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Yoon YJ, Kim SH, Jeong SH, Park CW, Lee HS, Lee PH, Kim YJ, Sohn YH, Jeong Y, Chung SJ. Occipital hypoperfusion and motor reserve in Parkinson's disease: an early-phase 18F-FP-CIT PET study. NPJ Parkinsons Dis 2024; 10:221. [PMID: 39551772 PMCID: PMC11570606 DOI: 10.1038/s41531-024-00834-8] [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: 04/02/2024] [Accepted: 11/01/2024] [Indexed: 11/19/2024] Open
Abstract
Individual variability exists in parkinsonian motor symptoms despite a similar degree of nigrostriatal dopamine depletion in Parkinson's disease (PD), called motor reserve. We enrolled 397 patients newly diagnosed with PD who underwent dual-phase 18F-FP-CIT PET upon initial assessment. Individual motor reserve was estimated based on initial parkinsonian motor symptoms and striatal dopamine transporter availability using a residual model. Patients with low motor reserve (the lowest quartile group, n = 100) exhibited decreased uptake in the occipital region compared to those with high motor reserve (the highest quartile group, n = 100) on early-phase 18F-FP-CIT PET images. Patients with high motor reserve had a lower risk of conversion to dementia than the those with low motor reserve, whereas the effect of PD groups on the risk of dementia conversion was not mediated by occipital hypoperfusion. These findings suggest that cerebral hypoperfusion in the occipital region is associated with low motor reserve in patients with PD.
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Affiliation(s)
- Yeo Jun Yoon
- Department of Neurology, Yonsei University College of Medicine, Seoul, South Korea
| | - Su Hong Kim
- Department of Radiology, Yeungnam University College of Medicine, Daegu, South Korea
- Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology, Daejeon, South Korea
- KAIST Institute for Health Science Technology, Korea Advanced Institute of Science and Technology, Daejeon, South Korea
| | - Seong Ho Jeong
- Department of Neurology, Inje University Sanggye Paik Hospital, Seoul, South Korea
| | - Chan Wook Park
- Department of Neurology, Yonsei University College of Medicine, Seoul, South Korea
- Department of Physiology, Yonsei University College of Medicine, Seoul, South Korea
| | - Hye Sun Lee
- Biostatistics Collaboration Unit, Yonsei University College of Medicine, Seoul, South Korea
| | - Phil Hyu Lee
- Department of Neurology, Yonsei University College of Medicine, Seoul, South Korea
| | - Yun Joong Kim
- Department of Neurology, Yonsei University College of Medicine, Seoul, South Korea
- Department of Neurology, Yongin Severance Hospital, Yonsei University Health System, Yongin, South Korea
- YONSEI BEYOND LAB, Yongin, South Korea
| | - Young H Sohn
- Department of Neurology, Yonsei University College of Medicine, Seoul, South Korea
| | - Yong Jeong
- Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology, Daejeon, South Korea
- KAIST Institute for Health Science Technology, Korea Advanced Institute of Science and Technology, Daejeon, South Korea
- Program of Brain and Cognitive Engineering, Korea Advanced Institute of Science and Technology, Daejeon, South Korea
- Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology, Daejeon, South Korea
| | - Seok Jong Chung
- Department of Neurology, Yonsei University College of Medicine, Seoul, South Korea.
- Department of Neurology, Yongin Severance Hospital, Yonsei University Health System, Yongin, South Korea.
- YONSEI BEYOND LAB, Yongin, South Korea.
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2
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Mana J, Bezdicek O, Růžička F, Lasica A, Šmídová A, Klempířová O, Nikolai T, Uhrová T, Růžička E, Urgošík D, Jech R. Preoperative cognitive profile predictive of cognitive decline after subthalamic deep brain stimulation in Parkinson's disease. Eur J Neurosci 2024; 60:5764-5784. [PMID: 39212074 DOI: 10.1111/ejn.16521] [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: 10/05/2023] [Revised: 08/07/2024] [Accepted: 08/15/2024] [Indexed: 09/04/2024]
Abstract
Cognitive decline represents a severe non-motor symptom of Parkinson's disease (PD) that can significantly reduce the benefits of subthalamic deep brain stimulation (STN DBS). Here, we aimed to describe post-surgery cognitive decline and identify pre-surgery cognitive profile associated with faster decline in STN DBS-treated PD patients. A retrospective observational study of 126 PD patients treated by STN DBS combined with oral dopaminergic therapy followed for 3.54 years on average (SD = 2.32) with repeated assessments of cognition was conducted. Pre-surgery cognitive profile was obtained via a comprehensive neuropsychological examination and data analysed using exploratory factor analysis and Bayesian generalized linear mixed models. On the whole, we observed a mild annual cognitive decline of 0.90 points from a total of 144 points in the Mattis Dementia Rating Scale (95% posterior probability interval [-1.19, -0.62]) with high inter-individual variability. However, true score changes did not reach previously reported reliable change cut-offs. Executive deficit was the only pre-surgery cognitive variable to reliably predict the rate of post-surgery cognitive decline. On the other hand, exploratory analysis of electrode localization did not yield any statistically clear results. Overall, our data and models imply mild gradual average annual post-surgery cognitive decline with high inter-individual variability in STN DBS-treated PD patients. Nonetheless, patients with worse long-term cognitive prognosis can be reliably identified via pre-surgery examination of executive functions. To further increase the utility of our results, we demonstrate how our models can help with disentangling true score changes from measurement error in future studies of post-surgery cognitive changes.
