic individuals, mean [SD] age, 14.31 [2.4] years; 42 male [85.7%] and 97 neurotypical individuals, mean [SD] age, 14.10 [2.5] years; 58 male [59.8%]). Maturational between-group differences in cortical thickness and surface area were established that were mostly driven by sensorimotor regions (eg, across features, absolute loadings for early visual cortex ranged from 0.07 to 0.11, whereas absolute loadings for dorsolateral prefrontal cortex ranged from 0.005 to 0.06). Neurodevelopmental differences were transcriptomically enriched for genes expressed in several cell types and during various neurodevelopmental stages, and autism candidate genes (eg, downregulated genes in autism, including those regulating synaptic transmission; enrichment odds ratio =3.7; P =2.6 × -10). A more neurotypical, less autismlike maturational profile was associated with fewer social difficulties and more typical sensory processing (false discovery rate P <.05; Pearson r ≥0.17). Results were replicated in the independently collected BrainMapASD cohort.

Conclusions and Relevance

Results of this case-control study suggest that the coordinated development of brain regions was altered in autism, involved a complex interplay of temporally sensitive molecular mechanisms, and may be associated with both lower-order (eg, sensory) and higher-order (eg, social) clinical features of autism. Thus, examining maturational patterns may provide an analytic framework to study the neurobiological origins of clinical profiles in neurodevelopmental/mental health conditions.

Potential key pathophysiological participant and treatment target in autism spectrum disorder: Microglia

Autism spectrum disorder (ASD) is a group of neurodevelopmental disorders characterized by social and communication deficits, as well as restricted or repetitive behaviors or interests. Although the etiology of ASD remains unclear, there is abundant evidence suggesting that microglial dysfunction is likely to be a significant factor in the pathophysiology of ASD. Microglia, the primary innate immune cells in the central nervous system (CNS), play a crucial role in brain development and homeostasis. Recently, numerous studies have shown that microglia in ASD models display various abnormalities including morphology, function, cellular interactions, genetic and epigenetic factors, as well as the expression of receptors, transcription factors, and cytokines. They impact normal neural development through various mechanisms contributing to ASD, such as neuroinflammation, and alterations in synaptic formation and pruning. The focus of this review is on recent studies regarding microglial abnormalities in ASD and their effects on the onset and progression of ASD at both cellular and molecular levels. It can provide insight into the specific contribution of microglia to ASD pathogenesis and help in designing potential therapeutic and preventative strategies targeting microglia.

Medial prefrontal cortex circuitry and social behaviour in autism

Autism spectrum disorder (ASD) has proven to be highly enigmatic due to the diversity of its underlying genetic causes and the huge variability in symptom presentation. Uncovering common phenotypes across people with ASD and pre-clinical models allows us to better understand the influence on brain function of the many different genetic and cellular processes thought to contribute to ASD aetiology. One such feature of ASD is the convergent evidence implicating abnormal functioning of the medial prefrontal cortex (mPFC) across studies. The mPFC is a key part of the 'social brain' and may contribute to many of the changes in social behaviour observed in people with ASD. Here we review recent evidence for mPFC involvement in both ASD and social behaviours. We also highlight how pre-clinical mouse models can be used to uncover important cellular and circuit-level mechanisms that may underly atypical social behaviours in ASD. This article is part of the Special Issue on "PFC circuit function in psychiatric disease and relevant models".

Shared genetic architecture and causality between autism spectrum disorder and irritable bowel syndrome, multisite pain, and fatigue

Autism spectrum disorder (ASD) often co-occurs with functional somatic syndromes (FSS), such as irritable bowel syndrome (IBS), multisite pain, and fatigue. However, the underlying genetic mechanisms and causality have not been well studied. Using large-scale genome-wide association study (GWAS) data, we investigated the shared genetic architecture and causality between ASD and FSS. Specifically, we first estimated genetic correlations and then conducted a multi-trait analysis of GWAS (MTAG) to detect potential novel genetic variants for single traits. Afterwards, polygenic risk scores (PRS) of ASD were derived from GWAS and MTAG to examine the associations with phenotypes in the large Dutch Lifelines cohort. Finally, we performed Mendelian randomization (MR) to evaluate the causality. We observed positive genetic correlations between ASD and FSS (IBS: rg = 0.27, adjusted p = 2.04 × 10-7; multisite pain: rg = 0.13, adjusted p = 1.10 × 10-3; fatigue: rg = 0.33, adjusted p = 5.21 × 10-9). Leveraging these genetic correlations, we identified 3 novel genome-wide significant independent loci for ASD by conducting MTAG, mapped to NEDD4L, MFHAS1, and RP11-10A14.4. PRS of ASD derived from both GWAS and MTAG were associated with ASD and FSS in Lifelines, and MTAG-derived PRS showed a bigger effect size, larger explained variance, and smaller p-values. We did not observe significant causality using MR. Our study found genetic associations between ASD and FSS, specifically with IBS, multisite pain, and fatigue. These findings suggest that a shared genetic architecture may partly explain the co-occurrence between ASD and FSS. Further research is needed to investigate the causality between ASD and FSS due to current limited statistical power of the GWASs.

