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Lee H, Kim HF, Hikosaka O. Implication of regional selectivity of dopamine deficits in impaired suppressing of involuntary movements in Parkinson's disease. Neurosci Biobehav Rev 2024; 162:105719. [PMID: 38759470 PMCID: PMC11167649 DOI: 10.1016/j.neubiorev.2024.105719] [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: 12/06/2023] [Revised: 04/26/2024] [Accepted: 05/09/2024] [Indexed: 05/19/2024]
Abstract
To improve the initiation and speed of intended action, one of the crucial mechanisms is suppressing unwanted movements that interfere with goal-directed behavior, which is observed relatively aberrant in Parkinson's disease patients. Recent research has highlighted that dopamine deficits in Parkinson's disease predominantly occur in the caudal lateral part of the substantia nigra pars compacta (SNc) in human patients. We previously found two parallel circuits within the basal ganglia, primarily divided into circuits mediated by the rostral medial part and caudal lateral part of the SNc dopamine neurons. We have further discovered that the indirect pathway in caudal basal ganglia circuits, facilitated by the caudal lateral part of the SNc dopamine neurons, plays a critical role in suppressing unnecessary involuntary movements when animals perform voluntary goal-directed actions. We thus explored recent research in humans and non-human primates focusing on the distinct functions and networks of the caudal lateral part of the SNc dopamine neurons to elucidate the mechanisms involved in the impairment of suppressing involuntary movements in Parkinson's disease patients.
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Affiliation(s)
- Hyunchan Lee
- Laboratory of Sensorimotor Research, National Eye Institute, National Institutes of Health, Bethesda, MD 20892-4435, USA.
| | - Hyoung F Kim
- School of Biological Sciences, College of Natural Sciences, Seoul National University (SNU), Seoul 08826, Republic of Korea
| | - Okihide Hikosaka
- Laboratory of Sensorimotor Research, National Eye Institute, National Institutes of Health, Bethesda, MD 20892-4435, USA
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Yamada K. Imaging Studies Play a Pivotal Role in Elucidating the Pathophysiology of Parkinson Disease. Radiology 2024; 311:e241285. [PMID: 38916505 DOI: 10.1148/radiol.241285] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/26/2024]
Affiliation(s)
- Kei Yamada
- From the Department of Radiology, Kyoto Prefectural University of Medicine, 465 Kajii-cho Kawaramachi-Hirokoji, Kamigyo-ku, Kyoto, Japan 602-8566
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Monchi O, Pinilla-Monsalve GD, Almgren H, Ghahremani M, Kibreab M, Maarouf N, Kathol I, Boré A, Rheault F, Descoteaux M, Ismail Z. White Matter Microstructural Underpinnings of Mild Behavioral Impairment in Parkinson's Disease. Mov Disord 2024; 39:1026-1036. [PMID: 38661496 DOI: 10.1002/mds.29804] [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: 11/13/2023] [Revised: 02/13/2024] [Accepted: 03/18/2024] [Indexed: 04/26/2024] Open
Abstract
BACKGROUND Patients with Parkinson's disease (PD) experience changes in behavior, personality, and cognition that can manifest even in the initial stages of the disease. Previous studies have suggested that mild behavioral impairment (MBI) should be considered an early marker of cognitive decline. However, the precise neurostructural underpinnings of MBI in early- to mid-stage PD remain poorly understood. OBJECTIVE The aim was to explore the changes in white matter microstructure linked to MBI and mild cognitive impairment (MCI) in early- to mid-stage PD using diffusion magnetic resonance imaging (dMRI). METHODS A total of 91 PD patients and 36 healthy participants were recruited and underwent anatomical MRI and dMRI, a comprehensive neuropsychological battery, and the completion of the Mild Behavioral Impairment-Checklist. Metrics of white matter integrity included tissue fractional anisotropy (FAt) and radial diffusivity (RDt), free water (FW), and fixel-based apparent fiber density (AFD). RESULTS The connection between the left amygdala and the putamen was disrupted when comparing PD patients with MBI (PD-MBI) to PD-non-MBI, as evidenced by increased RDt (η2 = 0.09, P = 0.004) and both decreased AFD (η2 = 0.05, P = 0.048) and FAt (η2 = 0.12, P = 0.014). Compared to controls, PD patients with both MBI and MCI demonstrated increased FW for the connection between the left orbitofrontal gyrus (OrG) and the hippocampus (η2 = 0.22, P = 0.008), augmented RDt between the right OrG and the amygdala (η2 = 0.14, P = 0.008), and increased RDt (η2 = 0.25, P = 0.028) with decreased AFD (η2 = 0.10, P = 0.046) between the right OrG and the caudate nucleus. CONCLUSION MBI is associated with abnormal microstructure of connections involving the orbitofrontal cortex, putamen, and amygdala. To our knowledge, this is the first assessment of the white matter microstructure in PD-MBI using dMRI. © 2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Oury Monchi
- Centre de recherche de l'Institut universitaire de gériatrie de Montréal, Montreal, Quebec, Canada
- Département de radiologie, radio-oncologie et médicine nucléaire, Université de Montréal, Montreal, Quebec, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
- Department of Clinical Neurosciences, University of Calgary, Calgary, Alberta, Canada
| | - Gabriel D Pinilla-Monsalve
- Centre de recherche de l'Institut universitaire de gériatrie de Montréal, Montreal, Quebec, Canada
- Département de radiologie, radio-oncologie et médicine nucléaire, Université de Montréal, Montreal, Quebec, Canada
| | - Hannes Almgren
- Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
- Department of Clinical Neurosciences, University of Calgary, Calgary, Alberta, Canada
| | - Maryam Ghahremani
- Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
- Departments of Psychiatry and Community Health Sciences, University of Calgary, Calgary, Alberta, Canada
| | - Mekale Kibreab
- Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
- Department of Clinical Neurosciences, University of Calgary, Calgary, Alberta, Canada
| | - Nadia Maarouf
- Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
- Department of Clinical Neurosciences, University of Calgary, Calgary, Alberta, Canada
| | - Iris Kathol
- Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
- Department of Clinical Neurosciences, University of Calgary, Calgary, Alberta, Canada
| | - Arnaud Boré
- Département d'informatique, Université de Sherbrooke, Sherbrooke, Quebec, Canada
| | - François Rheault
- Département d'informatique, Université de Sherbrooke, Sherbrooke, Quebec, Canada
| | - Maxime Descoteaux
- Département d'informatique, Université de Sherbrooke, Sherbrooke, Quebec, Canada
| | - Zahinoor Ismail
- Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
- Departments of Psychiatry and Community Health Sciences, University of Calgary, Calgary, Alberta, Canada
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Mulroy E, Erro R, Bhatia KP, Hallett M. Refining the clinical diagnosis of Parkinson's disease. Parkinsonism Relat Disord 2024; 122:106041. [PMID: 38360507 PMCID: PMC11069446 DOI: 10.1016/j.parkreldis.2024.106041] [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: 02/06/2024] [Accepted: 02/09/2024] [Indexed: 02/17/2024]
Abstract
Our ability to define, understand, and classify Parkinson's disease (PD) has undergone significant changes since the disorder was first described in 1817. Clinical features and neuropathologic signatures can now be supplemented by in-vivo interrogation of genetic and biological substrates of disease, offering great opportunity for further refining the diagnosis of PD. In this mini-review, we discuss the historical perspectives which shaped our thinking surrounding the definition and diagnosis of PD. We highlight the clinical, genetic, pathologic and biologic diversity which underpins the condition, and proceed to discuss how recent developments in our ability to define biologic and pathologic substrates of disease might impact PD definition, diagnosis, individualised prognostication, and personalised clinical care. We argue that Parkinson's 'disease', as currently diagnosed in the clinic, is actually a syndrome. It is the outward manifestation of any array of potential dysfunctional biologic processes, neuropathological changes, and disease aetiologies, which culminate in common outward clinical features which we term PD; each person has their own unique disease, which we can now define with increasing precision. This is an exciting time in PD research and clinical care. Our ability to refine the clinical diagnosis of PD, incorporating in-vivo assessments of disease biology, neuropathology, and neurogenetics may well herald the era of biologically-based, precision medicine approaches PD management. With this however comes a number of challenges, including how to integrate these technologies into clinical practice in a way which is acceptable to patients, promotes meaningful changes to care, and minimises health economic impact.
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Affiliation(s)
- Eoin Mulroy
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, London, WC1N 3BG, UK
| | - Roberto Erro
- Department of Medicine, Surgery and Dentistry "Scuola Medica Salernitana", University of Salerno, Baronissi, (SA), Italy
| | - Kailash P Bhatia
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, London, WC1N 3BG, UK
| | - Mark Hallett
- Human Motor Control Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA.
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Hermann MG, Schröter N, Rau A, Reisert M, Jarc N, Rijntjes M, Hosp JA, Reinacher PC, Jost WH, Urbach H, Weiller C, Coenen VA, Sajonz BEA. The connection of motor improvement after deep brain stimulation in Parkinson's disease and microstructural integrity of the substantia nigra and subthalamic nucleus. Neuroimage Clin 2024; 42:103607. [PMID: 38643635 PMCID: PMC11046219 DOI: 10.1016/j.nicl.2024.103607] [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: 01/02/2024] [Revised: 04/15/2024] [Accepted: 04/15/2024] [Indexed: 04/23/2024]
Abstract
BACKGROUND Nigrostriatal microstructural integrity has been suggested as a biomarker for levodopa response in Parkinson's disease (PD), which is a strong predictor for motor response to deep brain stimulation (DBS) of the subthalamic nucleus (STN). This study aimed to explore the impact of microstructural integrity of the substantia nigra (SN), STN, and putamen on motor response to STN-DBS using diffusion microstructure imaging. METHODS Data was collected from 23 PD patients (mean age 63 ± 7, 6 females) who underwent STN-DBS, had preoperative 3 T diffusion magnetic resonance imaging including multishell diffusion-weighted MRI with b-values of 1000 and 2000 s/mm2 and records of motor improvement available. RESULTS The association between a poorer DBS-response and increased free interstitial fluid showed notable effect sizes (rho > |0.4|) in SN and STN, but not in putamen. However, this did not reach significance after Bonferroni correction and controlling for sex and age. CONCLUSION Microstructural integrity of SN and STN are potential biomarkers for the prediction of therapy efficacy following STN-DBS, but further studies are required to confirm these associations.
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Affiliation(s)
- Marco G Hermann
- Department of Stereotactic and Functional Neurosurgery, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Nils Schröter
- Department of Neurology and Clinical Neuroscience, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Alexander Rau
- Department of Neuroradiology, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany; Department of Diagnostic and Interventional Radiology, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Marco Reisert
- Department of Stereotactic and Functional Neurosurgery, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany; Medical Physics, Department of Radiology, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Germany
| | - Nadja Jarc
- Department of Stereotactic and Functional Neurosurgery, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Michel Rijntjes
- Department of Neurology and Clinical Neuroscience, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Jonas A Hosp
- Department of Neurology and Clinical Neuroscience, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Peter C Reinacher
- Department of Stereotactic and Functional Neurosurgery, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany; Fraunhofer Institute for Laser Technology (ILT), Aachen, Germany
| | | | - Horst Urbach
- Department of Neuroradiology, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Cornelius Weiller
- Department of Neurology and Clinical Neuroscience, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Volker A Coenen
- Department of Stereotactic and Functional Neurosurgery, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany; Center for Deep Brain Stimulation, University of Freiburg, Germany
| | - Bastian E A Sajonz
- Department of Stereotactic and Functional Neurosurgery, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.
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Zhang D, Zhou L, Lu C, Feng T, Liu J, Wu T. Free-Water Imaging of the Nucleus Basalis of Meynert in Patients With Idiopathic REM Sleep Behavior Disorder and Parkinson Disease. Neurology 2024; 102:e209220. [PMID: 38489578 DOI: 10.1212/wnl.0000000000209220] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Accepted: 12/23/2023] [Indexed: 03/17/2024] Open
Abstract
BACKGROUND AND OBJECTIVES Cognitive impairments are common in idiopathic REM sleep behavior disorder (iRBD), in which the cholinergic degeneration of nucleus basalis of Meynert (NBM) may play an important role. However, the progressive changes of NBM, the relationship between progressive NBM degeneration and progression of cognitive impairments, and whether degeneration of the NBM can predict cognitive decline in patients with iRBD remain unclear. This study aimed to investigate the cross-sectional and longitudinal microstructural alterations in the NBM of patients with iRBD using free-water imaging and whether free water in the NBM is related to cognitive, mood, and autonomic function. METHODS We compared the baseline free-water values in the NBM between 59 healthy controls (HCs), 57 patients with iRBD, 57 patients with Parkinson disease (PD) with normal cognition (PD-NC), and 64 patients with PD with cognitive impairment (PD-CI). Thirty patients with iRBD and 40 HCs had one longitudinal data. In patients with iRBD, we explored the associations between baseline and longitudinal changes of free-water values in the NBM and clinical characteristics and whether baseline free-water values in the NBM could predict cognitive decline. RESULTS IRBD, PD-NC, and PD-CI groups had significantly increased free-water values in the NBM compared with HCs, whereas PD-CI had higher free-water values compared with iRBD and PD-NC. In patients with iRBD, free-water values in the NBM were progressively elevated over follow-up and correlated with the progression of cognitive impairment and depression. Free-water values in the NBM could predict cognitive decline in the iRBD group. Furthermore, we found that patients with iRBD with cognitive impairment had higher relative change of free-water value in the NBM compared with patients with iRBD with normal cognition over follow-up. DISCUSSION This study proves that free-water values in the NBM are elevated cross-sectionally and longitudinally and are associated with the progression of cognitive impairment and depression in patients with iRBD. Moreover, the free-water value in the NBM can predict cognitive decline in patients with iRBD. Whether free-water imaging of the NBM has the potential to be a marker for monitoring progressive cognitive impairment and predicting the conversion to dementia in synucleinopathies needs further investigation.
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Affiliation(s)
- Dongling Zhang
- From the Center for Movement Disorders (D.Z., T.F., T.W.), Department of Neurology, Beijing Tiantan Hospital, Capital Medical University; China National Clinical Research Center for Neurological Diseases (D.Z., T.F., T.W.), Beijing; Department of Neurology and Institute of Neurology (L.Z., J.L.), Ruijin Hospital, Shanghai Jiao Tong University School of Medicine; and Center for Brain Imaging Science and Technology (C.L.), College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
| | - Liche Zhou
- From the Center for Movement Disorders (D.Z., T.F., T.W.), Department of Neurology, Beijing Tiantan Hospital, Capital Medical University; China National Clinical Research Center for Neurological Diseases (D.Z., T.F., T.W.), Beijing; Department of Neurology and Institute of Neurology (L.Z., J.L.), Ruijin Hospital, Shanghai Jiao Tong University School of Medicine; and Center for Brain Imaging Science and Technology (C.L.), College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
| | - Chenxi Lu
- From the Center for Movement Disorders (D.Z., T.F., T.W.), Department of Neurology, Beijing Tiantan Hospital, Capital Medical University; China National Clinical Research Center for Neurological Diseases (D.Z., T.F., T.W.), Beijing; Department of Neurology and Institute of Neurology (L.Z., J.L.), Ruijin Hospital, Shanghai Jiao Tong University School of Medicine; and Center for Brain Imaging Science and Technology (C.L.), College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
| | - Tao Feng
- From the Center for Movement Disorders (D.Z., T.F., T.W.), Department of Neurology, Beijing Tiantan Hospital, Capital Medical University; China National Clinical Research Center for Neurological Diseases (D.Z., T.F., T.W.), Beijing; Department of Neurology and Institute of Neurology (L.Z., J.L.), Ruijin Hospital, Shanghai Jiao Tong University School of Medicine; and Center for Brain Imaging Science and Technology (C.L.), College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
| | - Jun Liu
- From the Center for Movement Disorders (D.Z., T.F., T.W.), Department of Neurology, Beijing Tiantan Hospital, Capital Medical University; China National Clinical Research Center for Neurological Diseases (D.Z., T.F., T.W.), Beijing; Department of Neurology and Institute of Neurology (L.Z., J.L.), Ruijin Hospital, Shanghai Jiao Tong University School of Medicine; and Center for Brain Imaging Science and Technology (C.L.), College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
| | - Tao Wu
- From the Center for Movement Disorders (D.Z., T.F., T.W.), Department of Neurology, Beijing Tiantan Hospital, Capital Medical University; China National Clinical Research Center for Neurological Diseases (D.Z., T.F., T.W.), Beijing; Department of Neurology and Institute of Neurology (L.Z., J.L.), Ruijin Hospital, Shanghai Jiao Tong University School of Medicine; and Center for Brain Imaging Science and Technology (C.L.), College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
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Yamashiro K, Takabayashi K, Kamagata K, Nishimoto Y, Togashi Y, Yamauchi Y, Ogaki K, Li Y, Hatano T, Motoi Y, Suzuki M, Miyakawa K, Ishikawa D, Aoki S, Urabe T, Hattori N. Free water in gray matter linked to gut microbiota changes with decreased butyrate producers in Alzheimer's disease and mild cognitive impairment. Neurobiol Dis 2024; 193:106464. [PMID: 38452948 DOI: 10.1016/j.nbd.2024.106464] [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: 01/05/2024] [Revised: 02/28/2024] [Accepted: 03/04/2024] [Indexed: 03/09/2024] Open
Abstract
Neuroinflammation contributes to the pathology and progression of Alzheimer's disease (AD), and it can be observed even with mild cognitive impairment (MCI), a prodromal phase of AD. Free water (FW) imaging estimates the extracellular water content and has been used to study neuroinflammation across several neurological diseases including AD. Recently, the role of gut microbiota has been implicated in the pathogenesis of AD. The relationship between FW imaging and gut microbiota was examined in patients with AD and MCI. Fifty-six participants underwent neuropsychological assessments, FW imaging, and gut microbiota analysis targeting the bacterial 16S rRNA gene. They were categorized into the cognitively normal control (NC) (n = 19), MCI (n = 19), and AD (n = 18) groups according to the neuropsychological assessments. The correlations of FW values, neuropsychological assessment scores, and the relative abundance of gut microbiota were analyzed. FW was higher in several white matter tracts and in gray matter regions, predominantly the frontal, temporal, limbic and paralimbic regions in the AD/MCI group than in the NC group. In the AD/MCI group, higher FW values in the temporal (superior temporal and temporal pole), limbic and paralimbic (insula, hippocampus and amygdala) regions were the most associated with worse neuropsychological assessment scores. In the AD/MCI group, FW values in these regions were negatively correlated with the relative abundances of butyrate-producing genera Anaerostipes, Lachnospiraceae UCG-004, and [Ruminococcus] gnavus group, which showed a significant decreasing trend in the order of the NC, MCI, and AD groups. The present study showed that increased FW in the gray matter regions related to cognitive impairment was associated with low abundances of butyrate producers in the AD/MCI group. These findings suggest an association between neuroinflammation and decreased levels of the short-chain fatty acid butyrate that is one of the major gut microbial metabolites having a potentially beneficial role in brain homeostasis.
