1
|
Rezende TJR, Adanyaguh I, Barsottini OGP, Bender B, Cendes F, Coutinho L, Deistung A, Dogan I, Durr A, Fernandez-Ruiz J, Göricke SL, Grisoli M, Hernandez-Castillo CR, Lenglet C, Mariotti C, Martinez ARM, Massuyama BK, Mochel F, Nanetti L, Nigri A, Ono SE, Öz G, Pedroso JL, Reetz K, Synofzik M, Teive H, Thomopoulos SI, Thompson PM, Timmann D, van de Warrenburg BPC, van Gaalen J, França MC, Harding IH. Genotype-specific spinal cord damage in spinocerebellar ataxias: an ENIGMA-Ataxia study. J Neurol Neurosurg Psychiatry 2024; 95:682-690. [PMID: 38383154 PMCID: PMC11187354 DOI: 10.1136/jnnp-2023-332696] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Accepted: 01/17/2024] [Indexed: 02/23/2024]
Abstract
BACKGROUND Spinal cord damage is a feature of many spinocerebellar ataxias (SCAs), but well-powered in vivo studies are lacking and links with disease severity and progression remain unclear. Here we characterise cervical spinal cord morphometric abnormalities in SCA1, SCA2, SCA3 and SCA6 using a large multisite MRI dataset. METHODS Upper spinal cord (vertebrae C1-C4) cross-sectional area (CSA) and eccentricity (flattening) were assessed using MRI data from nine sites within the ENIGMA-Ataxia consortium, including 364 people with ataxic SCA, 56 individuals with preataxic SCA and 394 nonataxic controls. Correlations and subgroup analyses within the SCA cohorts were undertaken based on disease duration and ataxia severity. RESULTS Individuals in the ataxic stage of SCA1, SCA2 and SCA3, relative to non-ataxic controls, had significantly reduced CSA and increased eccentricity at all examined levels. CSA showed large effect sizes (d>2.0) and correlated with ataxia severity (r<-0.43) and disease duration (r<-0.21). Eccentricity correlated only with ataxia severity in SCA2 (r=0.28). No significant spinal cord differences were evident in SCA6. In preataxic individuals, CSA was significantly reduced in SCA2 (d=1.6) and SCA3 (d=1.7), and the SCA2 group also showed increased eccentricity (d=1.1) relative to nonataxic controls. Subgroup analyses confirmed that CSA and eccentricity are abnormal in early disease stages in SCA1, SCA2 and SCA3. CSA declined with disease progression in all, whereas eccentricity progressed only in SCA2. CONCLUSIONS Spinal cord abnormalities are an early and progressive feature of SCA1, SCA2 and SCA3, but not SCA6, which can be captured using quantitative MRI.
Collapse
Affiliation(s)
- Thiago Junqueira Ribeiro Rezende
- Department of Neurology, University of Campinas (UNICAMP), Campinas, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology, Campinas, Brazil
| | - Isaac Adanyaguh
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, Minnesota, USA
| | | | - Benjamin Bender
- Department of Diagnostic and Interventional Neuroradiology, University Hospital Tübingen, Tübingen, Germany
| | - Fernando Cendes
- Department of Neurology, University of Campinas (UNICAMP), Campinas, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology, Campinas, Brazil
| | - Leo Coutinho
- Graduate program of Internal Medicine, Internal Medicine Department, Hospital de Clínicas, Federal University of Paraná, Curitiba, Brazil
| | - Andreas Deistung
- University Clinic and Outpatient Clinic for Radiology, Department for Radiation Medicine, University Hospital Halle (Saale), University Medicine Halle, Halle (Saale), Germany
| | - Imis Dogan
- Department of Neurology, RWTH Aachen University, Aachen, Germany
- JARA-BRAIN Institute Molecular Neuroscience and Neuroimaging, Research Center Jülich GmbH, Jülich, Germany
| | - Alexandra Durr
- Sorbonne Université, Paris Brain Institute (ICM), Pitié-Salpêtrière Hospital, AP-HP, INSERM, CNRS, University Hospital Pitié-Salpêtrière, Paris, France
| | - Juan Fernandez-Ruiz
- Neuropsychology Laboratory, Department of Physiology, Faculty of Medicine, National Autonomous University of Mexico, Mexico City, Mexico
| | - Sophia L Göricke
- Institute of Diagnostic and Interventional Radiology and Neuroradiology and Center for Translational Neuro- and Behavioral Sciences (C-TNBS), Essen University Hospital, University of Duisburg-Essen, Essen, Germany
| | - Marina Grisoli
- Department of Neuroradiology, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
| | | | - Christophe Lenglet
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, Minnesota, USA
| | - Caterina Mariotti
- Unit of Medical Genetics and Neurogenetics, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
| | - Alberto R M Martinez
- Department of Neurology, University of Campinas (UNICAMP), Campinas, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology, Campinas, Brazil
| | - Breno K Massuyama
- Department of Neurology, Federal University of São Paulo, São Paulo, SP, Brazil
| | - Fanny Mochel
- Assistance Publique-Hôpitaux de Paris, Pitié-Salpêtrière University Hospital, Paris, France
| | - Lorenzo Nanetti
- Unit of Medical Genetics and Neurogenetics, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
| | - Anna Nigri
- Department of Neuroradiology, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
| | - Sergio E Ono
- Clínica DAPI - Diagnóstico Avançado Por Imagem, Curitiba, Brazil
| | - Gülin Öz
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, Minnesota, USA
| | - José Luiz Pedroso
- Department of Neurology, Federal University of São Paulo, São Paulo, SP, Brazil
| | - Kathrin Reetz
- Department of Neurology, RWTH Aachen University, Aachen, Germany
- JARA-BRAIN Institute Molecular Neuroscience and Neuroimaging, Research Center Jülich GmbH, Jülich, Germany
| | - Matthis Synofzik
- Department of Neurodegenerative Diseases, Hertie Institute for Clinical Brain Research, Tübingen, Germany
- German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany
| | - Helio Teive
- Graduate program of Internal Medicine, Internal Medicine Department, Hospital de Clínicas, Federal University of Paraná, Curitiba, Brazil
- Movement Disorders Unit, Neurology Service, Internal Medicine Department, Hospital de Clínicas, Federal University of Paraná, Curitiba, Brazil
| | - Sophia I Thomopoulos
- Imaging Genetics Center, Mark and Mary Stevens Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Paul M Thompson
- Imaging Genetics Center, Mark and Mary Stevens Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Dagmar Timmann
- Department of Neurology and Center for Translational Neuro- and Behavioral Sciences (C-TNBS), Essen University Hospital, University of Duisburg-Essen, Essen, Germany
| | - Bart P C van de Warrenburg
- Department of Neurology, Donders Institute for Brain, Cognition, and Behaviour, Radboud University Medical Center, Nijmegen, Netherlands
- Department of Neurology, Rijnstate Hospital, Arnhem, Netherlands
| | - Judith van Gaalen
- Department of Neurology, Donders Institute for Brain, Cognition, and Behaviour, Radboud University Medical Center, Nijmegen, Netherlands
- Department of Neurology, Rijnstate Hospital, Arnhem, Netherlands
| | - Marcondes C França
- Department of Neurology, University of Campinas (UNICAMP), Campinas, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology, Campinas, Brazil
| | - Ian H Harding
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, Victoria, Australia
- Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia
| |
Collapse
|
2
|
Kleinerova J, Tahedl M, Tan EL, Delaney S, Hengeveld JC, Doherty MA, McLaughlin RL, Hardiman O, Chang KM, Finegan E, Bede P. Supra- and infra-tentorial degeneration patterns in primary lateral sclerosis: a multimodal longitudinal neuroradiology study. J Neurol 2024; 271:3239-3255. [PMID: 38438819 PMCID: PMC11136747 DOI: 10.1007/s00415-024-12261-z] [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: 12/21/2023] [Revised: 02/14/2024] [Accepted: 02/15/2024] [Indexed: 03/06/2024]
Abstract
BACKGROUND Primary lateral sclerosis (PLS) is traditionally solely associated with progressive upper motor neuron dysfunction manifesting in limb spasticity, gait impairment, bulbar symptoms and pseudobulbar affect. Recent studies have described frontotemporal dysfunction in some patients resulting in cognitive manifestations. Cerebellar pathology is much less well characterised despite sporadic reports of cerebellar disease. METHODS A multi-timepoint, longitudinal neuroimaging study was conducted to characterise the evolution of both intra-cerebellar disease burden and cerebro-cerebellar connectivity. The volumes of deep cerebellar nuclei, cerebellar cortical volumes, cerebro-cerebellar structural and functional connectivity were assessed longitudinally in a cohort of 43 individuals with PLS. RESULTS Cerebello-frontal, -temporal, -parietal, -occipital and cerebello-thalamic structural disconnection was detected at baseline based on radial diffusivity (RD) and cerebello-frontal decoupling was also evident based on fractional anisotropy (FA) alterations. Functional connectivity changes were also detected in cerebello-frontal, parietal and occipital projections. Volume reductions were identified in the vermis, anterior lobe, posterior lobe, and crura. Among the deep cerebellar nuclei, the dorsal dentate was atrophic. Longitudinal follow-up did not capture statistically significant progressive changes. Significant primary motor cortex atrophy and inter-hemispheric transcallosal degeneration were also captured. CONCLUSIONS PLS is not only associated with upper motor neuron dysfunction, but cerebellar cortical volume loss and deep cerebellar nuclear atrophy can also be readily detected. In addition to intra-cerebellar disease burden, cerebro-cerebellar connectivity alterations also take place. Our data add to the evolving evidence of widespread neurodegeneration in PLS beyond the primary motor regions. Cerebellar dysfunction in PLS is likely to exacerbate bulbar, gait and dexterity impairment and contribute to pseudobulbar affect.
Collapse
Affiliation(s)
- Jana Kleinerova
- Computational Neuroimaging Group (CNG), School of Medicine, Trinity College Dublin, Dublin 2, Ireland
| | - Marlene Tahedl
- Computational Neuroimaging Group (CNG), School of Medicine, Trinity College Dublin, Dublin 2, Ireland
| | - Ee Ling Tan
- Computational Neuroimaging Group (CNG), School of Medicine, Trinity College Dublin, Dublin 2, Ireland
| | - Siobhan Delaney
- Computational Neuroimaging Group (CNG), School of Medicine, Trinity College Dublin, Dublin 2, Ireland
- Department of Neurology, St James's Hospital, Dublin, Ireland
| | | | - Mark A Doherty
- Smurfit Institute of Genetics, Trinity College Dublin, Dublin, Ireland
| | | | - Orla Hardiman
- Computational Neuroimaging Group (CNG), School of Medicine, Trinity College Dublin, Dublin 2, Ireland
| | - Kai Ming Chang
- Computational Neuroimaging Group (CNG), School of Medicine, Trinity College Dublin, Dublin 2, Ireland
| | - Eoin Finegan
- Computational Neuroimaging Group (CNG), School of Medicine, Trinity College Dublin, Dublin 2, Ireland
| | - Peter Bede
- Computational Neuroimaging Group (CNG), School of Medicine, Trinity College Dublin, Dublin 2, Ireland.
- Department of Neurology, St James's Hospital, Dublin, Ireland.
| |
Collapse
|
3
|
Parnianpour P, Benatar M, Briemberg H, Dey A, Dionne A, Dupré N, Evans KC, Frayne R, Genge A, Graham SJ, Korngut L, McLaren DG, Seres P, Welsh RC, Wilman A, Zinman L, Kalra S. Mismatch between clinically defined classification of ALS stage and the burden of cerebral pathology. J Neurol 2024; 271:2547-2559. [PMID: 38282082 DOI: 10.1007/s00415-024-12190-x] [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: 11/16/2023] [Revised: 01/05/2024] [Accepted: 01/10/2024] [Indexed: 01/30/2024]
Abstract
This study aimed to investigate the clinical stratification of amyotrophic lateral sclerosis (ALS) patients in relation to in vivo cerebral degeneration. One hundred forty-nine ALS patients and one hundred forty-four healthy controls (HCs) were recruited from the Canadian ALS Neuroimaging Consortium (CALSNIC). Texture analysis was performed on T1-weighted scans to extract the texture feature "autocorrelation" (autoc), an imaging biomarker of cerebral degeneration. Patients were stratified at baseline into early and advanced disease stages based on criteria adapted from ALS clinical trials and the King's College staging system, as well as into slow and fast progressors (disease progression rates, DPR). Patients had increased autoc in the internal capsule. These changes extended beyond the internal capsule in early-stage patients (clinical trial-based criteria), fast progressors, and in advanced-stage patients (King's staging criteria). Longitudinal increases in autoc were observed in the postcentral gyrus, corticospinal tract, posterior cingulate cortex, and putamen; whereas decreases were observed in corpus callosum, caudate, central opercular cortex, and frontotemporal areas. Both longitudinal increases and decreases of autoc were observed in non-overlapping regions within insula and precentral gyrus. Within-criteria comparisons of autoc revealed more pronounced changes at baseline and longitudinally in early- (clinical trial-based criteria) and advanced-stage (King's staging criteria) patients and fast progressors. In summary, comparative patterns of baseline and longitudinal progression in cerebral degeneration are dependent on sub-group selection criteria, with clinical trial-based stratification insufficiently characterizing disease stage based on pathological cerebral burden.
