Mokaram Doust Delkhah Arman, Ghazvini Ali, Arabfard Masoud
Chemical Injuries Research Center, Systems Biology and Poisonings Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran.
Biochem Biophys Rep. 2025 Aug 1;43:102193. doi: 10.1016/j.bbrep.2025.102193. eCollection 2025 Sep.
Chronic obstructive pulmonary disease (COPD) is a leading challenge of global public health that predominantly affects developing countries. Although smoking is the main risk factor, only a fraction of smokers develop COPD. This study aimed to identify biomarkers or therapeutic targets that would effectively aid early diagnosis and treatment of smoking-induced COPD.
After retrieving GSE27597, GSE38974, GSE47460, GSE76925, and GSE239897 from the Gene Expression Omnibus, never-smokers were excluded from each dataset. Differential expression analysis and weighted gene co-expression network analysis (WGCNA) were employed to discern a reliable gene list. Subsequently, integrated data, which incorporated 120 control and 349 COPD samples, was analyzed by random forest (RF) and least absolute shrinkage and selection operator (LASSO) methods to identify key genes. Lastly, 6 genes with the area under the receiver operating characteristic curve exceeding 0.7 were selected as potential biomarkers of smoking-induced COPD. , , , , , and exhibited similar expression patterns across the datasets, reflecting their prominent contribution to COPD pathogenesis.
These results suggested , , , , , and as key genes for the development of COPD among smokers. While these potential biomarkers were identified by computational analyses, experimental studies are needed to evaluate their clinical applicability.
慢性阻塞性肺疾病（COPD）是全球公共卫生面临的主要挑战，主要影响发展中国家。虽然吸烟是主要危险因素，但只有一小部分吸烟者会患上COPD。本研究旨在确定能够有效辅助吸烟所致COPD早期诊断和治疗的生物标志物或治疗靶点。
从基因表达综合数据库中检索GSE27597、GSE38974、GSE47460、GSE76925和GSE239897后，每个数据集中排除从不吸烟者。采用差异表达分析和加权基因共表达网络分析（WGCNA）来辨别出一份可靠的基因列表。随后，通过随机森林（RF）和最小绝对收缩和选择算子（LASSO）方法对纳入120例对照和349例COPD样本的整合数据进行分析，以识别关键基因。最后，选择6个受试者工作特征曲线下面积超过0.7的基因作为吸烟所致COPD的潜在生物标志物。 、 、 、 、 和 在各数据集中表现出相似的表达模式，反映了它们对COPD发病机制的突出贡献。
这些结果表明 、 、 、 、 和 是吸烟者中COPD发生发展的关键基因。虽然这些潜在生物标志物是通过计算分析确定的，但仍需要进行实验研究来评估它们的临床适用性。
