Variants of Asthma and Chronic Obstructive Pulmonary Disease Genes and Lung Function Decline in Aging
Bibliographic record
Abstract
BACKGROUND: A substantial proportion of the general population has low lung function, and lung function is known to decrease as we age. Low lung function is a feature of several pulmonary disorders, such as uncontrolled asthma and chronic obstructive pulmonary disease. The objective of this study is to investigate the association of polymorphisms in asthma and chronic obstructive pulmonary disease candidate genes with rates of lung function decline in a general population sample of aging men. METHODS: We analyzed data from a cohort of 1,047 Caucasian men without known lung disease, who had a mean of 25 years of lung function data, and on whom DNA was available. The cohort was randomly divided into two groups, and we tested a total of 940 single-nucleotide polymorphisms in 44 asthma and chronic obstructive pulmonary disease candidate genes in the first group (testing cohort, n = 545) for association with change in forced expiratory volume in 1 second over time. RESULTS: One hundred nineteen single-nucleotide polymorphisms that showed nominal associations in the testing cohort were then genotyped and tested in the second group (replication cohort, n = 502). Evidence for association from the testing and replication cohorts were combined, and after adjustment for multiple testing, seven variants of three genes (DPP10, NPSR1, and ADAM33) remained significantly associated with change in forced expiratory volume in 1 second over time. CONCLUSIONS: Our findings that genetic variants of genes involved in asthma and chronic obstructive pulmonary disease are associated with lung function decline in normal aging participants suggest that similar genetic mechanisms may underlie lung function decline in both disease and normal aging processes.
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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 | 0.001 | 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".