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Affiliation(s)
- Kazuo Yamashiro
- Department of Neurology, Juntendo University School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo 113-8421, Japan; Department of Neurology, Juntendo University Urayasu Hospital, 2-1-1 Tomioka, Urayasu, Chiba 279-0021, Japan.
| | - Kaito Takabayashi
- Department of Radiology, Juntendo University School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo 113-8421, Japan
| | - Koji Kamagata
- Department of Radiology, Juntendo University School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo 113-8421, Japan
| | - Yuichiro Nishimoto
- Metagen Inc., 246-2 Mizukami, Kakuganji, Tsuruoka, Yamagata 997-0052, Japan
| | - Yuka Togashi
- Metagen Inc., 246-2 Mizukami, Kakuganji, Tsuruoka, Yamagata 997-0052, Japan
| | - Yohsuke Yamauchi
- Metagen Inc., 246-2 Mizukami, Kakuganji, Tsuruoka, Yamagata 997-0052, Japan
| | - Kotaro Ogaki
- Department of Neurology, Juntendo University Urayasu Hospital, 2-1-1 Tomioka, Urayasu, Chiba 279-0021, Japan
| | - Yuanzhe Li
- Department of Neurology, Juntendo University School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo 113-8421, Japan
| | - Taku Hatano
- Department of Neurology, Juntendo University School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo 113-8421, Japan
| | - Yumiko Motoi
- Department of Neurology, Juntendo University School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo 113-8421, Japan
| | - Michimasa Suzuki
- Department of Radiology, Juntendo University Urayasu Hospital, 2-1-1 Tomioka, Urayasu, Chiba 279-0021, Japan
| | - Koichi Miyakawa
- Department of Psychiatry, Juntendo University Urayasu Hospital, 2-1-1 Tomioka, Urayasu, Chiba 279-0021, Japan
| | - Dai Ishikawa
- Metagen Inc., 246-2 Mizukami, Kakuganji, Tsuruoka, Yamagata 997-0052, Japan; Department of Gastroenterology, Juntendo University School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo 113-8421, Japan
| | - Shigeki Aoki
- Department of Radiology, Juntendo University School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo 113-8421, Japan
| | - Takao Urabe
- Department of Neurology, Juntendo University Urayasu Hospital, 2-1-1 Tomioka, Urayasu, Chiba 279-0021, Japan
| | - Nobutaka Hattori
- Department of Neurology, Juntendo University School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo 113-8421, Japan; Neurodegenerative Disorders Collaborative Laboratory, RIKEN Center for Brain Science, 2-1 Hirosawa Wako, Saitama 351-0198, Japan
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DeSimone JC, Wang W, Loewenstein DA, Duara R, Smith GE, McFarland KN, Armstrong MJ, Weber DM, Barker W, Coombes SA, Vaillancourt DE. Diffusion MRI relates to plasma Aβ42/40 in PET negative participants without dementia. Alzheimers Dement 2024; 20:2830-2842. [PMID: 38441274 PMCID: PMC11032550 DOI: 10.1002/alz.13693] [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: 09/14/2023] [Revised: 12/19/2023] [Accepted: 12/21/2023] [Indexed: 03/10/2024]
Abstract
INTRODUCTION Magnetic resonance imaging (MRI) biomarkers are needed for indexing early biological stages of Alzheimer's disease (AD), such as plasma amyloid-β (Aβ42/40) positivity in Aβ positron emission tomography (PET) negative individuals. METHODS Diffusion free-water (FW) MRI was acquired in individuals with normal cognition (NC) and mild cognitive impairment (MCI) with Aβ plasma-/PET- (NC = 22, MCI = 60), plasma+/PET- (NC = 5, MCI = 20), and plasma+/PET+ (AD dementia = 21) biomarker status. Gray and white matter FW and fractional anisotropy (FAt) were compared cross-sectionally and the relationships between imaging, plasma and PET biomarkers were assessed. RESULTS Plasma+/PET- demonstrated increased FW (24 regions) and decreased FAt (66 regions) compared to plasma-/PET-. FW (16 regions) and FAt (51 regions) were increased in plasma+/PET+ compared to plasma+/PET-. Composite brain FW correlated with plasma Aβ42/40 and p-tau181. DISCUSSION FW imaging changes distinguish plasma Aβ42/40 positive and negative groups, independent of group differences in cognitive status, Aβ PET status, and other plasma biomarkers (i.e., t-tau, p-tau181, glial fibrillary acidic protein, neurofilament light). HIGHLIGHTS Plasma Aβ42/40 positivity is associated with brain microstructure decline. Plasma+/PET- demonstrated increased FW in 24 total GM and WM regions. Plasma+/PET- demonstrated decreased FAt in 66 total GM and WM regions. Whole-brain FW correlated with plasma Aβ42/40 and p-tau181 measures. Plasma+/PET- demonstrated decreased cortical volume and thickness.
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Affiliation(s)
- Jesse C. DeSimone
- Department of Applied Physiology and KinesiologyUniversity of FloridaGainesvilleFloridaUSA
- 1Florida Alzheimer's Disease Research CenterGainesvilleFloridaUSA
| | - Wei‐en Wang
- Department of Applied Physiology and KinesiologyUniversity of FloridaGainesvilleFloridaUSA
- 1Florida Alzheimer's Disease Research CenterGainesvilleFloridaUSA
| | - David A. Loewenstein
- 1Florida Alzheimer's Disease Research CenterGainesvilleFloridaUSA
- Center for Cognitive Neuroscience and AgingUniversity of Miami Miller School of MedicineMiamiFloridaUSA
- Department of Psychiatry and Behavioral SciencesUniversity of Miami Miller School of MedicineMiamiFloridaUSA
| | - Ranjan Duara
- 1Florida Alzheimer's Disease Research CenterGainesvilleFloridaUSA
- Wien Center for Alzheimer's Disease and Memory DisordersMount Sinai Medical CenterMiami BeachFloridaUSA
| | - Glenn E. Smith
- 1Florida Alzheimer's Disease Research CenterGainesvilleFloridaUSA
- Department of Clinical and Health PsychologyUniversity of FloridaGainesvilleFloridaUSA
| | - Karen N. McFarland
- 1Florida Alzheimer's Disease Research CenterGainesvilleFloridaUSA
- Department of NeurologyUniversity of FloridaGainesvilleFloridaUSA
| | - Melissa J. Armstrong
- 1Florida Alzheimer's Disease Research CenterGainesvilleFloridaUSA
- Department of NeurologyUniversity of FloridaGainesvilleFloridaUSA
- Norman Fixel Institute for Neurological DiseasesUniversity of FloridaGainesvilleFloridaUSA
| | - Darren M. Weber
- Quest Diagnostics Nichols InstituteSan Juan CapistranoCaliforniaUSA
| | - Warren Barker
- 1Florida Alzheimer's Disease Research CenterGainesvilleFloridaUSA
- Wien Center for Alzheimer's Disease and Memory DisordersMount Sinai Medical CenterMiami BeachFloridaUSA
| | - Stephen A. Coombes
- Department of Applied Physiology and KinesiologyUniversity of FloridaGainesvilleFloridaUSA
- 1Florida Alzheimer's Disease Research CenterGainesvilleFloridaUSA
- J. Crayton Pruitt Family Department of Biomedical EngineeringUniversity of FloridaGainesvilleFloridaUSA
| | - David E. Vaillancourt
- Department of Applied Physiology and KinesiologyUniversity of FloridaGainesvilleFloridaUSA
- 1Florida Alzheimer's Disease Research CenterGainesvilleFloridaUSA
- Department of NeurologyUniversity of FloridaGainesvilleFloridaUSA
- Norman Fixel Institute for Neurological DiseasesUniversity of FloridaGainesvilleFloridaUSA
- J. Crayton Pruitt Family Department of Biomedical EngineeringUniversity of FloridaGainesvilleFloridaUSA
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Ofori E, Vaillancourt DE, Greig-Custo MT, Barker W, Hanson K, DeKosky ST, Garvan CS, Adjouadi M, Golde T, Loewenstein DA, Stecher C, Fowers R, Duara R. Free-water imaging reveals unique brain microstructural deficits in hispanic individuals with Dementia. Brain Imaging Behav 2024; 18:106-116. [PMID: 37903991 PMCID: PMC11157151 DOI: 10.1007/s11682-023-00819-w] [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: 10/22/2023] [Indexed: 11/01/2023]
Abstract
Prior evidence suggests that Hispanic and non-Hispanic individuals differ in potential risk factors for the development of dementia. Here we determine whether specific brain regions are associated with cognitive performance for either ethnicity along various stages of Alzheimer's disease. For this cross-sectional study, we examined 108 participants (61 Hispanic vs. 47 Non-Hispanic individuals) from the 1Florida Alzheimer's Disease Research Center (1Florida ADRC), who were evaluated at baseline with diffusion-weighted and T1-weighted imaging, and positron emission tomography (PET) amyloid imaging. We used FreeSurfer to segment 34 cortical regions of interest. Baseline Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) were used as measures of cognitive performance. Group analyses assessed free-water measures (FW) and volume. Statistically significant FW regions based on ethnicity x group interactions were used in a stepwise regression function to predict total MMSE and MoCA scores. Random forest models were used to identify the most predictive brain-based measures of a dementia diagnosis separately for Hispanic and non-Hispanic groups. Results indicated elevated FW values for the left inferior temporal gyrus, left middle temporal gyrus, left banks of the superior temporal sulcus, left supramarginal gyrus, right amygdala, and right entorhinal cortex in Hispanic AD subjects compared to non-Hispanic AD subjects. These alterations occurred in the absence of different volumes of these regions in the two AD groups. FW may be useful in detecting individual differences potentially reflective of varying etiology that can influence cognitive decline and identify MRI predictors of cognitive performance, particularly among Hispanics.
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Affiliation(s)
- Edward Ofori
- College of Health Solutions, Arizona State University, 425 N. 5th St Phoenix, Phoenix, AZ, 85004, USA.
| | - David E Vaillancourt
- Department of Applied Physiology and Kinesiology, University of Florida, Gainesville, FL, USA
| | - Maria T Greig-Custo
- Wien Center for Alzheimer's Disease and Memory Disorders, Mount Sinai Medical Center, Miami, FL, USA
| | - Warren Barker
- Wien Center for Alzheimer's Disease and Memory Disorders, Mount Sinai Medical Center, Miami, FL, USA
| | - Kevin Hanson
- Clinical and Translational Science Institute, University of Florida, Gainesville, FL, USA
| | - Steven T DeKosky
- Emory Center for Neurodegenerative Disease, Departments of Pharmacology, Chemical Biology, & Neurology, Atlanta, GA, USA
| | - Cynthia S Garvan
- Department of Anesthesiology, University of Florida, Gainesville, FL, USA
| | - Malek Adjouadi
- Electrical and Computer Engineering, Florida International University, Miami, FL, USA
| | - Todd Golde
- Emory Center for Neurodegenerative Disease, Departments of Pharmacology, Chemical Biology, & Neurology, Atlanta, GA, USA
- Department of Psychiatry, Miller School of Medicine, Center for Cognitive Neuroscience and Aging University of Miami, Miami, FL, USA
| | - David A Loewenstein
- Department of Psychiatry, Miller School of Medicine, Center for Cognitive Neuroscience and Aging University of Miami, Miami, FL, USA
| | - Chad Stecher
- College of Health Solutions, Arizona State University, 425 N. 5th St Phoenix, Phoenix, AZ, 85004, USA
| | - Rylan Fowers
- College of Health Solutions, Arizona State University, 425 N. 5th St Phoenix, Phoenix, AZ, 85004, USA
| | - Ranjan Duara
- Wien Center for Alzheimer's Disease and Memory Disorders, Mount Sinai Medical Center, Miami, FL, USA
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Wilkes BJ, Archer DB, Farmer AL, Bass C, Korah H, Vaillancourt DE, Lewis MH. Cortico-basal ganglia white matter microstructure is linked to restricted repetitive behavior in autism spectrum disorder. Mol Autism 2024; 15:6. [PMID: 38254158 PMCID: PMC10804694 DOI: 10.1186/s13229-023-00581-2] [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: 08/18/2023] [Accepted: 12/23/2023] [Indexed: 01/24/2024] Open
Abstract
BACKGROUND Restricted repetitive behavior (RRB) is one of two behavioral domains required for the diagnosis of autism spectrum disorder (ASD). Neuroimaging is widely used to study brain alterations associated with ASD and the domain of social and communication deficits, but there has been less work regarding brain alterations linked to RRB. METHODS We utilized neuroimaging data from the National Institute of Mental Health Data Archive to assess basal ganglia and cerebellum structure in a cohort of children and adolescents with ASD compared to typically developing (TD) controls. We evaluated regional gray matter volumes from T1-weighted anatomical scans and assessed diffusion-weighted scans to quantify white matter microstructure with free-water imaging. We also investigated the interaction of biological sex and ASD diagnosis on these measures, and their correlation with clinical scales of RRB. RESULTS Individuals with ASD had significantly lower free-water corrected fractional anisotropy (FAT) and higher free-water (FW) in cortico-basal ganglia white matter tracts. These microstructural differences did not interact with biological sex. Moreover, both FAT and FW in basal ganglia white matter tracts significantly correlated with measures of RRB. In contrast, we found no significant difference in basal ganglia or cerebellar gray matter volumes. LIMITATIONS The basal ganglia and cerebellar regions in this study were selected due to their hypothesized relevance to RRB. Differences between ASD and TD individuals that may occur outside the basal ganglia and cerebellum, and their potential relationship to RRB, were not evaluated. CONCLUSIONS These new findings demonstrate that cortico-basal ganglia white matter microstructure is altered in ASD and linked to RRB. FW in cortico-basal ganglia and intra-basal ganglia white matter was more sensitive to group differences in ASD, whereas cortico-basal ganglia FAT was more closely linked to RRB. In contrast, basal ganglia and cerebellar volumes did not differ in ASD. There was no interaction between ASD diagnosis and sex-related differences in brain structure. Future diffusion imaging investigations in ASD may benefit from free-water estimation and correction in order to better understand how white matter is affected in ASD, and how such measures are linked to RRB.
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Affiliation(s)
- Bradley J Wilkes
- Department of Applied Physiology and Kinesiology, University of Florida, P.O. Box 118205, Gainesville, FL, 32611, USA.
| | - Derek B Archer
- Vanderbilt Memory and Alzheimer's Center, Department of Neurology, Vanderbilt School of Medicine, Nashville, TN, USA
- Department of Neurology, Vanderbilt Genetics Institute, Vanderbilt School of Medicine, Nashville, TN, USA
| | - Anna L Farmer
- Department of Psychology, University of Florida, Gainesville, FL, USA
| | - Carly Bass
- Department of Psychiatry, University of Florida, Gainesville, FL, USA
| | - Hannah Korah
- Department of Pharmacology, College of Medicine, University of Arizona, Tucson, AZ, USA
| | - David E Vaillancourt
- Department of Applied Physiology and Kinesiology, University of Florida, P.O. Box 118205, Gainesville, FL, 32611, USA
- Department of Biomedical Engineering, University of Florida, Gainesville, FL, USA
- Department of Neurology, Fixel Center for Neurological Diseases, Program in Movement Disorders and Neurorestoration, University of Florida, Gainesville, FL, USA
| | - Mark H Lewis
- Department of Psychology, University of Florida, Gainesville, FL, USA
- Department of Psychiatry, University of Florida, Gainesville, FL, USA
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11
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Savoie FA, Arpin DJ, Vaillancourt DE. Magnetic Resonance Imaging and Nuclear Imaging of Parkinsonian Disorders: Where do we go from here? Curr Neuropharmacol 2024; 22:1583-1605. [PMID: 37533246 DOI: 10.2174/1570159x21666230801140648] [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: 08/10/2022] [Revised: 01/11/2023] [Accepted: 01/13/2023] [Indexed: 08/04/2023] Open
Abstract
Parkinsonian disorders are a heterogeneous group of incurable neurodegenerative diseases that significantly reduce quality of life and constitute a substantial economic burden. Nuclear imaging (NI) and magnetic resonance imaging (MRI) have played and continue to play a key role in research aimed at understanding and monitoring these disorders. MRI is cheaper, more accessible, nonirradiating, and better at measuring biological structures and hemodynamics than NI. NI, on the other hand, can track molecular processes, which may be crucial for the development of efficient diseasemodifying therapies. Given the strengths and weaknesses of NI and MRI, how can they best be applied to Parkinsonism research going forward? This review aims to examine the effectiveness of NI and MRI in three areas of Parkinsonism research (differential diagnosis, prodromal disease identification, and disease monitoring) to highlight where they can be most impactful. Based on the available literature, MRI can assist with differential diagnosis, prodromal disease identification, and disease monitoring as well as NI. However, more work is needed, to confirm the value of MRI for monitoring prodromal disease and predicting phenoconversion. Although NI can complement or be a substitute for MRI in all the areas covered in this review, we believe that its most meaningful impact will emerge once reliable Parkinsonian proteinopathy tracers become available. Future work in tracer development and high-field imaging will continue to influence the landscape for NI and MRI.
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Affiliation(s)
- Félix-Antoine Savoie
- Department of Applied Physiology and Kinesiology, Laboratory for Rehabilitation Neuroscience, University of Florida, Gainesville, FL, USA
| | - David J Arpin
- Department of Applied Physiology and Kinesiology, Laboratory for Rehabilitation Neuroscience, University of Florida, Gainesville, FL, USA
| | - David E Vaillancourt
- Department of Applied Physiology and Kinesiology, Laboratory for Rehabilitation Neuroscience, University of Florida, Gainesville, FL, USA
- Department of Neurology, Fixel Institute for Neurological Diseases, University of Florida, Gainesville, FL, USA
- J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, FL, USA
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12
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Vijiaratnam N, Foltynie T. How should we be using biomarkers in trials of disease modification in Parkinson's disease? Brain 2023; 146:4845-4869. [PMID: 37536279 PMCID: PMC10690028 DOI: 10.1093/brain/awad265] [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: 05/10/2023] [Revised: 07/18/2023] [Accepted: 07/22/2023] [Indexed: 08/05/2023] Open
Abstract
The recent validation of the α-synuclein seed amplification assay as a biomarker with high sensitivity and specificity for the diagnosis of Parkinson's disease has formed the backbone for a proposed staging system for incorporation in Parkinson's disease clinical studies and trials. The routine use of this biomarker should greatly aid in the accuracy of diagnosis during recruitment of Parkinson's disease patients into trials (as distinct from patients with non-Parkinson's disease parkinsonism or non-Parkinson's disease tremors). There remain, however, further challenges in the pursuit of biomarkers for clinical trials of disease modifying agents in Parkinson's disease, namely: optimizing the distinction between different α-synucleinopathies; the selection of subgroups most likely to benefit from a candidate disease modifying agent; a sensitive means of confirming target engagement; and the early prediction of longer-term clinical benefit. For example, levels of CSF proteins such as the lysosomal enzyme β-glucocerebrosidase may assist in prognostication or allow enrichment of appropriate patients into disease modifying trials of agents with this enzyme as the target; the presence of coexisting Alzheimer's disease-like pathology (detectable through CSF levels of amyloid-β42 and tau) can predict subsequent cognitive decline; imaging techniques such as free-water or neuromelanin MRI may objectively track decline in Parkinson's disease even in its later stages. The exploitation of additional biomarkers to the α-synuclein seed amplification assay will, therefore, greatly add to our ability to plan trials and assess the disease modifying properties of interventions. The choice of which biomarker(s) to use in the context of disease modifying clinical trials will depend on the intervention, the stage (at risk, premotor, motor, complex) of the population recruited and the aims of the trial. The progress already made lends hope that panels of fluid biomarkers in tandem with structural or functional imaging may provide sensitive and objective methods of confirming that an intervention is modifying a key pathophysiological process of Parkinson's disease. However, correlation with clinical progression does not necessarily equate to causation, and the ongoing validation of quantitative biomarkers will depend on insightful clinical-genetic-pathophysiological comparisons incorporating longitudinal biomarker changes from those at genetic risk with evidence of onset of the pathophysiology and those at each stage of manifest clinical Parkinson's disease.
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Affiliation(s)
- Nirosen Vijiaratnam
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
| | - Thomas Foltynie
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
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13
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Bower AE, Crisomia SJ, Chung JW, Martello JP, Burciu RG. Free water imaging unravels unique patterns of longitudinal structural brain changes in Parkinson's disease subtypes. Front Neurol 2023; 14:1278065. [PMID: 37965163 PMCID: PMC10642764 DOI: 10.3389/fneur.2023.1278065] [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: 08/15/2023] [Accepted: 10/12/2023] [Indexed: 11/16/2023] Open
Abstract
Background Research shows that individuals with Parkinson's disease (PD) who have a postural instability and gait difficulties (PIGD) subtype have a faster disease progression compared to those with a tremor dominant (TD) subtype. Nevertheless, our understanding of the structural brain changes contributing to these clinical differences remains limited, primarily because many brain imaging techniques are only capable of detecting changes in the later stages of the disease. Objective Free water (FW) has emerged as a robust progression marker in several studies, showing increased values in the posterior substantia nigra that predict symptom worsening. Here, we examined longitudinal FW changes in TD and PIGD across multiple brain regions. Methods Participants were TD and PIGD enrolled in the Parkinson's Progression Marker Initiative (PPMI) study who underwent diffusion MRI at baseline and 2 years later. FW changes were quantified for regions of interest (ROI) within the basal ganglia, thalamus, brainstem, and cerebellum. Results Baseline FW in all ROIs did not differ between groups. Over 2 years, PIGD had a greater percentage increase in FW in the putamen, globus pallidus, and cerebellar lobule V. A logistic regression model incorporating percent change in motor scores and FW in these brain regions achieved 91.4% accuracy in discriminating TD and PIGD, surpassing models based solely on clinical measures (74.3%) or imaging (76.1%). Conclusion The results further suggest the use of FW to study disease progression in PD and provide insight into the differential course of brain changes in early-stage PD subtypes.
