Genetic Mutations in Familial Pulmonary Fibrosis: A Next Generation Sequencing (NGS) Study.
Bibliographic record
Abstract
Introduction. Familial Pulmonary Fibrosis (FPF) occurs when two or more family members are affected by Idiopathic Pulmonary Fibrosis (IPF) or any form of Idiopathic Interstitial Pneumonia (IIP). FPF is often underdiagnosed, particularly in patients without a clear family history or with nonspecific early-stage symptoms. Early identification of genetic mutations linked to pulmonary fibrosis is crucial but raises ethical concerns, especially given the lack of curative treatment. Aim. To identify genetic mutations associated with FPF in a family with multiple affected members. Methods. A NGS gene panel targeting genes involved in pulmonary fibrosis was designed and tested at the Pneumology Unit of IRCCS Policlinico San Matteo Hospital on a family with three first-degree relatives affected by pulmonary fibrosis. Results. Identified mutations included heterozygous: SLC7A7 c.1417C>T, TGFBR2 c.458del, TERT c.2608T>G. The TERT mutation was present in both the proband (a female with IPF features) and her brother (who showed IPF features). Another brother died from unspecified pulmonary fibrosis. The SLC7A7, TGFBR2 and TERT mutations were found in both the proband and her niece, who was healthy. Comprehensive radiological studies were performed on all affected family members, and patients with IPF features were treated with antifibrotic agents. Discussion. The SLC7A7 mutation has been associated with lysinuric protein intolerance, TGFBR2 with cardiovascular and neurocognitive syndromes, and the TERT mutation (c.2608T>G) is novel. While these mutations have not been previously linked to FPF, their combined presence in one individual may suggest a potential pathogenic relationship.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".