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

Psychiatric Genomics 2025: State of the Art and the Path Forward

Psychiatric genetics has evolved from candidate-gene studies to whole-genome sequencing efforts. With hundreds of disease-associated loci now identified, functional interpretation of the associated loci becomes the critical next step toward translational applications. The article discusses achievements, challenges, and opportunities in psychiatric genomics associated with complexity and heterogeneity. Brain expression quantitative trait loci, single-cell ribonucleic acid-sequence, and functional genomics technologies are highlighted. It also covers newly developed techniques with improved spatiotemporal resolution, quality and sensitivity, coupled with advanced analytical methods and artificial intelligence. The power of collaborative research and inclusion of diverse populations will ensure a bright future for precision psychiatry.

A Gene Cluster of Mitochondrial Complexes Contributes to the Cognitive Decline of COVID-19 Infection

"Brain fog," a persistent cognitive impairment syndrome, stands out as a significant neurological aftermath of coronavirus disease 2019 (COVID-19). Yet, the underlying mechanisms by which COVID-19 induces cognitive deficits remain elusive. In our study, we observed an upregulation in the expression of genes linked to the inflammatory response and oxidative stress, whereas genes associated with cognitive function were downregulated in the brains of patients infected with COVID-19. Through single-nucleus RNA sequencing (snRNA-seq) analysis, we found that COVID-19 infection triggers the immune responses in microglia and astrocytes and exacerbates oxidative stress in oligodendrocytes, oligodendrocyte progenitors (OPCs), and neurons. Further investigations revealed that COVID-19 infection elevates LUC7L2 expression, which inhibits mitochondrial oxidative phosphorylation (OXPHOS) and suppresses the expression of mitochondrial complex genes such as MT-ND1, MT-ND2, MT-ND3, MT-ND4L, MT-CYB, MT-CO3, and MT-ATP6. A holistic approach to protect mitochondrial complex function, rather than targeting a single molecular, should be an effective therapeutic strategy to prevent and treat the long-term consequences of "long COVID."

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.

Precision medicine in the pediatric and neonatal intensive care units through genomics

PURPOSE OF REVIEW

Genome-wide sequencing technologies have revolutionized the understanding of human disorders and advanced precision medicine, especially for pediatric disorders. Here, we discuss the utility of genomic technologies in advancing the care of children admitted to the pediatric and neonatal intensive care units.

RECENT FINDINGS

Rapid molecular diagnosis permitted by genomic medicine has yielded clinically actionable findings that influence decision-making and facilitate timely therapeutic interventions. Identifying a genetic association provides a causal anchor to understanding disease biology at the single nucleotide resolution, revealing hidden biological heterogeneity that may be obscured by traditional imaging, laboratory, and pathological workup. The importance of a genetic diagnosis is further highlighted by the promise of gene therapy to correct the underlying genetic perturbation, as evidenced by the recent emergence of FDA-approved gene therapies for childhood genetic conditions.

SUMMARY

We predict that whole-genome sequencing, in conjunction with other omic technologies, will become critical diagnostic adjuncts in the clinical workup of critically ill children.

Machine learning identification of enhancers in the rhesus macaque genome

Nonhuman primate (NHP) neuroanatomy and cognitive complexity make NHPs ideal models to study human neurobiology and disease. However, NHP circuit-function investigations are limited by the availability of molecular reagents that are effective in NHPs. This calls for reagent development approaches that prioritize NHPs. Therefore, we derived enhancers from the NHP genome. We defined cell-type-specific open chromatin regions (OCRs) in single-cell data from rhesus macaques. We trained machine-learning models to rank those OCRs according to their potential as cell-type-specific enhancers for cells in the dorsolateral prefrontal cortex (DLPFC). We packaged the top-ranked layer-3-pyramidal-neuron enhancer into AAV and injected it into the macaque DLPFC. Expression was mostly restricted to layers 2 and 3 and confirmed with light-driven activation of channelrhodopsin. These results provide a crucial tool for studying the causal functions of DLPFC and provide a roadmap for optimized gene delivery in primates.

Single-Nucleus Transcriptomics of the Nucleus Accumbens Reveals Cell-Type-Specific Dysregulation in Adolescent Macaques with Depressive-Like Behaviors

Adolescent depression is increasingly recognized as a serious mental health disorder with distinct clinical and molecular features. Using single-nucleus RNA sequencing, we identified cell-specific transcriptomic changes in the nucleus accumbens (NAc), particularly in astrocytes, of adolescent macaques exhibiting depressive-like behaviors. The level of diacylglycerol kinase beta was significantly reduced in neurons and glial cells of depressed macaques, while FKBP5 levels increased in glial cells. Disruption of GABAergic synapses and disruption of D-glutamine and D-glutamate metabolism were linked to depressive phenotypes in medium spiny neurons (MSNs) and subtypes of astrocytes. Communication pathways between astrocytes and D1/D2-MSNs were also disrupted, involving factors like bone morphogenetic protein-6 and Erb-B2 receptor tyrosine kinase-4. Bulk transcriptomic and proteomic analyses corroborated these findings, and FKBP5 upregulation was confirmed by qRT-PCR, western blotting, and immunofluorescence in the NAc of rats and macaques with chronic unpredictable mild stress. Our results highlight the specific roles of different cell types in adolescent depression in the NAc, offering potential targets for new antidepressant therapies.

Boosting 2-arachidonoylglycerol, but not N-acylethanolamine, ameliorates autism symptoms in VPA-exposed rats by modulating abnormal neuroinflammation

Research has implicated endocannabinoids (eCBs) as significant regulators of neuroinflammation that may contribute to autism spectrum disorder (ASD). This study investigated the effect of the main eCBs, namely N-acylethanolamine (NAE) and 2-arachidonoylglycerol (2-AG), on ASD and their underlying mechanisms through in vivo and in vitro experiments. Results showed that elevating NAE or 2-AG ameliorated social deficits and restricted and repetitive behaviors and corrected neuropathological damage. Additionally, enhancing 2-AG protected valproic acid (VPA)-exposed rats against nerve damage by modulating abnormal neuroinflammation, as evidenced by the fact that 2-AG decreased microglial reactivity with reduced pro-inflammatory responses and increased anti-inflammatory responses. While, NAE only had a subtle effect on regulating neuroinflammation. Collectively, these findings suggested that elevating both NAE and 2-AG could improve ASD symptoms. Elevating 2-AG may play a neuroprotective role by generating a reparative milieu reactive to abnormal neuroinflammation, but NAE does not. Therefore, eCBs may be a promising therapeutic target for ASD.