Collapse
Affiliation(s)
- Pedram Parnianpour
- Neuroscience and Mental Health Institute, University of Alberta, 562 Heritage Medical Research Centre, 11313-87 Ave, Edmonton, AB, T6G2S2, Canada.
| | - Michael Benatar
- Department of Neurology, University of Miami Miller School of Medicine, Miami, USA
| | - Hannah Briemberg
- Division of Neurology, University of British Columbia, Vancouver, BC, Canada
| | - Avyarthana Dey
- Neuroscience and Mental Health Institute, University of Alberta, 562 Heritage Medical Research Centre, 11313-87 Ave, Edmonton, AB, T6G2S2, Canada
| | - Annie Dionne
- Axe Neurosciences, CHU de Québec-Université Laval, Québec City, QC, Canada
- Department of Medicine, Faculty of Medicine, Université Laval, Quebec City, QC, Canada
| | - Nicolas Dupré
- Axe Neurosciences, CHU de Québec-Université Laval, Québec City, QC, Canada
- Department of Medicine, Faculty of Medicine, Université Laval, Quebec City, QC, Canada
| | | | - Richard Frayne
- Hotchkiss Brain Institute, University of Calgary, Calgary, Canada
| | - Angela Genge
- Montreal Neurological Institute, McGill University, Montreal, Canada
| | - Simon J Graham
- Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, University of Toronto, Toronto, Canada
| | - Lawrence Korngut
- Hotchkiss Brain Institute, University of Calgary, Calgary, Canada
| | | | - Peter Seres
- Department of Biomedical Engineering, University of Alberta, Edmonton, Canada
| | - Robert C Welsh
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, UCLA, Los Angeles, CA, USA
| | - Alan Wilman
- Department of Radiology and Diagnostic Imaging, University of Alberta, Edmonton, AB, Canada
| | - Lorne Zinman
- Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, University of Toronto, Toronto, Canada
| | - Sanjay Kalra
- Neuroscience and Mental Health Institute, University of Alberta, 562 Heritage Medical Research Centre, 11313-87 Ave, Edmonton, AB, T6G2S2, Canada
- Department of Biomedical Engineering, University of Alberta, Edmonton, Canada
- Division of Neurology, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, AB, Canada
| |
Collapse
|
4
|
Thompson AG, Taschler B, Smith SM, Turner MR. Premorbid brain structure influences risk of amyotrophic lateral sclerosis. J Neurol Neurosurg Psychiatry 2024; 95:360-365. [PMID: 38050140 PMCID: PMC10958375 DOI: 10.1136/jnnp-2023-332322] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Accepted: 09/25/2023] [Indexed: 12/06/2023]
Abstract
BACKGROUND Amyotrophic lateral sclerosis (ALS) is a disease of the motor network associated with brain structure and functional connectivity alterations that are implicated in disease progression. Whether such changes have a causal role in ALS, fitting with a postulated influence of premorbid cerebral architecture on the phenotypes associated with neurodegenerative disorders is not known. METHODS This study considered causal effects and shared genetic risk of 2240 structural and functional MRI brain scan imaging-derived phenotypes (IDPs) on ALS using two sample Mendelian randomisation, with putative associations further examined with extensive sensitivity analysis. Shared genetic predisposition between IDPs and ALS was explored using genetic correlation analysis. RESULTS Increased white matter volume in the cerebral hemispheres was causally associated with ALS. Weaker causal associations were observed for brain stem grey matter volume, parieto-occipital white matter surface and volume of the left thalamic ventral anterior nucleus. Genetic correlation was observed between ALS and intracellular volume fraction and isotropic free water volume fraction within the posterior limb of the internal capsule. CONCLUSIONS This study provides evidence that premorbid brain structure, in particular white matter volume, contributes to the risk of ALS.
Collapse
Affiliation(s)
| | - Bernd Taschler
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Stephen M Smith
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Martin R Turner
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| |
Collapse
|
5
|
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.
Collapse
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
| |
Collapse
|
6
|
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.
Collapse
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.
| |
Collapse
|
7
|
Sattler R, Traynor BJ, Robertson J, Van Den Bosch L, Barmada SJ, Svendsen CN, Disney MD, Gendron TF, Wong PC, Turner MR, Boxer A, Babu S, Benatar M, Kurnellas M, Rohrer JD, Donnelly CJ, Bustos LM, Van Keuren-Jensen K, Dacks PA, Sabbagh MN. Roadmap for C9ORF72 in Frontotemporal Dementia and Amyotrophic Lateral Sclerosis: Report on the C9ORF72 FTD/ALS Summit. Neurol Ther 2023; 12:1821-1843. [PMID: 37847372 PMCID: PMC10630271 DOI: 10.1007/s40120-023-00548-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/06/2023] [Accepted: 09/14/2023] [Indexed: 10/18/2023] Open
Abstract
A summit held March 2023 in Scottsdale, Arizona (USA) focused on the intronic hexanucleotide expansion in the C9ORF72 gene and its relevance in frontotemporal dementia (FTD) and amyotrophic lateral sclerosis (ALS; C9ORF72-FTD/ALS). The goal of this summit was to connect basic scientists, clinical researchers, drug developers, and individuals affected by C9ORF72-FTD/ALS to evaluate how collaborative efforts across the FTD-ALS disease spectrum might break down existing disease silos. Presentations and discussions covered recent discoveries in C9ORF72-FTD/ALS disease mechanisms, availability of disease biomarkers and recent advances in therapeutic development, and clinical trial design for prevention and treatment for individuals affected by C9ORF72-FTD/ALS and asymptomatic pathological expansion carriers. The C9ORF72-associated hexanucleotide repeat expansion is an important locus for both ALS and FTD. C9ORF72-FTD/ALS may be characterized by loss of function of the C9ORF72 protein and toxic gain of functions caused by both dipeptide repeat (DPR) proteins and hexanucleotide repeat RNA. C9ORF72-FTD/ALS therapeutic strategies discussed at the summit included the use of antisense oligonucleotides, adeno-associated virus (AAV)-mediated gene silencing and gene delivery, and engineered small molecules targeting RNA structures associated with the C9ORF72 expansion. Neurofilament light chain, DPR proteins, and transactive response (TAR) DNA-binding protein 43 (TDP-43)-associated molecular changes were presented as biomarker candidates. Similarly, brain imaging modalities (i.e., magnetic resonance imaging [MRI] and positron emission tomography [PET]) measuring structural, functional, and metabolic changes were discussed as important tools to monitor individuals affected with C9ORF72-FTD/ALS, at both pre-symptomatic and symptomatic disease stages. Finally, summit attendees evaluated current clinical trial designs available for FTD or ALS patients and concluded that therapeutics relevant to FTD/ALS patients, such as those specifically targeting C9ORF72, may need to be tested with composite endpoints covering clinical symptoms of both FTD and ALS. The latter will require novel clinical trial designs to be inclusive of all patient subgroups spanning the FTD/ALS spectrum.
Collapse
Affiliation(s)
- Rita Sattler
- Barrow Neurological Institute, 2910 N Third Ave, Phoenix, AZ, 85013, USA.
| | - Bryan J Traynor
- Neuromuscular Diseases Research Section, Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
| | - Janice Robertson
- Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, Toronto, ON, Canada
| | - Ludo Van Den Bosch
- VIB, Center for Brain & Disease Research, Laboratory of Neurobiology and KU Leuven, Leuven, Belgium
- Department of Neurosciences, Experimental Neurology and Leuven Brain Institute (LBI), University of Leuven, Leuven, Belgium
| | - Sami J Barmada
- Department of Neurology, Neuroscience Program, University of Michigan, Ann Arbor, MI, USA
| | - Clive N Svendsen
- Board of Governors Regenerative Medicine Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Matthew D Disney
- Department of Chemistry, The Herbert Wertheim UF-Scripps Institute for Biomedical Research and Innovation, The Scripps Research Institute, Jupiter, FL, USA
| | - Tania F Gendron
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA
| | - Philip C Wong
- Departments of Pathology and Neuroscience, Johns Hopkins Medicine, Baltimore, MD, USA
| | - Martin R Turner
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Adam Boxer
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of San Francisco, San Francisco, CA, USA
| | - Suma Babu
- Sean M. Healey and AMG Center for ALS and the Neurological Clinical Research Institute, Massachusetts General Hospital-Harvard Medical School, Boston, MA, USA
| | - Michael Benatar
- Department of Neurology, University of Miami Miller School of Medicine, Miami, FL, 33129, USA
| | | | - Jonathan D Rohrer
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Christopher J Donnelly
- LiveLikeLou Center for ALS Research, Brain Institute, University of Pittsburgh, Pittsburgh, USA
- Department of Neurobiology, University of Pittsburgh School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Lynette M Bustos
- Barrow Neurological Institute, 2910 N Third Ave, Phoenix, AZ, 85013, USA
| | | | - Penny A Dacks
- The Association for Frontotemporal Degeneration and FTD Disorders Registry, King of Prussia, PA, USA
| | - Marwan N Sabbagh
- Barrow Neurological Institute, 2910 N Third Ave, Phoenix, AZ, 85013, USA.
| |
Collapse
|
8
|
Bede P, Lulé D, Müller HP, Tan EL, Dorst J, Ludolph AC, Kassubek J. Presymptomatic grey matter alterations in ALS kindreds: a computational neuroimaging study of asymptomatic C9orf72 and SOD1 mutation carriers. J Neurol 2023; 270:4235-4247. [PMID: 37178170 PMCID: PMC10421803 DOI: 10.1007/s00415-023-11764-5] [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: 03/16/2023] [Revised: 05/02/2023] [Accepted: 05/03/2023] [Indexed: 05/15/2023]
Abstract
BACKGROUND The characterisation of presymptomatic disease-burden patterns in asymptomatic mutation carriers has a dual academic and clinical relevance. The understanding of disease propagation mechanisms is of considerable conceptual interests, and defining the optimal time of pharmacological intervention is essential for improved clinical trial outcomes. METHODS In a prospective, multimodal neuroimaging study, 22 asymptomatic C9orf72 GGGGCC hexanucleotide repeat carriers, 13 asymptomatic subjects with SOD1, and 54 "gene-negative" ALS kindreds were enrolled. Cortical and subcortical grey matter alterations were systematically appraised using volumetric, morphometric, vertex, and cortical thickness analyses. Using a Bayesian approach, the thalamus and amygdala were further parcellated into specific nuclei and the hippocampus was segmented into anatomically defined subfields. RESULTS Asymptomatic GGGGCC hexanucleotide repeat carriers in C9orf72 exhibited early subcortical changes with the preferential involvement of the pulvinar and mediodorsal regions of the thalamus, as well as the lateral aspect of the hippocampus. Volumetric approaches, morphometric methods, and vertex analyses were anatomically consistent in capturing focal subcortical changes in asymptomatic C9orf72 hexanucleotide repeat expansion carriers. SOD1 mutation carriers did not exhibit significant subcortical grey matter alterations. In our study, none of the two asymptomatic cohorts exhibited cortical grey matter alterations on either cortical thickness or morphometric analyses. DISCUSSION The presymptomatic radiological signature of C9orf72 is associated with selective thalamic and focal hippocampal degeneration which may be readily detectable before cortical grey matter changes ensue. Our findings confirm selective subcortical grey matter involvement early in the course of C9orf72-associated neurodegeneration.
Collapse
Affiliation(s)
- Peter Bede
- Computational Neuroimaging Group (CNG), School of Medicine, Trinity College Dublin, Dublin, D02 RS90, Ireland.
- Department of Neurology, St James's Hospital, Dublin, Ireland.
| | - Dorothée Lulé
- Department of Neurology, University of Ulm, Ulm, Germany
| | | | - Ee Ling Tan
- Computational Neuroimaging Group (CNG), School of Medicine, Trinity College Dublin, Dublin, D02 RS90, Ireland
| | - Johannes Dorst
- Department of Neurology, University of Ulm, Ulm, Germany
| | - Albert C Ludolph
- Department of Neurology, University of Ulm, Ulm, Germany
- German Centre of Neurodegenerative Diseases (DZNE), Ulm, Germany
| | - Jan Kassubek
- Department of Neurology, University of Ulm, Ulm, Germany
- German Centre of Neurodegenerative Diseases (DZNE), Ulm, Germany
| |
Collapse
|
9
|
Bede P, Pradat PF. Editorial: The gap between academic advances and therapy development in motor neuron disease. Curr Opin Neurol 2023; 36:335-337. [PMID: 37462047 DOI: 10.1097/wco.0000000000001179] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/20/2023]
Affiliation(s)
- Peter Bede
- Computational Neuroimaging Group, School of Medicine, Trinity College
- Department of Neurology, St James's Hospital, Dublin, Ireland
- Department of Neurology, Pitié-Salpêtrière University Hospital
| | - Pierre-Francois Pradat
- Department of Neurology, Pitié-Salpêtrière University Hospital
- Laboratoire d'Imagerie Biomédicale, Sorbonne University, CNRS, INSERM, Paris, France
| |
Collapse
|
10
|
Ravnik Glavač M, Mezzavilla M, Dolinar A, Koritnik B, Glavač D. Aberrantly Expressed Hsa_circ_0060762 and CSE1L as Potential Peripheral Blood Biomarkers for ALS. Biomedicines 2023; 11:biomedicines11051316. [PMID: 37238987 DOI: 10.3390/biomedicines11051316] [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: 03/24/2023] [Revised: 04/25/2023] [Accepted: 04/26/2023] [Indexed: 05/28/2023] Open
Abstract
Amyotrophic lateral sclerosis (ALS) is a rapidly progressive adult-onset neurodegenerative disease that is often diagnosed with a delay due to initial non-specific symptoms. Therefore, reliable and easy-to-obtain biomarkers are an absolute necessity for earlier and more accurate diagnostics. Circular RNAs (circRNAs) have already been proposed as potential biomarkers for several neurodegenerative diseases. In this study, we further investigated the usefulness of circRNAs as potential biomarkers for ALS. We first performed a microarray analysis of circRNAs on peripheral blood mononuclear cells of a subset of ALS patients and controls. Among the differently expressed circRNA by microarray analysis, we selected only the ones with a host gene that harbors the highest level of conservation and genetic constraints. This selection was based on the hypothesis that genes under selective pressure and genetic constraints could have a major role in determining a trait or disease. Then we performed a linear regression between ALS cases and controls using each circRNA as a predictor variable. With a False Discovery Rate (FDR) threshold of 0.1, only six circRNAs passed the filtering and only one of them remained statistically significant after Bonferroni correction: hsa_circ_0060762 and its host gene CSE1L. Finally, we observed a significant difference in expression levels between larger sets of patients and healthy controls for both hsa_circ_0060762 and CSE1L. CSE1L is a member of the importin β family and mediates inhibition of TDP-43 aggregation; the central pathogenicity in ALS and hsa_circ_0060762 has binding sites for several miRNAs that have been already proposed as biomarkers for ALS. In addition, receiver operating characteristics curve analysis showed diagnostic potential for CSE1L and hsa_circ_0060762. Hsa_circ_0060762 and CSE1L thus represent novel potential peripheral blood biomarkers and therapeutic targets for ALS.