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Affiliation(s)
- Josef Mana
- Department of Neurology and Centre of Clinical Neuroscience, First Faculty of Medicine and General University Hospital in Prague, Charles University, Prague, Czech Republic
| | - Ondrej Bezdicek
- Department of Neurology and Centre of Clinical Neuroscience, First Faculty of Medicine and General University Hospital in Prague, Charles University, Prague, Czech Republic
| | - Filip Růžička
- Department of Neurology and Centre of Clinical Neuroscience, First Faculty of Medicine and General University Hospital in Prague, Charles University, Prague, Czech Republic
| | - Andrej Lasica
- Department of Neurology and Centre of Clinical Neuroscience, First Faculty of Medicine and General University Hospital in Prague, Charles University, Prague, Czech Republic
| | - Anna Šmídová
- Department of Neurology and Centre of Clinical Neuroscience, First Faculty of Medicine and General University Hospital in Prague, Charles University, Prague, Czech Republic
| | - Olga Klempířová
- Department of Neurology and Centre of Clinical Neuroscience, First Faculty of Medicine and General University Hospital in Prague, Charles University, Prague, Czech Republic
| | - Tomáš Nikolai
- Department of Neurology and Centre of Clinical Neuroscience, First Faculty of Medicine and General University Hospital in Prague, Charles University, Prague, Czech Republic
| | - Tereza Uhrová
- Department of Neurology and Centre of Clinical Neuroscience, First Faculty of Medicine and General University Hospital in Prague, Charles University, Prague, Czech Republic
| | - Evžen Růžička
- Department of Neurology and Centre of Clinical Neuroscience, First Faculty of Medicine and General University Hospital in Prague, Charles University, Prague, Czech Republic
| | - Dušan Urgošík
- Department of Stereotactic and Radiation Neurosurgery, Na Homolce Hospital, Prague, Czech Republic
| | - Robert Jech
- Department of Neurology and Centre of Clinical Neuroscience, First Faculty of Medicine and General University Hospital in Prague, Charles University, Prague, Czech Republic
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Loo RTJ, Tsurkalenko O, Klucken J, Mangone G, Khoury F, Vidailhet M, Corvol JC, Krüger R, Glaab E. Levodopa-induced dyskinesia in Parkinson's disease: Insights from cross-cohort prognostic analysis using machine learning. Parkinsonism Relat Disord 2024; 126:107054. [PMID: 38991633 DOI: 10.1016/j.parkreldis.2024.107054] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/28/2024] [Revised: 06/29/2024] [Accepted: 07/02/2024] [Indexed: 07/13/2024]
Abstract
BACKGROUND Prolonged levodopa treatment in Parkinson's disease (PD) often leads to motor complications, including levodopa-induced dyskinesia (LID). Despite continuous levodopa treatment, some patients do not develop LID symptoms, even in later stages of the disease. OBJECTIVE This study explores machine learning (ML) methods using baseline clinical characteristics to predict the development of LID in PD patients over four years, across multiple cohorts. METHODS Using interpretable ML approaches, we analyzed clinical data from three independent longitudinal PD cohorts (LuxPARK, n = 356; PPMI, n = 484; ICEBERG, n = 113) to develop cross-cohort prognostic models and identify potential predictors for the development of LID. We examined cohort-specific and shared predictive factors, assessing model performance and stability through cross-validation analyses. RESULTS Consistent cross-validation results for single and multiple cohort analyses highlighted the effectiveness of the ML models and identified baseline clinical characteristics with significant predictive value for the LID prognosis in PD. Predictors positively correlated with LID include axial symptoms, freezing of gait, and rigidity in the lower extremities. Conversely, the risk of developing LID was inversely associated with the occurrence of resting tremors, higher body weight, later onset of PD, and visuospatial abilities. CONCLUSIONS This study presents interpretable ML models for dyskinesia prognosis with significant predictive power in cross-cohort analyses. The models may pave the way for proactive interventions against dyskinesia in PD by optimizing levodopa dosing regimens and adjunct treatments with dopamine agonists or MAO-B inhibitors, and by employing non-pharmacological interventions such as dietary adjustments affecting levodopa absorption for high-risk LID patients.
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Affiliation(s)
- Rebecca Ting Jiin Loo
- Biomedical Data Science, Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Esch-sur-Alzette, Luxembourg
| | - Olena Tsurkalenko
- Translational Neuroscience, Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Esch-sur-Alzette, Luxembourg; Transversal Translational Medicine, Luxembourg Institute of Health (LIH), Strassen, Luxembourg; Digital Medicine Group, Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Esch-sur-Alzette, Luxembourg; Digital Medicine Group, Department of Precision Health, Luxembourg Institute of Health (LIH), Strassen, Luxembourg; Digital Medicine Group, Centre Hospitalier de Luxembourg (CHL), Luxembourg
| | - Jochen Klucken
- Digital Medicine Group, Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Esch-sur-Alzette, Luxembourg; Digital Medicine Group, Department of Precision Health, Luxembourg Institute of Health (LIH), Strassen, Luxembourg; Digital Medicine Group, Centre Hospitalier de Luxembourg (CHL), Luxembourg
| | - Graziella Mangone
- Sorbonne Université, Paris Brain Institute - ICM, Inserm, CNRS, Assistance Publique Hôpitaux de Paris, Pitié-Salpêtrière Hospital, Department of Neurology, Paris, 75013, France
| | - Fouad Khoury
- Sorbonne Université, Paris Brain Institute - ICM, Inserm, CNRS, Assistance Publique Hôpitaux de Paris, Pitié-Salpêtrière Hospital, Department of Neurology, Paris, 75013, France
| | - Marie Vidailhet
- Sorbonne Université, Paris Brain Institute - ICM, Inserm, CNRS, Assistance Publique Hôpitaux de Paris, Pitié-Salpêtrière Hospital, Department of Neurology, Paris, 75013, France
| | - Jean-Christophe Corvol
- Sorbonne Université, Paris Brain Institute - ICM, Inserm, CNRS, Assistance Publique Hôpitaux de Paris, Pitié-Salpêtrière Hospital, Department of Neurology, Paris, 75013, France
| | - Rejko Krüger
- Translational Neuroscience, Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Esch-sur-Alzette, Luxembourg; Transversal Translational Medicine, Luxembourg Institute of Health (LIH), Strassen, Luxembourg; Department of Neurology, Centre Hospitalier de Luxembourg (CHL), Luxembourg
| | - Enrico Glaab
- Biomedical Data Science, Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Esch-sur-Alzette, Luxembourg.
