Defining the role of systemic autoimmune markers in adult epilepsy: A focus on autoimmune‐associated epilepsy
Bibliographic record
Abstract
OBJECTIVE: Autoimmune mechanisms are a recognized cause of adult epilepsy, with immunotherapy offering etiology-specific treatment. Autoimmune-associated epilepsy is an emerging clinical entity, for which early diagnosis remains challenging and largely depends on neuronal antibody testing. This study investigates the utility of serum systemic autoantibodies as surrogate markers for positive neuronal antibodies and their potential in predicting epilepsy outcomes. METHODS: We retrospectively enrolled adult epilepsy patients, excluding those with prior autoimmune diseases. All patients had baseline laboratory data, including ESR, ANA, and anti-ENA. Further immunological evaluations included serum or CSF studies for systemic or neuronal autoantibodies. We compared the prevalence of systemic autoantibodies, seizure patterns, and EEG characteristics across immune, other, and unknown etiological groups and assessed epilepsy outcomes based on autoimmune comorbidities and systemic autoantibody presence. RESULTS: Among 333 patients (immune = 12, other = 122, unknown = 199), autoimmune-associated epilepsy showed higher rates of status epilepticus (41.7% vs. 0.5% vs. 2.5%, p < 0.001), multifocal epileptogenicity (41.7% vs. 9.1% vs. 8.2%, p < 0.01), ≥2 anti-seizure medications (83.3% vs. 28.6% vs. 43.4%, p < 0.001), and a worse seizure outcome. Systemic autoantibodies were prevalent across subgroups (27.6%-41.7%), and autoimmune comorbidities were newly diagnosed in 5.5%-9.8% of cases, but no differences were observed across groups. The prevalence of antiphospholipid syndrome (2.1%) and Sjögren's syndrome (1.5%) was high in our study cohort. Neither autoimmune comorbidities nor systemic autoantibodies correlated with seizure types, EEG patterns, seizure frequency, number of ASMs, or outcomes. SIGNIFICANCE: Autoantibody testing contributes to unexpectedly high rates of new rheumatological diagnoses following epilepsy, often preceding systemic symptoms. However, systemic autoantibodies cannot reliably predict epilepsy characteristics or outcomes. Multifocal epileptogenicity on EEG and high seizure burden may be characteristic features in autoimmune-associated epilepsy. These findings suggest that adult epilepsy patients should benefit from a tiered approach to immunological evaluation. PLAIN LANGUAGE SUMMARY: Autoimmune causes of epilepsy are increasingly recognized, and some patients may benefit from immunotherapy in addition to standard anti-seizure drugs. We retrospectively analyzed adult epilepsy patients by underlying cause and examined their clinical features, EEG findings, and blood tests for systemic autoantibodies. In our study, although these systemic autoantibodies were prevalent, they did not help predict seizure type, EEG pattern, or treatment outcome. However, we found that patients with seizure activity coming from several parts of the brain or frequent, hard-to-control seizures may have autoimmune-associated epilepsy and could benefit from advanced immune evaluation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".