| Title | The Study of Remyelinating Therapies in Multiple Sclerosis: Visual Outcomes as a Window Into Repair |
| Creator | Leah R. Zuroff; Ari J. Green |
| Affiliation | Department of Neurology (LZ), Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania; and Department of Neurology (AJG), University of California San Francisco, San Francisco, California |
| Abstract | Introduction: Amelioration of disability in multiple sclerosis requires the development of complementary therapies that target neurodegeneration and promote repair. Remyelination is a promising neuroprotective strategy that may protect axons from damage and subsequent neurodegeneration. Methods: A review of key literature plus additional targeted search of PubMed and Google Scholar was conducted. Results: There has been a rapid expansion of clinical trials studying putative remyelinating candidates, but further growth of the field is limited by the lack of consensus on key aspects of trial design. We have not yet defined the ideal study population, duration of therapy, or the appropriate outcome measures to detect remyelination in humans. The varied natural history of multiple sclerosis, coupled with the short time frame of phase II clinical trials, requires that we develop and validate biomarkers of remyelination that can serve as surrogate endpoints in clinical trials. Conclusions: We propose that the visual system may be the most well-suited and validated model for the study potential remyelinating agents. In this review, we discuss the pathophysiology of demyelination and summarize the current clinical trial landscape of remyelinating agents. We present some of the challenges in the study of remyelinating agents and discuss current potential biomarkers of remyelination and repair, emphasizing both established and emerging visual outcome measures. |
| Subject | Humans; Multiple Sclerosis / drug therapy; Multiple Sclerosis / physiopathology; Myelin Sheath; Remyelination / drug effects; Remyelination / physiology |
| OCR Text | Show Basic and Translational Research The Study of Remyelinating Therapies in Multiple Sclerosis: Visual Outcomes as a Window Into Repair Leah R. Zuroff, MD, MSTR, Ari J. Green, MD, MCR Introduction: Amelioration of disability in multiple sclerosis requires the development of complementary therapies that target neurodegeneration and promote repair. Remyelination is a promising neuroprotective strategy that may protect axons from damage and subsequent neurodegeneration. Methods: A review of key literature plus additional targeted search of PubMed and Google Scholar was conducted. Results: There has been a rapid expansion of clinical trials studying putative remyelinating candidates, but further growth of the field is limited by the lack of consensus on key aspects of trial design. We have not yet defined the ideal study population, duration of therapy, or the appropriate outcome measures to detect remyelination in humans. The varied natural history of multiple sclerosis, coupled with the short time frame of phase II clinical trials, requires that we develop and validate biomarkers of remyelination that can serve as surrogate endpoints in clinical trials. Conclusions: We propose that the visual system may be the most well-suited and validated model for the study potential remyelinating agents. In this review, we discuss the pathophysiology of demyelination and summarize the current clinical trial landscape of remyelinating agents. We present some of the challenges in the study of remyelinating agents and discuss current potential biomarkers of remyelination and repair, emphasizing both established and emerging visual outcome measures. Journal of Neuro-Ophthalmology 2024;44:143–156 doi: 10.1097/WNO.0000000000002149 D evelopment of highly effective immunomodulatory disease-modifying therapies (DMTs) has revolutionized the treatment of multiple sclerosis (MS). However, ongoing disability progression independent of relapse activity has highDepartment of Neurology (LZ), Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania; and Department of Neurology (AJG), University of California San Francisco, San Francisco, California. L. Zuroff has received speaker fees from EMD Serono. A. J. Green reports other from Bionure, grants, personal fees, and other from Pipeline Pharmaceuticals, grants from National MS Society, and personal fees from JAMA Neurology. In addition, Dr. Green has a patent Small Molecule drug for Remyelination pending and has worked on testing off-label compounds for remyelination. lighted the need for therapeutic interventions aimed at preventing neurodegeneration and promoting repair. Chronic demyelination in the MS central nervous system (CNS) renders axons susceptible to injury and subsequent neurodegeneration.1,2 Remyelination has thus emerged as a promising therapeutic strategy for the prevention of disability and promotion of repair. Advances in our understanding of myelin physiology and ability to identify potential remyelinating candidates has led to a rapid expansion of clinical trials investigating these agents. Although this represents an exciting opportunity for discovery, there are many inherent challenges to studying a novel therapeutic class in MS. There is no consensus on the ideal study population, duration of therapy, or appropriate outcomes to detect remyelination in humans. Thoughtful trial design is critical to ensure that progress is made. We propose that the visual system may be the most wellsuited model for studying remyelinating therapies in MS. Visual system dysfunction is incredibly common in MS and contributes to overall disability.3,4 Dynamic injury and recovery along the visual pathway reflect that of the brain,4,5 and both acute and chronic demyelination of the visual system can be studied. Well-established functional, electrophysiologic, and structural measures are highly sensitive to changes along the visual pathway.3,4,6,7 These outcome measures are easily implemented in trials of remyelination, although it is still necessary to validate these measures as biomarkers. METHODS We review the pathophysiology of demyelination and reasons for remyelination failure in MS, including a targeted search of PubMed and Google Scholar. We then summarize key therapies under investigation in clinical trials and elaborate on the unique challenges encountered in the study of remyelinating agents. We end with a discussion of potential biomarkers of remyelination, focusing on the utility of established and emerging visual outcomes. RESULTS Address correspondence to Ari J. Green, MD, MCR, Department of Neurology, University of California San Francisco, 675 Nelson Rising Lane, #216A, San Francisco, CA 94158; E-mail: agreen@ucsf.edu Pathophysiology of Demyelination and Remyelination Failure in MS © 2024 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the North American Neuro-Opthalmology Society. This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4. 0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal. Oligodendrocyte precursor cells (OPCs) arise from neural stem cells lining the ventricles during development and from the subventricular zones during adulthood,8 migrating throughout the CNS in response to attraction and repulsion cues.1 Successful myelination of axons occurs Zuroff and Green: J Neuro-Ophthalmol 2024; 44: 143-156 143 Basic and Translational Research when OPCs differentiate into mature oligodendrocytes capable of producing myelin sheaths that concentrically wrap around axons. OPC recruitment and differentiation is regulated by signals from oligodendrocytes, immune cells, and extracellular matrix components.9,10 Myelin debris11,12 and the presence of intact axons13–19 can either inhibit or promote remyelination, respectively. In MS, there is heterogeneous remyelination capacity between individuals and lesion types.20–22 Remyelination is thought to decrease with age and disease duration,23,24 suggesting that lifelong exposure to inflammation may limit remyelination. MS demyelinating plaques evolve through different stages25,26 and exhibit varied reasons for remyelination failure, including impaired OPC recruitment and differentiation,27–29 reduced myelin sheath formation,30 and aberrant myeloid-mediated inflammation.30 Taken together, multiple mechanisms for failed remyelination may coexist within the same patient. These mechanisms also represent potential intervention targets (Fig. 1). Strategies for promoting remyelination have primarily focused on enhancing OPC differentiation.31–34 Modulation of myelin sheath formation has yet to be explored as a therapeutic strategy. Accumulating evidence highlights the inhibitory role of the proinflammatory milieu and repeated demyelinating events on remyelination.1,10,35 A multimodal approach to promoting repair and preventing degeneration in MS is critical: immune-modulating therapies can prevent relapses that limit remyelinating efforts, and additional therapies should target the CNScompartmentalized immune response that potentiates demyelination and axonal injury. In parallel, therapies targeting remyelination and repair are greatly needed. Identifying Potential Remyelinating Candidates A stepwise approach to developing proremyelinating agents is provided in Figure 2. Several in vitro assays allow for high throughput screening of