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Koopman M, Güngördü L, Janssen L, Seinstra RI, Richmond JE, Okerlund N, Wardenaar R, Islam P, Hogewerf W, Brown AEX, Jorgensen EM, Nollen EAA. Rebalancing the motor circuit restores movement in a Caenorhabditis elegans model for TDP-43 toxicity. Cell Rep 2024; 43:114204. [PMID: 38748878 DOI: 10.1016/j.celrep.2024.114204] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2023] [Revised: 02/29/2024] [Accepted: 04/23/2024] [Indexed: 06/01/2024] Open
Abstract
Amyotrophic lateral sclerosis can be caused by abnormal accumulation of TAR DNA-binding protein 43 (TDP-43) in the cytoplasm of neurons. Here, we use a C. elegans model for TDP-43-induced toxicity to identify the biological mechanisms that lead to disease-related phenotypes. By applying deep behavioral phenotyping and subsequent dissection of the neuromuscular circuit, we show that TDP-43 worms have profound defects in GABA neurons. Moreover, acetylcholine neurons appear functionally silenced. Enhancing functional output of repressed acetylcholine neurons at the level of, among others, G-protein-coupled receptors restores neurotransmission, but inefficiently rescues locomotion. Rebalancing the excitatory-to-inhibitory ratio in the neuromuscular system by simultaneous stimulation of the affected GABA- and acetylcholine neurons, however, not only synergizes the effects of boosting individual neurotransmitter systems, but instantaneously improves movement. Our results suggest that interventions accounting for the altered connectome may be more efficient in restoring motor function than those solely focusing on diseased neuron populations.
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Affiliation(s)
- Mandy Koopman
- European Research Institute for the Biology of Ageing, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - Lale Güngördü
- European Research Institute for the Biology of Ageing, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - Leen Janssen
- European Research Institute for the Biology of Ageing, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - Renée I Seinstra
- European Research Institute for the Biology of Ageing, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - Janet E Richmond
- Department of Biological Sciences, University of Illinois at Chicago, Chicago, IL 60607, USA
| | - Nathan Okerlund
- Howard Hughes Medical Institute and School of Biological Science, The University of Utah, Salt Lake City, UT, USA
| | - René Wardenaar
- European Research Institute for the Biology of Ageing, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - Priota Islam
- MRC London Institute of Medical Sciences, London, UK; Institute of Clinical Sciences, Imperial College London, London, UK
| | - Wytse Hogewerf
- European Research Institute for the Biology of Ageing, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - Andre E X Brown
- MRC London Institute of Medical Sciences, London, UK; Institute of Clinical Sciences, Imperial College London, London, UK
| | - Erik M Jorgensen
- Howard Hughes Medical Institute and School of Biological Science, The University of Utah, Salt Lake City, UT, USA
| | - Ellen A A Nollen
- European Research Institute for the Biology of Ageing, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands.
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Castelli L, Vasta R, Allen SP, Waller R, Chiò A, Traynor BJ, Kirby J. From use of omics to systems biology: Identifying therapeutic targets for amyotrophic lateral sclerosis. INTERNATIONAL REVIEW OF NEUROBIOLOGY 2024; 176:209-268. [PMID: 38802176 DOI: 10.1016/bs.irn.2024.02.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/29/2024]
Abstract
Amyotrophic lateral sclerosis (ALS) is a heterogeneous progressive neurodegenerative disorder with available treatments such as riluzole and edaravone extending survival by an average of 3-6 months. The lack of highly effective, widely available therapies reflects the complexity of ALS. Omics technologies, including genomics, transcriptomic and proteomics have contributed to the identification of biological pathways dysregulated and targeted by therapeutic strategies in preclinical and clinical trials. Integrating clinical, environmental and neuroimaging information with omics data and applying a systems biology approach can further improve our understanding of the disease with the potential to stratify patients and provide more personalised medicine. This chapter will review the omics technologies that contribute to a systems biology approach and how these components have assisted in identifying therapeutic targets. Current strategies, including the use of genetic screening and biosampling in clinical trials, as well as the future application of additional technological advances, will also be discussed.
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Affiliation(s)
- Lydia Castelli
- Sheffield Institute for Translational Neuroscience, School of Medicine and Population Health, University of Sheffield, Sheffield, United Kingdom; Neuroscience Institute, University of Sheffield, Sheffield, United Kingdom
| | - Rosario Vasta
- ALS Expert Center,'Rita Levi Montalcini' Department of Neuroscience, University of Turin, Turin, Italy; Neuromuscular Diseases Research Section, National Institute on Aging, National Institutes of Health, Bethesda, MD, United States
| | - Scott P Allen
- Sheffield Institute for Translational Neuroscience, School of Medicine and Population Health, University of Sheffield, Sheffield, United Kingdom; Neuroscience Institute, University of Sheffield, Sheffield, United Kingdom
| | - Rachel Waller
- Sheffield Institute for Translational Neuroscience, School of Medicine and Population Health, University of Sheffield, Sheffield, United Kingdom; Neuroscience Institute, University of Sheffield, Sheffield, United Kingdom
| | - Adriano Chiò
- ALS Expert Center,'Rita Levi Montalcini' Department of Neuroscience, University of Turin, Turin, Italy; Neurology 1, Azienda Ospedaliero-Universitaria Città della Salute e della Scienza of Turin, Turin, Italy
| | - Bryan J Traynor
- Neuromuscular Diseases Research Section, National Institute on Aging, National Institutes of Health, Bethesda, MD, United States; RNA Therapeutics Laboratory, National Center for Advancing Translational Sciences, NIH, Rockville, MD, United States; National Institute of Neurological Disorders and Stroke, Bethesda, MD, United States; Department of Neurology, Johns Hopkins University Medical Center, Baltimore, MD, United States; Reta Lila Weston Institute, UCL Queen Square Institute of Neurology,University College London, London, United Kingdom
| | - Janine Kirby
- Sheffield Institute for Translational Neuroscience, School of Medicine and Population Health, University of Sheffield, Sheffield, United Kingdom; Neuroscience Institute, University of Sheffield, Sheffield, United Kingdom.
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Trubshaw M, Gohil C, Yoganathan K, Kohl O, Edmond E, Proudfoot M, Thompson AG, Talbot K, Stagg CJ, Nobre AC, Woolrich M, Turner MR. The cortical neurophysiological signature of amyotrophic lateral sclerosis. Brain Commun 2024; 6:fcae164. [PMID: 38779353 PMCID: PMC11109820 DOI: 10.1093/braincomms/fcae164] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2024] [Revised: 03/11/2024] [Accepted: 03/09/2024] [Indexed: 05/25/2024] Open
Abstract
The progressive loss of motor function characteristic of amyotrophic lateral sclerosis is associated with widespread cortical pathology extending beyond primary motor regions. Increasing muscle weakness reflects a dynamic, variably compensated brain network disorder. In the quest for biomarkers to accelerate therapeutic assessment, the high temporal resolution of magnetoencephalography is uniquely able to non-invasively capture micro-magnetic fields generated by neuronal activity across the entire cortex simultaneously. This study examined task-free magnetoencephalography to characterize the cortical oscillatory signature of amyotrophic lateral sclerosis for having potential as a pharmacodynamic biomarker. Eight to ten minutes of magnetoencephalography in the task-free, eyes-open state was recorded in amyotrophic lateral sclerosis (n = 36) and healthy age-matched controls (n = 51), followed by a structural MRI scan for co-registration. Extracted magnetoencephalography metrics from the delta, theta, alpha, beta, low-gamma, high-gamma frequency bands included oscillatory power (regional activity), 1/f exponent (complexity) and amplitude envelope correlation (connectivity). Groups were compared using a permutation-based general linear model with correction for multiple comparisons and confounders. To test whether the extracted metrics could predict disease severity, a random forest regression model was trained and evaluated using nested leave-one-out cross-validation. Amyotrophic lateral sclerosis was characterized by reduced sensorimotor beta band and increased high-gamma band power. Within the premotor cortex, increased disability was associated with a reduced 1/f exponent. Increased disability was more widely associated with increased global connectivity in the delta, theta and high-gamma bands. Intra-hemispherically, increased disability scores were particularly associated with increases in temporal connectivity and inter-hemispherically with increases in frontal and occipital connectivity. The random forest model achieved a coefficient of determination (R2) of 0.24. The combined reduction in cortical sensorimotor beta and rise in gamma power is compatible with the established hypothesis of loss of inhibitory, GABAergic interneuronal circuits in pathogenesis. A lower 1/f exponent potentially reflects a more excitable cortex and a pathology unique to amyotrophic lateral sclerosis when considered with the findings published in other neurodegenerative disorders. Power and complexity changes corroborate with the results from paired-pulse transcranial magnetic stimulation. Increased magnetoencephalography connectivity in worsening disability is thought to represent compensatory responses to a failing motor system. Restoration of cortical beta and gamma band power has significant potential to be tested in an experimental medicine setting. Magnetoencephalography-based measures have potential as sensitive outcome measures of therapeutic benefit in drug trials and may have a wider diagnostic value with further study, including as predictive markers in asymptomatic carriers of disease-causing genetic variants.
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Affiliation(s)
- Michael Trubshaw
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, OX3 7JX, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, UK
| | - Chetan Gohil
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, OX3 7JX, UK
- Department of Psychiatry, University of Oxford, Oxford, OX3 7JX, UK
| | - Katie Yoganathan
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, OX3 7JX, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, UK
| | - Oliver Kohl
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, OX3 7JX, UK
- Department of Psychiatry, University of Oxford, Oxford, OX3 7JX, UK
| | - Evan Edmond
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, OX3 7JX, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, UK
| | - Malcolm Proudfoot
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, UK
| | - Alexander G Thompson
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, UK
| | - Kevin Talbot
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, UK
| | - Charlotte J Stagg
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, OX3 7JX, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, UK
| | - Anna C Nobre
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, OX3 7JX, UK
- Department of Psychiatry, University of Oxford, Oxford, OX3 7JX, UK
| | - Mark Woolrich
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, OX3 7JX, UK
- Department of Psychiatry, University of Oxford, Oxford, OX3 7JX, UK
| | - Martin R Turner
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, OX3 7JX, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, UK
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4
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Dukic S, Fasano A, Coffey A, Buxó T, McMackin R, Chipika R, Heverin M, Bede P, Muthuraman M, Lowery M, Carson RG, Hardiman O, Nasseroleslami B. Electroencephalographic β-band oscillations in the sensorimotor network reflect motor symptom severity in amyotrophic lateral sclerosis. Eur J Neurol 2024; 31:e16201. [PMID: 38235854 DOI: 10.1111/ene.16201] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Revised: 11/27/2023] [Accepted: 12/21/2023] [Indexed: 01/19/2024]
Abstract
BACKGROUND AND PURPOSE Resting-state electroencephalography (EEG) holds promise for assessing brain networks in amyotrophic lateral sclerosis (ALS). We investigated whether neural β-band oscillations in the sensorimotor network could serve as an objective quantitative measure of progressive motor impairment and functional disability in ALS patients. METHODS Resting-state EEG was recorded in 18 people with ALS and 38 age- and gender-matched healthy controls. We estimated source-localized β-band spectral power in the sensorimotor cortex. Clinical evaluation included lower (LMN) and upper motor neuron scores, Amyotrophic Lateral Sclerosis Functional Rating Scale-Revised score, fine motor function (FMF) subscore, and progression rate. Correlations between clinical scores and β-band power were analysed and corrected using a false discovery rate of q = 0.05. RESULTS β-Band power was significantly lower in people with ALS than controls (p = 0.004), and correlated with LMN score (R = -0.65, p = 0.013), FMF subscore (R = -0.53, p = 0.036), and FMF progression rate (R = 0.52, p = 0.036). CONCLUSIONS β-Band spectral power in the sensorimotor cortex reflects clinically evaluated motor impairment in ALS. This technology merits further investigation as a biomarker of progressive functional disability.
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Affiliation(s)
- Stefan Dukic
- Academic Unit of Neurology, School of Medicine, Trinity College Dublin, University of Dublin, Dublin, Ireland
- Department of Neurology, University Medical Centre Utrecht Brain Centre, Utrecht University, Utrecht, the Netherlands
| | - Antonio Fasano
- Academic Unit of Neurology, School of Medicine, Trinity College Dublin, University of Dublin, Dublin, Ireland
| | - Amina Coffey
- Academic Unit of Neurology, School of Medicine, Trinity College Dublin, University of Dublin, Dublin, Ireland
| | - Teresa Buxó
- Academic Unit of Neurology, School of Medicine, Trinity College Dublin, University of Dublin, Dublin, Ireland
| | - Roisin McMackin
- Academic Unit of Neurology, School of Medicine, Trinity College Dublin, University of Dublin, Dublin, Ireland
- Discipline of Physiology, School of Medicine, Trinity College Dublin, University of Dublin, Dublin, Ireland
| | - Rangariroyashe Chipika
- Academic Unit of Neurology, School of Medicine, Trinity College Dublin, University of Dublin, Dublin, Ireland
| | - Mark Heverin
- Academic Unit of Neurology, School of Medicine, Trinity College Dublin, University of Dublin, Dublin, Ireland
| | - Peter Bede
- Computational Neuroimaging Group, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Dublin, Ireland
| | - Muthuraman Muthuraman
- Neural Engineering With Signal Analytics and Artificial Intelligence, Department of Neurology, University of Würzburg, Würzburg, Germany
| | - Madeleine Lowery
- School of Electrical and Electronic Engineering, University College Dublin, Dublin, Ireland
| | - Richard G Carson
- Trinity College Institute of Neuroscience and School of Psychology, Trinity College Dublin, University of Dublin, Dublin, Ireland
- School of Psychology, Queen's University Belfast, Belfast, Ireland
| | - Orla Hardiman
- Academic Unit of Neurology, School of Medicine, Trinity College Dublin, University of Dublin, Dublin, Ireland
- Department of Neurology, Beaumont Hospital, Dublin, Ireland
| | - Bahman Nasseroleslami
- Academic Unit of Neurology, School of Medicine, Trinity College Dublin, University of Dublin, Dublin, Ireland
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5
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Zeller D, Hiew S, Odorfer T, Nguemeni C. Considering the response in addition to the challenge - a narrative review in appraisal of a motor reserve framework. Aging (Albany NY) 2024; 16:5772-5791. [PMID: 38499388 PMCID: PMC11006496 DOI: 10.18632/aging.205667] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Accepted: 01/04/2024] [Indexed: 03/20/2024]
Abstract
The remarkable increase in human life expectancy over the past century has been achieved at the expense of the risk of age-related impairment and disease. Neurodegeneration, be it part of normal aging or due to neurodegenerative disorders, is characterized by loss of specific neuronal populations, leading to increasing clinical impairment. The individual course may be described as balance between aging- or disease-related pathology and intrinsic mechanisms of adaptation. There is plenty of evidence that the human brain is provided with exhaustible resources to maintain function in the face of adverse conditions. While a reserve concept has mainly been coined in cognitive neuroscience, emerging evidence suggests similar mechanisms to underlie individual differences of adaptive capacity within the motor system. In this narrative review, we summarize what has been proposed to date about a motor reserve (mR) framework. We present current evidence from research in aging subjects and people with neurological conditions, followed by a description of what is known about potential neuronal substrates of mR so far. As there is no gold standard of mR quantification, we outline current approaches which describe various indicators of mR. We conclude by sketching out potential future directions of research. Expediting our understanding of differences in individual motor resilience towards aging and disease will eventually contribute to new, individually tailored therapeutic strategies. Provided early diagnosis, enhancing the individual mR may be suited to postpone disease onset by years and may be an efficacious contribution towards healthy aging, with an increased quality of life for the elderly.
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Affiliation(s)
- Daniel Zeller
- Department of Neurology, University Hospital Würzburg, Würzburg 97080, Germany
| | - Shawn Hiew
- Department of Neurology, University Hospital Würzburg, Würzburg 97080, Germany
| | - Thorsten Odorfer
- Department of Neurology, University Hospital Würzburg, Würzburg 97080, Germany
| | - Carine Nguemeni
- Department of Neurology, University Hospital Würzburg, Würzburg 97080, Germany
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Tzeplaeff L, Jürs AV, Wohnrade C, Demleitner AF. Unraveling the Heterogeneity of ALS-A Call to Redefine Patient Stratification for Better Outcomes in Clinical Trials. Cells 2024; 13:452. [PMID: 38474416 PMCID: PMC10930688 DOI: 10.3390/cells13050452] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2024] [Revised: 02/26/2024] [Accepted: 02/28/2024] [Indexed: 03/14/2024] Open
Abstract
Despite tremendous efforts in basic research and a growing number of clinical trials aiming to find effective treatments, amyotrophic lateral sclerosis (ALS) remains an incurable disease. One possible reason for the lack of effective causative treatment options is that ALS may not be a single disease entity but rather may represent a clinical syndrome, with diverse genetic and molecular causes, histopathological alterations, and subsequent clinical presentations contributing to its complexity and variability among individuals. Defining a way to subcluster ALS patients is becoming a central endeavor in the field. Identifying specific clusters and applying them in clinical trials could enable the development of more effective treatments. This review aims to summarize the available data on heterogeneity in ALS with regard to various aspects, e.g., clinical, genetic, and molecular.