Collapse
Affiliation(s)
- Metka Ravnik Glavač
- Institute of Biochemistry and Molecular Genetics, Faculty of Medicine, University of Ljubljana, 1000 Ljubljana, Slovenia
| | | | - Ana Dolinar
- Department of Molecular Genetics, Institute of Pathology, Faculty of Medicine, University of Ljubljana, 1000 Ljubljana, Slovenia
| | - Blaž Koritnik
- Institute of Clinical Neurophysiology, Division of Neurology, University Medical Centre Ljubljana, 1000 Ljubljana, Slovenia
- Department of Neurology, Faculty of Medicine, University of Ljubljana, 1000 Ljubljana, Slovenia
| | - Damjan Glavač
- Department of Molecular Genetics, Institute of Pathology, Faculty of Medicine, University of Ljubljana, 1000 Ljubljana, Slovenia
- Center for Human Genetics & Pharmacogenomics, Faculty of Medicine, University of Maribor, 2000 Maribor, Slovenia
| |
Collapse
|
11
|
Tahedl M, Tan EL, Chipika RH, Hengeveld JC, Vajda A, Doherty MA, McLaughlin RL, Siah WF, Hardiman O, Bede P. Brainstem-cortex disconnection in amyotrophic lateral sclerosis: bulbar impairment, genotype associations, asymptomatic changes and biomarker opportunities. J Neurol 2023:10.1007/s00415-023-11682-6. [PMID: 37022479 DOI: 10.1007/s00415-023-11682-6] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2023] [Revised: 03/19/2023] [Accepted: 03/21/2023] [Indexed: 04/07/2023]
Abstract
BACKGROUND Bulbar dysfunction is a cardinal feature of ALS with important quality of life and management implications. The objective of this study is the longitudinal evaluation of a large panel imaging metrics pertaining to bulbar dysfunction, encompassing cortical measures, structural and functional cortico-medullary connectivity indices and brainstem metrics. METHODS A standardised, multimodal imaging protocol was implemented with clinical and genetic profiling to systematically appraise the biomarker potential of specific metrics. A total of 198 patients with ALS and 108 healthy controls were included. RESULTS Longitudinal analyses revealed progressive structural and functional disconnection between the motor cortex and the brainstem over time. Cortical thickness reduction was an early feature on cross-sectional analyses with limited further progression on longitudinal follow-up. Receiver operating characteristic analyses of the panel of MR metrics confirmed the discriminatory potential of bulbar imaging measures between patients and controls and area-under-the-curve values increased significantly on longitudinal follow-up. C9orf72 carriers exhibited lower brainstem volumes, lower cortico-medullary structural connectivity and faster cortical thinning. Sporadic patients without bulbar symptoms, already exhibit significant brainstem and cortico-medullary connectivity alterations. DISCUSSION Our results indicate that ALS is associated with multi-level integrity change from cortex to brainstem. The demonstration of significant corticobulbar alterations in patients without bulbar symptoms confirms considerable presymptomatic disease burden in sporadic ALS. The systematic assessment of radiological measures in a single-centre academic study helps to appraise the diagnostic and monitoring utility of specific measures for future clinical and clinical trial applications.
Collapse
Affiliation(s)
- Marlene Tahedl
- Computational Neuroimaging Group (CNG), Trinity Biomedical Sciences Institute, Trinity College Dublin, Room 5.43, Pearse Street, Dublin 2, Dublin, Ireland
| | - Ee Ling Tan
- Computational Neuroimaging Group (CNG), Trinity Biomedical Sciences Institute, Trinity College Dublin, Room 5.43, Pearse Street, Dublin 2, Dublin, Ireland
| | - Rangariroyashe H Chipika
- Computational Neuroimaging Group (CNG), Trinity Biomedical Sciences Institute, Trinity College Dublin, Room 5.43, Pearse Street, Dublin 2, Dublin, Ireland
| | | | - Alice Vajda
- Smurfit Institute of Genetics, Trinity College Dublin, Dublin, Ireland
| | - Mark A Doherty
- Smurfit Institute of Genetics, Trinity College Dublin, Dublin, Ireland
| | | | - We Fong Siah
- Computational Neuroimaging Group (CNG), Trinity Biomedical Sciences Institute, Trinity College Dublin, Room 5.43, Pearse Street, Dublin 2, Dublin, Ireland
| | - Orla Hardiman
- Computational Neuroimaging Group (CNG), Trinity Biomedical Sciences Institute, Trinity College Dublin, Room 5.43, Pearse Street, Dublin 2, Dublin, Ireland
| | - Peter Bede
- Computational Neuroimaging Group (CNG), Trinity Biomedical Sciences Institute, Trinity College Dublin, Room 5.43, Pearse Street, Dublin 2, Dublin, Ireland.
- Department of Neurology, St James's Hospital, Dublin, Ireland.
| |
Collapse
|
12
|
Pérez-Millan A, Borrego-Écija S, van Swieten JC, Jiskoot L, Moreno F, Laforce R, Graff C, Masellis M, Tartaglia MC, Rowe JB, Borroni B, Finger E, Synofzik M, Galimberti D, Vandenberghe R, de Mendonça A, Butler CR, Gerhard A, Ducharme S, Le Ber I, Santana I, Pasquier F, Levin J, Otto M, Sorbi S, Tiraboschi P, Seelaar H, Langheinrich T, Rohrer JD, Sala-Llonch R, Sánchez-Valle R. Loss of brainstem white matter predicts onset and motor neuron symptoms in C9orf72 expansion carriers: a GENFI study. J Neurol 2023; 270:1573-1586. [PMID: 36443488 DOI: 10.1007/s00415-022-11435-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Revised: 10/17/2022] [Accepted: 10/18/2022] [Indexed: 11/30/2022]
Abstract
BACKGROUND AND OBJECTIVES The C9orf72 expansion is the most common genetic cause of frontotemporal dementia (FTD) and/or motor neuron disease (MND). Corticospinal degeneration has been described in post-mortem neuropathological studies in these patients, especially in those with MND. We used MRI to analyze white matter (WM) volumes in presymptomatic and symptomatic C9orf72 expansion carriers and investigated whether its measure may be helpful in predicting the onset of symptoms. METHODS We studied 102 presymptomatic C9orf72 mutation carriers, 52 symptomatic carriers: 42 suffering from FTD and 11 from MND, and 75 non-carriers from the Genetic Frontotemporal dementia Initiative (GENFI). All subjects underwent T1-MRI acquisition. We used FreeSurfer to estimate the volume proportion of WM in the brainstem regions (midbrain, pons, and medulla oblongata). We calculated group differences with ANOVA tests and performed linear and non-linear regressions to assess group-by-age interactions. RESULTS A reduced WM ratio was found in all brainstem subregions in symptomatic carriers compared to both noncarriers and pre-symptomatic carriers. Within symptomatic carriers, MND patients presented a lower ratio in pons and medulla oblongata compared with FTD patients. No differences were found between presymptomatic carriers and non-carriers. Clinical severity was negatively associated with the WM ratio. C9orf72 carriers presented greater age-related WM loss than non-carriers, with MND patients showing significantly more atrophy in pons and medulla oblongata. DISCUSSION We find consistent brainstem WM loss in C9orf72 symptomatic carriers with differences related to the clinical phenotype supporting the use of brainstem measures as neuroimaging biomarkers for disease tracking.
Collapse
Affiliation(s)
- Agnès Pérez-Millan
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, Institut d'Investigacions Biomèdiques August Pi I Sunyer, University of Barcelona, Villarroel, 170, 08036, Barcelona, Spain
- Department of Biomedicine, Faculty of Medicine, Institute of Neurosciences, University of Barcelona, 08036, Barcelona, Spain
| | - Sergi Borrego-Écija
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, Institut d'Investigacions Biomèdiques August Pi I Sunyer, University of Barcelona, Villarroel, 170, 08036, Barcelona, Spain
| | - John C van Swieten
- Department of Neurology and Alzheimer Center Erasmus MC, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Lize Jiskoot
- Department of Neurology and Alzheimer Center Erasmus MC, Erasmus MC University Medical Center, Rotterdam, The Netherlands
- Department of Neurodegenerative Disease, Dementia Research Centre, UCL Institute of Neurology, Queen Square, London, UK
| | - Fermin Moreno
- Cognitive Disorders Unit, Department of Neurology, Donostia University Hospital, San Sebastian, Gipuzkoa, Spain
- Neuroscience Area, Biodonostia Health Research Institute, San Sebastian, Gipuzkoa, Spain
| | - Robert Laforce
- Département des Sciences Neurologiques, Clinique Interdisciplinaire de Mémoire, CHU de Québec, and Faculté de Médecine, Université Laval, Quebec City, QC, Canada
| | - Caroline Graff
- Division of Neurogeriatrics, Department of Neurobiology, Care Sciences and Society, Bioclinicum, Center for Alzheimer Research, Karolinska Institutet, Solna, Sweden
- Unit for Hereditary Dementias, Theme Aging, Karolinska University Hospital, Solna, Sweden
| | - Mario Masellis
- Sunnybrook Health Sciences Centre, Sunnybrook Research Institute, University of Toronto, Toronto, Canada
| | - Maria Carmela Tartaglia
- Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, Toronto, Canada
| | - James B Rowe
- Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust and Medical Research Council Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
| | - Barbara Borroni
- Department of Clinical and Experimental Sciences, Centre for Neurodegenerative Disorders, University of Brescia, Brescia, Italy
| | - Elizabeth Finger
- Department of Clinical Neurological Sciences, University of Western Ontario, London, ON, Canada
| | - Matthis Synofzik
- Department of Neurodegenerative Diseases, Hertie-Institute for Clinical Brain Research and Center of Neurology, University of Tübingen, Tübingen, Germany
- Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany
| | - Daniela Galimberti
- Department of Biomedical, Surgical and Dental Sciences, University of Milan, Milan, Italy
- Fondazione IRCCS Ca' Granda, Ospedale Maggiore Policlinico, Milan, Italy
| | - Rik Vandenberghe
- Laboratory for Cognitive Neurology, Department of Neurosciences, KU Leuven, Leuven, Belgium
- Neurology Service, University Hospitals Leuven, Leuven, Belgium
| | | | - Chris R Butler
- Nuffield Department of Clinical Neurosciences, Medical Sciences Division, University of Oxford, Oxford, UK
- Department of Brain Sciences, Imperial College London, London, UK
| | - Alexander Gerhard
- Division of Neuroscience and Experimental Psychology, Wolfson Molecular Imaging Centre, University of Manchester, Manchester, UK
- Department of Geriatric Medicine and Nuclear Medicine, Center for Translational Neuro- and Behavioral Sciences, University Medicine Essen, Essen, Germany
| | - Simon Ducharme
- Department of Psychiatry, Douglas Mental Health University Institute, McGill University, Montreal, Canada
- Department of Neurology and Neurosurgery, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Canada
| | - Isabelle Le Ber
- Sorbonne Université, Paris Brain Institute - Institut du Cerveau - ICM, Inserm U1127, CNRS UMR 7225, AP-HP - Hôpital Pitié-Salpêtrière (DMU Neurosciences Paris 6), Paris, France
- Département de Neurologie, AP-HP - Hôpital Pitié-Salpêtrière (DMU Neurosciences Paris 6), Paris, France
| | - Isabel Santana
- Neurology Service, Faculty of Medicine, University Hospital of Coimbra (HUC), University of Coimbra, Coimbra, Portugal
- Center for Neuroscience and Cell Biology, Faculty of Medicine, University of Coimbra, Coimbra, Portugal
| | - Florence Pasquier
- Univ Lille, Lille, France
- CHU, CNR-MAJ, Labex Distalz, LiCEND, Lille, France
| | - Johannes Levin
- Neurologische Klinik und Poliklinik, Ludwig-Maximilians-Universität, Munich, Germany
- German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
| | - Markus Otto
- Department of Neurology, University of Ulm, Ulm, Germany
| | - Sandro Sorbi
- Department of Neurofarba, University of Florence, Florence, Italy
| | | | - Harro Seelaar
- Department of Neurology and Alzheimer Center Erasmus MC, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Tobias Langheinrich
- Division of Neuroscience and Experimental Psychology, Wolfson Molecular Imaging Centre, University of Manchester, Manchester, UK
| | - Jonathan D Rohrer
- Department of Neurodegenerative Disease, Dementia Research Centre, UCL Institute of Neurology, Queen Square, London, UK
| | - Roser Sala-Llonch
- Department of Biomedicine, Faculty of Medicine, Institute of Neurosciences, University of Barcelona, 08036, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Barcelona, Spain
| | - Raquel Sánchez-Valle
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, Institut d'Investigacions Biomèdiques August Pi I Sunyer, University of Barcelona, Villarroel, 170, 08036, Barcelona, Spain.
| | | |
Collapse
|
13
|
McKenna MC, Lope J, Bede P, Tan EL. Thalamic pathology in frontotemporal dementia: Predilection for specific nuclei, phenotype-specific signatures, clinical correlates, and practical relevance. Brain Behav 2023; 13:e2881. [PMID: 36609810 PMCID: PMC9927864 DOI: 10.1002/brb3.2881] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Revised: 12/17/2022] [Accepted: 12/18/2022] [Indexed: 01/09/2023] Open
Abstract
BACKGROUND Frontotemporal dementia (FTD) phenotypes are classically associated with distinctive cortical atrophy patterns and regional hypometabolism. However, the spectrum of cognitive and behavioral manifestations in FTD arises from multisynaptic network dysfunction. The thalamus is a key hub of several corticobasal and corticocortical circuits. The main circuits relayed via the thalamic nuclei include the dorsolateral prefrontal circuit, the anterior cingulate circuit, and the orbitofrontal circuit. METHODS In this paper, we have reviewed evidence for thalamic pathology in FTD based on radiological and postmortem studies. Original research papers were systematically reviewed for preferential involvement of specific thalamic regions, for phenotype-associated thalamic disease burden patterns, characteristic longitudinal changes, and genotype-associated thalamic signatures. Moreover, evidence for presymptomatic thalamic pathology was also reviewed. Identified papers were systematically scrutinized for imaging methods, cohort sizes, clinical profiles, clinicoradiological associations, and main anatomical findings. The findings of individual research papers were amalgamated for consensus observations and their study designs further evaluated for stereotyped shortcomings. Based on the limitations of existing studies and conflicting reports in low-incidence FTD variants, we sought to outline future research directions and pressing research priorities. RESULTS FTD is associated with focal thalamic degeneration. Phenotype-specific thalamic traits mirror established cortical vulnerability patterns. Thalamic nuclei mediating behavioral and language functions are preferentially involved. Given the compelling evidence for considerable thalamic disease burden early in the course of most FTD subtypes, we also reflect on the practical relevance, diagnostic role, prognostic significance, and monitoring potential of thalamic metrics in FTD. CONCLUSIONS Cardinal manifestations of FTD phenotypes are likely to stem from thalamocortical circuitry dysfunction and are not exclusively driven by focal cortical changes.
