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Owens-Walton C, Nir TM, Al-Bachari S, Ambrogi S, Anderson TJ, Aventurato ÍK, Cendes F, Chen YL, Ciullo V, Cook P, Dalrymple-Alford JC, Dirkx MF, Druzgal J, Emsley HCA, Guimarães R, Haroon HA, Helmich RC, Hu MT, Johansson ME, Kim HB, Klein JC, Laansma M, Lawrence KE, Lochner C, Mackay C, McMillan CT, Melzer TR, Nabulsi L, Newman B, Opriessnig P, Parkes LM, Pellicano C, Piras F, Piras F, Pirpamer L, Pitcher TL, Poston KL, Roos A, Silva LS, Schmidt R, Schwingenschuh P, Shahid-Besanti M, Spalletta G, Stein DJ, Thomopoulos SI, Tosun D, Tsai CC, van den Heuvel OA, van Heese E, Vecchio D, Villalón-Reina JE, Vriend C, Wang JJ, Wu YR, Yasuda CL, Thompson PM, Jahanshad N, van der Werf Y. A worldwide study of white matter microstructural alterations in people living with Parkinson's disease. NPJ Parkinsons Dis 2024; 10:151. [PMID: 39128907 PMCID: PMC11317500 DOI: 10.1038/s41531-024-00758-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2024] [Accepted: 07/22/2024] [Indexed: 08/13/2024] Open
Abstract
The progression of Parkinson's disease (PD) is associated with microstructural alterations in neural pathways, contributing to both motor and cognitive decline. However, conflicting findings have emerged due to the use of heterogeneous methods in small studies. Here we performed a large diffusion MRI study in PD, integrating data from 17 cohorts worldwide, to identify stage-specific profiles of white matter differences. Diffusion-weighted MRI data from 1654 participants diagnosed with PD (age: 20-89 years; 33% female) and 885 controls (age: 19-84 years; 47% female) were analyzed using the ENIGMA-DTI protocol to evaluate white matter microstructure. Skeletonized maps of fractional anisotropy (FA) and mean diffusivity (MD) were compared across Hoehn and Yahr (HY) disease groups and controls to reveal the profile of white matter alterations at different stages. We found an enhanced, more widespread pattern of microstructural alterations with each stage of PD, with eventually lower FA and higher MD in almost all regions of interest: Cohen's d effect sizes reached d = -1.01 for FA differences in the fornix at PD HY Stage 4/5. The early PD signature in HY stage 1 included higher FA and lower MD across the entire white matter skeleton, in a direction opposite to that typical of other neurodegenerative diseases. FA and MD were associated with motor and non-motor clinical dysfunction. While overridden by degenerative changes in the later stages of PD, early PD is associated with paradoxically higher FA and lower MD in PD, consistent with early compensatory changes associated with the disorder.
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Grants
- R01 AG058854 NIA NIH HHS
- P41 EB015922 NIBIB NIH HHS
- R01NS107513 U.S. Department of Health & Human Services | NIH | National Institute of Neurological Disorders and Stroke (NINDS)
- R01 MH117601 NIMH NIH HHS
- R01 NS107513 NINDS NIH HHS
- U19 AG062418 NIA NIH HHS
- F32 MH122057 NIMH NIH HHS
- R01 AG059874 NIA NIH HHS
- U.S. Alzheimer’s Association (AARG-23-1149996)
- Health Research Council of New Zealand (20/538; 21/165)
- São Paulo Research Foundation FAPESP-BRAINN Grants# 2013-07559-3 / FAPESP #2022-1178-4
- São Paulo Research Foundation FAPESP-BRAINN Grant # 2013–07559-3.
- Health Research Council of New Zealand (20/538); Marsden Fund New Zealand (UOC2105); Neurological Foundation of New Zealand (2232 PRG); Research and Education Trust Pacific Radiology (MRIJDA).
- Grant from ParkinsonNL (P2023-14); Honoraria from Movement Disorders Society Quebec.
- NINDS R01NS107513
- Engineering and Physical Sciences Research Council (EPSRC) UK
- Parkinson's UK, Cure Parkinsons Trust, Oxford Biomedical Research Centre, GSK-Oxford IMCM.
- JK is supported by the National Institute for Health Research (NIHR) Oxford Biomedical Research Centre (BRC), and the NIHR Oxford Health Clinical Research Facility. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health.
- NIMH 32MH122057
- U19 AG062418
- Health Research Council of New Zealand (20/538); Neurological Foundation of New Zealand (2232 PRG); Research and Education Trust Pacific Radiology (MRIJDA).
- EPSRC UK, MRC UK, GE medical systems, Academy of Medical Sciences UK
- Italian Ministry of Health, grant number RF-2019-12370182
- Health Research Council of New Zealand (21/165)
- Personal fees from Bial, AbbVie and Boston Scientific.
- NIH/NIA
- São Paulo Research Foundation FAPESP-BRAINN Grant # 2013–07559-3; CNPQ (#315953/2021-7) National Council for Scientific and Technological Development
- U.S. Department of Health & Human Services | NIH | National Institute of Neurological Disorders and Stroke (NINDS)
- R01AG059874, R01MH117601, R01NS107513, R01AG058854, P41EB015922
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Affiliation(s)
- Conor Owens-Walton
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA.
| | - Talia M Nir
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | | | - Sonia Ambrogi
- Laboratory of Neuropsychiatry, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Tim J Anderson
- Department of Medicine, University of Otago, Christchurch, Christchurch, New Zealand
- New Zealand Brain Research Institute, Christchurch, New Zealand
- Neurology Department, Te Whatu Ora-Health New Zealand Waitaha Canterbury, Christchurch, New Zealand
| | - Ítalo Karmann Aventurato
- Department of Neurology, University of Campinas-UNICAMP, Campinas, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology, Campinas, Brazil
| | - Fernando Cendes
- Department of Neurology, University of Campinas-UNICAMP, Campinas, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology, Campinas, Brazil
| | - Yao-Liang Chen
- Department of Diagnostic Radiology, Chang Gung Memorial Hospital, Keelung, Taiwan, ROC
- Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital, Linkou Medical Center, Taoyuan City, Taiwan, ROC
| | - Valentina Ciullo
- Laboratory of Neuropsychiatry, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Phil Cook
- University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - John C Dalrymple-Alford
- New Zealand Brain Research Institute, Christchurch, New Zealand
- Te Kura Mahi ā- Hirikapo | School of Psychology, Speech and Hearing, University of Canterbury, Christchurch, New Zealand
| | - Michiel F Dirkx
- Department of Neurology and Center of Expertise for Parkinson & Movement Disorders, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands
| | - Jason Druzgal
- Department of Radiology and Medical Imaging, University of Virginia, Charlottesville, VA, USA
| | - Hedley C A Emsley
- Lancaster Medical School, Lancaster University, Lancaster, UK
- Department of Neurology, Lancashire Teaching Hospitals NHS Foundation Trust, Preston, UK
| | - Rachel Guimarães
- Department of Neurology, University of Campinas-UNICAMP, Campinas, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology, Campinas, Brazil
| | - Hamied A Haroon
- Division of Psychology, Communication & Human Neuroscience, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester Academic Health Science Centre, Manchester, UK
- Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, Northern Care Alliance & University of Manchester, Manchester, UK
| | - Rick C Helmich
- Department of Neurology and Center of Expertise for Parkinson & Movement Disorders, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands
- Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, The Netherlands
| | - Michele T Hu
- Oxford Parkinson's Disease Centre, Nuffield, Department of Clinical Neurosciences, Division of Clinical Neurology, University of Oxford, Oxford, UK
| | - Martin E Johansson
- Department of Neurology and Center of Expertise for Parkinson & Movement Disorders, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands
- Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, The Netherlands
| | - Ho Bin Kim
- Department of Neurology & Neurological Sciences, Stanford University, Palo Alto, CA, USA
| | - Johannes C Klein
- Oxford Parkinson's Disease Centre, Nuffield, Department of Clinical Neurosciences, Division of Clinical Neurology, University of Oxford, Oxford, UK
| | - Max Laansma
- Amsterdam UMC, Dept. Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Katherine E Lawrence
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Christine Lochner
- SA MRC Unit on Risk and Resilience in Mental Disorders, Department of Psychiatry, Stellenbosch University, Cape Town, South Africa
| | - Clare Mackay
- Oxford Parkinson's Disease Centre, Nuffield, Department of Clinical Neurosciences, Division of Clinical Neurology, University of Oxford, Oxford, UK
| | - Corey T McMillan
- University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Tracy R Melzer
- Department of Medicine, University of Otago, Christchurch, Christchurch, New Zealand
- New Zealand Brain Research Institute, Christchurch, New Zealand
- Te Kura Mahi ā- Hirikapo | School of Psychology, Speech and Hearing, University of Canterbury, Christchurch, New Zealand
| | - Leila Nabulsi
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Ben Newman
- Department of Radiology and Medical Imaging, University of Virginia, Charlottesville, VA, USA
| | - Peter Opriessnig
- Department of Neurology, Clinical Division of Neurogeriatrics, Medical University Graz, Graz, Austria
| | - Laura M Parkes
- Division of Psychology, Communication & Human Neuroscience, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester Academic Health Science Centre, Manchester, UK
- Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, Northern Care Alliance & University of Manchester, Manchester, UK
| | - Clelia Pellicano
- Laboratory of Neuropsychiatry, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Fabrizio Piras
- Laboratory of Neuropsychiatry, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Federica Piras
- Laboratory of Neuropsychiatry, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Lukas Pirpamer
- Department of Neurology, Clinical Division of Neurogeriatrics, Medical University Graz, Graz, Austria
| | - Toni L Pitcher
- Department of Medicine, University of Otago, Christchurch, Christchurch, New Zealand
- New Zealand Brain Research Institute, Christchurch, New Zealand
| | - Kathleen L Poston
- Department of Neurology & Neurological Sciences, Stanford University, Palo Alto, CA, USA
| | - Annerine Roos
- SA MRC Unit on Risk and Resilience in Mental Disorders, Department of Psychiatry and Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Lucas Scárdua Silva
- Department of Neurology, University of Campinas-UNICAMP, Campinas, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology, Campinas, Brazil
| | - Reinhold Schmidt
- Department of Neurology, Clinical Division of Neurogeriatrics, Medical University Graz, Graz, Austria
| | - Petra Schwingenschuh
- Department of Neurology, Clinical Division of Neurogeriatrics, Medical University Graz, Graz, Austria
| | - Marian Shahid-Besanti
- Department of Neurology & Neurological Sciences, Stanford University, Palo Alto, CA, USA
| | | | - Dan J Stein
- SA MRC Unit on Risk and Resilience in Mental Disorders, Department of Psychiatry and Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Sophia I Thomopoulos
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Duygu Tosun
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Chih-Chien Tsai
- Healthy Aging Research Center, Chang Gung University, Taoyuan City, Taiwan, ROC
- Department of Medical Imaging and Radiological Sciences, Chang Gung University, Taoyuan City, Taiwan, ROC
| | - Odile A van den Heuvel
- Department of Neurology & Neurological Sciences, Stanford University, Palo Alto, CA, USA
- Amsterdam UMC, Dept. Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam UMC, Department of Psychiatry, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Eva van Heese
- Department of Neurology & Neurological Sciences, Stanford University, Palo Alto, CA, USA
- Amsterdam UMC, Dept. Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Daniela Vecchio
- Laboratory of Neuropsychiatry, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Julio E Villalón-Reina
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Chris Vriend
- Department of Neurology & Neurological Sciences, Stanford University, Palo Alto, CA, USA
- Amsterdam UMC, Department of Psychiatry, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging program, Amsterdam, The Netherlands
| | - Jiun-Jie Wang
- Department of Diagnostic Radiology, Chang Gung Memorial Hospital, Keelung, Taiwan, ROC
- Healthy Aging Research Center, Chang Gung University, Taoyuan City, Taiwan, ROC
- Department of Medical Imaging and Radiological Sciences, Chang Gung University, Taoyuan City, Taiwan, ROC
- Department of Chemical Engineering, Ming-Chi University of Technology, New Taipei City, Taiwan, ROC
| | - Yih-Ru Wu
- Department of Neurology, Chang Gung Memorial Hospital, Linkou Medical Center, Taoyuan City, Taiwan, ROC
- Department of Neurology, College of Medicine, Chang Gung University, Taoyuan City, Taiwan, ROC
| | - Clarissa Lin Yasuda
- Department of Neurology, University of Campinas-UNICAMP, Campinas, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology, Campinas, Brazil
| | - Paul M Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Neda Jahanshad
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Ysbrand van der Werf
- Department of Neurology & Neurological Sciences, Stanford University, Palo Alto, CA, USA
- Amsterdam UMC, Dept. Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
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Chen YS, Kuo CY, Lu CH, Wang YW, Chou KH, Lin WC. Multiscale brain age prediction reveals region-specific accelerated brain aging in Parkinson's disease. Neurobiol Aging 2024; 140:122-129. [PMID: 38776615 DOI: 10.1016/j.neurobiolaging.2024.05.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2023] [Revised: 04/20/2024] [Accepted: 05/08/2024] [Indexed: 05/25/2024]
Abstract
Brain biological age, which measures the aging process in the brain using neuroimaging data, has been used to assess advanced brain aging in neurodegenerative diseases, including Parkinson disease (PD). However, assuming that whole brain degeneration is uniform may not be sufficient for assessing the complex neurodegenerative processes in PD. In this study we constructed a multiscale brain age prediction models based on structural MRI of 1240 healthy participants. To assess the brain aging patterns using the brain age prediction model, 93 PD patients and 91 healthy controls matching for sex and age were included. We found increased global and regional brain age in PD patients. The advanced aging regions were predominantly noted in the frontal and temporal cortices, limbic system, basal ganglia, thalamus, and cerebellum. Furthermore, region-level rather than global brain age in PD patients was associated with disease severity. Our multiscale brain age prediction model could aid in the development of objective image-based biomarkers to detect advanced brain aging in neurodegenerative diseases.
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Affiliation(s)
- Yueh-Sheng Chen
- Department of Diagnostic Radiology, Kaohsiung Chang Gung Memorial Hospital, and Chang Gung University College of Medicine, Kaohsiung, Taiwan
| | - Chen-Yuan Kuo
- Institute of Neuroscience, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Cheng-Hsien Lu
- Department of Neurology, Kaohsiung Chang Gung Memorial Hospital, and Chang Gung University College of Medicine, Kaohsiung, Taiwan
| | - Yuan-Wei Wang
- The Science & Technology Policy Research and Information Center, National Applied Research Laboratories(NARLabs), Taipei, Taiwan
| | - Kun-Hsien Chou
- Institute of Neuroscience, National Yang Ming Chiao Tung University, Taipei, Taiwan; Brain Research Center, National Yang Ming Chiao Tung University, Taipei, Taiwan.
| | - Wei-Che Lin
- Department of Diagnostic Radiology, Kaohsiung Chang Gung Memorial Hospital, and Chang Gung University College of Medicine, Kaohsiung, Taiwan.
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3
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Zhao S, Huang Y, Shi S, Chen W, Chen R, Wang Z, Wang D. Causal effects of hypertensive disorders of pregnancy on structural changes in specific brain regions: a Mendelian randomization study. Cereb Cortex 2024; 34:bhae282. [PMID: 38984704 DOI: 10.1093/cercor/bhae282] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2024] [Revised: 06/16/2024] [Accepted: 06/21/2024] [Indexed: 07/11/2024] Open
Abstract
This study utilized Mendelian randomization to explore the impact of hypertensive disorders of pregnancy and their subtypes on brain structures, using genome-wide association study data from the FinnGen consortium for hypertensive disorders of pregnancy exposure and brain structure data from the ENIGMA consortium as outcomes. The inverse-variance weighted method, along with Cochran's Q test, Mendelian randomization-Egger regression, Mendelian randomization-PRESSO global test, and the leave-one-out approach, were applied to infer causality and assess heterogeneity and pleiotropy. Findings indicate hypertensive disorders of pregnancy are associated with structural brain alterations, including reduced cortical thickness in areas like the insula, isthmus cingulate gyrus, superior temporal gyrus, temporal pole, and transverse temporal gyrus, and an increased surface area in the superior frontal gyrus. Specific associations were found for hypertensive disorders of pregnancy subtypes: chronic hypertension with superimposed preeclampsia increased cortical thickness in the supramarginal gyrus; preeclampsia/eclampsia led to thinner cortex in the lingual gyrus and larger hippocampal volume and superior parietal lobule surface area. Chronic hypertension was associated with reduced cortical thickness in the caudal and rostral anterior cingulate and increased surface area of the cuneus and thickness of the pars orbitalis cortex. Gestational hypertension showed no significant brain region changes. These insights clarify hypertensive disorders of pregnancies' neurological and cognitive effects by identifying affected brain regions.
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Affiliation(s)
- Shanshan Zhao
- Department of Obstetrics and Gynecology, The First Affiliated Hospital of Sun Yat-sen University, 58 Zhongshan Road II, Guangzhou 510080, China
- Guangdong Provincial Clinical Research Center for Obstetrical and Gynecological Diseases, 58 Zhongshan Road II, Guangzhou 510080, China
| | - Yihong Huang
- Department of Obstetrics and Gynecology, The First Affiliated Hospital of Sun Yat-sen University, 58 Zhongshan Road II, Guangzhou 510080, China
- Guangdong Provincial Clinical Research Center for Obstetrical and Gynecological Diseases, 58 Zhongshan Road II, Guangzhou 510080, China
| | - Shaole Shi
- Department of Obstetrics and Gynecology, The First Affiliated Hospital of Sun Yat-sen University, 58 Zhongshan Road II, Guangzhou 510080, China
- Guangdong Provincial Clinical Research Center for Obstetrical and Gynecological Diseases, 58 Zhongshan Road II, Guangzhou 510080, China
| | - Wei Chen
- Department of Obstetrics and Gynecology, The First Affiliated Hospital of Sun Yat-sen University, 58 Zhongshan Road II, Guangzhou 510080, China
- Guangdong Provincial Clinical Research Center for Obstetrical and Gynecological Diseases, 58 Zhongshan Road II, Guangzhou 510080, China
| | - Run Chen
- Department of Obstetrics and Gynecology, The First Affiliated Hospital of Sun Yat-sen University, 58 Zhongshan Road II, Guangzhou 510080, China
- Guangdong Provincial Clinical Research Center for Obstetrical and Gynecological Diseases, 58 Zhongshan Road II, Guangzhou 510080, China
| | - Zilian Wang
- Department of Obstetrics and Gynecology, The First Affiliated Hospital of Sun Yat-sen University, 58 Zhongshan Road II, Guangzhou 510080, China
- Guangdong Provincial Clinical Research Center for Obstetrical and Gynecological Diseases, 58 Zhongshan Road II, Guangzhou 510080, China
| | - Dongyu Wang
- Department of Obstetrics and Gynecology, The First Affiliated Hospital of Sun Yat-sen University, 58 Zhongshan Road II, Guangzhou 510080, China
- Guangdong Provincial Clinical Research Center for Obstetrical and Gynecological Diseases, 58 Zhongshan Road II, Guangzhou 510080, China
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Jia M, Yang S, Li S, Chen S, Wu L, Li J, Wang H, Wang C, Liu Q, Wu K. Early identification of Parkinson's disease with anxiety based on combined clinical and MRI features. Front Aging Neurosci 2024; 16:1414855. [PMID: 38903898 PMCID: PMC11188332 DOI: 10.3389/fnagi.2024.1414855] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2024] [Accepted: 05/15/2024] [Indexed: 06/22/2024] Open
Abstract
Objective To identify cortical and subcortical volume, thickness and cortical area features and the networks they constituted related to anxiety in Parkinson's disease (PD) using structural magnetic resonance imaging (sMRI), and to integrate multimodal features based on machine learning to identify PD-related anxiety. Methods A total of 219 patients with PD were retrospectively enrolled in the study. 291 sMRI features including cortical volume, subcortical volume, cortical thickness, and cortical area, as well as 17 clinical features, were extracted. Graph theory analysis was used to explore structural networks. A support vector machine (SVM) combination model, which used both sMRI and clinical features to identify participants with PD-related anxiety, was developed and evaluated. The performance of SVM models were evaluated. The mean impact value (MIV) of the feature importance evaluation algorithm was used to rank the relative importance of sMRI features and clinical features within the model. Results 17 significant sMRI variables associated with PD-related anxiety was used to build a brain structural network. And seven sMRI and 5 clinical features with statistically significant differences were incorporated into the SVM model. The comprehensive model achieved higher performance than clinical features or sMRI features did alone, with an accuracy of 0.88, a precision of 0.86, a sensitivity of 0.81, an F1-Score of 0.83, a macro-average of 0.85, a weighted-average of 0.92, an AUC of 0.88, and a result of 10-fold cross-validation of 0.91 in test set. The sMRI feature right medialorbitofrontal thickness had the highest impact on the prediction model. Conclusion We identified the brain structural features and networks related to anxiety in PD, and developed and internally validated a comprehensive model with multimodal features in identifying.
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Affiliation(s)
- Min Jia
- Department of Neurology, The Central Hospital of Enshi Tujia and Miao Autonomous Prefecture, Enshi, Hubei, China
| | - Shijun Yang
- Department of Neurology, The Central Hospital of Enshi Tujia and Miao Autonomous Prefecture, Enshi, Hubei, China
| | - Shanshan Li
- Department of Medical Ultrasound, The Central Hospital of Enshi Tujia and Miao Autonomous Prefecture, Enshi, Hubei, China
| | - Siying Chen
- Hubei Minzu University, The Central Hospital of Enshi Tujia and Miao Autonomous Prefecture, Enshi, Hubei, China
| | - Lishuang Wu
- Department of Neurology, The Central Hospital of Enshi Tujia and Miao Autonomous Prefecture, Enshi, Hubei, China
| | - Jinlan Li
- Department of Neurology, The Central Hospital of Enshi Tujia and Miao Autonomous Prefecture, Enshi, Hubei, China
| | - Hanlin Wang
- Department of Medicine, The Xi’an Jiaotong University, Xi’an, Shanxi, China
| | - Congping Wang
- Department of Neurology, The Central Hospital of Enshi Tujia and Miao Autonomous Prefecture, Enshi, Hubei, China
| | - Qunhui Liu
- Department of Neurology, The Central Hospital of Enshi Tujia and Miao Autonomous Prefecture, Enshi, Hubei, China
| | - Kemei Wu
- Department of Neurology, The Central Hospital of Enshi Tujia and Miao Autonomous Prefecture, Enshi, Hubei, China
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Basaia S, Agosta F, Sarasso E, Balestrino R, Stojković T, Stanković I, Tomić A, Marković V, Vignaroli F, Stefanova E, Kostić VS, Filippi M. Brain Connectivity Networks Constructed Using MRI for Predicting Patterns of Atrophy Progression in Parkinson Disease. Radiology 2024; 311:e232454. [PMID: 38916507 DOI: 10.1148/radiol.232454] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/26/2024]
Abstract
Background Whether connectome mapping of structural and functional connectivity across the brain could be used to predict patterns of atrophy progression in patients with mild Parkinson disease (PD) has not been well studied. Purpose To assess the structural and functional connectivity of brain regions in healthy controls and its relationship with the spread of gray matter (GM) atrophy in patients with mild PD. Materials and Methods This prospective study included participants with mild PD and controls recruited from a single center between January 2012 and December 2023. Participants with PD underwent three-dimensional T1-weighted brain MRI, and the extent of regional GM atrophy was determined at baseline and every year for 3 years. The structural and functional brain connectome was constructed using diffusion tensor imaging and resting-state functional MRI in healthy controls. Disease exposure (DE) indexes-indexes of the pathology of each brain region-were defined as a function of the structural or functional connectivity of all the connected regions in the healthy connectome and the severity of atrophy of the connected regions in participants with PD. Partial correlations were tested between structural and functional DE indexes of each GM region at 1- or 2-year follow-up and atrophy progression at 2- or 3-year follow-up. Prediction models of atrophy at 2- or 3-year follow-up were constructed using exhaustive feature selection. Results A total of 86 participants with mild PD (mean age at MRI, 60 years ± 8 [SD]; 48 male) and 60 healthy controls (mean age at MRI, 62 years ± 9; 31 female) were included. DE indexes at 1 and 2 years were correlated with atrophy at 2 and 3 years (r range, 0.22-0.33; P value range, .002-.04). Models including DE indexes predicted GM atrophy accumulation over 3 years in the right caudate nucleus and some frontal, parietal, and temporal brain regions (R2 range, 0.40-0.61; all P < .001). Conclusion The structural and functional organization of the brain connectome plays a role in atrophy progression in the early stages of PD. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Yamada in this issue.