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.

Maternal COVID-19 infection associated with offspring neurodevelopmental disorders

Maternal COVID-19 infection increases the incidence of neurodevelopmental disorders (NDDs) in offspring, although the underlying mechanisms have not been elucidated. This study demonstrated that COVID-19 infection during pregnancy disrupted the balance of maternal and fetal immune environments, driving alterations in astrocytes, endothelial cells, and excitatory neurons. A risk score was established using 47 unique genes in the single-cell transcriptome of gestational mothers. The high risk score in CD4 proliferating T cell level served as an indicator for increased risk of offspring NDDs. Summary-based Mendelian randomization and phenome-wide association study analyses were conducted to identify the causal association of the transcriptional changes with the increased risk of offspring NDDs. Additionally, 10 drugs were identified as potential therapeutic candidates. Our findings support a model where the maternal COVID-19 infection changed the levels of CD4 proliferating T cells, leading to the alterations of astrocytes, endothelial cells, and excitatory neurons in offspring, contributing to the increased risk of NDDs in these individuals.

Deciphering the longitudinal trajectories of glioblastoma ecosystems by integrative single-cell genomics

The evolution of isocitrate dehydrogenase (IDH)-wildtype glioblastoma (GBM) after standard-of-care therapy remains poorly understood. Here we analyzed matched primary and recurrent GBMs from 59 patients using single-nucleus RNA sequencing and bulk DNA sequencing, assessing the longitudinal evolution of the GBM ecosystem across layers of cellular and molecular heterogeneity. The most consistent change was a lower malignant cell fraction at recurrence and a reciprocal increase in glial and neuronal cell types in the tumor microenvironment (TME). The predominant malignant cell state differed between most matched pairs, but no states were exclusive or highly enriched in either time point, nor was there a consistent longitudinal trajectory across the cohort. Nevertheless, specific trajectories were enriched in subsets of patients. Changes in malignant state abundances mirrored changes in TME composition and baseline profiles, reflecting the co-evolution of the GBM ecosystem. Our study provides a blueprint of GBM's diverse longitudinal trajectories and highlights the treatment and TME modifiers that shape them.

The multilayered transcriptional architecture of glioblastoma ecosystems

In isocitrate dehydrogenase wildtype glioblastoma (GBM), cellular heterogeneity across and within tumors may drive therapeutic resistance. Here we analyzed 121 primary and recurrent GBM samples from 59 patients using single-nucleus RNA sequencing and bulk tumor DNA sequencing to characterize GBM transcriptional heterogeneity. First, GBMs can be classified by their broad cellular composition, encompassing malignant and nonmalignant cell types. Second, in each cell type we describe the diversity of cellular states and their pathway activation, particularly an expanded set of malignant cell states, including glial progenitor cell-like, neuronal-like and cilia-like. Third, the remaining variation between GBMs highlights three baseline gene expression programs. These three layers of heterogeneity are interrelated and partially associated with specific genetic aberrations, thereby defining three stereotypic GBM ecosystems. This work provides an unparalleled view of the multilayered transcriptional architecture of GBM. How this architecture evolves during disease progression is addressed in the companion manuscript by Spitzer et al.

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.

DEAD/DEAH-box RNA helicases shape the risk of neurodevelopmental disorders

The DEAD/DEAH-box family of RNA helicases (RHs) is among the most abundant and conserved in eukaryotes. These proteins catalyze the remodeling of RNAs to regulate their splicing, stability, localization, and translation. Rare genetic variants in DEAD/DEAH-box proteins have recently emerged as being associated with neurodevelopmental disorders (NDDs). Analyses in cellular and animal models have uncovered fundamental roles for these proteins during brain development. We discuss the genetic and functional evidence that implicates DEAD/DEAH-box proteins in brain development and NDDs, with a focus on how structural insights from paralogous genes can be leveraged to advance our understanding of the pathogenic mechanisms at play.

Single-cell genotyping and transcriptomic profiling of mosaic focal cortical dysplasia

Focal cortical dysplasia type II (FCDII) is a cortical malformation causing refractory epilepsy. FCDII arises from developmental somatic activating mutations in mTOR pathway genes, leading to focal cortical dyslamination and abnormal cytomegalic cells. Which cell types carry pathogenic mutations and how they affect cell-type-specific transcriptional programs remain unknown. In the present study, we combined several single-nucleus genotyping and transcriptomics approaches with spatial resolution in surgical cortical specimens from patients with genetically mosaic FCDII. Mutations were detected in distinct cell types, including glutamatergic neurons and astrocytes, and a small fraction of mutated cells exhibited cytomegalic features. Moreover, we identified cell-type-specific transcriptional dysregulations in both mutated and nonmutated FCDII cells, including synapse- and neurodevelopment-related pathways, that may account for epilepsy and dysregulation of mitochondrial metabolism pathways in cytomegalic cells. Together, these findings reveal cell-autonomous and non-cell-autonomous features of FCDII that may be leveraged for precision medicine.

Selenium promotes neural development through the regulation of GPX4 and SEPP1 in an iPSC-derived neuronal model

Selenium (Se) is incorporated into selenoproteins in the form of selenocysteine, which has biological functions associated with neural development. Unfortunately, the specific roles and mechanisms of selenoproteins at different stages of neuronal development are still unclear. Therefore, in this study, we successfully established a neuronal model derived from induced pluripotent stem cells (iPSC-iNeuron) and used Se nanoparticles (SeNPs@LNT) with high bioavailability to intervene at different stages of neural development in iPSC-iNeuron model. Interestingly, our results showed that SeNPs@LNT could not only accelerate the proliferation of neural progenitor cells (NPCs) by upregulating glutathione peroxidase 4 (GPX4) during the NPC stage, but also can promote neuronal differentiation by increasing selenoprotein P (SEPP1) during the neuronal stage, resulting in efficient and rapid neural development. In addition, further mechanistic studies showed that SeNPs@LNT can regulate selenoproteins by activating the PI3K/Akt/Nrf2 signaling pathway, thereby affecting neuronal development. Notably, Further analysis of ASD patients in National Center for Biotechnology Information single-cell RNA-seq datasets also revealed significantly lower GPX4 expression within NRGN-expressing neurons in ASD patients, and GO enrichment analysis of genes in NRGN-expressing neurons from ASD patients showed that the downregulation of selenoproteins due to aberrant selenoprotein synthesis may be closely associated with decreased ATP synthesis resulting from abnormal mitochondrial and respiratory chain signaling pathways. Taken together, this study provides evidence that SeNPs@LNT exerts a beneficial effect on early neural development through the regulation of selenoproteins.