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Affiliation(s)
- Laura Tzeplaeff
- Department of Neurology, Rechts der Isar Hospital, Technical University of Munich, 81675 München, Germany
| | - Alexandra V. Jürs
- Translational Neurodegeneration Section “Albrecht Kossel”, Department of Neurology, University Medical Center Rostock, 18057 Rostock, Germany
| | - Camilla Wohnrade
- Department of Neurology, Hannover Medical School, 30625 Hannover, Germany;
| | - Antonia F. Demleitner
- Department of Neurology, Rechts der Isar Hospital, Technical University of Munich, 81675 München, Germany
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7
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Fernandes SR, Callejón-Leblic MA, Ferreira HA. How does the electric field induced by tDCS influence motor-related connectivity? Model-guided perspectives. Phys Med Biol 2024; 69:055007. [PMID: 38266295 DOI: 10.1088/1361-6560/ad222d] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Accepted: 01/24/2024] [Indexed: 01/26/2024]
Abstract
Over the last decade, transcranial direct current stimulation (tDCS) has been applied not only to modulate local cortical activation, but also to address communication between functionally-related brain areas. Stimulation protocols based on simple two-electrode placements are being replaced by multi-electrode montages to target intra- and inter-hemispheric neural networks using multichannel/high definition paradigms.Objective. This study aims to investigate the characteristics of electric field (EF) patterns originated by tDCS experiments addressing changes in functional brain connectivity.Methods. A previous selection of tDCS experimental studies aiming to modulate motor-related connectivity in health and disease was conducted. Simulations of the EF induced in the cortex were then performed for each protocol selected. The EF magnitude and orientation are determined and analysed in motor-related cortical regions for five different head models to account for inter-subject variability. Functional connectivity outcomes obtained are qualitatively analysed at the light of the simulated EF and protocol characteristics, such as electrode position, number and stimulation dosing.Main findings. The EF magnitude and orientation predicted by computational models can be related with the ability of tDCS to modulate brain functional connectivity. Regional differences in EF distributions across subjects can inform electrode placements more susceptible to inter-subject variability in terms of brain connectivity-related outcomes.Significance. Neuronal facilitation/inhibition induced by tDCS fields may indirectly influence intra and inter-hemispheric connectivity by modulating neural components of motor-related networks. Optimization of tDCS using computational models is essential for adequate dosing delivery in specific networks related to clinically relevant connectivity outcomes.
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Affiliation(s)
- Sofia Rita Fernandes
- Instituto de Biofísica e Engenharia Biomédica, Faculdade de Ciências, Universidade de Lisboa, Portugal
| | - M Amparo Callejón-Leblic
- Oticon Medical, Madrid, Spain
- Grupo de Ingeniería Biomédica, Escuela Técnica Superior de Ingeniería, Universidad de Sevilla, Spain
- Servicio de Otorrinolaringología, Hospital Universitario Virgen Macarena, Sevilla, Spain
| | - Hugo Alexandre Ferreira
- Instituto de Biofísica e Engenharia Biomédica, Faculdade de Ciências, Universidade de Lisboa, Portugal
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Cano LA, Albarracín AL, Pizá AG, García-Cena CE, Fernández-Jover E, Farfán FD. Assessing Cognitive Workload in Motor Decision-Making through Functional Connectivity Analysis: Towards Early Detection and Monitoring of Neurodegenerative Diseases. SENSORS (BASEL, SWITZERLAND) 2024; 24:1089. [PMID: 38400247 PMCID: PMC10893317 DOI: 10.3390/s24041089] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Revised: 09/04/2023] [Accepted: 02/05/2024] [Indexed: 02/25/2024]
Abstract
Neurodegenerative diseases (NDs), such as Alzheimer's, Parkinson's, amyotrophic lateral sclerosis, and frontotemporal dementia, among others, are increasingly prevalent in the global population. The clinical diagnosis of these NDs is based on the detection and characterization of motor and non-motor symptoms. However, when these diagnoses are made, the subjects are often in advanced stages where neuromuscular alterations are frequently irreversible. In this context, we propose a methodology to evaluate the cognitive workload (CWL) of motor tasks involving decision-making processes. CWL is a concept widely used to address the balance between task demand and the subject's available resources to complete that task. In this study, multiple models for motor planning during a motor decision-making task were developed by recording EEG and EMG signals in n=17 healthy volunteers (9 males, 8 females, age 28.66±8.8 years). In the proposed test, volunteers have to make decisions about which hand should be moved based on the onset of a visual stimulus. We computed functional connectivity between the cortex and muscles, as well as among muscles using both corticomuscular and intermuscular coherence. Despite three models being generated, just one of them had strong performance. The results showed two types of motor decision-making processes depending on the hand to move. Moreover, the central processing of decision-making for the left hand movement can be accurately estimated using behavioral measures such as planning time combined with peripheral recordings like EMG signals. The models provided in this study could be considered as a methodological foundation to detect neuromuscular alterations in asymptomatic patients, as well as to monitor the process of a degenerative disease.
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Affiliation(s)
- Leonardo Ariel Cano
- Neuroscience and Applied Technologies Laboratory (LINTEC), Bioengineering Department, Faculty of Exact Sciences and Technology (FACET), National University of Tucuman, Superior Institute of Biological Research (INSIBIO), National Scientific and Technical Research Council (CONICET), Av. Independencia 1800, San Miguel de Tucuman 4000, Argentina
| | - Ana Lía Albarracín
- Neuroscience and Applied Technologies Laboratory (LINTEC), Bioengineering Department, Faculty of Exact Sciences and Technology (FACET), National University of Tucuman, Superior Institute of Biological Research (INSIBIO), National Scientific and Technical Research Council (CONICET), Av. Independencia 1800, San Miguel de Tucuman 4000, Argentina
| | - Alvaro Gabriel Pizá
- Neuroscience and Applied Technologies Laboratory (LINTEC), Bioengineering Department, Faculty of Exact Sciences and Technology (FACET), National University of Tucuman, Superior Institute of Biological Research (INSIBIO), National Scientific and Technical Research Council (CONICET), Av. Independencia 1800, San Miguel de Tucuman 4000, Argentina
| | - Cecilia Elisabet García-Cena
- ETSIDI-Center for Automation and Robotics, Universidad Politécnica de Madrid, Ronda de Valencia 3, 28012 Madrid, Spain
| | - Eduardo Fernández-Jover
- Institute of Bioengineering, Universidad Miguel Hernández of Elche, 03202 Elche, Spain
- Research Networking Center in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), 28029 Madrid, Spain
| | - Fernando Daniel Farfán
- Neuroscience and Applied Technologies Laboratory (LINTEC), Bioengineering Department, Faculty of Exact Sciences and Technology (FACET), National University of Tucuman, Superior Institute of Biological Research (INSIBIO), National Scientific and Technical Research Council (CONICET), Av. Independencia 1800, San Miguel de Tucuman 4000, Argentina
- Institute of Bioengineering, Universidad Miguel Hernández of Elche, 03202 Elche, Spain
- Research Networking Center in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), 28029 Madrid, Spain
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9
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Metzger M, Dukic S, McMackin R, Giglia E, Mitchell M, Bista S, Costello E, Peelo C, Tadjine Y, Sirenko V, Plaitano S, Coffey A, McManus L, Farnell Sharp A, Mehra P, Heverin M, Bede P, Muthuraman M, Pender N, Hardiman O, Nasseroleslami B. Functional network dynamics revealed by EEG microstates reflect cognitive decline in amyotrophic lateral sclerosis. Hum Brain Mapp 2024; 45:e26536. [PMID: 38087950 PMCID: PMC10789208 DOI: 10.1002/hbm.26536] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Revised: 10/26/2023] [Accepted: 10/31/2023] [Indexed: 01/16/2024] Open
Abstract
Recent electroencephalography (EEG) studies have shown that patterns of brain activity can be used to differentiate amyotrophic lateral sclerosis (ALS) and control groups. These differences can be interrogated by examining EEG microstates, which are distinct, reoccurring topographies of the scalp's electrical potentials. Quantifying the temporal properties of the four canonical microstates can elucidate how the dynamics of functional brain networks are altered in neurological conditions. Here we have analysed the properties of microstates to detect and quantify signal-based abnormality in ALS. High-density resting-state EEG data from 129 people with ALS and 78 HC were recorded longitudinally over a 24-month period. EEG topographies were extracted at instances of peak global field power to identify four microstate classes (labelled A-D) using K-means clustering. Each EEG topography was retrospectively associated with a microstate class based on global map dissimilarity. Changes in microstate properties over the course of the disease were assessed in people with ALS and compared with changes in clinical scores. The topographies of microstate classes remained consistent across participants and conditions. Differences were observed in coverage, occurrence, duration, and transition probabilities between ALS and control groups. The duration of microstate class B and coverage of microstate class C correlated with lower limb functional decline. The transition probabilities A to D, C to B and C to B also correlated with cognitive decline (total ECAS) in those with cognitive and behavioural impairments. Microstate characteristics also significantly changed over the course of the disease. Examining the temporal dependencies in the sequences of microstates revealed that the symmetry and stationarity of transition matrices were increased in people with late-stage ALS. These alterations in the properties of EEG microstates in ALS may reflect abnormalities within the sensory network and higher-order networks. Microstate properties could also prospectively predict symptom progression in those with cognitive impairments.
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Affiliation(s)
- Marjorie Metzger
- Academic Unit of Neurology, School of Medicine, Trinity Biomedical Sciences Institute, Trinity College DublinUniversity of DublinDublinIreland
| | - Stefan Dukic
- Academic Unit of Neurology, School of Medicine, Trinity Biomedical Sciences Institute, Trinity College DublinUniversity of DublinDublinIreland
- Department of Neurology, University Medical Centre Utrecht Brain CentreUtrecht UniversityUtrechtThe Netherlands
| | - Roisin McMackin
- Academic Unit of Neurology, School of Medicine, Trinity Biomedical Sciences Institute, Trinity College DublinUniversity of DublinDublinIreland
- Discipline of Physiology, School of Medicine, Trinity Biomedical Sciences Institute, Trinity College DublinUniversity of DublinDublinIreland
| | - Eileen Giglia
- Academic Unit of Neurology, School of Medicine, Trinity Biomedical Sciences Institute, Trinity College DublinUniversity of DublinDublinIreland
| | - Matthew Mitchell
- Academic Unit of Neurology, School of Medicine, Trinity Biomedical Sciences Institute, Trinity College DublinUniversity of DublinDublinIreland
| | - Saroj Bista
- Academic Unit of Neurology, School of Medicine, Trinity Biomedical Sciences Institute, Trinity College DublinUniversity of DublinDublinIreland
| | - Emmet Costello
- Academic Unit of Neurology, School of Medicine, Trinity Biomedical Sciences Institute, Trinity College DublinUniversity of DublinDublinIreland
| | - Colm Peelo
- Academic Unit of Neurology, School of Medicine, Trinity Biomedical Sciences Institute, Trinity College DublinUniversity of DublinDublinIreland
| | - Yasmine Tadjine
- Academic Unit of Neurology, School of Medicine, Trinity Biomedical Sciences Institute, Trinity College DublinUniversity of DublinDublinIreland
| | - Vladyslav Sirenko
- Academic Unit of Neurology, School of Medicine, Trinity Biomedical Sciences Institute, Trinity College DublinUniversity of DublinDublinIreland
| | - Serena Plaitano
- Academic Unit of Neurology, School of Medicine, Trinity Biomedical Sciences Institute, Trinity College DublinUniversity of DublinDublinIreland
| | - Amina Coffey
- Academic Unit of Neurology, School of Medicine, Trinity Biomedical Sciences Institute, Trinity College DublinUniversity of DublinDublinIreland
| | - Lara McManus
- Academic Unit of Neurology, School of Medicine, Trinity Biomedical Sciences Institute, Trinity College DublinUniversity of DublinDublinIreland
| | - Adelais Farnell Sharp
- Academic Unit of Neurology, School of Medicine, Trinity Biomedical Sciences Institute, Trinity College DublinUniversity of DublinDublinIreland
| | - Prabhav Mehra
- Academic Unit of Neurology, School of Medicine, Trinity Biomedical Sciences Institute, Trinity College DublinUniversity of DublinDublinIreland
| | - Mark Heverin
- Academic Unit of Neurology, School of Medicine, Trinity Biomedical Sciences Institute, Trinity College DublinUniversity of DublinDublinIreland
| | - Peter Bede
- Academic Unit of Neurology, School of Medicine, Trinity Biomedical Sciences Institute, Trinity College DublinUniversity of DublinDublinIreland
| | - Muthuraman Muthuraman
- Neural Engineering with Signal Analytics and Artificial Intelligence, Department of NeurologyUniversity of WürzburgWürzburgGermany
| | - Niall Pender
- Academic Unit of Neurology, School of Medicine, Trinity Biomedical Sciences Institute, Trinity College DublinUniversity of DublinDublinIreland
- Department of PsychologyBeaumont HospitalDublinIreland
| | - Orla Hardiman
- Academic Unit of Neurology, School of Medicine, Trinity Biomedical Sciences Institute, Trinity College DublinUniversity of DublinDublinIreland
- Department of NeurologyBeaumont HospitalDublinIreland
| | - Bahman Nasseroleslami
- Academic Unit of Neurology, School of Medicine, Trinity Biomedical Sciences Institute, Trinity College DublinUniversity of DublinDublinIreland
- FutureNeuro ‐ SFI Research Centre for Chronic and Rare Neurological DiseasesRoyal College of SurgeonsDublinIreland
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10
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de Carvalho M, Swash M. Diagnosis and differential diagnosis of MND/ALS: IFCN handbook chapter. Clin Neurophysiol Pract 2023; 9:27-38. [PMID: 38249779 PMCID: PMC10796809 DOI: 10.1016/j.cnp.2023.12.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2023] [Revised: 11/01/2023] [Accepted: 12/07/2023] [Indexed: 01/23/2024] Open
Abstract
•Accurate and rapid diagnosis of amyotrophic lateral sclerosis (ALS) is important to prevent erroneous interventions. •The recent Gold Coast criteria are easily applicable and have high sensitivity and specificity. •Future developments will help to distinguish ALS as a specific clinical-pathologic entity. Accurate and rapid diagnosis of amyotrophic lateral sclerosis (ALS) is essential in order to provide accurate information for patient and family, to avoid time-consuming investigations and to permit an appropriate management plan. ALS is variable regarding presentation, disease progression, genetic profile and patient reaction to the diagnosis. It is obviously important to exclude treatable conditions but, in most patients, for experienced neurologists the diagnosis is clear-cut, depending on the presence of progressive upper and lower motor neuron signs. Patients with signs of restricted lower motor neuron (LMN) or upper motor neuron (UMN) dysfunction may present diagnostic difficulty, but electromyography (EMG) is often a determinant diagnostic test since it may exclude other disorders. Transcranial magnetic stimulation may aid detection of UMN dysfunction, and brain and spinal cord MRI, ultrasound and blood neurofilament measurements, have begun to have clinical impact, although none are themselves diagnostic tests. Several sets of diagnostic criteria have been proposed in the past; all rely on clinical LMN and UMN signs in different anatomic territories, EMG changes, exclusion of other disorders, and disease progression, in particular evidence of spreading to other anatomic territories. Fasciculations are a characteristic clinical feature and increased importance is now attached to fasciculation potentials detected by EMG, when associated with classical signs of denervation and reinnervation. The Gold Coast diagnostic criteria rely on the presence of UMN and LMN signs in one (or more) anatomic territory, or LMN signs in two (or more) anatomic territories, recognizing the fundamental clinical requirements of disease progression and exclusion of other diseases. Recent studies confirm a high sensitivity without loss of specificity using these Gold Coast criteria. In considering the diagnosis of ALS a critical question for future understanding is whether ALS should be considered a syndrome or a specific clinico-pathologic entity; this can only be addressed in the light of more complete knowledge.
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Affiliation(s)
- Mamede de Carvalho
- Faculdade de Medicina- Instituto de Medicina Molecular, Centro de Estudos Egas Moniz, Universidade de Lisboa, Lisbon, Portugal
- Department of Neurosciences and Mental Health, Hospital de Santa Maria, Centro Hospitalar Universitário Lisboa-Norte, Lisbon, Portugal
| | - Michael Swash
- Faculdade de Medicina- Instituto de Medicina Molecular, Centro de Estudos Egas Moniz, Universidade de Lisboa, Lisbon, Portugal
- Departments of Neurology and Neurosciences, Barts and the London School of Medicine, Queen Mary University of London and Royal London Hospital, UK
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11
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McMackin R, Bede P, Ingre C, Malaspina A, Hardiman O. Biomarkers in amyotrophic lateral sclerosis: current status and future prospects. Nat Rev Neurol 2023; 19:754-768. [PMID: 37949994 DOI: 10.1038/s41582-023-00891-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/09/2023] [Indexed: 11/12/2023]
Abstract
Disease heterogeneity in amyotrophic lateral sclerosis poses a substantial challenge in drug development. Categorization based on clinical features alone can help us predict the disease course and survival, but quantitative measures are also needed that can enhance the sensitivity of the clinical categorization. In this Review, we describe the emerging landscape of diagnostic, categorical and pharmacodynamic biomarkers in amyotrophic lateral sclerosis and their place in the rapidly evolving landscape of new therapeutics. Fluid-based markers from cerebrospinal fluid, blood and urine are emerging as useful diagnostic, pharmacodynamic and predictive biomarkers. Combinations of imaging measures have the potential to provide important diagnostic and prognostic information, and neurophysiological methods, including various electromyography-based measures and quantitative EEG-magnetoencephalography-evoked responses and corticomuscular coherence, are generating useful diagnostic, categorical and prognostic markers. Although none of these biomarker technologies has been fully incorporated into clinical practice or clinical trials as a primary outcome measure, strong evidence is accumulating to support their clinical utility.
