Journal article

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

Louise V Wain, Nick Shrine, Maria Soler Artigas, A Mesut Erzurumluoglu, Boris Noyvert, Lara Bossini-Castillo, Ma'en Obeidat, Amanda P Henrys, Michael A Portelli, Robert J Hall, Charlotte K Billington, Tracy L Rimington, Anthony G Fenech, Catherine John, Tineka Blake, Victoria E Jackson, Richard J Allen, Bram P Prins, Archie Campbell, David J Porteous Show all

NATURE GENETICS | NATURE RESEARCH | Published : 2017

Abstract

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 ..

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University of Melbourne Researchers

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Awarded by Medical Research Council (MRC)


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Awarded by ESRC


Awarded by MRC


Awarded by Biotechnology and Biological Sciences Research Council


Awarded by Chief Scientist Office


Awarded by Economic and Social Research Council


Awarded by Medical Research Council


Funding Acknowledgements

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.