Private information leakage from single-cell count matrices

The increase in publicly available human single-cell datasets, encompassing millions of cells from many donors, has significantly enhanced our understanding of complex biological processes. However, the accessibility of these datasets raises significant privacy concerns. Due to the inherent noise in single-cell measurements and the scarcity of population-scale single-cell datasets, recent private information quantification studies have focused on bulk gene expression data sharing. To address this gap, we demonstrate that individuals in single-cell gene expression datasets are vulnerable to linking attacks, where attackers can infer their sensitive phenotypic information using publicly available tissue or cell-type-specific expression quantitative trait loci (eQTLs) information. We further develop a method for genotype prediction and genotype-phenotype linking that remains effective without relying on eQTL information. We show that variants from one study can be exploited to uncover private information about individuals in another study.

Complement and microglia activation mediate stress-induced synapse loss in layer 2/3 of the medial prefrontal cortex in male mice

Spatially heterogeneous synapse loss is a characteristic of many psychiatric and neurological disorders, but the underlying mechanisms are unclear. Here, we show that spatially-restricted complement activation mediates stress-induced heterogeneous microglia activation and synapse loss localized to the upper layers of the medial prefrontal cortex (mPFC) in male mice. Single cell RNA sequencing also reveals a stress-associated microglia state marked by high expression of the apolipoprotein E gene (Apoehigh) localized to the upper layers of the mPFC. Mice lacking complement component C3 are protected from stress-induced layer-specific synapse loss, and the Apoehigh microglia population is markedly reduced in the mPFC of these mice. Furthermore, C3 knockout mice are also resilient to stress-induced anhedonia and working memory behavioral deficits. Our findings suggest that region-specific complement and microglia activation can contribute to the disease-specific spatially restricted patterns of synapse loss and clinical symptoms found in many brain diseases.

Brain-wide alterations revealed by spatial transcriptomics and proteomics in COVID-19 infection

Understanding the pathophysiology of neurological symptoms observed after severe acute respiratory syndrome coronavirus 2 (SARS-CoV2) infection is essential to optimizing outcomes and therapeutics. To date, small sample sizes and narrow molecular profiling have limited the generalizability of findings. In this study, we profiled multiple cortical and subcortical regions in postmortem brains of patients with coronavirus disease 2019 (COVID-19) and controls with matched pulmonary pathology (total n = 42) using spatial transcriptomics, bulk gene expression and proteomics. We observed a multi-regional antiviral response without direct active SARS-CoV2 infection. We identified dysregulation of mitochondrial and synaptic pathways in deep-layer excitatory neurons and upregulation of neuroinflammation in glia, consistent across both mRNA and protein. Remarkably, these alterations overlapped substantially with changes in age-related neurodegenerative diseases, including Parkinson's disease and Alzheimer's disease. Our work, combining multiple experimental and analytical methods, demonstrates the brain-wide impact of severe acute/subacute COVID-19, involving both cortical and subcortical regions, shedding light on potential therapeutic targets within pathways typically associated with pathological aging and neurodegeneration.

Single-nucleus RNA sequencing-based construction of a hippocampal neuron atlas in mice with epileptic cognitive impairment

The hippocampus plays a critical role in learning and memory, and mice with epileptic cognitive impairment exhibit hippocampal atrophy. However, there is still a lack of research on the hippocampal cell atlas related to these disorders. Here, we utilized snRNA-seq to characterize the transcriptomic changes in hippocampal neurons of drug-resistant epilepsy (DRE) cognitive-impaired mice. The intercellular heterogeneity of 20 subpopulations of neurons was analyzed, focusing on aspects such as cell communication, gene expressions, GO and KEGG enrichment analysis, and module gene set analysis. Based on the degree of relevance to synaptic biological functions, the subpopulations associated with cognitive impairment (ExN1, 3, 8 and InN1, 6) were preliminarily identified. We also identified some key biomarkers in DRE cognitive-impaired mice, such as Ptprz1 and Calb1. Finally, we integrate and validate our dataset using identified well-annotated marker genes in the hippocampal region, further supporting the functional annotation of neuronal subpopulations.

