The UK BiLEVE study, a genetic study of smoking behaviour, lung function, and COPD in UK Biobank

Speaker: Martin Tobin

Abstract

UK Biobank comprises 502,682 participants with extensive health and lifestyle data, health related measures and DNA. COPD is the third leading cause of death worldwide and smoking, a major risk factor for COPD, cancers and cardiovascular disease, accounts for around 5.1 million deaths annually. In the UK BiLEVE study, 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 assay rare coding variants relevant to the UK population. In these nested case-control studies, we discovered novel associations (P<5x10-8) with lung function extremes, COPD and with smoking behaviour.

The study has improved our understanding of the genetic and molecular basis of smoking behaviour and lung function and provided potential targets for therapeutic intervention.  A similar approach could be adopted for genetic studies of other health-related traits in UK Biobank, utilising either new genetic assays or the extensive genome-wide data that we and UK Biobank have generated. This research has been conducted using the UK Biobank Resource.

Biography

Martin Tobin holds a UK Medical Research Council Senior Clinical Fellowship and is Professor of Genetic Epidemiology and Public Health at the University of Leicester, UK. He has established, led and co-led national and international genomic epidemiology studies. The collaborative studies of genomics of lung function and COPD he has co-led for the SpiroMeta and UK BiLEVE consortia have produced over 14 papers to date, and have identified key genomic loci now known to influence lung function and COPD risk.

The work of his group crosses disease areas and extends to a range of traits and to multimorbidity. He is principal investigator for the Quantitative Methods, Machine Learning and Functional Genomics Clinical Interpretation Partnership of Genomics England (GeCIP), and principal investigator for the EXCEED study, which aims to improve drug target validation.