candidate molecules by assessing OPC proliferation and differentiation.36–38 These approaches have identified similar candidates, including the antimuscarinic compounds benztropine37 and clemastine.38 Identified agents are then validated using animal models of demyelination. Toxin-induced demyelination models (e.g., cuprizone39 or lysolecithin40,41) can assess myelin dynamics but do not capture the inflammatory component characteristic of MS. Meanwhile, experimental autoimmune encephalomyelitis (EAE) models recapitulate some key features of inflammatory demyelination42 and can evaluate the effect of candidate therapies on disease severity and potential offtarget immunosuppressive effects. However, key aspects of neurodegeneration and disease progression, which are highly relevant to the study of remyelination and repair, are incompletely captured. Genetic models of demyelination can also allow us to disentangle whether the benefits of the candidate drug are due to remyelination or reduction of inflammatory injury.43,44 144 Current State of Remyelinating Therapies in Multiple Sclerosis We focus our discussion on 3 key compounds with robust clinical trial data. Table 1 includes a description of agents in phase II/III clinical trials with strong preclinical data supporting their remyelinating potential. Clemastine Clemastine fumarate, a first-generation antihistamine with additional antimuscarinic properties, has been available over the counter in the United States since 1992. It was identified as a proremyelinating candidate using micropillar arrays (BIMA) (Fig. 2)38 and exerts it effect through muscarinic receptor M1 antagonism in a cell-specific manner.38,44–46 The ReBUILD trial, a phase II, randomized, doubleblind, placebo-controlled trial, studied clemastine fumarate in relapsing MS patients with demyelinating optic neuropathy.31 It was the first trial to demonstrate efficacy of a remyelinating agent in chronic demyelinating injury. The study employed a crossover design, wherein study participants were randomized to receive clemastine for 90 days followed by placebo for 60 days or vice versa. The crossover design increased study power and enabled the assessment of carryover of treatment effect into the control period. Although the presence of carryover effects supports clemastine’s efficacy, it also presents a statistical challenge. Because the standard statistical approach for a crossover design assumes no carryover, it underestimates the true magnitude of the treatment effect. Hence, clemastine decreased P100 latency of whole-field visual evoked potentials (VEPs) by 1.7 msec/eye if analyzed as a crossover trial and 3.2 msec/ eye if analyzed as a delayed treatment trial. Similarly, lowcontrast letter acuity (LCLA) showed no significant increase using the crossover model but reached a prespecified threshold for significance using the delayed treatment model (1.6 letters per eye).31 Notably, a 6-msec improvement in VEP latency is considered clinically significant,47,48 and a post hoc analysis using a 6-msec improvement threshold showed that clemastine performed better than placebo.31 There are now 4 ongoing clinical trials of clemastine in MS (Table 1). Bexarotene Bexarotene is a nonselective retinoid X receptor g (RXRg) agonist approved for the treatment of cutaneous T-cell lymphoma. Signaling through RXRg was shown to promote oligodendrocyte maturation in vitro and in murine models of toxin-induced demyelination.49,50 In a phase IIa, doubleblind, placebo-controlled trial in relapsing MS, 52 patients stable on dimethyl fumarate were randomized to receive either bexarotene or placebo for 6 months.34 The primary efficacy endpoint—patient-level change in magnetization transfer ratio (MTR) within demyelinated lesions—was not met. However, treatment effects were observed in some prespecified exploratory analyses. Bexarotene significantly Zuroff and Green: J Neuro-Ophthalmol 2024; 44: 143-156 Basic and Translational Research FIG. 1. Process of remyelination following inflammatory demyelination in MS: potential intervention targets. Following inflammatory destruction of myelin that is characteristic of acute relapses in MS, successful remyelination is a multistep process. It requires 1) clearance of myelin debris by macrophages and microglia followed by 2) successful recruitment of oligodendrocyte precursor cells (OPCs) over a variable time frame. OPCs make initial contact with demyelinated axons, stimulating 3) the formation of the paranode with binding of axonal elements (Caspr and Contactin 1, Cntn1) with oligodendrocyte (OL) elements (neurofascin-155, Nf155). There is bidirectional input between axon and OL processes that stimulates further OL differentiation and myelin wrapping, culminating in 4) compact myelin sheath formation and 5) formation of the final nodal and paranodal architecture. This includes appropriate sequestration of voltage-gated sodium channels at the node to facilitate saltatory conduction. Finally, all of the aforementioned stages of remyelination are tightly regulated by secretory products released by glia and infiltrating macrophages. In the context of the chronic demyelinating conditions of the MS CNS, chronically activated microglia and astrocytes are more prone to release proinflammatory, negative regulators of remyelination. Each step in this pathway represents a potential intervention target for the promotion of remyelination. Asterisks denote the stage of development of potential disease-modifying therapies (DMTs) targeting each mechanism. The green asterisk indicates that available DMTs target step 1 in this pathway by preventing the inflammatory demyelination of relapses, although therapies that promote clearance of myelin debris have not been explored. The blue asterisk indicates that agents with the capacity to promote OPC differentiation are currently under study. Red asterisks denote those steps in the pathway that could be amenable to therapeutic intervention but have not yet been studied. Neurons/axons are shown in purple and OL lineage cells are shown in yellow. Created with BioRender.com. increased lesional MTR in gray matter and brainstem and decreased VEP latency in chronically demyelinated eyes.34 These findings were tempered by the fact that all patients receiving bexarotene had at least one adverse event. The study authors concluded that bexarotene was not safe in MS patients but that targeted RXRg agonists might be beneficial. Opicinumab Opicinumab (BIIB033) is an inhibitory monoclonal antibody against LINGO-1 that was tested in a robust clinical trial program that was ultimately unsuccessful.32,33,51 LINGO-1 is a cell surface receptor expressed on neurons and oligodendrocytes that is thought to negatively regulate OPC differentiation, myelination, and axonal regeneration.52–54 In both toxin54,55 and EAE models,54,56,57 inhibition of LINGO-1 promoted remyelination and functional Zuroff and Green: J Neuro-Ophthalmol 2024; 44: 143-156 recovery. However, there was limited replication of these observations, and the relevance of LINGO-1 in MS was only examined in one small postmortem study.58 In the double-blind, placebo-controlled RENEW trial,32 patients with a first episode of optic neuritis within 4 weeks of study enrolment were randomized to receive opicinumab or placebo over 6 months. The primary endpoint—change in full-field VEP latency compared with the unaffected eye —was not met in the intention-to-treat population. A perprotocol analysis revealed a trend for improvement at week 24 (7.6 msec, P = 0.050) and a statistically significant improvement at week 32 (9.1 msec, P = 0.011). A separate important observation was that most ganglion cell/inner plexiform layer (GCL/IPL) thinning occurred before study enrolment (i.e., within 4 weeks of optic neuritis onset). This was suggested as evidence of early neurodegeneration in optic neuritis and that neuroprotective strategies may need 145 Basic and Translational Research firmed disability improvement at 72 weeks using 2 novel, multicomponent, functional endpoints. Both trials failed to show a clinical benefit, and Biogen subsequently discontinued opicinumab’s clinical development. CHALLENGES IN THE STUDY OF REMYELINATING AGENTS: IMPORTANCE OF TRIAL DESIGN Defining the Study Population: Acute or Chronic Demyelination FIG. 2. Pipeline for screening of remyelinating agents. 1) Development of several screening strategies has allowed for more rapid identification of potential proremyelinating candidates. Two similar strategies use rodent pluripotent epiblast stem cell–derived OPCs36 and primary rat optic nerve–derived OPCs37 to screen a large number of bioactive compounds for their ability to stimulate OPC differentiation and myelin expression. Another in vitro approach, known as the binary indicant for myelination using micropillar arrays (BIMA), assesses the ability of OPCs and oligodendrocytes to wrap myelin around freestanding conical nanofibers or micropillars.38 Due to the conical structure of the micropillar, a single 2-dimensional image can evaluate both the extent and length of myelin wrapping and discriminate between OPC proliferation and maturation. 