HBI: a hierarchical Bayesian interaction model to estimate cell-type-specific methylation quantitative trait loci incorporating priors from cell-sorted bisulfite sequencing data

Methylation quantitative trait loci (meQTLs) quantify the effects of genetic variants on DNA methylation levels. However, most published studies utilize bulk methylation datasets composed of different cell types and limit our understanding of cell-type-specific methylation regulation. We propose a hierarchical Bayesian interaction (HBI) model to infer cell-type-specific meQTLs, which integrates a large-scale bulk methylation data and a small-scale cell-type-specific methylation data. Through simulations, we show that HBI enhances the estimation of cell-type-specific meQTLs. In real data analyses, we demonstrate that HBI can further improve the functional annotation of genetic variants and identify biologically relevant cell types for complex traits.

scCTS: identifying the cell type-specific marker genes from population-level single-cell RNA-seq

Single-cell RNA-sequencing (scRNA-seq) provides gene expression profiles of individual cells from complex samples, facilitating the detection of cell type-specific marker genes. In scRNA-seq experiments with multiple donors, the population level variation brings an extra layer of complexity in cell type-specific gene detection, for example, they may not appear in all donors. Motivated by this observation, we develop a statistical model named scCTS to identify cell type-specific genes from population-level scRNA-seq data. Extensive data analyses demonstrate that the proposed method identifies more biologically meaningful cell type-specific genes compared to traditional methods.

Evolutionary neurogenomics at single-cell resolution

The human brain is composed of increasingly recognized heterogeneous cell types. Applying single-cell genomics to brain tissue can elucidate relative cell type proportions as well as differential gene expression and regulation among humans and other species. Here, we review recent studies that utilized high-throughput genomics approaches to compare brains among species at single-cell resolution. These studies identified genomic elements that are similar among species as well as evolutionary novelties on the human lineage. We focus on those human-relevant innovations and discuss the biological implications of these modifications. Finally, we discuss areas of comparative single-cell genomics that remain unexplored either due to needed technological advances or due to biological availability at the brain region or species level.

Single-nucleus transcriptomic profiling of human orbitofrontal cortex reveals convergent effects of aging and psychiatric disease

Aging is a complex biological process and represents the largest risk factor for neurodegenerative disorders. The risk for neurodegenerative disorders is also increased in individuals with psychiatric disorders. Here, we characterized age-related transcriptomic changes in the brain by profiling ~800,000 nuclei from the orbitofrontal cortex from 87 individuals with and without psychiatric diagnoses and replicated findings in an independent cohort with 32 individuals. Aging affects all cell types, with LAMP5+LHX6+ interneurons, a cell-type abundant in primates, by far the most affected. Disrupted synaptic transmission emerged as a convergently affected pathway in aged tissue. Age-related transcriptomic changes overlapped with changes observed in Alzheimer's disease across multiple cell types. We find evidence for accelerated transcriptomic aging in individuals with psychiatric disorders and demonstrate a converging signature of aging and psychopathology across multiple cell types. Our findings shed light on cell-type-specific effects and biological pathways underlying age-related changes and their convergence with effects driven by psychiatric diagnosis.

An integrative single-cell atlas for exploring the cellular and temporal specificity of genes related to neurological disorders during human brain development

Single-cell technologies have enhanced comprehensive knowledge regarding the human brain by facilitating an extensive transcriptomic census across diverse brain regions. Nevertheless, understanding the cellular and temporal specificity of neurological disorders remains ambiguous due to developmental variations. To address this gap, we illustrated the dynamics of disorder risk gene expression under development by integrating multiple single-cell RNA sequencing datasets. We constructed a comprehensive single-cell atlas of the developing human brain, encompassing 393,060 single cells across diverse developmental stages. Temporal analysis revealed the distinct expression patterns of disorder risk genes, including those associated with autism, highlighting their temporal regulation in different neuronal and glial lineages. We identified distinct neuronal lineages that diverged across developmental stages, each exhibiting temporal-specific expression patterns of disorder-related genes. Lineages of nonneuronal cells determined by molecular profiles also showed temporal-specific expression, indicating a link between cellular maturation and the risk of disorder. Furthermore, we explored the regulatory mechanisms involved in early brain development, revealing enriched patterns of fetal cell types associated with neuronal disorders indicative of the prenatal stage's influence on disease determination. Our findings facilitate unbiased comparisons of cell type‒disorder associations and provide insight into dynamic alterations in risk genes during development, paving the way for a deeper understanding of neurological disorders.

Modelling cell type-specific lncRNA regulatory network in autism with Cycle

BACKGROUND

Autism spectrum disorder (ASD) is a class of complex neurodevelopment disorders with high genetic heterogeneity. Long non-coding RNAs (lncRNAs) are vital regulators that perform specific functions within diverse cell types and play pivotal roles in neurological diseases including ASD. Therefore, exploring lncRNA regulation would contribute to deciphering ASD molecular mechanisms. Existing computational methods utilize bulk transcriptomics data to identify lncRNA regulation in all of samples, which could reveal the commonalities of lncRNA regulation in ASD, but ignore the specificity of lncRNA regulation across various cell types.

