Transforming Growth Factor-β Receptor-3 Is Associated with Pulmonary Emphysema
Bibliographic record
Abstract
Chronic obstructive pulmonary disease (COPD) is a heterogeneous syndrome, including emphysema and airway disease. Phenotypes defined on the basis of chest computed tomography (CT) may decrease disease heterogeneity and aid in the identification of candidate genes for COPD subtypes. To identify these genes, we performed genome-wide linkage analysis in extended pedigrees from the Boston Early-Onset COPD Study, stratified by emphysema status (defined by chest CT scans) of the probands, followed by genetic association analysis of positional candidate genes. A region on chromosome 1p showed strong evidence of linkage to lung function traits in families of emphysema-predominant probands in the stratified analysis (LOD score = 2.99 in families of emphysema-predominant probands versus 1.98 in all families). Association analysis in 949 individuals from 127 early-onset COPD pedigrees revealed association for COPD-related traits with an intronic single-nucleotide polymorphism (SNP) in transforming growth factor-beta receptor-3 (TGFBR3) (P = 0.005). This SNP was significantly associated with COPD affection status comparing 389 cases from the National Emphysema Treatment Trial to 472 control smokers (P = 0.04), and with FEV(1) (P = 0.004) and CT emphysema (P = 0.05) in 3,117 subjects from the International COPD Genetics Network. Gene-level replication of association with lung function was seen in 427 patients with COPD from the Lung Health Study. In conclusion, stratified linkage analysis followed by association testing identified TGFBR3 (betaglycan) as a potential susceptibility gene for COPD. Published human microarray and murine linkage studies have also demonstrated the importance of TGFBR3 in emphysema and lung function, and our group and others have previously found association of COPD-related traits with TGFB1, a ligand for TGFBR3.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".