DOCK8 and STAT3 cooperate to restrain IgE-inducing T follicular helper cells
Bibliographic record
Abstract
Patients with loss-of-function DOCK8 or dominant-negative STAT3 variants have hyper-IgE syndrome, although only DOCK8 deficiency consistently presents with elevated food-specific IgE and symptomatic allergy. We previously found in mice that DOCK8 restricts the differentiation of IL-13+ T follicular helper (Tfh13) cells that drive anaphylactic IgE, although the mechanisms were unclear. Here, we show that DOCK8 promotes STAT3 activity, which inhibits GATA3 in T cells. However, only patients with DOCK8, but not STAT3, deficiency had elevated Tfh13 cells. Cell-specific deletion of either Dock8 (T-Dock8-/-) or Stat3 (T-Stat3-/-) augmented peanut-specific IgE and Tfh13s when oral sensitization was promoted by adjuvants. However, the phenotypes diverged during adjuvant-free oral peanut exposure: only T-Dock8-/- mice developed Tfh13 cells and peanut-specific IgE, accompanied by reduced Foxp3+ Tregs. Treg depletion in T-Stat3-/- mice unmasked Tfh13 induction to oral antigen alone. Thus, DOCK8 and STAT3 cooperate to restrain Tfh13 differentiation to food allergens, and additional Treg impairment in DOCK8 deficiency allows for Tfh13 cell induction and allergy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".