Patient-derived Brain Organoids Reveal Divergent Neuronal Activity Across Subpopulations of Autism Spectrum Disorder

Abstract Patient-derived brain organoids have emerged as a powerful model for investigating the mechanisms underlying neurological and psychiatric disorders. They provide novel insights into autism spectrum disorder (ASD), a heterogeneous neurodevelopmental condition whose underlying mechanisms remain poorly understood. Recent advancements in generating electrophysiological functional 3D brain organoids enable the study of molecular and network-level neuronal activity. Here, we aimed to characterize the neurophysiological underpinnings of ASD by comparing electrophysiological properties of brain organoids derived from eleven individuals diagnosed with autism spectrum disorder -10 with monogenic syndromic ASD across five genetic subtypes, and 1 with idiopathic ASD -to organoids derived from 4 neurotypical control individuals. We identified distinct differences in baseline activity (resting state) and evoked responses (synaptic plasticity and network dynamics) across ASD subgroups. To comprehensively assess these differences, we applied dimensionality reduction and machine learning (principal component analysis, PCA) to integrate multiple electrophysiological features into a unified framework. Our findings reveal subtype-specific neurophysiological alterations in ASD brain organoids, offering mechanistic insights into ASD heterogeneity and potential applications for early diagnostics, drug screening, and therapeutic development.