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Affiliation(s)
- Roisin McMackin
- Discipline of Physiology, School of Medicine, Trinity Biomedical Sciences Institute, Trinity College Dublin, The University of Dublin, Dublin, Ireland
- Academic Unit of Neurology, School of Medicine, Trinity Biomedical Sciences Institute, Trinity College Dublin, The University of Dublin, Dublin, Ireland
| | - Peter Bede
- Academic Unit of Neurology, School of Medicine, Trinity Biomedical Sciences Institute, Trinity College Dublin, The University of Dublin, Dublin, Ireland
- Computational Neuroimaging Group, School of Medicine, Trinity College Dublin, The University of Dublin, Dublin, Ireland
- Department of Neurology, St James's Hospital, Dublin, Ireland
| | - Caroline Ingre
- Department of Neuroscience, Karolinska Institute, Stockholm, Sweden
- Department of Neurology, Karolinska University Hospital, Stockholm, Sweden
| | - Andrea Malaspina
- Department of Neuromuscular Diseases, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Orla Hardiman
- Academic Unit of Neurology, School of Medicine, Trinity Biomedical Sciences Institute, Trinity College Dublin, The University of Dublin, Dublin, Ireland.
- Department of Neurology, Beaumont Hospital, Dublin, Ireland.
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12
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Theme 08 - Clinical Imaging and Electrophysiology. Amyotroph Lateral Scler Frontotemporal Degener 2023; 24:192-208. [PMID: 37966324 DOI: 10.1080/21678421.2023.2260200] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2023]
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13
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Siciliano L, Olivito G, Urbini N, Silveri MC, Leggio M. The rising role of cognitive reserve and associated compensatory brain networks in spinocerebellar ataxia type 2. J Neurol 2023; 270:5071-5084. [PMID: 37421466 PMCID: PMC10511586 DOI: 10.1007/s00415-023-11855-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Revised: 06/26/2023] [Accepted: 06/27/2023] [Indexed: 07/10/2023]
Abstract
Pre-existing or enhanced cognitive abilities influence symptom onset and severity in neurodegenerative diseases, which improve an individual's ability to deal with neurodegeneration. This process is named cognitive reserve (CR), and it has acquired high visibility in the field of neurodegeneration. However, the investigation of CR has been neglected in the context of cerebellar neurodegenerative disorders. The present study assessed CR and its impact on cognitive abilities in spinocerebellar ataxia type 2 (SCA2), which is a rare cerebellar neurodegenerative disease. We investigated the existence of CR networks in terms of compensatory mechanisms and neural reserve driven by increased cerebello-cerebral functional connectivity. The CR of 12 SCA2 patients was assessed using the Cognitive Reserve Index Questionnaire (CRIq), which was developed for appraising life-span CR. Patients underwent several neuropsychological tests to evaluate cognitive functioning and a functional MRI examination. Network based statistics analysis was used to assess functional brain networks. The results revealed significant correlations of CRIq measures with cognitive domains and patterns of increased connectivity in specific cerebellar and cerebral regions, which likely indicated CR networks. This study showed that CR may influence disease-related cognitive deficits, and it was related to the effective use of specific cerebello-cerebral networks that reflect a CR biomarker.
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Affiliation(s)
- Libera Siciliano
- Department of Psychology, Sapienza University of Rome, 00185 Rome, Italy
- Ataxia Laboratory, Fondazione Santa Lucia IRCCS, 00179 Rome, Italy
| | - Giusy Olivito
- Department of Psychology, Sapienza University of Rome, 00185 Rome, Italy
- Ataxia Laboratory, Fondazione Santa Lucia IRCCS, 00179 Rome, Italy
| | - Nicole Urbini
- Department of Psychology, Sapienza University of Rome, 00185 Rome, Italy
- Ataxia Laboratory, Fondazione Santa Lucia IRCCS, 00179 Rome, Italy
| | | | - Maria Leggio
- Department of Psychology, Sapienza University of Rome, 00185 Rome, Italy
- Ataxia Laboratory, Fondazione Santa Lucia IRCCS, 00179 Rome, Italy
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14
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Sennfält S, Pagani M, Fang F, Savitcheva I, Estenberg U, Ingre C. FDG-PET shows weak correlation between focal motor weakness and brain metabolic alterations in ALS. Amyotroph Lateral Scler Frontotemporal Degener 2023:1-10. [PMID: 36755485 DOI: 10.1080/21678421.2023.2174881] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/10/2023]
Abstract
Objective: Amyotrophic lateral sclerosis (ALS) is a clinically heterogenous disease, typically presenting with focal motor weakness that eventually generalizes. Weather there is a correlation between focal motor weakness and metabolic alterations in specific areas of the brain has not been thoroughly explored. This study aims to systematically investigate this by using fluorodeoxyglucose-positron emission tomography (FDG-PET), including longitudinal imaging. Methods: This observational imaging study included 131 ALS patients diagnosed and examined with FDG-PET at the ALS Clinical Research Center at the Karolinska University Hospital in Stockholm, Sweden. Thirteen ALS patients had a second scan and were analyzed longitudinally. The findings were compared to 39 healthy controls examined at the University Medical Center of Gröningen, the Netherlands. Results: There was a general pattern of brain metabolic alterations consistent with previously reported findings in ALS, namely hypometabolism in frontal regions and hypermetabolism in posterior regions. A higher symptom burden was associated with increased hypometabolism and decreased hypermetabolism. However, there was no clear correlation between focal motor weakness and specific metabolic alterations, neither when analyzing focal motor weakness with concomitant upper motor neuron signs or when including all focal motor weakness. Longitudinal FDG-PET imaging showed inconsistent results with little correlation between progression of motor weakness and metabolic alterations. Conclusion: Our results support the disease model of ALS as a diffuse process since no clear correlation was seen between focal motor weakness and specific metabolic alterations. However, there is need for further research on a larger number of patients, particularly including longitudinal imaging.
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Affiliation(s)
- Stefan Sennfält
- Department of Neurology, Karolinska University Hospital, Stockholm, Sweden.,Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Marco Pagani
- Institute of Cognitive Sciences and Technologies, C.N.R, Rome, Italy.,Department of Medical Radiation Physics and Nuclear Medicine, Karolinska University Hospital, Stockholm, Sweden, and
| | - Fang Fang
- Unit of Integrative Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Irina Savitcheva
- Department of Medical Radiation Physics and Nuclear Medicine, Karolinska University Hospital, Stockholm, Sweden, and
| | - Ulrika Estenberg
- Department of Medical Radiation Physics and Nuclear Medicine, Karolinska University Hospital, Stockholm, Sweden, and
| | - Caroline Ingre
- Department of Neurology, Karolinska University Hospital, Stockholm, Sweden.,Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
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15
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Díaz-Rivera MN, Birba A, Fittipaldi S, Mola D, Morera Y, de Vega M, Moguilner S, Lillo P, Slachevsky A, González Campo C, Ibáñez A, García AM. Multidimensional inhibitory signatures of sentential negation in behavioral variant frontotemporal dementia. Cereb Cortex 2022; 33:403-420. [PMID: 35253864 PMCID: PMC9837611 DOI: 10.1093/cercor/bhac074] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Revised: 01/31/2022] [Accepted: 02/07/2022] [Indexed: 01/19/2023] Open
Abstract
BACKGROUND Processing of linguistic negation has been associated to inhibitory brain mechanisms. However, no study has tapped this link via multimodal measures in patients with core inhibitory alterations, a critical approach to reveal direct neural correlates and potential disease markers. METHODS Here we examined oscillatory, neuroanatomical, and functional connectivity signatures of a recently reported Go/No-go negation task in healthy controls and behavioral variant frontotemporal dementia (bvFTD) patients, typified by primary and generalized inhibitory disruptions. To test for specificity, we also recruited persons with Alzheimer's disease (AD), a disease involving frequent but nonprimary inhibitory deficits. RESULTS In controls, negative sentences in the No-go condition distinctly involved frontocentral delta (2-3 Hz) suppression, a canonical inhibitory marker. In bvFTD patients, this modulation was selectively abolished and significantly correlated with the volume and functional connectivity of regions supporting inhibition (e.g. precentral gyrus, caudate nucleus, and cerebellum). Such canonical delta suppression was preserved in the AD group and associated with widespread anatomo-functional patterns across non-inhibitory regions. DISCUSSION These findings suggest that negation hinges on the integrity and interaction of spatiotemporal inhibitory mechanisms. Moreover, our results reveal potential neurocognitive markers of bvFTD, opening a new agenda at the crossing of cognitive neuroscience and behavioral neurology.
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Affiliation(s)
- Mariano N Díaz-Rivera
- Centro de Neurociencias Cognitivas, Universidad de San Andrés, Vito Dumas 284, Buenos Aires B1644BID, Argentina.,Agencia Nacional de Promoción Científica y Tecnológica (ANPCyT), C1425FQD, Godoy Cruz 2370, Buenos Aires, Argentina
| | - Agustina Birba
- Centro de Neurociencias Cognitivas, Universidad de San Andrés, Vito Dumas 284, Buenos Aires B1644BID, Argentina.,National Scientific and Technical Research Council (CONICET), C1425FQD, Godoy Cruz 2290, Buenos Aires, Argentina
| | - Sol Fittipaldi
- Centro de Neurociencias Cognitivas, Universidad de San Andrés, Vito Dumas 284, Buenos Aires B1644BID, Argentina.,National Scientific and Technical Research Council (CONICET), C1425FQD, Godoy Cruz 2290, Buenos Aires, Argentina
| | - Débora Mola
- Instituto de Investigaciones Psicológicas, CONICET, 5000, Universidad Nacional de Córdoba, Córdoba, Argentina
| | - Yurena Morera
- Instituto Universitario de Neurociencia (IUNE), Universidad de La Laguna, Campus de Guajara, 38205 La Laguna, Santa Cruz de Tenerife, Spain
| | - Manuel de Vega
- Instituto Universitario de Neurociencia (IUNE), Universidad de La Laguna, Campus de Guajara, 38205 La Laguna, Santa Cruz de Tenerife, Spain
| | - Sebastian Moguilner
- Global Brain Health Institute, University of California, San Francisco, CA94158, US; and Trinity College, Dublin D02DP21, , Ireland.,Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibáñez, 8320000, Santiago, Chile
| | - Patricia Lillo
- Departamento de Neurología Sur, Facultad de Medicina, Universidad de Chile, 8380000, Santiago, Chile.,Unidad de Neurología, Hospital San José, 8380000, Santiago, Chile.,Geroscience Center for Brain Health and Metabolism (GERO), 7800003, Santiago, Chile
| | - Andrea Slachevsky
- Geroscience Center for Brain Health and Metabolism (GERO), 7800003, Santiago, Chile.,Neuropsychology and Clinical Neuroscience Laboratory (LANNEC), Physiopathology Department, Neuroscience and East Neuroscience Departments, Faculty of Medicine, Institute of Biomedical Sciences (ICBM), University of Chile, 8380000, Santiago, Chile.,Memory and Neuropsychiatric Clinic (CMYN) Neurology Department, Hospital del Salvador and Faculty of Medicine, University of Chile, 7500000, Santiago, Chile.,Departamento de Medicina, Servicio de Neurología, Clínica Alemana-Universidad del Desarrollo, 7550000, Santiago, Chile
| | - Cecilia González Campo
- Centro de Neurociencias Cognitivas, Universidad de San Andrés, Vito Dumas 284, Buenos Aires B1644BID, Argentina.,National Scientific and Technical Research Council (CONICET), C1425FQD, Godoy Cruz 2290, Buenos Aires, Argentina
| | - Agustín Ibáñez
- Centro de Neurociencias Cognitivas, Universidad de San Andrés, Vito Dumas 284, Buenos Aires B1644BID, Argentina.,National Scientific and Technical Research Council (CONICET), C1425FQD, Godoy Cruz 2290, Buenos Aires, Argentina.,Global Brain Health Institute, University of California, San Francisco, CA94158, US; and Trinity College, Dublin D02DP21, , Ireland.,Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibáñez, 8320000, Santiago, Chile
| | - Adolfo M García
- Centro de Neurociencias Cognitivas, Universidad de San Andrés, Vito Dumas 284, Buenos Aires B1644BID, Argentina.,National Scientific and Technical Research Council (CONICET), C1425FQD, Godoy Cruz 2290, Buenos Aires, Argentina.,Global Brain Health Institute, University of California, San Francisco, CA94158, US; and Trinity College, Dublin D02DP21, , Ireland.,Departamento de Lingüística y Literatura, Facultad de Humanidades, Universidad de Santiago de Chile, 7550000, Santiago, Chile
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16
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Notturno F, Croce P, Ornello R, Sacco S, Zappasodi F. Yield of EEG features as markers of disease severity in amyotrophic lateral sclerosis: a pilot study. Amyotroph Lateral Scler Frontotemporal Degener 2022; 24:295-303. [PMID: 37078278 DOI: 10.1080/21678421.2022.2152696] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
OBJECTIVE To clarify the role of electroencephalography (EEG) as a promising marker of severity in amyotrophic lateral sclerosis (ALS). We characterized the brain spatio-temporal patterns activity at rest by means of both spectral band powers and EEG microstates and correlated these features with clinical scores. METHODS Eyes closed EEG was acquired in 15 patients with ALS and spectral band power was calculated in frequency bands, defined on the basis of individual alpha frequency (IAF): delta-theta band (1-7 Hz); low alpha (IAF - 2 Hz - IAF); high alpha (IAF - IAF + 2 Hz); beta (13 - 25 Hz). EEG microstate metrics (duration, occurrence, and coverage) were also evaluated. Spectral band powers and microstate metrics were correlated with several clinical scores of disabilities and disease progression. As a control group, 15 healthy volunteers were enrolled. RESULTS The beta-band power in motor/frontal regions was higher in patients with higher disease burden, negatively correlated with clinical severity scores and positively correlated with disease progression. Overall microstate duration was longer and microstate occurrence was lower in patients than in controls. Longer duration was correlated with a worse clinical status. CONCLUSIONS Our results showed that beta-band power and microstate metrics may be good candidates of disease severity in ALS. Increased beta and longer microstate duration in clinically worse patients suggest a possible impairment of both motor and non-motor network activities to fast modify their status. This can be interpreted as an attempt in ALS patients to compensate the disability but resulting in an ineffective and probably maladaptive behavior.
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Affiliation(s)
| | - Pierpaolo Croce
- Department of Neuroscience, Imaging and Clinical Sciences, University “Gabriele d’Annunzio” of Chieti-Pescara, Chieti, Italy
- Behavioral Imaging and Neural Dynamics Center, University “Gabriele d’Annunzio” of Chieti–Pescara, Chieti, Italy
| | - Raffaele Ornello
- Department of Biotechnological and Applied Clinical Sciences, University of L'Aquila, L'Aquila, Italy, and
| | - Simona Sacco
- Department of Biotechnological and Applied Clinical Sciences, University of L'Aquila, L'Aquila, Italy, and
| | - Filippo Zappasodi
- Department of Neuroscience, Imaging and Clinical Sciences, University “Gabriele d’Annunzio” of Chieti-Pescara, Chieti, Italy
- Behavioral Imaging and Neural Dynamics Center, University “Gabriele d’Annunzio” of Chieti–Pescara, Chieti, Italy
- Institute for Advanced Biomedical Technologies, University “Gabriele d’Annunzio” of Chieti–Pescara, Chieti, Italy
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17
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Feldman EL, Goutman SA, Petri S, Mazzini L, Savelieff MG, Shaw PJ, Sobue G. Amyotrophic lateral sclerosis. Lancet 2022; 400:1363-1380. [PMID: 36116464 PMCID: PMC10089700 DOI: 10.1016/s0140-6736(22)01272-7] [Citation(s) in RCA: 225] [Impact Index Per Article: 112.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/08/2022] [Revised: 05/24/2022] [Accepted: 06/23/2022] [Indexed: 01/07/2023]
Abstract
Amyotrophic lateral sclerosis is a fatal CNS neurodegenerative disease. Despite intensive research, current management of amyotrophic lateral sclerosis remains suboptimal from diagnosis to prognosis. Recognition of the phenotypic heterogeneity of amyotrophic lateral sclerosis, global CNS dysfunction, genetic architecture, and development of novel diagnostic criteria is clarifying the spectrum of clinical presentation and facilitating diagnosis. Insights into the pathophysiology of amyotrophic lateral sclerosis, identification of disease biomarkers and modifiable risks, along with new predictive models, scales, and scoring systems, and a clinical trial pipeline of mechanism-based therapies, are changing the prognostic landscape. Although most recent advances have yet to translate into patient benefit, the idea of amyotrophic lateral sclerosis as a complex syndrome is already having tangible effects in the clinic. This Seminar will outline these insights and discuss the status of the management of amyotrophic lateral sclerosis for the general neurologist, along with future prospects that could improve care and outcomes for patients with amyotrophic lateral sclerosis.
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Affiliation(s)
- Eva L Feldman
- Department of Neurology, Michigan Medicine, University of Michigan, Ann Arbor, MI, USA.
| | - Stephen A Goutman
- Department of Neurology, Michigan Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Susanne Petri
- Department of Neurology, Hannover Medical School, Hannover, Germany
| | - Letizia Mazzini
- ALS Centre, Azienda Ospedaliero-Universitaria Maggiore della Carità, Novara, Italy; Department of Neurology, University of Piemonte Orientale, Novara, Italy
| | - Masha G Savelieff
- Department of Neurology, Michigan Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Pamela J Shaw
- Sheffield Institute for Translational Neuroscience (SITraN), University of Sheffield, Sheffield, UK
| | - Gen Sobue
- Department of Neurology, Aichi Medical University, Nagakute, Aichi, Japan
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18
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Siciliano L, Olivito G, Urbini N, Silveri MC, Leggio M. “Mens Sana in Corpore Sano”: The Emerging Link of Motor Reserve with Motor and Cognitive Abilities and Compensatory Brain Networks in SCA2 Patients. Biomedicines 2022; 10:biomedicines10092166. [PMID: 36140267 PMCID: PMC9496032 DOI: 10.3390/biomedicines10092166] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Revised: 08/30/2022] [Accepted: 08/30/2022] [Indexed: 11/16/2022] Open
Abstract
The ability to resiliently cope with neuropathological lesions is a key scientific concern. Accordingly, this study aims to investigate whether motor reserve (MR), likely to be boosted by exercise engagement in a lifetime, affects motor symptom severity, cognitive functioning, and functional brain networks in spinocerebellar ataxia type 2 (SCA2)—a cerebellar neurodegenerative disease. The MR of 12 SCA2 patients was assessed using the Motor Reserve Index Questionnaire (MRIq), developed ad hoc for estimating lifespan MR. The International Cooperative Ataxia Rating Scale was used to assess clinical motor features, and neuropsychological tests were used to evaluate cognitive functioning. Patients underwent an MRI examination, and network-based statistics (NBS) analysis was carried out to detect patterns of functional connectivity (FC). Significant correlations were found between MRIq measures and the severity of motor symptoms, educational and intellectual levels, executive function, and processing speed. NBS analysis revealed a higher FC within subnetworks consisting of specific cerebellar and cerebral areas. FC patterns were positively correlated with MRIq measures, likely indicating the identification of an MR network. The identified network might reflect a biomarker likely to underlie MR, influenced by education and cognitive functioning, and impacting the severity of motor symptoms.