RESULTS

Here, we present Cycle (Cell type-specific lncRNA regulatory network) to construct the landscape of cell type-specific lncRNA regulation in ASD. We have found that each ASD cell type is unique in lncRNA regulation, and more than one-third and all cell type-specific lncRNA regulatory networks are characterized as scale-free and small-world, respectively. Across 17 ASD cell types, we have discovered 19 rewired and 11 stable modules, along with eight rewired and three stable hubs within the constructed cell type-specific lncRNA regulatory networks. Enrichment analysis reveals that the discovered rewired and stable modules and hubs are closely related to ASD. Furthermore, more similar ASD cell types tend to be connected with higher strength in the constructed cell similarity network. Finally, the comparison results demonstrate that Cycle is a potential method for uncovering cell type-specific lncRNA regulation.

CONCLUSION

Overall, these results illustrate that Cycle is a promising method to model the landscape of cell type-specific lncRNA regulation, and provides insights into understanding the heterogeneity of lncRNA regulation between various ASD cell types.

Reducing Filamin A Restores Cortical Synaptic Connectivity and Early Social Communication Following Cellular Mosaicism in Autism Spectrum Disorder Pathways

Communication in the form of nonverbal, social vocalization, or crying is evolutionary conserved in mammals and is impaired early in human infants that are later diagnosed with autism spectrum disorder (ASD). Defects in infant vocalization have been proposed as an early sign of ASD that may exacerbate ASD development. However, the neural mechanisms associated with early communicative deficits in ASD are not known. Here, we expressed a constitutively active mutant of Rheb (RhebS16H), which is known to upregulate two ASD core pathways, mTOR complex 1 (mTORC1) and ERK1/2, in Layer (L) 2/3 pyramidal neurons of the neocortex of mice of either sex. We found that cellular mosaic expression of RhebS16H in L2/3 pyramidal neurons altered the production of isolation calls from neonatal mice. This was accompanied by an expected misplacement of neurons and dendrite overgrowth, along with an unexpected increase in spine density and length, which was associated with increased excitatory synaptic activity. This contrasted with the known decrease in spine density in RhebS16H neurons of 1-month-old mice. Reducing the levels of the actin cross-linking and adaptor protein filamin A (FLNA), known to be increased downstream of ERK1/2, attenuated dendrite overgrowth and fully restored spine properties, synaptic connectivity, and the production of pup isolation calls. These findings suggest that upper-layer cortical pyramidal neurons contribute to communicative deficits in a condition known to affect two core ASD pathways and that these mechanisms are regulated by FLNA.

Unveiling the role of IGF1R in autism spectrum disorder: a multi-omics approach to decipher common pathogenic mechanisms in the IGF signaling pathway

Autism spectrum disorder (ASD) is a complex neurodevelopmental condition marked by impairments in social interaction, communication, and repetitive behaviors. Emerging evidence suggests that the insulin-like growth factor (IGF) signaling pathway plays a critical role in ASD pathogenesis; however, the precise pathogenic mechanisms remain elusive. This study utilizes multi-omics approaches to investigate the pathogenic mechanisms of ASD susceptibility genes within the IGF pathway. Whole-exome sequencing (WES) revealed a significant enrichment of rare variants in key IGF signaling components, particularly the IGF receptor 1 (IGF1R), in a cohort of Chinese Han individuals diagnosed with ASD, as well as in ASD patients from the SFARI SPARK WES database. Subsequent single-cell RNA sequencing (scRNA-seq) of cortical tissues from children with ASD demonstrated elevated expression of IGF receptors in parvalbumin (PV) interneurons, suggesting a substantial impact on their development. Notably, IGF1R appears to mediate the effects of IGF2R on these neurons. Additionally, transcriptomic analysis of brain organoids derived from ASD patients indicated a significant association between IGF1R and ASD. Protein-protein interaction (PPI) and gene regulatory network (GRN) analyses further identified ASD susceptibility genes that interact with and regulate IGF1R expression. In conclusion, IGF1R emerges as a central node within the IGF signaling pathway, representing a potential common pathogenic mechanism and therapeutic target for ASD. These findings highlight the need for further investigation into the modulation of this pathway as a strategy for ASD intervention.

