Abstract
Background and Objectives
Neuromyelitis optica spectrum disorders (NMOSDs) are severe autoimmune diseases characterized by recurrent CNS inflammation and high risk of persistent disability. Effective disease monitoring is essential for timely intervention and relapse prevention. While biomarkers such as soluble glial fibrillary acidic protein and neurofilament light chain indicate astrocytic and neuronal damage, additional markers are needed to improve disease monitoring and treatment strategies. The ligand-activated transcription factor aryl hydrocarbon receptor (AHR) is a key immune regulator in autoimmune diseases such as multiple sclerosis, where its ligands correlate with disease activity. Given overlapping immunologic pathways, AHR signaling may also influence NMOSD pathophysiology. In this context, this study examines serum levels of AHR ligand in NMOSD, assessing their regulation and association with disease activity. Elucidating the role of AHR signaling may pave the way to explore novel markers of disease activity and therapeutic intervention in NMOSD.
Methods
AHR agonistic activity was assessed in the serum of 102 patients with aquaporin-4 antibody–positive NMOSD across various stages of the disease. As control, serum samples from 36 patients with noninflammatory diseases were evaluated for AHR agonistic activity. In addition, we measured AHR activity longitudinally in 10 individuals at 3 distinct time points—during a quiescent phase preceding relapse, at relapse, and during a postrelapse quiescent phase—to evaluate the dynamic changes in AHR activity over time.
Results
Serum AHR agonistic activity was globally decreased in the NMOSD cohort compared with the control group. AHR agonistic activity was further reduced during or near relapses. Finally, we conducted longitudinal analyses on individual serum samples obtained from patients with NMOSD. Our findings reveal that AHR activity significantly decreases during the relapse phase compared with the quiescent phase, with a subsequent recovery after relapse.
Discussion
Serum AHR agonistic activity is reduced in patients with NMOSD compared with controls and further modulated in temporal vicinity to a relapse. Furthermore, our longitudinal analysis confirmed that AHR activity is markedly reduced during relapse, underscoring its dynamic modulation in relation to disease activity. AHR agonist activity might represent a potential tool to monitor disease activity and develop novel therapeutic strategies.
Classification of Evidence
This study provides Class III evidence that serum levels of AHR agonistic activity are reduced in patients with NMOSD compared with noninflammatory controls, and that these levels are further modulated across different stages of the disease.
Introduction
In neuromyelitis optica spectrum disorders (NMOSDs), monitoring disease course and preventing relapses are of paramount importance.1 As disease activity increases the risk of permanent disability, early initiation of disease-modifying therapies as well as monitoring of disease activity is imperative.2 Current candidate markers of disease activity include soluble glial fibrillary acidic protein (sGFAP) and neurofilament light chain, which correlate with disease activity and neuronal injury, respectively.3,4
In our previous work, we have observed that ligands to the aryl hydrocarbon receptor (AHR) are decreased in multiple sclerosis (MS) and modulated over the disease course, acting on both peripheral and central cellular components of the immune system. Indeed, modulating AHR agonists might represent a potential route to monitor disease and potentially mitigate inflammatory and degenerative components in MS.5,6 In this context, we were able to correlate serum levels of AHR agonists with disease activity. Mechanistically, tryptophan-derived metabolites generated by the gut flora are capable of crossing the blood-brain barrier to modulate astrocyte and microglial type 1 interferon–induced expression of AHR, suggesting a connection between dietary habits, the microbiome, and inflammatory activity in MS.7,8 While the regulation of AHR ligands in NMOSD has yet to be explored, the relationship between heightened interferon signaling and NMOSD disease activity in animal models and clinical cases suggests that AHR signaling may also affect the course of NMOSD.9-11
Because there are numerous AHR ligands with both inhibitory and agonistic functions, our aim was to measure the overall AHR agonistic activity, which reflects the combined effect of these ligands on the AHR signaling network, as previously described.5,12,13 This approach allowed us to assess the net AHR activation, accounting for the complex interactions of both agonistic and inhibitory effects within the biological system.
