Integrated metabolomics coupled with pattern recognition and pathway analysis to reveal molecular mechanism of cadmium-induced diabetic nephropathy

Abstract

Abstract Diabetic nephropathy (DN) is becoming a worldwide public health problem and its pathophysiological mechanism is not well understood. Emerging evidences indicated that cadmium (Cd), an industrial material but also an environmental toxin, may be involved in the development and progression of diabetes and diabetes-related kidney disease. However, the underlying mechanism is still unclear. Herein, a DN animal model was constructed by exposing to Cd, the metabolomic profiling of DN mice were obtained by using ultra performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF/MS), pattern recognition and pathway analysis were performed to screen potential biomarker. Moreover, western blotting was employed to verify the possible mechanism involved in the occurrence of Cd-induced DN. A total of 66 metabolites in serum have been screened out and identified as biomarkers, including free fatty acids, phospholipids, sphingomyelins, glycerides, and others. Significant differences were demonstrated between the metabolic profiles, including decreased levels of phospholipid and increased content of triglyceride, diacylglycerols, ceramide, lysophosphatidylcholine in Cd-induced DN mice compared with control. Protein expression level of p38 MAPK and Wnt/β-catenin were significantly increased. UPLC-Q-TOF/MS-based serum metabolomics coupled with pattern recognition methods and pathway analysis provide a powerful approach to identify potential biomarkers and is a new strategy to predict the underlying mechanism of disease caused by environmental toxicant.