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Record W4412984063 · doi:10.1212/nxi.0000000000200457

Serum Levels of Aryl Hydrocarbon Receptor Plasma Agonist Activity Are Reduced in Patients With NMOSD and Correlate With Disease Activity

2025· article· en· W4412984063 on OpenAlexaff
Thanos Tsaktanis, Leander Ammon, Lena Lößlein, Anne Peter, Oliver Vandrey, Ulrike Naumann, Megan Behne, Lawrence J. Cook, Michael Levy, Michael R. Yeaman, Jeffrey L. Bennett, Veit Rothhammer

Bibliographic record

VenueNeurology Neuroimmunology & Neuroinflammation · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicToxic Organic Pollutants Impact
Canadian institutionsInstitute of Infection and Immunity
Fundersnot available
KeywordsAryl hydrocarbon receptorAgonistHydrocarbonDiseaseArylReceptorChemistryMedicineInternal medicinePharmacologyOrganic chemistryBiochemistry

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.005
GPT teacher head0.193
Teacher spread0.188 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2025
Admission routes1
Has abstractyes

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