Genome-wide association studies (GWAS) of complex diseases like COPD have identified many genomic regions associated with disease, but the molecular mechanisms by which these genetic loci influence disease pathogenesis are largely unknown. The phenotypic effects of genetic alterations can result from disruptions of the coordinated interactions between proteins. However, the key genes within COPD GWAS loci have only been proven in a minority of those COPD GWAS regions, and network connections between the COPD GWAS gene products have rarely been identified. In this project, we will utilize COPD susceptibility genes supported by both GWAS and murine emphysema models to develop cell type-specific and disease-specific protein-protein interaction network modules related to COPD. We hypothesize that building disease network modules based on experimentally validated protein-protein interactions between COPD GWAS genes will identify novel biological connections that influence COPD-related disease processes of cell death, cellular senescence, and/or inflammation. We will perform affinity purification/mass spectrometry (AP-MS) assays of nine well-established COPD GWAS gene products. Interacting proteins that are part of network links between COPD GWAS genes based on the AP-MS assays will be further validated with co-immunoprecipitation assays. We will utilize disease network module building approaches that combine the new AP-MS experiments with existing molecular interactome data to find biological linkages between COPD GWAS gene products. We will identify cell type- specific protein-protein interaction networks by removing non-expressed genes based on RNA-Seq data in bronchial epithelial cells and alveolar macrophages, and disease-specific protein-protein interaction networks based on TOPMed RNA-Seq data from lung tissue in the Lung Tissue Research Consortium. For network paths linking COPD GWAS genes in the protein-protein interaction network, we will perturb disease network module components using CRISPR-Cas9 approaches. First, we will assess the effects of these perturbations on protein interactions of putative disease network paths. Second, we will assess the impact of these network node removal perturbations on cell-based COPD-related readouts, including cell death, cellular senescence, and inflammation. Positive phenotypic readouts in cell line experiments will be validated in primary human lung cells. This project will combine state-of-the-art computational and laboratory approaches to identify the protein-protein interaction network relationships between COPD GWAS genes within multiple lung cell types and to validate those network relationships using cell-based readouts of relevant biological processes for COPD pathogenesis.
Chronic obstructive pulmonary disease (COPD) is a major public health problem that is strongly influenced by cigarette smoking and genetic predisposition. Although previous studies have identified genomic regions associated with COPD, the networks of interacting genes and proteins that influence COPD have not been identified. We will use protein-protein interaction data to build biological networks related to COPD susceptibility, which will provide new insights into the biological mechanisms causing COPD and suggest new pathways for treatment.