Clinical, Neurophysiological, and MRI Markers of Fampridine Responsiveness in Multiple Sclerosis-An Explorative Study

Sepehr Mamoei, Henrik Boye Jensen, Andreas Kristian Pedersen, Mikkel Karl Emil Nygaard, Simon Fristed Eskildsen, Ulrik Dalgas, Egon Stenager, Sepehr Mamoei, Henrik Boye Jensen, Andreas Kristian Pedersen, Mikkel Karl Emil Nygaard, Simon Fristed Eskildsen, Ulrik Dalgas, Egon Stenager

Abstract

Objective: Persons with multiple sclerosis (PwMS), already established as responders or non-responders to Fampridine treatment, were compared in terms of disability measures, physical and cognitive performance tests, neurophysiology, and magnetic resonance imaging (MRI) outcomes in a 1-year explorative longitudinal study. Materials and Methods: Data from a 1-year longitudinal study were analyzed. Examinations consisted of the timed 25-foot walk test (T25FW), six spot step test (SSST), nine-hole peg test (9-HPT), five times sit-to-stand test (5-STS), symbol digit modalities test (SDMT), transcranial magnetic stimulation (TMS) elicited motor evoked potentials (MEP) examining central motor conduction times (CMCT), peripheral motor conduction times (PMCT) and their amplitudes, electroneuronography (ENG) of the lower extremities, and brain structural MRI measures. Results: Forty-one responders and eight non-responders to Fampridine treatment were examined. There were no intergroup differences except for the PMCT, where non-responders had prolonged conduction times compared to responders to Fampridine. Six spot step test was associated with CMCT throughout the study. After 1 year, CMCT was further prolonged and cortical MEP amplitudes decreased in both groups, while PMCT and ENG did not change. Throughout the study, CMCT was associated with the expanded disability status scale (EDSS) and 12-item multiple sclerosis walking scale (MSWS-12), while SDMT was associated with number of T2-weighted lesions, lesion load, and lesion load normalized to brain volume. Conclusions: Peripheral motor conduction time is prolonged in non-responders to Fampridine when compared to responders. Transcranial magnetic stimulation-elicited MEPs and SDMT can be used as markers of disability progression and lesion activity visualized by MRI, respectively. Clinical Trial Registration: www.ClinicalTrials.gov, identifier: NCT03401307.

Keywords: demyelination; magnetic resonance imaging; multiple sclerosis; neurodegeneration; neurophysiology; performance test.

Conflict of interest statement

UD has received research support, travel grants, and/or teaching honorary from Biogen Idec, Merck Serono, Novartis, Bayer Schering, and Sanofi Aventis as well as honoraria from serving on scientific advisory boards of Biogen Idec and Genzyme. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2021 Mamoei, Jensen, Pedersen, Nygaard, Eskildsen, Dalgas and Stenager.

Figures

Figure 1
Figure 1
Mechanism of action of Fampridine in demyelinated axons. Potassium efflux from the voltage-gated potassium channels in the denuded axon is prevented, minimizing hyperpolarization leading to improved neural conduction.
Figure 2
Figure 2
Flowchart of study design and participant selection.
Figure 3
Figure 3
Central and peripheral motor conduction (vastus medialis muscle) derived from transcranial magnetic stimulation elicited motor evoked potentials in responders and non-responders to Fampridine treatment at baseline and 1-year follow-up. 95% CI, 95% confidence interval.

