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

Neuroimaging endophenotypes reveal underlying mechanisms and genetic factors contributing to progression and development of four brain disorders

Recent work leveraging artificial intelligence has offered promise to dissect disease heterogeneity by identifying complex intermediate brain phenotypes, called dimensional neuroimaging endophenotypes (DNEs). We advance the argument that these DNEs capture the degree of expression of respective neuroanatomical patterns measured, offering a dimensional neuroanatomical representation for studying disease heterogeneity and similarities of neurologic and neuropsychiatric diseases. We investigate the presence of nine DNEs derived from independent yet harmonized studies on Alzheimer's disease, autism spectrum disorder, late-life depression and schizophrenia in the UK Biobank study. Phenome-wide associations align with genome-wide associations, revealing 31 genomic loci (P < 5 × 10-8/9) associated with the nine DNEs. The nine DNEs, along with their polygenic risk scores, significantly enhanced the predictive accuracy for 14 systemic disease categories, particularly for conditions related to mental health and the central nervous system, as well as mortality outcomes. These findings underscore the potential of the nine DNEs to capture the expression of disease-related brain phenotypes in individuals of the general population and to relate such measures with genetics, lifestyle factors and chronic diseases.

Cognitive and Synaptic Impairment Induced by Deficiency of Autism Risk Gene Smarcc2 and its Rescue by Histone Deacetylase Inhibition

SMARCC2 , which encodes BAF170, a core subunit of chromatin remodeling BAF complex, is one of the top-ranking risk genes for autism spectrum disorder (ASD). However, the mechanisms linking SMARCC2 haploinsufficiency to ASD remain poorly understood. Genome-wide RNA-seq analysis revealed that SMARCC2 was significantly diminished in iPSC-derived neurons from idiopathic ASD patients. ChIP-seq of SMARCC2 demonstrated its binding to many other ASD risk genes involved in transcriptional regulation. Smarcc2 deficiency in prefrontal cortex (PFC) of adolescent mice led to impaired working memory, with largely intact social and anxiety-like behaviors. Significant downregulation of genes enriched in synaptic transmission were found in PFC of S marcc2 -deficient mice by RNA-seq and qPCR profiling. In parallel, electrophysiological recordings uncovered the significant impairment of GABAergic and glutamatergic synaptic currents in S marcc2 -deficient PFC pyramidal neurons. Smarcc2 bound to HDAC2, and Smarcc2 deficiency led to the reduced global histone acetylation and H3K9ac enrichment at synaptic gene Slc1a3 (EAAT1), Slc6a1 (GAT1), and Slc32a1 (VGAT) promoters. Treatment of S marcc2 -deficient mice with romidepsin, a class I HDAC inhibitor, restored histone acetylation, working memory and some synaptic gene expression. These findings highlight the critical role of Smarcc2 in regulating cognitive and synaptic function, suggesting that targeting HDAC could alleviate deficits in Smarcc2-associated neurodevelopmental disorders.

Alternative splicing in autism spectrum disorder: Recent insights from mechanisms to therapy

Alternative splicing (AS) is a vital and highly dynamic RNA regulatory mechanism that allows a single gene to generate multiple mRNA and protein isoforms. Dysregulation of AS has been identified as a key contributor to the pathogenesis of autism spectrum disorders (ASD). A comprehensive understanding of aberrant splicing mechanisms and their functional consequences in ASD can help uncover the molecular basis of the disorder and facilitate the development of therapeutic strategies. This review focuses on the major aberrant splicing events and key splicing regulators associated with ASD, highlighting their roles in linking defective splicing to ASD pathogenesis. In addition, a discussion of how emerging technologies, such as long-read sequencing, single-cell sequencing, spatial transcriptomics and CRISPR-Cas systems are offering novel insights into the role and mechanisms of AS in ASD is presented. Finally, the RNA splicing-based therapeutic strategies are evaluated, emphasizing their potential to address unmet clinical needs in ASD treatment.