In this context, we have determined the regulation of AHR ligand levels in patients with NMOSD as well as their modulation over the course of the disease.
Methods
Primary Research Questions
This study provides Class III evidence that serum levels of AHR agonistic activity are reduced in patients with NMOSD compared with noninflammatory controls, and that these levels are further modulated across different stages of the disease.
Biospecimens and Associated Clinical Data
Patient serum samples and clinical data were collected and provided by the CIRCLES Study Group.14 No CSF samples were available for the assessment of AHR agonistic activity in this study.
We included patients diagnosed with AQP4-IgG–positive neuromyelitis optica spectrum disorder (NMOSD, n = 102) and individuals with noninflammatory neurologic conditions (n = 36). The control group included individuals with noninflammatory neurologic disorders, such as idiopathic intracranial hypertension (pseudotumor cerebri) or primary headache disorders. In addition, we measured AHR activity in 10 individuals at 3 distinct time points—during a quiescent phase preceding relapse, at relapse or near, and during a postrelapse quiescent phase—to assess the dynamic changes in AHR activity. Relapse events were defined as the onset of new or worsening NMOSD-related symptoms, confirmed by a trained neurologist from the CIRCLES Group. The relapse period encompassed the window from 30 days before to 30 days after symptom onset. Given that a universally accepted definition of relapse is lacking in routine clinical practice outside formal trials, our method integrated both subjective clinical assessments and objective indicators such as the appearance of new or worsening NMOSD-related symptoms. Samples and clinical data were collected from patients either during a relapse or within <30 days of its onset.14
For every relapse, we documented comprehensive details including the exact onset date, clinical symptoms, presumed lesion location, and treatment interventions (e.g., IV steroids, plasma exchange, or IV immunoglobulin), which were given after blood sampling. Symptom information was self-reported by patients and, where possible, cross-validated with contemporaneous medical records. The onset date was precisely recorded based on confirmation from medical documentation or patient diaries.
Symptoms were assigned to specific lesion sites based on established clinical criteria. For instance, motor, sensory, bladder, and limb pain symptoms were attributed to spinal cord lesions unless accompanied by brainstem or cerebral signs; limb symptoms with ataxia, vestibular disturbances, or cranial nerve abnormalities were considered indicative of brainstem or cerebellar involvement. Visual disturbances were linked to lesions in the optic nerve, chiasm, or tracts unless concurrent brainstem signs suggested otherwise. In this study, we defined the relapse period as the 30-day interval beginning 30 days before the onset of clinical symptoms and extending to 30 days after symptom onset, during which additional specimen sampling was performed. Patients sampled between 30 and 90 days before relapse onset were categorized as belonging to the “near-relapse” group, reflecting a period during which subclinical disease activity might be present. This classification scheme was chosen in line with current clinical standards, wherein a new attack is recognized only if it occurs more than 30 days after the previous episode. To further explore the potential for subclinical disease activity preceding overt clinical relapses, an exploratory analysis was conducted using an extended 90-day window for both the pre-relapse and postrelapse phases. This additional stratification aimed to differentiate pre-relapse immunologic changes—potentially indicative of subclinical activity—from postrelapse residual inflammatory activity. However, the primary analysis remained focused on the 30-day definitions because these are more consistently supported by existing clinical practice and the available data set.
The annualized relapse rate (ARR) was calculated using negative binomial regression models. For 10 patients, we obtained longitudinal data sets capturing measurements during the late phase preceding a relapse and during the relapse itself.
Additional demographic and clinical characteristics of the study participants are summarized in eTables 1 and 2.