Endolysosomal dysfunction in radial glia progenitor cells leads to defective cerebral angiogenesis and compromised blood-brain barrier integrity

The neurovascular unit (NVU) is a complex multicellular structure that helps maintain cerebral homeostasis and blood-brain barrier (BBB) integrity. While extensive evidence links NVU alterations to cerebrovascular diseases and neurodegeneration, the underlying molecular mechanisms remain unclear. Here, we use zebrafish embryos carrying a mutation in Scavenger Receptor B2, a highly conserved endolysosomal protein expressed predominantly in Radial Glia Cells (RGCs), to investigate the interplay among different NVU components. Through live imaging and genetic manipulations, we demonstrate that compromised acidification of the endolysosomal compartment in mutant RGCs leads to impaired Notch3 signaling, thereby inducing excessive neurogenesis and reduced glial differentiation. We further demonstrate that alterations to the neuron/glia balance result in impaired VEGF and Wnt signaling, leading to severe vascular defects, hemorrhages, and a leaky BBB. Altogether, our findings provide insights into NVU formation and function and offer avenues for investigating diseases involving white matter defects and vascular abnormalities.

Arachidonic acid-derived dihydroxy fatty acids in neonatal cord blood relate symptoms of autism spectrum disorders and social adaptive functioning: Hamamatsu Birth Cohort for Mothers and Children (HBC Study)

AIM

Autism spectrum disorder (ASD) is associated with abnormal lipid metabolism, such as a high total ratio of omega-6 to omega-3 in polyunsaturated fatty acids (PUFAs). PUFAs are metabolized to epoxy fatty acids by cytochrome P450 (CYP); then, dihydroxy fatty acid is produced by soluble epoxide hydrolase. This study examined the association between PUFA metabolites in the cord blood and ASD symptoms and adaptive functioning in children.

METHODS

This prospective cohort study utilized cord blood to quantify PUFA metabolites of the CYP pathway. The Autism Diagnostic Observation Schedule (ADOS-2) and Vineland Adaptive Behaviors Scales, Second Edition (VABS-II) were used to assess subsequent ASD symptoms and adaptive functioning in children at 6 years. The analysis included 200 children and their mothers.

RESULTS

Arachidonic acid-derived diols, 11,12-diHETrE was found to impact ASD symptom severity on the ADOS-2-calibrated severity scores and impairment in the socialization domain as assessed by the VABS-II (P = 0.0003; P = 0.004, respectively). High levels of 11,12-diHETrE impact social affect in ASD symptoms (P = 0.002), while low levels of 8,9-diHETrE impact repetitive/restrictive behavior (P = 0.003). Notably, there was specificity in the association between diHETrE and ASD symptoms, especially in girls.

CONCLUSION

These findings suggest that the dynamics of diHETrE during the fetal period is important in the developmental trajectory of children after birth. Given that the role of diol metabolites in neurodevelopment in vivo is completely uncharacterized, the results of this study provide important insight into the role of diHETrE and ASD pathophysiology.

Single cell spatial biology over developmental time can decipher pediatric brain pathologies

Pediatric low grade brain tumors and neurodevelopmental disorders share proteins, signaling pathways, and networks. They also share germline mutations and an impaired prenatal differentiation origin. They may differ in the timing of the events and proliferation. We suggest that their pivotal distinct, albeit partially overlapping, outcomes relate to the cell states, which depend on their spatial location, and timing of gene expression during brain development. These attributes are crucial as the brain develops sequentially, and single-cell spatial organization influences cell state, thus function. Our underlying premise is that the root cause in neurodevelopmental disorders and pediatric tumors is impaired prenatal differentiation. Data related to pediatric brain tumors, neurodevelopmental disorders, brain cell (sub)types, locations, and timing of expression in the developing brain are scant. However, emerging single cell technologies, including transcriptomic, spatial biology, spatial high-resolution imaging performed over the brain developmental time, could be transformational in deciphering brain pathologies thereby pharmacology.

Calcium Hexacyanoferrate (III) Nanocatalyst Enables Redox Homeostasis for Autism Spectrum Disorder Treatment

Autism spectrum disorder (ASD) is a multifaced neurodevelopmental disorder with considerable heterogeneity, in which over-generated reactive oxygen species (ROS) induce a cascade of pathological changes, including cellular apoptosis and inflammatory responses. Given the complex etiology of ASD, no effective treatment is available for ASD. In this work, a specific catalytic nanoenzyme, calcium hexacyanoferrate (III) nanocatalysts (CaH NCs), is designed and engineered for efficient ASD treatment. CaH NCs can mimic the activities of natural enzymes including superoxide dismutase, peroxidase, catalase, and glutathione peroxidase, which mitigates intracellular excessive ROS and regulates redox equilibrium. These CaH NCs modulate mitochondrial membrane potential, elevate B-cell lymphoma-2 levels, and suppress pro-apoptotic proteins, including Caspase-3 and B-cell lymphoma-2-associated X, thus effectively reducing cellular apoptosis. Importantly, CaH NCs alleviate inflammation by upregulating anti-inflammatory cytokine interleukin-10 and downregulating pro-inflammatory factors, resulting in attenuated activation of microglial and astrocytic and subsequent reduction in neuroinflammation. Subsequently, CaH NCs enhance social abilities, decrease anxiety levels, ameliorate repetitive behaviors, and improve learning and memory in ASD animal models through inflammation regulation and apoptosis inhibition. The CaH NCs in managing and preventing ASD represents a paradigm shift in autism treatment, paving the alternative but efficient way for clinical interventions in neurological conditions.

