A Test to Comprehensively Capture the Known Genetic Component of Familial Pulmonary Fibrosis
Bibliographic record
Abstract
Abstract The recent European Respiratory Society statement on familial pulmonary fibrosis supports the need for genetic testing in the care of patients and their relatives. However, no solution (i.e., a concrete test) was provided to implement genetic testing in daily practice. Herein, we tabulated and standardized the nomenclature of 128 genetic variants in 20 genes implicated in adult-onset pulmonary fibrosis. The objective was to develop a laboratory-developed test (LDT) on the basis of standard Sanger sequencing to capture all known familial pulmonary fibrosis–associated variants. Targeted DNA fragments were amplified using harmonized PCR conditions to perform the LDT in a single 96-well plate. The new genetic test was evaluated in 62 sporadic cases of idiopathic pulmonary fibrosis. As expected in this population, we observed a low yield of disease-causing mutations. More important, 100% of targeted variants by the LDT were successfully evaluated. Furthermore, four variants of uncertain significance with in silico–predicted deleterious scores were identified in three patients, suggesting novel pathogenic variants in genes known to cause idiopathic pulmonary fibrosis. Finally, the MUC5B promoter variant rs35705950 was strongly enriched in these patients with a minor allele frequency of 41.1% compared with 10.6% in a matched population-based cohort (n = 29,060), leading to an estimation that this variant may explain up to 35% of the population-attributable risk. This LDT provides a solution for rapid clinical translation. Technical laboratory details are provided so that specialized pulmonary centers can implement the LDT in house to expedite the clinical recommendations of expert panels.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".