AHR Agonistic Activity Measurement
To measure AHR agonistic activity, we used a transient transfection system using HEK293 cells as previously described.5,12 In brief, we plated 20,000 cells per well in 96-well flat bottom plates. After 24 hours, cells were transfected with equal amounts of pGud-Luc (35) and pTK-Renilla (Renilla luciferase under the control of constitutively active thymidine kinase promoter, Promega) using FuGene-HD Transfection Reagent (Promega) following the manufacturer's recommendations. The transfected cells were then incubated with Dulbecco’s Modified Eagle Medium supplemented with 10% of patient serum in duplicate. After 24 hours, we analyzed luciferase activity using the Dual Luciferase Reporter System (Promega) and normalized firefly luciferase activity to Renilla luciferase activity to determine the relative AHR agonistic activity.
Statistical Analysis
Statistical analysis was conducted using Prism software (GraphPad Prism 8.4, San Diego, CA). AHR agonistic activity was assessed in serum samples from patients with noninflammatory disease (controls; n = 36) and patients with AQP4-IgG–seropositive NMOSD (n = 102). Because the data did not follow a normal distribution, as confirmed by the D'Agostino-Pearson normality test, nonparametric tests were applied. Values represent the median of technical duplicate measurements, with lines indicating the median and error bars showing the interquartile range. To assess statistical significance, the Mann-Whitney U test was used. In addition, all p values were corrected for multiple comparisons using the Dunn multiple comparison test.
Standard Protocol Approvals, Registrations, and Patient Consents
The study protocol and sample collection were approved by the respective ethics committees and local regulatory authorities.
Data Availability
Anonymized data that are not published in this article will be made available on request from any qualified investigator.
Results
Serum AHR Agonistic Activity Is Decreased in Patients With NMOSD
Serum AHR agonistic activity was measured in 102 patients with AQP4-IgG–seropositive NMOSD and 36 individuals with noninflammatory disease using a luciferase-based reporter assay (eTable 1). Compared with controls, AHR agonistic activity was reduced in the NMOSD cohort (Figure 1). Notably, AHR ligand levels were not influenced by age, sex, the use of immunosuppressive treatments, or race and ethnicity (eFigure 1 A–D).
Figure 1. AHR Agonistic Activity Is Decreased in Patients With NMOSD.
AHR agonistic activity was assessed in serum samples from patients with noninflammatory disease (controls; n = 36) and those with AQP4-IgG seropositive NMOSD (n = 102). Values represent the median of technical duplicate measurements, with lines indicating the median and error bars showing the interquartile range (IQR). Statistical significance was determined using the Mann-Whitney U test (****p < 0.0001). AHR = aryl hydrocarbon receptor; NMOSD = neuromyelitis optica spectrum disorder.
Serum AHR Agonistic Activity Is Dynamic Over NMOSD Disease Stages
We assessed AHR agonistic activity in patients at 3 distinct stages of disease (Figure 2A): (1) during the relapse, characterized by the emergence of acute clinical symptoms necessitating therapeutic intervention and encompassing the period within 30 days before or after symptom onset; (2) nearing a relapse, defined as the interval between 30 and 90 days before relapse onset, reflecting a phase of potential subclinical disease activity; and (3) remission, defined as a stable phase of disease activity occurring more than 90 days before or after a relapse event. These patient groups were compared with the control group. In these analyses, AHR agonistic activity was further reduced during or shortly before a relapse compared with the levels observed during the remission phase (Figure 2B).
Figure 2. AHR Agonistic Activity Is Modulated Over the Disease Course in Patients With NMOSD.
