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Sci Rep. 2017 Mar 13;7:44232. doi: 10.1038/srep44232.

Functional interactors of three genome-wide association study genes are differentially expressed in severe chronic obstructive pulmonary disease lung tissue.

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Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA, USA.
Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA, USA.
Department of Medicine, New York Presbyterian/Weill Cornell Medical Center, New York, NY, USA.
Department of Critical Care Medicine and Pulmonary Disease, Baystate Medical Center, Springfield, MA, USA.
Division of Pulmonary and Critical Care Medicine, Temple University, Philadelphia, PA, USA.
Division of Thoracic Surgery, Brigham and Women's Hospital, Boston, MA, USA.
Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA, USA.


In comparison to genome-wide association studies (GWAS), there has been poor replication of gene expression studies in chronic obstructive pulmonary disease (COPD). We performed microarray gene expression profiling on a large sample of resected lung tissues from subjects with severe COPD. Comparing 111 COPD cases and 40 control smokers, 204 genes were differentially expressed; none were at significant GWAS loci. The top differentially expressed gene was HMGB1, which interacts with AGER, a known COPD GWAS gene. Differentially expressed genes showed enrichment for putative interactors of the first three identified COPD GWAS genes IREB2, HHIP, and FAM13A, based on gene sets derived from protein and RNA binding studies, RNA-interference, a murine smoking model, and expression quantitative trait locus analyses. The gene module most highly associated for COPD in Weighted Gene Co-Expression Network Analysis (WGCNA) was enriched for B cell pathways, and shared seventeen genes with a mouse smoking model and twenty genes with previous emphysema studies. As in other common diseases, genes at COPD GWAS loci were not differentially expressed; however, using a combination of network methods, experimental studies and careful phenotype definition, we found differential expression of putative interactors of these genes, and we replicated previous human and mouse microarray results.

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