Collapse
Affiliation(s)
- Mary Clare McKenna
- Computational Neuroimaging Group, Trinity Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland.,Department of Neurology, St James's Hospital, Dublin, Ireland
| | - Jasmin Lope
- Computational Neuroimaging Group, Trinity Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland
| | - Peter Bede
- Computational Neuroimaging Group, Trinity Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland.,Department of Neurology, St James's Hospital, Dublin, Ireland
| | - Ee Ling Tan
- Computational Neuroimaging Group, Trinity Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland
| |
Collapse
|
14
|
Barbo M, Ravnik-Glavač M. Extracellular Vesicles as Potential Biomarkers in Amyotrophic Lateral Sclerosis. Genes (Basel) 2023; 14:genes14020325. [PMID: 36833252 PMCID: PMC9956314 DOI: 10.3390/genes14020325] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2022] [Revised: 01/19/2023] [Accepted: 01/20/2023] [Indexed: 01/28/2023] Open
Abstract
Amyotrophic lateral sclerosis (ALS) is described as a fatal and rapidly progressive neurodegenerative disorder caused by the degeneration of upper motor neurons in the primary motor cortex and lower motor neurons of the brainstem and spinal cord. Due to ALS's slowly progressive characteristic, which is often accompanied by other neurological comorbidities, its diagnosis remains challenging. Perturbations in vesicle-mediated transport and autophagy as well as cell-autonomous disease initiation in glutamatergic neurons have been revealed in ALS. The use of extracellular vesicles (EVs) may be key in accessing pathologically relevant tissues for ALS, as EVs can cross the blood-brain barrier and be isolated from the blood. The number and content of EVs may provide indications of the disease pathogenesis, its stage, and prognosis. In this review, we collected a recent study aiming at the identification of EVs as a biomarker of ALS with respect to the size, quantity, and content of EVs in the biological fluids of patients compared to controls.
Collapse
|
15
|
Toh C, Keslake A, Payne T, Onwuegbuzie A, Harding J, Baster K, Hoggard N, Shaw PJ, Wilkinson ID, Jenkins TM. Analysis of brain and spinal MRI measures in a common domain to investigate directional neurodegeneration in motor neuron disease. J Neurol 2023; 270:1682-1690. [PMID: 36509983 PMCID: PMC9971079 DOI: 10.1007/s00415-022-11520-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Revised: 11/26/2022] [Accepted: 12/06/2022] [Indexed: 12/14/2022]
Abstract
BACKGROUND Magnetic resonance imaging (MRI) of the brain and cervical spinal cord is often performed in diagnostic evaluation of suspected motor neuron disease/amyotrophic lateral sclerosis (MND/ALS). Analysis of MRI-derived tissue damage metrics in a common domain facilitates group-level inferences on pathophysiology. This approach was applied to address competing hypotheses of directionality of neurodegeneration, whether anterograde, cranio-caudal dying-forward from precentral gyrus or retrograde, dying-back. METHODS In this cross-sectional study, MRI was performed on 75 MND patients and 13 healthy controls. Precentral gyral thickness was estimated from volumetric T1-weighted images using FreeSurfer, corticospinal tract fractional anisotropy (FA) from diffusion tensor imaging using FSL, and cross-sectional cervical cord area between C1-C8 levels using Spinal Cord Toolbox. To analyse these multimodal data within a common domain, individual parameter estimates representing tissue damage at each corticospinal tract level were first converted to z-scores, referenced to healthy control norms. Mixed-effects linear regression models were then fitted to these z-scores, with gradients hypothesised to represent directionality of neurodegeneration. RESULTS At group-level, z-scores did not differ significantly between precentral gyral and intracranial corticospinal tract tissue damage estimates (regression coefficient - 0.24, [95% CI - 0.62, 0.14], p = 0.222), but step-changes were evident between intracranial corticospinal tract and C1 (1.14, [95% CI 0.74, 1.53], p < 0.001), and between C5 and C6 cord levels (0.98, [95% CI 0.58, 1.38], p < 0.001). DISCUSSION Analysis of brain and cervical spinal MRI data in a common domain enabled investigation of pathophysiological hypotheses in vivo. A cranio-caudal step-change in MND patients was observed, and requires further investigation in larger cohorts.
Collapse
Affiliation(s)
- C Toh
- Sheffield Institute for Translational Neuroscience, University of Sheffield, Sheffield, UK
| | - A Keslake
- Sheffield Institute for Translational Neuroscience, University of Sheffield, Sheffield, UK
| | - T Payne
- Sheffield Institute for Translational Neuroscience, University of Sheffield, Sheffield, UK
| | - A Onwuegbuzie
- Sheffield Institute for Translational Neuroscience, University of Sheffield, Sheffield, UK
| | - J Harding
- Sheffield Institute for Translational Neuroscience, University of Sheffield, Sheffield, UK
| | - K Baster
- School of Mathematics and Statistics, University of Sheffield, Sheffield, UK
| | - N Hoggard
- Academic Unit of Radiology, University of Sheffield, Sheffield, UK
- Sheffield Teaching Hospitals NHS Foundation Trust, Sheffield, UK
| | - P J Shaw
- Sheffield Institute for Translational Neuroscience, University of Sheffield, Sheffield, UK
- Sheffield Teaching Hospitals NHS Foundation Trust, Sheffield, UK
| | - I D Wilkinson
- Academic Unit of Radiology, University of Sheffield, Sheffield, UK
| | - T M Jenkins
- Sheffield Institute for Translational Neuroscience, University of Sheffield, Sheffield, UK.
- Royal Perth Hospital, Victoria Square, Perth, WA, 6000, Australia.
| |
Collapse
|
16
|
Rezende TJR, Adanyeguh IM, Arrigoni F, Bender B, Cendes F, Corben LA, Deistung A, Delatycki M, Dogan I, Egan GF, Göricke SL, Georgiou-Karistianis N, Henry PG, Hutter D, Jahanshad N, Joers JM, Lenglet C, Lindig T, Martinez ARM, Martinuzzi A, Paparella G, Peruzzo D, Reetz K, Romanzetti S, Schöls L, Schulz JB, Synofzik M, Thomopoulos SI, Thompson PM, Timmann D, Harding IH, França MC. Progressive Spinal Cord Degeneration in Friedreich's Ataxia: Results from ENIGMA-Ataxia. Mov Disord 2023; 38:45-56. [PMID: 36308733 PMCID: PMC9852007 DOI: 10.1002/mds.29261] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2022] [Revised: 08/23/2022] [Accepted: 10/04/2022] [Indexed: 01/22/2023] Open
Abstract
BACKGROUND Spinal cord damage is a hallmark of Friedreich's ataxia (FRDA), but its progression and clinical correlates remain unclear. OBJECTIVE The objective of this study was to perform a characterization of cervical spinal cord structural damage in a large multisite FRDA cohort. METHODS We performed a cross-sectional analysis of cervical spinal cord (C1-C4) cross-sectional area (CSA) and eccentricity using magnetic resonance imaging data from eight sites within the ENIGMA-Ataxia initiative, including 256 individuals with FRDA and 223 age- and sex-matched control subjects. Correlations and subgroup analyses within the FRDA cohort were undertaken based on disease duration, ataxia severity, and onset age. RESULTS Individuals with FRDA, relative to control subjects, had significantly reduced CSA at all examined levels, with large effect sizes (d > 2.1) and significant correlations with disease severity (r < -0.4). Similarly, we found significantly increased eccentricity (d > 1.2), but without significant clinical correlations. Subgroup analyses showed that CSA and eccentricity are abnormal at all disease stages. However, although CSA appears to decrease progressively, eccentricity remains stable over time. CONCLUSIONS Previous research has shown that increased eccentricity reflects dorsal column (DC) damage, while decreased CSA reflects either DC or corticospinal tract (CST) damage, or both. Hence our data support the hypothesis that damage to the DC and damage to CST follow distinct courses in FRDA: developmental abnormalities likely define the DC, while CST alterations may be both developmental and degenerative. These results provide new insights about FRDA pathogenesis and indicate that CSA of the cervical spinal cord should be investigated further as a potential biomarker of disease progression. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
Collapse
Affiliation(s)
- Thiago JR Rezende
- Department of Neurology, School of Medical Sciences, University of Campinas (UNICAMP), Campinas, SP, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), School of Medical Sciences, University of Campinas (UNICAMP), Campinas, SP, Brazil
| | - Isaac M Adanyeguh
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA
| | - Filippo Arrigoni
- Neuroimaging Unit, Scientific Institute, IRCCS Eugenio Medea, Bosisio Parini, Italy
| | - Benjamin Bender
- Department of Diagnostic and Interventional Neuroradiology, University Hospital Tübingen, Tübingen, Germany
| | - Fernando Cendes
- Department of Neurology, School of Medical Sciences, University of Campinas (UNICAMP), Campinas, SP, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), School of Medical Sciences, University of Campinas (UNICAMP), Campinas, SP, Brazil
| | - Louise A Corben
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, VIC, Australia
- Bruce Lefroy Centre, Murdoch Children’s Research Institute, Parkville, VIC, Australia
- Department of Paediatrics, University of Melbourne, Parkville, VIC, Australia
| | - Andreas Deistung
- University Clinic and Outpatient Clinic for Radiology, Department for Radiation Medicine, University Hospital Halle (Saale), Halle (Saale), Germany
- Department of Neurology and Center for Translational and Behavioral Neuroscience “(C-TNBS), Essen University Hospital, University of Duisburg-Essen, Essen, Germany
| | - Martin Delatycki
- Bruce Lefroy Centre, Murdoch Children’s Research Institute, Parkville, VIC, Australia
- Department of Paediatrics, University of Melbourne, Parkville, VIC, Australia
| | - Imis Dogan
- Department of Neurology, RWTH Aachen University, Aachen, Germany
- JARA-BRAIN Institute Molecular Neuroscience and Neuroimaging, Research Center Jülich GmbH, Jülich, Germany
| | - Gary F Egan
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, VIC, Australia
- Monash Biomedical Imaging, Monash University, Clayton, VIC, Australia
| | - Sophia L Göricke
- Institute of Diagnostic and Interventional Radiology and Neuroradiology, Essen University Hospital, University of Duisburg-Essen, Essen, Germany
| | - Nellie Georgiou-Karistianis
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, VIC, Australia
| | - Pierre-Gilles Henry
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA
| | - Diane Hutter
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA
| | - Neda Jahanshad
- Imaging Genetics Center, Mark and Mary Stevens Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - James M Joers
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA
| | - Christophe Lenglet
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA
| | - Tobias Lindig
- Department of Diagnostic and Interventional Neuroradiology, University Hospital Tübingen, Tübingen, Germany
| | - Alberto RM Martinez
- Department of Neurology, School of Medical Sciences, University of Campinas (UNICAMP), Campinas, SP, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), School of Medical Sciences, University of Campinas (UNICAMP), Campinas, SP, Brazil
| | - Andrea Martinuzzi
- Scientific Institute, IRCCS Eugenio Medea, Conegliano-Pieve di Soligo Research Centre, Conegliano, Italy
| | - Gabriella Paparella
- Scientific Institute, IRCCS Eugenio Medea, Conegliano-Pieve di Soligo Research Centre, Conegliano, Italy
| | - Denis Peruzzo
- Neuroimaging Unit, Scientific Institute, IRCCS Eugenio Medea, Bosisio Parini, Italy
| | - Kathrin Reetz
- Department of Neurology, RWTH Aachen University, Aachen, Germany
- JARA-BRAIN Institute Molecular Neuroscience and Neuroimaging, Research Center Jülich GmbH, Jülich, Germany
| | - Sandro Romanzetti
- Department of Neurology, RWTH Aachen University, Aachen, Germany
- JARA-BRAIN Institute Molecular Neuroscience and Neuroimaging, Research Center Jülich GmbH, Jülich, Germany
| | - Ludger Schöls
- Department of Neurodegenerative Diseases, Center of Neurology and Hertie Institute for Clinical Brain Research,University Tuübingen, Tübingen, Germany
- German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany
| | - Jörg B Schulz
- Department of Neurology, RWTH Aachen University, Aachen, Germany
- JARA-BRAIN Institute Molecular Neuroscience and Neuroimaging, Research Center Jülich GmbH, Jülich, Germany
| | - Matthis Synofzik
- Department of Neurodegenerative Diseases, Center of Neurology and Hertie Institute for Clinical Brain Research,University Tuübingen, Tübingen, Germany
- German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany
| | - Sophia I Thomopoulos
- Imaging Genetics Center, Mark and Mary Stevens Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Paul M Thompson
- Imaging Genetics Center, Mark and Mary Stevens Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Dagmar Timmann
- Department of Neurology and Center for Translational and Behavioral Neuroscience “(C-TNBS), Essen University Hospital, University of Duisburg-Essen, Essen, Germany
| | - Ian H Harding
- Monash Biomedical Imaging, Monash University, Clayton, VIC, Australia
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, VIC, Australia
| | - Marcondes C. França
- Department of Neurology, School of Medical Sciences, University of Campinas (UNICAMP), Campinas, SP, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), School of Medical Sciences, University of Campinas (UNICAMP), Campinas, SP, Brazil
| |
Collapse
|
17
|
Banack SA, Dunlop RA, Stommel EW, Mehta P, Cox PA. miRNA extracted from extracellular vesicles is a robust biomarker of amyotrophic lateral sclerosis. J Neurol Sci 2022; 442:120396. [PMID: 36081303 DOI: 10.1016/j.jns.2022.120396] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Revised: 08/18/2022] [Accepted: 08/24/2022] [Indexed: 10/31/2022]
Abstract
BACKGROUND AND OBJECTIVES We examined miRNA biomarkers for ALS extracted from extracellular vesicles in blood samples using a large and diverse patient and control population. Different blood collection and storage protocols by different investigators could impact repeatability of miRNA analysis. We tested the hypotheses that miRNA extracted from extracellular vesicles using immunoaffinity purification techniques are robust and repeatable across investigators, laboratories and in a broad ALS population. METHODS De-identified patient blood plasma samples obtained from the U.S. National ALS Biorepository were compared with plasma from non-ALS controls. Extracellular vesicles were extracted and isolated using L1CAM immunoaffinity purification. Total RNA was extracted, and miRNA quantified using qPCR following careful quality control measures. Gene fold expressions of eight miRNAs were compared using a Mann-Whitney two-tailed test. RESULTS One hundred blinded, blood plasma samples were analyzed. Thirty-five men and 15 women with ALS were compared with controls consisting of 30 men and 20 women. None of the ALS patient cohort reported family members with ALS suggesting sporadic ALS. Five of the eight biomarkers previously published were found to significantly discriminate ALS patient samples from control samples. DISCUSSION The methods used in this study provide a repeatable measure of miRNA biomarkers that statistically differentiate ALS patient samples from control samples. The broad inclusion criteria for both the ALS patient cohort and controls along with the collection of blood samples by different investigators suggest that these methods are robust and represent good candidates for further research and development aimed at clinical application.