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Affiliation(s)
- Abigail E. Bower
- Department of Kinesiology and Applied Physiology, University of Delaware, Newark, DE, United States
| | - Sophia J. Crisomia
- Department of Kinesiology and Applied Physiology, University of Delaware, Newark, DE, United States
| | - Jae Woo Chung
- Department of Neurology, University of Minnesota, Minneapolis, MN, United States
| | - Justin P. Martello
- Department of Neurosciences, Christiana Care Health System, Newark, DE, United States
| | - Roxana G. Burciu
- Department of Kinesiology and Applied Physiology, University of Delaware, Newark, DE, United States
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14
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López-Aguirre M, Matarazzo M, Blesa J, Monje MHG, Rodríguez-Rojas R, Sánchez-Ferro A, Obeso JA, Pineda-Pardo JA. Dopaminergic denervation and associated MRI microstructural changes in the nigrostriatal projection in early Parkinson's disease patients. NPJ Parkinsons Dis 2023; 9:144. [PMID: 37852988 PMCID: PMC10584921 DOI: 10.1038/s41531-023-00586-x] [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: 02/20/2023] [Accepted: 10/03/2023] [Indexed: 10/20/2023] Open
Abstract
Loss of dopaminergic neurons in the substantia nigra pars compacta (SNc) and a profound reduction of striatal dopamine are two hallmarks of Parkinson's disease (PD). However, it's unclear whether degeneration starts at the neuronal soma or the striatal presynaptic terminals, and how microstructural degeneration is linked to dopaminergic loss is also uncertain. In this study, thirty de novo PD patients and twenty healthy subjects (HS) underwent 6-[18F]-fluoro-L-dopa (FDOPA) PET and MRI studies no later than 12 months from clinical diagnosis. FDOPA uptake rate (Ki), fractional volume of free-water (FW), and iron-sensitive R2* relaxometry were quantified within nigrostriatal regions. Inter-group differences (PD vs HS) were studied using non-parametric statistics and complemented with Cohen's d effect sizes and Bayesian statistics. Correlation analyses were performed exploring biomarker dependencies and their association with bradykinesia scores. PD patients exhibited a significant decline in nigrostriatal dopaminergic activity, being post-commissural putamen (-67%) and posterolateral SNc (-11.7%) the most affected subregions within striatum and SNc respectively. Microstructural alterations (FW) were restricted to the hemisphere corresponding to the most affected side and followed similar spatial gradients as FDOPA Ki (+20% in posterior putamen and +11% in posterolateral SNc). R2* revealed no relevant significant changes. FDOPA and FW were correlated within the posterolateral SNc, and clinical severity was associated with FDOPA Ki loss. The asymmetry between striatal and SNc changes for both dopaminergic depletion and microstructural degeneration biomarkers is consistent with a neurodegenerative process that begins in the striatal terminals before progressing toward the cell bodies in the SNc.
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Affiliation(s)
- M López-Aguirre
- HM CINAC (Centro Integral de Neurociencias Abarca Campal). Hospital Universitario HM Puerta del Sur, HM Hospitales, Madrid, Spain
- PhD Program in Physics, Complutense University of Madrid, Madrid, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
- Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD, 20815, USA
| | - M Matarazzo
- HM CINAC (Centro Integral de Neurociencias Abarca Campal). Hospital Universitario HM Puerta del Sur, HM Hospitales, Madrid, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
| | - J Blesa
- HM CINAC (Centro Integral de Neurociencias Abarca Campal). Hospital Universitario HM Puerta del Sur, HM Hospitales, Madrid, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
- Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD, 20815, USA
| | - M H G Monje
- HM CINAC (Centro Integral de Neurociencias Abarca Campal). Hospital Universitario HM Puerta del Sur, HM Hospitales, Madrid, Spain
- Ken and Ruth Davee Department of Neurology, Northwestern University, Feinberg School of Medicine, Chicago, IL, USA
| | - R Rodríguez-Rojas
- HM CINAC (Centro Integral de Neurociencias Abarca Campal). Hospital Universitario HM Puerta del Sur, HM Hospitales, Madrid, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
| | - A Sánchez-Ferro
- HM CINAC (Centro Integral de Neurociencias Abarca Campal). Hospital Universitario HM Puerta del Sur, HM Hospitales, Madrid, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
- Department of Neurology, University Hospital 12 de Octubre, Madrid, Spain
- Department of Medicine, Complutense University of Madrid, Madrid, Spain
| | - J A Obeso
- HM CINAC (Centro Integral de Neurociencias Abarca Campal). Hospital Universitario HM Puerta del Sur, HM Hospitales, Madrid, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
- Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD, 20815, USA
- University CEU-San Pablo, Madrid, Spain
| | - J A Pineda-Pardo
- HM CINAC (Centro Integral de Neurociencias Abarca Campal). Hospital Universitario HM Puerta del Sur, HM Hospitales, Madrid, Spain.
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain.
- Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD, 20815, USA.
- University CEU-San Pablo, Madrid, Spain.
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15
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Chen M, Wang Y, Zhang C, Li J, Li Z, Guan X, Bao J, Zhang Y, Cheng J, Wei H. Free water and iron content in the substantia nigra at different stages of Parkinson's disease. Eur J Radiol 2023; 167:111030. [PMID: 37579561 DOI: 10.1016/j.ejrad.2023.111030] [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: 03/29/2023] [Revised: 07/28/2023] [Accepted: 08/08/2023] [Indexed: 08/16/2023]
Abstract
PURPOSE Abnormalities in free water (FW) and susceptibility values exist in the substantia nigra (SN) of patients with Parkinson's disease (PD), but their role in characterizing the disease processes remains uncertain. This study investigated these values at various SN locations and stages of PD, and their relationship with clinical symptoms. METHOD FW and quantitative susceptibility mapping (QSM) values were evaluated in the anterior and posterior SN, along with swallow-tail-sign (STS) ratings, in patients with PD (early-stage: n = 39; middle-to-advanced-stage: n = 97) and healthy controls (n = 82). The correlation between these indices and motor and non-motor symptoms, and their capability to distinguish PD from healthy controls, were also examined. RESULTS Increased FW in the anterior and posterior SN and increased QSM values in the posterior SN were observed in both early-stage and middle-to-advanced-stage PD patients (p < 0.05). However, there was no significant difference in FW, QSM values, or STS ratings among patients at different stages. FW and QSM values correlated with motor symptoms in middle-to-advanced-stage patients (p < 0.05), while STS ratings were associated with non-motor symptoms (p < 0.05). Additionally, combining FW and QSM values in the posterior SN with STS ratings in logistic regression showed better performance in distinguishing PD (area under curve = 0.931) compared to using STS ratings alone (area under curve = 0.880). CONCLUSIONS Findings suggest elevated FW and iron content in PD at different stages, with dissociation in SN location between the two indices. Elevated signals are related to the motor symptom severity in middle-to-advanced-stage patients, and may have the potential for PD diagnosis and symptom assessment.
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Affiliation(s)
- Mingxing Chen
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Yutong Wang
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Chunyan Zhang
- Functional Magnetic Resonance and Molecular Imaging Key Laboratory of Henan Province, Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, Henan, China
| | - Jun Li
- School of Information and Science and Technology, ShanghaiTech University, Shanghai, China; Department of Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Zhenghao Li
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Xiaojun Guan
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University, Zhejiang University School of Medicine, Hangzhou, China
| | - Jianfeng Bao
- Functional Magnetic Resonance and Molecular Imaging Key Laboratory of Henan Province, Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, Henan, China
| | - Yuyao Zhang
- School of Information and Science and Technology, ShanghaiTech University, Shanghai, China
| | - Jingliang Cheng
- Functional Magnetic Resonance and Molecular Imaging Key Laboratory of Henan Province, Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, Henan, China
| | - Hongjiang Wei
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.
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16
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Archer DB, Schilling K, Shashikumar N, Jasodanand V, Moore EE, Pechman KR, Bilgel M, Beason‐Held LL, An Y, Shafer A, Ferrucci L, Risacher SL, Gifford KA, Landman BA, Jefferson AL, Saykin AJ, Resnick SM, Hohman TJ. Leveraging longitudinal diffusion MRI data to quantify differences in white matter microstructural decline in normal and abnormal aging. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2023; 15:e12468. [PMID: 37780863 PMCID: PMC10540270 DOI: 10.1002/dad2.12468] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Revised: 06/27/2023] [Accepted: 07/05/2023] [Indexed: 10/03/2023]
Abstract
Introduction It is unclear how rates of white matter microstructural decline differ between normal aging and abnormal aging. Methods Diffusion MRI data from several well-established longitudinal cohorts of aging (Alzheimer's Disease Neuroimaging Initiative [ADNI], Baltimore Longitudinal Study of Aging [BLSA], Vanderbilt Memory & Aging Project [VMAP]) were free-water corrected and harmonized. This dataset included 1723 participants (age at baseline: 72.8 ± 8.87 years, 49.5% male) and 4605 imaging sessions (follow-up time: 2.97 ± 2.09 years, follow-up range: 1-13 years, mean number of visits: 4.42 ± 1.98). Differences in white matter microstructural decline in normal and abnormal agers was assessed. Results While we found a global decline in white matter in normal/abnormal aging, we found that several white matter tracts (e.g., cingulum bundle) were vulnerable to abnormal aging. Conclusions There is a prevalent role of white matter microstructural decline in aging, and future large-scale studies in this area may further refine our understanding of the underlying neurodegenerative processes. HIGHLIGHTS Longitudinal data were free-water corrected and harmonized.Global effects of white matter decline were seen in normal and abnormal aging.The free-water metric was most vulnerable to abnormal aging.Cingulum free-water was the most vulnerable to abnormal aging.
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Affiliation(s)
- Derek B. Archer
- Vanderbilt Memory and Alzheimer's CenterVanderbilt University School of MedicineNashvilleTennesseeUSA
- Vanderbilt Genetics InstituteVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Kurt Schilling
- Vanderbilt University Institute of Imaging ScienceVanderbilt University Medical CenterNashvilleTennesseeUSA
- Department of Radiology & Radiological SciencesVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Niranjana Shashikumar
- Vanderbilt Memory and Alzheimer's CenterVanderbilt University School of MedicineNashvilleTennesseeUSA
| | - Varuna Jasodanand
- Vanderbilt Memory and Alzheimer's CenterVanderbilt University School of MedicineNashvilleTennesseeUSA
| | - Elizabeth E. Moore
- Vanderbilt Memory and Alzheimer's CenterVanderbilt University School of MedicineNashvilleTennesseeUSA
| | - Kimberly R. Pechman
- Vanderbilt Memory and Alzheimer's CenterVanderbilt University School of MedicineNashvilleTennesseeUSA
| | - Murat Bilgel
- Laboratory of Behavioral NeuroscienceNational Institute on AgingNational Institutes of HealthBaltimoreMarylandUSA
| | - Lori L. Beason‐Held
- Laboratory of Behavioral NeuroscienceNational Institute on AgingNational Institutes of HealthBaltimoreMarylandUSA
| | - Yang An
- Laboratory of Behavioral NeuroscienceNational Institute on AgingNational Institutes of HealthBaltimoreMarylandUSA
| | - Andrea Shafer
- Laboratory of Behavioral NeuroscienceNational Institute on AgingNational Institutes of HealthBaltimoreMarylandUSA
| | - Luigi Ferrucci
- Longitudinal Studies Section, Translational Gerontology BranchNational Institute on AgingBaltimoreMDUSA
| | - Shannon L. Risacher
- Indiana University School of MedicineIndianapolisIndianaUSA
- Indiana Alzheimer's Disease Research CenterIndianapolisIndianaUSA
| | - Katherine A. Gifford
- Vanderbilt Memory and Alzheimer's CenterVanderbilt University School of MedicineNashvilleTennesseeUSA
| | - Bennett A. Landman
- Vanderbilt University Institute of Imaging ScienceVanderbilt University Medical CenterNashvilleTennesseeUSA
- Department of Radiology & Radiological SciencesVanderbilt University Medical CenterNashvilleTennesseeUSA
- Department of Biomedical EngineeringVanderbilt UniversityNashvilleTennesseeUSA
- Department of Electrical and Computer EngineeringVanderbilt UniversityNashvilleTennesseeUSA
| | - Angela L. Jefferson
- Vanderbilt Memory and Alzheimer's CenterVanderbilt University School of MedicineNashvilleTennesseeUSA
- Department of MedicineVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Andrew J. Saykin
- Indiana University School of MedicineIndianapolisIndianaUSA
- Indiana Alzheimer's Disease Research CenterIndianapolisIndianaUSA
| | - Susan M. Resnick
- Laboratory of Behavioral NeuroscienceNational Institute on AgingNational Institutes of HealthBaltimoreMarylandUSA
| | - Timothy J. Hohman
- Vanderbilt Memory and Alzheimer's CenterVanderbilt University School of MedicineNashvilleTennesseeUSA
- Vanderbilt Genetics InstituteVanderbilt University Medical CenterNashvilleTennesseeUSA
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Zhang D, Zhou L, Yao J, Shi Y, He H, Wei H, Tong Q, Liu J, Wu T. Increased Free Water in the Putamen in Idiopathic REM Sleep Behavior Disorder. Mov Disord 2023; 38:1645-1654. [PMID: 37342973 DOI: 10.1002/mds.29499] [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: 03/16/2023] [Revised: 05/05/2023] [Accepted: 05/24/2023] [Indexed: 06/23/2023] Open
Abstract
BACKGROUND It has been suggested that the loss of nigrostriatal dopaminergic axon terminals occurs before the loss of dopaminergic neurons in the substantia nigra (SN) in Parkinson's disease (PD). This study aimed to use free-water imaging to evaluate microstructural changes in the dorsoposterior putamen (DPP) of idiopathic rapid eye movement (REM) sleep behavior disorder (iRBD) patients, which is considered a prodromal stage of synucleinopathies. METHODS Free water values in the DPP, dorsoanterior putamen (DAP), and posterior SN were compared between the healthy controls (n = 48), iRBD (n = 43) and PD (n = 47) patients. In iRBD patients, the relationships between baseline and longitudinal free water values and clinical manifestations or dopamine transporter (DAT) striatal binding ratio (SBR) were analyzed. RESULTS Free water values were significantly higher in the DPP and posterior substantia nigra (pSN), but not in the DAP, in the iRBD and PD groups than in controls. In iRBD patients, free water values in the DPP were progressively increased and correlated with the progression of clinical manifestations and the striatal DAT SBR. Baseline free water in the DPP was negatively correlated with striatal DAT SBR and hyposmia and positively correlated with motor deficits. CONCLUSIONS This study demonstrates that free water values in the DPP are increased cross-sectionally and longitudinally and associated with clinical manifestations and the function of the dopaminergic system in the prodromal stage of synucleinopathies. Our findings indicate that free-water imaging of the DPP has the potential to be a valid marker of early diagnosis and progression of synucleinopathies. © 2023 International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Dongling Zhang
- Center for Movement Disorders, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
- Parkinson's Disease Center, Beijing Institute for Brain Disorders, Capital Medical University, Beijing, China
| | - Liche Zhou
- Department of Neurology and Institute of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Junye Yao
- Center for Brain Imaging Science and Technology, College of Biomedical Engineering and Instrument Science, Zhejiang University, Zhejiang, China
| | - Yuting Shi
- Institute for Medical Imaging Technology, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Hongjian He
- Center for Brain Imaging Science and Technology, College of Biomedical Engineering and Instrument Science, Zhejiang University, Zhejiang, China
- School of Physics, Zhejiang University, Zhejiang, China
| | - Hongjiang Wei
- Institute for Medical Imaging Technology, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Qiqi Tong
- Research Center for Healthcare Data Science, Zhejiang Lab, Zhejiang, China
| | - Jun Liu
- Department of Neurology and Institute of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Tao Wu
- Center for Movement Disorders, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
- Parkinson's Disease Center, Beijing Institute for Brain Disorders, Capital Medical University, Beijing, China
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18
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Zhou C, Wang L, Cheng W, Lv J, Guan X, Guo T, Wu J, Zhang W, Gao T, Liu X, Bai X, Wu H, Cao Z, Gu L, Chen J, Wen J, Huang P, Xu X, Zhang B, Feng J, Zhang M. Two distinct trajectories of clinical and neurodegeneration events in Parkinson's disease. NPJ Parkinsons Dis 2023; 9:111. [PMID: 37443179 PMCID: PMC10344958 DOI: 10.1038/s41531-023-00556-3] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2023] [Accepted: 07/04/2023] [Indexed: 07/15/2023] Open
Abstract
Increasing evidence suggests that Parkinson's disease (PD) exhibits disparate spatial and temporal patterns of progression. Here we used a machine-learning technique-Subtype and Stage Inference (SuStaIn) - to uncover PD subtypes with distinct trajectories of clinical and neurodegeneration events. We enrolled 228 PD patients and 119 healthy controls with comprehensive assessments of olfactory, autonomic, cognitive, sleep, and emotional function. The integrity of substantia nigra (SN), locus coeruleus (LC), amygdala, hippocampus, entorhinal cortex, and basal forebrain were assessed using diffusion and neuromelanin-sensitive MRI. SuStaIn model with above clinical and neuroimaging variables as input was conducted to identify PD subtypes. An independent dataset consisting of 153 PD patients and 67 healthy controls was utilized to validate our findings. We identified two distinct PD subtypes: subtype 1 with rapid eye movement sleep behavior disorder (RBD), autonomic dysfunction, and degeneration of the SN and LC as early manifestations, and cognitive impairment and limbic degeneration as advanced manifestations, while subtype 2 with hyposmia, cognitive impairment, and limbic degeneration as early manifestations, followed later by RBD and degeneration of the LC in advanced disease. Similar subtypes were shown in the validation dataset. Moreover, we found that subtype 1 had weaker levodopa response, more GBA mutations, and poorer prognosis than subtype 2. These findings provide new insights into the underlying disease biology and might be useful for personalized treatment for patients based on their subtype.
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Affiliation(s)
- Cheng Zhou
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 310000, Hangzhou, China
| | - Linbo Wang
- Institute of Science and Technology for Brain-inspired Intelligence, Fudan University, 200433, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
- MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China
- Zhangjiang Fudan International Innovation Center, Shanghai, China
| | - Wei Cheng
- Institute of Science and Technology for Brain-inspired Intelligence, Fudan University, 200433, Shanghai, China.
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China.
- MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China.
- Zhangjiang Fudan International Innovation Center, Shanghai, China.
- Department of Computer Science, University of Warwick, Coventry, CV4 7AL, United Kingdom.
| | - JinChao Lv
- Institute of Science and Technology for Brain-inspired Intelligence, Fudan University, 200433, Shanghai, China
| | - Xiaojun Guan
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 310000, Hangzhou, China
| | - Tao Guo
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 310000, Hangzhou, China
| | - Jingjing Wu
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 310000, Hangzhou, China
| | - Wei Zhang
- Institute of Science and Technology for Brain-inspired Intelligence, Fudan University, 200433, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
- MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China
- Zhangjiang Fudan International Innovation Center, Shanghai, China
| | - Ting Gao
- Department of Neurology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 310000, Hangzhou, China
| | - Xiaocao Liu
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 310000, Hangzhou, China
| | - Xueqin Bai
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 310000, Hangzhou, China
| | - Haoting Wu
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 310000, Hangzhou, China
| | - Zhengye Cao
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 310000, Hangzhou, China
| | - Luyan Gu
- Department of Neurology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 310000, Hangzhou, China
| | - Jingwen Chen
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 310000, Hangzhou, China
| | - Jiaqi Wen
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 310000, Hangzhou, China
| | - Peiyu Huang
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 310000, Hangzhou, China
| | - Xiaojun Xu
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 310000, Hangzhou, China
| | - Baorong Zhang
- Department of Neurology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 310000, Hangzhou, China
| | - Jianfeng Feng
- Institute of Science and Technology for Brain-inspired Intelligence, Fudan University, 200433, Shanghai, China.
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China.
- MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China.
- Zhangjiang Fudan International Innovation Center, Shanghai, China.
- Department of Computer Science, University of Warwick, Coventry, CV4 7AL, United Kingdom.
| | - Minming Zhang
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 310000, Hangzhou, China.