2) Identified agents are then validated using animal models of demyelination. Each model presents with unique advantages and disadvantages. Toxin-mediated models allow for the assessment of demyelination and spontaneous remyelination but do not have a primary inflammatory component. Experimental autoimmune encephalomyelitis (EAE) models include inflammatory demyelination and allow for the assessment of potential off-target immunosuppressive effects of the candidate compound but do not incorporate key features of neurodegeneration. 3) Compounds shown to promote remyelination and repair in vivo are then tested in clinical trials in humans. Created with BioRender.com. to be employed earlier to see clinical benefit. Although in the future it may be possible to administer a neuroprotective agent concurrently with corticosteroids, a shorter timeline for intervention poses a logistical barrier for study recruitment. Volumetric measurements do not fully represent underlying pathophysiology and alternative explanations for this finding, such as fluid shifts during acute inflammation, are possible. Two additional phase II trials were then undertaken in the context of chronic demyelination (SYNERGY33 and AFFINITY, NCT03222973). The primary endpoint in both trials was the percentage of patients achieving con146 A key question is when treatment with remyelinating therapies would be most beneficial: during acute inflammatory demyelination or when axons remain chronically demyelinated. Evidence from both histopathologic and imaging studies suggest that there is greater remyelinating potential soon after acute demyelination.30,59 Meanwhile, chronic inflammation, specifically with older age, prolonged disease duration, and within chronic active lesions, is thought to create a more hostile environment for remyelination.27–29 Acute optic neuritis is an attractive model to study effects of remyelinating candidates in acute demyelination. Advantages are that the contralateral, unaffected eye can serve as an internal control, and there are strong structure–function relationships in the visual system with well-established electrophysiologic, structural, and functional outcomes.4 However, not all patients with acute optic neuritis develop MS, and there is variability in expected recovery based on etiology.60 Alternative methods for studying acute demyelination include application of novel imaging sequences to assess remyelination within gadolinium-enhancing lesions.61,62 Multiple trials are underway that employ both models of acute demyelination (Table 1). Although chronically demyelinated lesions may be less amenable to remyelination in the “natural” disease state, promoting remyelination in this context may still be beneficial. Studies of chronic demyelination typically include MS patients on DMT without recent disease activity. Chronic demyelinating optic neuropathy is a frequently employed model and presents similar advantages to the acute model. Defining the appropriate model to study remyelination in other CNS regions is more challenging. Studies primarily rely on novel MRI sequences to assess remyelination either within existing demyelinated plaques34,63 or normal-appearing white matter (NAWM).64 The structure–function relationship of remyelination in varied brain regions is not well established and makes functional outcomes harder to define. Defining the Functional Outcome: Recovery or Prevention of Disability Accrual Another important question is whether remyelinating therapies should be expected to reverse existing deficits Zuroff and Green: J Neuro-Ophthalmol 2024; 44: 143-156 Basic and Translational Research TABLE 1. Summary of clinical trial data for key potential remyelinating candidates Drug Name Design Model Primary Outcome Measure Additional Visual Outcomes Key Findings Reference None Study ongoing NCT04002934 Change in P100 Bazedoxifene acetate Phase II, randomized, Chronic latency of full-field demyelination of (ReWRAP) placebo-controlled, VEP at 3 months the visual pathway double-blind, delayed-start trial in postmenopausal women with stable RRMS on DMT and electrophysiologic evidence of optic pathway demyelination 34 Primary efficacy Change in P100 Bexarotene Phase IIa, randomized, Chronic demyelination Change in mean endpoint not met, latency of full-field in brain lesions lesional MTR at 6 double-blind, and bexarotene VEP (exploratory) months placebo-controlled, was poorly parallel-group trial tolerated. in stable RRMS on dimethyl fumarate Withdrawn NCT04079088 BIIB061 Phase II, randomized, Chronic demyelination Disability improvement None at 48 weeks based double-blind, on overall response placebo-controlled, score, a composite parallel-group, functional metric, dose-ranging study including change in in relapsing MS on EDSS, T25W, and IFNb1 or glatiramer 9HPT acetate Change in low-contrast Primary endpoint met: 31 Clemastine (ReBUILD) Phase II, randomized, Chronic demyelination Change in P100 Clemastine letter VA latency of full-field of the visual double-blind, reduced latency (secondary) VEP at 3 months pathway placebo-controlled, delay by 1.7 ms/ Change in RNFL crossover trial in eye but did not thickness RRMS with chronic improve low(exploratory) demyelinating optic contrast letter VA neuropathy on DMT using ITT population Study ongoing NCT02521311 Change in RNFL Change in P100 Clemastine (ReCOVER) Phase II, randomized, Acute optic neuritis thickness latency of full-field double-blind, (secondary) VEP at 9 months placebo-controlled, Change in low-contrast parallel group trial letter VA at 9 in acute optic months neuritis Study ongoing NCT05338450 Change in other Clemastine (RESTORE) Phase III, randomized, Chronic demyelination Change in versional infrared of the brainstem dysconjugacy index double-blind, oculography (VDI) at 6 and 36 placebo-controlled measures months trial in stable MS (secondary) with INO receiving 6 Change in high- and months of low-contrast visual treatment followed acuity (secondary) by 30 months of Change in visual follow-up complaints (secondary) Clemastine (ReVIVE) Phase II randomized Chronic demyelination Change in corpus None Study ongoing NCT05359653 double-blinded, callosum MWF, T1 placebo-controlled, relaxation time, and delayed treatment UTE fraction at 3 and 6 months study in RRMS NCT05131828 Change in multifocal Study ongoing Clemastine + Phase IIa, randomized, Chronic demyelination Change in P100 VEP latency for eyes latency of full-field of the visual metformin double-blind, with delayed VEP at 26 weeks pathway placebo-controlled latency at baseline trial in stable RRMS (secondary) on DMT with Change in other VEP electrophysiologic measures evidence of optic (exploratory) pathway Change in color vision demyelination (exploratory) Change in RNFL thickness (exploratory) Zuroff and Green: J Neuro-Ophthalmol 2024; 44: 143-156 147 Basic and Translational Research (Continued ) Drug Name Domperidone Design Model Primary Outcome Measure Phase II, randomized, Chronic demyelination Worsening of the T25FW open-label, Simon performance by 2-stage, single-arm $20% at 12 futility trial in SPMS months Additional Visual Outcomes None Key Findings Reference Primary endpoint not 97 met. Patients experienced significant disability worsening consistent with expected levels in SPMS Completed, results NCT02493049 pending None Phase II, randomized, Acute demyelination in Change in texture brain lesions analysis, DTI, and open-label trial of MTI within Gd+ T1 domperidone as lesions at 16 and add-on therapy to 32 weeks DMT in RRMS vs no add-on therapy. RRMS patients must have at least one Gd+ lesion on MRI One primary endpoint 62 GSK239512 Phase II, randomized, Acute demyelination in Mean change in MTR None met: there was brain lesions in Gd+ lesions from double-blind, a small positive before to .3 placebo-controlled, effect of months after lesion parallel-arm trial in GSK239512 on formation RRMS on IFNb1a or change in MTR in Mean change in MTR glatiramer acetate Gd+ lesions, but no in delta-MTR lesions that accumulated significant effect in from before to .3 new Gd+ lesions or delta-MTR lesions. months after lesion other demyelinating formation lesions, defined as lesions with prespecified changes in MTR values Change in RGCL/IPL Primary endpoint not 32 Change in P100 Opicinumab (RENEW) Phase II, randomized, Acute optic neuritis met. Opicinumab and RNFL thickness latency in full-field double-blind, enhanced recovery (secondary) VEP at 24 weeks in placebo-controlled, of optic nerve Change in low-contrast ITT and PP parallel-arm trial in conduction latency letter VA (secondary) population patients with first at 32 weeks in PP episode of population only. unilateral acute optic neuritis Opicinumab Phase II, randomized, Chronic demyelination Proportion of None Primary endpoint not 33 (SYNERGY) double-blind, met. There was no participants with placebo-controlled, linear dose– confirmed disability parallel-arm, doseresponse in the improvement in 1+ ranging trial in probability of functional relapsing MS1 on confirmed disability measures at 72 improvement weeks, including IFNb-1a EDSS, T25W, 9HPT, and PASAT Opicinumab (AFFINITY) Phase II, randomized, Chronic demyelination Disability improvement None Terminated NCT03222973 double-blind, at 72 weeks based placebo-controlled, on overall response parallel-arm trial in score, a composite relapsing MS1 on functional metric including change in DMT EDSS, T25W, 9HPT Domperidone 9HPT, 9 hole peg test; DMT, disease-modifying