MOG Antibody Disease: Nuances in Presentation, Diagnosis, and Management.

PURPOSE OF REVIEW: Myelin oligodendrocyte glycoprotein antibody disease (MOGAD) is a distinct neuroinflammatory condition characterized by attacks of optic neuritis, transverse myelitis, and other demyelinating events. Though it can mimic multiple sclerosis and neuromyelitis optica spectrum disorder, distinct clinical and radiologic features which can discriminate these conditions are now recognized. This review highlights recent advances in our understanding of clinical manifestations, diagnosis, and treatment of MOGAD. RECENT FINDINGS: Studies have identified subtleties of common clinical attacks and identified more rare phenotypes, including cerebral cortical encephalitis, which have broadened our understanding of the clinicoradiologic spectrum of MOGAD and culminated in the recent publication of proposed diagnostic criteria with a familiar construction to those diagnosing other neuroinflammatory conditions. These criteria, in combination with advances in antibody testing, should simultaneously lead to wider recognition and reduced incidence of misdiagnosis. In addition, recent observational studies have raised new questions about when to treat MOGAD chronically, and with which agent. MOGAD pathophysiology informs some of the relatively unique clinical and radiologic features which have come to define this condition, and similarly has implications for diagnosis and management. Further prospective studies and the first clinical trials of therapeutic options will answer several remaining questions about the peculiarities of this condition.

Central vein sign and other radiographic features distinguishing myelin oligodendrocyte glycoprotein antibody disease from multiple sclerosis and aquaporin-4 antibody-positive neuromyelitis optica.

BACKGROUND: Myelin oligodendrocyte glycoprotein antibody disease (MOGAD) can radiographically mimic multiple sclerosis (MS) and aquaporin-4 (AQP4) antibody-positive neuromyelitis optica spectrum disorder (NMOSD). Central vein sign (CVS) prevalence has not yet been well-established in MOGAD. OBJECTIVE: Characterize the magnetic resonance imaging (MRI) appearance and CVS prevalence of MOGAD patients in comparison to matched cohorts of MS and AQP4+ NMOSD. METHODS: Clinical MRIs from 26 MOGAD patients were compared to matched cohorts of MS and AQP4+ NMOSD. Brain MRIs were assessed for involvement within predefined regions of interest. CVS was assessed by overlaying fluid-attenuated inversion recovery (FLAIR) and susceptibility-weighted sequences. Topographic analyses were performed on spinal cord and orbital MRIs when available. RESULTS: MOGAD patients had fewer brain lesions and average CVS+ rate of 12.1%, compared to 44.4% in MS patients (p = 0.0008). MOGAD spinal cord and optic nerve involvement was lengthier than MS (5.8 vs 1.0 vertebral segments, p = 0.020; 3.0 vs 0.5 cm, p < 0.0001). MOGAD patients tended to have bilateral/anterior optic nerve pathology with perineural contrast enhancement, contrasting with posterior optic nerve involvement in NMOSD. CONCLUSION: CVS+ rate and longer segments of involvement in the spinal cord and optic nerve can differentiate MOGAD from MS, but do not discriminate as well between MOGAD and AQP4+ NMOSD.

Time-Dependent Deep Learning Prediction of Multiple Sclerosis Disability.

The majority of deep learning models in medical image analysis concentrate on single snapshot timepoint circumstances, such as the identification of current pathology on a given image or volume. This is often in contrast to the diagnostic methodology in radiology where presumed pathologic findings are correlated to prior studies and subsequent changes over time. For multiple sclerosis (MS), the current body of literature describes various forms of lesion segmentation with few studies analyzing disability progression over time. For the purpose of longitudinal time-dependent analysis, we propose a combinatorial analysis of a video vision transformer (ViViT) benchmarked against traditional recurrent neural network of Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) architectures and a hybrid Vision Transformer-LSTM (ViT-LSTM) to predict long-term disability based upon the Extended Disability Severity Score (EDSS). The patient cohort was procured from a two-site institution with 703 patients' multisequence, contrast-enhanced MRIs of the cervical spine between the years 2002 and 2023. Following a competitive performance analysis, a VGG-16-based CNN-LSTM was compared to ViViT with an ablation analysis to determine time-dependency of the models. The VGG16-LSTM predicted trinary classification of EDSS score in 6 years with 0.74 AUC versus the ViViT with 0.84 AUC (p-value < 0.001 per 5 × 2 cross-validation F-test) on an 80:20 hold-out testing split. However, the VGG16-LSTM outperformed ViViT when patients with only 2 years of MRIs (n = 94) (0.75 AUC versus 0.72 AUC, respectively). Exact EDSS classification was investigated for both models using both classification and regression strategies but showed collectively worse performance. Our experimental results demonstrate the ability of time-dependent deep learning models to predict disability in MS using trinary stratification of disability, mimicking clinical practice. Further work includes external validation and subsequent observational clinical trials.

