Journal article

Novel insights into the genetics of smoking behaviour, lung function, and chronic obstructive pulmonary disease (UK BiLEVE): a genetic association study in UK Biobank

Louise V Wain, Nick Shrine, Suzanne Miller, Victoria E Jackson, Ioanna Ntalla, Maria Soler Artigas, Charlotte K Billington, Abdul Kader Kheirallah, Richard Allen, James P Cook, Kelly Probert, Ma'en Obeidat, Yohan Bosse, Ke Hao, Dirkje S Postma, Peter D Pare, Adaikalavan Ramasamy, Reedik Maegi, Evelin Mihailov, Eva Reinmaa Show all

The Lancet Respiratory Medicine | ELSEVIER SCI LTD | Published : 2015

Abstract

BACKGROUND: Understanding the genetic basis of airflow obstruction and smoking behaviour is key to determining the pathophysiology of chronic obstructive pulmonary disease (COPD). We used UK Biobank data to study the genetic causes of smoking behaviour and lung health. METHODS: We sampled individuals of European ancestry from UK Biobank, from the middle and extremes of the forced expiratory volume in 1 s (FEV1) distribution among heavy smokers (mean 35 pack-years) and never smokers. We developed a custom array for UK Biobank to provide optimum genome-wide coverage of common and low-frequency variants, dense coverage of genomic regions already implicated in lung health and disease, and to ass..

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University of Melbourne Researchers

Grants

Awarded by Medical Research Council (MRC)


Awarded by MRC fellowships


Awarded by MRC programme


Awarded by Wellcome Trust


Awarded by ERC Consolidator Grant


Awarded by Canadian Institutes of Health Research


Awarded by FP7



Awarded by Medical Research Council


Awarded by Chief Scientist Office


Awarded by British Lung Foundation


Funding Acknowledgements

This work was funded by a Medical Research Council (MRC) strategic award to MDT, IPH, DPS, and LVW (MC_PC_12010). This research was done using the UK Biobank resource. MDT was supported by MRC fellowships G0501942 and G0902313. IPH is supported by an MRC programme grant (G1000861). This Article presents independent research funded partially by the National Institute for Health Research (NIHR). The views expressed are those of the authors and not necessarily those of the National Health Service, the NIHR, or the Department of Health. We thank Affymetrix for their role in array design and for undertaking genotyping and genotype calling. We thank all members of the UK Biobank Array Design Group: Peter Donnelly (chair), Jose Bras, Adam Butterworth, Richard Durbin, Paul Elliott, Ian Hall, John Hardy, Mark McCarthy, Gil McVean, Tim Peakman, Nazneen Rahman, Nilesh Samani, Martin Tobin, and Hugh Watkins. This study makes use of data generated by the UK10K Consortium, derived from samples from TwinsUK and ALSPAC. A full list of the investigators who contributed to the generation of the data is available from the UK10K website. Funding for UK10K was provided by the Wellcome Trust under award WT091310. JM is funded by an ERC Consolidator Grant (617306). APM is a Wellcome Trust Senior Research Fellow in Basic Biomedical Science (grant number WT098017). The lung eQTL study at Laval University was supported by the Chaire de pneumologie de la Fondation JD Begin de l'Universite Laval, the Fondation de l'Institut universitaire de cardiologie et de pneumologie de Quebec, the Respiratory Health Network of the FRQS, the Canadian Institutes of Health Research (MOP - 123369), and the Cancer Research Society and Read for the Cure. YB is the recipient of a Junior 2 Research Scholar award from the Fonds de recherche Quebec - Sante (FRQS). EGCUT received financing by FP7 grants (278913, 306031, 313010), Center of Excellence in Genomics (EXCEGEN), and University of Tartu (SP1GVARENG). We thank EGCUT technical personnel, especially V Soo and S Smit. Data analyses were done in part in the High Performance Computing Center of University of Tartu. We thank Paul Jennings for assistance with generation of code to extract expression data. MO is a Postdoctoral Fellow of the Michael Smith Foundation for Health Research and the Canadian Institute for Health Research Integrated and Mentored Pulmonary and Cardiovascular Training program. This research used the ALICE and SPECTRE High Performance Computing Facilities at the University of Leicester.