Abstract 2292: Lung function and lung cancer risk: a Mendelian randomization study of UK Biobank cohort and the International Lung Cancer Consortium
Bibliographic record
Abstract
Abstract Background: Impaired lung function (LF) is strongly associated with increased lung cancer risk. However, since airflow obstruction is a diagnostic criterion for obstructive lung disease, and a consequence of tobacco smoking, isolating the causal relationship between LF and lung cancer has remained a challenge. Methods: We investigated 3 standardized (mean=0, standard deviation=1) LF metrics: forced expiratory volume in 1 second (FEV1), forced vital capacity (FVC), and FEV1/FVC. To evaluate the causal relevance of LF in lung cancer etiology we conducted: i) survival analyses in the UK Biobank cohort (UKB); and ii) Mendelian Randomization (MR) analyses using genetic instrumental variables (IVs) developed in UKB and tested using individual-level data from the OncoArray, a genome-wide array with in-depth coverage for common cancers. Results: 702 incident lung cancers were diagnosed in 484,194 UKB participants during follow-up. Cox regression was used to estimate hazard ratios (HR) and 95% confidence intervals (CI), adjusted for age, sex, smoking status, socioeconomic status, and assessment center. Adjustment for other smoking metrics yielded similar results. Lung cancer risk increased per 1 unit decrease in FEV1 (HR=1.80, 95% CI: 1.64-1.98, p=3.3×10-34), FVC (HR=1.45, 1.30-1.60, p=2.3×10-12), and FEV1/FVC (HR=1.39, 1.33-1.46, p=1.3×10-38). This pattern was observed for adenocarcinoma (n=300): FEV1 (HR=1.77, p=6.0×10-12), FVC (HR=1.48, p=1.4×10-5), FEV1/FVC (HR=1.34, p=8.3×10-11); and squamous cell carcinoma (n=166): FEV1 (HR=1.97, p=9.9×10-10), FVC (HR=1.60, p=1.0×10-4), FEV1/FVC (HR=1.38, p=5.9×10-8). Next, a genome-wide association study of 67,708 UKB participants and 12.6 million variants was carried out to develop genetic IVs for LF. Results were filtered to retain independent variants (R2<0.2) associated with each LF phenotype (p<5×10-8). The following IVs were developed: FEV1 (n=28 variants, 0.72% of variation explained), FVC (n=44, 1.08%), and FEV1/FVC (n=45, 1.85%). Odds ratios (OR) for each IV and lung cancer were estimated for 18,686 cases 15,190 controls (>80% European ancestry) from 23 studies. Effect estimates were combined using maximum-likelihood MR models to estimate causal ORs. MR results indicate that genetic scores associated with improved airflow are unrelated to lung cancer risk: FEV1 (OR=1.00, 95% CI: 0.96-1.03, p=0.86), FVC (OR=1.00, 0.97-1.03, p=0.93) and FEV1/FVC (OR=1.00, 0.91-1.10, p=0.95). The null association observed for the genetic determinants of FEV1, FVC and FEV1/FVC was not modified by tumor histology or smoking status. Conclusions: LF is a robust predictor of lung cancer risk, however, our findings do not support the existence of causal pathways that are independent of obstructive lung disease or smoking. This apparent lack of a causal relationship should be interpreted with caution since pleiotropic effects of LF loci cannot be ruled out. Citation Format: Linda Kachuri, Mattias Johansson, Paul Brennan, Phillip Haycock, Geoffrey Liu, Maria Teresa Landi, David C. Christiani, Neil E. Caporaso, Xifeng Wu, Melinda C. Aldrich, Demetrius Albanes, Adonina Tardón, Gad Rennert, Chu Chen, Gary E. Goodman, Jennifer A. Doherty, Heike Bickeböller, Dawn Teare, Lambertus A. Kiemeney, Stig E. Bojesen, John K. Field, Aage Haugen, Stephen Lam, Loic Le Marchand, Matthew B. Schabath, Angeline S. Andrew, Jonas Manjer, Philip Lazarus, Susanne M. Arnold, Valérie Gaborieau, Richard Martin, Caroline Relton, George Davey Smith, Christopher I. Amos, James D. McKay, Rayjean J. Hung. Lung function and lung cancer risk: a Mendelian randomization study of UK Biobank cohort and the International Lung Cancer Consortium [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 2292. doi:10.1158/1538-7445.AM2017-2292
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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 | 0.006 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".