Understanding autism: Causes, diagnosis, and advancing therapies

Autism Spectrum Disorder (ASD) is a neurodevelopmental condition marked by difficulties in social communication, languages, and repetitive behaviors. Its rising prevalence has made it a critical global public health issue. ASD is believed to arise from a combination of genetic and environmental influences. While some gene mutations associated with ASD have been identified, most cases lack clear genetic explanations. Evidence increasingly points to early-life environmental factors as key contributors to ASD, including advanced parental age, maternal diabetes during pregnancy, infections, hormonal imbalances, certain medications, and exposure to air pollution. Currently, ASD diagnosis relies on behavioral assessments, but the absence of specific molecular biomarkers poses significant obstacles to early detection and targeted therapies. Encouragingly, research has identified potential biomarkers, such as neuroimaging classifiers, electroencephalography patterns, eye-tracking data, digital analytics, gene expression profiles, inflammatory and chemokine markers, proteomic and metabolomic profiles, and gut microbiota characteristics. Potential therapeutical strategies under investigation include digital therapies, non-invasive brain stimulation, antioxidants, oxytocin, AVPR1a antagonists, PPAR agonists, and mTOR inhibitors. This review explores ASD across five areas: epidemiological trends, genetic mechanisms, early-life environmental factors and their potential roles, diagnostic biomarkers, and therapeutic approaches.

ASiDentify (ASiD): a machine learning model to predict new autism spectrum disorder risk genes

Autism spectrum disorder (ASD) is a neurodevelopmental disorder that affects nearly 3% of children and has a strong genetic component. While hundreds of ASD risk genes have been identified through sequencing studies, the genetic heterogeneity of ASD makes identifying additional risk genes using these methods challenging. To predict candidate ASD risk genes, we developed a simple machine learning model, ASiDentify (ASiD), using human genomic, RNA- and protein-based features. ASiD identified over 1,300 candidate ASD risk genes, over 300 of which have not been previously predicted. ASiD made accurate predictions of ASD risk genes using 6 features predictive of ASD risk gene status, including mutational constraint, synapse localization and gene expression in neurons, astrocytes and non-brain tissues. Particular functional groups of proteins found to be strongly implicated in ASD include RNA-binding proteins (RBPs) and chromatin regulators. We constructed additional logistic regression models to make predictions and assess informative features specific to RBPs, including mutational constraint, or chromatin regulators, for which both expression level in excitatory neurons and mutational constraint were informative. The fact that RBPs and chromatin regulators had informative features distinct from all protein-coding genes suggests that specific biological pathways connect risk genes with different molecular functions to ASD.

A practical guide for single-cell transcriptome data analysis in neuroscience

Single-cell RNA sequencing (scRNA-seq) has revolutionized our ability to analyze gene expression at the single-cell level, providing unprecedented insights into cellular heterogeneity, rare cell populations, and dynamic cellular processes. In neuroscience, scRNA-seq has enabled the identification of diverse brain cell types, elucidation of developmental pathways, and discovery of mechanisms underlying neurological diseases. This tutorial provides a practical guide to scRNA-seq data analysis in neuroscience, focusing on the essential workflows and theoretical foundations. Key steps covered include quality control, data preprocessing, integration, cell clustering, and differential expression analysis. Using the Seurat R package, the tutorial demonstrates a comparative analysis approach for identifying differentially expressed genes between conditions, emphasizing the biological interpretation of results. By addressing the unique challenges of scRNA-seq data and illustrating methods for robust analysis, this work aims to enhance the reliability and reproducibility of scRNA-seq studies in neuroscience, supporting the exploration of cellular mechanisms and advancing research into brain function and disease.

