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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; on behalf of the IMAGEN Consortium

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Frauke Nees

Tobias Banaschewski

Arun L. W. Bokde

Sylvane Desrivières

Antoine Grigis

Hugh Garavan

Yvonne Grimmer

Andreas Heinz

Rüdiger Brühl

Corinna Isensee

Andreas Becker

Jean Luc Martinot

Marie Laure Paillère Martinot

Eric Artiges

Dimitri Papadopoulos Orfanos

Hervé Lemaître

Argyris Stringaris

Betteke van Noort

Tomáš Paus

Jani Penttilä

Sabina Millenet

Juliane H. Fröhner

Michael N. Smolka

Henrik Walter

Robert Whelan

Gunter Schumann

Luise Poustka

on behalf of the IMAGEN Consortium


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.


Nees, F., Banaschewski, T., Bokde, A. L. W., Desrivières, S., Grigis, A., Garavan, H., …on behalf of the IMAGEN Consortium. (2022). Global and Regional Structural Differences and Prediction of Autistic Traits during Adolescence. Brain Sciences, 12(9), Article 1187.

Journal Article Type Article
Acceptance Date Aug 23, 2022
Online Publication Date Sep 2, 2022
Publication Date Sep 2, 2022
Deposit Date Feb 4, 2023
Publicly Available Date Feb 7, 2023
Journal Brain Sciences
Electronic ISSN 2076-3425
Publisher MDPI AG
Peer Reviewed Peer Reviewed
Volume 12
Issue 9
Article Number 1187
Keywords adolescents; autism spectrum disorder; autistic traits; social responsiveness; structural imaging
Public URL
Publisher URL


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