Clinical IRAK4 deficiency caused by homozygosity for the novel <i>IRAK4</i> (c.1049delG, p.Gly350Glufs*15) variant
Bibliographic record
Abstract
The innate immune system allows for rapid recognition of pathogens. Toll-like receptor (TLR) signaling is a key aspect of the innate immune response, and interleukin-1 receptor-associated kinase 4 (IRAK4) plays a vital role in the TLR signaling cascade. Each TLR recognizes a distinct set of pathogen-associated molecular patterns (PAMPs) that encompass conserved microbial components such as lipopolysaccharides and flagellin. Upon binding of PAMPs and TLR activation, TLR intracellular domains initiate the oligomerization of the myeloid differentiation primary response 88 (MyD88), IRAK1, IRAK2, and IRAK4 signaling platform known as the Myddosome complex while also triggering the Toll/IL-1R domain-containing adaptor-inducing IFN-β (TRIF)-dependent pathway. The Myddosome complex initiates signal transduction pathways enabling the activation of NF-κB and mitogen-activated protein kinase (MAPK) transcription factors and the subsequent production of inflammatory cytokines. Human IRAK4 deficiency is an autosomal recessive inborn error of immunity that classically presents with blunted or delayed inflammatory response to infection and susceptibility to a narrow spectrum of pyogenic bacteria, particularly Streptococcus pneumoniae, Staphylococcus aureus, and Pseudomonas aeruginosa. We describe a case of IRAK4 deficiency in an 11-mo-old boy with concurrent S. pneumoniae bacteremia and S. aureus cervical lymphadenitis with a blunted inflammatory response to invasive infection. Although initial clinical immune profiling was unremarkable, a high degree of suspicion for an innate immune defect prompted genetic sequencing. Genetic testing revealed a novel variant in the IRAK4 gene (c.1049delG, p.(Gly350Glufs*15)) predicted to be likely pathogenic. Functional testing showed a loss of IRAK4 protein expression and abolished TLR signaling, confirming the pathogenicity of this novel IRAK4 variant.
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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) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".