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Yang X, Liechti MD, Kanber B, Sudre CH, Castellazzi G, Zhang J, Yiannakas MC, Gonzales G, Prados F, Toosy AT, Gandini Wheeler-Kingshott CAM, Panicker JN. White Matter Magnetic Resonance Diffusion Measures in Multiple Sclerosis with Overactive Bladder. Brain Sci 2024; 14:975. [PMID: 39451989 PMCID: PMC11506346 DOI: 10.3390/brainsci14100975] [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: 08/14/2024] [Revised: 09/22/2024] [Accepted: 09/25/2024] [Indexed: 10/26/2024] Open
Abstract
BACKGROUND Lower urinary tract (LUT) symptoms are reported in more than 80% of patients with multiple sclerosis (MS), most commonly an overactive bladder (OAB). The relationship between brain white matter (WM) changes in MS and OAB symptoms is poorly understood. OBJECTIVES We aim to evaluate (i) microstructural WM differences across MS patients (pwMS) with OAB symptoms, patients without LUT symptoms, and healthy subjects using diffusion tensor imaging (DTI), and (ii) associations between clinical OAB symptom scores and DTI indices. METHODS Twenty-nine female pwMS [mean age (SD) 43.3 years (9.4)], including seventeen with OAB [mean age (SD) 46.1 years (8.6)] and nine without LUT symptoms [mean age (SD) 37.5 years (8.9)], and fourteen healthy controls (HCs) [mean age (SD) 48.5 years (20)] were scanned in a 3T MRI with a DTI protocol. Additionally, clinical scans were performed for WM lesion segmentation. Group differences in fractional anisotropy (FA) were evaluated using tract-based spatial statistics. The Urinary Symptom Profile questionnaire assessed OAB severity. RESULTS A statistically significant reduction in FA (p = 0.004) was identified in microstructural WM in pwMS, compared with HCs. An inverse correlation was found between FA in frontal and parietal WM lobes and OAB scores (p = 0.021) in pwMS. Areas of lower FA, although this did not reach statistical significance, were found in both frontal lobes and the rest of the non-dominant hemisphere in pwMS with OAB compared with pwMS without LUT symptoms (p = 0.072). CONCLUSIONS This study identified that lesions affecting different WM tracts in MS can result in OAB symptoms and demonstrated the role of the WM in the neural control of LUT functions. By using DTI, the association between OAB symptom severity and WM changes were identified, adding knowledge to the current LUT working model. As MS is predominantly a WM disease, these findings suggest that regional WM involvement, including of the anterior corona radiata, anterior thalamic radiation, superior longitudinal fasciculus, and superior frontal-occipital fasciculus and a non-dominant prevalence in WM, can result in OAB symptoms. OAB symptoms in MS correlate with anisotropy changes in different white matter tracts as demonstrated by DTI. Structural impairment in WM tracts plays an important role in LUT symptoms in MS.
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Affiliation(s)
- Xixi Yang
- Department of Neurology, Xuan Wu Hospital of Capital Medical University, Beijing 100053, China
- Department of Brain Repair and Rehabilitation, Faculty of Brain Sciences, Queen Square Institute of Neurology, University College London, London WC1E 6BT, UK; (M.D.L.); (J.N.P.)
- Department of Uro-Neurology, The National Hospital for Neurology and Neurosurgery, London WC1N 3BG, UK;
- NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, University College London, London WC1E 6BT, UK; (B.K.); (G.C.); (M.C.Y.); (F.P.); (A.T.T.); (C.A.M.G.W.-K.)
| | - Martina D. Liechti
- Department of Brain Repair and Rehabilitation, Faculty of Brain Sciences, Queen Square Institute of Neurology, University College London, London WC1E 6BT, UK; (M.D.L.); (J.N.P.)
- Department of Uro-Neurology, The National Hospital for Neurology and Neurosurgery, London WC1N 3BG, UK;
- NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, University College London, London WC1E 6BT, UK; (B.K.); (G.C.); (M.C.Y.); (F.P.); (A.T.T.); (C.A.M.G.W.-K.)
- Department of Neuro-Urology, Balgrist University Hospital, University of Zürich, 8006 Zürich, Switzerland
| | - Baris Kanber
- NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, University College London, London WC1E 6BT, UK; (B.K.); (G.C.); (M.C.Y.); (F.P.); (A.T.T.); (C.A.M.G.W.-K.)
