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Introduction: Chronic obstructive pulmonary disease (COPD) is a complex disease involving inflammation, cell senescence, and autoimmunity. Dialectical treatment for COPD with traditional Chinese medicine (TCM) has the advantage of fewer side effects, more effective suppression of inflammation, and improved immune function. However, the biological base of TCM pattern differentiation in COPD remains unclear., Methods: Liquid Chromatography-Quadrupole-Orbitrap mass spectrometry (LC-Q-Orbitrap MS/MS) based metabolomics and lipidomics were used to analyze the serum samples from COPD patients of three TCM patterns in Lung Qi Deficiency (n=65), Lung-Kidney Qi Deficiency (n=54), Lung-Spleen Qi Deficiency (n=52), and healthy subjects (n=41). Three cross-comparisons were performed to characterize metabolic markers for different TCM patterns of COPD vs healthy subjects., Results: We identified 28, 8, and 16 metabolites with differential abundance between three TCM patterns of COPD vs healthy subjects, respectively, the metabolic markers included cortisol, hypoxanthine, fatty acids, alkyl-/alkenyl-substituted phosphatidylethanolamine, and phosphatidylcholine, etc. Three panels of metabolic biomarkers specific to the above three TCM patterns yielded areas under the receiver operating characteristic curve of 0.992, 0.881, and 0.928, respectively, with sensitivity of 97.1%, 88.6%, and 91.4%, respectively, and specificity of 96.4%, 81.8%, and 83.9%, respectively., Discussion: Combining metabolomics and lipidomics can more comprehensively and accurately trace metabolic markers. As a result, the differences in metabolism were proven to underlie different TCM patterns of COPD, which provided evidence to aid our understanding of the biological basis of dialectical treatment, and can also serve as biomarkers for more accurate diagnosis., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Li, Liu, Shi, Xie, Yang, Du, Zhang and Wu.)