(A) Schematic overview illustrating the definition of disease stages relative to relapse onset. (B) AHR agonistic activity was measured in serum samples from patients with noninflammatory neurologic diseases (controls; n = 36) and from patients with AQP4-IgG–seropositive NMOSD across 3 clinical stages: (1) near relapse (n = 40), defined as the interval between 30 and 90 days before relapse onset, representing a phase of potential subclinical disease activity; (2) relapse (n = 18), defined as the period spanning 30 days before to 30 days after the onset of a clinically confirmed relapse; and (3) remission (n = 44), defined as a stable phase of disease activity occurring more than 90 days before or after a relapse event. Values represent the median of duplicate measurements, with lines indicating the median and interquartile range (IQR). Statistical significance was assessed using a nonparametric Kruskal-Wallis test with the Dunn multiple comparison test for correction of multiple comparisons. Significance levels: ****p < 0.0001, **p < 0.001, *p < 0.01, n.s. = nonsignificant. AHR = aryl hydrocarbon receptor; NMOSD = neuromyelitis optica spectrum disorder.
Correlation of Serum AHR Agonistic Activity With Relapse Rate
Linear regression analysis revealed a negative correlation between AHR agonistic activity and ARR in the NMOSD cohort (Figure 3A). Longitudinal serum samples from 10 patients (eTable 2) at 3 time points (pre-relapse, relapse/near relapse, and postrelapse) demonstrated intraindividual fluctuations in AHR activity. Seven of 10 patients exhibited decreased AHR activity during relapse or near relapse compared with quiescent phases, whereas 3 did not show a consistent pattern (Figure 3, B and C).
Figure 3. Serum AHR Agonistic Activity Is Negatively Correlated With Relapse Rate.
(A) Solid line shows linear regression with correlation of AHR agonistic activity and annual relapse rate as determined using negative binomial models in patients with NMOSD (n = 102). Values represent the median of technical duplicate measurements. Numbers indicated R and p value of linear regression analysis. p < 0.05 is considered as statistically significant. (B and C) Serial analysis of AHR agonistic activity in 10 individual patients. Measurements were obtained during a quiescent phase preceding relapse, at relapse or near, and in the postrelapse phase. AHR = aryl hydrocarbon receptor; NMOSD = neuromyelitis optica spectrum disorder.
Discussion
Innovative approaches are required to identify specific biological indicators of disease activity in NMOSD, as well as to develop novel treatments. AHR, a ligand-activated transcription factor that modulates immune reactions, holds significance in the pathogenesis of autoimmune diseases.15 These include inflammatory bowel disease and MS.5,12,13 AHR agonists, which are required for the activation of the ligand-activated transcription factor AHR, contribute to the control of CNS inflammation through peripheral and CNS-intrinsic effects.7 In this context, AHR agonists are produced by the interplay between the gut microbiome and host metabolism. We and others have previously shown that AHR agonists cross the blood-brain barrier, diminishing CNS inflammation through the activation of AHR in both astrocytes and microglia.7 We have also documented decreased AHR activity within MS brain lesions and have identified a correlation of serum AHR ligand levels with both disease stage and activity in patients with MS.12
While both role and regulation of AHR ligand levels have not been explored in NMOSD, their immune modulatory actions suggest a potential impact on disease activity in NMOSD. In addition, discerning the role of AHR anti-inflammatory activity in NMOSD might shed light on the significance of environmental factors and the microbiome in NMOSD. In this study, we examined AHR agonist activity levels in patients with NMOSD during remission, relapse, and convalescence stages of the disease, aiming to evaluate the relationship between AHR-controlled mechanisms and disease activity. By doing so, we used an established luciferase-based assay that has been widely used in previous studies and validated across different experimental settings.7,13 Given our previous data in MS,5,12 we anticipated that levels of AHR ligands might correlate with the presence of disease and even reflect NMOSD disease activity. Indeed, we found decreased activity of the AHR ligands in patients with NMOSD relative to controls. Moreover, during or near a relapse, AHR ligand activity was further decreased compared with its reduced baseline levels during stable phases of the disease.