Disentangling the Switching Behavior in Functional Connectivity Dynamics in Autism Spectrum Disorder: Insights from Developmental Cohort Analysis and Molecular-Cellular Associations

Characterizing the transition or switching behavior between multistable brain states in functional connectivity dynamics (FCD) holds promise for uncovering the underlying neuropathology of Autism Spectrum Disorder (ASD). However, whether and how switching behaviors in FCD change in patients with developmental ASD, as well as their cellular and molecular basis, remains unexplored. This study develops a region-wise FCD switching index (RFSI) to investigate the drivers of FCD. This work finds that brain regions within the salience, default mode, and frontoparietal networks serve as abnormal drivers of FCD in ASD across different developmental stages. Additionally, changes in RFSI at different developmental stages of ASD correlated with transcriptomic profiles and neurotransmitter density maps. Importantly, the abnormal RFSI identifies in humans has also been observed in genetically edited ASD monkeys. Finally, single-nucleus RNA sequencing data from patients with developmental ASD are analyzed and aberrant switching behaviors in FCD may be mediated by somatostatin-expressing interneurons and altered differentiation patterns in astrocyte State2. In conclusion, this study provides the first evidence of abnormal drivers of FCD across different stages of ASD and their associated cellular and molecular mechanisms. These findings deepen the understanding of ASD neuropathology and offer valuable insights into treatment strategies.

Regional and aging-specific cellular architecture of non-human primate brains

BACKGROUND

Deciphering the functionality and dynamics of brain networks across different regions and age groups in non-human primates (NHPs) is crucial for understanding the evolution of human cognition as well as the processes underlying brain pathogenesis. However, systemic delineation of the cellular composition and molecular connections among multiple brain regions and their alterations induced by aging in NHPs remain largely unresolved.

METHODS

In this study, we performed single-nucleus RNA sequencing on 39 samples collected from 10 brain regions of two young and two aged rhesus macaques using the DNBelab C4 system. Validation of protein expression of signatures specific to particular cell types, brain regions, and aging was conducted through a series of immunofluorescence and immunohistochemistry staining experiments. Loss-of-function experiments mediated by short hairpin RNA (shRNA) targeting two age-related genes (i.e., VSNL1 and HPCAL4) were performed in U251 glioma cells to verify their aging effects. Senescence-associated beta-galactosidase (SA-β-gal) staining and quantitative PCR (qPCR) of senescence marker genes were employed to assess cellular senescence in U251 cells.

RESULTS

We have established a large-scale cell atlas encompassing over 330,000 cells for the rhesus macaque brain. Our analysis identified numerous gene expression signatures that were specific to particular cell types, subtypes, brain regions, and aging. These datasets greatly expand our knowledge of primate brain organization and highlight the potential involvement of specific molecular and cellular components in both the regionalization and functional integrity of the brain. Our analysis also disclosed extensive transcriptional alterations and cell-cell connections across brain regions in the aging macaques. Finally, by examining the heritability enrichment of human complex traits and diseases, we determined that neurological traits were significantly enriched in neuronal cells and multiple regions with aging-relevant gene expression signatures, while immune-related traits exhibited pronounced enrichment in microglia.

CONCLUSIONS

Taken together, our study presents a valuable resource for investigating the cellular and molecular architecture of the primate nervous system, thereby expanding our understanding of the mechanisms underlying brain function, aging, and disease.

Proteomic analysis of hippocampus reveals metabolic reprogramming in a piglet model of mild hypoxic ischemic encephalopathy

Neonatal hypoxic-ischemic encephalopathy (HIE) remains a leading cause of long-term neurologic morbidity. Fifty percent of HIE cases are mild and do not have clearly defined therapeutic interventions. Emergent evidence now demonstrates that up to 25% of children with mild HIE suffer motor and developmental delay by 18 months and 35% have cognitive impairments by age 5 years. Interestingly, the hippocampus, which is responsible for learning and memory, does not show overt injury but does demonstrate volume changes on imaging that correlate with cognitive and behavioral outcomes. Although there is extensive data regarding pathophysiological changes following moderate and severe HIE, there is a paucity of understanding regarding the extent, duration, and compensatory adaptations in the mild neonatal HIE brain. We performed hippocampal proteomic analysis using a swine model of mild neonatal hypoxia-asphyxia. Hippocampi were collected at 24 or 72 hours after injury, and proteomics was performed by liquid chromatography tandem mass spectrometry (LC-MS/MS). Pathway analysis demonstrated that several metabolic pathways are temporally regulated after mild HIE. Specifically, amino acid, carbohydrate, and one-carbon metabolism increased at 24 hours while fat metabolism and oxidative phosphorylation decreased at 24 hours. Downregulation of oxidative phosphorylation was more pronounced at 72 hours. Our data demonstrate that metabolic reprogramming occurs after mild HIE, and these changes persist up to 72 hours after injury. These results provide new evidence that mild HIE disrupts brain metabolism, emphasizing the need for a better understanding of the underlying pathophysiology of mild HIE and development of targeted therapeutic interventions for this population.

Advancing autism research: Insights from brain organoid modeling

Autism Spectrum Disorders (ASD) are characterized by a variety of behavioral symptoms and a complex genetic architecture, posing significant challenges in understanding the mechanistic processes underlying their pathology. Despite extensive research, the mechanisms linking genetic variations to the phenotypic outcomes associated with ASD remain elusive. Consistent evidence indicates disruptions in early brain development among individuals with ASD. The advent of brain organoids offers a unique opportunity for uncovering, how brain development changes in ASD patients. Brain organoids are three-dimensional in vitro model systems derived from pluripotent stem cells that recapitulate early human brain development across multiple biological levels. They have become an invaluable tool for studying human-specific brain development processes and neurodevelopmental disorders. In this review, we discuss recent findings using brain organoid technologies to model ASD and discuss, how these new technologies can enhance our understanding of ASD genetics and pathology at the molecular, cellular, and tissue levels.

Genetic association between gene expression profiles in oligodendrocyte precursor cells and psychiatric disorders

Background

Although neuronal dysfunction has been the focus of many studies on psychiatric disorders, accumulating evidence suggests that white matter abnormalities and oligodendrocyte lineage cells, including oligodendrocyte precursor cells (OPCs), play an important role. Beyond their established contribution to myelination, synaptic genes in OPCs form connections to neurons and influence neuronal circuits and plasticity, thereby potentially contributing to psychiatric pathology.

