Abstract: Inflammation can occur at any time in many diseases, and affect the activity of metabolism enzymes and transporters, so change the blood concentration and therapeutic effect of therapeutic drugs. Therefore, it is necessary to study the metabolic changes during the acute-phase response (APR) of inflammation. In this study, urine metabolomics was performed to investigate the possible differential metabolic pathways in New Zealand white rabbit APR inflammation model. An APR rabbit model with normal hepatic and renal function was induced by intravenous injection of lipopolysaccharide (LPS) in low-dose escalation, at 0.1, 0.2, 0.5, 1, 1.5, 2 and 2 μg/kg from 1 to 7 days. The urine samples were collected at prior of dosing, 2-day and 7-day after the first dose of LPS, and detected using ultra-high liquid chromatography coupled with high resolution mass spectrometry (UPLC-HRMS). The samples were separated by a Kinetex F5 column (150 mm×2.1 mm×2.6 μm) with the mobile phase of water containing 0.05% formic acid and acetonitrile containing 0.05% formic acid. ZenoTOF^TM 7600 HRMS was operated under positive and negative ion modes to collect data, and the high-resolution mass spectral data was acquired by utilizing information dependent acquisition (IDA) and dynamic background subtraction (DBS). Non-targeted metabolomics analysis was completed by principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) to search for differential metabolites. Then the differential metabolic pathway analysis was carried out using the metaboAnalyst 5.0 website and KEGG database. The analysis results indicated that the method has high stability and reproducibility with quality control samples clustered together in PCA. The quality control and APR model groups can be separated well by OPLS-DA, which showed that the metabolism in rabbits is significantly disturbed during APR period. Clustering heatmap analysis was performed on the screened differential metabolites which were judged by variable importance projection (VIP>1), significance (p<0.05), and folds of change (FC>2). The results showed differential metabolites in urine at 2-day and 7-day after LPS administration are significantly different from those before administration, 41 and 161 differential metabolites are identified in the two groups of samples, respectively. Furtherly, the differential metabolic pathway analysis revealed that the differential metabolites are significantly correlated with the steroid hormone biosynthesis pathway (p<0.01). Pregnenolone, 11-deoxycorticosterone, 17α,21-dihydroxypregnenolone, 11-deoxycortisol, dehydroepiandrosterone sulphate, 19-oxosteroids, cortisol, 16α-hydroxyandrost-4-ene-3,17-dione, epinephrine, 19-oxoandrost-4-ene-3,17-dione, cortisone, 11β-hydroxyprogesterone, 18-hydroxycorticosterone, 11-dehydrocorticosterone, estrone glucosinolate, and corticosterone are in an up-regulated trend on steroid hormone biosynthesis pathway. The study provides the important information for target verification and disease treatment during the APR of inflammation, and facilitates further understanding of inflammatory response mechanisms.