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

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 wh...

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Main Authors: Knolle, Franziska, Arumugham, Shyam S., Barker, Roger A., Chee, Michael W. L., Justicia, Azucena, Kamble, Nitish, Lee, Jimmy, Liu, Siwei, Lenka, Abhishek, Lewis, Simon J. G., Murray, Graham K., Pal, Pramod Kumar, Saini, Jitender, Szeto, Jennifer, Yadav, Ravi, Zhou, Juan H., Koch, Kathrin
Other Authors: Lee Kong Chian School of Medicine (LKCMedicine)
Format: Article
Language:English
Published: 2024
Subjects:
Online Access:https://hdl.handle.net/10356/173634
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Institution: Nanyang Technological University
Language: English
id sg-ntu-dr.10356-173634
record_format dspace
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Medicine, Health and Life Sciences
Brain region
Cerebellum
spellingShingle Medicine, Health and Life Sciences
Brain region
Cerebellum
Knolle, Franziska
Arumugham, Shyam S.
Barker, Roger A.
Chee, Michael W. L.
Justicia, Azucena
Kamble, Nitish
Lee, Jimmy
Liu, Siwei
Lenka, Abhishek
Lewis, Simon J. G.
Murray, Graham K.
Pal, Pramod Kumar
Saini, Jitender
Szeto, Jennifer
Yadav, Ravi
Zhou, Juan H.
Koch, Kathrin
A multicentre study on grey matter morphometric biomarkers for classifying early schizophrenia and parkinson's disease psychosis
description 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.
author2 Lee Kong Chian School of Medicine (LKCMedicine)
author_facet Lee Kong Chian School of Medicine (LKCMedicine)
Knolle, Franziska
Arumugham, Shyam S.
Barker, Roger A.
Chee, Michael W. L.
Justicia, Azucena
Kamble, Nitish
Lee, Jimmy
Liu, Siwei
Lenka, Abhishek
Lewis, Simon J. G.
Murray, Graham K.
Pal, Pramod Kumar
Saini, Jitender
Szeto, Jennifer
Yadav, Ravi
Zhou, Juan H.
Koch, Kathrin
format Article
author Knolle, Franziska
Arumugham, Shyam S.
Barker, Roger A.
Chee, Michael W. L.
Justicia, Azucena
Kamble, Nitish
Lee, Jimmy
Liu, Siwei
Lenka, Abhishek
Lewis, Simon J. G.
Murray, Graham K.
Pal, Pramod Kumar
Saini, Jitender
Szeto, Jennifer
Yadav, Ravi
Zhou, Juan H.
Koch, Kathrin
author_sort Knolle, Franziska
title A multicentre study on grey matter morphometric biomarkers for classifying early schizophrenia and parkinson's disease psychosis
title_short A multicentre study on grey matter morphometric biomarkers for classifying early schizophrenia and parkinson's disease psychosis
title_full A multicentre study on grey matter morphometric biomarkers for classifying early schizophrenia and parkinson's disease psychosis
title_fullStr A multicentre study on grey matter morphometric biomarkers for classifying early schizophrenia and parkinson's disease psychosis
title_full_unstemmed A multicentre study on grey matter morphometric biomarkers for classifying early schizophrenia and parkinson's disease psychosis
title_sort multicentre study on grey matter morphometric biomarkers for classifying early schizophrenia and parkinson's disease psychosis
publishDate 2024
url https://hdl.handle.net/10356/173634
_version_ 1794549356915851264
spelling sg-ntu-dr.10356-1736342024-02-25T15:38:00Z A multicentre study on grey matter morphometric biomarkers for classifying early schizophrenia and parkinson's disease psychosis Knolle, Franziska Arumugham, Shyam S. Barker, Roger A. Chee, Michael W. L. Justicia, Azucena Kamble, Nitish Lee, Jimmy Liu, Siwei Lenka, Abhishek Lewis, Simon J. G. Murray, Graham K. Pal, Pramod Kumar Saini, Jitender Szeto, Jennifer Yadav, Ravi Zhou, Juan H. Koch, Kathrin Lee Kong Chian School of Medicine (LKCMedicine) Medicine, Health and Life Sciences Brain region Cerebellum 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. Agency for Science, Technology and Research (A*STAR) National Medical Research Council (NMRC) National Research Foundation (NRF) Published version 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). 2024-02-20T04:33:02Z 2024-02-20T04:33:02Z 2023 Journal Article Knolle, F., Arumugham, S. S., Barker, R. A., Chee, M. W. L., Justicia, A., Kamble, N., Lee, J., Liu, S., Lenka, A., Lewis, S. J. G., Murray, G. K., Pal, P. K., Saini, J., Szeto, J., Yadav, R., Zhou, J. H. & Koch, K. (2023). A multicentre study on grey matter morphometric biomarkers for classifying early schizophrenia and parkinson's disease psychosis. Npj Parkinson's Disease, 9(1), 87-. https://dx.doi.org/10.1038/s41531-023-00522-z 2373-8057 https://hdl.handle.net/10356/173634 10.1038/s41531-023-00522-z 37291143 2-s2.0-85161414205 1 9 87 en NMRC/TCR/003/2008 BRC-13/1/96/19/ 687 CBRG/0088/ 2015 npj Parkinson's Disease © 2023 The Author(s). 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