Protocol of a prospective multicenter study on comorbidity impact on multiple sclerosis and antibody-mediated diseases of the central nervous system (COMMIT)

Comorbidities in patients with multiple sclerosis (MS) and antibody-mediated diseases of the central nervous system (CNS) including neuromyelitis optica spectrum disorder (NMOSD), and myelin oligodendrocyte glycoprotein (MOG)-antibody-associated disease (MOGAD) are common and may influence the course of their neurological disease. Comorbidity may contribute to neuronal injury and therefore limit recovery from attacks, accelerate disease progression, and increase disability. This study aims to explore the impact of comorbidity, particularly vascular comorbidity, and related risk factors on clinical and paraclinical parameters of MS, NMOSD and MOGAD. We propose COMMIT, a prospective multicenter study with longitudinal follow-up of patients with MS, NMOSD, and MOGAD, with or without comorbidities, as well as healthy subjects as controls. Subjects will be stratified by age, sex and ethnicity. In consecutive samples we will analyze levels of inflammation and neurodegeneration markers in both fluid and cellular compartments of the peripheral blood and cerebrospinal fluid (CSF) using multiple state-of-the-art technologies, including untargeted proteomics and targeted ultrasensitive ELISA assays and quantitative reverse transcription polymerase chain reaction (RT-qPCR) as well as high-dimensional single-cell technologies i.e., mass cytometry and single-cell RNA sequencing. Algorithm-based data analyses will be used to unravel the relationship between these markers, optical coherence tomography (OCT) and magnetic resonance imaging (MRI), and clinical outcomes including frequency and severity of relapses, long-term disability, and quality of life. The goal is to evaluate the impact of comorbidities on MS, NMOSD, and MOGAD which may lead to development of treatment approaches to improve outcomes of inflammatory demyelinating diseases of the CNS.


