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Zhang X, Li R, Xia Y, Zhao H, Cai L, Sha J, Xiao Q, Xiang J, Zhang C, Xu K. Topological patterns of motor networks in Parkinson’s disease with different sides of onset: A resting-state-informed structural connectome study. Front Aging Neurosci 2022; 14:1041744. [DOI: 10.3389/fnagi.2022.1041744] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2022] [Accepted: 10/12/2022] [Indexed: 11/13/2022] Open
Abstract
Parkinson’s disease (PD) has a characteristically unilateral pattern of symptoms at onset and in the early stages; this lateralization is considered a diagnostically important diagnosis feature. We aimed to compare the graph-theoretical properties of whole-brain networks generated by using resting-state functional MRI (rs-fMRI), diffusion tensor imaging (DTI), and the resting-state-informed structural connectome (rsSC) in patients with left-onset PD (LPD), right-onset PD (RPD), and healthy controls (HCs). We recruited 26 patients with PD (13 with LPD and 13 with RPD) as well as 13 age- and sex-matched HCs. Rs-fMRI and DTI were performed in all subjects. Graph-theoretical analysis was used to calculate the local and global efficiency of a whole-brain network generated by rs-fMRI, DTI, and rsSC. Two-sample t-tests and Pearson correlation analysis were conducted. Significantly decreased global and local efficiency were revealed specifically in LPD patients compared with HCs when the rsSC network was used; no significant intergroup difference was found by using rs-fMRI or DTI alone. For rsSC network analysis, multiple network metrics were found to be abnormal in LPD. The degree centrality of the left precuneus was significantly correlated with the Unified Parkinson’s Disease Rating Scale (UPDRS) score and disease duration (p = 0.030, r = 0.599; p = 0.037, r = 0.582). The topological properties of motor-related brain networks can differentiate LPD and RPD. Nodal metrics may serve as important structural features for PD diagnosis and monitoring of disease progression. Collectively, these findings may provide neurobiological insights into the lateralization of PD onset.
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Pelzer EA, Stürmer S, Feis DL, Melzer C, Schwartz F, Scharge M, Eggers C, Tittgemeyer M, Timmermann L. Clustering of Parkinson subtypes reveals strong influence of DRD2 polymorphism and gender. Sci Rep 2022; 12:6038. [PMID: 35411010 PMCID: PMC9001640 DOI: 10.1038/s41598-022-09657-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2021] [Accepted: 03/07/2022] [Indexed: 12/11/2022] Open
Abstract
AbstractMost classification approaches for idiopathic Parkinson’s disease subtypes primarily focus on motor and non-motor symptoms. Besides these characteristics, other features, including gender or genetic polymorphism of dopamine receptors are potential factors influencing the disease’s phenotype. By utilizing a kmeans-clustering algorithm we were able to identify three subgroups mainly characterized by gender, DRD2 Taq1A (rs1800497) polymorphism—associated with changes in dopamine signaling in the brain—and disease progression. A subsequent regression analysis of these subgroups further suggests an influence of their characteristics on the daily levodopa dosage, an indicator for medication response. These findings could promote further enhancements in individualized therapies for idiopathic Parkinson’s disease.
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Cuesta MJ, Lecumberri P, Moreno-Izco L, López-Ilundain JM, Ribeiro M, Cabada T, Lorente-Omeñaca R, de Erausquin G, García-Martí G, Sanjuan J, Sánchez-Torres AM, Gómez M, Peralta V. Motor abnormalities and basal ganglia in first-episode psychosis (FEP). Psychol Med 2021; 51:1625-1636. [PMID: 32114994 DOI: 10.1017/s0033291720000343] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
BACKGROUND Motor abnormalities (MAs) are the primary manifestations of schizophrenia. However, the extent to which MAs are related to alterations of subcortical structures remains understudied. METHODS We aimed to investigate the associations of MAs and basal ganglia abnormalities in first-episode psychosis (FEP) and healthy controls. Magnetic resonance imaging was performed on 48 right-handed FEP and 23 age-, gender-, handedness-, and educational attainment-matched controls, to obtain basal ganglia shape analysis, diffusion tensor imaging techniques (fractional anisotropy and mean diffusivity), and relaxometry (R2*) to estimate iron load. A comprehensive motor battery was applied including the assessment of parkinsonism, catatonic signs, and neurological soft signs (NSS). A fully automated model-based segmentation algorithm on 1.5T MRI anatomical images and accurate corregistration of diffusion and T2* volumes and R2* was used. RESULTS FEP patients showed significant local atrophic changes in left globus pallidus nucleus regarding controls. Hypertrophic changes in left-side caudate were associated with higher scores in sensory integration, and in right accumbens with tremor subscale. FEP patients showed lower fractional anisotropy measures than controls but no significant differences regarding mean diffusivity and iron load of basal ganglia. However, iron load in left basal ganglia and right accumbens correlated significantly with higher extrapyramidal and motor coordination signs in FEP patients. CONCLUSIONS Taken together, iron load in left basal ganglia may have a role in the emergence of extrapyramidal signs and NSS of FEP patients and in consequence in the pathophysiology of psychosis.
