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A multicentre study on grey matter morphometric biomarkers for classifying early schizophrenia and parkinson's disease psychosis

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dc.contributor.author Knolle, Franziska
dc.contributor.author Arumugham, Shyam S.
dc.contributor.author Barker, Roger A.
dc.contributor.author Chee, Michael W. L.
dc.contributor.author Justicia Díaz, Azucena
dc.contributor.author Kamble, Nitish
dc.contributor.author Lee, Jimmy
dc.contributor.author Liu, Siwei
dc.contributor.author Lenka, Abhishek
dc.contributor.author Lewis, Simon J. G.
dc.contributor.author Murray, Graham K.
dc.contributor.author Pal, Pramod Kumar
dc.contributor.author Saini, Jitender
dc.contributor.author Szeto, Jennifer
dc.contributor.author Yadav, Ravi
dc.contributor.author Zhou, Juan H.
dc.contributor.author Koch, Kathrin
dc.date.accessioned 2024-04-08T09:39:50Z
dc.date.available 2024-04-08T09:39:50Z
dc.date.issued 2023
dc.identifier.citation Knolle F, Arumugham SS, Barker RA, Chee MWL, Justicia A, Kamble N, et al. A multicentre study on grey matter morphometric biomarkers for classifying early schizophrenia and parkinson's disease psychosis. NPJ Parkinsons Dis. 2023 Jun 8;9(1):87. DOI: 10.1038/s41531-023-00522-z
dc.identifier.issn 2373-8057
dc.identifier.uri http://hdl.handle.net/10230/59686
dc.description.abstract Psychotic symptoms occur in a majority of schizophrenia patients and in ~50% of all Parkinson's disease (PD) patients. Altered grey matter (GM) structure within several brain areas and networks may contribute to their pathogenesis. Little is known, however, about transdiagnostic similarities when psychotic symptoms occur in different disorders, such as in schizophrenia and PD. The present study investigated a large, multicenter sample containing 722 participants: 146 patients with first episode psychosis, FEP; 106 individuals in at-risk mental state for developing psychosis, ARMS; 145 healthy controls matching FEP and ARMS, Con-Psy; 92 PD patients with psychotic symptoms, PDP; 145 PD patients without psychotic symptoms, PDN; 88 healthy controls matching PDN and PDP, Con-PD. We applied source-based morphometry in association with receiver operating curves (ROC) analyses to identify common GM structural covariance networks (SCN) and investigated their accuracy in identifying the different patient groups. We assessed group-specific homogeneity and variability across the different networks and potential associations with clinical symptoms. SCN-extracted GM values differed significantly between FEP and Con-Psy, PDP and Con-PD, PDN and Con-PD, as well as PDN and PDP, indicating significant overall grey matter reductions in PD and early schizophrenia. ROC analyses showed that SCN-based classification algorithms allow good classification (AUC ~0.80) of FEP and Con-Psy, and fair performance (AUC ~0.72) when differentiating PDP from Con-PD. Importantly, the best performance was found in partly the same networks, including the thalamus. Alterations within selected SCNs may be related to the presence of psychotic symptoms in both early schizophrenia and PD psychosis, indicating some commonality of underlying mechanisms. Furthermore, results provide evidence that GM volume within specific SCNs may serve as a biomarker for identifying FEP and PDP.
dc.description.sponsorship We thank all participants for their time and dedication. F.K. received funding from the European Union’s Horizon 2020 [Grant number 754462]. Subjects recruited at the National Institute of Mental Health and Neurosciences (NIMHANS), Bangalore, India, were part of a project funded by the Indian Council of Medical Research (ICMR). [ICMR/003/304/2013/00694]. S.J.G.L. is supported by a National Health and Medical Research Council Leadership Fellowship (1195830). The Singapore Translational and Clinical Research in Psychosis is supported by the National Research Foundation Singapore under the National Medical Research Council Translational and Clinical Research Flagship Programme (NMRC/TCR/003/2008). This study is also supported by the Agency for Science, Technology, and Research (A*STAR) Singapore under the Biomedical Research Council (13/1/96/19/ 687), National Medical Research Council (CBRG/0088/2015), and Duke-NUS Medical School Signature Research Programme funded by Ministry of Health and Yong Loo Lin School of Medicine Research fund, National University of Singapore. SSA is supported by DBT/Wellcome Trust India Alliance Intermediate Clinical and Public Health Fellowship grant (IA/CPHI/18/1/50393).
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher Nature Research
dc.relation.ispartof NPJ Parkinsons Dis. 2023 Jun 8;9(1):87
dc.rights © The Author(s) 2023. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
dc.rights.uri http://creativecommons.org/licenses/by/4.0/
dc.title A multicentre study on grey matter morphometric biomarkers for classifying early schizophrenia and parkinson's disease psychosis
dc.type info:eu-repo/semantics/article
dc.identifier.doi http://dx.doi.org/10.1038/s41531-023-00522-z
dc.subject.keyword Parkinson's disease
dc.subject.keyword Psychosis
dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/754462
dc.rights.accessRights info:eu-repo/semantics/openAccess
dc.type.version info:eu-repo/semantics/publishedVersion

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