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Le Stanc L, Lunven M, Giavazzi M, Sliwinski A, Youssov K, Bachoud-Lévi AC, Jacquemot C. Cognitive reserve involves decision making and is associated with left parietal and hippocampal hypertrophy in neurodegeneration. Commun Biol 2024; 7:741. [PMID: 38890487 PMCID: PMC11189446 DOI: 10.1038/s42003-024-06416-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2023] [Accepted: 06/05/2024] [Indexed: 06/20/2024] Open
Abstract
Cognitive reserve is the ability to actively cope with brain deterioration and delay cognitive decline in neurodegenerative diseases. It operates by optimizing performance through differential recruitment of brain networks or alternative cognitive strategies. We investigated cognitive reserve using Huntington's disease (HD) as a genetic model of neurodegeneration to compare premanifest HD, manifest HD, and controls. Contrary to manifest HD, premanifest HD behave as controls despite neurodegeneration. By decomposing the cognitive processes underlying decision making, drift diffusion models revealed a response profile that differs progressively from controls to premanifest and manifest HD. Here, we show that cognitive reserve in premanifest HD is supported by an increased rate of evidence accumulation compensating for the abnormal increase in the amount of evidence needed to make a decision. This higher rate is associated with left superior parietal and hippocampal hypertrophy, and exhibits a bell shape over the course of disease progression, characteristic of compensation.
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Affiliation(s)
- Lorna Le Stanc
- Département d'Études Cognitives, École Normale Supérieure-PSL, Paris, France
- Institut Mondor de Recherche Biomédicale, Inserm U955, Equipe E01 Neuropsychologie Interventionnelle, Créteil, France
- Université Paris-Est Créteil, Faculté de Santé, Créteil, France
- Université Paris Cité, LaPsyDÉ, CNRS, F-75005 Paris, France
| | - Marine Lunven
- Département d'Études Cognitives, École Normale Supérieure-PSL, Paris, France
- Institut Mondor de Recherche Biomédicale, Inserm U955, Equipe E01 Neuropsychologie Interventionnelle, Créteil, France
- Université Paris-Est Créteil, Faculté de Santé, Créteil, France
| | - Maria Giavazzi
- Département d'Études Cognitives, École Normale Supérieure-PSL, Paris, France
- Institut Mondor de Recherche Biomédicale, Inserm U955, Equipe E01 Neuropsychologie Interventionnelle, Créteil, France
- Université Paris-Est Créteil, Faculté de Santé, Créteil, France
| | - Agnès Sliwinski
- Département d'Études Cognitives, École Normale Supérieure-PSL, Paris, France
- Institut Mondor de Recherche Biomédicale, Inserm U955, Equipe E01 Neuropsychologie Interventionnelle, Créteil, France
- Université Paris-Est Créteil, Faculté de Santé, Créteil, France
- AP-HP, Centre de Référence Maladie de Huntington, Service de Neurologie, Hôpital Henri Mondor-Albert Chenevier, Créteil, France
| | - Katia Youssov
- Département d'Études Cognitives, École Normale Supérieure-PSL, Paris, France
- Institut Mondor de Recherche Biomédicale, Inserm U955, Equipe E01 Neuropsychologie Interventionnelle, Créteil, France
- Université Paris-Est Créteil, Faculté de Santé, Créteil, France
- AP-HP, Centre de Référence Maladie de Huntington, Service de Neurologie, Hôpital Henri Mondor-Albert Chenevier, Créteil, France
| | - Anne-Catherine Bachoud-Lévi
- Département d'Études Cognitives, École Normale Supérieure-PSL, Paris, France
- Institut Mondor de Recherche Biomédicale, Inserm U955, Equipe E01 Neuropsychologie Interventionnelle, Créteil, France
- Université Paris-Est Créteil, Faculté de Santé, Créteil, France
- AP-HP, Centre de Référence Maladie de Huntington, Service de Neurologie, Hôpital Henri Mondor-Albert Chenevier, Créteil, France
| | - Charlotte Jacquemot
- Département d'Études Cognitives, École Normale Supérieure-PSL, Paris, France.
- Institut Mondor de Recherche Biomédicale, Inserm U955, Equipe E01 Neuropsychologie Interventionnelle, Créteil, France.
- Université Paris-Est Créteil, Faculté de Santé, Créteil, France.
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Barrett MJ, Negida A, Mukhopadhyay N, Kim JK, Nawaz H, Jose J, Testa C. Optimizing Screening for Intrastriatal Interventions in Huntington's Disease Using Predictive Models. Mov Disord 2024; 39:855-862. [PMID: 38465778 PMCID: PMC11102310 DOI: 10.1002/mds.29749] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Revised: 01/09/2024] [Accepted: 02/02/2024] [Indexed: 03/12/2024] Open
Abstract
BACKGROUND Intrastriatal delivery of potential therapeutics in Huntington's disease (HD) requires sufficient caudate and putamen volumes. Currently, volumetric magnetic resonance imaging is rarely done in clinical practice, and these data are not available in large research cohorts such as Enroll-HD. OBJECTIVE The objective of this study was to investigate whether predictive models can accurately classify HD patients who exceed caudate and putamen volume thresholds required for intrastriatal therapeutic interventions. METHODS We obtained and merged data for 1374 individuals across three HD cohorts: IMAGE-HD, PREDICT-HD, and TRACK-HD/TRACK-ON. We imputed missing data for clinical variables with >72% non-missing values and used the model-building algorithm BORUTA to identify the 10 most important variables. A random forest algorithm was applied to build a predictive model for putamen volume >2500 mm3 and caudate volume >2000 mm3 bilaterally. Using the same 10 predictors, we constructed a logistic regression model with predictors significant at P < 0.05. RESULTS The random forest model with 1000 trees and minimal terminal node size of 5 resulted in 83% area under the curve (AUC). The logistic regression model retaining age, CAG repeat size, and symbol digit modalities test-correct had 85.1% AUC. A probability cutoff of 0.8 resulted in 5.4% false positive and 66.7% false negative rates. CONCLUSIONS Using easily obtainable clinical data and machine learning-identified initial predictor variables, random forest, and logistic regression models can successfully identify people with sufficient striatal volumes for inclusion cutoffs. Adopting these models in prescreening could accelerate clinical trial enrollment in HD and other neurodegenerative disorders when volume cutoffs are necessary enrollment criteria. © 2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Matthew J. Barrett
- Department of Neurology, Virginia Commonwealth University, Richmond, VA, USA
| | - Ahmed Negida
- Department of Neurology, Virginia Commonwealth University, Richmond, VA, USA
| | - Nitai Mukhopadhyay
- Department of Biostatistics, Virginia Commonwealth University, Richmond, VA, USA
| | - Jin K. Kim
- Department of Neurology, Virginia Commonwealth University, Richmond, VA, USA
| | - Huma Nawaz
- Department of Neurology, Virginia Commonwealth University, Richmond, VA, USA
| | - Jefin Jose
- Department of Neurology, Virginia Commonwealth University, Richmond, VA, USA
| | - Claudia Testa
- Department of Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
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Hobbs NZ, Papoutsi M, Delva A, Kinnunen KM, Nakajima M, Van Laere K, Vandenberghe W, Herath P, Scahill RI. Neuroimaging to Facilitate Clinical Trials in Huntington's Disease: Current Opinion from the EHDN Imaging Working Group. J Huntingtons Dis 2024; 13:163-199. [PMID: 38788082 DOI: 10.3233/jhd-240016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/26/2024]
Abstract
Neuroimaging is increasingly being included in clinical trials of Huntington's disease (HD) for a wide range of purposes from participant selection and safety monitoring, through to demonstration of disease modification. Selection of the appropriate modality and associated analysis tools requires careful consideration. On behalf of the EHDN Imaging Working Group, we present current opinion on the utility and future prospects for inclusion of neuroimaging in HD trials. Covering the key imaging modalities of structural-, functional- and diffusion- MRI, perfusion imaging, positron emission tomography, magnetic resonance spectroscopy, and magnetoencephalography, we address how neuroimaging can be used in HD trials to: 1) Aid patient selection, enrichment, stratification, and safety monitoring; 2) Demonstrate biodistribution, target engagement, and pharmacodynamics; 3) Provide evidence for disease modification; and 4) Understand brain re-organization following therapy. We also present the challenges of translating research methodology into clinical trial settings, including equipment requirements and cost, standardization of acquisition and analysis, patient burden and invasiveness, and interpretation of results. We conclude, that with appropriate consideration of modality, study design and analysis, imaging has huge potential to facilitate effective clinical trials in HD.
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Affiliation(s)
- Nicola Z Hobbs
- HD Research Centre, UCL Institute of Neurology, UCL, London, UK
| | - Marina Papoutsi
- HD Research Centre, UCL Institute of Neurology, UCL, London, UK
- IXICO plc, London, UK
| | - Aline Delva
- Department of Neurosciences, KU Leuven, Belgium
- Department of Neurology, University Hospitals Leuven, Belgium
| | | | | | - Koen Van Laere
- Department of Imaging and Pathology, Nuclear Medicine and Molecular Imaging, KU Leuven, Belgium
- Division of Nuclear Medicine, University Hospitals Leuven, Belgium
| | - Wim Vandenberghe
- Department of Neurosciences, KU Leuven, Belgium
- Department of Neurology, University Hospitals Leuven, Belgium
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Estevez-Fraga C, Altmann A, Parker CS, Scahill RI, Costa B, Chen Z, Manzoni C, Zarkali A, Durr A, Roos RAC, Landwehrmeyer B, Leavitt BR, Rees G, Tabrizi SJ, McColgan P. Genetic topography and cortical cell loss in Huntington's disease link development and neurodegeneration. Brain 2023; 146:4532-4546. [PMID: 37587097 PMCID: PMC10629790 DOI: 10.1093/brain/awad275] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Revised: 07/12/2023] [Accepted: 07/28/2023] [Indexed: 08/18/2023] Open
Abstract
Cortical cell loss is a core feature of Huntington's disease (HD), beginning many years before clinical motor diagnosis, during the premanifest stage. However, it is unclear how genetic topography relates to cortical cell loss. Here, we explore the biological processes and cell types underlying this relationship and validate these using cell-specific post-mortem data. Eighty premanifest participants on average 15 years from disease onset and 71 controls were included. Using volumetric and diffusion MRI we extracted HD-specific whole brain maps where lower grey matter volume and higher grey matter mean diffusivity, relative to controls, were used as proxies of cortical cell loss. These maps were combined with gene expression data from the Allen Human Brain Atlas (AHBA) to investigate the biological processes relating genetic topography and cortical cell loss. Cortical cell loss was positively correlated with the expression of developmental genes (i.e. higher expression correlated with greater atrophy and increased diffusivity) and negatively correlated with the expression of synaptic and metabolic genes that have been implicated in neurodegeneration. These findings were consistent for diffusion MRI and volumetric HD-specific brain maps. As wild-type huntingtin is known to play a role in neurodevelopment, we explored the association between wild-type huntingtin (HTT) expression and developmental gene expression across the AHBA. Co-expression network analyses in 134 human brains free of neurodegenerative disorders were also performed. HTT expression was correlated with the expression of genes involved in neurodevelopment while co-expression network analyses also revealed that HTT expression was associated with developmental biological processes. Expression weighted cell-type enrichment (EWCE) analyses were used to explore which specific cell types were associated with HD cortical cell loss and these associations were validated using cell specific single nucleus RNAseq (snRNAseq) data from post-mortem HD brains. The developmental transcriptomic profile of cortical cell loss in preHD was enriched in astrocytes and endothelial cells, while the neurodegenerative transcriptomic profile was enriched for neuronal and microglial cells. Astrocyte-specific genes differentially expressed in HD post-mortem brains relative to controls using snRNAseq were enriched in the developmental transcriptomic profile, while neuronal and microglial-specific genes were enriched in the neurodegenerative transcriptomic profile. Our findings suggest that cortical cell loss in preHD may arise from dual pathological processes, emerging as a consequence of neurodevelopmental changes, at the beginning of life, followed by neurodegeneration in adulthood, targeting areas with reduced expression of synaptic and metabolic genes. These events result in age-related cell death across multiple brain cell types.
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Affiliation(s)
- Carlos Estevez-Fraga
- Department of Neurodegenerative Disease, University College London, London WC1B 5EH, UK
| | - Andre Altmann
- Centre for Medical Image Computing, University College London, London WC1V 6LJ, UK
| | - Christopher S Parker
- Centre for Medical Image Computing, University College London, London WC1V 6LJ, UK
| | - Rachael I Scahill
- Department of Neurodegenerative Disease, University College London, London WC1B 5EH, UK
| | - Beatrice Costa
- Department of Neurodegenerative Disease, University College London, London WC1B 5EH, UK
- Gladstone Institutes, San Francisco, CA 94158, USA
| | - Zhongbo Chen
- Department of Neurodegenerative Disease, University College London, London WC1B 5EH, UK
| | - Claudia Manzoni
- School of Pharmacy, University College London, London WC1N 1AX, UK
| | - Angeliki Zarkali
- Dementia Research Centre, University College London, London WC1N 3AR, UK
| | - Alexandra Durr
- Sorbonne Université, Paris Brain Institute (ICM), AP-HP, Inserm, CNRS, Paris 75013, France
| | - Raymund A C Roos
- Department of Neurology, Leiden University Medical Centre, Leiden 2333, The Netherlands
| | | | - Blair R Leavitt
- Centre for Molecular Medicine and Therapeutics, Department of Medical Genetics, University of British Columbia, Vancouver BC V5Z 4H4Canada
- Division of Neurology, Department of Medicine, University of British Columbia Hospital, Vancouver BC V6T 2B5, Canada
| | - Geraint Rees
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London WC1N 3AR, UK
| | - Sarah J Tabrizi
- Department of Neurodegenerative Disease, University College London, London WC1B 5EH, UK
| | - Peter McColgan
- Department of Neurodegenerative Disease, University College London, London WC1B 5EH, UK
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Shen XZ, Zhang YX, You QY. Case report of 18F-FDG PET/CT features of hypoglycemic encephalopathy. Medicine (Baltimore) 2023; 102:e34025. [PMID: 37327258 PMCID: PMC10270514 DOI: 10.1097/md.0000000000034025] [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: 04/07/2023] [Accepted: 05/26/2023] [Indexed: 06/18/2023] Open
Abstract
RATIONALE Hypoglycemia may cause diverse neurological manifestations, ranging from focal neurological deficits to irreversible coma. Severe and persistent hypoglycemia can lead to hypoglycemic encephalopathy (HE). Imaging findings of HE at different stages of 18F-FDG positron emission tomography/computed tomography (PET/CT) have rarely been reported. Herein, we describe a case of HE occurring in the medial frontal cortex, cerebellar cortex, and dentate nucleus using 18F-FDG PET/CT images from different periods. 18F-FDG PET/CT has a high value in displaying the lesion range and indicating the prognosis. PATIENT CONCERNS A 57-year-old male patient with type 2 diabetes (T2D) was transferred to the hospital with a history of unconsciousness for 1 night. The patient showed a significant decrease in blood glucose levels. DIAGNOSES The patient was initially diagnosed with a hypoglycemic coma. INTERVENTIONS The patient subsequently underwent a comprehensive treatment. The 18F-FDG PET/CT examination on the fifth day after admission revealed a significant symmetrical fluorodeoxyglucose (FDG)-positive accumulation in the bilateral medial frontal gyrus, cerebellar cortex, and dentate nucleus. A follow-up PET/CT examination 6 months later revealed hypometabolism in the bilateral medial frontal gyrus and no abnormalities in FDG uptake in the bilateral cerebellar cortex and dentate nucleus. OUTCOMES The patient condition was stable 6 months later, with a slow response, memory deterioration, occasional dizziness, and episodes of hypoglycemia. LESSONS HE lesions with a high metabolic status may be related to a metabolic compensation mechanism in response to gray matter loss. Some of the more severely damaged cells eventually die even after the blood sugar levels return to normal. Less damaged nerve cells can be recovered. 18F-FDG PET/CT has high value in indicating the lesion range and prognosis of HE.
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Affiliation(s)
- Xun-Ze Shen
- PET/CT Center, Shaoxing People’s Hospita, Shaoxing, Zhejiang Province, China
| | - Yan-Xing Zhang
- Department of Neurology, Shaoxing People’s Hospital, Shaoxing, Zhejiang Province, China
| | - Qiao-Ying You
- Department of Endocrinology, Shaoxing People’s Hospital, Shaoxing, Zhejiang Province, China
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Whiteside DJ, Malpetti M, Jones PS, Ghosh BCP, Coyle‐Gilchrist I, van Swieten JC, Seelaar H, Jiskoot L, Borroni B, Sanchez‐Valle R, Moreno F, Laforce R, Graff C, Synofzik M, Galimberti D, Masellis M, Tartaglia MC, Finger E, Vandenberghe R, de Mendonça A, Tagliavini F, Butler CR, Santana I, Ber IL, Gerhard A, Ducharme S, Levin J, Danek A, Otto M, Sorbi S, Pasquier F, Bouzigues A, Russell LL, Rohrer JD, Rowe JB, Rittman T. Temporal dynamics predict symptom onset and cognitive decline in familial frontotemporal dementia. Alzheimers Dement 2023; 19:1947-1962. [PMID: 36377606 PMCID: PMC7614527 DOI: 10.1002/alz.12824] [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: 07/05/2022] [Revised: 09/13/2022] [Accepted: 09/19/2022] [Indexed: 11/16/2022]
Abstract
INTRODUCTION We tested whether changes in functional networks predict cognitive decline and conversion from the presymptomatic prodrome to symptomatic disease in familial frontotemporal dementia (FTD). METHODS For hypothesis generation, 36 participants with behavioral variant FTD (bvFTD) and 34 controls were recruited from one site. For hypothesis testing, we studied 198 symptomatic FTD mutation carriers, 341 presymptomatic mutation carriers, and 329 family members without mutations. We compared functional network dynamics between groups, with clinical severity and with longitudinal clinical progression. RESULTS We identified a characteristic pattern of dynamic network changes in FTD, which correlated with neuropsychological impairment. Among presymptomatic mutation carriers, this pattern of network dynamics was found to a greater extent in those who subsequently converted to the symptomatic phase. Baseline network dynamic changes predicted future cognitive decline in symptomatic participants and older presymptomatic participants. DISCUSSION Dynamic network abnormalities in FTD predict cognitive decline and symptomatic conversion. HIGHLIGHTS We investigated brain network predictors of dementia symptom onset Frontotemporal dementia results in characteristic dynamic network patterns Alterations in network dynamics are associated with neuropsychological impairment Network dynamic changes predict symptomatic conversion in presymptomatic carriers Network dynamic changes are associated with longitudinal cognitive decline.