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Affiliation(s)
- Silvia Basaia
- From the Neuroimaging Research Unit, Division of Neuroscience (S.B., F.A., E. Sarasso, R.B., M.F.), Neurology Unit (F.A., M.F.), Department of Rehabilitation and Functional Recovery (E. Sarasso), Neurorehabilitation Unit (M.F.), and Neurophysiology Service (M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan, Italy; Vita-Salute San Raffaele University, Milan, Italy (F.A., R.B., M.F.); Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, and Maternal Child Health, University of Genoa, Genoa, Italy (E. Sarasso); Clinic of Neurology, Faculty of Medicine, University of Belgrade, Belgrade, Serbia (T.S., I.S., A.T., V.M., E. Stefanova, V.S.K.); and Neurology Unit, University Hospital Maggiore della Carità, Novara, Italy (F.V.)
| | - Federica Agosta
- From the Neuroimaging Research Unit, Division of Neuroscience (S.B., F.A., E. Sarasso, R.B., M.F.), Neurology Unit (F.A., M.F.), Department of Rehabilitation and Functional Recovery (E. Sarasso), Neurorehabilitation Unit (M.F.), and Neurophysiology Service (M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan, Italy; Vita-Salute San Raffaele University, Milan, Italy (F.A., R.B., M.F.); Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, and Maternal Child Health, University of Genoa, Genoa, Italy (E. Sarasso); Clinic of Neurology, Faculty of Medicine, University of Belgrade, Belgrade, Serbia (T.S., I.S., A.T., V.M., E. Stefanova, V.S.K.); and Neurology Unit, University Hospital Maggiore della Carità, Novara, Italy (F.V.)
| | - Elisabetta Sarasso
- From the Neuroimaging Research Unit, Division of Neuroscience (S.B., F.A., E. Sarasso, R.B., M.F.), Neurology Unit (F.A., M.F.), Department of Rehabilitation and Functional Recovery (E. Sarasso), Neurorehabilitation Unit (M.F.), and Neurophysiology Service (M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan, Italy; Vita-Salute San Raffaele University, Milan, Italy (F.A., R.B., M.F.); Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, and Maternal Child Health, University of Genoa, Genoa, Italy (E. Sarasso); Clinic of Neurology, Faculty of Medicine, University of Belgrade, Belgrade, Serbia (T.S., I.S., A.T., V.M., E. Stefanova, V.S.K.); and Neurology Unit, University Hospital Maggiore della Carità, Novara, Italy (F.V.)
| | - Roberta Balestrino
- From the Neuroimaging Research Unit, Division of Neuroscience (S.B., F.A., E. Sarasso, R.B., M.F.), Neurology Unit (F.A., M.F.), Department of Rehabilitation and Functional Recovery (E. Sarasso), Neurorehabilitation Unit (M.F.), and Neurophysiology Service (M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan, Italy; Vita-Salute San Raffaele University, Milan, Italy (F.A., R.B., M.F.); Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, and Maternal Child Health, University of Genoa, Genoa, Italy (E. Sarasso); Clinic of Neurology, Faculty of Medicine, University of Belgrade, Belgrade, Serbia (T.S., I.S., A.T., V.M., E. Stefanova, V.S.K.); and Neurology Unit, University Hospital Maggiore della Carità, Novara, Italy (F.V.)
| | - Tanja Stojković
- From the Neuroimaging Research Unit, Division of Neuroscience (S.B., F.A., E. Sarasso, R.B., M.F.), Neurology Unit (F.A., M.F.), Department of Rehabilitation and Functional Recovery (E. Sarasso), Neurorehabilitation Unit (M.F.), and Neurophysiology Service (M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan, Italy; Vita-Salute San Raffaele University, Milan, Italy (F.A., R.B., M.F.); Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, and Maternal Child Health, University of Genoa, Genoa, Italy (E. Sarasso); Clinic of Neurology, Faculty of Medicine, University of Belgrade, Belgrade, Serbia (T.S., I.S., A.T., V.M., E. Stefanova, V.S.K.); and Neurology Unit, University Hospital Maggiore della Carità, Novara, Italy (F.V.)
| | - Iva Stanković
- From the Neuroimaging Research Unit, Division of Neuroscience (S.B., F.A., E. Sarasso, R.B., M.F.), Neurology Unit (F.A., M.F.), Department of Rehabilitation and Functional Recovery (E. Sarasso), Neurorehabilitation Unit (M.F.), and Neurophysiology Service (M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan, Italy; Vita-Salute San Raffaele University, Milan, Italy (F.A., R.B., M.F.); Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, and Maternal Child Health, University of Genoa, Genoa, Italy (E. Sarasso); Clinic of Neurology, Faculty of Medicine, University of Belgrade, Belgrade, Serbia (T.S., I.S., A.T., V.M., E. Stefanova, V.S.K.); and Neurology Unit, University Hospital Maggiore della Carità, Novara, Italy (F.V.)
| | - Aleksandra Tomić
- From the Neuroimaging Research Unit, Division of Neuroscience (S.B., F.A., E. Sarasso, R.B., M.F.), Neurology Unit (F.A., M.F.), Department of Rehabilitation and Functional Recovery (E. Sarasso), Neurorehabilitation Unit (M.F.), and Neurophysiology Service (M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan, Italy; Vita-Salute San Raffaele University, Milan, Italy (F.A., R.B., M.F.); Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, and Maternal Child Health, University of Genoa, Genoa, Italy (E. Sarasso); Clinic of Neurology, Faculty of Medicine, University of Belgrade, Belgrade, Serbia (T.S., I.S., A.T., V.M., E. Stefanova, V.S.K.); and Neurology Unit, University Hospital Maggiore della Carità, Novara, Italy (F.V.)
| | - Vladana Marković
- From the Neuroimaging Research Unit, Division of Neuroscience (S.B., F.A., E. Sarasso, R.B., M.F.), Neurology Unit (F.A., M.F.), Department of Rehabilitation and Functional Recovery (E. Sarasso), Neurorehabilitation Unit (M.F.), and Neurophysiology Service (M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan, Italy; Vita-Salute San Raffaele University, Milan, Italy (F.A., R.B., M.F.); Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, and Maternal Child Health, University of Genoa, Genoa, Italy (E. Sarasso); Clinic of Neurology, Faculty of Medicine, University of Belgrade, Belgrade, Serbia (T.S., I.S., A.T., V.M., E. Stefanova, V.S.K.); and Neurology Unit, University Hospital Maggiore della Carità, Novara, Italy (F.V.)
| | - Francesca Vignaroli
- From the Neuroimaging Research Unit, Division of Neuroscience (S.B., F.A., E. Sarasso, R.B., M.F.), Neurology Unit (F.A., M.F.), Department of Rehabilitation and Functional Recovery (E. Sarasso), Neurorehabilitation Unit (M.F.), and Neurophysiology Service (M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan, Italy; Vita-Salute San Raffaele University, Milan, Italy (F.A., R.B., M.F.); Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, and Maternal Child Health, University of Genoa, Genoa, Italy (E. Sarasso); Clinic of Neurology, Faculty of Medicine, University of Belgrade, Belgrade, Serbia (T.S., I.S., A.T., V.M., E. Stefanova, V.S.K.); and Neurology Unit, University Hospital Maggiore della Carità, Novara, Italy (F.V.)
| | - Elka Stefanova
- From the Neuroimaging Research Unit, Division of Neuroscience (S.B., F.A., E. Sarasso, R.B., M.F.), Neurology Unit (F.A., M.F.), Department of Rehabilitation and Functional Recovery (E. Sarasso), Neurorehabilitation Unit (M.F.), and Neurophysiology Service (M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan, Italy; Vita-Salute San Raffaele University, Milan, Italy (F.A., R.B., M.F.); Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, and Maternal Child Health, University of Genoa, Genoa, Italy (E. Sarasso); Clinic of Neurology, Faculty of Medicine, University of Belgrade, Belgrade, Serbia (T.S., I.S., A.T., V.M., E. Stefanova, V.S.K.); and Neurology Unit, University Hospital Maggiore della Carità, Novara, Italy (F.V.)
| | - Vladimir S Kostić
- From the Neuroimaging Research Unit, Division of Neuroscience (S.B., F.A., E. Sarasso, R.B., M.F.), Neurology Unit (F.A., M.F.), Department of Rehabilitation and Functional Recovery (E. Sarasso), Neurorehabilitation Unit (M.F.), and Neurophysiology Service (M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan, Italy; Vita-Salute San Raffaele University, Milan, Italy (F.A., R.B., M.F.); Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, and Maternal Child Health, University of Genoa, Genoa, Italy (E. Sarasso); Clinic of Neurology, Faculty of Medicine, University of Belgrade, Belgrade, Serbia (T.S., I.S., A.T., V.M., E. Stefanova, V.S.K.); and Neurology Unit, University Hospital Maggiore della Carità, Novara, Italy (F.V.)
| | - Massimo Filippi
- From the Neuroimaging Research Unit, Division of Neuroscience (S.B., F.A., E. Sarasso, R.B., M.F.), Neurology Unit (F.A., M.F.), Department of Rehabilitation and Functional Recovery (E. Sarasso), Neurorehabilitation Unit (M.F.), and Neurophysiology Service (M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan, Italy; Vita-Salute San Raffaele University, Milan, Italy (F.A., R.B., M.F.); Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, and Maternal Child Health, University of Genoa, Genoa, Italy (E. Sarasso); Clinic of Neurology, Faculty of Medicine, University of Belgrade, Belgrade, Serbia (T.S., I.S., A.T., V.M., E. Stefanova, V.S.K.); and Neurology Unit, University Hospital Maggiore della Carità, Novara, Italy (F.V.)
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6
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Wang Z, Yang X, Li H, Wang S, Liu Z, Wang Y, Zhang X, Chen Y, Xu Q, Xu J, Wang Z, Wang J. Bidirectional two-sample Mendelian randomization analyses support causal relationships between structural and diffusion imaging-derived phenotypes and the risk of major neurodegenerative diseases. Transl Psychiatry 2024; 14:215. [PMID: 38806463 PMCID: PMC11133432 DOI: 10.1038/s41398-024-02939-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/14/2023] [Revised: 05/10/2024] [Accepted: 05/16/2024] [Indexed: 05/30/2024] Open
Abstract
Previous observational investigations suggest that structural and diffusion imaging-derived phenotypes (IDPs) are associated with major neurodegenerative diseases; however, whether these associations are causal remains largely uncertain. Herein we conducted bidirectional two-sample Mendelian randomization analyses to infer the causal relationships between structural and diffusion IDPs and major neurodegenerative diseases using common genetic variants-single nucleotide polymorphism (SNPs) as instrumental variables. Summary statistics of genome-wide association study (GWAS) for structural and diffusion IDPs were obtained from 33,224 individuals in the UK Biobank cohort. Summary statistics of GWAS for seven major neurodegenerative diseases were obtained from the largest GWAS for each disease to date. The forward MR analyses identified significant or suggestively statistical causal effects of genetically predicted three structural IDPs on Alzheimer's disease (AD), frontotemporal dementia (FTD), and multiple sclerosis. For example, the reduction in the surface area of the left superior temporal gyrus was associated with a higher risk of AD. The reverse MR analyses identified significantly or suggestively statistical causal effects of genetically predicted AD, Lewy body dementia (LBD), and FTD on nine structural and diffusion IDPs. For example, LBD was associated with increased mean diffusivity in the right superior longitudinal fasciculus and AD was associated with decreased gray matter volume in the right ventral striatum. Our findings might contribute to shedding light on the prediction and therapeutic intervention for the major neurodegenerative diseases at the neuroimaging level.
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Affiliation(s)
- Zirui Wang
- Department of Radiology, Tianjin Key Lab of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Xuan Yang
- Department of Radiology, Tianjin Key Lab of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin, 300052, China
- Department of Radiology, Jining No.1 People's Hospital, Jining, Shandong, 272000, China
| | - Haonan Li
- Department of Radiology, Tianjin Key Lab of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Siqi Wang
- Department of Radiology, Tianjin Key Lab of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Zhixuan Liu
- Department of Radiology, Tianjin Key Lab of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Yaoyi Wang
- Department of Radiology, Tianjin Key Lab of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Xingyu Zhang
- Department of Radiology, Tianjin Key Lab of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Yayuan Chen
- Department of Radiology, Tianjin Key Lab of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Qiang Xu
- Department of Radiology, Tianjin Key Lab of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Jiayuan Xu
- Department of Radiology, Tianjin Key Lab of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin, 300052, China.
| | - Zengguang Wang
- Department of Neurosurgery, Tianjin Medical University General Hospital, Tianjin, 300052, China.
| | - Junping Wang
- Department of Radiology, Tianjin Key Lab of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin, 300052, China.
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7
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Haliasos N, Giakoumettis D, Gnanaratnasingham P, Low HL, Misbahuddin A, Zikos P, Sakkalis V, Cleo S, Vakis A, Bisdas S. Personalizing Deep Brain Stimulation Therapy for Parkinson's Disease With Whole-Brain MRI Radiomics and Machine Learning. Cureus 2024; 16:e59915. [PMID: 38854362 PMCID: PMC11161197 DOI: 10.7759/cureus.59915] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/08/2024] [Indexed: 06/11/2024] Open
Abstract
Background Deep brain stimulation (DBS) is a well-recognised treatment for advanced Parkinson's disease (PD) patients. Structural brain alterations of the white matter can correlate with disease progression and act as a biomarker for DBS therapy outcomes. This study aims to develop a machine learning-driven predictive model for DBS patient selection using whole-brain white matter radiomics and common clinical variables. Methodology A total of 120 PD patients underwent DBS of the subthalamic nucleus. Their therapy effect was assessed at the one-year follow-up with the Unified Parkinson's Disease Rating Scale-part III (UPDRSIII) motor component. Radiomics analysis of whole-brain white matter was performed with PyRadiomics. The following machine learning methods were used: logistic regression (LR), support vector machine, naïve Bayes, K-nearest neighbours, and random forest (RF) to allow prediction of clinically meaningful UPRDSIII motor response before and after. Clinical variables were also added to the model to improve accuracy. Results The RF model showed the best performance on the final whole dataset with an area under the curve (AUC) of 0.99, accuracy of 0.95, sensitivity of 0.93, and specificity of 0.97. At the same time, the LR model showed an AUC of 0.93, accuracy of 0.88, sensitivity of 0.84, and specificity of 0.91. Conclusions Machine learning models can be used in clinical decision support tools which can deliver true personalised therapy recommendations for PD patients. Clinicians and engineers should choose between best-performing, less interpretable models vs. most interpretable, lesser-performing models. Larger clinical trials would allow to build trust among clinicians and patients to widely use these AI tools in the future.
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Affiliation(s)
- Nikolaos Haliasos
- Neurosurgery, Queen's Hospital, Romford, GBR
- Centre for Neuroscience, Surgery and Trauma, Blizard Institute, Queen Mary University, London, GBR
- Health and Medical Sciences, The Alan Turing Institute for Data Science and Artificial Intelligence, London, GBR
| | | | | | | | | | | | - Vangelis Sakkalis
- Institute of Computer Science, Foundation for Research and Technology, Heraklion, GRC
| | - Spanaki Cleo
- Neurology, School of Medicine, University of Crete, Heraklion, GRC
| | - Antonios Vakis
- Neurosurgery, School of Medicine, University of Crete, Heraklion, GRC
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8
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Zarkali A, Hannaway N, McColgan P, Heslegrave AJ, Veleva E, Laban R, Zetterberg H, Lees AJ, Fox NC, Weil RS. Neuroimaging and plasma evidence of early white matter loss in Parkinson's disease with poor outcomes. Brain Commun 2024; 6:fcae130. [PMID: 38715714 PMCID: PMC11073930 DOI: 10.1093/braincomms/fcae130] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Revised: 02/26/2024] [Accepted: 04/23/2024] [Indexed: 06/30/2024] Open
Abstract
Parkinson's disease is a common and debilitating neurodegenerative disorder, with over half of patients progressing to postural instability, dementia or death within 10 years of diagnosis. However, the onset and rate of progression to poor outcomes is highly variable, underpinned by heterogeneity in underlying pathological processes. Quantitative and sensitive measures predicting poor outcomes will be critical for targeted treatment, but most studies to date have been limited to a single modality or assessed patients with established cognitive impairment. Here, we used multimodal neuroimaging and plasma measures in 98 patients with Parkinson's disease and 28 age-matched controls followed up over 3 years. We examined: grey matter (cortical thickness and subcortical volume), white matter (fibre cross-section, a measure of macrostructure; and fibre density, a measure of microstructure) at whole-brain and tract level; structural and functional connectivity; and plasma levels of neurofilament light chain and phosphorylated tau 181. We evaluated relationships with subsequent poor outcomes, defined as development of mild cognitive impairment, dementia, frailty or death at any time during follow-up, in people with Parkinson's disease. We show that extensive white matter macrostructural changes are already evident at baseline assessment in people with Parkinson's disease who progress to poor outcomes (n = 31): with up to 19% reduction in fibre cross-section in multiple tracts, and a subnetwork of reduced structural connectivity strength, particularly involving connections between right frontoparietal and left frontal, right frontoparietal and left parietal and right temporo-occipital and left parietal modules. In contrast, grey matter volumes and functional connectivity were preserved in people with Parkinson's disease with poor outcomes. Neurofilament light chain, but not phosphorylated tau 181 levels were increased in people with Parkinson's disease with poor outcomes, and correlated with white matter loss. These findings suggest that imaging sensitive to white matter macrostructure and plasma neurofilament light chain may be useful early markers of poor outcomes in Parkinson's disease. As new targeted treatments for neurodegenerative disease are emerging, these measures show important potential to aid patient selection for treatment and improve stratification for clinical trials.
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Affiliation(s)
- Angeliki Zarkali
- Dementia Research Centre, Institute of Neurology, University College London, London WC1N 3AR, UK
| | - Naomi Hannaway
- Dementia Research Centre, Institute of Neurology, University College London, London WC1N 3AR, UK
| | - Peter McColgan
- Huntington’s Disease Centre, Institute of Neurology, University College London, London WC1B 5EH, UK
| | - Amanda J Heslegrave
- UK DRI Fluid Biomarker Lab and Biomarker Factory, University College London, London WC1E 6BT, UK
| | - Elena Veleva
- UK DRI Fluid Biomarker Lab and Biomarker Factory, University College London, London WC1E 6BT, UK
| | - Rhiannon Laban
- UK DRI Fluid Biomarker Lab and Biomarker Factory, University College London, London WC1E 6BT, UK
| | - Henrik Zetterberg
- Dementia Research Centre, Institute of Neurology, University College London, London WC1N 3AR, UK
- UK DRI Fluid Biomarker Lab and Biomarker Factory, University College London, London WC1E 6BT, UK
| | - Andrew J Lees
- Reta Lila Weston Institute of Neurological Studies, University College London, London WC1N 1PJ, UK
| | - Nick C Fox
- Dementia Research Centre, Institute of Neurology, University College London, London WC1N 3AR, UK
- National Hospital for Neurology and Neurosurgery, University College London Hospitals, London WC1N 3BG, UK
| | - Rimona S Weil
- Dementia Research Centre, Institute of Neurology, University College London, London WC1N 3AR, UK
- National Hospital for Neurology and Neurosurgery, University College London Hospitals, London WC1N 3BG, UK
- Movement Disorders Centre, University College London, London WC1N 3BG, UK
- The Wellcome Centre for Human Neuroimaging, Institute of Neurology, University College London, London WC1N 3AR, UK
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9
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Camacho M, Wilms M, Almgren H, Amador K, Camicioli R, Ismail Z, Monchi O, Forkert ND. Exploiting macro- and micro-structural brain changes for improved Parkinson's disease classification from MRI data. NPJ Parkinsons Dis 2024; 10:43. [PMID: 38409244 PMCID: PMC10897162 DOI: 10.1038/s41531-024-00647-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Accepted: 01/22/2024] [Indexed: 02/28/2024] Open
Abstract
Parkinson's disease (PD) is the second most common neurodegenerative disease. Accurate PD diagnosis is crucial for effective treatment and prognosis but can be challenging, especially at early disease stages. This study aimed to develop and evaluate an explainable deep learning model for PD classification from multimodal neuroimaging data. The model was trained using one of the largest collections of T1-weighted and diffusion-tensor magnetic resonance imaging (MRI) datasets. A total of 1264 datasets from eight different studies were collected, including 611 PD patients and 653 healthy controls (HC). These datasets were pre-processed and non-linearly registered to the MNI PD25 atlas. Six imaging maps describing the macro- and micro-structural integrity of brain tissues complemented with age and sex parameters were used to train a convolutional neural network (CNN) to classify PD/HC subjects. Explainability of the model's decision-making was achieved using SmoothGrad saliency maps, highlighting important brain regions. The CNN was trained using a 75%/10%/15% train/validation/test split stratified by diagnosis, sex, age, and study, achieving a ROC-AUC of 0.89, accuracy of 80.8%, specificity of 82.4%, and sensitivity of 79.1% on the test set. Saliency maps revealed that diffusion tensor imaging data, especially fractional anisotropy, was more important for the classification than T1-weighted data, highlighting subcortical regions such as the brainstem, thalamus, amygdala, hippocampus, and cortical areas. The proposed model, trained on a large multimodal MRI database, can classify PD patients and HC subjects with high accuracy and clinically reasonable explanations, suggesting that micro-structural brain changes play an essential role in the disease course.
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Affiliation(s)
- Milton Camacho
- Biomedical Engineering Graduate Program, University of Calgary, Calgary, AB, Canada.
