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Shin-Yi Lin C, Howells J, Rutkove S, Nandedkar S, Neuwirth C, Noto YI, Shahrizaila N, Whittaker RG, Bostock H, Burke D, Tankisi H. Neurophysiological and imaging biomarkers of lower motor neuron dysfunction in motor neuron diseases/amyotrophic lateral sclerosis: IFCN handbook chapter. Clin Neurophysiol 2024; 162:91-120. [PMID: 38603949 DOI: 10.1016/j.clinph.2024.03.015] [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: 10/03/2023] [Revised: 02/07/2024] [Accepted: 03/12/2024] [Indexed: 04/13/2024]
Abstract
This chapter discusses comprehensive neurophysiological biomarkers utilised in motor neuron disease (MND) and, in particular, its commonest form, amyotrophic lateral sclerosis (ALS). These encompass the conventional techniques including nerve conduction studies (NCS), needle and high-density surface electromyography (EMG) and H-reflex studies as well as novel techniques. In the last two decades, new methods of assessing the loss of motor units in a muscle have been developed, that are more convenient than earlier methods of motor unit number estimation (MUNE),and may use either electrical stimulation (e.g. MScanFit MUNE) or voluntary activation (MUNIX). Electrical impedance myography (EIM) is another novel approach for the evaluation that relies upon the application and measurement of high-frequency, low-intensity electrical current. Nerve excitability techniques (NET) also provide insights into the function of an axon and reflect the changes in resting membrane potential, ion channel dysfunction and the structural integrity of the axon and myelin sheath. Furthermore, imaging ultrasound techniques as well as magnetic resonance imaging are capable of detecting the constituents of morphological changes in the nerve and muscle. The chapter provides a critical description of the ability of each technique to provide neurophysiological insight into the complex pathophysiology of MND/ALS. However, it is important to recognise the strengths and limitations of each approach in order to clarify utility. These neurophysiological biomarkers have demonstrated reliability, specificity and provide additional information to validate and assess lower motor neuron dysfunction. Their use has expanded the knowledge about MND/ALS and enhanced our understanding of the relationship between motor units, axons, reflexes and other neural circuits in relation to clinical features of patients with MND/ALS at different stages of the disease. Taken together, the ultimate goal is to aid early diagnosis, distinguish potential disease mimics, monitor and stage disease progression, quantify response to treatment and develop potential therapeutic interventions.
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Affiliation(s)
- Cindy Shin-Yi Lin
- Faculty of Medicine and Health, Central Clinical School, Brain and Mind Centre, University of Sydney, Sydney 2006, Australia.
| | - James Howells
- Central Clinical School, Faculty of Medicine and Health, University of Sydney, Sydney, Australia
| | - Seward Rutkove
- Department of Neurology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
| | - Sanjeev Nandedkar
- Natus Medical Inc, Middleton, Wisconsin, USA and Medical College of Wisconsin, Milwaukee, WI, USA
| | - Christoph Neuwirth
- Neuromuscular Diseases Unit/ALS Clinic, Kantonsspital, St. Gallen, Switzerland
| | - Yu-Ichi Noto
- Department of Neurology, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kyoto, Japan
| | - Nortina Shahrizaila
- Division of Neurology, Department of Medicine, University of Malaya, Kuala Lumpur 50603, Malaysia
| | - Roger G Whittaker
- Newcastle University Translational and Clinical Research Institute (NUTCRI), Newcastle University., Newcastle Upon Tyne, United Kingdom
| | - Hugh Bostock
- Department of Neuromuscular Diseases, UCL Queen Square Institute of Neurology, Queen Square, WC1N 3BG, London, United Kingdom
| | - David Burke
- Central Clinical School, Faculty of Medicine and Health, University of Sydney, Sydney, Australia
| | - Hatice Tankisi
- Department of Clinical Neurophysiology, Aarhus University Hospital and Department of Clinical Medicine, Aarhus University, Aarhus, Denmark.
