<i>IRAK-4</i> Mutation (Q293X): Rapid Detection and Characterization of Defective Post-Transcriptional TLR/IL-1R Responses in Human Myeloid and Non-Myeloid Cells
Bibliographic record
Abstract
Innate immunodeficiency has recently been reported as resulting from the Q293X IRAK-4 mutation with consequent defective TLR/IL-1R signaling. In this study we report a method for the rapid allele-specific detection of this mutation and demonstrate both cell type specificity and ligand specificity in defective IL-1R-associated kinase (IRAK)-4-deficient cellular responses, indicating differential roles for this protein in human PBMCs and primary dermal fibroblasts and in LPS, IL-1beta, and TNF-alpha signaling. We demonstrate transcriptional and post-transcriptional defects despite NF-kappaB signaling and intact MyD88-independent signaling and propose that dysfunctional complex 1 (IRAK1/TRAF6/TAK1) signaling, as a consequence of IRAK-4 deficiency, generates specific defects in MAPK activation that could underpin this patient's innate immunodeficiency. These studies demonstrate the importance of studying primary human cells bearing a clinically relevant mutation; they underscore the complexity of innate immune signaling and illuminate novel roles for IRAK-4 and the fundamental importance of accessory proinflammatory signaling to normal human innate immune responses and immunodeficiencies.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".