High prevalence of <i>CCDC103</i> p.His154Pro mutation causing primary ciliary dyskinesia disrupts protein oligomerisation and is associated with normal diagnostic investigations
Bibliographic record
Abstract
Rationale Primary ciliary dyskinesia is a genetically heterogeneous inherited condition characterised by progressive lung disease arising from abnormal cilia function. Approximately half of patients have situs inversus. The estimated prevalence of primary ciliary dyskinesia in the UK South Asian population is 1:2265. Early, accurate diagnosis is key to implementing appropriate management but clinical diagnostic tests can be equivocal. Objectives To determine the importance of genetic screening for primary ciliary dyskinesia in a UK South Asian population with a typical clinical phenotype, where standard testing is inconclusive. Methods Next-generation sequencing was used to screen 86 South Asian patients who had a clinical history consistent with primary ciliary dyskinesia. The effect of a CCDC103 p.His154Pro missense variant compared with other dynein arm-associated gene mutations on diagnostic/phenotypic variability was tested. CCDC103 p.His154Pro variant pathogenicity was assessed by oligomerisation assay. Results Sixteen of 86 (19%) patients carried a homozygous CCDC103 p.His154Pro mutation which was found to disrupt protein oligomerisation. Variable diagnostic test results were obtained including normal nasal nitric oxide levels, normal ciliary beat pattern and frequency and a spectrum of partial and normal dynein arm retention. Fifteen (94%) patients or their sibling(s) had situs inversus suggesting CCDC103 p.His154Pro patients without situs inversus are missed. Conclusions The CCDC103 p.His154Pro mutation is more prevalent than previously thought in the South Asian community and causes primary ciliary dyskinesia that can be difficult to diagnose using pathology-based clinical tests. Genetic testing is critical when there is a strong clinical phenotype with inconclusive standard diagnostic tests.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".