A PHARMACOMETABONOMICS STUDY TO PREDICT AZATHIOPRINE (AZA)-INDUCED MYELOTOXICITY IN PATIENTS WITH RHEUMATOLOGICAL DISEASE

Azathioprine (AZA) is an immunosuppressive agent widely used in clinical therapy. However, the application of AZA is restricted by its myelotoxicity. AZA-induced myelotoxicity varies greatly among patients, so it is difficult to predict. In this study, untargeted metabolomics based on Ultra Performance Liquid Chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC Q-TOF/MS) was performed to identify metabolite biomarkers for predicting AZA-induced myelotoxicity in Chinese rheumatological disease patients. Fifty-two patients diagnosed with rheumatological disease at the Quanzhou First Hospital Affiliated with Fujian Medical University, Fujian, China, were enrolled in this study. Patients were assigned to an ADR group (patients with myelotoxicity) (n = 15) or a NO ADR group (patients without myelotoxicity) (n = 15), and 22 patients without myelotoxicity withdrew, according to the presence of myelotoxicity. Serum was collected prior to treatment with AZA. Then, untargeted metabolomics based on LC/MS was performed to analyze the metabolic differences between the two groups. Several Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were significantly enriched in differential metabolites found between two groups (P 0.05, impact 0.1); the most enriched pathway, with an impact factor of 0.63, was the Sphingolipid metabolism pathway. Twenty-two potential biomarkers were identified. Finally, two candidate biomarkers were selected to predict AZA-induced myelotoxicity, namely, sphingomyelin SM(d18:1/24:1(15Z)), phytosphingosine. They may be useful biomarkers for predicting AZA-induced myelotoxicity in Chinese patients with rheumatological disease. This study can aid future clinical studies of AZA-induced myelotoxicity and the development of personalized medicine.