- Department of Radiology, University of Calgary, Calgary, AB, Canada.
| | - Matthias Wilms
- Department of Radiology, University of Calgary, Calgary, AB, Canada
- Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, Canada
- Department of Pediatrics and Community Health Sciences, University of Calgary, Calgary, AB, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Hannes Almgren
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
- Department of Clinical Neurosciences, University of Calgary, Calgary, AB, Canada
| | - Kimberly Amador
- Biomedical Engineering Graduate Program, University of Calgary, Calgary, AB, Canada
- Department of Radiology, University of Calgary, Calgary, AB, Canada
| | - Richard Camicioli
- Neuroscience and Mental Health Institute and Department of Medicine (Neurology), University of Alberta, Edmonton, AB, Canada
| | - Zahinoor Ismail
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
- Department of Clinical Neurosciences, University of Calgary, Calgary, AB, Canada
- Department of Psychiatry, University of Calgary, Calgary, AB, Canada
- College of Medicine and Health, University of Exeter, Exeter, UK
| | - Oury Monchi
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
- Department of Clinical Neurosciences, University of Calgary, Calgary, AB, Canada
- Department of Radiology, Radio-oncology and Nuclear Medicine, Université de Montréal, Montréal, QC, Canada
- Centre de Recherche, Institut Universitaire de Gériatrie de Montréal, Montréal, QC, Canada
| | - Nils D Forkert
- Department of Radiology, University of Calgary, Calgary, AB, Canada
- Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, Canada
- Department of Pediatrics and Community Health Sciences, University of Calgary, Calgary, AB, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
- Department of Clinical Neurosciences, University of Calgary, Calgary, AB, Canada
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10
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Zhu S, Wang L, Lv X, Xu Y, Dou W, Zhang H, Ye J. Application of diffusional kurtosis imaging for insights into structurally aberrant topology in Parkinson's disease. Acta Radiol 2024; 65:233-240. [PMID: 38017711 DOI: 10.1177/02841851231216039] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2023]
Abstract
BACKGROUND Parkinson's disease (PD) has been regarded as a disconnection syndrome with functional and structural disturbances. However, as the anatomic determinants, the structural disconnections in PD have yet to be fully elucidated. PURPOSE To non-invasively construct structural networks based on microstructural complexity and to further investigate their potential topological abnormalities in PD given the technical superiority of diffusion kurtosis imaging (DKI) to the quantification of microstructure. MATERIAL AND METHODS The microstructural data of gray matter in both the PD group and the healthy control (HC) group were acquired using DKI. The structural networks were constructed at the group level by a covariation approach, followed by the calculation of topological properties based on graph theory and statistical comparisons between groups. RESULTS A total of 51 patients with PD and 50 HCs were enrolled. Individuals were matched between groups with respect to demographic characteristics (P >0.05). The constructed structural networks in both the PD and HC groups featured small-world properties. In comparison with the HC group, the PD group exhibited significantly altered global properties, with higher normalized characteristic path lengths, clustering coefficients, local efficiency values, and characteristic path lengths and lower global efficiency values (P <0.05). In terms of nodal centralities, extensive nodal disruptions were observed in patients with PD (P <0.05); these disruptions were mainly distributed in the sensorimotor network, default mode network, frontal-parietal network, visual network, and subcortical network. CONCLUSION These findings contribute to the technical application of DKI and the elucidation of disconnection syndrome in PD.
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Affiliation(s)
- Siying Zhu
- Department of Medical imaging center, Clinical Medical College, Yangzhou University, Yangzhou, PR China
| | - Lijuan Wang
- Department of Radiology, Jintang First People's Hospital, Sichuan University, Chengdu, PR China
| | - Xiang Lv
- Department of Neurology, Clinical Medical College, Yangzhou University, Yangzhou, PR China
| | - Yao Xu
- Department of Neurology, Clinical Medical College, Yangzhou University, Yangzhou, PR China
| | - Weiqiang Dou
- MR Research China, GE Healthcare, Beijing, PR China
| | - Hongying Zhang
- Department of Medical imaging center, Clinical Medical College, Yangzhou University, Yangzhou, PR China
| | - Jing Ye
- Department of Medical imaging center, Clinical Medical College, Yangzhou University, Yangzhou, PR China
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11
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Di Tella S, Isernia S, Cabinio M, Rossetto F, Borgnis F, Pagliari C, Cazzoli M, Navarro J, Silveri MC, Baglio F. Cognitive Reserve proxies can modulate motor and non-motor basal ganglia circuits in early Parkinson's Disease. Brain Imaging Behav 2024; 18:220-230. [PMID: 37993754 PMCID: PMC10844415 DOI: 10.1007/s11682-023-00829-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/19/2023] [Indexed: 11/24/2023]
Abstract
Parkinson's Disease (PD) is hallmarked by dysfunctional circuitry between the basal ganglia and dorsolateral-prefrontal cortex. Recently progress has been made in understanding factors contributing to differential susceptibility to pathology mitigating disease-related cognitive decline. Cognitive reserve, the brain processing resources accumulated throughout life while engaged in mentally stimulating activities, can play an important protective role in cognitive performance. We tested the hypothesis that Cognitive Reserve proxies may exert an impact on the basal ganglia and dorsolateral-prefrontal atrophy in early PD. Forty-five early patients with PD and 20 age-gender-matched healthy controls (HC) completed the Cognitive Reserve Index questionnaire to quantify Cognitive Reserve proxies by three indexes (CRI-Education, CRI-Working Activity, CRI-Leisure Time) and a structural MRI examination (3T). Morphometrical indexes for basal ganglia (bilateral putamen, caudate, pallidum volume) and dorsolateral-prefrontal cortex (cortical thickness) were computed. Significant differences between HC and PD were tested by direct comparisons in demographics, cognitive level, and cognitive reserve proxies indexes. Then two multiple regression analyses were performed to identify predictors of the basal ganglia and dorsolateral-prefrontal cortex structural integrity. Regression analysis revealed that basal ganglia volume was significantly predicted by CRI-Education (pFDR = 0.029), sex (pFDR = 0.029), and Total Intracranial Volume (pFDR < 0.001). Instead, the dorsolateral-prefrontal thickness was predicted by CRI-Leisure Time (pFDR = 0.030) and age (pFDR = 0.010). Cognitive Reserve proxies, especially education and leisure-time activities, can play a protective role on the structural integrity of the basal ganglia and dorsolateral-prefrontal cortex, respectively, critical regions hallmarking brain status of early phases of PD.
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Affiliation(s)
- Sonia Di Tella
- Department of Psychology, Università Cattolica del Sacro Cuore, Milan, Italy
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy
| | - Sara Isernia
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy.
| | - Monia Cabinio
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy
| | | | | | | | - Marta Cazzoli
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy
| | - Jorge Navarro
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy
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Giehl K, Theis H, Ophey A, Hammes J, Reker P, Eggers C, Fink GR, Kalbe E, van Eimeren T. Working Memory Training Responsiveness in Parkinson's Disease Is Not Determined by Cortical Thickness or White Matter Lesions. JOURNAL OF PARKINSON'S DISEASE 2024; 14:347-351. [PMID: 38277302 PMCID: PMC10977422 DOI: 10.3233/jpd-230367] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 12/20/2023] [Indexed: 01/28/2024]
Abstract
Patients with Parkinson's disease are highly vulnerable for cognitive decline. Thus, early intervention by means of working memory training (WMT) may be effective for the preservation of cognition. However, the influence of structural brain properties, i.e., cortical thickness and volume of white matter lesions on training responsiveness have not been studied. Here, behavioral and neuroimaging data of 46 patients with Parkinson's disease, 21 of whom engaged in home-based, computerized adaptive WMT, was analyzed. While cortical thickness and white matter lesions volume were associated with cognitive performance at baseline, these structural brain properties do not seem to determine WMT responsiveness.
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Affiliation(s)
- Kathrin Giehl
- Department of Nuclear Medicine, Faculty of Medicine and University Hospital Cologne, University of Cologne, Multimodal Neuroimaging Group, Cologne, Germany
- Research Center Jülich, Institute for Neuroscience and Medicine (INM-2), Jülich, Germany
| | - Hendrik Theis
- Department of Nuclear Medicine, Faculty of Medicine and University Hospital Cologne, University of Cologne, Multimodal Neuroimaging Group, Cologne, Germany
- Department of Neurology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Anja Ophey
- Department of Medical Psychology, Faculty of Medicine and University Hospital Cologne, Neuropsychology and Gender Studies and Center for Neuropsychological Diagnostics and Intervention (CeNDI), University of Cologne, Cologne, Germany
| | - Jochen Hammes
- Department of Nuclear Medicine, Faculty of Medicine and University Hospital Cologne, University of Cologne, Multimodal Neuroimaging Group, Cologne, Germany
- Nuklearmedizin, Radiologische Allianz, Hamburg, Germany
| | - Paul Reker
- Department of Neurology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Carsten Eggers
- Department of Neurology, Knappschaftskrankenhaus Bottrop, Bottrop, Germany
| | - Gereon R. Fink
- Department of Neurology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
- Research Center Jülich, Institute for Neuroscience and Medicine (INM-3), Jülich, Germany
| | - Elke Kalbe
- Department of Medical Psychology, Faculty of Medicine and University Hospital Cologne, Neuropsychology and Gender Studies and Center for Neuropsychological Diagnostics and Intervention (CeNDI), University of Cologne, Cologne, Germany
| | - Thilo van Eimeren
- Department of Nuclear Medicine, Faculty of Medicine and University Hospital Cologne, University of Cologne, Multimodal Neuroimaging Group, Cologne, Germany
- Department of Neurology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
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13
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Jellinger KA. Pathobiology of Cognitive Impairment in Parkinson Disease: Challenges and Outlooks. Int J Mol Sci 2023; 25:498. [PMID: 38203667 PMCID: PMC10778722 DOI: 10.3390/ijms25010498] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2023] [Revised: 12/11/2023] [Accepted: 12/27/2023] [Indexed: 01/12/2024] Open
Abstract
Cognitive impairment (CI) is a characteristic non-motor feature of Parkinson disease (PD) that poses a severe burden on the patients and caregivers, yet relatively little is known about its pathobiology. Cognitive deficits are evident throughout the course of PD, with around 25% of subtle cognitive decline and mild CI (MCI) at the time of diagnosis and up to 83% of patients developing dementia after 20 years. The heterogeneity of cognitive phenotypes suggests that a common neuropathological process, characterized by progressive degeneration of the dopaminergic striatonigral system and of many other neuronal systems, results not only in structural deficits but also extensive changes of functional neuronal network activities and neurotransmitter dysfunctions. Modern neuroimaging studies revealed multilocular cortical and subcortical atrophies and alterations in intrinsic neuronal connectivities. The decreased functional connectivity (FC) of the default mode network (DMN) in the bilateral prefrontal cortex is affected already before the development of clinical CI and in the absence of structural changes. Longitudinal cognitive decline is associated with frontostriatal and limbic affections, white matter microlesions and changes between multiple functional neuronal networks, including thalamo-insular, frontoparietal and attention networks, the cholinergic forebrain and the noradrenergic system. Superimposed Alzheimer-related (and other concomitant) pathologies due to interactions between α-synuclein, tau-protein and β-amyloid contribute to dementia pathogenesis in both PD and dementia with Lewy bodies (DLB). To further elucidate the interaction of the pathomechanisms responsible for CI in PD, well-designed longitudinal clinico-pathological studies are warranted that are supported by fluid and sophisticated imaging biomarkers as a basis for better early diagnosis and future disease-modifying therapies.
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Affiliation(s)
- Kurt A Jellinger
- Institute of Clinical Neurobiology, Alberichgasse 5/13, A-1150 Vienna, Austria
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14
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Hu L, Lin C, Lin F, Wang L, Li Z, Cai Z, Liu X, Ye Q, Wu Y, Cai G. Different impulse control disorder evolution patterns and white matter microstructural damage in the progression of Parkinson's disease. Front Aging Neurosci 2023; 15:1260630. [PMID: 38187360 PMCID: PMC10768538 DOI: 10.3389/fnagi.2023.1260630] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Accepted: 09/25/2023] [Indexed: 01/09/2024] Open
Abstract
Background The course of impulse control disorders (ICD) varies in the early stage of Parkinson's disease (PD). Aim We aimed to delineate the association between the evolution pattern of ICD and the progression of PD. Methods A total of 321 de novo PD patients from the Parkinson's Progression Markers Initiative database were included. Patients were followed up for a mean of 6.8 years and were classified into different groups according to the evolution patterns of ICD. Disease progression was compared among groups using survival analysis, in which the endpoint was defined as progression to Hoehn and Yahr stage 3 or higher for motor progression and progression to mild cognitive impairment for cognitive decline. In the fourth year of follow-up, four types of ICD evolution patterns were identified: (1) non-ICD-stable (68.2%), a patient who is consistently free of ICD; (2) late-ICD (14.6%), ICD developed during the follow-up of patients; (3) ICD-stable (11.5%), patients showed persistent ICD; and (4) ICD-reversion (5.6%), baseline ICD disappeared during the follow-up of patients with ICD. Results The ICD-reversion type shows daily life non-motor symptoms [Movement Disorder Society-Unified Parkinson Disease Rating Scale (MDS-UPDRS) part I], daily life motor symptoms (MDS-UPDRS part II), rapid eye movement sleep behavior disorder, and anxiety symptoms has a greater impact. PD patients with different ICD evolution patterns had different changes in white matter microstructure at the onset of the disease. Those relevant brain regions are involved in ICD and non-motor functions. Conclusion Four early ICD evolution patterns are identified in de novo PD, with different prognoses and brain white matter microstructural damage patterns, and they may predict motor progression and cognitive decline in PD patients.
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Affiliation(s)
- Ling Hu
- Department of Neurology, Ganzhou People’s Hospital, Ganzhou, China
| | - Changfu Lin
- Department of Medicine, Zhangzhou Fifth Hospital, Zhangzhou, China
| | - Fabin Lin
- Department of Neurosurgery, Fujian Medical University Union Hospital, Fuzhou, China
| | - Lingling Wang
- Department of Neurology and Institute of Neurology, Ruijin Hospital Affiliated to Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Zhenzhen Li
- Department of Medicine, Zhangzhou Fifth Hospital, Zhangzhou, China
| | - Zhijun Cai
- Department of Medicine, Zhangzhou Fifth Hospital, Zhangzhou, China
| | - Xianghong Liu
- Department of Neurology, Ganzhou People’s Hospital, Ganzhou, China
| | - Qinyong Ye
- Department of Neurology, Fujian Medical University Union Hospital, Fuzhou, China
- Department of Neurology, Fujian Institute of Geriatrics, Fujian Medical University Union Hospital, Fujian Medical University Union Hospital, Fujian, China
- Fujian Key Laboratory of Molecular Neurology, Institute of Neuroscience, Fujian Medical University, Fuzhou, China
| | - Yiwen Wu
- Department of Neurology and Institute of Neurology, Ruijin Hospital Affiliated to Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Guoen Cai
- Department of Neurology, Fujian Medical University Union Hospital, Fuzhou, China
- Department of Neurology, Fujian Institute of Geriatrics, Fujian Medical University Union Hospital, Fujian Medical University Union Hospital, Fujian, China
- Fujian Key Laboratory of Molecular Neurology, Institute of Neuroscience, Fujian Medical University, Fuzhou, China
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Jahanshahi A, Ghareaghaji N, Hassanpour S, Vafadar A, Mousavi S, Khezerloo D. Cortical gray matter and cerebral white matter atrophy and asymmetry in Parkinson's disease patients with normal cognitive precede. Int J Neurosci 2023:1-6. [PMID: 38085250 DOI: 10.1080/00207454.2023.2294260] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Accepted: 12/08/2023] [Indexed: 12/19/2023]
Abstract
BACKGROUND Parkinson's disease is the second most common neurodegenerative disorder with complex and distributed motor and non-motor symptoms. In this study, cortical gray matter (GM) and cerebral white matter (WM) overall atrophy, and asymmetry of atrophy are investigated in PD with normal cognitive function. METHOD Forty-eight male Parkinson's disease(PD) patients with normal cognitive precede (PD-NC), and thirty matched healthy control (HC) subjects were selected from the Parkinson's Progression Markers Initiative (PPMI) database. Brain structures volumes were extracted using Freesurfer software based on subject 3 tesla MRI images. The normalized volume of cortical GM and cerebral WM were compared in two study groups, and then the asymmetry index (AI) of GM and WM atrophy was also assessed in two groups. Statistical analysis was constructed using a t-test with p < 0.05 of significance. RESULTS No significant difference was observed in the volume of cortical GM and cerebral WM in the two study groups. The cortical GM asymmetry index in the PD-NC group was significantly (p = 0.01) higher than the HC group, however, no difference was observed for the cerebral WM asymmetry index. CONCLUSION Atrophy in cortical GM and WM was not observed between the PD-NC and the HC group, however, the asymmetry index in GM was significant between the two group. It seems that the brain's bilateral balance has ruptured in PD. Cortical GM asymmetry in PD-NC can be considered a potent biomarker and should be investigated more in the future. In future studies, construction of a longitudinal study on this issue could be useful.
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Affiliation(s)
- Amirreza Jahanshahi
- Department of Radiology, Faculty of Medicine, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Nahideh Ghareaghaji
- Department of Radiology, Faculty of Allied Medical Sciences, Tabriz University of Medical Science, Tabriz, Iran
| | - Samaneh Hassanpour
- Department of Medical Physics, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran
| | - Ali Vafadar
- Department of Medical Physics, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran
| | - Saeid Mousavi
- Department of Statistics and Epidemiology, Faculty of Health Sciences, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Davood Khezerloo
- Department of Radiology, Faculty of Allied Medical Sciences, Tabriz University of Medical Science, Tabriz, Iran
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16
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Marques A, Macias E, Pereira B, Durand E, Chassain C, Vidal T, Defebvre L, Carriere N, Fraix V, Moro E, Thobois S, Metereau E, Mangone G, Vidailhet M, Corvol JC, Lehéricy S, Menjot de Champfleur N, Geny C, Spampinato U, Meissner WG, Frismand S, Schmitt E, Doé de Maindreville A, Portefaix C, Remy P, Fénelon G, Houeto JL, Colin O, Rascol O, Peran P, Bonny JM, Fantini ML, Durif F. Volumetric changes and clinical trajectories in Parkinson's disease: a prospective multicentric study. J Neurol 2023; 270:6033-6043. [PMID: 37648911 DOI: 10.1007/s00415-023-11947-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Revised: 05/15/2023] [Accepted: 08/16/2023] [Indexed: 09/01/2023]
Abstract
BACKGROUND Longitudinal measures of structural brain changes using MRI in relation to clinical features and progression patterns in PD have been assessed in previous studies, but few were conducted in well-defined and large cohorts, including prospective clinical assessments of both motor and non-motor symptoms. OBJECTIVE We aimed to identify brain volumetric changes characterizing PD patients, and determine whether regional brain volumetric characteristics at baseline can predict motor, psycho-behavioral and cognitive evolution at one year in a prospective cohort of PD patients. METHODS In this multicentric 1 year longitudinal study, PD patients and healthy controls from the MPI-R2* cohort were assessed for demographical, clinical and brain volumetric characteristics. Distinct subgroups of PD patients according to motor, cognitive and psycho-behavioral evolution were identified at the end of follow-up. RESULTS One hundred and fifty PD patients and 73 control subjects were included in our analysis. Over one year, there was no significant difference in volume variations between PD and control subjects, regardless of the brain region considered. However, we observed a reduction in posterior cingulate cortex volume at baseline in PD patients with motor deterioration at one year (p = 0.017). We also observed a bilateral reduction of the volume of the amygdala (p = 0.015 and p = 0.041) and hippocampus (p = 0.015 and p = 0.053) at baseline in patients with psycho-behavioral deterioration, regardless of age, dopaminergic treatment and center. CONCLUSION Brain volumetric characteristics at baseline may predict clinical trajectories at 1 year in PD as posterior cingulate cortex atrophy was associated with motor decline, while amygdala and hippocampus atrophy were associated with psycho-behavioral decline.
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Affiliation(s)
- Ana Marques
- University Clermont Auvergne, CNRS, Clermont Auvergne INP, IGCNC, Institute Pascal, Clermont-Ferrand, France.
- Neurology Department and NS-PARK/FCRIN Network, Clermont-Ferrand University Hospital, Clermont-Ferrand, France.
