Identification of Metabolism-Associated Molecular Subtypes of Chronic Obstructive Pulmonary Disease

Purpose This study aimed to identify the COPD molecular subtypes reflecting pulmonary function damage on basis of metabolism-related gene expression, which provided opportunity metabolic heterogeneity and association pathways with damage. Methods Univariate linear regression Boruta algorithm were used select genes associated forced expiratory volume in first second (FEV1) FEV1/forced vital capacity (FVC) Evaluation Longitudinally Identify Predictive Surrogate Endpoints (ECLIPSE) cohort. further identified by consensus clustering best-fit. Then, we analyzed differences clinical characteristics, pathways, immune cell transcription features among subtypes. Results two (C1 C2). C1 exhibited higher levels lower innate immunity than C2. Ten confirmed as key pathways. The related N-glycan, hexosamine, purine, alanine, aspartate glutamate tended be positively abundance adaptive cells negatively cells. In addition, other had opposite trends. All results verified Genetic Epidemiology (COPDGene) datasets. Conclusion reflect help understand mechanism COPD. Further studies are needed prove prognostic therapeutic value