Extracellular vesicles in neurodegenerative, mental, and other neurological disorders: Perspectives into mechanisms, biomarker potential, and therapeutic implications

Extracellular vesicles (EVs) are produced, secreted, and targeted by most human cells, including cells that compose nervous system tissues. EVs carry several types of biomolecules, such as lipids, proteins and microRNA, and can function as signaling agents in physiological and pathological processes. In this chapter, we will focus on EVs and their cargo secreted by brain cells, especially neurons and glia, and how these aspects are affected in pathological conditions. The chapter covers neurodegenerative disorders, including Alzheimer's disease, Parkinson's disease and amyotrophic lateral sclerosis, as well as several psychiatric disorders, namely schizophrenia, autism spectrum disorder and major depressive disorder. This chapter also addresses other types of neurological dysfunctions, epilepsy and traumatic brain injury. EVs can cross the blood brain barrier, and thus brain EVs may be detected in more accessible peripheral tissue, such as circulating blood. Alterations in EV composition and contents can therefore impart valuable clues into the molecular etiology of these disorders, and serve biomarkers regarding disease prevalence, progression and treatment. EVs can also be used to carry drugs and biomolecules into brain tissue, considered as a promising drug delivery agent for neurological diseases. Therefore, although this area of research is still in its early development, it offers great potential in further elucidating and in treating neurological disorders.

AUTS2 disruption causes neuronal differentiation defects in human cerebral organoids through hyperactivation of the WNT/β-catenin pathway

Individuals with the Autism Susceptibility Candidate 2 (AUTS2) gene disruptions exhibit symptoms such as intellectual disability, microcephaly, growth retardation, and distinct skeletal and facial differences. The role of AUTS2 in neurodevelopment has been investigated using animal and embryonic stem cell models. However, the precise molecular mechanisms of how AUTS2 influences neurodevelopment, particularly in humans, are not thoroughly understood. Our study employed a 3D human cerebral organoid culture system, in combination with genetic, genomic, cellular, and molecular approaches, to investigate how AUTS2 impacts neurodevelopment through cellular signaling pathways. We used CRISPR/Cas9 technology to create AUTS2-deficient human embryonic stem cells and then generated cerebral organoids with these cells. Our transcriptomic analyses revealed that the absence of AUTS2 in cerebral organoids reduces the populations of cells committed to the neuronal lineage, resulting in an overabundance of cells with a transcription profile resembling that of choroid plexus (ChP) cells. Intriguingly, we found that AUTS2 negatively regulates the WNT/β-catenin signaling pathway, evidenced by its overactivation in AUTS2-deficient cerebral organoids and in luciferase reporter cells lacking AUTS2. Importantly, treating the AUTS2-deficient cerebral organoids with a WNT inhibitor reversed the overexpression of ChP genes and increased the downregulated neuronal gene expression. This study offers new insights into the role of AUTS2 in neurodevelopment and suggests potential targeted therapies for neurodevelopmental disorders.

The neocortical infrastructure for language involves region-specific patterns of laminar gene expression

The language network of the human brain has core components in the inferior frontal cortex and superior/middle temporal cortex, with left-hemisphere dominance in most people. Functional specialization and interconnectivity of these neocortical regions is likely to be reflected in their molecular and cellular profiles. Excitatory connections between cortical regions arise and innervate according to layer-specific patterns. Here, we generated a gene expression dataset from human postmortem cortical tissue samples from core language network regions, using spatial transcriptomics to discriminate gene expression across cortical layers. Integration of these data with existing single-cell expression data identified 56 genes that showed differences in laminar expression profiles between the frontal and temporal language cortex together with upregulation in layer II/III and/or layer V/VI excitatory neurons. Based on data from large-scale genome-wide screening in the population, DNA variants within these 56 genes showed set-level associations with interindividual variation in structural connectivity between the left-hemisphere frontal and temporal language cortex, and with the brain-related disorders dyslexia and schizophrenia which often involve affected language. These findings identify region-specific patterns of laminar gene expression as a feature of the brain's language network.

cytoKernel: Robust kernel embeddings for assessing differential expression of single cell data

