A multicentre study on grey matter morphometric biomarkers for classifying early schizophrenia and parkinson’s disease psychosis
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 similaritie...
| Main Authors: | , , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2023-06-01
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| Series: | npj Parkinson's Disease |
| Online Access: | https://doi.org/10.1038/s41531-023-00522-z |
| _version_ | 1797429540900831232 |
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| author | Franziska Knolle Shyam S. Arumugham Roger A. Barker Michael W. L. Chee Azucena Justicia Nitish Kamble Jimmy Lee Siwei Liu Abhishek Lenka Simon J. G. Lewis Graham K. Murray Pramod Kumar Pal Jitender Saini Jennifer Szeto Ravi Yadav Juan H. Zhou Kathrin Koch |
| author_facet | Franziska Knolle Shyam S. Arumugham Roger A. Barker Michael W. L. Chee Azucena Justicia Nitish Kamble Jimmy Lee Siwei Liu Abhishek Lenka Simon J. G. Lewis Graham K. Murray Pramod Kumar Pal Jitender Saini Jennifer Szeto Ravi Yadav Juan H. Zhou Kathrin Koch |
| author_sort | Franziska Knolle |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-03-09T09:14:37Z |
| format | Article |
| id | doaj.art-2d35a5e88232492d8efb7578fcbc0a17 |
| institution | Directory Open Access Journal |
| issn | 2373-8057 |
| language | English |
| last_indexed | 2024-03-09T09:14:37Z |
| publishDate | 2023-06-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | npj Parkinson's Disease |
| spelling | doaj.art-2d35a5e88232492d8efb7578fcbc0a172023-12-02T07:28:10ZengNature Portfolionpj Parkinson's Disease2373-80572023-06-019111310.1038/s41531-023-00522-zA multicentre study on grey matter morphometric biomarkers for classifying early schizophrenia and parkinson’s disease psychosisFranziska Knolle0Shyam S. Arumugham1Roger A. Barker2Michael W. L. Chee3Azucena Justicia4Nitish Kamble5Jimmy Lee6Siwei Liu7Abhishek Lenka8Simon J. G. Lewis9Graham K. Murray10Pramod Kumar Pal11Jitender Saini12Jennifer Szeto13Ravi Yadav14Juan H. Zhou15Kathrin Koch16Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Technical University of MunichDepartment of Psychiatry, National Institute of Mental Health & Neurosciences (NIMHANS)Department of Clinical Neuroscience, University of CambridgeCentre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of SingaporeDepartment of Psychiatry, University of CambridgeDepartment of Neurology, National Institute of Mental Health & Neurosciences (NIMHANS)Research Division, Institute of Mental HealthCentre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of SingaporeDepartment of Neurology, National Institute of Mental Health & Neurosciences (NIMHANS)ForeFront Parkinson’s Disease Research Clinic, Brain and Mind Centre, School of Medical Sciences, University of SydneyDepartment of Psychiatry, University of CambridgeDepartment of Neurology, National Institute of Mental Health & Neurosciences (NIMHANS)Department of Neurology, National Institute of Mental Health & Neurosciences (NIMHANS)ForeFront Parkinson’s Disease Research Clinic, Brain and Mind Centre, School of Medical Sciences, University of SydneyDepartment of Psychiatry, National Institute of Mental Health & Neurosciences (NIMHANS)Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of SingaporeDepartment of Diagnostic and Interventional Neuroradiology, School of Medicine, Technical University of MunichAbstract 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.https://doi.org/10.1038/s41531-023-00522-z |
| spellingShingle | Franziska Knolle Shyam S. Arumugham Roger A. Barker Michael W. L. Chee Azucena Justicia Nitish Kamble Jimmy Lee Siwei Liu Abhishek Lenka Simon J. G. Lewis Graham K. Murray Pramod Kumar Pal Jitender Saini Jennifer Szeto Ravi Yadav Juan H. Zhou Kathrin Koch A multicentre study on grey matter morphometric biomarkers for classifying early schizophrenia and parkinson’s disease psychosis npj Parkinson's Disease |
| 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 |
| url | https://doi.org/10.1038/s41531-023-00522-z |
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