A potential novel genetic etiology of autoimmune encephalopathy
Bibliographic record
Abstract
Background: Encephalitis refers to inflammation of the brain parenchyma, which frequently leads to significant morbidity and mortality. A specific cause is identified in only half of the cases, with viral and autoimmune origins being the most common. In the remaining cases, the cause of encephalitis often remains unknown. Rare genetic conditions manifesting as encephalitis have been identified. Interferon regulatory factor 3 (IRF3) is a key transcription regulator involved in cellular responses, playing an essential role in innate immunity. However, IRF3 may also contribute to harmful immune responses, such as those seen in proinflammatory and autoimmune diseases. Several genetic variants or single nucleotide polymorphisms within IRF genes have been found at higher frequencies in patients with autoimmune diseases compared to healthy controls, suggesting a link to either increased risk or protection against these diseases. Methods: Our patient’s medical record was analyzed retrospectively, including his medical history, as well as results from immune laboratory tests and genetic analyses. Results: We present a 19-year-old male with autoimmune encephalopathy. Whole exome sequencing analysis revealed a novel heterozygous variant in the IRF3 gene (NM_001571.6), c.910G>A resulting in p.Gly304Arg. Conclusion: The presence of IRF3 mutations may lead to the development of autoimmune encephalopathy. Statement of Novelty: We have identified a novel variant in the IRF3 gene in a patient with autoimmune encephalopathy.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".