- Centre for Medical Image Computing (CMIC), Department of Medical Physics and Biomedical Engineering, University College London, London WC1E 6BT, UK;
| | - Carole H. Sudre
- Centre for Medical Image Computing (CMIC), Department of Medical Physics and Biomedical Engineering, University College London, London WC1E 6BT, UK;
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
- Dementia Research Centre, Institute of Neurology, University College London, London WC1E 6BT, UK
| | - Gloria Castellazzi
- NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, University College London, London WC1E 6BT, UK; (B.K.); (G.C.); (M.C.Y.); (F.P.); (A.T.T.); (C.A.M.G.W.-K.)
- Department of Electrical, Computer and Biomedical Engineering, University of Pavia, 27100 Pavia, Italy
| | - Jiaying Zhang
- School of Artificial Intelligence, Beijing University of Post and Communications, Beijing 100876, China;
- Department of Computer Science and Centre for Medical Image Computing, University College London, London WC1E 6BT, UK
| | - Marios C. Yiannakas
- NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, University College London, London WC1E 6BT, UK; (B.K.); (G.C.); (M.C.Y.); (F.P.); (A.T.T.); (C.A.M.G.W.-K.)
| | - Gwen Gonzales
- Department of Uro-Neurology, The National Hospital for Neurology and Neurosurgery, London WC1N 3BG, UK;
| | - Ferran Prados
- NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, University College London, London WC1E 6BT, UK; (B.K.); (G.C.); (M.C.Y.); (F.P.); (A.T.T.); (C.A.M.G.W.-K.)
- Centre for Medical Image Computing (CMIC), Department of Medical Physics and Biomedical Engineering, University College London, London WC1E 6BT, UK;
- e-Health Centre, Universitat Oberta de Catalunya, 08018 Barcelona, Spain
| | - Ahmed T. Toosy
- NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, University College London, London WC1E 6BT, UK; (B.K.); (G.C.); (M.C.Y.); (F.P.); (A.T.T.); (C.A.M.G.W.-K.)
| | - Claudia A. M. Gandini Wheeler-Kingshott
- NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, University College London, London WC1E 6BT, UK; (B.K.); (G.C.); (M.C.Y.); (F.P.); (A.T.T.); (C.A.M.G.W.-K.)
- Department of Brain and Behavioral Sciences, University of Pavia, 27100 Pavia, Italy
- Digital Neuroscience Centre, IRCCS Mondino Foundation, 27100 Pavia, Italy
| | - Jalesh N. Panicker
- Department of Brain Repair and Rehabilitation, Faculty of Brain Sciences, Queen Square Institute of Neurology, University College London, London WC1E 6BT, UK; (M.D.L.); (J.N.P.)
- Department of Uro-Neurology, The National Hospital for Neurology and Neurosurgery, London WC1N 3BG, UK;
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Sampedro F. The success of assessing cortical microstructure through surface-based diffusion-weighted neuroimaging. Clin Neurol Neurosurg 2023; 234:107990. [PMID: 37806052 DOI: 10.1016/j.clineuro.2023.107990] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2023] [Revised: 09/20/2023] [Accepted: 09/23/2023] [Indexed: 10/10/2023]
Affiliation(s)
- Frederic Sampedro
- Radiology Department, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain.
