Li Ma1, Xiaoqing Zhang1, Feng Pan2, Yue Cui1, Ting Yang1, Linlin Deng1, Yong Shao3, Min Ding4. 1. Key Laboratory of Clinical Laboratory Diagnostics, Ministry of Education, College of Laboratory Medicine, Chongqing Medical University, Chongqing 400016, PR China. 2. Biomedical Analysis Center, Third Military Medical University, Chongqing 400030, PR China. 3. Department of Obstetrics and Gynecology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, PR China. 4. Key Laboratory of Clinical Laboratory Diagnostics, Ministry of Education, College of Laboratory Medicine, Chongqing Medical University, Chongqing 400016, PR China. Electronic address: dingmin@cqmu.edu.cn.
Abstract
BACKGROUND: Intrahepatic cholestasis of pregnancy (ICP), a pregnancy-related liver disease, leads to complications for both mothers and fetuses. Metabolomic approach has been applied to maternal-fetal medicine. The global metabolomic alterations that are specific in ICP as yet have not been investigated. METHODS: Based on high performance liquid chromatography/hybrid quadrupole time-of-flight (HPLC/Q-TOF) mass spectrometry, the untargeted metabolomics was used to analyze the changes of urinary metabolites between ICP group and the control group. RESULTS: One hundred nine variables in positive model and 119 variables in negative model were significantly different (p<0.05) between the ICP group and the control group, with the VIP (variable importance in the project) score>1 by the orthogonal partial least squares discriminant analysis (OPLS-DA). 14 metabolites in positive model and 18 metabolites in negative model were selected and identified based on HMDB (human metabolome database). Most of these metabolites were involved in bile acids biosynthesis and metabolism, hormone metabolism and lipid metabolism. A metabolite panel (MG (22:5), LysoPE (22:5), l-homocysteine sulfonic acid, glycocholic acid and chenodeoxycholic acid 3-sulfate) was contrusted by the binary logistic regression analysis with high diagnostic accuracy for ICP. The area under the receiver operating characteristic curve was 0.988 with the sensitivity of 90.0% and specificity of 93.3%. CONCLUSIONS: Urinary metabolites allow for the discrimination of ICP from the controls by orthogonal partial least squares discriminant analysis. Therefore, these findings may provide deep insights for the etiopathogenesis of ICP. Moreover, the maternal urinary metabolite panel has the potential to be used as non-invasive biomarkers for the diagnosis of ICP.
BACKGROUND:Intrahepatic cholestasis of pregnancy (ICP), a pregnancy-related liver disease, leads to complications for both mothers and fetuses. Metabolomic approach has been applied to maternal-fetal medicine. The global metabolomic alterations that are specific in ICP as yet have not been investigated. METHODS: Based on high performance liquid chromatography/hybrid quadrupole time-of-flight (HPLC/Q-TOF) mass spectrometry, the untargeted metabolomics was used to analyze the changes of urinary metabolites between ICP group and the control group. RESULTS: One hundred nine variables in positive model and 119 variables in negative model were significantly different (p<0.05) between the ICP group and the control group, with the VIP (variable importance in the project) score>1 by the orthogonal partial least squares discriminant analysis (OPLS-DA). 14 metabolites in positive model and 18 metabolites in negative model were selected and identified based on HMDB (human metabolome database). Most of these metabolites were involved in bile acids biosynthesis and metabolism, hormone metabolism and lipid metabolism. A metabolite panel (MG (22:5), LysoPE (22:5), l-homocysteine sulfonic acid, glycocholic acid and chenodeoxycholic acid 3-sulfate) was contrusted by the binary logistic regression analysis with high diagnostic accuracy for ICP. The area under the receiver operating characteristic curve was 0.988 with the sensitivity of 90.0% and specificity of 93.3%. CONCLUSIONS: Urinary metabolites allow for the discrimination of ICP from the controls by orthogonal partial least squares discriminant analysis. Therefore, these findings may provide deep insights for the etiopathogenesis of ICP. Moreover, the maternal urinary metabolite panel has the potential to be used as non-invasive biomarkers for the diagnosis of ICP.