Linking functional and structural brain organisation with behaviour in autism

• Verfasst von: Oblong, Lennart [VerfasserIn]
• Verfasst von: Llera, Alberto [VerfasserIn]
• Verfasst von: Mei, Ting [VerfasserIn]
• Verfasst von: Haak, Koen [VerfasserIn]
• Verfasst von: Isakoglou, Christina [VerfasserIn]
• Verfasst von: Floris, Dorothea L. [VerfasserIn]
• Verfasst von: Durston, Sarah [VerfasserIn]
• Verfasst von: Mößnang, Carolin Ulrike [VerfasserIn]
• Verfasst von: Banaschewski, Tobias [VerfasserIn]
• Verfasst von: Baron-Cohen, Simon [VerfasserIn]
• Verfasst von: Loth, Eva [VerfasserIn]
• Verfasst von: Dell’Acqua, Flavio [VerfasserIn]
• Verfasst von: Charman, Tony [VerfasserIn]
• Verfasst von: Murphy, Declan G. M. [VerfasserIn]
• Verfasst von: Ecker, Christine [VerfasserIn]
• Verfasst von: Buitelaar, Jan K. [VerfasserIn]
• Verfasst von: Beckmann, Christian F. [VerfasserIn]
• Verfasst von: Forde, Natalie J. [VerfasserIn]
• Titel: Linking functional and structural brain organisation with behaviour in autism
• Titelzusatz: a multimodal EU-AIMS Longitudinal European Autism Project (LEAP) study
• Verf.angabe: Lennart M. Oblong, Alberto Llera, Ting Mei, Koen Haak, Christina Isakoglou, Dorothea L. Floris, Sarah Durston, Carolin Moessnang, Tobias Banaschewski, Simon Baron-Cohen, Eva Loth, Flavio Dell’Acqua, Tony Charman, Declan G. M. Murphy, Christine Ecker, Jan K. Buitelaar, Christian F. Beckmann, the EU-AIMS LEAP Group and Natalie J. Forde
• Jahr: 2023
• Umfang: 13 S.
• Illustrationen: Illustrationen
• Fussnoten: Veröffentlicht: 31. August 2023 ; Gesehen am 19.10.2023
• Titel Quelle: Enthalten in: Molecular autism
• Ort Quelle: London : BioMed Central, 2010
• Jahr Quelle: 2023
• Band/Heft Quelle: 14(2023), Artikel-ID 32, Seite 1-13
• ISSN Quelle: 2040-2392
• DOI: doi:10.1186/s13229-023-00564-3
• Datenträger: Online-Ressource
• Sprache: eng
• Sach-SW: Autism spectrum disorder
• Sach-SW: Brain-behaviour associations
• Sach-SW: Linked ICA
• K10plus-PPN: 1866392662

Abstract

Neuroimaging analyses of brain structure and function in autism have typically been conducted in isolation, missing the sensitivity gains of linking data across modalities. Here we focus on the integration of structural and functional organisational properties of brain regions. We aim to identify novel brain-organisation phenotypes of autism. We utilised multimodal MRI (T1-, diffusion-weighted and resting state functional), behavioural and clinical data from the EU AIMS Longitudinal European Autism Project (LEAP) from autistic (n = 206) and non-autistic (n = 196) participants. Of these, 97 had data from 2 timepoints resulting in a total scan number of 466. Grey matter density maps, probabilistic tractography connectivity matrices and connectopic maps were extracted from respective MRI modalities and were then integrated with Linked Independent Component Analysis. Linear mixed-effects models were used to evaluate the relationship between components and group while accounting for covariates and non-independence of participants with longitudinal data. Additional models were run to investigate associations with dimensional measures of behaviour. We identified one component that differed significantly between groups (coefficient = 0.33, padj = 0.02). This was driven (99%) by variance of the right fusiform gyrus connectopic map 2. While there were multiple nominal (uncorrected p < 0.05) associations with behavioural measures, none were significant following multiple comparison correction. Our analysis considered the relative contributions of both structural and functional brain phenotypes simultaneously, finding that functional phenotypes drive associations with autism. These findings expanded on previous unimodal studies by revealing the topographic organisation of functional connectivity patterns specific to autism and warrant further investigation.