Collapse
Affiliation(s)
| | | | - Elijah W Stommel
- Department of Neurology, Dartmouth-Hitchcock Medical Center, Lebanon, NH, USA
| | - Paul Mehta
- Centers for Disease Control and Prevention/Agency for Toxic Substances and Disease Registry, National ALS Registry (CDC/ATSDR), Atlanta, GA, USA
| | | |
Collapse
|
18
|
Chipika RH, Mulkerrin G, Pradat PF, Murad A, Ango F, Raoul C, Bede P. Cerebellar pathology in motor neuron disease: neuroplasticity and neurodegeneration. Neural Regen Res 2022; 17:2335-2341. [PMID: 35535867 PMCID: PMC9120698 DOI: 10.4103/1673-5374.336139] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
Amyotrophic lateral sclerosis is a relentlessly progressive multi-system condition. The clinical picture is dominated by upper and lower motor neuron degeneration, but extra-motor pathology is increasingly recognized, including cerebellar pathology. Post-mortem and neuroimaging studies primarily focus on the characterization of supratentorial disease, despite emerging evidence of cerebellar degeneration in amyotrophic lateral sclerosis. Cardinal clinical features of amyotrophic lateral sclerosis, such as dysarthria, dysphagia, cognitive and behavioral deficits, saccade abnormalities, gait impairment, respiratory weakness and pseudobulbar affect are likely to be exacerbated by co-existing cerebellar pathology. This review summarizes in vivo and post mortem evidence for cerebellar degeneration in amyotrophic lateral sclerosis. Structural imaging studies consistently capture cerebellar grey matter volume reductions, diffusivity studies readily detect both intra-cerebellar and cerebellar peduncle white matter alterations and functional imaging studies commonly report increased functional connectivity with supratentorial regions. Increased functional connectivity is commonly interpreted as evidence of neuroplasticity representing compensatory processes despite the lack of post-mortem validation. There is a scarcity of post-mortem studies focusing on cerebellar alterations, but these detect pTDP-43 in cerebellar nuclei. Cerebellar pathology is an overlooked facet of neurodegeneration in amyotrophic lateral sclerosis despite its contribution to a multitude of clinical symptoms, widespread connectivity to spinal and supratentorial regions and putative role in compensating for the degeneration of primary motor regions.
Collapse
Affiliation(s)
- Rangariroyashe H Chipika
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland
| | - Grainne Mulkerrin
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland
| | | | - Aizuri Murad
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland
| | - Fabrice Ango
- The Neuroscience Institute of Montpellier (INM), INSERM, CNRS, Montpellier, France
| | - Cédric Raoul
- The Neuroscience Institute of Montpellier (INM), INSERM, CNRS, Montpellier, France
| | - Peter Bede
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland; Pitié-Salpêtrière University Hospital, Sorbonne University, Paris, France
| |
Collapse
|
19
|
Corcia P, Hergesheimer R, Couratier P. The future of ALS comes from its past. Rev Neurol (Paris) 2022; 178:754-755. [PMID: 36116983 DOI: 10.1016/j.neurol.2022.07.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2022] [Revised: 07/20/2022] [Accepted: 07/21/2022] [Indexed: 11/17/2022]
Affiliation(s)
- P Corcia
- Centre SLA, CHU Bretonneau, 2, boulevard Tonnelle, 37044 Tours Cedex 1, France; UMR 1253 iBrain neurogénomique et physiopathologie neuronale, université de Tours, Inserm, Tours, France.
| | - R Hergesheimer
- UMR 1253 iBrain neurogénomique et physiopathologie neuronale, université de Tours, Inserm, Tours, France
| | - P Couratier
- Centre SLA, CHU de Limoges, 2, avenue Martin Luther King, 87000 Limoges, France
| |
Collapse
|
20
|
Mulkerrin G, França MC, Lope J, Tan EL, Bede P. Neuroimaging in hereditary spastic paraplegias: from qualitative cues to precision biomarkers. Expert Rev Mol Diagn 2022; 22:745-760. [PMID: 36042576 DOI: 10.1080/14737159.2022.2118048] [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: 01/18/2023]
Abstract
INTRODUCTION : Hereditary spastic paraplegias (HSP) include a clinically and genetically heterogeneous group of conditions. Novel imaging modalities have been increasingly applied to HSP cohorts which helps to quantitatively evaluate the integrity of specific anatomical structures and develop monitoring markers for both clinical care and future clinical trials. AREAS COVERED : Advances in HSP imaging are systematically reviewed with a focus on cohort sizes, imaging modalities, study design, clinical correlates, methodological approaches, and key findings. EXPERT OPINION : A wide range of imaging techniques have been recently applied to HSP cohorts. Common shortcomings of existing studies include the evaluation of genetically unconfirmed or admixed cohorts, limited sample sizes, unimodal imaging approaches, lack of postmortem validation, and a limited clinical battery, often exclusively focusing on motor aspects of the condition. A number of innovative methodological approaches have also be identified, such as robust longitudinal study designs, the implementation of multimodal imaging protocols, complementary cognitive assessments, and the comparison of HSP cohorts to MND cohorts. Collaborative multicentre initiatives may overcome sample limitations, and comprehensive clinical profiling with motor, extrapyramidal, cerebellar, and neuropsychological assessments would permit systematic clinico-radiological correlations. Academic achievements in HSP imaging have the potential to be developed into viable clinical applications to expedite the diagnosis and monitor disease progression.
Collapse
Affiliation(s)
| | - Marcondes C França
- Department of Neurology, The State University of Campinas, São Paulo, Brazil
| | - Jasmin Lope
- Computational Neuroimaging Group, Trinity College Dublin, Ireland
| | - Ee Ling Tan
- Computational Neuroimaging Group, Trinity College Dublin, Ireland
| | - Peter Bede
- Department of Neurology, St James's Hospital, Dublin, Ireland.,Computational Neuroimaging Group, Trinity College Dublin, Ireland
| |
Collapse
|
21
|
Zejlon C, Nakhostin D, Winklhofer S, Pangalu A, Kulcsar Z, Lewandowski S, Finnsson J, Piehl F, Ingre C, Granberg T, Ineichen BV. Structural magnetic resonance imaging findings and histopathological correlations in motor neuron diseases—A systematic review and meta-analysis. Front Neurol 2022; 13:947347. [PMID: 36110394 PMCID: PMC9468579 DOI: 10.3389/fneur.2022.947347] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Accepted: 07/08/2022] [Indexed: 11/13/2022] Open
Abstract
ObjectivesThe lack of systematic evidence on neuroimaging findings in motor neuron diseases (MND) hampers the diagnostic utility of magnetic resonance imaging (MRI). Thus, we aimed at performing a systematic review and meta-analysis of MRI features in MND including their histopathological correlation.MethodsIn a comprehensive literature search, out of 5941 unique publications, 223 records assessing brain and spinal cord MRI findings in MND were eligible for a qualitative synthesis. 21 records were included in a random effect model meta-analysis.ResultsOur meta-analysis shows that both T2-hyperintensities along the corticospinal tracts (CST) and motor cortex T2*-hypointensitites, also called “motor band sign”, are more prevalent in ALS patients compared to controls [OR 2.21 (95%-CI: 1.40–3.49) and 10.85 (95%-CI: 3.74–31.44), respectively]. These two imaging findings correlate to focal axonal degeneration/myelin pallor or glial iron deposition on histopathology, respectively. Additionally, certain clinical MND phenotypes such as amyotrophic lateral sclerosis (ALS) seem to present with distinct CNS atrophy patterns.ConclusionsAlthough CST T2-hyperintensities and the “motor band sign” are non-specific imaging features, they can be leveraged for diagnostic workup of suspected MND cases, together with certain brain atrophy patterns. Collectively, this study provides high-grade evidence for the usefulness of MRI in the diagnostic workup of suspected MND cases.Systematic review registrationhttps://www.crd.york.ac.uk/PROSPERO/, identifier: CRD42020182682.
Collapse
Affiliation(s)
- Charlotte Zejlon
- Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Dominik Nakhostin
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zürich, Switzerland
| | - Sebastian Winklhofer
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zürich, Switzerland
| | - Athina Pangalu
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zürich, Switzerland
| | - Zsolt Kulcsar
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zürich, Switzerland
| | | | - Johannes Finnsson
- Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Fredrik Piehl
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Center of Neurology, Academic Specialist Center, Stockholm Health Services, Stockholm, Sweden
| | - Caroline Ingre
- Department of Neurology, Karolinska University Hospital, Stockholm, Sweden
| | - Tobias Granberg
- Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Benjamin Victor Ineichen
- Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zürich, Switzerland
- *Correspondence: Benjamin Victor Ineichen
| |
Collapse
|
22
|
Juengling FD, Wuest F, Kalra S, Agosta F, Schirrmacher R, Thiel A, Thaiss W, Müller HP, Kassubek J. Simultaneous PET/MRI: The future gold standard for characterizing motor neuron disease-A clinico-radiological and neuroscientific perspective. Front Neurol 2022; 13:890425. [PMID: 36061999 PMCID: PMC9428135 DOI: 10.3389/fneur.2022.890425] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2022] [Accepted: 07/20/2022] [Indexed: 01/18/2023] Open
Abstract
Neuroimaging assessment of motor neuron disease has turned into a cornerstone of its clinical workup. Amyotrophic lateral sclerosis (ALS), as a paradigmatic motor neuron disease, has been extensively studied by advanced neuroimaging methods, including molecular imaging by MRI and PET, furthering finer and more specific details of the cascade of ALS neurodegeneration and symptoms, facilitated by multicentric studies implementing novel methodologies. With an increase in multimodal neuroimaging data on ALS and an exponential improvement in neuroimaging technology, the need for harmonization of protocols and integration of their respective findings into a consistent model becomes mandatory. Integration of multimodal data into a model of a continuing cascade of functional loss also calls for the best attempt to correlate the different molecular imaging measurements as performed at the shortest inter-modality time intervals possible. As outlined in this perspective article, simultaneous PET/MRI, nowadays available at many neuroimaging research sites, offers the perspective of a one-stop shop for reproducible imaging biomarkers on neuronal damage and has the potential to become the new gold standard for characterizing motor neuron disease from the clinico-radiological and neuroscientific perspectives.
Collapse
Affiliation(s)
- Freimut D. Juengling
- Division of Oncologic Imaging, University of Alberta, Edmonton, AB, Canada
- Neuroscience and Mental Health Institute, University of Alberta, Edmonton, AB, Canada
- Faculty of Medicine, University Bern, Bern, Switzerland
| | - Frank Wuest
- Division of Oncologic Imaging, University of Alberta, Edmonton, AB, Canada
| | - Sanjay Kalra
- Neuroscience and Mental Health Institute, University of Alberta, Edmonton, AB, Canada
- Department of Neurology, University of Alberta, Edmonton, AB, Canada
| | - Federica Agosta
- Division of Neuroscience, San Raffaele Scientific Institute, University Vita Salute San Raffaele, Milan, Italy
| | - Ralf Schirrmacher
- Division of Oncologic Imaging, University of Alberta, Edmonton, AB, Canada
- Medical Isotope and Cyclotron Facility, University of Alberta, Edmonton, AB, Canada
| | - Alexander Thiel
- Lady Davis Institute for Medical Research, Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
| | - Wolfgang Thaiss
- Department of Nuclear Medicine, University of Ulm Medical Center, Ulm, Germany
- Department of Diagnostic and Interventional Radiology, University of Ulm Medical Center, Ulm, Germany
| | - Hans-Peter Müller
- Department of Neurology, Ulm University Medical Center, Ulm, Germany
| | - Jan Kassubek
- Department of Neurology, Ulm University Medical Center, Ulm, Germany
| |
Collapse
|
23
|
McKenna MC, Lope J, Tan EL, Bede P. Pre-symptomatic radiological changes in frontotemporal dementia: propagation characteristics, predictive value and implications for clinical trials. Brain Imaging Behav 2022; 16:2755-2767. [PMID: 35920960 DOI: 10.1007/s11682-022-00711-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/19/2022] [Indexed: 11/25/2022]
Abstract
Computational imaging and quantitative biomarkers offer invaluable insights in the pre-symptomatic phase of neurodegenerative conditions several years before clinical manifestation. In recent years, there has been a focused effort to characterize pre-symptomatic cerebral changes in familial frontotemporal dementias using computational imaging. Accordingly, a systematic literature review was conducted of original articles investigating pre-symptomatic imaging changes in frontotemporal dementia focusing on study design, imaging modalities, data interpretation, control cohorts and key findings. The review is limited to the most common genotypes: chromosome 9 open reading frame 72 (C9orf72), progranulin (GRN), or microtubule-associated protein tau (MAPT) genotypes. Sixty-eight studies were identified with a median sample size of 15 (3-141) per genotype. Only a minority of studies were longitudinal (28%; 19/68) with a median follow-up of 2 (1-8) years. MRI (97%; 66/68) was the most common imaging modality, and primarily grey matter analyses were conducted (75%; 19/68). Some studies used multimodal analyses 44% (30/68). Genotype-associated imaging signatures are presented, innovative study designs are highlighted, common methodological shortcomings are discussed and lessons for future studies are outlined. Emerging academic observations have potential clinical implications for expediting the diagnosis, tracking disease progression and optimising the timing of pharmaceutical trials.