AHR plays an important role in the control of the adaptive immune response. It is important to note that it controls differentiation and activity of specific B-cell populations.16 Because seropositive NMOSD includes antibody-mediated B cell–driven aspects of the disease, AHR activity may affect the activation state of B cells. Indeed, AHR has been identified as a key regulatory factor that integrates environmental, dietary, and microbial signals into innate and adaptive immune responses during B-cell responses.16-18 While this might be a causal mechanism linking AHR ligand levels to disease activity in NMOSD, further exploration in mechanistic studies assessing antibody titers, B-cell activation, and plasma cell states is warranted. It is important to note that constitutive AHR signaling has been shown to constrain type I interferon–mediated responses.19 Type I interferon activity plays a critical role in immune regulation, and dysregulation of this pathway has been implicated in autoimmune diseases, including NMOSD. Indeed, type I interferon treatment in neuromyelitis optica has been implicated in disease relapse or exacerbation, in relation to elevated aquaporin-4 antibody titers and increased Th17 pathway cytokines.20 While type I interferons, such as interferon beta, are known to activate AHR pathways and exert anti-inflammatory effects in certain contexts, clinical outcomes observed in patients with NMOSD indicate a paradoxical response.20 Specifically, despite potential AHR activation, interferon beta treatment is associated with increased relapse rates and AQP4 antibody titers, suggesting that other immunologic mechanisms may override the anti-inflammatory effects of AHR activation in this setting. Given that type I interferons counter-regulate type II interferons (interferon gamma), a plausible explanation may be that type I interferons de-repress Th17 inflammation and promote NMOSD disease activity.
Our observation of decreased AHR agonist activity in NMOSD, particularly during relapses, aligns with the hypothesis that impaired AHR signaling may contribute to heightened disease activity. It is possible that exogenous AHR activation through type I interferons does not confer clinical benefit in NMOSD because of disease-specific immune dysregulation or distinct effects on pathogenic astrocyte responses.
These complexities underscore the need for a deeper mechanistic understanding of AHR modulators and their role in NMOSD. Future investigations should focus on elucidating context-specific AHR responses and the cell type–specific effects that may reconcile these seemingly contradictory findings. Moreover, reduced AHR activity observed during relapse phases in NMOSD may reflect a mechanism of mitigating heightened inflammatory responses, including type I interferon–driven activity, thereby contributing to disease modulation. The results are supported by an analysis of most of the individual patients monitored longitudinally. In these cases, the outcomes were not unequivocal, indicating that multiple factors may contribute to the developmental process. Nevertheless, they reinforce the cross-sectional findings of an increased AHR agonistic activity. This mechanistic link not only positions AHR as a key regulator of immune activity but also highlights its potential as a biomarker of ongoing inflammation and disease activity in NMOSD. Exploring this relationship further through mechanistic studies may clarify the role of AHR in the immune pathogenesis of NMOSD and strengthen its therapeutic implications.
Several limitations need to be taken into account within our study. First and foremost, although we detected effects on AHR ligand level modulations in NMOSD, these observations need to be confirmed in larger patient cohorts and in comparison with other CNS inflammatory diseases. Furthermore, validation in larger longitudinal samples collected from individual patients over the course of the disease is necessary to strengthen these observations. Moreover, future studies should incorporate correlations with additional serologic markers, such as NFL and GFAP, alongside corroborative imaging data, to further validate and strengthen these observations. Second, influence of disease-modifying therapies on AHR ligand stability, its generation, and metabolism needs to be assessed in the future. Third, mechanistic studies are needed to examine the underlying mechanisms causing the reduction of AHR ligand levels in NMOSD, focusing on microbiome composition and influence of disease-modifying therapies, among others. This is particularly noteworthy because the variability observed within the stable group and among individual patients likely reflects the inherent heterogeneity of immune activity during clinically quiescent phases, as well as the multifactorial regulation of the AHR signaling pathway. Consistent with this notion, in the analysis correlating serum AHR agonistic activity and relapse rate, a few individual outliers were identified. These deviations likely represent underlying biological and clinical variability among patients with NMOSD. Nevertheless, the overall trend demonstrated a robust and statistically significant inverse relationship between serum AHR agonistic activity and relapse frequency, supporting the validity and relevance of our findings. Finally, the results of the current studies were derived from 1 cohort of patients participating in the CIRCLES Study performed in North America before the advent of regulatory-approved therapies. Findings herein will benefit from validation in comparison with other cohorts from geographically diverse regions.