High-throughput sequencing of single-cell data can be used to rigorously evlauate cell specification and enable intricate variations between groups or conditions. Many popular existing methods for differential expression target differences in aggregate measurements (mean, median, sum) and limit their approaches to detect only global differential changes. We present a robust method for differential expression of single-cell data using a kernel-based score test, cytoKernel. cytoKernel is specifically designed to assess the differential expression of single cell RNA sequencing and high-dimensional flow or mass cytometry data using the full probability distribution pattern. cytoKernel is based on kernel embeddings which employs the probability distributions of the single cell data, by calculating the pairwise divergence/distance between distributions of subjects. It can detect both patterns involving aggregate changes, as well as more elusive variations that are often overlooked due to the multimodal characteristics of single cell data. We performed extensive benchmarks across both simulated and real data sets from mass cytometry data and single-cell RNA sequencing. The cytoKernel procedure effectively controls the False Discovery Rate (FDR) and shows favourable performance compared to existing methods. The method is able to identify more differential patterns than existing approaches. We apply cytoKernel to assess gene expression and protein marker expression differences from cell subpopulations in various publicly available single-cell RNAseq and mass cytometry data sets. The methods described in this paper are implemented in the open-source R package cytoKernel, which is freely available from Bioconductor at http://bioconductor.org/packages/cytoKernel.

Cell type-specific dysregulation of gene expression due to Chd8 haploinsufficiency during mouse cortical development

Disruptive variants in the chromodomain helicase CHD8, which acts as a transcriptional regulator during neurodevelopment, are strongly associated with risk for autism spectrum disorder (ASD). Loss of CHD8 function is hypothesized to perturb gene regulatory networks in the developing brain, thereby contributing to ASD etiology. However, insight into the cell type-specific transcriptional effects of CHD8 loss of function remains limited. We used single-cell and single-nucleus RNA-sequencing to globally profile gene expression and identify dysregulated genes in the embryonic and juvenile wild type and Chd8 +/- mouse cortex, respectively. Chd8 and other ASD risk-associated genes showed a convergent expression trajectory that was largely conserved between the mouse and human developing cortex, increasing from the progenitor zones to the cortical plate. Genes associated with risk for neurodevelopmental disorders and genes involved in neuron projection development, chromatin remodeling, signaling, and migration were dysregulated in Chd8 +/- embryonic day (E) 12.5 radial glia. Genes implicated in synaptic organization and activity were dysregulated in Chd8 +/- postnatal day (P) 25 deep- and upper-layer excitatory cortical neurons, suggesting a delay in synaptic maturation or impaired synaptogenesis due to CHD8 loss of function. Our findings reveal a complex pattern of transcriptional dysregulation in Chd8 +/- developing cortex, potentially with distinct biological impacts on progenitors and maturing neurons in the excitatory neuronal lineage.

Proximity analysis of native proteomes reveals phenotypic modifiers in a mouse model of autism and related neurodevelopmental conditions

One of the main drivers of autism spectrum disorder is risk alleles within hundreds of genes, which may interact within shared but unknown protein complexes. Here we develop a scalable genome-editing-mediated approach to target 14 high-confidence autism risk genes within the mouse brain for proximity-based endogenous proteomics, achieving the identification of high-specificity spatial proteomes. The resulting native proximity proteomes are enriched for human genes dysregulated in the brain of autistic individuals, and reveal proximity interactions between proteins from high-confidence risk genes with those of lower-confidence that may provide new avenues to prioritize genetic risk. Importantly, the datasets are enriched for shared cellular functions and genetic interactions that may underlie the condition. We test this notion by spatial proteomics and CRISPR-based regulation of expression in two autism models, demonstrating functional interactions that modulate mechanisms of their dysregulation. Together, these results reveal native proteome networks in vivo relevant to autism, providing new inroads for understanding and manipulating the cellular drivers underpinning its etiology.

Cell-type-specific effects of autism-associated 15q duplication syndrome in the human brain

Recurrent copy-number variation represents one of the most well-established genetic drivers in neurodevelopmental disorders, including autism spectrum disorder. Duplication of 15q11-q13 (dup15q) is a well-described neurodevelopmental syndrome that increases the risk of autism more than 40-fold. However, the effects of this duplication on gene expression and chromatin accessibility in specific cell types in the human brain remain unknown. To identify the cell-type-specific transcriptional and epigenetic effects of dup15q in the human frontal cortex, we conducted single-nucleus RNA sequencing and multi-omic sequencing on dup15q-affected individuals (n = 6) as well as individuals with non-dup15q autism (n = 7) and neurotypical control individuals (n = 7). Cell-type-specific differential expression analysis identified significantly regulated genes, critical biological pathways, and differentially accessible genomic regions. Although there was overall increased gene expression across the duplicated genomic region, cellular identity represented an important factor mediating gene-expression changes. As compared to other cell types, neuronal subtypes showed greater upregulation of gene expression across a critical region within the duplication. Genes that fell within the duplicated region and had high baseline expression in control individuals showed only modest changes in dup15q, regardless of cell type. Of note, dup15q and autism had largely distinct signatures of chromatin accessibility but shared the majority of transcriptional regulatory motifs, suggesting convergent biological pathways. However, the transcriptional binding-factor motifs implicated in each condition implicated distinct biological mechanisms: neuronal JUN and FOS networks in autism vs. an inflammatory transcriptional network in dup15q microglia. This work provides a cell-type-specific analysis of how dup15q changes gene expression and chromatin accessibility in the human brain, and it finds evidence of marked cell-type-specific effects of this genetic driver. These findings have implications for guiding therapeutic development in dup15q syndrome, as well as understanding the functional effects of copy-number variants more broadly in neurodevelopmental disorders.

