A Role for <i>VAV1</i> in Experimental Autoimmune Encephalomyelitis and Multiple Sclerosis
Bibliographic record
Abstract
Multiple sclerosis, the most common cause of progressive neurological disability in young adults, is a chronic inflammatory disease. There is solid evidence for a genetic influence in multiple sclerosis, and deciphering the causative genes could reveal key pathways influencing the disease. A genome region on rat chromosome 9 regulates experimental autoimmune encephalomyelitis, a model for multiple sclerosis. Using interval-specific congenic rat lines and association of single-nucleotide polymorphisms with inflammatory phenotypes, we localized the gene of influence to Vav1, which codes for a signal-transducing protein in leukocytes. Analysis of seven human cohorts (12,735 individuals) demonstrated an association of rs2546133-rs2617822 haplotypes in the first VAV1 intron with multiple sclerosis (CA: odds ratio, 1.18; CG: odds ratio, 0.86; TG: odds ratio, 0.90). The risk CA haplotype also predisposed for higher VAV1 messenger RNA expression. VAV1 expression was increased in individuals with multiple sclerosis and correlated with tumor necrosis factor and interferon-gamma expression in peripheral blood and cerebrospinal fluid cells. We conclude that VAV1 plays a central role in controlling central nervous system immune-mediated disease and proinflammatory cytokine production critical for disease pathogenesis.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".