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Affiliation(s)
- David J. Whiteside
- Department of Clinical NeurosciencesUniversity of CambridgeCambridgeCambridgeshireUK
- Cambridge University Hospitals NHS Foundation TrustCambridgeUK
| | - Maura Malpetti
- Department of Clinical NeurosciencesUniversity of CambridgeCambridgeCambridgeshireUK
| | - P. Simon Jones
- Department of Clinical NeurosciencesUniversity of CambridgeCambridgeCambridgeshireUK
| | - Boyd C. P. Ghosh
- Wessex Neurological CentreUniversity Hospital SouthamptonSouthamptonUK
| | | | | | - Harro Seelaar
- Department of NeurologyErasmus Medical CentreRotterdamNetherlands
| | - Lize Jiskoot
- Department of NeurologyErasmus Medical CentreRotterdamNetherlands
| | - Barbara Borroni
- Centre for Neurodegenerative DisordersDepartment of Clinical and Experimental SciencesUniversity of BresciaBresciaItaly
| | - Raquel Sanchez‐Valle
- Alzheimer's Disease and Other Cognitive Disorders UnitNeurology Service, Hospital ClínicInstitut d'Investigacións Biomèdiques August Pi I SunyerUniversity of BarcelonaBarcelonaSpain
| | - Fermin Moreno
- Cognitive Disorders UnitDepartment of NeurologyDonostia University HospitalSan SebastianGipuzkoaSpain
- Neuroscience AreaBiodonostia Health Research InstituteSan SebastianGipuzkoaSpain
| | - Robert Laforce
- CHU de Québec, and Faculté de MédecineDépartement des Sciences NeurologiquesClinique Interdisciplinaire de Mémoire, Université LavalQCCanada
| | - Caroline Graff
- Center for Alzheimer ResearchDivision of NeurogeriatricsDepartment of Neurobiology, Care Sciences and SocietyBioclinicum, Karolinska InstitutetSolnaSweden
- Unit for Hereditary Dementias, Theme AgingKarolinska University HospitalSolnaSweden
| | - Matthis Synofzik
- Department of Neurodegenerative DiseasesHertie‐Institute for Clinical Brain ResearchTübingenGermany
- Center of NeurologyUniversity of TübingenTübingenGermany
| | - Daniela Galimberti
- Fondazione IRCCS Ospedale PoliclinicoMilanItaly
- Department of Biomedical, Surgical and Dental SciencesUniversity of MilanMilanItaly
| | - Mario Masellis
- Sunnybrook Health Sciences CentreSunnybrook Research InstituteUniversity of TorontoTorontoCanada
| | | | - Elizabeth Finger
- Department of Clinical Neurological SciencesUniversity of Western OntarioLondonOntarioCanada
| | - Rik Vandenberghe
- Laboratory for Cognitive NeurologyDepartment of NeurosciencesKU LeuvenLeuvenBelgium
- Neurology ServiceUniversity Hospitals LeuvenBelgium
- Leuven Brain InstituteKU LeuvenLeuvenBelgium
| | | | | | - Chris R. Butler
- Nuffield Department of Clinical NeurosciencesMedical Sciences DivisionUniversity of OxfordOxfordUK
- Department of Brain SciencesImperial College LondonLondonUK
| | - Isabel Santana
- University Hospital of Coimbra (HUC)Neurology Service, Faculty of MedicineUniversity of CoimbraCoimbraPortugal
- Center for Neuroscience and Cell BiologyFaculty of MedicineUniversity of CoimbraCoimbraPortugal
| | - Isabelle Le Ber
- Paris Brain Institute – Institut du Cerveau – ICMInserm U1127, CNRS UMR 7225, AP‐HP ‐ Hôpital Pitié‐SalpêtrièreSorbonne UniversitéParisFrance
- Centre de référence des démences rares ou précoces, IM2ADépartement de NeurologieAP‐HP ‐ Hôpital Pitié‐SalpêtrièreParisFrance
- Département de NeurologieAP‐HP ‐ Hôpital Pitié‐SalpêtrièreParisFrance
| | - Alexander Gerhard
- Division of Neuroscience and Experimental PsychologyWolfson Molecular Imaging CentreUniversity of ManchesterManchesterUK
- Departments of Geriatric Medicine and Nuclear MedicineUniversity of Duisburg‐ EssenDuisburgGermany
| | - Simon Ducharme
- Department of PsychiatryMcGill University Health CentreMcGill UniversityMontrealQuébecCanada
- Department of Neurology & NeurosurgeryMcConnell Brain Imaging CentreMontreal Neurological InstituteMcGill UniversityMontrealCanada
| | - Johannes Levin
- Neurologische KlinikLudwig‐Maximilians‐Universität MünchenMunichGermany
- German Center for Neurodegenerative Diseases (DZNE)MunichGermany
- Munich Cluster of Systems NeurologyMunichGermany
| | - Adrian Danek
- Neurologische KlinikLudwig‐Maximilians‐Universität MünchenMunichGermany
| | - Markus Otto
- Department of NeurologyUniversity of UlmUlmGermany
| | - Sandro Sorbi
- Department of NeurofarbaUniversity of FlorenceFlorenceItaly
- IRCCS Fondazione Don Carlo GnocchiFlorenceItaly
| | - Florence Pasquier
- Univ LilleLilleFrance
- Inserm 1172LilleFrance
- CHU, CNR‐MAJ, Labex DistalzLiCEND LilleLilleFrance
| | - Arabella Bouzigues
- Department of Neurodegenerative DiseaseDementia Research Centre UCL Institute of NeurologyQueen SquareLondonUK
| | - Lucy L. Russell
- Department of Neurodegenerative DiseaseDementia Research Centre UCL Institute of NeurologyQueen SquareLondonUK
| | - Jonathan D. Rohrer
- Department of Neurodegenerative DiseaseDementia Research Centre UCL Institute of NeurologyQueen SquareLondonUK
| | - James B. Rowe
- Department of Clinical NeurosciencesUniversity of CambridgeCambridgeCambridgeshireUK
- Cambridge University Hospitals NHS Foundation TrustCambridgeUK
- MRC Cognition and Brain Sciences UnitUniversity of CambridgeCambridgeUK
| | - Timothy Rittman
- Department of Clinical NeurosciencesUniversity of CambridgeCambridgeCambridgeshireUK
- Cambridge University Hospitals NHS Foundation TrustCambridgeUK
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7
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Estevez-Fraga C, Elmalem MS, Papoutsi M, Durr A, Rees EM, Hobbs NZ, Roos RAC, Landwehrmeyer B, Leavitt BR, Langbehn DR, Scahill RI, Rees G, Tabrizi SJ, Gregory S. Progressive alterations in white matter microstructure across the timecourse of Huntington's disease. Brain Behav 2023; 13:e2940. [PMID: 36917716 PMCID: PMC10097137 DOI: 10.1002/brb3.2940] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Revised: 02/01/2023] [Accepted: 02/14/2023] [Indexed: 03/16/2023] Open
Abstract
BACKGROUND Whole-brain longitudinal diffusion studies are crucial to examine changes in structural connectivity in neurodegeneration. Here, we investigated the longitudinal alterations in white matter (WM) microstructure across the timecourse of Huntington's disease (HD). METHODS We examined changes in WM microstructure from premanifest to early manifest disease, using data from two cohorts with different disease burden. The TrackOn-HD study included 67 controls, 67 premanifest, and 10 early manifest HD (baseline and 24-month data); the PADDINGTON study included 33 controls and 49 early manifest HD (baseline and 15-month data). Longitudinal changes in fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity, and radial diffusivity from baseline to last study visit were investigated for each cohort using tract-based spatial statistics. An optimized pipeline was employed to generate participant-specific templates to which diffusion tensor imaging maps were registered and change maps were calculated. We examined longitudinal differences between HD expansion-carriers and controls, and correlations with clinical scores, including the composite UHDRS (cUHDRS). RESULTS HD expansion-carriers from TrackOn-HD, with lower disease burden, showed a significant longitudinal decline in FA in the left superior longitudinal fasciculus and an increase in MD across subcortical WM tracts compared to controls, while in manifest HD participants from PADDINGTON, there were significant widespread longitudinal increases in diffusivity compared to controls. Baseline scores in clinical scales including the cUHDRS predicted WM microstructural change in HD expansion-carriers. CONCLUSION The present study showed significant longitudinal changes in WM microstructure across the HD timecourse. Changes were evident in larger WM areas and across more metrics as the disease advanced, suggesting a progressive alteration of WM microstructure with disease evolution.
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Affiliation(s)
- Carlos Estevez-Fraga
- Huntington's Disease Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Michael S Elmalem
- Huntington's Disease Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Marina Papoutsi
- Huntington's Disease Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Alexandra Durr
- Sorbonne Université, Paris Brain Institute (ICM), AP-HP, Inserm, CNRS, Pitié-Salpêtrière University Hospital, Paris, France
| | | | - Nicola Z Hobbs
- Huntington's Disease Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Raymund A C Roos
- Department of Neurology, Leiden University Medical Centre, Leiden, The Netherlands
| | | | - Blair R Leavitt
- Centre for Huntington's Disease at UBC Hospital, Department of Medical Genetics and Division of Neurology, Department of Medicine, University of British Columbia, Vancouver, BC, Canada
| | | | - Rachael I Scahill
- Huntington's Disease Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Geraint Rees
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Sarah J Tabrizi
- Huntington's Disease Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Sarah Gregory
- Huntington's Disease Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
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8
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Kanishka, Jha SK. Compensatory cognition in neurological diseases and aging: A review of animal and human studies. AGING BRAIN 2023; 3:100061. [PMID: 36911258 PMCID: PMC9997140 DOI: 10.1016/j.nbas.2022.100061] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2022] [Revised: 12/06/2022] [Accepted: 12/12/2022] [Indexed: 12/27/2022] Open
Abstract
Specialized individual circuits in the brain are recruited for specific functions. Interestingly, multiple neural circuitries continuously compete with each other to acquire the specialized function. However, the dominant among them compete and become the central neural network for that particular function. For example, the hippocampal principal neural circuitries are the dominant networks among many which are involved in learning processes. But, in the event of damage to the principal circuitry, many times, less dominant networks compensate for the primary network. This review highlights the psychopathologies of functional loss and the aspects of functional recuperation in the absence of the hippocampus.
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Affiliation(s)
- Kanishka
- School of Life Sciences, Jawaharlal Nehru University, New Delhi 110067, India
| | - Sushil K Jha
- School of Life Sciences, Jawaharlal Nehru University, New Delhi 110067, India
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9
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Cunningham CN, Jenkins LC, Chang WJ, McAuley JH, Schabrun SM. Relative and absolute reliability of somatosensory evoked potentials in response to non-noxious electrical stimulation of the paraspinal muscles in healthy participants at an interval of 3-months. Int J Neurosci 2023; 133:103-109. [PMID: 33663320 DOI: 10.1080/00207454.2021.1893722] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Abstract
BACKGROUND Somatosensory evoked potentials (SEPs) are used extensively to quantify cortical activity in response to noxious and/or non-noxious sensory stimuli. However, data demonstrating the reliability of SEP measures in response to non-noxious stimulation over time are scarce. AIM We investigated the relative and absolute reliability, and the smallest detectable change at 95% confidence (SDC95) for SEPs evoked by non-noxious electrical stimulation of the paraspinal muscles in thirty-nine healthy participants at a 3-month interval. METHODS SEPs were evoked at an intensity three-times that of each participant's perceptual threshold and recorded from a single electrode placed over the primary somatosensory cortex (S1). RESULTS Our analyses reveal that i) latency, as a measure of activity onset, has poor relative reliability but good absolute reliability; ii) area, as a measure of cortical activity, has good relative and absolute reliability (except for the N150 component) and iii) perceptual threshold and stimulation intensity was not reliable over time. CONCLUSION These findings suggest that the area of the N80 and P260 SEP components, and the area of the N80-N150-P260 SEP complex, can be utilised in future studies as reliable markers of cortical activity.
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Affiliation(s)
- Chelsea N Cunningham
- Centre for Pain IMPACT, Neuroscience Research Australia, Randwick, NSW, Australia
| | - Luke C Jenkins
- Centre for Pain IMPACT, Neuroscience Research Australia, Randwick, NSW, Australia.,School of Science and Health, Western Sydney University, Penrith, NSW, Australia
| | - Wei-Ju Chang
- Centre for Pain IMPACT, Neuroscience Research Australia, Randwick, NSW, Australia
| | - James H McAuley
- Centre for Pain IMPACT, Neuroscience Research Australia, Randwick, NSW, Australia
| | - Siobhan M Schabrun
- Centre for Pain IMPACT, Neuroscience Research Australia, Randwick, NSW, Australia
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10
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Castro E, Polosecki P, Pustina D, Wood A, Sampaio C, Cecchi GA. Predictive Modeling of Huntington's Disease Unfolds Thalamic and Caudate Atrophy Dissociation. Mov Disord 2022; 37:2407-2416. [PMID: 36173150 DOI: 10.1002/mds.29219] [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: 03/16/2022] [Revised: 06/16/2022] [Accepted: 07/28/2022] [Indexed: 01/18/2023] Open
Abstract
BACKGROUND Atrophy in the striatum is a hallmark of Huntington's disease (HD), including the period before clinical motor diagnosis (before-CMD), but it extends to other subcortical structures. The study of the covariation of these structures could improve the detection of disease-related longitudinal progression before-CMD, provide mechanistic insights of the disease, and potentially be used to obtain accurate prospective estimates of atrophy before-CMD and early after-CMD. METHODS We analyzed data from 337 before-CMD individuals, 236 healthy control subjects, and 95 early after-CMD individuals from three studies, and we used nine subcortical regions volumes in two analyses. First, we discriminated before-CMD from healthy control trajectories by integrating volume changes from these regions. Second, we estimated prospective atrophy before-CMD and early after-CMD by considering the influence of a region's present volume over the future volume of another one. RESULTS Before-CMD progression was robustly detected across studies. Indeed, detection of before-CMD progression improved when multiple structures were integrated, as opposed to analyzing the striatum alone, likely because of the reduced partial correlation between caudate and thalamic volume change before-CMD. Our multivariate atrophy prediction model found a thalamus-caudate association that is consistent with this pattern, which yields an improved caudate atrophy prediction in early after-CMD. CONCLUSIONS This study is the first attempt to validate before-CMD multivariate subcortical change detection across studies and to do multivariate prospective atrophy prediction in HD. These models achieve improved performance by detecting a dissociation between caudate and thalamic atrophy trajectories, and they provide a possible mechanistic understanding of the dynamics of HD. © 2022 International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Eduardo Castro
- Digital Health, IBM T.J. Watson Research Center, Yorktown Heights, New York, USA
| | - Pablo Polosecki
- Digital Health, IBM T.J. Watson Research Center, Yorktown Heights, New York, USA
| | - Dorian Pustina
- CHDI Management/CHDI Foundation, Princeton, New Jersey, USA
| | - Andrew Wood
- CHDI Management/CHDI Foundation, Princeton, New Jersey, USA
| | | | - Guillermo A Cecchi
- Digital Health, IBM T.J. Watson Research Center, Yorktown Heights, New York, USA
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11
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McColgan P, Gregory S, Zeun P, Zarkali A, Johnson EB, Parker C, Fayer K, Lowe J, Nair A, Estevez-Fraga C, Papoutsi M, Zhang H, Scahill RI, Tabrizi SJ, Rees G. Neurofilament light-associated connectivity in young-adult Huntington's disease is related to neuronal genes. Brain 2022; 145:3953-3967. [PMID: 35758263 PMCID: PMC9679168 DOI: 10.1093/brain/awac227] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2021] [Revised: 05/27/2022] [Accepted: 06/03/2022] [Indexed: 11/13/2022] Open
Abstract
Upregulation of functional network connectivity in the presence of structural degeneration is seen in the premanifest stages of Huntington's disease (preHD) 10-15 years from clinical diagnosis. However, whether widespread network connectivity changes are seen in gene carriers much further from onset has yet to be explored. We characterized functional network connectivity throughout the brain and related it to a measure of disease pathology burden (CSF neurofilament light, NfL) and measures of structural connectivity in asymptomatic gene carriers, on average 24 years from onset. We related these measurements to estimates of cortical and subcortical gene expression. We found no overall differences in functional (or structural) connectivity anywhere in the brain comparing control and preHD participants. However, increased functional connectivity, particularly between posterior cortical areas, correlated with increasing CSF NfL level in preHD participants. Using the Allen Human Brain Atlas and expression-weighted cell-type enrichment analysis, we demonstrated that this functional connectivity upregulation occurred in cortical regions associated with regional expression of genes specific to neuronal cells. This relationship was validated using single-nucleus RNAseq data from post-mortem Huntington's disease and control brains showing enrichment of neuronal-specific genes that are differentially expressed in Huntington's disease. Functional brain networks in asymptomatic preHD gene carriers very far from disease onset show evidence of upregulated connectivity correlating with increased disease burden. These changes occur among brain areas that show regional expression of genes specific to neuronal GABAergic and glutamatergic cells.
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Affiliation(s)
- Peter McColgan
- Huntington’s Disease Centre, Department of Neurodegenerative disease, UCL Queen Square Institute of Neurology, University College London, London WC1N 3BG, UK
| | - Sarah Gregory
- Huntington’s Disease Centre, Department of Neurodegenerative disease, UCL Queen Square Institute of Neurology, University College London, London WC1N 3BG, UK
| | - Paul Zeun
- Huntington’s Disease Centre, Department of Neurodegenerative disease, UCL Queen Square Institute of Neurology, University College London, London WC1N 3BG, UK
| | - Angeliki Zarkali
- Dementia Research Centre, University College London, London WC1N 3AR, UK
| | - Eileanoir B Johnson
- Huntington’s Disease Centre, Department of Neurodegenerative disease, UCL Queen Square Institute of Neurology, University College London, London WC1N 3BG, UK
| | - Christopher Parker
- Department of Computer Science and Centre for Medical Image Computing, University College London, London WC1V 6LJ, UK
| | - Kate Fayer
- Huntington’s Disease Centre, Department of Neurodegenerative disease, UCL Queen Square Institute of Neurology, University College London, London WC1N 3BG, UK
| | - Jessica Lowe
- Huntington’s Disease Centre, Department of Neurodegenerative disease, UCL Queen Square Institute of Neurology, University College London, London WC1N 3BG, UK
| | - Akshay Nair
- Huntington’s Disease Centre, Department of Neurodegenerative disease, UCL Queen Square Institute of Neurology, University College London, London WC1N 3BG, UK
- Max Planck University College London Centre for Computational Psychiatry and Ageing Research, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
| | - Carlos Estevez-Fraga
- Huntington’s Disease Centre, Department of Neurodegenerative disease, UCL Queen Square Institute of Neurology, University College London, London WC1N 3BG, UK
| | - Marina Papoutsi
- Huntington’s Disease Centre, Department of Neurodegenerative disease, UCL Queen Square Institute of Neurology, University College London, London WC1N 3BG, UK
| | - Hui Zhang
- Dementia Research Centre, University College London, London WC1N 3AR, UK
| | - Rachael I Scahill
- Huntington’s Disease Centre, Department of Neurodegenerative disease, UCL Queen Square Institute of Neurology, University College London, London WC1N 3BG, UK
| | - Sarah J Tabrizi
- Huntington’s Disease Centre, Department of Neurodegenerative disease, UCL Queen Square Institute of Neurology, University College London, London WC1N 3BG, UK
- Dementia Research Centre, University College London, London WC1N 3AR, UK
| | - Geraint Rees
- University College London Institute of Cognitive Neuroscience, University College London, London WC1N 3AZ, UK
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12
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Koval I, Dighiero-Brecht T, Tobin AJ, Tabrizi SJ, Scahill RI, Tezenas du Montcel S, Durrleman S, Durr A. Forecasting individual progression trajectories in Huntington disease enables more powered clinical trials. Sci Rep 2022; 12:18928. [PMID: 36344508 PMCID: PMC9640581 DOI: 10.1038/s41598-022-18848-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2022] [Accepted: 08/22/2022] [Indexed: 11/09/2022] Open
Abstract
Variability in neurodegenerative disease progression poses great challenges for the evaluation of potential treatments. Identifying the persons who will experience significant progression in the short term is key for the implementation of trials with smaller sample sizes. We apply here disease course mapping to forecast biomarker progression for individual carriers of the pathological CAG repeat expansions responsible for Huntington disease. We used data from two longitudinal studies (TRACK-HD and TRACK-ON) to synchronize temporal progression of 15 clinical and imaging biomarkers from 290 participants with Huntington disease. We used then the resulting HD COURSE MAP to forecast clinical endpoints from the baseline data of 11,510 participants from ENROLL-HD, an external validation cohort. We used such forecasts to select participants at risk for progression and compute the power of trials for such an enriched population. HD COURSE MAP forecasts biomarkers 5 years after the baseline measures with a maximum mean absolute error of 10 points for the total motor score and 2.15 for the total functional capacity. This allowed reducing sample sizes in trial up to 50% including participants with a higher risk for progression ensuring a more homogeneous group of participants.