Introduction
Inflammatory demyelinating diseases (IDDs) of the central nervous system (CNS) are immune-mediated disorders that lead to the destruction of myelin, either primarily [multiple sclerosis (MS) and myelin oligodendrocyte glycoprotein-antibody-associated disease (MOGAD)] or secondarily [neuromyelitis optica spectrum disorder (NMOSD)].There is a variable degree of axonal injury and loss, which is the ultimate substrate of disability (1,2).The development and pathogenesis of IDDs are complicated immune mechanisms, presumably involving both innate and adaptive immunity, reflecting defects in autoimmune tolerance mechanisms.Likewise, the immunobiology of injury and repair is multifactorial and influenced by genetic and environmental factors.Remyelination may protect against axonal degeneration by oligodendrocyte precursor cell (OPC) proliferation and maturation to oligodendrocytes (OLs) in the case of actual OL loss to a variable degree (3).OLs have high metabolic requirements to maintain myelin synthesis and metabolic support of axons (3).The most well-defined IDDs are multiple sclerosis (MS), widely believed to be T-cellmediated, and NMOSD and MOGAD, both of which are believed to be antibody-mediated.
Clusters of chronic conditions and comorbidities may occur in IDDs and are an area of current interest (4)(5)(6)(7)(8)(9)(10)(11)(12).Comorbidity refers to the burden caused by the presence and severity of any distinct additional entity other than the specific index disease and may result from similar predisposing genetic or environmental factors (13) or from treatment of IDDs (14,15).For instance, corticosteroids can precipitate the onset of diabetes and hyperglycemia, while other certain immunosuppressive drugs are linked to an increased risk of cardiovascular disease (4).The co-occurrence of two or more chronic conditions, i.e., so-called multimorbidity, may be present even at the time of diagnosis (4).
In IDDs, comorbidity may contribute to remyelination failure and neuronal injury and adversely affect a broad range of outcomes, including the risk of relapse, diminished quality of life (QoL), and long-term disability.
Multimorbidity is a growing concern, with an increase in the prevalence of chronic somatic conditions as well as mental disorders, in part reflecting an aging population (10-12, 16, 17).Many factors such as lifestyle and socioeconomic status may lead to the onset of multimorbidity at a younger age (13).Emerging evidence underscores a high prevalence of comorbidity, i.e., vascular comorbidities and related risk factors in patients with multiple sclerosis (18), exemplified by type 2 diabetes mellitus (T2DM), which is a highly prevalent disorder worldwide.Patients with T2DM are at high risk for microvascular complications, owing to hyperglycemia and insulin resistance (metabolic syndrome) (19).Oral antidiabetic drugs such as metformin and pioglitazone may beneficially impact MS disease progression by reducing inflammatory mediators such as interferon-g, interleukin (IL)-6, and TNF-alpha (20).T2DM may influence brain function and may cause brain insulin resistance, neuroinflammation including microglia activation, blood-brain barrier (BBB) impairment, and mitochondrial dysfunction, resulting in neuronal metabolic defects and neuronal cell death (21).The most common comorbidities in patients with NMOSD are hypertension and cardiovascular disease (4,22), although uniquely in NMOSD, other autoimmune conditions, such as systemic lupus erythematosus, rheumatoid arthritis, Sjögren's syndrome, and autoimmune encephalitis, may occur as concurrent comorbid diseases because of defective B-cell development checkpoints (5,6).MOGAD has only recently been recognized and may be regarded as a relatively rare disorder (23), so the pattern of comorbidity has not yet been elucidated; however, anti-N-methyl-Daspartate receptor encephalitis (anti-NMDAR encephalitis) and autoimmune thyroid disorders have been reported to occur (7).
Investigations of the impact of comorbidities on clinical outcomes of IDD have only been conducted to a limited extent.Comorbid conditions can be associated with a prolonged interval between the disease onset and its subsequent diagnosis.An increase in the frequency of relapses has been observed in NMOSD patients with comorbidities compared to NMOSD patients without comorbidities, with severe motor episodes and severe optic neuritis (ON) (15).Multifocal CNS lesions as a presenting symptom are more prevalent in patients with comorbidities compared to those without.Moreover, comorbidity can be indicative of reduced treatment responsiveness, heightened disability, and an elevated mortality rate (15,24).
However, the current knowledge is mainly based on retrospective and cross-sectional studies with a small number of patients.A prospective and longitudinal study with an evaluation of the interaction between clinical and paraclinical parameters of comorbidity of subjects with MS, NMOSD, and MOGAD will be a timely effort.

Advancing data collection and protocols for comorbidity analysis and management
The high occurrence of comorbidities suggests screening for concomitant medical conditions as a routine part of patient care, as comorbidities may influence the clinical features, prognosis, and treatment outcomes.So far unexplored, the comorbidity and certain clusters of chronic conditions may have a negative impact on the levels of proinflammatory and neurodegenerative mediators, and they may negatively influence disease progression.Such knowledge will be important for optimizing treatment strategies and thereby hopefully improve QoL.Comorbidities may vary depending on age, sex, ethnicity, geographic region, socioeconomic composition, and healthcare system, highlighting the importance of a multicenter design.Furthermore, analytical pipelines for the determination of molecular and cellular markers as well as downstream algorithmbased (integrative) data analysis have been established and are in the process of validation.This multicentric study will analyze data from different sets of patients without or with one or more comorbidities, with follow-up visits.We aim to determine the levels of inflammatory and neurodegenerative mediators in patients with MS, NMOSD, and MOGAD, both with and without comorbidities, and evaluate whether changes may affect disease outcomes.Furthermore, we aim to assess whether comorbidity influences optical coherence tomography (OCT) and magnetic resonance imaging (MRI) parameters and its association with clinical outcomes.