Quantitative MRI identifies lesional and non-lesional abnormalities in MOGAD.

BACKGROUND: Myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD) is a distinct central nervous system (CNS) disorder that shares features with multiple sclerosis (MS) and may be misdiagnosed as MS. MOGAD and MS share a frequently relapsing clinical course and lesions with inflammatory demyelinating pathology. One key feature of MS pathology is tissue damage in normal-appearing white matter (NAWM) outside of discrete lesions, whereas the extent to which similar non-lesional damage occurs in MOGAD is not known and could be assessed using qGRE. The goal of this study was to examine the brains of people with MOGAD using quantitative gradient-recalled echo (qGRE) magnetic resonance imaging and to compare tissue damage with MS patients matched for disability. METHODS: MOGAD and MS patients were recruited to match in terms of age and disability. Similarly aged healthy control (HC) data were drawn from existing studies. qGRE brain imaging of HC (N = 15), MOGAD (N = 17), and MS (N = 15) patients was used to examine the severity and extent of tissue damage within and outside of discrete lesions. The qGRE metric R2t* is sensitive to changes in tissue microstructure and was measured in white matter lesions (WMLs), NAWM, cortical (CGM) and deep gray matter (DGM). Statistical inference was performed with linear models. RESULTS: R2t* was reduced in CGM (p = 0.00047), DGM (p = 0.0055) and NAWM (p = 0.0019) in MOGAD and MS compared to similar regions in age-matched HCs. However, the degree of R2t* reduction in all these regions was less in the MOGAD patients compared with MS. WMLs in MOGAD demonstrated reduced R2t* compared to NAWM but this reduction was modest compared to changes associated with WMLs in MS (p = 0.026). CONCLUSION: These results demonstrate abnormalities in lesional and non-lesional CNS tissues in MOGAD that are not detectable on standard MRI. The abnormalities seen in NAWM, CGM, and DGM were less severe in MOGAD compared to MS. MOGAD-related WMLs showed reduced R2t*, but were less abnormal than WMLs in MS. These data reveal damage to non-lesional tissues in two different demyelinating diseases, suggesting that damage outside of WMLs may be a common feature of demyelinating diseases. The lesser degree of R2t* abnormality in MOGAD tissues compared to MS suggests less underlying tissue damage and may underlie the greater propensity for recovery in MOGAD.

Perspectives and experiences with COVID-19 vaccines in people with MS.

Background: People with MS may have unique perspectives on COVID-19 vaccines due to their condition and/or medications. Objective: Assess perspectives and experiences with COVID-19 vaccination, and quantify variables impacting COVID-19 vaccine willingness in people with MS. Methods: A survey captured demographics, MS characteristics, and COVID-19 infection and exposures data; opinions on COVID-19 vaccine safety, side effects, and efficacy; and experiences following vaccination. Chi-square tests and a logistic regression model were used to denote between-group differences and variables predicting vaccine willingness, respectively. Results: Most (87.8%) of the 237 participants were willing to receive the vaccine. Fifteen percent held or delayed a DMT dose for vaccination. MS symptoms worsened in a minority (7.6% first/only dose; 14.7% second dose), and most side effects were mild (80.0%; 55.3%). Those not planning to receive the vaccine were primarily concerned with long-term safety (70.4%). Medical comorbidities (adjusted odds ratio [aOR]=5.222; p=0.04) and following infection prevention precautions (aOR=6.330; p=0.008) were associated with vaccine willingness. Conclusion: Most individuals with MS surveyed plan to receive the COVID-19 vaccine. People with MS experience similar side effects to the general population, and few experience transient MS symptom worsening. These results can inform conversations on vaccination between providers and people with MS.