Overgrowth-intellectual disability disorders: progress in biology, patient advocacy and innovative therapies

Overgrowth-intellectual disability (OGID) syndromes encompass a group of rare neurodevelopmental disorders that frequently share common clinical presentations. Although the genetic causes of many OGID syndromes are now known, we lack a clear mechanistic understanding of how such variants disrupt developmental processes and ultimately culminate in overgrowth and neurological symptoms. Patient advocacy groups, such as the Overgrowth Syndromes Alliance (OSA), are mobilising patients, families, clinicians and researchers to work together towards a deeper understanding of the clinical needs of patients with OGID, as well as to understand the fundamental biology of the relevant genes, with the goal of developing treatments. In this Review, we summarise three OGID syndromes encompassed by the OSA, namely Sotos syndrome, Malan syndrome and Tatton-Brown-Rahman syndrome. We discuss similarities and differences in the biology behind each disorder and explore future approaches that could potentially provide a way to ameliorate some of the unmet clinical needs of patients with OGID.

The "don't eat me" signal CD47 is associated with microglial phagocytosis defects and autism-like behaviors in 16p11.2 deletion mice

Various pathological characteristics of autism spectrum disorder (ASD) stem from abnormalities in brain resident immune cells, specifically microglia, to prune unnecessary synapses or neural connections during early development. Animal models of ASD exhibit an abundance of synapses in different brain regions, which is strongly linked to the appearance of ASD behaviors. Overexpression of CD47 on neurons acts as a "don't eat me" signal, safeguarding synapses from inappropriate pruning by microglia. Indeed, CD47 overexpression occurs in 16p11.2 deletion carriers, causing decreased synaptic phagocytosis and the manifestation of ASD characteristics. However, the role of CD47 in synaptic pruning impairment leading to ASD phenotypes in the 16p11.2 deletion mouse model is unclear. Moreover, whether blocking CD47 can alleviate ASD mice's behavioral deficits remains unknown. Here, we demonstrate a strong link between increased CD47 expression, decreased microglia phagocytosis capacity, and increased impairment in social novelty preference in the 16p11.2 deletion mice. The reduction in microglia phagocytosis caused a rise in excitatory synapses and transmission in the prefrontal cortex of 16p11.2 deletion mice. Importantly, blocking CD47 using a specific CD47 antibody or reducing CD47 expression using a specific short hairpin RNA (shRNA) enhanced the microglia phagocytosis and reduced excitatory transmission. Reduction in CD47 expression improved social novelty preference deficits in 16p11.2 mice. These findings demonstrate that CD47 is associated with the ASD phenotypes in the 16p11.2 deletion mice and could be a promising target for the development of treatment for ASD.

Simultaneous CRISPR screening and spatial transcriptomics reveal intracellular, intercellular, and functional transcriptional circuits

Pooled optical screens have enabled the study of cellular interactions, morphology, or dynamics at massive scale, but they have not yet leveraged the power of highly plexed single-cell resolved transcriptomic readouts to inform molecular pathways. Here, we present a combination of imaging spatial transcriptomics with parallel optical detection of in situ amplified guide RNAs (Perturb-FISH). Perturb-FISH recovers intracellular effects that are consistent with single-cell RNA-sequencing-based readouts of perturbation effects (Perturb-seq) in a screen of lipopolysaccharide response in cultured monocytes, and it uncovers intercellular and density-dependent regulation of the innate immune response. Similarly, in three-dimensional xenograft models, Perturb-FISH identifies tumor-immune interactions altered by genetic knockout. When paired with a functional readout in a separate screen of autism spectrum disorder risk genes in human-induced pluripotent stem cell (hIPSC) astrocytes, Perturb-FISH shows common calcium activity phenotypes and their associated genetic interactions and dysregulated molecular pathways. Perturb-FISH is thus a general method for studying the genetic and molecular associations of spatial and functional biology at single-cell resolution.

Single-cell technology grows up: Leveraging high-resolution omics approaches to understand neurodevelopmental disorders

The identification of hundreds of neurodevelopmental disorder (NDD) genes in the last decade led to numerous genetic models for understanding NDD gene mutation consequences and delineating putative neurobiological mediators of disease. In parallel, single-cell and single-nucleus genomic technologies have been developed and implemented to create high-resolution atlases of cell composition, gene expression, and circuit connectivity in the brain. Here, we discuss the opportunities to leverage mutant models (or human tissue, where available) and genomics approaches to systematically define NDD etiology at cellular resolution. We review progress in applying single-cell and spatial transcriptomics to interrogate developmental trajectories, cellular composition, circuit activity, and connectivity across human tissue and NDD models. We discuss considerations for implementing these approaches at scale to maximize insights and facilitate reproducibility. Finally, we highlight how standardized application of these technologies promises to not only define etiologies of individual disorders but also identify molecular, cellular, and circuit level convergence across NDDs.

