We present here a combined GC–MS and LC–MS metabolic profiling approach to unraveling the pathological outcomes of aristolochic acid (AA)-induced nephrotoxicity. Urine samples were analyzed by GC–MS and LC–MS in combination with pattern recognition techniques, e.g. principal component analysis (PCA), orthogonal projection to latent structure-discriminant analysis. The work indicates that AA-induced acute renal toxicity as evidenced by histopathological examinations could be characterized by systemic disturbance of metabolic network involving free fatty acids generation, energy and amino acids metabolism, and alteration in the structure of gut microbiota. Therefore, this method is potentially applicable to the toxicological study, providing a comprehensive understanding of systems response to xenobiotic intervention.