51
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Eisen A, Braak H, Del Tredici K, Lemon R, Ludolph AC, Kiernan MC. Cortical influences drive amyotrophic lateral sclerosis. J Neurol Neurosurg Psychiatry 2017; 88:917-924. [PMID: 28710326 DOI: 10.1136/jnnp-2017-315573] [Citation(s) in RCA: 141] [Impact Index Per Article: 20.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/15/2017] [Revised: 04/26/2017] [Accepted: 05/02/2017] [Indexed: 11/04/2022]
Abstract
The early motor manifestations of sporadic amyotrophic lateral sclerosis (ALS), while rarely documented, reflect failure of adaptive complex motor skills. The development of these skills correlates with progressive evolution of a direct corticomotoneuronal system that is unique to primates and markedly enhanced in humans. The failure of this system in ALS may translate into the split hand presentation, gait disturbance, split leg syndrome and bulbar symptomatology related to vocalisation and breathing, and possibly diffuse fasciculation, characteristic of ALS. Clinical neurophysiology of the brain employing transcranial magnetic stimulation has convincingly demonstrated a presymptomatic reduction or absence of short interval intracortical inhibition, accompanied by increased intracortical facilitation, indicating cortical hyperexcitability. The hallmark of the TDP-43 pathological signature of sporadic ALS is restricted to cortical areas as well as to subcortical nuclei that are under the direct control of corticofugal projections. This provides anatomical support that the origins of the TDP-43 pathology reside in the cerebral cortex itself, secondarily in corticofugal fibres and the subcortical targets with which they make monosynaptic connections. The latter feature explains the multisystem degeneration that characterises ALS. Consideration of ALS as a primary neurodegenerative disorder of the human brain may incorporate concepts of prion-like spread at synaptic terminals of corticofugal axons. Further, such a concept could explain the recognised widespread imaging abnormalities of the ALS neocortex and the accepted relationship between ALS and frontotemporal dementia.
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Affiliation(s)
- Andrew Eisen
- Division of Neurology, University of British Columbia, Vancouver, British Columbia, Canada
| | - Heiko Braak
- Clinical Neuroanatomy Section, Department of Neurology, Center for Biomedical Research, University of Ulm, Ulm, Baden-Württemberg, Germany
| | - Kelly Del Tredici
- Clinical Neuroanatomy Section, Department of Neurology, Center for Biomedical Research, University of Ulm, Ulm, Baden-Württemberg, Germany
| | - Roger Lemon
- Sobell Department of Motor Neuroscience and Movement Disorders, Sobell Department of Motor Neuroscience and Movement Disorders, UCL Institute of Neurology, Queen Square, London, UK
| | | | - Matthew C Kiernan
- Brain and Mind Centre, The University of Sydney, Sydney, NSW, Australia
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Fibroblast bioenergetics to classify amyotrophic lateral sclerosis patients. Mol Neurodegener 2017; 12:76. [PMID: 29065921 PMCID: PMC5655870 DOI: 10.1186/s13024-017-0217-5] [Citation(s) in RCA: 45] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2017] [Accepted: 10/17/2017] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND The objective of this study was to investigate cellular bioenergetics in primary skin fibroblasts derived from patients with amyotrophic lateral sclerosis (ALS) and to determine if they can be used as classifiers for patient stratification. METHODS We assembled a collection of unprecedented size of fibroblasts from patients with sporadic ALS (sALS, n = 171), primary lateral sclerosis (PLS, n = 34), ALS/PLS with C9orf72 mutations (n = 13), and healthy controls (n = 91). In search for novel ALS classifiers, we performed extensive studies of fibroblast bioenergetics, including mitochondrial membrane potential, respiration, glycolysis, and ATP content. Next, we developed a machine learning approach to determine whether fibroblast bioenergetic features could be used to stratify patients. RESULTS Compared to controls, sALS and PLS fibroblasts had higher average mitochondrial membrane potential, respiration, and glycolysis, suggesting that they were in a hypermetabolic state. Only membrane potential was elevated in C9Orf72 lines. ATP steady state levels did not correlate with respiration and glycolysis in sALS and PLS lines. Based on bioenergetic profiles, a support vector machine (SVM) was trained to classify sALS and PLS with 99% specificity and 70% sensitivity. CONCLUSIONS sALS, PLS, and C9Orf72 fibroblasts share hypermetabolic features, while presenting differences of bioenergetics. The absence of correlation between energy metabolism activation and ATP levels in sALS and PLS fibroblasts suggests that in these cells hypermetabolism is a mechanism to adapt to energy dissipation. Results from SVM support the use of metabolic characteristics of ALS fibroblasts and multivariate analysis to develop classifiers for patient stratification.