References

    1. Dunn J, Blight A. Dalfampridine: a brief review of its mechanism of action and efficacy as a treatment to improve walking in patients with multiple sclerosis. Curr Med Res Opin. (2011) 27:1415–23. 10.1185/03007995.2011.583229
    1. Arnold R, Huynh W, Kiernan MC, Krishnan AV. Ion channel modulation as a therapeutic approach in multiple sclerosis. Curr Med Chem. (2015) 22:4366–78. 10.2174/0929867322666151029104452
    1. Krishnan AV, Kiernan MC. Sustained-release fampridine and the role of ion channel dysfunction in multiple sclerosis. Mult Scler. (2013) 19:385–91. 10.1177/1352458512463769
    1. Mamoei S, Hvid LG, Boye Jensen H, Zijdewind I, Stenager E, Dalgas U. Neurophysiological impairments in multiple sclerosis – central and peripheral motor pathways. Acta Neurol Scand. (2020) 142:401–17. 10.1111/ane.13289
    1. Huynh W, Pickering H, Howells J, Murray J, Cormack C, Lin CS-Y, et al. . Effect of fampridine on axonal excitability in multiple sclerosis. Clin Neurophysiol. (2016) 127:2636–42. 10.1016/j.clinph.2016.04.010
    1. Filippi M, Bar-Or A, Piehl F, Preziosa P, Solari A, Vukusic S. Multiple sclerosis. Nat Rev Dis Primers. (2018) 4:43. 10.1038/s41572-018-0050-3
    1. Filli L, Werner J, Beyer G, Reuter K, Petersen JA, Weller M, et al. . Predicting responsiveness to fampridine in gait-impaired patients with multiple sclerosis. Eur J Neurol. (2019) 26:281–9. 10.1111/ene.13805
    1. Cofré Lizama LE, Khan F, Lee PV, Galea MP. The use of laboratory gait analysis for understanding gait deterioration in people with multiple sclerosis. Mult Scler. (2016) 22:1768–76. 10.1177/1352458516658137
    1. Heesen C, Böhm J, Reich C, Kasper J, Goebel M, Gold S. Patient perception of bodily functions in multiple sclerosis: gait and visual function are the most valuable. Mult Scler. (2008) 14:988–91. 10.1177/1352458508088916
    1. Ahdab R, Shatila MM, Shatila AR, Khazen G, Freiha J, Salem M, et al. . Cortical excitability measures may predict clinical response to fampridine in patients with multiple sclerosis and gait impairment. Brain Sci. (2019). 9:357. 10.3390/brainsci9120357
    1. Judge SIV, Bever CT, Jr. Potassium channel blockers in multiple sclerosis: neuronal Kv channels and effects of symptomatic treatment. Pharmacol Ther. (2006). 111:224–59. 10.1016/j.pharmthera.2005.10.006
    1. Solari A, Uitdehaag BM, Giuliani G, Pucci E, Taus C. Aminopyridines for symptomatic treatment in multiple sclerosis. Cochrane Database Syst Rev. (2002). 4:CD001330. 10.1002/14651858.CD001330
    1. Jensen H, Ravnborg M, Mamoei S, Dalgas U, Stenager E. Changes in cognition, arm function and lower body function after slow-release fampridine treatment. Mult Scler. (2014) 20:1872–80. 10.1177/1352458514533844
    1. Goodman AD, Bethoux F, Brown TR, Schapiro RT, Cohen R, Marinucci LN, et al. . Long-term safety and efficacy of dalfampridine for walking impairment in patients with multiple sclerosis: results of open-label extensions of two phase 3 clinical trials. Mult Scler. (2015) 21:1322–31. 10.1177/1352458514563591
    1. Allart E, Benoit A, Blanchard-Dauphin A, Tiffreau V, Thevenon A, Zephir H, et al. . Sustained-released fampridine in multiple sclerosis: effects on gait parameters, arm function, fatigue, and quality of life. J Neurol. (2015) 262:1936–45. 10.1007/s00415-015-7797-1
    1. Fragoso YD, Adoni T, Alves-Leon SV, Apostolos-Pereira SL, Barreira AA, Brooks JBB, et al. . Real-life experience with fampridine (Fampyra®) for patients with multiple sclerosis and gait disorders. NeuroRehabilitation. (2016) 39:301–4. 10.3233/NRE-161361
    1. Goodman AD, Brown TR, Krupp LB, Schapiro RT, Schwid SR, Cohen R, et al. . Sustained-release oral fampridine in multiple sclerosis: a randomised, double-blind, controlled trial. Lancet. (2009) 373:732–8. 10.1016/S0140-6736(09)60442-6