Multiomic single-cell profiling identifies critical regulators of postnatal brain

Human brain development spans from embryogenesis to adulthood, with dynamic gene expression controlled by cell-type-specific cis-regulatory element activity and three-dimensional genome organization. To advance our understanding of postnatal brain development, we simultaneously profiled gene expression and chromatin accessibility in 101,924 single nuclei from four brain regions across ten donors, covering five key postnatal stages from infancy to late adulthood. Using this dataset and chromosome conformation capture data, we constructed enhancer-based gene regulatory networks to identify cell-type-specific regulators of brain development and interpret genome-wide association study loci for ten main brain disorders. Our analysis connected 2,318 cell-specific loci to 1,149 unique genes, representing 41% of loci linked to the investigated traits, and highlighted 55 genes influencing several disease phenotypes. Pseudotime analysis revealed distinct stages of postnatal oligodendrogenesis and their regulatory programs. These findings provide a comprehensive dataset of cell-type-specific gene regulation at critical timepoints in postnatal brain development.

A general principle of neuronal evolution reveals a human-accelerated neuron type potentially underlying the high prevalence of autism in humans

The remarkable ability of a single genome sequence to encode a diverse collection of distinct cell types, including the thousands of cell types found in the mammalian brain, is a key characteristic of multicellular life. While it has been observed that some cell types are far more evolutionarily conserved than others, the factors driving these differences in evolutionary rate remain unknown. Here, we hypothesized that highly abundant neuronal cell types may be under greater selective constraint than rarer neuronal types, leading to variation in their rates of evolution. To test this, we leveraged recently published cross-species single-nucleus RNA-sequencing datasets from three distinct regions of the mammalian neocortex. We found a strikingly consistent relationship where more abundant neuronal subtypes show greater gene expression conservation between species, which replicated across three independent datasets covering >106 neurons from six species. Based on this principle, we discovered that the most abundant type of neocortical neurons-layer 2/3 intratelencephalic excitatory neurons-has evolved exceptionally quickly in the human lineage compared to other apes. Surprisingly, this accelerated evolution was accompanied by the dramatic down-regulation of autism-associated genes, which was likely driven by polygenic positive selection specific to the human lineage. In sum, we introduce a general principle governing neuronal evolution and suggest that the exceptionally high prevalence of autism in humans may be a direct result of natural selection for lower expression of a suite of genes that conferred a fitness benefit to our ancestors while also rendering an abundant class of neurons more sensitive to perturbation.

Astrocytic-supplied cholesterol drives synaptic gene expression programs in developing neurons and downstream astrocytic transcriptional programs

Astrocytes participate in neuronal synaptic programs that are enriched for genetic associations in schizophrenia and autism spectrum disorders (ASD). To better understand how these co-regulated cellular programs are induced during early neuronal development, we studied astrocytes and iPSC-derived neurons in co-cultures and mono-cultures at 16 time points spanning 0.5 hours to 8 days. We found that upregulation in astrocytes of genes involved in cholesterol biosynthesis preceded the activation of synaptic gene programs in neurons and upregulation of the astrocytic Nrxn1. Neuronal knockdown of key cholesterol receptors led to downregulation of neuronal synaptic genes and induced a robust transcriptional response in the astrocytes, including further upregulation of Nrxn1. This suggests that astrocyte-supplied cholesterol drives these neuronal changes and that bi-directional signalling is occuring. The genes upregulated in neurons were enriched for deleterious variants in schizophrenia and neurodevelopmental disorders, suggesting that their pathogenic effect may be, in part, mediated by reduced buffering capacity for changes in the astrocyte cholesterol supply to neurons. These findings highlight the critical role of astrocyte-neuron interactions in psychiatric and neurodevelopmental disorders, particularly in relation to lipid metabolism and synaptic plasticity.

