Determinants of Gliadin-Specific T Cell Selection in Celiac Disease
Bibliographic record
Abstract
In HLA-DQ8-associated celiac disease (CD), the pathogenic T cell response is directed toward an immunodominant α-gliadin-derived peptide (DQ8-glia-α1). However, our knowledge of TCR gene usage within the primary intestinal tissue of HLA-DQ8 (+) CD patients is limited. We identified two populations of HLA-DQ8-glia-α1 tetramer(+) CD4(+) T cells that were essentially undetectable in biopsy samples from patients on a gluten-free diet but expanded rapidly and specifically after antigenic stimulation. Distinguished by expression of TRBV9, both T cell populations displayed biased clonotypic repertoires and reacted similarly against HLA-DQ8-glia-α1. In particular, TRBV9 paired most often with TRAV26-2, whereas the majority of TRBV9(-) TCRs used TRBV6-1 with no clear TRAV gene preference. Strikingly, both tetramer(+)/TRBV9(+) and tetramer(+)/TRBV9(-) T cells possessed a non-germline-encoded arginine residue in their CDR3α and CDR3β loops, respectively. Comparison of the crystal structures of three TRBV9(+) TCRs and a TRBV9(-) TCR revealed that, as a result of distinct TCR docking modes, the HLA-DQ8-glia-α1 contacts mediated by the CDR3-encoded arginine were almost identical between TRBV9(+) and TRBV9(-) TCRs. In all cases, this interaction centered on two hydrogen bonds with a specific serine residue in the bound peptide. Replacement of serine with alanine at this position abrogated TRBV9(+) and TRBV9(-) clonal T cell proliferation in response to HLA-DQ8-glia-α1. Gluten-specific memory CD4(+) T cells with structurally and functionally conserved TCRs therefore predominate in the disease-affected tissue of patients with HLA-DQ8-mediated CD.
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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) | 0.001 | 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".