- Neurology Department, Parkinson Expert Center, CHRU Gabriel Montpied, 63000, Clermont-Ferrand, France.
| | - Elise Macias
- University Clermont Auvergne, CNRS, Clermont Auvergne INP, IGCNC, Institute Pascal, Clermont-Ferrand, France
- Neurology Department and NS-PARK/FCRIN Network, Clermont-Ferrand University Hospital, Clermont-Ferrand, France
| | - Bruno Pereira
- Clermont-Ferrand University Hospital, Biostatistics Unit (DRCI), Clermont-Ferrand, France
| | - Elodie Durand
- University Clermont Auvergne, CNRS, Clermont Auvergne INP, IGCNC, Institute Pascal, Clermont-Ferrand, France
- Neurology Department and NS-PARK/FCRIN Network, Clermont-Ferrand University Hospital, Clermont-Ferrand, France
| | - Carine Chassain
- University Clermont Auvergne, CNRS, Clermont Auvergne INP, IGCNC, Institute Pascal, Clermont-Ferrand, France
- Neurology Department and NS-PARK/FCRIN Network, Clermont-Ferrand University Hospital, Clermont-Ferrand, France
| | - Tiphaine Vidal
- University Clermont Auvergne, CNRS, Clermont Auvergne INP, IGCNC, Institute Pascal, Clermont-Ferrand, France
- Neurology Department and NS-PARK/FCRIN Network, Clermont-Ferrand University Hospital, Clermont-Ferrand, France
| | - Luc Defebvre
- Department of Movement Disorder and NS-PARK/FCRIN Network, Inserm 1172, University of Lille, Lille, France
| | - Nicolas Carriere
- Department of Movement Disorder and NS-PARK/FCRIN Network, Inserm 1172, University of Lille, Lille, France
| | - Valerie Fraix
- Université Grenoble Alpes, CHU de Grenoble, Service de Neurologie, Grenoble Institute of Neuroscience, and NS-PARK/FCRIN Network, Grenoble, France
| | - Elena Moro
- Université Grenoble Alpes, CHU de Grenoble, Service de Neurologie, Grenoble Institute of Neuroscience, and NS-PARK/FCRIN Network, Grenoble, France
| | - Stéphane Thobois
- CNRS, Institut des Sciences Cognitives Marc Jeannerod, UMR 5229 CNRS, Lyon, France
- Université Claude Bernard, Lyon I, Lyon, France
- Hospices Civils de Lyon, Hôpital Neurologique Pierre Wertheimer, Service de Neurologie C and NS-PARK/FCRIN Network, Lyon, France
| | - Elise Metereau
- CNRS, Institut des Sciences Cognitives Marc Jeannerod, UMR 5229 CNRS, Lyon, France
- Université Claude Bernard, Lyon I, Lyon, France
- Hospices Civils de Lyon, Hôpital Neurologique Pierre Wertheimer, Service de Neurologie C and NS-PARK/FCRIN Network, Lyon, France
| | - Graziella Mangone
- Département de Neurologie and NS-PARK/FCRIN Network, Sorbonne Université; Institut du Cerveau-ICM, Assistance Publique Hôpitaux de Paris; Inserm 1127, CNRS 7225, CIC Neurosciences, Hôpital Pitié-Salpêtrière, Paris, France
| | - Marie Vidailhet
- Département de Neurologie and NS-PARK/FCRIN Network, Sorbonne Université; Institut du Cerveau-ICM, Assistance Publique Hôpitaux de Paris; Inserm 1127, CNRS 7225, CIC Neurosciences, Hôpital Pitié-Salpêtrière, Paris, France
| | - Jean-Christophe Corvol
- Département de Neurologie and NS-PARK/FCRIN Network, Sorbonne Université; Institut du Cerveau-ICM, Assistance Publique Hôpitaux de Paris; Inserm 1127, CNRS 7225, CIC Neurosciences, Hôpital Pitié-Salpêtrière, Paris, France
| | - Stéphane Lehéricy
- Département de Neuroradiologie and NS-PARK/FCRIN Network, Sorbonne Université; Institut du Cerveau-ICM, Assistance Publique Hôpitaux de Paris; Inserm 1127, CNRS 7225; Hôpital Pitié-Salpêtrière, Paris, France
| | - Nicolas Menjot de Champfleur
- Department of Neuroradiology, Montpellier University Hospital Center, Gui de Chauliac Hospital, Montpellier, France
- I2FH, Institut d'Imagerie Fonctionnelle Humaine, Hôpital Gui de Chauliac, CHRU de Montpellier, Montpellier, France
| | - Christian Geny
- Department of Geriatrics and NS-PARK/FCRIN Network, Montpellier University Hospital, Montpellier University, Montpellier, France
| | - Umberto Spampinato
- Service de Neurologie-Maladies Neurodégénératives and NS-PARK/FCRIN Network, CHU Bordeaux, 33000, Bordeaux, France
- INCIA-UMR 5287, Team P3TN, CNRS/Université de Bordeaux, Bordeaux, France
| | - Wassilios G Meissner
- Service de Neurologie-Maladies Neurodégénératives and NS-PARK/FCRIN Network, CHU Bordeaux, 33000, Bordeaux, France
- Univ. Bordeaux, CNRS, IMN, UMR 5293, Bordeaux, 33000, Bordeaux, France
- Dept. Medicine, University of Otago, Christchurch, New Zealand
- New Zealand Brain Research Institute, Christchurch, New Zealand
| | - Solène Frismand
- Department of Neurology and NS-PARK/FCRIN Network, Nancy University Hospital Center, Nancy, France
| | - Emmanuelle Schmitt
- Department of Neuroradiology, Nancy University Hospital Center, Nancy, France
| | | | - Christophe Portefaix
- Department of Radiology, Hôpital Maison Blanche, Reims, France
- CReSTIC Laboratory, University of Reims Champagne-Ardenne, Reims, France
| | - Philippe Remy
- Centre Expert Parkinson and NS-PARK/FCRIN Network, CHU Henri Mondor; AP-HP et Equipe Neuropsychologie Interventionnelle, INSERM-IMRB, Faculté de Santé, Université Paris-Est Créteil et Ecole Normale Supérieure Paris Sorbonne Université, Créteil, France
| | - Gilles Fénelon
- Centre Expert Parkinson and NS-PARK/FCRIN Network, CHU Henri Mondor; AP-HP et Equipe Neuropsychologie Interventionnelle, INSERM-IMRB, Faculté de Santé, Université Paris-Est Créteil et Ecole Normale Supérieure Paris Sorbonne Université, Créteil, France
| | - Jean Luc Houeto
- INSERM, CHU de Poitiers, Université de Poitiers, Centre d'Investigation Clinique CIC1402; Service de Neurologie and NS-PARK/FCRIN Network, Poitiers, France
- CHU-Centre Expert Parkinson de Limoges, Limoges, France
| | - Olivier Colin
- INSERM, CHU de Poitiers, Université de Poitiers, Centre d'Investigation Clinique CIC1402; Service de Neurologie and NS-PARK/FCRIN Network, CH Brive la Gaillarde, Poitiers, France
| | - Olivier Rascol
- Centre Expert Parkinson, Départements de Pharmacologie Clinique et Neurosciences, Centre d'Investigation Clinique CIC 1436, UMR 1214 TONIC, NeuroToul and NS-PARK/FCRIN Network, INSERM, CHU de Toulouse et Université de Toulouse3, Toulouse, France
| | - Patrice Peran
- ToNIC, Toulouse NeuroImaging Center, Université de Toulouse, INSERM, UPS, Toulouse, France
| | - Jean-Marie Bonny
- INRAE, UR QuaPA, 63122, Saint-Genès-Champanelle, France
- Nuclear Magnetic Resonance Facility for Agronomy, Food and Health, AgroResonance, INRAE, 2018, Saint-Genès-Champanelle, France
| | - Maria Livia Fantini
- University Clermont Auvergne, CNRS, Clermont Auvergne INP, IGCNC, Institute Pascal, Clermont-Ferrand, France
- Neurology Department and NS-PARK/FCRIN Network, Clermont-Ferrand University Hospital, Clermont-Ferrand, France
| | - Franck Durif
- University Clermont Auvergne, CNRS, Clermont Auvergne INP, IGCNC, Institute Pascal, Clermont-Ferrand, France
- Neurology Department and NS-PARK/FCRIN Network, Clermont-Ferrand University Hospital, Clermont-Ferrand, France
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Vijayakumari AA, Mandava N, Hogue O, Fernandez HH, Walter BL. A novel MRI-based volumetric index for monitoring the motor symptoms in Parkinson's disease. J Neurol Sci 2023; 453:120813. [PMID: 37742348 DOI: 10.1016/j.jns.2023.120813] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2023] [Accepted: 09/18/2023] [Indexed: 09/26/2023]
Abstract
BACKGROUND Conventional MRI scans have limited usefulness in monitoring Parkinson's disease as they typically do not show any disease-specific brain abnormalities. This study aimed to identify an imaging biomarker for tracking motor symptom progression by using a multivariate statistical approach that can combine gray matter volume information from multiple brain regions into a single score specific to each PD patient. METHODS A cohort of 150 patients underwent MRI at baseline and had their motor symptoms tracked for up to 10 years using MDS-UPDRS-III, with motor symptoms focused on total and subscores, including rigidity, bradykinesia, postural instability, and gait disturbances, resting tremor, and postural-kinetic tremor. Gray matter volume extracted from MRI data was summarized into a patient-specific summary score using Mahalanobis distance, MGMV. MDS-UPDRS-III's progression and its association with MGMV were modeled via linear mixed-effects models over 5- and 10-year follow-up periods. RESULTS Over the 5-year follow-up, there was a significant increase (P < 0.05) in MDS-UPDRS-III total and subscores, except for postural-kinetic tremor. Over the 10-year follow-up, all MDS-UPDRS-III scores increased significantly (P < 0.05). A higher baseline MGMV was associated with a significant increase in MDS-UPDRS-III total, bradykinesia, postural instability and gait disturbances, and resting tremor (P < 0.05) over the 5-year follow-up, but only with total, bradykinesia, and postural instability and gait disturbances during the 10-year follow-up (P < 0.05). CONCLUSIONS Higher MGMV scores were linked to faster motor symptom progression, suggesting it could be a valuable marker for clinicians monitoring Parkinson's disease over time.
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Affiliation(s)
- Anupa A Vijayakumari
- Center for Neurological Restoration, Neurological Institute, 9500 Euclid Avenue, Cleveland Clinic, Cleveland, OH 44195, USA
| | - Nymisha Mandava
- Department of Quantitative Health Sciences, Lerner Research Institute, 9500 Euclid Avenue, Cleveland Clinic, Cleveland, OH 44195, USA
| | - Olivia Hogue
- Department of Quantitative Health Sciences, Lerner Research Institute, 9500 Euclid Avenue, Cleveland Clinic, Cleveland, OH 44195, USA
| | - Hubert H Fernandez
- Center for Neurological Restoration, Neurological Institute, 9500 Euclid Avenue, Cleveland Clinic, Cleveland, OH 44195, USA
| | - Benjamin L Walter
- Center for Neurological Restoration, Neurological Institute, 9500 Euclid Avenue, Cleveland Clinic, Cleveland, OH 44195, USA.
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18
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Rashid-López R, Macías-García P, Sánchez-Fernández FL, Cano-Cano F, Sarrias-Arrabal E, Sanmartino F, Méndez-Bértolo C, Lozano-Soto E, Gutiérrez-Cortés R, González-Moraleda Á, Forero L, López-Sosa F, Zuazo A, Gómez-Molinero R, Gómez-Ramírez J, Paz-Expósito J, Rubio-Esteban G, Espinosa-Rosso R, Cruz-Gómez ÁJ, González-Rosa JJ. Neuroimaging and serum biomarkers of neurodegeneration and neuroplasticity in Parkinson's disease patients treated by intermittent theta-burst stimulation over the bilateral primary motor area: a randomized, double-blind, sham-controlled, crossover trial study. Front Aging Neurosci 2023; 15:1258315. [PMID: 37869372 PMCID: PMC10585115 DOI: 10.3389/fnagi.2023.1258315] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Accepted: 09/12/2023] [Indexed: 10/24/2023] Open
Abstract
Background and objectives Intermittent theta-burst stimulation (iTBS) is a patterned form of excitatory transcranial magnetic stimulation that has yielded encouraging results as an adjunctive therapeutic option to alleviate the emergence of clinical deficits in Parkinson's disease (PD) patients. Although it has been demonstrated that iTBS influences dopamine-dependent corticostriatal plasticity, little research has examined the neurobiological mechanisms underlying iTBS-induced clinical enhancement. Here, our primary goal is to verify whether iTBS bilaterally delivered over the primary motor cortex (M1) is effective as an add-on treatment at reducing scores for both motor functional impairment and nonmotor symptoms in PD. We hypothesize that these clinical improvements following bilateral M1-iTBS could be driven by endogenous dopamine release, which may rebalance cortical excitability and restore compensatory striatal volume changes, resulting in increased striato-cortico-cerebellar functional connectivity and positively impacting neuroglia and neuroplasticity. Methods A total of 24 PD patients will be assessed in a randomized, double-blind, sham-controlled crossover study involving the application of iTBS over the bilateral M1 (M1 iTBS). Patients on medication will be randomly assigned to receive real iTBS or control (sham) stimulation and will undergo 5 consecutive sessions (5 days) of iTBS over the bilateral M1 separated by a 3-month washout period. Motor evaluation will be performed at different follow-up visits along with a comprehensive neurocognitive assessment; evaluation of M1 excitability; combined structural magnetic resonance imaging (MRI), resting-state electroencephalography and functional MRI; and serum biomarker quantification of neuroaxonal damage, astrocytic reactivity, and neural plasticity prior to and after iTBS. Discussion The findings of this study will help to clarify the efficiency of M1 iTBS for the treatment of PD and further provide specific neurobiological insights into improvements in motor and nonmotor symptoms in these patients. This novel project aims to yield more detailed structural and functional brain evaluations than previous studies while using a noninvasive approach, with the potential to identify prognostic neuroprotective biomarkers and elucidate the structural and functional mechanisms of M1 iTBS-induced plasticity in the cortico-basal ganglia circuitry. Our approach may significantly optimize neuromodulation paradigms to ensure state-of-the-art and scalable rehabilitative treatment to alleviate motor and nonmotor symptoms of PD.
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Affiliation(s)
- Raúl Rashid-López
- Psychophysiology and Neuroimaging Group, Institute of Biomedical Research Cadiz (INiBICA), Cadiz, Spain
- Department of Neurology, Puerta del Mar University Hospital, Cadiz, Spain
| | - Paloma Macías-García
- Psychophysiology and Neuroimaging Group, Institute of Biomedical Research Cadiz (INiBICA), Cadiz, Spain
- Department of Psychology, University of Cadiz, Cádiz, Spain
| | - F. Luis Sánchez-Fernández
- Psychophysiology and Neuroimaging Group, Institute of Biomedical Research Cadiz (INiBICA), Cadiz, Spain
- Department of Psychology, University of Cadiz, Cádiz, Spain
| | - Fátima Cano-Cano
- Psychophysiology and Neuroimaging Group, Institute of Biomedical Research Cadiz (INiBICA), Cadiz, Spain
| | - Esteban Sarrias-Arrabal
- Psychophysiology and Neuroimaging Group, Institute of Biomedical Research Cadiz (INiBICA), Cadiz, Spain
- Department of Psychology, University of Cadiz, Cádiz, Spain
| | - Florencia Sanmartino
- Psychophysiology and Neuroimaging Group, Institute of Biomedical Research Cadiz (INiBICA), Cadiz, Spain
- Department of Psychology, University of Cadiz, Cádiz, Spain
| | - Constantino Méndez-Bértolo
- Psychophysiology and Neuroimaging Group, Institute of Biomedical Research Cadiz (INiBICA), Cadiz, Spain
- Department of Psychology, University of Cadiz, Cádiz, Spain
| | - Elena Lozano-Soto
- Psychophysiology and Neuroimaging Group, Institute of Biomedical Research Cadiz (INiBICA), Cadiz, Spain
- Department of Psychology, University of Cadiz, Cádiz, Spain
| | - Remedios Gutiérrez-Cortés
- Psychophysiology and Neuroimaging Group, Institute of Biomedical Research Cadiz (INiBICA), Cadiz, Spain
| | - Álvaro González-Moraleda
- Psychophysiology and Neuroimaging Group, Institute of Biomedical Research Cadiz (INiBICA), Cadiz, Spain
- Department of Psychology, University of Cadiz, Cádiz, Spain
| | - Lucía Forero
- Psychophysiology and Neuroimaging Group, Institute of Biomedical Research Cadiz (INiBICA), Cadiz, Spain
- Department of Neurology, Puerta del Mar University Hospital, Cadiz, Spain
| | - Fernando López-Sosa
- Psychophysiology and Neuroimaging Group, Institute of Biomedical Research Cadiz (INiBICA), Cadiz, Spain
- Department of Psychology, University of Cadiz, Cádiz, Spain
| | - Amaya Zuazo
- Department of Radiodiagnostic and Medical Imaging, Puerta del Mar University Hospital, Cadiz, Spain
| | | | - Jaime Gómez-Ramírez
- Psychophysiology and Neuroimaging Group, Institute of Biomedical Research Cadiz (INiBICA), Cadiz, Spain
| | - José Paz-Expósito
- Department of Radiodiagnostic and Medical Imaging, Puerta del Mar University Hospital, Cadiz, Spain
| | | | - Raúl Espinosa-Rosso
- Psychophysiology and Neuroimaging Group, Institute of Biomedical Research Cadiz (INiBICA), Cadiz, Spain
- Department of Neurology, Jerez de la Frontera University Hospital, Jerez de la Frontera, Spain
| | - Álvaro J. Cruz-Gómez
- Psychophysiology and Neuroimaging Group, Institute of Biomedical Research Cadiz (INiBICA), Cadiz, Spain
- Department of Psychology, University of Cadiz, Cádiz, Spain
| | - Javier J. González-Rosa
- Psychophysiology and Neuroimaging Group, Institute of Biomedical Research Cadiz (INiBICA), Cadiz, Spain
- Department of Psychology, University of Cadiz, Cádiz, Spain
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Huo S, Zhang X, Xu J, Zhang J, Du J, Li B, Song M, Shao B, Li Y, Xu F. Parkin-mediated mitophagy protects against aluminum trichloride-induced hippocampal apoptosis in mice via the mtROS-NLRP3 pathway. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2023; 264:115459. [PMID: 37703808 DOI: 10.1016/j.ecoenv.2023.115459] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Revised: 08/25/2023] [Accepted: 09/07/2023] [Indexed: 09/15/2023]
Abstract
Aluminum is a neurotoxic food contaminant. Aluminum trichloride (AlCl3) causes hippocampal mitochondrial damage, leading to hippocampal injury. Damaged mitochondria can release mitochondrial reactive oxygen species (mtROS) and activate nucleotide-binding oligomerization domain-like receptor-containing 3 (NLRP3) inflammasomes and apoptosis. E3 ubiquitin ligase PARK2 (Parkin)-mediated mitophagy can attenuate mitochondrial damage. However, the role of mitophagy in AlCl3-induced mice hippocampal damage and its regulatory mechanism remain elusive. First, C57BL/6 N mice were treated with 0, 44.825, 89.65, and 179.3 mg/kg body weight AlCl3 drinking water for 90 d. Apoptosis, NLRP3-inflammasome activation and mitochondrial damage were increased in AlCl3-induced hippocampal damage. In addition, Parkin-mediated mitophagy peaked in the middle-dose group and was slightly attenuated in the high-dose group. Subsequently, we used wild-type and Parkin knockout (Parkin-/-) mice to investigate the AlCl3-induced hippocampal damage. The results showed that Parkin-/- inhibited mitophagy, and aggravated AlCl3-induced mitochondrial damage, NLRP3-inflammasome activation, apoptosis and hippocampal damage. Finally, we administered MitoQ (mtROS inhibitor) and MCC950 (NLRP3 inhibitor) to AlCl3-treated Parkin-/- mice to investigate the mechanism of Parkin-mediated mitophagy. The results showed that inhibition of mtROS and NLRP3 attenuated hippocampal NLRP3-inflammasome activation, apoptosis, and damage in AlCl3-treated Parkin-/- mice. These findings indicate that Parkin-mediated mitophagy protects against AlCl3-induced hippocampal apoptosis in mice via the mtROS-NLRP3 pathway.
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Affiliation(s)
- Siming Huo
- Key Laboratory of the Provincial Education, Department of Heilongjiang for Common Animal Disease Prevention and Treatment, College of Veterinary Medicine, Northeast Agricultural University, Harbin 150030, China
| | - Xuliang Zhang
- Key Laboratory of the Provincial Education, Department of Heilongjiang for Common Animal Disease Prevention and Treatment, College of Veterinary Medicine, Northeast Agricultural University, Harbin 150030, China
| | - Jinyu Xu
- Department of Histology and Embryology, College of Basic Medicine, Binzhou Medical University, Yantai 264003, China
| | - Jian Zhang
- Key Laboratory of the Provincial Education, Department of Heilongjiang for Common Animal Disease Prevention and Treatment, College of Veterinary Medicine, Northeast Agricultural University, Harbin 150030, China
| | - Jiayu Du
- Key Laboratory of the Provincial Education, Department of Heilongjiang for Common Animal Disease Prevention and Treatment, College of Veterinary Medicine, Northeast Agricultural University, Harbin 150030, China
| | - Bo Li
- Key Laboratory of the Provincial Education, Department of Heilongjiang for Common Animal Disease Prevention and Treatment, College of Veterinary Medicine, Northeast Agricultural University, Harbin 150030, China
| | - Miao Song
- Key Laboratory of the Provincial Education, Department of Heilongjiang for Common Animal Disease Prevention and Treatment, College of Veterinary Medicine, Northeast Agricultural University, Harbin 150030, China
| | - Bing Shao
- Key Laboratory of the Provincial Education, Department of Heilongjiang for Common Animal Disease Prevention and Treatment, College of Veterinary Medicine, Northeast Agricultural University, Harbin 150030, China
| | - Yanfei Li
- Key Laboratory of the Provincial Education, Department of Heilongjiang for Common Animal Disease Prevention and Treatment, College of Veterinary Medicine, Northeast Agricultural University, Harbin 150030, China
| | - Feibo Xu
- Department of Histology and Embryology, College of Basic Medicine, Binzhou Medical University, Yantai 264003, China.
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20
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Gao X, Wei T, Xu S, Sun W, Zhang B, Li C, Sui R, Fei N, Li Y, Xu W, Han D. Sleep disorders causally affect the brain cortical structure: A Mendelian randomization study. Sleep Med 2023; 110:243-253. [PMID: 37657176 DOI: 10.1016/j.sleep.2023.08.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Revised: 07/14/2023] [Accepted: 08/13/2023] [Indexed: 09/03/2023]
Abstract
BACKGROUND s: Previous studies have reported that patients with sleep disorders have altered brain cortical structures. However, the causality has not been determined. We performed a two-sample Mendelian randomization (MR) to reveal the causal effect of sleep disorders on brain cortical structure. METHODS We included as exposures 11 phenotypes of sleep disorders including subjective and objective sleep duration, insomnia symptom and poor sleep efficiency, daytime sleepiness (narcolepsy)/napping, morning/evening preference, and four sleep breathing related traits from nine European-descent genome-wide association studies (GWASs). Further, outcome variables were provided by ENIGMA Consortium GWAS for full brain and 34 region-specific cortical thickness (TH) and surface area (SA) of grey matter. Inverse-variance weighted (IVW) was used as the primary estimate whereas alternative MR methods were implemented as sensitivity analysis approaches to ensure results robustness. RESULTS At the global level, both self-reported or accelerometer-measured shorter sleep duration decreases the thickness of full brain both derived from self-reported data (βIVW = 0.03 mm, standard error (SE) = 0.02, P = 0.038; βIVW = 0.02 mm, SE = 0.01, P = 0.010). At the functional level, there were 66 associations of suggestive evidence of causality. Notably, one robust evidence after multiple testing correction (1518 tests) suggests the without global weighted SA of superior parietal lobule was influenced significantly by sleep efficiency (βIVW = -285.28 mm2, SE = 68.59, P = 3.2 × 10-5). CONCLUSIONS We found significant evidence that shorter sleep duration, as estimated by self-reported interview and accelerometer measurements, was causally associated with atrophy in the entire human brain.