Collapse
Affiliation(s)
- Mary Clare McKenna
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Room 5.43, Pearse Street, Dublin 2, Ireland.,Department of Neurology, St James's Hospital, Dublin, Ireland
| | - Jasmin Lope
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Room 5.43, Pearse Street, Dublin 2, Ireland
| | - Ee Ling Tan
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Room 5.43, Pearse Street, Dublin 2, Ireland
| | - Peter Bede
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Room 5.43, Pearse Street, Dublin 2, Ireland. .,Department of Neurology, St James's Hospital, Dublin, Ireland.
| |
Collapse
|
24
|
Pan S, Liu X, Liu T, Zhao Z, Dai Y, Wang YY, Jia P, Liu F. Causal Inference of Genetic Variants and Genes in Amyotrophic Lateral Sclerosis. Front Genet 2022; 13:917142. [PMID: 35812739 PMCID: PMC9257137 DOI: 10.3389/fgene.2022.917142] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2022] [Accepted: 05/16/2022] [Indexed: 11/13/2022] Open
Abstract
Amyotrophic lateral sclerosis (ALS) is a fatal progressive multisystem disorder with limited therapeutic options. Although genome-wide association studies (GWASs) have revealed multiple ALS susceptibility loci, the exact identities of causal variants, genes, cell types, tissues, and their functional roles in the development of ALS remain largely unknown. Here, we reported a comprehensive post-GWAS analysis of the recent large ALS GWAS (n = 80,610), including functional mapping and annotation (FUMA), transcriptome-wide association study (TWAS), colocalization (COLOC), and summary data-based Mendelian randomization analyses (SMR) in extensive multi-omics datasets. Gene property analysis highlighted inhibitory neuron 6, oligodendrocytes, and GABAergic neurons (Gad1/Gad2) as functional cell types of ALS and confirmed cerebellum and cerebellar hemisphere as functional tissues of ALS. Functional annotation detected the presence of multiple deleterious variants at three loci (9p21.2, 12q13.3, and 12q14.2) and highlighted a list of SNPs that are potentially functional. TWAS, COLOC, and SMR identified 43 genes at 24 loci, including 23 novel genes and 10 novel loci, showing significant evidence of causality. Integrating multiple lines of evidence, we further proposed that rs2453555 at 9p21.2 and rs229243 at 14q12 functionally contribute to the development of ALS by regulating the expression of C9orf72 in pituitary and SCFD1 in skeletal muscle, respectively. Together, these results advance our understanding of the biological etiology of ALS, feed into new therapies, and provide a guide for subsequent functional experiments.
Collapse
Affiliation(s)
- Siyu Pan
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Xinxuan Liu
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, China
- School of Future Technology, University of Chinese Academy of Sciences, Beijing, China
| | - Tianzi Liu
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, China
| | - Zhongming Zhao
- Center for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, United States
| | - Yulin Dai
- Center for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, United States
| | - Yin-Ying Wang
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, China
| | - Peilin Jia
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, China
- *Correspondence: Fan Liu, ; Peilin Jia,
| | - Fan Liu
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, China
- School of Future Technology, University of Chinese Academy of Sciences, Beijing, China
- *Correspondence: Fan Liu, ; Peilin Jia,
| |
Collapse
|
25
|
Bede P, Chang KM, Tan EL. Machine-learning in motor neuron diseases: Prospects and pitfalls. Eur J Neurol 2022; 29:2555-2556. [PMID: 35699315 PMCID: PMC9546434 DOI: 10.1111/ene.15443] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2022] [Revised: 05/26/2022] [Accepted: 06/09/2022] [Indexed: 12/22/2022]
Affiliation(s)
- Peter Bede
- Computational Neuroimaging Group, Trinity College Dublin, Dublin, Ireland.,Department of Neurology, St James's Hospital, Dublin, Ireland
| | - Kai Ming Chang
- Computational Neuroimaging Group, Trinity College Dublin, Dublin, Ireland.,Department of Electronics and Computer Science, University of Southampton, Southampton, UK
| | - Ee Ling Tan
- Computational Neuroimaging Group, Trinity College Dublin, Dublin, Ireland
| |
Collapse
|
26
|
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.
Collapse
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.
| |
Collapse
|
27
|
The Advent of Omics Sciences in Clinical Trials of Motor Neuron Diseases. J Pers Med 2022; 12:jpm12050758. [PMID: 35629180 PMCID: PMC9144989 DOI: 10.3390/jpm12050758] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Revised: 05/03/2022] [Accepted: 05/05/2022] [Indexed: 02/04/2023] Open
Abstract
The “omics revolution” has totally changed the scientific research approach and is contributing to the development of personalized therapies. In motor neuron diseases (MNDs), a set of complex, multifactorial, late-onset and chronic neurodegenerative diseases, the use of multi-omics approaches in clinical trials is providing new opportunities to stratify patients and develop target therapies. To show how omics science is gaining momentum in MNDs, in this work, we review the interventional clinical trials for MNDs based on the application of omics sciences. We analyze a total of 62 clinical trials listed in the ClinicalTrials database where different omics approaches have been applied in an initial phase, for diagnosis or patient selection, or in subsequent stages to cluster subjects, identify molecular signatures or evaluate drugs security or efficacy. The rise of omics sciences in clinical experimentation of MNDs is leading to an upheaval in their diagnosis and therapy that will require significant investments and means to ensure the correct and rapid evolution of personalized medicine.
Collapse
|
28
|
How can we define the presymptomatic C9orf72 disease in 2022? An overview on the current definitions of preclinical and prodromal phases. Rev Neurol (Paris) 2022; 178:426-436. [PMID: 35525633 DOI: 10.1016/j.neurol.2022.03.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2022] [Accepted: 03/08/2022] [Indexed: 11/24/2022]
Abstract
Repeat expansions in C9orf72 gene are the main genetic cause of frontotemporal dementia, amyotrophic lateral sclerosis and related phenotypes. With the advent of disease-modifying treatments, the presymptomatic disease phase is getting increasing interest as an ideal time window in which innovant therapeutic approaches could be administered. Recommendations issued from international study groups distinguish between a preclinical disease stage, during which lesions accumulate in absence of any symptoms or signs, and a prodromal stage, marked by the appearance the first subtle cognitive, behavioral, psychiatric and motor signs, before the full-blown disease. This paper summarizes the current definitions and criteria for these stages, in particular focusing on how fluid-based, neuroimaging and cognitive biomarkers can be useful to monitor disease trajectory across the presymptomatic phase, as well as to detect the earliest signs of clinical conversion. Continuous advances in the knowledge of C9orf72 pathophysiology, and the integration of biomarkers in the clinical evaluation of mutation carriers will allow a better diagnostic definition of C9orf72 disease spectrum from the earliest stages, with relevant impact on the possibility of disease prevention.
Collapse
|
29
|
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: 144] [Impact Index Per Article: 72.0] [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.
Collapse
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.
| |
Collapse
|
30
|
McKenna MC, Li Hi Shing S, Murad A, Lope J, Hardiman O, Hutchinson S, Bede P. Focal thalamus pathology in frontotemporal dementia: Phenotype-associated thalamic profiles. J Neurol Sci 2022; 436:120221. [DOI: 10.1016/j.jns.2022.120221] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Revised: 02/21/2022] [Accepted: 03/03/2022] [Indexed: 11/25/2022]
|
31
|
Bede P, Lope J. Biomarker development in Amyotrophic Lateral Sclerosis: challenges and viable strategies. Eur J Neurol 2022; 29:1867-1868. [PMID: 35467797 DOI: 10.1111/ene.15372] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Revised: 04/18/2022] [Accepted: 04/21/2022] [Indexed: 11/28/2022]
Affiliation(s)
- Peter Bede
- Computational Neuroimaging Group, Trinity College Dublin, Ireland.,Department of Neurology, St James's Hospital, Dublin
| | - Jasmin Lope
- Computational Neuroimaging Group, Trinity College Dublin, Ireland
| |
Collapse
|
32
|
Sangari S, Peyre I, Lackmy‐Vallée A, Bayen E, Pradat P, Marchand‐Pauvert V. Transient increase in recurrent inhibition in amyotrophic lateral sclerosis as a putative protection from neurodegeneration. Acta Physiol (Oxf) 2022; 234:e13758. [PMID: 34981890 DOI: 10.1111/apha.13758] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Revised: 12/15/2021] [Accepted: 01/01/2022] [Indexed: 11/28/2022]
Abstract
AIM Adaptive mechanisms in spinal circuits are likely involved in homeostatic responses to maintain motor output in amyotrophic lateral sclerosis. Given the role of Renshaw cells in regulating the motoneuron input/output gain, we investigated the modulation of heteronymous recurrent inhibition. METHODS Electrical stimulations were used to activate recurrent collaterals resulting in the Hoffmann reflex depression. Inhibitions from soleus motor axons to quadriceps motoneurons, and vice versa, were tested in 38 patients and matched group of 42 controls. RESULTS Compared with controls, the mean depression of quadriceps reflex was larger in patients, while that of soleus was smaller, suggesting that heteronymous recurrent inhibition was enhanced in quadriceps but reduced in soleus. The modulation of recurrent inhibition was linked to the size of maximal direct motor response and lower limb dysfunctions, suggesting a significant relationship with the integrity of the target motoneuron pool and functional abilities. No significant link was found between the integrity of motor axons activating Renshaw cells and the level of inhibition. Enhanced inhibition was particularly observed in patients within the first year after symptom onset and with slow progression of lower limb dysfunctions. Normal or reduced inhibitions were mainly observed in patients with motor weakness first in lower limbs and greater dysfunctions in lower limbs. CONCLUSION We provide the first evidence for enhanced recurrent inhibition and speculate that Renshaw cells might have transient protective role on motoneuron by counteracting hyperexcitability at early stages. Several mechanisms likely participate including cortical influence on Renshaw cell and reinnervation by slow motoneurons.
Collapse
Affiliation(s)
- Sina Sangari
- Laboratoire d’Imagerie Biomédicale Sorbonne Université INSERM CNRS Paris France
- Shirley Ryan AbilityLab Chicago Illinois USA
- Department of Physical Medicine and Rehabilitation Northwestern University Chicago Illinois USA
| | - Iseline Peyre
- Laboratoire d’Imagerie Biomédicale Sorbonne Université INSERM CNRS Paris France
| | | | - Eléonore Bayen
- Laboratoire d’Imagerie Biomédicale Sorbonne Université INSERM CNRS Paris France
- Pôle MSN, Hôpital Pitié‐Salpêtrière AP‐HP Paris France
| | - Pierre‐François Pradat
- Laboratoire d’Imagerie Biomédicale Sorbonne Université INSERM CNRS Paris France
- Pôle MSN, Hôpital Pitié‐Salpêtrière AP‐HP Paris France
| | | |
Collapse
|
33
|
Clusters of anatomical disease-burden patterns in ALS: a data-driven approach confirms radiological subtypes. J Neurol 2022; 269:4404-4413. [PMID: 35333981 PMCID: PMC9294023 DOI: 10.1007/s00415-022-11081-3] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Revised: 03/10/2022] [Accepted: 03/11/2022] [Indexed: 12/28/2022]
Abstract
Amyotrophic lateral sclerosis (ALS) is associated with considerable clinical heterogeneity spanning from diverse disability profiles, differences in UMN/LMN involvement, divergent progression rates, to variability in frontotemporal dysfunction. A multitude of classification frameworks and staging systems have been proposed based on clinical and neuropsychological characteristics, but disease subtypes are seldom defined based on anatomical patterns of disease burden without a prior clinical stratification. A prospective research study was conducted with a uniform imaging protocol to ascertain disease subtypes based on preferential cerebral involvement. Fifteen brain regions were systematically evaluated in each participant based on a comprehensive panel of cortical, subcortical and white matter integrity metrics. Using min–max scaled composite regional integrity scores, a two-step cluster analysis was conducted. Two radiological clusters were identified; 35.5% of patients belonging to ‘Cluster 1’ and 64.5% of patients segregating to ‘Cluster 2’. Subjects in Cluster 1 exhibited marked frontotemporal change. Predictor ranking revealed the following hierarchy of anatomical regions in decreasing importance: superior lateral temporal, inferior frontal, superior frontal, parietal, limbic, mesial inferior temporal, peri-Sylvian, subcortical, long association fibres, commissural, occipital, ‘sensory’, ‘motor’, cerebellum, and brainstem. While the majority of imaging studies first stratify patients based on clinical criteria or genetic profiles to describe phenotype- and genotype-associated imaging signatures, a data-driven approach may identify distinct disease subtypes without a priori patient categorisation. Our study illustrates that large radiology datasets may be potentially utilised to uncover disease subtypes associated with unique genetic, clinical or prognostic profiles.
Collapse
|
34
|
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.
Collapse
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
| |
Collapse
|
35
|
Bede P, Murad A, Lope J, Li Hi Shing S, Finegan E, Chipika RH, Hardiman O, Chang KM. Phenotypic categorisation of individual subjects with motor neuron disease based on radiological disease burden patterns: A machine-learning approach. J Neurol Sci 2022; 432:120079. [PMID: 34875472 DOI: 10.1016/j.jns.2021.120079] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2021] [Revised: 11/25/2021] [Accepted: 11/29/2021] [Indexed: 12/20/2022]
Abstract
Motor neuron disease is an umbrella term encompassing a multitude of clinically heterogeneous phenotypes. The early and accurate categorisation of patients is hugely important, as MND phenotypes are associated with markedly different prognoses, progression rates, care needs and benefit from divergent management strategies. The categorisation of patients shortly after symptom onset is challenging, and often lengthy clinical monitoring is needed to assign patients to the appropriate phenotypic subgroup. In this study, a multi-class machine-learning strategy was implemented to classify 300 patients based on their radiological profile into diagnostic labels along the UMN-LMN spectrum. A comprehensive panel of cortical thickness measures, subcortical grey matter variables, and white matter integrity metrics were evaluated in a multilayer perceptron (MLP) model. Additional exploratory analyses were also carried out using discriminant function analyses (DFA). Excellent classification accuracy was achieved for amyotrophic lateral sclerosis in the testing cohort (93.7%) using the MLP model, but poor diagnostic accuracy was detected for primary lateral sclerosis (43.8%) and poliomyelitis survivors (60%). Feature importance analyses highlighted the relevance of white matter diffusivity metrics and the evaluation of cerebellar indices, cingulate measures and thalamic radiation variables to discriminate MND phenotypes. Our data suggest that radiological data from single patients may be meaningfully interpreted if large training data sets are available and the provision of diagnostic probability outcomes may be clinically useful in patients with short symptom duration. The computational interpretation of multimodal radiology datasets herald viable diagnostic, prognostic and clinical trial applications.