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Affiliation(s)
- Manuel J Cuesta
- Department of Psychiatry, Complejo Hospitalario de Navarra, Pamplona, Spain
- IdiSNA, Navarra Institute for Health Research, Pamplona, Spain
| | - Pablo Lecumberri
- IdiSNA, Navarra Institute for Health Research, Pamplona, Spain
- Movalsys S. L., NavarraBiomed, Pamplona, Spain
| | - Lucia Moreno-Izco
- Department of Psychiatry, Complejo Hospitalario de Navarra, Pamplona, Spain
- IdiSNA, Navarra Institute for Health Research, Pamplona, Spain
| | - Jose M López-Ilundain
- Department of Psychiatry, Complejo Hospitalario de Navarra, Pamplona, Spain
- IdiSNA, Navarra Institute for Health Research, Pamplona, Spain
| | - María Ribeiro
- Department of Psychiatry, Complejo Hospitalario de Navarra, Pamplona, Spain
- IdiSNA, Navarra Institute for Health Research, Pamplona, Spain
| | - Teresa Cabada
- IdiSNA, Navarra Institute for Health Research, Pamplona, Spain
- Department of Neuroradiology, Complejo Hospitalario de Navarra, Pamplona, Spain
| | - Ruth Lorente-Omeñaca
- Department of Psychiatry, Complejo Hospitalario de Navarra, Pamplona, Spain
- IdiSNA, Navarra Institute for Health Research, Pamplona, Spain
| | - Gabriel de Erausquin
- Zachry Foundation, The Glenn Biggs Institute of Alzheimer's & Neurodegenerative Disorders, UT Heath San Antonio, Texas, USA
| | - Gracian García-Martí
- Radiology Department, CIBERSAM, Valencia, España, Quirón Salud Hospital, Valencia, España
| | - Julio Sanjuan
- Research Institute of Clinic University Hospital of Valencia (INCLIVA), Valencia, Spain
- CIBERSAM, Biomedical Research Network on Mental Health Area, Madrid, Spain
- Department of Psychiatric, University of Valencia School of Medicine, Valencia, Spain
| | - Ana M Sánchez-Torres
- Department of Psychiatry, Complejo Hospitalario de Navarra, Pamplona, Spain
- IdiSNA, Navarra Institute for Health Research, Pamplona, Spain
| | - Marisol Gómez
- IdiSNA, Navarra Institute for Health Research, Pamplona, Spain
- Movalsys S. L., NavarraBiomed, Pamplona, Spain
- Department of Statistics, Computer Science and Mathematics, Universidad Pública de Navarra (UPNA), Pamplona, Spain
| | - Victor Peralta
- IdiSNA, Navarra Institute for Health Research, Pamplona, Spain
- Mental Health Department, Servicio Navarro de Salud, Pamplona, Spain
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Wagner D, Eslinger PJ, Sterling NW, Du G, Lee EY, Styner M, Lewis MM, Huang X. Lexical-semantic search related to side of onset and putamen volume in Parkinson's disease. BRAIN AND LANGUAGE 2020; 209:104841. [PMID: 32818719 PMCID: PMC8189666 DOI: 10.1016/j.bandl.2020.104841] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/29/2019] [Revised: 07/20/2020] [Accepted: 07/21/2020] [Indexed: 06/11/2023]
Abstract
Parkinson's disease (PD) is characterized by dopaminergic cell loss and reduced striatal volume. Prior studies have demonstrated striatal involvement in access to lexical-semantic knowledge and damage to this structure may be evident in the lexical properties of responses. Semantic fluency task responses from early stage, non-demented PD participants with right (PD-R) or left (PD-L) lateralizing symptoms were compared to matched controls on lexical properties (word frequency, age of acquisition) and correlated with striatal volumes segmented from T1-weighted brain MR images. PD-R participants produced semantic fluency responses of a lower age of acquisition than PD-L and control participants (p < 0.05). PD-R age of acquisition responses correlated positively with putamen volume (p < 0.05), while age of acquisition of responses correlated negatively with caudate volume in controls (p < 0.05). Findings provide evidence for a role of the striatum in lexical-semantic access and qualitative changes in lexical access in select PD patients.