therapy; DTI, diffusion tensor imaging; EDSS, Expanded Disability Status Scale; Gd+, gadolinium-enhancing; IFNb, interferon beta; INO, internuclear ophthalmoplegia; ITT, intention to treat; MTR, magnetization transfer ratio; MWF, myelin water fraction; PASAT, Paced Auditory Serial Addition Test; PP, per protocol; RGCL/IPL, retinal ganglion cell layer/inner plexiform layer; RNFL, retinal nerve fiber layer; RRMS, relapsing remitting multiple sclerosis; T25W, Timed 25-Foot Walk Test; UTE, ultrashort echo time; VA, visual acuity; VEP, visual evoked potentials. or prevent disability worsening. Compared with acute demyelination, where the goal is to improve recovery from the episode, differentiating between these 2 goals is critical in the context of chronic demyelination. MS 148 disability is thought to be driven by neuroaxonal damage and subsequent neurodegeneration.25,26,65 Because chronically demyelinated axons are more susceptible to injury, remyelination may prevent neuroaxonal loss and Zuroff and Green: J Neuro-Ophthalmol 2024; 44: 143-156 Basic and Translational Research protect against subsequent decline.1 Prevention of disability accrual thus represents a logical target for remyelinating therapies, although not without logistical challenges. In the era of high-efficacy DMTs, many RRMS patients do not experience significant disability worsening over years.66,67 This makes it exceedingly difficult to demonstrate an effect on disease progression over the short time frame of a phase II clinical trial. For this reason, many trials instead assess improvement in functional outcomes. The physiologic relevance of remyelination to disability improvement is less well established, and appropriate functional outcomes are not well defined. Efforts should be made to determine the most clinically relevant functional measure for the study population. For instance, in studies evaluating the visual system, well-established functional outcomes such as visual acuity and visual qualityof-life (QoL) metrics may improve our ability to detect meaningful changes.4 Outside of the visual system, demonstrating improvement on global metrics of cognitive or physical function (e.g., Expanded Disability Status Scale, EDSS), would represent a huge breakthrough, but it may be unrealistic over a short study period. The potentially inappropriate expectation of functional improvement runs the risk of underestimating an agent’s possible clinical benefit. Identifying and Validating Biomarkers for Remyelination The varied natural history of MS disease progression combined with the short time frame of phase II clinical trials necessitates the development of biomarkers that can serve as surrogate endpoints. In 2008, an international consensus meeting on “Imaging Outcomes for Protection and Repair in Multiple Sclerosis” suggested 5 categories of performance by which imaging biomarkers could be assessed for use in remyelination and repair trials.61 We propose that these criteria can be broadened to assess all biomarkers studied for this indication (Box 1). We use these adapted criteria as a framework to assess the validation status of more common and emerging biomarkers of remyelination (Table 2). BIOMARKERS OF REMYELINATION Neuroimaging Most conventional MRI sequences lack the necessary sensitivity to detect changes in myelin content. To address this limitation, numerous quantitative MRI techniques have been developed with varying sensitivity and specificity for myelin (reviewed in Refs. 68–70). In Table 2, we summarize the validation status of several key approaches —magnetization transfer imaging,71,72 myelin water imaging,73,74 and ultrashort echo time MRI.75,76 Positron emission tomography (PET) imaging is another promising Zuroff and Green: J Neuro-Ophthalmol 2024; 44: 143-156 method for direct myelin visualization. Several myelinbinding PET tracers have been repurposed from the Alzheimer disease space, including 11C-Pittsburgh compound B (PiB),77 18F-Florbetapir,78,79 and 18FFlorbetaben.80 PiB has been most extensively studied. These imaging techniques have focused almost exclusively on brain lesions. MRI imaging of optic nerve lesions may complement existing measures of optic nerve de/ remyelination, described below. Double inversion recovery has emerged as a more sensitive technique for detecting acute optic neuritis compared with FLAIR81—which may also be less specific for inflammatory injury82—but none of these methods resolve inflammation, astrogliosis from myelin injury. Visual Outcomes Visual Evoked Potentials VEPs measure the electrical potentials generated in the occipital cortex in response to a visual stimulus. P100 latency is the typical outcome of interest and is thought to represent the degree of myelination. Multiple studies in animal models support this assertion.83–85 We recently demonstrated that VEP latency corresponds to measures of nodal structure and extent of myelinated axons in both inflammatory and chemical models of demyelination.85 VEP latency improved following treatment with clemastine in cuprizone-fed mice, an effect that was dependent on the ability of OPCs to form new myelin.85 This study supports the use of VEP latency as a preclinical biomarker for the validation of putative remyelinating agents. When applying the proposed biomarker criteria (Box 1), VEPs are the most robustly validated (Table 2) but do not necessarily translate to improved visual function or QoL. Notably, full-field rather than multifocal VEPs have been more widely adopted in clinical trials. Optical Coherence Tomography OCT uses near-infrared light to create detailed cross-sectional retinal images. Semiautomated segmentation allows for the quantitative assessment of discrete neuronal and axonal layers with high interrater and intrarater reliability.86,87 The GCL/ IPL and peripapillary retinal nerve fiber layer (pRNFL) have been most extensively studied in MS.4,6,88 Thinning of the pRNFL and GCL/IPL is thought to reflect axonal injury and neurodegeneration, respectively,88 and do not directly detect changes in myelin. Therefore, we cannot assume that treatment-related effects on OCT measurements provide proof of remyelinating capacity but rather may capture a downstream neuroprotective benefit or other off-target effect. Functional Visual Outcomes LCLA, assessed with the low-contrast Sloan letter chart, has greater sensitivity than high-contrast VA for detecting 149 Basic and Translational Research TABLE 2. Validation status of potential neuroimaging and visual system biomarkers of remyelination Method Neuroimaging biomarkers MTR MWF UTE 150 Pathological Specificity Reproducibility Sensitivity to Change Clinical Relevance Response to Treatment MTR measurements of Changes in lesional MTR Differences in lesional Bexarotene treatment MTR decreased with brain and cervical can be followed and whole-brain MTR increased MTR in GM demyelination and spinal cord were longitudinally, values correlated with lesions, with lower increased with reproducible in healthy including with new lesion type, disease treatment effects near remyelination in MS adults104 lesion formation and phenotype, and the CSF spaces63,* plaques in autopsy recurrent disease severity71,107 GSK239512 treatment tissue71,72,98,99 Systematic review of demyelination35,59,106 Lesional MTR values only increased MTR in GdMTR correlated with reproducibility of qMRI enhancing lesions of myelin content and modestly correlated techniques RRMS patients 3 axonal loss in spinal with EDSS108 demonstrated only fair months after lesion cords of MS test–retest formation62,* patients100 reproducibility of MTR decreased following MTR105 demyelination with lysolecithin but failed to increase with subsequent remyelination101 Confounding MTR can be influenced by axonal density, inflammation, extracellular tissue components, and local water content71,98,102,103 MWF correlated with myelin content in demyelinated and remyelinated lesions and in NAWM in human autopsy tissue99,109,110 MWF varied between lesions, NAWM, and healthy control WM in vivo74,111 MWF varied with de/ remyelination in lysolecithin model101 MWF measurements were reproducible in healthy adults116,117 Confounding MWF registered myelin debris112,113 and changes in total water signal114 The orientation of WM tracts relative to main magnetic field influence MWF115 UTE signal correlated — with demyelination within lesions in ex vivo MS brain tissue75,76,123 UTE distinguished MS lesions, NAWM, and healthy control WM75,124 in vivo UTE correlated with demyelination in the cuprizone model125,126 MWF in total brain, Differences in myelin Clemastine treatment in lesions, and cervical heterogeneity index in the ReBUILD trial cord have been shown NAWM of MS patients increased MWF in the to change over time in was associated with corpus callosum of MS patients118–121 cognitive MS patients64 performance122 Decreased MWF in specific brain regions of PPMS patients was associated with worse performance on outcomes relevant to those regions’ function116 — UTE signal in the NAWM — of MS patients declined with age and associated with degree of disability127 Zuroff and Green: J Neuro-Ophthalmol 2024; 44: 143-156 Basic and Translational Research (Continued ) Method PiB PET Pathological Specificity Reproducibility Sensitivity to Change Clinical Relevance Response to