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Zhang D, Lu Z, Gong W, Zhou P. Effect of surface electrode recording area on compound muscle action potential scan processing for motor unit number estimation. Front Neurosci 2024; 18:1382871. [PMID: 38841095 PMCID: PMC11150645 DOI: 10.3389/fnins.2024.1382871] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2024] [Accepted: 04/17/2024] [Indexed: 06/07/2024] Open
Abstract
Introduction MScanFit is a model-based algorithm for motor unit number estimation (MUNE) from compound muscle action potential (CMAP) scan data. It is a clinically applicable tool because of its quick and automatic implementation. Electrodes with different recording areas were employed to record CMAP scan data in existing studies. However, the effect of electrode recording area on MScanFit MUNE and other CMAP scan parameters has not been studied. Methods CMAP scan was performed on the abductor pollicis brevis muscle of both hands on 14 healthy subjects using three different electrodes with recording areas of 10 mm × 10 mm, 11 mm × 14 mm, and 22 mm × 26 mm, respectively. Motor unit number was estimated using MScanFit for each CMAP scan. Two motor unit number index parameters, i.e., D50 and step index (STEPIX), were also derived from the CMAP scan data. Results No significant difference in D50, STEPIX, and MScanFit MUNE was observed across three different electrode recording areas, although the amplitude of CMAP decreased significantly when a larger electrode was used. Intraclass correlation coefficients of 0.792 and 0.782 were obtained for MScanFit MUNE and STEPIX, respectively. Discussion Compared with CMAP amplitude, D50, STEPIX, and MScanFit MUNE are less sensitive to variation in electrode recording area. However, the repeatability of MScanFit MUNE could be compromised by the inconsistency in the electrode recording area.
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Affiliation(s)
- Dan Zhang
- School of Rehabilitation Medicine, Shandong Second Medical University, Weifang, Shandong, China
| | - Zhiyuan Lu
- School of Rehabilitation Science and Engineering, University of Health and Rehabilitation Sciences, Qingdao, Shandong, China
| | - Weijun Gong
- School of Rehabilitation Medicine, Shandong Second Medical University, Weifang, Shandong, China
- Department of Neurological Rehabilitation, Beijing Rehabilitation Hospital, Capital Medical University, Beijing, China
| | - Ping Zhou
- School of Rehabilitation Science and Engineering, University of Health and Rehabilitation Sciences, Qingdao, Shandong, China
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Tzeplaeff L, Jürs AV, Wohnrade C, Demleitner AF. Unraveling the Heterogeneity of ALS-A Call to Redefine Patient Stratification for Better Outcomes in Clinical Trials. Cells 2024; 13:452. [PMID: 38474416 PMCID: PMC10930688 DOI: 10.3390/cells13050452] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2024] [Revised: 02/26/2024] [Accepted: 02/28/2024] [Indexed: 03/14/2024] Open
Abstract
Despite tremendous efforts in basic research and a growing number of clinical trials aiming to find effective treatments, amyotrophic lateral sclerosis (ALS) remains an incurable disease. One possible reason for the lack of effective causative treatment options is that ALS may not be a single disease entity but rather may represent a clinical syndrome, with diverse genetic and molecular causes, histopathological alterations, and subsequent clinical presentations contributing to its complexity and variability among individuals. Defining a way to subcluster ALS patients is becoming a central endeavor in the field. Identifying specific clusters and applying them in clinical trials could enable the development of more effective treatments. This review aims to summarize the available data on heterogeneity in ALS with regard to various aspects, e.g., clinical, genetic, and molecular.
