Distinction and Temporal Stability of Conformational Epitopes on Myelin Oligodendrocyte Glycoprotein Recognized by Patients with Different Inflammatory Central Nervous System Diseases
Bibliographic record
Abstract
Autoantibodies targeting conformationally intact myelin oligodendrocyte glycoprotein (MOG) are found in different inflammatory diseases of the CNS, but their antigenic epitopes have not been mapped. We expressed mutants of MOG on human HeLa cells and analyzed sera from 111 patients (104 children, 7 adults) who recognized cell-bound human MOG, but had different diseases, including acute disseminated encephalomyelitis (ADEM), one episode of transverse myelitis or optic neuritis, multiple sclerosis (MS), anti-aquaporin-4 (AQP4)-negative neuromyelitis optica (NMO), and chronic relapsing inflammatory optic neuritis (CRION). We obtained insight into the recognition of epitopes in 98 patients. All epitopes identified were located at loops connecting the β strands of MOG. The most frequently recognized MOG epitope was revealed by the P42S mutation positioned in the CC'-loop. Overall, we distinguished seven epitope patterns, including the one mainly recognized by mouse mAbs. In half of the patients, the anti-MOG response was directed to a single epitope. The epitope specificity was not linked to certain disease entities. Longitudinal analysis of 11 patients for up to 5 y indicated constant epitope recognition without evidence for intramolecular epitope spreading. Patients who rapidly lost their anti-MOG IgG still generated a long-lasting IgG response to vaccines, indicating that their loss of anti-MOG reactivity did not reflect a general lack of capacity for long-standing IgG responses. The majority of human anti-MOG Abs did not recognize rodent MOG, which has implications for animal studies. Our findings might assist in future detection of potential mimotopes and pave the way to Ag-specific depletion.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".