We acknowledge that the absence of paraclinical parameters such as imaging findings or biomarkers such as sGFAP and NfL limits our ability to more precisely correlate AHR activity with subclinical disease activity. Indeed, while our findings suggest a potential role for AHR agonistic activity as a biomarker, additional studies incorporating paraclinical markers and validation in diverse cohorts are necessary to assess clinical utility.
Together, our study provides initial evidence that serum AHR agonistic activity is decreased in patients with NMOSD. Future studies need to solidify whether AHR ligand levels might be of relevance as a marker of disease activity or even point to future research avenues including microbiome studies on patients with NMOSD, treatment-specific effects relevant to AHR signaling, and potentially novel therapeutic approaches.
Glossary
- AHR
aryl hydrocarbon receptor
- ARR
annualized relapse rate
- MS
multiple sclerosis
- NMOSD
neuromyelitis optica spectrum disorder
- sGFAP
soluble glial fibrillary acidic protein
Appendix. Coinvestigators
| Name | Location | Role | Contribution |
| Lilyana Amezcua, MD | Department of Neurology, Keck School of Medicine, University of Southern CA, Los Angeles | Site investigator | Collected study data and biospecimens and reviewed and revised the manuscript for intellectual content |
| Jacinta M. Behne, MA | The Guthy-Jackson Charitable Foundation, Beverly Hills, CA | Site investigator | Collected study data and biospecimens and reviewed and revised the manuscript for intellectual content |
| Megan K. Behne | The Guthy-Jackson Charitable Foundation, Beverly Hills, CA | Site investigator | Collected study data and biospecimens and reviewed and revised the manuscript for intellectual content |
| Jeffrey L. Bennett | Departments of Neurology and Ophthalmology, University of Colorado School of Medicine, Aurora, CO | Site investigator | Collected study data and biospecimens and reviewed and revised the manuscript for intellectual content |
| Robert E. Boone IV, MB | University of Utah School of Medicine, Salt Lake City, UT | Site investigator | Collected study data and biospecimens and reviewed and revised the manuscript for intellectual content |
| Robert L. Carruthers, MD | Department of Medicine and Neurology, University of British Columbia, Vancouver BC, Canada | Site investigator | Collected study data and biospecimens and reviewed and revised the manuscript for intellectual content |
| Tanuja Chitnis, MD | Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA | Site investigator | Collected study data and biospecimens and reviewed and revised the manuscript for intellectual content |
| Lawrence J. Cook PhD | University of Utah School of Medicine, Salt Lake City, UT | Site investigator | Collected study data and biospecimens and reviewed and revised the manuscript for intellectual content |
| May H. Han, MD | Department of Neurology and Neurological Sciences, Division of Neuroimmunology and Multiple Sclerosis Center, Stanford University, Stanford, CA | Site investigator | Collected study data and biospecimens and reviewed and revised the manuscript for intellectual content |
| Ilya Kister, MD | NYU Langone Health, NY | Site investigator | Collected study data and biospecimens and reviewed and revised manuscript for intellectual content |
| Michael Levy, MD, PhD | Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA | Site investigator | Collected study data and biospecimens and reviewed and revised the manuscript for intellectual content |
| Sarah M. Planchon, PhD | Mellen Center for MS Treatment and Research, Neurological Institute, Cleveland Clinic, Cleveland, OH | Site investigator | Collected study data and biospecimens and reviewed and revised the manuscript for intellectual content |
| Claire S. Riley, MD | Department of Neurology, Columbia University Medical Center, NY | Site investigator | Collected study data and biospecimens and reviewed and revised the manuscript for intellectual content |
