Plasma lipidomic profiling of thiopurine-induced leukopenia after NUDT15 genotype-guided dosing in Chinese IBD patients - Li, Pan; Chao, Kang; Hu, Zhanhua; Qin, Lulu; Yang, Ting; Mao, Jing; Zhu, Xia; Hu, Pinjin; Wang, Xueding; Gao, Xiang; Huang, Min (Frontiers in Nutrition, 2023)
Thiopurines, azathiopurine (AZA) and mercaptopurine (6-MP) have been regularly used for the treatment of inflammatory bowel disease (IBD) patients. Even with optimized dosage based on the NUDT15 genotypes, some patients still discontinue or change treatment regimens due to thiopurine-induced leukopenia. Therefore, we performed a prospective observational study of lipidomics to reveal the lipids perturbations associated with thiopurine-induced leukopenia. One hundred and twenty-seven IBD participants treated with thiopurine were enrolled (27 IBD patients developed thiopurine-induced leucopenia and 100 patients did not). Plasma lipid profiles were measured using ultrahigh-performance liquid chromatography coupled with Q-Exactive spectrometry. Lipidomic alterations were validated with an independent validation cohort (leukopenia n=26, non-leukopenia n=74). Using univariate and multivariate analysis, there were 16 lipid species from four lipid classes, triglyceride (n=11), sphingomyelin (n=1), phosphatidylcholine (n=1) and lactosylceramide(n=3) identified. Based on machine learning feature reduction and variable screening strategies, the random forest algorithm established by six lipids showed an excellent performance to distinguish the leukopenia group from the normal group, with a model accuracy of 95.28% (discovery cohort), 79.00% (validation cohort) and an area under the receiver operating characteristic (ROC) curve (ROC-AUC) of 0.9989(discovery cohort), 0.8098(validation cohort). Collectively, lipidomic provided unique insights into formulating individualized medication strategies for thiopurines in IBD patients.