Abstract
SummaryBackgroundGenetic factors influence chronic obstructive pulmonary disease (COPD) risk, but the individual variants that have been identified have small effects. We hypothesised that a polygenic risk score using additional variants would predict COPD and associated phenotypes.MethodsWe constructed a polygenic risk score using a genome-wide association study of lung function (FEV1 and FEV1/forced vital capacity [FVC]) from the UK Biobank and SpiroMeta. We tested this polygenic risk score in nine cohorts of multiple ethnicities for an association with moderate-to-severe COPD (defined as FEV1/FVC <0·7 and FEV1 <80% of predicted). Associations were tested using logistic regression models, adjusting for age, sex, height, smoking pack-years, and principal components of genetic ancestry. We assessed predictive performance of models by area under the curve. In a subset of studies, we also studied quantitative and qualitative CT imaging phenotypes that reflect parenchymal and airway pathology, and patterns of reduced lung growth.FindingsThe polygenic risk score was associated with COPD in European (odds ratio [OR] per SD 1·81 [95% CI 1·74–1·88] and non-European (1·42 [1·34–1·51]) populations. Compared with the first decile, the tenth decile of the polygenic risk score was associated with COPD, with an OR of 7·99 (6·56–9·72) in European ancestry and 4·83 (3·45–6·77) in non-European ancestry cohorts. The polygenic risk score was superior to previously described genetic risk scores and, when combined with clinical risk factors (ie, age, sex, and smoking pack-years), showed improved prediction for COPD compared with a model comprising clinical risk factors alone (AUC 0·80 [0·79–0·81] vs 0·76 [0·75–0·76]). The polygenic risk score was associated with CT imaging phenotypes, including wall area percent, quantitative and qualitative measures of emphysema, local histogram emphysema patterns, and destructive emphysema subtypes. The polygenic risk score was associated with a reduced lung growth pattern.InterpretationA risk score comprised of genetic variants can identify a small subset of individuals at markedly increased risk for moderate-to-severe COPD, emphysema subtypes associated with cigarette smoking, and patterns of reduced lung growth.FundingUS National Institutes of Health, Wellcome Trust.
Highlights
Chronic obstructive pulmonary disease (COPD) is characterised by irreversible airflow limitation
After filtering on variants present in test cohorts and applying a penalised regression framework, our final individual polygenic risk score for FEV1 contained 1·7 million single nucleotide polymorphisms (SNPs) and the individual polygenic risk score for FEV1/forced vital capacity (FVC) contained 1·2 million SNPs with non-zero effect sizes; 455 432 SNPs were present in both scores
We developed a polygenic risk score using Genome-wide association studies (GWASs) summary statistics from more than 400 000 participants, and used it to predict the diagnosis of chronic obstructive pulmonary disease (COPD) in nine population-based and case-control cohorts
Summary
Chronic obstructive pulmonary disease (COPD) is characterised by irreversible airflow limitation. Genome-wide association studies (GWASs) of COPD and lung function have identified numerous genetic variants associated with COPD risk.[7,8,9,10,11,12,13] The effect size of each of these GWAS variants is generally small. Each individual variant only explains a small proportion of COPD risk, the combination of many genetic variants into a single genetic risk score explains a greater proportion of the risk.[7,11,14,15] Genetic risk scores have been developed for lung function, with predictive power for COPD.[7,13,14] Genetic risk scores based on larger GWASs, and including more variants, tend to exhibit higher predictive performance.[7] www.thelancet.com/respiratory Vol 8 July 2020. Genetic factors influence chronic obstructive pulmonary disease (COPD) risk, but the individual variants that have been identified have small effects. We hypothesised that a polygenic risk score using additional variants would predict COPD and associated phenotypes
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