- Children with ASD show significantly reduced sleep spindle amplitude, number, density and activity during stage 2 NREM sleep compared with typically developing peers.
- Spindle duration is significantly prolonged in children with ASD, suggesting altered thalamocortical temporal dynamics.
- Quantitative spindle metrics associate with ASD and may serve as scalable, non-invasive neurophysiological biomarkers for early identification and outcome monitoring.
Clin Neurophysiol. 2026 Sep 13;192:2112405. doi: 10.1016/j.clinph.2026.2112405. Online ahead of print.
ABSTRACT
OBJECTIVE: Neurophysiological biomarkers for autism spectrum disorder (ASD) remain limited, and sleep spindle alterations reflecting thalamocortical network function are not yet fully characterized; therefore, we aimed to compare sleep spindle features between children with ASD and typically developing peers.
METHODS: In this observational cross-sectional study, polysomnography-derived sleep spindle parameters including amplitude, frequency, duration, density, and activity, were analyzed during stage 2 non-rapid eye movement (NREM) sleep in children with ASD and compared with those of age-matched healthy controls.
RESULTS: The amplitude, number, density, and activity of sleep spindles were significantly reduced in children with ASD compared to the control group, while spindle duration was significantly longer. Univariate logistic regression analysis revealed that the spindle amplitude, number of spindles, spindle density, and spindle activity were significantly associated with ASD. In the multivariate analysis, a higher number of spindles (p = 0.033, OR = 0.776, 95 % CI: 0.615-0.979) and greater spindle activity (p = 0.015, OR = 0.954, 95 % CI: 0.919-0.991) were significantly associated with a reduced likelihood of ASD.
CONCLUSIONS: Sleep spindle abnormalities in ASD may reflect alterations in thalamocortical dynamics and could represent an objective marker of neurodevelopmental dysfunction.
SIGNIFICANCE: Quantitative sleep spindle analysis may represent a scalable, non-invasive neurophysiological biomarker with potential applications in early identification, mechanistic research, and outcome monitoring in ASD.
PMID:42753649 | DOI:10.1016/j.clinph.2026.2112405
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