Methods

We analyzed publicly available single-nucleus RNA sequencing (snRNA-seq) data from white matter cells of healthy donors with SCZ genome-wide association study (GWAS) summary statistics. We assessed cell-type-specific enrichment of SCZ-associated genetic variants and performed weighted gene co-expression network analysis (WGCNA) to identify disease-related gene modules in implicated cell types.

Results

OPCs exhibited significant enrichment of SCZ-associated genetic risk variants and showed pronounced specificity in gene expression patterns. Through WGCNA, we identified a distinct co-expression module in OPCs that was enriched for synaptic genes associated with SCZ.

Conclusion

The present results highlight the previously underappreciated role of OPCs in psychiatric disorders, suggesting that OPC-involved synaptic interactions may contribute to the pathophysiology of SCZ. This work underscores the importance of considering OPCs as active players in neural network dysfunction, with potential implications for future therapeutic strategies.

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.

GPR37L1 identifies spinal cord astrocytes and protects neuropathic pain after nerve injury

Astrocytes in the spinal cord dorsal horn (SDH) play a pivotal role in synaptic transmission and neuropathic pain. However, the precise classification of SDH astrocytes in health and disease remains elusive. Here, we reveal Gpr37l1 as a marker and functional regulator of spinal astrocytes. Through single-nucleus RNA sequencing, we identified Gpr37l1 as a selective G-protein-coupled receptor (GPCR) marker for spinal cord astrocytes. Notably, SDH displayed reactive astrocyte phenotypes and exacerbated neuropathic pain following nerve injury combined with Gpr37l1 deficiency. In naive animals, Gpr37l1 knockdown in SDH astrocytes induces astrogliosis and pain hypersensitivity, while Gpr37l1-/- mice fail to recover from neuropathic pain. GPR37L1 activation by maresin 1 increased astrocyte glutamate transporter 1 (GLT-1) activity and reduced spinal EPSCs and neuropathic pain. Selective overexpression of Gpr37l1 in SDH astrocytes reversed neuropathic pain and astrogliosis after nerve injury. Our findings illuminate astrocyte GPR37l1 as an essential negative regulator of pain, which protects against neuropathic pain through astrocyte signaling in SDH.

Hypometabolism in Autism Spectrum Disorder: Insights from Brain and Blood Transcriptomics

Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by challenges in social communication, repetitive behaviors, and restricted interests. Recent research has emphasized the importance of metabolic dysfunctions in the pathophysiology of ASD. This study investigates metabolic alterations associated with ASD by analyzing transcriptomic data obtained from the prefrontal cortex (bulk tissue and single-nucleus) and data from peripheral blood mononuclear cells (PBMC). We assessed the metabolic activity of each patient based on gene expression profiles, revealing significant downregulation of vital metabolic pathways, including glycolysis, the tricarboxylic acid (TCA) cycle, and oxidative phosphorylation, indicative of hypometabolism. Our analysis also highlighted dysregulation in lipid, vitamin, amino acid, and heme metabolism, which may contribute to the neurodevelopmental delays associated with ASD. Cell-specific metabolic activities in the ASD brain showed altered pathways in astrocytes, oligodendrocytes, excitatory neurons, and interneurons. Furthermore, we identified critical metabolic pathways and genes from PBMC gene expression data that distinguish ASD patients from typically developing individuals. Our findings demonstrate a consistent pattern of metabolic dysfunction across brain and blood samples. This research provides a comprehensive understanding of metabolic alterations in ASD, paving the way for exploring potential therapeutic strategies targeting metabolic dysregulation.

High-resolution reconstruction of cell-type specific transcriptional regulatory processes from bulk sequencing samples

Biological systems exhibit remarkable heterogeneity, characterized by intricate interplay among diverse cell types. Resolving the regulatory processes of specific cell types is crucial for delineating developmental mechanisms and disease etiologies. While single-cell sequencing methods such as scRNA-seq and scATAC-seq have revolutionized our understanding of individual cellular functions, adapting bulk genome-wide assays to achieve single-cell resolution of other genomic features remains a significant technical challenge. Here, we introduce Deep-learning-based DEconvolution of Tissue profiles with Accurate Interpretation of Locus-specific Signals (DeepDETAILS), a novel quasi-supervised framework to reconstruct cell-type-specific genomic signals with base-pair precision. DeepDETAILS' core innovation lies in its ability to perform cross-modality deconvolution using scATAC-seq reference libraries for other bulk datasets, benefiting from the affordability and availability of scATAC-seq data. DeepDETAILS enables high-resolution mapping of genomic signals across diverse cell types, with great versatility for various omics datasets, including nascent transcript sequencing (such as PRO-cap and PRO-seq) and ChIP-seq for chromatin modifications. Our results demonstrate that DeepDETAILS significantly outperformed traditional statistical deconvolution methods. Using DeepDETAILS, we developed a comprehensive compendium of high-resolution nascent transcription and histone modification signals across 39 diverse human tissues and 86 distinct cell types. Furthermore, we applied our compendium to fine-map risk variants associated with Primary Sclerosing Cholangitis (PSC), a progressive cholestatic liver disorder, and revealed a potential etiology of the disease. Our tool and compendium provide invaluable insights into cellular complexity, opening new avenues for studying biological processes in various contexts.

Transcriptomic and morphologic vascular aberrations underlying FCDIIb etiology

Focal cortical dysplasia type II (FCDII) is a major cause of drug-resistant epilepsy, but genetic factors explain only some cases, suggesting other mechanisms. In this study, we conduct a molecular analysis of brain lesions and adjacent areas in FCDIIb patients. By analyzing over 217,506 single-nucleus transcriptional profiles from 15 individuals, we find significant changes in smooth muscle cells (SMCs) and astrocytes. We identify abnormal vascular malformations and a unique type of SMC that we call "Firework cells", which migrate from blood vessels into the brain parenchyma and associate with VIM+ cells. These abnormalities create localized ischemic-hypoxic (I/H) microenvironments, as confirmed by clinical data, further impairing astrocyte function, activating the HIF-1α/mTOR/S6 pathway, and causing neuronal loss. Using zebrafish models, we demonstrate that vascular abnormalities resulting in I/H environments promote seizures. Our results highlight vascular malformations as a factor in FCDIIb pathogenesis, suggesting potential therapeutic avenues.