| Ben Thrower, MD | Shepherd Center, Atlanta, GA | Site investigator | Collected study data and biospecimens and reviewed and revised the manuscript for intellectual content |
| Anthony Traboulsee, MD | Department of Medicine and Neurology, University of British Columbia, Vancouver BC, Canada | Site investigator | Collected study data and biospecimens and reviewed and revised the manuscript for intellectual content |
| Michael Waltz, MAS | University of Utah School of Medicine, Salt Lake City, UT | Site investigator | Collected study data and biospecimens and reviewed and revised the manuscript for intellectual content |
Contributor Information
for the Guthy-Jackson Charitable Foundation CIRCLES Study Group:
Lilyana Amezcua, Jacinta M. Behne, Megan K. Behne, Jeffrey L. Bennett, Robert E. Boone, IV, Robert L. Carruthers, Tanuja Chitnis, Lawrence J. Cook, May H. Han, Ilya Kister, Michael Levy, Sarah M. Planchon, Claire S. Riley, Ben Thrower, Anthony Traboulsee, and Michael Waltz
Author Contributions
T. Tsaktanis: drafting/revision of the manuscript for content, including medical writing for content; major role in the acquisition of data; analysis or interpretation of data. L. Ammon: drafting/revision of the manuscript for content, including medical writing for content; analysis or interpretation of data. L. Lößlein: drafting/revision of the manuscript for content, including medical writing for content. A. Peter: drafting/revision of the manuscript for content, including medical writing for content. O. Vandrey: drafting/revision of the manuscript for content, including medical writing for content. U.J. Naumann: major role in the acquisition of data. M. Behne: drafting/revision of the manuscript for content, including medical writing for content. L.J. Cook: drafting/revision of the manuscript for content, including medical writing for content. M. Levy: drafting/revision of the manuscript for content, including medical writing for content. M.R. Yeaman: drafting/revision of the manuscript for content, including medical writing for content; study concept or design; analysis or interpretation of data. J.L. Bennett: drafting/revision of the manuscript for content, including medical writing for content; study concept or design; analysis or interpretation of data. V. Rothhammer: drafting/revision of the manuscript for content, including medical writing for content; study concept or design; analysis or interpretation of data.
Study Funding
This study was funded by German Research Council Deutsche Forschungsgemeinschaft (DFG)(RO4866-3/1, RO4866-4/1) and European Research Council (851,693 HB-EGF in CNS inflammation [HICI]). T. Tsaktanis was funded by the Interdisziplinäres Zentrum für Klinische Forschung. T. Tsaktanis received a SEED fellowship provided by the Disease-related Competence Network Multiple Sclerosis (Krankheitsbezogenes Kompetenznetz Multiple Sklerose, KKNMS). V. Rothhammer was supported by a Heisenberg fellowship and Sachmittel support provided by the German Research Foundation (Deutsche Forschungsgemeinschaft, DFG, Project ID 401772351, grant nos. RO4866-1/1, 2/-1, 3/1, 4/1, 5/1, 6/1) as well as by transregional and collaborative research centers funded by the German Research Foundation (DFG, Project ID 408885537-TRR274, Project ID 261193037-CRC1181, Project ID 270949263-GRK2162, Project ID 405969122-FOR2886, Project ID 505539112-GB.com) and by a European Research Council Starting Grant by the European Research Council (HICI 851693). J.L. Bennett was supported by a grant from the National Eye Institute (NEI R01EY022936). The CIRCLES biorepository biospecimens and associated clinical metadata used in this study were supported by The Guthy-Jackson Charitable Foundation.
Disclosure
The authors report no relevant disclosures. Go to Neurology.org/NN for full disclosures.
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Associated Data
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Data Availability Statement
Anonymized data that are not published in this article will be made available on request from any qualified investigator.