Brain volumes, cognitive, and adaptive skills in school-age children with Down syndrome / Rebecca GRZADZINSKI in Journal of Neurodevelopmental Disorders, 16 (2024)  

Public ISBD [article]  inJournal of Neurodevelopmental Disorders > 16 (2024) Titre : Brain volumes, cognitive, and adaptive skills in school-age children with Down syndrome Type de document : texte imprimé Auteurs : Rebecca GRZADZINSKI, Auteur ; Kattia MATA, Auteur ; Ambika S. BHATT, Auteur ; Alapika JATKAR, Auteur ; Dea GARIC, Auteur ; Mark D. SHEN, Auteur ; Jessica B. GIRAULT, Auteur ; Tanya ST JOHN, Auteur ; Juhi PANDEY, Auteur ; Lonnie ZWAIGENBAUM, Auteur ; Annette ESTES, Auteur ; Audrey M. SHEN, Auteur ; Stephen DAGER, Auteur ; Robert SCHULTZ, Auteur ; Kelly BOTTERON, Auteur ; Natasha MARRUS, Auteur ; Martin STYNER, Auteur ; Alan EVANS, Auteur ; Sun Hyung KIM, Auteur ; Robert MCKINSTRY, Auteur ; Guido GERIG, Auteur ; Joseph PIVEN, Auteur ; Heather HAZLETT, Auteur ; IBIS NETWORK, Auteur Langues : Anglais (eng) Mots-clés : Humans  Down Syndrome/diagnostic imaging/physiopathology/pathology  Male  Female  Child  Magnetic Resonance Imaging  Adaptation, Psychological/physiology  Cognition/physiology  Brain/diagnostic imaging/pathology/physiopathology  Autism Spectrum Disorder/diagnostic imaging/physiopathology/pathology  Organ Size  Cerebellum/diagnostic imaging/pathology/physiopathology  Adaptive  Autism spectrum disorder  Brain volumes  Cognitive  Cortical volumes  Down syndrome  Intellectual disability  Mri  Neurobehavioral/behavioral profiles  Neurodevelopmental disorder  Neuroimaging  School-age children  in this work was approved by the local Institutional Review Board. Consent for  publication: All authors have reviewed the manuscript and approved it for  publication. Competing interests: The authors declare no competing interests. Index. décimale : PER Périodiques Résumé : BACKGROUND: Down syndrome (DS) is the most common congenital neurodevelopmental disorder, present in about 1 in every 700 live births. Despite its prevalence, literature exploring the neurobiology underlying DS and how this neurobiology is related to behavior is limited. This study fills this gap by examining cortical volumes and behavioral correlates in school-age children with DS. METHODS: School-age children (mean = 9.7 years ± 1.1) underwent comprehensive assessments, including cognitive and adaptive assessments, as well as an MRI scan without the use of sedation. Children with DS (n = 35) were compared to available samples of typically developing (TD; n = 80) and ASD children (n = 29). ANOVAs were conducted to compare groups on cognitive and adaptive assessments. ANCOVAs (covarying for age, sex, and total cerebral volume; TCV) compared cortical brain volumes between groups. Correlations between behavioral metrics and cortical and cerebellar volumes (separately for gray (GM) and white matter (WM)) were conducted separately by group. RESULTS: As expected, children with DS had significantly lower cognitive skills compared to ASD and TD children. Daily Living adaptive skills were comparable between ASD children and children with DS, and both groups scored lower than TD children. Children with DS exhibited a smaller TCV compared to ASD and TD children. Additionally, when controlling for TCV, age, and sex, children with DS had significantly smaller total GM and tissue volumes. Cerebellum volumes were significantly correlated with Daily Living adaptive behaviors in the DS group only. CONCLUSIONS: Despite children with DS exhibiting lower cognitive skills and smaller brain volume overall than children with ASD, their deficits in Socialization and Daily Living adaptive skills are comparable. Differences in lobar volumes (e.g., Right Frontal GM/WM, Left Frontal WM, and Left and Right Temporal WM) were observed above and beyond overall differences in total volume. The correlation between cerebellum volumes and Daily Living adaptive behaviors in the DS group provides a novel area to explore in future research. En ligne : https://dx.doi.org/10.1186/s11689-024-09581-6 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=576 [article] Brain volumes, cognitive, and adaptive skills in school-age children with Down syndrome [texte imprimé] / Rebecca GRZADZINSKI, Auteur ; Kattia MATA, Auteur ; Ambika S. BHATT, Auteur ; Alapika JATKAR, Auteur ; Dea GARIC, Auteur ; Mark D. SHEN, Auteur ; Jessica B. GIRAULT, Auteur ; Tanya ST JOHN, Auteur ; Juhi PANDEY, Auteur ; Lonnie ZWAIGENBAUM, Auteur ; Annette ESTES, Auteur ; Audrey M. SHEN, Auteur ; Stephen DAGER, Auteur ; Robert SCHULTZ, Auteur ; Kelly BOTTERON, Auteur ; Natasha MARRUS, Auteur ; Martin STYNER, Auteur ; Alan EVANS, Auteur ; Sun Hyung KIM, Auteur ; Robert