Study design
The study comprises a prospective, multicenter investigation of patients with MS, AQP4-IgG-positive NMOSD, and MOGAD, with or without comorbidities with 3 years of follow-up in collaboration with multiple centers from Denmark (2), Germany (2), the USA (4), UK (1), Iran (2), Italy (1), Israel (1), and South Korea (1).All patients will be offered follow-up after 6, 12, 18, 24, and 36 months after baseline.The baseline is defined as the time of entry into the study, i.e., any time point during the disease course.
The COMMIT study will adhere to the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) guidelines for reporting (25).Approval will be sought from local ethical institutional review boards in all centers, and informed consent will be obtained from the patients.The study will be conducted in accordance with the provisions of the Declaration of Helsinki and the guidelines for good clinical practice set forth by the International Conference on Harmonization (26).

Study population and diagnosis
We will recruit MS (27), NMOSD (seropositive for AQP4-IgG) (28), and MOGAD (23) patients, age-matched with or without comorbidities.Participants will undergo an assessment to determine the presence of comorbidity using a predefined list tailored for each organ system.All comorbidities will be listed, including common comorbidities such as cardiovascular diseases and their associated risk factors, as well as autoimmune disorders.For comorbidities with predefined quantitative criteria, screening will be conducted to confirm that patients have advanced beyond the pre-diagnostic stage (e.g., pre-diabetes) to actual diagnosis (e.g., T2DM).In addition to identifying diseases (e.g., ischemic heart disease), we will screen for risk factors such as obesity, hypertension, and hyperlipidemia (29).We will recruit a healthy control group from each region without known chronic conditions or comorbidities matched for age and sex.

Inclusion and exclusion criteria
Eligible participants must possess competence for written informed consent, be ≥18 years of age, and have a diagnosis of MS, NMOSD, or MOGAD with an Expanded Disability Status Scale (EDSS) assessment score from 0 to 6.5 inclusive at the time of recruitment (30,31).
Patients will be excluded if they are unable to cooperate, have active drug or alcohol abuse, are pregnant, or have an active systemic infection, ON within the preceding 3 months, and steroid treatment in the past 1 month.Dropout criteria will be evaluated during follow-up visits (Table 1).

Medical history and clinical examination
The patients will undergo a clinical examination at baseline visit and on follow-up after 6, 12, 24, and 36 months.Blood sampling, cerebrospinal fluid (CSF) testing, MRI, and OCT will be performed at baseline and annually during the follow-up period.The process is outlined in Table 2. Clinical information including age, sex, ethnicity, height, weight, and lifestyle factors such as tobacco and alcohol use, as well as drug abuse history, is recorded.After a combination of interviews and review of past medical records, we will determine disease onset; assess current symptoms; and record histories of relapses or attacks, comorbidities, and comprehensive treatment details, encompassing both pharmacological and nonpharmacological therapies.The neurological evaluation employs the EDSS in accordance with neurostatus definitions (30,31).The visual system score is determined through best-corrected highcontrast visual acuity testing (15) (Table 1).

Comorbid conditions
At the start of the study, comorbidity data, including the date of diagnosis, the characteristics, and the associated treatments of the identified comorbidities, will be abstracted from the 'patients' medical records (Table 4).In cases where medical records are either ambiguous or lack specific details, patients will be interviewed to obtain information on their distinct comorbid conditions.Each comorbidity will be categorized into main categories utilizing global standard codes for primary and secondary diagnoses using the International Statistical Classification of Diseases and Related Health Problem (ICD) system (version 10 or 11) (Table 3).For enhanced analytical clarity, patients will be grouped based on whether they have a single comorbid condition or multiple conditions.Special emphasis will be placed on cardiovascular comorbidities for subanalysis.Regular medical assessments at predetermined intervals will enable detection through ICD diagnosis, documentation, and treatment of any new comorbidities.