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Affiliation(s)
- Laura Tzeplaeff
- Department of Neurology, Rechts der Isar Hospital, Technical University of Munich, 81675 München, Germany
| | - Alexandra V. Jürs
- Translational Neurodegeneration Section “Albrecht Kossel”, Department of Neurology, University Medical Center Rostock, 18057 Rostock, Germany
| | - Camilla Wohnrade
- Department of Neurology, Hannover Medical School, 30625 Hannover, Germany;
| | - Antonia F. Demleitner
- Department of Neurology, Rechts der Isar Hospital, Technical University of Munich, 81675 München, Germany
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Chen M, Lu Z, Li X, Zong Y, Xie Q, Li S, Zhou P. Compound muscle action potential (CMAP) scan examination of paretic and contralateral muscles reveals motor unit alterations after stroke. SCIENCE CHINA. LIFE SCIENCES 2023; 66:2604-2613. [PMID: 37258801 PMCID: PMC11057326 DOI: 10.1007/s11427-022-2308-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/24/2022] [Accepted: 03/19/2023] [Indexed: 06/02/2023]
Abstract
This study presents a novel compound muscle action potential (CMAP) examination of motor unit changes in paretic muscle post stroke. CMAP scan of the first dorsal interosseous (FDI) muscle was performed bilaterally in 16 chronic stroke subjects. Various parameters were derived from the CMAP scan to examine paretic muscle changes, including CMAP amplitude, D50, step index (STEPIX) and amplitude index (AMPIX). A significant decrease in CMAP amplitude and STEPIX was observed in paretic muscles compared with contralateral muscles (CMAP amplitude: paretic (9.0±0.5) mV, contralateral (11.3±0.9) mV, P=0.024; STEPIX: paretic 101.2±7.6, contralateral 121.9±6.5, P=0.020). No significant difference in D50 and AMPIX was observed between the paretic and contralateral sides (P>0.05). The findings revealed complex paretic muscle changes including motor unit degeneration, muscle fiber denervation, reinnervation and atrophy, providing useful insights to help understand neuromuscular mechanisms associated with weakness and other functional deterioration post stroke. The CMAP scan experimental protocols and the applied processing methods are noninvasive, convenient, and automated, offering practical benefits for clinical application.
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Affiliation(s)
- Maoqi Chen
- School of Rehabilitation Science and Engineering, University of Health and Rehabilitation Sciences, Qingdao, 266071, China
| | - Zhiyuan Lu
- School of Rehabilitation Science and Engineering, University of Health and Rehabilitation Sciences, Qingdao, 266071, China.
| | - Xiaoyan Li
- Department of Neurology, Medical College of Wisconsin, Milwaukee, WI, 53226, USA
- Fischell Department of Bioengineering, University of Maryland at College Park, College Park, MD, 20742, USA
| | - Ya Zong
- Department of Rehabilitation Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Qing Xie
- Department of Rehabilitation Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Sheng Li
- Department of Physical Medicine and Rehabilitation, University of Texas Health Science Center, Houston, TX, 77030, USA
- TIRR Memorial Hermann Research Center, TIRR Memorial Hermann Hospital, Houston, TX, 77030, USA
| | - Ping Zhou
- School of Rehabilitation Science and Engineering, University of Health and Rehabilitation Sciences, Qingdao, 266071, China
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Sleutjes BTHM, Stikvoort García DJL, van Doorn PA, Goedee HS, van den Berg LH. Simulating progressive motor neuron degeneration and collateral reinnervation in motor neuron diseases using a dynamic muscle model based on human single motor unit recordings. J Neural Eng 2023; 20:056039. [PMID: 37774693 DOI: 10.1088/1741-2552/acfe9d] [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: 12/20/2022] [Accepted: 09/29/2023] [Indexed: 10/01/2023]
Abstract
Objective.To simulate progressive motor neuron loss and collateral reinnervation in motor neuron diseases (MNDs) by developing a dynamic muscle model based on human single motor unit (MU) surface-electromyography (EMG) recordings.Approach.Single MU potentials recorded with high-density surface-EMG from thenar muscles formed the basic building blocks of the model. From the baseline MU pool innervating a muscle, progressive MU loss was simulated by removal of MUs, one-by-one. These removed MUs underwent collateral reinnervation with scenarios varying from 0% to 100%. These scenarios were based on a geometric variable, reflecting the overlap in MU territories using the spatiotemporal profiles of single MUs and a variable reflecting the efficacy of the reinnervation process. For validation, we tailored the model to generate compound muscle action potential (CMAP) scans, which is a promising surface-EMG method for monitoring MND patients. Selected scenarios for reinnervation that matched observed MU enlargements were used to validate the model by comparing markers (including the maximum CMAP and a motor unit number estimate (MUNE)) derived from simulated and recorded CMAP scans in a cohort of 49 MND patients and 22 age-matched healthy controls.Main results.The maximum CMAP at baseline was 8.3 mV (5th-95th percentile: 4.6 mV-11.8 mV). Phase cancellation caused an amplitude drop of 38.9% (5th-95th percentile, 33.0%-45.7%). To match observations, the geometric variable had to be set at 40% and the efficacy variable at 60%-70%. The Δ maximum CMAP between recorded and simulated CMAP scans as a function of fitted MUNE was -0.4 mV (5th-95th percentile = -4.0 - +2.4 mV).Significance.The dynamic muscle model could be used as a platform to train personnel in applying surface-EMG methods prior to their use in clinical care and trials. Moreover, the model may pave the way to compare biomarkers more efficiently, without directly posing unnecessary burden on patients.