Genetic advances in neurodevelopmental disorders

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

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

INTRODUCTION

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSION

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

Transcriptomic and spatial GABAergic neuron subtypes in zona incerta mediate distinct innate behaviors

Understanding the anatomical connection and behaviors of transcriptomic neuron subtypes is critical to delineating cell type-specific functions in the brain. Here we integrated single-nucleus transcriptomic sequencing, in vivo circuit mapping, optogenetic and chemogenetic approaches to dissect the molecular identity and function of heterogeneous GABAergic neuron populations in the zona incerta (ZI) in mice, a region involved in modulating various behaviors. By microdissecting ZI for transcriptomic and spatial gene expression analyses, our results revealed two non-overlapping Ecel1- and Pde11a-expressing GABAergic neurons with dominant expression in the rostral and medial zona incerta (ZIrEcel1 and ZImPde11a), respectively. The GABAergic projection from ZIrEcel1 to periaqueductal gray mediates self-grooming, while the GABAergic projection from ZImPde11a to the oral part of pontine reticular formation promotes transition from sleep to wakefulness. Together, our results revealed the molecular markers, spatial organization and specific neuronal circuits of two discrete GABAergic projection neuron populations in segregated subregions of the ZI that mediate distinct innate behaviors, advancing our understanding of the functional organization of the brain.

Myelinated fiber labeling and orientation mapping of the human brain with light-sheet fluorescence microscopy

The convoluted network of myelinated fibers that supports behavior, cognition, and sensory processing in the human brain is the source of its extraordinary complexity. Advancements in tissue optical clearing, 3D fluorescence microscopy, and automated image analysis have enabled unprecedented insights into the architecture of these networks. Here, we investigate the multiscale organization of myelinated fibers in human brain tissue from the brainstem, Broca's area, hippocampus, and primary visual cortex by exploiting a specific fiber staining method, light-sheet fluorescence microscopy (LSFM), and an advanced spatial orientation analysis tool. Using an optimized protocol that integrates tissue clearing with the lipophilic DiD probe to achieve uniform and deep myelinated fiber labeling, we generate micrometerresolution volumetric reconstructions of multiple brain regions through an inverted LSFM. Automated image processing, employing unsupervised 3D multiscale Frangi filters, provides orientation distribution functions and local orientation dispersion maps. This enables precise characterization of the directionality of white matter bundles, linking mesoscopic structural properties to orientation details computed at the native micrometric resolution of the LSFM apparatus. The presented workflow illustrates a robust platform for large-scale, high-resolution brain mapping, which may facilitate the investigation of pathological alterations with unparalleled spatial resolution and, furthermore, the validation of other neuroimaging modalities.

Single-cell network biology enabling cell-type-resolved disease genetics

Gene network models provide a foundation for graph theory approaches, aiding in the novel discovery of drug targets, disease genes, and genetic mechanisms for various biological functions. Disease genetics must be interpreted within the cellular context of disease-associated cell types, which cannot be achieved with datasets consisting solely of organism-level samples. Single-cell RNA sequencing (scRNA-seq) technology allows computational distinction of cell states which provides a unique opportunity to understand cellular biology that drives disease processes. Importantly, the abundance of cell samples with their transcriptome-wide profile allows the modeling of systemic cell-type-specific gene networks (CGNs), offering insights into gene-cell-disease relationships. In this review, we present reference-based and de novo inference of gene functional interaction networks that we have recently developed using scRNA-seq datasets. We also introduce a compendium of CGNs as a useful resource for cell-type-resolved disease genetics. By leveraging these advances, we envision single-cell network biology as the key approach for mapping the gene-cell-disease axis.

Mosaic H3K9me3 at BREACHes predicts synaptic gene expression associated with fragile X syndrome cognitive severity

Diseases vary in clinical presentation across individuals despite the same molecular diagnosis. In fragile X syndrome (FXS), mutation-length expansion of a CGG short tandem repeat (STR) in FMR1 causes reduced gene expression and FMRP loss. Nevertheless, FMR1 and FMRP are limited predictors of adaptive functioning and cognition in FXS patients, suggesting that molecular correlates of clinical measures would add diagnostic value. We recently uncovered Megabase-scale domains of heterochromatin (BREACHes) in FXS patient-derived iPSCs. Here, we identify BREACHes in FXS brain tissue (N=4) and absent from sex/age-matched neurotypical controls (N=4). BREACHes span >250 genes and exhibit patient-specific H3K9me3 variation. Using N=4 FXS iPSC lines and N=7 single-cell isogenic FXS iPSC subclones, we observe a strong correlation between inter-sample H3K9me3 variation and heterogeneous BREACH gene repression. We demonstrate improved prediction of cognitive metrics in FXS patients with an additive model of blood FMRP and mRNA levels of H3K9me3-mosaic, but not H3K9me3-invariant, BREACH genes. Our results highlight the utility of H3K9me3 variation at BREACHes for identifying genes associated with FXS clinical metrics.

scMEDAL for the interpretable analysis of single-cell transcriptomics data with batch effect visualization using a deep mixed effects autoencoder

scRNA-seq data has the potential to provide new insights into cellular heterogeneity and data acquisition; however, a major challenge is unraveling confounding from technical and biological batch effects. Existing batch correction algorithms suppress and discard these effects, rather than quantifying and modeling them. Here, we present scMEDAL, a framework for s ingle- c ell M ixed E ffects D eep A utoencoder L earning, which separately models batch-invariant and batch-specific effects using two complementary autoencoder networks. One network is trained through adversarial learning to capture a batch-invariant representation, while a Bayesian autoencoder learns a batch-specific representation. Comprehensive evaluations spanning conditions (e.g., autism, leukemia, and cardiovascular), cell types, and technical and biological effects demonstrate that scMEDAL suppresses batch effects while modeling batch-specific variation, enhancing accuracy and interpretability. Unlike prior approaches, the framework's fixed- and random-effects autoencoders enable retrospective analyses, including predicting a cell's expression as if it had been acquired in a different batch via genomap projections at the cellular level, revealing the impact of biological (e.g., diagnosis) and technical (e.g., acquisition) effects. By combining scMEDAL's batch-agnostic and batch-specific latent spaces, it enables more accurate predictions of disease status, donor group, and cell type, making scMEDAL a valuable framework for gaining deeper insight into data acquisition and cellular heterogeneity.