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19
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Pizarro-Galleguillos BM, Kunert L, Brüggemann N, Prasuhn J. Neuroinflammation and Mitochondrial Dysfunction in Parkinson's Disease: Connecting Neuroimaging with Pathophysiology. Antioxidants (Basel) 2023; 12:1411. [PMID: 37507950 PMCID: PMC10375976 DOI: 10.3390/antiox12071411] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Revised: 07/07/2023] [Accepted: 07/10/2023] [Indexed: 07/30/2023] Open
Abstract
There is a pressing need for disease-modifying therapies in patients suffering from neurodegenerative diseases, including Parkinson's disease (PD). However, these disorders face unique challenges in clinical trial designs to assess the neuroprotective properties of potential drug candidates. One of these challenges relates to the often unknown individual disease mechanisms that would, however, be relevant for targeted treatment strategies. Neuroinflammation and mitochondrial dysfunction are two proposed pathophysiological hallmarks and are considered to be highly interconnected in PD. Innovative neuroimaging methods can potentially help to gain deeper insights into one's predominant disease mechanisms, can facilitate patient stratification in clinical trials, and could potentially map treatment responses. This review aims to highlight the role of neuroinflammation and mitochondrial dysfunction in patients with PD (PwPD). We will specifically introduce different neuroimaging modalities, their respective technical hurdles and challenges, and their implementation into clinical practice. We will gather preliminary evidence for their potential use in PD research and discuss opportunities for future clinical trials.
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Affiliation(s)
- Benjamin Matís Pizarro-Galleguillos
- Facultad de Medicina, Universidad de Chile, Santiago 8380453, Chile
- Department of Neurology, University Medical Center Schleswig-Holstein, Campus Lübeck, 23562 Lübeck, Germany
- Institute of Neurogenetics, University of Lübeck, 23562 Lübeck, Germany
- Center for Brain, Behavior, and Metabolism, University of Lübeck, 23562 Lübeck, Germany
| | - Liesa Kunert
- Department of Neurology, University Medical Center Schleswig-Holstein, Campus Lübeck, 23562 Lübeck, Germany
- Institute of Neurogenetics, University of Lübeck, 23562 Lübeck, Germany
- Center for Brain, Behavior, and Metabolism, University of Lübeck, 23562 Lübeck, Germany
| | - Norbert Brüggemann
- Department of Neurology, University Medical Center Schleswig-Holstein, Campus Lübeck, 23562 Lübeck, Germany
- Center for Brain, Behavior, and Metabolism, University of Lübeck, 23562 Lübeck, Germany
| | - Jannik Prasuhn
- Department of Neurology, University Medical Center Schleswig-Holstein, Campus Lübeck, 23562 Lübeck, Germany
- Institute of Neurogenetics, University of Lübeck, 23562 Lübeck, Germany
- Center for Brain, Behavior, and Metabolism, University of Lübeck, 23562 Lübeck, Germany
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD 21287, USA
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20
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Wilkes BJ, Tobin ER, Arpin DJ, Wang WE, Okun MS, Jaffee MS, McFarland NR, Corcos DM, Vaillancourt DE. Distinct cortical and subcortical predictors of Purdue Pegboard decline in Parkinson's disease and atypical parkinsonism. NPJ Parkinsons Dis 2023; 9:85. [PMID: 37277372 PMCID: PMC10241903 DOI: 10.1038/s41531-023-00521-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2022] [Accepted: 05/15/2023] [Indexed: 06/07/2023] Open
Abstract
Objective measures of disease progression are critically needed in research on Parkinson's disease (PD) and atypical Parkinsonism but may be hindered by both practicality and cost. The Purdue Pegboard Test (PPT) is objective, has high test-retest reliability, and has a low cost. The goals of this study were to determine: (1) longitudinal changes in PPT in a multisite cohort of patients with PD, atypical Parkinsonism, and healthy controls; (2) whether PPT performance reflects brain pathology revealed by neuroimaging; (3) quantify kinematic deficits shown by PD patients during PPT. Parkinsonian patients showed a decline in PPT performance that correlated with motor symptom progression, which was not seen in controls. Neuroimaging measures from basal ganglia were significant predictors of PPT performance in PD, whereas cortical, basal ganglia, and cerebellar regions were predictors for atypical Parkinsonism. Accelerometry in a subset of PD patients showed a diminished range of acceleration and irregular patterns of acceleration, which correlated with PPT scores.
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Affiliation(s)
- Bradley J Wilkes
- Department of Applied Physiology and Kinesiology, University of Florida, Gainesville, FL, USA.
| | - Emily R Tobin
- Department of Applied Physiology and Kinesiology, University of Florida, Gainesville, FL, USA
| | - David J Arpin
- Department of Applied Physiology and Kinesiology, University of Florida, Gainesville, FL, USA
| | - Wei-En Wang
- Department of Applied Physiology and Kinesiology, University of Florida, Gainesville, FL, USA
| | - Michael S Okun
- Department of Neurology, Norman Fixel Institute for Neurological Diseases, University of Florida, Gainesville, FL, USA
| | - Michael S Jaffee
- Department of Neurology, Norman Fixel Institute for Neurological Diseases, University of Florida, Gainesville, FL, USA
| | - Nikolaus R McFarland
- Department of Neurology, Norman Fixel Institute for Neurological Diseases, University of Florida, Gainesville, FL, USA
| | - Daniel M Corcos
- Department of Physical Therapy and Human Movement Sciences, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - David E Vaillancourt
- Department of Applied Physiology and Kinesiology, University of Florida, Gainesville, FL, USA
- Department of Neurology, Norman Fixel Institute for Neurological Diseases, University of Florida, Gainesville, FL, USA
- Department of Biomedical Engineering, University of Florida, Gainesville, FL, USA
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21
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Guttuso T, Shepherd R, Frick L, Feltri ML, Frerichs V, Ramanathan M, Zivadinov R, Bergsland N. Lithium's effects on therapeutic targets and MRI biomarkers in Parkinson's disease: A pilot clinical trial. IBRO Neurosci Rep 2023; 14:429-434. [PMID: 37215748 PMCID: PMC10196787 DOI: 10.1016/j.ibneur.2023.05.001] [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: 03/11/2023] [Accepted: 05/05/2023] [Indexed: 05/24/2023] Open
Abstract
Background Lithium has a wide range of neuroprotective actions, has been effective in Parkinson's disease (PD) animal models and may account for the decreased risk of PD in smokers. Methods This open-label pilot clinical trial randomized 16 PD patients to "high-dose" (n = 5, lithium carbonate titrated to achieve serum level of 0.4-0.5 mmol/L), "medium-dose" (n = 6, 45 mg/day lithium aspartate) or "low-dose" (n = 5, 15 mg/day lithium aspartate) lithium therapy for 24-weeks. Peripheral blood mononuclear cell (PBMC) mRNA expression of nuclear receptor-related-1 (Nurr1) and superoxide dismutase-1 (SOD1) were assessed by qPCR in addition to other PD therapeutic targets. Two patients from each group received multi-shell diffusion MRI scans to assess for free water (FW) changes in the dorsomedial nucleus of the thalamus and nucleus basalis of Meynert, which reflect cognitive decline in PD, and the posterior substantia nigra, which reflects motor decline in PD. Results Two of the six patients receiving medium-dose lithium therapy withdrew due to side effects. Medium-dose lithium therapy was associated with the greatest numerical increases in PBMC Nurr1 and SOD1 expression (679% and 127%, respectively). Also, medium-dose lithium therapy was the only dosage associated with mean numerical decreases in brain FW in all three regions of interest, which is the opposite of the known longitudinal FW changes in PD. Conclusion Medium-dose lithium aspartate therapy was associated with engagement of blood-based therapeutic targets and improvements in MRI disease-progression biomarkers but was poorly tolerated in 33% of patients. Further PD clinical research is merited examining lithium's tolerability, effects on biomarkers and potential disease-modifying effects.
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Affiliation(s)
- Thomas Guttuso
- Department of Neurology, Clinical and Translational Science Institute, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo, NY, United States
| | - Rachel Shepherd
- Department of Neurology, Clinical and Translational Science Institute, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo, NY, United States
| | - Luciana Frick
- Department of Neurology, Clinical and Translational Science Institute, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo, NY, United States
| | - M. Laura Feltri
- Department of Neurology, Clinical and Translational Science Institute, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo, NY, United States
| | - Valerie Frerichs
- Department of Chemistry, Clinical and Translational Science Institute, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo, NY, United States
| | - Murali Ramanathan
- Department of Pharmaceutical Sciences, Clinical and Translational Science Institute, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo, NY, United States
| | - Robert Zivadinov
- Department of Neurology, Clinical and Translational Science Institute, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo, NY, United States
- Center for Biomedical Imaging, Clinical and Translational Science Institute, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo, NY, United States
| | - Niels Bergsland
- Department of Neurology, Clinical and Translational Science Institute, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo, NY, United States
- Center for Biomedical Imaging, Clinical and Translational Science Institute, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo, NY, United States
- IRCCS, Fondazione Don Carlo Gnocchi, Milan, Italy
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22
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Archer DB, Schilling K, Shashikumar N, Jasodanand V, Moore EE, Pechman KR, Bilgel M, Beason-Held LL, An Y, Shafer A, Ferrucci L, Risacher SL, Gifford KA, Landman BA, Jefferson AL, Saykin AJ, Resnick SM, Hohman TJ. Leveraging longitudinal diffusion MRI data to quantify differences in white matter microstructural decline in normal and abnormal aging. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.05.17.541182. [PMID: 37292885 PMCID: PMC10245725 DOI: 10.1101/2023.05.17.541182] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
INTRODUCTION It is unclear how rates of white matter microstructural decline differ between normal aging and abnormal aging. METHODS Diffusion MRI data from several well-established longitudinal cohorts of aging [Alzheimer's Neuroimaging Initiative (ADNI), Baltimore Longitudinal Study of Aging (BLSA), Vanderbilt Memory & Aging Project (VMAP)] was free-water corrected and harmonized. This dataset included 1,723 participants (age at baseline: 72.8±8.87 years, 49.5% male) and 4,605 imaging sessions (follow-up time: 2.97±2.09 years, follow-up range: 1-13 years, mean number of visits: 4.42±1.98). Differences in white matter microstructural decline in normal and abnormal agers was assessed. RESULTS While we found global decline in white matter in normal/abnormal aging, we found that several white matter tracts (e.g., cingulum bundle) were vulnerable to abnormal aging. CONCLUSIONS There is a prevalent role of white matter microstructural decline in aging, and future large-scale studies in this area may further refine our understanding of the underlying neurodegenerative processes. HIGHLIGHTS Longitudinal data was free-water corrected and harmonizedGlobal effects of white matter decline were seen in normal and abnormal agingThe free-water metric was most vulnerable to abnormal agingCingulum free-water was the most vulnerable to abnormal aging.
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Affiliation(s)
- Derek B. Archer
- Vanderbilt Memory and Alzheimer’s Center, Vanderbilt University School of Medicine, Nashville, TN, USA
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Kurt Schilling
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Radiology & Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Niranjana Shashikumar
- Vanderbilt Memory and Alzheimer’s Center, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Varuna Jasodanand
- Vanderbilt Memory and Alzheimer’s Center, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Elizabeth E. Moore
- Vanderbilt Memory and Alzheimer’s Center, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Kimberly R. Pechman
- Vanderbilt Memory and Alzheimer’s Center, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Murat Bilgel
- Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Lori L. Beason-Held
- Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Yang An
- Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Andrea Shafer
- Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | | | - Shannon L. Risacher
- Indiana University School of Medicine, Indianapolis, IN, USA
- Indiana Alzheimer’s Disease Research Center, Indianapolis, IN, USA
| | - Katherine A. Gifford
- Vanderbilt Memory and Alzheimer’s Center, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Bennett A. Landman
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA
- Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA
- Department of Radiology & Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Angela L. Jefferson
- Vanderbilt Memory and Alzheimer’s Center, Vanderbilt University School of Medicine, Nashville, TN, USA
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Andrew J. Saykin
- Indiana University School of Medicine, Indianapolis, IN, USA
- Indiana Alzheimer’s Disease Research Center, Indianapolis, IN, USA
| | - Susan M. Resnick
- Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Timothy J. Hohman
- Vanderbilt Memory and Alzheimer’s Center, Vanderbilt University School of Medicine, Nashville, TN, USA
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
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23
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Zhou G, Ren J, Rong D, Zhou H, Ning H, Wang H, Pan C, Wang Y, Zhang R, Guo Z, Huang P, Liu W. Monitoring Substantia Nigra Degeneration Using Free Water Imaging across Prodromal and Clinical Parkinson's Disease. Mov Disord 2023; 38:774-782. [PMID: 36947674 DOI: 10.1002/mds.29366] [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: 12/01/2022] [Revised: 02/07/2023] [Accepted: 02/10/2023] [Indexed: 03/24/2023] Open
Abstract
BACKGROUND Substantia nigra (SN) free water has been suggested as a good surrogate marker in Parkinson's disease (PD). However, its usefulness for diagnosing prodromal PD (pPD) and monitoring disease progression warrants further validation. OBJECTIVE The aim was to investigate SN free water values across prodromal and clinical stages of PD. METHODS Four groups were enrolled in this study: 48 healthy controls (HC), 43 pPD patients, 50 de novo PD (dnPD) patients, and 49 medicated PD (mPD) patients. Based on diffusion tensor images, free water maps were calculated, and SN free water values were extracted from the anterior SN (ASN) and posterior SN (PSN). The SN free water values were compared among the four groups, and associations between free water and clinical symptoms were explored. The distinguishing power of PSN free water was evaluated using the receiver operating characteristic curve analysis. Follow-up was performed for 14 pPD patients. RESULTS PSN free water in the pPD group was significantly higher than that in the HC group and significantly lower than that in the dnPD group. Surprisingly, the mPD group showed decreased PSN free water compared to the dnPD group. There was a positive correlation between motor symptoms and PSN free water in the pPD and dnPD groups. Longitudinal analysis showed a significant increase in PSN free water in pPD patients over time. CONCLUSIONS The PSN free water increased from prodromal to early clinical stages, but the trend might be reversed in late disease stages. This biphasic trend should be considered when applying this marker in future studies. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Gaiyan Zhou
- Department of Neurology, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China
| | - Jingru Ren
- Department of Neurology, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China
| | - Danyan Rong
- Department of Neurology, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China
| | - Hao Zhou
- Department of Neurology, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China
| | - Houxu Ning
- Department of Neurology, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China
| | - Hui Wang
- Department of Neurology, Lianyungang Hospital of Traditional Chinese Medicine, Lianyungang, China
| | - Chenxi Pan
- Department of Neurology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Yajie Wang
- Department of Neurology, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China
| | - Ronggui Zhang
- Department of Neurology, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China
| | - Zhiying Guo
- Department of Neurology, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China
| | - Peiyu Huang
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Weiguo Liu
- Department of Neurology, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China
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24
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Chahine LM, Merchant K, Siderowf A, Sherer T, Tanner C, Marek K, Simuni T. Proposal for a Biologic Staging System of Parkinson's Disease. JOURNAL OF PARKINSON'S DISEASE 2023; 13:297-309. [PMID: 37066922 DOI: 10.3233/jpd-225111] [Citation(s) in RCA: 23] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/18/2023]
Abstract
The Parkinson's disease (PD) research field has seen the advent of several promising biomarkers and a deeper understanding of the clinical features of the disease from the earliest stages of pathology to manifest disease. Despite progress, a biologically based PD staging system does not exist. Such staging would be a useful framework within which to model the disease, develop and validate biomarkers, guide therapeutic development, and inform clinical trials design. We propose that the presence of aggregated neuronal α-synuclein, dopaminergic neuron dysfunction/degeneration, and clinical signs and symptoms identifies a group of individuals that have Lewy body pathology, which in early stages manifests with what is now referred to as prodromal non-motor features and later stages with the manifestations of PD and related Lewy body diseases as defined by clinical diagnostic criteria. Based on the state of the field, we herein propose a definition and staging of PD based on biology. We present the biologic basis for such a staging system and review key assumptions and evidence that support the proposed approach. We identify gaps in knowledge and delineate crucial research priorities that will inform the ultimate integrated biologic staging system for PD.
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Affiliation(s)
- Lana M Chahine
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Kalpana Merchant
- Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Andrew Siderowf
- Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Todd Sherer
- The Michael J Fox Foundation for Parkinson's Research, New York, NY, USA
| | - Caroline Tanner
- Department of Neurology, Weill Institute for Neurosciences, University of San Francisco, San Francisco, CA, USA
| | | | - Tanya Simuni
- Department of Neurology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
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25
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Bates S, Dumoulin SO, Folkers PJM, Formisano E, Goebel R, Haghnejad A, Helmich RC, Klomp D, van der Kolk AG, Li Y, Nederveen A, Norris DG, Petridou N, Roell S, Scheenen TWJ, Schoonheim MM, Voogt I, Webb A. A vision of 14 T MR for fundamental and clinical science. MAGMA (NEW YORK, N.Y.) 2023; 36:211-225. [PMID: 37036574 PMCID: PMC10088620 DOI: 10.1007/s10334-023-01081-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/07/2022] [Revised: 03/20/2023] [Accepted: 03/21/2023] [Indexed: 04/11/2023]
Abstract
OBJECTIVE We outline our vision for a 14 Tesla MR system. This comprises a novel whole-body magnet design utilizing high temperature superconductor; a console and associated electronic equipment; an optimized radiofrequency coil setup for proton measurement in the brain, which also has a local shim capability; and a high-performance gradient set. RESEARCH FIELDS The 14 Tesla system can be considered a 'mesocope': a device capable of measuring on biologically relevant scales. In neuroscience the increased spatial resolution will anatomically resolve all layers of the cortex, cerebellum, subcortical structures, and inner nuclei. Spectroscopic imaging will simultaneously measure excitatory and inhibitory activity, characterizing the excitation/inhibition balance of neural circuits. In medical research (including brain disorders) we will visualize fine-grained patterns of structural abnormalities and relate these changes to functional and molecular changes. The significantly increased spectral resolution will make it possible to detect (dynamic changes in) individual metabolites associated with pathological pathways including molecular interactions and dynamic disease processes. CONCLUSIONS The 14 Tesla system will offer new perspectives in neuroscience and fundamental research. We anticipate that this initiative will usher in a new era of ultra-high-field MR.
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Affiliation(s)
- Steve Bates
- Tesla Engineering Ltd., Water Lane, Storrington, West Sussex, RH20 3EA, UK
| | - Serge O Dumoulin
- Spinoza Centre for Neuroimaging, Amsterdam, The Netherlands
- Computational Cognitive Neuroscience and Neuroimaging, Netherlands Institute for Neuroscience, Amsterdam, The Netherlands
- Experimental and Applied Psychology, Vrije University Amsterdam, Amsterdam, The Netherlands
- Experimental Psychology, Utrecht University, Utrecht, The Netherlands
| | | | - Elia Formisano
- Department of Cognitive Neuroscience, Maastricht University, Maastricht, The Netherlands
- Maastricht Brain Imaging Centre (MBIC), Maastricht University, Maastricht, The Netherlands
| | - Rainer Goebel
- Department of Cognitive Neuroscience, Maastricht University, Maastricht, The Netherlands
- Maastricht Brain Imaging Centre (MBIC), Maastricht University, Maastricht, The Netherlands
| | | | - Rick C Helmich
- Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Radboud University, Nijmegen, The Netherlands
- Department of Neurology, Center of Expertise for Parkinson and Movement Disorders, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Dennis Klomp
- Radiology Department, Center for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Anja G van der Kolk
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Yi Li
- Independent Researcher, Magdeburg, Germany
| | - Aart Nederveen
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, Amsterdam Cardiovascular Sciences, University of Amsterdam, Amsterdam, The Netherlands
| | - David G Norris
- Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Radboud University, Nijmegen, The Netherlands.
- Erwin L. Hahn Institute for Magnetic Resonance Imaging UNESCO World Cultural Heritage Zollverein, Kokereiallee 7, Building C84, 45141, Essen, Germany.
