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Using human pluripotent stem cell models to study autism in the era of big data / Ralda NEHME in Molecular Autism, 11 (2020)
[article]
Titre : Using human pluripotent stem cell models to study autism in the era of big data Type de document : Texte imprimé et/ou numérique Auteurs : Ralda NEHME, Auteur ; Lindy E. BARRETT, Auteur Article en page(s) : 21 p. Langues : Anglais (eng) Mots-clés : Differentiation esc Human brain In vivo Regulatory policy Sample size Variance hPSC iPSC Index. décimale : PER Périodiques Résumé : Advances in human pluripotent stem cell (hPSC) biology coupled with protocols to generate diverse brain cell types in vitro have provided neuroscientists with opportunities to dissect basic and disease mechanisms in increasingly relevant cellular substrates. At the same time, large data collections and analyses have facilitated unprecedented insights into autism genetics, normal human genetic variation, and the molecular landscape of the developing human brain. While such insights have enabled the investigation of key mechanistic questions in autism, they also highlight important limitations associated with the use of existing hPSC models. In this review, we discuss four such issues which influence the efficacy of hPSC models for studying autism, including (i) sources of variance, (ii) scale and format of study design, (iii) divergence from the human brain in vivo, and (iv) regulatory policies and compliance governing the use of hPSCs. Moreover, we advocate for a set of immediate and long-term priorities to address these issues and to accelerate the generation and reproducibility of data in order to facilitate future fundamental as well as therapeutic discoveries. En ligne : http://dx.doi.org/10.1186/s13229-020-00322-9 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=427
in Molecular Autism > 11 (2020) . - 21 p.[article] Using human pluripotent stem cell models to study autism in the era of big data [Texte imprimé et/ou numérique] / Ralda NEHME, Auteur ; Lindy E. BARRETT, Auteur . - 21 p.
Langues : Anglais (eng)
in Molecular Autism > 11 (2020) . - 21 p.
Mots-clés : Differentiation esc Human brain In vivo Regulatory policy Sample size Variance hPSC iPSC Index. décimale : PER Périodiques Résumé : Advances in human pluripotent stem cell (hPSC) biology coupled with protocols to generate diverse brain cell types in vitro have provided neuroscientists with opportunities to dissect basic and disease mechanisms in increasingly relevant cellular substrates. At the same time, large data collections and analyses have facilitated unprecedented insights into autism genetics, normal human genetic variation, and the molecular landscape of the developing human brain. While such insights have enabled the investigation of key mechanistic questions in autism, they also highlight important limitations associated with the use of existing hPSC models. In this review, we discuss four such issues which influence the efficacy of hPSC models for studying autism, including (i) sources of variance, (ii) scale and format of study design, (iii) divergence from the human brain in vivo, and (iv) regulatory policies and compliance governing the use of hPSCs. Moreover, we advocate for a set of immediate and long-term priorities to address these issues and to accelerate the generation and reproducibility of data in order to facilitate future fundamental as well as therapeutic discoveries. En ligne : http://dx.doi.org/10.1186/s13229-020-00322-9 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=427 Dynamic lag analysis reveals atypical brain information flow in autism spectrum disorder / Ville RAATIKAINEN in Autism Research, 13-2 (February 2020)
[article]
Titre : Dynamic lag analysis reveals atypical brain information flow in autism spectrum disorder Type de document : Texte imprimé et/ou numérique Auteurs : Ville RAATIKAINEN, Auteur ; Vesa KORHONEN, Auteur ; Viola BORCHARDT, Auteur ; Niko HUOTARI, Auteur ; Heta HELAKARI, Auteur ; Janne KANANEN, Auteur ; Lauri RAITAMAA, Auteur ; Leena JOSKITT, Auteur ; Soile LOUKUSA, Auteur ; Tuula HURTIG, Auteur ; Hanna EBELING, Auteur ; Lucina Q. UDDIN, Auteur ; Vesa KIVINIEMI, Auteur ; Finnish Epilepsy ASSOCIATION, Auteur ; Instrumentariumin TIEDESAATIO, Auteur ; Jane ja Aatos Erkon SAATIO, Auteur Article en page(s) : p.244-258 Langues : Anglais (eng) Mots-clés : Asd Mreg dynamic lag analysis human brain lag pattern resting state fMRI Index. décimale : PER Périodiques Résumé : This study investigated whole-brain dynamic lag pattern variations between neurotypical (NT) individuals and individuals with autism spectrum disorder (ASD) by applying a novel technique called dynamic lag analysis (DLA). The use of 3D magnetic resonance encephalography data with repetition time = 100 msec enables highly accurate analysis of the spread of activity between brain networks. Sixteen resting-state networks (RSNs) with the highest spatial correlation between NT individuals (n = 20) and individuals with ASD (n = 20) were analyzed. The dynamic lag pattern variation between each RSN pair was investigated using DLA, which measures time lag variation between each RSN pair combination and statistically defines how these lag patterns are altered between ASD and NT groups. DLA analyses indicated that 10.8% of the 120 RSN pairs had statistically significant (P-value <0.003) dynamic lag pattern differences that survived correction with surrogate data thresholding. Alterations in lag patterns were concentrated in salience, executive, visual, and default-mode networks, supporting earlier findings of impaired brain connectivity in these regions in ASD. 92.3% and 84.6% of the significant RSN pairs revealed shorter mean and median temporal lags in ASD versus NT, respectively. Taken together, these results suggest that altered lag patterns indicating atypical spread of activity between large-scale functional brain networks may contribute to the ASD phenotype. Autism Res 2020, 13: 244-258. (c) 2019 The Authors. Autism Research published by International Society for Autism Research published by Wiley Periodicals, Inc. LAY SUMMARY: Autism spectrum disorder (ASD) is characterized by atypical neurodevelopment. Using an ultra-fast neuroimaging procedure, we investigated communication across brain regions in adults with ASD compared with neurotypical (NT) individuals. We found that ASD individuals had altered information flow patterns across brain regions. Atypical patterns were concentrated in salience, executive, visual, and default-mode network areas of the brain that have previously been implicated in the pathophysiology of the disorder. En ligne : http://dx.doi.org/10.1002/aur.2218 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=420
in Autism Research > 13-2 (February 2020) . - p.244-258[article] Dynamic lag analysis reveals atypical brain information flow in autism spectrum disorder [Texte imprimé et/ou numérique] / Ville RAATIKAINEN, Auteur ; Vesa KORHONEN, Auteur ; Viola BORCHARDT, Auteur ; Niko HUOTARI, Auteur ; Heta HELAKARI, Auteur ; Janne KANANEN, Auteur ; Lauri RAITAMAA, Auteur ; Leena JOSKITT, Auteur ; Soile LOUKUSA, Auteur ; Tuula HURTIG, Auteur ; Hanna EBELING, Auteur ; Lucina Q. UDDIN, Auteur ; Vesa KIVINIEMI, Auteur ; Finnish Epilepsy ASSOCIATION, Auteur ; Instrumentariumin TIEDESAATIO, Auteur ; Jane ja Aatos Erkon SAATIO, Auteur . - p.244-258.
Langues : Anglais (eng)
in Autism Research > 13-2 (February 2020) . - p.244-258
Mots-clés : Asd Mreg dynamic lag analysis human brain lag pattern resting state fMRI Index. décimale : PER Périodiques Résumé : This study investigated whole-brain dynamic lag pattern variations between neurotypical (NT) individuals and individuals with autism spectrum disorder (ASD) by applying a novel technique called dynamic lag analysis (DLA). The use of 3D magnetic resonance encephalography data with repetition time = 100 msec enables highly accurate analysis of the spread of activity between brain networks. Sixteen resting-state networks (RSNs) with the highest spatial correlation between NT individuals (n = 20) and individuals with ASD (n = 20) were analyzed. The dynamic lag pattern variation between each RSN pair was investigated using DLA, which measures time lag variation between each RSN pair combination and statistically defines how these lag patterns are altered between ASD and NT groups. DLA analyses indicated that 10.8% of the 120 RSN pairs had statistically significant (P-value <0.003) dynamic lag pattern differences that survived correction with surrogate data thresholding. Alterations in lag patterns were concentrated in salience, executive, visual, and default-mode networks, supporting earlier findings of impaired brain connectivity in these regions in ASD. 92.3% and 84.6% of the significant RSN pairs revealed shorter mean and median temporal lags in ASD versus NT, respectively. Taken together, these results suggest that altered lag patterns indicating atypical spread of activity between large-scale functional brain networks may contribute to the ASD phenotype. Autism Res 2020, 13: 244-258. (c) 2019 The Authors. Autism Research published by International Society for Autism Research published by Wiley Periodicals, Inc. LAY SUMMARY: Autism spectrum disorder (ASD) is characterized by atypical neurodevelopment. Using an ultra-fast neuroimaging procedure, we investigated communication across brain regions in adults with ASD compared with neurotypical (NT) individuals. We found that ASD individuals had altered information flow patterns across brain regions. Atypical patterns were concentrated in salience, executive, visual, and default-mode network areas of the brain that have previously been implicated in the pathophysiology of the disorder. En ligne : http://dx.doi.org/10.1002/aur.2218 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=420