Chromatin accessibility provides a window into the genetic etiology of human brain disease

Neuropsychiatric and neurodegenerative diseases have a significant genetic component. Risk variants often affect the noncoding genome, altering cis-regulatory elements (CREs) and chromatin structure, ultimately impacting gene expression. Chromatin accessibility profiling methods, especially assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq), have been used to pinpoint disease-associated SNPs and link them to affected genes and cell types in the brain. The integration of single-cell technologies with genome-wide association studies (GWAS) and transcriptomic data has further advanced our understanding of cell-specific chromatin dynamics. This review discusses recent findings regarding the role played by chromatin accessibility in brain disease, highlighting the need for high-quality data and rigorous computational tools. Future directions include spatial chromatin studies and CRISPR-based functional validation to bridge genetic discovery and clinical applications, paving the way for targeted gene-regulatory therapies.

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.

Unraveling pathogenesis and potential biomarkers for autism spectrum disorder associated with HIF1A pathway based on machine learning and experiment validation

BACKGROUND

Autism spectrum disorder (ASD) is a neurodevelopmental disorder with a high social burden and limited treatments. Hypoxic condition of the brain is considered an important pathological mechanism of ASD. HIF1A is a key participant in brain hypoxia, but its contribution to the pathophysiological landscape of ASD remains unclear.

METHODS

ASD-related datasets were obtained from GEO database, and HIF1A-related genes from GeneCards. Co-expression module analysis identified module genes, which were intersected with HIF1A-related genes to identify common genes. Machine learning identified hub genes from intersection genes and PPI networks were constructed to explore relationships among hub and HIF1A. Single-cell RNA sequencing analyzed hub gene distribution across cell clusters. ASD mouse model was created by inducing maternal immune activation (MIA) with poly(I:C) injections, verified through behavioral tests. Validation of HIF1A pathway and hub genes was confirmed through Western Blot, qPCR, and immunofluorescence in ASD mice and microglia BV-2 cells.

RESULTS

Using CEMiTool and GeneCards, 45 genes associated with ASD and HIF1A pathway were identified. Machine learning identified CDKN1A, ETS2, LYN, and SLC16A3 as potential ASD diagnostic markers. Single-cell sequencing pinpointed activated microglia as key immune cells. Behavioral tests showed MIA offspring mice exhibited typical ASD-like behaviors. Immunofluorescence confirmed the activation of microglia and HIF1A pathway in frontal cortex of ASD mice. Additionally, IL-6 contributed to ASD by activating JUN/HIF1A pathway, affecting CDKN1A, LYN, and SLC16A3 expression in microglia.

CONCLUSIONS

HIF1A-related genes CDKN1A, ETS2, LYN, and SLC16A3 are strong diagnostic markers for ASD and the activation of IL-6/JUN/HIF1A pathway in microglia contributes to the pathogenesis of ASD.

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.

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.

Deciphering autism heterogeneity: a molecular stratification approach in four mouse models

Autism spectrum disorder (ASD) is a complex neurodevelopmental condition characterized by impairments in social interaction and communication, as well as restrained or stereotyped behaviors. The inherent heterogeneity within the autism spectrum poses challenges for developing effective pharmacological treatments targeting core features. Successful clinical trials require the identification of robust markers to enable patient stratification. In this study, we identified molecular markers within the oxytocin and immediate early gene families across five interconnected brain structures of the social circuit. We used wild-type and four heterogeneous mouse models, each exhibiting unique autism-like behaviors modeling the autism spectrum. While dysregulations in the oxytocin family were model-specific, immediate early genes displayed widespread alterations, reflecting global changes across the four models. Through integrative analysis, we identified Egr1, Foxp1, Homer1a, Oxt, and Oxtr as five robust and discriminant molecular markers that allowed the successful stratification of the four models. Importantly, our stratification demonstrated predictive values when challenged with a fifth mouse model or identifying subgroups of mice potentially responsive to oxytocin treatment. Beyond providing insights into oxytocin and immediate early gene mRNA dynamics, this proof-of-concept study represents a significant step toward the potential stratification of individuals with ASD. This work has implications for the success of clinical trials and the development of personalized medicine in autism.