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Affiliation(s)
- Libera Siciliano
- Department of Psychology, Sapienza University of Rome, 00185 Rome, Italy
- Ataxia Laboratory, Fondazione Santa Lucia IRCCS, 00179 Rome, Italy
| | - Giusy Olivito
- Department of Psychology, Sapienza University of Rome, 00185 Rome, Italy
- Ataxia Laboratory, Fondazione Santa Lucia IRCCS, 00179 Rome, Italy
| | - Nicole Urbini
- Department of Psychology, Sapienza University of Rome, 00185 Rome, Italy
- Ataxia Laboratory, Fondazione Santa Lucia IRCCS, 00179 Rome, Italy
| | | | - Maria Leggio
- Department of Psychology, Sapienza University of Rome, 00185 Rome, Italy
- Ataxia Laboratory, Fondazione Santa Lucia IRCCS, 00179 Rome, Italy
- Correspondence:
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19
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Romano A, Trosi Lopez E, Liparoti M, Polverino A, Minino R, Trojsi F, Bonavita S, Mandolesi L, Granata C, Amico E, Sorrentino G, Sorrentino P. The progressive loss of brain network fingerprints in Amyotrophic Lateral Sclerosis predicts clinical impairment. Neuroimage Clin 2022; 35:103095. [PMID: 35764029 PMCID: PMC9241102 DOI: 10.1016/j.nicl.2022.103095] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2022] [Revised: 05/31/2022] [Accepted: 06/19/2022] [Indexed: 10/25/2022]
Abstract
Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease characterised by functional connectivity alterations in both motor and extra-motor brain regions. Within the framework of network analysis, fingerprinting represents a reliable approach to assess subject-specific connectivity features within a given population (healthy or diseased). Here, we applied the Clinical Connectome Fingerprint (CCF) analysis to source-reconstructed magnetoencephalography (MEG) signals in a cohort of seventy-eight subjects: thirty-nine ALS patients and thirty-nine healthy controls. We set out to develop an identifiability matrix to assess the extent to which each patient was recognisable based on his/her connectome, as compared to healthy controls. The analysis was performed in the five canonical frequency bands. Then, we built a multilinear regression model to test the ability of the "clinical fingerprint" to predict the clinical evolution of the disease, as assessed by the Amyotrophic Lateral Sclerosis Functional Rating Scale-Revised (ALSFRS-r), the King's disease staging system, and the Milano-Torino Staging (MiToS) disease staging system. We found a drop in the identifiability of patients in the alpha band compared to the healthy controls. Furthermore, the "clinical fingerprint" was predictive of the ALSFRS-r (p = 0.0397; β = 32.8), the King's (p = 0.0001; β = -7.40), and the MiToS (p = 0.0025; β = -4.9) scores. Accordingly, it negatively correlated with the King's (Spearman's rho = -0.6041, p = 0.0003) and MiToS scales (Spearman's rho = -0.4953, p = 0.0040). Our results demonstrated the ability of the CCF approach to predict the individual motor impairment in patients affected by ALS. Given the subject-specificity of our approach, we hope to further exploit it to improve disease management.
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Affiliation(s)
- Antonella Romano
- Department of Motor Sciences and Wellness - University of Naples "Parthenope", via Medina 40, 80133 Naples, Italy
| | - Emahnuel Trosi Lopez
- Department of Motor Sciences and Wellness - University of Naples "Parthenope", via Medina 40, 80133 Naples, Italy
| | - Marianna Liparoti
- Department of Social and Developmental Psychology, University of Rome "Sapienza", Italy
| | - Arianna Polverino
- Institute of Diagnosis and Treatment Hermitage Capodimonte, via Cupa delle Tozzole 2, 80131 Naples, Italy
| | - Roberta Minino
- Department of Motor Sciences and Wellness - University of Naples "Parthenope", via Medina 40, 80133 Naples, Italy
| | - Francesca Trojsi
- Department of Advanced Medical and Surgical Sciences, Division of Neurology, University of Campania "Luigi Vanvitelli", Naples, Italy
| | - Simona Bonavita
- Department of Advanced Medical and Surgical Sciences, Division of Neurology, University of Campania "Luigi Vanvitelli", Naples, Italy
| | - Laura Mandolesi
- Department of Humanistic Studies, University of Naples Federico II, via Porta di Massa 1, 80133, Naples, Italy
| | - Carmine Granata
- Institute of Applied Sciences and Intelligent Systems, CNR, via Campi Flegrei 34, 80078 Pozzuoli, NA, Italy
| | - Enrico Amico
- Institute of Bioengineering, Center for Neuroprosthetics, EPFL, Geneva, Switzerland; Department of Radiology and Medical Informatics, University of Geneva (UNIGE), Geneva, Switzerland
| | - Giuseppe Sorrentino
- Department of Motor Sciences and Wellness - University of Naples "Parthenope", via Medina 40, 80133 Naples, Italy; Institute of Diagnosis and Treatment Hermitage Capodimonte, via Cupa delle Tozzole 2, 80131 Naples, Italy; Institute of Applied Sciences and Intelligent Systems, CNR, via Campi Flegrei 34, 80078 Pozzuoli, NA, Italy.
| | - Pierpaolo Sorrentino
- Institute of Applied Sciences and Intelligent Systems, CNR, via Campi Flegrei 34, 80078 Pozzuoli, NA, Italy; Institut de Neurosciences des Systèmes, Aix-Marseille Université, Marseille, France
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20
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McKenna MC, Tahedl M, Lope J, Chipika RH, Li Hi Shing S, Doherty MA, Hengeveld JC, Vajda A, McLaughlin RL, Hardiman O, Hutchinson S, Bede P. Mapping cortical disease-burden at individual-level in frontotemporal dementia: implications for clinical care and pharmacological trials. Brain Imaging Behav 2022; 16:1196-1207. [PMID: 34882275 PMCID: PMC9107414 DOI: 10.1007/s11682-021-00523-7] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/20/2021] [Indexed: 01/25/2023]
Abstract
Imaging studies of FTD typically present group-level statistics between large cohorts of genetically, molecularly or clinically stratified patients. Group-level statistics are indispensable to appraise unifying radiological traits and describe genotype-associated signatures in academic studies. However, in a clinical setting, the primary objective is the meaningful interpretation of imaging data from individual patients to assist diagnostic classification, inform prognosis, and enable the assessment of progressive changes compared to baseline scans. In an attempt to address the pragmatic demands of clinical imaging, a prospective computational neuroimaging study was undertaken in a cohort of patients across the spectrum of FTD phenotypes. Cortical changes were evaluated in a dual pipeline, using standard cortical thickness analyses and an individualised, z-score based approach to characterise subject-level disease burden. Phenotype-specific patterns of cortical atrophy were readily detected with both methodological approaches. Consistent with their clinical profiles, patients with bvFTD exhibited orbitofrontal, cingulate and dorsolateral prefrontal atrophy. Patients with ALS-FTD displayed precentral gyrus involvement, nfvPPA patients showed widespread cortical degeneration including insular and opercular regions and patients with svPPA exhibited relatively focal anterior temporal lobe atrophy. Cortical atrophy patterns were reliably detected in single individuals, and these maps were consistent with the clinical categorisation. Our preliminary data indicate that standard T1-weighted structural data from single patients may be utilised to generate maps of cortical atrophy. While the computational interpretation of single scans is challenging, it offers unrivalled insights compared to visual inspection. The quantitative evaluation of individual MRI data may aid diagnostic classification, clinical decision making, and assessing longitudinal changes.
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Affiliation(s)
- Mary Clare McKenna
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland
| | - Marlene Tahedl
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland
- Department of Psychiatry and Psychotherapy, University of Regensburg, Regensburg, Germany
- Institute for Psychology, University of Regensburg, Regensburg, Germany
| | - Jasmin Lope
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland
| | - Rangariroyashe H Chipika
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland
| | - Stacey Li Hi Shing
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland
| | - Mark A Doherty
- Complex Trait Genomics Laboratory, Smurfit Institute of Genetics, Trinity College Dublin, Dublin, Ireland
| | - Jennifer C Hengeveld
- Complex Trait Genomics Laboratory, Smurfit Institute of Genetics, Trinity College Dublin, Dublin, Ireland
| | - Alice Vajda
- Complex Trait Genomics Laboratory, Smurfit Institute of Genetics, Trinity College Dublin, Dublin, Ireland
| | - Russell L McLaughlin
- Complex Trait Genomics Laboratory, Smurfit Institute of Genetics, Trinity College Dublin, Dublin, Ireland
| | - Orla Hardiman
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland
| | | | - Peter Bede
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland.
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21
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Govaarts R, Beeldman E, Fraschini M, Griffa A, Engels MMA, van Es MA, Veldink JH, van den Berg LH, van der Kooi AJ, Pijnenburg YAL, de Visser M, Stam CJ, Raaphorst J, Hillebrand A. Cortical and subcortical changes in resting-state neuronal activity and connectivity in early symptomatic ALS and advanced frontotemporal dementia. Neuroimage Clin 2022; 34:102965. [PMID: 35217500 PMCID: PMC8867127 DOI: 10.1016/j.nicl.2022.102965] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Revised: 02/08/2022] [Accepted: 02/09/2022] [Indexed: 01/17/2023]
Abstract
The objective of this study was to examine if patterns of resting-state brain activity and functional connectivity in cortical and subcortical regions in patients with early symptomatic amyotrophic lateral sclerosis (ALS) resemble those of behavioural variant frontotemporal dementia (bvFTD). In a cross-sectional design, eyes-closed resting-state magnetoencephalography (MEG) data of 34 ALS patients, 18 bvFTD patients and 18 age- and gender-matched healthy controls (HCs) were projected to source-space using an atlas-based beamformer. Group differences in peak frequency, band-specific oscillatory activity and functional connectivity (corrected amplitude envelope correlation) in 78 cortical regions and 12 subcortical regions were determined. False discovery rate was used to correct for multiple comparisons. BvFTD patients, as compared to ALS and HCs, showed lower relative beta power in parietal, occipital, temporal and nearly all subcortical regions. Compared to HCs, patients with ALS and patients with bvFTD had a higher delta (0.5-4 Hz) and gamma (30-48 Hz) band resting-state functional connectivity in a high number of overlapping regions in the frontal lobe and in limbic and subcortical regions. Higher delta band connectivity was widespread in the bvFTD patients compared to HCs. ALS showed a more widespread higher gamma band functional connectivity compared to bvFTD. In conclusion, MEG in early symptomatic ALS patients shows resting-state functional connectivity changes in frontal, limbic and subcortical regions that overlap considerably with bvFTD. The findings show the potential of MEG to detect brain changes in early symptomatic phases of ALS and contribute to our understanding of the disease spectrum, with ALS and bvFTD at the two extreme ends.
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Affiliation(s)
- Rosanne Govaarts
- Amsterdam University Medical Centers, University of Amsterdam, Department of Neurology, Amsterdam Neuroscience, Amsterdam, the Netherlands.
| | - Emma Beeldman
- Amsterdam University Medical Centers, University of Amsterdam, Department of Neurology, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Matteo Fraschini
- University of Cagliari, Department of Electrical and Electronic Engineering, Cagliari, Italy
| | - Alessandra Griffa
- Department of Clinical Neurosciences, Division of Neurology, Geneva University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland; Institute of Bioengineering, Center of Neuroprosthetics, École Polytechnique Fédérale De Lausanne (EPFL), Geneva, Switzerland
| | - Marjolein M A Engels
- Amsterdam University Medical Centers, Vrije Universiteit Amsterdam, Department of Clinical Neurophysiology, Magnetoencephalography Centre, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Michael A van Es
- University Medical Centre Utrecht, Department of Neurology, Brain Centre Rudolf Magnus, Utrecht, the Netherlands
| | - Jan H Veldink
- University Medical Centre Utrecht, Department of Neurology, Brain Centre Rudolf Magnus, Utrecht, the Netherlands
| | - Leonard H van den Berg
- University Medical Centre Utrecht, Department of Neurology, Brain Centre Rudolf Magnus, Utrecht, the Netherlands
| | - Anneke J van der Kooi
- Amsterdam University Medical Centers, University of Amsterdam, Department of Neurology, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Yolande A L Pijnenburg
- Amsterdam University Medical Centers, Vrije Universiteit, Alzheimer Center, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Marianne de Visser
- Amsterdam University Medical Centers, University of Amsterdam, Department of Neurology, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Cornelis J Stam
- Amsterdam University Medical Centers, Vrije Universiteit Amsterdam, Department of Clinical Neurophysiology, Magnetoencephalography Centre, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Joost Raaphorst
- Amsterdam University Medical Centers, University of Amsterdam, Department of Neurology, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Arjan Hillebrand
- Amsterdam University Medical Centers, Vrije Universiteit Amsterdam, Department of Clinical Neurophysiology, Magnetoencephalography Centre, Amsterdam Neuroscience, Amsterdam, the Netherlands
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22
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Goutman SA, Hardiman O, Al-Chalabi A, Chió A, Savelieff MG, Kiernan MC, Feldman EL. Recent advances in the diagnosis and prognosis of amyotrophic lateral sclerosis. Lancet Neurol 2022; 21:480-493. [PMID: 35334233 PMCID: PMC9513753 DOI: 10.1016/s1474-4422(21)00465-8] [Citation(s) in RCA: 124] [Impact Index Per Article: 62.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2021] [Revised: 11/24/2021] [Accepted: 12/16/2021] [Indexed: 12/14/2022]
Abstract
The diagnosis of amyotrophic lateral sclerosis can be challenging due to its heterogeneity in clinical presentation and overlap with other neurological disorders. Diagnosis early in the disease course can improve outcomes as timely interventions can slow disease progression. An evolving awareness of disease genotypes and phenotypes and new diagnostic criteria, such as the recent Gold Coast criteria, could expedite diagnosis. Improved prognosis, such as that achieved with the survival model from the European Network for the Cure of ALS, could inform the patient and their family about disease course and improve end-of-life planning. Novel staging and scoring systems can help monitor disease progression and might potentially serve as clinical trial outcomes. Lastly, new tools, such as fluid biomarkers, imaging modalities, and neuromuscular electrophysiological measurements, might increase diagnostic and prognostic accuracy.
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Affiliation(s)
| | - Orla Hardiman
- Academic Unit of Neurology, Trinity Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland
| | - Ammar Al-Chalabi
- Department of Basic and Clinical Neuroscience, Maurice Wohl Clinical Neuroscience Institute, and Department of Neurology, King's College London, London, UK
| | - Adriano Chió
- Rita Levi Montalcini Department of Neurosciences, University of Turin, Turin, Italy
| | | | - Matthew C Kiernan
- Brain and Mind Centre, University of Sydney, Sydney, NSW, Australia; Department of Neurology, Royal Prince Alfred Hospital, Sydney, NSW, Australia
| | - Eva L Feldman
- Department of Neurology, University of Michigan, Ann Arbor, MI, USA.
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23
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Shi JY, Cai LM, Lin JH, Zou ZY, Zhang XH, Chen HJ. Dynamic Alterations in Functional Connectivity Density in Amyotrophic Lateral Sclerosis: A Resting-State Functional Magnetic Resonance Imaging Study. Front Aging Neurosci 2022; 14:827500. [PMID: 35370623 PMCID: PMC8967369 DOI: 10.3389/fnagi.2022.827500] [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: 12/02/2021] [Accepted: 02/14/2022] [Indexed: 11/13/2022] Open
Abstract
Background and Aims Current knowledge on the temporal dynamics of the brain functional organization in amyotrophic lateral sclerosis (ALS) is limited. This is the first study on alterations in the patterns of dynamic functional connection density (dFCD) involving ALS. Methods We obtained resting-state functional magnetic resonance imaging (fMRI) data from 50 individuals diagnosed with ALS and 55 healthy controls (HCs). We calculated the functional connectivity (FC) between a given voxel and all other voxels within the entire brain and yield the functional connection density (FCD) value per voxel. dFCD was assessed by sliding window correlation method. In addition, the standard deviation (SD) of dFCD across the windows was computed voxel-wisely to measure dFCD variability. The difference in dFCD variability between the two groups was compared using a two-sample t-test following a voxel-wise manner. The receiver operating characteristic (ROC) curve was used to assess the between-group recognition performance of the dFCD variability index. Results The dFCD variability was significantly reduced in the bilateral precentral and postcentral gyrus compared with the HC group, whereas a marked increase was observed in the left middle frontal gyrus of ALS patients. dFCD variability exhibited moderate potential (areas under ROC curve = 0.753–0.837, all P < 0.001) in distinguishing two groups. Conclusion ALS patients exhibit aberrant dynamic property in brain functional architecture. The dFCD evaluation improves our understanding of the pathological mechanisms underlying ALS and may assist in its diagnosis.
