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Autism Spectrum Disorder and Childhood Apraxia of Speech: Early Language-Related Hallmarks across Structural MRI Study
Autism Spectrum Disorder (ASD) and Childhood Apraxia of Speech (CAS) are developmental disorders with distinct diagnostic criteria and different epidemiology. However, a common genetic background as well as overlapping clinical features between ASD and CAS have been recently reported. To date, brain...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7768516/ https://www.ncbi.nlm.nih.gov/pubmed/33322765 http://dx.doi.org/10.3390/jpm10040275 |
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author | Conti, Eugenia Retico, Alessandra Palumbo, Letizia Spera, Giovanna Bosco, Paolo Biagi, Laura Fiori, Simona Tosetti, Michela Cipriani, Paola Cioni, Giovanni Muratori, Filippo Chilosi, Anna Calderoni, Sara |
author_facet | Conti, Eugenia Retico, Alessandra Palumbo, Letizia Spera, Giovanna Bosco, Paolo Biagi, Laura Fiori, Simona Tosetti, Michela Cipriani, Paola Cioni, Giovanni Muratori, Filippo Chilosi, Anna Calderoni, Sara |
author_sort | Conti, Eugenia |
collection | PubMed |
description | Autism Spectrum Disorder (ASD) and Childhood Apraxia of Speech (CAS) are developmental disorders with distinct diagnostic criteria and different epidemiology. However, a common genetic background as well as overlapping clinical features between ASD and CAS have been recently reported. To date, brain structural language-related abnormalities have been detected in both the conditions, but no study directly compared young children with ASD, CAS and typical development (TD). In the current work, we aim: (i) to test the hypothesis that ASD and CAS display neurostructural differences in comparison with TD through morphometric Magnetic Resonance Imaging (MRI)-based measures (ASD vs. TD and CAS vs. TD); (ii) to investigate early possible disease-specific brain structural patterns in the two clinical groups (ASD vs. CAS); (iii) to evaluate predictive power of machine-learning (ML) techniques in differentiating the three samples (ASD, CAS, TD). We retrospectively analyzed the T1-weighted brain MRI scans of 68 children (age range: 34–74 months) grouped into three cohorts: (1) 26 children with ASD (mean age ± standard deviation: 56 ± 11 months); (2) 24 children with CAS (57 ± 10 months); (3) 18 children with TD (55 ± 13 months). Furthermore, a ML analysis based on a linear-kernel Support Vector Machine (SVM) was performed. All but one brain structures displayed significant higher volumes in both ASD and CAS children than TD peers. Specifically, ASD alterations involved fronto-temporal regions together with basal ganglia and cerebellum, while CAS alterations are more focused and shifted to frontal regions, suggesting a possible speech-related anomalies distribution. Caudate, superior temporal and hippocampus volumes directly distinguished the two conditions in terms of greater values in ASD compared to CAS. The ML analysis identified significant differences in brain features between ASD and TD children, whereas only some trends in the ML classification capability were detected in CAS as compared to TD peers. Similarly, the MRI structural underpinnings of two clinical groups were not significantly different when evaluated with linear-kernel SVM. Our results may represent the first step towards understanding shared and specific neural substrate in ASD and CAS conditions, which subsequently may contribute to early differential diagnosis and tailoring specific early intervention. |
format | Online Article Text |
id | pubmed-7768516 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-77685162020-12-29 Autism Spectrum Disorder and Childhood Apraxia of Speech: Early Language-Related Hallmarks across Structural MRI Study Conti, Eugenia Retico, Alessandra Palumbo, Letizia Spera, Giovanna Bosco, Paolo Biagi, Laura Fiori, Simona Tosetti, Michela Cipriani, Paola Cioni, Giovanni Muratori, Filippo Chilosi, Anna Calderoni, Sara J Pers Med Article Autism Spectrum Disorder (ASD) and Childhood Apraxia of Speech (CAS) are developmental disorders with distinct diagnostic criteria and different epidemiology. However, a common genetic background as well as overlapping clinical features between ASD and CAS have been recently reported. To date, brain structural language-related abnormalities have been detected in both the conditions, but no study directly compared young children with ASD, CAS and typical development (TD). In the current work, we aim: (i) to test the hypothesis that ASD and CAS display neurostructural differences in comparison with TD through morphometric Magnetic Resonance Imaging (MRI)-based measures (ASD vs. TD and CAS vs. TD); (ii) to investigate early possible disease-specific brain structural patterns in the two clinical groups (ASD vs. CAS); (iii) to evaluate predictive power of machine-learning (ML) techniques in differentiating the three samples (ASD, CAS, TD). We retrospectively analyzed the T1-weighted brain MRI scans of 68 children (age range: 34–74 months) grouped into three cohorts: (1) 26 children with ASD (mean age ± standard deviation: 56 ± 11 months); (2) 24 children with CAS (57 ± 10 months); (3) 18 children with TD (55 ± 13 months). Furthermore, a ML analysis based on a linear-kernel Support Vector Machine (SVM) was performed. All but one brain structures displayed significant higher volumes in both ASD and CAS children than TD peers. Specifically, ASD alterations involved fronto-temporal regions together with basal ganglia and cerebellum, while CAS alterations are more focused and shifted to frontal regions, suggesting a possible speech-related anomalies distribution. Caudate, superior temporal and hippocampus volumes directly distinguished the two conditions in terms of greater values in ASD compared to CAS. The ML analysis identified significant differences in brain features between ASD and TD children, whereas only some trends in the ML classification capability were detected in CAS as compared to TD peers. Similarly, the MRI structural underpinnings of two clinical groups were not significantly different when evaluated with linear-kernel SVM. Our results may represent the first step towards understanding shared and specific neural substrate in ASD and CAS conditions, which subsequently may contribute to early differential diagnosis and tailoring specific early intervention. MDPI 2020-12-12 /pmc/articles/PMC7768516/ /pubmed/33322765 http://dx.doi.org/10.3390/jpm10040275 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Conti, Eugenia Retico, Alessandra Palumbo, Letizia Spera, Giovanna Bosco, Paolo Biagi, Laura Fiori, Simona Tosetti, Michela Cipriani, Paola Cioni, Giovanni Muratori, Filippo Chilosi, Anna Calderoni, Sara Autism Spectrum Disorder and Childhood Apraxia of Speech: Early Language-Related Hallmarks across Structural MRI Study |
title | Autism Spectrum Disorder and Childhood Apraxia of Speech: Early Language-Related Hallmarks across Structural MRI Study |
title_full | Autism Spectrum Disorder and Childhood Apraxia of Speech: Early Language-Related Hallmarks across Structural MRI Study |
title_fullStr | Autism Spectrum Disorder and Childhood Apraxia of Speech: Early Language-Related Hallmarks across Structural MRI Study |
title_full_unstemmed | Autism Spectrum Disorder and Childhood Apraxia of Speech: Early Language-Related Hallmarks across Structural MRI Study |
title_short | Autism Spectrum Disorder and Childhood Apraxia of Speech: Early Language-Related Hallmarks across Structural MRI Study |
title_sort | autism spectrum disorder and childhood apraxia of speech: early language-related hallmarks across structural mri study |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7768516/ https://www.ncbi.nlm.nih.gov/pubmed/33322765 http://dx.doi.org/10.3390/jpm10040275 |
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