Da-Yong Hu1, Ying Luo1, Chang-Bin Li1, Chun-Yu Zhou1, Xin-Hua Li1, Ai Peng1, Jun-Yan Liu2. 1. Division of Nephrology and Rheumatology, Shanghai Tenth People's Hospital, Center for Nephrology and Metabolomics, Tongji University School of Medicine, Shanghai, People's Republic of China. 2. Division of Nephrology and Rheumatology, Shanghai Tenth People's Hospital, Center for Nephrology and Metabolomics, Tongji University School of Medicine, Shanghai, People's Republic of China. jyliu@tongji.edu.cn.
Abstract
INTRODUCTION: Nearly all the enzymes that mediate the metabolism of polyunsaturated fatty acids (PUFAs) are present in the kidney. However, the correlation of renal dysfunction with PUFAs metabolism in uremic patients remains unknown. OBJECTIVES: To test whether the alterations in the metabolism of PUFAs reflect the renal dysfunction in uremic patients. METHODS: LC-MS/MS-based oxylipin profiling was conducted for the plasma samples from the uremic patients and controls. The data were analyzed by principal component analysis (PCA) and orthogonal partial least squares-discriminant analysis (OPLS-DA). The receiver operating characteristic (ROC) curves and the correlation of the estimated glomerular filtration rate (eGFR) with the key markers were evaluated. Furthermore, qPCR analysis of the whole blood cells was conducted to investigate the possible mechanisms. In addition, a 2nd cohort was used to validate the findings from the 1st cohort. RESULTS: The plasma oxylipin profile distinguished the uremic patients from the controls successfully by using both PCA and OPLS-DA models. 5,6-Dihydroxyeicosatrienoic acid (5,6-DHET), 5-hydroxyeicosatetraenoic acid (5-HETE), 9(10)-epoxyoctadecamonoenoic acid [9(10)-EpOME] and 12(13)-EpOME were identified as the key markers to discriminate the patients from controls. The excellent predictive performance of these four markers was validated by ROC analysis. The eGFR significantly correlated with plasma levels of 5,6-DHET and 5-HETE positively but with plasma 9(10)-EpOME and 12(13)-EpOME negatively. The changes of these markers may account for the inactivation of cytochrome P450 2C18, 2C19, microsome epoxide hydrolase (EPHX1), and 5-lipoxygenase in the patients. CONCLUSION: The alterations in plasma metabolic profile reflect the renal dysfunction in the uremic patients.
INTRODUCTION: Nearly all the enzymes that mediate the metabolism of polyunsaturated fatty acids (PUFAs) are present in the kidney. However, the correlation of renal dysfunction with PUFAs metabolism in uremicpatients remains unknown. OBJECTIVES: To test whether the alterations in the metabolism of PUFAs reflect the renal dysfunction in uremicpatients. METHODS: LC-MS/MS-based oxylipin profiling was conducted for the plasma samples from the uremicpatients and controls. The data were analyzed by principal component analysis (PCA) and orthogonal partial least squares-discriminant analysis (OPLS-DA). The receiver operating characteristic (ROC) curves and the correlation of the estimated glomerular filtration rate (eGFR) with the key markers were evaluated. Furthermore, qPCR analysis of the whole blood cells was conducted to investigate the possible mechanisms. In addition, a 2nd cohort was used to validate the findings from the 1st cohort. RESULTS: The plasma oxylipin profile distinguished the uremicpatients from the controls successfully by using both PCA and OPLS-DA models. 5,6-Dihydroxyeicosatrienoic acid (5,6-DHET), 5-hydroxyeicosatetraenoic acid (5-HETE), 9(10)-epoxyoctadecamonoenoic acid [9(10)-EpOME] and 12(13)-EpOME were identified as the key markers to discriminate the patients from controls. The excellent predictive performance of these four markers was validated by ROC analysis. The eGFR significantly correlated with plasma levels of 5,6-DHET and 5-HETE positively but with plasma 9(10)-EpOME and 12(13)-EpOME negatively. The changes of these markers may account for the inactivation of cytochrome P450 2C18, 2C19, microsome epoxide hydrolase (EPHX1), and 5-lipoxygenase in the patients. CONCLUSION: The alterations in plasma metabolic profile reflect the renal dysfunction in the uremicpatients.
Entities:
Keywords:
Chronic kidney disease (CKD); Cytochrome P450 2C (CYP2C); End stage renal disease (ESRD); Epoxide hydrolase; Metabolomics; Renal function
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