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Affiliation(s)
- Jia-Yan Shi
- Department of Radiology, Fujian Medical University Union Hospital, Fuzhou, China
| | - Li-Min Cai
- Department of Radiology, Fujian Medical University Union Hospital, Fuzhou, China
| | - Jia-Hui Lin
- Department of Radiology, Fujian Medical University Union Hospital, Fuzhou, China
| | - Zhang-Yu Zou
- Department of Neurology, Fujian Medical University Union Hospital, Fuzhou, China
| | - Xiao-Hong Zhang
- Department of Radiology, Fujian Medical University Union Hospital, Fuzhou, China
| | - Hua-Jun Chen
- Department of Radiology, Fujian Medical University Union Hospital, Fuzhou, China
- *Correspondence: Hua-Jun Chen,
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24
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Brain Connectivity and Network Analysis in Amyotrophic Lateral Sclerosis. Neurol Res Int 2022; 2022:1838682. [PMID: 35178253 PMCID: PMC8844436 DOI: 10.1155/2022/1838682] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2021] [Accepted: 01/13/2022] [Indexed: 12/11/2022] Open
Abstract
Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease with no effective treatment or cure. ALS is characterized by the death of lower motor neurons (LMNs) in the spinal cord and upper motor neurons (UMNs) in the brain and their networks. Since the lower motor neurons are under the control of UMN and the networks, cortical degeneration may play a vital role in the pathophysiology of ALS. These changes that are not apparent on routine imaging with CT scans or MRI brain can be identified using modalities such as diffusion tensor imaging, functional MRI, arterial spin labelling (ASL), electroencephalogram (EEG), magnetoencephalogram (MEG), functional near-infrared spectroscopy (fNIRS), and positron emission tomography (PET) scan. They can help us generate a representation of brain networks and connectivity that can be visualized and parsed out to characterize and quantify the underlying pathophysiology in ALS. In addition, network analysis using graph measures provides a novel way of understanding the complex network changes occurring in the brain. These have the potential to become biomarker for the diagnosis and treatment of ALS. This article is a systematic review and overview of the various connectivity and network-based studies in ALS.
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25
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McKenna MC, Tahedl M, Murad A, Lope J, Hardiman O, Hutchinson S, Bede P. White matter microstructure alterations in frontotemporal dementia: Phenotype-associated signatures and single-subject interpretation. Brain Behav 2022; 12:e2500. [PMID: 35072974 PMCID: PMC8865163 DOI: 10.1002/brb3.2500] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Revised: 11/22/2021] [Accepted: 01/01/2022] [Indexed: 12/26/2022] Open
Abstract
BACKGROUND Frontotemporal dementias (FTD) include a genetically heterogeneous group of conditions with distinctive molecular, radiological and clinical features. The majority of radiology studies in FTD compare FTD subgroups to healthy controls to describe phenotype- or genotype-associated imaging signatures. While the characterization of group-specific imaging traits is academically important, the priority of clinical imaging is the meaningful interpretation of individual datasets. METHODS To demonstrate the feasibility of single-subject magnetic resonance imaging (MRI) interpretation, we have evaluated the white matter profile of 60 patients across the clinical spectrum of FTD. A z-score-based approach was implemented, where the diffusivity metrics of individual patients were appraised with reference to demographically matched healthy controls. Fifty white matter tracts were systematically evaluated in each subject with reference to normative data. RESULTS The z-score-based approach successfully detected white matter pathology in single subjects, and group-level inferences were analogous to the outputs of standard track-based spatial statistics. CONCLUSIONS Our findings suggest that it is possible to meaningfully evaluate the diffusion profile of single FTD patients if large normative datasets are available. In contrast to the visual review of FLAIR and T2-weighted images, computational imaging offers objective, quantitative insights into white matter integrity changes even at single-subject level.
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Affiliation(s)
- Mary Clare McKenna
- Computational Neuroimaging Group, Trinity College Dublin, Dublin, Ireland
| | - Marlene Tahedl
- Computational Neuroimaging Group, Trinity College Dublin, Dublin, Ireland
| | - Aizuri Murad
- Computational Neuroimaging Group, Trinity College Dublin, Dublin, Ireland
| | - Jasmin Lope
- Computational Neuroimaging Group, Trinity College Dublin, Dublin, Ireland
| | - Orla Hardiman
- Computational Neuroimaging Group, Trinity College Dublin, Dublin, Ireland
| | | | - Peter Bede
- Computational Neuroimaging Group, Trinity College Dublin, Dublin, Ireland.,Department of Neurology, St James's Hospital, Dublin, Ireland
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26
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Finegan E, Siah WF, Li Hi Shing S, Chipika RH, Hardiman O, Bede P. Cerebellar degeneration in primary lateral sclerosis: an under-recognized facet of PLS. Amyotroph Lateral Scler Frontotemporal Degener 2022; 23:542-553. [PMID: 34991421 DOI: 10.1080/21678421.2021.2023188] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/01/2022]
Abstract
While primary lateral sclerosis (PLS) has traditionally been regarded as a pure upper motor neuron disorder, recent clinical, neuroimaging and postmortem studies have confirmed significant extra-motor involvement. Sporadic reports have indicated that in addition to the motor cortex and corticospinal tracts, the cerebellum may also be affected in PLS. Cerebellar manifestations are difficult to ascertain in PLS as the clinical picture is dominated by widespread upper motor neuron signs. The likely contribution of cerebellar dysfunction to gait disturbance, falls, pseudobulbar affect and dysarthria may be overlooked in the context of progressive spasticity. The objective of this study is the comprehensive characterization of cerebellar gray and white matter degeneration in PLS using multiparametric quantitative neuroimaging methods to systematically evaluate each cerebellar lobule and peduncle. Forty-two patients with PLS and 117 demographically-matched healthy controls were enrolled in a prospective MRI study. Complementary volumetric and voxelwise analyses revealed focal cerebellar alterations instead of global cerebellar atrophy. Bilateral gray matter volume reductions were observed in lobules III, IV and VIIb. Significant diffusivity alterations within the superior cerebellar peduncle indicate disruption of the main cerebellar outflow tracts. These findings suggest that the considerable intra-cerebellar disease-burden is coupled with concomitant cerebro-cerebellar connectivity disruptions. While cerebellar dysfunction is challenging to demonstrate clinically, cerebellar pathology is likely to be a significant contributor to disability in PLS.
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Affiliation(s)
- Eoin Finegan
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland
| | - We Fong Siah
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland
| | - Stacey Li Hi Shing
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland
| | - Rangariroyashe H Chipika
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland
| | - Orla Hardiman
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland
| | - Peter Bede
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland.,Department of Neurology, St James's Hospital Dublin, Dublin, Ireland
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27
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Pasniceanu IS, Atwal MS, Souza CDS, Ferraiuolo L, Livesey MR. Emerging Mechanisms Underpinning Neurophysiological Impairments in C9ORF72 Repeat Expansion-Mediated Amyotrophic Lateral Sclerosis/Frontotemporal Dementia. Front Cell Neurosci 2022; 15:784833. [PMID: 34975412 PMCID: PMC8715728 DOI: 10.3389/fncel.2021.784833] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Accepted: 11/10/2021] [Indexed: 12/15/2022] Open
Abstract
Amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) are characterized by degeneration of upper and lower motor neurons and neurons of the prefrontal cortex. The emergence of the C9ORF72 hexanucleotide repeat expansion mutation as the leading genetic cause of ALS and FTD has led to a progressive understanding of the multiple cellular pathways leading to neuronal degeneration. Disturbances in neuronal function represent a major subset of these mechanisms and because such functional perturbations precede degeneration, it is likely that impaired neuronal function in ALS/FTD plays an active role in pathogenesis. This is supported by the fact that ALS/FTD patients consistently present with neurophysiological impairments prior to any apparent degeneration. In this review we summarize how the discovery of the C9ORF72 repeat expansion mutation has contributed to the current understanding of neuronal dysfunction in ALS/FTD. Here, we discuss the impact of the repeat expansion on neuronal function in relation to intrinsic excitability, synaptic, network and ion channel properties, highlighting evidence of conserved and divergent pathophysiological impacts between cortical and motor neurons and the influence of non-neuronal cells. We further highlight the emerging association between these dysfunctional properties with molecular mechanisms of the C9ORF72 mutation that appear to include roles for both, haploinsufficiency of the C9ORF72 protein and aberrantly generated dipeptide repeat protein species. Finally, we suggest that relating key pathological observations in C9ORF72 repeat expansion ALS/FTD patients to the mechanistic impact of the C9ORF72 repeat expansion on neuronal function will lead to an improved understanding of how neurophysiological dysfunction impacts upon pathogenesis.
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Affiliation(s)
- Iris-Stefania Pasniceanu
- Sheffield Institute for Translational Neuroscience, University of Sheffield, Sheffield, United Kingdom
| | - Manpreet Singh Atwal
- Sheffield Institute for Translational Neuroscience, University of Sheffield, Sheffield, United Kingdom
| | - Cleide Dos Santos Souza
- Sheffield Institute for Translational Neuroscience, University of Sheffield, Sheffield, United Kingdom
| | - Laura Ferraiuolo
- Sheffield Institute for Translational Neuroscience, University of Sheffield, Sheffield, United Kingdom
| | - Matthew R Livesey
- Sheffield Institute for Translational Neuroscience, University of Sheffield, Sheffield, United Kingdom
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28
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Panopoulou N, Christidi F, Kourtesis P, Ferentinos P, Karampetsou P, Tsirtsiridis G, Theodosiou T, Xirou S, Zouvelou V, Evdokimidis I, Rentzos M, Zalonis I. The association of theory of mind with language and visuospatial abilities in amyotrophic lateral sclerosis: a pilot study. Amyotroph Lateral Scler Frontotemporal Degener 2021; 23:462-469. [PMID: 34907827 DOI: 10.1080/21678421.2021.2013893] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Abstract
Objective: Dysfunction of social cognition is well-recognized as one of amyotrophic lateral sclerosis (ALS) cognitive impairments. Previous studies have mostly associated social cognition subcomponents, including Theory of Mind (ToM), with executive dysfunction using highly-demanding tasks. In the present study, we investigate dysfunction of affective ToM in a sample of ALS patients without dementia and evaluate any possible associations both with executive and non-executive dysfunction.Methods: We included 42 ALS patients and 30 healthy controls (HC) and administered the Edinburgh Cognitive and Behavioral Amyotrophic Lateral Sclerosis Screen (ECAS). Affective ToM was examined based on the ECAS judgment of preference task; total score and type of errors ("favourite", "unclassified") were recorded for all participants.Results: A significant proportion of ALS patients (31%) were impaired on ToM task, scoring significantly lower compared to HC. Impairments in ToM task were more frequent (45%) in patients with cognitive impairment compared to those with intact cognition (15%). ALS patients showed significantly more errors on ToM task compared to HC. A significant association was found between ToM score and ECAS language and visuospatial abilities but not fluency, executive or memory function.Conclusion: Dysfunction of affective ToM appears prevalent in ALS patients without dementia, and associates with language and visuospatial abilities. These associations align with motor and extra-motor symptoms due to the degeneration across corresponding networks. Impaired ToM should be considered in clinical settings, since it might contribute to patients' social life, as well as the burden of their caregivers and relatives.
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Affiliation(s)
- Niki Panopoulou
- Neuropsychological Laboratory, First Department of Neurology, Aeginition Hospital, Medical School, National and Kapodistrian University of Athens, Athens, Greece
| | - Foteini Christidi
- Neuropsychological Laboratory, First Department of Neurology, Aeginition Hospital, Medical School, National and Kapodistrian University of Athens, Athens, Greece.,First Department of Neurology, Aeginition Hospital, Medical School, National and Kapodistrian University of Athens, Athens, Greece.,Second Department of Psychiatry, Attikon General University Hospital, Medical School, National and Kapodistrian University of Athens, Athens, Greece.,Laboratory of Medical Physics, Medical School, National and Kapodistrian University of Athens, Athens, Greece
| | - Panagiotis Kourtesis
- National Research Institute of Computer Science and Automation, INRIA, Rennes, France.,Univ Rennes, Rennes, France.,Research Institute of Computer Science and Random Systems, IRISA, Rennes, France, and.,French National Centre for Scientific Research, CNRS, Rennes, France
| | - Panagiotis Ferentinos
- Second Department of Psychiatry, Attikon General University Hospital, Medical School, National and Kapodistrian University of Athens, Athens, Greece
| | - Panagiota Karampetsou
- Neuropsychological Laboratory, First Department of Neurology, Aeginition Hospital, Medical School, National and Kapodistrian University of Athens, Athens, Greece
| | - Georgios Tsirtsiridis
- Neuropsychological Laboratory, First Department of Neurology, Aeginition Hospital, Medical School, National and Kapodistrian University of Athens, Athens, Greece
| | - Thomas Theodosiou
- Neuropsychological Laboratory, First Department of Neurology, Aeginition Hospital, Medical School, National and Kapodistrian University of Athens, Athens, Greece
| | - Sofia Xirou
- First Department of Neurology, Aeginition Hospital, Medical School, National and Kapodistrian University of Athens, Athens, Greece
| | - Vasiliki Zouvelou
- First Department of Neurology, Aeginition Hospital, Medical School, National and Kapodistrian University of Athens, Athens, Greece
| | - Ioannis Evdokimidis
- First Department of Neurology, Aeginition Hospital, Medical School, National and Kapodistrian University of Athens, Athens, Greece
| | - Michail Rentzos
- First Department of Neurology, Aeginition Hospital, Medical School, National and Kapodistrian University of Athens, Athens, Greece
| | - Ioannis Zalonis
- Neuropsychological Laboratory, First Department of Neurology, Aeginition Hospital, Medical School, National and Kapodistrian University of Athens, Athens, Greece
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Tahedl M, Li Hi Shing S, Finegan E, Chipika RH, Lope J, Murad A, Hardiman O, Bede P. Imaging data reveal divergent longitudinal trajectories in PLS, ALS and poliomyelitis survivors: Group-level and single-subject traits. Data Brief 2021; 39:107484. [PMID: 34901337 PMCID: PMC8640870 DOI: 10.1016/j.dib.2021.107484] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2021] [Revised: 09/28/2021] [Accepted: 10/11/2021] [Indexed: 01/02/2023] Open
Abstract
Imaging profiles from a longitudinal single-centre motor neuron disease study are presented. A standardized T1-weighted MRI protocol was implemented to characterise cortical disease burden trajectories across the UMN (upper motor neuron) - LMN (lower motor neuron) spectrum of motor neuron diseases (MNDs) (Tahedl et al., 2021). Patients with amyotrophic lateral sclerosis (ALS n = 61), patients with primary lateral sclerosis (PLS n = 23) and poliomyelitis survivors (PMS n = 45) were included. Up to four longitudinal scans were available for each patient, separated by an inter-scan-interval of four months. Individual and group-level cortical thickness profiles were appraised using a normalisation procedure with reference to subject-specific control groups. A z-scoring approach was utilised, where each patients' cortex was first segmented into 1000 cortical regions, and then rated as 'thin', 'thick', or 'comparable' to the corresponding region of a demographically-matched control cohort. Fractions of significantly 'thin' and 'thick' patches were calculated across the entire cerebral vertex as well as in specific brain regions, such as the motor cortex, parietal, frontal and temporal cortices. This approach allows the characterisation of disease burden in individual subjects as well as at a group-level, both cross-sectionally and longitudinally. The presented framework may aid the interpretation of individual cortical disease burden in other patient cohorts.
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Affiliation(s)
- Marlene Tahedl
- Computational Neuroimaging Group, Trinity Biomedical Sciences Institute, Trinity College Dublin, Pearse Street Room 5.43, Dublin, Ireland.,Department of Psychiatry and Psychotherapy and Institute for Psychology, University of Regensburg, Germany
| | - Stacey Li Hi Shing
- Computational Neuroimaging Group, Trinity Biomedical Sciences Institute, Trinity College Dublin, Pearse Street Room 5.43, Dublin, Ireland
| | - Eoin Finegan
- Computational Neuroimaging Group, Trinity Biomedical Sciences Institute, Trinity College Dublin, Pearse Street Room 5.43, Dublin, Ireland
| | - Rangariroyashe H Chipika
- Computational Neuroimaging Group, Trinity Biomedical Sciences Institute, Trinity College Dublin, Pearse Street Room 5.43, Dublin, Ireland
| | - Jasmin Lope
- Computational Neuroimaging Group, Trinity Biomedical Sciences Institute, Trinity College Dublin, Pearse Street Room 5.43, Dublin, Ireland
| | - Aizuri Murad
- Computational Neuroimaging Group, Trinity Biomedical Sciences Institute, Trinity College Dublin, Pearse Street Room 5.43, Dublin, Ireland
| | - Orla Hardiman
- Computational Neuroimaging Group, Trinity Biomedical Sciences Institute, Trinity College Dublin, Pearse Street Room 5.43, Dublin, Ireland
| | - Peter Bede
- Computational Neuroimaging Group, Trinity Biomedical Sciences Institute, Trinity College Dublin, Pearse Street Room 5.43, Dublin, Ireland.,Pitié-Salpêtrière University Hospital, Sorbonne University, Paris, France
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30
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Li Hi Shing S, Bede P. The neuroradiology of upper motor neuron degeneration: PLS, HSP, ALS. Amyotroph Lateral Scler Frontotemporal Degener 2021; 23:1-3. [PMID: 34894929 DOI: 10.1080/21678421.2021.1951293] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Affiliation(s)
- Stacey Li Hi Shing
- Computational Neuroimaging Group, Trinity College Dublin, Dublin, Ireland
| | - Peter Bede
- Computational Neuroimaging Group, Trinity College Dublin, Dublin, Ireland
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31
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Eisen A, Bede P. The strength of corticomotoneuronal drive underlies ALS split phenotypes and reflects early upper motor neuron dysfunction. Brain Behav 2021; 11:e2403. [PMID: 34710283 PMCID: PMC8671797 DOI: 10.1002/brb3.2403] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/05/2021] [Revised: 09/02/2021] [Accepted: 10/05/2021] [Indexed: 01/06/2023] Open
Abstract
BACKGROUND Split phenotypes, (split hand, elbow, leg, and foot), are probably unique to ALS, and are characterized by having a shared peripheral input of both affected and unaffected muscles. This implies an anatomical origin rostral to the spinal cord, primarily within the cerebral cortex. Therefore, split phenotypes are a potential marker of ALS upper motor neuron pathology. However, to date, reports documenting upper motor neuron dysfunction in split phenotypes have been limited to using transcranial magnetic stimulation and cortical threshold tracking techniques. Here, we consider several other potential methodologies that could confirm a primary upper motor neuron pathology in split phenotypes. METHODS We review the potential of: 1. measuring the compound excitatory post-synaptic potential recorded from a single activated motor unit, 2. cortical-muscular coherence, and 3. new advanced modalities of neuroimaging (high-resolution imaging protocols, ultra-high field MRI platforms [7T], and novel Non-Gaussian diffusion models). CONCLUSIONS We propose that muscles involved in split phenotypes are those functionally involved in the human motor repertoire used particularly in complex activities. Their anterior horn cells receive the strongest corticomotoneuronal input. This is also true of the weakest muscles that are the earliest to be affected in ALS. Descriptions of split hand in non-ALS cases and proposals that peripheral nerve or muscle dysfunction may be causative are contentious. Only a few carefully controlled cases of each form of split phenotype, using upper motor neuron directed methodologies, are necessary to prove our postulate.