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Affiliation(s)
- Igor Koval
- Institut du Cerveau - Paris Brain Institute - ICM, CNRS, Inria, Inserm, AP-HP, Hôpital de la Pitié Salpêtrière, Sorbonne Université, 75013, Paris, France
| | - Thomas Dighiero-Brecht
- Institut du Cerveau - Paris Brain Institute - ICM, CNRS, Inria, Inserm, AP-HP, Hôpital de la Pitié Salpêtrière, Sorbonne Université, 75013, Paris, France
| | - Allan J Tobin
- Biological Adaptation and Ageing, Sorbonne Université, Paris, France
- Brain Research Institute, University of California Los Angeles, Los Angeles, CA, USA
| | - Sarah J Tabrizi
- UCL Queen Square Institute of Neurology, University College London, Queen Square, London, UK
| | - Rachael I Scahill
- UCL Queen Square Institute of Neurology, University College London, Queen Square, London, UK
| | - Sophie Tezenas du Montcel
- Institut du Cerveau - Paris Brain Institute - ICM, CNRS, Inria, Inserm, AP-HP, Hôpital de la Pitié Salpêtrière, Sorbonne Université, 75013, Paris, France
| | - Stanley Durrleman
- Institut du Cerveau - Paris Brain Institute - ICM, CNRS, Inria, Inserm, AP-HP, Hôpital de la Pitié Salpêtrière, Sorbonne Université, 75013, Paris, France.
| | - Alexandra Durr
- Department of Neurology, DMU Neurosciences, Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, CNRS, Inserm, AP-HP, Hôpital de la Pitié Salpêtrière, 75013, Paris, France.
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13
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Teismann H, Schubert R, Reilmann R, Berger K. Effects of age and sex on outcomes of the Q-Motor speeded finger tapping and grasping and lifting tests-findings from the population-based BiDirect Study. Front Neurol 2022; 13:965031. [PMID: 36247774 PMCID: PMC9561931 DOI: 10.3389/fneur.2022.965031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2022] [Accepted: 08/30/2022] [Indexed: 12/03/2022] Open
Abstract
Background Q-Motor is a suite of motor tests originally designed to assess motor symptoms in Huntington's disease. Among others, Q-Motor encompasses a finger tapping task and a grasping and lifting task. To date, there are no systematic investigations regarding effects of variables which may affect the performance in specific Q-Motor tests per se, and normative Q-Motor data based on a large population-based sample are not yet available. Objective We investigated effects of age and sex on five selected Q-Motor outcomes representing the two core Q-Motor tasks speeded finger tapping and grasping and lifting in a community sample of middle-aged to elderly adults. Furthermore, we explored effects of the potentially mediating variables educational attainment, alcohol consumption, smoking status, and depressive symptoms. Moreover, we explored inter-examiner variability. Finally, we compared the findings to findings for the Purdue Pegboard test. Methods Based on a sample of 726 community-dwelling adults and using multiple (Gaussian) regression analysis, we modeled the motor outcomes using age, sex, years in full-time education, depressive symptoms in the past seven days, alcohol consumption in the past seven days, and smoking status as explanatory variables. Results With regard to the Q-Motor tests, we found that more advanced age was associated with reduced tapping speed, male sex was associated with increased tapping speed and less irregularity, female sex was associated with less involuntary movement, more years of education were associated with increased tapping speed and less involuntary movement, never smoking was associated with less involuntary movement compared to current smoking, and more alcohol consumed was associated with more involuntary movement. Conclusion The present results show specific effects of age and sex on Q-Motor finger tapping and grasping and lifting performance. In addition, besides effects of education, there also were specific effects of smoking status and alcohol consumption. Importantly, the present study provides normative Q-Motor data based on a large population-based sample. Overall, the results are in favor of the feasibility and validity of Q-Motor finger tapping and grasping and lifting for large observational studies. Due to their low task-complexity and lack of placebo effects, Q-Motor tests may generate additional value in particular with regard to clinical conditions such as Huntington's or Parkinson's disease.
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Affiliation(s)
- Henning Teismann
- Institute of Epidemiology and Social Medicine, University of Münster, Münster, Germany
- *Correspondence: Henning Teismann
| | | | - Ralf Reilmann
- George-Huntington-Institute, Münster, Germany
- Institute of Clinical Radiology, University of Münster, Münster, Germany
- Department of Neurodegenerative Diseases and Hertie-Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
| | - Klaus Berger
- Institute of Epidemiology and Social Medicine, University of Münster, Münster, Germany
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14
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Kang W, Wang J, Malvaso A. Inhibitory Control in Aging: The Compensation-Related Utilization of Neural Circuits Hypothesis. Front Aging Neurosci 2022; 13:771885. [PMID: 35967887 PMCID: PMC9371469 DOI: 10.3389/fnagi.2021.771885] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2021] [Accepted: 10/20/2021] [Indexed: 11/13/2022] Open
Abstract
As one of the core executive functions, inhibitory control plays an important role in human life. Inhibitory control refers to the ability to suppress task irrelevant information both internally and externally. Modern cognitive neuroscience has extensively investigated the neural basis of inhibitory control, less is known about the inhibitory control mechanisms in aging. Growing interests in cognitive declines of aging have given raise to the compensation-related utilization of neural circuits hypothesis (CRUNCH). In this review, we survey both behavioral, functional, and structural changes relevant to inhibitory control in aging. In line with CRUNCH, we found that older adults engage additional brain regions than younger adults when performing the same cognitive task, to compensate for declining brain structures and functions. Moreover, we propose CRUNCH could well take functional inhibitory deficits in older adults into account. Finally, we provide three sensible future research directions.
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Affiliation(s)
- Weixi Kang
- Imperial College London, London, United Kingdom
- *Correspondence: Weixi Kang,
| | - Junxin Wang
- Beijing University of Chinese Medicine, Beijing, China
| | - Antonio Malvaso
- School of Medicine and Surgery, Vita-Salute San Raffaele University, Milan, Italy
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15
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Tabrizi SJ, Schobel S, Gantman EC, Mansbach A, Borowsky B, Konstantinova P, Mestre TA, Panagoulias J, Ross CA, Zauderer M, Mullin AP, Romero K, Sivakumaran S, Turner EC, Long JD, Sampaio C. A biological classification of Huntington's disease: the Integrated Staging System. Lancet Neurol 2022; 21:632-644. [PMID: 35716693 DOI: 10.1016/s1474-4422(22)00120-x] [Citation(s) in RCA: 69] [Impact Index Per Article: 34.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2021] [Revised: 02/11/2022] [Accepted: 03/11/2022] [Indexed: 12/24/2022]
Abstract
The current research paradigm for Huntington's disease is based on participants with overt clinical phenotypes and does not address its pathophysiology nor the biomarker changes that can precede by decades the functional decline. We have generated a new research framework to standardise clinical research and enable interventional studies earlier in the disease course. The Huntington's Disease Integrated Staging System (HD-ISS) comprises a biological research definition and evidence-based staging centred on biological, clinical, and functional assessments. We used a formal consensus method that involved representatives from academia, industry, and non-profit organisations. The HD-ISS characterises individuals for research purposes from birth, starting at Stage 0 (ie, individuals with the Huntington's disease genetic mutation without any detectable pathological change) by using a genetic definition of Huntington's disease. Huntington's disease progression is then marked by measurable indicators of underlying pathophysiology (Stage 1), a detectable clinical phenotype (Stage 2), and then decline in function (Stage 3). Individuals can be precisely classified into stages based on thresholds of stage-specific landmark assessments. We also demonstrated the internal validity of this system. The adoption of the HD-ISS could facilitate the design of clinical trials targeting populations before clinical motor diagnosis and enable data standardisation across ongoing and future studies.
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Affiliation(s)
- Sarah J Tabrizi
- UCL Huntington's Disease Centre, Department of Neurodegenerative Diseases, UCL Queen Square Institute of Neurology, UK Dementia Research Institute, University College London, UK.
| | - Scott Schobel
- Product Development Neuroscience, F Hoffmann-La Roche, Basel, Switzerland
| | | | | | | | | | - Tiago A Mestre
- Parkinson's Disease and Movement Disorders Centre, Division of Neurology, Department of Medicine, The Ottawa Hospital Research Institute, University of Ottawa Brain and Mind Research Institute, Ottawa, ON, Canada
| | | | - Christopher A Ross
- Division of Neurobiology, Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Departments of Neurology, Neuroscience, and Pharmacology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | | | | | - Klaus Romero
- Critical Path Institute, Tucson, Arizona 85718, USA
| | | | | | - Jeffrey D Long
- Department of Psychiatry, Department of Biostatistics, University of Iowa, Iowa City, IA, USA
| | - Cristina Sampaio
- CHDI Management/CHDI Foundation, Princeton, NJ, USA; Clinical Pharmacology Laboratory, Faculdade de Medicina de Lisboa, University of Lisbon, Lisbon, Portugal.
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16
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Lei W, Xiao Q, Wang C, Gao W, Xiao Y, Dai Y, Lu G, Su L, Zhong Y. Cell-type-specific genes associated with cortical structural abnormalities in pediatric bipolar disorder. PSYCHORADIOLOGY 2022; 2:56-65. [PMID: 38665968 PMCID: PMC11044809 DOI: 10.1093/psyrad/kkac009] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/14/2022] [Revised: 08/06/2022] [Accepted: 08/19/2022] [Indexed: 04/28/2024]
Abstract
Background Pediatric bipolar disorder (PBD) has been proven to be related to abnormal brain structural connectivity, but how the abnormalities in PBD correlate with gene expression is debated. Objective This study aims at identification of cell-type-specific gene modules based on cortical structural differences in PBD. Methods Morphometric similarity networks (MSN) were computed as a marker of interareal cortical connectivity based on MRI data from 102 participants (59 patients and 43 controls). Partial least squares (PLS) regression was used to calculate MSN differences related to transcriptomic data in AHBA. The biological processes and cortical cell types associated with this gene expression profile were determined by gene enrichment tools. Results MSN analysis results demonstrated differences of cortical structure between individuals diagnosed with PBD and healthy control participants. MSN differences were spatially correlated with the PBD-related weighted genes. The weighted genes were enriched for "trans-synaptic signaling" and "regulation of ion transport", and showed significant specific expression in excitatory and inhibitory neurons. Conclusions This study identified the genes that contributed to structural network aberrations in PBD. It was found that transcriptional changes of excitatory and inhibitory neurons might be associated with abnormal brain structural connectivity in PBD.
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Affiliation(s)
- Wenkun Lei
- School of Psychology, Nanjing Normal University, Nanjing, Jiangsu 210097, China
- Nanjing Normal University, Jiangsu Key Laboratory of Mental Health and Cognitive Science, Nanjing, Jiangsu 210097, China
| | - Qian Xiao
- The Mental Health Centre of Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
| | - Chun Wang
- The Department of Psychiatry, Nanjing Brain Hospital Affiliated to Nanjing Medical University, Nanjing, Jiangsu 210029, China
| | - Weijia Gao
- The Children's Hospital affiliated to the Medical College of Zhejiang University, Hangzhou, Zhejiang 310003, China
| | - Yiwen Xiao
- School of Psychology, Nanjing Normal University, Nanjing, Jiangsu 210097, China
- Nanjing Normal University, Jiangsu Key Laboratory of Mental Health and Cognitive Science, Nanjing, Jiangsu 210097, China
| | - Yingliang Dai
- School of Psychology, Nanjing Normal University, Nanjing, Jiangsu 210097, China
- Nanjing Normal University, Jiangsu Key Laboratory of Mental Health and Cognitive Science, Nanjing, Jiangsu 210097, China
| | - Guangming Lu
- The Department of Medical Imaging, Jinling Hospital, Nanjing University School of Medicine, Nanjing, Jiangsu 210002, China
| | - Linyan Su
- The Second Xiangya Hospital of Central South University, Changsha, Hunan 410008, China
| | - Yuan Zhong
- School of Psychology, Nanjing Normal University, Nanjing, Jiangsu 210097, China
- Nanjing Normal University, Jiangsu Key Laboratory of Mental Health and Cognitive Science, Nanjing, Jiangsu 210097, China
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17
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Zeun P, McColgan P, Dhollander T, Gregory S, Johnson EB, Papoutsi M, Nair A, Scahill RI, Rees G, Tabrizi SJ. Timing of selective basal ganglia white matter loss in premanifest Huntington's disease. Neuroimage Clin 2022; 33:102927. [PMID: 34999565 PMCID: PMC8757039 DOI: 10.1016/j.nicl.2021.102927] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2021] [Revised: 11/30/2021] [Accepted: 12/21/2021] [Indexed: 12/13/2022]
Abstract
OBJECTIVES To investigate the timeframe prior to symptom onset when cortico-basal ganglia white matter (white matter) loss begins in premanifest Huntington's disease (preHD), and which striatal and thalamic sub-region white matter tracts are most vulnerable. METHODS We performed fixel-based analysis, which allows resolution of crossing white matter fibres at the voxel level, on diffusion tractography derived white matter tracts of striatal and thalamic sub-regions in two independent cohorts; TrackON-HD, which included 72 preHD (approx. 11 years before disease onset) and 85 controls imaged at three time points over two years; and the HD young adult study (HD-YAS), which included 54 preHD (approx. 25 years before disease onset) and 53 controls, imaged at one time point. Group differences in fibre density and cross section (FDC) were investigated. RESULTS We found no significant group differences in cortico-basal ganglia sub-region FDC in preHD gene carriers 25 years before onset. In gene carriers 11 years before onset, there were reductions in striatal (limbic and caudal motor) and thalamic (premotor, motor and sensory) FDC at baseline, with no significant change over 2 years. Caudal motor-striatal, pre-motor-thalamic, and primary motor-thalamic FDC at baseline, showed significant correlations with the Unified Huntington's disease rating scale (UHDRS) total motor score (TMS). Limbic cortico-striatal FDC and apathy were also significantly correlated. CONCLUSIONS Our findings suggest that limbic and motor white matter tracts to the striatum and thalamus are most susceptible to early degeneration in HD but that approximately 25 years from onset, these tracts appear preserved. These findings may have importance in determining the optimum time to initiate future disease modifying therapies in HD.
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Affiliation(s)
- Paul Zeun
- Huntington's Disease Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, WC1N 3BG, UK
| | - Peter McColgan
- Huntington's Disease Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, WC1N 3BG, UK
| | - Thijs Dhollander
- The Murdoch Children's Research Institute, Parkville Victoria 3052, Australia
| | - Sarah Gregory
- Huntington's Disease Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, WC1N 3BG, UK
| | - Eileanoir B Johnson
- Huntington's Disease Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, WC1N 3BG, UK
| | - Marina Papoutsi
- Huntington's Disease Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, WC1N 3BG, UK
| | - Akshay Nair
- Huntington's Disease Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, WC1N 3BG, UK; Max Planck UCL Centre for Computational Psychiatry and Ageing Research, UCL Queen Square Institute of Neurology, University College London, WC1N 3BG, UK
| | - Rachael I Scahill
- Huntington's Disease Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, WC1N 3BG, UK
| | - Geraint Rees
- UCL Institute of Cognitive Neuroscience, Queen Square, London WC1N 3BG, UK
| | - Sarah J Tabrizi
- Huntington's Disease Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, WC1N 3BG, UK; Dementia Research Institute at UCL, London WC1N 3BG, UK.
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18
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Nair A, Razi A, Gregory S, Rutledge RR, Rees G, Tabrizi SJ. Imbalanced basal ganglia connectivity is associated with motor deficits and apathy in Huntington's disease. Brain 2021; 145:991-1000. [PMID: 34633421 PMCID: PMC9050569 DOI: 10.1093/brain/awab367] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2021] [Revised: 08/16/2021] [Accepted: 08/24/2021] [Indexed: 11/12/2022] Open
Abstract
The gating of movement depends on activity within the cortico-striato-thalamic loops. Within these loops, emerging from the cells of the striatum, run two opponent pathways—the direct and indirect basal ganglia pathways. Both are complex and polysynaptic, but the overall effect of activity within these pathways is thought to encourage and inhibit movement, respectively. In Huntington’s disease, the preferential early loss of striatal neurons forming the indirect pathway is thought to lead to disinhibition, giving rise to the characteristic motor features of the condition. But early Huntington’s disease is also associated with apathy, a loss of motivation and failure to engage in goal-directed movement. We hypothesized that in Huntington’s disease, motor signs and apathy may be selectively correlated with indirect and direct pathway dysfunction, respectively. We used spectral dynamic casual modelling of resting-state functional MRI data to model effective connectivity in a model of these cortico-striatal pathways. We tested both of these hypotheses in vivo for the first time in a large cohort of patients with prodromal Huntington’s disease. Using an advanced approach at the group level we combined parametric empirical Bayes and Bayesian model reduction procedures to generate a large number of competing models and compare them using Bayesian model comparison. With this automated Bayesian approach, associations between clinical measures and connectivity parameters emerge de novo from the data. We found very strong evidence (posterior probability > 0.99) to support both of our hypotheses. First, more severe motor signs in Huntington’s disease were associated with altered connectivity in the indirect pathway components of our model and, by comparison, loss of goal-direct behaviour or apathy, was associated with changes in the direct pathway component. The empirical evidence we provide here demonstrates that imbalanced basal ganglia connectivity may play an important role in the pathogenesis of some of commonest and disabling features of Huntington’s disease and may have important implications for therapeutics.
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Affiliation(s)
- Akshay Nair
- Huntington's Disease Centre, UCL Queen Square Institute of Neurology, University College London, Russell Square House, London, WC1B 5EH, UK.,UCL Institute of Cognitive Neuroscience, University College London, Alexandra House, 17-19 Queen Square, Bloomsbury, London, WC1N 3AZ, UK
| | - Adeel Razi
- Turner Institute for Brain and Mental Health, Monash Biomedical Imaging, Monash University, 770 Blackburn Road, Clayton 3800, Australia.,Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, 12 Queen Square, London, WC1N 3AR, UK
| | - Sarah Gregory
- Huntington's Disease Centre, UCL Queen Square Institute of Neurology, University College London, Russell Square House, London, WC1B 5EH, UK
| | - Robb R Rutledge
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, 12 Queen Square, London, WC1N 3AR, UK.,Max Planck UCL Centre for Computational Psychiatry and Ageing Research, UCL Queen Square Institute of Neurology, University College London, Russell Square House, London, WC1B 5EH, UK.,Department of Psychology, Yale University, New Haven, CT 06511, USA
| | - Geraint Rees
- Huntington's Disease Centre, UCL Queen Square Institute of Neurology, University College London, Russell Square House, London, WC1B 5EH, UK.,UCL Institute of Cognitive Neuroscience, University College London, Alexandra House, 17-19 Queen Square, Bloomsbury, London, WC1N 3AZ, UK.,Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, 12 Queen Square, London, WC1N 3AR, UK
| | - Sarah J Tabrizi
- Huntington's Disease Centre, UCL Queen Square Institute of Neurology, University College London, Russell Square House, London, WC1B 5EH, UK.,Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, 12 Queen Square, London, WC1N 3AR, UK
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19
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Aslan DH, Hernandez ME, Frechette ML, Gephart AT, Soloveychik IM, Sosnoff JJ. The neural underpinnings of motor learning in people with neurodegenerative diseases: A scoping review. Neurosci Biobehav Rev 2021; 131:882-898. [PMID: 34624367 DOI: 10.1016/j.neubiorev.2021.10.006] [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: 12/18/2020] [Revised: 09/02/2021] [Accepted: 10/02/2021] [Indexed: 11/25/2022]
Abstract
Chronic progressive neurodegenerative diseases (NDD) cause mobility and cognitive impairments that disrupt quality of life. The learning of new motor skills, motor learning, is a critical component of rehabilitation efforts to counteract these chronic progressive impairments. In people with NDD, there are impairments in motor learning which appear to scale with the severity of impairment. Compensatory cortical activity plays a role in counteracting motor learning impairments in NDD. Yet, the functional and structural brain alterations associated with motor learning have not been synthesized in people with NDD. The purpose of this scoping review is to explore the neural alterations of motor learning in NDD. Thirty-five peer-reviewed original articles met the inclusion criteria. Participant demographics, motor learning results, and brain imaging results were extracted. Distinct motor learning associated compensatory processes were identified across NDD populations. Evidence from this review suggests the success of motor learning in NDD populations depends on the neural alterations and their interaction with motor learning networks, as well as the progression of disease.
