bioRxiv Science⌕ Search

bioRxiv · 10.1101/2025.07.18.664735

Distinct Synaptic Mechanisms Drive NRXN1 Variant-Mediated Pathogenesis in iPSC-Derived Neuronal Models of Autism and Schizophrenia

Abstract

Copy number deletions in the 2p16.3/NRXN1 locus confer genome wide risk for autism spectrum disorder (ASD) and schizophrenia (SCZ). Prior work demonstrated that heterozygous NRXN1 deletions decreases synaptic strength and neurotransmitter release probability in human-iPSC derived cortical glutamatergic induced neurons and this synaptic phenotype is replicated in SCZ patient iPSCs with varying NRXN1 genomic deletions. What is unknown, however, is whether similar synaptic impairment exists in ASD patients carrying NRXN1 deletions. Answering this question is important to determine whether all NRXN1 deletion carriers should be treated similarly or individually, based on their genetic backgrounds and deletion breakpoints. Here, using previously uncharacterized ASD patient iPSC lines, we show that ASD-NRXN1 deletions impact cortical synaptic function and plasticity in unique ways compared to SCZ-NRXN1 deletions. Specifically, at a single neuronal level, ASD-NRXN1 deletions alter basal spontaneous synaptic transmission by selectively enhancing excitatory synaptic signaling with no changes at inhibitory synapses while SCZ-NRXN1 deletions reduce both excitatory and inhibitory synaptic transmission. At the neuronal network level, there exists enhanced transmission probability and irregular firing patterns in ASD-NRXN1 deletions. Such changes at the synaptic and network level connectivity patterns influence a critical form of developmental cortical plasticity, synaptic scaling, as ASD-NRXN1 deletions uniquely fail to upscale their synaptic strength in response to chronic neuronal silencing. Together, these findings highlight the disorder-specific consequences of NRXN1 deletions on synaptic function and connectivity, offering mechanistic insights with implications for therapeutic targeting and refinement strategies for NRXN1-associated synaptopathies. HighlightsO_LINovel ASD patient-iPSC-derived E-I culture model to investigate pathogenic NRXN1 deletions on cortical synaptic function and plasticity C_LIO_LIASD-NRXN1 deletions enhance basal synaptic transmission by specifically increasing excitatory neurotransmitter release, opposite of SCZ-NRXN1 deletions C_LIO_LISynaptic scaling homeostasis is impaired in ASD-NRXN1 deletions C_LIO_LISpike train cross-correlation analysis reveals increased transmission probability and irregular firing patterns in ASD-NRXN1 deletions C_LI

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Pak, C., English, J., McSweeney, D., Geng, J., Howell, E., Ribbe, F., Hinderhofer, M., Proskauer, L., Sebastian, R., Wang, L., Sharf, T., Pang, Z. P.. 2025-07-19. Distinct Synaptic Mechanisms Drive NRXN1 Variant-Mediated Pathogenesis in iPSC-Derived Neuronal Models of Autism and Schizophrenia. https://doi.org/10.1101/2025.07.18.664735

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

The Unreasonable Effectiveness of Cell Types in Describing Neuronal Physiological Features

Single-cell RNA sequencing (scRNA-seq) captures detailed gene expression profiles at scale, while patch-clamp recordings measure intrinsic neuronal electrophysiological properties. Modeling the relations between these two modalities remains a challenge. Here, we compare how well electrophysiological features can be predicted by traditional transcriptomic cell type classification, representations derived from a foundational model (scGPT) pretrained on large-scale scRNA-seq datasets, ion channel-coding genes, and highly variable genes. Using paired transcriptomic and electrophysiological patch-sequencing data from 495 human neurons from neurosurgical tissue, we find that cluster-level cell type representations consistently outperform highly variable gene selection, ion channel gene selection, and context-enriched scGPT embeddings. Notably, performance varies across model architectures and initializations, and the best results are obtained by combining the outputs of separate cell type and scGPT-based models. Together, these findings suggest that traditional discrete cellular classification is highly effective in predicting physiological features. For maximum performance it can be complemented by pretrained transformer models.

neuroscience↗

A nonlinear inhibition pathway underlying cortical responses to tuned holographic optogenetic perturbations

Optogenetics enables causal manipulation of cortical activity. Perturbation responses can be counterintuitive due to network interactions, making theory essential for predicting them. Existing approaches often rely on linear approximations, which fail for many biologically relevant perturbations. Here we develop a nonlinear theory of responses to holographic perturbations in cell-type-specific recurrent networks with structured connectivity. We fit a nonlinear model to mouse V1 data, which shows cotuned-ensemble suppression: perturbing spatially clustered neurons with similar preferred orientations yields markedly stronger short-range suppression than perturbing untuned ensembles. We show that cotuned-ensemble suppression arises from a feature-tuned, nonlinear inhibition pathway implicating somatostatin-positive (SST) interneurons. The theory predicts that cotuned ensembles suppress parvalbumin-positive (PV) neurons but facilitate SST neurons, and links the degree of cotuned-ensemble suppression or facilitation to the variance of the SST response. This framework identifies mechanisms by which nonlinear inhibition sculpts cortical dynamics and establishes a predictive basis for targeted optogenetic interventions.

neuroscience↗

Proteomic signatures of APOE ε4 across human tissues and cell types in Alzheimers disease

The apolipoprotein E {varepsilon}4 (APOE {varepsilon}4) allele is the strongest genetic risk factor for late-onset Alzheimers disease (AD). However, the underlying molecular mechanisms remain unclear. This study included 1691 participants from the Religious Orders Study and Rush Memory and Aging Project (ROSMAP), 1226 participants from the Accelerating Medicines Partnership - Alzheimers Disease (AMP-AD) Diverse Cohorts Study, and 735 participants from the Alzheimers Disease Neuroimaging Initiative (ADNI). To characterise APOE {varepsilon}4 molecular effects, we analysed proteomic data from plasma, cerebrospinal fluid (CSF), and induced pluripotent stem cell (iPSC)-derived astrocytes and neurons, as well as transcriptomic and proteomic data from multiple brain regions. The association of APOE {varepsilon}4 with AD neuropathology was also examined. APOE {varepsilon}4 carriers shared a plasma proteomic signature enriched for immune processes, irrespective of AD diagnosis. A machine learning classifier trained on this signature discriminated APOE {varepsilon}4 carriers from non-carriers in an independent cohort using CSF proteomics. APOE {varepsilon}4 carriage was associated with higher Braak stages and Consortium to Establish a Registry for Alzheimers Disease (CERAD) score. However, only limited APOE {varepsilon}4-associated transcriptomic and proteomic changes were observed in bulk brain tissue, with poor cross-layer concordance. Proteomic analyses of iPSC-derived astrocytes and neurons further revealed cell-type-specific APOE {varepsilon}4-associated changes. APOE {varepsilon}4 is associated with a consistent proteomic signature across plasma and CSF. Its molecular effects in the brain differ across cell types, brain regions and molecular layers. These findings support the need for cell-type-resolved multi-omic studies to elucidate how APOE {varepsilon}4 confers AD risk.

neuroscience↗