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Affiliation(s)
- Boudewijn T H M Sleutjes
- Department of Neurology, Brain Center Utrecht, University Medical Center Utrecht, Utrecht, The Netherlands
| | | | - Pieter A van Doorn
- Department of Neurology, Erasmus Medical Center Rotterdam, Rotterdam, The Netherlands
| | - H Stephan Goedee
- Department of Neurology, Brain Center Utrecht, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Leonard H van den Berg
- Department of Neurology, Brain Center Utrecht, University Medical Center Utrecht, Utrecht, The Netherlands
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Sørensen DM, Bostock H, Abrahao A, Alaamel A, Alaydin HC, Ballegaard M, Boran E, Cengiz B, de Carvalho M, Dunker Ø, Fuglsang-Frederiksen A, Graffe CC, Jones KE, Kallio M, Kalra S, Krarup C, Krøigård T, Liguori R, Lupescu T, Maitland S, Matamala JM, Moldovan M, Moreno-Roco J, Nilsen KB, Phung L, Santos MO, Themistocleous AC, Uysal H, Vacchiano V, Whittaker RG, Zinman L, Tankisi H. Estimating motor unit numbers from a CMAP scan: Repeatability study on three muscles at 15 centres. Clin Neurophysiol 2023; 151:92-99. [PMID: 37236129 DOI: 10.1016/j.clinph.2023.04.008] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2023] [Revised: 03/16/2023] [Accepted: 04/15/2023] [Indexed: 05/28/2023]
Abstract
OBJECTIVE To assess the repeatability and suitability for multicentre studies of MScanFit motor unit number estimation (MUNE), which involves modelling compound muscle action potential (CMAP) scans. METHODS Fifteen groups in 9 countries recorded CMAP scans twice, 1-2 weeks apart in healthy subjects from abductor pollicis brevis (APB), abductor digiti minimi (ADM) and tibialis anterior (TA) muscles. The original MScanFit program (MScanFit-1) was compared with a revised version (MScanFit-2), designed to accommodate different muscles and recording conditions by setting the minimal motor unit size as a function of maximum CMAP. RESULTS Complete sets of 6 recordings were obtained from 148 subjects. CMAP amplitudes differed significantly between centres for all muscles, and the same was true for MScanFit-1 MUNE. With MScanFit-2, MUNE differed less between centres but remained significantly different for APB. Coefficients of variation between repeats were 18.0% for ADM, 16.8% for APB, and 12.1% for TA. CONCLUSIONS It is recommended for multicentre studies to use MScanFit-2 for analysis. TA provided the least variable MUNE values between subjects and the most repeatable within subjects. SIGNIFICANCE MScanFit was primarily devised to model the discontinuities in CMAP scans in patients and is less suitable for healthy subjects with smooth scans.