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Affiliation(s)
- Daniel H Aslan
- Department of Kinesiology and Community Health, United States.
| | | | - Mikaela L Frechette
- Department of Molecular and Cellular Biology, University of Illinois, Urbana Champaign, United States
| | - Aaron T Gephart
- Department of Molecular and Cellular Biology, University of Illinois, Urbana Champaign, United States
| | - Isaac M Soloveychik
- Department of Molecular and Cellular Biology, University of Illinois, Urbana Champaign, United States
| | - Jacob J Sosnoff
- Department of Molecular and Cellular Biology, University of Illinois, Urbana Champaign, United States
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20
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Di Lazzaro V, Bella R, Benussi A, Bologna M, Borroni B, Capone F, Chen KHS, Chen R, Chistyakov AV, Classen J, Kiernan MC, Koch G, Lanza G, Lefaucheur JP, Matsumoto H, Nguyen JP, Orth M, Pascual-Leone A, Rektorova I, Simko P, Taylor JP, Tremblay S, Ugawa Y, Dubbioso R, Ranieri F. Diagnostic contribution and therapeutic perspectives of transcranial magnetic stimulation in dementia. Clin Neurophysiol 2021; 132:2568-2607. [PMID: 34482205 DOI: 10.1016/j.clinph.2021.05.035] [Citation(s) in RCA: 86] [Impact Index Per Article: 28.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2020] [Revised: 04/22/2021] [Accepted: 05/28/2021] [Indexed: 02/07/2023]
Abstract
Transcranial magnetic stimulation (TMS) is a powerful tool to probe in vivo brain circuits, as it allows to assess several cortical properties such asexcitability, plasticity and connectivity in humans. In the last 20 years, TMS has been applied to patients with dementia, enabling the identification of potential markers of thepathophysiology and predictors of cognitive decline; moreover, applied repetitively, TMS holds promise as a potential therapeutic intervention. The objective of this paper is to present a comprehensive review of studies that have employed TMS in dementia and to discuss potential clinical applications, from the diagnosis to the treatment. To provide a technical and theoretical framework, we first present an overview of the basic physiological mechanisms of the application of TMS to assess cortical excitability, excitation and inhibition balance, mechanisms of plasticity and cortico-cortical connectivity in the human brain. We then review the insights gained by TMS techniques into the pathophysiology and predictors of progression and response to treatment in dementias, including Alzheimer's disease (AD)-related dementias and secondary dementias. We show that while a single TMS measure offers low specificity, the use of a panel of measures and/or neurophysiological index can support the clinical diagnosis and predict progression. In the last part of the article, we discuss the therapeutic uses of TMS. So far, only repetitive TMS (rTMS) over the left dorsolateral prefrontal cortex and multisite rTMS associated with cognitive training have been shown to be, respectively, possibly (Level C of evidence) and probably (Level B of evidence) effective to improve cognition, apathy, memory, and language in AD patients, especially at a mild/early stage of the disease. The clinical use of this type of treatment warrants the combination of brain imaging techniques and/or electrophysiological tools to elucidate neurobiological effects of neurostimulation and to optimally tailor rTMS treatment protocols in individual patients or specific patient subgroups with dementia or mild cognitive impairment.
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Affiliation(s)
- Vincenzo Di Lazzaro
- Unit of Neurology, Neurophysiology, Neurobiology, Department of Medicine, Università Campus Bio-Medico di Roma, Rome, Italy.
| | - Rita Bella
- Department of Medical and Surgical Sciences and Advanced Technologies, Section of Neurosciences, University of Catania, Catania, Italy
| | - Alberto Benussi
- Centre for Neurodegenerative Disorders, Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy
| | - Matteo Bologna
- Department of Human Neurosciences, Sapienza University of Rome, Italy; IRCCS Neuromed, Pozzilli, IS, Italy
| | - Barbara Borroni
- Centre for Neurodegenerative Disorders, Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy
| | - Fioravante Capone
- Unit of Neurology, Neurophysiology, Neurobiology, Department of Medicine, Università Campus Bio-Medico di Roma, Rome, Italy
| | - Kai-Hsiang S Chen
- Department of Neurology, National Taiwan University Hospital Hsin-Chu Branch, Hsin-Chu, Taiwan
| | - Robert Chen
- Division of Neurology, Department of Medicine, University of Toronto, Toronto, Canada; Division of Brain, Imaging& Behaviour, Krembil Brain Institute, Toronto, Canada
| | | | - Joseph Classen
- Department of Neurology, University Hospital Leipzig, Leipzig University Medical Center, Germany
| | - Matthew C Kiernan
- Department of Neurology, Royal Prince Alfred Hospital, Brain and Mind Centre, University of Sydney, Sydney, New South Wales, Australia
| | - Giacomo Koch
- Non Invasive Brain Stimulation Unit/Department of Behavioral and Clinical Neurology, Santa Lucia Foundation IRCCS, Rome, Italy; Department of Neuroscience and Rehabilitation, University of Ferrara, Ferrara, Italy
| | - Giuseppe Lanza
- Department of Surgery and Medical-Surgical Specialties, University of Catania, Catania, Italy; Department of Neurology IC, Oasi Research Institute-IRCCS, Troina, Italy
| | - Jean-Pascal Lefaucheur
- ENT Team, EA4391, Faculty of Medicine, Paris Est Créteil University, Créteil, France; Clinical Neurophysiology Unit, Department of Physiology, Henri Mondor Hospital, Assistance Publique - Hôpitaux de Paris, Créteil, France
| | | | - Jean-Paul Nguyen
- Pain Center, clinique Bretéché, groupe ELSAN, Multidisciplinary Pain, Palliative and Supportive care Center, UIC 22/CAT2 and Laboratoire de Thérapeutique (EA3826), University Hospital, Nantes, France
| | - Michael Orth
- University Hospital of Old Age Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland; Swiss Huntington's Disease Centre, Siloah, Bern, Switzerland
| | - Alvaro Pascual-Leone
- Hinda and Arthur Marcus Institute for Aging Research, Center for Memory Health, Hebrew SeniorLife, USA; Department of Neurology, Harvard Medical School, Boston, MA, USA; Guttmann Brain Health Institute, Universitat Autonoma Barcelona, Spain
| | - Irena Rektorova
- Applied Neuroscience Research Group, Central European Institute of Technology, Masaryk University (CEITEC MU), Brno, Czech Republic; Department of Neurology, St. Anne's University Hospital and Faculty of Medicine, Masaryk University, Brno, Czech Republic
| | - Patrik Simko
- Applied Neuroscience Research Group, Central European Institute of Technology, Masaryk University (CEITEC MU), Brno, Czech Republic; Faculty of Medicine, Masaryk University, Brno, Czech Republic
| | - John-Paul Taylor
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Sara Tremblay
- Department of Cellular and Molecular Medicine, Faculty of Medicine, University of Ottawa, ON, Canada; Royal Ottawa Institute of Mental Health Research, Ottawa, ON, Canada
| | - Yoshikazu Ugawa
- Department of Human Neurophysiology, School of Medicine, Fukushima Medical University, Fukushima, Japan
| | - Raffaele Dubbioso
- Department of Neurosciences, Reproductive Sciences and Odontostomatology, University of Naples "Federico II", Naples, Italy
| | - Federico Ranieri
- Unit of Neurology, Department of Neuroscience, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
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21
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Wijeratne PA, Garbarino S, Gregory S, Johnson EB, Scahill RI, Paulsen JS, Tabrizi SJ, Lorenzi M, Alexander DC. Revealing the Timeline of Structural MRI Changes in Premanifest to Manifest Huntington Disease. Neurol Genet 2021; 7:e617. [PMID: 34660889 PMCID: PMC8515202 DOI: 10.1212/nxg.0000000000000617] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2021] [Accepted: 07/06/2021] [Indexed: 01/18/2023]
Abstract
BACKGROUND AND OBJECTIVES Longitudinal measurements of brain atrophy using structural MRI (sMRI) can provide powerful markers for tracking disease progression in neurodegenerative diseases. In this study, we use a disease progression model to learn individual-level disease times and hence reveal a new timeline of sMRI changes in Huntington disease (HD). METHODS We use data from the 2 largest cohort imaging studies in HD-284 participants from TRACK-HD (100 control, 104 premanifest, and 80 manifest) and 159 participants from PREDICT-HD (36 control and 128 premanifest)-to train and test the model. We longitudinally register T1-weighted sMRI scans from 3 consecutive time points to reduce intraindividual variability and calculate regional brain volumes using an automated segmentation tool with rigorous manual quality control. RESULTS Our model reveals, for the first time, the relative magnitude and timescale of subcortical and cortical atrophy changes in HD. We find that the largest (∼20% average change in magnitude) and earliest (∼2 years before average abnormality) changes occur in the subcortex (pallidum, putamen, and caudate), followed by a cascade of changes across other subcortical and cortical regions over a period of ∼11 years. We also show that sMRI, when combined with our disease progression model, provides improved prediction of onset over the current best method (root mean square error = 4.5 years and maximum error = 7.9 years vs root mean square error = 6.6 years and maximum error = 18.2 years). DISCUSSION Our findings support the use of disease progression modeling to reveal new information from sMRI, which can potentially inform imaging marker selection for clinical trials.
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Affiliation(s)
- Peter A. Wijeratne
- From the Centre for Medical Image Computing (P.A.W., D.C.A.), Department of Computer Science, University College London, Gower Street; Huntington's Disease Research Centre (P.A.W., S. Gregory, E.B.J., R.I.S., S.J.T.), Department of Neurodegenerative Disease, University College London, Queen Square Institute of Neurology, London, United Kingdom; Dipartimento di Matematica (S. Garbarino), UNIGE, DIMA, Genova, Italy; Departments of Neurology and Psychiatry (J.S.P.), Carver College of Medicine, University of Iowa; and Université Côte d’Azur (M.L.), Inria, Epione Research Project, Valbonne, France
| | - Sara Garbarino
- From the Centre for Medical Image Computing (P.A.W., D.C.A.), Department of Computer Science, University College London, Gower Street; Huntington's Disease Research Centre (P.A.W., S. Gregory, E.B.J., R.I.S., S.J.T.), Department of Neurodegenerative Disease, University College London, Queen Square Institute of Neurology, London, United Kingdom; Dipartimento di Matematica (S. Garbarino), UNIGE, DIMA, Genova, Italy; Departments of Neurology and Psychiatry (J.S.P.), Carver College of Medicine, University of Iowa; and Université Côte d’Azur (M.L.), Inria, Epione Research Project, Valbonne, France
| | - Sarah Gregory
- From the Centre for Medical Image Computing (P.A.W., D.C.A.), Department of Computer Science, University College London, Gower Street; Huntington's Disease Research Centre (P.A.W., S. Gregory, E.B.J., R.I.S., S.J.T.), Department of Neurodegenerative Disease, University College London, Queen Square Institute of Neurology, London, United Kingdom; Dipartimento di Matematica (S. Garbarino), UNIGE, DIMA, Genova, Italy; Departments of Neurology and Psychiatry (J.S.P.), Carver College of Medicine, University of Iowa; and Université Côte d’Azur (M.L.), Inria, Epione Research Project, Valbonne, France
| | - Eileanoir B. Johnson
- From the Centre for Medical Image Computing (P.A.W., D.C.A.), Department of Computer Science, University College London, Gower Street; Huntington's Disease Research Centre (P.A.W., S. Gregory, E.B.J., R.I.S., S.J.T.), Department of Neurodegenerative Disease, University College London, Queen Square Institute of Neurology, London, United Kingdom; Dipartimento di Matematica (S. Garbarino), UNIGE, DIMA, Genova, Italy; Departments of Neurology and Psychiatry (J.S.P.), Carver College of Medicine, University of Iowa; and Université Côte d’Azur (M.L.), Inria, Epione Research Project, Valbonne, France
| | - Rachael I. Scahill
- From the Centre for Medical Image Computing (P.A.W., D.C.A.), Department of Computer Science, University College London, Gower Street; Huntington's Disease Research Centre (P.A.W., S. Gregory, E.B.J., R.I.S., S.J.T.), Department of Neurodegenerative Disease, University College London, Queen Square Institute of Neurology, London, United Kingdom; Dipartimento di Matematica (S. Garbarino), UNIGE, DIMA, Genova, Italy; Departments of Neurology and Psychiatry (J.S.P.), Carver College of Medicine, University of Iowa; and Université Côte d’Azur (M.L.), Inria, Epione Research Project, Valbonne, France
| | - Jane S. Paulsen
- From the Centre for Medical Image Computing (P.A.W., D.C.A.), Department of Computer Science, University College London, Gower Street; Huntington's Disease Research Centre (P.A.W., S. Gregory, E.B.J., R.I.S., S.J.T.), Department of Neurodegenerative Disease, University College London, Queen Square Institute of Neurology, London, United Kingdom; Dipartimento di Matematica (S. Garbarino), UNIGE, DIMA, Genova, Italy; Departments of Neurology and Psychiatry (J.S.P.), Carver College of Medicine, University of Iowa; and Université Côte d’Azur (M.L.), Inria, Epione Research Project, Valbonne, France
| | - Sarah J. Tabrizi
- From the Centre for Medical Image Computing (P.A.W., D.C.A.), Department of Computer Science, University College London, Gower Street; Huntington's Disease Research Centre (P.A.W., S. Gregory, E.B.J., R.I.S., S.J.T.), Department of Neurodegenerative Disease, University College London, Queen Square Institute of Neurology, London, United Kingdom; Dipartimento di Matematica (S. Garbarino), UNIGE, DIMA, Genova, Italy; Departments of Neurology and Psychiatry (J.S.P.), Carver College of Medicine, University of Iowa; and Université Côte d’Azur (M.L.), Inria, Epione Research Project, Valbonne, France
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22
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Di Pietro M, Russo M, Dono F, Carrarini C, Thomas A, Di Stefano V, Telese R, Bonanni L, Sensi SL, Onofrj M, Franciotti R. A Critical Review of Alien Limb-Related Phenomena and Implications for Functional Magnetic Resonance Imaging Studies. Front Neurol 2021; 12:661130. [PMID: 34566830 PMCID: PMC8458742 DOI: 10.3389/fneur.2021.661130] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2021] [Accepted: 07/06/2021] [Indexed: 11/27/2022] Open
Abstract
Consensus criteria on corticobasal degeneration (CBD) include alien limb (AL) phenomena. However, the gist of the behavioral features of AL is still “a matter of debate.” CBD-related AL has so far included the description of involuntary movements, frontal release phenomena (frontal AL), or asomatognosia (posterior or “real” AL). In this context, the most frequent symptoms are language and praxis deficits and cortical sensory misperception. However, asomatognosia requires, by definition, intact perception and cognition. Thus, to make a proper diagnosis of AL in the context of CBD, cognitive and language dysfunctions must be carefully verified and objectively assessed. We reviewed the current literature on AL in CBD and now propose that the generic use of the term AL should be avoided. This catchall AL term should instead be deconstructed. We propose that the term AL is appropriate to describe clinical features associated with specific brain lesions. More discrete sets of regionally bound clinical signs that depend on dysfunctions of specific brain areas need to be assessed and presented when posing the diagnosis. Thus, in our opinion, the AL term should be employed in association with precise descriptions of the accompanying involuntary movements, sensory misperceptions, agnosia-asomatognosia contents, and the presence of utilization behavior. The review also offers an overview of functional magnetic resonance imaging-based studies evaluating AL-related phenomena. In addition, we provide a complementary set of video clips depicting CBD-related involuntary movements that should not mistakenly be interpreted as signs of AL.
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Affiliation(s)
- Martina Di Pietro
- Department of Neuroscience, Imaging and Clinical Sciences, "G. D'Annunzio" University of Chieti-Pescara, Chieti, Italy.,Center for Advanced Studies and Technology (CAST), "G. D'Annunzio" University, Chieti, Italy
| | - Mirella Russo
- Department of Neuroscience, Imaging and Clinical Sciences, "G. D'Annunzio" University of Chieti-Pescara, Chieti, Italy.,Center for Advanced Studies and Technology (CAST), "G. D'Annunzio" University, Chieti, Italy
| | - Fedele Dono
- Department of Neuroscience, Imaging and Clinical Sciences, "G. D'Annunzio" University of Chieti-Pescara, Chieti, Italy.,Center for Advanced Studies and Technology (CAST), "G. D'Annunzio" University, Chieti, Italy
| | - Claudia Carrarini
- Department of Neuroscience, Imaging and Clinical Sciences, "G. D'Annunzio" University of Chieti-Pescara, Chieti, Italy.,Center for Advanced Studies and Technology (CAST), "G. D'Annunzio" University, Chieti, Italy
| | - Astrid Thomas
- Department of Neuroscience, Imaging and Clinical Sciences, "G. D'Annunzio" University of Chieti-Pescara, Chieti, Italy.,Center for Advanced Studies and Technology (CAST), "G. D'Annunzio" University, Chieti, Italy
| | - Vincenzo Di Stefano
- Department of Neuroscience, Imaging and Clinical Sciences, "G. D'Annunzio" University of Chieti-Pescara, Chieti, Italy.,Department of Biomedicine, Neuroscience and Advanced Diagnostic (BiND), University of Palermo, Palermo, Italy
| | - Roberta Telese
- Department of Neuroscience, Imaging and Clinical Sciences, "G. D'Annunzio" University of Chieti-Pescara, Chieti, Italy.,IRCCS C. Mondino Foundation, Pavia, Italy
| | - Laura Bonanni
- Department of Neuroscience, Imaging and Clinical Sciences, "G. D'Annunzio" University of Chieti-Pescara, Chieti, Italy.,Center for Advanced Studies and Technology (CAST), "G. D'Annunzio" University, Chieti, Italy
| | - Stefano L Sensi
- Department of Neuroscience, Imaging and Clinical Sciences, "G. D'Annunzio" University of Chieti-Pescara, Chieti, Italy.,Center for Advanced Studies and Technology (CAST), "G. D'Annunzio" University, Chieti, Italy
| | - Marco Onofrj
- Department of Neuroscience, Imaging and Clinical Sciences, "G. D'Annunzio" University of Chieti-Pescara, Chieti, Italy.,Center for Advanced Studies and Technology (CAST), "G. D'Annunzio" University, Chieti, Italy.,YDA Foundation, Institute of Immune Therapy and Advanced Biological Treatment, Pescara, Italy
| | - Raffaella Franciotti
- Department of Neuroscience, Imaging and Clinical Sciences, "G. D'Annunzio" University of Chieti-Pescara, Chieti, Italy
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23
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Sathe S, Ware J, Levey J, Neacy E, Blumenstein R, Noble S, Mühlbäck A, Rosser A, Landwehrmeyer GB, Sampaio C. Enroll-HD: An Integrated Clinical Research Platform and Worldwide Observational Study for Huntington's Disease. Front Neurol 2021; 12:667420. [PMID: 34484094 PMCID: PMC8416308 DOI: 10.3389/fneur.2021.667420] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2021] [Accepted: 06/21/2021] [Indexed: 12/20/2022] Open
Abstract
Established in July 2012, Enroll-HD is both an integrated clinical research platform and a worldwide observational study designed to meet the clinical research requirements necessary to develop therapeutics for Huntington's disease (HD). The platform offers participants a low-burden entry into HD research, providing a large, well-characterized, research-engaged cohort with associated clinical data and biosamples that facilitates recruitment into interventional trials and other research studies. Additional studies that use Enroll-HD data and/or biosamples are built into the platform to further research on biomarkers and outcome measures. Enroll-HD is now operating worldwide in 21 countries at 159 clinical sites across four continents—Europe, North America, Latin America, and Australasia—and has recruited almost 25,000 participants, generating a large, rich clinical database with associated biosamples to expedite HD research; any researcher at a verifiable research organization can access the clinical datasets and biosamples from Enroll-HD and nested studies. Important operational features of Enroll-HD include a strong emphasis on standardization, data quality, and protecting participant identity, a single worldwide study protocol, a flexible EDC system capable of integrating multiple studies, a comprehensive monitoring infrastructure, an online portal to train and certify site personnel, and standardized study documents including informed consent forms and contractual agreements.