Collapse
Affiliation(s)
- Peter Bede
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Ireland; Pitié-Salpêtrière University Hospital, Sorbonne University, Paris, France.
| | - Aizuri Murad
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Ireland
| | - Jasmin Lope
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Ireland
| | - 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
| | - Orla Hardiman
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Ireland
| | - Kai Ming Chang
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Ireland; Department of Electronics and Computer Science, University of Southampton, UK
| |
Collapse
|
36
|
Leoni TB, Rezende TJR, Peluzzo TM, Martins MP, Neto ARC, Gonzalez-Salazar C, Cruzeiro MM, Camargos ST, de Souza LC, França MC. Structural brain and spinal cord damage in symptomatic and pre-symptomatic VAPB-related ALS. J Neurol Sci 2022; 434:120126. [PMID: 35007920 DOI: 10.1016/j.jns.2021.120126] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2021] [Revised: 12/08/2021] [Accepted: 12/27/2021] [Indexed: 12/12/2022]
Abstract
INTRODUCTION The VAPB gene is associated with fALS (fALS 8). This disease presents a variable phenotype and no study sought to characterize its neuroanatomical abnormalities until now. This study aims to evaluate structural brain and spinal cord abnormalities in symptomatic and pre-symptomatic VAPB-related ALS. METHODS This cohort included 10 presymptomatic and 20 symptomatic carriers of the Pro56Ser VAPB variant as well as 30 matched controls and 20 individuals with sporadic ALS. They underwent detailed clinical evaluation and MRI in a 3 T scanner. Using volumetric T1 sequence, we computed cerebral cortical thickness (FreeSurfer), basal ganglia volumetry (T1 Multi-atlas) and SC morphometry (SpineSeg). DTI was used to assess white matter integrity (DTI Multi-atlas). Groups were compared using a generalized linear model with Bonferroni-corrected p values<0.05. We also plotted VAPB brain expression map using Allen Human Brain Atlas to compare with imaging findings. RESULTS Mean age of presymptomatic and symptomatic subjects were 43.2 and 51.9 years, respectively. Most patients had a predominant lower motor neuron phenotype (16/20). Sleep complaints and tremor were the most frequent additional manifestations. Compared to controls, symptomatic subjects had pallidal, brainstem and SC atrophy, whereas presymptomatic only had SC atrophy. This pattern also contrasted with the sALS group that presented motor cortex and corticospinal abnormalities. Brain structural damage and VAPB expression maps were highly overlapping. CONCLUSION VAPB-related ALS has a distinctive structural signature that targets the basal ganglia, brainstem and SC, which are regions with high VAPB expression. Neuroanatomical SC changes are evident before clinical onset of the disease.
Collapse
Affiliation(s)
- Tauana B Leoni
- Department of Neurology, School of Medical Sciences - University of Campinas (UNICAMP), Campinas, SP, Brazil
| | - Thiago Junqueira R Rezende
- Department of Neurology, School of Medical Sciences - University of Campinas (UNICAMP), Campinas, SP, Brazil
| | - Thiago M Peluzzo
- Department of Medical Genetics, School of Medical Sciences - University of Campinas (UNICAMP), Campinas, SP, Brazil
| | - Melina P Martins
- Department of Neurology, School of Medical Sciences - University of Campinas (UNICAMP), Campinas, SP, Brazil
| | | | - Carelis Gonzalez-Salazar
- Department of Neurology, School of Medical Sciences - University of Campinas (UNICAMP), Campinas, SP, Brazil
| | - Marcelo Maroco Cruzeiro
- Department of Internal Medicine, Federal University of Juiz de Fora (UFJF), Juiz de Fora, MG, Brazil
| | - Sarah Teixeira Camargos
- Department of Internal Medicine, School of Medicine - Federal University of Minas Gerais (UFMG), Belo Horizonte, MG, Brazil
| | - Leonardo Cruz de Souza
- Department of Internal Medicine, School of Medicine - Federal University of Minas Gerais (UFMG), Belo Horizonte, MG, Brazil
| | - Marcondes C França
- Department of Neurology, School of Medical Sciences - University of Campinas (UNICAMP), Campinas, SP, Brazil.
| |
Collapse
|
37
|
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.
Collapse
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
| |
Collapse
|
38
|
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
| |
Collapse
|
39
|
Querin G, Grazia Biferi M, Pradat PF. Biomarkers for C9orf7-ALS in Symptomatic and Pre-symptomatic Patients: State-of-the-art in the New Era of Clinical Trials. J Neuromuscul Dis 2021; 9:25-37. [PMID: 34864683 PMCID: PMC8842771 DOI: 10.3233/jnd-210754] [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] [Indexed: 12/11/2022]
Abstract
The development of new possible treatments for C9orf72-related ALS and the possibility of early identification of subjects genetically at risk of developing the disease is creating a critical need for biomarkers to track neurodegeneration that could be used as outcome measures in clinical trials. Current candidate biomarkers in C9orf72-ALS include neuropsychology tests, imaging, electrophysiology as well as different circulating biomarkers. Neuropsychology tests show early executive and verbal function involvement both in symptomatic and asymptomatic mutation carriers. At brain MRI, C9orf72-ALS patients present diffuse white and grey matter degeneration, which are already identified up to 20 years before symptom onset and that seem to be slowly progressive over time, while regions of altered connectivity at fMRI and of hypometabolism at [18F]FDG PET have been described as well. At the same time, spinal cord MRI has also shown progressive decrease of FA in the cortico-spinal tract over time. On the side of wet biomarkers, neurofilament proteins are increased both in the CSF and serum just before symptom onset and tend to slowly increase over time, while poly(GP) protein can be detected in the CSF and probably used as target engagement marker in clinical trials.
Collapse
Affiliation(s)
- Giorgia Querin
- Institut de Myologie, I-Motion Adult ClinicalTrials Platform, Hôpital Pitié-Salpêtrière, Paris, France.,APHP, Centre de référence desmaladies neuromusculaires Nord/Est/Ile de France, HôpitalPitié-Salpêtrière, Paris, France
| | - Maria Grazia Biferi
- Sorbonne Université, Inserm UMRS974, Centre of Research in Myology (CRM), Institut de Myologie, GH PitiéSalpêtrière, Paris, France
| | - Pierre-Francois Pradat
- APHP, Département de Neurologie, Centre Référent SLA, Hôpital Pitié-Salpêtrière, Paris, France.,Laboratoire d'Imagerie Biomédicale, CNRS, INSERM, Sorbonne Université, Paris, France.,Northern Ireland Centre for Stratified Medicine, Biomedical Sciences Research Institute Ulster University, C-TRIC, Altnagelvin Hospital, Londonderry, United Kingdom
| |
Collapse
|
40
|
Hernandez ALCC, Rezende TJR, Martinez ARM, de Brito MR, França MC. Tract-Specific Spinal Cord Diffusion Tensor Imaging in Friedreich's Ataxia. Mov Disord 2021; 37:354-364. [PMID: 34713932 DOI: 10.1002/mds.28841] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2021] [Revised: 09/30/2021] [Accepted: 10/02/2021] [Indexed: 11/09/2022] Open
Abstract
BACKGROUND Spinal cord (SC) damage is a hallmark in Friedreich's ataxia (FRDA). Neuroimaging has been able to capture some SC macroscopic changes, but no study has evaluated microstructural SC white matter (WM) damage in vivo. OBJECTIVES We designed a cross-sectional study to evaluate microstructural integrity in SC WM tracts of FRDA patients using diffusion tensor imaging (DTI) with an automated analysis pipeline. METHODS Thirty patients and 30 matched healthy controls underwent 3 Tesla (T) magnetic resonance imaging (MRI). We obtained cervical SC T2 and diffusion-weighted imaging (DWI) acquisitions. Images were processed using the Spinal Cord Toolbox v.4.3.0. For levels C2-C5, we measured cross-sectional area (CSA) and WM DTI parameters (axial diffusivity [AD], fractional anisotropy [FA], radial diffusivity [RD], and mean diffusivity [MD]). Age, duration, and FARS scores were also obtained. RESULTS Mean age and disease duration of patients were 31 ± 10 and 11 ± 9 years, respectively. There was CSA reduction in FRDA amongst all levels. Between-group differences in FA, MD, and RD in total white matter (TWM), dorsal columns (DC), fasciculus gracilis (FG), fasciculus cuneatus (FC), and corticospinal tracts (CST) were present in all levels. FA and RD from TWM, DC, FC, and CST correlated with FARS scores, and in CST they also correlated with disease duration. CONCLUSION DTI uncovered abnormalities in SC WM tracts, which correlated with clinical features in FRDA. CSA and CST FA in C2 correlated best with disease severity, whereas DC FA showed the largest effect size to differentiate patients and healthy controls. SC WM microstructure is a potential neuroimaging biomarker to be explored in the disease. © 2021 International Parkinson and Movement Disorder Society.
Collapse
Affiliation(s)
- Ana Luisa C C Hernandez
- Department of Neurology and Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), School of Medical Sciences - University of Campinas (UNICAMP), Campinas, Brazil
| | - Thiago J R Rezende
- Department of Neurology and Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), School of Medical Sciences - University of Campinas (UNICAMP), Campinas, Brazil
| | - Alberto R M Martinez
- Department of Neurology and Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), School of Medical Sciences - University of Campinas (UNICAMP), Campinas, Brazil
| | - Mariana R de Brito
- Department of Neurology and Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), School of Medical Sciences - University of Campinas (UNICAMP), Campinas, Brazil
| | - Marcondes C França
- Department of Neurology and Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), School of Medical Sciences - University of Campinas (UNICAMP), Campinas, Brazil
| |
Collapse
|
41
|
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.
Collapse
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.
| |
Collapse
|
42
|
Cohen-Adad J, Alonso-Ortiz E, Abramovic M, Arneitz C, Atcheson N, Barlow L, Barry RL, Barth M, Battiston M, Büchel C, Budde M, Callot V, Combes AJE, De Leener B, Descoteaux M, de Sousa PL, Dostál M, Doyon J, Dvorak A, Eippert F, Epperson KR, Epperson KS, Freund P, Finsterbusch J, Foias A, Fratini M, Fukunaga I, Wheeler-Kingshott CAMG, Germani G, Gilbert G, Giove F, Gros C, Grussu F, Hagiwara A, Henry PG, Horák T, Hori M, Joers J, Kamiya K, Karbasforoushan H, Keřkovský M, Khatibi A, Kim JW, Kinany N, Kitzler H, Kolind S, Kong Y, Kudlička P, Kuntke P, Kurniawan ND, Kusmia S, Labounek R, Laganà MM, Laule C, Law CS, Lenglet C, Leutritz T, Liu Y, Llufriu S, Mackey S, Martinez-Heras E, Mattera L, Nestrasil I, O'Grady KP, Papinutto N, Papp D, Pareto D, Parrish TB, Pichiecchio A, Prados F, Rovira À, Ruitenberg MJ, Samson RS, Savini G, Seif M, Seifert AC, Smith AK, Smith SA, Smith ZA, Solana E, Suzuki Y, Tackley G, Tinnermann A, Valošek J, Van De Ville D, Yiannakas MC, Weber KA, Weiskopf N, Wise RG, Wyss PO, Xu J. Generic acquisition protocol for quantitative MRI of the spinal cord. Nat Protoc 2021; 16:4611-4632. [PMID: 34400839 PMCID: PMC8811488 DOI: 10.1038/s41596-021-00588-0] [Citation(s) in RCA: 52] [Impact Index Per Article: 17.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2020] [Accepted: 06/10/2021] [Indexed: 02/08/2023]
Abstract
Quantitative spinal cord (SC) magnetic resonance imaging (MRI) presents many challenges, including a lack of standardized imaging protocols. Here we present a prospectively harmonized quantitative MRI protocol, which we refer to as the spine generic protocol, for users of 3T MRI systems from the three main manufacturers: GE, Philips and Siemens. The protocol provides guidance for assessing SC macrostructural and microstructural integrity: T1-weighted and T2-weighted imaging for SC cross-sectional area computation, multi-echo gradient echo for gray matter cross-sectional area, and magnetization transfer and diffusion weighted imaging for assessing white matter microstructure. In a companion paper from the same authors, the spine generic protocol was used to acquire data across 42 centers in 260 healthy subjects. The key details of the spine generic protocol are also available in an open-access document that can be found at https://github.com/spine-generic/protocols . The protocol will serve as a starting point for researchers and clinicians implementing new SC imaging initiatives so that, in the future, inclusion of the SC in neuroimaging protocols will be more common. The protocol could be implemented by any trained MR technician or by a researcher/clinician familiar with MRI acquisition.
Collapse
Affiliation(s)
- Julien Cohen-Adad
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, Quebec, Canada.
- Functional Neuroimaging Unit, CRIUGM, University of Montreal, Montreal, Quebec, Canada.
