Identification of a novel RAG1 hypomorphic mutation in a child presenting with disseminated vaccine-strain varicella
Why this work is in the frame
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Bibliographic record
Abstract
Background: Recombination-activating gene 1 (RAG1) and recombination-activating gene 2 (RAG2) encode unique lymphocyte endonuclease proteins that are crucial in T and B cell development through V(D)J recombination. RAG1 gene defects lead to variable phenotypes, ranging from immunocompetent to severe combined immunodeficiency (SCID). Curative therapy for severe manifestations can be achieved through hematopoietic stem cell transplantation (HSCT). Advances in genomic sequencing have led to the discovery of new variants and it is recognized that the level of recombinase activity correlates with disease severity. Aim: To report the clinical presentation, immunological work-up, decision process to undergo HSCT, and confirmatory genetic diagnosis in a patient who was well until her initial presentation with disseminated vaccine-strain varicella. Methods: Clinical data was gathered through retrospective chart review. Immunological investigations, targeted gene sequencing, and thymic biopsy results were reviewed. Further genetic analysis, including whole exome and whole genome sequencing was performed. Results: Whole exome sequencing identified a single missense mutation in RAG1, R474C (c.1420C>T), which would not account for the clinical presentation. Healthy individuals with only 1 mutation have been reported. Subsequently, whole genome sequencing revealed a novel second heterozygous missense variant, H945D (c.2833G>T) in the RAG1 gene. Conclusion: Hypomorphic RAG1 mutations with residual activity have a diverse phenotypic expression. Identifying and understanding the implications of these mutations is crucial for disease prognostication and tailoring management. Statement of novelty: We present a novel RAG1 missense variant, with likely complete or partial loss of function, in a patient with significant impairment in cellular immunity.
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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 | 0.001 |
| 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 it