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Genome-wide association analyses for lung function and chronic obstructive pulmonary disease identify new loci and potential druggable targets

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Wain, LV 
Shrine, N 
Artigas, MS 
Erzurumluoglu, AM 
Noyvert, B 


Chronic obstructive pulmonary disease (COPD) is characterized by reduced lung function and is the third leading cause of death globally. Through genome-wide association discovery in 48,943 individuals, selected from extremes of the lung function distribution in UK Biobank, and follow-up in 95,375 individuals, we increased the yield of independent signals for lung function from 54 to 97. A genetic risk score was associated with COPD susceptibility (odds ratio per 1 s.d. of the risk score (∼6 alleles) (95% confidence interval) = 1.24 (1.20-1.27), P = 5.05 × 10‾⁴⁹), and we observed a 3.7-fold difference in COPD risk between individuals in the highest and lowest genetic risk score deciles in UK Biobank. The 97 signals show enrichment in genes for development, elastic fibers and epigenetic regulation pathways. We highlight targets for drugs and compounds in development for COPD and asthma (genes in the inositol phosphate metabolism pathway and CHRM3) and describe targets for potential drug repositioning from other clinical indications.



Adult, Aged, Aged, 80 and over, Alleles, Asthma, Epigenesis, Genetic, Female, Genetic Loci, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Lung, Male, Middle Aged, Polymorphism, Single Nucleotide, Pulmonary Disease, Chronic Obstructive, Risk Factors

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Nature Genetics

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Nature Publishing Group
Medical Research Council (MC_PC_12026)
This work was funded by a Medical Research Council (MRC) strategic award to M.D.T., I.P.H., D.S. and L.V.W. (MC_PC_12010). This research has been conducted using the UK Biobank Resource under application 648. This article presents independent research funded partially by the National Institute for Health Research (NIHR). The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the UK Department of Health. This research used the ALICE and SPECTRE High-Performance Computing Facilities at the University of Leicester. Additional acknowledgments and funding details can be found in the Supplementary Note.