Cognitive assessment
The 'participant's level of education and hand preference will be determined through an interview (32).A professional will administer the Montreal Cognitive Assessment (MoCA) in alignment with its official guidelines.MoCA serves as a comprehensive clinical tool designed to evaluate a broad spectrum of cognitive functions related to MS and other conditions (33).This assessment includes cognitive domains such as memory, attention, language, abstraction, delayed recall, orientation, and visuospatial skills.The entire cognitive assessment with MoCA typically takes about 15 min.Additionally, the European Quality of Life-5 Dimensions (EQ-5D) index and the EQ-5D visual analog scale (VAS) (34) will be performed.
At baseline and at the 24-month follow-up, peripheral blood mononuclear cells (PBMCs) will be isolated and undergo flow  The list of comorbid conditions, along with the corresponding questionnaires and clinical examinations, can be found in Table 3.This also includes the date of diagnosis, the severity (when available), the number of comorbid conditions grouped by main categories, and the actual raw numbers.Neuro-QOL Fatigue Scale, European Quality of Life-5 Dimensions (EQ-5D) index, EQ-5D visual analog scale (VAS) cytometry for quantitative analysis to determine the numbers of CD4, CD8 T lymphocytes, B lymphocytes, dendritic cells, monocytes, monocyte-derived macrophages, FOXP3 + regulatory T cells, and FoxA1 + Treg and natural killer T cells, as well as mass cytometry for in-depth immune characterization.Additionally, hydrophilic interaction chromatography/mass spectrometry-based proteomics for unbiased screening of plasma/serum will be performed, backed up by targeted highly sensitive assays (Simoa), and RT-qPCR performed centrally.All biospecimens will be collected and analyzed at the University of Southern Denmark.

Patient-reported outcomes
For assessing fatigue, the short-form Neuro-QOL Fatigue Scale (37) will be utilized to measure current levels of fatigue.This scale provides a valuable insight into the impact of fatigue on the quality of life of participants.

Vision and the visual system
Participants will undergo ophthalmological examinations at baseline and at the final visit for the study, which include refraction, high-and low-contrast visual acuity tests, visual fields, and visual evoked potentials (VEPs).Additionally, the National Eye Institute 25-item Visual Function Questionnaire (NEI-VFQ-25) will be utilized to evaluate patients' visual health-related quality of life (38,39).
High-resolution OCT images of the retina will be created for all patients and controls (majority of the data for this study will be derived from the Heidelberg Spectralis SD-OCT device as per our retrospective dataset.However, data may be obtained from other OCT devices, including Cirrus HD-OCT, Carl Zeiss; Topcon, Optovue, Canon).The imaging scans for this study will be conducted following the guidelines set forth by the Advised Protocol for OCT Study Terminology and Elements (APOSTEL) 2.0 9-point recommendations (40) and the OSCAR-IB quality criteria (41,42).We will not consider patients whose documentation is incomplete or who underwent OCT imaging using time-domain devices.
The OCT protocol encompasses various scans such as a peripapillary ring scan, a volume scan of the macula, and a volume scan of the optic nerve head.The measurements taken by the OCT include the peripapillary retinal nerve fiber layer (pRNFL) thickness, ganglion cell-inner plexiform layer (GCIP) thickness, inner nuclear layer (INL) thickness, outer nuclear layer (ONL) thickness, and macular thickness.
Additionally, OCT angiography (OCTA) will be utilized, providing a detailed view of the retinal and choroidal vasculature.Equipment from both Heidelberg and Zeiss will be used to obtain images.Through these images, vascular density, the foveal avascular zone, flow regions, and qualitative vascular irregularities will be assessed.A high standard of image quality will be maintained.Scans meeting an acceptable signal strength index will be selected for analysis centrally, and those compromised by artifacts or other quality issues will be carefully excluded (1).All OCT data will be collected at Charite University, Berlin, Germany.

CNS MRI
In the comparative analysis of MRI findings for the index disease, both with and without comorbidity, our initial primary focus centers on vascular comorbid conditions.MRI scans will be conducted using a 3T system compatible with Siemens, Philips, and GE scanners.The core structural protocol includes the brain, orbit, and spinal cord.

