The Co-inhibitor BTLA Is Functional in ANCA-Associated Vasculitis and Suppresses Th17 Cells
Bibliographic record
Abstract
Objectives: The activation and inhibition of T-cells has been well studied under physiological conditions. Co-inhibition is an important mechanism to keep effector T-cells in check. Co-inhibitors mediate peripheral self-tolerance and limit the immune response. Dysfunctional co-inhibition is associated with loss of T-cell regulation and induction of autoimmunity. Therefore, we investigated the co-inhibitor B- and T-Lymphocyte attenuator (BTLA) in ANCA-associated vasculitis (AAV). Methods: 56 AAV patients and 32 healthy controls (HC) were recruited. Flow cytometry was performed to investigate the expression of BTLA on T-cells. Double negative T-cells were defined as CD3+CD4-CD8-. To assess the functionality of BTLA, CFSE-labelled T-cells were stimulated in presence or absence of an agonistic anti-BTLA antibody. In addition, impact of BTLA-mediated co-inhibition on Th17 cells was studied. Results: AAV patients in remission had a decreased expression of BTLA on double negative T-cells (CD3+CD4-CD8-). On all other subtypes of T-cells, expression of BTLA was comparable to healthy controls. TCR-independent stimulation of T-cells resulted in down-regulation of BTLA on Th cells in AAV and HC, being significantly lower in HC. Co-inhibition via BTLA led to suppression of T-cell proliferation in AAV as well as in HC. As a result of BTLA mediated co-inhibition, Th17 cells were suppressed to the same extent in AAV and HC. Conclusion: BTLA expression is altered on double negative T-cells but not on other T-cell subsets in AAV. BTLA-induced co-inhibition has the capacity to suppress Th17 cells and is functional in AAV. Thus, BTLA-mediated co-inhibition might be exploited for future targeted therapies in AAV.
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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 | 0.000 |
| 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".