- Department of Clinical Neurophysiology (CNPH), Faculty Science and Technology, University of Twente, Enschede, The Netherlands.
| | - Natalia Petridou
- Radiology Department, Center for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Stefan Roell
- Neoscan Solutions GmbH, Joseph-von-Fraunhofer-Str. 6, 39106, Magdeburg, Germany
| | - Tom W J Scheenen
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Menno M Schoonheim
- Department of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Location VUmc, P.O. Box 7057, 1007 MB, Amsterdam, The Netherlands
| | - Ingmar Voogt
- Wavetronica, Padualaan 8, 3584 CH, Utrecht, The Netherlands
| | - Andrew Webb
- Department of Radiology, C.J. Gorter MRI Centre, Leiden University Medical Center, Albinusdreef 2, 2333 ZA, Leiden, The Netherlands
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26
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Li G, Zhu J, Wu X, Liu T, Hu P, Tian Y, Wang K. Baseline free water within the visual processing system predicts future psychosis in Parkinson disease. Eur J Neurol 2023; 30:892-901. [PMID: 36583634 DOI: 10.1111/ene.15668] [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: 11/14/2022] [Accepted: 12/08/2022] [Indexed: 12/31/2022]
Abstract
BACKGROUND AND PURPOSE As psychosis is associated with decreased quality of life, increased institutionalization, and mortality in Parkinson disease (PD), it is essential to identify individuals at risk for future psychosis. This longitudinal study aimed to investigate whether diffusion tensor imaging (DTI) metrics of white matter hold independent utility for predicting future psychosis in PD, and whether they could be combined with clinical predictors to improve the prognostication of PD psychosis. METHODS This study included 123 newly diagnosed PD patients collected in the Parkinson's Progression Markers Initiative. Tract-based spatial statistics were used to compare baseline DTI metrics between PD patients who developed psychosis and those who did not during follow-up. Binary logistic regression analyses were performed to identify the clinical and white matter markers predictive of psychosis. RESULTS Among DTI measures, both higher baseline whole brain (odds ratio [OR] = 1.711, p = 0.016) free water (FW) and visual processing system (OR = 1.680, p < 0.001) FW were associated with an increased risk of future psychosis. Baseline FW remained a significant indicator of future psychosis in PD after controlling for clinical predictors. Moreover, the accuracy of prediction of psychosis using clinical predictors alone (area under the curve [AUC] = 0.742, 95% confidence interval [CI] = 0.655-0.816) was significantly improved by the addition of the visual processing system FW (AUC = 0.856, 95% CI = 0.781-0.912; Delong method, p = 0.022). CONCLUSIONS Baseline FW of the visual processing system incurs an independent risk of future psychosis in PD, thus providing an opportunity for multiple-modality marker models to include a white matter marker.
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Affiliation(s)
- Guanglu Li
- Department of Neurology, First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Jiajia Zhu
- Department of Radiology, First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Xingqi Wu
- Department of Neurology, First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Tingting Liu
- Department of Neurology, First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Panpan Hu
- Department of Neurology, First Affiliated Hospital of Anhui Medical University, Hefei, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China
- Collaborative Innovation Center of Neuropsychiatric Disorder and Mental Health, Hefei, China
| | - Yanghua Tian
- Department of Neurology, First Affiliated Hospital of Anhui Medical University, Hefei, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China
- Collaborative Innovation Center of Neuropsychiatric Disorder and Mental Health, Hefei, China
- Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, China
- Department of Psychology and Sleep Medicine, Second Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Kai Wang
- Department of Neurology, First Affiliated Hospital of Anhui Medical University, Hefei, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei, China
- Collaborative Innovation Center of Neuropsychiatric Disorder and Mental Health, Hefei, China
- Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, China
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27
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Santos-García D, de Deus Fonticoba T, Cores Bartolomé C, Feal Painceiras MJ, Íñiguez-Alvarado MC, García Díaz I, Jesús S, Buongiorno MT, Planellas L, Cosgaya M, García Caldentey J, Caballol N, Legarda I, Hernández Vara J, Cabo I, López Manzanares L, González Aramburu I, Ávila Rivera MA, Gómez Mayordomo V, Nogueira V, Puente V, Dotor García-Soto J, Borrué C, Solano Vila B, Álvarez Sauco M, Vela L, Escalante S, Cubo E, Carrillo Padilla F, Martínez Castrillo JC, Sánchez Alonso P, Alonso Losada MG, López Ariztegui N, Gastón I, Kulisevsky J, Menéndez González M, Seijo M, Ruiz Martínez J, Valero C, Kurtis M, González Ardura J, Alonso Redondo R, Ordás C, López Díaz LM, McAfee D, Calopa M, Carrillo F, Escamilla Sevilla F, Freire-Alvarez E, Gómez Esteban JC, García Ramos R, Luquín MRI, Martínez-Torres I, Sesar Ignacio Á, Martinez-Martin P, Mir P. Staging Parkinson's Disease According to the MNCD (Motor/Non-motor/Cognition/Dependency) Classification Correlates with Disease Severity and Quality of Life. JOURNAL OF PARKINSON'S DISEASE 2023; 13:379-402. [PMID: 36911948 DOI: 10.3233/jpd-225073] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/09/2023]
Abstract
BACKGROUND Recently, a novel simple classification called MNCD, based on 4 axes (Motor; Non-motor; Cognition; Dependency) and 5 stages, has been proposed to classify Parkinson's disease (PD). OBJECTIVE Our aim was to apply the MNCD classification in a cohort of PD patients for the first time and also to analyze the correlation with quality of life (QoL) and disease severity. METHODS Data from the baseline visit of PD patients recruited from 35 centers in Spain from the COPPADIS cohort fromJanuary 2016 to November 2017 were used to apply the MNCD classification. Three instruments were used to assess QoL:1) the 39-item Parkinson's disease Questionnaire [PDQ-39]); PQ-10; the EUROHIS-QOL 8-item index (EUROHIS-QOL8). RESULTS Four hundred and thirty-nine PD patients (62.05±7.84 years old; 59% males) were included. MNCD stage was:stage 1, 8.4% (N = 37); stage 2, 62% (N = 272); stage 3, 28.2% (N = 124); stage 4-5, 1.4% (N = 6). A more advancedMNCD stage was associated with a higher score on the PDQ39SI (p < 0.0001) and a lower score on the PQ-10 (p< 0.0001) and EUROHIS-QOL8 (p< 0.0001). In many other aspects of the disease, such as disease duration, levodopa equivalent daily dose, motor symptoms, non-motor symptoms, and autonomy for activities of daily living, an association between the stage and severity was observed, with data indicating a progressive worsening related to disease progression throughout the proposed stages. CONCLUSION Staging PD according to the MNCD classification correlated with QoL and disease severity. The MNCD could be a proper tool to monitor the progression of PD.
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Affiliation(s)
| | | | | | | | | | - Iago García Díaz
- CHUAC, Complejo Hospitalario Universitario de A Coruña, A Coruña, Spain
| | - Silvia Jesús
- Unidad de Trastornos del Movimiento, Servicio de Neurología y Neurofisiología Clínica, Instituto de Biomedicina de Sevilla, Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, Seville, Spain.,CIBERNED (Centro de Investigación Biomédica en Red Enfermedades Neurodegenerativas), Spain
| | | | | | | | | | - Nuria Caballol
- Consorci Sanitari Integral, Hospital Moisés Broggi, Sant Joan Despí, Barcelona, Spain
| | - Ines Legarda
- Hospital Universitario Son Espases, Palma de Mallorca, Spain
| | - Jorge Hernández Vara
- CIBERNED (Centro de Investigación Biomédica en Red Enfermedades Neurodegenerativas), Spain.,Hospital Universitario Valld' Hebron, Barcelona, Spain
| | - Iria Cabo
- Complejo Hospitalario Universitario de Pontevedra (CHOP), Pontevedra, Spain
| | | | - Isabel González Aramburu
- CIBERNED (Centro de Investigación Biomédica en Red Enfermedades Neurodegenerativas), Spain.,Hospital Universitario Marqués de Valdecilla, Santander Spain
| | - Maria A Ávila Rivera
- Consorci Sanitari Integral, Hospital General de LΉospitalet, LΉospitalet de Llobregat, Barcelona,Spain
| | | | | | | | | | | | - Berta Solano Vila
- Institut d'Assistència Sanitària (IAS) - Institut Cataè de la Salut, Girona, Spain
| | | | - Lydia Vela
- Fundación Hospital de Alcorcón, Madrid,Spain
| | - Sonia Escalante
- Hospital de Tortosa Verge de la Cinta (HTVC), Tortosa, Tarragona, Spain
| | - Esther Cubo
- Complejo Asistencial Universitario de Burgos, Burgos, Spain
| | | | - Juan C Martínez Castrillo
- Unidad de Trastornos del Movimiento, Servicio de Neurología y Neurofisiología Clínica, Instituto de Biomedicina de Sevilla, Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, Seville, Spain
| | | | - Maria G Alonso Losada
- Unidad de Trastornos del Movimiento, Servicio de Neurología y Neurofisiología Clínica, Instituto de Biomedicina de Sevilla, Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, Seville, Spain
| | - Nuria López Ariztegui
- CIBERNED (Centro de Investigación Biomédica en Red Enfermedades Neurodegenerativas), Spain
| | - Itziar Gastón
- Hospital Universitari Mutua de Terrassa, Terrassa, Barcelona, Spain
| | - Jaime Kulisevsky
- CIBERNED (Centro de Investigación Biomédica en Red Enfermedades Neurodegenerativas), Spain.,Clínica del Pilar, Barcelona, Spain
| | | | - Manuel Seijo
- Complejo Hospitalario Universitario de Pontevedra (CHOP), Pontevedra, Spain
| | | | - Caridad Valero
- Consorci Sanitari Integral, Hospital Moisés Broggi, Sant Joan Despí, Barcelona, Spain
| | - Mónica Kurtis
- Hospital Universitario Son Espases, Palma de Mallorca, Spain
| | | | | | - Carlos Ordás
- Hospital Universitario La Princesa, Madrid, Spain, Pontevedra, Spain
| | - Luis M López Díaz
- Unidad de Trastornos del Movimiento, Servicio de Neurología y Neurofisiología Clínica, Instituto de Biomedicina de Sevilla, Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, Seville, Spain
| | - Darrian McAfee
- Hospital Universitario Marqués de Valdecilla, Santander Spain
| | - Matilde Calopa
- Consorci Sanitari Integral, Hospital General de LΉospitalet, LΉospitalet de Llobregat, Barcelona,Spain
| | - Fátima Carrillo
- Unidad de Trastornos del Movimiento, Servicio de Neurología y Neurofisiología Clínica, Instituto de Biomedicina de Sevilla, Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, Seville, Spain.,CIBERNED (Centro de Investigación Biomédica en Red Enfermedades Neurodegenerativas), Spain
| | | | | | | | | | | | | | | | - Pablo Martinez-Martin
- CIBERNED (Centro de Investigación Biomédica en Red Enfermedades Neurodegenerativas), Spain
| | - Pablo Mir
- Unidad de Trastornos del Movimiento, Servicio de Neurología y Neurofisiología Clínica, Instituto de Biomedicina de Sevilla, Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, Seville, Spain.,CIBERNED (Centro de Investigación Biomédica en Red Enfermedades Neurodegenerativas), Spain
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28
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Sasikumar S, Strafella AP. Structural and Molecular Imaging for Clinically Uncertain Parkinsonism. Semin Neurol 2023; 43:95-105. [PMID: 36878467 DOI: 10.1055/s-0043-1764228] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/08/2023]
Abstract
Neuroimaging is an important adjunct to the clinical assessment of Parkinson disease (PD). Parkinsonism can be challenging to differentiate, especially in early disease stages, when it mimics other movement disorders or when there is a poor response to dopaminergic therapies. There is also a discrepancy between the phenotypic presentation of degenerative parkinsonism and the pathological outcome. The emergence of more sophisticated and accessible neuroimaging can identify molecular mechanisms of PD, the variation between clinical phenotypes, and the compensatory mechanisms that occur with disease progression. Ultra-high-field imaging techniques have improved spatial resolution and contrast that can detect microstructural changes, disruptions in neural pathways, and metabolic and blood flow alterations. We highlight the imaging modalities that can be accessed in clinical practice and recommend an approach to the diagnosis of clinically uncertain parkinsonism.
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Affiliation(s)
- Sanskriti Sasikumar
- Morton and Gloria Shulman Movement Disorder Unit and Edmond J. Safra Parkinson Disease Program, Neurology Division, Department of Medicine, University of Toronto, Toronto Western Hospital, UHN, Ontario, Canada
| | - Antonio P Strafella
- Morton and Gloria Shulman Movement Disorder Unit and Edmond J. Safra Parkinson Disease Program, Neurology Division, Department of Medicine, University of Toronto, Toronto Western Hospital, UHN, Ontario, Canada.,Krembil Brain Institute, University Health Network and Brain Health Imaging Centre, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, University of Toronto, Toronto, Ontario, Canada
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29
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The challenging quest of neuroimaging: From clinical to molecular-based subtyping of Parkinson disease and atypical parkinsonisms. HANDBOOK OF CLINICAL NEUROLOGY 2023; 192:231-258. [PMID: 36796945 DOI: 10.1016/b978-0-323-85538-9.00004-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/16/2023]
Abstract
The current framework of Parkinson disease (PD) focuses on phenotypic classification despite its considerable heterogeneity. We argue that this method of classification has restricted therapeutic advances and therefore limited our ability to develop disease-modifying interventions in PD. Advances in neuroimaging have identified several molecular mechanisms relevant to PD, variation within and between clinical phenotypes, and potential compensatory mechanisms with disease progression. Magnetic resonance imaging (MRI) techniques can detect microstructural changes, disruptions in neural pathways, and metabolic and blood flow alterations. Positron emission tomography (PET) and single-photon emission computed tomography (SPECT) imaging have informed the neurotransmitter, metabolic, and inflammatory dysfunctions that could potentially distinguish disease phenotypes and predict response to therapy and clinical outcomes. However, rapid advancements in imaging techniques make it challenging to assess the significance of newer studies in the context of new theoretical frameworks. As such, there needs to not only be a standardization of practice criteria in molecular imaging but also a rethinking of target approaches. In order to harness precision medicine, a coordinated shift is needed toward divergent rather than convergent diagnostic approaches that account for interindividual differences rather than similarities within an affected population, and focus on predictive patterns rather than already lost neural activity.
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30
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Khan MA, Haider N, Singh T, Bandopadhyay R, Ghoneim MM, Alshehri S, Taha M, Ahmad J, Mishra A. Promising biomarkers and therapeutic targets for the management of Parkinson's disease: recent advancements and contemporary research. Metab Brain Dis 2023; 38:873-919. [PMID: 36807081 DOI: 10.1007/s11011-023-01180-z] [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: 08/11/2022] [Accepted: 02/04/2023] [Indexed: 02/23/2023]
Abstract
Parkinson's disease (PD) is one of the progressive neurological diseases which affect around 10 million population worldwide. The clinical manifestation of motor symptoms in PD patients appears later when most dopaminergic neurons have degenerated. Thus, for better management of PD, the development of accurate biomarkers for the early prognosis of PD is imperative. The present work will discuss the potential biomarkers from various attributes covering biochemical, microRNA, and neuroimaging aspects (α-synuclein, DJ-1, UCH-L1, β-glucocerebrosidase, BDNF, etc.) for diagnosis, recent development in PD management, and major limitations with current and conventional anti-Parkinson therapy. This manuscript summarizes potential biomarkers and therapeutic targets, based on available preclinical and clinical evidence, for better management of PD.
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Affiliation(s)
- Mohammad Ahmed Khan
- Department of Pharmacology, School of Pharmaceutical Education and Research, Jamia Hamdard, New Delhi, 110062, India
| | - Nafis Haider
- Prince Sultan Military College of Health Sciences, Dhahran, 34313, Saudi Arabia
| | - Tanveer Singh
- Department of Neuroscience and Experimental Therapeutics, College of Medicine, Texas A&M University Health Science Center, Bryan, TX, 77807, USA
| | - Ritam Bandopadhyay
- Department of Pharmacology, School of Pharmaceutical Sciences, Lovely Professional University, Phagwara, 144411, Punjab, India
| | - Mohammed M Ghoneim
- Department of Pharmacy Practice, College of Pharmacy, AlMaarefa University, Ad Diriyah, 13713, Saudi Arabia
| | - Sultan Alshehri
- Department of Pharmaceutics, College of Pharmacy, King Saud University, Riyadh, 11451, Saudi Arabia
| | - Murtada Taha
- Prince Sultan Military College of Health Sciences, Dhahran, 34313, Saudi Arabia
| | - Javed Ahmad
- Department of Pharmaceutics, College of Pharmacy, Najran University, Najran, 11001, Saudi Arabia
| | - Awanish Mishra
- Department of Pharmacology and Toxicology, National Institute of Pharmaceutical Education and Research (NIPER) - Guwahati, Sila Katamur (Halugurisuk), Kamrup, Changsari, Assam, 781101, India.
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31
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Su D, Gan Y, Zhang Z, Cui Y, Zhang Z, Liu Z, Wang Z, Zhou J, Sossi V, Stoessl AJ, Wu T, Jing J, Feng T. Multimodal Imaging of Substantia Nigra in Parkinson's Disease with Levodopa-Induced Dyskinesia. Mov Disord 2023; 38:616-625. [PMID: 36799459 DOI: 10.1002/mds.29320] [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: 09/07/2022] [Revised: 12/01/2022] [Accepted: 12/20/2022] [Indexed: 02/18/2023] Open
Abstract
BACKGROUND Degeneration of the substantia nigra (SN) may contribute to levodopa-induced dyskinesia (LID) in Parkinson's disease (PD), but the exact characteristics of SN in LID remain unclear. OBJECTIVE To further understand the pathogenesis of patients with PD with LID (PD-LID), we explored the structural and functional characteristics of SN in PD-LID using multimodal magnetic resonance imaging (MRI). METHODS Twenty-nine patients with PD-LID, 37 patients with PD without LID (PD-nLID), and 28 healthy control subjects underwent T1-weighted MRI, quantitative susceptibility mapping, neuromelanin-sensitive MRI, multishell diffusion MRI, and resting-state functional MRI. Different measures characterizing the SN were obtained using a region of interest-based approach. RESULTS Compared with patients with PD-nLID and healthy control subjects, the quantitative susceptibility mapping values of SN pars compacta (SNpc) were significantly higher (P = 0.049 and P = 0.00002), and the neuromelanin contrast-to-noise ratio values in SNpc were significantly lower (P = 0.012 and P = 0.000002) in PD-LID. The intracellular volume fraction of the posterior SN in PD-LID was significantly higher compared with PD-nLID (P = 0.037). Resting-state fMRI indicated that PD-LID in the medication off state showed higher functional connectivity between the SNpc and putamen compared with PD-nLID (P = 0.031), and the functional connectivity changes in PD-LID were positively correlated with Unified Dyskinesia Rating Scale total scores (R = 0.427, P = 0.042). CONCLUSIONS Our multimodal imaging findings highlight greater neurodegeneration in SN and the altered nigrostriatal connectivity in PD-LID. These characteristics provide a new perspective into the role of SN in the pathophysiological mechanisms underlying PD-LID. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Dongning Su
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Yawen Gan
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Zhe Zhang
- China National Clinical Research Center for Neurological Diseases, Beijing, China.,Tiantan Neuroimaging Center of Excellence, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Yusha Cui
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Zhijin Zhang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Zhu Liu
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Zhan Wang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Junhong Zhou
- Hinda and Arthur Marcus Institute for Aging Research, Hebrew SeniorLife, Roslindale, Boston, Massachusetts, USA.,Harvard Medical School, Boston, Massachusetts, USA
| | - Vesna Sossi
- Department of Physics and Astronomy, University of British Columbia, Vancouver, British Columbia, Canada.,Djavad Mowafaghian Centre for Brain Health, Pacific Parkinson's Research Centre, University of British Columbia & Vancouver Coastal Health, Vancouver, British Columbia, Canada
| | - A Jon Stoessl
- Djavad Mowafaghian Centre for Brain Health, Pacific Parkinson's Research Centre, University of British Columbia & Vancouver Coastal Health, Vancouver, British Columbia, Canada.,Division of Neurology, Department of Medicine, University of British Columbia, Vancouver, British Columbia, Canada
| | - Tao Wu
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Jing Jing
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Tiantan Neuroimaging Center of Excellence, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Tao Feng
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China
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32
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Zhang D, Shi Y, Yao J, Zhou L, Wei H, Liu J, Tong Q, Ma L, He H, Wu T. Free-Water Imaging of the Substantia Nigra in GBA Pathogenic Variant Carriers. Mov Disord 2023. [PMID: 36797645 DOI: 10.1002/mds.29356] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Revised: 01/30/2023] [Accepted: 02/01/2023] [Indexed: 02/18/2023] Open
Abstract
BACKGROUND Pathogenic variants in the glucocerebrosidase gene (GBA) have been identified as the most common genetic risk factor for Parkinson's disease (PD). However, the features of substantia nigra damage in GBA pathogenic variant carriers remain unclear. OBJECTIVE We aimed to evaluate the microstructural changes in the substantia nigra in non-manifesting GBA pathogenic variant carriers (GBA-NMC) and PD patients with GBA pathogenic variant (GBA-PD) with free-water imaging. METHODS First, we compared free water values in the posterior substantia nigra between non-manifesting non-carriers (NMNC, n = 29), GBA-NMC (n = 26), and GBA-PD (n = 16). Then, free water values in the posterior substantia nigra were compared between GBA-PD and early- (n = 19) and late-onset (n = 40) idiopathic PD (iPD) patients. Furthermore, we examined whether the baseline free water values could predict the progressions of clinical symptoms. RESULTS The free water values in the posterior substantia nigra were significantly higher in the GBA-NMC and GBA-PD groups compared to NMNC, and were significantly increased in the GBA-PD group than both early- and late-onset iPD. Free water values in the posterior substantia nigra could predict the progression of anxiety and cognitive decline in GBA-NMC and GBA-PD groups. CONCLUSIONS We demonstrate that free water values are elevated in the substantia nigra and predict the development of non-motor symptoms in GBA-NMC and GBA-PD. Our findings demonstrate that a significant nigral impairment already exists in GBA-NMC, and nigral injury may be more severe in GBA-PD than in iPD. These results support that free-water imaging can as a potential early marker of substantia nigra damage. © 2023 International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Dongling Zhang
- Center for Movement Disorders, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Parkinson's Disease Center, Beijing Institute for Brain Disorders, Capital Medical University, Beijing, China
| | - Yuting Shi
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Junye Yao
- Center for Brain Imaging Science and Technology, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
| | - Liche Zhou
- Department of Neurology and Institute of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Hongjiang Wei
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Jun Liu
- Department of Neurology and Institute of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Qiqi Tong
- Research Center for Healthcare Data Science, Zhejiang Lab, Hangzhou, China
| | - Lingyan Ma
- Center for Movement Disorders, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Parkinson's Disease Center, Beijing Institute for Brain Disorders, Capital Medical University, Beijing, China
| | - Hongjian He
- Center for Brain Imaging Science and Technology, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China.,School of Physics, Zhejiang University, Hangzhou, China
| | - Tao Wu
- Center for Movement Disorders, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Parkinson's Disease Center, Beijing Institute for Brain Disorders, Capital Medical University, Beijing, China
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Pietracupa S, Belvisi D, Piervincenzi C, Tommasin S, Pasqua G, Petsas N, De Bartolo MI, Fabbrini A, Costanzo M, Manzo N, Berardelli A, Pantano P. White and gray matter alterations in de novo PD patients: which matter most? J Neurol 2023; 270:2734-2742. [PMID: 36773059 DOI: 10.1007/s00415-023-11607-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2022] [Revised: 02/02/2023] [Accepted: 02/03/2023] [Indexed: 02/12/2023]
Abstract
OBJECTIVES This paper aimed to identify white matter (WM) and gray matter (GM) abnormalities in a sample of early PD patients, and their correlations with motor and non-motor symptom severity. METHODS We enrolled 62 de novo PD patients and 31 healthy subjects. Disease severity and non-motor symptom burden were assessed by the Unified Parkinson's Disease Rating Scale part III and the Non-Motor Symptoms Scale, respectively. Cognitive performance was assessed using Montreal Cognitive Assessment and Frontal Assessment Battery. All subjects underwent a 3-Tesla MRI protocol. MRI analyses included tract-based spatial statistics, cortical thickness, and subcortical and cerebellar volumetry. RESULTS In comparison to control subjects, PD patients exhibited lower fractional anisotropy and higher mean, axial, and radial diffusivity in most WM bundles, including corticospinal tracts, the internal and external capsule, the anterior and posterior thalamic radiations, the genu and body of the corpus callosum, cerebellar peduncles, and superior and inferior longitudinal and fronto-occipital fasciculi. Correlations between Montreal Cognitive Assessment scores and fractional anisotropy values in the right posterior thalamic radiation, left superior corona radiata, right inferior-fronto-occipital fasciculus, left inferior longitudinal fasciculus, bilateral anterior thalamic radiations, and bilateral superior longitudinal fasciculi were found. Smaller cerebellar volumes in early PD patients in the left and right crus I were also found. No GM changes were present in subcortical or cortical regions. CONCLUSION The combined evaluation of WM and GM in the same patient sample demonstrates that WM microstructural abnormalities precede GM structural changes in early PD patients.
