Publication Details

AFRICAN RESEARCH NEXUS

SHINING A SPOTLIGHT ON AFRICAN RESEARCH

medicine

Exome-wide analysis of rare coding variation identifies novel associations with COPD and airflow limitation in MOCS3, IFIT3 and SERPINA12

Thorax, Volume 71, No. 6, Year 2016

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 metaanalysing 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.

Statistics
Citations: 40
Authors: 40
Affiliations: 27
Identifiers
Research Areas
Genetics And Genomics
Noncommunicable Diseases
Study Design
Cross Sectional Study
Study Approach
Systematic review