Abstract Background Chronic obstructive pulmonary disease (COPD) is a complex, heterogeneous disease influenced by genetic and environmental factors. However, the interactions between COPD risk genes and their collective role in COPD susceptibility remain largely elusive. We hypothesize that the protein-protein interaction (PPI) network of genes associated with COPD risk loci can provide insight into the mechanisms of COPD pathogenesis. Methods We used Affinity Purification Mass Spectrometry (AP-MS) to detect protein-protein interactions of six well-established COPD GWAS gene products (including AGER, FAM13A, FBXO38, HHIP, IREB2, MFAP2) in two relevant lung cell lines (IMR90, 16HBE). These genes are located in significant COPD GWAS regions, and their role in COPD has been previously confirmed by functional studies. We analyzed the impact of the newly identified interactions in contextual, cell type-specific PPI networks built from the combination of publicly available PPI data (HUBRIS) and cell type-specific gene expression data. Results Using AP-MS, we identified 482 unique interactors across 701 newly identified protein interactions with the six GWAS gene products (AGER: 122, FAM13A: 83, FBXO38: 71, HHIP: 108, IREB2: 8, MFAP2: 309 interactions from both cell lines). Subsequent network analysis incorporating these new PPIs with public PPI databases revealed: (1) the new interactions significantly reduce the network distance between COPD GWAS gene products compared to a null model of new edges connecting the GWAS genes to random interactors (p = 0.03); (2) 26.3% of the newly identified interactors are differentially expressed/abundant between COPD cases and controls in lung transcriptomic (16.8%) and/or proteomic (12.0%) data from the Lung Tissue Research Consortium (LTRC); (3) 152 (31.5%) of the newly identified interactors are directly connected to more than one of the six COPD GWAS genes; 47 (31%) of these 152 interactors showed differential protein levels in COPD vs. control lungs. We identified a tightly connected core network of multiple intersecting signals consisting of 8 proteins, which includes 4 of the 6 GWAS gene products (AGER, FBXO38, HHIP and MFAP2) as well as CAVIN1, MAPK1, TGM2, and THBS1, proteins with strong evidence in the scientific literature confirming their role in phenotypes associated with COPD. Conclusions By combining AP-MS experimental data, multiple types of “omics” data, and network analysis, we have constructed a disease network module related to COPD. This module can be a foundation for understanding the collective mechanism of COPD GWAS genes in disease pathogenesis. This abstract is funded by: NIH
Deritei et al. (Fri,) studied this question.