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Affiliation(s)
- Swati Sathe
- CHDI Management/CHDI Foundation, Princeton, NJ, United States
| | - Jen Ware
- CHDI Management/CHDI Foundation, Princeton, NJ, United States
| | - Jamie Levey
- CHDI Management/CHDI Foundation, Princeton, NJ, United States
| | - Eileen Neacy
- CHDI Management/CHDI Foundation, Princeton, NJ, United States
| | | | - Simon Noble
- CHDI Management/CHDI Foundation, Princeton, NJ, United States
| | | | - Anne Rosser
- Brain Repair Group, School of Biosciences, Cardiff University, Cardiff, United Kingdom.,Division of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, School of Medicine, Cardiff University, Cardiff, United Kingdom.,Brain Research and Intracranial Neurotherapeutics Unit, Cardiff University, Cardiff, United Kingdom
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24
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Abeyasinghe PM, Long JD, Razi A, Pustina D, Paulsen JS, Tabrizi SJ, Poudel GR, Georgiou-Karistianis N. Tracking Huntington's Disease Progression Using Motor, Functional, Cognitive, and Imaging Markers. Mov Disord 2021; 36:2282-2292. [PMID: 34014005 DOI: 10.1002/mds.28650] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2020] [Revised: 04/25/2021] [Accepted: 04/27/2021] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND Potential therapeutic targets and clinical trials for Huntington's disease have grown immensely in the last decade. However, to improve clinical trial outcomes, there is a need to better characterize profiles of signs and symptoms across different epochs of the disease to improve selection of participants. OBJECTIVE The objective of the present study was to best distinguish longitudinal trajectories across different Huntington's disease progression groups. METHODS Clinical and morphometric imaging data from 1082 participants across IMAGE-HD, TRACK-HD, and PREDICT-HD studies were combined, with longitudinal times ranging between 1 and 10 years. Participants were classified into 4 groups using CAG and age product. Using multivariate linear mixed modeling, 63 combinations of markers were tested for their sensitivity in differentiating CAG and age product groups. Next, multivariate linear mixed modeling was applied to define the best combination of markers to track progression across individual CAG and age product groups. RESULTS Putamen and caudate volumes, individually and/or combined, were identified as the best variables to both differentiate CAG and age product groups and track progression within them. The model using only caudate volume best described advanced disease progression in the combined data set. Contrary to expectations, combining clinical markers and volumetric measures did not improve tracking longitudinal progression. CONCLUSIONS Monitoring volumetric changes throughout a trial (alongside primary and secondary clinical end points) may provide a more comprehensive understanding of improvements in functional outcomes and help to improve the design of clinical trials. Alternatively, our results suggest that imaging deserves consideration as an end point in clinical trials because of the prospect of greater sensitivity. © 2021 International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Pubu M Abeyasinghe
- School of Psychological Sciences and Turner Institute for Brain and Mental Health, Monash University, Melbourne, Victoria, Australia
| | - Jeffrey D Long
- Department of Psychiatry, Carver Collage of Medicine, The University of Iowa, Iowa City, Iowa, USA.,Department of Biostatistics, College of Public Health, The University of Iowa, Iowa City, Iowa, USA
| | - Adeel Razi
- School of Psychological Sciences and Turner Institute for Brain and Mental Health, Monash University, Melbourne, Victoria, Australia.,Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia.,Wellcome Centre for Human Neuroimaging, UCL, London, United Kingdom
| | - Dorian Pustina
- CHDI Management/CHDI Foundation, Princeton, New Jersey, USA
| | - Jane S Paulsen
- Department of Neurology, University of Wisconsin, Madison, Wisconsin, USA
| | - Sarah J Tabrizi
- UCL Department of Neurodegenerative Disease and Huntington's Disease Centre, UCL Queen Square Institute of Neurology, Dementia Research Institute at UCL, London, United Kingdom
| | - Govinda R Poudel
- Mary MacKillop Institute for Health Research, Australian Catholic University, Melbourne, Victoria, Australia
| | - Nellie Georgiou-Karistianis
- School of Psychological Sciences and Turner Institute for Brain and Mental Health, Monash University, Melbourne, Victoria, Australia
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Schneider WT, Vas S, Nicol AU, Morton AJ. Abnormally abrupt transitions from sleep-to-wake in Huntington's disease sheep (Ovis aries) are revealed by automated analysis of sleep/wake transition dynamics. PLoS One 2021; 16:e0251767. [PMID: 33984047 PMCID: PMC8118338 DOI: 10.1371/journal.pone.0251767] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2021] [Accepted: 05/02/2021] [Indexed: 11/28/2022] Open
Abstract
Sleep disturbance is a common and disruptive symptom of neurodegenerative diseases such as Alzheimer’s and Huntington’s disease (HD). In HD patients, sleep fragmentation appears at an early stage of disease, although features of the earliest sleep abnormalities in presymptomatic HD are not fully established. Here we used novel automated analysis of quantitative electroencephalography to study transitions between wake and non-rapid eye movement sleep in a sheep model of presymptomatic HD. We found that while the number of transitions between sleep and wake were similar in normal and HD sheep, the dynamics of transitions from sleep-to-wake differed markedly between genotypes. Rather than the gradual changes in EEG power that occurs during transitioning from sleep-to-wake in normal sheep, transition into wake was abrupt in HD sheep. Furthermore, transitions to wake in normal sheep were preceded by a significant reduction in slow wave power, whereas in HD sheep this prior reduction in slow wave power was far less pronounced. This suggests an impaired ability to prepare for waking in HD sheep. The abruptness of awakenings may also have potential to disrupt sleep-dependent processes if they are interrupted in an untimely and disjointed manner. We propose that not only could these abnormal dynamics of sleep transitions be useful as an early biomarker of HD, but also that our novel methodology would be useful for studying transition dynamics in other sleep disorders.
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Affiliation(s)
- William T. Schneider
- Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, United Kingdom
| | - Szilvia Vas
- Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, United Kingdom
| | - Alister U. Nicol
- Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, United Kingdom
| | - A. Jennifer Morton
- Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, United Kingdom
- * E-mail:
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Johnson EB, Ziegler G, Penny W, Rees G, Tabrizi SJ, Scahill RI, Gregory S. Dynamics of Cortical Degeneration Over a Decade in Huntington's Disease. Biol Psychiatry 2021; 89:807-816. [PMID: 33500176 PMCID: PMC7986936 DOI: 10.1016/j.biopsych.2020.11.009] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/06/2020] [Revised: 10/14/2020] [Accepted: 11/08/2020] [Indexed: 12/13/2022]
Abstract
BACKGROUND Characterizing changing brain structure in neurodegeneration is fundamental to understanding long-term effects of pathology and ultimately providing therapeutic targets. It is well established that Huntington's disease (HD) gene carriers undergo progressive brain changes during the course of disease, yet the long-term trajectory of cortical atrophy is not well defined. Given that genetic therapies currently tested in HD are primarily expected to target the cortex, understanding atrophy across this region is essential. METHODS Capitalizing on a unique longitudinal dataset with a minimum of 3 and maximum of 7 brain scans from 49 HD gene carriers and 49 age-matched control subjects, we implemented a novel dynamical systems approach to infer patterns of regional neurodegeneration over 10 years. We use Bayesian hierarchical modeling to map participant- and group-level trajectories of atrophy spatially and temporally, additionally relating atrophy to the genetic marker of HD (CAG-repeat length) and motor and cognitive symptoms. RESULTS We show, for the first time, that neurodegenerative changes exhibit complex temporal dynamics with substantial regional variation around the point of clinical diagnosis. Although widespread group differences were seen across the cortex, the occipital and parietal regions undergo the greatest rate of cortical atrophy. We have established links between atrophy and genetic markers of HD while demonstrating that specific cortical changes predict decline in motor and cognitive performance. CONCLUSIONS HD gene carriers display regional variability in the spatial pattern of cortical atrophy, which relates to genetic factors and motor and cognitive symptoms. Our findings indicate a complex pattern of neuronal loss, which enables greater characterization of HD progression.
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Affiliation(s)
- Eileanoir B Johnson
- Huntington's Disease Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom.
| | - Gabriel Ziegler
- Institute of Cognitive Neurology and Dementia Research, Otto-von-Guericke-University Magdeburg, Magdeburg, Germany; German Center for Neurodegenerative Diseases, Magdeburg, Germany.
| | - William Penny
- School of Psychology, University of East Anglia, Norwich, United Kingdom
| | - Geraint Rees
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Sarah J Tabrizi
- Huntington's Disease Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom; Dementia Research Institute at University College London, London, United Kingdom
| | - Rachael I Scahill
- Huntington's Disease Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Sarah Gregory
- Huntington's Disease Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
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Raj A, Powell F. Network model of pathology spread recapitulates neurodegeneration and selective vulnerability in Huntington's Disease. Neuroimage 2021; 235:118008. [PMID: 33789134 DOI: 10.1016/j.neuroimage.2021.118008] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2021] [Revised: 03/16/2021] [Accepted: 03/23/2021] [Indexed: 12/12/2022] Open
Abstract
Huntington's Disease (HD), an autosomal dominant genetic disorder caused by a mutation in the Huntingtin gene (HTT), displays a stereotyped topography in the human brain and a stereotyped progression, initially appearing in the striatum. Like other degenerative diseases, spatial topography of HD is divorced from where implicated genes are expressed, a dissociation whose mechanistic underpinning is not currently understood. Cell autonomous molecular factors characterized by gene expression signatures, including proteolytic and post translational modifications, play a role in vulnerability to disease. Non-autonomous mechanisms, likely involving the brain's anatomic or functional connectivity patterns, might also be responsible for selective vulnerability in HD. Leveraging a large dataset of 635 subjects from a multinational study, this paper tests various cell-autonomous and non-autonomous models that can explain HD topography. We test whether the expression patterns of implicated genes is sufficient to explain regional HD atrophy, or whether the network transmission of protein products is required to explain them. We find that network models are capable of predicting, to a high degree, observed atrophy in human subjects. Lastly, we propose a model of anterograde network transmission, and show that it is the most parsimonious yet most likely to explain observed atrophy patterns in HD. Collectively, these data indicate that pathology spread in HD may be mediated by the brain's intrinsic structural network organization. This is the first study to systematically and quantitatively test multiple hypotheses of pathology spread in living human subjects with HD.
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Affiliation(s)
- Ashish Raj
- Department of Radiology and Biomedical Imaging, University of California at San Francisco, USA; UCSF-UC Berkeley Graduate Program in BioEngineering, University of California at San Francisco, USA; Department of Radiology, Weill Cornell Medical College of Cornell University, 407 E. 61 Street, RR106, New York, NY 10065, USA.
| | - Fon Powell
- Department of Radiology, Weill Cornell Medical College of Cornell University, 407 E. 61 Street, RR106, New York, NY 10065, USA
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Tsvetanov KA, Gazzina S, Simon Jones P, van Swieten J, Borroni B, Sanchez-Valle R, Moreno F, LaforceJr R, Graff C, Synofzik M, Galimberti D, Masellis M, Tartaglia MC, Finger E, Vandenberghe R, de Mendonça A, Tagliavini F, Santana I, Ducharme S, Butler C, Gerhard A, Danek A, Levin J, Otto M, Frisoni G, Ghidoni R, Sorbi S, Rohrer JD, Rowe JB. Brain functional network integrity sustains cognitive function despite atrophy in presymptomatic genetic frontotemporal dementia. Alzheimers Dement 2021; 17:500-514. [PMID: 33215845 PMCID: PMC7611220 DOI: 10.1002/alz.12209] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2019] [Revised: 09/07/2020] [Accepted: 09/12/2020] [Indexed: 12/12/2022]
Abstract
INTRODUCTION The presymptomatic phase of neurodegenerative disease can last many years, with sustained cognitive function despite progressive atrophy. We investigate this phenomenon in familial frontotemporal dementia (FTD). METHODS We studied 121 presymptomatic FTD mutation carriers and 134 family members without mutations, using multivariate data-driven approach to link cognitive performance with both structural and functional magnetic resonance imaging. Atrophy and brain network connectivity were compared between groups, in relation to the time from expected symptom onset. RESULTS There were group differences in brain structure and function, in the absence of differences in cognitive performance. Specifically, we identified behaviorally relevant structural and functional network differences. Structure-function relationships were similar in both groups, but coupling between functional connectivity and cognition was stronger for carriers than for non-carriers, and increased with proximity to the expected onset of disease. DISCUSSION Our findings suggest that the maintenance of functional network connectivity enables carriers to maintain cognitive performance.
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Affiliation(s)
- Kamen A. Tsvetanov
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
- Cambridge Centre for Ageing and Neuroscience (Cam-CAN), University of Cambridge and MRC Cognition and Brain Sciences Unit, Cambridge, UK
| | - Stefano Gazzina
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
- Department of Neurology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - P. Simon Jones
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - John van Swieten
- Department of Neurology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Barbara Borroni
- Centre for Neurodegenerative Disorders, Neurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy
| | - Raquel Sanchez-Valle
- Alzheimer’s disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic, Institut d’Investigacións iomèdiques August Pi I Sunyer, University of Barcelona, Barcelona, Spain
| | - Fermin Moreno
- Cognitive Disorders Unit, Department of Neurology, Hospital Universitario Donostia, San Sebastian, Gipuzkoa, Spain
- Neuroscience Area, Biodonostia Health Research Insitute, San Sebastian, Gipuzkoa, Spain
| | - Robert LaforceJr
- Clinique Interdisciplinaire de Mémoire, Département des Sciences Neurologiques, CHU de Québec, and Faculté de Médecine, Université Laval, Québec, Canada
| | - Caroline Graff
- Karolinska Institutet, Department NVS, Center for Alzheimer Research, Division of Neurogenetics, Stockholm, Sweden
| | - Matthis Synofzik
- Department of Neurodegenerative Diseases, Hertie-Institute for Clinical Brain Research & Center of Neurology, University of Tübingen, Germany
- German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany
| | - Daniela Galimberti
- University of Milan, Centro Dino Ferrari, Milan, Italy
- Fondazione IRCSS Ca’ Granda, Ospedale Maggiore Policlinico, Neurodegenerative Diseases Unit, Milan, Italy
| | - Mario Masellis
- LC Campbell Cognitive Neurology Research Unit, Sunnybrook Research Institute, Toronto, Ontario, Canada
| | - Maria Carmela Tartaglia
- Toronto Western Hospital, Tanz Centre for Research in Neurodegenerative Disease, Toronto, Ontario, Canada
| | - Elizabeth Finger
- Department of Clinical Neurological Sciences, University of Western Ontario, London, ON, Canada
| | - Rik Vandenberghe
- Laboratory for Cognitive Neurology, Department of Neurosciences, KU Leuven, Leuven, Belgium
- Neurology Service, University Hospitals Leuven, Belgium, Laboratory for Neurobiology, VIB-KU
| | - Alexandre de Mendonça
- Laboratory of Neurosciences, Institute of Molecular Medicine, Faculty of Medicine, University of Lisbon, Lisbon, Portugal
| | - Fabrizio Tagliavini
- Fondazione Istituto di Ricovero e Cura a Carattere Scientifico Istituto Neurologico Carlo Besta, Milan, Ital
| | - Isabel Santana
- Neurology Department, Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal
- Faculty of Medicine, University of Coimbra, Coimbra, Portugal
- Centre of Neurosciences and Cell biology, Universidade de Coimbra, Coimbra, Portugal
| | - Simon Ducharme
- Department of Psychiatry, McGill University Health Centre, McGill University, Montreal, Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Canada
| | - Chris Butler
- Nuffield Department of Clinical Neurosciences, Medical Sciences Division, University of Oxford, Oxford, UK
| | - Alexander Gerhard
- Division of Neuroscience and Experimental Psychology, Wolfson Molecular Imaging Centre, University of Manchester, Manchester, UK
- Departments of Geriatric Medicine and Nuclear Medicine, University of Duisburg-Essen, Germany
| | - Adrian Danek
- Neurologische Klinik und Poliklinik, Ludwig-Maximilians-Universität, Munich, German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
| | - Johannes Levin
- Neurologische Klinik und Poliklinik, Ludwig-Maximilians-Universität, Munich, German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
| | - Markus Otto
- Department of Neurology, University Hospital Ulm, Ulm, Germany
| | - Giovanni Frisoni
- Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
- Memory Clinic and LANVIE-Laboratory of Neuroimaging of Aging, University Hospitals and University of Geneva, Geneva, Switzerland
| | - Roberta Ghidoni
- Molecular Markers Laboratory, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Sandro Sorbi
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy
- Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) “Don Gnocchi”, Florence, Italy
| | - Jonathan D. Rohrer
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK
| | - James B. Rowe
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
- Cambridge Centre for Ageing and Neuroscience (Cam-CAN), University of Cambridge and MRC Cognition and Brain Sciences Unit, Cambridge, UK
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Abstract
The biomarker networks measured by different modalities of data (e.g., structural magnetic resonance imaging (sMRI), diffusion tensor imaging (DTI)) may share the same true underlying biological model. In this work, we propose a node-wise biomarker graphical model to leverage the shared mechanism between multi-modality data to provide a more reliable estimation of the target modality network and account for the heterogeneity in networks due to differences between subjects and networks of external modality. Latent variables are introduced to represent the shared unobserved biological network and the information from the external modality is incorporated to model the distribution of the underlying biological network. We propose an efficient approximation to the posterior expectation of the latent variables that reduces computational cost by at least 50%. The performance of the proposed method is demonstrated by extensive simulation studies and an application to construct gray matter brain atrophy network of Huntington's disease by using sMRI data and DTI data. The identified network connections are more consistent with clinical literature and better improve prediction in follow-up clinical outcomes and separate subjects into clinically meaningful subgroups with different prognosis than alternative methods.
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Affiliation(s)
- Shanghong Xie
- Department of Biostatistics, Mailman School of Public Health, Columbia University
| | - Donglin Zeng
- Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina at Chapel Hill
| | - Yuanjia Wang
- Department of Biostatistics, Mailman School of Public Health, Columbia University
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30
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Langley C, Gregory S, Osborne-Crowley K, O'Callaghan C, Zeun P, Lowe J, Johnson EB, Papoutsi M, Scahill RI, Rees G, Tabrizi SJ, Robbins TW, Sahakian BJ. Fronto-striatal circuits for cognitive flexibility in far from onset Huntington's disease: evidence from the Young Adult Study. J Neurol Neurosurg Psychiatry 2021; 92:143-149. [PMID: 33130575 PMCID: PMC7841479 DOI: 10.1136/jnnp-2020-324104] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/05/2020] [Revised: 08/11/2020] [Accepted: 09/22/2020] [Indexed: 11/08/2022]
Abstract
OBJECTIVES Cognitive flexibility, which is key for adaptive decision-making, engages prefrontal cortex (PFC)-striatal circuitry and is impaired in both manifest and premanifest Huntington's disease (pre-HD). The aim of this study was to examine cognitive flexibility in a far from onset pre-HD cohort to determine whether an early impairment exists and if so, whether fronto-striatal circuits were associated with this deficit. METHODS In the present study, we examined performance of 51 pre-HD participants (mean age=29.22 (SD=5.71) years) from the HD Young Adult Study cohort and 53 controls matched for age, sex and IQ, on the Cambridge Neuropsychological Test Automated Battery (CANTAB) Intra-Extra Dimensional Set-Shift (IED) task. This cohort is unique as it is the furthest from disease onset comprehensively studied to date (mean years=23.89 (SD=5.96) years). The IED task measures visual discrimination learning, cognitive flexibility and specifically attentional set-shifting. We used resting-state functional MRI to examine whether the functional connectivity between specific fronto-striatal circuits was dysfunctional in pre-HD, compared with controls, and whether these circuits were associated with performance on the critical extradimensional shift stage. RESULTS Our results demonstrated that the CANTAB IED task detects a mild early impairment in cognitive flexibility in a pre-HD group far from onset. Attentional set-shifting was significantly related to functional connectivity between the ventrolateral PFC and ventral striatum in healthy controls and to functional connectivity between the dorsolateral PFC and caudate in pre-HD participants. CONCLUSION We postulate that this incipient impairment of cognitive flexibility may be associated with intrinsically abnormal functional connectivity of fronto-striatal circuitry in pre-HD.