Myelin oligodendrocyte glycoprotein-IgG associated disorders (MOGAD) following SARS-CoV-2 infection: A case series.

This case series describes 9 patients diagnosed with myelin oligodendrocyte glycoprotein (MOG)-IgG associated disorder (MOGAD) following severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Patients developed neurological symptoms between 4 days and 5 weeks following SARS-CoV-2 infection. Myelitis was observed in 4 patients; 4 presented with optic neuritis; and encephalopathy was observed in 3. Serum MOG-IgG cell-based assay was medium or high positive in each case. The majority of patients had near-complete recovery following acute immunosuppression. This series adds to the growing number of cases of central nervous system demyelination following SARS-CoV-2 infection and highlights a potential role of infection in the immunopathogenesis of MOGAD.

Effects of MS disease-modifying therapies on responses to vaccinations: A review.

BACKGROUND: Development of long-term immunologic memory relies upon humoral and cellular immune responses. Vaccinations aim to stimulate these responses against pathogens. Several studies have evaluated the impact of multiple sclerosis disease-modifying therapies on immune response to vaccines. Findings from these studies have important implications for people with multiple sclerosis who require vaccination and are using disease-modifying therapies. METHODS: Searches using PubMed and other engines were conducted in May 2020 to collect studies evaluating the impact of various disease-modifying therapies on immune responses to vaccination. RESULTS: Several studies demonstrated preserved immune responses in people treated with beta-interferons to multiple vaccine types. Limited data suggest vaccine responses to be preserved with dimethyl fumarate treatment, as well. Vaccine responses were reduced to varying degrees in those treated with glatiramer acetate, teriflunomide, sphingosine-1-phosphate receptor modulators, and natalizumab. The timing of vaccination played an important role in those treated with alemtuzumab. Humoral vaccine responses were significantly impaired by B cell depleting anti-CD20 monoclonal antibody therapies, particularly to a neoantigen. Data are lacking on vaccine responses in patients with multiple sclerosis taking cladribine and high-dose corticosteroids. Notably, the majority of these studies have focused on humoral responses, with few examining cellular immune responses to vaccination. CONCLUSIONS: Prior investigations into the effects of individual disease-modifying therapies on immune responses to existing vaccines can serve as a guide to expected responses to a SARS-CoV-2 vaccine. Responses to any vaccination depend on the vaccine type, the type of response (recall versus response to a novel antigen), and the impact of the individual disease-modifying therapy on humoral and cellular immunity in response to that vaccine type. When considering a given therapy, clinicians should weigh its efficacy against MS for the individual patient versus potential impact on responses to vaccinations that may be needed in the future.

Clinical and laboratory features distinguishing MOG antibody disease from multiple sclerosis and AQP4 antibody-positive neuromyelitis optica.