    1. Ramió-Torrentà L, Álvarez-Cermeño JC, Arroyo R, Casanova-Estruch B, Fernández O, García-Merino JA, et al. . A guide to treating gait impairment with prolonged-release fampridine (Fampyra ®) in patients with multiple sclerosis. Neurologie (Engl Ed). (2018) 33:327–37. 10.1016/j.nrleng.2015.11.019
    1. Zeller D, Reiners K, Brauninger S, Buttmann M. Central motor conduction time may predict response to fampridine in patients with multiple sclerosis. J Neurol Neurosurg Psychiatry. (2014). 85:707–9. 10.1136/jnnp-2013-306860
    1. Brambilla L, Rossi Sebastiano D, Aquino D, Torri Clerici V, Brenna G, Moscatelli M, et al. . Early effect of dalfampridine in patients with MS: a multi-instrumental approach to better investigate responsiveness. J Neurol Sci. (2016) 368:402–7. 10.1016/j.jns.2016.06.019
    1. Mamoei S, Jensen HB, Dalgas U, Zijdewind I, Pedersen AK, Nygaard MKE, et al. . A cross-sectional comparison of performance, neurophysiological and MRI outcomes of responders and non-responders to fampridine treatment in multiple sclerosis – an explorative study. J Clin Neurosci. (2020) 82:179–85. 10.1016/j.jocn.2020.10.034
    1. Thompson AJ, Banwell BL, Barkhof F, Carroll WM, Coetzee T, Comi G, et al. . Diagnosis of multiple sclerosis: 2017 revisions of the McDonald criteria. Lancet Neurol. (2018) 17:162–73. 10.1016/S1474-4422(17)30470-2
    1. Motl RW, Cohen JA, Benedict R, Phillips G, LaRocca N, Hudson LD, et al. . Validity of the timed 25-foot walk as an ambulatory performance outcome measure for multiple sclerosis. Mult Scler. (2017) 23:704–10. 10.1177/1352458517690823
    1. Nieuwenhuis MM, Van Tongeren H, Sørensen PS, Ravnborg M. The Six Spot Step Test: a new measurement for walking ability in multiple sclerosis. Mult Scler. (2006) 12:495–500. 10.1191/1352458506ms1293oa
    1. de Melo TA, Duarte ACM, Bezerra TS, França F, Soares NS, Brito D. The Five Times Sit-to-Stand Test: safety and reliability with older intensive care unit patients at discharge. Rev Brasil Terap Intens. (2019) 31:27–33. 10.5935/0103-507X.20190006
    1. Feys P, Lamers I, Francis G, Benedict R, Phillips G, LaRocca N, et al. . The Nine-Hole Peg Test as a manual dexterity performance measure for multiple sclerosis. Mult Scler. (2017) 23:711–20. 10.1177/1352458517690824
    1. Van Schependom J, D'hooghe MB, Cleynhens K, D'hooge M, Haelewyck MC, De Keyser J, et al. . The Symbol Digit Modalities Test as sentinel test for cognitive impairment in multiple sclerosis. Eur J Neurol. (2014) 21:1219–25, e71–2. 10.1111/ene.12463
    1. Coupe P, Yger P, Prima S, Hellier P, Kervrann C, Barillot C. An optimized blockwise nonlocal means denoising filter for 3-D magnetic resonance images. IEEE Trans Med Imaging. (2008) 27:425–41. 10.1109/TMI.2007.906087
    1. Sled JG, Zijdenbos AP, Evans AC. A nonparametric method for automatic correction of intensity nonuniformity in MRI data. IEEE Trans Med Imaging. (1998) 17:87–97. 10.1109/42.668698
    1. Collins DL, Neelin P, Peters TM, Evans AC. Automatic 3D intersubject registration of MR volumetric data in standardized Talairach space. J Comput Assist Tomogr. 18:192–205. 10.1097/00004728-199403000-00005
    1. Fonov V, Evans AC, Botteron K, Almli CR, McKinstry RC, Collins DL, et al. . Unbiased average age-appropriate atlases for pediatric studies. Neuroimage. (2011) 54:313–27. 10.1016/j.neuroimage.2010.07.033
    1. Eskildsen SF, Coupé P, Fonov V, Manjón JV, Leung KK, Guizard N, et al. . BEaST: brain extraction based on nonlocal segmentation technique. Neuroimage. (2012) 59:2362–73. 10.1016/j.neuroimage.2011.09.012
    1. Rice CM. Assessment of bone marrow-derived Cellular Therapy in progressive Multiple Sclerosis (ACTiMuS): study protocol for a randomised controlled trial. Trials. (2015). 16:463. 10.1186/s13063-015-0953-1