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Chen X, He C, Ma J, Yang R, Qi Q, Gao Z, Du T, Zhang P, Li Y, Cai M, Zhang Y. Motor progression trajectories and risk of mild cognitive impairment in Parkinson's disease: A latent class trajectory model from PPMI cohort. CNS Neurosci Ther 2024; 30:e14918. [PMID: 39129413 PMCID: PMC11317696 DOI: 10.1111/cns.14918] [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: 01/02/2024] [Revised: 06/14/2024] [Accepted: 07/30/2024] [Indexed: 08/13/2024] Open
Abstract
AIMS Rare studies have investigated the association between heterogeneity of motor progression and risk of early cognitive impairment in Parkinson's disease (PD). In this study, we aim to identify distinct trajectories of motor progression longitudinally and investigate their impact on predicting mild cognitive impairment (MCI). METHODS A 5-year cohort including 415 PD patients at baseline was collected from the Parkinson's Progression Markers Initiative. The severity of motor symptoms was evaluated using the Movement Disorder Society Unified Parkinson's Disease Rating Scale part III. The latent class trajectory model and nonlinear mixed-effects model were used to analyze and delineate the longitudinal changes in motor symptoms. Propensity score matching (PSM) was used to minimize the impact of potential confounders. Cox proportional hazard models were applied to calculate hazard ratios for MCI, and a Kaplan-Meier curve was generated using the occurrence of MCI during the follow-up as the time-to-event. RESULTS Two latent trajectories were identified: a mild and remitting motor symptoms class (Class 1, 33.01%) and a severe and progressive motor symptom class (Class 2, 66.99%). Patients in Class 2 initially exhibited severe motor symptoms that worsened progressively despite receiving anti-PD medications. In comparison, patients in Class 1 exhibited milder symptoms that improved following drug therapy and a slower progression. During a 5-year follow-up, patients in Class 2 showed a higher risk of developing MCI compared to those in Class 1 before PSM (Log-Rank 28.58, p < 0.001) and after PSM (Log-Rank 8.20, p = 0.004). CONCLUSIONS PD patients with severe and progressive motor symptoms are more likely to develop MCI than those with mild and stable motor symptoms.
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Affiliation(s)
- Xi Chen
- Shantou University Medical CollegeShantouGuangdong ProvinceChina
- Department of Neurology, Guangdong Neuroscience Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences)Southern Medical UniversityGuangzhouGuangdong ProvinceChina
| | - Chentao He
- Department of Neurology, Guangdong Neuroscience Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences)Southern Medical UniversityGuangzhouGuangdong ProvinceChina
| | - Jianrui Ma
- Shantou University Medical CollegeShantouGuangdong ProvinceChina
| | - Rui Yang
- Department of Neurology, Guangdong Neuroscience Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences)Southern Medical UniversityGuangzhouGuangdong ProvinceChina
- School of MedicineSouth China University of TechnologyGuangzhouChina
| | - Qi Qi
- Department of Neurology, Guangdong Neuroscience Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences)Southern Medical UniversityGuangzhouGuangdong ProvinceChina
- Guangdong Cardiovascular InstituteGuangdong Provincial People's Hospital, Guangdong Academy of Medical SciencesGuangzhouChina
| | - Ziqi Gao
- Department of Neurology, Guangdong Neuroscience Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences)Southern Medical UniversityGuangzhouGuangdong ProvinceChina
- School of MedicineSouth China University of TechnologyGuangzhouChina
| | - Tingyue Du
- Shantou University Medical CollegeShantouGuangdong ProvinceChina
| | - Piao Zhang
- Department of Neurology, Guangdong Neuroscience Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences)Southern Medical UniversityGuangzhouGuangdong ProvinceChina
| | - Yan Li
- Department of Neurology, Guangdong Neuroscience Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences)Southern Medical UniversityGuangzhouGuangdong ProvinceChina
| | - Mengfei Cai
- Department of Neurology, Guangdong Neuroscience Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences)Southern Medical UniversityGuangzhouGuangdong ProvinceChina
- Guangdong Cardiovascular InstituteGuangdong Provincial People's Hospital, Guangdong Academy of Medical SciencesGuangzhouChina
| | - Yuhu Zhang
- Shantou University Medical CollegeShantouGuangdong ProvinceChina
- Department of Neurology, Guangdong Neuroscience Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences)Southern Medical UniversityGuangzhouGuangdong ProvinceChina
- Guangzhou Key Laboratory of Diagnosis and Treatment for Neurodegenerative DiseasesGuangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences)GuangzhouChina
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Doskas T, Vadikolias K, Ntoskas K, Vavougios GD, Tsiptsios D, Stamati P, Liampas I, Siokas V, Messinis L, Nasios G, Dardiotis E. Neurocognitive Impairment and Social Cognition in Parkinson's Disease Patients. Neurol Int 2024; 16:432-449. [PMID: 38668129 PMCID: PMC11054167 DOI: 10.3390/neurolint16020032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2024] [Revised: 04/06/2024] [Accepted: 04/11/2024] [Indexed: 04/29/2024] Open
Abstract
In addition to motor symptoms, neurocognitive impairment (NCI) affects patients with prodromal Parkinson's disease (PD). NCI in PD ranges from subjective cognitive complaints to dementia. The purpose of this review is to present the available evidence of NCI in PD and highlight the heterogeneity of NCI phenotypes as well as the range of factors that contribute to NCI onset and progression. A review of publications related to NCI in PD up to March 2023 was performed using PubMed/Medline. There is an interconnection between the neurocognitive and motor symptoms of the disease, suggesting a common underlying pathophysiology as well as an interconnection between NCI and non-motor symptoms, such as mood disorders, which may contribute to confounding NCI. Motor and non-motor symptom evaluation could be used prognostically for NCI onset and progression in combination with imaging, laboratory, and genetic data. Additionally, the implications of NCI on the social cognition of afflicted patients warrant its prompt management. The etiology of NCI onset and its progression in PD is multifactorial and its effects are equally grave as the motor effects. This review highlights the importance of the prompt identification of subjective cognitive complaints in PD patients and NCI management.
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Affiliation(s)
- Triantafyllos Doskas
- Department of Neurology, Athens Naval Hospital, 11521 Athens, Greece;
- Department of Neurology, General University Hospital of Alexandroupoli, 68100 Alexandroupoli, Greece; (K.V.); (D.T.)
| | - Konstantinos Vadikolias
- Department of Neurology, General University Hospital of Alexandroupoli, 68100 Alexandroupoli, Greece; (K.V.); (D.T.)
| | | | - George D. Vavougios
- Department of Neurology, Athens Naval Hospital, 11521 Athens, Greece;
- Department of Neurology, Faculty of Medicine, University of Cyprus, 1678 Lefkosia, Cyprus
- Department of Respiratory Medicine, Faculty of Medicine, School of Health Sciences, University of Thessaly, 41500 Larissa, Greece
| | - Dimitrios Tsiptsios
- Department of Neurology, General University Hospital of Alexandroupoli, 68100 Alexandroupoli, Greece; (K.V.); (D.T.)
| | - Polyxeni Stamati
- Department of Neurology, Faculty of Medicine, School of Health Sciences, University of Thessaly, 41110 Larissa, Greece; (P.S.); (I.L.); (V.S.); (E.D.)
| | - Ioannis Liampas
- Department of Neurology, Faculty of Medicine, School of Health Sciences, University of Thessaly, 41110 Larissa, Greece; (P.S.); (I.L.); (V.S.); (E.D.)
| | - Vasileios Siokas
- Department of Neurology, Faculty of Medicine, School of Health Sciences, University of Thessaly, 41110 Larissa, Greece; (P.S.); (I.L.); (V.S.); (E.D.)
| | - Lambros Messinis
- School of Psychology, Laboratory of Neuropsychology and Behavioural Neuroscience, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece;
| | - Grigorios Nasios
- Department of Speech and Language Therapy, School of Health Sciences, University of Ioannina, 45500 Ioannina, Greece;
| | - Efthimios Dardiotis
- Department of Neurology, Faculty of Medicine, School of Health Sciences, University of Thessaly, 41110 Larissa, Greece; (P.S.); (I.L.); (V.S.); (E.D.)