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Arai T, Kamagata K, Uchida W, Andica C, Takabayashi K, Saito Y, Tuerxun R, Mahemuti Z, Morita Y, Irie R, Kirino E, Aoki S. Reduced neurite density index in the prefrontal cortex of adults with autism assessed using neurite orientation dispersion and density imaging. Front Neurol 2023; 14:1110883. [PMID: 37638188 PMCID: PMC10450631 DOI: 10.3389/fneur.2023.1110883] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Accepted: 07/27/2023] [Indexed: 08/29/2023] Open
Abstract
Background Core symptoms of autism-spectrum disorder (ASD) have been associated with prefrontal cortex abnormalities. However, the mechanisms behind the observation remain incomplete, partially due to the challenges of modeling complex gray matter (GM) structures. This study aimed to identify GM microstructural alterations in adults with ASD using neurite orientation dispersion and density imaging (NODDI) and voxel-wise GM-based spatial statistics (GBSS) to reduce the partial volume effects from the white matter and cerebrospinal fluid. Materials and methods A total of 48 right-handed participants were included, of which 22 had ASD (17 men; mean age, 34.42 ± 8.27 years) and 26 were typically developing (TD) individuals (14 men; mean age, 32.57 ± 9.62 years). The metrics of NODDI (neurite density index [NDI], orientation dispersion index [ODI], and isotropic volume fraction [ISOVF]) were compared between groups using GBSS. Diffusion tensor imaging (DTI) metrics and surface-based cortical thickness were also compared. The associations between magnetic resonance imaging-based measures and ASD-related scores, including ASD-spectrum quotient, empathizing quotient, and systemizing quotient were also assessed in the region of interest (ROI) analysis. Results After controlling for age, sex, and intracranial volume, GBSS demonstrated significantly lower NDI in the ASD group than in the TD group in the left prefrontal cortex (caudal middle frontal, lateral orbitofrontal, pars orbitalis, pars triangularis, rostral middle frontal, and superior frontal region). In the ROI analysis of individuals with ASD, a significantly positive correlation was observed between the NDI in the left rostral middle frontal, superior frontal, and left frontal pole and empathizing quotient score. No significant between-group differences were observed in all DTI metrics, other NODDI (i.e., ODI and ISOVF) metrics, and cortical thickness. Conclusion GBSS analysis was used to demonstrate the ability of NODDI metrics to detect GM microstructural alterations in adults with ASD, while no changes were detected using DTI and cortical thickness evaluation. Specifically, we observed a reduced neurite density index in the left prefrontal cortices associated with reduced empathic abilities.
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Affiliation(s)
- Takashi Arai
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Koji Kamagata
- Faculty of Health Data Science, Juntendo University, Chiba, Japan
| | - Wataru Uchida
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Christina Andica
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan
- Faculty of Health Data Science, Juntendo University, Chiba, Japan
| | - Kaito Takabayashi
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Yuya Saito
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Rukeye Tuerxun
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Zaimire Mahemuti
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Yuichi Morita
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan
- Department of Radiology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Ryusuke Irie
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Eiji Kirino
- Department of Psychiatry, Juntendo University Graduate School of Medicine, Tokyo, Japan
- Department of Psychiatry, Juntendo University Shizuoka Hospital, Shizuoka, Japan
| | - Shigeki Aoki
- Department of Radiology, Juntendo University Graduate School of Medicine, Tokyo, Japan
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Wang D, Zhou J, Huang Y, Yu H. Identifying the changes in the cortical activity of various brain regions for different balance tasks: A review. NeuroRehabilitation 2023:NRE220285. [PMID: 37125575 DOI: 10.3233/nre-220285] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/02/2023]
Abstract
BACKGROUND Balance support is critical to a person's overall function and health. Previous neuroimaging studies have shown that cortical structures play an essential role in postural control. OBJECTIVE This review aims to identify differences in the pattern of neural activity induced by balance tasks with different balance control requirements. METHODS Seventy-four articles were selected from the field of balance training and were examined based on four brain function detection technologies. RESULTS In general, most studies focused on the activity changes of various cortical areas during training at different difficulty levels, but more and more attention has also begun to focus on the functional changes of other cortical and deep subcortical structures. Our analysis also revealed the neglect of certain task types. CONCLUSION Based on these results, we identify and discuss future research directions that may contribute to a clear understanding of neural functional plasticity under different tasks.