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Affiliation(s)
- Daymond Wagner
- Departments of Neurology, Pennsylvania State University-Milton S. Hershey Medical Center, Hershey, PA 17033, United States.
| | - Paul J Eslinger
- Departments of Neurology, Pennsylvania State University-Milton S. Hershey Medical Center, Hershey, PA 17033, United States; Departments of Neural and Behavioral Sciences, Pennsylvania State University-Milton S. Hershey Medical Center, Hershey, PA 17033, United States; Departments of Radiology, Pennsylvania State University-Milton S. Hershey Medical Center, Hershey, PA 17033, United States.
| | - Nicholas W Sterling
- Departments of Neurology, Pennsylvania State University-Milton S. Hershey Medical Center, Hershey, PA 17033, United States.
| | - Guangwei Du
- Departments of Neurology, Pennsylvania State University-Milton S. Hershey Medical Center, Hershey, PA 17033, United States.
| | - Eun-Young Lee
- Departments of Neurology, Pennsylvania State University-Milton S. Hershey Medical Center, Hershey, PA 17033, United States.
| | - Martin Styner
- Departments of Psychiatry, University of North Carolina-Chapel Hill, Chapel Hill, NC 27599, United States; Departments of Computer Science, University of North Carolina-Chapel Hill, Chapel Hill, NC 27599, United States.
| | - Mechelle M Lewis
- Departments of Neurology, Pennsylvania State University-Milton S. Hershey Medical Center, Hershey, PA 17033, United States; Departments of Pharmacology, Pennsylvania State University-Milton S. Hershey Medical Center, Hershey, PA 17033, United States.
| | - Xuemei Huang
- Departments of Neurology, Pennsylvania State University-Milton S. Hershey Medical Center, Hershey, PA 17033, United States; Departments of Pharmacology, Pennsylvania State University-Milton S. Hershey Medical Center, Hershey, PA 17033, United States; Departments of Neurosurgery, Pennsylvania State University-Milton S. Hershey Medical Center, Hershey, PA 17033, United States; Departments of Kinesiology, Pennsylvania State University-Milton S. Hershey Medical Center, Hershey, PA 17033, United States.
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Liu Y, Tong S, Ding L, Liu N, Gao D. Serum levels of glial cell line-derived neurotrophic factor and multiple neurotransmitters: In relation to cognitive performance in Parkinson's disease with mild cognitive impairment. Int J Geriatr Psychiatry 2020; 35:153-162. [PMID: 31650626 DOI: 10.1002/gps.5222] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/25/2018] [Accepted: 09/24/2019] [Indexed: 11/06/2022]
Abstract
OBJECTIVES Mild cognitive impairment is a common non-motor feature of Parkinson's disease, termed PD-MCI. But there is a scarcity of data on the role of glial cell line-derived neurotrophic factor (GDNF) and neurotransmitters in pathogenesis of PD-MCI. The aim of this project was to detect the serum levels of GDNF and multiple neurotranmitters and explore their relationships with cognitive performance in PD-MCI patients. METHODS Neuropsychological testing was administered to PD patients and healthy controls to investigate different domains of cognitive function. Serum levels of GDNF and four cognition-related neurotransmitters including Dopamine metabolites Homovanillic acid (HVA), acetylcholine (Ach), γ-aminobutyric acid (GABA) and 5-hydroxytryptamine (5-HT) were detected by enzyme-linked immunosorbent assay and liquid chromatography-electrospray ionization tandem mass spectrometry analysis respectively. RESULTS The more serious cognitive impairment of PD, the lower levels of GDNF, HVA and 5-HT. In PD-MCI patients, the levels of GDNF, HVA, Ach, 5-HT, and GABA had a significant positive correlation with Digit span backward test (DSB-T) scores and negative correlation with the scores of Trail Making Test A (TMT-A) and Trail Making Test B (TMT-B) respectively. Effect size analysis showed that GDNF and GDNF*Ach have a significant effect on DSB-T, TMT-A and TMT-B respectively; GDNF*HVA, GDNF*5-HT and GDNF*GABA play important part in Auditory Verbal Learning Test separately. CONCLUSIONS Serum GDNF may be involved in the impairment of attention, memory and executive function of PD-MCI patients, by acting alone or in conjunction with neurotransmitters (HVA, 5-HT, GABA, and Ach).