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Chung SJ, Kim SH, Park CW, Lee HS, Yun M, Kim YJ, Sohn YH, Jeong Y, Lee PH. Patterns of regional cerebral hypoperfusion in early Parkinson's disease: Clinical implications. Parkinsonism Relat Disord 2024; 121:106024. [PMID: 38377658 DOI: 10.1016/j.parkreldis.2024.106024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/28/2023] [Revised: 01/07/2024] [Accepted: 02/01/2024] [Indexed: 02/22/2024]
Abstract
INTRODUCTION This study aimed to investigate whether regional cerebral perfusion patterns on early-phase 18F-FP-CIT PET scans, which is typically coupled to cerebral metabolism, predict the long-term prognosis of Parkinson's disease (PD). METHODS We enrolled 397 drug-naïve patients with early-stage PD who underwent dual-phase 18F-FP-CIT PET scans. After quantifying the early-phase 18F-FP-CIT PET images, cluster analysis was performed to delineate the PD subtypes according to the patterns of regional cerebral perfusion. We compared the risk of developing levodopa-induced dyskinesia (LID), wearing-off, freezing of gait (FOG), and dementia between the PD subtypes. RESULTS Cluster analysis classified patients into three subtypes: cluster 1 (relatively preserved cortical uptake; n = 175), cluster 2 (decreased uptake in the frontal, parietal, and temporal regions; n = 151), and cluster 3 (decreased uptake in more extensive regions, additionally involving the lateral occipital regions; n = 71). Cluster 1 was characterized by a younger age-of-onset, less severe motor deficits, less severely decreased 18F-FP-CIT binding in the caudate, and better cognitive performance. Cluster 3 was characterized by an older age-of-onset, more severe motor deficits, and poorer cognitive performance. Cluster 2 was intermediate between clusters 1 and 3. Cox regression analyses demonstrated that clusters 2 and 3 had a higher risk for dementia conversion than cluster 1, whereas the risk for developing LID, wearing-off, and FOG did not differ among the clusters. CONCLUSION The patterns of regional cerebral perfusion can provide information on long-term prognosis with regards to cognitive, but not motor aspects of patients with early-stage PD.
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Affiliation(s)
- Seok Jong Chung
- Department of Neurology, Yonsei University College of Medicine, Seoul, South Korea; Department of Neurology, Yongin Severance Hospital, Yonsei University Health System, Yongin, South Korea; YONSEI BEYOND LAB, Yongin, South Korea
| | - Su Hong Kim
- Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology, Daejeon, South Korea; KAIST Institute for Health Science Technology, Korea Advanced Institute of Science and Technology, Daejeon, South Korea; Department of Radiology, Yeungnam University College of Medicine, Daegu, South Korea
| | - Chan Wook Park
- Department of Neurology, Yonsei University College of Medicine, Seoul, South Korea; Department of Physiology, Yonsei University College of Medicine, Seoul, South Korea
| | - Hye Sun Lee
- Biostatistics Collaboration Unit, Yonsei University College of Medicine, Seoul, South Korea
| | - Mijin Yun
- Department of Nuclear Medicine, Yonsei University College of Medicine, Seoul, South Korea
| | - Yun Joong Kim
- Department of Neurology, Yonsei University College of Medicine, Seoul, South Korea; Department of Neurology, Yongin Severance Hospital, Yonsei University Health System, Yongin, South Korea; YONSEI BEYOND LAB, Yongin, South Korea
| | - Young H Sohn
- Department of Neurology, Yonsei University College of Medicine, Seoul, South Korea
| | - Yong Jeong
- KAIST Institute for Health Science Technology, Korea Advanced Institute of Science and Technology, Daejeon, South Korea; Department of Radiology, Yeungnam University College of Medicine, Daegu, South Korea; Program of Brain and Cognitive Engineering, Korea Advanced Institute of Science and Technology, Daejeon, South Korea; Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology, Daejeon, South Korea.
| | - Phil Hyu Lee
- Department of Neurology, Yonsei University College of Medicine, Seoul, South Korea; Severance Biomedical Science Institute, Yonsei University College of Medicine, Seoul, South Korea.
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Chun MY, Chung SJ, Kim SH, Park CW, Jeong SH, Lee HS, Lee PH, Sohn YH, Jeong Y, Kim YJ. Hippocampal Perfusion Affects Motor and Cognitive Functions in Parkinson Disease: An Early Phase 18 F-FP-CIT Positron Emission Tomography Study. Ann Neurol 2024; 95:388-399. [PMID: 37962393 DOI: 10.1002/ana.26827] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2023] [Revised: 10/04/2023] [Accepted: 10/23/2023] [Indexed: 11/15/2023]
Abstract
OBJECTIVE We investigated whether hippocampal perfusion changes are associated with cognitive decline, motor deficits, and the risk of dementia conversion in patients with Parkinson disease (PD). METHODS We recruited patients with newly diagnosed and nonmedicated PD and healthy participants who underwent dual phase 18 F-N-(3-fluoropropyl)-2β-carboxymethoxy-3β-(4-iodophenyl) nortropane positron emission tomography scans. Patients were classified into 3 groups according to hippocampal perfusion measured by standard uptake value ratios (SUVRs): (1) PD hippocampal hypoperfusion group (1 standard deviation [SD] below the mean hippocampal SUVR of healthy controls; PD-hippo-hypo), (2) PD hippocampal hyperperfusion group (1 SD above the mean; PD-hippo-hyper), and (3) the remaining patients (PD-hippo-normal). We compared the baseline cognitive performance, severity of motor deficits, hippocampal volume, striatal dopamine transporter (DAT) availability, and risk of dementia conversion among the groups. RESULTS We included 235 patients (PD-hippo-hypo, n = 21; PD-hippo-normal, n = 157; PD-hippo-hyper, n = 57) and 48 healthy participants. Patients in the PD-hippo-hypo group were older and had smaller hippocampal volumes than those in the other PD groups. The PD-hippo-hypo group showed less severely decreased DAT availability in the putamen than the other groups despite similar severities of motor deficit. The PD-hippo-hypo group had a higher risk of dementia conversion compared to the PD-hippo-normal (hazard ratio = 2.59, p = 0.013) and PD-hippo-hyper (hazard ratio = 3.73, p = 0.006) groups, despite similar cognitive performance at initial assessment between groups. INTERPRETATION Hippocampal hypoperfusion may indicate a reduced capacity to cope with neurodegenerative processes in terms of the development of motor deficits and cognitive decline in patients with PD. ANN NEUROL 2024;95:388-399.