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Affiliation(s)
- Duojin Wang
- Institute of Rehabilitation Engineering and Technology, University of Shanghai for Science and Technology, Shanghai, China
- Shanghai Engineering Research Center of Assistive Devices, Shanghai, China
| | - Jiankang Zhou
- Institute of Rehabilitation Engineering and Technology, University of Shanghai for Science and Technology, Shanghai, China
| | - Yanping Huang
- Institute of Rehabilitation Engineering and Technology, University of Shanghai for Science and Technology, Shanghai, China
| | - Hongliu Yu
- Institute of Rehabilitation Engineering and Technology, University of Shanghai for Science and Technology, Shanghai, China
- Shanghai Engineering Research Center of Assistive Devices, Shanghai, China
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Frigerio I, Laansma MA, Lin CP, Hermans EJM, Bouwman MMA, Bol JGJM, Galis-de Graaf Y, Hepp DH, Rozemuller AJM, Barkhof F, van de Berg WDJ, Jonkman LE. Neurofilament light chain is increased in the parahippocampal cortex and associates with pathological hallmarks in Parkinson's disease dementia. Transl Neurodegener 2023; 12:3. [PMID: 36658627 PMCID: PMC9854202 DOI: 10.1186/s40035-022-00328-8] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Accepted: 11/17/2022] [Indexed: 01/21/2023] Open
Abstract
BACKGROUND Increased neurofilament levels in biofluids are commonly used as a proxy for neurodegeneration in several neurodegenerative disorders. In this study, we aimed to investigate the distribution of neurofilaments in the cerebral cortex of Parkinson's disease (PD), PD with dementia (PDD) and dementia with Lewy bodies (DLB) donors, and its association with pathology load and MRI measures of atrophy and diffusivity. METHODS Using a within-subject post-mortem MRI-pathology approach, we included 9 PD, 12 PDD/DLB and 18 age-matched control donors. Cortical thickness and mean diffusivity (MD) metrics were extracted respectively from 3DT1 and DTI at 3T in-situ MRI. After autopsy, pathological hallmarks (pSer129-αSyn, p-tau and amyloid-β load) together with neurofilament light-chain (NfL) and phosphorylated-neurofilament medium- and heavy-chain (p-NfM/H) immunoreactivity were quantified in seven cortical regions, and studied in detail with confocal-laser scanning microscopy. The correlations between MRI and pathological measures were studied using linear mixed models. RESULTS Compared to controls, p-NfM/H immunoreactivity was increased in all cortical regions in PD and PDD/DLB, whereas NfL immunoreactivity was increased in the parahippocampal and entorhinal cortex in PDD/DLB. NfL-positive neurons showed degenerative morphological features and axonal fragmentation. The increased p-NfM/H correlated with p-tau load, and NfL correlated with pSer129-αSyn but more strongly with p-tau load in PDD/DLB. Lastly, neurofilament immunoreactivity correlated with cortical thinning in PD and with increased cortical MD in PDD/DLB. CONCLUSIONS Taken together, increased neurofilament immunoreactivity suggests underlying axonal injury and neurofilament accumulation in morphologically altered neurons with increased pathological burden. Importantly, we demonstrate that such neurofilament markers at least partly explain MRI measures that are associated with the neurodegenerative process.
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Affiliation(s)
- Irene Frigerio
- Section Clinical Neuroanatomy and Biobanking, Department of Anatomy and Neurosciences, Amsterdam UMC Location Vrije Universiteit Amsterdam, De Boelelaan 1118, Amsterdam, The Netherlands. .,Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands. .,Amsterdam Neuroscience, Brain Imaging, Amsterdam, The Netherlands.
| | - Max A. Laansma
- grid.12380.380000 0004 1754 9227Section Clinical Neuroanatomy and Biobanking, Department of Anatomy and Neurosciences, Amsterdam UMC Location Vrije Universiteit Amsterdam, De Boelelaan 1118, Amsterdam, The Netherlands ,grid.484519.5Amsterdam Neuroscience, Brain Imaging, Amsterdam, The Netherlands
| | - Chen-Pei Lin
- grid.12380.380000 0004 1754 9227Section Clinical Neuroanatomy and Biobanking, Department of Anatomy and Neurosciences, Amsterdam UMC Location Vrije Universiteit Amsterdam, De Boelelaan 1118, Amsterdam, The Netherlands ,grid.484519.5Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands ,grid.484519.5Amsterdam Neuroscience, Brain Imaging, Amsterdam, The Netherlands
| | - Emma J. M. Hermans
- grid.12380.380000 0004 1754 9227Section Clinical Neuroanatomy and Biobanking, Department of Anatomy and Neurosciences, Amsterdam UMC Location Vrije Universiteit Amsterdam, De Boelelaan 1118, Amsterdam, The Netherlands
| | - Maud M. A. Bouwman
