Identification of the SLAM Adapter Molecule EAT-2 as a Lupus-Susceptibility Gene That Acts through Impaired Negative Regulation of Dendritic Cell Signaling
Bibliographic record
Abstract
We showed previously that C57BL/6 congenic mice with an introgressed homozygous 70 cM (125.6 Mb) to 100 cM (179.8 Mb) interval on c1 from the lupus-prone New Zealand Black (NZB) mouse develop high titers of antinuclear Abs and severe glomerulonephritis. Using subcongenic mice, we found that a genetic locus in the 88-96 cM region was associated with altered dendritic cell (DC) function and synergized with T cell functional defects to promote expansion of pathogenic proinflammatory T cell subsets. In this article, we show that the promoter region of the NZB gene encoding the SLAM signaling pathway adapter molecule EWS-activated transcript 2 (EAT-2) is polymorphic, which results in an ∼ 70% reduction in EAT-2 in DC. Silencing of the EAT-2 gene in DC that lacked this polymorphism led to increased production of IL-12 and enhanced differentiation of T cells to a Th1 phenotype in T cell-DC cocultures, reproducing the phenotype observed for DC from congenic mice with the NZB c1 70-100 cM interval. SLAM signaling was shown to inhibit production of IL-12 by CD40L-activated DCs. Consistent with a role for EAT-2 in this inhibition, knockdown of EAT-2 resulted in increased production of IL-12 by CD40-stimulated DC. Assessment of downstream signaling following CD40 cross-linking in the presence or absence of SLAM cross-linking revealed that SLAM coengagement blocked activation of p38 MAPK and JNK signaling pathways in DC, which was reversed in DC with the NZB EAT-2 allele. We conclude that EAT-2 negatively regulates cytokine production in DC downstream of SLAM engagement and that a genetic polymorphism that disturbs this process promotes the development of lupus.
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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 | 0.000 |
| 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 | 0.001 |
| 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".