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...
| Main Authors: | , , , , , , , , , , , , , , , , |
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| Format: | Journal Article |
| Language: | English |
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2024
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| Online Access: | https://hdl.handle.net/10356/173634 |
| _version_ | 1826118603868471296 |
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| 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 |
| 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 |
| author_sort | Knolle, Franziska |
| collection | NTU |
| 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. |
| first_indexed | 2024-10-01T04:46:12Z |
| format | Journal Article |
| id | ntu-10356/173634 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T04:46:12Z |
| publishDate | 2024 |
| record_format | dspace |
| spelling | ntu-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). 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/. application/pdf |
| 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 |
| title | 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_short | 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 |
| topic | Medicine, Health and Life Sciences Brain region Cerebellum |
| url | https://hdl.handle.net/10356/173634 |
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