@article{Artigas2017,
title = {Targeted Sequencing of Lung Function Loci in Chronic Obstructive Pulmonary Disease Cases and Controls},
author = {María Soler Artigas, Louise V. Wain , Nick Shrine, Tricia M. McKeever, UK BiLEVE , Ian Sayers, Ian P. Hall, Martin D. Tobin
},
url = {http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0170222},
year = {2017},
date = {2017-01-23},
journal = {PLOS One},
abstract = {Chronic obstructive pulmonary disease (COPD) is the third leading cause of death worldwide; smoking is the main risk factor for COPD, but genetic factors are also relevant contributors. Genome-wide association studies (GWAS) of the lung function measures used in the diagnosis of COPD have identified a number of loci, however association signals are often broad and collectively these loci only explain a small proportion of the heritability. In order to examine the association with COPD risk of genetic variants down to low allele frequencies, to aid fine-mapping of association signals and to explain more of the missing heritability, we undertook a targeted sequencing study in 300 COPD cases and 300 smoking controls for 26 loci previously reported to be associated with lung function. We used a pooled sequencing approach, with 12 pools of 25 individuals each, enabling high depth (30x) coverage per sample to be achieved. This pooled design maximised sample size and therefore power, but led to challenges during variant-calling since sequencing error rates and minor allele frequencies for rare variants can be very similar. For this reason we employed a rigorous quality control pipeline for variant detection which included the use of 3 independent calling algorithms. In order to avoid false positive associations we also developed tests to detect variants with potential batch effects and removed them before undertaking association testing. We tested for the effects of single variants and the combined effect of rare variants within a locus. We followed up the top signals with data available (only 67% of collapsing methods signals) in 4,249 COPD cases and 11,916 smoking controls from UK Biobank. We provide suggestive evidence for the combined effect of rare variants on COPD risk in TNXB and in sliding windows within MECOM and upstream of HHIP. These findings can lead to an improved understanding of the molecular pathways involved in the development of COPD},
keywords = {648, COPD, GWAS, lung function},
pubstate = {published},
tppubtype = {article}
}

@article{Jackson2016,
title = {Exome-wide analysis of rare coding variation identifies novel associations with COPD and airflow limitation in MOCS3, IFIT3 and SERPINA12},
author = {Victoria E Jackson, Ioanna Ntalla, Ian Sayers, Richard Morris, Peter Whincup, Juan-Pablo Casas, Antoinette Amuzu, Minkyoung Choi, Caroline Dale, Meena Kumari, Jorgen Engmann, Noor Kalsheker, Sally Chappell, Tamar Guetta-Baranes, Tricia M McKeever, Colin N A Palmer, Roger Tavendale, John W Holloway, Avan A Sayer, Elaine M Dennison, Cyrus Cooper, Mona Bafadhel, Bethan Barker, Chris Brightling, Charlotte E Bolton, Michelle E John, Stuart G Parker, Miriam F Moffat, Andrew J Wardlaw, Martin J Connolly, David J Porteous, Blair H Smith, Sandosh Padmanabhan, Lynne Hocking, Kathleen E Stirrups, Panos Deloukas, David P Strachan, Ian P Hall, Martin D Tobin, Louise V Wain },
url = {http://thorax.bmj.com/content/early/2016/02/25/thoraxjnl-2015-207876.abstract},
year = {2016},
date = {2016-02-25},
journal = {Thorax},
abstract = {
Background Several regions of the genome have shown to be associated with COPD in genome-wide association studies of common variants.

Objective To determine rare and potentially functional single nucleotide polymorphisms (SNPs) associated with the risk of COPD and severity of airflow limitation.

Methods 3226 current or former smokers of European ancestry with lung function measures indicative of Global Initiative for Chronic Obstructive Lung Disease (GOLD) 2 COPD or worse were genotyped using an exome array. An analysis of risk of COPD was carried out using ever smoking controls (n=4784). Associations with %predicted FEV1 were tested in cases. We followed-up signals of interest (p<10−5) in independent samples from a subset of the UK Biobank population and also undertook a more powerful discovery study by meta-analysing the exome array data and UK Biobank data for variants represented on both arrays.

Results Among the associated variants were two in regions previously unreported for COPD; a low frequency non-synonymous SNP in MOCS3 (rs7269297, pdiscovery=3.08×10−6, preplication=0.019) and a rare SNP in IFIT3, which emerged in the meta-analysis (rs140549288, pmeta=8.56×10−6). In the meta-analysis of % predicted FEV1 in cases, the strongest association was shown for a splice variant in a previously unreported region, SERPINA12 (rs140198372, pmeta=5.72×10−6). We also confirmed previously reported associations with COPD risk at MMP12, HHIP, GPR126 and CHRNA5. No associations in novel regions reached a stringent exome-wide significance threshold (p<3.7×10−7).

