Genome-Wide Association Study Identification of Novel Loci Associated with Airway Responsiveness in Chronic Obstructive Pulmonary Disease
Bibliographic record
Abstract
Increased airway responsiveness is linked to lung function decline and mortality in subjects with chronic obstructive pulmonary disease (COPD); however, the genetic contribution to airway responsiveness remains largely unknown. A genome-wide association study (GWAS) was performed using the Illumina (San Diego, CA) Human660W-Quad BeadChip on European Americans with COPD from the Lung Health Study. Linear regression models with correlated meta-analyses, including data from baseline (n = 2,814) and Year 5 (n = 2,657), were used to test for common genetic variants associated with airway responsiveness. Genotypic imputation was performed using reference 1000 Genomes Project data. Expression quantitative trait loci (eQTL) analyses in lung tissues were assessed for the top 10 markers identified, and immunohistochemistry assays assessed protein staining for SGCD and MYH15. Four genes were identified within the top 10 associations with airway responsiveness. Markers on chromosome 9p21.2 flanked by LINGO2 met a predetermined threshold of genome-wide significance (P < 9.57 × 10(-8)). Markers on chromosomes 3q13.1 (flanked by MYH15), 5q33 (SGCD), and 6q21 (PDSS2) yielded suggestive evidence of association (9.57 × 10(-8) < P ≤ 4.6 × 10(-6)). Gene expression studies in lung tissue showed single nucleotide polymorphisms on chromosomes 5 and 3 to act as eQTL for SGCD (P = 2.57 × 10(-9)) and MYH15 (P = 1.62 × 10(-6)), respectively. Immunohistochemistry confirmed localization of SGCD protein to airway smooth muscle and vessels and MYH15 to airway epithelium, vascular endothelium, and inflammatory cells. We identified novel loci associated with airway responsiveness in a GWAS among smokers with COPD. Risk alleles on chromosomes 5 and 3 acted as eQTLs for SGCD and MYH15 messenger RNA, and these proteins were expressed in lung cells relevant to the development of airway responsiveness.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".