MCKINSTRY, Auteur ; Guido GERIG, Auteur ; Joseph PIVEN, Auteur ; Heather HAZLETT, Auteur ; IBIS NETWORK, Auteur. Langues : Anglais (eng) in Journal of Neurodevelopmental Disorders > 16 (2024) Mots-clés : Humans  Down Syndrome/diagnostic imaging/physiopathology/pathology  Male  Female  Child  Magnetic Resonance Imaging  Adaptation, Psychological/physiology  Cognition/physiology  Brain/diagnostic imaging/pathology/physiopathology  Autism Spectrum Disorder/diagnostic imaging/physiopathology/pathology  Organ Size  Cerebellum/diagnostic imaging/pathology/physiopathology  Adaptive  Autism spectrum disorder  Brain volumes  Cognitive  Cortical volumes  Down syndrome  Intellectual disability  Mri  Neurobehavioral/behavioral profiles  Neurodevelopmental disorder  Neuroimaging  School-age children  in this work was approved by the local Institutional Review Board. Consent for  publication: All authors have reviewed the manuscript and approved it for  publication. Competing interests: The authors declare no competing interests. Index. décimale : PER Périodiques Résumé : BACKGROUND: Down syndrome (DS) is the most common congenital neurodevelopmental disorder, present in about 1 in every 700 live births. Despite its prevalence, literature exploring the neurobiology underlying DS and how this neurobiology is related to behavior is limited. This study fills this gap by examining cortical volumes and behavioral correlates in school-age children with DS. METHODS: School-age children (mean = 9.7 years ± 1.1) underwent comprehensive assessments, including cognitive and adaptive assessments, as well as an MRI scan without the use of sedation. Children with DS (n = 35) were compared to available samples of typically developing (TD; n = 80) and ASD children (n = 29). ANOVAs were conducted to compare groups on cognitive and adaptive assessments. ANCOVAs (covarying for age, sex, and total cerebral volume; TCV) compared cortical brain volumes between groups. Correlations between behavioral metrics and cortical and cerebellar volumes (separately for gray (GM) and white matter (WM)) were conducted separately by group. RESULTS: As expected, children with DS had significantly lower cognitive skills compared to ASD and TD children. Daily Living adaptive skills were comparable between ASD children and children with DS, and both groups scored lower than TD children. Children with DS exhibited a smaller TCV compared to ASD and TD children. Additionally, when controlling for TCV, age, and sex, children with DS had significantly smaller total GM and tissue volumes. Cerebellum volumes were significantly correlated with Daily Living adaptive behaviors in the DS group only. CONCLUSIONS: Despite children with DS exhibiting lower cognitive skills and smaller brain volume overall than children with ASD, their deficits in Socialization and Daily Living adaptive skills are comparable. Differences in lobar volumes (e.g., Right Frontal GM/WM, Left Frontal WM, and Left and Right Temporal WM) were observed above and beyond overall differences in total volume. The correlation between cerebellum volumes and Daily Living adaptive behaviors in the DS group provides a novel area to explore in future research. En ligne : https://dx.doi.org/10.1186/s11689-024-09581-6 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=576

Development of a phenotype ontology for autism spectrum disorder by natural language processing on electronic health records / Mengge ZHAO in Journal of Neurodevelopmental Disorders, 14 (2022)  

Public ISBD [article]  inJournal of Neurodevelopmental Disorders > 14 (2022) Titre : Development of a phenotype ontology for autism spectrum disorder by natural language processing on electronic health records Type de document : texte imprimé Auteurs : Mengge ZHAO, Auteur ; James HAVRILLA, Auteur ; Jacqueline PENG, Auteur ; Madison DRYE, Auteur ; Maddie FECHER, Auteur ; Whitney GUTHRIE, Auteur ; Birkan TUNC, Auteur ; Robert SCHULTZ, Auteur ; Kai WANG, Auteur ; Yunyun ZHOU, Auteur Langues : Anglais (eng) Mots-clés : Autism Spectrum Disorder/diagnosis/genetics  Electronic Health Records  Humans  Natural Language Processing  Phenotype  Vocabulary  Autism  Autism spectrum disorder  Electronic health record  Natural language processing  Phenotype ontology  Terminology set Index. décimale : PER Périodiques Résumé : BACKGROUND: Autism spectrum disorder (ASD) is a complex neurodevelopmental condition characterized by restricted, repetitive behavior, and impaired social communication and interactions. However, significant challenges remain in diagnosing and subtyping ASD due in part to the lack of a validated, standardized vocabulary to characterize clinical phenotypic presentation