Data-driven identification of subtypes of executive function across typical development, attention deficit hyperactivity disorder, and autism spectrum disorders / C. J. VAIDYA in Journal of Child Psychology and Psychiatry, 61-1 (January 2020)  

Public ISBD [article]  inJournal of Child Psychology and Psychiatry > 61-1 (January 2020) . - p.51-61 Titre : Data-driven identification of subtypes of executive function across typical development, attention deficit hyperactivity disorder, and autism spectrum disorders Type de document : Texte imprimé et/ou numérique Auteurs : C. J. VAIDYA, Auteur ; X. YOU, Auteur ; S. MOSTOFSKY, Auteur ; F. PEREIRA, Auteur ; M. M. BERL, Auteur ; L. KENWORTHY, Auteur Article en page(s) : p.51-61 Langues : Anglais (eng) Mots-clés : Attention deficit hyperactivity disorder  autism spectrum disorders  functional MRI (fMRI)  individual differences  machine learning Index. décimale : PER Périodiques Résumé : BACKGROUND: Impairment of executive function (EF), the goal-directed regulation of thoughts, actions, and emotions, drives negative outcomes and is common across neurodevelopmental disorders including attention deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD). A primary challenge to its amelioration is heterogeneity in symptom expression within and across disorders. Parsing this heterogeneity is necessary to attain diagnostic precision, a goal of the NIMH Research Domain Criteria Initiative. We aimed to identify transdiagnostic subtypes of EF that span the normal to impaired spectrum and establish their predictive and neurobiological validity. METHODS: Community detection was applied to clinical parent-report measures in 8-14-year-old children with and without ADHD and ASD from two independent cohorts (discovery N = 320; replication N = 692) to identify subgroups with distinct behavioral profiles. Support vector machine (SVM) classification was used to predict subgroup membership of unseen cases. Preliminary neurobiological validation was obtained with existing functional magnetic resonance imaging (fMRI) data on a subsample (N = 84) by testing hypotheses about sensitivity of EF subgroups versus DSM categories. RESULTS: We observed three transdiagnostic EF subtypes characterized by behavioral profiles that were defined by relative weakness in: (a) flexibility and emotion regulation; (b) inhibition; and (c) working memory, organization, and planning. The same tripartite structure was also present in the typically developing children. SVM trained on the discovery sample and tested on the replication sample classified subgroup membership with 77.0% accuracy. Split-half SVM classification on the combined sample (N = 1,012) yielded 88.9% accuracy (this SVM is available for public use). As hypothesized, frontal-parietal engagement was better distinguished by EF subtype than DSM diagnosis and the subgroup characterized with inflexibility failed to modulate right IPL activation in response to increased executive demands. CONCLUSIONS: The observed transdiagnostic subtypes refine current diagnostic nosology and augment clinical decision-making for personalizing treatment of executive dysfunction in children. En ligne : http://dx.doi.org/10.1111/jcpp.13114 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=413 [article] Data-driven identification of subtypes of executive function across typical development, attention deficit hyperactivity disorder, and autism spectrum disorders [Texte imprimé et/ou numérique] / C. J. VAIDYA, Auteur ; X. YOU, Auteur ; S. MOSTOFSKY, Auteur ; F. PEREIRA, Auteur ; M. M. BERL, Auteur ; L. KENWORTHY, Auteur . - p.51-61. Langues : Anglais (eng) in Journal of Child Psychology and Psychiatry > 61-1 (January 2020) . - p.51-61 Mots-clés : Attention deficit hyperactivity disorder  autism spectrum disorders  functional MRI (fMRI)  individual differences  machine learning Index. décimale : PER Périodiques Résumé : BACKGROUND: Impairment of executive function (EF), the goal-directed regulation of thoughts, actions, and emotions, drives negative outcomes and is common across neurodevelopmental disorders including attention deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD). A primary challenge to its amelioration is heterogeneity in symptom expression within and across disorders. Parsing this heterogeneity is necessary to attain diagnostic precision, a goal of the NIMH Research Domain Criteria Initiative. We aimed to identify transdiagnostic subtypes of EF that span the normal to impaired spectrum and establish their predictive and neurobiological validity. METHODS: Community detection was applied to clinical parent-report measures in 8-14-year-old children with and without ADHD and ASD from two independent cohorts (discovery N = 320; replication N = 692) to identify subgroups with distinct behavioral profiles. Support vector machine (SVM) classification was used to predict subgroup membership of unseen cases. Preliminary neurobiological validation was obtained with existing functional magnetic resonance imaging (fMRI) data on a subsample (N = 84) by testing hypotheses about sensitivity of EF subgroups versus DSM categories. RESULTS: We observed three transdiagnostic EF subtypes characterized by behavioral profiles that were defined by relative weakness in: (a) flexibility and emotion regulation; (b) inhibition; and (c) working memory, organization, and planning. The same tripartite structure was also present in the typically developing children. SVM trained on the discovery sample and tested on the replication sample classified subgroup membership with 77.0% accuracy. Split-half SVM classification on the combined sample (N = 1,012) yielded 88.9% accuracy (this SVM is available for public use). As hypothesized, frontal-parietal engagement was better distinguished by EF subtype than DSM diagnosis and the subgroup characterized with inflexibility failed to modulate right IPL activation in response to increased executive demands. CONCLUSIONS: The observed transdiagnostic subtypes refine current diagnostic nosology and augment clinical decision-making for personalizing treatment of executive dysfunction in children. En ligne : http://dx.doi.org/10.1111/jcpp.13114 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=413

