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Age-dependent white matter microstructural disintegrity in autism spectrum disorder

There has been increasing evidence of White Matter (WM) microstructural disintegrity and connectome disruption in Autism Spectrum Disorder (ASD). We evaluated the effects of age on WM microstructure by examining Diffusion Tensor Imaging (DTI) metrics and connectome Edge Density (ED) in a large datas...

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Autores principales: Weber, Clara F., Lake, Evelyn M. R., Haider, Stefan P., Mozayan, Ali, Mukherjee, Pratik, Scheinost, Dustin, Bamford, Nigel S., Ment, Laura, Constable, Todd, Payabvash, Seyedmehdi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9490315/
https://www.ncbi.nlm.nih.gov/pubmed/36161157
http://dx.doi.org/10.3389/fnins.2022.957018
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author Weber, Clara F.
Lake, Evelyn M. R.
Haider, Stefan P.
Mozayan, Ali
Mukherjee, Pratik
Scheinost, Dustin
Bamford, Nigel S.
Ment, Laura
Constable, Todd
Payabvash, Seyedmehdi
author_facet Weber, Clara F.
Lake, Evelyn M. R.
Haider, Stefan P.
Mozayan, Ali
Mukherjee, Pratik
Scheinost, Dustin
Bamford, Nigel S.
Ment, Laura
Constable, Todd
Payabvash, Seyedmehdi
author_sort Weber, Clara F.
collection PubMed
description There has been increasing evidence of White Matter (WM) microstructural disintegrity and connectome disruption in Autism Spectrum Disorder (ASD). We evaluated the effects of age on WM microstructure by examining Diffusion Tensor Imaging (DTI) metrics and connectome Edge Density (ED) in a large dataset of ASD and control patients from different age cohorts. N = 583 subjects from four studies from the National Database of Autism Research were included, representing four different age groups: (1) A Longitudinal MRI Study of Infants at Risk of Autism [infants, median age: 7 (interquartile range 1) months, n = 155], (2) Biomarkers of Autism at 12 months [toddlers, 32 (11)m, n = 102], (3) Multimodal Developmental Neurogenetics of Females with ASD [adolescents, 13.1 (5.3) years, n = 230], (4) Atypical Late Neurodevelopment in Autism [young adults, 19.1 (10.7)y, n = 96]. For each subject, we created Fractional Anisotropy (FA), Mean- (MD), Radial- (RD), and Axial Diffusivity (AD) maps as well as ED maps. We performed voxel-wise and tract-based analyses to assess the effects of age, ASD diagnosis and sex on DTI metrics and connectome ED. We also optimized, trained, tested, and validated different combinations of machine learning classifiers and dimensionality reduction algorithms for prediction of ASD diagnoses based on tract-based DTI and ED metrics. There is an age-dependent increase in FA and a decline in MD and RD across WM tracts in all four age cohorts, as well as an ED increase in toddlers and adolescents. After correction for age and sex, we found an ASD-related decrease in FA and ED only in adolescents and young adults, but not in infants or toddlers. While DTI abnormalities were mostly limited to the corpus callosum, connectomes showed a more widespread ASD-related decrease in ED. Finally, the best performing machine-leaning classification model achieved an area under the receiver operating curve of 0.70 in an independent validation cohort. Our results suggest that ASD-related WM microstructural disintegrity becomes evident in adolescents and young adults—but not in infants and toddlers. The ASD-related decrease in ED demonstrates a more widespread involvement of the connectome than DTI metrics, with the most striking differences being localized in the corpus callosum.
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spelling pubmed-94903152022-09-22 Age-dependent white matter microstructural disintegrity in autism spectrum disorder Weber, Clara F. Lake, Evelyn M. R. Haider, Stefan P. Mozayan, Ali Mukherjee, Pratik Scheinost, Dustin Bamford, Nigel S. Ment, Laura Constable, Todd Payabvash, Seyedmehdi Front Neurosci Neuroscience There has been increasing evidence of White Matter (WM) microstructural disintegrity and connectome disruption in Autism Spectrum Disorder (ASD). We evaluated the effects of age on WM microstructure by examining Diffusion Tensor Imaging (DTI) metrics and connectome Edge Density (ED) in a large dataset of ASD and control patients from different age cohorts. N = 583 subjects from four studies from the National Database of Autism Research were included, representing four different age groups: (1) A Longitudinal MRI Study of Infants at Risk of Autism [infants, median age: 7 (interquartile range 1) months, n = 155], (2) Biomarkers of Autism at 12 months [toddlers, 32 (11)m, n = 102], (3) Multimodal Developmental Neurogenetics of Females with ASD [adolescents, 13.1 (5.3) years, n = 230], (4) Atypical Late Neurodevelopment in Autism [young adults, 19.1 (10.7)y, n = 96]. For each subject, we created Fractional Anisotropy (FA), Mean- (MD), Radial- (RD), and Axial Diffusivity (AD) maps as well as ED maps. We performed voxel-wise and tract-based analyses to assess the effects of age, ASD diagnosis and sex on DTI metrics and connectome ED. We also optimized, trained, tested, and validated different combinations of machine learning classifiers and dimensionality reduction algorithms for prediction of ASD diagnoses based on tract-based DTI and ED metrics. There is an age-dependent increase in FA and a decline in MD and RD across WM tracts in all four age cohorts, as well as an ED increase in toddlers and adolescents. After correction for age and sex, we found an ASD-related decrease in FA and ED only in adolescents and young adults, but not in infants or toddlers. While DTI abnormalities were mostly limited to the corpus callosum, connectomes showed a more widespread ASD-related decrease in ED. Finally, the best performing machine-leaning classification model achieved an area under the receiver operating curve of 0.70 in an independent validation cohort. Our results suggest that ASD-related WM microstructural disintegrity becomes evident in adolescents and young adults—but not in infants and toddlers. The ASD-related decrease in ED demonstrates a more widespread involvement of the connectome than DTI metrics, with the most striking differences being localized in the corpus callosum. Frontiers Media S.A. 2022-09-07 /pmc/articles/PMC9490315/ /pubmed/36161157 http://dx.doi.org/10.3389/fnins.2022.957018 Text en Copyright © 2022 Weber, Lake, Haider, Mozayan, Mukherjee, Scheinost, Bamford, Ment, Constable and Payabvash. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Weber, Clara F.
Lake, Evelyn M. R.
Haider, Stefan P.
Mozayan, Ali
Mukherjee, Pratik
Scheinost, Dustin
Bamford, Nigel S.
Ment, Laura
Constable, Todd
Payabvash, Seyedmehdi
Age-dependent white matter microstructural disintegrity in autism spectrum disorder
title Age-dependent white matter microstructural disintegrity in autism spectrum disorder
title_full Age-dependent white matter microstructural disintegrity in autism spectrum disorder
title_fullStr Age-dependent white matter microstructural disintegrity in autism spectrum disorder
title_full_unstemmed Age-dependent white matter microstructural disintegrity in autism spectrum disorder
title_short Age-dependent white matter microstructural disintegrity in autism spectrum disorder
title_sort age-dependent white matter microstructural disintegrity in autism spectrum disorder
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9490315/
https://www.ncbi.nlm.nih.gov/pubmed/36161157
http://dx.doi.org/10.3389/fnins.2022.957018
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