Neurodevelopmental impact of CNV models in ASD: Recent advances and future directions

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by social communication impairments and restricted, repetitive behaviors. ASD exhibits a strong genetic basis, with rare and common genetic variants contributing to its etiology. Copy number variations (CNVs), deletions or duplications of chromosomal segments, have emerged as key contributors to ASD risk. Rare CNVs often demonstrate large effect sizes and can directly cause ASD, while common variants collectively exert subtle influences. Recent advances have identified numerous ASD-associated CNVs, including recurrent loci such as 1q21.1, 2p16.3, 7q11.23, 15q11.2, 15q11-q13, 16p11.2 and 22q11.2. Mouse models carrying these CNVs have provided profound insights into the underlying neurobiological mechanisms. Recent studies integrating transcriptomic, proteomic, and functional imaging approaches have revealed alterations in synaptic function, neuronal differentiation, myelination, metabolic pathways, and circuit connectivity. Notably, investigations leveraging conditional knockout models, high magnetic field MRI, and single-cell analyses highlight disruptions in excitatory-inhibitory balance, white matter integrity, and dynamic gene regulatory networks. Parallel human-based approaches, including iPSC-derived neurons, cerebral organoids, and large-scale single-nucleus sequencing, are combined with animal model data. These integrative strategies promise to refine our understanding of ASD's genetic architecture, bridging the gap between fundamental discoveries in model organisms and clinically relevant biomarkers, subtypes, and therapeutic targets in humans. This review summarizes key findings from recent CNV mouse model studies and highlights emerging technologies applied to human ASD samples. Finally, we outline prospects for translating findings from mouse studies to humans. By illuminating both unique and convergent genetic mechanisms, these advances offer a critical framework for unraveling etiological complexity in ASD.

scMEDAL for the interpretable analysis of single-cell transcriptomics data with batch effect visualization using a deep mixed effects autoencoder

scRNA-seq data has the potential to provide new insights into cellular heterogeneity and data acquisition; however, a major challenge is unraveling confounding from technical and biological batch effects. Existing batch correction algorithms suppress and discard these effects, rather than quantifying and modeling them. Here, we present scMEDAL, a framework for single-cell Mixed Effects Deep Autoencoder Learning, which separately models batch-invariant and batch-specific effects using two complementary autoencoder networks. One network is trained through adversarial learning to capture a batch-invariant representation, while a Bayesian autoencoder learns a batch-specific representation. Comprehensive evaluations spanning conditions (e.g., autism, leukemia, and cardiovascular), cell types, and technical and biological effects demonstrate that scMEDAL suppresses batch effects while modeling batch-specific variation, enhancing accuracy and interpretability. Unlike prior approaches, the framework's fixed- and random-effects autoencoders enable retrospective analyses, including predicting a cell's expression as if it had been acquired in a different batch via genomap projections at the cellular level, revealing the impact of biological (e.g., diagnosis) and technical (e.g., acquisition) effects. By combining scMEDAL's batch-agnostic and batch-specific latent spaces, it enables more accurate predictions of disease status, donor group, and cell type, making scMEDAL a valuable framework for gaining deeper insight into data acquisition and cellular heterogeneity.

Mesenchymal stem cell-derived extracellular vesicles alleviate autism by regulating microglial glucose metabolism reprogramming and neuroinflammation through PD-1/PD-L1 interaction

Neuroinflammation triggered by microglia activation is hallmark of autism spectrum disorder (ASD), and this process includes crucial metabolic reprogramming from oxidative phosphorylation to glycolysis, which may cause neuron loss and functional impairment. The inhibitory immune checkpoint programmed cell death protein 1 (PD-1) on immune cells is an important target for tumor immunotherapy. However, the immunomodulatory effects of PD-1 in ASD remains to be elusive. Mesenchymal stem cell-derived extracellular vesicles (MSC-EVs) exhibit immunomodulatory capabilities in a range of neurological diseases. Our findings indicated the expression of PD-L1 on MSC-EVs, potentially facilitating signaling to PD-1-expressing microglia. Here, we showed how MSC-EVs activated of PD-L1/PD-1 axis and ameliorated glycolysis, neuroinflammation and autism-like behaviors. After first detecting elevated glycolysis and neuroinflammation in prefrontal cortex (PFC) tissue from the maternal immune activation (MIA) mice, we also demonstrated that PD-1 expression level was upregulated in microglia. Following given MSC-EVs carried PD-L1 into adult MIA offspring mice via intranasal administration, which bound with PD-1 on microglia and then the autism-like behaviors were alleviated as well. Further experiments verified that MSC-EVs could decreased the level of glycolysis and neuroinflammation by PD-1/ERK/HIF-1α pathway in the primary microglia in PFC of MIA offspring mice. Pharmacological blockade and genetic inhibition of PD-1 could weaken the effect of MSC-EVs and aggravate microglial dysfunction, glycolysis and autism-like behaviors in MIA offspring mice. Futhermore, PD-L1 deficient weakened the effect of MSC-EVs on neuroinflammation, glycolysis and autism-like behaviors in MIA offspring mice. Our research indicated the significant immunomodulatory capabilities of MSC-EVs, which play an important role in reprogramming microglial glucose metabolism and suppressing neuroinflammation in ASD. By activating the PD-L1/PD-1 axis and inhibiting the downstream ERK/HIF-1α pathway, MSC-EVs were found to alleviate autism-like behaviors, which revealing a novel pathological mechanism and offering promising therapeutic insights into ASD.

Perturbations in the microbiota-gut-brain axis shaped by social status loss

Social status is closely linked to physiological and psychological states. Loss of social dominance can lead to brain disorders such as depression, but the underlying mechanisms remain unclear. The gut microbiota can sense stress and contribute to brain disorders via the microbiota-gut-brain axis (MGBA). Here, using a forced loss paradigm to demote dominant mice to subordinate ranks, we find that stress alters the composition and function of the gut microbiota, increasing Muribaculaceae abundance and enhancing butanoate metabolism, and gut microbial depletion resists forced loss-induced hierarchical demotion and behavioral alteration. Single-nucleus transcriptomic analysis of the prefrontal cortex (PFC) indicates that social status loss primarily affected interneurons, altering GABAergic synaptic transmission. Weighted gene co-expression network analysis (WGCNA) reveals modules linked to forced loss in the gut microbiota, colon, PFC, and PFC interneurons, suggesting changes in the PI3K-Akt signaling pathway and the glutamatergic synapse. Our findings provide evidence for MGBA perturbations induced by social status loss, offering potential intervention targets for related brain disorders.