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53
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Ferraro PM, Agosta F, Riva N, Copetti M, Spinelli EG, Falzone Y, Sorarù G, Comi G, Chiò A, Filippi M. Multimodal structural MRI in the diagnosis of motor neuron diseases. NEUROIMAGE-CLINICAL 2017; 16:240-247. [PMID: 28794983 PMCID: PMC5545829 DOI: 10.1016/j.nicl.2017.08.002] [Citation(s) in RCA: 47] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/11/2017] [Revised: 07/17/2017] [Accepted: 08/01/2017] [Indexed: 01/18/2023]
Abstract
This prospective study developed an MRI-based method for identification of individual motor neuron disease (MND) patients and test its accuracy at the individual patient level in an independent sample compared with mimic disorders. 123 patients with amyotrophic lateral sclerosis (ALS), 44 patients with predominantly upper motor neuron disease (PUMN), 20 patients with ALS-mimic disorders, and 78 healthy controls were studied. The diagnostic accuracy of precentral cortical thickness and diffusion tensor (DT) MRI metrics of corticospinal and motor callosal tracts were assessed in a training cohort and externally proved in a validation cohort using a random forest analysis. In the training set, precentral cortical thickness showed 0.86 and 0.89 accuracy in differentiating ALS and PUMN patients from controls, while DT MRI distinguished the two groups from controls with 0.78 and 0.92 accuracy. In ALS vs controls, the combination of cortical thickness and DT MRI metrics (combined model) improved the classification pattern (0.91 accuracy). In the validation cohort, the best accuracy was reached by DT MRI (0.87 and 0.95 accuracy in ALS and PUMN vs mimic disorders). The combined model distinguished ALS and PUMN patients from mimic syndromes with 0.87 and 0.94 accuracy. A multimodal MRI approach that incorporates motor cortical and white matter alterations yields statistically significant improvement in accuracy over using each modality separately in the individual MND patient classification. DT MRI represents the most powerful tool to distinguish MND from mimic disorders. Motor cortical and white matter alterations yield high accuracy in the individual MND patient classification. DT MRI represents the most powerful tool to distinguish MND from mimic disorders. The most pronounced damage in MND patients relative to mimic subjects was found in the motor callosal fibers.
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Affiliation(s)
- Pilar M Ferraro
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
| | - Federica Agosta
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
| | - Nilo Riva
- Department of Neurology, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
| | - Massimiliano Copetti
- Biostatistics Unit, IRCCS-Ospedale Casa Sollievo della Sofferenza, San Giovanni Rotondo, Foggia, Italy
| | - Edoardo Gioele Spinelli
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy.,Department of Neurology, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
| | - Yuri Falzone
- Department of Neurology, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
| | - Gianni Sorarù
- Department of Neuroscience, University of Padova, Padova, Italy
| | - Giancarlo Comi
- Department of Neurology, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
| | - Adriano Chiò
- ALS Center, 'Rita Levi Montalcini' Department of Neuroscience, University of Torino, Torino, Italy
| | - Massimo Filippi
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy.,Department of Neurology, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
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Rocha AJD, Chieia MA. Revealing the microstructural brain damage in amyotrophic lateral sclerosis: the relentless pursuit to approach an imaging biomarker. ARQUIVOS DE NEURO-PSIQUIATRIA 2017; 75:265-266. [PMID: 28591383 DOI: 10.1590/0004-282x20170055] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/17/2017] [Accepted: 04/24/2017] [Indexed: 11/21/2022]
Affiliation(s)
- Antônio José da Rocha
- Santa Casa de Misericórdia de São Paulo, Serviço de Diagnóstico por Imagem, São Paulo SP, Brasil
| | - Marco Antonio Chieia
- Universidade Federal de São Paulo, Departamento de Neurologia e Neurocirurgia, São Paulo SP, Brasil
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Querin G, El Mendili MM, Lenglet T, Delphine S, Marchand-Pauvert V, Benali H, Pradat PF. Spinal cord multi-parametric magnetic resonance imaging for survival prediction in amyotrophic lateral sclerosis. Eur J Neurol 2017; 24:1040-1046. [PMID: 28586096 DOI: 10.1111/ene.13329] [Citation(s) in RCA: 36] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2017] [Accepted: 04/13/2017] [Indexed: 12/11/2022]
Abstract
BACKGROUND AND PURPOSE Assessing survival is a critical issue in patients with amyotrophic lateral sclerosis (ALS). Neuroimaging seems to be promising in the assessment of disease severity and several studies also suggest a strong relationship between spinal cord (SC) atrophy described by magnetic resonance imaging (MRI) and disease progression. The aim of the study was to determine the predictive added value of multimodal SC MRI on survival. METHODS Forty-nine ALS patients were recruited and clinical data were collected. Patients were scored on the Revised ALS Functional Rating Scale and manual muscle testing. They were followed longitudinally to assess survival. The cervical SC was imaged using the 3 T MRI system. Cord volume and cross-sectional area (CSA) at each vertebral level were computed. Diffusion tensor imaging metrics were measured. Imaging metrics and clinical variables were used as inputs for a multivariate Cox regression survival model. RESULTS On building a multivariate Cox regression model with clinical and MRI parameters, fractional anisotropy, magnetization transfer ratio and CSA at C2-C3, C4-C5, C5-C6 and C6-C7 vertebral levels were significant. Moreover, the hazard ratio calculated for CSA at the C3-C4 and C5-C6 levels indicated an increased risk for patients with SC atrophy (respectively 0.66 and 0.68). In our cohort, MRI parameters seem to be more predictive than clinical variables, which had a hazard ratio very close to 1. CONCLUSIONS It is suggested that multimodal SC MRI could be a useful tool in survival prediction especially if used at the beginning of the disease and when combined with clinical variables. To validate it as a biomarker, confirmation of the results in bigger independent cohorts of patients is warranted.
