Expanded genetic landscape of chronic obstructive pulmonary disease reveals heterogeneous cell type and phenotype associations

Abstract

SummaryChronic obstructive pulmonary disease (COPD) is the leading cause of respiratory mortality worldwide. Genetic risk loci provide novel insights into disease pathogenesis. To broaden COPD genetic risk loci discovery and identify cell type and phenotype associations we performed a genome-wide association study in 35,735 cases and 222,076 controls from the UK Biobank and additional studies from the International COPD Genetics Consortium. We identified 82 loci with P value < 5×10−8; 47 were previously described in association with either COPD or population-based lung function. Of the remaining 35 novel loci, 13 were associated with lung function in 79,055 individuals from the SpiroMeta consortium. Using gene expression and regulation data, we identified enrichment for loci in lung tissue, smooth muscle and alveolar type II cells. We found 9 shared genomic regions between COPD and asthma and 5 between COPD and pulmonary fibrosis. COPD genetic risk loci clustered into groups of quantitative imaging features and comorbidity associations. Our analyses provide further support to the genetic susceptibility and heterogeneity of COPD.

Mixed-model admixture mapping identifies smoking-dependent loci of lung function in African Americans

“…Nevertheless, we were able to reproduce some of the top SNP-smoking interactions in the CHARGE consortium 53 at nominal significant level. More importantly, our study identified 3 loci 2q37.3, 11p15.2-3 and 7p15.2-3 using a dataset of only 3,300 African-American individuals, while the same loci only passed the genome-wide significance threshold of standard univariate association in an independent replication cohort including up to 400,000 individuals 54,55 . Further, the method for admixture mapping can also be optimized.…”

“…We considered two large studies of pulmonary phenotypes and COPD conducted in individuals of European ancestry: the CHARGE consortium (N = 50,047) which had genome-wide summary results for SNP-by-smoking interaction 53 ; and the most recent and largest meta-analysis of UK Biobank and SpiroMeta cohorts (COPD cases = 35,735, COPD controls = 222,076; N = 400,102 for pulmonary function phenotypes) which provides an up-to-date list of variants with genome-wide significant marginal genetic effect. 54,55 .…”

“…We next assessed the presence of marginal genetic effect at our seven loci using the aforementioned meta-analysis of pulmonary phenotypes 54 and COPD 55 . Although our marginal signals of top local ancestry segments and SNPs were weak (Supplementary Table S10-11), we observed that nine genome-wide significant SNPs from GWASs 54,55 were located less than 1Mb away from the three loci 2q37.3, 11p15.2-3 and 7p15.2-3 ( Supplementary Table S9).…”

“…In particular, two SNPs rs80145403 and rs80145403 were within the same PARVA and TEAD1 genes in Chromosome 11 as in our SNP-smoking interaction analysis (Table 3). Notably, five SNPs come from two loci that each has three distinct signals estimated by the conditional analysis 55 . Such a scenario with multiple SNPs driving either marginal or interaction association is beneficial for our ancestry-based approach to detect gene-environment interactions, and, thus, may explain the signal overlap at the gene-level for two 11p15.2-3 and 2q37.3 loci.…”

Dissecting respiratory disease heterogeneity through the genetics of diffusing capacity

“…Machine learning techniques are one approach to discover enrichment of association of known genetic risk loci with a subgroup of COPD patients with shared clinical features [18]. The differential strength of association of COPD risk variants with COPD-related phenotypes, such as quantitative imaging features, can also be used to explore the genetic basis for COPD heterogeneity [9,19]. Aside from these techniques, studying the genetics of sub-phenotypes and key physiological features of respiratory diseases may allow us to more directly evaluate the biological processes contributing to the clinical and physiological heterogeneity of these diseases, and in particular, COPD.…”