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Affiliation(s)
- Min Young Chun
- Department of Neurology, Yonsei University College of Medicine, Seoul, South Korea
- Department of Neurology, Yongin Severance Hospital, Yonsei University Health System, Yongin, South Korea
- Yonsei Beyond Lab, Yongin, South Korea
| | - Seok Jong Chung
- Department of Neurology, Yonsei University College of Medicine, Seoul, South Korea
- Department of Neurology, Yongin Severance Hospital, Yonsei University Health System, Yongin, South Korea
- Yonsei Beyond Lab, Yongin, South Korea
| | - Su Hong Kim
- Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology, Daejeon, South Korea
- Institute for Health Science Technology, Korea Advanced Institute of Science and Technology, Daejeon, South Korea
- Department of Radiology, Yeungnam University College of Medicine, Daegu, South Korea
| | - Chan Wook Park
- Department of Neurology, Yonsei University College of Medicine, Seoul, South Korea
- Department of Physiology, Yonsei University College of Medicine, Seoul, South Korea
| | - Seong Ho Jeong
- Department of Neurology, Yonsei University College of Medicine, Seoul, South Korea
- Department of Neurology, Inje University Sanggye Paik Hospital, Seoul, South Korea
| | - Hye Sun Lee
- Biostatistics Collaboration Unit, Yonsei University College of Medicine, Seoul, South Korea
| | - Phil Hyu Lee
- Department of Neurology, Yonsei University College of Medicine, Seoul, South Korea
| | - Young H Sohn
- Department of Neurology, Yonsei University College of Medicine, Seoul, South Korea
| | - Yong Jeong
- Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology, Daejeon, South Korea
- Institute for Health Science Technology, Korea Advanced Institute of Science and Technology, Daejeon, South Korea
- Program of Brain and Cognitive Engineering, Korea Advanced Institute of Science and Technology, Daejeon, South Korea
- Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology, Daejeon, South Korea
| | - Yun Joong Kim
- Department of Neurology, Yonsei University College of Medicine, Seoul, South Korea
- Department of Neurology, Yongin Severance Hospital, Yonsei University Health System, Yongin, South Korea
- Yonsei Beyond Lab, Yongin, South Korea
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Herman T, Barer Y, Bitan M, Sobol S, Giladi N, Hausdorff JM. A meta-analysis identifies factors predicting the future development of freezing of gait in Parkinson's disease. NPJ Parkinsons Dis 2023; 9:158. [PMID: 38049430 PMCID: PMC10696025 DOI: 10.1038/s41531-023-00600-2] [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: 06/11/2023] [Accepted: 11/02/2023] [Indexed: 12/06/2023] Open
Abstract
Freezing of gait (FOG) is a debilitating problem that is common among many, but not all, people with Parkinson's disease (PD). Numerous attempts have been made at treating FOG to reduce its negative impact on fall risk, functional independence, and health-related quality of life. However, optimal treatment remains elusive. Observational studies have recently investigated factors that differ among patients with PD who later develop FOG, compared to those who do not. With prediction and prevention in mind, we conducted a systematic review and meta-analysis of publications through 31.12.2022 to identify risk factors. Studies were included if they used a cohort design, included patients with PD without FOG at baseline, data on possible FOG predictors were measured at baseline, and incident FOG was assessed at follow-up. 1068 original papers were identified, 38 met a-priori criteria, and 35 studies were included in the meta-analysis (n = 8973; mean follow-up: 4.1 ± 2.7 years). Factors significantly associated with a risk of incident FOG included: higher age at onset of PD, greater severity of motor symptoms, depression, anxiety, poorer cognitive status, and use of levodopa and COMT inhibitors. Most results were robust in four subgroup analyses. These findings indicate that changes associated with FOG incidence can be detected in a subset of patients with PD, sometimes as long as 12 years before FOG manifests, supporting the possibility of predicting FOG incidence. Intriguingly, some of these factors may be modifiable, suggesting that steps can be taken to lower the risk and possibly even prevent the future development of FOG.
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Affiliation(s)
- Talia Herman
- Center for the Study of Movement, Cognition and Mobility, Neurological Institute, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel
| | - Yael Barer
- Maccabitech, Maccabi Institute for Research and Innovation, Maccabi Healthcare Services, Tel Aviv, Israel
| | - Michal Bitan
- School of Computer Science, The College of Management, Rishon LeZion, Israel
| | - Shani Sobol
- Center for the Study of Movement, Cognition and Mobility, Neurological Institute, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel
| | - Nir Giladi
- Center for the Study of Movement, Cognition and Mobility, Neurological Institute, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
- Department of Neurology, Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Jeffrey M Hausdorff
- Center for the Study of Movement, Cognition and Mobility, Neurological Institute, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel.
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel.
- Department of Orthopedic Surgery and Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA.
- Department of Physical Therapy, Faculty of Medicine, Tel Aviv, Israel.