Treatment Increased PiB uptake in — PiB differentially bound PiB signal in healthy adult Changes in PiB uptake WM demonstrated within lesions can be demyelinated lesions demyelinated and excellent measured over over time (presumed remyelinated sections reproducibility in time128,129 remyelination) was of postmortem MS a test–retest study132 inversely associated tissue77 Variations in PiB binding with disability128 differentiated MS Reduced PiB uptake in lesions and NAWM lesions and NAWM in vivo128,129 correlated with decreased visuospatial PiB correlated with performance in MS45 varying levels of myelin content in animal models of demyelination77,130 Confounding Not specific for myelin; PiB binds other compounds like amyloid beta131 Visual system biomarkers VEPs OCT LCLA mfVEP latency133 and full- VEPs are reproducible field VEP latency134 across sites135 correlate with extent of optic nerve lesions VEP latency correlates with nodal structure and myelination in MOG-EAE and chemical models of demyelination85 VEPs are sensitive to Prolonged full-field VEP Clemastine reduced fulllongitudinal change in latency predicts field VEP latency in MS patients85,135 subsequent disability chronically 136 progression demyelinated eyes31 and neuroaxonal loss137 Bexarotene reduced fullfield VEP latency in all Change in full-field VEP eyes in the per-protocol latency correlates with plasma NfL levels in analysis but not in the the ReBUILD trial138 intention to treat population34,* Opicinumab improved recovery of optic nerve conduction latency in the per-protocol analysis but not in the intention to treat population32,* Confounding High inter- and intrarater Changes in pRNFL and Changes in pRNFL and — OCTs provide reliability of GCL/IPL can be readily GCL/IPL are volumetric quantitative structural detected following associated with measurements that measures86,87 acute attacks of optic changes in visual reflect neuroaxonal neuritis139–141 and acuity and global and with subclinical loss. It is not a direct regional measures of injury142,143 measure of myelin and brain atrophy143–149 is inherently not specific† LCLA correlates with Clemastine increased Confounding LCLA has good interrater LCLA demonstrated changes over time in brain lesion volume LCLA in the delayed LCLA is not specific to reliability90 myelination of the response to along the optic treatment model but visual pathway† immunomodulatory pathway,150 validated not in the crossover measures of global therapies7,91 model31 disability,151,152 and real-world functional disability153 *Clinical trials that did not meet their primary endpoint. The significance of positive treatment effects on secondary and exploratory endpoints should be interpreted with caution, as it is not known whether the study drug exerts a proremyelinating effect. † Biomarkers for which pathological specificity for myelination status is not possible due to characteristics of the test. The findings supporting other validation criteria should be interpreted within this context. Gd, gadolinium; GCL/IPL, ganglion cell layer/inner plexiform layer; LCLA, low-contrast letter visual acuity; mfVEP, multifocal VEP; MTR, magnetization transfer ratio; MWF, myelin water fraction; NfL, neurofilament light chain; OCT, optical coherence tomography; pRNFL, peripapillary retinal nerve fiber layer; PiB PET, [11C]Pittsburgh compound B positron emission tomography; UTE, ultrashort echo time; VEP, visual evoked potentials; WM, white matter. meaningful vision changes in MS89 and has reported excellent interrater reliability.90 The finding that LCLA was improved following treatment with immunomodulatory Zuroff and Green: J Neuro-Ophthalmol 2024; 44: 143-156 therapies7,91 raises the concern that change in LCLA may not reflect remyelination but instead capture off-target antiinflammatory effects. Improvements in LCLA can support 151 Basic and Translational Research BOX 1. Adapted Remyelination61 Criteria for Biomarkers of • Pathological specificity: does the biomarker have a clear pathologic correlate, wherein changes in measurement are specific to change in myelin and not other pathologies? • Reproducibility: is the technique of biomarker acquisition precise and reproducible within and across centers over time? • Sensitivity to change: does the biomarker detect changes in myelination in vivo that can be measured longitudinally? • Clinical relevance: is the biomarker associated with clinical outcomes that could be used to measure neuroprotection and repair, such as progression of disability or reversal of clinical impairment? • Response to treatment: is the biomarker responsive to therapeutic intervention and, thus, potentially predictive of a clinical outcome? the clinical relevance of putative remyelinating agents, but concordance with electrophysiologic data or other biomarkers with greater pathologic specificity will be needed. Additional important functional visual outcomes include visual field assessment and visual QoL metrics.92 The Efferent Visual System: Emerging Biomarkers Most patients with MS experience some form of efferent visual dysfunction.3 Several quantitative techniques have been developed to detect subtle visuomotor abnormalities. One study employed a custom-built retinal eye tracker to quantify features of fixational microsaccades.93 This technique discriminated MS patients from healthy controls, and number of microsaccades correlated with measures of disability. Infrared video oculography is another noninvasive method for quantifying aspects of saccadic eye movements.94,95 This method detected subtle findings of an internuclear ophthalmoplegia (INO) in 34% of patients studied based on differences in movements between the abducting and adducting eye (the versional dyconjugacy index, VDI).96 Change in VDI is currently the primary endpoint in a phase III trial of clemastine in patients with chronic INO (NCT05338450). CONCLUSIONS Initial success in the study of remyelinating therapies in MS suggest that neuroprotection and repair may be achievable. As more potential therapies are identified, we must ensure that candidates are validated in preclinical models, and clinical trials are properly designed to best assess efficacy in the 152 particular patient population. This requires rigorous validation of biomarkers of remyelination for use in clinical trials. Key advantages of using visual assessments in remyelination trials include their low-cost, sensitivity, and accessibility. Well-established functional, electrophysiologic, and structural measures allow for multimodal assessment of the visual pathway. Although these measures may have varying specificity for remyelination, a combination of techniques applied in either acute or chronic demyelination may increase our understanding of the interplay between inflammation, remyelination, and neurodegeneration in MS. Although we have emphasized the visual system as an important model, we acknowledge that remyelination must be assessed in other disease-relevant regions and for their effect on other measures of disability. The outcomes of multiple ongoing clinical trials are highly anticipated and represent a potentially pivotal moment for the field of MS. STATEMENT OF AUTHORSHIP Conception and design: L. Zuroff, A. J. Green; Acquisition of data: L. Zuroff, A. J. Green; Analysis and interpretation of data: L. Zuroff, A. J. Green. Drafting the manuscript: L. Zuroff, A. J. Green; Revising the manuscript for intellectual content: L. Zuroff, A. J. Green. Final approval of the completed manuscript: L. Zuroff, A. J. Green. REFERENCES 1. Lubetzki C, Zalc B, Williams A, Stadelmann C, Stankoff B. Remyelination in multiple sclerosis: from basic science to clinical translation. Lancet Neurol. 2020;19:678–688. 2. Plemel JR, Liu W-Q, Yong VW. Remyelination therapies: a new direction and challenge in multiple sclerosis. Nat Rev Drug Discov. 2017;16:617–634. 3. Graves J, Balcer LJ. Eye disorders in patients with multiple sclerosis: natural history and management. Clin Ophthalmol. 2010;4:1409–1422. 4. Graves JS, Oertel FC, Van der Walt A, et al. IMSVISUAL. Leveraging visual outcome measures to advance therapy development in neuroimmunologic disorders. Neurol Neuroimmunol Neuroinflamm. 2022;9:e1126. 5. Mey GM, DeSilva TM. Utility of the visual system to monitor neurodegeneration in multiple sclerosis. Front Mol Neurosci. 2023;16:1125115. 6. Balcer LJ, Miller DH, Reingold SC, Cohen JA. Vision and vision-related outcome measures in multiple sclerosis. Brain. 2015;138:11–27. 7. Nolan RC, Akhand O, Rizzo J-R, Galetta SL, Balcer LJ. Evolution of visual outcomes in clinical trials for multiple sclerosis disease-modifying therapies. J Neuroophthalmol. 2018;38:202–209. 8. Xing YL, Röth PT, Stratton JAS, et al. Adult neural precursor cells from the subventricular zone contribute significantly to oligodendrocyte regeneration and remyelination. J Neurosci. 2014;34:14128–14146. 9. Bove RM, Green AJ. Remyelinating pharmacotherapies in multiple sclerosis. Neurotherapeutics. 2017;14:894–904. 10. Klotz L, Antel J, Kuhlmann T. Inflammation in multiple sclerosis: consequences for remyelination and disease progression. Nat Rev Neurol. 2023;19:305–320. 11. Kotter MR, Li W-W, Zhao C, Franklin RJM. Myelin impairs CNS remyelination by inhibiting oligodendrocyte precursor cell differentiation. J Neurosci. 