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Global and Regional Structural Differences and Prediction of Autistic Traits during Adolescence

Background: Autistic traits are commonly viewed as dimensional in nature, and as continuously distributed in the general population. In this respect, the identification of predictive values of markers such as subtle autism-related alterations in brain morphology for parameter values of autistic trai...

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Autores principales: Nees, Frauke, Banaschewski, Tobias, Bokde, Arun L. W., Desrivières, Sylvane, Grigis, Antoine, Garavan, Hugh, Gowland, Penny, Grimmer, Yvonne, Heinz, Andreas, Brühl, Rüdiger, Isensee, Corinna, Becker, Andreas, Martinot, Jean-Luc, Paillère Martinot, Marie-Laure, Artiges, Eric, Papadopoulos Orfanos, Dimitri, Lemaître, Hervé, Stringaris, Argyris, van Noort, Betteke, Paus, Tomáš, Penttilä, Jani, Millenet, Sabina, Fröhner, Juliane H., Smolka, Michael N., Walter, Henrik, Whelan, Robert, Schumann, Gunter, Poustka, Luise
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9496772/
https://www.ncbi.nlm.nih.gov/pubmed/36138923
http://dx.doi.org/10.3390/brainsci12091187
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author Nees, Frauke
Banaschewski, Tobias
Bokde, Arun L. W.
Desrivières, Sylvane
Grigis, Antoine
Garavan, Hugh
Gowland, Penny
Grimmer, Yvonne
Heinz, Andreas
Brühl, Rüdiger
Isensee, Corinna
Becker, Andreas
Martinot, Jean-Luc
Paillère Martinot, Marie-Laure
Artiges, Eric
Papadopoulos Orfanos, Dimitri
Lemaître, Hervé
Stringaris, Argyris
van Noort, Betteke
Paus, Tomáš
Penttilä, Jani
Millenet, Sabina
Fröhner, Juliane H.
Smolka, Michael N.
Walter, Henrik
Whelan, Robert
Schumann, Gunter
Poustka, Luise
author_facet Nees, Frauke
Banaschewski, Tobias
Bokde, Arun L. W.
Desrivières, Sylvane
Grigis, Antoine
Garavan, Hugh
Gowland, Penny
Grimmer, Yvonne
Heinz, Andreas
Brühl, Rüdiger
Isensee, Corinna
Becker, Andreas
Martinot, Jean-Luc
Paillère Martinot, Marie-Laure
Artiges, Eric
Papadopoulos Orfanos, Dimitri
Lemaître, Hervé
Stringaris, Argyris
van Noort, Betteke
Paus, Tomáš
Penttilä, Jani
Millenet, Sabina
Fröhner, Juliane H.
Smolka, Michael N.
Walter, Henrik
Whelan, Robert
Schumann, Gunter
Poustka, Luise
author_sort Nees, Frauke
collection PubMed
description Background: Autistic traits are commonly viewed as dimensional in nature, and as continuously distributed in the general population. In this respect, the identification of predictive values of markers such as subtle autism-related alterations in brain morphology for parameter values of autistic traits could increase our understanding of this dimensional occasion. However, currently, very little is known about how these traits correspond to alterations in brain morphology in typically developing individuals, particularly during a time period where changes due to brain development processes do not provide a bias. Therefore, in the present study, we analyzed brain volume, cortical thickness (CT) and surface area (SA) in a cohort of 14–15-year-old adolescents (N = 285, female: N = 162) and tested their predictive value for autistic traits, assessed with the social responsiveness scale (SRS) two years later at the age of 16–17 years, using a regression-based approach. We found that autistic traits were significantly predicted by volumetric changes in the amygdala (r = 0.181), cerebellum (r = 0.128) and hippocampus (r = −0.181, r = −0.203), both in boys and girls. Moreover, the CT of the superior frontal region was negatively correlated (r = −0.144) with SRS scores. Furthermore, we observed a significant association between the SRS total score and smaller left putamen volume, specifically in boys (r = −0.217), but not in girls. Our findings suggest that neural correlates of autistic traits also seem to lie on a continuum in the general population, are determined by limbic–striatal neuroanatomical brain areas, and are partly dependent on sex. As we imaged adolescents from a large population-based cohort within a small age range, these data may help to increase the understanding of autistic-like occasions in otherwise typically developing individuals.
