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