2006;26:328–332. Zuroff and Green: J Neuro-Ophthalmol 2024; 44: 143-156 Basic and Translational Research 12. Plemel JR, Manesh SB, Sparling JS, Tetzlaff W. Myelin inhibits oligodendroglial maturation and regulates oligodendrocytic transcription factor expression. Glia. 2013;61:1471–1487. 13. Coman I, Aigrot MS, Seilhean D, et al. Nodal, paranodal and juxtaparanodal axonal proteins during demyelination and remyelination in multiple sclerosis. Brain. 2006;129:3186– 3195. 14. Charles P, Reynolds R, Seilhean D, et al. Re‐expression of PSA‐NCAM by demyelinated axons: an inhibitor of remyelination in multiple sclerosis? Brain. 2002;125:1972– 1979. 15. Barres BA, Raff MC. Proliferation of oligodendrocyte precursor cells depends on electrical activity in axons. Nature. 1993;361:258–260. 16. Gibson EM, Purger D, Mount CW, et al. Neuronal activity promotes oligodendrogenesis and adaptive myelination in the mammalian brain. Science. 2014;344:1252304. 17. Ortiz FC, Habermacher C, Graciarena M, et al. Neuronal activity in vivo enhances functional myelin repair. Jci Insight. 2019;5:e123434. 18. Wake H, Ortiz FC, Woo DH, Lee PR, Angulo MC, Fields RD. Nonsynaptic junctions on myelinating glia promote preferential myelination of electrically active axons. Nat Commun. 2015;6:7844. 19. Demerens C, Stankoff B, Logak M, et al. Induction of myelination in the central nervous system by electrical activity. Proc Natl Acad Sci USA. 1996;93:9887–9892. 20. Patrikios P, Stadelmann C, Kutzelnigg A, et al. Remyelination is extensive in a subset of multiple sclerosis patients. Brain. 2006;129:3165–3172. 21. Bramow S, Frischer JM, Lassmann H, et al. Demyelination versus remyelination in progressive multiple sclerosis. Brain. 2010;133:2983–2998. 22. Prineas JW, Barnard RO, Kwon EE, Sharer LR, Cho ES. Multiple sclerosis: remyelination of nascent lesions. Ann Neurol. 1993;33:137–151. 23. Frischer JM, Weigand SD, Guo Y, et al. Clinical and pathological insights into the dynamic nature of the white matter multiple sclerosis plaque. Ann Neurol. 2015;78:710– 721. 24. Goldschmidt T, Antel J, König FB, Brück W, Kuhlmann T. Remyelination capacity of the MS brain decreases with disease chronicity. Neurology. 2009;72:1914–1921. 25. Lassmann H. Multiple sclerosis pathology. Cold Spring Harbor Perspect Med. 2018;8:a028936. 26. Lassmann H, van Horssen J, Mahad D. Progressive multiple sclerosis: pathology and pathogenesis. Nat Rev Neurol. 2012;8:647–656. 27. Kuhlmann T, Miron V, Cui Q, Wegner C, Antel J, Brück W. Differentiation block of oligodendroglial progenitor cells as a cause for remyelination failure in chronic multiple sclerosis. Brain. 2008;131:1749–1758. 28. Boyd A, Zhang H, Williams A. Insufficient OPC migration into demyelinated lesions is a cause of poor remyelination in MS and mouse models. Acta Neuropathol. 2013;125:841–859. 29. Wolswijk G. Oligodendrocyte survival, loss and birth in lesions of chronic-stage multiple sclerosis. Brain. 2000;123(Pt 1):105–115. 30. Heß K, Starost L, Kieran NW, et al. Lesion stage-dependent causes for impaired remyelination in MS. Acta Neuropathol. 2020;140:359–375. 31. Green AJ, Gelfand JM, Cree BA, et al. Clemastine fumarate as a remyelinating therapy for multiple sclerosis (ReBUILD): a randomised, controlled, double-blind, crossover trial. Lancet. 2017;390:2481–2489. 32. Cadavid D, Balcer L, Galetta S, et al. RENEW Study Investigators. Safety and efficacy of opicinumab in acute optic neuritis (RENEW): a randomised, placebo-controlled, phase 2 trial. Lancet Neurol. 2017;16:189–199. 33. Cadavid D, Mellion M, Hupperts R, et al. SYNERGY study investigators. Safety and efficacy of opicinumab in patients with relapsing multiple sclerosis (SYNERGY): a randomised, Zuroff and Green: J Neuro-Ophthalmol 2024; 44: 143-156 placebo-controlled, phase 2 trial. Lancet Neurol. 2019;18:845–856. 34. Brown JWL, Cunniffe NG, Prados F, et al. Safety and efficacy of bexarotene in patients with relapsing-remitting multiple sclerosis (CCMR One): a randomised, double-blind, placebocontrolled, parallel-group, phase 2a study. Lancet Neurol. 2021;20:709–720. 35. Brown RA, Narayanan S, Arnold DL. Imaging of repeated episodes of demyelination and remyelination in multiple sclerosis. Neuroimage Clin. 2014;6:20–25. 36. Najm FJ, Madhavan M, Zaremba A, et al. Drug-based modulation of endogenous stem cells promotes functional remyelination in vivo. Nature. 2015;522:216–220. 37. Deshmukh VA, Tardif V, Lyssiotis CA, et al. A regenerative approach to the treatment of multiple sclerosis. Nature. 2013;502:327–332. 38. Mei F, Fancy SPJ, Shen Y-AA, et al. Micropillar arrays as a high-throughput screening platform for therapeutics in multiple sclerosis. Nat Med. 2014;20:954–960. 39. Leo H, Kipp M. Remyelination in multiple sclerosis: findings in the cuprizone model. Int J Mol Sci. 2022;23:16093. 40. Hall SM. The effect of injections of lysophosphatidyl choline into white matter of the adult mouse spinal cord. J Cell Sci. 1972;10:535–546. 41. Woodruff RH, Franklin RJM. Demyelination and remyelination of the caudal cerebellar peduncle of adult rats following stereotaxic injections of lysolecithin, ethidium bromide, and complement/anti‐galactocerebroside: a comparative study. Glia. 1999;25:216–228. 42. Lassmann H, Bradl M. Multiple sclerosis: experimental models and reality. Acta Neuropathol. 2017;133:223–244. 43. Duncan GJ, Ingram SD, Emberley K, et al. Remyelination protects neurons from DLK-mediated neurodegeneration. bioRxiv [Preprint]. 2023:2023.09.30.560267. 44. Mei F, Lehmann-Horn K, Shen Y-AA, et al. Accelerated remyelination during inflammatory demyelination prevents axonal loss and improves functional recovery. Elife. 2016;5:e18246. 45. Li Z, He Y, Fan S, Sun B. Clemastine rescues behavioral changes and enhances remyelination in the cuprizone mouse model of demyelination. Neurosci Bull. 2015;31:617–625. 46. Liu J, Dupree JL, Gacias M, et al. Clemastine enhances myelination in the prefrontal cortex and rescues behavioral changes in socially isolated mice. J Neurosci. 2016;36:957– 962. 47. Niklas A, Sebraoui H, Hess E, Wagner A, Then Bergh F. Outcome measures for trials of remyelinating agents in multiple sclerosis: retrospective longitudinal analysis of visual evoked potential latency. Mult Scler. 2009;15:68–74. 48. Walsh JC, Garrick R, Cameron J, McLeod JG. Evoked potential changes in clinically definite multiple sclerosis: a two year follow up study. J Neurol Neurosurg Psychiatry. 1982;45:494–500. 49. de la Fuente AG, Errea O, van Wijngaarden P, et al. Vitamin D receptor–retinoid X receptor heterodimer signaling regulates oligodendrocyte progenitor cell differentiation. J Cell Biol. 2015;211:975–985. 50. Huang JK, Jarjour AA, Nait Oumesmar B, et al. Retinoid X receptor gamma signaling accelerates CNS remyelination. Nat Neurosci. 2011;14:45–53. 51. Cadavid D, Balcer L, Galetta S, et al. RENEW Study Investigators. Predictors of response to opicinumab in acute optic neuritis. Ann Clin Translat Neurol. 2018;5:1154–1162. 52. Mi S, Lee X, Shao Z, et al. LINGO-1 is a component of the Nogo-66 receptor/p75 signaling complex. Nat Neurosci. 2004;7:221–228. 53. Mi S, Miller RH, Lee X, et al. LINGO-1 negatively regulates myelination by oligodendrocytes. Nat Neurosci. 2005;8:745– 751. 54. Mi S, Miller RH, Tang W, et al. Promotion of central nervous system remyelination by induced differentiation of oligodendrocyte precursor cells. Ann Neurol. 2009;65:304– 315. 153 Basic and Translational Research 55. Zhang Y, Zhang YP, Pepinsky B, et al. Inhibition of LINGO-1 promotes functional recovery after experimental spinal cord demyelination. Exp Neurol. 2015;266:68–73. 56. Mi S, Hu B, Hahm K, et al. LINGO-1 antagonist promotes spinal cord remyelination and axonal integrity in MOG-induced experimental autoimmune encephalomyelitis. Nat Med. 2007;13:1228–1233. 57. Sun J-J, Ren Q-G, Xu L, Zhang Z-J. LINGO-1 antibody ameliorates myelin impairment and spatial memory deficits in experimental autoimmune encephalomyelitis mice. Scientific Rep. 2015;5:14235. 58. Satoh J, Tabunoki H, Yamamura T, Arima K, Konno H. TROY and LINGO‐1 expression in astrocytes and macrophages/ microglia in multiple sclerosis lesions. Neuropathol Appl Neurobiol. 2007;33:99–107. 59. Chen JT, Collins DL, Atkins HL, Freedman MS, Arnold DL, Canadian MS/BMT Study Group. Magnetization transfer ratio evolution with demyelination and remyelination in multiple sclerosis lesions. Ann Neurol. 2008;63:254–262. 60. Sotirchos ES, Filippatou A, Fitzgerald KC, et al. Aquaporin-4 IgG seropositivity is associated with worse visual outcomes after optic neuritis than MOG-IgG seropositivity and multiple sclerosis, independent of macular ganglion cell layer thinning. Mult Scler. 2020;26:1360–1371. 61. Barkhof F, Calabresi PA, Miller DH, Reingold SC. Imaging outcomes for neuroprotection and repair in multiple sclerosis trials. Nat Rev Neurol. 2009;5:256–266. 62. Schwartzbach CJ, Grove RA, Brown R, Tompson D, Then Bergh F, Arnold DL. Lesion remyelinating activity of GSK239512 versus placebo in patients with relapsingremitting multiple sclerosis: a randomised, single-blind, phase II study. J Neurol. 2017;264:304–315. 63. Brown JWL, Prados F, Altmann DR, et al. Remyelination varies between and within lesions in multiple sclerosis following bexarotene. Ann Clin Translat Neurol. 2022;9:1626–1642. 