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Affiliation(s)
- Yi Liu
- Department of Cell Biology and Neurobiology, Xuzhou Key Laboratory of Neurobiology, Xuzhou Medical University. 209 Tongshan Road, Xuzhou, PR China
| | - Shuyan Tong
- Department of Cell Biology and Neurobiology, Xuzhou Key Laboratory of Neurobiology, Xuzhou Medical University. 209 Tongshan Road, Xuzhou, PR China
| | - Li Ding
- Department of Cell Biology and Neurobiology, Xuzhou Key Laboratory of Neurobiology, Xuzhou Medical University. 209 Tongshan Road, Xuzhou, PR China
| | - Na Liu
- Department of Cell Biology and Neurobiology, Xuzhou Key Laboratory of Neurobiology, Xuzhou Medical University. 209 Tongshan Road, Xuzhou, PR China
| | - Dianshuai Gao
- Department of Cell Biology and Neurobiology, Xuzhou Key Laboratory of Neurobiology, Xuzhou Medical University. 209 Tongshan Road, Xuzhou, PR China
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Isaacs BR, Trutti AC, Pelzer E, Tittgemeyer M, Temel Y, Forstmann BU, Keuken MC. Cortico-basal white matter alterations occurring in Parkinson's disease. PLoS One 2019; 14:e0214343. [PMID: 31425517 PMCID: PMC6699705 DOI: 10.1371/journal.pone.0214343] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2019] [Accepted: 07/17/2019] [Indexed: 01/01/2023] Open
Abstract
Magnetic resonance imaging studies typically use standard anatomical atlases for identification and analyses of (patho-)physiological effects on specific brain areas; these atlases often fail to incorporate neuroanatomical alterations that may occur with both age and disease. The present study utilizes Parkinson's disease and age-specific anatomical atlases of the subthalamic nucleus for diffusion tractography, assessing tracts that run between the subthalamic nucleus and a-priori defined cortical areas known to be affected by Parkinson's disease. The results show that the strength of white matter fiber tracts appear to remain structurally unaffected by disease. Contrary to that, Fractional Anisotropy values were shown to decrease in Parkinson's disease patients for connections between the subthalamic nucleus and the pars opercularis of the inferior frontal gyrus, anterior cingulate cortex, the dorsolateral prefrontal cortex and the pre-supplementary motor, collectively involved in preparatory motor control, decision making and task monitoring. While the biological underpinnings of fractional anisotropy alterations remain elusive, they may nonetheless be used as an index of Parkinson's disease. Moreover, we find that failing to account for structural changes occurring in the subthalamic nucleus with age and disease reduce the accuracy and influence the results of tractography, highlighting the importance of using appropriate atlases for tractography.