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Affiliation(s)
| | - Sarah Gregory
- Huntington's Disease Centre, Department of Neurodegenerative disease, Institute of Neurology, University College London, London, UK
| | - Katie Osborne-Crowley
- Huntington's Disease Centre, Department of Neurodegenerative disease, Institute of Neurology, University College London, London, UK
- Division of Equity, Diversity and Inclusion, University of New South Wales, Sydney, New South Wales, Australia
| | - Claire O'Callaghan
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Brain and Mind Centre, Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia
| | - Paul Zeun
- Huntington's Disease Centre, Department of Neurodegenerative disease, Institute of Neurology, University College London, London, UK
| | - Jessica Lowe
- Huntington's Disease Centre, Department of Neurodegenerative disease, Institute of Neurology, University College London, London, UK
| | - Eileanoir B Johnson
- Huntington's Disease Centre, Department of Neurodegenerative disease, Institute of Neurology, University College London, London, UK
| | - Marina Papoutsi
- Huntington's Disease Centre, Department of Neurodegenerative disease, Institute of Neurology, University College London, London, UK
| | - Rachael I Scahill
- Huntington's Disease Centre, Department of Neurodegenerative disease, Institute of Neurology, University College London, London, UK
| | - Geraint Rees
- University College London Institute of Cognitive Neuroscience, UCL, London, UK
| | - Sarah J Tabrizi
- Huntington's Disease Centre, Department of Neurodegenerative disease, Institute of Neurology, University College London, London, UK
| | - Trevor W Robbins
- Department of Psychology and Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge, UK
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Donaldson J, Powell S, Rickards N, Holmans P, Jones L. What is the Pathogenic CAG Expansion Length in Huntington's Disease? J Huntingtons Dis 2021; 10:175-202. [PMID: 33579866 PMCID: PMC7990448 DOI: 10.3233/jhd-200445] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Huntington's disease (HD) (OMIM 143100) is caused by an expanded CAG repeat tract in the HTT gene. The inherited CAG length is known to expand further in somatic and germline cells in HD subjects. Age at onset of the disease is inversely correlated with the inherited CAG length, but is further modulated by a series of genetic modifiers which are most likely to act on the CAG repeat in HTT that permit it to further expand. Longer repeats are more prone to expansions, and this expansion is age dependent and tissue-specific. Given that the inherited tract expands through life and most subjects develop disease in mid-life, this implies that in cells that degenerate, the CAG length is likely to be longer than the inherited length. These findings suggest two thresholds- the inherited CAG length which permits further expansion, and the intracellular pathogenic threshold, above which cells become dysfunctional and die. This two-step mechanism has been previously proposed and modelled mathematically to give an intracellular pathogenic threshold at a tract length of 115 CAG (95% confidence intervals 70- 165 CAG). Empirically, the intracellular pathogenic threshold is difficult to determine. Clues from studies of people and models of HD, and from other diseases caused by expanded repeat tracts, place this threshold between 60- 100 CAG, most likely towards the upper part of that range. We assess this evidence and discuss how the intracellular pathogenic threshold in manifest disease might be better determined. Knowing the cellular pathogenic threshold would be informative for both understanding the mechanism in HD and deploying treatments.
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Affiliation(s)
- Jasmine Donaldson
- MRC Centre for Neuropsychiatric Genetics and Genomics, School of Medicine, Cardiff University, Cardiff, UK
| | - Sophie Powell
- MRC Centre for Neuropsychiatric Genetics and Genomics, School of Medicine, Cardiff University, Cardiff, UK
| | - Nadia Rickards
- MRC Centre for Neuropsychiatric Genetics and Genomics, School of Medicine, Cardiff University, Cardiff, UK
| | - Peter Holmans
- MRC Centre for Neuropsychiatric Genetics and Genomics, School of Medicine, Cardiff University, Cardiff, UK
| | - Lesley Jones
- MRC Centre for Neuropsychiatric Genetics and Genomics, School of Medicine, Cardiff University, Cardiff, UK
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Sampedro F, Stantonyonge N, Martínez-Horta S, Nan N, Camacho V, Chico A. Increased cerebral FDG-PET uptake in type 1 diabetes patients with impaired awareness of hypoglycaemia. J Neuroendocrinol 2021; 33:e12910. [PMID: 33176042 DOI: 10.1111/jne.12910] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/28/2020] [Revised: 09/29/2020] [Accepted: 09/29/2020] [Indexed: 11/26/2022]
Abstract
Approximately 20% of type 1 diabetes (T1D) patients have an impaired awareness of hypoglyceamia (IAH). IAH represents a risk factor for severe and recurrent hypoglycaemic events, which can lead to brain damage. Because no effective treatments are currently available to prevent IAH in this population, characterising the set of brain alterations associated with IAH may reveal novel preclinical diagnostic or therapeutic strategies. Using state-of-the art neuroimaging techniques, we compared 18 F-fluorodeoxyglucose-positron emission tomography (FDG-PET) uptake at rest between 10 T1D patients with IAH and nine patients with normal awareness of hypoglycaemia (NAH). T1D-IAH patients showed a pattern of increased FDG-PET uptake with respect to NAH patients (P < .05 corrected). Topographically, glucose metabolism was increased in the frontal and precuneus regions. Importantly, within the IAH group, this abnormal hypermetabolism correlated with IAH severity. This hypermetabolic state appeared to be unrelated to compensatory mechanisms as a result of reduced grey matter density or a neuroinflammatory state. We observed an abnormal increase in FDG-uptake in T1D patients with IAH in brain regions strongly related to cognition. Because this hypermetabolic state correlated with IAH severity, its biological characterisation could reveal new preventive or therapeutic strategies. A possible mechanism could be that glucose transport is increased in hypoglycaemia unawareness to compensate for recurrent hypoglycaemia, although this need to be confirmed in further research.
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Affiliation(s)
- Frederic Sampedro
- Institut d'Investigacions Biomèdiques- Sant Pau (IIB-Sant Pau), Barcelona, Spain
- Centro de Investigación en Red-Enfermedades Neurodegenerativas (CIBERNED), Madrid, Spain
- Neurology Department, Movement Disorders Unit, Santa Creu i Sant Pau Hospital, Barcelona, Spain
| | - Nicole Stantonyonge
- Department of Endocrinology and Nutrition, Santa Creu i Sant Pau Hospital, Barcelona, Spain
- Department of Medicine, Universitat Autònoma de Barcelona (U.A.B.), Barcelona, Spain
| | - Saul Martínez-Horta
- Institut d'Investigacions Biomèdiques- Sant Pau (IIB-Sant Pau), Barcelona, Spain
- Centro de Investigación en Red-Enfermedades Neurodegenerativas (CIBERNED), Madrid, Spain
- Neurology Department, Movement Disorders Unit, Santa Creu i Sant Pau Hospital, Barcelona, Spain
| | - Nicoleta Nan
- Department of Biochemistry, Santa Creu i Sant Pau Hospital, Barcelona, Spain
| | - Valle Camacho
- Department of Nuclear Medicine, Santa Creu i Sant Pau Hospital, Barcelona, Spain
| | - Ana Chico
- Department of Endocrinology and Nutrition, Santa Creu i Sant Pau Hospital, Barcelona, Spain
- Department of Medicine, Universitat Autònoma de Barcelona (U.A.B.), Barcelona, Spain
- CIBER Bioengineering, Biomaterials and Nanotechnology (CIBER-BBN), Instituto de Salud Carlos III, Madrid, Spain
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Pini L, Youssov K, Sambataro F, Bachoud‐Levi A, Vallesi A, Jacquemot C. Striatal connectivity in pre‐manifest Huntington’s disease is differentially affected by disease burden. Eur J Neurol 2020; 27:2147-2157. [DOI: 10.1111/ene.14423] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2020] [Accepted: 06/25/2020] [Indexed: 11/26/2022]
Affiliation(s)
- L. Pini
- Department of Neuroscience & Padova Neuroscience Center University of Padova Padova Italy
| | - K. Youssov
- Département d'Études Cognitives École Normale Supérieure PSL University ParisFrance
- Faculté de Santé Université Paris‐Est Créteil CréteilFrance
- Inserm U955 Equipe E01 NeuroPsychologie Interventionnelle Institut Mondor de Recherche Biomédicale CréteilFrance
- Centre de référence Maladie de Huntington Service de Neurologie Hôpital Henri Mondor, AP‐HP Créteil France
| | - F. Sambataro
- Department of Neuroscience & Padova Neuroscience Center University of Padova Padova Italy
| | - A.‐C. Bachoud‐Levi
- Département d'Études Cognitives École Normale Supérieure PSL University ParisFrance
- Faculté de Santé Université Paris‐Est Créteil CréteilFrance
- Inserm U955 Equipe E01 NeuroPsychologie Interventionnelle Institut Mondor de Recherche Biomédicale CréteilFrance
- Centre de référence Maladie de Huntington Service de Neurologie Hôpital Henri Mondor, AP‐HP Créteil France
| | - A. Vallesi
- Department of Neuroscience & Padova Neuroscience Center University of Padova Padova Italy
- Brain Imaging and Neural Dynamics Research Group IRCCS San Camillo Hospital Venice Italy
| | - C. Jacquemot
- Département d'Études Cognitives École Normale Supérieure PSL University ParisFrance
- Faculté de Santé Université Paris‐Est Créteil CréteilFrance
- Inserm U955 Equipe E01 NeuroPsychologie Interventionnelle Institut Mondor de Recherche Biomédicale CréteilFrance
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Gregory S, Lohse KR, Johnson EB, Leavitt BR, Durr A, Roos RAC, Rees G, Tabrizi SJ, Scahill RI, Orth M. Longitudinal Structural MRI in Neurologically Healthy Adults. J Magn Reson Imaging 2020; 52:1385-1399. [PMID: 32469154 PMCID: PMC8425332 DOI: 10.1002/jmri.27203] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2020] [Revised: 05/07/2020] [Accepted: 05/07/2020] [Indexed: 01/25/2023] Open
Abstract
BACKGROUND Structural brain MRI measures are frequently examined in both healthy and clinical groups, so an understanding of how these measures vary over time is desirable. PURPOSE To test the stability of structural brain MRI measures over time. POPULATION In all, 112 healthy volunteers across four sites. STUDY TYPE Retrospective analysis of prospectively acquired data. FIELD STRENGTH/SEQUENCE 3 T, magnetization prepared - rapid gradient echo, and single-shell diffusion sequence. ASSESSMENT Diffusion, cortical thickness, and volume data from the sensorimotor network were assessed for stability over time across 3 years. Two sites used a Siemens MRI scanner, two sites a Philips scanner. STATISTICAL TESTS The stability of structural measures across timepoints was assessed using intraclass correlation coefficients (ICC) for absolute agreement, cutoff ≥0.80, indicating high reliability. Mixed-factorial analysis of variance (ANOVA) was used to examine between-site and between-scanner type differences in individuals over time. RESULTS All cortical thickness and gray matter volume measures in the sensorimotor network, plus all diffusivity measures (fractional anisotropy plus mean, axial and radial diffusivities) for primary and premotor cortices, primary somatosensory thalamic connections, and the cortico-spinal tract met ICC. The majority of measures differed significantly between scanners, with a trend for sites using Siemens scanners to produce larger values for connectivity, cortical thickness, and volume measures than sites using Philips scanners. DATA CONCLUSION Levels of reliability over time for all tested structural MRI measures were generally high, indicating that any differences between measurements over time likely reflect underlying biological differences rather than inherent methodological variability. LEVEL OF EVIDENCE 4. TECHNICAL EFFICACY STAGE 1.
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Affiliation(s)
- Sarah Gregory
- Huntington's Disease Research Centre, Institute of Neurology, University College London, London, UK.,Wellcome Centre for Human Neuroimaging, Institute of Neurology, University College London, London, UK
| | - Keith R Lohse
- Department of Health, Kinesiology, and Recreation, University of Utah, Salt Lake City, Utah, USA.,Department of Physical Therapy and Athletic Training, University of Utah, Salt Lake City, Utah, USA
| | - Eileanoir B Johnson
- Huntington's Disease Research Centre, Institute of Neurology, University College London, London, UK
| | - Blair R Leavitt
- Centre for Molecular Medicine and Therapeutics, Department of Medical Genetics, University of British Columbia, Vancouver, British Columbia, Canada
| | - Alexandra Durr
- APHP Department of Genetics, Pitié-Salpêtrière University Hospital, and Institut du Cerveau et de la Moell épinière (ICM), Sorbonne Université, Paris, France
| | - Raymund A C Roos
- Department of Neurology, Leiden University Medical Centre, Leiden, The Netherlands
| | - Geraint Rees
- Wellcome Centre for Human Neuroimaging, Institute of Neurology, University College London, London, UK.,Institute of Cognitive Neuroscience, University College London, London, UK
| | - Sarah J Tabrizi
- Huntington's Disease Research Centre, Institute of Neurology, University College London, London, UK
| | - Rachael I Scahill
- Huntington's Disease Research Centre, Institute of Neurology, University College London, London, UK
| | - Michael Orth
- Department of Neurology, Ulm University Hospital, Ulm, Germany.,Neurozentrum Siloah, Bern, Switzerland
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Papoutsi M, Magerkurth J, Josephs O, Pépés SE, Ibitoye T, Reilmann R, Hunt N, Payne E, Weiskopf N, Langbehn D, Rees G, Tabrizi SJ. Activity or connectivity? A randomized controlled feasibility study evaluating neurofeedback training in Huntington's disease. Brain Commun 2020; 2:fcaa049. [PMID: 32954301 PMCID: PMC7425518 DOI: 10.1093/braincomms/fcaa049] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2019] [Revised: 02/11/2020] [Accepted: 03/27/2020] [Indexed: 12/20/2022] Open
Abstract
Non-invasive methods, such as neurofeedback training, could support cognitive symptom management in Huntington’s disease by targeting brain regions whose function is impaired. The aim of our single-blind, sham-controlled study was to collect rigorous evidence regarding the feasibility of neurofeedback training in Huntington’s disease by examining two different methods, activity and connectivity real-time functional MRI neurofeedback training. Thirty-two Huntington’s disease gene-carriers completed 16 runs of neurofeedback training, using an optimized real-time functional MRI protocol. Participants were randomized into four groups, two treatment groups, one receiving neurofeedback derived from the activity of the supplementary motor area, and another receiving neurofeedback based on the correlation of supplementary motor area and left striatum activity (connectivity neurofeedback training), and two sham control groups, matched to each of the treatment groups. We examined differences between the groups during neurofeedback training sessions and after training at follow-up sessions. Transfer of training was measured by measuring the participants’ ability to upregulate neurofeedback training target levels without feedback (near transfer), as well as by examining change in objective, a priori defined, behavioural measures of cognitive and psychomotor function (far transfer) before and at 2 months after training. We found that the treatment group had significantly higher neurofeedback training target levels during the training sessions compared to the control group. However, we did not find robust evidence of better transfer in the treatment group compared to controls, or a difference between the two neurofeedback training methods. We also did not find evidence in support of a relationship between change in cognitive and psychomotor function and learning success. We conclude that although there is evidence that neurofeedback training can be used to guide participants to regulate the activity and connectivity of specific regions in the brain, evidence regarding transfer of learning and clinical benefit was not robust.
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Affiliation(s)
- Marina Papoutsi
- UCL Huntington’s Disease Centre, Queen Square Institute of Neurology, University College London, London WC1B 5EH, UK
- Correspondence to: Marina Papoutsi, PhD UCL Huntington’s Disease Centre, Queen Square Institute of Neurology University College London, Russell Square House, 10–12 Russell Square London WC1B 5EH, UK E-mail:
| | - Joerg Magerkurth
- Birkbeck-UCL Centre for Neuroimaging, University College London, London WC1H 0AP, UK
| | - Oliver Josephs
- Wellcome Centre for Human Neuroimaging, Queen Square Institute of Neurology, University College London, London WC1N 3AR, UK
| | - Sophia E Pépés
- University of Oxford, Harris Manchester College, Oxford OX1 3TD, UK
| | - Temi Ibitoye
- UCL Huntington’s Disease Centre, Queen Square Institute of Neurology, University College London, London WC1B 5EH, UK
| | - Ralf Reilmann
- George Huntington Institute, 48149 Münster, Germany
- Department of Radiology, University of Muenster, 48149 Münster, Germany
- Section for Neurodegeneration and Hertie Institute for Clinical Brain Research, University of Tuebingen, 72076 Tübingen, Germany
| | - Nigel Hunt
- Eastman Dental Institute, University College London, London WC1X 8LD, UK
| | - Edwin Payne
- Eastman Dental Institute, University College London, London WC1X 8LD, UK
| | - Nikolaus Weiskopf
- Wellcome Centre for Human Neuroimaging, Queen Square Institute of Neurology, University College London, London WC1N 3AR, UK
- Max Planck Institute for Human Cognitive and Brain Sciences, D-04103 Leipzig, Germany
| | - Douglas Langbehn
- Carver College of Medicine, University of Iowa, Iowa City, IA 52242, USA
| | - Geraint Rees
- Wellcome Centre for Human Neuroimaging, Queen Square Institute of Neurology, University College London, London WC1N 3AR, UK
- Institute of Cognitive Neuroscience, University College London, London WC1N 3AZ, UK
| | - Sarah J Tabrizi
- UCL Huntington’s Disease Centre, Queen Square Institute of Neurology, University College London, London WC1B 5EH, UK
- UK Dementia Research Institute at University College London, London WC1E 6BT, UK
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36
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Soloveva MV, Jamadar SD, Hughes M, Velakoulis D, Poudel G, Georgiou-Karistianis N. Brain compensation during response inhibition in premanifest Huntington's disease. Brain Cogn 2020; 141:105560. [PMID: 32179366 DOI: 10.1016/j.bandc.2020.105560] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2019] [Revised: 02/26/2020] [Accepted: 02/28/2020] [Indexed: 01/21/2023]
Abstract
Premanifest Huntington's disease (pre-HD) individuals typically show increased task-related functional magnetic resonance imaging (fMRI), suggested to reflect compensatory strategies. Despite the evidence, no study has attempted to understand the compensatory process in light of 'formal' models of compensation. We used a quantitative model of compensation - the Compensation-Related Utilization of Neural Circuits Hypothesis (CRUNCH), to characterise compensation in pre-HD using fMRI. Pre-HD individuals (n = 15) and controls (n = 15) performed a modified stop-signal task that incremented in four levels of stop difficulty. Our results did not support the critical assumption of the CRUNCH model - controls did not show increased fMRI activity with increased level of stop difficulty; however, controls showed decreased fMRI activity with increased stop difficulty in right inferior frontal gyrus and right caudate nucleus. Relative to controls, pre-HD individuals showed increased fMRI activity in right inferior frontal gyrus and in right caudate nucleus at higher levels of stop difficulty, which is the opposite effect to that predicted by the model. Our findings suggest a compensatory process of the response inhibition network in pre-HD; however, the pattern of fMRI activity was not in the manner expected by CRUNCH.