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Affiliation(s)
- D M Sørensen
- Department of Clinical Neurophysiology, Aarhus University Hospital, Denmark
| | - H Bostock
- UCL Queen Square Institute of Neurology, Queen Square, London, United Kingdom
| | - A Abrahao
- Department of Medicine, University of Toronto, Toronto, Canada
| | - A Alaamel
- Department of Neurology, Akdeniz University Hospital, Antalya, Turkey
| | - H C Alaydin
- Department of Neurology, Gazi University, Ankara, Turkey
| | - M Ballegaard
- Department of Clinical Neurology, Zealand University Hospital, Roskilde, Denmark
| | - E Boran
- Department of Neurology, Gazi University, Ankara, Turkey
| | - B Cengiz
- Department of Neurology, Gazi University, Ankara, Turkey
| | - M de Carvalho
- Faculty of Medicine, iMM, Centro de Estudos Egas Moniz, Universidade de Lisboa, Department of Neurosciences and Mental Health, CHULN, Lisbon, Portugal
| | - Ø Dunker
- Department of Neurology and Department of Research and Innovation, Division of Clinical Neuroscience, Oslo University Hospital, Norway
| | - A Fuglsang-Frederiksen
- Department of Clinical Neurophysiology, Aarhus University Hospital, Denmark; Department of Clinical Institute, Aarhus University, Aarhus, Denmark
| | - C C Graffe
- Department of Clinical Neurophysiology, Rigshospitalet, Copenhagen, Denmark
| | - K E Jones
- Neuroscience and Mental Health Institute, University of Alberta, Edmonton, Canada
| | - M Kallio
- Department of Clinical Neurophysiology, Oulu University Hospital, Oulu, Finland
| | - S Kalra
- Neuroscience and Mental Health Institute, University of Alberta, Edmonton, Canada
| | - C Krarup
- Department of Clinical Neurophysiology, Rigshospitalet, Copenhagen, Denmark
| | - T Krøigård
- Department of Neurology, Odense University Hospital, Denmark
| | - R Liguori
- Dipertimento di Scienze Biomediche e Neuromotorie, Università di Bologna, Bologna, Italy
| | - T Lupescu
- Department of Neurology, Agrippa Ionescu Hospital, Bucharest, Romania
| | - S Maitland
- Translational and Clinical Research Institute, Newcastle University, United Kingdom
| | - J M Matamala
- Translational Neurology and Neurophysiology Lab, Department of Neurological Sciences and Biomedical Neuroscience Institute, University of Chile, Santiago, Chile
| | - M Moldovan
- Department of Clinical Neurophysiology, Rigshospitalet, Copenhagen, Denmark
| | - J Moreno-Roco
- Translational Neurology and Neurophysiology Lab, Department of Neurological Sciences and Biomedical Neuroscience Institute, University of Chile, Santiago, Chile
| | - K B Nilsen
- Department of Neurology and Department of Research and Innovation, Division of Clinical Neuroscience, Oslo University Hospital, Norway
| | - L Phung
- Department of Medicine, University of Toronto, Toronto, Canada
| | - M O Santos
- Faculty of Medicine, iMM, Centro de Estudos Egas Moniz, Universidade de Lisboa, Department of Neurosciences and Mental Health, CHULN, Lisbon, Portugal
| | - A C Themistocleous
- Nuffield Department of Clinical Neurosciences University of Oxford, Oxford, United Kingdom
| | - H Uysal
- Department of Medicine, University of Toronto, Toronto, Canada
| | - V Vacchiano
- Dipertimento di Scienze Biomediche e Neuromotorie, Università di Bologna, Bologna, Italy
| | - R G Whittaker
- Translational and Clinical Research Institute, Newcastle University, United Kingdom
| | - L Zinman
- UCL Queen Square Institute of Neurology, Queen Square, London, United Kingdom
| | - H Tankisi
- Department of Clinical Neurophysiology, Aarhus University Hospital, Denmark; Department of Clinical Institute, Aarhus University, Aarhus, Denmark.
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Maguina M, Kang PB, Tsai AC, Pacak CA. Peripheral neuropathies associated with DNA repair disorders. Muscle Nerve 2023; 67:101-110. [PMID: 36190439 PMCID: PMC10075233 DOI: 10.1002/mus.27721] [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: 12/13/2021] [Revised: 09/08/2022] [Accepted: 09/10/2022] [Indexed: 01/25/2023]
Abstract
Repair of genomic DNA is a fundamental housekeeping process that quietly maintains the health of our genomes. The consequences of a genetic defect affecting a component of this delicate mechanism are quite harmful, characterized by a cascade of premature aging that injures a variety of organs, including the nervous system. One part of the nervous system that is impaired in certain DNA repair disorders is the peripheral nerve. Chronic motor, sensory, and sensorimotor polyneuropathies have all been observed in affected individuals, with specific physiologies associated with different categories of DNA repair disorders. Cockayne syndrome has classically been linked to demyelinating polyneuropathies, whereas xeroderma pigmentosum has long been associated with axonal polyneuropathies. Three additional recessive DNA repair disorders are associated with neuropathies, including trichothiodystrophy, Werner syndrome, and ataxia-telangiectasia. Although plausible biological explanations exist for why the peripheral nerves are specifically vulnerable to impairments of DNA repair, specific mechanisms such as oxidative stress remain largely unexplored in this context, and bear further study. It is also unclear why different DNA repair disorders manifest with different types of neuropathy, and why neuropathy is not universally present in those diseases. Longitudinal physiological monitoring of these neuropathies with serial electrodiagnostic studies may provide valuable noninvasive outcome data in the context of future natural history studies, and thus the responses of these neuropathies may become sentinel outcome measures for future clinical trials of treatments currently in development such as adeno-associated virus gene replacement therapies.
