Abstract
BackgroundThere is a need for more powerful methods to identify low-effect SNPs that contribute to hereditary COPD pathogenesis. We hypothesized that SNPs contributing to COPD risk through cis-regulatory effects are enriched in genes comprised by bronchial epithelial cell (BEC) expression patterns associated with COPD.MethodsTo test this hypothesis, normal BEC specimens were obtained by bronchoscopy from 60 subjects: 30 subjects with COPD defined by spirometry (FEV1/FVC < 0.7, FEV1% < 80%), and 30 non-COPD controls. Targeted next generation sequencing was used to measure total and allele-specific expression of 35 genes in genome maintenance (GM) genes pathways linked to COPD pathogenesis, including seven TP53 and CEBP transcription factor family members. Shrinkage linear discriminant analysis (SLDA) was used to identify COPD-classification models. COPD GWAS were queried for putative cis-regulatory SNPs in the targeted genes.ResultsOn a network basis, TP53 and CEBP transcription factor pathway gene pair network connections, including key DNA repair gene ERCC5, were significantly different in COPD subjects (e.g., Wilcoxon rank sum test for closeness, p-value = 5.0E-11). ERCC5 SNP rs4150275 association with chronic bronchitis was identified in a set of Lung Health Study (LHS) COPD GWAS SNPs restricted to those in putative regulatory regions within the targeted genes, and this association was validated in the COPDgene non-hispanic white (NHW) GWAS. ERCC5 SNP rs4150275 is linked (D’ = 1) to ERCC5 SNP rs17655 which displayed differential allelic expression (DAE) in BEC and is an expression quantitative trait locus (eQTL) in lung tissue (p = 3.2E-7). SNPs in linkage (D’ = 1) with rs17655 were predicted to alter miRNA binding (rs873601). A classifier model that comprised gene features CAT, CEBPG, GPX1, KEAP1, TP73, and XPA had pooled 10-fold cross-validation receiver operator characteristic area under the curve of 75.4% (95% CI: 66.3%–89.3%). The prevalence of DAE was higher than expected (p = 0.0023) in the classifier genes.ConclusionsGM genes comprised by COPD-associated BEC expression patterns were enriched for SNPs with cis-regulatory function, including a putative cis-rSNP in ERCC5 that was associated with COPD risk. These findings support additional total and allele-specific expression analysis of gene pathways with high prior likelihood for involvement in COPD pathogenesis.
Highlights
There is a need for more powerful methods to identify low-effect Single nucleotide polymorphism (SNP) that contribute to hereditary chronic obstructive pulmonary disease (COPD) pathogenesis
Study subjects and biospecimens Homogeneous bronchial epithelial cell (BEC) biospecimens were obtained by bronchoscopic brush biopsy of normal appearing airway epithelium from 30 COPD and 30 nonCOPD control subjects who were enrolled in the Lung Cancer Risk Test (LCRT) study (NCT 01130285 at Clinicaltrials.gov) [91]
In addition to the BEC samples and matched peripheral blood cell (PBC) samples from 60 Lung cancer risk test (LCRT) subjects used in COPD classifier development, we evaluated archival BEC (120) and PBC (117) samples from additional subjects who were not characterized for COPD status for the purpose of differential allelic expression (DAE) analysis
Summary
There is a need for more powerful methods to identify low-effect SNPs that contribute to hereditary COPD pathogenesis. Each variant identified by COPD GWAS required large sample size for detection due to small effect on heritability [3, 4] Those that remain to be discovered will likely have an even lower effect. To address this challenge, one recent study was designed to discover rare coding variants with large effect on COPD risk, similar to that of alpha-1-antitrypsin deficiency [5]. One recent study was designed to discover rare coding variants with large effect on COPD risk, similar to that of alpha-1-antitrypsin deficiency [5] In another approach, GWAS metaanalyses were used to identify common SNPs with very low effect through very large sample size [3, 6, 7]
Sign-in/Register to view highlights & summary 
Published Version (
Free)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call