Abstract
Recently, several genes and genetic loci associated with both asthma and chronic obstructive pulmonary disease (COPD) have been described as common susceptibility factors for the two diseases. In complex diseases such as asthma and COPD, a large number of molecular and cellular components may interact through complex networks involving gene-gene and gene-environment interactions. We sought to understand the functional and regulatory pathways that play central roles in the pathobiology of asthma and COPD and to understand the overlap between these pathways. We searched the PubMed database up to September 2012 to identify genes found to be associated with asthma, COPD, tuberculosis, or essential hypertension in at least two independent reports of candidate-gene associations or in genome-wide studies. To learn how the identified genes interact with each other and other cellular proteins, we conducted pathway-based analysis using Ingenuity Pathway Analysis software. We identified 108 genes and 58 genes that were significantly associated with asthma and COPD in at least two independent studies, respectively. These susceptibility genes were grouped into networks based on functional annotation: 12 (for asthma) and eleven (for COPD) networks were identified. Analysis of the networks for overlap between the two diseases revealed that the networks form a single complex network with 229 overlapping molecules. These overlapping molecules are significantly involved in canonical pathways including the "aryl hydrocarbon receptor signaling," "role of cytokines in mediating communication between immune cells," "glucocorticoid receptor signaling," and "IL-12 signaling and production in macrophages" pathways. The Jaccard similarity index for the comparison between asthma and COPD was 0.81 for the network-level comparison, and the odds ratio was 3.62 (P < 0.0001) for the asthma/COPD pair in comparison with the tuberculosis/ essential hypertension pair. In conclusion, although the identification of asthma and COPD networks is still far from complete, these networks may be used as frameworks for integrating other genome-scale information including expression profiling and phenotypic analysis. Network overlap between asthma and COPD may indicate significant overlap between the pathobiology of these two diseases, which are thought to be genetically related.