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Affiliation(s)
- Xiang Gao
- Department of Otolaryngology Head and Neck Surgery, Beijing Tongren Hospital, Capital Medical University, Beijing, 100730, People's Republic of China; Obstructive Sleep Apnea-Hypopnea Syndrome Clinical Diagnosis and Therapy and Research Centre, Capital Medical University, Beijing, 100730, People's Republic of China; Key Laboratory of Otolaryngology Head and Neck Surgery, Ministry of Education, Capital Medical University, Beijing, 100730, People's Republic of China
| | - Tao Wei
- Department of Neurology & Innovation Center for Neurological Disorders, Xuanwu Hospital, Capital Medical University, National Center for Neurological Disorders, Beijing, 100053, People's Republic of China
| | - Shenglong Xu
- Department of Otolaryngology Head and Neck Surgery, Beijing Tongren Hospital, Capital Medical University, Beijing, 100730, People's Republic of China; Obstructive Sleep Apnea-Hypopnea Syndrome Clinical Diagnosis and Therapy and Research Centre, Capital Medical University, Beijing, 100730, People's Republic of China; Key Laboratory of Otolaryngology Head and Neck Surgery, Ministry of Education, Capital Medical University, Beijing, 100730, People's Republic of China
| | - Wei Sun
- Department of Neurology, Xuanwu Hospital, Capital Medical University, National Center for Neurological Disorders, Beijing, 100053, People's Republic of China
| | - Bowen Zhang
- Department of Otolaryngology Head and Neck Surgery, Beijing Tongren Hospital, Capital Medical University, Beijing, 100730, People's Republic of China; Obstructive Sleep Apnea-Hypopnea Syndrome Clinical Diagnosis and Therapy and Research Centre, Capital Medical University, Beijing, 100730, People's Republic of China; Key Laboratory of Otolaryngology Head and Neck Surgery, Ministry of Education, Capital Medical University, Beijing, 100730, People's Republic of China
| | - Cancan Li
- Department of Epidemiology and Health Statistics, School of Public Halth, Capital Medical University, Beijing, 100069, People's Republic of China
| | - Rongcui Sui
- Department of Otolaryngology Head and Neck Surgery, Beijing Tongren Hospital, Capital Medical University, Beijing, 100730, People's Republic of China; Obstructive Sleep Apnea-Hypopnea Syndrome Clinical Diagnosis and Therapy and Research Centre, Capital Medical University, Beijing, 100730, People's Republic of China; Key Laboratory of Otolaryngology Head and Neck Surgery, Ministry of Education, Capital Medical University, Beijing, 100730, People's Republic of China
| | - Nanxi Fei
- Department of Radiology, Beijing Tongren Hospital, Capital Medical University, Beijing, 100730, People's Republic of China
| | - Yanru Li
- Department of Otolaryngology Head and Neck Surgery, Beijing Tongren Hospital, Capital Medical University, Beijing, 100730, People's Republic of China; Obstructive Sleep Apnea-Hypopnea Syndrome Clinical Diagnosis and Therapy and Research Centre, Capital Medical University, Beijing, 100730, People's Republic of China; Key Laboratory of Otolaryngology Head and Neck Surgery, Ministry of Education, Capital Medical University, Beijing, 100730, People's Republic of China.
| | - Wen Xu
- Department of Otolaryngology Head and Neck Surgery, Beijing Tongren Hospital, Capital Medical University, Beijing, 100730, People's Republic of China; Obstructive Sleep Apnea-Hypopnea Syndrome Clinical Diagnosis and Therapy and Research Centre, Capital Medical University, Beijing, 100730, People's Republic of China; Key Laboratory of Otolaryngology Head and Neck Surgery, Ministry of Education, Capital Medical University, Beijing, 100730, People's Republic of China
| | - Demin Han
- Department of Otolaryngology Head and Neck Surgery, Beijing Tongren Hospital, Capital Medical University, Beijing, 100730, People's Republic of China; Obstructive Sleep Apnea-Hypopnea Syndrome Clinical Diagnosis and Therapy and Research Centre, Capital Medical University, Beijing, 100730, People's Republic of China; Key Laboratory of Otolaryngology Head and Neck Surgery, Ministry of Education, Capital Medical University, Beijing, 100730, People's Republic of China.
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21
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Lee YG, Park M, Jeong SH, Baik K, Kang S, Yoon SH, Na HK, Sohn YH, Lee PH. Association of Neuropsychiatric Symptom Profiles With Cognitive Decline in Patients With Parkinson Disease and Mild Cognitive Impairment. Neurology 2023; 101:e1186-e1195. [PMID: 37524535 PMCID: PMC10516268 DOI: 10.1212/wnl.0000000000207623] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Accepted: 05/19/2023] [Indexed: 08/02/2023] Open
Abstract
BACKGROUND AND OBJECTIVES Neuropsychiatric symptoms (NPS) are closely associated with cognitive decline in patients with Parkinson disease (PD). We investigated which profiles of NPS are associated with the risk of dementia in PD with mild cognitive impairment (PD-MCI). METHODS We retrospectively assessed 338 patients with PD-MCI from a single tertiary hospital, who underwent neuropsychological tests and a neuropsychiatric inventory (NPI) questionnaire. We conducted a factor analysis of the dichotomized presence of 12 NPI symptoms, yielding 3 NPI factors: factor 1, mood symptoms; factor 2, hyperactivity-related symptoms; and factor 3, psychotic symptoms. Factor analysis of the severity of NPI symptoms also identified similar NPI factors. The neuropsychiatric correlates of NPI factors were evaluated using general linear models for cognitive tests. Subsequently, we evaluated the hazard ratio (HR) of NPI factors on conversion to dementia. RESULTS A higher prevalence factor 1 score was associated with lower scores in the verbal memory (β = -0.15; 95% CI -0.24 to -0.06; p = 0.001) and executive domains (β = -0.16; 95% CI -0.28 to -0.04; p = 0.007), whereas higher severity factor 2 scores were associated with lower scores in the naming (β = -0.16; 95% CI -0.28 to -0.03; p = 0.012), visuospatial (β = -0.24; 95% CI -0.41 to -0.07; p = 0.005), and verbal memory domains (β = -0.15; 95% CI -0.24 to -0.05; p = 0.005). A higher severity factor 3 score was associated with lower scores in the visuospatial domain (β = -0.25; 95% CI -0.46 to -0.07; p = 0.007). Cox regression models demonstrated that the risk of dementia was increased in those with higher prevalence factor 1 (HR = 1.48, 95% CI 1.17-1.88, p = 0.001) and factor 2 scores (HR = 1.27, 95% CI 1.07-1.51, p = 0.007) and severity factor 3 score (HR = 1.52, 95% CI 1.29-1.80, p < 0.001) after adjusting for age, sex, education, disease duration, scores for cognition and parkinsonism, and levodopa equivalent dose. DISCUSSION This study demonstrated that a higher burden of NPS is associated with dementia conversion in patients with PD-MCI.
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Affiliation(s)
- Young-Gun Lee
- From the Department of Neurology (Y.-g.L., Y.B., S.K., S.H.Y., H.K.N., Y.H.S., P.H.L.), Yonsei University College of Medicine, Seoul; Department of Neurology (Y.-g.L.), Ilsan Paik Hospital, Inje University College of Medicine, Goyang; Department of Neurology (M.P.), Chung-Ang University College of Medicine and Graduate School of Medicine, Gwangmyeong Hospital; Department of Neurology (S.H.J.), Sanggye Paik Hospital, Inje University College of Medicine; and Severance Biomedical Science Institute, Yonsei University College of Medicine, Seoul, South Korea (P.H.L.).
| | - Mincheol Park
- From the Department of Neurology (Y.-g.L., Y.B., S.K., S.H.Y., H.K.N., Y.H.S., P.H.L.), Yonsei University College of Medicine, Seoul; Department of Neurology (Y.-g.L.), Ilsan Paik Hospital, Inje University College of Medicine, Goyang; Department of Neurology (M.P.), Chung-Ang University College of Medicine and Graduate School of Medicine, Gwangmyeong Hospital; Department of Neurology (S.H.J.), Sanggye Paik Hospital, Inje University College of Medicine; and Severance Biomedical Science Institute, Yonsei University College of Medicine, Seoul, South Korea (P.H.L.)
| | - Seong Ho Jeong
- From the Department of Neurology (Y.-g.L., Y.B., S.K., S.H.Y., H.K.N., Y.H.S., P.H.L.), Yonsei University College of Medicine, Seoul; Department of Neurology (Y.-g.L.), Ilsan Paik Hospital, Inje University College of Medicine, Goyang; Department of Neurology (M.P.), Chung-Ang University College of Medicine and Graduate School of Medicine, Gwangmyeong Hospital; Department of Neurology (S.H.J.), Sanggye Paik Hospital, Inje University College of Medicine; and Severance Biomedical Science Institute, Yonsei University College of Medicine, Seoul, South Korea (P.H.L.)
| | - Kyoungwon Baik
- From the Department of Neurology (Y.-g.L., Y.B., S.K., S.H.Y., H.K.N., Y.H.S., P.H.L.), Yonsei University College of Medicine, Seoul; Department of Neurology (Y.-g.L.), Ilsan Paik Hospital, Inje University College of Medicine, Goyang; Department of Neurology (M.P.), Chung-Ang University College of Medicine and Graduate School of Medicine, Gwangmyeong Hospital; Department of Neurology (S.H.J.), Sanggye Paik Hospital, Inje University College of Medicine; and Severance Biomedical Science Institute, Yonsei University College of Medicine, Seoul, South Korea (P.H.L.)
| | - Sungwoo Kang
- From the Department of Neurology (Y.-g.L., Y.B., S.K., S.H.Y., H.K.N., Y.H.S., P.H.L.), Yonsei University College of Medicine, Seoul; Department of Neurology (Y.-g.L.), Ilsan Paik Hospital, Inje University College of Medicine, Goyang; Department of Neurology (M.P.), Chung-Ang University College of Medicine and Graduate School of Medicine, Gwangmyeong Hospital; Department of Neurology (S.H.J.), Sanggye Paik Hospital, Inje University College of Medicine; and Severance Biomedical Science Institute, Yonsei University College of Medicine, Seoul, South Korea (P.H.L.)
| | - So Hoon Yoon
- From the Department of Neurology (Y.-g.L., Y.B., S.K., S.H.Y., H.K.N., Y.H.S., P.H.L.), Yonsei University College of Medicine, Seoul; Department of Neurology (Y.-g.L.), Ilsan Paik Hospital, Inje University College of Medicine, Goyang; Department of Neurology (M.P.), Chung-Ang University College of Medicine and Graduate School of Medicine, Gwangmyeong Hospital; Department of Neurology (S.H.J.), Sanggye Paik Hospital, Inje University College of Medicine; and Severance Biomedical Science Institute, Yonsei University College of Medicine, Seoul, South Korea (P.H.L.)
| | - Han Kyu Na
- From the Department of Neurology (Y.-g.L., Y.B., S.K., S.H.Y., H.K.N., Y.H.S., P.H.L.), Yonsei University College of Medicine, Seoul; Department of Neurology (Y.-g.L.), Ilsan Paik Hospital, Inje University College of Medicine, Goyang; Department of Neurology (M.P.), Chung-Ang University College of Medicine and Graduate School of Medicine, Gwangmyeong Hospital; Department of Neurology (S.H.J.), Sanggye Paik Hospital, Inje University College of Medicine; and Severance Biomedical Science Institute, Yonsei University College of Medicine, Seoul, South Korea (P.H.L.)
| | - Young H Sohn
- From the Department of Neurology (Y.-g.L., Y.B., S.K., S.H.Y., H.K.N., Y.H.S., P.H.L.), Yonsei University College of Medicine, Seoul; Department of Neurology (Y.-g.L.), Ilsan Paik Hospital, Inje University College of Medicine, Goyang; Department of Neurology (M.P.), Chung-Ang University College of Medicine and Graduate School of Medicine, Gwangmyeong Hospital; Department of Neurology (S.H.J.), Sanggye Paik Hospital, Inje University College of Medicine; and Severance Biomedical Science Institute, Yonsei University College of Medicine, Seoul, South Korea (P.H.L.)
| | - Phil Hyu Lee
- From the Department of Neurology (Y.-g.L., Y.B., S.K., S.H.Y., H.K.N., Y.H.S., P.H.L.), Yonsei University College of Medicine, Seoul; Department of Neurology (Y.-g.L.), Ilsan Paik Hospital, Inje University College of Medicine, Goyang; Department of Neurology (M.P.), Chung-Ang University College of Medicine and Graduate School of Medicine, Gwangmyeong Hospital; Department of Neurology (S.H.J.), Sanggye Paik Hospital, Inje University College of Medicine; and Severance Biomedical Science Institute, Yonsei University College of Medicine, Seoul, South Korea (P.H.L.).
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Waggan I, Rissanen E, Tuisku J, Matilainen M, Parkkola R, Rinne JO, Airas L. Adenosine A 2A receptor availability in cerebral gray and white matter of patients with Parkinson's disease. Parkinsonism Relat Disord 2023; 113:105766. [PMID: 37480614 DOI: 10.1016/j.parkreldis.2023.105766] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Revised: 06/23/2023] [Accepted: 07/15/2023] [Indexed: 07/24/2023]
Abstract
OBJECTIVE Atrophic changes in cerebral gray matter of patients with PD have been reported extensively. There is evidence suggesting an association between cortical gyrification changes and white matter abnormalities. Adenosine A2A receptors have been shown to be upregulated in cerebral white matter and on reactive astrocytes in preclinical models of neurodegenerative diseases. We, therefore, sought to investigate in vivo changes in A2A receptor availability in cerebral gray and white matter of PD patients and its association with gray matter atrophy. METHODS Eighteen patients with PD without dyskinesia and seven healthy controls were enrolled for this study. Brain MRI and dynamic PET scan was acquired with [11C]TMSX radioligand which binds selectively to A2A receptors. FreeSurfer software was used to segment cerebral gray and white matter structures. The resulting masks were used to calculate region specific volumes and to derive distribution volume ratios (DVRs), after co-registration with PET images, for the quantification of specific [11C]TMSX binding. RESULTS We showed an increase in A2A receptor availability in frontal (P < 0.001) and parietal (P < 0.001) white matter and a decrease in occipital (P = 0.02) gray matter of PD patients as compared to healthy controls. A decrease in gray matter volume ratios was observed in frontal (P < 0.01), parietal (P < 0.001), temporal (P < 0.01) and occipital (P < 0.01) ROIs in patients with PD versus healthy controls. CONCLUSIONS Our results suggest a role of A2A receptor-based signaling in the neurodegenerative changes seen in the cerebral gray and white matter of patients with PD.
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Affiliation(s)
- Imran Waggan
- Turku PET Centre, Turku University Hospital and University of Turku, Turku, Finland; Division of Clinical Neurosciences, Turku University Hospital, Turku, Finland.
| | - Eero Rissanen
- Turku PET Centre, Turku University Hospital and University of Turku, Turku, Finland; Division of Clinical Neurosciences, Turku University Hospital, Turku, Finland
| | - Jouni Tuisku
- Turku PET Centre, Turku University Hospital and University of Turku, Turku, Finland
| | - Markus Matilainen
- Turku PET Centre, Turku University Hospital and University of Turku, Turku, Finland
| | - Riitta Parkkola
- Turku PET Centre, Turku University Hospital and University of Turku, Turku, Finland; Radiology Department, Division of Medical Imaging, Turku University Hospital, Turku, Finland
| | - Juha O Rinne
- Turku PET Centre, Turku University Hospital and University of Turku, Turku, Finland; Division of Clinical Neurosciences, Turku University Hospital, Turku, Finland
| | - Laura Airas
- Turku PET Centre, Turku University Hospital and University of Turku, Turku, Finland; Division of Clinical Neurosciences, Turku University Hospital, Turku, Finland
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23
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Shih YC, Ooi LQR, Li HH, Allen JC, Hartono S, Welton T, Tan EK, Chan LL. Serial deep gray nuclear DTI changes in Parkinson's disease over twelve years. Front Aging Neurosci 2023; 15:1169254. [PMID: 37409008 PMCID: PMC10318173 DOI: 10.3389/fnagi.2023.1169254] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2023] [Accepted: 05/30/2023] [Indexed: 07/07/2023] Open
Abstract
Background Deep gray nuclear pathology relates to motor deterioration in idiopathic Parkinson's disease (PD). Inconsistent deep nuclear diffusion tensor imaging (DTI) findings in cross-sectional or short-term longitudinal studies have been reported. Long-term studies in PD are clinically challenging; decade-long deep nuclear DTI data are nonexistent. We investigated serial DTI changes and clinical utility in a case-control PD cohort of 149 subjects (72 patients/77 controls) over 12 years. Methods Participating subjects underwent brain MRI at 1.5T; DTI metrics from segmented masks of caudate, putamen, globus pallidus and thalamus were extracted from three timepoints with 6-year gaps. Patients underwent clinical assessment, including Unified Parkinson Disease Rating Scale Part 3 (UPDRS-III) and Hoehn and Yahr (H&Y) staging. A multivariate linear mixed-effects regression model with adjustments for age and gender was used to assess between-group differences in DTI metrics at each timepoint. Partial Pearson correlation analysis was used to correlate clinical motor scores with DTI metrics over time. Results MD progressively increased over time and was higher in the putamen (p < 0.001) and globus pallidus (p = 0.002). FA increased (p < 0.05) in the thalamus at year six, and decreased in the putamen and globus pallidus at year 12. Putaminal (p = 0.0210), pallidal (p = 0.0066) and caudate MD (p < 0.0001) correlated with disease duration. Caudate MD (p < 0.05) also correlated with UPDRS-III and H&Y scores. Conclusion Pallido-putaminal MD showed differential neurodegeneration in PD over 12 years on longitudinal DTI; putaminal and thalamic FA changes were complex. Caudate MD could serve as a surrogate marker to track late PD progression.
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Affiliation(s)
- Yao-Chia Shih
- Department of Diagnostic Radiology, Singapore General Hospital, Singapore, Singapore
- Duke-NUS Medical School, Singapore, Singapore
- Graduate Institute of Medicine, Yuan Ze University, Taoyuan City, Taiwan
| | - Leon Qi Rong Ooi
- Department of Neurology, National Neuroscience Institute, Singapore, Singapore
| | - Hui-Hua Li
- Duke-NUS Medical School, Singapore, Singapore
- Health Services Research Unit, Singapore General Hospital, Singapore, Singapore
| | | | - Septian Hartono
- Duke-NUS Medical School, Singapore, Singapore
- Department of Neurology, National Neuroscience Institute, Singapore, Singapore
| | - Thomas Welton
- Duke-NUS Medical School, Singapore, Singapore
- Department of Neurology, National Neuroscience Institute, Singapore, Singapore
| | - Eng-King Tan
- Duke-NUS Medical School, Singapore, Singapore
- Department of Neurology, National Neuroscience Institute, Singapore, Singapore
| | - Ling Ling Chan
- Department of Diagnostic Radiology, Singapore General Hospital, Singapore, Singapore
- Duke-NUS Medical School, Singapore, Singapore
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Filippi M, Balestrino R. The "Glymphatic" Window on Neurodegeneration in Synucleinopathies. Radiology 2023; 307:e230817. [PMID: 37158718 DOI: 10.1148/radiol.230817] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/10/2023]
Affiliation(s)
- Massimo Filippi
- From the Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience (M.F.), Neurology Unit (M.F., R.B.), Neurorehabilitation Unit (M.F., R.B.), and Neurophysiology Service (M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan, Italy; and Vita-Salute San Raffaele University, Milan, Italy (M.F., R.B.)
| | - Roberta Balestrino
- From the Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience (M.F.), Neurology Unit (M.F., R.B.), Neurorehabilitation Unit (M.F., R.B.), and Neurophysiology Service (M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan, Italy; and Vita-Salute San Raffaele University, Milan, Italy (M.F., R.B.)
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25
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Bosco P, Lancione M, Retico A, Nigri A, Aquino D, Baglio F, Carne I, Ferraro S, Giulietti G, Napolitano A, Palesi F, Pavone L, Savini G, Tagliavini F, Bruzzone MG, Gandini Wheeler-Kingshott CAM, Tosetti M, Biagi L. Quality assessment, variability and reproducibility of anatomical measurements derived from T1-weighted brain imaging: The RIN-Neuroimaging Network case study. Phys Med 2023; 110:102577. [PMID: 37126963 DOI: 10.1016/j.ejmp.2023.102577] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Revised: 03/01/2023] [Accepted: 04/05/2023] [Indexed: 05/03/2023] Open
Abstract
Initiatives for the collection of harmonized MRI datasets are growing continuously, opening questions on the reliability of results obtained in multi-site contexts. Here we present the assessment of the brain anatomical variability of MRI-derived measurements obtained from T1-weighted images, acquired according to the Standard Operating Procedures, promoted by the RIN-Neuroimaging Network. A multicentric dataset composed of 77 brain T1w acquisitions of young healthy volunteers (mean age = 29.7 ± 5.0 years), collected in 15 sites with MRI scanners of three different vendors, was considered. Parallelly, a dataset of 7 "traveling" subjects, each undergoing three acquisitions with scanners from different vendors, was also used. Intra-site, intra-vendor, and inter-site variabilities were evaluated in terms of the percentage standard deviation of volumetric and cortical thickness measures. Image quality metrics such as contrast-to-noise and signal-to-noise ratio in gray and white matter were also assessed for all sites and vendors. The results showed a measured global variability that ranges from 11% to 19% for subcortical volumes and from 3% to 10% for cortical thicknesses. Univariate distributions of the normalized volumes of subcortical regions, as well as the distributions of the thickness of cortical parcels appeared to be significantly different among sites in 8 subcortical (out of 17) and 21 cortical (out of 68) regions of i nterest in the multicentric study. The Bland-Altman analysis on "traveling" brain measurements did not detect systematic scanner biases even though a multivariate classification approach was able to classify the scanner vendor from brain measures with an accuracy of 0.60 ± 0.14 (chance level 0.33).
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Affiliation(s)
- Paolo Bosco
- Laboratory of Medical Physics and Magnetic Resonance, IRCCS Stella Maris Foundation, Pisa, Italy
| | - Marta Lancione
- Laboratory of Medical Physics and Magnetic Resonance, IRCCS Stella Maris Foundation, Pisa, Italy
| | - Alessandra Retico
- Pisa Division, INFN - National Institute for Nuclear Physics, Pisa, Italy
| | - Anna Nigri
- Neuroradiology Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
| | - Domenico Aquino
- Neuroradiology Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
| | | | - Irene Carne
- Neuroradiology Unit, IRCCS Istituti Clinici Scientifici Maugeri, Pavia, Italy
| | - Stefania Ferraro
- Neuroradiology Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy; MOE Key Laboratory for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Giovanni Giulietti
- Neuroimaging Laboratory, IRCCS Santa Lucia Foundation, Rome, Italy; SAIMLAL Department, Sapienza University of Rome, Rome, Italy
| | - Antonio Napolitano
- Medical Physics, IRCCS Istituto Ospedale Pediatrico Bambino Gesù, Rome, Italy
| | - Fulvia Palesi
- Neuroradiology Unit, IRCCS Mondino Foundation, Pavia, Italy; Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
| | | | - Giovanni Savini
- Neuroradiology Unit, IRCCS Humanitas Research Hospital, Milan, Italy
| | - Fabrizio Tagliavini
- Scientific Direction, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
| | - Maria Grazia Bruzzone
- Neuroradiology Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
| | - Claudia A M Gandini Wheeler-Kingshott
- Neuroradiology Unit, IRCCS Mondino Foundation, Pavia, Italy; Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy; NMR Research Unit, Department of Neuroinflammation, Queen Square MS Centre, UCL Queen Square, Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom
| | - Michela Tosetti
- Laboratory of Medical Physics and Magnetic Resonance, IRCCS Stella Maris Foundation, Pisa, Italy.
| | - Laura Biagi
- Laboratory of Medical Physics and Magnetic Resonance, IRCCS Stella Maris Foundation, Pisa, Italy
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Camacho M, Wilms M, Mouches P, Almgren H, Souza R, Camicioli R, Ismail Z, Monchi O, Forkert ND. Explainable classification of Parkinson's disease using deep learning trained on a large multi-center database of T1-weighted MRI datasets. Neuroimage Clin 2023; 38:103405. [PMID: 37079936 PMCID: PMC10148079 DOI: 10.1016/j.nicl.2023.103405] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Revised: 02/13/2023] [Accepted: 04/11/2023] [Indexed: 04/22/2023]
Abstract
INTRODUCTION Parkinson's disease (PD) is a severe neurodegenerative disease that affects millions of people. Early diagnosis is important to facilitate prompt interventions to slow down disease progression. However, accurate PD diagnosis can be challenging, especially in the early disease stages. The aim of this work was to develop and evaluate a robust explainable deep learning model for PD classification trained from one of the largest collections of T1-weighted magnetic resonance imaging datasets. MATERIALS AND METHODS A total of 2,041 T1-weighted MRI datasets from 13 different studies were collected, including 1,024 datasets from PD patients and 1,017 datasets from age- and sex-matched healthy controls (HC). The datasets were skull stripped, resampled to isotropic resolution, bias field corrected, and non-linearly registered to the MNI PD25 atlas. The Jacobian maps derived from the deformation fields together with basic clinical parameters were used to train a state-of-the-art convolutional neural network (CNN) to classify PD and HC subjects. Saliency maps were generated to display the brain regions contributing the most to the classification task as a means of explainable artificial intelligence. RESULTS The CNN model was trained using an 85%/5%/10% train/validation/test split stratified by diagnosis, sex, and study. The model achieved an accuracy of 79.3%, precision of 80.2%, specificity of 81.3%, sensitivity of 77.7%, and AUC-ROC of 0.87 on the test set while performing similarly on an independent test set. Saliency maps computed for the test set data highlighted frontotemporal regions, the orbital-frontal cortex, and multiple deep gray matter structures as most important. CONCLUSION The developed CNN model, trained on a large heterogenous database, was able to differentiate PD patients from HC subjects with high accuracy with clinically feasible classification explanations. Future research should aim to investigate the combination of multiple imaging modalities with deep learning and on validating these results in a prospective trial as a clinical decision support system.
