Abstract
BackgroundIdentifying or prioritizing genes for chronic obstructive pulmonary disease (COPD), one type of complex disease, is particularly important for its prevention and treatment.MethodsIn this paper, a novel method was proposed to Prioritize genes using Expression information in Protein–protein interaction networks with disease risks transferred between genes (abbreviated as PEP). A weighted COPD PPI network was constructed using expression information and then COPD candidate genes were prioritized based on their corresponding disease risk scores in descending order.ResultsFurther analysis demonstrated that the PEP method was robust in prioritizing disease candidate genes, and superior to other existing prioritization methods exploiting either topological or functional information. Top-ranked COPD candidate genes and their significantly enriched functions were verified to be related to COPD. The top 200 candidate genes might be potential disease genes in the diagnosis and treatment of COPD.ConclusionsThe proposed method could provide new insights to the research of prioritizing candidate genes of COPD or other complex diseases with expression information from sequencing or microarray data.
Highlights
Identifying or prioritizing genes for chronic obstructive pulmonary disease (COPD), one type of complex disease, is important for its prevention and treatment
Parameters of the PEP method Optimal value of parameter h Parameter h was used to evaluate the significance of the COPD disease genes and candidate genes in the weighted COPD protein–protein interactions (PPIs) network
Leave One Out Cross-Validation (LOOCV) was used to investigate the performance for a range of h values (1, 10, 15 and 30), which were shown as Receiver Operation Characteristic (ROC) curves (Fig. 1)
Summary
Identifying or prioritizing genes for chronic obstructive pulmonary disease (COPD), one type of complex disease, is important for its prevention and treatment. Chronic obstructive pulmonary disease (COPD) is a public health problem causing morbidity and mortality [1]. As a multifactorial and polygenic disease, COPD is caused by many factors, including smoking, advanced age, systemic inflammation, and especially pathways or processes influenced by protein–protein interactions (PPIs), such as oxidative stress and protease activity affected by interactions between glutathione S-transferase M1 and matrix metalloproteinases 1, 9, and 12 in the pathogenesis of COPD [2]. Identification or prioritizing COPD candidate genes is important for its prevention and treatment
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