Whole exome sequencing analysis in severe chronic obstructive pulmonary disease. (27th July 2018)

• Record Type: Journal Article
• Authors: Qiao, Dandi; Ameli, Asher; Prokopenko, Dmitry; Chen, Han; Kho, Alvin T; Parker, Margaret M; Morrow, Jarrett; Hobbs, Brian D; Liu, Yanhong; Beaty, Terri H; Crapo, James D; Barnes, Kathleen C; Nickerson, Deborah A; Bamshad, Michael; Hersh, Craig P; Lomas, David A; Agusti, Alvar; Make, Barry J; Calverley, Peter M A; Donner, Claudio F; Wouters, Emiel F; Vestbo, Jørgen; Paré, Peter D; Levy, Robert D; Rennard, Stephen I; Tal-Singer, Ruth; Spitz, Margaret R; Sharma, Amitabh; Ruczinski, Ingo; Lange, Christoph; Silverman, Edwin K; Cho, Michael H;
• Is Part Of: Human molecular genetics. Volume 27:Number 21(2018:Nov. 01)
• Page Start: 3801
• Page End: 3812
• Publication Date: 2018-07-27
• Subjects: Human molecular genetics -- Periodicals; Human chromosome abnormalities -- Periodicals; 572.8
• DOI: 10.1093/hmg/ddy269
• Languages: English
• ISSNs: 0964-6906

Abstract

Abstract: Chronic obstructive pulmonary disease (COPD), one of the leading causes of death worldwide, is substantially influenced by genetic factors. Alpha-1 antitrypsin deficiency demonstrates that rare coding variants of large effect can influence COPD susceptibility. To identify additional rare coding variants in patients with severe COPD, we conducted whole exome sequencing analysis in 2543 subjects from two family-based studies (Boston Early-Onset COPD Study and International COPD Genetics Network) and one case–control study (COPDGene). Applying a gene-based segregation test in the family-based data, we identified significant segregation of rare loss of function variants in TBC1D10A and RFPL1 ( P -value < 2x10–6), but were unable to find similar variants in the case–control study. In single-variant, gene-based and pathway association analyses, we were unable to find significant findings that replicated or were significant in meta-analysis . However, we found that the top results in the two datasets were in proximity to each other in the protein–protein interaction network ( P -value = 0.014), suggesting enrichment of these results for similar biological processes. A network of these association results and their neighbors was significantly enriched in the transforming growth factor beta-receptor binding and cilia-related pathways. Finally, in a more detailed examination of candidate genes, we identified individuals with putative high-risk variants, including patients harboring homozygous mutations in genes associated with cutis laxa and Niemann–Pick Disease Type C. Our results likely reflect heterogeneity of genetic risk for COPD along with limitations of statistical power and functional annotation, and highlight the potential of network analysis to gain insight into genetic association studies.