REM Sleep Abnormalities in Children With Autism Spectrum Disorder / Jiasen MA in Autism Research, 19-5 (May 2026)  

Public ISBD [article]  inAutism Research > 19-5 (May 2026) . - p.e70222 Titre : REM Sleep Abnormalities in Children With Autism Spectrum Disorder Type de document : texte imprimé Auteurs : Jiasen MA, Auteur ; Junjun QIN, Auteur ; Hongfang JIANG, Auteur ; Yueping CHE, Auteur ; Haifeng LI, Auteur ; Daqing MA, Auteur ; Jinpiao ZHU, Auteur Article en page(s) : p.e70222 Langues : Anglais (eng) Mots-clés : autism spectrum disorder (ASD)  machine learning  rapid eye movement sleep (REM)  SHapley additive explanation (SHAP) Index. décimale : PER Périodiques Résumé : ABSTRACT Sleep disturbances are common in children with autism spectrum disorder (ASD). However, the sleep pattern changes including rapid eye movement (REM) sleep for ASD in pediatric populations remain unknown. Using polysomnography (PSG) data from the National Children's Hospital (NCH) Sleep Databank, we identified 193 children with ASD and matched them with 193 Non-ASD controls. We found children with ASD showed reduced REM sleep proportion (17.8%?±?6.4% vs. 19.1%?±?7.0%; p?=?0.049) and duration (71.5 [49.5?91.0] min vs. 81.5 [52.5?98.0] min; p?=?0.036), prolonged REM latency (134.5 [94.0?181.5] min vs. 116.0 [82.0?157.0] min; p?=?0.009), and increased 1st REM duration (13.0 [7.0?19.0] min vs. 10.5 [6.0?16.5] min; p?=?0.024) compared with Non-ASD peers. They also showed higher 1st REM proportion (18.8 [11.0?31.3] vs. 15.7 [8.3?25.4]; p?=?0.003), particularly in children aged 3?5?years and 6?8?years. Using these REM features, the XGBoost machine learning model was achieved to be the best predictive performance. SHAP analysis further showed that decreased REM sleep duration, increased 1st REM proportion or duration, and prolonged REM latency were discriminative features for children with ASD. These findings suggest that REM sleep abnormalities are common in young patients with ASD but its contribution to the disease's severity and/or development needs to be explored further. En ligne : https://doi.org/10.1002/aur.70222 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=587 [article] REM Sleep Abnormalities in Children With Autism Spectrum Disorder [texte imprimé] / Jiasen MA, Auteur ; Junjun QIN, Auteur ; Hongfang JIANG, Auteur ; Yueping CHE, Auteur ; Haifeng LI, Auteur ; Daqing MA, Auteur ; Jinpiao ZHU, Auteur . - p.e70222. Langues : Anglais (eng) in Autism Research > 19-5 (May 2026) . - p.e70222 Mots-clés : autism spectrum disorder (ASD)  machine learning  rapid eye movement sleep (REM)  SHapley additive explanation (SHAP) Index. décimale : PER Périodiques Résumé : ABSTRACT Sleep disturbances are common in children with autism spectrum disorder (ASD). However, the sleep pattern changes including rapid eye movement (REM) sleep for ASD in pediatric populations remain unknown. Using polysomnography (PSG) data from the National Children's Hospital (NCH) Sleep Databank, we identified 193 children with ASD and matched them with 193 Non-ASD controls. We found children with ASD showed reduced REM sleep proportion (17.8%?±?6.4% vs. 19.1%?±?7.0%; p?=?0.049) and duration (71.5 [49.5?91.0] min vs. 81.5 [52.5?98.0] min; p?=?0.036), prolonged REM latency (134.5 [94.0?181.5] min vs. 116.0 [82.0?157.0] min; p?=?0.009), and increased 1st REM duration (13.0 [7.0?19.0] min vs. 10.5 [6.0?16.5] min; p?=?0.024) compared with Non-ASD peers. They also showed higher 1st REM proportion (18.8 [11.0?31.3] vs. 15.7 [8.3?25.4]; p?=?0.003), particularly in children aged 3?5?years and 6?8?years. Using these REM features, the XGBoost machine learning model was achieved to be the best predictive performance. SHAP analysis further showed that decreased REM sleep duration, increased 1st REM proportion or duration, and prolonged REM latency were discriminative features for children with ASD. These findings suggest that REM sleep abnormalities are common in young patients with ASD but its contribution to the disease's severity and/or development needs to be explored further. En ligne : https://doi.org/10.1002/aur.70222 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=587

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