Spinal cord
The protocol includes a 3D T2 SPACE sequence, a 3D T1 MPRAGE sequence for the cervical cord, and a 3D T2 sequence for the thoracic cord (~12 min).

Optic nerve
The MRI protocol will feature a high-resolution, 3D T2-weighted orbit sequence focused on the optic nerves with a slice thickness of 2 mm or less.Fat suppression techniques will be employed to enhance contrast and reduce artifacts, and a post-contrast T1-weighted sequence may also be used to assess inflammatory or demyelinating changes in the optic nerve (~10-15 min) (49-52).All MRI data will be evaluated at the University of Oxford, UK.

Outcome measures and assessment timeline
In this study, a comprehensive set of outcome parameters, as detailed above, will be monitored and analyzed at each clinical visit to the participating centers (Table 2).Assessments are scheduled to be conducted at the initiation of the study (baseline) and subsequently at 6, 12, 24, and 36 months.This scheduling allows for the tracking of changes over time (Table 2, Figure 1).As an interim analysis specifically oriented at regional differences, we will conduct subgroup analyses to explore cross-sectional region-specific effects.

Assessments and endpoints
In MS, the evaluation of disease progression is refined through advanced measures, with a primary focus on no evidence of disease activity (NEDA-4) (40, 53, 54).NEDA-4 assessment in our study includes four criteria: no clinical relapses; no new/enlarged T2weighted MRI lesions; no disability progression over 6 months, assessed by the EDSS score; and a mean annual brain volume loss rate under 0.4%.
For NMOSD and MOGAD, the primary endpoint is relapse frequency [annualized relapse rate (ARR)] and time to relapse.Secondary endpoints are clinically important change from baseline in Hauser Ambulation Index (HAI) score (55), changes from baseline in EQ-5D index and EQ-5D visual analog scale (VAS), disability worsening from baseline in EDSS score (30) and change from baseline in low-contrast visual acuity binocular score (by lowcontrast Landolt C broken ring chart), and cumulative total number of active MRI lesions (new gadolinium-enhancing lesions, or new or enlarging T2 lesions, measured across the optic nerve, brain, brainstem, and spinal cord).
The number of IDD-related hospital admissions will be recorded.Patient-reported outcomes also provide further insights

Comorbidity (coincidence and concurrent diseases or comorbid conditions)
This general term refers to the presence of one or more additional diseases or disorders occurring concurrently with a primary disease or disorder.Based on Table 3 categories.

Multimorbidity (polypathology or polymorbidity)
This is the coexistence of two or more chronic diseases or conditions in a patient.The term is often used interchangeably with comorbidity, but while comorbidity refers to the effect of all other diseases an individual patient might have other than the primary disease, multimorbidity refers to the presence of two or more chronic diseases without establishing a primary disease.

Health determinants and indicators
These broader terms encompass a variety of conditions and factors that affect health.For example, in the context of vascular health, this could include both comorbid conditions and risk factors related to vascular diseases.

Comorbid conditions (concurrent disorders and co-existing diseases)
These refer to actual health conditions or diseases an individual has in addition to their primary disease.For instance, in the realm of vascular health, examples could include conditions like heart disease, stroke, and hypertension.These comorbid conditions co-occur with the primary disease and can interact with it in complex ways, potentially impacting treatment and outcomes.

Risk factors (predictors)
These are characteristics or behaviors that increase the likelihood of developing certain diseases.For example, in the case of vascular health, risk factors might include behaviors like smoking, lifestyle factors like lack of exercise or obesity, and genetic predispositions such as family history of vascular disease.