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9
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Aiello EN, D'Iorio A, Solca F, Torre S, Bonetti R, Scheveger F, Colombo E, Maranzano A, Maderna L, Morelli C, Doretti A, Amboni M, Vitale C, Verde F, Ferrucci R, Barbieri S, Zirone E, Priori A, Pravettoni G, Santangelo G, Silani V, Ticozzi N, Ciammola A, Poletti B. Clinimetrics and feasibility of the Italian version of the Frontal Assessment Battery (FAB) in non-demented Parkinson's disease patients. J Neural Transm (Vienna) 2023; 130:687-696. [PMID: 36976351 DOI: 10.1007/s00702-023-02624-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Accepted: 03/18/2023] [Indexed: 03/29/2023]
Abstract
BACKGROUND This study aimed at assessing the cross-sectional and longitudinal clinimetrics and feasibility of the Frontal Assessment Battery (FAB) in non-demented Parkinson's disease (PD) patients. METHODS N = 109 PD patients underwent the FAB and the Montreal Cognitive Assessment (MoCA). A subsample of patients further underwent a thorough motor, functional and behavioral evaluation (the last including measures of anxiety, depression and apathy). A further subsample was administered a second-level cognitive battery tapping on attention, executive functioning, language, memory, praxis and visuo-spatial abilities. The following properties of the FAB were tested: (1) concurrent validity and diagnostics against the MoCA; (2) convergent validity against the second-level cognitive battery; (4) association with motor, functional and behavioral measures; (5) capability to discriminate patients from healthy controls (HCs; N = 96); (6) assessing its test-retest reliability, susceptibility to practice effects and predictive validity against the MoCA, as well as deriving reliable change indices (RCIs) for it, at a ≈ 6-month interval, within a subsample of patients (N = 33). RESULTS The FAB predicted MoCA scores at both T0 and T1, converged with the vast majority of second-level cognitive measures and was associated with functional independence and apathy. It accurately identified cognitive impairment (i.e., a below-cut-off MoCA score) in patients, also discriminating patients from HCs. The FAB was reliable at retest and free of practice effects; RCIs were derived according to a standardized regression-based approach. DISCUSSION The FAB is a clinimetrically sound and feasible screener for detecting dysexecutive-based cognitive impairment in non-demented PD patients.
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Affiliation(s)
- Edoardo Nicolò Aiello
- Department of Neurology and Laboratory of Neuroscience, IRCCS Istituto Auxologico Italiano, Piazzale Brescia 20, 20149, Milan, MI, Italy
| | - Alfonsina D'Iorio
- Department of Psychology, University of Campania "Luigi Vanvitelli", Caserta, Italy
| | - Federica Solca
- Department of Neurology and Laboratory of Neuroscience, IRCCS Istituto Auxologico Italiano, Piazzale Brescia 20, 20149, Milan, MI, Italy
| | - Silvia Torre
- Department of Neurology and Laboratory of Neuroscience, IRCCS Istituto Auxologico Italiano, Piazzale Brescia 20, 20149, Milan, MI, Italy
| | - Ruggero Bonetti
- Neurology Residency Program, Università Degli Studi Di Milano, Milan, Italy
| | | | - Eleonora Colombo
- Department of Neurology and Laboratory of Neuroscience, IRCCS Istituto Auxologico Italiano, Piazzale Brescia 20, 20149, Milan, MI, Italy
| | - Alessio Maranzano
- Department of Neurology and Laboratory of Neuroscience, IRCCS Istituto Auxologico Italiano, Piazzale Brescia 20, 20149, Milan, MI, Italy
| | - Luca Maderna
- Department of Neurology and Laboratory of Neuroscience, IRCCS Istituto Auxologico Italiano, Piazzale Brescia 20, 20149, Milan, MI, Italy
| | - Claudia Morelli
- Department of Neurology and Laboratory of Neuroscience, IRCCS Istituto Auxologico Italiano, Piazzale Brescia 20, 20149, Milan, MI, Italy
| | - Alberto Doretti
- Department of Neurology and Laboratory of Neuroscience, IRCCS Istituto Auxologico Italiano, Piazzale Brescia 20, 20149, Milan, MI, Italy
| | - Marianna Amboni
- Institute of Diagnosis and Health, IDC-Hermitage Capodimonte, Naples, Italy
- Department of Medicine, Surgery and Dentistry, University of Salerno, Salerno, Italy
| | - Carmine Vitale
- Institute of Diagnosis and Health, IDC-Hermitage Capodimonte, Naples, Italy
- Department of Motor Sciences and Wellness, University "Parthenope", Naples, Italy
| | - Federico Verde
- Department of Neurology and Laboratory of Neuroscience, IRCCS Istituto Auxologico Italiano, Piazzale Brescia 20, 20149, Milan, MI, Italy
- Department of Pathophysiology and Transplantation, "Dino Ferrari Center", Università Degli Studi Di Milano, Milan, Italy
| | - Roberta Ferrucci
- Department of Oncology and Hemato-Oncology, University of Milan, Milan, Italy
- Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Sergio Barbieri
- Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Eleonora Zirone
- Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Alberto Priori
- ASST Santi Paolo e Carlo, San Paolo University Hospital, Milan, Italy
- Department of Health Sciences, "Aldo Ravelli" Center for Neurotechnology and Experimental Brain Therapeutics, University of Milan, Milan, Italy
| | - Gabriella Pravettoni
- Department of Oncology and Hemato-Oncology, University of Milan, Milan, Italy
- Applied Research Division for Cognitive and Psychological Science, IEO, European Institute of Oncology, IRCCS, Milan, Italy
| | - Gabriella Santangelo
- Department of Psychology, University of Campania "Luigi Vanvitelli", Caserta, Italy
| | - Vincenzo Silani
- Department of Neurology and Laboratory of Neuroscience, IRCCS Istituto Auxologico Italiano, Piazzale Brescia 20, 20149, Milan, MI, Italy
- Department of Pathophysiology and Transplantation, "Dino Ferrari Center", Università Degli Studi Di Milano, Milan, Italy
| | - Nicola Ticozzi
- Department of Neurology and Laboratory of Neuroscience, IRCCS Istituto Auxologico Italiano, Piazzale Brescia 20, 20149, Milan, MI, Italy
- Department of Pathophysiology and Transplantation, "Dino Ferrari Center", Università Degli Studi Di Milano, Milan, Italy
| | - Andrea Ciammola
- Department of Neurology and Laboratory of Neuroscience, IRCCS Istituto Auxologico Italiano, Piazzale Brescia 20, 20149, Milan, MI, Italy
| | - Barbara Poletti
- Department of Neurology and Laboratory of Neuroscience, IRCCS Istituto Auxologico Italiano, Piazzale Brescia 20, 20149, Milan, MI, Italy.