64. Caverzasi E, Papinutto N, Cordano C, et al. MWF of the corpus callosum is a robust measure of remyelination: results from the ReBUILD trial. Proc Natl Acad Sci USA. 2023;120:e2217635120. 65. Reynolds R, Roncaroli F, Nicholas R, Radotra B, Gveric D, Howell O. The neuropathological basis of clinical progression in multiple sclerosis. Acta Neuropathol. 2011;122:155–170. 66. University of California San Francisco MS-EPIC Team, Cree BAC, Gourraud PA, Oksenberg JR, et al. Long‐term evolution of multiple sclerosis disability in the treatment era. Ann Neurol. 2016;80:499–510. 67. Lublin FD, Häring DA, Ganjgahi H, et al. How patients with multiple sclerosis acquire disability. Brain. 2022;145:3147– 3161. 68. Mallik S, Samson RS, Wheeler-Kingshott CAM, Miller DH. Imaging outcomes for trials of remyelination in multiple sclerosis. J Neurol Neurosurg Psychiatry. 2014;85:1396– 1404. 69. van der Weijden CWJ, Biondetti E, Gutmann IW, et al. Quantitative myelin imaging with MRI and PET: an overview of techniques and their validation status. Brain. 2023;146:1243–1266. 70. Bodini B, Tonietto M, Airas L, Stankoff B. Positron emission tomography in multiple sclerosis—straight to the target. Nat Rev Neurol. 2021;17:663–675. 71. Schmierer K, Scaravilli F, Altmann DR, Barker GJ, Miller DH. Magnetization transfer ratio and myelin in postmortem multiple sclerosis brain. Ann Neurol. 2004;56:407–415. 72. Barkhof F, Bruck W, De Groot CJ, et al. Remyelinated lesions in multiple sclerosis: magnetic resonance image appearance. Arch Neurol. 2003;60:1073–1081. 73. Laule C, Moore GRW. Myelin water imaging to detect demyelination and remyelination and its validation in pathology. Brain Pathol. 2018;28:750–764. 74. Laule C, Vavasour IM, Moore GR, et al. Water content and myelin water fraction in multiple sclerosis. A T2 relaxation study. J Neurol. 2004;251:284–293. 154 75. Ma Y-J, Jang H, Wei Z, et al. Myelin imaging in human brain using a short repetition time adiabatic inversion recovery prepared ultrashort echo time (STAIR-UTE) MRI sequence in multiple sclerosis. Radiology. 2020;297:392–404. 76. Sheth V, Shao H, Chen J, et al. Magnetic resonance imaging of myelin using ultrashort Echo time (UTE) pulse sequences: phantom, specimen, volunteer and multiple sclerosis patient studies. Neuroimage. 2016;136:37–44. 77. Stankoff B, Freeman L, Aigrot MS, et al. Imaging central nervous system myelin by positron emission tomography in multiple sclerosis using [methyl-¹¹C]-2-(4’-methylaminophenyl)6-hydroxybenzothiazole. Ann Neurol. 2011;69:673–680. 78. Zhang M, Ni Y, Zhou Q, et al. 18F-florbetapir PET/MRI for quantitatively monitoring myelin loss and recovery in patients with multiple sclerosis: a longitudinal study. Eclinicalmedicine. 2021;37:100982. 79. Carotenuto A, Giordano B, Dervenoulas G, et al. [18F] Florbetapir PET/MR imaging to assess demyelination in multiple sclerosis. Eur J Nucl Med Mol Imaging. 2020;47:366–378. 80. Auvity S, Tonietto M, Caillé F, et al. Repurposing radiotracers for myelin imaging: a study comparing 18F-florbetaben, 18Fflorbetapir, 18F-flutemetamol,11C-MeDAS, and 11C-PiB. Eur J Nucl Med Mol Imaging. 2020;47:490–501. 81. Murumkar V, Priyadarshini Baishya P, Kulanthaivelu K, Saini J, Manjunath N, Kumar Gupta R. Comparison of 3D double inversion recovery (DIR) versus 3D fluid attenuated inversion recovery (FLAIR) in precise diagnosis of acute optic neuritis. Eur J Radiol. 2022;155:110505. 82. Labella Álvarez F, Mosleh R, Bouthour W, et al. Optic nerve MRI T2-hyperintensity: a nonspecific marker of optic nerve damage. J Neuroophthalmol. 2024;44:22–29. 83. You Y, Klistorner A, Thie J, Graham SL. Latency delay of visual evoked potential is a real measurement of demyelination in a rat model of optic neuritis. Invest Ophthalmol Vis Sci. 2011;52:6911–6918. 84. Heidari M, Radcliff AB, McLellan GJ, et al. Evoked potentials as a biomarker of remyelination. Proc Natl Acad Sci USA. 2019;116:27074–27083. 85. Cordano C, Sin JH, Timmons G, et al. Validating visual evoked potentials as a preclinical, quantitative biomarker for remyelination efficacy. Brain. 2022;145:3943–3952. 86. Syc SB, Warner CV, Hiremath GS, et al. Reproducibility of high-resolution optical coherence tomography in multiple sclerosis. Mult Scler. 2010;16:829–839. 87. Cettomai D, Pulicken M, Gordon-Lipkin E, et al. Reproducibility of optical coherence tomography in multiple sclerosis. Arch Neurol. 2008;65:1218–1222. 88. Alonso R, Gonzalez-Moron D, Garcea O. Optical coherence tomography as a biomarker of neurodegeneration in multiple sclerosis: a review. Mult Scler Relat Disord. 2018;22:77–82. 89. Balcer LJ, Raynowska J, Nolan R, et al. Multiple Sclerosis Outcome Assessments Consortium. Validity of low-contrast letter acuity as a visual performance outcome measure for multiple sclerosis. Mult Scler. 2017;23:734–747. 90. Balcer LJ, Baier ML, Pelak VS, et al. New low-contrast vision charts: reliability and test characteristics in patients with multiple sclerosis. Mult Scler. 2000;6:163–171. 91. Balcer LJ, Galetta SL, Polman CH, et al. Low-contrast acuity measures visual improvement in phase 3 trial of natalizumab in relapsing MS. J Neurol Sci. 2012;318:119–124. 92. Mangione CM, Lee PP, Gutierrez PR, Spritzer K, Berry S, Hays RD, National Eye Institute Visual Function Questionnaire Field Test Investigators. Development of the 25-item national eye institute visual function questionnaire. Arch Ophthalmol. 2001;119:1050–1058. 93. Sheehy CK, Bensinger ES, Romeo A, et al. Fixational microsaccades: a quantitative and objective measure of disability in multiple sclerosis. Mult Scler. 2020;26:343– 353. 94. Nij Bijvank JA, Petzold A, Balk LJ, et al. A standardized protocol for quantification of saccadic eye movements: DEMoNS. PLoS One. 2018;13:e0200695. Zuroff and Green: J Neuro-Ophthalmol 2024; 44: 143-156 Basic and Translational Research 95. Nij Bijvank JA, Petzold A, Coric D, et al. Saccadic delay in multiple sclerosis: a quantitative description. Vis Res. 2020;168:33–41. 96. Nij Bijvank JA, van Rijn LJ, Balk LJ, Tan HS, Uitdehaag BMJ, Petzold A. Diagnosing and quantifying a common deficit in multiple sclerosis: internuclear ophthalmoplegia. Neurology. 2019;92:e2299–e2308. 97. Koch MW, Sage K, Kaur S, et al. Repurposing domperidone in secondary progressive multiple sclerosis: a simon 2-stage phase 2 futility trial. Neurology. 2021;96:e2313–e2322. 98. Wiggermann V, Endmayr V, Hernández‐Torres E, et al. Quantitative magnetic resonance imaging reflects different levels of histologically determined myelin densities in multiple sclerosis, including remyelination in inactive multiple sclerosis lesions. Brain Pathol. 2023;33:e13150. 99. Galbusera R, Bahn E, Weigel M, et al. Postmortem quantitative MRI disentangles histological lesion types in multiple sclerosis. Brain Pathol. 2023;33:e13136. 100. Mottershead JP, Schmierer K, Clemence M, et al. High field MRI correlates of myelin content and axonal density in multiple sclerosis—a post-mortem study of the spinal cord. J Neurol. 2003;250:1293–1301. 101. McCreary CR, Bjarnason TA, Skihar V, Mitchell JR, Yong VW, Dunn JF. Multiexponential T2 and magnetization transfer MRI of demyelination and remyelination in murine spinal cord. Neuroimage. 2009;45:1173–1182. 102. Vavasour IM, Laule C, Li DKB, Traboulsee AL, MacKay AL. Is the magnetization transfer ratio a marker for myelin in multiple sclerosis? J Magn Reson Imaging. 2011;33:710–718. 103. Gareau PJ, Rutt BK, Karlik SJ, Mitchell JR. Magnetization transfer and multicomponent T2 relaxation measurements with histopathologic correlation in an experimental model of MS. J Magn Reson Imaging. 2000;11:586–595. 104. Combès B, Monteau L, Bannier E, et al. EMISEP study group. Measurement of magnetization transfer ratio (MTR) from cervical spinal cord: multicenter reproducibility and variability. J Magn Reson Imaging. 2019;49:1777–1785. 105. van der Weijden CWJ, García DV, Borra RJH, et al. Myelin quantification with MRI: a systematic review of accuracy and reproducibility. Neuroimage. 2021;226:117561. 106. Levesque IR, Giacomini PS, Narayanan S, et al. Quantitative magnetization transfer and myelin water imaging of the evolution of acute multiple sclerosis lesions. Magn Reson Med. 2010;63:633–640. 107. Filippi M, Iannucci G, Tortorella C, et al. Comparison of MS clinical phenotypes using conventional and magnetization transfer MRI. Neurology. 1999;52:588–594. 108. Zhang L, Wen B, Chen T, et al. A comparison study of inhomogeneous magnetization transfer (ihMT) and magnetization transfer (MT) in multiple sclerosis based on whole brain acquisition at 3.0 T. Magn Reson Imaging. 2020;70:43–49. 109. Laule C, Leung E, Lis DK, et al. Myelin water imaging in multiple sclerosis: quantitative correlations with histopathology. Mult Scler. 2006;12:747–753. 110. Laule C, Kozlowski P, Leung E, Li DK, Mackay AL, Moore GR. Myelin water imaging of multiple sclerosis at 7 T: correlations with histopathology. Neuroimage. 2008;40:1575–1580. 111. Faizy TD, Thaler C, Kumar D, et al. Heterogeneity of multiple sclerosis lesions in multislice myelin water imaging. PLoS One. 2016;11:e0151496. 112. Webb S, Munro CA, Midha R, Stanisz GJ. Is multicomponent T2 a good measure of myelin content in peripheral nerve? Magn Reson Med. 2003;49:638–645. 113. Jelescu IO, Zurek M, Winters KV, et al. In vivo quantification of demyelination and recovery using compartment-specific diffusion MRI metrics validated by electron microscopy. Neuroimage. 