Exome Sequencing of Neonatal Blood Spots and the Identification of Genes Implicated in Bronchopulmonary Dysplasia
Bibliographic record
Abstract
RATIONALE: Bronchopulmonary dysplasia (BPD), a prevalent severe lung disease of premature infants, has a strong genetic component. Large-scale genome-wide association studies for common variants have not revealed its genetic basis. OBJECTIVES: Given the historical high mortality rate of extremely preterm infants who now survive and develop BPD, we hypothesized that risk loci underlying this disease are under severe purifying selection during evolution; thus, rare variants likely explain greater risk of the disease. METHODS: We performed exome sequencing on 50 BPD-affected and unaffected twin pairs using DNA isolated from neonatal blood spots and identified genes affected by extremely rare nonsynonymous mutations. Functional genomic approaches were then used to systematically compare these affected genes. MEASUREMENTS AND MAIN RESULTS: We identified 258 genes with rare nonsynonymous mutations in patients with BPD. These genes were highly enriched for processes involved in pulmonary structure and function including collagen fibril organization, morphogenesis of embryonic epithelium, and regulation of Wnt signaling pathway; displayed significantly elevated expression in fetal and adult lungs; and were substantially up-regulated in a murine model of BPD. Analyses of mouse mutants revealed their phenotypic enrichment for embryonic development and the cyanosis phenotype, a clinical manifestation of BPD. CONCLUSIONS: Our study supports the role of rare variants in BPD, in contrast with the role of common variants targeted by genome-wide association studies. Overall, our study is the first to sequence BPD exomes from newborn blood spot samples and identify with high confidence genes implicated in BPD, thereby providing important insights into its biology and molecular etiology.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".