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Affiliation(s)
- Maria V Soloveva
- School of Psychological Sciences and Turner Institute for Brain and Mental Health, Monash University, Clayton, Victoria 3800, Australia
| | - Sharna D Jamadar
- School of Psychological Sciences and Turner Institute for Brain and Mental Health, Monash University, Clayton, Victoria 3800, Australia; Monash Biomedical Imaging, 770 Blackburn Road, Clayton, Victoria 3800, Australia; Australian Research Council Centre of Excellence for Integrative Brain Function, Clayton, Victoria 3800, Australia
| | - Matthew Hughes
- School of Health Sciences, Brain and Psychological Sciences Centre, Swinburne University, Hawthorn, Victoria 3122, Australia
| | - Dennis Velakoulis
- Department of Psychiatry, Melbourne Neuropsychiatry Center, University of Melbourne, Parkville, Victoria 3010, Australia
| | - Govinda Poudel
- School of Psychological Sciences and Turner Institute for Brain and Mental Health, Monash University, Clayton, Victoria 3800, Australia; Mary MacKillop Institute for Health Research, Australian Catholic University, Melbourne, Victoria 3000, Australia
| | - Nellie Georgiou-Karistianis
- School of Psychological Sciences and Turner Institute for Brain and Mental Health, Monash University, Clayton, Victoria 3800, Australia.
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37
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Trinkler I, Chéhère P, Salgues J, Monin ML, Tezenas du Montcel S, Khani S, Gargiulo M, Durr A. Contemporary Dance Practice Improves Motor Function and Body Representation in Huntington's Disease: A Pilot Study. J Huntingtons Dis 2020; 8:97-110. [PMID: 30776016 DOI: 10.3233/jhd-180315] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Physical exercise improves neurological conditions, but adherence is hard to establish. Dance might be a promising alternative; however, since patients with Huntington's disease (HD) suffer from rhythmic movement execution deficits, any metric dance practice must be avoided. OBJECTIVE Here we asked, if contemporary dance, a lyrical dance form, practiced for two hours per week over five months, might improve motor function, neuropsychiatric variables, cognition and brain volume of HD patients. METHODS Nineteen patients aged between 43 and 78 years with mild to moderate HD (TFC range 7-13, UHDRS motor score range 3-58) participated in this randomized, controlled pilot study (NCT 01842919). The primary outcome measure was total motor score. Secondary outcome measures were differences in brain structure, cognitive function, neuropsychiatric variables, apathy and quality of life. A semi-structured interview assessed participants' experiences. RESULTS Adherence to dance classes was very good. All participants completed 5 months of dance practice. Motor impairment (median [IQR] decreased from 28[6-51] to 27[7-33] for the dance group compared to an increase of 19[13-35] - 25[14-42] for usual care, Z = -2.44, p = 0.015). No other behavioral measures showed any changes.Brain volume increased in the medial superior parietal and paracentral lobule, in line with compensatory structural brain changes in areas supporting spatial and somatosensory processing. These changes were also reflected in patients' reports that contemporary dance altered the way they "felt and lived in their bodies". CONCLUSIONS Contemporary dance practice, through work on spatial and bodily representations, helps improve motor function in HD patients.
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Affiliation(s)
- Iris Trinkler
- Brain and Spine Institute (ICM), Sorbonne Université, Pitié-Salpêtrière University Hospital, Paris, France.,Current affiliation: Department of Sport Sciences, Adapted Physical Activity and Health Unit, University of Strasbourg, 14 Rue René Descartes, 67084 Strasbourg Cedex, France
| | | | | | - Marie-Lorraine Monin
- Brain and Spine Institute (ICM), Sorbonne Université, Pitié-Salpêtrière University Hospital, Paris, France.,AP-HP, Department of Genetics, Pitié-Salpêtrière University Hospital, Paris, France
| | - Sophie Tezenas du Montcel
- AP-HP, Department of Biostatistics and Medical Informatics, Pitié-Salpêtrière University Hospital, Paris, France.,Sorbonne University, Pierre Louis Institute of Epidemiology and Public Health, Paris, France
| | - Sonia Khani
- Brain and Spine Institute (ICM), Sorbonne Université, Pitié-Salpêtrière University Hospital, Paris, France
| | - Marcela Gargiulo
- AP-HP, Department of Genetics, Pitié-Salpêtrière University Hospital, Paris, France.,Laboratory of Clinical Psychology, Psychopathology and Psychoanalysis PCPP, EA 4056, University Paris Descartes, Sorbonne Paris City, Psychology Institute, Boulogne-Billancourt, France.,Institute of Myology, Pitié-Salpêtrière University Hospital, Paris, France
| | - Alexandra Durr
- Brain and Spine Institute (ICM), Sorbonne Université, Pitié-Salpêtrière University Hospital, Paris, France.,AP-HP, Department of Genetics, Pitié-Salpêtrière University Hospital, Paris, France
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38
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Polosecki P, Castro E, Rish I, Pustina D, Warner JH, Wood A, Sampaio C, Cecchi GA. Resting-state connectivity stratifies premanifest Huntington's disease by longitudinal cognitive decline rate. Sci Rep 2020; 10:1252. [PMID: 31988371 PMCID: PMC6985137 DOI: 10.1038/s41598-020-58074-8] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2019] [Accepted: 01/10/2020] [Indexed: 11/17/2022] Open
Abstract
Patient stratification is critical for the sensitivity of clinical trials at early stages of neurodegenerative disorders. In Huntington’s disease (HD), genetic tests make cognitive, motor and brain imaging measurements possible before symptom manifestation (pre-HD). We evaluated pre-HD stratification models based on single visit resting-state functional MRI (rs-fMRI) data that assess observed longitudinal motor and cognitive change rates from the multisite Track-On HD cohort (74 pre-HD, 79 control participants). We computed longitudinal performance change on 10 tasks (including visits from the preceding TRACK-HD study when available), as well as functional connectivity density (FCD) maps in single rs-fMRI visits, which showed high test-retest reliability. We assigned pre-HD subjects to subgroups of fast, intermediate, and slow change along single tasks or combinations of them, correcting for expectations based on aging; and trained FCD-based classifiers to distinguish fast- from slow-progressing individuals. For robustness, models were validated across imaging sites. Stratification models distinguished fast- from slow-changing participants and provided continuous assessments of decline applicable to the whole pre-HD population, relying on previously-neglected white matter functional signals. These results suggest novel correlates of early deterioration and a robust stratification strategy where a single MRI measurement provides an estimate of multiple ongoing longitudinal changes.
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Affiliation(s)
- Pablo Polosecki
- IBM T.J. Watson Research Center, Yorktown Heights, Yorktown, NY, USA.
| | - Eduardo Castro
- IBM T.J. Watson Research Center, Yorktown Heights, Yorktown, NY, USA
| | - Irina Rish
- IBM T.J. Watson Research Center, Yorktown Heights, Yorktown, NY, USA
| | | | | | - Andrew Wood
- CHDI Management/CHDI Foundation, Princeton, NJ, USA
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39
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Gregory S, Johnson E, Byrne LM, Rodrigues FB, Henderson A, Moss J, Thomas D, Zhang H, De Vita E, Tabrizi SJ, Rees G, Scahill RI, Wild EJ. Characterizing White Matter in Huntington's Disease. Mov Disord Clin Pract 2020; 7:52-60. [PMID: 31970212 PMCID: PMC6962665 DOI: 10.1002/mdc3.12866] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2019] [Revised: 09/27/2019] [Accepted: 10/28/2019] [Indexed: 01/10/2023] Open
Abstract
BACKGROUND Investigating early white matter (WM) change in Huntington's disease (HD) can improve our understanding of the way in which disease spreads from the striatum. OBJECTIVES We provide a detailed characterization of pathology-related WM change in HD. We first examined WM microstructure using diffusion-weighted imaging and then investigated both underlying biological properties of WM and products of WM damage including iron, myelin plus neurofilament light, a biofluid marker of axonal degeneration-in parallel with the mutant huntingtin protein. METHODS We examined WM change in HD gene carriers from the HD-CSFcohort, baseline visit. We used standard-diffusion magnetic resonance imaging to measure metrics including fractional anisotropy, a marker of WM integrity, and diffusivity; a novel diffusion model (neurite orientation dispersion and density imaging) to measure axonal density and organization; T1-weighted and T2-weighted structural magnetic resonance imaging images to derive proxy iron content and myelin-contrast measures; and biofluid concentrations of neurofilament light (in cerebrospinal fluid (CSF) and plasma) and mutant huntingtin protein (in CSF). RESULTS HD gene carriers displayed reduced fractional anisotropy and increased diffusivity when compared with controls, both of which were also associated with disease progression, CSF, and mutant huntingtin protein levels. HD gene carriers also displayed proxy measures of reduced myelin contrast and iron in the striatum. CONCLUSION Collectively, these findings present a more complete characterization of HD-related microstructural brain changes. The correlation between reduced fractional anisotropy, increased axonal orientation, and biofluid markers suggest that axonal breakdown is associated with increased WM degeneration, whereas higher quantitative T2 signal and lower myelin-contrast may indicate a process of demyelination limited to the striatum.
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Affiliation(s)
- Sarah Gregory
- University College London Huntington's Disease Centre, Department of Neurodegenerative DiseaseUniversity College London Queen Square Institute of Neurology, University College LondonLondonUnited Kingdom
| | - Eileanoir Johnson
- University College London Huntington's Disease Centre, Department of Neurodegenerative DiseaseUniversity College London Queen Square Institute of Neurology, University College LondonLondonUnited Kingdom
| | - Lauren M. Byrne
- University College London Huntington's Disease Centre, Department of Neurodegenerative DiseaseUniversity College London Queen Square Institute of Neurology, University College LondonLondonUnited Kingdom
| | - Filipe B. Rodrigues
- University College London Huntington's Disease Centre, Department of Neurodegenerative DiseaseUniversity College London Queen Square Institute of Neurology, University College LondonLondonUnited Kingdom
| | - Alexandra Henderson
- University College London Huntington's Disease Centre, Department of Neurodegenerative DiseaseUniversity College London Queen Square Institute of Neurology, University College LondonLondonUnited Kingdom
| | - John Moss
- University College London Huntington's Disease Centre, Department of Neurodegenerative DiseaseUniversity College London Queen Square Institute of Neurology, University College LondonLondonUnited Kingdom
| | - David Thomas
- Department of Brain Repair and Rehabilitation, University College London Queen Square Institute of NeurologyUniversity College LondonUnited Kingdom
- Leonard Wolfson Experimental Neurology Centre, University College London Queen Square Institute of NeurologyUniversity College LondonUnited Kingdom
| | - Hui Zhang
- Department of Computer Science and Centre for Medical Image ComputingUniversity College LondonLondonUnited Kingdom
| | - Enrico De Vita
- Lysholm Department of NeuroradiologyNational Hospital for Neurology and NeurosurgeryLondonUnited Kingdom
- Department of Biomedical Engineering, School of Biomedical Engineering and Imaging SciencesKing's College LondonLondonUnited Kingdom
| | - Sarah J. Tabrizi
- University College London Huntington's Disease Centre, Department of Neurodegenerative DiseaseUniversity College London Queen Square Institute of Neurology, University College LondonLondonUnited Kingdom
| | - Geraint Rees
- Wellcome Trust Centre for Neuroimaging, Institute of NeurologyUniversity College LondonLondonUnited Kingdom
| | - Rachael I. Scahill
- University College London Huntington's Disease Centre, Department of Neurodegenerative DiseaseUniversity College London Queen Square Institute of Neurology, University College LondonLondonUnited Kingdom
| | - Edward J. Wild
- University College London Huntington's Disease Centre, Department of Neurodegenerative DiseaseUniversity College London Queen Square Institute of Neurology, University College LondonLondonUnited Kingdom
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40
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Soloveva MV, Jamadar SD, Velakoulis D, Poudel G, Georgiou-Karistianis N. Brain compensation during visuospatial working memory in premanifest Huntington's disease. Neuropsychologia 2020; 136:107262. [DOI: 10.1016/j.neuropsychologia.2019.107262] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2018] [Revised: 11/04/2019] [Accepted: 11/11/2019] [Indexed: 01/21/2023]
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41
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Gregory S, Odish OFF, Mayer I, Mills J, Johnson EB, Scahill RI, Rothwell J, Rees G, Long JD, Tabrizi SJ, Roos RAC, Orth M. Multimodal characterization of the visual network in Huntington's disease gene carriers. Clin Neurophysiol 2019; 130:2053-2059. [PMID: 31541982 DOI: 10.1016/j.clinph.2019.08.018] [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: 06/11/2019] [Revised: 07/25/2019] [Accepted: 08/12/2019] [Indexed: 11/24/2022]
Abstract
OBJECTIVE A sensorimotor network structural phenotype predicted motor task performance in a previous study in Huntington's disease (HD) gene carriers. We investigated in the visual network whether structure - function - behaviour relationship patterns, and the effects of the HD mutation, extended beyond the sensorimotor network. METHODS We used multimodal visual network MRI structural measures (cortical thickness and white matter connectivity), plus visual evoked potentials and task performance (Map Search; Symbol Digit Modalities Test) in healthy controls and HD gene carriers. RESULTS Using principal component (PC) analysis, we identified a structure - function relationship common to both groups. PC scores differed between groups indicating white matter disorganization (higher RD, lower FA) and slower, and more disperse, VEP signal transmission (higher VEP P100 latency and lower VEP P100 amplitude) in HD than controls while task performance was similar. CONCLUSIONS HD may be associated with reduced white matter organization and efficient visual network function but normal task performance. SIGNIFICANCE These findings indicate that structure - function relationships in the visual network, and the effects of the HD mutation, share some commonalities with those in the sensorimotor network. However, implications for task performance differ between the two networks suggesting the influence of network specific factors.
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Affiliation(s)
- Sarah Gregory
- Huntington's Disease Centre, UCL Institute of Neurology, London, UK
| | - Omar F F Odish
- Department of Neurology, University Medical Center Groningen, Groningen, the Netherlands
| | - Isabella Mayer
- Department of Neurology, Ulm University Hospital, Ulm, Germany
| | - James Mills
- Department of Psychiatry, University of Iowa, Iowa City, IA, USA
| | | | | | - John Rothwell
- Sobell Department of Motor Neuroscience and Movement Disorders, University College London Institute of Neurology, Queen Square, London, UK
| | - Geraint Rees
- Wellcome Trust Centre for Neuroimaging, University College London, London, UK
| | - Jeffrey D Long
- Department of Psychiatry, University of Iowa, Iowa City, IA, USA; Department of Biostatistics, University of Iowa, Iowa City, IA, USA
| | - Sarah J Tabrizi
- Huntington's Disease Centre, UCL Institute of Neurology, London, UK
| | - Raymund A C Roos
- Department of Neurology, Leiden University Medical Centre, Leiden, the Netherlands
| | - Michael Orth
- Department of Neurology, Ulm University Hospital, Ulm, Germany.
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42
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Langbehn DR, Stout JC, Gregory S, Mills JA, Durr A, Leavitt BR, Roos RAC, Long JD, Owen G, Johnson HJ, Borowsky B, Craufurd D, Reilmann R, Landwehrmeyer GB, Scahill RI, Tabrizi SJ. Association of CAG Repeats With Long-term Progression in Huntington Disease. JAMA Neurol 2019; 76:1375-1385. [PMID: 31403680 PMCID: PMC6692683 DOI: 10.1001/jamaneurol.2019.2368] [Citation(s) in RCA: 38] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2019] [Accepted: 05/02/2019] [Indexed: 11/14/2022]
Abstract
IMPORTANCE In Huntington disease (HD), mutation severity is defined by the length of the CAG trinucleotide sequence, a well-known predictor of clinical onset age. The association with disease trajectory is less well characterized. Quantifiable summary measures of trajectory applicable over decades of early disease progression are lacking. An accurate model of the age-CAG association with early progression is critical to clinical trial design, informing both sample size and intervention timing. OBJECTIVE To succinctly capture the decades-long early progression of HD and its dependence on CAG repeat length. DESIGN, SETTING, AND PARTICIPANTS Prospective study at 4 academic HD treatment and research centers. Participants were the combined sample from the TRACK-HD and Track-On HD studies consisting of 290 gene carriers (presymptomatic to stage II), recruited from research registries at participating centers, and 153 nonbiologically related controls, generally spouses or friends. Recruitment was targeted to match a balanced, prespecified spectrum of age, CAG repeat length, and diagnostic status. In the TRACK-HD and Track-On HD studies, 13 and 5 potential participants, respectively, failed study screening. Follow-up ranged from 0 to 6 years. The study dates were January 2008 to November 2014. These analyses were performed between December 2015 and January 2019. MAIN OUTCOMES AND MEASURES The outcome measures were principal component summary scores of motor-cognitive function and of brain volumes. The main outcome was the association of these scores with age and CAG repeat length. RESULTS We analyzed 2065 visits from 443 participants (247 female [55.8%]; mean [SD] age, 44.4 [10.3] years). Motor-cognitive measures were highly correlated and had similar CAG repeat length-dependent associations with age. A composite summary score accounted for 67.6% of their combined variance. This score was well approximated by a score combining 3 items (total motor score, Symbol Digit Modalities Test, and Stroop word reading) from the Unified Huntington's Disease Rating Scale. For either score, initial progression age and then acceleration rate were highly CAG repeat length dependent. The acceleration continues through at least stage II disease. In contrast, 3 distinct patterns emerged among brain measures (basal ganglia, gray matter, and a combination of whole-brain, ventricular, and white matter volumes). The basal ganglia pattern showed considerable change in even the youngest participants but demonstrated minimal acceleration of loss with aging. Each clinical and brain summary score was strongly associated with the onset and rate of decline in total functional capacity. CONCLUSIONS AND RELEVANCE Results of this study suggest that succinct summary measures of function and brain loss characterize HD progression across a wide disease span. CAG repeat length strongly predicts their decline rate. This work aids our understanding of the age and CAG repeat length-dependent association between changes in the brain and clinical manifestations of HD.
