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Updated: Oct 22, 2026

Strategies for Assessing Autistic-Like Behaviors in Mice
Published on: September 20, 2024
Autism: epidemiology, genetics, molecular mechanisms, clinical features, diagnosis, and management
Ruonan Fan1, Yilin Wang2, Tingting Miao3
1Department of Human Anatomy, School of Basic Medicine, China Medical University, Shenyang, 110122, China.
Abstract:
Autism spectrum disorder (ASD) is a lifelong neurodevelopmental condition characterized by persistent deficits in social communication and restricted, repetitive behaviors. Global prevalence has risen steadily, yet reported rates vary markedly across regions and populations. These discrepancies reflect inequities in diagnostic access and screening capacity rather than true differences in incidence. This review integrates recent advances across the full ASD research spectrum. We first examine global epidemiological patterns and demographic disparities. We then dissect the genetic architecture of ASD, including rare and common variants, copy number variations, and gene-environment interactions that disrupt prenatal and early postnatal brain development. At the molecular level, diverse risk factors converge on shared neurodevelopmental mechanisms. These include synaptic dysfunction, dysregulated signaling through mTOR, Ras-ERK-MAPK, Wnt and Notch pathways, impaired neurogenesis, chronic neuroimmune inflammation, and excitatory-inhibitory imbalance. We also discuss how these mechanisms manifest in core clinical features, including social deficits, repetitive behaviors, and sensory abnormalities. We summarize current diagnostic standards and their limitations. Cross-species animal models, from Drosophila to non-human primates, are evaluated for their essential roles in mechanistic validation and therapeutic screening. Finally, we assess clinical management strategies, ranging from behavioral and educational interventions to pharmacological and supportive services. By tracing a continuous path from risk factors at the population level through molecular pathophysiology to interventions guided by mechanism, this review offers an integrative synthesis that connects basic discovery to clinical translation. We further discuss how multi-omics and artificial intelligence may advance precise diagnosis rooted in mechanism and personalized treatment.
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