2016;132:104–114. 114. Vavasour IM, Chang KL, Combes AJE, et al. Water content changes in new multiple sclerosis lesions have a minimal effect on the determination of myelin water fraction values. J Neuroimaging. 2021;31:1119–1125. Zuroff and Green: J Neuro-Ophthalmol 2024; 44: 143-156 115. Birkl C, Doucette J, Fan M, Hernández-Torres E, Rauscher A. Myelin water imaging depends on white matter fiber orientation in the human brain. Magn Reson Med. 2021;85:2221–2231. 116. Kolind S, Matthews L, Johansen-Berg H, et al. Myelin water imaging reflects clinical variability in multiple sclerosis. Neuroimage. 2012;60:263–270. 117. Meyers SM, Vavasour IM, Mädler B, et al. Multicenter measurements of myelin water fraction and geometric mean T2: intra- and intersite reproducibility. J Magn Reson Imaging. 2013;38:1445–1453. 118. Vargas WS, Monohan E, Pandya S, et al. Measuring longitudinal myelin water fraction in new multiple sclerosis lesions. Neuroimage Clin. 2015;9:369–375. 119. Vavasour IM, Huijskens SC, Li DKB, et al. Global loss of myelin water over 5 years in multiple sclerosis normalappearing white matter. Mult Scler. 2018;24:1557–1568. 120. Laule C, Vavasour IM, Zhao Y, et al. Two-year study of cervical cord volume and myelin water in primary progressive multiple sclerosis. Mult Scler. 2010;16:670–677. 121. Kitzler HH, Wahl H, Kuntke P, et al. Exploring in vivo lesion myelination dynamics: longitudinal myelin water imaging in early multiple sclerosis. Neuroimage Clin. 2022;36:103192. 122. Abel S, Vavasour I, Lee LE, et al. Associations between findings from myelin water imaging and cognitive performance among individuals with multiple sclerosis. Jama Netw Open. 2020;3:e2014220. 123. Ma YJ, Searleman AC, Jang H, et al. Volumetric imaging of myelin in vivo using 3D inversion recovery‐prepared ultrashort echo time cones magnetic resonance imaging. NMR Biomed. 2020;33:e4326. 124. Ma Y-J, Searleman AC, Jang H, et al. Whole-brain myelin imaging using 3D double-echo sliding inversion recovery ultrashort echo time (DESIRE UTE) MRI. Radiology. 2020;294:362–374. 125. Soustelle L, Antal MC, Lamy J, Rousseau F, Armspach JP, Loureiro de Sousa P. Correlations of quantitative MRI metrics with myelin basic protein (MBP) staining in a murine model of demyelination. NMR Biomed. 2019;32:e4116. 126. Guglielmetti C, Boucneau T, Cao P, Van der Linden A, Larson PEZ, Chaumeil MM. Longitudinal evaluation of demyelinated lesions in a multiple sclerosis model using ultrashort echo time magnetization transfer (UTE-MT) imaging. Neuroimage. 2020;208:116415. 127. Jang H, Ma YJ, Chang EY, et al. Inversion recovery ultrashort TE MR imaging of myelin is significantly correlated with disability in patients with multiple sclerosis. AJNR Am J Neuroradiol. 2021;42:868–874. 128. Bodini B, Veronese M, García‐Lorenzo D, et al. Dynamic imaging of individual remyelination profiles in multiple sclerosis. Ann Neurol. 2016;79:726–738. 129. Zeydan B, Lowe VJ, Schwarz CG, et al. Pittsburgh compoundB PET white matter imaging and cognitive function in late multiple sclerosis. Mult Scler. 2018;24:739–749. 130. de Paula Faria D, Copray S, Sijbesma JWA, et al. PET imaging of focal demyelination and remyelination in a rat model of multiple sclerosis: comparison of [11C]MeDAS, [11C]CIC and [11C]PIB. Eur J Nucl Med Mol Imaging. 2014;41:995–1003. 131. Klunk WE, Engler H, Nordberg A, et al. Imaging brain amyloid in Alzheimer’s disease with Pittsburgh Compound-B. Ann Neurol. 2004;55:306–319. 132. Veronese M, Bodini B, García-Lorenzo D, et al. Quantification of [11C]PIB PET for imaging myelin in the human brain: a test —retest reproducibility study in high-resolution research tomography. J Cereb Blood Flow Metab. 2015;35:1771– 1782. 133. van der Walt A, Kolbe S, Mitchell P, et al. Parallel changes in structural and functional measures of optic nerve myelination after optic neuritis. Plos One. 2015;10:e0121084. 134. Davies MB, Williams R, Haq N, Pelosi L, Hawkins CP. MRI of optic nerve and postchiasmal visual pathways and visual 155 Basic and Translational Research evoked potentials in secondary progressive multiple sclerosis. Neuroradiology. 1998;40:765–770. 135. Oertel FC, Krämer J, Motamedi S, et al. Visually evoked potential as prognostic biomarker for neuroaxonal damage in multiple sclerosis from a multicenter longitudinal cohort. Neurol Neuroimmunol Neuroinflamm. 2023;10:e200092. 136. Fuhr P, Borggrefe-Chappuis A, Schindler C, Kappos L. Visual and motor evoked potentials in the course of multiple sclerosis. Brain. 2001;124:2162–2168. 137. Henderson APD, Altmann DR, Trip SA, et al. Early factors associated with axonal loss after optic neuritis. Ann Neurol. 2011;70:955–963. 138. Abdelhak A, Cordano C, Boscardin WJ, et al. Plasma neurofilament light chain levels suggest neuroaxonal stability following therapeutic remyelination in people with multiple sclerosis. J Neurol Neurosurg Psychiatry. 2022;93:972–977. 139. Syc SB, Saidha S, Newsome SD, et al. Optical coherence tomography segmentation reveals ganglion cell layer pathology after optic neuritis. Brain. 2012;135:521–533. 140. Kupersmith MJ, Garvin MK, Wang J-K, Durbin M, Kardon R. Retinal ganglion cell layer thinning within one month of presentation for optic neuritis. Mult Scler. 2016;22:641–648. 141. Costello F, Hodge W, Pan YI, Eggenberger E, Coupland S, Kardon RH. Tracking retinal nerve fiber layer loss after optic neuritis: a prospective study using optical coherence tomography. Mult Scler. 2008;14:893–905. 142. Abalo-Lojo JM, Treus A, Arias M, Gómez-Ulla F, Gonzalez F. Longitudinal study of retinal nerve fiber layer thickness changes in a multiple sclerosis patients cohort: a long term 5 year follow-up. Mult Scler Relat Disord. 2018;19:124–128. 143. Talman LS, Bisker ER, Sackel DJ, et al. Longitudinal study of vision and retinal nerve fiber layer thickness in multiple sclerosis. Ann Neurol. 2010;67:749–760. 156 144. Fisher JB, Jacobs DA, Markowitz CE, et al. Relation of visual function to retinal nerve fiber layer thickness in multiple sclerosis. Ophthalmology. 2006;113:324–332. 145. Henderson APD, Altmann DR, Trip AS, et al. A serial study of retinal changes following optic neuritis with sample size estimates for acute neuroprotection trials. Brain. 2010;133:2592–2602. 146. Saidha S, Sotirchos ES, Oh J, et al. Relationships between retinal axonal and neuronal measures and global central nervous system pathology in multiple sclerosis. Jama Neurol. 2013;70:34–43. 147. Saidha S, Al-Louzi O, Ratchford JN, et al. Optical coherence tomography reflects brain atrophy in multiple sclerosis: a fouryear study. Ann Neurol. 2015;78:801–813. 148. Walter SD, Ishikawa H, Galetta KM, et al. Ganglion cell loss in relation to visual disability in multiple sclerosis. Ophthalmology. 2012;119:1250–1257. 149. Gordon-Lipkin E, Chodkowski B, Reich DS, et al. Retinal nerve fiber layer is associated with brain atrophy in multiple sclerosis. Neurology. 2007;69:1603–1609. 150. Wu GF, Schwartz ED, Lei T, et al. Relation of vision to global and regional brain MRI in multiple sclerosis. Neurology. 2007;69:2128–2135. 151. Balcer LJ, Baier ML, Cohen JA, et al. Contrast letter acuity as a visual component for the multiple sclerosis functional composite. Neurology. 2003;61:1367–1373. 152. Baier ML, Cutter GR, Rudick RA, et al. Low-contrast letter acuity testing captures visual dysfunction in patients with multiple sclerosis. Neurology. 2005;64:992–995. 153. Mowry EM, Loguidice MJ, Daniels AB, et al. Vision related quality of life in multiple sclerosis: correlation with new measures of low and high contrast letter acuity. J Neurol Neurosurg Psychiatry. 2009;80:767–772. Zuroff and Green: J Neuro-Ophthalmol 2024; 44: 143-156 |
| Date | 2024-06 |
| Date Digital | 2024-06 |
| References | Lubetzki C, Zalc B, Williams A, Stadelmann C, Stankoff B. Remyelination in multiple sclerosis: from basic science to clinical translation. Lancet Neurol. 2020;19:678-688. Plemel JR, Liu W-Q, Yong VW. Remyelination therapies: a new direction and challenge in multiple sclerosis. Nat Rev Drug Discov. 2017;16:617-634. Graves J, Balcer LJ. Eye disorders in patients with multiple sclerosis: natural history and management. Clin Ophthalmol. 2010;4:1409-1422. Graves JS, Oertel FC, Van der Walt A, et al. IMSVISUAL. Leveraging visual outcome measures to advance therapy development in neuroimmunologic disorders. Neurol Neuroimmunol Neuroinflamm. 2022;9:e1126. Mey GM, DeSilva TM. Utility of the visual system to monitor neurodegeneration in multiple sclerosis. Front Mol Neurosci. 2023;16:1125115. |
| Language | eng |
| Format | application/pdf |
| Type | Text |
| Publication Type | Journal Article |
| Source | Journal of Neuro-Ophthalmology, June 2024, Volume 44, Issue 2 |
| Collection | Neuro-Ophthalmology Virtual Education Library: Journal of Neuro-Ophthalmology Archives: https://novel.utah.edu/jno/ |
| Publisher | Lippincott, Williams & Wilkins |
| Holding Institution | North American Neuro-Ophthalmology Association. NANOS Executive Office 5841 Cedar Lake Road, Suite 204, Minneapolis, MN 55416 |
| Rights Management | © North American Neuro-Ophthalmology Society |
| ARK | ark:/87278/s63kcg2e |
| Setname | ehsl_novel_jno |
| ID | 2721565 |
| Reference URL | https://collections.lib.utah.edu/ark:/87278/s63kcg2e |