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Affiliation(s)
- Bethany. R. Isaacs
- Integrative Model-based Cognitive Neuroscience research unit, University of Amsterdam, Amsterdam, the Netherlands
- Department of Neurosurgery, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Anne. C. Trutti
- Integrative Model-based Cognitive Neuroscience research unit, University of Amsterdam, Amsterdam, the Netherlands
- Cognitive Psychology, University of Leiden, Leiden, the Netherlands
| | - Esther Pelzer
- Translational Neurocircuitry, Max Planck Institute for Metabolism Research, Cologne, Germany
- Department of Neurology, University Clinics, Cologne, Germany
| | - Marc Tittgemeyer
- Translational Neurocircuitry, Max Planck Institute for Metabolism Research, Cologne, Germany
- Department of Neurology, University Clinics, Cologne, Germany
| | - Yasin Temel
- Department of Neurosurgery, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Birte. U. Forstmann
- Integrative Model-based Cognitive Neuroscience research unit, University of Amsterdam, Amsterdam, the Netherlands
| | - Max. C. Keuken
- Integrative Model-based Cognitive Neuroscience research unit, University of Amsterdam, Amsterdam, the Netherlands
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Xu J, Zhang M. Use of Magnetic Resonance Imaging and Artificial Intelligence in Studies of Diagnosis of Parkinson's Disease. ACS Chem Neurosci 2019; 10:2658-2667. [PMID: 31083923 DOI: 10.1021/acschemneuro.9b00207] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
Parkinson's disease (PD) is a common neurodegenerative disorder. It has a delitescent onset and a slow progress. The clinical manifestations of PD in patients are highly heterogeneous. Thus, PD diagnosis process is complex and mainly depends on the professional knowledge and experience of the physician. Magnetic resonance imaging (MRI) could detect the small changes in the brain of PD patients, and quantitative analysis of brain MRI may improve the clinical diagnosis efficiency. However, due to the complexity of clinical courses in PD and the high dimensionality in multimodal MRI data, traditional mathematical analysis could not effectively extract the huge information in them. Up to now, the accuracy of PD diagnosis in large sample size is still unsatisfying. As artificial intelligence (AI) is becoming more mature, varieties of statistical models and machine learning (ML) algorithms have been used for quantitative imaging data analysis to explore a diagnostic result. This review aims to state an overview of existing research recently that used statistical ML/AI methods to perform quantitative analysis of MR image data for the study of PD diagnosis. First we review the recent research in three subareas: diagnosis, differential diagnosis, and subtyping of PD. Then we described the overall workflow from MR image to classification result. Finally, we summarized a critical assessment of the current research and provide some recommendations for likely future research developments and trends.
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Affiliation(s)
- Jingjing Xu
- Department of Radiology, the Second Affiliated Hospital of Zhejiang University, School of Medicine, No.88 Jiefang Road, Shangcheng District, Hangzhou 31000, China
| | - Minming Zhang
- Department of Radiology, the Second Affiliated Hospital of Zhejiang University, School of Medicine, No.88 Jiefang Road, Shangcheng District, Hangzhou 31000, China
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A survey on computer-assisted Parkinson's Disease diagnosis. Artif Intell Med 2019; 95:48-63. [DOI: 10.1016/j.artmed.2018.08.007] [Citation(s) in RCA: 66] [Impact Index Per Article: 13.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2017] [Revised: 06/14/2018] [Accepted: 08/25/2018] [Indexed: 12/28/2022]
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Tanner JJ, McFarland NR, Price CC. Striatal and Hippocampal Atrophy in Idiopathic Parkinson's Disease Patients without Dementia: A Morphometric Analysis. Front Neurol 2017; 8:139. [PMID: 28450849 PMCID: PMC5389981 DOI: 10.3389/fneur.2017.00139] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2016] [Accepted: 03/27/2017] [Indexed: 12/16/2022] Open
Abstract
Background Analyses of subcortical gray structure volumes in non-demented idiopathic Parkinson’s disease (PD) often, but not always, show volume loss of the putamen, caudate nucleus, nucleus accumbens, and hippocampus. There is building evidence that structure morphometry might be more sensitive to disease-related processes than volume. Objective To assess morphometric differences of subcortical structures (putamen, caudate nucleus, thalamus, globus pallidus, nucleus accumbens, and amygdala) as well as the hippocampus in non-demented individuals with PD relative to age and education matched non-PD peers. Methods Prospective recruitment of idiopathic no-dementia PD and non-PD peers as part of a federally funded investigation. T1-weighted isovoxel metrics acquired via 3-T Siemens Verio for all individuals [PD n = 72 (left side onset n = 27, right side onset n = 45); non-PD n = 48]. FIRST (FMRIB Software Library) applications provided volumetric and vertex analyses on group differences for structure size and morphometry. Results Group volume differences were observed only for putamen and hippocampi (PD < non-PD) with hippocampal volume significantly associating with disease duration. Group shape differences were observed for bilateral putamen, caudate nucleus, and hippocampus with greater striatal atrophy contralateral to side of motor symptom onset. Hippocampal shape differences disappeared when removing the effects of volume. Conclusion The putamen was the primary structure to show both volume and shape differences in PD, indicating that the putamen is the predominant site of basal ganglia atrophy in early- to mid-stage PD. Side of PD symptom onset associates with contralateral striatal atrophy. Left-onset PD might experience more extensive striatal atrophy than right-onset PD. Hippocampus morphometric results suggest possible primary atrophy of CA3/4 and dentate gyrus.
