Supplementary Material for: Beyond GWAS in COPD: Probing the Landscape between Gene-Set Associations, Genome-Wide Associations and Protein-Protein Interaction Networks
2014-08-27T00:00:00Z (GMT) by
<b><i>Objectives:</i></b> To use a systems biology approach to integrate genotype and protein-protein interaction (PPI) data to identify disease network modules associated with chronic obstructive pulmonary disease (COPD) and to perform traditional pathway analysis. <b><i>Methods:</i></b> We utilized a standard gene-set association approach (FORGE) using gene-based association analysis and gene-set definitions from the molecular signatures database (MSigDB). As a discovery step, we analyzed GWAS results from 2 well-characterized COPD cohorts: COPDGene and GenKOLS. We used a third well-characterized COPD case-control cohort for replication: ECLIPSE. Next, we used dmGWAS, a method that integrates GWAS results with PPI, to identify COPD disease modules. <b><i>Results:</i></b> No gene-sets reached experiment-wide significance in either discovery population. We identified a consensus network of 10 genes identified in modules by integrating GWAS results with PPI that replicated in COPDGene, GenKOLS, and ECLIPSE. Members of 4 gene-sets were enriched among these 10 genes: (i) lung adenocarcinoma tumor-sequencing genes, (ii) IL-7 pathway genes, (iii) kidney cell response to arsenic, and (iv) CD4 T-cell responses. Further, several genes have also been associated with pathophysiology relevant to COPD including <i>KCNK3</i>, <i>NEDD4L</i>, and <i>RIN3</i>. In particular, <i>KCNK3</i> has been associated with pulmonary arterial hypertension, a common complication in advanced COPD. <b><i>Conclusion:</i></b> We report a set of new genes that may influence the etiology of COPD that would not have been identified using traditional GWAS and pathway analyses alone.