of ASD. Although the human phenotype ontology (HPO) plays an important role in delineating nuanced phenotypes for rare genetic diseases, it is inadequate to capture characteristic of behavioral and psychiatric phenotypes for individuals with ASD. There is a clear need, therefore, for a well-established phenotype terminology set that can assist in characterization of ASD phenotypes from patients' clinical narratives. METHODS: To address this challenge, we used natural language processing (NLP) techniques to identify and curate ASD phenotypic terms from high-quality unstructured clinical notes in the electronic health record (EHR) on 8499 individuals with ASD, 8177 individuals with non-ASD psychiatric disorders, and 8482 individuals without a documented psychiatric disorder. We further performed dimensional reduction clustering analysis to subgroup individuals with ASD, using nonnegative matrix factorization method. RESULTS: Through a note-processing pipeline that includes several steps of state-of-the-art NLP approaches, we identified 3336 ASD terms linking to 1943 unique medical concepts, which represents among the largest ASD terminology set to date. The extracted ASD terms were further organized in a formal ontology structure similar to the HPO. Clustering analysis showed that these terms could be used in a diagnostic pipeline to differentiate individuals with ASD from individuals with other psychiatric disorders. CONCLUSION: Our ASD phenotype ontology can assist clinicians and researchers in characterizing individuals with ASD, facilitating automated diagnosis, and subtyping individuals with ASD to facilitate personalized therapeutic decision-making. En ligne : https://dx.doi.org/10.1186/s11689-022-09442-0 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=574 [article] Development of a phenotype ontology for autism spectrum disorder by natural language processing on electronic health records [texte imprimé] / Mengge ZHAO, Auteur ; James HAVRILLA, Auteur ; Jacqueline PENG, Auteur ; Madison DRYE, Auteur ; Maddie FECHER, Auteur ; Whitney GUTHRIE, Auteur ; Birkan TUNC, Auteur ; Robert SCHULTZ, Auteur ; Kai WANG, Auteur ; Yunyun ZHOU, Auteur. Langues : Anglais (eng) in Journal of Neurodevelopmental Disorders > 14 (2022) Mots-clés : Autism Spectrum Disorder/diagnosis/genetics  Electronic Health Records  Humans  Natural Language Processing  Phenotype  Vocabulary  Autism  Autism spectrum disorder  Electronic health record  Natural language processing  Phenotype ontology  Terminology set Index. décimale : PER Périodiques Résumé : BACKGROUND: Autism spectrum disorder (ASD) is a complex neurodevelopmental condition characterized by restricted, repetitive behavior, and impaired social communication and interactions. However, significant challenges remain in diagnosing and subtyping ASD due in part to the lack of a validated, standardized vocabulary to characterize clinical phenotypic presentation of ASD. Although the human phenotype ontology (HPO) plays an important role in delineating nuanced phenotypes for rare genetic diseases, it is inadequate to capture characteristic of behavioral and psychiatric phenotypes for individuals with ASD. There is a clear need, therefore, for a well-established phenotype terminology set that can assist in characterization of ASD phenotypes from patients' clinical narratives. METHODS: To address this challenge, we used natural language processing (NLP) techniques to identify and curate ASD phenotypic terms from high-quality unstructured clinical notes in the electronic health record (EHR) on 8499 individuals with ASD, 8177 individuals with non-ASD psychiatric disorders, and 8482 individuals without a documented psychiatric disorder. We further performed dimensional reduction clustering analysis to subgroup individuals with ASD, using nonnegative matrix factorization method. RESULTS: Through a note-processing pipeline that includes several steps of state-of-the-art NLP approaches, we identified 3336 ASD terms linking to 1943 unique medical concepts, which represents among the largest ASD terminology set to date. The extracted ASD terms were further organized in a formal ontology structure similar to the HPO. Clustering analysis showed that these terms could be used in a diagnostic pipeline to differentiate individuals with ASD from individuals with other psychiatric disorders. CONCLUSION: Our ASD phenotype ontology can assist clinicians and researchers in characterizing individuals with ASD, facilitating automated diagnosis, and subtyping individuals with ASD to facilitate personalized therapeutic decision-making. En ligne : https://dx.doi.org/10.1186/s11689-022-09442-0 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=574

