Integrating molecular interactions and gene expression to identify biomarkers and network modules of chronic obstructive pulmonary disease

Abstract

BACKGROUND: Chronic obstructive pulmonary disease (COPD) causes chronic obstructive conditions, chronic bronchitis, and emphysema, and is a major cause of death worldwide. Although several efforts for identifying biomarkers and pathways have been made, specific causal COPD mechanism remains unknown. OBJECTIVE: This study combined biological interaction data with gene expression data for a better understanding of the biological process and network module for COPD. METHODS: Using a sparse network-based method, we selected 49 genes from peripheral blood mononuclear cell expression data of 136 subjects, including 42 ex-smoking controls and 94 subjects with COPD. RESULTS: These 49 genes might influence biological processes and molecular functions related to COPD. For example, our result suggests that FoxO signaling may contribute to the atrophy of COPD peripheral muscle tissues via oxidative stress. CONCLUSIONS: Our approach enhances the existing understanding of COPD disease pathogenesis and predicts new genetic markers and pathways that may influence COPD pathogenesis.