BACKGROUND: Antibodies to myelin oligodendrocyte glycoprotein (MOG) are associated with a CNS inflammatory disorder distinct from multiple sclerosis (MS) and aquaporin-4 antibody-positive neuromyelitis optica (NMO). Knowledge of the clinical spectrum of MOG antibody disease (MOGAD) remains incomplete, particularly in comparison to two related inflammatory demyelinating diseases, MS and NMO. OBJECTIVE: Compare demographics, clinical characteristics, estimated disability, laboratory results, and treatment responses of a U.S. MOGAD cohort with age- and sex-matched MS and NMO patients. DESIGN, SETTING, AND PARTICIPANTS: This observational, case-control, single-center study identified each group via ICD-10 diagnosis code searches through the electronic medical records of adult patients seen at the John L. Trotter MS Center between January 1, 2019 and January 1, 2020. MOGAD and NMO patients were confirmed to have at least one positive antibody test; those in the MS group had a confirmed diagnosis by a physician with MS subspecialty training. Data were collected after IRB approval. RESULTS: Twenty-six patients were included in each group. MOGAD patients were predominantly Caucasian (88.5%) with mean onset age of 43.9 years. MOGAD patients had no comorbid other autoimmune diseases and comparatively lower rates of family members with autoimmune disease (20.0%) than either MS (40.0%) or NMO (34.6%) matched cohorts. 91% of MOGAD attacks were monofocal, and over 70% presented with optic neuritis. Severity of MOGAD attacks was similar to that of seropositive NMO, but the robust degree of recovery was more similar to MS. Four MOGAD patients converted to negative antibody status, with no attacks occurring after conversion. Serum ANA and ENA were less frequently elevated in MOGAD (21.7%, 5.0%) than in seropositive NMO patients (66.7%, 42.9%). Elevated IgG synthesis rate and positive CSF-restricted oligoclonal bands were not seen in our MOGAD cohort, and only one MOGAD patient had an elevated IgG index. Despite anti-CD20 therapy, 28.6% of MOGAD patients continued to suffer relapses. CONCLUSIONS: MOGAD was characterized by a predominantly monofocal presentation (typically optic neuritis) and severe attacks with better recovery than seen with seropositive NMO attacks. Lack of CSF-restricted oligoclonal bands distinguished MOGAD from MS.

Clinical instrument to retrospectively capture levels of EDSS.

BACKGROUND: The Expanded Disability Status Scale (EDSS), a common outcome measure in Multiple Sclerosis (MS), is obtained prospectively through a direct standardized evaluation. The objective of this study is to develop and validate an algorithm to derive EDSS scores from previous neurological clinical documentation. METHODS: The algorithm utilizes data from the history, review of systems, and physical exam. EDSS scores formally obtained from research patients were compared to captured EDSS (c-EDSS) scores. To test inter-rater reliability, a second investigator captured scores from a subset of patients. Agreement between formal and c-EDSS scores was assessed using a weighted kappa. Clinical concordance was defined as a difference of one-step in EDSS (0.5) and functional system (1.0) scores. RESULTS: Clinical documentation from 92 patients (EDSS range 0.0-8.5) was assessed. Substantial agreement between the c-EDSS and formal EDSS (kappa 0.80; 95% CI 0.74-0.86) was observed. The mean difference between scores was 0.16. The clinical concordance was 78%. Near-perfect agreement was found between the two raters (kappa 0.89; 95% CI 0.84-0.95). The mean inter-rater difference in c-EDSS was 0.23. CONCLUSIONS: This algorithm reliably captures EDSS scores retrospectively with substantial correlation with formal EDSS and high inter-rater agreement. This algorithm may have practical implications in clinic, MS research and clinical trials.

Disease-Modifying Treatment in Progressive Multiple Sclerosis.

PURPOSE OF REVIEW: Multiple sclerosis (MS) is an immune-mediated disorder that affects the central nervous system (CNS), often first affecting people in early adulthood. Although most MS patients have a relapsing-remitting course (RRMS) at disease onset, a substantial proportion later develop chronic progression, termed secondary progressive MS (SPMS). Approximately 10% of MS patients experience chronic progression from disease onset, termed primary progressive multiple sclerosis (PPMS). Although several disease-modifying treatment (DMT) options exist for relapsing forms of this disease, DMT options are few for progressive MS (PPMS and SPMS). Herein, we strive to define progressive MS, review major clinical trials aimed at progressive MS, and delineate potential strategies in the management of progressive MS. RECENT FINDINGS: In 2017, the first DMT for PPMS, the B lymphocyte-depleting monoclonal antibody, ocrelizumab, came to market. Ocrelizumab reduced 12-week confirmed disability progression (CDP) by 24% versus placebo. Siponimod, a selective sphingosine-1-phosphate receptor modulator, reduced 3-month CDP by 21% versus placebo in SPMS. Ibudilast slowed brain atrophy in PPMS and SPMS patients in a multicenter phase 2b study. Smaller early phase studies of alpha-lipoic acid and simvastatin each found slowing of rate of whole brain atrophy in SPMS patients. Reasons now exist for optimism in the search for DMTs for progressive MS. It remains a challenge to identify outcome measures that accurately reflect the underlying pathology in progressive MS, which is less inflammatory and more degenerative than RRMS.