- grid.12380.380000 0004 1754 9227Section Clinical Neuroanatomy and Biobanking, Department of Anatomy and Neurosciences, Amsterdam UMC Location Vrije Universiteit Amsterdam, De Boelelaan 1118, Amsterdam, The Netherlands ,grid.484519.5Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands ,grid.484519.5Amsterdam Neuroscience, Brain Imaging, Amsterdam, The Netherlands
| | - John G. J. M. Bol
- grid.12380.380000 0004 1754 9227Section Clinical Neuroanatomy and Biobanking, Department of Anatomy and Neurosciences, Amsterdam UMC Location Vrije Universiteit Amsterdam, De Boelelaan 1118, Amsterdam, The Netherlands
| | - Yvon Galis-de Graaf
- grid.12380.380000 0004 1754 9227Section Clinical Neuroanatomy and Biobanking, Department of Anatomy and Neurosciences, Amsterdam UMC Location Vrije Universiteit Amsterdam, De Boelelaan 1118, Amsterdam, The Netherlands
| | - Dagmar H. Hepp
- grid.12380.380000 0004 1754 9227Section Clinical Neuroanatomy and Biobanking, Department of Anatomy and Neurosciences, Amsterdam UMC Location Vrije Universiteit Amsterdam, De Boelelaan 1118, Amsterdam, The Netherlands ,grid.12380.380000 0004 1754 9227Department of Neurology, Amsterdam UMC Location Vrije Universiteit Amsterdam, De Boelelaan 1117, Amsterdam, The Netherlands
| | - Annemieke J. M. Rozemuller
- grid.12380.380000 0004 1754 9227Department of Pathology, Amsterdam UMC Location Vrije Universiteit Amsterdam, De Boelelaan 1117, Amsterdam, The Netherlands
| | - Frederik Barkhof
- grid.484519.5Amsterdam Neuroscience, Brain Imaging, Amsterdam, The Netherlands ,grid.12380.380000 0004 1754 9227Department of Radiology and Nuclear Medicine, Amsterdam UMC Location Vrije Universiteit Amsterdam, De Boelelaan 1117, Amsterdam, The Netherlands ,grid.83440.3b0000000121901201Institutes of Neurology and Healthcare Engineering, University College London, London, UK
| | - Wilma D. J. van de Berg
- grid.12380.380000 0004 1754 9227Section Clinical Neuroanatomy and Biobanking, Department of Anatomy and Neurosciences, Amsterdam UMC Location Vrije Universiteit Amsterdam, De Boelelaan 1118, Amsterdam, The Netherlands ,grid.484519.5Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Laura E. Jonkman
- grid.12380.380000 0004 1754 9227Section Clinical Neuroanatomy and Biobanking, Department of Anatomy and Neurosciences, Amsterdam UMC Location Vrije Universiteit Amsterdam, De Boelelaan 1118, Amsterdam, The Netherlands ,grid.484519.5Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands ,grid.484519.5Amsterdam Neuroscience, Brain Imaging, Amsterdam, The Netherlands
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Plasma TDP-43 Reflects Cortical Neurodegeneration and Correlates with Neuropsychiatric Symptoms in Huntington's Disease. Clin Neuroradiol 2022; 32:1077-1085. [PMID: 35238950 DOI: 10.1007/s00062-022-01150-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2021] [Accepted: 02/02/2022] [Indexed: 12/15/2022]
Abstract
PURPOSE Huntington's disease (HD) is a monogenic neurodegenerative disease with no effective treatment currently available. The pathological hallmark of HD is the aggregation of mutant huntingtin in the medium spiny neurons of the striatum, leading to severe subcortical atrophy. Cortical degeneration also occurs in HD from its very early stages, although its biological origin is poorly understood. Among the possible pathological mechanisms that could promote cortical damage in HD, the in vivo study of TDP-43 pathology remains to be explored, which was the main objective of this work. METHODS We investigated the clinical and structural brain correlates of plasma TDP-43 levels in a sample of 36 HD patients. Neuroimaging alterations were assessed both at the macrostructural (cortical thickness) and microstructural (intracortical diffusivity) levels. Importantly, we controlled for mutant huntingtin and tau biomarkers in order to assess the independent role of TDP-43 in HD neurodegeneration. RESULTS Plasma TDP-43 levels in HD specifically correlated with the presence and severity of apathy (p = 0.003). The TDP-43 levels also reflected cortical thinning and microstructural degeneration, especially in frontal and anterior-temporal regions (p < 0.05 corrected). These TDP-43-related brain alterations correlated, in turn, with the severity of cognitive, motor and behavioral symptoms. CONCLUSION Our results suggest that the presence of TDP-43 pathology in HD has an independent contribution to the severity of neuropsychiatric symptoms and frontotemporal degeneration. These findings point out the importance of TDP-43 as an additional pathological process to be taken into consideration in this devastating disorder.
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