Blood-Based T-Cell Diagnosis of Celiac Disease
Bibliographic record
Abstract
Background & Aims Current diagnosis of celiac disease (CeD) is inaccurate in patients following a gluten-free diet (GFD). Blood-based diagnostics targeting gluten-specific T cells, like tetramer assays, are highly sensitive and specific but are impractical for clinical use. We evaluated the potential of a simple whole blood assay measuring interleukin-2 release (WBAIL-2) for detecting gluten-specific T cells to aid in CeD diagnosis. Methods WBAIL-2 was assessed in 181 adults; 88 with CeD (75 on GFD, 13 consuming gluten) and 93 controls (32 on GFD with non-celiac gluten sensitivity, 61 healthy). In vitro IL-2 release in whole blood after gluten peptide stimulation was measured. The assay's performance was compared to tetramer-based methods, and serum IL-2 levels were monitored before and after a single-dose gluten challenge. Correlations between IL-2 levels, tetramer+ T-cell frequencies, and symptoms were examined. Results The WBAIL-2 assay demonstrates high accuracy for CeD diagnosis, even in patients following a strict GFD. Optimized dual cut-offs in HLA-DQ2.5+ patients showed high sensitivity (90%) and specificity (95%), with lower sensitivity (56%) in HLA-DQ8+ CeD. WBAIL-2 correlated strongly with the frequency of tetramer+ gluten-specific CD4+ T cells and serum IL-2 levels after gluten challenge. Elevated WBAIL-2 levels predicted gluten-induced symptom severity, such as vomiting. The assay required only small blood volumes and performed comparably to tetramer-based methods. Conclusions Gluten-stimulated IL-2 secretion indicates the presence of pathogenic gluten-specific CD4+ T cells and is a useful diagnostic for CeD. WBAIL-2 and serum IL-2 after gluten could be complementary and allow biopsy-free CeD diagnosis. WBAIL-2 may help diagnose and monitor other CD4+ T cell-driven diseases.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".