Detailed conditions Severity metrics
Diseases of the genitourinary system Glomerular diseases, chronic kidney disease, renal failure, renal tubulo-interstitial diseases, urolithiasis, benign prostatic hyperplasia, disorders of the breast, disorders of the female/male genital tract Stages of CKD (chronic kidney disease progression), The International Prostate Symptom Score (IPSS) (prostate-related symptoms)

Infections and parasitic diseases
Tuberculosis, malaria, HIV/AIDS, Epstein-Barr virus (EBV), herpesvirus 6, varicella-zoster virus, Helicobacter pylori, Clostridium perfringens Antibody level: a measure of specific antibodies in the blood, indicating immune system activity or response to vaccination into the patient's experience of the disease in this study (56).Exploratory outcomes include OCT parameters and clinically relevant biomarkers like NfL levels and GFAP for NMOSD (57,58).

Data management and quality control
Data associated with the study will be stored within the REDCap database system (59).Monthly data monitoring will be conducted using a REDCap query function for completeness and accuracy by the research team to ensure that any errors or inconsistencies are identified and addressed in a timely manner.

Streamlined dataset protocol for multicenter coordination
To achieve consistent data collection across various centers, it is crucial to establish a standardized minimal dataset.This standardized approach is key to facilitating data sharing and analysis, ensuring uniformity and reliability in study outcomes across diverse facilities.It is planned that the specifics of the data subsets for each center will be thoroughly discussed with all participating centers.A primary milestone for the multicentric part of this project is the initiation of cross-sectional data collection.

Statistical analysis
The data will be analyzed in two stages: first cross-sectionally and then longitudinally.The cross-sectional analysis will focus on examining the relationships among the variables at a single point in time, while the longitudinal analysis will explore changes in these relationships over time.
In the initial stage of analysis, the data will be evaluated crosssectionally.This will encompass descriptive statistics to summarize central aspects like means, medians for continuous variables, and frequencies for categorical ones.Additionally, correlation analyses will gauge the linear relationships between pairs of variables, while regression analysis will investigate the predictive influence of independent variables on a designated dependent variable.In the subsequent phase, the focus will be on the evolution and patterns in relationships over time.Repeated measures ANOVA will be employed to compare means across different times and identify any significant changes.Growth curve modeling will be done to understand the trajectory of variables over time and to determine if there are individual differences in the change trajectories.Furthermore, to accommodate instances of missing data or irregular time intervals, mixed-effects models will be utilized, considering both fixed and random influences.
To determine the sample size, the study's primary objectives and expected effect sizes will be considered by using R statistical software.A-priori power analyses will be utilized to establish the needed sample size with an optimal power, usually set at 0.80, for a typical significance level of 0.05.Practical significance of the observed relationships or differences will be assessed.
Association analyses of outcomes with comorbidity and age (including comorbidity-age interactions) as well as relations between the different outcomes will be a major focus.Predictive modeling of disease progression will be the content of a follow-up analysis beyond this project's period, where we intend to use both disease biomarkers and the related risk factor markers for vascular comorbidities as predictors together with techniques from machine learning and algorithm-based data analyses.
The study has a confounder bias, as subjects with comorbidity will receive treatment as the standard of care at different time points.Comorbidity treatment initiated between the baseline and follow-up will be analyzed as potential confounders.The influence of confounders will be minimized by advanced biostatistical techniques, including confounder adjustment.