Cross-disorder and disease-specific pathways in dementia revealed by single-cell genomics

The development of successful therapeutics for dementias requires an understanding of their shared and distinct molecular features in the human brain. We performed single-nuclear RNA-seq and ATAC-seq in Alzheimer's disease (AD), frontotemporal dementia (FTD), and progressive supranuclear palsy (PSP), analyzing 41 participants and ∼1 million cells (RNA + ATAC) from three brain regions varying in vulnerability and pathological burden. We identify 32 shared, disease-associated cell types and 14 that are disease specific. Disease-specific cell states represent glial-immune mechanisms and selective neuronal vulnerability impacting layer 5 intratelencephalic neurons in AD, layer 2/3 intratelencephalic neurons in FTD, and layer 5/6 near-projection neurons in PSP. We identify disease-associated gene regulatory networks and cells impacted by causal genetic risk, which differ by disorder. These data illustrate the heterogeneous spectrum of glial and neuronal compositional and gene expression alterations in different dementias and identify therapeutic targets by revealing shared and disease-specific cell states.

The gut microbiota-oligodendrocyte axis: A promising pathway for modulating oligodendrocyte homeostasis and demyelination-associated disorders

The bidirectional regulation between the gut microbiota and brain, known as gut-brain axis, has received significant attention. The myelin sheath, produced by oligodendrocytes or Schwann cells, is essential for efficient nervous signal transmission and the maintenance of brain function. Growing evidence shows that both oligodendrogenesis and myelination are modulated by gut microbiota and its metabolites, and when dysbiosis occurs, changes in the microbiota composition and/or associated metabolites may impact developmental myelination and the occurrence of neurodevelopmental disabilities. Although the link between the microbiota and demyelinating disease such as multiple sclerosis has been extensively studied, our knowledge about the role of the microbiota in other myelin-related disorders, such as neurodegenerative diseases, is limited. Mechanistically, the microbiota-oligodendrocyte axis is primarily mediated by factors such as inflammation, the vagus nerve, endocrine hormones, and microbiota metabolites as evidenced by metagenomics, metabolomics, vagotomy, and morphological and molecular approaches. Treatments targeting this axis include probiotics, prebiotics, microbial metabolites, herbal bioactive compounds, and specific dietary management. In addition to the commonly used approaches, viral vector-mediated tracing and gene manipulation, integrated multiomics and multicenter clinical trials will greatly promote the mechanistic and interventional studies and ultimately, the development of new preventive and therapeutic strategies against gut-oligodendrocyte axis-mediated brain impairments. Interestingly, recent findings showed that microbiota dysbiosis can be induced by hippocampal myelin damage and is reversible by myelin-targeted drugs, which provides new insights into understanding how hippocampus-based functional impairment (such as in neurodegenerative Alzheimer's disease) regulates the peripheral homeostasis of microbiota and associated systemic disorders.

A scalable, high-throughput neural development platform identifies shared impact of ASD genes on cell fate and differentiation

Background

Deleterious mutations in hundreds of genes confer high risk for neurodevelopmental disorders (NDDs), posing significant challenges for therapeutic development. Identifying convergent pathways shared across NDD genes could reveal high-impact therapeutic targets.

Methods

To identity convergent pathways in NDD genes, we optimized Perturb-seq, a method combining CRISPR perturbation with single-cell RNA sequencing (scRNA-seq), and applied structural topic modeling (STM) to simultaneously assess impact on cell fate and developmental stage. We then studied a subset of autism spectrum disorder (ASD) genes implicated in regulation of gene expression using these improved molecular and analytical approaches.