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Affiliation(s)
| | - Daniele Belvisi
- IRCCS Neuromed, Pozzilli, IS, Italy.,Department of Human Neuroscience, Sapienza University of Rome, Rome, Italy
| | | | - Silvia Tommasin
- Department of Human Neuroscience, Sapienza University of Rome, Rome, Italy
| | - Gabriele Pasqua
- Department of Human Neuroscience, Sapienza University of Rome, Rome, Italy
| | | | | | - Andrea Fabbrini
- Department of Human Neuroscience, Sapienza University of Rome, Rome, Italy
| | | | | | - Alfredo Berardelli
- IRCCS Neuromed, Pozzilli, IS, Italy.,Department of Human Neuroscience, Sapienza University of Rome, Rome, Italy
| | - Patrizia Pantano
- IRCCS Neuromed, Pozzilli, IS, Italy.,Department of Human Neuroscience, Sapienza University of Rome, Rome, Italy
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Chan L, Chung CC, Hsieh YC, Wu RM, Hong CT. Plasma extracellular vesicle tau, β-amyloid, and α-synuclein and the progression of Parkinson's disease: a follow-up study. Ther Adv Neurol Disord 2023; 16:17562864221150329. [PMID: 36741351 PMCID: PMC9896092 DOI: 10.1177/17562864221150329] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Accepted: 12/22/2022] [Indexed: 02/04/2023] Open
Abstract
Background Plasma extracellular vesicle (EV) contents are promising biomarkers of Parkinson's disease (PD). The pathognomonic proteins of PD, including α-synuclein, tau, and β-amyloid, are altered in people with PD (PwP) and are associated with clinical presentation in previous cross-sectional studies. However, the dynamic changes in these plasma EV proteins in PwP and their correlation with clinical progression remain unclear. Objective We investigated the dynamic changes in plasma EV α-synuclein, tau, and β-amyloid and their correlation with/prediction of clinical progression in PwP. Design A cohort study. Methods In total, 103 PwP and 37 healthy controls (HCs) completed baseline assessment and 1-year follow-up. Clinical assessments included Unified Parkinson's Disease Rating Scale (UPDRS) parts II and III, Mini-Mental State Examination (MMSE), and Montreal Cognitive Assessment (MoCA). Plasma EVs were isolated, and immunomagnetic reduction-based immunoassay was used to assess α-synuclein, tau, and β-amyloid 1-42 (Aβ1-42) levels within the EVs. Results Compared with HCs, significant differences were noted in the annual changes in all three EV pathognomonic proteins in PwP. Although the absolute changes in plasma EV pathognomonic proteins did not significantly correlate with clinical changes, PwP with elevated baseline plasma EV tau (upper-half) levels demonstrated significantly greater decline in motor and cognition, and increased plasma EV α-synuclein levels were associated with postural instability and the gait disturbance motor subtype. For PwP with elevated levels of all three biomarkers, clinical deterioration was significant, as indicated by UPDRS-II scores, postural instability and gait disturbance subscores of UPDRS-III, and MMSE score. Conclusion The combination of plasma EV α-synuclein, tau, and Aβ1-42 may identify PwP with a high risk of deterioration. Our findings can elucidate the interaction between these pathognomonic proteins, and they may serve as treatment response markers and can be applied in treatment approaches for disease modification.
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Affiliation(s)
| | | | - Yi-Chen Hsieh
- Ph.D. Program in Medical Neuroscience, College
of Medical Science and Technology, Taipei Medical University, Taipei
| | - Ruey-Meei Wu
- Department of Neurology, Centre of Parkinson
and Movement Disorders, National Taiwan University Hospital, College of
Medicine, National Taiwan University, Taipei, Taiwan
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35
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Kerstens VS, Fazio P, Sundgren M, Brumberg J, Halldin C, Svenningsson P, Varrone A. Longitudinal DAT changes measured with [ 18F]FE-PE2I PET in patients with Parkinson's disease; a validation study. Neuroimage Clin 2023; 37:103347. [PMID: 36822016 PMCID: PMC9978841 DOI: 10.1016/j.nicl.2023.103347] [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: 10/13/2022] [Revised: 02/07/2023] [Accepted: 02/10/2023] [Indexed: 02/13/2023]
Abstract
BACKGROUND Dopamine transporter (DAT) PET provides higher resolution than DAT SPECT and opportunity for integrated imaging with MRI. The radioligand [18F]FE-PE2I is highly selective for the DAT, and PET measurements with this radioligand have good reliability and repeatability in patients with non-advanced Parkinson's disease. OBJECTIVES To validate [18F]FE-PE2I PET as measurement tool of longitudinal DAT changes in patients with Parkinson's disease. METHODS Thirty-seven subjects with Parkinson's disease (Hoehn and Yahr stage < 3) were included in a longitudinal PET study with [18F]FE-PE2I. DAT availability (BPND) in the caudate nucleus, putamen, sensorimotor striatum, and substantia nigra, was estimated with parametric imaging using Logan graphical analysis and cerebellum as reference region. For comparison with DAT-SPECT literature, sample size calculations for disease intervention studies were made. RESULTS Baseline and follow-up PET data (interval: 2.3 ± 0.5 years) were available for 25 patients (9 females, 16 males). Median age was 64.7 years (range 46-76); symptom duration: 3 years (0.25-14); Hoehn and Yahr stage (H&Y): 1 (1-2). Annualized DAT decline and effect size were: -8.5 ± 6.6 % and 1.08 for caudate nucleus; -7.1 ± 6.1 % and 1.02 for putamen; -8.3 ± 8.5 % and 0.99 for sensorimotor striatum; -0.11 ± 9.3 % and 0.11 for substantia nigra. The estimated minimum sample size needed for a treatment trial using [18F]FE-PE2I PET as imaging marker is 2-3 times lower than is reported in literature on [123I]FP-CIT SPECT. CONCLUSIONS Longitudinal [18F]FE-PE2I PET measurements in non-advanced PD demonstrate a striatal DAT decline consistent with previous SPECT and PET studies. No obvious changes of DAT availability were observed in the substantia nigra, indicating perhaps slower progression or compensatory changes. The effect sizes were numerically larger than reported in the literature for other DAT radioligands, suggesting that [18F]FE-PE2I might detect smaller DAT changes, and can be well used as progression marker in clinical trials.
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Affiliation(s)
- V S Kerstens
- Department of Clinical Neuroscience, Centre for Psychiatry Research, Karolinska Institutet and Stockholm Health Care Services, Stockholm, Sweden.
| | - P Fazio
- Department of Clinical Neuroscience, Centre for Psychiatry Research, Karolinska Institutet and Stockholm Health Care Services, Stockholm, Sweden
| | - M Sundgren
- Karolinska University Hospital, Neuro Department, Stockholm, Sweden
| | - J Brumberg
- Department of Clinical Neuroscience, Centre for Psychiatry Research, Karolinska Institutet and Stockholm Health Care Services, Stockholm, Sweden
| | - C Halldin
- Department of Clinical Neuroscience, Centre for Psychiatry Research, Karolinska Institutet and Stockholm Health Care Services, Stockholm, Sweden
| | - P Svenningsson
- Karolinska University Hospital, Neuro Department, Stockholm, Sweden
| | - A Varrone
- Department of Clinical Neuroscience, Centre for Psychiatry Research, Karolinska Institutet and Stockholm Health Care Services, Stockholm, Sweden
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36
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Jing XZ, Li GY, Wu YP, Yuan XZ, Luo XG, Chen JL, Taximaimaiti R, Wang XP, Li JQ. Free water imaging as a novel biomarker in Wilson's disease: A cross-sectional study. Parkinsonism Relat Disord 2023; 106:105234. [PMID: 36481719 DOI: 10.1016/j.parkreldis.2022.105234] [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: 10/05/2022] [Revised: 11/27/2022] [Accepted: 11/30/2022] [Indexed: 12/03/2022]
Abstract
BACKGROUND The bi-tensor free water imaging may provide more specific information in detecting microstructural brain tissue alterations than conventional single tensor diffusion tensor imaging. The study aimed to investigate microstructural changes in deep gray matter (DGM) nuclei of Wilson's disease (WD) using a bi-tensor free water imaging and whether the findings correlate with the neurological impairment in WD patients. METHODS The study included 29 WD patients and 25 controls. Free water and free water corrected fractional anisotropy (FAT) in DGM nuclei of WD patients were calculated. The correlations of free water and FAT with the Unified WD Rating Scale (UWDRS) neurological subscale of WD patients were performed. RESULTS Free water and FAT values were significantly increased in multiple DGM nuclei of neurological WD patients compared to controls. WD patients with normal appearing on conventional MRI also had significantly higher free water and FAT values in multiple DGM nuclei than controls. Positive correlations were noted between the UWDRS neurological subscores and free water values of the putamen and pontine tegmentum as well as FAT values of the dentate nucleus, red nucleus, and globus pallidus. In addition, the measured free water and FAT values of specific structures also showed a positive correlation with specific clinical symptoms in neurological WD patients, such as dysarthria, parkinsonian signs, tremor, dystonia, and ataxia. CONCLUSIONS Free water imaging detects microstructural changes in both normal and abnormal appearing DGM nuclei of WD patients. Free water imaging indices were correlated with the severity of neurological impairment in WD patients.
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Affiliation(s)
- Xiao-Zhong Jing
- Department of Neurology, Jiading Branch of Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Department of Neurology, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Gai-Ying Li
- Shanghai Key Laboratory of Magnetic Resonance, School of Physics and Electronic Science, East China Normal University, Shanghai, China.
| | - Yu-Peng Wu
- Shanghai Key Laboratory of Magnetic Resonance, School of Physics and Electronic Science, East China Normal University, Shanghai, China.
| | - Xiang-Zhen Yuan
- Department of Neurology, Weifang People's Hospital, Weifang, Shandong, China.
| | - Xing-Guang Luo
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA.
| | - Jia-Lin Chen
- Shanghai Key Laboratory of Magnetic Resonance, School of Physics and Electronic Science, East China Normal University, Shanghai, China.
| | - Reyisha Taximaimaiti
- Department of Neurology, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Xiao-Ping Wang
- Department of Neurology, Jiading Branch of Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Department of Neurology, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Jian-Qi Li
- Shanghai Key Laboratory of Magnetic Resonance, School of Physics and Electronic Science, East China Normal University, Shanghai, China.
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37
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Huang P, Zhang M. Magnetic Resonance Imaging Studies of Neurodegenerative Disease: From Methods to Translational Research. Neurosci Bull 2023; 39:99-112. [PMID: 35771383 PMCID: PMC9849544 DOI: 10.1007/s12264-022-00905-x] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2022] [Accepted: 05/07/2022] [Indexed: 01/22/2023] Open
Abstract
Neurodegenerative diseases (NDs) have become a significant threat to an aging human society. Numerous studies have been conducted in the past decades to clarify their pathologic mechanisms and search for reliable biomarkers. Magnetic resonance imaging (MRI) is a powerful tool for investigating structural and functional brain alterations in NDs. With the advantages of being non-invasive and non-radioactive, it has been frequently used in both animal research and large-scale clinical investigations. MRI may serve as a bridge connecting micro- and macro-level analysis and promoting bench-to-bed translational research. Nevertheless, due to the abundance and complexity of MRI techniques, exploiting their potential is not always straightforward. This review aims to briefly introduce research progress in clinical imaging studies and discuss possible strategies for applying MRI in translational ND research.
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Affiliation(s)
- Peiyu Huang
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310009 China
| | - Minming Zhang
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310009 China
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38
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Weil EL, Nakawah MO, Masdeu JC. Advances in the neuroimaging of motor disorders. HANDBOOK OF CLINICAL NEUROLOGY 2023; 195:359-381. [PMID: 37562878 DOI: 10.1016/b978-0-323-98818-6.00039-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/12/2023]
Abstract
Neuroimaging is a valuable adjunct to the history and examination in the evaluation of motor system disorders. Conventional imaging with computed tomography or magnetic resonance imaging depicts important anatomic information and helps to identify imaging patterns which may support diagnosis of a specific motor disorder. Advanced imaging techniques can provide further detail regarding volume, functional, or metabolic changes occurring in nervous system pathology. This chapter is an overview of the advances in neuroimaging with particular emphasis on both standard and less well-known advanced imaging techniques and findings, such as diffusion tensor imaging or volumetric studies, and their application to specific motor disorders. In addition, it provides reference to emerging imaging biomarkers in motor system disorders such as Parkinson disease, amyotrophic lateral sclerosis, and Huntington disease, and briefly reviews the neuroimaging findings in different causes of myelopathy and peripheral nerve disorders.
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Affiliation(s)
- Erika L Weil
- Department of Neurology, University of Michigan, Ann Arbor, MI, United States; Stanley H. Appel Department of Neurology, Houston Methodist Hospital, Houston, TX, United States.
| | - Mohammad Obadah Nakawah
- Stanley H. Appel Department of Neurology, Houston Methodist Hospital, Houston, TX, United States; Department of Neurology, Weill Cornell Medicine, New York, NY, United States
| | - Joseph C Masdeu
- Stanley H. Appel Department of Neurology, Houston Methodist Hospital, Houston, TX, United States; Department of Neurology, Weill Cornell Medicine, New York, NY, United States
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39
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Tinaz S. Magnetic resonance imaging modalities aid in the differential diagnosis of atypical parkinsonian syndromes. Front Neurol 2023; 14:1082060. [PMID: 36816565 PMCID: PMC9932598 DOI: 10.3389/fneur.2023.1082060] [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: 10/27/2022] [Accepted: 01/16/2023] [Indexed: 02/05/2023] Open
Abstract
Accurate and timely diagnosis of atypical parkinsonian syndromes (APS) remains a challenge. Especially early in the disease course, the clinical manifestations of the APS overlap with each other and with those of idiopathic Parkinson's disease (PD). Recent advances in magnetic resonance imaging (MRI) technology have introduced promising imaging modalities to aid in the diagnosis of APS. Some of these MRI modalities are also included in the updated diagnostic criteria of APS. Importantly, MRI is safe for repeated use and more affordable and accessible compared to nuclear imaging. These advantages make MRI tools more appealing for diagnostic purposes. As the MRI field continues to advance, the diagnostic use of these techniques in APS, alone or in combination, are expected to become commonplace in clinical practice.
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Affiliation(s)
- Sule Tinaz
- Division of Movement Disorders, Department of Neurology, Yale School of Medicine, New Haven, CT, United States
- Department of Neurology, Clinical Neurosciences Imaging Center, Yale School of Medicine, New Haven, CT, United States
- *Correspondence: Sule Tinaz ✉
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Zhang D, Zhou L, Shi Y, Liu J, Wei H, Tong Q, He H, Wu T. Increased Free Water in the Substantia Nigra in Asymptomatic LRRK2 G2019S Mutation Carriers. Mov Disord 2023; 38:138-142. [PMID: 36253640 DOI: 10.1002/mds.29253] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2022] [Revised: 09/05/2022] [Accepted: 09/26/2022] [Indexed: 01/21/2023] Open
Abstract
BACKGROUND The alteration of substantia nigra (SN) degeneration in populations at risk of Parkinson's disease (PD) is unclear. OBJECTIVE We investigated free water (FW) values in the posterior SN (pSN) in asymptomatic LRRK2 G2019S mutation carriers. METHODS We analyzed diffusion imaging data from 28 asymptomatic LRRK2 G2019S mutation carriers and 30 healthy controls (HCs), whereas 11 asymptomatic LRRK2 G2019S carriers and 11 HCs were followed up. FW values in the pSN were measured and compared between the groups. The relationship between longitudinal changes in FW in the pSN and dopamine transporter striatal binding ratio (SBR) was analyzed. RESULTS FW values in the pSN were significantly elevated and kept increasing during follow-up in asymptomatic LRRK2 G2019S carriers. There was a negative correlation between FW changes in the left pSN and SBR changes in the left putamen. CONCLUSION FW in the pSN has the potential to be a progression imaging marker of early dopaminergic degeneration in the population at risk of PD. © 2022 International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Dongling Zhang
- Center for Movement Disorders, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Parkinson's Disease Center, Beijing Institute for Brain Disorders, Capital Medical University, Beijing, China
| | - Liche Zhou
- Department of Neurology and Institute of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yuting Shi
- Institute for Medical Imaging Technology, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Jun Liu
- Department of Neurology and Institute of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Hongjiang Wei
- Institute for Medical Imaging Technology, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Qiqi Tong
- Research Center for Healthcare Data Science, Zhejiang Lab, Hangzhou, Zhejiang, China
| | - Hongjian He
- Center for Brain Imaging Science and Technology, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China
| | - Tao Wu
- Center for Movement Disorders, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Parkinson's Disease Center, Beijing Institute for Brain Disorders, Capital Medical University, Beijing, China
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Zhang D, Yao J, Sun J, Tong Q, Zhu S, Wang J, Chen L, Ma J, He H, Wu T. Quantitative Susceptibility Mapping and Free Water Imaging of Substantia Nigra in Parkinson's Disease. JOURNAL OF PARKINSON'S DISEASE 2022; 12:2469-2478. [PMID: 36404557 DOI: 10.3233/jpd-223499] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND The utility of imaging methods to detect iron content in the substantia nigra pars compacta (SNc) and free water imaging in the posterior substantia nigra (pSN) has the potential to be imaging markers for the detection of Parkinson's disease (PD). OBJECTIVE This study aimed to compare the discriminative power of above methods, and whether the combination can improve the diagnostic potential of PD. METHODS Quantitative susceptibility mapping (QSM) and diffusion-weighted data were obtained from 41 healthy controls (HC), 37 patients with idiopathic REM sleep behavior disorder (RBD), and 65 patients with PD. Mean QSM values of bilateral SNc and mean isotropic volume fraction (Viso) values of bilateral pSN (mean QSM|Viso values of bilateral SNc|pSN) were separately calculated and compared among the groups. RESULTS Mean QSM|Viso values of bilateral SNc|pSN were significantly higher for RBD and PD patients compared to HC and were significantly higher in PD patients than in RBD patients. The power of the mean QSM|Viso values of bilateral SNc|pSN and combined mean QSM and Viso values was 0.873, 0.870, and 0.961 in discriminating PD and HC, 0.779, 0.719, and 0.864 in discriminating RBD from HC, 0.634, 0.636, and 0.689 in discriminating PD and RBD patients. CONCLUSION QSM and free water imaging have similar discriminative power in the detection of prodromal and clinical PD, while combination of these two methods increases discriminative power. Our findings suggest that the combination of QSM and free water imaging has the potential to become an imaging marker for the diagnosis of PD.