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Affiliation(s)
- Andrew Eisen
- Division of Neurology, Department of Medicine, University of British Columbia, British Columbia, Canada
| | - Peter Bede
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland.,Pitié-Salpêtrière University Hospital, Sorbonne University, Paris, France
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32
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Dukic S, McMackin R, Costello E, Metzger M, Buxo T, Fasano A, Chipika R, Pinto-Grau M, Schuster C, Hammond M, Heverin M, Coffey A, Broderick M, Iyer PM, Mohr K, Gavin B, McLaughlin R, Pender N, Bede P, Muthuraman M, van den Berg L, Hardiman O, Nasseroleslami B. Resting-state EEG reveals four subphenotypes of amyotrophic lateral sclerosis. Brain 2021; 145:621-631. [PMID: 34791079 PMCID: PMC9014749 DOI: 10.1093/brain/awab322] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2021] [Revised: 06/25/2021] [Accepted: 07/26/2021] [Indexed: 11/14/2022] Open
Abstract
Amyotrophic lateral sclerosis is a devastating disease characterized primarily by motor system degeneration, with clinical evidence of cognitive and behavioural change in up to 50% of cases. Amyotrophic lateral sclerosis is both clinically and biologically heterogeneous. Subgrouping is currently undertaken using clinical parameters, such as site of symptom onset (bulbar or spinal), burden of disease (based on the modified El Escorial Research Criteria) and genomics in those with familial disease. However, with the exception of genomics, these subcategories do not take into account underlying disease pathobiology, and are not fully predictive of disease course or prognosis. Recently, we have shown that resting-state EEG can reliably and quantitatively capture abnormal patterns of motor and cognitive network disruption in amyotrophic lateral sclerosis. These network disruptions have been identified across multiple frequency bands, and using measures of neural activity (spectral power) and connectivity (comodulation of activity by amplitude envelope correlation and synchrony by imaginary coherence) on source-localized brain oscillations from high-density EEG. Using data-driven methods (similarity network fusion and spectral clustering), we have now undertaken a clustering analysis to identify disease subphenotypes and to determine whether different patterns of disruption are predictive of disease outcome. We show that amyotrophic lateral sclerosis patients (n = 95) can be subgrouped into four phenotypes with distinct neurophysiological profiles. These clusters are characterized by varying degrees of disruption in the somatomotor (α-band synchrony), frontotemporal (β-band neural activity and γl-band synchrony) and frontoparietal (γl-band comodulation) networks, which reliably correlate with distinct clinical profiles and different disease trajectories. Using an in-depth stability analysis, we show that these clusters are statistically reproducible and robust, remain stable after reassessment using a follow-up EEG session, and continue to predict the clinical trajectory and disease outcome. Our data demonstrate that novel phenotyping using neuroelectric signal analysis can distinguish disease subtypes based exclusively on different patterns of network disturbances. These patterns may reflect underlying disease neurobiology. The identification of amyotrophic lateral sclerosis subtypes based on profiles of differential impairment in neuronal networks has clear potential in future stratification for clinical trials. Advanced network profiling in amyotrophic lateral sclerosis can also underpin new therapeutic strategies that are based on principles of neurobiology and designed to modulate network disruption.
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Affiliation(s)
- Stefan Dukic
- Academic Unit of Neurology, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Ireland.,Department of Neurology, University Medical Centre Utrecht Brain Centre, Utrecht University, Utrecht, The Netherlands
| | - Roisin McMackin
- Academic Unit of Neurology, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Ireland
| | - Emmet Costello
- Academic Unit of Neurology, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Ireland
| | - Marjorie Metzger
- Academic Unit of Neurology, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Ireland
| | - Teresa Buxo
- Academic Unit of Neurology, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Ireland
| | - Antonio Fasano
- Academic Unit of Neurology, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Ireland
| | - Rangariroyashe Chipika
- Computational Neuroimaging Group, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Ireland
| | - Marta Pinto-Grau
- Academic Unit of Neurology, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Ireland
| | - Christina Schuster
- Computational Neuroimaging Group, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Ireland
| | - Michaela Hammond
- Academic Unit of Neurology, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Ireland
| | - Mark Heverin
- Academic Unit of Neurology, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Ireland
| | - Amina Coffey
- Academic Unit of Neurology, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Ireland
| | - Michael Broderick
- Academic Unit of Neurology, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Ireland
| | - Parameswaran M Iyer
- Academic Unit of Neurology, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Ireland
| | - Kieran Mohr
- Academic Unit of Neurology, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Ireland
| | - Brighid Gavin
- Academic Unit of Neurology, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Ireland
| | - Russell McLaughlin
- Academic Unit of Neurology, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Ireland
| | - Niall Pender
- Academic Unit of Neurology, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Ireland
| | - Peter Bede
- Computational Neuroimaging Group, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Ireland
| | - Muthuraman Muthuraman
- Movement disorders and Neurostimulation, Biomedical Statistics and Multimodal Signal Processing Unit, Department of Neurology, Johannes-Gutenberg-University Hospital, Mainz, Germany
| | - Leonard van den Berg
- Department of Neurology, University Medical Centre Utrecht Brain Centre, Utrecht University, Utrecht, The Netherlands
| | - Orla Hardiman
- Academic Unit of Neurology, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Ireland.,Trinity College Institute of Neuroscience, Trinity College Dublin, University of Dublin, Ireland.,Department of Neurology, Beaumont Hospital, Dublin, Ireland
| | - Bahman Nasseroleslami
- Academic Unit of Neurology, Trinity Biomedical Sciences Institute, Trinity College Dublin, University of Dublin, Ireland
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33
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Wei J, Lin JH, Cai LM, Shi JY, Zhang XH, Zou ZY, Chen HJ. Abnormal Stability of Dynamic Functional Architecture in Amyotrophic Lateral Sclerosis: A Preliminary Resting-State fMRI Study. Front Neurol 2021; 12:744688. [PMID: 34721270 PMCID: PMC8548741 DOI: 10.3389/fneur.2021.744688] [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: 07/20/2021] [Accepted: 09/08/2021] [Indexed: 12/28/2022] Open
Abstract
Purpose: Static and dynamic analyses for identifying functional connectivity (FC) have demonstrated brain dysfunctions in amyotrophic lateral sclerosis (ALS). However, few studies on the stability of dynamic FC have been conducted among ALS patients. This study explored the change of functional stability in ALS and how it correlates with disease severity. Methods: We gathered resting-state functional magnetic resonance data from 20 patients with ALS and 22 healthy controls (HCs). The disease severity was assessed with the Revised ALS Functional Rating Scale (ALSFRS-R). We used a sliding window correlation approach to identify dynamic FC and measured the concordance of dynamic FC over time to obtain the functional stability of each voxel. We assessed the between-group difference in functional stability by voxel-wise two-sample t-test. The correlation between the functional stability index and ALSFRS-R in ALS patients was evaluated using Spearman's correlation analysis. Results: Compared with the HC group, the ALS group had significantly increased functional stability in the left pre-central and post-central gyrus and right temporal pole while decreased functional stability in the right middle and inferior frontal gyrus. The results revealed a significant correlation between ALSFRS-R and the mean functional stability in the right temporal pole (r = −0.452 and P = 0.046) in the ALS patients. Conclusions: ALS patients have abnormal stability of brain functional architecture, which is associated with the severity of the disease.
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Affiliation(s)
- Jin Wei
- Department of Radiology, Fujian Medical University Union Hospital, Fuzhou, China
| | - Jia-Hui Lin
- Department of Radiology, Fujian Medical University Union Hospital, Fuzhou, China
| | - Li-Min Cai
- Department of Radiology, Fujian Medical University Union Hospital, Fuzhou, China
| | - Jia-Yan Shi
- Department of Radiology, Fujian Medical University Union Hospital, Fuzhou, China
| | - Xiao-Hong Zhang
- Department of Radiology, Fujian Medical University Union Hospital, Fuzhou, China
| | - Zhang-Yu Zou
- Department of Neurology, Fujian Medical University Union Hospital, Fuzhou, China
| | - Hua-Jun Chen
- Department of Radiology, Fujian Medical University Union Hospital, Fuzhou, China
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34
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Bede P, Chipika RH, Christidi F, Hengeveld JC, Karavasilis E, Argyropoulos GD, Lope J, Li Hi Shing S, Velonakis G, Dupuis L, Doherty MA, Vajda A, McLaughlin RL, Hardiman O. Genotype-associated cerebellar profiles in ALS: focal cerebellar pathology and cerebro-cerebellar connectivity alterations. J Neurol Neurosurg Psychiatry 2021; 92:1197-1205. [PMID: 34168085 PMCID: PMC8522463 DOI: 10.1136/jnnp-2021-326854] [Citation(s) in RCA: 32] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/12/2021] [Accepted: 06/02/2021] [Indexed: 12/11/2022]
Abstract
OBJECTIVE Cerebellar disease burden and cerebro-cerebellar connectivity alterations are poorly characterised in amyotrophic lateral sclerosis (ALS) despite the likely contribution of cerebellar pathology to the clinical heterogeneity of the condition. METHODS A prospective imaging study has been undertaken with 271 participants to systematically evaluate cerebellar grey and white matter alterations, cerebellar peduncle integrity and cerebro-cerebellar connectivity in ALS. Participants were stratified into four groups: (1) patients testing positive for GGGGCC repeat expansions in C9orf72, (2) patients carrying an intermediate-length repeat expansion in ATXN2, (3) patients without established ALS-associated mutations and (4) healthy controls. Additionally, the cerebellar profile of a single patient with ALS who had an ATXN2 allele length of 62 was evaluated. Cortical thickness, grey matter and white matter volumes were calculated in each cerebellar lobule complemented by morphometric analyses to characterise genotype-associated atrophy patterns. A Bayesian segmentation algorithm was used for superior cerebellar peduncle volumetry. White matter diffusivity parameters were appraised both within the cerebellum and in the cerebellar peduncles. Cerebro-cerebellar connectivity was assessed using deterministic tractography. RESULTS Cerebellar pathology was confined to lobules I-V of the anterior lobe in patients with sporadic ALS in contrast to the considerable posterior lobe and vermis disease burden identified in C9orf72 mutation carriers. Patients with intermediate ATXN2 expansions did not exhibit significant cerebellar pathology. CONCLUSIONS Focal rather than global cerebellar degeneration characterises ALS. Pathognomonic ALS symptoms which are typically attributed to other anatomical regions, such as dysarthria, dysphagia, pseudobulbar affect, eye movement abnormalities and cognitive deficits, may be modulated, exacerbated or partially driven by cerebellar changes in ALS.
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Affiliation(s)
- Peter Bede
- Computational Neuroimaging Group, Trinity College Dublin, Dublin, Ireland
| | | | - Foteini Christidi
- Computational Neuroimaging Group, Trinity College Dublin, Dublin, Ireland
- National and Kapodistrian University of Athens, Athens, Greece
| | | | | | | | - Jasmin Lope
- Computational Neuroimaging Group, Trinity College Dublin, Dublin, Ireland
| | - Stacey Li Hi Shing
- Computational Neuroimaging Group, Trinity College Dublin, Dublin, Ireland
| | | | - Léonie Dupuis
- Smurfit Institute of Genetics, Trinity College Dublin, Dublin, Ireland
- University of Central Florida College of Medicine, Orlando, Florida, USA
| | - Mark A Doherty
- Smurfit Institute of Genetics, Trinity College Dublin, Dublin, Ireland
| | - Alice Vajda
- Smurfit Institute of Genetics, Trinity College Dublin, Dublin, Ireland
| | | | - Orla Hardiman
- Computational Neuroimaging Group, Trinity College Dublin, Dublin, Ireland
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35
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Tahedl M, Li Hi Shing S, Finegan E, Chipika RH, Lope J, Hardiman O, Bede P. Propagation patterns in motor neuron diseases: Individual and phenotype-associated disease-burden trajectories across the UMN-LMN spectrum of MNDs. Neurobiol Aging 2021; 109:78-87. [PMID: 34656922 DOI: 10.1016/j.neurobiolaging.2021.04.031] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2021] [Revised: 03/29/2021] [Accepted: 04/13/2021] [Indexed: 01/18/2023]
Abstract
Motor neuron diseases encompass a divergent group of conditions with considerable differences in clinical manifestations, survival, and genetic vulnerability. One of the key aspects of clinical heterogeneity is the preferential involvement of upper (UMN) and lower motor neurons (LMN). While longitudinal imaging patters are relatively well characterized in ALS, progressive cortical changes in UMN,- and LMN-predominant conditions are seldom evaluated. Accordingly, the objective of this study is the juxtaposition of longitudinal trajectories in 3 motor neuron phenotypes; a UMN-predominant syndrome (PLS), a mixed UMN-LMN condition (ALS), and a lower motor neuron condition (poliomyelitis survivors). A standardized imaging protocol was implemented in a prospective, multi-timepoint longitudinal study with a uniform follow-up interval of 4 months. Forty-five poliomyelitis survivors, 61 patients with amyotrophic lateral sclerosis (ALS), and 23 patients with primary lateral sclerosis (PLS) were included. Cortical thickness alterations were evaluated in a dual analysis pipeline, using standard cortical thickness analyses, and a z-score-based individualized approach. Our results indicate that PLS patients exhibit rapidly progressive cortical thinning primarily in motor regions; ALS patients show cortical atrophy in both motor and extra-motor regions, while poliomyelitis survivors exhibit cortical thickness gains in a number of cerebral regions. Our findings suggest that dynamic cortical changes in motor neuron diseases may depend on relative UMN and/or LMN involvement, and increased cortical thickness in LMN-predominant conditions may represent compensatory, adaptive processes.
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Affiliation(s)
- Marlene Tahedl
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Ireland; Department of Psychiatry and Psychotherapy and Institute for Psychology, University of Regensburg, 93053 Regensburg, Germany
| | - Stacey Li Hi Shing
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Ireland
| | - Eoin Finegan
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Ireland
| | - Rangariroyashe H Chipika
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Ireland
| | - Jasmin Lope
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Ireland
| | - Orla Hardiman
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Ireland
| | - Peter Bede
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Ireland; Pitié-Salpêtrière University Hospital, Sorbonne University, Paris, France.
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36
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Pathological neural networks and artificial neural networks in ALS: diagnostic classification based on pathognomonic neuroimaging features. J Neurol 2021; 269:2440-2452. [PMID: 34585269 PMCID: PMC9021106 DOI: 10.1007/s00415-021-10801-5] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2021] [Revised: 09/07/2021] [Accepted: 09/09/2021] [Indexed: 12/26/2022]
Abstract
The description of group-level, genotype- and phenotype-associated imaging traits is academically important, but the practical demands of clinical neurology centre on the accurate classification of individual patients into clinically relevant diagnostic, prognostic and phenotypic categories. Similarly, pharmaceutical trials require the precision stratification of participants based on quantitative measures. A single-centre study was conducted with a uniform imaging protocol to test the accuracy of an artificial neural network classification scheme on a cohort of 378 participants composed of patients with ALS, healthy subjects and disease controls. A comprehensive panel of cerebral volumetric measures, cortical indices and white matter integrity values were systematically retrieved from each participant and fed into a multilayer perceptron model. Data were partitioned into training and testing and receiver-operating characteristic curves were generated for the three study-groups. Area under the curve values were 0.930 for patients with ALS, 0.958 for disease controls, and 0.931 for healthy controls relying on all input imaging variables. The ranking of variables by classification importance revealed that white matter metrics were far more relevant than grey matter indices to classify single subjects. The model was further tested in a subset of patients scanned within 6 weeks of their diagnosis and an AUC of 0.915 was achieved. Our study indicates that individual subjects may be accurately categorised into diagnostic groups in an observer-independent classification framework based on multiparametric, spatially registered radiology data. The development and validation of viable computational models to interpret single imaging datasets are urgently required for a variety of clinical and clinical trial applications.
