TY - JOUR
T1 - Autism Is Associated With Interindividual Variations of Gray and White Matter Morphology
AU - The EU-AIMS LEAP Group
AU - Mei, Ting
AU - Forde, Natalie J.
AU - Floris, Dorothea L.
AU - Dell'Acqua, Flavio
AU - Stones, Richard
AU - Ilioska, Iva
AU - Durston, Sarah
AU - Moessnang, Carolin
AU - Banaschewski, Tobias
AU - Holt, Rosemary J.
AU - Baron-Cohen, Simon
AU - Rausch, Annika
AU - Loth, Eva
AU - Oakley, Bethany
AU - Charman, Tony
AU - Ecker, Christine
AU - Murphy, Declan G.M.
AU - Buitelaar, Jan K.
AU - Ahmad, Jumana
AU - Ambrosino, Sara
AU - Auyeung, Bonnie
AU - Baumeister, Sarah
AU - Beckmann, Christian F.
AU - Bölte, Sven
AU - Bourgeron, Thomas
AU - Bours, Carsten
AU - Brammer, Michael
AU - Brandeis, Daniel
AU - Brogna, Claudia
AU - de Bruijn, Yvette
AU - Chakrabarti, Bhismadev
AU - Cornelissen, Ineke
AU - Crawley, Daisy
AU - Dumas, Guillaume
AU - Faulkner, Jessica
AU - Frouin, Vincent
AU - Garcés, Pilar
AU - Goyard, David
AU - Ham, Lindsay
AU - Hayward, Hannah
AU - Hipp, Joerg
AU - Holt, Rosemary
AU - Lythgoe, David J.
AU - Marquand, Andre
AU - Mason, Luke
AU - Ruggeri, Barbara
AU - San José Cáceres, Antonia
AU - Simonoff, Emily
AU - Tillmann, Julian
AU - Williams, Steve C.R.
N1 - Funding Information:
This work was also supported by the China Scholarship Council (Grant No. 201806010408 [to TM]), European Union’s Horizon 2020 Research and Innovation Programme under the Marie Skłodowska-Curie grant agreement (Grant No. 101025785 [to DLF]), European Union Seventh Framework Programme (Grant Nos. 602805 [AGGRESSOTYPE], 603016 [MATRICS], and 278948 [TACTICS] [to JKB], European Community’s Horizon 2020 Programme H2020/2014–2020 (Grant Nos. 643051 [MiND] and 642996 [BRAINVIEW] [to JKB] and Grant No. 847818 [CANDY; to JKB and CFB], Netherlands Organization for Scientific Research VICI (Grant No. 2020/TTW/00836465 [to CFB]), Wellcome Trust Collaborative Award (Grant No. 215573/Z/19/Z [to CFB]), and Autism Research Trust (to SB-C).
Funding Information:
This work was primarily supported by the EU-AIMS consortium (European Autism Interventions), which receives support from Innovative Medicines Initiative Joint Undertaking (Grant No. 115300 ), the resources of which are composed of financial contributions from the European Union’s Seventh Framework Programme (Grant No. FP7/2007-2013), from the European Federation of Pharmaceutical Industries and Associations companies’ in-kind contributions, and by the AIMS-2-TRIALS consortium, which has received funding from the Innovative Medicines Initiative 2 Joint Undertaking (Grant No. 777394). This Joint Undertaking receives support from the European Union’s Horizon 2020 research and innovation programme; European Federation of Pharmaceutical Industries and Associations; and Autism Speaks, Autistica, and Simons Foundation Autism Research Initiative. This work reflects the authors’ views, and neither Innovative Medicines Initiative nor the European Union, European Federation of Pharmaceutical Industries and Associations, or any associated partners are responsible for any use that may be made of the information contained therein.
Publisher Copyright:
© 2022 Society of Biological Psychiatry
PY - 2022
Y1 - 2022
N2 - Background: Although many studies have explored atypicalities in gray matter (GM) and white matter (WM) morphology of autism, most of them relied on unimodal analyses that did not benefit from the likelihood that different imaging modalities may reflect common neurobiology. We aimed to establish brain patterns of modalities that differentiate between individuals with and without autism and explore associations between these brain patterns and clinical measures in the autism group. Methods: We studied 183 individuals with autism and 157 nonautistic individuals (age range, 6–30 years) in a large, deeply phenotyped autism dataset (EU-AIMS LEAP [European Autism Interventions—A Multicentre Study for Developing New Medications Longitudinal European Autism Project]). Linked independent component analysis was used to link all participants’ GM volume and WM diffusion tensor images, and group comparisons of modality shared variances were examined. Subsequently, we performed univariate and multivariate brain-behavior correlation analyses to separately explore the relationships between brain patterns and clinical profiles. Results: One multimodal pattern was significantly related to autism. This pattern was primarily associated with GM volume in bilateral insula and frontal, precentral and postcentral, cingulate, and caudate areas and co-occurred with altered WM features in the superior longitudinal fasciculus. The brain-behavior correlation analyses showed a significant multivariate association primarily between brain patterns that involved variation of WM and symptoms of restricted and repetitive behavior in the autism group. Conclusions: Our findings demonstrate the assets of integrated analyses of GM and WM alterations to study the brain mechanisms that underpin autism and show that the complex clinical autism phenotype can be interpreted by brain covariation patterns that are spread across the brain involving both cortical and subcortical areas.
AB - Background: Although many studies have explored atypicalities in gray matter (GM) and white matter (WM) morphology of autism, most of them relied on unimodal analyses that did not benefit from the likelihood that different imaging modalities may reflect common neurobiology. We aimed to establish brain patterns of modalities that differentiate between individuals with and without autism and explore associations between these brain patterns and clinical measures in the autism group. Methods: We studied 183 individuals with autism and 157 nonautistic individuals (age range, 6–30 years) in a large, deeply phenotyped autism dataset (EU-AIMS LEAP [European Autism Interventions—A Multicentre Study for Developing New Medications Longitudinal European Autism Project]). Linked independent component analysis was used to link all participants’ GM volume and WM diffusion tensor images, and group comparisons of modality shared variances were examined. Subsequently, we performed univariate and multivariate brain-behavior correlation analyses to separately explore the relationships between brain patterns and clinical profiles. Results: One multimodal pattern was significantly related to autism. This pattern was primarily associated with GM volume in bilateral insula and frontal, precentral and postcentral, cingulate, and caudate areas and co-occurred with altered WM features in the superior longitudinal fasciculus. The brain-behavior correlation analyses showed a significant multivariate association primarily between brain patterns that involved variation of WM and symptoms of restricted and repetitive behavior in the autism group. Conclusions: Our findings demonstrate the assets of integrated analyses of GM and WM alterations to study the brain mechanisms that underpin autism and show that the complex clinical autism phenotype can be interpreted by brain covariation patterns that are spread across the brain involving both cortical and subcortical areas.
KW - Autism
KW - Canonical correlation analysis
KW - Gray matter
KW - Multimodal analysis
KW - Multivariate analysis
KW - White matter
UR - http://www.scopus.com/inward/record.url?scp=85159261764&partnerID=8YFLogxK
U2 - 10.1016/j.bpsc.2022.08.011
DO - 10.1016/j.bpsc.2022.08.011
M3 - Article
C2 - 36075529
AN - SCOPUS:85159261764
SN - 2451-9022
JO - Biological Psychiatry: Cognitive Neuroscience and Neuroimaging
JF - Biological Psychiatry: Cognitive Neuroscience and Neuroimaging
ER -