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10
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Gan Y, Xie H, Qin G, Wu D, Shan M, Hu T, Yin Z, An Q, Ma R, Wang S, Zhang Q, Zhu G, Zhang J. Association between Cognitive Impairment and Freezing of Gait in Patients with Parkinson's Disease. J Clin Med 2023; 12:jcm12082799. [PMID: 37109137 PMCID: PMC10145607 DOI: 10.3390/jcm12082799] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Revised: 03/27/2023] [Accepted: 04/04/2023] [Indexed: 04/29/2023] Open
Abstract
Background: Freezing of gait (FOG) is a common disabling symptom in Parkinson's disease (PD). Cognitive impairment may contribute to FOG. Nevertheless, their correlations remain controversial. We aimed to investigate cognitive differences between PD patients with and without FOG (nFOG), explore correlations between FOG severity and cognitive performance and assess cognitive heterogeneity within the FOG patients. Methods: Seventy-four PD patients (41 FOG, 33 nFOG) and 32 healthy controls (HCs) were included. Comprehensive neuropsychological assessments testing cognitive domains of global cognition, executive function/attention, working memory, and visuospatial function were performed. Cognitive performance was compared between groups using independent t-test and ANCOVA adjusting for age, sex, education, disease duration and motor symptoms. The k-means cluster analysis was used to explore cognitive heterogeneity within the FOG group. Correlation between FOG severity and cognition were analyzed using partial correlations. Results: FOG patients showed significantly poorer performance in global cognition (MoCA, p < 0.001), frontal lobe function (FAB, p = 0.015), attention and working memory (SDMT, p < 0.001) and executive function (SIE, p = 0.038) than nFOG patients. The FOG group was divided into two clusters using the cluster analysis, of which cluster 1 exhibited worse cognition, and with older age, lower improvement rate, higher FOGQ3 score, and higher proportion of levodopa-unresponsive FOG than cluster 2. Further, in the FOG group, cognition was significantly correlated with FOG severity in MoCA (r = -0.382, p = 0.021), Stroop-C (r = 0.362, p = 0.030) and SIE (r = 0.369, p = 0.027). Conclusions: This study demonstrated that the cognitive impairments of FOG were mainly reflected by global cognition, frontal lobe function, executive function, attention and working memory. There may be heterogeneity in the cognitive impairment of FOG patients. Additionally, executive function was significantly correlated with FOG severity.
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Affiliation(s)
- Yifei Gan
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
| | - Hutao Xie
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
| | - Guofan Qin
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
| | - Delong Wu
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
| | - Ming Shan
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
- Department of Neurosurgery, The First Affiliated Hospital of Anhui Medical University, Jixi Road 218, Hefei 230022, China
| | - Tianqi Hu
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
| | - Zixiao Yin
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
| | - Qi An
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
| | - Ruoyu Ma
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
| | - Shu Wang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
| | - Quan Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
| | - Guanyu Zhu
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
| | - Jianguo Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
- Beijing Key Laboratory of Neurostimulation, Beijing 100070, China
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11
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Harrington DL, Shen Q, Wei X, Litvan I, Huang M, Lee RR. Functional topologies of spatial cognition predict cognitive and motor progression in Parkinson’s. Front Aging Neurosci 2022; 14:987225. [PMID: 36299614 PMCID: PMC9589098 DOI: 10.3389/fnagi.2022.987225] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2022] [Accepted: 09/12/2022] [Indexed: 11/23/2022] Open
Abstract
Background Spatial cognition deteriorates in Parkinson’s disease (PD), but the neural substrates are not understood, despite the risk for future dementia. It is also unclear whether deteriorating spatial cognition relates to changes in other cognitive domains or contributes to motor dysfunction. Objective This study aimed to identify functional connectivity abnormalities in cognitively normal PD (PDCN) in regions that support spatial cognition to determine their relationship to interfacing cognitive functions and motor disability, and to determine if they predict cognitive and motor progression 2 years later in a PDCN subsample. Methods Sixty-three PDCN and 43 controls underwent functional MRI while judging whether pictures, rotated at various angles, depicted the left or right hand. The task activates systems that respond to increases in rotation angle, a proxy for visuospatial difficulty. Angle-modulated functional connectivity was analyzed for frontal cortex, posterior cortex, and basal ganglia regions. Results Two aberrant connectivity patterns were found in PDCN, which were condensed into principal components that characterized the strength and topology of angle-modulated connectivity. One topology related to a marked failure to amplify frontal, posterior, and basal ganglia connectivity with other brain areas as visuospatial demands increased, unlike the control group (control features). Another topology related to functional reorganization whereby regional connectivity was strengthened with brain areas not recruited by the control group (PDCN features). Functional topologies correlated with diverse cognitive domains at baseline, underscoring their influences on spatial cognition. In PDCN, expression of topologies that were control features predicted greater cognitive progression longitudinally, suggesting inefficient communications within circuitry normally recruited to handle spatial demands. Conversely, stronger expression of topologies that were PDCN features predicted less longitudinal cognitive decline, suggesting functional reorganization was compensatory. Parieto-occipital topologies (control features) had different prognostic implications for longitudinal changes in motor disability. Expression of one topology predicted less motor decline, whereas expression of another predicted increased postural instability and gait disturbance (PIGD) feature severity. Concurrently, greater longitudinal decline in spatial cognition predicted greater motor and PIGD feature progression, suggesting deterioration in shared substrates. Conclusion These novel discoveries elucidate functional mechanisms of visuospatial cognition in PDCN, which foreshadow future cognitive and motor disability.
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Affiliation(s)
- Deborah L. Harrington
- Research Service, VA San Diego Healthcare System, San Diego, CA, United States
- Department of Radiology, University of California, San Diego, La Jolla, CA, United States
- *Correspondence: Deborah L. Harrington,
| | - Qian Shen
- Research Service, VA San Diego Healthcare System, San Diego, CA, United States
- Department of Radiology, University of California, San Diego, La Jolla, CA, United States
| | - Xiangyu Wei
- Research Service, VA San Diego Healthcare System, San Diego, CA, United States
- Revelle College, University of California, San Diego, La Jolla, CA, United States
| | - Irene Litvan
- Department of Neurosciences, University of California, San Diego, La Jolla, CA, United States
| | - Mingxiong Huang
- Department of Radiology, University of California, San Diego, La Jolla, CA, United States
- Radiology Service, VA San Diego Healthcare System, San Diego, CA, United States
| | - Roland R. Lee
- Department of Radiology, University of California, San Diego, La Jolla, CA, United States
- Radiology Service, VA San Diego Healthcare System, San Diego, CA, United States
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12
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Chung SJ, Kim YJ, Kim YJ, Lee HS, Yun M, Lee PH, Jeong Y, Sohn YH. Potential Link Between Cognition and Motor Reserve in Patients With Parkinson's Disease. J Mov Disord 2022; 15:249-257. [PMID: 36065615 DOI: 10.14802/jmd.22063] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2022] [Accepted: 06/17/2022] [Indexed: 11/24/2022] Open
Abstract
Objective To investigate whether there is a link between cognitive function and motor reserve (i.e., individual capacity to cope with nigrostriatal dopamine depletion) in patients with newly diagnosed Parkinson's disease (PD). Methods A total of 163 patients with drug-naïve PD who underwent 18F-FP-CIT PET, brain MRI, and a detailed neuropsychological test were enrolled. We estimated individual motor reserve based on initial motor deficits and striatal dopamine depletion using a residual model. We performed correlation analyses between motor reserve estimates and cognitive composite scores. Diffusion connectometry analysis was performed to map the white matter fiber tracts, of which fractional anisotropy (FA) values were well correlated with motor reserve estimates. Additionally, Cox regression analysis was used to assess the effect of initial motor reserve on the risk of dementia conversion. Results The motor reserve estimate was positively correlated with the composite score of the verbal memory function domain (γ = 0.246) and with the years of education (γ = 0.251). Connectometry analysis showed that FA values in the left fornix were positively correlated with the motor reserve estimate, while no fiber tracts were negatively correlated with the motor reserve estimate. Cox regression analysis demonstrated that higher motor reserve estimates tended to be associated with a lower risk of dementia conversion (hazard ratio, 0.781; 95% confidence interval, 0.576-1.058). Conclusion The present study demonstrated that the motor reserve estimate was well correlated with verbal memory function and with white matter integrity in the left fornix, suggesting a possible link between cognition and motor reserve in patients with PD.
