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1H NMR based pharmacometabolomics analysis of metabolic phenotype on predicting metabolism characteristics of losartan in healthy volunteers
Journal of Chromatography B ( IF 2.8 ) Pub Date : 2018-07-17 , DOI: 10.1016/j.jchromb.2018.07.016
Chenjie He , Yongbin Liu , Yicheng Wang , Jie Tang , Zhirong Tan , Xi Li , Yao Chen , Yuanfei Huang , Xiaoping Chen , Dongsheng Ouyang , Honghao Zhou , Jingbo Peng

Inter-individual variability in drug metabolism and disposition is common in both preclinical and clinical researches. Losartan and its active metabolite EXP3174 present a high degree of inter-individual differences in blood concentrations that affect drug efficacy and side effect. Pharmacometabolomics has been increasingly applied on predicting the drug responses by analyzing the differences in metabolic profile. A pre-dose metabolic phenotype was investigated to interpret inter-individual variations in the metabolism characteristics of losartan. 1H Nuclear Magnetic Resonance (NMR) spectroscopy-based metabolic profiles were performed on 36 healthy Chinese male volunteers by measuring their pre-dose plasma samples. After oral administration of losartan, the concentrations of losartan and its bioactive metabolite EXP3174 were monitored by liquid chromatography-mass spectrometry (LC-MS). Orthogonal partial least-squares (O-PLS) model was conducted to select potential biomarkers that substantially contributed to the inter-individual variations in the metabolism features via analyzing the ratio of pharmacokinetics (PK) parameters of its metabolite to parent drug. Potential metabolites such as glycine, phosphorylcholine, choline, creatine, creatinine, lactate, citrate, α-glucose, and lipids showed strong correlations with metabolism features of losartan. In addition, the pathway analysis revealed that baseline lipid metabolism, the glycine, serine and threonine pathway, and glycolysis or gluconeogenesis metabolism pathway were significantly associated with the ratio of PK parameters of EXP3174 to losartan. Step-wise multiple linear regression (MLR) was constructed to investigate the potential roles of the selected biomarkers in predicting individualized metabolism characteristics of losartan. These results showed that the pre-dose individual metabolic traits may be a useful approach for characterizing individual differences in losartan metabolism characteristics and therefore for expediting personalized dose-setting in further clinical studies.

更新日期:2018-07-17
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