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37
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McKenna MC, Corcia P, Couratier P, Siah WF, Pradat PF, Bede P. Frontotemporal Pathology in Motor Neuron Disease Phenotypes: Insights From Neuroimaging. Front Neurol 2021; 12:723450. [PMID: 34484106 PMCID: PMC8415268 DOI: 10.3389/fneur.2021.723450] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2021] [Accepted: 07/22/2021] [Indexed: 01/18/2023] Open
Abstract
Frontotemporal involvement has been extensively investigated in amyotrophic lateral sclerosis (ALS) but remains relatively poorly characterized in other motor neuron disease (MND) phenotypes such as primary lateral sclerosis (PLS), progressive muscular atrophy (PMA), spinal muscular atrophy (SMA), spinal bulbar muscular atrophy (SBMA), post poliomyelitis syndrome (PPS), and hereditary spastic paraplegia (HSP). This review focuses on insights from structural, metabolic, and functional neuroimaging studies that have advanced our understanding of extra-motor disease burden in these phenotypes. The imaging literature is limited in the majority of these conditions and frontotemporal involvement has been primarily evaluated by neuropsychology and post mortem studies. Existing imaging studies reveal that frontotemporal degeneration can be readily detected in ALS and PLS, varying degree of frontotemporal pathology may be captured in PMA, SBMA, and HSP, SMA exhibits cerebral involvement without regional predilection, and there is limited evidence for cerebral changes in PPS. Our review confirms the heterogeneity extra-motor pathology across the spectrum of MNDs and highlights the role of neuroimaging in characterizing anatomical patterns of disease burden in vivo. Despite the contribution of neuroimaging to MND research, sample size limitations, inclusion bias, attrition rates in longitudinal studies, and methodological constraints need to be carefully considered. Frontotemporal involvement is a quintessential clinical facet of MND which has important implications for screening practices, individualized management strategies, participation in clinical trials, caregiver burden, and resource allocation. The academic relevance of imaging frontotemporal pathology in MND spans from the identification of genetic variants, through the ascertainment of presymptomatic changes to the design of future epidemiology studies.
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Affiliation(s)
- Mary Clare McKenna
- Computational Neuroimaging Group, Trinity College Dublin, Dublin, Ireland
| | - Philippe Corcia
- Department of Neurology-Neurophysiology, CRMR ALS, Tours, France.,UMR 1253 iBrain, University of Tours, Tours, France.,LITORALS, Federation of ALS Centres: Tours-Limoges, Limoges, France
| | - Philippe Couratier
- LITORALS, Federation of ALS Centres: Tours-Limoges, Limoges, France.,ALS Centre, Limoges University Hospital (CHU de Limoges), Limoges, France
| | - We Fong Siah
- Computational Neuroimaging Group, Trinity College Dublin, Dublin, Ireland
| | | | - Peter Bede
- Computational Neuroimaging Group, Trinity College Dublin, Dublin, Ireland.,Pitié-Salpêtrière University Hospital, Sorbonne University, Paris, France
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38
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Imaging data indicate cerebral reorganisation in poliomyelitis survivors: Possible compensation for longstanding lower motor neuron pathology. Data Brief 2021; 38:107316. [PMID: 34485646 PMCID: PMC8397913 DOI: 10.1016/j.dib.2021.107316] [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: 04/28/2021] [Revised: 08/16/2021] [Accepted: 08/19/2021] [Indexed: 12/14/2022] Open
Abstract
A standardised, single-centre cross-sectional imaging protocol was utilised to investigate cortical grey matter and cerebral white matter alterations in 36 poliomyelitis survivors in contrast to healthy individuals and patients with amyotrophic lateral sclerosis (ALS) as a 'disease-control' group. [1] T1-weighted imaging and 32-direction diffusion tensor imaging data were obtained on a 3 Tesla Philips Achieva MRI system, using an IR-SPGR sequence and SE-EPI sequence respectively. Raw region-of-interest data and percentage change with respect to reference estimated marginal mean values are presented for grey and white matter metrics in key anatomical regions. Poliomyelitis survivors exhibit no frank grey or white matter degeneration. To the contrary, increased partial volumes can be detected in the brainstem, cerebellum and occipital lobes compared to healthy individuals. Higher fractional anisotropy was also noted in the corticospinal tracts, cerebellum, bilateral mesial temporal lobes and inferior frontal brain regions in poliomyelitis survivors in contrast to controls. Anatomical patterns of superior integrity metrics in polio survivors were concordant with anatomical regions of focal degeneration in ALS. Our imaging data indicate cortical and white matter reorganisation in polio survivors, which may be interpreted as compensatory adaptation to severe lower motor neuron injury acquired in infancy.
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39
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Tahedl M, Murad A, Lope J, Hardiman O, Bede P. Evaluation and categorisation of individual patients based on white matter profiles: Single-patient diffusion data interpretation in neurodegeneration. J Neurol Sci 2021; 428:117584. [PMID: 34315000 DOI: 10.1016/j.jns.2021.117584] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2021] [Revised: 07/13/2021] [Accepted: 07/19/2021] [Indexed: 12/18/2022]
Abstract
The majority of radiology studies in neurodegenerative conditions infer group-level imaging traits from group comparisons. While this strategy is helpful to define phenotype-specific imaging signatures for academic use, the meaningful interpretation of single scans of individual subjects is more important in everyday clinical practice. Accordingly, we present a computational method to evaluate individual subject diffusion tensor data to highlight white matter integrity alterations. Fifty white matter tracts were quantitatively evaluated in 132 patients with amyotrophic lateral sclerosis (ALS) with respect to normative values from 100 healthy subjects. Fractional anisotropy and radial diffusivity alterations were assessed individually in each patient. The approach was validated against standard tract-based spatial statistics and further scrutinised by the assessment of 78 additional data sets with a blinded diagnosis. Our z-score-based approach readily detected white matter degeneration in individual ALS patients and helped to categorise single subjects with a 'blinded diagnosis' as likely 'ALS' or 'control'. The group-level inferences from the z-score-based approach were analogous to the standard TBSS output maps. The benefit of the z-score-based strategy is that it enables the interpretation of single DTI datasets as well as the comparison of study groups. Outputs can be summarised either visually by highlighting the affected tracts, or, listing the affected tracts in a text file with reference to normative data, making it particularly useful for clinical applications. While individual diffusion data cannot be visually appraised, our approach provides a viable framework for single-subject imaging data interpretation.
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Affiliation(s)
- Marlene Tahedl
- Computational Neuroimaging Group, Trinity College Dublin, Dublin, Ireland; Department of Psychiatry and Psychotherapy, Institute for Psychology, University of Regensburg, Germany
| | - Aizuri Murad
- Computational Neuroimaging Group, Trinity College Dublin, Dublin, Ireland
| | - Jasmin Lope
- Computational Neuroimaging Group, Trinity College Dublin, Dublin, Ireland
| | - Orla Hardiman
- Computational Neuroimaging Group, Trinity College Dublin, Dublin, Ireland
| | - Peter Bede
- Computational Neuroimaging Group, Trinity College Dublin, Dublin, Ireland; Pitié-Salpêtrière University Hospital, Sorbonne University, Paris, France.
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Secco A, Tonin A, Rana A, Jaramillo-Gonzalez A, Khalili-Ardali M, Birbaumer N, Chaudhary U. EEG power spectral density in locked-in and completely locked-in state patients: a longitudinal study. Cogn Neurodyn 2021; 15:473-480. [PMID: 34035865 PMCID: PMC8131474 DOI: 10.1007/s11571-020-09639-w] [Citation(s) in RCA: 6] [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: 03/01/2020] [Revised: 08/14/2020] [Accepted: 09/30/2020] [Indexed: 12/14/2022] Open
Abstract
Persons with their eye closed and without any means of communication is said to be in a completely locked-in state (CLIS) while when they could still open their eyes actively or passively and have some means of communication are said to be in locked-in state (LIS). Two patients in CLIS without any means of communication, and one patient in the transition from LIS to CLIS with means of communication, who have Amyotrophic Lateral Sclerosis were followed at a regular interval for more than 1 year. During each visit, resting-state EEG was recorded before the brain-computer interface (BCI) based communication sessions. The resting-state EEG of the patients was analyzed to elucidate the evolution of their EEG spectrum over time with the disease's progression to provide future BCI-research with the relevant information to classify changes in EEG evolution. Comparison of power spectral density (PSD) of these patients revealed a significant difference in the PSD's of patients in CLIS without any means of communication and the patient in the transition from LIS to CLIS with means of communication. The EEG of patients without any means of communication is devoid of alpha, beta, and higher frequencies than the patient in transition who still had means of communication. The results show that the change in the EEG frequency spectrum may serve as an indicator of the communication ability of such patients.
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Affiliation(s)
- Arianna Secco
- Department of Information Engineering, Bioengineering, Università Degli Studi di Padova, Padua, Italy
| | - Alessandro Tonin
- Wyss-Center for Bio- and Neuro-Engineering, Chemin de Mines 9, 1202 Geneva, Switzerland
| | - Aygul Rana
- Institute of Medical Psychology and Behavioral Neurobiology, University of Tübingen, Tübingen, Germany
| | - Andres Jaramillo-Gonzalez
- Institute of Medical Psychology and Behavioral Neurobiology, University of Tübingen, Tübingen, Germany
| | - Majid Khalili-Ardali
- Institute of Medical Psychology and Behavioral Neurobiology, University of Tübingen, Tübingen, Germany
| | - Niels Birbaumer
- Institute of Medical Psychology and Behavioral Neurobiology, University of Tübingen, Tübingen, Germany
| | - Ujwal Chaudhary
- Wyss-Center for Bio- and Neuro-Engineering, Chemin de Mines 9, 1202 Geneva, Switzerland
- Institute of Medical Psychology and Behavioral Neurobiology, University of Tübingen, Tübingen, Germany
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McKenna MC, Chipika RH, Li Hi Shing S, Christidi F, Lope J, Doherty MA, Hengeveld JC, Vajda A, McLaughlin RL, Hardiman O, Hutchinson S, Bede P. Infratentorial pathology in frontotemporal dementia: cerebellar grey and white matter alterations in FTD phenotypes. J Neurol 2021; 268:4687-4697. [PMID: 33983551 PMCID: PMC8563547 DOI: 10.1007/s00415-021-10575-w] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2021] [Revised: 04/19/2021] [Accepted: 04/19/2021] [Indexed: 12/16/2022]
Abstract
The contribution of cerebellar pathology to cognitive and behavioural manifestations is increasingly recognised, but the cerebellar profiles of FTD phenotypes are relatively poorly characterised. A prospective, single-centre imaging study has been undertaken with a high-resolution structural and diffusion tensor protocol to systematically evaluate cerebellar grey and white matter alterations in behavioural-variant FTD(bvFTD), non-fluent variant primary progressive aphasia(nfvPPA), semantic-variant primary progressive aphasia(svPPA), C9orf72-positive ALS-FTD(C9 + ALSFTD) and C9orf72-negative ALS-FTD(C9-ALSFTD). Cerebellar cortical thickness and complementary morphometric analyses were carried out to appraise atrophy patterns controlling for demographic variables. White matter integrity was assessed in a study-specific white matter skeleton, evaluating three diffusivity metrics: fractional anisotropy (FA), axial diffusivity (AD) and radial diffusivity (RD). Significant cortical thickness reductions were identified in: lobule VII and crus I in bvFTD; lobule VI VII, crus I and II in nfvPPA; and lobule VII, crus I and II in svPPA; lobule IV, VI, VII and Crus I and II in C9 + ALSFTD. Morphometry revealed volume reductions in lobule V in all groups; in addition to lobule VIII in C9 + ALSFTD; lobule VI, VIII and vermis in C9-ALSFTD; lobule V, VII and vermis in bvFTD; and lobule V, VI, VIII and vermis in nfvPPA. Widespread white matter alterations were demonstrated by significant fractional anisotropy, axial diffusivity and radial diffusivity changes in each FTD phenotype that were more focal in those with C9 + ALSFTD and svPPA. Our findings indicate that FTD subtypes are associated with phenotype-specific cerebellar signatures with the selective involvement of specific lobules instead of global cerebellar atrophy.
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Affiliation(s)
- Mary Clare McKenna
- Computational Neuroimaging Group, Trinity Biomedical Sciences Institute, Trinity College Dublin, Peter Bede, Room 5.43, Pearse Street, Dublin 2, Ireland
| | - Rangariroyashe H Chipika
- Computational Neuroimaging Group, Trinity Biomedical Sciences Institute, Trinity College Dublin, Peter Bede, Room 5.43, Pearse Street, Dublin 2, Ireland
| | - Stacey Li Hi Shing
- Computational Neuroimaging Group, Trinity Biomedical Sciences Institute, Trinity College Dublin, Peter Bede, Room 5.43, Pearse Street, Dublin 2, Ireland
| | - Foteini Christidi
- Computational Neuroimaging Group, Trinity Biomedical Sciences Institute, Trinity College Dublin, Peter Bede, Room 5.43, Pearse Street, Dublin 2, Ireland
| | - Jasmin Lope
- Computational Neuroimaging Group, Trinity Biomedical Sciences Institute, Trinity College Dublin, Peter Bede, Room 5.43, Pearse Street, Dublin 2, Ireland
| | - Mark A Doherty
- Complex Trait Genomics Laboratory, Smurfit Institute of Genetics, Trinity College Dublin, Dublin 2, Ireland
| | - Jennifer C Hengeveld
- Complex Trait Genomics Laboratory, Smurfit Institute of Genetics, Trinity College Dublin, Dublin 2, Ireland
| | - Alice Vajda
- Complex Trait Genomics Laboratory, Smurfit Institute of Genetics, Trinity College Dublin, Dublin 2, Ireland
| | - Russell L McLaughlin
- Complex Trait Genomics Laboratory, Smurfit Institute of Genetics, Trinity College Dublin, Dublin 2, Ireland
| | - Orla Hardiman
- Computational Neuroimaging Group, Trinity Biomedical Sciences Institute, Trinity College Dublin, Peter Bede, Room 5.43, Pearse Street, Dublin 2, Ireland
| | | | - Peter Bede
- Computational Neuroimaging Group, Trinity Biomedical Sciences Institute, Trinity College Dublin, Peter Bede, Room 5.43, Pearse Street, Dublin 2, Ireland. .,Department of Neurology, St James's Hospital, Dublin, Ireland.
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Perkins EM, Burr K, Banerjee P, Mehta AR, Dando O, Selvaraj BT, Suminaite D, Nanda J, Henstridge CM, Gillingwater TH, Hardingham GE, Wyllie DJA, Chandran S, Livesey MR. Altered network properties in C9ORF72 repeat expansion cortical neurons are due to synaptic dysfunction. Mol Neurodegener 2021; 16:13. [PMID: 33663561 PMCID: PMC7931347 DOI: 10.1186/s13024-021-00433-8] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2020] [Accepted: 02/14/2021] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND Physiological disturbances in cortical network excitability and plasticity are established and widespread in amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) patients, including those harbouring the C9ORF72 repeat expansion (C9ORF72RE) mutation - the most common genetic impairment causal to ALS and FTD. Noting that perturbations in cortical function are evidenced pre-symptomatically, and that the cortex is associated with widespread pathology, cortical dysfunction is thought to be an early driver of neurodegenerative disease progression. However, our understanding of how altered network function manifests at the cellular and molecular level is not clear. METHODS To address this we have generated cortical neurons from patient-derived iPSCs harbouring C9ORF72RE mutations, as well as from their isogenic expansion-corrected controls. We have established a model of network activity in these neurons using multi-electrode array electrophysiology. We have then mechanistically examined the physiological processes underpinning network dysfunction using a combination of patch-clamp electrophysiology, immunocytochemistry, pharmacology and transcriptomic profiling. RESULTS We find that C9ORF72RE causes elevated network burst activity, associated with enhanced synaptic input, yet lower burst duration, attributable to impaired pre-synaptic vesicle dynamics. We also show that the C9ORF72RE is associated with impaired synaptic plasticity. Moreover, RNA-seq analysis revealed dysregulated molecular pathways impacting on synaptic function. All molecular, cellular and network deficits are rescued by CRISPR/Cas9 correction of C9ORF72RE. Our study provides a mechanistic view of the early dysregulated processes that underpin cortical network dysfunction in ALS-FTD. CONCLUSION These findings suggest synaptic pathophysiology is widespread in ALS-FTD and has an early and fundamental role in driving altered network function that is thought to contribute to neurodegenerative processes in these patients. The overall importance is the identification of previously unidentified defects in pre and postsynaptic compartments affecting synaptic plasticity, synaptic vesicle stores, and network propagation, which directly impact upon cortical function.