- Mila-Quebec AI Institute, Montreal, Quebec, Canada.
| | - Eva Alonso-Ortiz
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, Quebec, Canada
| | - Mihael Abramovic
- Department of Radiology, Swiss Paraplegic Centre, Nottwil, Switzerland
| | - Carina Arneitz
- Department of Radiology, Swiss Paraplegic Centre, Nottwil, Switzerland
| | - Nicole Atcheson
- Centre for Advanced Imaging, The University of Queensland, Brisbane, Queensland, Australia
| | - Laura Barlow
- Department of Radiology, University of British Columbia, Vancouver, British Columbia, Canada
| | - Robert L Barry
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
- Harvard-Massachusetts Institute of Technology Health Sciences & Technology, Cambridge, MA, USA
| | - Markus Barth
- School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane, Queensland, Australia
| | - Marco Battiston
- NMR Research Unit, Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
| | - Christian Büchel
- Department of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Matthew Budde
- Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Virginie Callot
- Aix-Marseille Univ, CNRS, CRMBM, Marseille, France
- APHM, Hopital Universitaire Timone, CEMEREM, Marseille, France
| | - Anna J E Combes
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Benjamin De Leener
- Department of Computer and Software Engineering, Polytechnique Montreal, Montreal, Quebec, Canada
- CHU Sainte-Justine Research Centre, Montreal, Quebec, Canada
| | - Maxime Descoteaux
- Centre de Recherche CHUS, CIMS, Sherbrooke, Quebec, Canada
- Sherbrooke Connectivity Imaging Lab (SCIL), Computer Science department, Université de Sherbrooke, Sherbrooke, Quebec, Canada
| | | | - Marek Dostál
- UHB - University Hospital Brno and Masaryk University, Department of Radiology and Nuclear Medicine, Brno, Czech Republic
| | - Julien Doyon
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Adam Dvorak
- Department of Physics and Astronomy, University of British Columbia, Vancouver, British Columbia, Canada
| | - Falk Eippert
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Karla R Epperson
- Richard M. Lucas Center, Stanford University School of Medicine, Stanford, CA, USA
| | - Kevin S Epperson
- Richard M. Lucas Center, Stanford University School of Medicine, Stanford, CA, USA
| | - Patrick Freund
- Spinal Cord Injury Center Balgrist, University of Zurich, Zurich, Switzerland
| | - Jürgen Finsterbusch
- Department of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Alexandru Foias
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, Quebec, Canada
| | - Michela Fratini
- Institute of Nanotechnology, CNR, Rome, Italy
- IRCCS Santa Lucia Foundation, Rome, Italy
| | - Issei Fukunaga
- Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan
| | - Claudia A M Gandini Wheeler-Kingshott
- NMR Research Unit, Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy
- Brain MRI 3T Research Centre, IRCCS Mondino Foundation, Pavia, Italy
| | - Giancarlo Germani
- Brain MRI 3T Research Centre, IRCCS Mondino Foundation, Pavia, Italy
| | | | - Federico Giove
- IRCCS Santa Lucia Foundation, Rome, Italy
- CREF - Museo storico della fisica e Centro studi e ricerche Enrico Fermi, Rome, Italy
| | - Charley Gros
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, Quebec, Canada
- Centre for Advanced Imaging, The University of Queensland, Brisbane, Queensland, Australia
| | - Francesco Grussu
- NMR Research Unit, Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- Radiomics Group, Vall d'Hebron Institute of Oncology, Vall d'Hebron Barcelona Hospital Campus, Barcelona, Spain
| | - Akifumi Hagiwara
- Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan
| | - Pierre-Gilles Henry
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA
| | - Tomáš Horák
- Multimodal and functional imaging laboratory, Central European Institute of Technology (CEITEC), Brno, Czech Republic
| | - Masaaki Hori
- Department of Radiology, Toho University Omori Medical Center, Tokyo, Japan
| | - James Joers
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA
| | - Kouhei Kamiya
- Department of Radiology, the University of Tokyo, Tokyo, Japan
| | - Haleh Karbasforoushan
- Interdepartmental Neuroscience Program, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
- Department of Psychiatry and Behavioral Sciences, School of Medicine, Stanford University, Stanford, CA, USA
| | - Miloš Keřkovský
- UHB - University Hospital Brno and Masaryk University, Department of Radiology and Nuclear Medicine, Brno, Czech Republic
| | - Ali Khatibi
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
- Centre of Precision Rehabilitation for Spinal Pain (CPR Spine), School of Sport, Exercise and Rehabilitation Sciences, College of Life and Environmental Sciences, University of Birmingham, Edgbaston, Birmingham, UK
| | - Joo-Won Kim
- BioMedical Engineering and Imaging Institute (BMEII), Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Nawal Kinany
- Institute of Bioengineering/Center for Neuroprosthetics, Ecole Polytechnique Fédérale de Lausanne, Geneva, Switzerland
- Department of Radiology and Medical Informatics, University of Geneva, Geneva, Switzerland
| | - Hagen Kitzler
- Institute of Diagnostic and Interventional Neuroradiology, Carl Gustav Carus University Hospital, Technische Universität Dresden, Dresden, Germany
| | - Shannon Kolind
- Department of Radiology, University of British Columbia, Vancouver, British Columbia, Canada
- Department of Physics and Astronomy, University of British Columbia, Vancouver, British Columbia, Canada
- Department of Medicine (Neurology), University of British Columbia, Vancouver, British Columbia, Canada
| | - Yazhuo Kong
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
- Wellcome Centre For Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Petr Kudlička
- Multimodal and functional imaging laboratory, Central European Institute of Technology (CEITEC), Brno, Czech Republic
| | - Paul Kuntke
- Institute of Diagnostic and Interventional Neuroradiology, Carl Gustav Carus University Hospital, Technische Universität Dresden, Dresden, Germany
| | - Nyoman D Kurniawan
- Centre for Advanced Imaging, The University of Queensland, Brisbane, Queensland, Australia
| | - Slawomir Kusmia
- CUBRIC, Cardiff University, Wales, UK
- Centre for Medical Image Computing (CMIC), Medical Physics and Biomedical Engineering Department, University College London, London, UK
- Epilepsy Society MRI Unit, Chalfont St Peter, UK
| | - René Labounek
- Division of Clinical Behavioral Neuroscience, Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA
- Departments of Neurology and Biomedical Engineering, University Hospital Olomouc, Olomouc, Czech Republic
| | | | - Cornelia Laule
- Departments of Radiology, Pathology & Laboratory Medicine, Physics & Astronomy; International Collaboration on Repair Discoveries (ICORD), University of British Columbia, Vancouver, British Columbia, Canada
| | - Christine S Law
- Division of Pain Medicine, Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Christophe Lenglet
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA
| | - Tobias Leutritz
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Yaou Liu
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- Tiantan Image Research Center, China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Sara Llufriu
- Center of Neuroimmunology, Laboratory of Advanced Imaging in Neuroimmunological Diseases, Hospital Clinic Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS) and Universitat de Barcelona, Barcelona, Spain
| | - Sean Mackey
- Division of Pain Medicine, Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Eloy Martinez-Heras
- Center of Neuroimmunology, Laboratory of Advanced Imaging in Neuroimmunological Diseases, Hospital Clinic Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS) and Universitat de Barcelona, Barcelona, Spain
| | - Loan Mattera
- Fondation Campus Biotech Genève, Geneva, Switzerland
| | - Igor Nestrasil
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA
- Division of Clinical Behavioral Neuroscience, Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA
| | - Kristin P O'Grady
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Radiology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Nico Papinutto
- UCSF Weill Institute for Neurosciences, Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - Daniel Papp
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, Quebec, Canada
- Wellcome Centre For Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Deborah Pareto
- Neuroradiology Section, Vall d'Hebron University Hospital, Barcelona, Spain
| | - Todd B Parrish
- Interdepartmental Neuroscience Program, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Anna Pichiecchio
- Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy
- Brain MRI 3T Research Centre, IRCCS Mondino Foundation, Pavia, Italy
| | - Ferran Prados
- NMR Research Unit, Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- Centre for Medical Image Computing (CMIC), Medical Physics and Biomedical Engineering Department, University College London, London, UK
- E-health Centre, Universitat Oberta de Catalunya, Barcelona, Spain
| | - Àlex Rovira
- Neuroradiology Section, Vall d'Hebron University Hospital, Barcelona, Spain
| | - Marc J Ruitenberg
- School of Biomedical Sciences, Faculty of Medicine, The University of Queensland, Brisbane, Queensland, Australia
| | - Rebecca S Samson
- NMR Research Unit, Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
| | - Giovanni Savini
- Brain MRI 3T Research Centre, IRCCS Mondino Foundation, Pavia, Italy
| | - Maryam Seif
- Spinal Cord Injury Center Balgrist, University of Zurich, Zurich, Switzerland
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Alan C Seifert
- BioMedical Engineering and Imaging Institute (BMEII), Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Alex K Smith
- Wellcome Centre For Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Seth A Smith
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Radiology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Zachary A Smith
- University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Elisabeth Solana
- Center of Neuroimmunology, Laboratory of Advanced Imaging in Neuroimmunological Diseases, Hospital Clinic Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS) and Universitat de Barcelona, Barcelona, Spain
| | - Yuichi Suzuki
- Department of Radiology, the University of Tokyo, Tokyo, Japan
| | | | - Alexandra Tinnermann
- Department of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Jan Valošek
- Department of Neurology, Faculty of Medicine and Dentistry, Palacký University and University Hospital Olomouc, Olomouc, Czech Republic
| | - Dimitri Van De Ville
- Institute of Bioengineering/Center for Neuroprosthetics, Ecole Polytechnique Fédérale de Lausanne, Geneva, Switzerland
- Department of Radiology and Medical Informatics, University of Geneva, Geneva, Switzerland
| | - Marios C Yiannakas
- NMR Research Unit, Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
| | - Kenneth A Weber
- Division of Pain Medicine, Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Nikolaus Weiskopf
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, Leipzig University, Leipzig, Germany
| | - Richard G Wise
- CUBRIC, Cardiff University, Wales, UK
- Institute for Advanced Biomedical Technologies, Department of Neuroscience, Imaging and Clinical Sciences, "G. D'Annunzio University" of Chieti-Pescara, Chieti, Italy
| | - Patrik O Wyss
- Department of Radiology, Swiss Paraplegic Centre, Nottwil, Switzerland
| | - Junqian Xu
- BioMedical Engineering and Imaging Institute (BMEII), Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| |
Collapse
|
43
|
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.
Collapse
|
44
|
Barton SK, Gregory JM, Selvaraj BT, McDade K, Henstridge CM, Spires-Jones TL, James OG, Mehta AR, Story D, Burr K, Magnani D, Isaacs AM, Smith C, Chandran S. Dysregulation in Subcellular Localization of Myelin Basic Protein mRNA Does Not Result in Altered Myelination in Amyotrophic Lateral Sclerosis. Front Neurosci 2021; 15:705306. [PMID: 34539336 PMCID: PMC8440970 DOI: 10.3389/fnins.2021.705306] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2021] [Accepted: 07/23/2021] [Indexed: 11/13/2022] Open
Abstract
Pathological hallmarks of amyotrophic lateral sclerosis (ALS), including protein misfolding, are well established in oligodendrocytes. More recently, an RNA trafficking deficit of key myelin proteins has been suggested in oligodendrocytes in ALS but the extent to which this affects myelination and the relative contribution of this to disease pathogenesis is unclear. ALS autopsy research findings showing demyelination contrasts with the routine clinical-pathological workup of ALS cases where it is rare to see white matter abnormalities other than simple Wallerian degeneration secondary to widespread neuronal loss. To begin to address this apparent variance, we undertook a comprehensive evaluation of myelination at an RNA, protein and structural level using human pathological material from sporadic ALS patients, genetic ALS patients (harboring C9orf72 mutation) and age- and sex-matched non-neurological controls. We performed (i) quantitative spatial profiling of the mRNA transcript encoding myelin basic protein (MBP), (ii) quantification of MBP protein and (iii) the first quantitative structural assessment of myelination in ALS post-mortem specimens by electron microscopy. We show no differences in MBP protein levels or ultrastructural myelination, despite a significant dysregulation in the subcellular trafficking of MBP mRNA in ALS patients compared to controls. We therefore confirm that whilst there are cell autonomous mRNA trafficking deficits affecting oligodendrocytes in ALS, this has no effect on myelin structure.
Collapse
Affiliation(s)
- Samantha K. Barton
- Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Melbourne, VIC, Australia
- Euan MacDonald Centre for MND Research, The University of Edinburgh, Edinburgh, United Kingdom
- Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, United Kingdom
- UK Dementia Research Institute at The University of Edinburgh, The University of Edinburgh, Edinburgh, United Kingdom
| | - Jenna M. Gregory
- Euan MacDonald Centre for MND Research, The University of Edinburgh, Edinburgh, United Kingdom
- Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, United Kingdom
- UK Dementia Research Institute at The University of Edinburgh, The University of Edinburgh, Edinburgh, United Kingdom
| | - Bhuvaneish T. Selvaraj
- Euan MacDonald Centre for MND Research, The University of Edinburgh, Edinburgh, United Kingdom
- Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, United Kingdom
- UK Dementia Research Institute at The University of Edinburgh, The University of Edinburgh, Edinburgh, United Kingdom
| | - Karina McDade
- Euan MacDonald Centre for MND Research, The University of Edinburgh, Edinburgh, United Kingdom
- Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, United Kingdom
| | - Christopher M. Henstridge
- Euan MacDonald Centre for MND Research, The University of Edinburgh, Edinburgh, United Kingdom
- UK Dementia Research Institute at The University of Edinburgh, The University of Edinburgh, Edinburgh, United Kingdom
- Centre for Discovery Brain Sciences, The University of Edinburgh, Edinburgh, United Kingdom
| | - Tara L. Spires-Jones
- Euan MacDonald Centre for MND Research, The University of Edinburgh, Edinburgh, United Kingdom
- UK Dementia Research Institute at The University of Edinburgh, The University of Edinburgh, Edinburgh, United Kingdom
- Centre for Discovery Brain Sciences, The University of Edinburgh, Edinburgh, United Kingdom
| | - Owen G. James
- Euan MacDonald Centre for MND Research, The University of Edinburgh, Edinburgh, United Kingdom
- Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, United Kingdom
- UK Dementia Research Institute at The University of Edinburgh, The University of Edinburgh, Edinburgh, United Kingdom
| | - Arpan R. Mehta
- Euan MacDonald Centre for MND Research, The University of Edinburgh, Edinburgh, United Kingdom
- Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, United Kingdom
- UK Dementia Research Institute at The University of Edinburgh, The University of Edinburgh, Edinburgh, United Kingdom
| | - David Story
- Euan MacDonald Centre for MND Research, The University of Edinburgh, Edinburgh, United Kingdom
- Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, United Kingdom
- UK Dementia Research Institute at The University of Edinburgh, The University of Edinburgh, Edinburgh, United Kingdom
| | - Karen Burr
- Euan MacDonald Centre for MND Research, The University of Edinburgh, Edinburgh, United Kingdom
- Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, United Kingdom
- UK Dementia Research Institute at The University of Edinburgh, The University of Edinburgh, Edinburgh, United Kingdom
| | - Dario Magnani
- Euan MacDonald Centre for MND Research, The University of Edinburgh, Edinburgh, United Kingdom
- Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, United Kingdom
- UK Dementia Research Institute at The University of Edinburgh, The University of Edinburgh, Edinburgh, United Kingdom
| | - Adrian M. Isaacs
- UK Dementia Research Institute at UCL, Faculty of Brain Sciences, University College London, London, United Kingdom
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Colin Smith
- Euan MacDonald Centre for MND Research, The University of Edinburgh, Edinburgh, United Kingdom
- Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, United Kingdom
| | - Siddharthan Chandran
- Euan MacDonald Centre for MND Research, The University of Edinburgh, Edinburgh, United Kingdom
- Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, United Kingdom
- UK Dementia Research Institute at The University of Edinburgh, The University of Edinburgh, Edinburgh, United Kingdom
| |
Collapse
|
45
|
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.
Collapse
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.
| |
Collapse
|
46
|
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.
Collapse
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.
| |
Collapse
|
47
|
The future of ALS might move towards Genetic Therapy. Rev Neurol (Paris) 2021; 177:613-614. [PMID: 33775441 DOI: 10.1016/j.neurol.2021.01.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2020] [Revised: 01/20/2021] [Accepted: 01/21/2021] [Indexed: 11/23/2022]
|
48
|
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.
Collapse
|
49
|
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.
Collapse
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.
| |
Collapse
|
50
|
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
| |
Collapse
|