Matsumura K, et al. - Due to the complexity and heterogeneity of the pathogenesis in smokers or early stage of chronic obstructive pulmonary disease (COPD) patients, difficulties are encountered in their prognosis, researchers here investigated if computational analyses of omics technologies could serve as one of the solutions to resolve such complexities. The potential descriptive marker genes were sought via assessing transcriptomic data by in vitro testing with exposures of human bronchial epithelial cells to the inducers for early events of COPD. In vitro tissues exposed to known inducible factors for earlier events of COPD (exposure to cigarette smoke, DNA damage, oxidative stress, and inflammation) commonly showed the expression levels of 15 genes; of these, 10 genes and their corresponding proteins have not previously reported as COPD biomarkers. Although these genes allowed prediction of each group with 65% accuracy, the accuracy with which they distinguished COPD individuals from smokers was only 29%. Furthermore, logistic regression allowed the conversion of gene expression levels to a numerical index, the “potential risk factor (PRF)” index that can quantitatively reflect the risk continuum across smoking and COPD pathogenesis. It is expected to enhance the understanding concerning smoking effects and provide new insights into COPD.