Sleep in Infants with Down Syndrome or Familial Likelihood of Autism in the First Year of Life / Emma R. COCO 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.4439-4449 Titre : Sleep in Infants with Down Syndrome or Familial Likelihood of Autism in the First Year of Life Type de document : texte imprimé Auteurs : Emma R. COCO, Auteur ; Jeffrey MUNSON, Auteur ; Tanya ST JOHN, Auteur ; Stephen R. DAGER, Auteur ; Kelly BOTTERON, Auteur ; Jed ELISON, Auteur ; Dea GARIC, Auteur ; Heather HAZLETT, Auteur ; Chimei LEE, Auteur ; Natasha MARRUS, Auteur ; John R. PRUETT, Auteur ; Robert SCHULTZ, Auteur ; Mark SHEN, Auteur ; Lonnie ZWAIGENBAUM, Auteur ; Joseph PIVEN, Auteur ; Annette ESTES, Auteur Article en page(s) : p.4439-4449 Langues : Anglais (eng) Index. décimale : PER Périodiques Résumé : Sleep problems have been associated with atypical development, but there is limited understanding of when sleep problems arise and how they differ across clinical populations. We aimed to evaluate sleep characteristics of infants with Down syndrome (DS), higher familial likelihood of autism (HL) and lower familial likelihood of autism (LL) at 6 and 12 months of age. Participants were from two longitudinal, multi-site, studies. Sleep was estimated by parent report on the Brief Infant Sleep Questionnaire at 6 months (59 DS, 173 HL, 54 LL); 12 months (58 DS, 129 HL, 30 LL); and in a longitudinal subset at both 6 and 12 months (100 HL; 23 LL; 33 DS). At 6-months, DS parents reported less concern about infant sleep and less night wakefulness than LL parents; HL parents reported longer sleep onset latency (SOL). At 12 months DS parents reported less night sleep and more night wakefulness; HL parents reported less night sleep, more night wakefulness and longer SOL compared to LL. Night wakefulness increased significantly in the DS and HL groups from 6 to 12 months of age. A higher proportion of DS and HL infants decreased Night Sleep and increased Night Wakefulness compared with the LL group. A higher proportion of DS infants increased SOL compared with the LL group. Sleep alterations are present in the first year of life and may differ in DS and HL infants. The mechanisms behind these sleep alterations may be an important early intervention target. En ligne : https://doi.org/10.1007/s10803-025-06927-4 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=572 [article] Sleep in Infants with Down Syndrome or Familial Likelihood of Autism in the First Year of Life [texte imprimé] / Emma R. COCO, Auteur ; Jeffrey MUNSON, Auteur ; Tanya ST JOHN, Auteur ; Stephen R. DAGER, Auteur ; Kelly BOTTERON, Auteur ; Jed ELISON, Auteur ; Dea GARIC, Auteur ; Heather HAZLETT, Auteur ; Chimei LEE, Auteur ; Natasha MARRUS, Auteur ; John R. PRUETT, Auteur ; Robert SCHULTZ, Auteur ; Mark SHEN, Auteur ; Lonnie ZWAIGENBAUM, Auteur ; Joseph PIVEN, Auteur ; Annette ESTES, Auteur . - p.4439-4449. Langues : Anglais (eng) in Journal of Autism and Developmental Disorders > 55-12 (December 2025) . - p.4439-4449 Index. décimale : PER Périodiques Résumé : Sleep problems have been associated with atypical development, but there is limited understanding of when sleep problems arise and how they differ across clinical populations. We aimed to evaluate sleep characteristics of infants with Down syndrome (DS), higher familial likelihood of autism (HL) and lower familial likelihood of autism (LL) at 6 and 12 months of age. Participants were from two longitudinal, multi-site, studies. Sleep was estimated by parent report on the Brief Infant Sleep Questionnaire at 6 months (59 DS, 173 HL, 54 LL); 12 months (58 DS, 129 HL, 30 LL); and in a longitudinal subset at both 6 and 12 months (100 HL; 23 LL; 33 DS). At 6-months, DS parents reported less concern about infant sleep and less night wakefulness than LL parents; HL parents reported longer sleep onset latency (SOL). At 12 months DS parents reported less night sleep and more night wakefulness; HL parents reported less night sleep, more night wakefulness and longer SOL compared to LL. Night wakefulness increased significantly in the DS and HL groups from 6 to 12 months of age. A higher proportion of DS and HL infants decreased Night Sleep and increased Night Wakefulness compared with the LL group. A higher proportion of DS infants increased SOL compared with the LL group. Sleep alterations are present in the first year of life and may differ in DS and HL infants. The mechanisms behind these sleep alterations may be an important early intervention target. En ligne : https://doi.org/10.1007/s10803-025-06927-4 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=572

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