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Affiliation(s)
- Dongling Zhang
- Center for Movement Disorders, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Junye Yao
- Center for Brain Imaging Science and Technology, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China
| | - Junyan Sun
- Center for Movement Disorders, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Qiqi Tong
- Research Center for Healthcare Data Science, Zhejiang Lab, Hangzhou, Zhejiang, China
| | - Silei Zhu
- Wellcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Junling Wang
- Center for Movement Disorders, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Lili Chen
- Center for Movement Disorders, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Jinghong Ma
- Department of Neurobiology, Xuanwu Hospital of Capital Medical University, Beijing Institute of Geriatrics, Beijing, China
| | - Hongjian He
- Center for Brain Imaging Science and Technology, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China.,School of Physics, Zhejiang University, Hangzhou, Zhejiang, China
| | - Tao Wu
- Center for Movement Disorders, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Parkinson's Disease Center, Beijing Institute for Brain Disorders, Capital Medical University, Beijing, China
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Langley J, Hwang KS, Hu XP, Huddleston DE. Nigral volumetric and microstructural measures in individuals with scans without evidence of dopaminergic deficit. Front Neurosci 2022; 16:1048945. [PMID: 36507343 PMCID: PMC9731284 DOI: 10.3389/fnins.2022.1048945] [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: 09/20/2022] [Accepted: 10/28/2022] [Indexed: 11/25/2022] Open
Abstract
Introduction Striatal dopamine transporter (DAT) imaging using 123I-ioflupane single photon positron emitted computed tomography (SPECT) (DaTScan, GE) identifies 5-20% of newly diagnosed Parkinson's disease (PD) subjects enrolling in clinical studies to have scans without evidence of dopaminergic deficit (SWEDD). These individuals meet diagnostic criteria for PD, but do not clinically progress as expected, and they are not believed to have neurodegenerative Parkinsonism. Inclusion of SWEDD participants in PD biomarker studies or therapeutic trials may therefore cause them to fail. DaTScan can identify SWEDD individuals, but it is expensive and not widely available; an alternative imaging approach is needed. Here, we evaluate the use of neuromelanin-sensitive, iron-sensitive, and diffusion contrasts in substantia nigra pars compacta (SNpc) to differentiate SWEDD from PD individuals. Methods Neuromelanin-sensitive, iron-sensitive, and diffusion imaging data for SWEDD, PD, and control subjects were downloaded from the Parkinson's progression markers initiative (PPMI) database. SNpc volume, SNpc iron (R 2), and SNpc free water (FW) were measured for each participant. Results Significantly smaller SNpc volume was seen in PD as compared to SWEDD (P < 10-3) and control (P < 10-3) subjects. SNpc FW was elevated in the PD group relative to controls (P = 0.017). No group difference was observed in SNpc R 2. Conclusion In conclusion, nigral volume and FW in the SWEDD group were similar to that of controls, while a reduction in nigral volume and increased FW were observed in the PD group relative to SWEDD and control participants. These results suggest that these MRI measures should be explored as a cost-effective alternative to DaTScan for evaluation of the nigrostriatal system.
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Affiliation(s)
- Jason Langley
- Center for Advanced Neuroimaging, University of California, Riverside, Riverside, CA, United States
| | - Kristy S. Hwang
- Department of Neurosciences, University of California, San Diego, San Diego, CA, United States
| | - Xiaoping P. Hu
- Center for Advanced Neuroimaging, University of California, Riverside, Riverside, CA, United States,Department of Bioengineering, University of California, Riverside, Riverside, CA, United States,*Correspondence: Xiaoping P. Hu,
| | - Daniel E. Huddleston
- Department of Neurology, Emory University, Atlanta, GA, United States,Daniel E. Huddleston,
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Gaurav R, Valabrègue R, Yahia-Chérif L, Mangone G, Narayanan S, Arnulf I, Vidailhet M, Corvol JC, Lehéricy S. NigraNet: An automatic framework to assess nigral neuromelanin content in early Parkinson's disease using convolutional neural network. Neuroimage Clin 2022; 36:103250. [PMID: 36451356 PMCID: PMC9668659 DOI: 10.1016/j.nicl.2022.103250] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2022] [Revised: 10/15/2022] [Accepted: 10/28/2022] [Indexed: 11/06/2022]
Abstract
BACKGROUND Parkinson's disease (PD) demonstrates neurodegenerative changes in the substantia nigra pars compacta (SNc) using neuromelanin-sensitive (NM)-MRI. As SNc manual segmentation is prone to substantial inter-individual variability across raters, development of a robust automatic segmentation framework is necessary to facilitate nigral neuromelanin quantification. Artificial intelligence (AI) is gaining traction in the neuroimaging community for automated brain region segmentation tasks using MRI. OBJECTIVE Developing and validating AI-based NigraNet, a fully automatic SNc segmentation framework allowing nigral neuromelanin quantification in patients with PD using NM-MRI. METHODS We prospectively included 199 participants comprising 144 early-stage idiopathic PD patients (disease duration = 1.5 ± 1.0 years) and 55 healthy volunteers (HV) scanned using a 3 Tesla MRI including whole brain T1-weighted anatomical imaging and NM-MRI. The regions of interest (ROI) were delineated in all participants automatically using NigraNet, a modified U-net, and compared to manual segmentations performed by two experienced raters. The SNc volumes (Vol), volumes corrected by total intracranial volume (Cvol), normalized signal intensity (NSI) and contrast-to-noise ratio (CNR) were computed. One-way GLM-ANCOVA was performed while adjusting for age and sex as covariates. Diagnostic performance measurement was assessed using the receiver operating characteristic (ROC) analysis. Inter and intra-observer variability were estimated using Dice similarity coefficient (DSC). The agreements between methods were tested using intraclass correlation coefficient (ICC) based on a mean-rating, two-way, mixed-effects model estimates for absolute agreement. Cronbach's alpha and Bland-Altman plots were estimated to assess inter-method consistency. RESULTS Using both methods, Vol, Cvol, NSI and CNR measurements differed between PD and HV with an effect of sex for Cvol and CNR. ICC values between the methods demonstrated optimal agreement for Cvol and CNR (ICC > 0.9) and high reproducibility (DSC: 0.80) was also obtained. The SNc measurements also showed good to excellent consistency values (Cronbach's alpha > 0.87). Bland-Altman plots of agreement demonstrated no association of SNc ROI measurement differences between the methods and ROI average measurements while confirming that 95 % of the data points were ranging between the limits of mean difference (d ± 1.96xSD). Percentage changes between PD and HV were -27.4 % and -17.7 % for Vol, -30.0 % and -22.2 % for Cvol, -15.8 % and -14.4 % for NSI, -17.1 % and -16.0 % for CNR for automatic and manual measurements respectively. Using automatic method, in the entire dataset, we obtained the areas under the ROC curve (AUC) of 0.83 for Vol, 0.85 for Cvol, 0.79 for NSI and 0.77 for CNR whereas in the training dataset of 0.96 for Vol, 0.95 for Cvol, 0.85 for NSI and 0.85 for CNR. Disease duration correlated negatively with NSI of the patients for both the automatic and manual measurements. CONCLUSIONS We presented an AI-based NigraNet framework that utilizes a small MRI training dataset to fully automatize the SNc segmentation procedure with an increased precision and more reproducible results. Considering the consistency, accuracy and speed of our approach, this study could be a crucial step towards the implementation of a time-saving non-rater dependent fully automatic method for studying neuromelanin changes in clinical settings and large-scale neuroimaging studies.
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Affiliation(s)
- Rahul Gaurav
- Paris Brain Institute – ICM, Sorbonne University, UPMC Univ Paris 06, INSERM U1127, CNRS UMR 7225, Pitié-Salpêtrière Hospital, Paris, France,Movement Investigations and Therapeutics Team (MOV’IT), ICM, Paris, France,Center for NeuroImaging Research – CENIR, ICM, Paris, France,Corresponding author at: Centre de NeuroImagerie de Recherche – CENIR, Institut du Cerveau – ICM, Hôpital Pitié-Salpêtrière, 47 Boulevard de l’Hôpital, 75013 Paris, France.
| | - Romain Valabrègue
- Paris Brain Institute – ICM, Sorbonne University, UPMC Univ Paris 06, INSERM U1127, CNRS UMR 7225, Pitié-Salpêtrière Hospital, Paris, France,Center for NeuroImaging Research – CENIR, ICM, Paris, France
| | - Lydia Yahia-Chérif
- Paris Brain Institute – ICM, Sorbonne University, UPMC Univ Paris 06, INSERM U1127, CNRS UMR 7225, Pitié-Salpêtrière Hospital, Paris, France,Center for NeuroImaging Research – CENIR, ICM, Paris, France
| | - Graziella Mangone
- Paris Brain Institute – ICM, Sorbonne University, UPMC Univ Paris 06, INSERM U1127, CNRS UMR 7225, Pitié-Salpêtrière Hospital, Paris, France,INSERM, Clinical Investigation Center for Neurosciences (CIC), Pitié-Salpêtrière Hospital, Paris, France
| | - Sridar Narayanan
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, 3801 University Street, Montreal, Quebec, H3A 2B4, Canada
| | - Isabelle Arnulf
- Paris Brain Institute – ICM, Sorbonne University, UPMC Univ Paris 06, INSERM U1127, CNRS UMR 7225, Pitié-Salpêtrière Hospital, Paris, France,Movement Investigations and Therapeutics Team (MOV’IT), ICM, Paris, France,Sleep Disorders Unit, Pitié-Salpêtrière Hospital, AP-HP, Paris, France
| | - Marie Vidailhet
- Paris Brain Institute – ICM, Sorbonne University, UPMC Univ Paris 06, INSERM U1127, CNRS UMR 7225, Pitié-Salpêtrière Hospital, Paris, France,Movement Investigations and Therapeutics Team (MOV’IT), ICM, Paris, France,Department of Neurology, Pitié-Salpêtrière Hospital, AP-HP, Paris, France
| | - Jean-Christophe Corvol
- Paris Brain Institute – ICM, Sorbonne University, UPMC Univ Paris 06, INSERM U1127, CNRS UMR 7225, Pitié-Salpêtrière Hospital, Paris, France,INSERM, Clinical Investigation Center for Neurosciences (CIC), Pitié-Salpêtrière Hospital, Paris, France,Department of Neurology, Pitié-Salpêtrière Hospital, AP-HP, Paris, France
| | - Stéphane Lehéricy
- Paris Brain Institute – ICM, Sorbonne University, UPMC Univ Paris 06, INSERM U1127, CNRS UMR 7225, Pitié-Salpêtrière Hospital, Paris, France,Movement Investigations and Therapeutics Team (MOV’IT), ICM, Paris, France,Center for NeuroImaging Research – CENIR, ICM, Paris, France,Department of Neuroradiology, Pitié-Salpêtrière Hospital, AP-HP, Paris, France
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Hou Y, Zhang L, Ou R, Wei Q, Gu X, Liu K, Lin J, Yang T, Xiao Y, Gong Q, Shang H. Motor progression marker for newly diagnosed drug-naïve patients with Parkinson's disease: A resting-state functional MRI study. Hum Brain Mapp 2022; 44:901-913. [PMID: 36250699 PMCID: PMC9875914 DOI: 10.1002/hbm.26110] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Revised: 09/30/2022] [Accepted: 10/01/2022] [Indexed: 01/28/2023] Open
Abstract
The effective early prediction of clinical outcomes of Parkinson's disease (PD) is of great significance in the implementation of appropriate interventions. We aimed to propose a method based on the use of baseline resting-state functional characteristics (i.e., fractional amplitude of low-frequency fluctuations, fALFF) to predict motor progression in PD patients. Resting-state functional magnetic resonance imaging was performed on 48 newly-diagnosed drug-naïve PD patients and 27 age- and sex- matched healthy controls (HCs). Two PD subgroups were defined with different annual increase of Unified PD Rating Scale Part III motor scores. Least absolute shrinkage and selection operator regression analysis was performed to explore the baseline region-functional indicators for PD discrimination as well as the predictors for future motor deficits. Two significant models composed of baseline fALFF values from cerebral subregions were proposed. The classification model that distinguished PD patients from HCs (area under the curve [AUC] = 0.897) showed the most significant imaging characteristics in the putamen and precentral gyrus. The other prediction model that evaluated the degree of future deterioration of motor symptoms in PD patients (AUC = 0.916) showed the most significant imaging characteristics in the superior occipital gyrus and caudate nucleus. Furthermore, the increased regional function in bilateral caudate nuclei was correlated with the lower annual increase in motor deficits in all PD patients. The caudate nucleus might be the core region responsible for future motor deficits in newly-diagnosed PD patients, which may aid the development of disease progression preventive strategies in clinical practice.
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Affiliation(s)
- Yanbing Hou
- Department of Neurology, Laboratory of Neurodegenerative Disorders, National Clinical Research Center for Geriatrics, West China HospitalSichuan UniversityChengduSichuanChina
| | - Lingyu Zhang
- Department of Neurology, Laboratory of Neurodegenerative Disorders, National Clinical Research Center for Geriatrics, West China HospitalSichuan UniversityChengduSichuanChina
| | - Ruwei Ou
- Department of Neurology, Laboratory of Neurodegenerative Disorders, National Clinical Research Center for Geriatrics, West China HospitalSichuan UniversityChengduSichuanChina
| | - Qianqian Wei
- Department of Neurology, Laboratory of Neurodegenerative Disorders, National Clinical Research Center for Geriatrics, West China HospitalSichuan UniversityChengduSichuanChina
| | - Xiaojing Gu
- Department of Neurology, Laboratory of Neurodegenerative Disorders, National Clinical Research Center for Geriatrics, West China HospitalSichuan UniversityChengduSichuanChina
| | - Kuncheng Liu
- Department of Neurology, Laboratory of Neurodegenerative Disorders, National Clinical Research Center for Geriatrics, West China HospitalSichuan UniversityChengduSichuanChina
| | - Junyu Lin
- Department of Neurology, Laboratory of Neurodegenerative Disorders, National Clinical Research Center for Geriatrics, West China HospitalSichuan UniversityChengduSichuanChina
| | - Tianmi Yang
- Department of Neurology, Laboratory of Neurodegenerative Disorders, National Clinical Research Center for Geriatrics, West China HospitalSichuan UniversityChengduSichuanChina
| | - Yi Xiao
- Department of Neurology, Laboratory of Neurodegenerative Disorders, National Clinical Research Center for Geriatrics, West China HospitalSichuan UniversityChengduSichuanChina
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China HospitalSichuan UniversityChengduSichuanChina
| | - Huifang Shang
- Department of Neurology, Laboratory of Neurodegenerative Disorders, National Clinical Research Center for Geriatrics, West China HospitalSichuan UniversityChengduSichuanChina
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Pasquini J, Firbank MJ, Ceravolo R, Silani V, Pavese N. Diffusion Magnetic Resonance Imaging Microstructural Abnormalities in Multiple System Atrophy: A Comprehensive Review. Mov Disord 2022; 37:1963-1984. [PMID: 36036378 DOI: 10.1002/mds.29195] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2022] [Revised: 07/22/2022] [Accepted: 08/01/2022] [Indexed: 01/07/2023] Open
Abstract
Multiple system atrophy (MSA) is a neurodegenerative disease characterized by autonomic failure, ataxia, and/or parkinsonism. Its prominent pathological alterations can be investigated using diffusion magnetic resonance imaging (dMRI), a technique that exploits the characteristics of water random motion inside brain tissue. The aim of this report was to review currently available literature on the application of dMRI in MSA and to describe microstructural abnormalities, diagnostic applications, and pathophysiological correlates. Sixty-four published studies involving microstructural investigation using dMRI in MSA were included. Widespread microstructural abnormalities of white matter were described, especially in the middle cerebellar peduncle, corticospinal tract, and hemispheric fibers. Gray matter degeneration was identified as well, with diffuse involvement of subcortical structures, especially in the putamina. Diagnostic applications of dMRI were mostly explored for the differential diagnosis between MSA parkinsonism and Parkinson's disease. Recently, machine learning algorithms for image processing and disease classification have demonstrated high diagnostic accuracy, showing potential for translation into clinical practice. To a lesser extent, clinical correlates of microstructural abnormalities have also been investigated, and abnormalities related to motor, ocular, and cognitive impairments were described. dMRI in MSA has contributed to in vivo identification of known pathological abnormalities. Translation into clinical practice of the latest advancements for the differential diagnosis between MSA and other forms of parkinsonism seems feasible. Current limitations involve the possibility of correctly diagnosing MSA in the very early stages, when the clinical diagnosis is most uncertain. Furthermore, pathophysiological correlates of microstructural abnormalities remain understudied. © 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)
- Jacopo Pasquini
- Clinical Ageing Research Unit, Newcastle University, Newcastle upon Tyne, United Kingdom.,Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Michael J Firbank
- Positron Emission Tomography Centre, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Roberto Ceravolo
- Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy.,Neurodegenerative Diseases Center, Azienda Ospedaliero Universitaria Pisana, Pisa, Italy
| | - Vincenzo Silani
- Department of Neurology and Laboratory of Neuroscience, Istituto Auxologico Italiano IRCCS, Milan, Italy.,Department of Pathophysiology and Transplantation, Dino Ferrari Center, Università degli Studi di Milano, Milan, Italy
| | - Nicola Pavese
- Clinical Ageing Research Unit, Newcastle University, Newcastle upon Tyne, United Kingdom.,Department of Nuclear Medicine and PET Centre, Aarhus University Hospital, Aarhus, Denmark
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Sun Y, Hu Y, Qiu Y, Zhang Y, Jiang C, Lu P, Xu Q, Shi Y, Wei H, Zhou Y. Characterization of white matter over 1–2 years in small vessel disease using MR-based quantitative susceptibility mapping and free-water mapping. Front Aging Neurosci 2022; 14:998051. [PMID: 36247993 PMCID: PMC9562046 DOI: 10.3389/fnagi.2022.998051] [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: 07/19/2022] [Accepted: 09/07/2022] [Indexed: 11/13/2022] Open
Abstract
PurposeThe aim of this study was to investigate alterations in white matter lesions (WMLs) and normal-appearing white matter (NAWM) with small vessel disease (SVD) over 1–2 years using quantitative susceptibility mapping (QSM) and free-water (FW) mapping.MethodsFifty-one SVD patients underwent MRI brain scans and neuropsychological testing both at baseline and follow-up. The main approach for treating these patients is the management of risk factors. Quantitative susceptibility (QS), fractional anisotropy (FA), mean diffusivity (MD), FW, FW-corrected FA (FAT), and FW-corrected MD (MDT) maps within WMLs and NAWM were generated. Furthermore, the JHU-ICBM-DTI label atlas was used as an anatomic guide, and the measurements of the segmented NAWMs were calculated. The average regional values were extracted, and a paired t-test was used to analyze the longitudinal change. Partial correlations were used to assess the relationship between the MRI indices changes (e.g., ΔQSfollowup − baseline/QSbaseline) and the cognitive function changes (e.g., ΔMoCAfollowup − baseline/MoCAbaseline).ResultsAfter SVD risk factor control, no gradual cognitive decline occurred during 1–2 years. However, we still found that the QS values (index of demyelination) increased in the NAWM at follow-up, especially in the NAWM part of the left superior frontal blade (SF), left occipital blade, right uncinate fasciculus, and right corticospinal tract (CST). FW (index of neuroinflammation/edema) analysis revealed that the follow-up group differed from the baseline group in the NAWM part of the right CST and inferior frontal blade (IF). Decreased FAT (index of axonal loss) was observed in the NAWM part of the right SF and IF at follow-up. In addition, the FAT changes in the NAWM part of the right IF were associated with overall cognitive performance changes. In contrast, no significant differences were found in the WMLs.ConclusionThe NAWM was still in the progressive injury process over time, while WMLs remained relatively stable, which supports the notion that SVD is a chronic progressive disease. The process of axonal loss in the NAWM part of the prefrontal lobe might be a biomarker of cognitive changes in the evolution of SVD.