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Affiliation(s)
- Milton Camacho
- Biomedical Engineering Program, University of Calgary, Canada; Department of Radiology, University of Calgary, Canada.
| | - Matthias Wilms
- Department of Radiology, University of Calgary, Canada; Alberta Children's Hospital Research Institute, University of Calgary, Canada
| | - Pauline Mouches
- Biomedical Engineering Program, University of Calgary, Canada; Department of Radiology, University of Calgary, Canada
| | - Hannes Almgren
- Department of Clinical Neurosciences, University of Calgary, Canada; Hotchkiss Brain Institute, University of Calgary, Canada
| | - Raissa Souza
- Biomedical Engineering Program, University of Calgary, Canada; Department of Radiology, University of Calgary, Canada
| | - Richard Camicioli
- Neuroscience and Mental Health Institute and Department of Medicine (Neurology), University of Alberta, Edmonton, Alberta, Canada
| | - Zahinoor Ismail
- Department of Clinical Neurosciences, University of Calgary, Canada; Hotchkiss Brain Institute, University of Calgary, Canada; Department of Psychiatry, University of Calgary, Canada
| | - Oury Monchi
- Department of Clinical Neurosciences, University of Calgary, Canada; Hotchkiss Brain Institute, University of Calgary, Canada; Department of Radiology, Radio-oncology and Nuclear Medicine, Université de Montréal, Quebec, Canada; Centre de Recherche, Institut Universitaire de Gériatrie de Montréal, Québec, Canada
| | - Nils D Forkert
- Department of Radiology, University of Calgary, Canada; Alberta Children's Hospital Research Institute, University of Calgary, Canada; Department of Clinical Neurosciences, University of Calgary, Canada; Hotchkiss Brain Institute, University of Calgary, Canada; Department of Electrical and Software Engineering, University of Calgary, Canada
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Gardoni A, Sarasso E, Agosta F, Filippi M, Corbetta D. Rehabilitative interventions for impaired handwriting in people with Parkinson's disease: a scoping review. Neurol Sci 2023:10.1007/s10072-023-06752-6. [PMID: 36964814 DOI: 10.1007/s10072-023-06752-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Accepted: 03/12/2023] [Indexed: 03/26/2023]
Abstract
BACKGROUND People with Parkinson's disease (PD) often complain about handwriting difficulties. Currently, there is no consensus on the rehabilitative treatment and outcome measures for handwriting rehabilitation in PD. OBJECTIVES This study aims to investigate evidence on handwriting rehabilitation in people with PD, examining characteristics of interventions and outcomes. METHODS A scoping review was conducted according to Arksey and O'Malley's framework and PRISMA-ScR List. We searched electronic databases of PubMed, Physiotherapy Evidence Database, Cochrane Central Register of Controlled Trials, and Embase since inception to January 2023. We included interventional studies assessing the effects of structured rehabilitation programs for impaired handwriting in people with PD. Two reviewers independently selected studies, extracted data, and assessed the risk of bias using the Cochrane Collaboration's tool for assessing Risk of Bias version 2 or the Risk Of Bias In Non-randomized Studies. We performed a narrative analysis on training characteristics and assessed outcomes. RESULTS We included eight studies. The risk of bias was generally high. Either handwriting-specific or handwriting-non-specific trainings were proposed, and most studies provided a home-based training. Handwriting-specific training improved writing amplitude while handwriting-non-specific trainings, such as resistance and stretching/relaxation programs, resulted in increased writing speed. CONCLUSIONS The current knowledge is based on few and heterogeneous studies with high risk of bias. Handwriting-specific training might show potential benefits on handwriting in people with PD. Further high-quality randomized controlled trials are needed to reveal the effect of handwriting training in people with PD on standardized outcome measures. Handwriting-specific training could be combined to resistance training and stretching, which seemed to influence writing performance.
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Affiliation(s)
- Andrea Gardoni
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Department of Rehabilitation and Functional Recovery, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Elisabetta Sarasso
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Department of Rehabilitation and Functional Recovery, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics and Maternal Child Health, University of Genoa, Genoa, Italy
| | - Federica Agosta
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Massimo Filippi
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurorehabilitation Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurophysiology Service, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Davide Corbetta
- Department of Rehabilitation and Functional Recovery, IRCCS San Raffaele Scientific Institute, Milan, Italy.
- Vita-Salute San Raffaele University, Milan, Italy.
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Cerebellar alterations in Parkinson's disease with postural instability and gait disorders. J Neurol 2023; 270:1735-1744. [PMID: 36534200 DOI: 10.1007/s00415-022-11531-y] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Revised: 12/10/2022] [Accepted: 12/13/2022] [Indexed: 12/23/2022]
Abstract
BACKGROUND Few studies interrogated the involvement of cerebellum in modulating gait in Parkinson's disease (PD) patients with postural instability and gait disorders (PD-PIGD). This study aimed at assessing cerebellar atrophy and activity alterations during functional MRI (fMRI) gait-simulating motor- and dual-tasks in PD-PIGD. METHODS Twenty-one PD-PIGD and 23 healthy controls underwent clinical assessment, structural MRI, and fMRI including a motor-task (foot anti-phase movements) and a dual-task (foot anti-phase movements while counting backwards by threes). Grey matter cerebellar volumes were assessed using SUIT atlas. FMRI activations were extracted from each cerebellar lobule, and we correlated cerebellar and basal ganglia activity. RESULTS PD-PIGD patients had reduced volumes of cerebellar motor and non-motor areas relative to controls. During fMRI motor-task, patients showed greater activation of cognitive cerebellar areas (VI and Crus I-II) vs controls. During fMRI dual-task, PD-PIGD patients showed increased activity of cognitive areas (Crus II) and reduced activity of motor areas (I-IV). Cerebellar structural alterations correlated with increased fMRI activity of cerebellar cognitive areas and with lower executive-attentive performance. The increased activity of Crus I during the motor-task correlated with a better motor performance in PD-PIGD. Moreover, the increased activity of cerebellum correlated with a reduced activity of putamen. CONCLUSIONS In PD-PIGD, the increased activity of non-motor cerebellar areas during gait-simulating tasks may be a consequence of grey matter atrophy or an attempt to compensate the functional failure of cerebellar motor areas and basal ganglia. Cerebellar MRI metrics are useful to characterize brain correlates of motor and dual-task abilities in PD-PIGD patients.
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Sarasso E, Filippi M, Agosta F. Clinical and MRI features of gait and balance disorders in neurodegenerative diseases. J Neurol 2023; 270:1798-1807. [PMID: 36577818 DOI: 10.1007/s00415-022-11544-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2022] [Revised: 12/20/2022] [Accepted: 12/21/2022] [Indexed: 12/29/2022]
Abstract
Gait and balance disorders are common signs in several neurodegenerative diseases such as Parkinson's disease, atypical parkinsonism, idiopathic normal pressure hydrocephalus, cerebrovascular disease, dementing disorders and multiple sclerosis. According to each condition, patients present with different gait and balance alterations depending on the structural and functional brain changes through the disease course. In this review, we will summarize the main clinical characteristics of gait and balance disorders in the major neurodegenerative conditions, providing an overview of the significant structural and functional MRI brain alterations underlying these deficits. We also will discuss the role of neurorehabilitation strategies in promoting brain plasticity and gait/balance improvements in these patients.
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Affiliation(s)
- Elisabetta Sarasso
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Via Olgettina, 60, 20132, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics and Maternal Child Health, University of Genoa, Genoa, Italy
| | - Massimo Filippi
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Via Olgettina, 60, 20132, Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurophysiology Service, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurorehabilitation Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Federica Agosta
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Via Olgettina, 60, 20132, Milan, Italy.
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.
- Vita-Salute San Raffaele University, Milan, Italy.
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Almgren H, Hanganu A, Camacho M, Kibreab M, Camicioli R, Ismail Z, Forkert ND, Monchi O. Motor symptoms in Parkinson's disease are related to the interplay between cortical curvature and thickness. Neuroimage Clin 2023; 37:103300. [PMID: 36580712 PMCID: PMC9827056 DOI: 10.1016/j.nicl.2022.103300] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2022] [Revised: 12/08/2022] [Accepted: 12/20/2022] [Indexed: 12/24/2022]
Abstract
INTRODUCTION Brain atrophy in Parkinson's disease occurs to varying degrees in different brain regions, even at the early stage of the disease. While cortical morphological features are often considered independently in structural brain imaging studies, research on the co-progression of different cortical morphological measurements could provide new insights regarding the progression of PD. This study's aim was to examine the interplay between cortical curvature and thickness as a function of PD diagnosis, motor symptoms, and cognitive performance. METHODS A total of 359 de novo PD patients and 159 healthy controls (HC) from the Parkinson's Progression Markers Initiative (PPMI) database were included in this study. Additionally, an independent cohort from four databases (182 PD, 132 HC) with longer disease durations was included to assess the effects of PD diagnosis in more advanced cases. Pearson correlation was used to determine subject-specific associations between cortical curvature and thickness estimated from T1-weighted MRI images. General linear modeling (GLM) was then used to assess the effect of PD diagnosis, motor symptoms, and cognitive performance on the curvature-thickness association. Next, longitudinal changes in the curvature-thickness correlation as well as the predictive effect of the cortical curvature-thickness association on changes in motor symptoms and cognitive performance across four years were investigated. Finally, Akaike information criterion (AIC) was used to build a GLM to model PD motor symptom severity cross-sectionally. RESULTS A significant interaction effect between PD motor symptoms and age on the curvature-thickness correlation was found (βstandardized = 0.11; t(350) = 2.12; p = 0.03). This interaction effect showed that motor symptoms in older patients were related to an attenuated curvature-thickness association. No significant effect of PD diagnosis was observed for the PPMI database (β = 0.03; t(510) = 0.35; p = 0.72). However, in patients with a longer disease duration, a significant effect of diagnosis on the curvature-thickness association was found (βstandardized = 0.31; t(306.7) = 3.49; p = 0.0006). Moreover, rigidity, but not tremor, in PD was significantly related to the curvature-thickness correlation (βstandardized = 0.11, t(350) = 2.24, p = 0.03; βstandardized = -0.03, t(350) = -0.58, p = 0.56, respectively). The curvature-thickness association was attenuated over time in both PD and HC, but the two groups did not show a significantly different effect (βstandardized = 0.03, t(184.7) = 0.78, p = 0.44). No predictive effects of the CC-CT correlation on longitudinal changes in cognitive performance or motor symptoms were observed (all p-values > 0.05). The best cross-sectional model for PD motor symptoms included the curvature-thickness correlation, cognitive performance, and putamen dopamine transporter (DAT) binding, which together explained 14 % of variance. CONCLUSION The association between cortical curvature and thickness is related to PD motor symptoms and age. This research shows the potential of modeling the curvature-thickness interplay in PD.
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Affiliation(s)
- Hannes Almgren
- Department of Clinical Neurosciences, University of Calgary, 2500 University Drive NW, Calgary, AB T2N 1N4, Canada; Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, 3330 Hospital Dr NW, Calgary, AB T2N 1N4, Canada.
| | - Alexandru Hanganu
- Département de Psychologie, Université de Montréal, Pavillon Marie-Victorin, 90 Vincent d'Indy Ave, Montréal, QC H2V 2S9, Canada; Centre de recherche de l'Institut universitaire de gériatrie de Montréal, 4565 Chemin Queen Mary, Montréal, QC H3W 1W5, Canada
| | - Milton Camacho
- Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, 3330 Hospital Dr NW, Calgary, AB T2N 1N4, Canada; Department of Radiology, University of Calgary, 2500 University Drive NW, Calgary, AB T2N 1N4, Canada
| | - Mekale Kibreab
- Department of Clinical Neurosciences, University of Calgary, 2500 University Drive NW, Calgary, AB T2N 1N4, Canada; Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, 3330 Hospital Dr NW, Calgary, AB T2N 1N4, Canada
| | - Richard Camicioli
- Division of Neurology, Department of Medicine, and Neuroscience and Mental Health Institute, University of Alberta, 7-112 Clinical Sciences Building 11350 83(rd) Avenue, Edmonton, Alberta, AB T6G 2G3, Canada
| | - Zahinoor Ismail
- Department of Clinical Neurosciences, University of Calgary, 2500 University Drive NW, Calgary, AB T2N 1N4, Canada; Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, 3330 Hospital Dr NW, Calgary, AB T2N 1N4, Canada; Department of Psychiatry, University of Calgary, 3280 Hospital Dr NW, Calgary, AB T2N 4Z6, Canada
| | - Nils D Forkert
- Department of Clinical Neurosciences, University of Calgary, 2500 University Drive NW, Calgary, AB T2N 1N4, Canada; Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, 3330 Hospital Dr NW, Calgary, AB T2N 1N4, Canada; Department of Radiology, University of Calgary, 2500 University Drive NW, Calgary, AB T2N 1N4, Canada; Alberta Children's Hospital Research Institute, University of Calgary, Heritage Medical Research Building, 3330 Hospital Dr. NW, Calgary, AB T2N 4N1, Canada
| | - Oury Monchi
- Department of Clinical Neurosciences, University of Calgary, 2500 University Drive NW, Calgary, AB T2N 1N4, Canada; Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, 3330 Hospital Dr NW, Calgary, AB T2N 1N4, Canada; Centre de recherche de l'Institut universitaire de gériatrie de Montréal, 4565 Chemin Queen Mary, Montréal, QC H3W 1W5, Canada; Department of Radiology, University of Calgary, 2500 University Drive NW, Calgary, AB T2N 1N4, Canada; Département de radiologie, radio-oncologie et médecine nucléaire, Faculté de médecine, Université de Montréal, Pavillon Roger-Gaudry, 2900 boulevard, Édouard-Montpetit, Montréal, QC H3T 1A4, Canada.
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Du J, Zhou X, Liang Y, Zhao L, Dai C, Zhong Y, Liu H, Liu G, Mo L, Tan C, Liu X, Chen L. Levodopa responsiveness and white matter alterations in Parkinson's disease: A DTI-based study and brain network analysis: A cross-sectional study. Brain Behav 2022; 12:e2825. [PMID: 36423257 PMCID: PMC9759147 DOI: 10.1002/brb3.2825] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/17/2022] [Revised: 09/24/2022] [Accepted: 11/01/2022] [Indexed: 11/27/2022] Open
Abstract
BACKGROUND Patients with Parkinson's disease (PD) present various responsiveness to levodopa, but the cause of such differences in levodopa responsiveness is unclear. Previous studies related the damage of brain white matter (WM) to levodopa responsiveness in PD patients, but no study investigated the relationship between the structural brain network change in PD patients and their levodopa responsiveness. METHODS PD patients were recruited and evaluated using the Unified Parkinson's Disease Rating Scale (UPDRS). Each patient received a diffusion tensor imaging (DTI) scan and an acute levodopa challenge test. The improvement rate of UPDRS-III was calculated. PD patients were grouped into irresponsive group (improvement rate < 30%) and responsive group (improvement rate ≥ 30%). Tract-based spatial statistics (TBSS), deterministic tracing (DT), region of interest (ROI) analysis, and automatic fiber identification (AFQ) analyses were performed. The structural brain network was also constructed and the topological parameters were calculated. RESULTS Fifty-four PD patients were included. TBSS identified significant differences in fractional anisotropy (FA) values in the corpus callosum and other regions of the brain. DT and ROI analysis of the corpus callosum found a significant difference in FA between the two groups. Graph theory analysis showed statistical differences in global efficiency, local efficiency, and characteristic path length. CONCLUSION PD patients with poor responsiveness to levodopa had WM damage in multiple brain areas, especially the corpus callosum, which might cause disruption of information integration of the structural brain network.
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Affiliation(s)
- Juncong Du
- Department of Neurology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, People's Republic of China
| | - Xuan Zhou
- Department of Neurology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, People's Republic of China
| | - Yi Liang
- Department of Neurology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, People's Republic of China
| | - Lili Zhao
- Department of Neurology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, People's Republic of China
| | - Chengcheng Dai
- Department of Neurology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, People's Republic of China
| | - Yuke Zhong
- Department of Neurology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, People's Republic of China
| | - Hang Liu
- Department of Neurology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, People's Republic of China
| | - Guohui Liu
- Department of Neurology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, People's Republic of China
| | - Lijuan Mo
- Department of Neurology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, People's Republic of China
| | - Changhong Tan
- Department of Neurology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, People's Republic of China
| | - Xi Liu
- Department of Neurology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, People's Republic of China
| | - Lifen Chen
- Department of Neurology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, People's Republic of China
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MRI biomarkers of freezing of gait development in Parkinson’s disease. NPJ Parkinsons Dis 2022; 8:158. [DOI: 10.1038/s41531-022-00426-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Accepted: 10/31/2022] [Indexed: 11/16/2022] Open
Abstract
AbstractThis study investigated longitudinal clinical, structural and functional brain alterations in Parkinson’s disease patients with freezing of gait (PD-FoG) and in those developing (PD-FoG-converters) and not developing FoG (PD-non-converters) over two years. Moreover, this study explored if any clinical and/or MRI metric predicts FoG development. Thirty PD-FoG, 11 PD-FoG-converters and 11 PD-non-converters were followed for two years. Thirty healthy controls were included at baseline. Participants underwent clinical and MRI visits. Cortical thickness, basal ganglia volumes and functional network graph metrics were evaluated at baseline and over time. In PD groups, correlations between baseline MRI and clinical worsening were tested. A ROC curve analysis investigated if baseline clinical and MRI measures, selected using a stepwise model procedure, could differentiate PD-FoG-converters from PD-non-converters. At baseline, PD-FoG patients had widespread cortical/subcortical atrophy, while PD-FoG-converters and non-converters showed atrophy in sensorimotor areas and basal ganglia relative to controls. Over time, PD-non-converters accumulated cortical thinning of left temporal pole and pallidum without significant clinical changes. PD-FoG-converters showed worsening of disease severity, executive functions, and mood together with an accumulation of occipital atrophy, similarly to PD-FoG. At baseline, PD-FoG-converters relative to controls and PD-FoG showed higher global and parietal clustering coefficient and global local efficiency. Over time, PD-FoG-converters showed reduced parietal clustering coefficient and sensorimotor local efficiency, PD-non-converters showed increased sensorimotor path length, while PD-FoG patients showed stable graph metrics. Stepwise prediction model including dyskinesia, postural instability and gait disorders scores and parietal clustering coefficient was the best predictor of FoG conversion. Combining clinical and MRI data, ROC curves provided the highest classification power to predict the conversion (AUC = 0.95, 95%CI: 0.86–1). Structural MRI is a useful tool to monitor PD progression, while functional MRI together with clinical features may be helpful to identify FoG conversion early.
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REDUCED POWER AND PHASE-LOCKING VALUES WERE ACCOMPANIED BY THALAMUS, PUTAMEN AND HIPPOCAMPUS ATROPHY IN PARKINSON'S DISEASE WITH MILD COGNITIVE IMPAIRMENT: AN EVENT-RELATED OSCILLATION STUDY. Neurobiol Aging 2022; 121:88-106. [DOI: 10.1016/j.neurobiolaging.2022.10.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2022] [Revised: 09/30/2022] [Accepted: 10/05/2022] [Indexed: 11/07/2022]
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Kent DM, Leung LY, Puttock EJ, Wang AY, Luetmer PH, Kallmes DF, Nelson J, Fu S, Zheng C, Vickery EM, Liu H, Noyce AJ, Chen W. Development of Parkinson Disease and Its Relationship with Incidentally Discovered White Matter Disease and Covert Brain Infarction in a Real-World Cohort. Ann Neurol 2022; 92:620-630. [PMID: 35866711 PMCID: PMC9489676 DOI: 10.1002/ana.26458] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Revised: 07/18/2022] [Accepted: 07/20/2022] [Indexed: 11/08/2022]
Abstract
OBJECTIVE This study aimed to examine the relationship between covert cerebrovascular disease, comprised of covert brain infarction and white matter disease, discovered incidentally in routine care, and subsequent Parkinson disease. METHODS Patients were ≥50 years and received neuroimaging for non-stroke indications in the Kaiser Permanente Southern California system from 2009 to 2019. Natural language processing identified incidentally discovered covert brain infarction and white matter disease and classified white matter disease severity. The Parkinson disease outcome was defined as 2 ICD diagnosis codes. RESULTS 230,062 patients were included (median follow-up 3.72 years). A total of 1,941 Parkinson disease cases were identified (median time-to-event 2.35 years). Natural language processing identified covert cerebrovascular disease in 70,592 (30.7%) patients, 10,622 (4.6%) with covert brain infarction and 65,814 (28.6%) with white matter disease. After adjustment for known risk factors, white matter disease was associated with Parkinson disease (hazard ratio 1.67 [95%CI, 1.44, 1.93] for patients <70 years and 1.33 [1.18, 1.50] for those ≥70 years). Greater severity of white matter disease was associated with increased incidence of Parkinson disease(/1,000 person-years), from 1.52 (1.43, 1.61) in patients without white matter disease to 4.90 (3.86, 6.13) in those with severe disease. Findings were robust when more specific definitions of Parkinson disease were used. Covert brain infarction was not associated with Parkinson disease (adjusted hazard ratio = 1.05 [0.88, 1.24]). INTERPRETATION Incidentally discovered white matter disease was associated with subsequent Parkinson disease, an association strengthened with younger age and increased white matter disease severity. Incidentally discovered covert brain infarction did not appear to be associated with subsequent Parkinson disease. ANN NEUROL 2022;92:620-630.