Discussion
Comorbidity refers to the total burden of any additional disease entity other than the specific index disease and may result from predisposing genetic or environmental factors or from treatment for IDDs.Comorbidity is prevalent among people with IDDs of the CNS, consistent with the rising prevalence of multimorbidity, estimated to affect approximately 40% of the European population.The prevalence of comorbidity not only signifies elevated mortality rates but also correlates with heightened healthcare resource utilization (17).Comorbidities may have decisive importance in terms of diagnosis, prognosis, and treatment effectiveness and safety.The scarcity of established modifiable risk factors for the burden of multimorbidity indicates that new knowledge is required to develop effective prevention and treatment strategies.
The COMMIT research program focuses on the three best-defined IDDs: MS, NMOSD, and MOGAD.NMOSD and MOGAD are antibody-associated diseases of the CNS.In NMOSD, an autoantibody targets the astrocyte water channel AQP4 and defines NMOSD as a primary astrocytopathy in AQP4-IgG-positive cases (60, 61).In MOGAD, an autoantibody targets myelin antigens, i.e., MOG, which is produced by oligodendrocytes and thus is involved in demyelination (62).MS is thought to be an autoimmune disease and to be a mainly myelin-directed disease although causative specificities have not been identified, and considerable overlap may occur between MS and MOGAD.The goal of the present study is to assess whether comorbidity has an impact on the levels of proinflammatory and neurodegenerative mediators and in practical terms whether they influence OCT and MRI parameters and is associated with clinical outcome.
In the COMMIT study, the patients with IDDs and comorbidity are the primary target group.This project advances the management of IDD patients with chronic comorbidities and may contribute to the pathogenesis of diseases.Identification of reliable biomarkers will allow evaluation of the impact of comorbidity on IDDs and enable early diagnosis and new therapeutic strategies.Our prospective multicenter study, which will be conducted over a 3-year follow-up period, aims to compile a detailed and systematic database for patients who exhibit various comorbid conditions.
A strength of the study is the multicenter design, with longitudinal, consecutive follow-up with sample collection and a uniform protocol.Given the exhaustive nature of the study protocol, it can be particularly challenging for individuals with disabilities.We will introduce a streamlined, standardized assessment to ease follow-ups.With an adequate sample size, our objective is to curtail the effects of confounding.

Conclusion
In conclusion, the intricate relationship between IDD and other chronic conditions represents an area for further research.The COMMIT study will address if the clinical and biochemical status of patients with MS, NMOSD, and MOGAD is affected by comorbid conditions.In addition, the study is cross-disciplinary, contributing to the characterization of disease mechanisms.The study will identify clinically relevant biomarkers, as well as address survival and quality of life.Recognizing the frequency and patterns of comorbidities and risk factors can be instrumental in developing preventive strategies.The results of the study are anticipated to have a strong and immediate impact on the perception and treatment of IDDs due to improvement in diagnostic and monitoring biomarkers.Shire; is an associate editor of Neurology: Neuroimmunology & Neuroinflammation; is an academic editor of PLoS ONE; consulted for Sanofi Genzyme, Biogen, MedImmune, Shire, and Alexion; received research support from Bayer, Novartis, Biogen, Teva, Sanofi-Aventis/Genzyme, Alexion, and Merck Serono; and received research support from the German Research Council, Werth Stiftung of the City of Cologne, German Ministry of Education and Research, Arthur Arnstein Stiftung Berlin, EU FP7 Framework Program, Arthur Arnstein Foundation Berlin, Guthy-Jackson Charitable Foundation, and NMSS.
The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.The author(s) declared that they were an editorial board member of Frontiers, at the time of submission.This had no impact on the peer review process and the final decision.

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FIGURE 1
FIGURE 1 Timeline of patient assessments and interventions in a clinical study spanning 36 months.
vascular endothelial growth factor-A.

TABLE 1
Inclusion and exclusion criteria.
Exclusion criteria are only considered at baseline, while dropout criteria are checked at each follow−up visit.

TABLE 2
Timeline of key assessments and measurements throughout the study period.

TABLE 2 Continued
*Further details can be found in the Method section.**Number of relapse(s) (a new or worsening acute neurologic symptom lasting ≥24 h and not explained by fever or infection).***Disabilityassessment with alteration in EDSS score of at least 0.5 from baseline at the clinical visits.-Allare relevant for healthy controls and are only assessed at the baseline visit.

TABLE 3
Overview of common comorbidities associated with MS, NMOSD, and MOGAD.

TABLE 4
Comorbidity: key terminology and definitions.