    1. Jensen H, Mamoei S, Ravnborg M, Dalgas U, Stenager E. Distribution-based estimates of minimum clinically important difference in cognition, arm function and lower body function after slow release-fampridine treatment of patients with multiple sclerosis. Mult Scler Relat Disord. (2016) 7:58–60. 10.1016/j.msard.2016.03.007
    1. Nardone R, Höller Y, Thomschewski A, Höller P, Bergmann J, Golaszewski S, et al. . Central motor conduction studies in patients with spinal cord disorders: a review. Spinal Cord. (2014) 52:420–7. 10.1038/sc.2014.48
    1. Leussink V-I, Stettner M, Warnke C, Hartung H-P. Fampridine-PR (prolonged released 4-aminopyridine) is not effective in patients with inflammatory demyelination of the peripheral nervous system. J Peripher Nerv Syst. (2016) 21:85–7. 10.1111/jns.12169
    1. Jende JME, Hauck GH, Diem R, Weiler M, Heiland S, Wildemann B, et al. . Peripheral nerve involvement in multiple sclerosis: demonstration by magnetic resonance neurography. Ann Neurol. (2017) 82:676–85. 10.1002/ana.25068
    1. Singh S, Dallenga T, Winkler A, Roemer S, Maruschak B, Siebert H, et al. . Relationship of acute axonal damage, Wallerian degeneration, and clinical disability in multiple sclerosis. J Neuroinflammation. (2017) 14:57. 10.1186/s12974-017-0831-8
    1. Misawa S, Kuwabara S, Mori M, Hayakawa S, Sawai S, Hattori T. Peripheral nerve demyelination in multiple sclerosis. Clin Neurophysiol. (2008) 119:1829–33. 10.1016/j.clinph.2008.04.010
    1. Kreutzfeldt M, Jensen HB, Ravnborg M, Markvardsen LH, Andersen H, Sindrup SH. The six-spot-step test SHa new method for monitoring walking ability in patients with chronic inflammatory polyneuropathy. J Peripher Nerv Syst. (2017) 22:131–8. 10.1111/jns.12210
    1. Bennett SE, Bromley LE, Fisher NM, Tomita MR, Niewczyk P. Validity and reliability of four clinical gait measures in patients with multiple sclerosis. Int J MS Care. (2017) 19:247–52. 10.7224/1537-2073.2015-006
    1. Hardmeier M, Leocani L, Fuhr P. A new role for evoked potentials in MS? Repurposing evoked potentials as biomarkers for clinical trials in MS. Mult Scler. (2017) 23:1309–19. 10.1177/1352458517707265
    1. Kallmann BA, Fackelmann S, Toyka KV, Rieckmann P, Reiners K. Early abnormalities of evoked potentials and future disability in patients with multiple sclerosis. Mult Scler. (2006) 12:58–65. 10.1191/135248506ms1244oa
    1. Leocani L, Rovaris M, Boneschi FM, Medaglini S, Rossi P, Martinelli V, et al. . Multimodal evoked potentials to assess the evolution of multiple sclerosis: a longitudinal study. J Neurol Neurosurg Psychiatry. (2006) 77:1030–5. 10.1136/jnnp.2005.086280
    1. Eshaghi A, Prados F, Brownlee WJ, Altmann DR, Tur C, Cardoso MJ, et al. . Deep gray matter volume loss drives disability worsening in multiple sclerosis. Ann Neurol. (2018) 83:210–22. 10.1002/ana.25145
    1. Andravizou A, Dardiotis E, Artemiadis A, Sokratous M, Siokas V, Tsouris Z, et al. . Brain atrophy in multiple sclerosis: mechanisms, clinical relevance and treatment options. Auto Immun Highlights. (2019). 10:7. 10.1186/s13317-019-0117-5
    1. Kalkers NF, Ameziane N, Bot JCJ, Minneboo A, Polman CH, Barkhof F. Longitudinal brain volume measurement in multiple sclerosis. Arch Neurol. (2002) 59:1572. 10.1001/archneur.59.10.1572
    1. Klineova S, Farber R, Saiote C, Farrell C, Delman BN, Tanenbaum LN, et al. . Relationship between timed 25-foot walk and diffusion tensor imaging in multiple sclerosis. Mult Scler J Exp Transl Clin. (2016) 2:205521731665536. 10.1177/2055217316655365
    1. Patti F, De Stefano M, Lavorgna L, Messina S, Chisari CG, Ippolito D, et al. . Lesion load may predict long-term cognitive dysfunction in multiple sclerosis patients. PLoS ONE. (2015) 10:e0120754. 10.1371/journal.pone.0120754
    1. Rao SM, Martin AL, Huelin R, Wissinger E, Khankhel Z, Kim E, et al. . Correlations between MRI and information processing speed in MS: a meta-analysis. Mult Scler Int. (2014). 2014:975803. 10.1155/2014/975803

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