PAC1R Genotype to Phenotype Correlations in Autism Spectrum Disorder / M. GOODRICH in Autism Research, 12-2 (February 2019)  

Public ISBD [article]  inAutism Research > 12-2 (February 2019) . - p.200-211 Titre : PAC1R Genotype to Phenotype Correlations in Autism Spectrum Disorder Type de document : Texte imprimé et/ou numérique Auteurs : M. GOODRICH, Auteur ; Anna Chelsea ARMOUR, Auteur ; K. PANCHAPAKESAN, Auteur ; X. YOU, Auteur ; J. DEVANEY, Auteur ; S. KNOBLACH, Auteur ; C. A. W. SULLIVAN, Auteur ; M. J. HERRERO, Auteur ; A. R. GUPTA, Auteur ; C. J. VAIDYA, Auteur ; L. KENWORTHY, Auteur ; Joshua G. CORBIN, Auteur Article en page(s) : p.200-211 Langues : Anglais (eng) Mots-clés : Pac1r  amygdala  autism  genetic modifier  neuroimaging Index. décimale : PER Périodiques Résumé : Amygdala dysfunction has been implicated in numerous neurodevelopmental disorders, including autism spectrum disorder (ASD). Previous studies in mice and humans, respectively, have linked Pac1r/PAC1R function to social behavior and PTSD-susceptibility. Based on this connection to social and emotional processing and the central role played by the amygdala in ASD, we examined a putative role for PAC1R in social deficits in ASD and determined the pattern of gene expression in the developing mouse and human amygdala. We reveal that Pac1r/PAC1R is expressed in both mouse and human amygdala from mid-neurogenesis through early postnatal stages, critical time points when altered brain trajectories are hypothesized to unfold in ASD. We further find that parents of autistic children carrying a previously identified PTSD-risk genotype (CC) report greater reciprocal social deficits compared to those carrying the non-risk GC genotype. Additionally, by exploring resting-state functional connectivity differences in a subsample of the larger behavioral sample, we find higher functional connectivity between the amygdala and right middle temporal gyrus in individuals with the CC risk genotype. Thus, using multimodal approaches, our data reveal that the amygdala-expressed PAC1R gene may be linked to severity of ASD social phenotype and possible alterations in brain connectivity, therefore potentially acting as a modifier of amygdala-related phenotypes. Autism Res 2019, 12: 200-211 (c) 2018 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: In this multimodal study across mouse and human, we examined expression patterns of Pac1r/PAC1R, a gene implicated in social behavior, and further explored whether a previously identified human PTSD-linked mutation in PAC1R can predict brain connectivity and social deficits in ASD. We find that PAC1R is highly expressed in the both the mouse and human amygdala. Furthermore, our human data suggest that PAC1R genotype is linked to severity of social deficits and functional amygdala connectivity in ASD. En ligne : http://dx.doi.org/10.1002/aur.2051 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=383 [article] PAC1R Genotype to Phenotype Correlations in Autism Spectrum Disorder [Texte imprimé et/ou numérique] / M. GOODRICH, Auteur ; Anna Chelsea ARMOUR, Auteur ; K. PANCHAPAKESAN, Auteur ; X. YOU, Auteur ; J. DEVANEY, Auteur ; S. KNOBLACH, Auteur ; C. A. W. SULLIVAN, Auteur ; M. J. HERRERO, Auteur ; A. R. GUPTA, Auteur ; C. J. VAIDYA, Auteur ; L. KENWORTHY, Auteur ; Joshua G. CORBIN, Auteur . - p.200-211. Langues : Anglais (eng) in Autism Research > 12-2 (February 2019) . - p.200-211 Mots-clés : Pac1r  amygdala  autism  genetic modifier  neuroimaging Index. décimale : PER Périodiques Résumé : Amygdala dysfunction has been implicated in numerous neurodevelopmental disorders, including autism spectrum disorder (ASD). Previous studies in mice and humans, respectively, have linked Pac1r/PAC1R function to social behavior and PTSD-susceptibility. Based on this connection to social and emotional processing and the central role played by the amygdala in ASD, we examined a putative role for PAC1R in social deficits in ASD and determined the pattern of gene expression in the developing mouse and human amygdala. We reveal that Pac1r/PAC1R is expressed in both mouse and human amygdala from mid-neurogenesis through early postnatal stages, critical time points when altered brain trajectories are hypothesized to unfold in ASD. We further find that parents of autistic children carrying a previously identified PTSD-risk genotype (CC) report greater reciprocal social deficits compared to those carrying the non-risk GC genotype. Additionally, by exploring resting-state functional connectivity differences in a subsample of the larger behavioral sample, we find higher functional connectivity between the amygdala and right middle temporal gyrus in individuals with the CC risk genotype. Thus, using multimodal approaches, our data reveal that the amygdala-expressed PAC1R gene may be linked to severity of ASD social phenotype and possible alterations in brain connectivity, therefore potentially acting as a modifier of amygdala-related phenotypes. Autism Res 2019, 12: 200-211 (c) 2018 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: In this multimodal study across mouse and human, we examined expression patterns of Pac1r/PAC1R, a gene implicated in social behavior, and further explored whether a previously identified human PTSD-linked mutation in PAC1R can predict brain connectivity and social deficits in ASD. We find that PAC1R is highly expressed in the both the mouse and human amygdala. Furthermore, our human data suggest that PAC1R genotype is linked to severity of social deficits and functional amygdala connectivity in ASD. En ligne : http://dx.doi.org/10.1002/aur.2051 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=383

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