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.