Altered white matter network topology is associated with more profound language impairment in children with autism spectrum disorder.

Children with autism spectrum disorder (ASD) often exhibit language deficits, yet the influence of varying language deficits on global white matter networks remains underexplored. In this study, diffusion-weighted imaging data were collected from a cohort of Chinese children with ASD (n = 67, 54 boys) and typically developing (TD) children (n = 36, 23 boys) aged 20 to 93 months. K-means clustering divided the ASD sample into higher language (ASD-HL, n = 29) and lower language (ASD-LL, n = 38) subgroups. We examined topological properties of brain networks and compared global and nodal characteristics across ASD subgroups and TD children. Relationships between autism symptom severity, language abilities, and brain network characteristics were also assessed. The ASD-LL subgroup showed reduced global efficiency (Eg), fewer hubs, decreased fiber connectivity, and fewer inter-hemispheric connections, compared to both ASD-HL and TD groups. Decreased Eg was associated with more severe autism symptoms in the ASD-LL subgroup, but not in the ASD-HL subgroup. Moderation analysis revealed that language ability significantly moderated the link between symptom severity and Eg: higher symptom severity was significantly associated with lower Eg in children with lower language ability, but not in those with higher language ability. These findings suggest that language deficits contribute to alterations in white matter networks and may modulate the impact of autism symptoms on brain structural inefficiency in children with ASD. This study underscores the importance of targeting language skills in interventions and using language ability as a key stratification factor in ASD research.