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Affiliation(s)
- Melissa Maguina
- Medical Education Program, Nova Southeastern University, Fort Lauderdale, Florida
| | - Peter B Kang
- Department of Neurology, Paul and Sheila Wellstone Muscular Dystrophy Center, University of Minnesota Medical School, Minneapolis, Minnesota.,Institute for Translational Neuroscience, University of Minnesota Medical School, Minneapolis, Minnesota
| | - Ang-Chen Tsai
- Department of Pediatrics, University of Florida College of Medicine, Gainesville, Florida
| | - Christina A Pacak
- Department of Neurology, Paul and Sheila Wellstone Muscular Dystrophy Center, University of Minnesota Medical School, Minneapolis, Minnesota
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Willemse SW, Roes KCB, Van Damme P, Hardiman O, Ingre C, Povedano M, Wray NR, Gijzen M, de Pagter MS, Demaegd KC, Janse AFC, Vink RG, Sleutjes BTHM, Chiò A, Corcia P, Reviers E, Al-Chalabi A, Kiernan MC, van den Berg LH, van Es MA, van Eijk RPA. Lithium carbonate in amyotrophic lateral sclerosis patients homozygous for the C-allele at SNP rs12608932 in UNC13A: protocol for a confirmatory, randomized, group-sequential, event-driven, double-blind, placebo-controlled trial. Trials 2022; 23:978. [PMID: 36471413 PMCID: PMC9721045 DOI: 10.1186/s13063-022-06906-5] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Accepted: 11/03/2022] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND Given the large genetic heterogeneity in amyotrophic lateral sclerosis (ALS), it seems likely that genetic subgroups may benefit differently from treatment. An exploratory meta-analysis identified that patients homozygous for the C-allele at SNP rs12608932, a single nucleotide polymorphism in the gene UNC13A, had a statistically significant survival benefit when treated with lithium carbonate. We aim to confirm the efficacy of lithium carbonate on the time to death or respiratory insufficiency in patients with ALS homozygous for the C-allele at SNP rs12608932 in UNC13A. METHODS A randomized, group-sequential, event-driven, double-blind, placebo-controlled trial will be conducted in 15 sites across Europe and Australia. Patients will be genotyped for UNC13A; those homozygous for the C-allele at SNP rs12608932 will be eligible. Patients must have a diagnosis of ALS according to the revised El Escorial criteria, and a TRICALS risk-profile score between -6.0 and -2.0. An expected number of 1200 patients will be screened in order to enroll a target sample size of 171 patients. Patients will be randomly allocated in a 2:1 ratio to lithium carbonate or matching placebo, and treated for a maximum duration of 24 months. The primary endpoint is the time to death or respiratory insufficiency, whichever occurs first. Key secondary endpoints include functional decline, respiratory function, quality of life, tolerability, and safety. An interim analysis for futility and efficacy will be conducted after the occurrence of 41 events. DISCUSSION Lithium carbonate has been proven to be safe and well-tolerated in patients with ALS. Given the favorable safety profile, the potential benefits are considered to outweigh the burden and risks associated with study participation. This study may provide conclusive evidence about the life-prolonging potential of lithium carbonate in a genetic ALS subgroup. TRIAL REGISTRATION EudraCT number 2020-000579-19 . Registered on 29 March 2021.