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Affiliation(s)
- David M. Kent
- Predictive Analytics and Comparative Effectiveness Center,
Tufts Medical Center, Boston, MA, USA
| | - Lester Y. Leung
- Department of Neurology, Tufts Medical Center, Boston, MA,
USA
| | - Eric J. Puttock
- Department of Research and Evaluation, Kaiser Permanente
Southern California, Pasadena, CA, USA
| | - Andy Y. Wang
- Predictive Analytics and Comparative Effectiveness Center,
Tufts Medical Center, Boston, MA, USA
| | | | | | - Jason Nelson
- Predictive Analytics and Comparative Effectiveness Center,
Tufts Medical Center, Boston, MA, USA
| | - Sunyang Fu
- Department of AI and Informatics, Mayo Clinic, Rochester,
MN, USA
| | - Chengyi Zheng
- Department of Research and Evaluation, Kaiser Permanente
Southern California, Pasadena, CA, USA
| | - Ellen M. Vickery
- Predictive Analytics and Comparative Effectiveness Center,
Tufts Medical Center, Boston, MA, USA
| | - Hongfang Liu
- Department of AI and Informatics, Mayo Clinic, Rochester,
MN, USA
| | - Alastair J. Noyce
- Preventive Neurology Unit, Wolfson Institute of Population
Health, Queen Mary University of London, UK
- Department of Clinical and Movement Neuroscience, UCL
Institute of Neurology, London, UK
| | - Wansu Chen
- Department of Research and Evaluation, Kaiser Permanente
Southern California, Pasadena, CA, USA
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Cerebro-cerebellar motor networks in clinical subtypes of Parkinson’s disease. NPJ Parkinsons Dis 2022; 8:113. [PMID: 36068246 PMCID: PMC9448730 DOI: 10.1038/s41531-022-00377-w] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2022] [Accepted: 08/12/2022] [Indexed: 11/30/2022] Open
Abstract
Parkinson’s disease (PD) patients can be classified in tremor-dominant (TD) and postural-instability-and-gait-disorder (PIGD) motor subtypes. PIGD represents a more aggressive form of the disease that TD patients have a potentiality of converting into. This study investigated functional alterations within the cerebro-cerebellar system in PD-TD and PD-PIGD patients using stepwise functional connectivity (SFC) analysis and identified neuroimaging features that predict TD to PIGD conversion. Thirty-two PD-TD, 26 PD-PIGD patients and 60 healthy controls performed clinical/cognitive evaluations and resting-state functional MRI (fMRI). Four-year clinical follow-up data were available for 28 PD-TD patients, who were classified in 10 converters (cTD-PD) and 18 non-converters (ncTD-PD) to PIGD. The cerebellar seed-region was identified using a fMRI motor task. SFC analysis, characterizing regions that connect brain areas to the cerebellar seed at different levels of link-step distances, evaluated similar and divergent alterations in PD-TD and PD-PIGD. The discriminatory power of clinical data and/or SFC in distinguishing cPD-TD from ncPD-TD patients was assessed using ROC curve analysis. Compared to PD-TD, PD-PIGD patients showed decreased SFC in temporal lobe and occipital lobes and increased SFC in cerebellar cortex and ponto-medullary junction. Considering the subtype-conversion analysis, cPD-TD patients were characterized by increased SFC in temporal and occipital lobes and in cerebellum and ponto-medullary junction relative to ncPD-TD group. Combining clinical and SFC data, ROC curves provided the highest classification power to identify conversion to PIGD. These findings provide novel insights into the pathophysiology underlying different PD motor phenotypes and a potential tool for early characterization of PD-TD patients at risk of conversion to PIGD.
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Park CH, Shin NY, Yoo SW, Seo H, Yoon U, Yoo JY, Ahn K, Kim JS. Simulating the progression of brain structural alterations in Parkinson's disease. NPJ Parkinsons Dis 2022; 8:86. [PMID: 35764657 PMCID: PMC9240031 DOI: 10.1038/s41531-022-00349-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2021] [Accepted: 06/10/2022] [Indexed: 12/01/2022] Open
Abstract
Considering brain structural alterations as neurodegenerative consequences of Parkinson's disease (PD), we sought to infer the progression of PD via the ordering of brain structural alterations from cross-sectional MRI observations. Having measured cortical thinning in gray matter (GM) regions and disintegrity in white matter (WM) regions as MRI markers of structural alterations for 130 patients with PD (69 ± 10 years, 72 men), stochastic simulation based on the probabilistic relationship between the brain regions was conducted to infer the ordering of structural alterations across all brain regions and the staging of structural alterations according to changes in clinical status. The ordering of structural alterations represented WM disintegrity tending to occur earlier than cortical thinning. The staging of structural alterations indicated structural alterations happening mostly before major disease complications such as postural instability and dementia. Later disease states predicted by the sequence of structural alterations were significantly related to more severe clinical symptoms. The relevance of the ordering of brain structural alterations to the severity of clinical symptoms suggests the clinical feasibility of predicting PD progression states.
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Affiliation(s)
- Chang-Hyun Park
- Department of Radiology, College of Medicine, Catholic University of Korea, Seoul, Korea.,Center for Neuroprosthetics and Brain Mind Institute, Swiss Federal Institute of Technology (EPFL), Geneva, Switzerland
| | - Na-Young Shin
- Department of Radiology, College of Medicine, Catholic University of Korea, Seoul, Korea.
| | - Sang-Won Yoo
- Department of Neurology, College of Medicine, Catholic University of Korea, Seoul, Korea
| | - Haeseok Seo
- Department of Biomedical Engineering, College of Bio and Medical Sciences, Daegu Catholic University, Gyeongsan, Gyeongbuk, Korea
| | - Uicheul Yoon
- Department of Biomedical Engineering, College of Bio and Medical Sciences, Daegu Catholic University, Gyeongsan, Gyeongbuk, Korea
| | - Ji-Yeon Yoo
- Department of Neurology, College of Medicine, Catholic University of Korea, Seoul, Korea
| | - Kookjin Ahn
- Department of Radiology, College of Medicine, Catholic University of Korea, Seoul, Korea
| | - Joong-Seok Kim
- Department of Neurology, College of Medicine, Catholic University of Korea, Seoul, Korea
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Morphological basis of Parkinson disease-associated cognitive impairment: an update. J Neural Transm (Vienna) 2022; 129:977-999. [PMID: 35726096 DOI: 10.1007/s00702-022-02522-4] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Accepted: 05/25/2022] [Indexed: 12/15/2022]
Abstract
Cognitive impairment is one of the most salient non-motor symptoms of Parkinson disease (PD) that poses a significant burden on the patients and carers as well as being a risk factor for early mortality. People with PD show a wide spectrum of cognitive dysfunctions ranging from subjective cognitive decline and mild cognitive impairment (MCI) to frank dementia. The mean frequency of PD with MCI (PD-MCI) is 25.8% and the pooled dementia frequency is 26.3% increasing up to 83% 20 years after diagnosis. A better understanding of the underlying pathological processes will aid in directing disease-specific treatment. Modern neuroimaging studies revealed considerable changes in gray and white matter in PD patients with cognitive impairment, cortical atrophy, hypometabolism, dopamine/cholinergic or other neurotransmitter dysfunction and increased amyloid burden, but multiple mechanism are likely involved. Combined analysis of imaging and fluid markers is the most promising method for identifying PD-MCI and Parkinson disease dementia (PDD). Morphological substrates are a combination of Lewy- and Alzheimer-associated and other concomitant pathologies with aggregation of α-synuclein, amyloid, tau and other pathological proteins in cortical and subcortical regions causing destruction of essential neuronal networks. Significant pathological heterogeneity within PD-MCI reflects deficits in various cognitive domains. This review highlights the essential neuroimaging data and neuropathological changes in PD with cognitive impairment, the amount and topographical distribution of pathological protein aggregates and their pathophysiological relevance. Large-scale clinicopathological correlative studies are warranted to further elucidate the exact neuropathological correlates of cognitive impairment in PD and related synucleinopathies as a basis for early diagnosis and future disease-modifying therapies.
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Neuroimaging signatures predicting motor improvement to focused ultrasound subthalamotomy in Parkinson's disease. NPJ Parkinsons Dis 2022; 8:70. [PMID: 35665753 PMCID: PMC9166695 DOI: 10.1038/s41531-022-00332-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2021] [Accepted: 05/13/2022] [Indexed: 11/24/2022] Open
Abstract
Subthalamotomy using transcranial magnetic resonance-guided focused ultrasound (tcMRgFUS) is a novel and promising treatment for Parkinson’s Disease (PD). In this study, we investigate if baseline brain imaging features can be early predictors of tcMRgFUS-subthalamotomy efficacy, as well as which are the post-treatment brain changes associated with the clinical outcomes. Towards this aim, functional and structural neuroimaging and extensive clinical data from thirty-five PD patients enrolled in a double-blind tcMRgFUS-subthalamotomy clinical trial were analyzed. A multivariate cross-correlation analysis revealed that the baseline multimodal imaging data significantly explain (P < 0.005, FWE-corrected) the inter-individual variability in response to treatment. Most predictive features at baseline included neural fluctuations in distributed cortical regions and structural integrity in the putamen and parietal regions. Additionally, a similar multivariate analysis showed that the population variance in clinical improvements is significantly explained (P < 0.001, FWE-corrected) by a distributed network of concurrent functional and structural brain changes in frontotemporal, parietal, occipital, and cerebellar regions, as opposed to local changes in very specific brain regions. Overall, our findings reveal specific quantitative brain signatures highly predictive of tcMRgFUS-subthalamotomy responsiveness in PD. The unanticipated weight of a cortical-subcortical-cerebellar subnetwork in defining clinical outcome extends the current biological understanding of the mechanisms associated with clinical benefits.
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Filippi M, Balestrino R, Basaia S, Agosta F. Neuroimaging in Glucocerebrosidase-Associated Parkinsonism: A Systematic Review. Mov Disord 2022; 37:1375-1393. [PMID: 35521899 PMCID: PMC9546404 DOI: 10.1002/mds.29047] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2022] [Revised: 04/14/2022] [Accepted: 04/18/2022] [Indexed: 12/11/2022] Open
Abstract
Background Mutations in the GBA gene cause Gaucher's disease (GD) and constitute the most frequent genetic risk factor for idiopathic Parkinson's disease (iPD). Nonmanifesting carriers of GBA mutations/variants (GBA‐NMC) constitute a potential PD preclinical population, whereas PD patients carrying some GBA mutations/variants (GBA‐PD) have a higher risk of a more aggressive disease course. Different neuroimaging techniques are emerging as potential biomarkers in PD and have been used to study GBA‐associated parkinsonism. Objective The aim is to critically review studies applying neuroimaging to GBA‐associated parkinsonism. Methods Literature search was performed using PubMed and EMBASE databases (last search February 7, 2022). Studies reporting neuroimaging findings in GBA‐PD, GD with and without parkinsonism, and GBA‐NMC were included. Results Thirty‐five studies were included. In longitudinal studies, GBA‐PD patients show a more aggressive disease than iPD at both structural magnetic resonance imaging and 123‐fluoropropylcarbomethoxyiodophenylnortropane single‐photon emission computed tomography. Fluorodeoxyglucose‐positron emission tomography and brain perfusion studies reported a greater cortical involvement in GBA‐PD compared to iPD. Overall, contrasting evidence is available regarding GBA‐NMC for imaging and clinical findings, although subtle differences have been reported compared with healthy controls with no mutations. Conclusions Although results must be interpreted with caution due to limitations of the studies, in line with previous clinical observations, GBA‐PD showed a more aggressive disease progression in neuroimaging longitudinal studies compared to iPD. Cognitive impairment, a “clinical signature” of GBA‐PD, seems to find its neuroimaging correlate in the greater cortical burden displayed by these patients as compared to iPD. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society
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Affiliation(s)
- Massimo Filippi
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Neurorehabilitation Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Neurophysiology Service, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Vita-Salute San Raffaele University, Milan, Italy
| | - Roberta Balestrino
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Vita-Salute San Raffaele University, Milan, Italy.,Department of Neurosurgery and Gamma Knife Radiosurgery, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Silvia Basaia
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Federica Agosta
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Vita-Salute San Raffaele University, Milan, Italy
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40
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Sanmartino F, Cruz-Gómez ÁJ, Rashid-López R, Lozano-Soto E, López-Sosa F, Zuazo A, Riqué-Dormido J, Espinosa-Rosso R, González-Rosa JJ. Subthalamic Beta Activity in Parkinson's Disease May Be Linked to Dorsal Striatum Gray Matter Volume and Prefrontal Cortical Thickness: A Pilot Study. Front Neurol 2022; 13:799696. [PMID: 35401426 PMCID: PMC8985754 DOI: 10.3389/fneur.2022.799696] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Accepted: 02/24/2022] [Indexed: 11/30/2022] Open
Abstract
Background Excessive oscillations at beta frequencies (13–35 Hz) in the subthalamic nucleus (STN) represent a pathophysiological hallmark of Parkinson's disease (PD), which correlates well with parkinsonian symptoms and is reduced in response to standard disease treatments. However, the association of disease-specific regional gray matter (GM) atrophy or cortical thickness (CT) with the presence of STN beta oscillatory activity has been poorly investigated but is of relevance given the potential of these variables for extracting information about PD pathophysiology. This exploratory study investigated the involvement of regional GM volume and CT in the basal ganglia-cortical network and its potential association with the presence of STN beta oscillatory activity in PD. Methods We acquired preoperative GM densities on T1-weighted magnetic resonance imaging scans and we carried out regional estimation of GM volume and CT. LFP activities from the STN were recorded post-operatively in 7 cognitively preserved PD patients off dopaminergic medication undergoing deep-brain stimulation surgery. Oscillatory beta power was determined by power spectral density of 4-min resting state STN LFP activity. Spearman partial correlations and regression analysis were used to screen the presence of STN beta power for their relationship with GM volume and CT measurements. Results After controlling for the effects of age, educational level, and disease duration, and after correcting for multiple testing, enhanced STN beta power showed significant and negative correlations between, first, volume of the right putamen and left caudate nucleus, and second, smaller CT in frontal regions involving the left rostral middle frontal gyrus (MFG) and left medial orbitofrontal gyrus. A lower volume in the right putamen and a lower CT in the left MFG demonstrated the strongest associations with increased STN beta power. Conclusions These tentative results seem to suggest that STN LFP beta frequencies may be mainly linked to different but ongoing parallel neurodegenerative processes, on the one hand, to GM volume reduction in dorsal striatum, and on the other hand, to CT reduction of prefrontal-“associative” regions. These findings could further delineate the brain structural interactions underpinning the exaggerated STN beta activity commonly observed in PD patients.
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Affiliation(s)
- Florencia Sanmartino
- Department of Psychology, University of Cadiz, Cádiz, Spain.,Psychophysiology and Neuroimaging Group, Institute of Biomedical Research Cadiz (INiBICA), Cádiz, Spain
| | - Álvaro J Cruz-Gómez
- Department of Psychology, University of Cadiz, Cádiz, Spain.,Psychophysiology and Neuroimaging Group, Institute of Biomedical Research Cadiz (INiBICA), Cádiz, Spain
| | - Raúl Rashid-López
- Psychophysiology and Neuroimaging Group, Institute of Biomedical Research Cadiz (INiBICA), Cádiz, Spain.,Department of Neurology, Puerta del Mar University Hospital, Cádiz, Spain
| | - Elena Lozano-Soto
- Department of Psychology, University of Cadiz, Cádiz, Spain.,Psychophysiology and Neuroimaging Group, Institute of Biomedical Research Cadiz (INiBICA), Cádiz, Spain
| | - Fernando López-Sosa
- Psychophysiology and Neuroimaging Group, Institute of Biomedical Research Cadiz (INiBICA), Cádiz, Spain
| | - Amaya Zuazo
- Department of Radiodiagnostic and Medical Imaging, Puerta del Mar University Hospital, Cádiz, Spain
| | - Jesús Riqué-Dormido
- Department of Neurosurgery, Puerta del Mar University Hospital, Cádiz, Spain
| | - Raúl Espinosa-Rosso
- Psychophysiology and Neuroimaging Group, Institute of Biomedical Research Cadiz (INiBICA), Cádiz, Spain.,Department of Neurology, Puerta del Mar University Hospital, Cádiz, Spain.,Department of Neurology, Jerez de la Frontera University Hospital, Jerez de la Frontera, Spain
| | - Javier J González-Rosa
- Department of Psychology, University of Cadiz, Cádiz, Spain.,Psychophysiology and Neuroimaging Group, Institute of Biomedical Research Cadiz (INiBICA), Cádiz, Spain
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41
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Calderón-Garcidueñas L, Hernández-Luna J, Mukherjee PS, Styner M, Chávez-Franco DA, Luévano-Castro SC, Crespo-Cortés CN, Stommel EW, Torres-Jardón R. Hemispheric Cortical, Cerebellar and Caudate Atrophy Associated to Cognitive Impairment in Metropolitan Mexico City Young Adults Exposed to Fine Particulate Matter Air Pollution. TOXICS 2022; 10:toxics10040156. [PMID: 35448417 PMCID: PMC9028857 DOI: 10.3390/toxics10040156] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/11/2022] [Revised: 03/14/2022] [Accepted: 03/22/2022] [Indexed: 12/16/2022]
Abstract
Exposures to fine particulate matter PM2.5 are associated with Alzheimer's, Parkinson's (AD, PD) and TDP-43 pathology in young Metropolitan Mexico City (MMC) residents. High-resolution structural T1-weighted brain MRI and/or Montreal Cognitive Assessment (MoCA) data were examined in 302 volunteers age 32.7 ± 6.0 years old. We used multivariate linear regressions to examine cortical surface area and thickness, subcortical and cerebellar volumes and MoCA in ≤30 vs. ≥31 years old. MMC residents were exposed to PM2.5 ~ 30.9 µg/m3. Robust hemispheric differences in frontal and temporal lobes, caudate and cerebellar gray and white matter and strong associations between MoCA total and index scores and caudate bilateral volumes, frontotemporal and cerebellar volumetric changes were documented. MoCA LIS scores are affected early and low pollution controls ≥ 31 years old have higher MoCA vs. MMC counterparts (p ≤ 0.0001). Residency in MMC is associated with cognitive impairment and overlapping targeted patterns of brain atrophy described for AD, PD and Fronto-Temporal Dementia (FTD). MMC children and young adult longitudinal studies are urgently needed to define brain development impact, cognitive impairment and brain atrophy related to air pollution. Identification of early AD, PD and FTD biomarkers and reductions on PM2.5 emissions, including poorly regulated heavy-duty diesel vehicles, should be prioritized to protect 21.8 million highly exposed MMC urbanites.
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Affiliation(s)
- Lilian Calderón-Garcidueñas
- College of Health, The University of Montana, Missoula, MT 59812, USA
- Escuela de Ciencias de la Salud, Universidad del Valle de México, Mexico City 14370, Mexico; (D.A.C.-F.); (S.C.L.-C.); (C.N.C.-C.)
- Correspondence: ; Tel.: +1-406-243-4785
| | | | - Partha S. Mukherjee
- Interdisciplinary Statistical Research Unit, Indian Statistical Institute, Kolkata 700108, India;
| | - Martin Styner
- Neuro Image Research and Analysis Lab, University of North Carolina, Chapel Hill, NC 27599, USA;
| | - Diana A. Chávez-Franco
- Escuela de Ciencias de la Salud, Universidad del Valle de México, Mexico City 14370, Mexico; (D.A.C.-F.); (S.C.L.-C.); (C.N.C.-C.)
| | - Samuel C. Luévano-Castro
- Escuela de Ciencias de la Salud, Universidad del Valle de México, Mexico City 14370, Mexico; (D.A.C.-F.); (S.C.L.-C.); (C.N.C.-C.)
| | - Celia Nohemí Crespo-Cortés
- Escuela de Ciencias de la Salud, Universidad del Valle de México, Mexico City 14370, Mexico; (D.A.C.-F.); (S.C.L.-C.); (C.N.C.-C.)
| | - Elijah W. Stommel
- Department of Neurology, Geisel School of Medicine at Dartmouth, Hanover, NH 03755, USA;
| | - Ricardo Torres-Jardón
- Instituto de Ciencias de la Atmósfera y Cambio Climático, Universidad Nacional Autónoma de México, Mexico City 04510, Mexico;
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Functional connectivity in Parkinson's disease candidates for deep brain stimulation. NPJ Parkinsons Dis 2022; 8:4. [PMID: 35013326 PMCID: PMC8748462 DOI: 10.1038/s41531-021-00268-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2021] [Accepted: 12/10/2021] [Indexed: 11/29/2022] Open
Abstract
This study aimed to identify functional neuroimaging patterns anticipating the clinical indication for deep brain stimulation (DBS) in patients with Parkinson’s disease (PD). A cohort of prospectively recruited patients with PD underwent neurological evaluations and resting-state functional MRI (RS-fMRI) at baseline and annually for 4 years. Patients were divided into two groups: 19 patients eligible for DBS over the follow-up and 41 patients who did not meet the criteria to undergo DBS. Patients selected as candidates for DBS did not undergo surgery at this stage. Sixty age- and sex-matched healthy controls performed baseline evaluations. Graph analysis and connectomics assessed global and local topological network properties and regional functional connectivity at baseline and at each time point. At baseline, network analysis showed a higher mean nodal strength, local efficiency, and clustering coefficient of the occipital areas in candidates for DBS over time relative to controls and patients not eligible for DBS. The occipital hyperconnectivity pattern was confirmed by regional analysis. At baseline, a decreased functional connectivity between basal ganglia and sensorimotor/frontal networks was found in candidates for DBS compared to patients not eligible for surgery. In the longitudinal analysis, patient candidate for DBS showed a progressively decreased topological brain organization and functional connectivity, mainly in the posterior brain networks, and a progressively increased connectivity of basal ganglia network compared to non-candidates for DBS. RS-fMRI may support the clinical indication to DBS and could be useful in predicting which patients would be eligible for DBS in the earlier stages of PD.
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Patriat R, Pisharady PK, Amundsen-Huffmaster S, Linn-Evans M, Howell M, Chung JW, Petrucci MN, Videnovic A, Holker E, De Kam J, Tuite P, Lenglet C, Harel N, MacKinnon CD. OUP accepted manuscript. Brain Commun 2022; 4:fcac027. [PMID: 35310831 PMCID: PMC8924652 DOI: 10.1093/braincomms/fcac027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2021] [Revised: 12/06/2021] [Accepted: 02/07/2022] [Indexed: 11/28/2022] Open
Abstract
People with Parkinson’s disease who have elevated muscle activity during rapid eye movement sleep (REM sleep without atonia) typically have a worse motor and cognitive impairment compared with those with normal muscle atonia during rapid eye movement sleep. This study used tract-based spatial statistics to compare diffusion MRI measures of fractional anisotropy, radial, mean and axial diffusivity (measures of axonal microstructure based on the directionality of water diffusion) in white matter tracts between people with Parkinson’s disease with and without rapid eye movement sleep without atonia and controls and their relationship to measures of motor and cognitive function. Thirty-eight individuals with mild-to-moderate Parkinson’s disease and 21 matched control subjects underwent ultra-high field MRI (7 T), quantitative motor assessments of gait and bradykinesia and neuropsychological testing. The Parkinson’s disease cohort was separated post hoc into those with and without elevated chin or leg muscle activity during rapid eye movement sleep based on polysomnography findings. Fractional anisotropy was significantly higher, and diffusivity significantly lower, in regions of the corpus callosum, projection and association white matter pathways in the Parkinson’s group with normal rapid eye movement sleep muscle tone compared with controls, and in a subset of pathways relative to the Parkinson’s disease group with rapid eye movement sleep without atonia. The Parkinson’s disease group with elevated rapid eye movement sleep muscle tone showed significant impairments in the gait and upper arm speed compared with controls and significantly worse scores in specific cognitive domains (executive function, visuospatial memory) compared with the Parkinson’s disease group with normal rapid eye movement sleep muscle tone. Regression analyses showed that gait speed and step length in the Parkinson’s disease cohort were predicted by measures of fractional anisotropy of the anterior corona radiata, whereas elbow flexion velocity was predicted by fractional anisotropy of the superior corona radiata. Visuospatial memory task performance was predicted by the radial diffusivity of the posterior corona radiata. These findings show that people with mild-to-moderate severity of Parkinson’s disease who have normal muscle tone during rapid eye movement sleep demonstrate compensatory-like adaptations in axonal microstructure that are associated with preserved motor and cognitive function, but these adaptations are reduced or absent in those with increased rapid eye movement sleep motor tone.
