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dc.contributor.authorZabihi, Mariam
dc.contributor.authorFloris, Dorothea L
dc.contributor.authorKia, Seyed Mostafa
dc.contributor.authorWolfers, Thomas
dc.contributor.authorTillmann, Julian
dc.contributor.authorArenas, Alberto Llera
dc.contributor.authorMoessnang, Carolin
dc.contributor.authorBanaschewski, Tobias
dc.contributor.authorHolt, Rosemary
dc.contributor.authorBaron-Cohen, Simon
dc.contributor.authorLoth, Eva
dc.contributor.authorCharman, Tony
dc.contributor.authorBourgeron, Thomas
dc.contributor.authorMurphy, Declan
dc.contributor.authorEcker, Christine
dc.contributor.authorBuitelaar, Jan K
dc.contributor.authorBeckmann, Christian F
dc.contributor.authorMarquand, Andre
dc.contributor.authorEU-AIMS LEAP Group
dc.date.accessioned2020-12-08T00:30:25Z
dc.date.available2020-12-08T00:30:25Z
dc.date.issued2020-11-06
dc.identifier.issn2158-3188
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/314829
dc.description.abstractAutism is a complex neurodevelopmental condition with substantial phenotypic, biological, and etiologic heterogeneity. It remains a challenge to identify biomarkers to stratify autism into replicable cognitive or biological subtypes. Here, we aim to introduce a novel methodological framework for parsing neuroanatomical subtypes within a large cohort of individuals with autism. We used cortical thickness (CT) in a large and well-characterized sample of 316 participants with autism (88 female, age mean: 17.2 ± 5.7) and 206 with neurotypical development (79 female, age mean: 17.5 ± 6.1) aged 6-31 years across six sites from the EU-AIMS multi-center Longitudinal European Autism Project. Five biologically based putative subtypes were derived using normative modeling of CT and spectral clustering. Three of these clusters showed relatively widespread decreased CT and two showed relatively increased CT. These subtypes showed morphometric differences from one another, providing a potential explanation for inconsistent case-control findings in autism, and loaded differentially and more strongly onto symptoms and polygenic risk, indicating a dilution of clinical effects across heterogeneous cohorts. Our results provide an important step towards parsing the heterogeneous neurobiology of autism.
dc.format.mediumElectronic
dc.languageeng
dc.publisherSpringer Science and Business Media LLC
dc.rightsAttribution 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectEU-AIMS LEAP Group
dc.subjectHumans
dc.subjectMagnetic Resonance Imaging
dc.subjectCase-Control Studies
dc.subjectAutistic Disorder
dc.subjectNeurobiology
dc.subjectAdolescent
dc.subjectAdult
dc.subjectChild
dc.subjectFemale
dc.subjectYoung Adult
dc.subjectAutism Spectrum Disorder
dc.titleFractionating autism based on neuroanatomical normative modeling.
dc.typeArticle
prism.issueIdentifier1
prism.publicationDate2020
prism.publicationNameTransl Psychiatry
prism.startingPage384
prism.volume10
dc.identifier.doi10.17863/CAM.61935
dcterms.dateAccepted2020-10-19
rioxxterms.versionofrecord10.1038/s41398-020-01057-0
rioxxterms.versionVoR
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserved
rioxxterms.licenseref.startdate2020-11-06
dc.contributor.orcidZabihi, Mariam [0000-0002-7083-2318]
dc.contributor.orcidKia, Seyed Mostafa [0000-0002-7128-814X]
dc.contributor.orcidBanaschewski, Tobias [0000-0003-4595-1144]
dc.contributor.orcidBaron-Cohen, Simon [0000-0001-9217-2544]
dc.contributor.orcidCharman, Tony [0000-0003-1993-6549]
dc.contributor.orcidMurphy, Declan [0000-0002-6664-7451]
dc.contributor.orcidBuitelaar, Jan K [0000-0001-8288-7757]
dc.identifier.eissn2158-3188
rioxxterms.typeJournal Article/Review
pubs.funder-project-idEuropean Commission (278948)
pubs.funder-project-idEuropean Commission and European Federation of Pharmaceutical Industries and Associations (EFPIA) FP7 Innovative Medicines Initiative (IMI) (115300)
cam.issuedOnline2020-11-06


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Attribution 4.0 International
Except where otherwise noted, this item's licence is described as Attribution 4.0 International