Contrasting genetic predisposition and diagnosis in psychiatric disorders: A multi-omic single-nucleus analysis of the human OFC

Psychiatric disorders like schizophrenia, bipolar disorder, and major depressive disorder exhibit substantial genetic and clinical overlap. However, their molecular architecture remains elusive due to their polygenic nature and complex brain cell interactions. We integrated clinical data with genetic susceptibility to investigate gene expression and chromatin accessibility in the orbitofrontal cortex of 92 postmortem human brain samples at the single-nucleus (sn) level. Using snRNA-seq and snATAC-seq, we analyzed ~800,000 and 400,000 nuclei, respectively. We observed cell-type-specific dysregulation related to clinical diagnosis and genetic risk. Dysregulation in gene expression and chromatin accessibility associated with diagnosis was pronounced in excitatory neurons. Conversely, genetic risk predominantly affected glial and endothelial cells. Notably, INO80E and HCN2 genes exhibited dysregulation in excitatory neurons' superficial layers 2/3 influenced by schizophrenia polygenic risk. This study unveils the complex genetic and epigenetic landscape of psychiatric disorders, emphasizing the importance of cell-type-specific analyses in understanding their pathogenesis and contrasting genetic predisposition with clinical diagnosis.

Multimodal single-cell analyses reveal molecular markers of neuronal senescence in human drug-resistant epilepsy

The histopathological neurons in the brain tissue of drug-resistant epilepsy exhibit aberrant cytoarchitecture and imbalanced synaptic circuit function. However, the gene expression changes of these neurons remain unknown, making it difficult to determine the diagnosis or to dissect the mechanism of drug-resistant epilepsy. By integrating whole-cell patch clamp recording and single-cell RNA-seq approaches, we identified a transcriptionally distinct subset of cortical pyramidal neurons. These neurons highly expressed genes CDKN1A (P21), CCL2, and NFKBIA, which associate with mTOR pathway, inflammatory response, and cellular senescence. We confirmed the expression of senescent marker genes in a subpopulation of cortical pyramidal neurons with enlarged soma size in the brain tissue of drug-resistant epilepsy. We further revealed the expression of senescent cell markers P21, P53, COX2, γ-H2AX, and β-Gal, and reduction of nuclear integrity marker Lamin B1 in histopathological neurons in the brain tissue of patients with drug-resistant epilepsy with different pathologies, but not in control brain tissue with no history of epilepsy. Additionally, chronic, but not acute, epileptic seizures induced senescent marker expression in cortical neurons in mouse models of drug-resistant epilepsy. These results provide important molecular markers for histopathological neurons and what we believe to be new insights into the pathophysiological mechanisms of drug-resistant epilepsy.

Decoding the blueprints of embryo development with single-cell and spatial omics

Embryonic development is a complex and intricately regulated process that encompasses precise control over cell differentiation, morphogenesis, and the underlying gene expression changes. Recent years have witnessed a remarkable acceleration in the development of single-cell and spatial omic technologies, enabling high-throughput profiling of transcriptomic and other multi-omic information at the individual cell level. These innovations offer fresh and multifaceted perspectives for investigating the intricate cellular and molecular mechanisms that govern embryonic development. In this review, we provide an in-depth exploration of the latest technical advancements in single-cell and spatial multi-omic methodologies and compile a systematic catalog of their applications in the field of embryonic development. We deconstruct the research strategies employed by recent studies that leverage single-cell sequencing techniques and underscore the unique advantages of spatial transcriptomics. Furthermore, we delve into both the current applications, data analysis algorithms and the untapped potential of these technologies in advancing our understanding of embryonic development. With the continuous evolution of multi-omic technologies, we anticipate their widespread adoption and profound contributions to unraveling the intricate molecular foundations underpinning embryo development in the foreseeable future.

Multi-omic analysis of the ciliogenic transcription factor RFX3 reveals a role in promoting activity-dependent responses via enhancing CREB binding in human neurons

Heterozygous loss-of-function (LoF) variants in RFX3, a transcription factor known to play key roles in ciliogenesis, result in autism spectrum disorder (ASD) and neurodevelopmental delay. RFX binding motifs are also enriched upstream of genes found to be commonly dysregulated in transcriptomic analyses of brain tissue from individuals with idiopathic ASD. Still, the precise functions of RFX3 in the human brain is unknown. Here, we studied the impact of RFX3 deficiency using human iPSC-derived neurons and forebrain organoids. Biallelic loss of RFX3 disrupted ciliary gene expression and delayed neuronal differentiation, while monoallelic loss of RFX3 did not. Instead, transcriptomic and DNA binding analyses demonstrated that monoallelic RFX3 loss disrupted synaptic target gene expression and diminished neuronal activity-dependent gene expression. RFX3 binding sites co-localized with CREB binding sites near activity-dependent genes, and RFX3 deficiency led to decreased CREB binding and impaired induction of CREB targets in response to neuronal depolarization. This study demonstrates a novel role of the ASD-associated gene RFX3 in shaping neuronal synaptic development and plasticity.

Multi Layered Omics Approaches Reveal Glia Specific Alterations in Alzheimer's Disease: A Systematic Review and Future Prospects

Alzheimer's disease (AD) is the most common neurodegenerative dementia with multi-layered complexity in its molecular etiology. Multiple omics-based approaches, such as genomics, epigenomics, transcriptomics, proteomics, metabolomics, and lipidomics are enabling researchers to dissect this molecular complexity, and to uncover a plethora of alterations yielding insights into the pathophysiology of this disease. These approaches reveal multi-omics alterations essentially in all cell types of the brain, including glia. In this systematic review, we screen the literature for human studies implementing any omics approach within the last 10 years, to discover AD-associated molecular perturbations in brain glial cells. The findings from over 200 AD-related studies are reviewed under four different glial cell categories: microglia, oligodendrocytes, astrocytes and brain vascular cells. Under each category, we summarize the shared and unique molecular alterations identified in glial cells through complementary omics approaches. We discuss the implications of these findings for the development, progression and ultimately treatment of this complex disease as well as directions for future omics studies in glia cells.

Systematic reconstruction of molecular pathway signatures using scalable single-cell perturbation screens

Recent advancements in functional genomics have provided an unprecedented ability to measure diverse molecular modalities, but predicting causal regulatory relationships from observational data remains challenging. Here, we leverage pooled genetic screens and single-cell sequencing (Perturb-seq) to systematically identify the targets of signalling regulators in diverse biological contexts. We demonstrate how Perturb-seq is compatible with recent and commercially available advances in combinatorial indexing and next-generation sequencing, and perform more than 1,500 perturbations split across six cell lines and five biological signalling contexts. We introduce an improved computational framework (Mixscale) to address cellular variation in perturbation efficiency, alongside optimized statistical methods to learn differentially expressed gene lists and conserved molecular signatures. Finally, we demonstrate how our Perturb-seq derived gene lists can be used to precisely infer changes in signalling pathway activation for in vivo and in situ samples. Our work enhances our understanding of signalling regulators and their targets, and lays a computational framework towards the data-driven inference of an 'atlas' of perturbation signatures.