Results

Results from targeting 60 high-confidence ASD risk genes revealed significant effects on neural development. As expected, ASD risk genes impacted both progenitor fate and/or neuronal differentiation. Using STM, we could identify latent topics jointly capturing cell types, cell fate, and differentiation stages. Repression of ASD risk genes led to changes in topic proportions and effects of four genes (DEAF1, KMT2A, MED13L, and MYT1L) were validated in an independent dataset.

Conclusions

Our optimized Perturb-seq method, combined with a novel analytical approach, provides a powerful, cost-effective framework for uncovering convergent mechanisms among genes involved in complex neurodevelopmental processes. Application of these methods advanced understanding of the impact of ASD mutations on multiple dimensions of neural development, and provides a framework for a broader examination of the function of NDD risk genes.

Dynamic convergence of autism disorder risk genes across neurodevelopment

Over a hundred risk genes underlie risk for autism spectrum disorder (ASD) but the extent to which they converge on shared downstream targets to increase ASD risk is unknown. To test the hypothesis that cellular context impacts the nature of convergence, here we apply a pooled CRISPR approach to target 29 ASD loss-of-function genes in human induced pluripotent stem cell (hiPSC)-derived neural progenitor cells, glutamatergic neurons, and GABAergic neurons. Two distinct approaches (gene-level and network-level analyses) demonstrate that convergence is greatest in mature glutamatergic neurons. Convergent effects are dynamic, varying in strength, composition, and biological role between cell types, increasing with functional similarity of the ASD genes examined, and driven by cell-type-specific gene co-expression patterns. Stratification of ASD genes yield targeted drug predictions capable of reversing gene-specific convergent signatures in human cells and ASD-related behaviors in zebrafish. Altogether, convergent networks downstream of ASD risk genes represent novel points of individualized therapeutic intervention.

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.

Single-cell atlas of ABCA7 loss-of-function reveals impaired neuronal respiration via choline-dependent lipid imbalances

Loss-of-function (LoF) variants in the lipid transporter ABCA7 significantly increase the risk of Alzheimer's disease (odds ratio ∼2), yet the pathogenic mechanisms and the neural cell types affected by these variants remain largely unknown. Here, we performed single-nuclear RNA sequencing of 36 human post-mortem samples from the prefrontal cortex of 12 ABCA7 LoF carriers and 24 matched non-carrier control individuals. ABCA7 LoF was associated with gene expression changes in all major cell types. Excitatory neurons, which expressed the highest levels of ABCA7, showed transcriptional changes related to lipid metabolism, mitochondrial function, cell cycle-related pathways, and synaptic signaling. ABCA7 LoF-associated transcriptional changes in neurons were similarly perturbed in carriers of the common AD missense variant ABCA7 p.Ala1527Gly (n = 240 controls, 135 carriers), indicating that findings from our study may extend to large portions of the at-risk population. Consistent with ABCA7's function as a lipid exporter, lipidomic analysis of isogenic iPSC-derived neurons (iNs) revealed profound intracellular triglyceride accumulation in ABCA7 LoF, which was accompanied by a relative decrease in phosphatidylcholine abundance. Metabolomic and biochemical analyses of iNs further indicated that ABCA7 LoF was associated with disrupted mitochondrial bioenergetics that suggested impaired lipid breakdown by uncoupled respiration. Treatment of ABCA7 LoF iNs with CDP-choline (a rate-limiting precursor of phosphatidylcholine synthesis) reduced triglyceride accumulation and restored mitochondrial function, indicating that ABCA7 LoF-induced phosphatidylcholine dyshomeostasis may directly disrupt mitochondrial metabolism of lipids. Treatment with CDP-choline also rescued intracellular amyloid β -42 levels in ABCA7 LoF iNs, further suggesting a link between ABCA7 LoF metabolic disruptions in neurons and AD pathology. This study provides a detailed transcriptomic atlas of ABCA7 LoF in the human brain and mechanistically links ABCA7 LoF-induced lipid perturbations to neuronal energy dyshomeostasis. In line with a growing body of evidence, our study highlights the central role of lipid metabolism in the etiology of Alzheimer's disease.