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Affiliation(s)
- Sean W Willemse
- Department of Neurology, UMC Utrecht, Utrecht, The Netherlands
| | - Kit C B Roes
- Department of Health Evidence, Radboud UMC, Nijmegen, The Netherlands
| | - Philip Van Damme
- Department of Neurology, University Hospitals Leuven, Leuven, Belgium
| | - Orla Hardiman
- Department of Neurology, National Neuroscience Centre, Beaumont Hospital, Dublin, Ireland
- FutureNeuro SFI Research Centre, Royal College of Surgeons in Ireland, Dublin, Ireland
| | - Caroline Ingre
- Department of Clinical Neuroscience, Karolinska Institute, Stockholm, Sweden
| | - Monica Povedano
- Functional Unit of Amyotrophic Lateral Sclerosis (UFELA), Service of Neurology, Bellvitge University Hospital, Hospitalet de Llobregat, Spain
| | - Naomi R Wray
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia
| | - Marleen Gijzen
- Department of Genetics, UMC Utrecht, Utrecht, The Netherlands
| | | | - Koen C Demaegd
- Department of Neurology, UMC Utrecht, Utrecht, The Netherlands
| | | | | | | | - Adriano Chiò
- 'Rita Levi Montalcini' Department of Neuroscience, University of Turin, Turin, Italy
- Neurology, AOU Città della Salute e della Scienza Hospital of Turin, Turin, Italy
| | - Philippe Corcia
- Centre Constitutif SLA, CHRU de Tours - Fédération des centres SLA Tours-Limoges, LitORALS, Tours, France
| | - Evy Reviers
- European Organization for Professionals and Patients with ALS (EUpALS) & ALS Liga Belgium, Leuven, Belgium
| | - Ammar Al-Chalabi
- Department of Basic and Clinical Neuroscience, King's College London, Maurice Wohl Clinical Neuroscience Institute, London, UK
- Department of Neurology, King's College Hospital, London, UK
| | - Matthew C Kiernan
- Department of Neurology, Royal Prince Alfred Hospital, Sydney, New South Wales, Australia
- Brain and Mind Centre, University of Sydney, Sydney, New South Wales, Australia
| | | | | | - Ruben P A van Eijk
- Department of Neurology, UMC Utrecht, Utrecht, The Netherlands.
- Biostatistics and Research Support, Julius Centre for Health Sciences and Primary Care, Utrecht University, Utrecht, Netherlands.
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Ahmed N, Baker MR, Bashford J. The landscape of neurophysiological outcome measures in ALS interventional trials: A systematic review. Clin Neurophysiol 2022; 137:132-141. [PMID: 35313253 PMCID: PMC10166714 DOI: 10.1016/j.clinph.2022.02.020] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2021] [Revised: 02/11/2022] [Accepted: 02/18/2022] [Indexed: 12/28/2022]
Abstract
OBJECTIVE We collated all interventional clinical trials in amyotrophic lateral sclerosis (ALS), which utilised at least one neurophysiological technique as a primary or secondary outcome measure. By identifying the strengths and limitations of these studies, we aim to guide study design in future trials. METHODS We conducted and reported this systematic review according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Eight databases were searched from inception. In total, 703 studies were retrieved for screening and eligibility assessment. RESULTS Dating back to 1986, 32 eligible interventional clinical trials were identified, recruiting a median of 30 patients per completed trial. The most widely employed neurophysiological techniques were electromyography, motor unit number estimation (including motor unit number index), neurophysiological index and transcranial magnetic stimulation (including resting motor threshold and short-interval intracortical inhibition). Almost 40% of trials reported a positive outcome with respect to at least one neurophysiological measure. The interventions targeted either ion channels, immune mechanisms or neuronal metabolic pathways. CONCLUSIONS Neurophysiology offers many promising biomarkers that can be utilised as outcome measures in interventional clinical trials in ALS. When selecting the most appropriate technique, key considerations include methodological standardisation, target engagement and logistical burden. SIGNIFICANCE Future trial design in ALS would benefit from a standardised, updated and easily accessible repository of neurophysiological outcome measures.
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Affiliation(s)
- N Ahmed
- GKT School of Medical Education, Faculty of Life Sciences and Medicine, King's College London, UK
| | - M R Baker
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle Upon Tyne, UK
| | - J Bashford
- UK Dementia Research Institute, Department of Basic and Clinical Neuroscience, Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK.
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