Novel links identified between genetics, lung function and smoking behavior

1. In this genome-wide genetic association study based on UK Biobank data, novel genome-wide signals of association were found between 6 loci and extremes of FEV1 (forced expiratory volume in 1 second).

2. Significant signals of association between 5 novel loci and smoking behavior were also identified.

Evidence Rating Level: 2 (Good)

Study Rundown: The association between tobacco smoking and lung diseases such as chronic obstructive pulmonary disease (COPD) has been firmly established. As the third leading cause of death in the US, COPD affects more than 30 million patients and is a major source of public health burden. Genetic susceptibilities to COPD have long been suspected, as development and progression vary significantly between individuals. However, understanding of its genetic components remains incomplete. In the current study, investigators sampled data from the UK Biobank and developed a custom array (Affymetrix Axiom) for genome-wide coverage, with dense coverage of regions known to be related to lung health and disease. The array was then used for genome-wide genotyping and to correlate clinically with patients’ lung function status, measured as forced expiratory volume in 1 second (FEV1). Several signals of association were noted between genotypes and low FEV1 regardless of tobacco use, as well as between genotypes and low FEV1 in with and without asthma. In addition, signals of association were also identified with smoking behavior by comparing heavy smokers and never smokers. The study results may eventually assist in identifying smokers most likely to progress to severe disease. One potential limitation is that the study used self-reporting of doctor-diagnosed asthma for asthma patients, and may have captured a slightly different subset of patients compared to US clinical practice.

The study was funded by Medical Research Council.

Click to read the study, published today in The Lancet

Relevant Reading: The COPD genetic association compendium: a comprehensive online database of COPD genetic associations

In-Depth: This genetic association study was based on data from the UK Biobank and aimed to analyze associations between variants of genotypes and the lung function status of patients. The lung function status was measured as FEV1, or forced expiratory volume in 1 second on spirometry. Genome-wide genotyping was performed with a new custom Affymetrix Axiom array (UK BiLEVE array; Santa Clara, CA, USA), with a particular focus on areas of human genome thought to be related to lung health and disease. Association test was performed with a Score test with imputed marker doses and adjusted for pack-years in smokers. A statistical level of p<5×10^-8 was used as the cut-off for genomic association analyses, and 5×10^‑8<p<5×10^-7 was used as the statistical range for suggestion of significance.

Substantial sharing of genetic causes was found between low FEV1 in heavy smokers and low FEV1 in never smokers (p=2.29×10^-16; p value threshold <0.5). Novel signals of association with p<5×10^-8 were identified between low FEV1 and 6 loci (TET2, NPNT, HLA-DQB1/HLA-DQA2, KANSL1, TSEN54, and RBM19/TBX5). Novel signals of association with p<5×10^-8 were also identified between smoking behavior (heavy smokers versus non-smokers) and 5 loci (NCAM1, TEX41/PABPC1P2, NOL4L, LPPR5, and DNAH8).

Image: PD

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