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

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

Multiple Sclerosis: Glial Cell Diversity in Time and Space

Multiple sclerosis (MS) is the most prevalent human inflammatory disease of the central nervous system with demyelination and glial scar formation as pathological hallmarks. Glial cells are key drivers of lesion progression in MS with roles in both tissue damage and repair depending on the surrounding microenvironment and the functional state of the individual glial subtype. In this review, we describe recent developments in the context of glial cell diversity in MS summarizing key findings with respect to pathological and maladaptive functions related to disease-associated glial subtypes. A particular focus is on the spatial and temporal dynamics of glial cells including subtypes of microglia, oligodendrocytes, and astrocytes. We contextualize recent high-dimensional findings suggesting that glial cells dynamically change with respect to epigenomic, transcriptomic, and metabolic features across the inflamed rim and during the progression of MS lesions. In summary, detailed knowledge of spatially restricted glial subtype functions is critical for a better understanding of MS pathology and its pathogenesis as well as the development of novel MS therapies targeting specific glial cell types.

Brain Proteome Profiling Reveals Common and Divergent Signatures in Parkinson's Disease, Multiple System Atrophy, and Progressive Supranuclear Palsy

The molecular pathogenesis of degenerative parkinsonisms, including Parkinson's disease (PD), progressive supranuclear palsy (PSP), and Multiple system atrophy (MSA), remains largely unknown. To gain novel insight into molecular processes associated with these diseases, we conducted a proteome-wide expression study in prefrontal cortex tissue from a cohort of 181 individuals, comprising PD (N = 73), PSP (N = 18), MSA (N = 17) and healthy control (N = 73). Using marker gene profiles, we first assess the cellular composition of the samples and, subsequently, identify distinct protein signatures for each disease, while correcting for cell composition. Our findings indicate that all three diseases are characterized by a structural and/or functional loss of deep cortical neurons, while PD exhibits an additional decrease in somatostatin-expressing interneurons, as well as in endothelial cells. Differential protein expression analysis identified multiple proteins and pathways with disease-specific expression, some of which have previously been associated with parkinsonism or neurodegeneration in general. Notably, we observed a strong mitochondrial signature which was present in both PD and PSP, albeit of a different composition and most pronounced in PSP, but not in MSA where immunological/inflammation-related pathways dominated. Additionally, we identified protein signatures associated with the severity of α-synuclein pathology in PD and showed that these are highly enriched in an upregulation of mitochondrial processes, specifically related to oxidative phosphorylation and in particular respiratory complexes I and IV. We identify multiple novel signatures of protein expression, associated with PD, PSP, and MSA, as well as with the severity of α-synuclein pathology in the PD brain.

Single-Cell Transcriptional Profiling Reveals Cell Type-Specific Sex-Dependent Molecular Patterns of Schizophrenia

Schizophrenia (SCZ) is a debilitating psychiatric disorder marked by alterations in cognition and social behavior, resulting in profound impacts on individuals and society. Although sex-dependent disparities in the epidemiology of SCZ are well established, the biological molecular basis of these disparities remains poorly understood. Investigating cell type-specific transcriptomic profiles is critical for identifying regulatory components underlying sex-dependent molecular dysregulation in SCZ, which could serve as targets for sex-specific therapeutic interventions. To address this, we systematically analyzed publicly available single-nucleus RNA sequencing datasets to characterize cell type-specific sex-dependent gene expression profiles in the prefrontal cortex of SCZ cases. Functional enrichment analyses revealed sex-dependent dysregulation patterns of SCZ at the pathway level. Furthermore, we constructed cell type-specific gene regulatory networks for males and females, identifying SCZ-associated transcription factors that interact with sex hormones and their receptors. By incorporating drug screening results from the Connectivity Map, we established disease-gene-drug connections, elucidating sex-dependent molecular mechanisms of SCZ from the single-gene to the regulatory network level. Our findings delineate the molecular patterns of sex-dependent disparities in SCZ, uncover regulatory mechanisms driving SCZ-associated sex-dependent dysregulation, and illustrate the signal flow through which the biological sex influences downstream cellular pathways in SCZ cases. Our study provides significant evidence supporting the neuroprotective role of estrogen in the pathophysiology of female SCZ cases, while also establishing a robust foundation for the development of sex-specific therapeutic approaches for both sexes.

Single-cell delineation of the microbiota-gut-brain axis: Probiotic intervention in Chd8 haploinsufficient mice

Emerging research underscores the gut microbiome's impact on the nervous system via the microbiota-gut-brain axis, yet comprehensive insights remain limited. Using a CHD8-haploinsufficient model for autism spectrum disorder (ASD), we explored host-gut microbiota interactions by constructing a single-cell transcriptome atlas of brain and intestinal tissues in wild-type and mutant mice across three developmental stages. CHD8 haploinsufficiency caused delayed development of radial glial precursors and excitatory neural progenitors in the E14.5 brain, inflammation in the adult brain, immunodeficiency, and abnormal intestinal development. Selective CHD8 knockdown in intestinal epithelial cells generated Chd8ΔIEC mice, which exhibited normal sociability but impaired social novelty recognition. Probiotic intervention with Lactobacillus murinus selectively rescued social deficits in Chd8ΔIEC mice, with single-cell transcriptome analysis revealing underlying mechanisms. This study provides a detailed single-cell transcriptomic dataset of ASD-related neural and intestinal changes, advancing our understanding of the gut-brain axis and offering potential therapeutic strategies for ASD.

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.

A Reproducibility Focused Meta-Analysis Method for Single-Cell Transcriptomic Case-Control Studies Uncovers Robust Differentially Expressed Genes

We assessed the reproducibility of differentially expressed genes (DEGs) in previously published Alzheimer's (AD), Parkinson's (PD), Schizophrenia (SCZ), and COVID-19 scRNA-seq studies. While transcriptional scores from DEGs of individual PD and COVID-19 datasets had moderate predictive power for case-control status of other datasets (AUC=0.77 and 0.75), genes from individual AD and SCZ datasets had poor predictive power (AUC=0.68 and 0.55). We developed a non-parametric meta-analysis method, SumRank, based on reproducibility of relative differential expression ranks across datasets, and found DEGs with improved predictive power (AUC=0.88, 0.91, 0.78, and 0.62). By multiple other metrics, specificity and sensitivity of these genes were substantially higher than those discovered by dataset merging and inverse variance weighted p-value aggregation methods. The DEGs revealed known and novel biological pathways, and we validate BCAT1 as down-regulated in AD mouse oligodendrocytes. Lastly, we evaluate factors influencing reproducibility of individual studies as a prospective guide for experimental design.

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.