Conclusions This study identified several associations with the risk of COPD and severity of airflow limitation, including novel regions MOCS3, IFIT3 and SERPINA12, which warrant further study.
},
keywords = {648, COPD, genetics},
pubstate = {published},
tppubtype = {article}
}

@article{Wain2015,
title = {Novel insights into the genetics of smoking behaviour, lung function, and chronic obstructive pulmonary disease (UK BiLEVE): a genetic association study in UK Biobank},
author = {Louise V Wain, PhD, Nick Shrine, PhD, Suzanne Miller, PhD, Victoria E Jackson, MSc, Ioanna Ntalla, PhD, María Soler Artigas, PhD, Charlotte K Billington, PhD, Abdul Kader Kheirallah, BSc, Richard Allen, MSc, James P Cook, PhD, Kelly Probert, BSc, Ma'en Obeidat, PhD, Yohan Bossé, PhD, Ke Hao, ScD, Prof Dirkje S Postma, PhD, Peter D Paré, MD, Adaikalavan Ramasamy, DPhil, UK Brain Expression Consortium (UKBEC)†, Reedik Mägi, PhD, Evelin Mihailov, MSc, Eva Reinmaa, MSc, Erik Melén, MD, Jared O'Connell, DPhil, Eleni Frangou, MSc[Res], Olivier Delaneau, PhD, OxGSK Consortium†, Colin Freeman, PhD, Desislava Petkova, PhD, Prof Mark McCarthy, MD, Ian Sayers, PhD, Prof Panos Deloukas, PhD, Prof Richard Hubbard, MD, Ian Pavord, FMedSci, Anna L Hansell, MBBChir, Prof Neil C Thomson, MD, Eleftheria Zeggini, MD, Prof Andrew P Morris, PhD, Prof Jonathan Marchini, DPhil, Prof David P Strachan, MD*, Prof Martin D Tobin, PhDcorrespondence*email, Prof Ian P Hall, DM},
url = {http://www.thelancet.com/journals/lanres/article/PIIS2213-2600(15)00283-0/fulltext},
year = {2015},
date = {2015-09-28},
journal = {Lancet Respiratory},
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 assay rare coding variants relevant to the UK population. We investigated whether there were shared genetic causes between different phenotypes defined by extremes of FEV1. We also looked for novel variants associated with extremes of FEV1 and smoking behaviour and assessed regions of the genome that had already shown evidence for a role in lung health and disease. We set genome-wide significance at p<5 × 10−8.

Findings
UK Biobank participants were recruited from March 15, 2006, to July 7, 2010. Sample selection for the UK BiLEVE study started on Nov 22, 2012, and was completed on Dec 20, 2012. We selected 50 008 unique samples: 10 002 individuals with low FEV1, 10 000 with average FEV1, and 5002 with high FEV1 from each of the heavy smoker and never smoker groups. We noted a substantial sharing of genetic causes of low FEV1 between heavy smokers and never smokers (p=2·29 × 10−16) and between individuals with and without doctor-diagnosed asthma (p=6·06 × 10−11). We discovered six novel genome-wide significant signals of association with extremes of FEV1, including signals at four novel loci (KANSL1, TSEN54, TET2, and RBM19/TBX5) and independent signals at two previously reported loci (NPNT and HLA-DQB1/HLA-DQA2). These variants also showed association with COPD, including in individuals with no history of smoking. The number of copies of a 150 kb region containing the 5′ end of KANSL1, a gene that is important for epigenetic gene regulation, was associated with extremes of FEV1. We also discovered five new genome-wide significant signals for smoking behaviour, including a variant in NCAM1 (chromosome 11) and a variant on chromosome 2 (between TEX41 and PABPC1P2) that has a trans effect on expression of NCAM1 in brain tissue.

Interpretation
By sampling from the extremes of the lung function distribution in UK Biobank, we identified novel genetic causes of lung function and smoking behaviour. These results provide new insight into the specific mechanisms underlying airflow obstruction, COPD, and tobacco addiction, and show substantial shared genetic architecture underlying airflow obstruction across individuals, irrespective of smoking behaviour and other airway disease.

Funding
Medical Research Council.},
keywords = {648, Lung Disease, lung function},
pubstate = {published},
tppubtype = {article}
}