Autism Spectrum Disorder Phenotypes Based on Sleep Dimensions and Core Autism Symptoms / Kristina P. LENKER in Journal of Autism and Developmental Disorders, 55-12 (December 2025)  

Public ISBD [article]  inJournal of Autism and Developmental Disorders > 55-12 (December 2025) . - p.4412-4424 Titre : Autism Spectrum Disorder Phenotypes Based on Sleep Dimensions and Core Autism Symptoms Type de document : texte imprimé Auteurs : Kristina P. LENKER, Auteur ; Yanling LI, Auteur ; Julio FERNANDEZ-MENDOZA, Auteur ; Susan D. MAYES, Auteur ; Susan L. CALHOUN, Auteur Article en page(s) : p.4412-4424 Langues : Anglais (eng) Index. décimale : PER Périodiques Résumé : Previous studies have used cluster analysis to address the diagnostic heterogeneity of autism spectrum disorder, but have been limited by identifying subgroups solely on the basis of core autism symptoms. The present study aimed to identify sleep phenotypes and their clustering with core autism symptoms in youth diagnosed with autism. 1397 patients (1-17y, M = 6.1 ± 3.3y; M IQ = 88.5 ± 27.2; 81.2% male, 89.0% white) with autism. Principal component analysis (PCA) was performed on 10 sleep items from the Pediatric Behavior Scale. Latent class analyses (LCA) determined phenotypes characterized by core autism symptoms and sleep clusters, accounting for age, sex, Intelligence Quotient (IQ), and medication use.PCA identified three distinct sleep clusters (disturbed sleep, insufficient sleep and hypersomnolence) explaining 48.4% of the variance. LCA revealed four phenotypes based on core ASD symptoms and sleep clusters. Compared to Class 1 (54.8%) as the reference group, Class 2 (26.3%) had a similar degree of sleep problems, higher IQ and milder autism symptoms, less problems with selective attention/fearlessness; Class 3 (14.5%) was characterized by insufficient and disturbed sleep, perseveration and somatosensory disturbance, and higher medication use, while Class 4 (4.4%) was by hypersomnolence, problems with social interactions, and higher medication use.We found four distinct clustering of core autism symptoms and sleep problems differing in their sleep profiles as well as in relation to clinical characteristics, demographics, internalizing/externalizing symptoms, and functional outcomes. Our findings underscore the heterogeneity of autism based on sleep-wake problems, advocating for personalized therapeutic interventions targeting nighttime sleep and daytime alertness. En ligne : https://doi.org/10.1007/s10803-025-06822-y Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=572 [article] Autism Spectrum Disorder Phenotypes Based on Sleep Dimensions and Core Autism Symptoms [texte imprimé] / Kristina P. LENKER, Auteur ; Yanling LI, Auteur ; Julio FERNANDEZ-MENDOZA, Auteur ; Susan D. MAYES, Auteur ; Susan L. CALHOUN, Auteur . - p.4412-4424. Langues : Anglais (eng) in Journal of Autism and Developmental Disorders > 55-12 (December 2025) . - p.4412-4424 Index. décimale : PER Périodiques Résumé : Previous studies have used cluster analysis to address the diagnostic heterogeneity of autism spectrum disorder, but have been limited by identifying subgroups solely on the basis of core autism symptoms. The present study aimed to identify sleep phenotypes and their clustering with core autism symptoms in youth diagnosed with autism. 1397 patients (1-17y, M = 6.1 ± 3.3y; M IQ = 88.5 ± 27.2; 81.2% male, 89.0% white) with autism. Principal component analysis (PCA) was performed on 10 sleep items from the Pediatric Behavior Scale. Latent class analyses (LCA) determined phenotypes characterized by core autism symptoms and sleep clusters, accounting for age, sex, Intelligence Quotient (IQ), and medication use.PCA identified three distinct sleep clusters (disturbed sleep, insufficient sleep and hypersomnolence) explaining 48.4% of the variance. LCA revealed four phenotypes based on core ASD symptoms and sleep clusters. Compared to Class 1 (54.8%) as the reference group, Class 2 (26.3%) had a similar degree of sleep problems, higher IQ and milder autism symptoms, less problems with selective attention/fearlessness; Class 3 (14.5%) was characterized by insufficient and disturbed sleep, perseveration and somatosensory disturbance, and higher medication use, while Class 4 (4.4%) was by hypersomnolence, problems with social interactions, and higher medication use.We found four distinct clustering of core autism symptoms and sleep problems differing in their sleep profiles as well as in relation to clinical characteristics, demographics, internalizing/externalizing symptoms, and functional outcomes. Our findings underscore the heterogeneity of autism based on sleep-wake problems, advocating for personalized therapeutic interventions targeting nighttime sleep and daytime alertness. En ligne : https://doi.org/10.1007/s10803-025-06822-y Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=572

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