Novel heterozygous <i>FOXN1</i> mutation identified following newborn screening for severe combined immunodeficiency is associated with improving immune parameters
Bibliographic record
Abstract
Background: Forkhead-box protein N1 (FOXN1) plays a critical role in the proper development and function of thymic epithelial cells, required for T cell ontogeny. Homozygous variants in the FOXN1 gene, encoding FOXN1, cause severe combined immunodeficiency (SCID), whereas heterozygous mutations are associated with variable presentations and over time, improving T cell function. Aim: To highlight the importance of broader genetic investigations to attain a definitive molecular diagnosis following abnormal newborn screening for SCID. Methods: Case report of a patient with immunodeficiency due to a novel de novo FOXN1 mutation. Results: The patient was identified following abnormal newborn screening for SCID in which T cell receptor excision circles were absent/very low. Initial immune investigations revealed severe T cell lymphopenia and poor lymphocyte function and she was diagnosed with T-B+NK+SCID. During work-up for hematopoietic stem cell transplantation, extensive genetic investigations identified a novel heterozygous mutation in FOXN1. A more conservative management approach was taken, and over the following months, the patient’s immune parameters improved. Conclusion: Newborn screening for SCID has facilitated the detection of SCID, as well as other T cell immunodeficiencies, before infectious complications and organ damage occur. Heterozygous mutations in FOXN1 are associated with more variable presentations including improving immune indices with age. Here, results of genetic investigations were essential for informing the management of this case. Statement of Novelty: We report a novel heterozygous mutation in FOXN1, presenting initially as T-B+NK+ SCID with gradual improvement of immune parameters over time.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".