Abstract 13259: Genome Sequencing in Pediatric Patients With Pulmonary Vein Stenosis
Bibliographic record
Abstract
Introduction: Pulmonary vein stenosis (PVS) is a rare and progressive disease of the vasculature, characterized by neointimal proliferation and is frequently lethal in pediatric patients. PVS is clinically heterogeneous, and its etiology remains unknown. Insight into the genetic basis of PVS can help to direct treatment interventions and improve clinical outcomes. Objectives: To examine the genetic mechanisms underlying PVS and to compare the genetic architecture in patients with severe disease to patients with disease stabilization. Methods: We performed genome sequencing in a cohort of 18 pediatric patients with PVS. The genomic data was analyzed for clinically reportable variants and biologically plausible candidates. We used a statistical overrepresentation test to investigate the overrepresentation of gene ontology (GO) terms in patients with aggressive disease compared with stabilized patients. Results: Seven patients (38.9%) had aggressive disease, resulting in death or lung transplant, 16 patients (88.9%) had concomitant congenital heart disease, and 11 patients (61.1%) had extracardiac anomalies. In two patients (11.1%) with a syndromic presentation, we identified Pathogenic/Likely Pathogenic variants in three genes: ANKRD11, associated with KBG syndrome, FOXP1 , and DYNC1H1 , associated with intellectual developmental disorders. In search of novel candidate genes, we identified de novo variants in PAK4 , AMBRA1 , and ANKRD50 , involved in cytoskeletal remodeling, mTOR-regulated autophagy, and protein trafficking, respectively. In patients with severe PVS, we found an overrepresentation of rare (minor allele frequency <0.15%) coding variants in genes involved in blood vessel morphogenesis (FDR <0.05), protein phosphorylation (FDR <0.05), dynein intermediate chain binding (FDR <0.05), and ATP binding (FDR <0.05). No GO terms were overrepresented in the patients with stabilized disease. Conclusions: This exploratory cohort of patients with PVS provides further insight into the genetic contributions to PVS. These results suggest distinct genetic landscapes between progressive and stabilized disease. Genetic testing in larger cohorts is needed to further define the molecular pathology of pediatric PVS.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".