Autosomal dominant variants in<i>FOXJ1</i>causing primary ciliary dyskinesia in two patients with obstructive hydrocephalus
Bibliographic record
Abstract
BACKGROUND: Primary ciliary dyskinesia (PCD) is a mostly autosomal recessive, genetic disease of abnormal motile cilia function, resulting in bronchiectasis, infertility, organ laterality defects, and chronic otolaryngology disease. Though motile, ependymal cilia influencing cerebrospinal fluid flow in the central nervous system share many aspects of structure and function with motile cilia in the respiratory tract, hydrocephalus is rarely associated with PCD. Recently, pathogenic variants in FOXJ1 (Chr 17q25.1) were identified causing PCD associated with hydrocephalus, reduced respiratory cilia number, axonemal microtubule disorganization, and occurring in a de novo, autosomal dominant inheritance pattern. METHOD: Two patients with chronic oto-sino-pulmonary disease and hydrocephalus underwent candidate testing of FOXJ1. Coding region and splice junctions were sequenced and analyzed under the auspices of Genetic Disorders of Mucociliary Clearance Consortium. RESULTS: Upon sequencing of the entire coding region and splice-junctions, heterozygous, pathogenic variants in FOXJ1 were discovered in exon 3 of two patients: an 11-month-old female with situs inversus totalis (NM_001454.4: c.945delC (p.Phe315Leufs*18)) and a 51 year-old male, post-double lung transplantation (NM_001454.4: c.929_932delACTG (p.Asp310Glyfs*22)). FOXJ1 variants were not detected in the available parents and the siblings of these probands. CONCLUSION: FOXJ1 pathogenic variants cause PCD in a de novo, autosomal dominant inheritance pattern, and are associated with hydrocephalus. Physicians treating patients with hydrocephalus and chronic oto-sino-pulmonary disease should be aware of this PCD association and test for FOXJ1 variants.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".