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Affiliation(s)
- Seok Jong Chung
- Department of Neurology, Yonsei University College of Medicine, Seoul, Korea.,Department of Neurology, Yongin Severance Hospital, Yonsei University Health System, Yongin, Korea.,YONSEI BEYOND LAB, Yongin, Korea
| | - Yae Ji Kim
- Program of Brain and Cognitive Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Korea.,KI for Health Science and Technology, Korea Advanced Institute of Science and Technology, Daejeon, Korea
| | - Yun Joong Kim
- Department of Neurology, Yonsei University College of Medicine, Seoul, Korea.,Department of Neurology, Yongin Severance Hospital, Yonsei University Health System, Yongin, Korea.,YONSEI BEYOND LAB, Yongin, Korea
| | - Hye Sun Lee
- Biostatistics Collaboration Unit, Yonsei University College of Medicine, Seoul, Korea
| | - Mijin Yun
- Department of Nuclear Medicine, Yonsei University College of Medicine, Seoul, Korea
| | - Phil Hyu Lee
- Department of Neurology, Yonsei University College of Medicine, Seoul, Korea
| | - Yong Jeong
- YONSEI BEYOND LAB, Yongin, Korea.,Program of Brain and Cognitive Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Korea.,Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Korea
| | - Young H Sohn
- Department of Neurology, Yonsei University College of Medicine, Seoul, Korea
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13
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Kim YJ, Park CW, Shin HW, Lee HS, Kim YJ, Yun M, Lee PH, Sohn YH, Jeong Y, Chung SJ. Identifying the white matter structural network of motor reserve in early Parkinson's disease. Parkinsonism Relat Disord 2022; 102:108-114. [PMID: 35987039 DOI: 10.1016/j.parkreldis.2022.08.005] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/26/2022] [Revised: 07/18/2022] [Accepted: 08/07/2022] [Indexed: 11/18/2022]
Abstract
INTRODUCTION Motor reserve refers to the individual capacity to cope with nigrostriatal dopamine depletion in Parkinson's disease (PD). This study aimed to explore the white matter structural network associated with motor reserve in patients with newly diagnosed PD. METHODS A total of 238 patients with early-stage drug-naïve PD who underwent 18F-FP-CIT PET and brain MRI scans at initial assessment were enrolled. We estimated individual motor reserve based on the Unified Parkinson's Disease Rating Scale Part III (UPDRS-III) scores and dopamine transporter availability in the posterior putamen using a residual model. Then, we performed threshold-free network-based statistics (TFNBS) analysis to identify the structural brain network associated with the estimated motor reserve. We also assessed the effect of the network connectivity strength on the longitudinal increase in levodopa-equivalent dose (LED). RESULTS The mean age at PD symptom onset was 69.10 ± 9.03 years and the mean UPDRS-III score at the time of PD diagnosis was 22.44 ± 9.72. TFNBS analysis identified a motor reserve-associated structural network whose nodes were mainly in the frontal region and cerebellum. Higher network strength (i.e., greater motor reserve) was associated with a slower longitudinal increase in LED during a 3-year follow-up period. CONCLUSION The structural brain network is associated with motor reserve in patients with PD. Connectivity strength within the identified network indicates the individual's capacity to tolerate PD-related pathologies, which is maintained with disease progression and affects the long-term motor prognosis of PD.
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Affiliation(s)
- Yae Ji Kim
- Program of Brain and Cognitive Engineering, Korea Advanced Institute of Science and Technology, Daejeon, South Korea; KI for Health Science and Technology, Korea Advanced Institute of Science and Technology, Daejeon, South Korea
| | - Chan Wook Park
- Department of Neurology, Yonsei University College of Medicine, Seoul, South Korea; Department of Physiology, Yonsei University College of Medicine, Seoul, South Korea
| | - Hye Won Shin
- Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology, Daejeon, South Korea
| | - Hye Sun Lee
- Biostatistics Collaboration Unit, Yonsei University College of Medicine, Seoul, South Korea
| | - Yun Joong Kim
- Department of Neurology, Yonsei University College of Medicine, Seoul, South Korea; Department of Neurology, Yongin Severance Hospital, Yonsei University Health System, Yongin, South Korea; YONSEI BEYOND LAB, Yongin, South Korea
| | - Mijin Yun
- Department of Nuclear Medicine, Yonsei University College of Medicine, Seoul, South Korea
| | - Phil Hyu Lee
- Department of Neurology, Yonsei University College of Medicine, Seoul, South Korea
| | - Young H Sohn
- Department of Neurology, Yonsei University College of Medicine, Seoul, South Korea
| | - Yong Jeong
- Program of Brain and Cognitive Engineering, Korea Advanced Institute of Science and Technology, Daejeon, South Korea; KI for Health Science and Technology, Korea Advanced Institute of Science and Technology, Daejeon, South Korea; Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology, Daejeon, South Korea.
| | - Seok Jong Chung
- Department of Neurology, Yonsei University College of Medicine, Seoul, South Korea; Department of Neurology, Yongin Severance Hospital, Yonsei University Health System, Yongin, South Korea; YONSEI BEYOND LAB, Yongin, South Korea.
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