Background: The molecular links between metabolism and inflammation that drive different inflammatory phenotypes in asthma are poorly understood. Objectives: To identify the metabolic signatures and underlying molecular pathways of different inflammatory asthma phenotypes. Method: In the discovery set (n=119), untargeted ultra-high performance liquid chromatography–mass spectrometry (UHPLC-MS) were applied to characterize the induced sputum metabolic profiles from asthmatic patients classified by different inflammatory phenotypes using orthogonal partial least-squares discriminant analysis (OPLS-DA) and pathway topology enrichment analysis. In the validation set (n = 114), differential metabolites were selected to perform targeted quantification. Correlations between targeted metabolites and clinical indexes in asthma patients were analyzed. Logistic and negative binomial regression models were established to assess the association between metabolites and severe asthma exacerbation. Results: 77 differential metabolites were identified in the discovery set. Pathway topology analysis uncovered that histidine metabolism, glycerophospholipid metabolism, nicotinate and nicotinamide metabolism, linoleic acid metabolism, phenylalanine, tyrosine and tryptophan biosynthesis were involved in the pathogenesis of different asthma phenotypes. In the validation set, 24 targeted quantification metabolites were significantly differentially expressed between asthma inflammatory phenotypes. Finally, adenosine 5’-monophosphate (RRadj = 1.000, 95%CI = [1.000, 1.000], P = 0.050), allantoin (RRadj = 1.000, 95%CI = [1.000, 1.000], P = 0.043) and nicotinamide (RRadj = 1.001, 95%CI = [1.000, 1.002], P = 0.021) were demonstrated to predict severe asthma exacerbation rate ratios. Conclusions: Different inflammatory asthma phenotypes have specific metabolic profiles in induced sputum. The potential metabolic signatures may serve as identification and therapeutic target in different inflammatory asthma phenotypes.