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Affiliation(s)
- Emma M. Perkins
- Euan MacDonald Centre for MND Research, University of Edinburgh, Edinburgh, EH16 4SB UK
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, EH16 4SB UK
- Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, EH8 9XD UK
| | - Karen Burr
- Euan MacDonald Centre for MND Research, University of Edinburgh, Edinburgh, EH16 4SB UK
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, EH16 4SB UK
- UK Dementia Research Institute at the University of Edinburgh, Edinburgh, EH16 4SB UK
| | - Poulomi Banerjee
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, EH16 4SB UK
- UK Dementia Research Institute at the University of Edinburgh, Edinburgh, EH16 4SB UK
| | - Arpan R. Mehta
- Euan MacDonald Centre for MND Research, University of Edinburgh, Edinburgh, EH16 4SB UK
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, EH16 4SB UK
- UK Dementia Research Institute at the University of Edinburgh, Edinburgh, EH16 4SB UK
| | - Owen Dando
- Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, EH8 9XD UK
- UK Dementia Research Institute at the University of Edinburgh, Edinburgh, EH16 4SB UK
- Simons Initiative for the Developing Brain, University of Edinburgh, Edinburgh, EH8 9XD UK
| | - Bhuvaneish T. Selvaraj
- Euan MacDonald Centre for MND Research, University of Edinburgh, Edinburgh, EH16 4SB UK
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, EH16 4SB UK
- UK Dementia Research Institute at the University of Edinburgh, Edinburgh, EH16 4SB UK
| | - Daumante Suminaite
- Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, EH8 9XD UK
| | - Jyoti Nanda
- Euan MacDonald Centre for MND Research, University of Edinburgh, Edinburgh, EH16 4SB UK
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, EH16 4SB UK
- UK Dementia Research Institute at the University of Edinburgh, Edinburgh, EH16 4SB UK
| | - Christopher M. Henstridge
- Euan MacDonald Centre for MND Research, University of Edinburgh, Edinburgh, EH16 4SB UK
- Division of Systems Medicine, School of Medicine, University of Dundee, Dundee, DD1 9SY UK
| | - Thomas H. Gillingwater
- Euan MacDonald Centre for MND Research, University of Edinburgh, Edinburgh, EH16 4SB UK
- Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, EH8 9XD UK
| | - Giles E. Hardingham
- Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, EH8 9XD UK
- UK Dementia Research Institute at the University of Edinburgh, Edinburgh, EH16 4SB UK
- Simons Initiative for the Developing Brain, University of Edinburgh, Edinburgh, EH8 9XD UK
| | - David J. A. Wyllie
- Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, EH8 9XD UK
- Simons Initiative for the Developing Brain, University of Edinburgh, Edinburgh, EH8 9XD UK
- Centre for Brain Development and Repair, inStem, Bangalore, 560065 India
| | - Siddharthan Chandran
- Euan MacDonald Centre for MND Research, University of Edinburgh, Edinburgh, EH16 4SB UK
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, EH16 4SB UK
- UK Dementia Research Institute at the University of Edinburgh, Edinburgh, EH16 4SB UK
- Simons Initiative for the Developing Brain, University of Edinburgh, Edinburgh, EH8 9XD UK
- Centre for Brain Development and Repair, inStem, Bangalore, 560065 India
| | - Matthew R. Livesey
- Euan MacDonald Centre for MND Research, University of Edinburgh, Edinburgh, EH16 4SB UK
- Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, EH8 9XD UK
- Simons Initiative for the Developing Brain, University of Edinburgh, Edinburgh, EH8 9XD UK
- Sheffield Institute for Translational Neuroscience, University of Sheffield, Sheffield, S10 2HQ UK
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Extra-motor manifestations in post-polio syndrome (PPS): fatigue, cognitive symptoms and radiological features. Neurol Sci 2021; 42:4569-4581. [PMID: 33635429 DOI: 10.1007/s10072-021-05130-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2020] [Accepted: 02/20/2021] [Indexed: 12/25/2022]
Abstract
BACKGROUND There is a paucity of cerebral neuroimaging studies in post-polio syndrome (PPS), despite the severity of neurological and neuropsychological sequelae associated with the condition. Fatigue, poor concentration, limited exercise tolerance, paraesthesia and progressive weakness are frequently reported, but the radiological underpinnings of these symptoms are poorly characterised. OBJECTIVE The aim of this study is to evaluate cortical and subcortical alterations in a cohort of adult polio survivors to explore the anatomical substrate of extra-motor manifestations. METHODS Thirty-six patients with post-polio syndrome, a disease-control group with amyotrophic lateral sclerosis patients and a cohort of healthy individuals were included in a prospective neuroimaging study with a standardised clinical and radiological protocol. Validated clinical instruments were utilised to assess mood, cognitive and behavioural domains and specific aspects of fatigue. Cortical thickness analyses, subcortical volumetry, brainstem segmentation and region-of-interest (ROI) white matter analyses were undertaken to assess regional grey and white matter alterations. RESULTS A high proportion of PPS patients exhibited apathy, verbal fluency deficits and reported self-perceived fatigue. On ROI analyses, cortical atrophy was limited to the cingulate gyrus, and the temporal pole and subcortical atrophy were only detected in the left nucleus accumbens. No FA reductions were noted to indicate white matter degeneration in any of the lobes. CONCLUSIONS Despite the high incidence of extra-motor manifestations in PPS, only limited cortical, subcortical and white matter degeneration was identified. Our findings suggest that non-structural causes, such as polypharmacy and poor sleep, may contribute to the complex symptomatology of post-polio syndrome.
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Extra-motor cerebral changes and manifestations in primary lateral sclerosis. Brain Imaging Behav 2021; 15:2283-2296. [PMID: 33409820 DOI: 10.1007/s11682-020-00421-4] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/12/2020] [Indexed: 12/22/2022]
Abstract
Primary lateral sclerosis (PLS) is classically considered a 'pure' upper motor neuron disorder. Motor cortex atrophy and pyramidal tract degeneration are thought to be pathognomonic of PLS, but extra-motor cerebral changes are poorly characterized. In a prospective neuroimaging study, forty PLS patients were systematically evaluated with a standardised imaging, genetic and clinical protocol. Patients were screened for ALS and HSP associated mutations, as well as C9orf72 hexanucleotide repeats. Clinical assessment included composite reflex scores, spasticity scales, functional rating scales, and screening for cognitive and behavioural deficits. The neuroimaging protocol evaluated cortical atrophy patterns, subcortical grey matter changes and white matter alterations in whole-brain and region-of-interest analyses. PLS patients tested negative for known ALS- and HSP-associated mutations and C9orf72 repeat expansions. Voxel-wise analyses revealed anterior cingulate, dorsolateral prefrontal, insular, opercular, orbitofrontal and bilateral mesial temporal grey matter changes and white matter alterations in the fornix, brainstem, temporal lobes, and cerebellum. Significant thalamus, caudate, hippocampus, putamen and accumbens nucleus volume reductions were also identified. Extra-motor clinical manifestations were dominated by verbal fluency deficits, language deficits, apathy and pseudobulbar affect. Our clinical and radiological evaluation confirms considerable extra-motor changes in a population-based cohort of PLS patients. Our data suggest that PLS should no longer be considered a neurodegenerative disorder selectively affecting the pyramidal system. PLS is associated with widespread extra-motor changes and manifestations which should be carefully considered in the multidisciplinary management of this low-incidence condition.
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Cortical progression patterns in individual ALS patients across multiple timepoints: a mosaic-based approach for clinical use. J Neurol 2021; 268:1913-1926. [PMID: 33399966 DOI: 10.1007/s00415-020-10368-7] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2020] [Revised: 12/09/2020] [Accepted: 12/10/2020] [Indexed: 12/11/2022]
Abstract
INTRODUCTION The majority of imaging studies in ALS infer group-level imaging signatures from group comparisons, as opposed to estimating disease burden in individual patients. In a condition with considerable clinical heterogeneity, the characterisation of individual patterns of pathology is hugely relevant. In this study, we evaluate a strategy to track progressive cortical involvement in single patients by using subject-specific reference cohorts. METHODS We have interrogated a multi-timepoint longitudinal dataset of 61 ALS patients to demonstrate the utility of estimating cortical disease burden and the expansion of cerebral atrophy over time. We contrast our strategy to the gold-standard approach to gauge the advantages and drawbacks of our method. We modelled the evolution of cortical integrity in a conditional growth model, in which we accounted for age, gender, disability, symptom duration, education and handedness. We hypothesised that the variance associated with demographic variables will be successfully eliminated in our approach. RESULTS In our model, the only covariate which modulated the expansion of atrophy was motor disability as measured by the ALSFRS-r (t(153) = - 2.533, p = 0.0123). Using the standard approach, age also significantly influenced progression of CT change (t(153) = - 2.151, p = 0.033) demonstrating the validity and potential clinical utility of our approach. CONCLUSION Our strategy of estimating the extent of cortical atrophy in individual patients with ALS successfully corrects for demographic factors and captures relevant cortical changes associated with clinical disability. Our approach provides a framework to interpret single T1-weighted images in ALS and offers an opportunity to track cortical propagation patterns both at individual subject level and at cohort level.
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Li Hi Shing S, McKenna MC, Siah WF, Chipika RH, Hardiman O, Bede P. The imaging signature of C9orf72 hexanucleotide repeat expansions: implications for clinical trials and therapy development. Brain Imaging Behav 2021; 15:2693-2719. [PMID: 33398779 DOI: 10.1007/s11682-020-00429-w] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/08/2020] [Indexed: 01/14/2023]
Abstract
While C9orf72-specific imaging signatures have been proposed by both ALS and FTD research groups and considerable presymptomatic alterations have also been confirmed in young mutation carriers, considerable inconsistencies exist in the literature. Accordingly, a systematic review of C9orf72-imaging studies has been performed to identify consensus findings, stereotyped shortcomings, and unique contributions to outline future directions. A formal literature review was conducted according to the STROBE guidelines. All identified papers were individually reviewed for sample size, choice of controls, study design, imaging modalities, statistical models, clinical profiling, and identified genotype-associated pathological patterns. A total of 74 imaging papers were systematically reviewed. ALS patients with GGGGCC repeat expansions exhibit relatively limited motor cortex involvement and widespread extra-motor pathology. C9orf72 positive FTD patients often show preferential posterior involvement. Reports of thalamic involvement are relatively consistent across the various phenotypes. Asymptomatic hexanucleotide repeat carriers often exhibit structural and functional changes decades prior to symptom onset. Common shortcomings included sample size limitations, lack of disease-controls, limited clinical profiling, lack of genetic testing in healthy controls, and absence of post mortem validation. There is a striking paucity of longitudinal studies and existing presymptomatic studies have not evaluated the predictive value of radiological changes with regard to age of onset and phenoconversion. With the advent of antisense oligonucleotide therapies, the meticulous characterisation of C9orf72-associated changes has gained practical relevance. Neuroimaging offers non-invasive biomarkers for future clinical trials, presymptomatic ascertainment, diagnostic and prognostic applications.
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Affiliation(s)
- Stacey Li Hi Shing
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland
| | - Mary Clare McKenna
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland
| | - We Fong Siah
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland
| | - Rangariroyashe H Chipika
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland
| | - Orla Hardiman
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland
| | - Peter Bede
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland.
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Bede P, Bogdahn U, Lope J, Chang KM, Xirou S, Christidi F. Degenerative and regenerative processes in amyotrophic lateral sclerosis: motor reserve, adaptation and putative compensatory changes. Neural Regen Res 2021; 16:1208-1209. [PMID: 33269779 PMCID: PMC8224145 DOI: 10.4103/1673-5374.300440] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Affiliation(s)
- Peter Bede
- Computational Neuroimaging Group, Trinity College Dublin, Dublin, Ireland; Biomedical Imaging Laboratory, Sorbonne University, Paris, France
| | - Ulrich Bogdahn
- Department of Neurology, University of Regensburg, Regensburg, Germany
| | - Jasmin Lope
- Computational Neuroimaging Group, Trinity College Dublin, Dublin, Ireland
| | - Kai Ming Chang
- Electronics and Computer Science, University of Southampton, Southampton, UK
| | - Sophia Xirou
- First Department of Neurology, Aeginition Hospital, National and Kapodistrian University of Athens, Athens, Greece
| | - Foteini Christidi
- First Department of Neurology, Aeginition Hospital, National and Kapodistrian University of Athens, Athens, Greece
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Deligani RJ, Hosni SI, Borgheai SB, McLinden J, Zisk AH, Mankodiya K, Shahriari Y. Electrical and Hemodynamic Neural Functions in People With ALS: An EEG-fNIRS Resting-State Study. IEEE Trans Neural Syst Rehabil Eng 2020; 28:3129-3139. [PMID: 33055020 DOI: 10.1109/tnsre.2020.3031495] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
OBJECTIVE Amyotrophic lateral sclerosis (ALS) is a complex neurodegenerative disease that causes the progressive loss of voluntary muscle control. Recent studies have reported conflicting results on alterations in resting-state functional brain networks in ALS by adopting unimodal techniques that measure either electrophysiological or vascular-hemodynamic neural functions. However, no study to date has explored simultaneous electrical and vascular-hemodynamic changes in the resting-state brain in ALS. Using complementary multimodal electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) recording and analysis techniques, we explored the underlying multidimensional neural contributions to altered oscillations and functional connectivity in people with ALS. METHODS 10 ALS patients and 9 age-matched controls underwent multimodal EEG-fNIRS recording in the resting state. Resting-state functional connectivity (RSFC) and power spectra of both modalities in both groups were analyzed and compared statistically. RESULTS Increased fronto-parietal EEG connectivity in the alpha and beta bands and increased interhemispheric and right intra-hemispheric fNIRS connectivity in the frontal and prefrontal regions were observed in ALS. Frontal, central, and temporal theta and alpha EEG power decreased in ALS, as did parietal and occipital alpha EEG power, while frontal and parietal hemodynamic spectral power increased in ALS. SIGNIFICANCE These results suggest that electro-vascular disruption in neuronal networks extends to the extra-motor regions in ALS patients, which can ultimately introduce novel neural markers of ALS that can be exploited further as diagnostic and prognostic tools.
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MRI data confirm the selective involvement of thalamic and amygdalar nuclei in amyotrophic lateral sclerosis and primary lateral sclerosis. Data Brief 2020; 32:106246. [PMID: 32944601 PMCID: PMC7481815 DOI: 10.1016/j.dib.2020.106246] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2020] [Revised: 08/12/2020] [Accepted: 08/25/2020] [Indexed: 12/20/2022] Open
Abstract
A standardised imaging protocol was implemented to evaluate disease burden in specific thalamic and amygdalar nuclei in 133 carefully phenotyped and genotyped motor neuron disease patients. “Switchboard malfunction in motor neuron diseases: selective pathology of thalamic nuclei in amyotrophic lateral sclerosis and primary lateral sclerosis” [1] “Amygdala pathology in amyotrophic lateral sclerosis and primary lateral sclerosis” [2] Raw volumetric data, group comparisons, effect sizes and percentage change are presented. Both ALS and PLS patients exhibited focal thalamus atrophy in ventral lateral and ventral anterior regions revealing extrapyramidal motor degeneration. Reduced accessory basal nucleus and cortical nucleus volumes were noted in the amygdala of C9orf72 negative ALS patients compared to healthy controls. ALS patients carrying the GGGGCC hexanucleotide repeats in C9orf72 exhibited preferential pathology in the mediodorsal-paratenial-reuniens thalamic nuclei and in the lateral nucleus and cortico-amygdaloid transition area of the amygdala. Considerable thalamic atrophy was observed in the sensory nuclei and lateral geniculate region of PLS patients. Our data demonstrate genotype-specific patterns of thalamus and amygdala involvement in ALS and a distinct disease-burden pattern in PLS. The dataset may be utilised for validation purposes, meta-analyses and the interpretation of thalamic and amygdalar profiles from other ALS genotypes.
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Finegan E, Siah WF, Shing SLH, Chipika RH, Chang KM, McKenna MC, Doherty MA, Hengeveld JC, Vajda A, Donaghy C, Hutchinson S, McLaughlin RL, Hardiman O, Bede P. Imaging and clinical data indicate considerable disease burden in 'probable' PLS: Patients with UMN symptoms for 2-4 years. Data Brief 2020; 32:106247. [PMID: 32944602 PMCID: PMC7481824 DOI: 10.1016/j.dib.2020.106247] [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: 08/04/2020] [Revised: 08/12/2020] [Accepted: 08/25/2020] [Indexed: 11/19/2022] Open
Abstract
Primary lateral sclerosis (PLS) is an adult-onset upper motor neuron disease manifesting in progressive spasticity and gradually resulting in considerably motor disability. In the absence of early disease-specific diagnostic indicators, the majority of patients with PLS face a circuitous diagnostic journey. Until the recent publication of consensus diagnostic criteria, 4-year symptom duration was required to establish the diagnosis. The new diagnostic criteria introduced the category of ‘probable PLS’ for patients with a symptom duration of 2–4 years. “Evolving diagnostic criteria in primary lateral sclerosis: The clinical and radiological basis of "probable PLS" [1]. This dataset provides radiological metrics in a cohort of ‘probable PLS’ patients, ‘definite PLS’ patients and age-matched healthy controls. Region-of-interest radiological data include diffusivity metrics in the corticospinal tracts and corpus callosum as well as mean cortical thickness values in the pre- and para-central gyri in each hemisphere. Our data indicate considerable grey matter and relatively limited white matter involvement in ‘probable PLS’ which supports the rationale for this diagnostic category as a clinically useful entity. The introduction of this diagnostic category will likely facilitate the timely recruitment of PLS patients into research studies and pharmacological trials before widespread neurodegenerative change ensues.
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Affiliation(s)
- Eoin Finegan
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Ireland
| | - We Fong Siah
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Ireland
| | - Stacey Li Hi Shing
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Ireland
| | | | - Kai Ming Chang
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Ireland
- Electronics and Computer Science, University of Southampton, Southampton, United Kingdom
| | - Mary Clare McKenna
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Ireland
| | - Mark A. Doherty
- Complex Trait Genomics Laboratory, Smurfit Institute of Genetics, Trinity College Dublin, Ireland
| | - Jennifer C. Hengeveld
- Complex Trait Genomics Laboratory, Smurfit Institute of Genetics, Trinity College Dublin, Ireland
| | - Alice Vajda
- Complex Trait Genomics Laboratory, Smurfit Institute of Genetics, Trinity College Dublin, Ireland
| | - Colette Donaghy
- Department of Neurology, Western Health & Social Care Trust, Belfast, United Kingdom
| | | | - Russel L. McLaughlin
- Complex Trait Genomics Laboratory, Smurfit Institute of Genetics, Trinity College Dublin, Ireland
| | - Orla Hardiman
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Ireland
| | - Peter Bede
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Ireland
- Corresponding author.
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