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Affiliation(s)
- Jared J Tanner
- Clinical and Health Psychology, University of Florida, Gainesville, FL, USA
| | - Nikolaus R McFarland
- Neurology, University of Florida, Gainesville, FL, USA.,Center for Movement Disorders and Neurorestoration, University of Florida, Gainesville, FL, USA
| | - Catherine C Price
- Clinical and Health Psychology, University of Florida, Gainesville, FL, USA
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Tanner JJ, Levy SA, Schwab NA, Hizel LP, Nguyen PT, Okun MS, Price CC. Marked brain asymmetry with intact cognitive functioning in idiopathic Parkinson's disease: a longitudinal analysis. Clin Neuropsychol 2017; 31:654-675. [PMID: 27813459 PMCID: PMC5334434 DOI: 10.1080/13854046.2016.1251973] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2016] [Accepted: 10/18/2016] [Indexed: 12/11/2022]
Abstract
OBJECTIVE A 71-year-old (MN) with an 11-year history of left onset tremor diagnosed as Parkinson's disease (PD) completed longitudinal brain magnetic resonance imaging (MRI) and neuropsychological testing. MRI scans showed an asymmetric caudate nucleus (right < left volume). We describe this asymmetry at baseline and the progression over time relative to other subcortical gray, frontal white matter, and cortical gray matter regions of interest. Isolated structural changes are compared to MN's cognitive profiles. METHOD MN completed yearly MRIs and neuropsychological assessments. For comparison, left onset PD (n = 15) and non-PD (n = 43) peers completed the same baseline protocol. All MRI scans were processed with FreeSurfer and the FMRIB Software Library to analyze gray matter structures and frontal fractional anisotropy (FA) metrics. Processing speed, working memory, language, verbal memory, abstract reasoning, visuospatial, and motor functions were examined using reliable change methods. RESULTS At baseline, MN had striatal volume and frontal lobe thickness asymmetry relative to peers with mild prefrontal white matter FA asymmetry. Over time only MN's right caudate nucleus showed accelerated atrophy. Cognitively, MN had slowed psychomotor speed and visuospatial-linked deficits with mild visuospatial working memory declines longitudinally. CONCLUSIONS This is a unique report using normative neuroimaging and neuropsychology to describe an individual diagnosed with PD who had striking striatal asymmetry followed secondarily by cortical thickness asymmetry and possible frontal white matter asymmetry. His decline and variability in visual working memory could be linked to ongoing atrophy of his right caudate nucleus.
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Affiliation(s)
- Jared J Tanner
- a Department of Clinical and Health Psychology , University of Florida , Gainesville , FL , USA
- b Center for Movement Disorders and Neurorestoration , University of Florida , Gainesville , FL , USA
| | - Shellie-Anne Levy
- a Department of Clinical and Health Psychology , University of Florida , Gainesville , FL , USA
- b Center for Movement Disorders and Neurorestoration , University of Florida , Gainesville , FL , USA
| | - Nadine A Schwab
- a Department of Clinical and Health Psychology , University of Florida , Gainesville , FL , USA
- b Center for Movement Disorders and Neurorestoration , University of Florida , Gainesville , FL , USA
| | - Loren P Hizel
- a Department of Clinical and Health Psychology , University of Florida , Gainesville , FL , USA
- b Center for Movement Disorders and Neurorestoration , University of Florida , Gainesville , FL , USA
| | - Peter T Nguyen
- a Department of Clinical and Health Psychology , University of Florida , Gainesville , FL , USA
- b Center for Movement Disorders and Neurorestoration , University of Florida , Gainesville , FL , USA
| | - Michael S Okun
- a Department of Clinical and Health Psychology , University of Florida , Gainesville , FL , USA
- b Center for Movement Disorders and Neurorestoration , University of Florida , Gainesville , FL , USA
| | - Catherine C Price
- a Department of Clinical and Health Psychology , University of Florida , Gainesville , FL , USA
- b Center for Movement Disorders and Neurorestoration , University of Florida , Gainesville , FL , USA
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