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Affiliation(s)
- Rémi Patriat
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA
- Correspondence to: Rémi Patriat, PhD 2021 6th Street S.E. Minneapolis MN 55455 USA E-mail:
| | - Pramod K. Pisharady
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA
| | | | - Maria Linn-Evans
- Department of Neurology, University of Minnesota, Minneapolis, MN, USA
- Department of Neuroscience, University of Minnesota, Minneapolis, MN, USA
| | - Michael Howell
- Department of Neurology, University of Minnesota, Minneapolis, MN, USA
| | - Jae Woo Chung
- Department of Neurology, University of Minnesota, Minneapolis, MN, USA
| | | | | | - Erin Holker
- Department of Rehabilitation Medicine, University of Minnesota, Minneapolis, MN, USA
| | - Joshua De Kam
- Department of Neurology, University of Minnesota, Minneapolis, MN, USA
| | - Paul Tuite
- Department of Neurology, University of Minnesota, Minneapolis, MN, USA
| | - Christophe Lenglet
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA
| | - Noam Harel
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA
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Martín-Bastida A, Delgado-Alvarado M, Navalpotro-Gómez I, Rodríguez-Oroz MC. Imaging Cognitive Impairment and Impulse Control Disorders in Parkinson's Disease. Front Neurol 2021; 12:733570. [PMID: 34803882 PMCID: PMC8602579 DOI: 10.3389/fneur.2021.733570] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Accepted: 09/28/2021] [Indexed: 12/04/2022] Open
Abstract
Dementia and mild forms of cognitive impairment as well as neuropsychiatric symptoms (i. e., impulse control disorders) are frequent and disabling non-motor symptoms of Parkinson's disease (PD). The identification of changes in neuroimaging studies for the early diagnosis and monitoring of the cognitive and neuropsychiatric symptoms associated with Parkinson's disease, as well as their pathophysiological understanding, are critical for the development of an optimal therapeutic approach. In the current literature review, we present an update on the latest structural and functional neuroimaging findings, including high magnetic field resonance and radionuclide imaging, assessing cognitive dysfunction and impulse control disorders in PD.
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Affiliation(s)
- Antonio Martín-Bastida
- Department of Neurology, Clínica Universidad de Navarra, Pamplona, Spain.,CIMA, Center of Applied Medical Research, Universidad de Navarra, Neurosciences Program, Pamplona, Spain
| | | | - Irene Navalpotro-Gómez
- Cognitive Impairment and Movement Disorders Unit, Neurology Department, Hospital del Mar, Barcelona, Spain.,Clinical and Biological Research in Neurodegenerative Diseases, Integrative Pharmacology and Systems Neurosciences Research Group, Neurosciences Research Program, Hospital del Mar Research Institute (IMIM), Barcelona, Spain.,Barcelonabeta Brain Research Center, Pasqual Maragall Foundation, Barcelona, Spain
| | - María Cruz Rodríguez-Oroz
- Department of Neurology, Clínica Universidad de Navarra, Pamplona, Spain.,CIMA, Center of Applied Medical Research, Universidad de Navarra, Neurosciences Program, Pamplona, Spain.,IdiSNA, Instituto de Investigación Sanitaria de Navarra, Pamplona, Spain
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45
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Scamarcia PG, Agosta F, Spinelli EG, Basaia S, Stojković T, Stankovic I, Sarasso E, Canu E, Markovic V, Petrović I, Stefanova E, Pagani E, Kostic VS, Filippi M. Longitudinal White Matter Damage Evolution in Parkinson's Disease. Mov Disord 2021; 37:315-324. [PMID: 34806799 DOI: 10.1002/mds.28864] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2021] [Revised: 10/27/2021] [Accepted: 11/02/2021] [Indexed: 11/07/2022] Open
Abstract
BACKGROUND White matter hyperintensities (WMHs) have a role in cognitive impairment in normal brain aging, while the effect on Parkinson's disease (PD) progression is still controversial. OBJECTIVE To investigate the longitudinal evolution of micro- and macrostructural damage of cerebral white matter (WM) and its relationship with the clinical picture in PD. METHODS A total of 154 PD patients underwent clinical, cognitive, and magnetic resonance imaging (MRI) assessment once a year for up to 4 years. Sixty healthy controls underwent the same protocol at baseline. WMHs were identified and total WMH volume was measured. WMHs were also used as exclusion masks to define normal-appearing white matter (NAWM). Using tract-based spatial statistics, diffusion tensor (DT) MRI metrics of whole-brain WM and NAWM were obtained. Linear mixed-effects models defined the longitudinal evolution and association between variables. WM alterations were tested as risk factors of disease progression using linear regression and Cox proportional hazards models. RESULTS At baseline, PD patients showed alterations of all DT MRI measures compared to controls. Longitudinally, DT MRI measures did not vary significantly and no association with clinical variables was found. WMH volume changed over time and was associated with impairment in global cognition, executive functions, and language. Baseline WMH volume was a moderate risk factor for progression to mild cognitive impairment. CONCLUSIONS Our study suggests an association between WMHs and cognitive deterioration in PD, whereas WM microstructural damage is a negligible contributor to clinical deterioration. WMHs assessed by MRI can provide an important tool for monitoring the development of cognitive impairment in PD patients. © 2021 International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Pietro Giuseppe Scamarcia
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Federica Agosta
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Vita-Salute San Raffaele University, Milan, Italy
| | - Edoardo Gioele Spinelli
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Vita-Salute San Raffaele University, Milan, Italy
| | - Silvia Basaia
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Tanja Stojković
- Clinic of Neurology, School of Medicine, University of Belgrade, Belgrade, Serbia
| | - Iva Stankovic
- Clinic of Neurology, School of Medicine, University of Belgrade, Belgrade, Serbia
| | - Elisabetta Sarasso
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Elisa Canu
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Vladana Markovic
- Clinic of Neurology, School of Medicine, University of Belgrade, Belgrade, Serbia
| | - Igor Petrović
- Clinic of Neurology, School of Medicine, University of Belgrade, Belgrade, Serbia
| | - Elka Stefanova
- Clinic of Neurology, School of Medicine, University of Belgrade, Belgrade, Serbia
| | - Elisabetta Pagani
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Vladimir S Kostic
- Clinic of Neurology, School of Medicine, University of Belgrade, Belgrade, Serbia
| | - Massimo Filippi
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Vita-Salute San Raffaele University, Milan, Italy.,Neurorehabilitation Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Neurophysiology Service, IRCCS San Raffaele Scientific Institute, Milan, Italy
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46
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Tremblay C, Rahayel S, Vo A, Morys F, Shafiei G, Abbasi N, Markello RD, Gan-Or Z, Misic B, Dagher A. Brain atrophy progression in Parkinson's disease is shaped by connectivity and local vulnerability. Brain Commun 2021; 3:fcab269. [PMID: 34859216 PMCID: PMC8633425 DOI: 10.1093/braincomms/fcab269] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2021] [Revised: 08/18/2021] [Accepted: 10/18/2021] [Indexed: 12/12/2022] Open
Abstract
Brain atrophy has been reported in the early stages of Parkinson's disease, but there have been few longitudinal studies. How intrinsic properties of the brain, such as anatomical connectivity, local cell-type distribution and gene expression combine to determine the pattern of disease progression also remains unknown. One hypothesis proposes that the disease stems from prion-like propagation of misfolded alpha-synuclein via the connectome that might cause varying degrees of tissue damage based on local properties. Here, we used MRI data from the Parkinson Progression Markers Initiative to map the progression of brain atrophy over 1, 2 and 4 years compared with baseline. We derived atrophy maps for four time points using deformation-based morphometry applied to T1-weighted MRI from 120 de novo Parkinson's disease patients, 74 of whom had imaging at all four time points (50 Men: 24 Women) and 157 healthy control participants (115 Men: 42 Women). In order to determine factors that may influence neurodegeneration, we related atrophy progression to brain structural and functional connectivity, cell-type expression and gene ontology enrichment analyses. After regressing out the expected age and sex effects associated with normal ageing, we found that atrophy significantly progressed over 2 and 4 years in the caudate, nucleus accumbens, hippocampus and posterior cortical regions. This progression was shaped by both structural and functional brain connectivity. Also, the progression of atrophy was more pronounced in regions with a higher expression of genes related to synapses and was inversely related to the prevalence of oligodendrocytes and endothelial cells. In sum, we demonstrate that the progression of atrophy in Parkinson's disease is in line with the prion-like propagation hypothesis of alpha-synuclein and provide evidence that synapses may be especially vulnerable to synucleinopathy. In addition to identifying vulnerable brain regions, this study reveals different factors that may be implicated in the neurotoxic mechanisms leading to progression in Parkinson's disease. All brain maps generated here are available on request.
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Affiliation(s)
- Christina Tremblay
- Montreal Neurological Institute, McGill University, Montreal, QC H3A 2B4, Canada
| | - Shady Rahayel
- Montreal Neurological Institute, McGill University, Montreal, QC H3A 2B4, Canada
- Centre for Advanced Research in Sleep Medicine, Hôpital du Sacré-Cœur de Montréal, Montreal, QC H4J 1C5, Canada
| | - Andrew Vo
- Montreal Neurological Institute, McGill University, Montreal, QC H3A 2B4, Canada
| | - Filip Morys
- Montreal Neurological Institute, McGill University, Montreal, QC H3A 2B4, Canada
| | - Golia Shafiei
- Montreal Neurological Institute, McGill University, Montreal, QC H3A 2B4, Canada
| | - Nooshin Abbasi
- Montreal Neurological Institute, McGill University, Montreal, QC H3A 2B4, Canada
| | - Ross D Markello
- Montreal Neurological Institute, McGill University, Montreal, QC H3A 2B4, Canada
| | - Ziv Gan-Or
- Montreal Neurological Institute, McGill University, Montreal, QC H3A 2B4, Canada
- Department of Human Genetics, McGill University, Montreal, QC H3A 0C7, Canada
| | - Bratislav Misic
- Montreal Neurological Institute, McGill University, Montreal, QC H3A 2B4, Canada
| | - Alain Dagher
- Montreal Neurological Institute, McGill University, Montreal, QC H3A 2B4, Canada
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47
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Seitz-Holland J, Lyons M, Kushan L, Lin A, Villalon-Reina JE, Cho KIK, Zhang F, Billah T, Bouix S, Kubicki M, Bearden CE, Pasternak O. Opposing white matter microstructure abnormalities in 22q11.2 deletion and duplication carriers. Transl Psychiatry 2021; 11:580. [PMID: 34759270 PMCID: PMC8581007 DOI: 10.1038/s41398-021-01703-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/01/2020] [Revised: 09/30/2021] [Accepted: 10/15/2021] [Indexed: 12/20/2022] Open
Abstract
Deletions and duplications at the 22q11.2 locus are associated with significant neurodevelopmental and psychiatric morbidity. Previous diffusion-weighted magnetic resonance imaging (MRI) studies in 22q11.2 deletion carriers (22q-del) found nonspecific white matter (WM) abnormalities, characterized by higher fractional anisotropy. Here, utilizing novel imaging and processing methods that allow separation of signal contribution from different tissue properties, we investigate whether higher anisotropy is driven by (1) extracellular changes, (2) selective degeneration of secondary fibers, or (3) volumetric differences. We further, for the first time, investigate WM microstructure in 22q11.2 duplication carriers (22q-dup). Multi-shell diffusion-weighted images were acquired from 26 22q-del, 19 22q-dup, and 18 healthy individuals (HC). Images were fitted with the free-water model to estimate anisotropy following extracellular free-water elimination and with the novel BedpostX model to estimate fractional volumes of primary and secondary fiber populations. Outcome measures were compared between groups, with and without correction for WM and cerebrospinal fluid (CSF) volumes. In 22q-del, anisotropy following free-water elimination remained significantly higher compared with controls. BedpostX did not identify selective secondary fiber degeneration. Higher anisotropy diminished when correcting for the higher CSF and lower WM volumes. In contrast, 22q-dup had lower anisotropy and greater extracellular space than HC, not influenced by macrostructural volumes. Our findings demonstrate opposing effects of reciprocal 22q11.2 copy-number variation on WM, which may arise from distinct pathologies. In 22q-del, microstructural abnormalities may be secondary to enlarged CSF space and more densely packed WM. In 22q-dup, we see evidence for demyelination similar to what is commonly observed in neuropsychiatric disorders.
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Affiliation(s)
- Johanna Seitz-Holland
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, 02115, MA, USA.
| | - Monica Lyons
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, 02115, MA, USA
| | - Leila Kushan
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California at Los Angeles, Los Angeles, 90095, CA, USA
| | - Amy Lin
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California at Los Angeles, Los Angeles, 90095, CA, USA
| | - Julio E Villalon-Reina
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California at Los Angeles, Los Angeles, 90095, CA, USA
| | - Kang Ik Kevin Cho
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, 02115, MA, USA
| | - Fan Zhang
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, 02115, MA, USA
| | - Tashrif Billah
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, 02115, MA, USA
| | - Sylvain Bouix
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, 02115, MA, USA
| | - Marek Kubicki
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, 02115, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, 02114, MA, USA
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, 02115, MA, USA
| | - Carrie E Bearden
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California at Los Angeles, Los Angeles, 90095, CA, USA
- Department of Psychology, University of California at Los Angeles, Los Angeles, 90095, CA, USA
| | - Ofer Pasternak
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, 02115, MA, USA
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, 02115, MA, USA
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48
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Sarasso E, Gardoni A, Tettamanti A, Agosta F, Filippi M, Corbetta D. Virtual reality balance training to improve balance and mobility in Parkinson's disease: a systematic review and meta-analysis. J Neurol 2021; 269:1873-1888. [PMID: 34713324 DOI: 10.1007/s00415-021-10857-3] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2021] [Revised: 10/13/2021] [Accepted: 10/15/2021] [Indexed: 12/29/2022]
Abstract
BACKGROUND In the last few years, virtual reality (VR) has been increasingly used to strengthen the effect of balance training (BT) in Parkinson's disease (PD). OBJECTIVE We performed a systematic review and meta-analysis of randomized controlled trials (RCTs) to compare the effects of VR-BT relative to BT alone for improving balance and mobility PD subjects with balance/mobility difficulties. METHODS Four electronic databases were searched: two reviewers independently selected RCTs, extracted data, and applied the Cochrane risk-of-bias tool for randomized trials (version 2) and the GRADE framework for assessing the certainty of evidence. Primary outcomes were balanced (Berg Balance Scale-BBS), mobility (Timed Up and Go-TUG) and walking speed. Secondary outcomes were falls, walking distance and stability, spatial gait parameters, balance confidence, sensory integration ability, motor signs and quality of life. RESULTS We included 22 studies (901 patients). Meta-analysis on fourteen trials (430 patients) showed a mean difference (MD) of 2.09 points (95% confidence interval [CI] 0.86-3.33) on BBS favoring VR-BT compared to BT (low certainty evidence). Subgroup analyses showed higher balance improvement in most affected subjects (moderate certainty evidence) and using VR rehabilitation-specific systems vs. VR non-specific systems. Eight trials (236 patients) assessing mobility showed a MD of 1.55 s (95% CI 0.04-3.06) on TUG favoring VR-BT (very low certainty evidence). No differences were observed in walking speed. Estimated effects were not maintained for any outcome at follow-up. CONCLUSIONS This review suggests that VR-BT is more effective than BT to improve balance in PD subjects immediately after training, particularly in individuals with higher postural instability at baseline.
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Affiliation(s)
- Elisabetta Sarasso
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Via Olgettina, 60, 20132, Milan, Italy.,Department of Rehabilitation and Functional Recovery, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Vita-Salute San Raffaele University, Milan, Italy
| | - Andrea Gardoni
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Via Olgettina, 60, 20132, Milan, Italy.,Department of Rehabilitation and Functional Recovery, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Andrea Tettamanti
- Department of Rehabilitation and Functional Recovery, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Vita-Salute San Raffaele University, Milan, Italy
| | - Federica Agosta
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Via Olgettina, 60, 20132, Milan, Italy.,Neurology Unit, IRCCS San Raffaele Scientific Institute, Via Olgettina, 60, 20132, Milan, Italy.,Vita-Salute San Raffaele University, Milan, Italy
| | - Massimo Filippi
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Via Olgettina, 60, 20132, Milan, Italy. .,Neurology Unit, IRCCS San Raffaele Scientific Institute, Via Olgettina, 60, 20132, Milan, Italy. .,Neurorehabilitation Unit, IRCCS San Raffaele Scientific Institute, Via Olgettina, 60, 20132, Milan, Italy. .,Neurophysiology Service, IRCCS San Raffaele Scientific Institute, Via Olgettina, 60, 20132, Milan, Italy. .,Vita-Salute San Raffaele University, Milan, Italy.
| | - Davide Corbetta
- Department of Rehabilitation and Functional Recovery, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Vita-Salute San Raffaele University, Milan, Italy
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Sarasso E, Agosta F, Piramide N, Gardoni A, Canu E, Leocadi M, Castelnovo V, Basaia S, Tettamanti A, Volontè MA, Filippi M. Action Observation and Motor Imagery Improve Dual Task in Parkinson's Disease: A Clinical/fMRI Study. Mov Disord 2021; 36:2569-2582. [PMID: 34286884 DOI: 10.1002/mds.28717] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2021] [Revised: 06/25/2021] [Accepted: 06/28/2021] [Indexed: 01/08/2023] Open
Abstract
BACKGROUND Action observation training and motor imagery may improve motor learning in Parkinson's disease (PD). OBJECTIVES The objectives of this study were to assess mobility and balance (performing motor and dual tasks) and brain functional reorganization following 6 weeks of action observation training and motor imagery associated with dual-task gait/balance exercises in PD patients with postural instability and gait disorders relative to dual-task training alone. METHODS Twenty-five PD-postural instability and gait disorder patients were randomized into 2 groups: the DUAL-TASK+AOT-MI group performed a 6-week gait/balance training consisting of action observation training-motor imagery combined with practicing the observed-imagined exercises; the DUAL-TASK group performed the same exercises combined with watching landscape videos. Exercises were increasingly difficult to include the dual task. At baseline and at 6 weeks, patients underwent: mobility, gait, and balance evaluations (also repeated 2 months after training), cognitive assessment, and functional MRI, including motor and dual tasks. RESULTS Dual-task gait/balance training enhanced mobility, during both single- and dual-task conditions, and executive functions in PD-postural instability and gait disorders, with a long-lasting effect at 14 weeks. When exercises were preceded by action observation training-motor imagery, PD-postural instability and gait disorders showed greater improvement of balance and gait velocity both with and without the dual task, particularly during the turning phase. After training, the DUAL-TASK+AOT-MI group showed reduced recruitment of frontal areas and increased activity of cerebellum during functional-MRI motor and dual task, correlating with balance/turning velocity and executive improvements, respectively. The DUAL-TASK group showed reduced activity of supplementary motor area and increased recruitment of temporo-parietal areas during the dual task and decreased cerebellar activity during the motor task correlating with faster turning velocity. Functional MRI results were not corrected for multiple comparisons and should be interpreted carefully. CONCLUSIONS Adding action observation training-motor imagery to dual-task gait/balance training promotes specific functional reorganization of brain areas involved in motor control and executive-attentive abilities and more long-lasting effects on dual-task mobility and balance in PD-postural instability and gait disorders. © 2021 International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Elisabetta Sarasso
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Department of Rehabilitation and Functional Recovery, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Federica Agosta
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Vita-Salute San Raffaele University, Milan, Italy
| | - Noemi Piramide
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Vita-Salute San Raffaele University, Milan, Italy
| | - Andrea Gardoni
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Department of Rehabilitation and Functional Recovery, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Elisa Canu
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Michela Leocadi
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Vita-Salute San Raffaele University, Milan, Italy
| | - Veronica Castelnovo
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Vita-Salute San Raffaele University, Milan, Italy
| | - Silvia Basaia
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Andrea Tettamanti
- Department of Rehabilitation and Functional Recovery, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | | | - Massimo Filippi
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Vita-Salute San Raffaele University, Milan, Italy.,Neurorehabilitation Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Neurophysiology Service, IRCCS San Raffaele Scientific Institute, Milan, Italy
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Xiao Y, Peters TM, Khan AR. Characterizing white matter alterations subject to clinical laterality in drug-naïve de novo Parkinson's disease. Hum Brain Mapp 2021; 42:4465-4477. [PMID: 34106502 PMCID: PMC8410564 DOI: 10.1002/hbm.25558] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2021] [Revised: 05/18/2021] [Accepted: 06/01/2021] [Indexed: 01/18/2023] Open
Abstract
Parkinson's disease (PD) is a progressive neurodegenerative disorder that is characterized by a range of motor and nonmotor symptoms, often with the motor dysfunction initiated unilaterally. Knowledge regarding disease‐related alterations in white matter pathways can effectively help improve the understanding of the disease and propose targeted treatment strategies. Microstructural imaging techniques, including diffusion tensor imaging (DTI), allows inspection of white matter integrity to study the pathogenesis of various neurological conditions. Previous voxel‐based analyses with DTI measures, such as fractional anisotropy and mean diffusivity have uncovered changes in brain regions that are associated with PD, but the conclusions were inconsistent, partially due to small patient cohorts and the lack of consideration for clinical laterality onset, particularly in early PD. Fixel‐based analysis (FBA) is a recent framework that offers tract‐specific insights regarding white matter health, but very few FBA studies on PD exist. We present a study that reveals strengthened and weakened white matter integrity that is subject to symptom laterality in a large drug‐naïve de novo PD cohort using complementary DTI and FBA measures. The findings suggest that the disease gives rise to tissue degeneration and potential re‐organization in the early stage.
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Affiliation(s)
- Yiming Xiao
- Department of Computer Science and Software Engineering, Concordia University, Montreal, Canada.,PERFORM Centre, Concordia University, Montreal, Canada
| | - Terry M Peters
- Imaging Research Laboratories, Robarts Research Institute, Western University, London, Canada.,Department of Medical Biophysics, Schulich School of Medicine and Dentistry, Western University, London, Canada.,School of Biomedical Engineering, Western University, London, Canada
| | - Ali R Khan
- Imaging Research Laboratories, Robarts Research Institute, Western University, London, Canada.,Department of Medical Biophysics, Schulich School of Medicine and Dentistry, Western University, London, Canada.,School of Biomedical Engineering, Western University, London, Canada.,The Brain and Mind Institute, Western University, London, Canada
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