The raw LC–MS data were first processed with Compound Discover 2.0 software (Thermo Fisher Scientific). The Compound Discover software finds components that have reproducible differences across multiple sample groups. The resultant data matrix including m/z, RT and intensity was imported into the SIMCA-P 14.0 (Umetrics, Umea, Sweden) software for multivariate statistical analysis. PCA and OPLS-DA analyses were performed, and the variable importance projection (VIP) value was used to screen potential biomarkers. Metabolites of interest (candidate biomarkers) were identified based on their accurate masses and/or MS/MS spectra information in both positive and negative ion mode. HMDB, KEGG and mzCloud databases were searched to assist with metabolite identification. Pathway analysis of the significant altered metabolites was performed with MetaboAnalyst 4.0.