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spelling pubmed-94967722022-09-23 Global and Regional Structural Differences and Prediction of Autistic Traits during Adolescence Nees, Frauke Banaschewski, Tobias Bokde, Arun L. W. Desrivières, Sylvane Grigis, Antoine Garavan, Hugh Gowland, Penny Grimmer, Yvonne Heinz, Andreas Brühl, Rüdiger Isensee, Corinna Becker, Andreas Martinot, Jean-Luc Paillère Martinot, Marie-Laure Artiges, Eric Papadopoulos Orfanos, Dimitri Lemaître, Hervé Stringaris, Argyris van Noort, Betteke Paus, Tomáš Penttilä, Jani Millenet, Sabina Fröhner, Juliane H. Smolka, Michael N. Walter, Henrik Whelan, Robert Schumann, Gunter Poustka, Luise Brain Sci Article Background: Autistic traits are commonly viewed as dimensional in nature, and as continuously distributed in the general population. In this respect, the identification of predictive values of markers such as subtle autism-related alterations in brain morphology for parameter values of autistic traits could increase our understanding of this dimensional occasion. However, currently, very little is known about how these traits correspond to alterations in brain morphology in typically developing individuals, particularly during a time period where changes due to brain development processes do not provide a bias. Therefore, in the present study, we analyzed brain volume, cortical thickness (CT) and surface area (SA) in a cohort of 14–15-year-old adolescents (N = 285, female: N = 162) and tested their predictive value for autistic traits, assessed with the social responsiveness scale (SRS) two years later at the age of 16–17 years, using a regression-based approach. We found that autistic traits were significantly predicted by volumetric changes in the amygdala (r = 0.181), cerebellum (r = 0.128) and hippocampus (r = −0.181, r = −0.203), both in boys and girls. Moreover, the CT of the superior frontal region was negatively correlated (r = −0.144) with SRS scores. Furthermore, we observed a significant association between the SRS total score and smaller left putamen volume, specifically in boys (r = −0.217), but not in girls. Our findings suggest that neural correlates of autistic traits also seem to lie on a continuum in the general population, are determined by limbic–striatal neuroanatomical brain areas, and are partly dependent on sex. As we imaged adolescents from a large population-based cohort within a small age range, these data may help to increase the understanding of autistic-like occasions in otherwise typically developing individuals. MDPI 2022-09-02 /pmc/articles/PMC9496772/ /pubmed/36138923 http://dx.doi.org/10.3390/brainsci12091187 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Nees, Frauke
Banaschewski, Tobias
Bokde, Arun L. W.
Desrivières, Sylvane
Grigis, Antoine
Garavan, Hugh
Gowland, Penny
Grimmer, Yvonne
Heinz, Andreas
Brühl, Rüdiger
Isensee, Corinna
Becker, Andreas
Martinot, Jean-Luc
Paillère Martinot, Marie-Laure
Artiges, Eric
Papadopoulos Orfanos, Dimitri
Lemaître, Hervé
Stringaris, Argyris
van Noort, Betteke
Paus, Tomáš
Penttilä, Jani
Millenet, Sabina
Fröhner, Juliane H.
Smolka, Michael N.
Walter, Henrik
Whelan, Robert
Schumann, Gunter
Poustka, Luise
Global and Regional Structural Differences and Prediction of Autistic Traits during Adolescence
title Global and Regional Structural Differences and Prediction of Autistic Traits during Adolescence
title_full Global and Regional Structural Differences and Prediction of Autistic Traits during Adolescence
title_fullStr Global and Regional Structural Differences and Prediction of Autistic Traits during Adolescence
title_full_unstemmed Global and Regional Structural Differences and Prediction of Autistic Traits during Adolescence
title_short Global and Regional Structural Differences and Prediction of Autistic Traits during Adolescence
title_sort global and regional structural differences and prediction of autistic traits during adolescence
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9496772/
https://www.ncbi.nlm.nih.gov/pubmed/36138923
http://dx.doi.org/10.3390/brainsci12091187
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