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Affiliation(s)
- Yawen Sun
- Department of Radiology, School of Medicine, Ren Ji Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Ying Hu
- Department of Radiology, School of Medicine, Ren Ji Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Yage Qiu
- Department of Radiology, School of Medicine, Ren Ji Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Yuyao Zhang
- School of Information and Science and Technology, ShanghaiTech University, Shanghai, China
| | - Changhao Jiang
- School of Information and Science and Technology, ShanghaiTech University, Shanghai, China
| | - Peiwen Lu
- Department of Neurology, School of Medicine, Ren Ji Hospital, Shanghai Jiao Tong University, Shanghai, China
- Ren Ji-UNSW CHeBA Neurocognitive Center, School of Medicine, Ren Ji Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Qun Xu
- Department of Neurology, School of Medicine, Ren Ji Hospital, Shanghai Jiao Tong University, Shanghai, China
- Ren Ji-UNSW CHeBA Neurocognitive Center, School of Medicine, Ren Ji Hospital, Shanghai Jiao Tong University, Shanghai, China
- Department of Health Manage Center, School of Medicine, Ren Ji Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Yuting Shi
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Hongjiang Wei
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
- *Correspondence: Yan Zhou
| | - Yan Zhou
- Department of Radiology, School of Medicine, Ren Ji Hospital, Shanghai Jiao Tong University, Shanghai, China
- Hongjiang Wei
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Wang L, Wu P, Brown P, Zhang W, Liu F, Han Y, Zuo CT, Cheng W, Feng J. Association of Structural Measurements of Brain Reserve With Motor Progression in Patients With Parkinson Disease. Neurology 2022; 99:e977-e988. [PMID: 35667838 PMCID: PMC7613818 DOI: 10.1212/wnl.0000000000200814] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2021] [Accepted: 04/19/2022] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND AND OBJECTIVES To investigate the relationship between baseline structural measurements of brain reserve and clinical progression in Parkinson disease (PD). To further provide a possible underlying mechanism for structural measurements of brain reserve in PD, we combined functional and transcriptional data and investigated their relationship with progression-associated patterns derived from structural measurements and longitudinal clinical scores. METHODS This longitudinal study collected data from June 2010 to March 2019 from 2 datasets. The Parkinson's Progression Markers Initiative (PPMI) included controls and patients with newly diagnosed PD from 24 participating sites worldwide. Results were confirmed using data from the Huashan dataset (Shanghai, China), which included controls and patients with PD. Clinical symptoms were assessed with Movement Disorder Society-sponsored revision of the Unified Parkinson's Disease Rating Scale (MDS-UPDRS) scores and Schwab & England activities of daily living (ADL). Both datasets were followed up to 5 years. Linear mixed-effects (LME) models were performed to examine whether changes in clinical scores over time differed as a function of brain structural measurements at baseline. RESULTS A total of 389 patients with PD (n = 346, age 61.3 ± 10.03, 35% female, PPMI dataset; n = 43, age 59.4 ± 7.3, 38.7% female, Huashan dataset) with T1-MRI and follow-up clinical assessments were included in this study. Results of LME models revealed significant interactions between baseline structural measurements of subcortical regions and time on longitudinal deterioration of clinical scores (MDS-UPDRS Part II, absolute β > 0.27; total MDS-UPDRS scores, absolute β > 1.05; postural instability-gait difficulty (PIGD) score, absolute β > 0.03; Schwab & England ADL, absolute β > 0.59; all p < 0.05, false discovery rate corrected). The interaction of baseline structural measurements of subcortical regions and time on longitudinal deterioration of the PIGD score was replicated using data from Huashan Hospital. Furthermore, the β-coefficients of these interactions recapitulated the spatial distribution of dopaminergic, metabolic, and structural changes between patients with PD and normal controls and the spatial distribution of expression of the α-synuclein gene (SNCA). DISCUSSION Patients with PD with greater brain resources (that is, higher deformation-based morphometry values) had greater compensatory capacity, which was associated with slower rates of clinical progression. This knowledge could be used to stratify and monitor patients for clinical trials.
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Affiliation(s)
- Linbo Wang
- From the Institute of Science and Technology for Brain-inspired Intelligence (L.W., W.Z., W.C., J.F.), Fudan University; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University) (L.W., W.Z., W.C., J.F.), Ministry of Education; PET Center (P.W., C.-T.Z.), Huashan Hospital, Fudan University, Shanghai, China; Medical Research Council Brain Network Dynamics Unit (P.B.), and Nuffield Department of Clinical Neurosciences (P.B.), John Radcliffe Hospital, University of Oxford, United Kingdom; Department of Neurology (F.L., C.-T.Z.), Huashan Hospital North, Fudan University; Department of Neurology (Y.H.), Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine; Human Phenome Institute (C.-T.Z.), Fudan University; Zhangjiang Fudan International Innovation Center (W.C., J.F.), Shanghai, China; Department of Computer Science (W.C., J.F.), University of Warwick, Coventry, United Kingdom; and Fudan ISTBI-ZJNU Algorithm Centre for Brain-inspired Intelligence (W.C., J.F.), Zhejiang Normal University, Jinhua, China
| | - Ping Wu
- From the Institute of Science and Technology for Brain-inspired Intelligence (L.W., W.Z., W.C., J.F.), Fudan University; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University) (L.W., W.Z., W.C., J.F.), Ministry of Education; PET Center (P.W., C.-T.Z.), Huashan Hospital, Fudan University, Shanghai, China; Medical Research Council Brain Network Dynamics Unit (P.B.), and Nuffield Department of Clinical Neurosciences (P.B.), John Radcliffe Hospital, University of Oxford, United Kingdom; Department of Neurology (F.L., C.-T.Z.), Huashan Hospital North, Fudan University; Department of Neurology (Y.H.), Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine; Human Phenome Institute (C.-T.Z.), Fudan University; Zhangjiang Fudan International Innovation Center (W.C., J.F.), Shanghai, China; Department of Computer Science (W.C., J.F.), University of Warwick, Coventry, United Kingdom; and Fudan ISTBI-ZJNU Algorithm Centre for Brain-inspired Intelligence (W.C., J.F.), Zhejiang Normal University, Jinhua, China
| | - Peter Brown
- From the Institute of Science and Technology for Brain-inspired Intelligence (L.W., W.Z., W.C., J.F.), Fudan University; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University) (L.W., W.Z., W.C., J.F.), Ministry of Education; PET Center (P.W., C.-T.Z.), Huashan Hospital, Fudan University, Shanghai, China; Medical Research Council Brain Network Dynamics Unit (P.B.), and Nuffield Department of Clinical Neurosciences (P.B.), John Radcliffe Hospital, University of Oxford, United Kingdom; Department of Neurology (F.L., C.-T.Z.), Huashan Hospital North, Fudan University; Department of Neurology (Y.H.), Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine; Human Phenome Institute (C.-T.Z.), Fudan University; Zhangjiang Fudan International Innovation Center (W.C., J.F.), Shanghai, China; Department of Computer Science (W.C., J.F.), University of Warwick, Coventry, United Kingdom; and Fudan ISTBI-ZJNU Algorithm Centre for Brain-inspired Intelligence (W.C., J.F.), Zhejiang Normal University, Jinhua, China
| | - Wei Zhang
- From the Institute of Science and Technology for Brain-inspired Intelligence (L.W., W.Z., W.C., J.F.), Fudan University; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University) (L.W., W.Z., W.C., J.F.), Ministry of Education; PET Center (P.W., C.-T.Z.), Huashan Hospital, Fudan University, Shanghai, China; Medical Research Council Brain Network Dynamics Unit (P.B.), and Nuffield Department of Clinical Neurosciences (P.B.), John Radcliffe Hospital, University of Oxford, United Kingdom; Department of Neurology (F.L., C.-T.Z.), Huashan Hospital North, Fudan University; Department of Neurology (Y.H.), Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine; Human Phenome Institute (C.-T.Z.), Fudan University; Zhangjiang Fudan International Innovation Center (W.C., J.F.), Shanghai, China; Department of Computer Science (W.C., J.F.), University of Warwick, Coventry, United Kingdom; and Fudan ISTBI-ZJNU Algorithm Centre for Brain-inspired Intelligence (W.C., J.F.), Zhejiang Normal University, Jinhua, China
| | - Fengtao Liu
- From the Institute of Science and Technology for Brain-inspired Intelligence (L.W., W.Z., W.C., J.F.), Fudan University; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University) (L.W., W.Z., W.C., J.F.), Ministry of Education; PET Center (P.W., C.-T.Z.), Huashan Hospital, Fudan University, Shanghai, China; Medical Research Council Brain Network Dynamics Unit (P.B.), and Nuffield Department of Clinical Neurosciences (P.B.), John Radcliffe Hospital, University of Oxford, United Kingdom; Department of Neurology (F.L., C.-T.Z.), Huashan Hospital North, Fudan University; Department of Neurology (Y.H.), Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine; Human Phenome Institute (C.-T.Z.), Fudan University; Zhangjiang Fudan International Innovation Center (W.C., J.F.), Shanghai, China; Department of Computer Science (W.C., J.F.), University of Warwick, Coventry, United Kingdom; and Fudan ISTBI-ZJNU Algorithm Centre for Brain-inspired Intelligence (W.C., J.F.), Zhejiang Normal University, Jinhua, China
| | - Yan Han
- From the Institute of Science and Technology for Brain-inspired Intelligence (L.W., W.Z., W.C., J.F.), Fudan University; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University) (L.W., W.Z., W.C., J.F.), Ministry of Education; PET Center (P.W., C.-T.Z.), Huashan Hospital, Fudan University, Shanghai, China; Medical Research Council Brain Network Dynamics Unit (P.B.), and Nuffield Department of Clinical Neurosciences (P.B.), John Radcliffe Hospital, University of Oxford, United Kingdom; Department of Neurology (F.L., C.-T.Z.), Huashan Hospital North, Fudan University; Department of Neurology (Y.H.), Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine; Human Phenome Institute (C.-T.Z.), Fudan University; Zhangjiang Fudan International Innovation Center (W.C., J.F.), Shanghai, China; Department of Computer Science (W.C., J.F.), University of Warwick, Coventry, United Kingdom; and Fudan ISTBI-ZJNU Algorithm Centre for Brain-inspired Intelligence (W.C., J.F.), Zhejiang Normal University, Jinhua, China
| | - Chuan-Tao Zuo
- From the Institute of Science and Technology for Brain-inspired Intelligence (L.W., W.Z., W.C., J.F.), Fudan University; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University) (L.W., W.Z., W.C., J.F.), Ministry of Education; PET Center (P.W., C.-T.Z.), Huashan Hospital, Fudan University, Shanghai, China; Medical Research Council Brain Network Dynamics Unit (P.B.), and Nuffield Department of Clinical Neurosciences (P.B.), John Radcliffe Hospital, University of Oxford, United Kingdom; Department of Neurology (F.L., C.-T.Z.), Huashan Hospital North, Fudan University; Department of Neurology (Y.H.), Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine; Human Phenome Institute (C.-T.Z.), Fudan University; Zhangjiang Fudan International Innovation Center (W.C., J.F.), Shanghai, China; Department of Computer Science (W.C., J.F.), University of Warwick, Coventry, United Kingdom; and Fudan ISTBI-ZJNU Algorithm Centre for Brain-inspired Intelligence (W.C., J.F.), Zhejiang Normal University, Jinhua, China
| | - Wei Cheng
- From the Institute of Science and Technology for Brain-inspired Intelligence (L.W., W.Z., W.C., J.F.), Fudan University; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University) (L.W., W.Z., W.C., J.F.), Ministry of Education; PET Center (P.W., C.-T.Z.), Huashan Hospital, Fudan University, Shanghai, China; Medical Research Council Brain Network Dynamics Unit (P.B.), and Nuffield Department of Clinical Neurosciences (P.B.), John Radcliffe Hospital, University of Oxford, United Kingdom; Department of Neurology (F.L., C.-T.Z.), Huashan Hospital North, Fudan University; Department of Neurology (Y.H.), Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine; Human Phenome Institute (C.-T.Z.), Fudan University; Zhangjiang Fudan International Innovation Center (W.C., J.F.), Shanghai, China; Department of Computer Science (W.C., J.F.), University of Warwick, Coventry, United Kingdom; and Fudan ISTBI-ZJNU Algorithm Centre for Brain-inspired Intelligence (W.C., J.F.), Zhejiang Normal University, Jinhua, China
| | - Jianfeng Feng
- From the Institute of Science and Technology for Brain-inspired Intelligence (L.W., W.Z., W.C., J.F.), Fudan University; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University) (L.W., W.Z., W.C., J.F.), Ministry of Education; PET Center (P.W., C.-T.Z.), Huashan Hospital, Fudan University, Shanghai, China; Medical Research Council Brain Network Dynamics Unit (P.B.), and Nuffield Department of Clinical Neurosciences (P.B.), John Radcliffe Hospital, University of Oxford, United Kingdom; Department of Neurology (F.L., C.-T.Z.), Huashan Hospital North, Fudan University; Department of Neurology (Y.H.), Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine; Human Phenome Institute (C.-T.Z.), Fudan University; Zhangjiang Fudan International Innovation Center (W.C., J.F.), Shanghai, China; Department of Computer Science (W.C., J.F.), University of Warwick, Coventry, United Kingdom; and Fudan ISTBI-ZJNU Algorithm Centre for Brain-inspired Intelligence (W.C., J.F.), Zhejiang Normal University, Jinhua, China.
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Xie L, Hu L. Research progress in the early diagnosis of Parkinson’s disease. Neurol Sci 2022; 43:6225-6231. [DOI: 10.1007/s10072-022-06316-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2022] [Accepted: 08/02/2022] [Indexed: 10/15/2022]
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49
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Wei L, Ding M, Zhang Y, Wang H. Decoding transcriptional signatures of the association between free water and macroscale organizations in healthy adolescents. Neuroimage 2022; 261:119514. [PMID: 35901916 DOI: 10.1016/j.neuroimage.2022.119514] [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: 01/04/2022] [Revised: 07/11/2022] [Accepted: 07/22/2022] [Indexed: 11/16/2022] Open
Abstract
We leveraged a novel index of diffusion MRI to investigate the relationships among cortical free water, macro-organizations and gene expression in healthy adults. Few research has been conducted to investigate the role of free water in the healthy adults due to it can easily be affected also by aging diseases. High quality data of 350 subjects from Human Connectome Project were used in our study. Cortical free water was estimated by using a bi-tensor model. The free water was high in the limbic, insular and somatosensory cortex, while being lower in motor and association cortex. The negative correlation between the free water and cortical thickness has been consistently identified in almost all the cortical regions. Negative correlation between the cortical free water and structural covariance (rho=-0.38, pspin=0.005) revealed the free water was sensitive to cortical heterogeneity. Using human gene expression dataset, we found the gene expression pattern of the relationship between the free water and cortical thickness spatially coupled with primary gradient of structural covariance network (rho=0.40, pspin=0.004). Our findings indicated the free water was sensitive to the cortical cellular status. The relationship between free water and macroscale organization also reflected hierarchal structures of cerebral cortex.
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Affiliation(s)
- Lei Wei
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, PR China.
| | - Ming Ding
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, PR China
| | - Yuwen Zhang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, PR China
| | - He Wang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, PR China; Human Phenome Institute, Fudan University, Shanghai, PR China; Department of Neurology, Zhongshan Hospital, Fudan University, Shanghai, PR China.
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50
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Berger M, Pirpamer L, Hofer E, Ropele S, Duering M, Gesierich B, Pasternak O, Enzinger C, Schmidt R, Koini M. Free water diffusion MRI and executive function with a speed component in healthy aging. Neuroimage 2022; 257:119303. [PMID: 35568345 PMCID: PMC9465649 DOI: 10.1016/j.neuroimage.2022.119303] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Revised: 05/06/2022] [Accepted: 05/09/2022] [Indexed: 11/12/2022] Open
Abstract
Extracellular free water (FW) increases are suggested to better provide pathophysiological information in brain aging than conventional biomarkers such as fractional anisotropy. The aim of the present study was to determine the relationship between conventional biomarkers, FW in white matter hyperintensities (WMH), FW in normal appearing white matter (NAWM) and in white matter tracts and executive functions (EF) with a speed component in elderly persons. We examined 226 healthy elderly participants (median age 69.83 years, IQR: 56.99–74.42) who underwent brain MRI and neuropsychological examination. FW in WMH and in NAWM as well as FW corrected diffusion metrics and measures derived from conventional MRI (white matter hyperintensities, brain volume, lacunes) were used in partial correlation (adjusted for age) to assess their correlation with EF with a speed component. Random forest analysis was used to assess the relative importance of these variables as determinants. Lastly, linear regression analyses of FW in white matter tracts corrected for risk factors of cognitive and white matter deterioration, were used to examine the role of specific tracts on EF with a speed component, which were then ranked with random forest regression. Partial correlation analyses revealed that almost all imaging metrics showed a significant association with EF with a speed component (r = −0.213 – 0.266). Random forest regression highlighted FW in WMH and in NAWM as most important among all diffusion and structural MRI metrics. The fornix (R2=0.421, p = 0.018) and the corpus callosum (genu (R2 = 0.418, p = 0.021), prefrontal (R2 = 0.416, p = 0.026), premotor (R2 = 0.418, p = 0.021)) were associated with EF with a speed component in tract based regression analyses and had highest variables importance. In a normal aging population FW in WMH and NAWM is more closely related to EF with a speed component than standard DTI and brain structural measures. Higher amounts of FW in the fornix and the frontal part of the corpus callosum leads to deteriorating EF with a speed component.
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Affiliation(s)
- Martin Berger
- Department of Neurology, Division of Neurogeriatrics, Medical University of Graz, Auenbruggerplatz 22, Graz 8036, Austria
| | - Lukas Pirpamer
- Department of Neurology, Division of Neurogeriatrics, Medical University of Graz, Auenbruggerplatz 22, Graz 8036, Austria
| | - Edith Hofer
- Department of Neurology, Division of Neurogeriatrics, Medical University of Graz, Auenbruggerplatz 22, Graz 8036, Austria; Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, Graz, Austria
| | - Stefan Ropele
- Department of Neurology, Division of Neurogeriatrics, Medical University of Graz, Auenbruggerplatz 22, Graz 8036, Austria
| | - Marco Duering
- Medical Image Analysis Center (MIAC AG) and Department of Biomedical Engineering, University of Basel, Basel, Switzerland
| | - Benno Gesierich
- Institute for Stroke and Dementia Research (ISD), University Hospital, Munich, Germany
| | - Ofer Pasternak
- Departments of Psychiatry and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | | | - Reinhold Schmidt
- Department of Neurology, Division of Neurogeriatrics, Medical University of Graz, Auenbruggerplatz 22, Graz 8036, Austria.
| | - Marisa Koini
- Department of Neurology, Division of Neurogeriatrics, Medical University of Graz, Auenbruggerplatz 22, Graz 8036, Austria
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