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Affiliation(s)
| | - Julie C. Stout
- School of Psychology and Psychiatry, Monash University, Melbourne, Victoria, Australia
| | - Sarah Gregory
- Huntington’s Disease Centre, UCL Institute of Neurology, University College London, Queen Square, London, United Kingdom
| | | | - Alexandra Durr
- Institut du Cerveau et de la Moelle Epinière (ICM), Genetic Department, Assistance Publique–Hôpitaux de Paris, Sorbonne Université, Institut National de la Santé et de la Recherche Médicale Unité 1127, Le Centre National de la Recherche Scientifique, Unités Mixtes de Recherche 7225, Pitié-Salpêtrière University Hospital, Paris, France
| | - Blair R. Leavitt
- Centre for Molecular Medicine and Therapeutics, Department of Medical Genetics, University of British Columbia, Vancouver, British Columbia, Canada
| | - Raymund A. C. Roos
- Department of Neurology, Leiden University Medical Centre, Leiden, the Netherlands
| | | | - Gail Owen
- Huntington’s Disease Centre, UCL Institute of Neurology, University College London, Queen Square, London, United Kingdom
| | - Hans J. Johnson
- Department of Electrical and Computer Engineering, University of Iowa, Iowa City
| | | | - David Craufurd
- Manchester Academic Health Sciences Centre, Central Manchester University Hospitals National Health Service Foundation Trust, University of Manchester, Manchester, United Kingdom
| | - Ralf Reilmann
- George-Huntington-Institute, Department of Radiology, University of Münster, Münster, Germany
- Hertie-Institute for Clinical Brain Research, Department of Neurodegenerative Diseases, University of Tübingen, Tübingen, Germany
| | | | - Rachael I. Scahill
- Huntington’s Disease Centre, UCL Institute of Neurology, University College London, Queen Square, London, United Kingdom
| | - Sarah J. Tabrizi
- Huntington’s Disease Centre, UCL Institute of Neurology, University College London, Queen Square, London, United Kingdom
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43
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Pini L, Jacquemot C, Cagnin A, Meneghello F, Semenza C, Mantini D, Vallesi A. Aberrant brain network connectivity in presymptomatic and manifest Huntington's disease: A systematic review. Hum Brain Mapp 2019; 41:256-269. [PMID: 31532053 PMCID: PMC7268025 DOI: 10.1002/hbm.24790] [Citation(s) in RCA: 37] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2019] [Revised: 07/29/2019] [Accepted: 08/26/2019] [Indexed: 12/12/2022] Open
Abstract
Resting‐state functional magnetic resonance imaging (rs‐fMRI) has the potential to shed light on the pathophysiological mechanisms of Huntington's disease (HD), paving the way to new therapeutic interventions. A systematic literature review was conducted in three online databases according to PRISMA guidelines, using keywords for HD, functional connectivity, and rs‐fMRI. We included studies investigating connectivity in presymptomatic (pre‐HD) and manifest HD gene carriers compared to healthy controls, implementing seed‐based connectivity, independent component analysis, regional property, and graph analysis approaches. Visual network showed reduced connectivity in manifest HD, while network/areas underpinning motor functions were consistently altered in both manifest HD and pre‐HD, showing disease stage‐dependent changes. Cognitive networks underlying executive and attentional functions showed divergent anterior–posterior alterations, possibly reflecting compensatory mechanisms. The involvement of these networks in pre‐HD is still unclear. In conclusion, aberrant connectivity of the sensory‐motor network is observed in the early stage of HD while, as pathology spreads, other networks might be affected, such as the visual and executive/attentional networks. Moreover, sensory‐motor and executive networks exhibit hyper‐ and hypo‐connectivity patterns following different spatiotemporal trajectories. These findings could potentially help to implement future huntingtin‐lowering interventions.
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Affiliation(s)
- Lorenzo Pini
- Department of Neuroscience & Padova Neuroscience Center, University of Padova, Padova, Italy
| | - Charlotte Jacquemot
- Département d'Etudes Cognitives, Ecole Normale Supérieure-PSL University, Paris, France.,Laboratoire de NeuroPsychologie Interventionnelle, Institut Mondor de Recherche Biomédicale, Institut National de la Santé et Recherche Médical (INSERM) U955, Equipe 01, Créteil, France.,Faculté de Médecine, Université Paris Est Créteil, Créteil, France
| | - Annachiara Cagnin
- Department of Neuroscience & Padova Neuroscience Center, University of Padova, Padova, Italy
| | - Francesca Meneghello
- Cognitive Neuroscience Research Group, IRCCS San Camillo Hospital, Venice, Italy
| | - Carlo Semenza
- Department of Neuroscience & Padova Neuroscience Center, University of Padova, Padova, Italy.,Cognitive Neuroscience Research Group, IRCCS San Camillo Hospital, Venice, Italy
| | - Dante Mantini
- Research Center for Motor Control and Neuroplasticity, KU Leuven, Leuven, Belgium.,Brain Imaging and Neural Dynamics Research Group, IRCCS San Camillo Hospital, Venice, Italy
| | - Antonino Vallesi
- Department of Neuroscience & Padova Neuroscience Center, University of Padova, Padova, Italy.,Brain Imaging and Neural Dynamics Research Group, IRCCS San Camillo Hospital, Venice, Italy
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44
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Johnson EB, Gregory S. Huntington's disease: Brain imaging in Huntington's disease. PROGRESS IN MOLECULAR BIOLOGY AND TRANSLATIONAL SCIENCE 2019; 165:321-369. [PMID: 31481169 DOI: 10.1016/bs.pmbts.2019.04.004] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Huntington's disease (HD) gene-carriers show prominent neuronal loss by end-stage disease, and the use of magnetic resonance imaging (MRI) has been increasingly used to quantify brain changes during earlier stages of the disease. MRI offers an in vivo method of measuring structural and functional brain change. The images collected via MRI are processed to measure different anatomical features, such as brain volume, macro- and microstructural changes within white matter and functional brain activity. Structural imaging has demonstrated significant volume loss across multiple white and gray matter regions in HD, particularly within subcortical structures. There also appears to be increasing disorganization of white matter tracts and between-region connectivity with increasing disease progression. Finally, functional changes are thought to represent changes in brain activity underlying compensatory mechanisms in HD. This chapter will provide an overview of the principles of MRI and practicalities associated with using MRI in HD studies, and summarize findings from MRI studies investigating brain structure and function in HD.
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Affiliation(s)
- Eileanoir B Johnson
- Huntington's Disease Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Sarah Gregory
- Huntington's Disease Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom.
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45
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Tuorto F, Parlato R. rRNA and tRNA Bridges to Neuronal Homeostasis in Health and Disease. J Mol Biol 2019; 431:1763-1779. [PMID: 30876917 DOI: 10.1016/j.jmb.2019.03.004] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2018] [Revised: 02/25/2019] [Accepted: 03/06/2019] [Indexed: 12/11/2022]
Abstract
Dysregulation of protein translation is emerging as a unifying mechanism in the pathogenesis of many neuronal disorders. Ribosomal RNA (rRNA) and transfer RNA (tRNA) are structural molecules that have complementary and coordinated functions in protein synthesis. Defects in both rRNAs and tRNAs have been described in mammalian brain development, neurological syndromes, and neurodegeneration. In this review, we present the molecular mechanisms that link aberrant rRNA and tRNA transcription, processing and modifications to translation deficits, and neuropathogenesis. We also discuss the interdependence of rRNA and tRNA biosynthesis and how their metabolism brings together proteotoxic stress and impaired neuronal homeostasis.
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Affiliation(s)
- Francesca Tuorto
- Division of Epigenetics, DKFZ-ZMBH Alliance, German Cancer Research Center, Im Neuenheimer Feld 580, 69120 Heidelberg, Germany.
| | - Rosanna Parlato
- Institute of Applied Physiology, University of Ulm, Albert Einstein Allee 11, 89081 Ulm, Germany; Institute of Anatomy and Cell Biology, Medical Cell Biology, University of Heidelberg, Im Neuenheimer Feld 307, 69120 Heidelberg, Germany.
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46
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Perneczky R, Kempermann G, Korczyn AD, Matthews FE, Ikram MA, Scarmeas N, Chetelat G, Stern Y, Ewers M. Translational research on reserve against neurodegenerative disease: consensus report of the International Conference on Cognitive Reserve in the Dementias and the Alzheimer's Association Reserve, Resilience and Protective Factors Professional Interest Area working groups. BMC Med 2019; 17:47. [PMID: 30808345 PMCID: PMC6391801 DOI: 10.1186/s12916-019-1283-z] [Citation(s) in RCA: 58] [Impact Index Per Article: 11.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/31/2018] [Accepted: 02/06/2019] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND The concept of reserve was established to account for the observation that a given degree of neurodegenerative pathology may result in varying degrees of symptoms in different individuals. There is a large amount of evidence on epidemiological risk and protective factors for neurodegenerative diseases and dementia, yet the biological mechanisms that underpin the protective effects of certain lifestyle and physiological variables remain poorly understood, limiting the development of more effective preventive and treatment strategies. Additionally, different definitions and concepts of reserve exist, which hampers the coordination of research and comparison of results across studies. DISCUSSION This paper represents the consensus of a multidisciplinary group of experts from different areas of research related to reserve, including clinical, epidemiological and basic sciences. The consensus was developed during meetings of the working groups of the first International Conference on Cognitive Reserve in the Dementias (24-25 November 2017, Munich, Germany) and the Alzheimer's Association Reserve and Resilience Professional Interest Area (25 July 2018, Chicago, USA). The main objective of the present paper is to develop a translational perspective on putative mechanisms underlying reserve against neurodegenerative disease, combining evidence from epidemiological and clinical studies with knowledge from animal and basic research. The potential brain functional and structural basis of reserve in Alzheimer's disease and other brain disorders are discussed, as well as relevant lifestyle and genetic factors assessed in both humans and animal models. CONCLUSION There is an urgent need to advance our concept of reserve from a hypothetical model to a more concrete approach that can be used to improve the development of effective interventions aimed at preventing dementia. Our group recommends agreement on a common dictionary of terms referring to different aspects of reserve, the improvement of opportunities for data sharing across individual cohorts, harmonising research approaches across laboratories and groups to reduce heterogeneity associated with human data, global coordination of clinical trials to more effectively explore whether reducing epidemiological risk factors leads to a reduced burden of neurodegenerative diseases in the population, and an increase in our understanding of the appropriateness of animal models for reserve research.
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Affiliation(s)
- Robert Perneczky
- Division of Mental Health in Older Adults and Alzheimer Therapy and Research Center, Department of Psychiatry and Psychotherapy, University Hospital, Ludwig Maximilian University Munich, 80336, Munich, Germany. .,German Center for Neurodegenerative Diseases (DZNE) Munich, Munich, Germany. .,Ageing Epidemiology (AGE) Research Unit, School of Public Health, Imperial College London, London, UK. .,Munich Cluster for Systems Neurology (SyNergy), Munich, Germany.
| | - Gerd Kempermann
- German Center for Neurodegenerative Diseases (DZNE) Dresden, Dresden, Germany.,Center for Regenerative Therapies Dresden (CRTD), Technische Universität Dresden, Dresden, Germany
| | - Amos D Korczyn
- Sackler School of Medicine, Tel- Aviv University, Ramat Aviv, Israel
| | - Fiona E Matthews
- Institute of Health and Society, Newcastle University Institute for Ageing, Newcastle University, Newcastle, UK.,MRC Biostatistics Unit, Cambridge University, Cambridge, UK
| | - M Arfan Ikram
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Nikolaos Scarmeas
- Department of Social Medicine, Psychiatry and Neurology, 1st Department of Neurology, Aeginition University Hospital, National and Kapodistrian University of Athens, Athens, Greece.,Cognitive Neuroscience Division, Department of Neurology and The Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Medical Center, New York, NY, USA
| | - Gael Chetelat
- Université Normandie, Inserm, Université de Caen-Normandie, Inserm UMR-S U1237, GIP Cyceron, Caen, France
| | - Yaakov Stern
- Cognitive Neuroscience Division, Department of Neurology and The Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Medical Center, New York, NY, USA
| | - Michael Ewers
- Institute for Stroke and Dementia Research, University Hospital, LMU Munich, Munich, Germany
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47
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Lane RM, Smith A, Baumann T, Gleichmann M, Norris D, Bennett CF, Kordasiewicz H. Translating Antisense Technology into a Treatment for Huntington's Disease. Methods Mol Biol 2019; 1780:497-523. [PMID: 29856033 DOI: 10.1007/978-1-4939-7825-0_23] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Abstract
Advances in molecular biology and genetics have been used to elucidate the fundamental genetic mechanisms underlying central nervous system (CNS) diseases, yet disease-modifying therapies are currently unavailable for most CNS conditions. Antisense oligonucleotides (ASOs) are synthetic single stranded chains of nucleic acids that bind to a specific sequence on ribonucleic acid (RNA) and regulate posttranscriptional gene expression. Decreased gene expression with ASOs might be able to reduce production of the disease-causing protein underlying dominantly inherited neurodegenerative disorders. Huntington's disease (HD), which is caused by a CAG repeat expansion in exon 1 of the huntingtin (HTT) gene and leads to the pathogenic expansion of a polyglutamine (PolyQ ) tract in the N terminus of the huntingtin protein (Htt), is a prime candidate for ASO therapy.State-of-the art translational science techniques can be applied to the development of an ASO targeting HTT RNA, allowing for a data-driven, stepwise progression through the drug development process. A deep and wide-ranging understanding of the basic, preclinical, clinical, and epidemiologic components of drug development will improve the likelihood of success. This includes characterizing the natural history of the disease, including evolution of biomarkers indexing the underlying pathology; using predictive preclinical models to assess the putative gain-of-function of mutant Htt protein and any loss-of-function of the wild-type protein; characterizing toxicokinetic and pharmacodynamic effects of ASOs in predictive animal models; developing sensitive and reliable biomarkers to monitor target engagement and effects on pathology that translate from animal models to patients with HD; establishing a drug delivery method that ensures reliable distribution to relevant CNS tissue; and designing clinical trials that move expeditiously from proof of concept to proof of efficacy. This review focuses on the translational science techniques that allow for efficient and informed development of an ASO for the treatment of HD.
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Affiliation(s)
| | - Anne Smith
- Ionis Pharmaceuticals, Carlsbad, CA, USA
| | | | | | - Dan Norris
- Ionis Pharmaceuticals, Carlsbad, CA, USA
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48
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Ciarochi JA, Johnson HJ, Calhoun VD, Liu J, Espinoza FA, Bockholt HJ, Misiura M, Caprihan A, Plis S, Paulsen JS, Turner JA. Concurrent Cross-Sectional and Longitudinal Analyses of Multivariate White Matter Profiles and Clinical Functioning in Pre-Diagnosis Huntington Disease. J Huntingtons Dis 2019; 8:199-219. [PMID: 30932891 DOI: 10.3233/jhd-180332] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Gray matter (GM) atrophy in the striatum and across the brain is a consistently reported feature of the Huntington Disease (HD) prodrome. More recently, widespread prodromal white matter (WM) degradation has also been detected. However, longitudinal WM studies are limited and conflicting, and most analyses comparing WM and clinical functioning have also been cross-sectional. OBJECTIVE We simultaneously assessed changes in WM and cognitive and motor functioning at various prodromal HD stages. METHODS Data from 1,336 (1,047 prodromal, 289 control) PREDICT-HD participants were analyzed (3,700 sessions). MRI images were used to create GM, WM, and cerebrospinal fluid probability maps. Using source-based morphometry, independent component analysis was applied to WM probability maps to extract covarying spatial patterns and their subject profiles. WM profiles were analyzed in two sets of linear mixed model (LMM) analyses: one to compare WM profiles across groups cross-sectionally and longitudinally, and one to concurrently compare WM profiles and clinical variables cross-sectionally and longitudinally within each group. RESULTS Findings illustrate widespread prodromal changes in GM-adjacent-WM, with premotor, supplementary motor, middle frontal and striatal changes early in the prodrome that subsequently extend sub-gyrally with progression. Motor functioning agreed most with WM until the near-onset prodromal stage, when Stroop interference was the best WM indicator. Across groups, Trail-Making Test part A outperformed other cognitive variables in its similarity to WM, particularly cross-sectionally. CONCLUSIONS Results suggest that distinct regions coincide with cognitive compared to motor functioning. Furthermore, at different prodromal stages, distinct regions appear to align best with clinical functioning. Thus, the informativeness of clinical measures may vary according to the type of data available (cross-sectional or longitudinal) as well as age and CAG-number.
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Affiliation(s)
| | - Hans J Johnson
- Department of Electrical and Computer Engineering, 1402 Seamans Center for the Engineering Arts and Science, The University of Iowa, Iowa City, IA, USA
| | - Vince D Calhoun
- The Mind Research Network, Albuquerque, NM, USA
- Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, NM, USA
| | - Jingyu Liu
- The Mind Research Network, Albuquerque, NM, USA
| | | | | | - Maria Misiura
- Department of Psychology, Georgia State University, Atlanta, GA, USA
| | | | - Sergey Plis
- The Mind Research Network, Albuquerque, NM, USA
| | - Jane S Paulsen
- Department of Psychiatry, Iowa Mental Health Clinical Research Center, University of Iowa, IA, USA
- Departments of Neurology and Psychology, University of Iowa, IA, USA
| | - Jessica A Turner
- Neuroscience Institute, Georgia State University, Atlanta, GA, USA
- Department of Psychology, Georgia State University, Atlanta, GA, USA
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49
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Rowley CD, Tabrizi SJ, Scahill RI, Leavitt BR, Roos RAC, Durr A, Bock NA. Altered Intracortical T 1-Weighted/T 2-Weighted Ratio Signal in Huntington's Disease. Front Neurosci 2018; 12:805. [PMID: 30455625 PMCID: PMC6230564 DOI: 10.3389/fnins.2018.00805] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2018] [Accepted: 10/16/2018] [Indexed: 01/04/2023] Open
Abstract
Huntington's disease (HD) is a genetic neurodegenerative disorder that is characterized by neuronal cell death. Although medium spiny neurons in the striatum are predominantly affected, other brain regions including the cerebral cortex also degenerate. Previous structural imaging studies have reported decreases in cortical thickness in HD. Here we aimed to further investigate changes in cortical tissue composition in vivo in HD using standard clinical T1-weighted (T1W) and T2-weighted (T2W) magnetic resonance images (MRIs). 326 subjects from the TRACK-HD dataset representing healthy controls and four stages of HD progression were analyzed. The intracortical T1W/T2W intensity was sampled in the middle depth of the cortex over 82 regions across the cortex. While these previously collected images were not optimized for intracortical analysis, we found a significant increase in T1W/T2W intensity (p < 0.05 Bonferroni-Holm corrected) beginning with HD diagnosis. Increases in ratio intensity were found in the insula, which then spread to ventrolateral frontal cortex, superior temporal gyrus, medial temporal gyral pole, and cuneus with progression into the most advanced HD group studied. Mirroring past histological reports, this increase in the ratio image intensity may reflect disease-related increases in myelin and/or iron in the cortex. These findings suggest that future imaging studies are warranted with imaging optimized to more sensitively and specifically assess which features of cortical tissue composition are abnormal in HD to better characterize disease progression.
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Affiliation(s)
- Christopher D. Rowley
- McMaster Integrative Neuroscience Discovery and Study Program, McMaster University, Hamilton, ON, Canada
| | - Sarah J. Tabrizi
- Huntington’s Disease Centre, University College London Institute of Neurology, National Hospital for Neurology and Neurosurgery, London, United Kingdom
| | - Rachael I. Scahill
- Huntington’s Disease Centre, University College London Institute of Neurology, National Hospital for Neurology and Neurosurgery, London, United Kingdom
| | - Blair R. Leavitt
- Department of Medical Genetics, The University of British Columbia, Vancouver, BC, Canada
| | - Raymund A. C. Roos
- Department of Neurology, Leiden University Medical Center, Leiden, Netherlands
| | - Alexandra Durr
- INSERM U1127, CNRS UMR7225, UMR_S1127, UPMC Université Paris VI, Institut du Cerveau et de la Moelle Epinière, Sorbonne University, Paris, France
- APHP, Department of Genetics, Pitié-Salpêtrière University Hospital, Paris, France
| | - Nicholas A. Bock
- Department of Psychology, Neuroscience and Behaviour, McMaster University, Hamilton, ON, Canada
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50
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Functional Magnetic Resonance Imaging in Huntington's Disease. INTERNATIONAL REVIEW OF NEUROBIOLOGY 2018; 142:381-408. [PMID: 30409260 DOI: 10.1016/bs.irn.2018.09.013] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/30/2023]
Abstract
Huntington's disease is an inherited neurodegenerative condition characterized by motor dysfunction, cognitive impairment and neuropsychiatric disturbance. The effects of the underlying pathology on brain morphology are relatively well understood. Numerous structural Magnetic Resonance Imaging (MRI) studies have demonstrated macrostructural change with widespread striatal and cortical atrophy and microstructural white matter loss in premanifest and manifest HD gene carriers. However, disease effects on brain function are less well characterized. Functional MRI provides an opportunity to examine differences in brain activity either in response to a particular task or in the brain at rest. There is increasing evidence that HD gene carriers exhibit altered activation patterns and functional connectivity between brain regions in response to the neurodegenerative process. Here we review the growing literature in this area and critically evaluate the utility of this imaging modality.
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