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Affiliation(s)
- G Querin
- Laboratoire d'Imagerie Biomédicale, CNRS, INSERM, Sorbonne Universités, UPMC Univ Paris 06, Paris, France
| | - M M El Mendili
- Laboratoire d'Imagerie Biomédicale, CNRS, INSERM, Sorbonne Universités, UPMC Univ Paris 06, Paris, France.,Department of Neurology, Icahn School of Medicine, Mount Sinai, NY, USA
| | - T Lenglet
- Département de Neurophysiologie, APHP, Hôpital Pitié-Salpêtrière, Paris, France
| | - S Delphine
- Laboratoire d'Imagerie Biomédicale, CNRS, INSERM, Sorbonne Universités, UPMC Univ Paris 06, Paris, France.,Institut des Neurosciences Translationnelles, Institut Du Cerveau Et De La Moelle Épinière - IHU-A-ICM, Paris, France
| | - V Marchand-Pauvert
- Laboratoire d'Imagerie Biomédicale, CNRS, INSERM, Sorbonne Universités, UPMC Univ Paris 06, Paris, France
| | - H Benali
- Laboratoire d'Imagerie Biomédicale, CNRS, INSERM, Sorbonne Universités, UPMC Univ Paris 06, Paris, France
| | - P-F Pradat
- Laboratoire d'Imagerie Biomédicale, CNRS, INSERM, Sorbonne Universités, UPMC Univ Paris 06, Paris, France.,Département des Maladies du Système Nerveux, Centre référent SLA, APHP, Hôpital Pitié-Salpêtrière Paris, Paris, France
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Multimodal assessment of white matter tracts in amyotrophic lateral sclerosis. PLoS One 2017; 12:e0178371. [PMID: 28575122 PMCID: PMC5456080 DOI: 10.1371/journal.pone.0178371] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2016] [Accepted: 05/11/2017] [Indexed: 11/19/2022] Open
Abstract
Several quantitative magnetic resonance imaging (MRI) techniques have been proposed to investigate microstructural tissue changes in amyotrophic lateral sclerosis (ALS) including diffusion tensor imaging (DTI), magnetization transfer imaging, and R2* mapping. Here, in this study, we compared these techniques with regard to their capability for detecting ALS related white matter (WM) changes in the brain and their association with clinical findings. We examined 27 ALS patients and 35 age-matched healthy controls. MRI was performed at 3T, after which we analyzed the diffusion properties, the magnetization transfer ratio (MTR), and the effective transversal relaxation rate R2* in 18 WM tracts that were obtained by a fully automated segmentation technique. ALS patients, especially with a bulbar onset, showed a bilateral increase in radial and mean diffusivity, as well as a reduction in fractional anisotropy of the corticospinal tract (CST), and diffusion changes in the parietal and temporal superior longitudinal fasciculus. A reduction of the MTR was found in both CSTs and an R2* reduction was seen only in the left CST. Tract-specific diffusion properties were not related to clinical status in a cross-sectional manner but demonstrated some association with disease progression over three subsequent months. DTI reveals more widespread WM tissue changes than MTR and R2*. These changes are not restricted to the CST, but affect also other WM tracts (especially in patients with bulbar onset), and are associated with the short term course of the disease.
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Shefner JM, Sabbagh MN. An Appraisal of Novel Biomarkers for Evaluating and Monitoring Neurologic Diseases: Editorial Introduction. Neurotherapeutics 2017; 14:1-3. [PMID: 27933486 PMCID: PMC5233637 DOI: 10.1007/s13311-016-0502-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Affiliation(s)
- Jeremy M. Shefner
- Department of Neurology, Barrow Neurological Institute, Phoenix, AZ USA
| | - Marwan N. Sabbagh
- Department of Neurology, Barrow Neurological Institute, Phoenix, AZ USA
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