Rapid Screening of Biomarkers in KYSE-150 Cells Exposed to Polycyclic Aromatic Hydrocarbons via Inkjet Printing Single-Cell Mass Spectrometry

Single-cell analysis by mass spectrometry (MS) is emerging as a powerful tool that not only contributes to cellular heterogeneity but also offers an unprecedented opportunity to predict pathology onset and facilitates novel biomarker discovery. However, the development of single-cell MS analysis techniques with a focus on sample extraction, separation, and ionization methods for volume-limited samples and complexity of cellular samples are still a big challenge. In this study, we present a high-throughput approach to inkjet drop on demand printing single-cell MS for rapid screening of biomarkers of polycyclic aromatic hydrocarbon (PAH) exposure at the KYSE-150 cell, aiming to elucidate the pathogenesis of PAH-induced esophageal cancer. With an analytical bulk KYSE-150 cell throughput of up to 51 cells per minute, the method provides a new opportunity for simultaneous single-cell analysis of multiple biomarkers. We screened 930 characteristic ions from 3,683 detected peak signals and identified 91 distinctive molecules that exhibited significant differences under various concentrations of PAH exposure. These molecules have potential as clinical diagnostic biomarkers. Additionally, the current study identifies specific biomarkers that behave completely opposite in single-cell and multicell lipidomics as the concentration of PAH changes. These biomarkers potentially subdivide KYSE-150 cells into PAH-sensitive and PAH-insensitive types, providing a basis for revealing PAH toxicity and disease pathogenesis from the heterogeneity of cellular metabolism.

BLEND: Probabilistic Cellular Deconvolution with Automated Reference Selection

Cellular deconvolution aims to estimate cell type fractions from bulk transcriptomic and other omics data. Most existing deconvolution methods fail to account for the heterogeneity in cell type-specific (CTS) expression across bulk samples, ignore discrepancies between CTS expression in bulk and cell type reference data, and provide no guidance on cell type reference selection or integration. To address these issues, we introduce BLEND, a hierarchical Bayesian method that leverages multiple reference datasets. BLEND learns the most suitable references for each bulk sample by exploring the convex hulls of references and employs a "bag-of-words" representation for bulk count data for deconvolution. To speed up the computation, we provide an efficient EM algorithm for parameter estimation. Notably, BLEND requires no data transformation, normalization, cell type marker gene selection, or reference quality evaluation. Benchmarking studies on both simulated and real human brain data highlight BLEND's superior performance in various scenarios. The analysis of Alzheimer's disease data illustrates BLEND's application in real data and reference resource integration.

The neuroanatomical organization of the hypothalamus is driven by spatial and topological efficiency

The hypothalamus in the mammalian brain is responsible for regulating functions associated with survival and reproduction representing a complex set of highly interconnected, yet anatomically and functionally distinct, sub-regions. It remains unclear what factors drive the spatial organization of sub-regions within the hypothalamus. One potential factor may be structural connectivity of the network that promotes efficient function with well-connected sub-regions placed closer together geometrically, i.e., the strongest axonal signal transferred through the shortest geometrical distance. To empirically test for such efficiency, we use hypothalamic data derived from the Allen Mouse Brain Connectivity Atlas, which provides a structural connectivity map of mouse brain regions derived from a series of viral tracing experiments. Using both cost function minimization and comparison with a weighted, sphere-packing ensemble, we demonstrate that the sum of the distances between hypothalamic sub-regions are not close to the minimum possible distance, consistent with prior whole brain studies. However, if such distances are weighted by the inverse of the magnitude of the connectivity, their sum is among the lowest possible values. Specifically, the hypothalamus appears within the top 94th percentile of neural efficiencies of randomly packed configurations and within one standard deviation of the median efficiency when packings are optimized for maximal neural efficiency. Our results, therefore, indicate that a combination of geometrical and topological constraints help govern the structure of the hypothalamus.