Begum Ferdouse, Ruczinski Ingo, Li Shengchao, Silverman Edwin K, Cho Michael H, Lynch David A, Curran-Everett Douglas, Crapo James, Scharpf Robert B, Parker Margaret M, Hetmanski Jacqueline B, Beaty Terri H
Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America.
Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America.
Genet Epidemiol. 2016 Jan;40(1):81-8. doi: 10.1002/gepi.21943. Epub 2015 Dec 7.
Chronic obstructive pulmonary disease (COPD) is a progressive disease with both environmental and genetic risk factors. Genome-wide association studies (GWAS) have identified multiple genomic regions influencing risk of COPD. To thoroughly investigate the genetic etiology of COPD, however, it is also important to explore the role of copy number variants (CNVs) because the presence of structural variants can alter gene expression and can be causal for some diseases. Here, we investigated effects of polymorphic CNVs on quantitative measures of pulmonary function and chest computed tomography (CT) phenotypes among subjects enrolled in COPDGene, a multisite study. COPDGene subjects consist of roughly one-third African American (AA) and two-thirds non-Hispanic white adult smokers (with or without COPD). We estimated CNVs using PennCNV on 9,076 COPDGene subjects using Illumina's Omni-Express genome-wide marker array. We tested for association between polymorphic CNV components (defined as disjoint intervals of copy number regions) for several quantitative phenotypes associated with COPD within each racial group. Among the AAs, we identified a polymorphic CNV on chromosome 5q35.2 located between two genes (FAM153B and SIMK1, but also harboring several pseudo-genes) giving genome-wide significance in tests of association with total lung capacity (TLCCT ) as measured by chest CT scans. This is the first study of genome-wide association tests of polymorphic CNVs and TLCCT . Although the ARIC cohort did not have the phenotype of TLCCT , we found similar counts of CNV deletions and amplifications among AA and European subjects in this second cohort.
慢性阻塞性肺疾病(COPD)是一种具有环境和遗传风险因素的进行性疾病。全基因组关联研究(GWAS)已经确定了多个影响COPD风险的基因组区域。然而,为了全面研究COPD的遗传病因,探索拷贝数变异(CNV)的作用也很重要,因为结构变异的存在可以改变基因表达,并且可能是某些疾病的病因。在这里,我们在一项多中心研究COPDGene中,调查了多态性CNV对肺功能定量指标和胸部计算机断层扫描(CT)表型的影响。COPDGene研究对象大致由三分之一的非裔美国人(AA)和三分之二的非西班牙裔白人成年吸烟者(有或没有COPD)组成。我们使用Illumina公司的全基因组标记芯片Omni-Express,通过PennCNV软件在9076名COPDGene研究对象中估计CNV。我们测试了每个种族群体中与COPD相关的几种定量表型的多态性CNV成分(定义为拷贝数区域的不连续区间)之间的关联。在非裔美国人中,我们在5号染色体q35.2区域发现了一个多态性CNV,它位于两个基因(FAM153B和SIMK1,但也包含几个假基因)之间,在与胸部CT扫描测量的肺总量(TLCCT)的关联测试中具有全基因组显著性。这是对多态性CNV与TLCCT进行全基因组关联测试的第一项研究。虽然动脉粥样硬化风险社区(ARIC)队列没有TLCCT表型,但我们在第二个队列的非裔美国人和欧洲研究对象中发现了类似数量的CNV缺失和扩增。