Tianlu Chen1, Kejun Zhou2, Tao Sun1, Chao Sang1, Wei Jia1,3, Guoxiang Xie2. 1. Shanghai Key Laboratory of Diabetes Mellitus and Center for Translational Medicine, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China. 2. Human Metabolomics Institute, Inc., Shenzhen, Guangdong, China. 3. Hong Kong Traditional Chinese Medicine Phenome Research Centre, School of Chinese Medicine, Hong Kong Baptist University, Kowloon Tong, Hong Kong.
Abstract
BACKGROUND AND AIM: The onset and progression of chronic liver disease (CLD) is a multistage process spanning years or several decades. Some bile acid (BA) features are identified as indicators for CLD progression. However, BAs are highly influenced by various factors and are stage and/or population specific. Emerging evidences demonstrated the association of structure of conjugated BAs and CLD progression. Here, we aimed to investigate the alteration of conjugated BAs and identify new features for CLD progression. METHODS: Based on liquid chromatography-mass spectrometry platform, 15 BAs were quantified in 1883 participants including healthy controls and CLD patients (non-alcoholic fatty liver [NAFL], non-alcoholic steatohepatitis [NASH], fibrosis, cirrhosis, and three types of liver cancer). Logistic regression was used to construct diagnostic models. Model performances were evaluated in discovery and test sets by area under the receiver operating characteristic curve, sensitivity, specificity, accuracy, and kappa index. RESULTS: Five BA glycine : taurine ratios were calculated, and glycocholic acid/taurocholic acid, glycodeoxycholic acid/taurodeoxycholic acid, and glycochenodeoxycholic acid/taurochenocholic acid were identified as candidates. Three diagnostic models were constructed for the differentiation of healthy control and early CLD (NAFL + NASH), early and advanced CLD (fibrosis + cirrhosis + liver cancer), and NAFL and NASH, respectively. The areas under the receiver operating characteristic curve of the models ranged from 0.91 to 0.97. The addition of age and gender improved model performances further. The alterations of the candidates and the performances of the diagnostic models were successfully validated by independent test sets (n = 291). CONCLUSIONS: Our findings revealed stage-specific BA perturbation patterns and provided new biomarkers and tools for the monitoring of liver disease progression.
BACKGROUND AND AIM: The onset and progression of chronic liver disease (CLD) is a multistage process spanning years or several decades. Some bile acid (BA) features are identified as indicators for CLD progression. However, BAs are highly influenced by various factors and are stage and/or population specific. Emerging evidences demonstrated the association of structure of conjugated BAs and CLD progression. Here, we aimed to investigate the alteration of conjugated BAs and identify new features for CLD progression. METHODS: Based on liquid chromatography-mass spectrometry platform, 15 BAs were quantified in 1883 participants including healthy controls and CLD patients (non-alcoholic fatty liver [NAFL], non-alcoholic steatohepatitis [NASH], fibrosis, cirrhosis, and three types of liver cancer). Logistic regression was used to construct diagnostic models. Model performances were evaluated in discovery and test sets by area under the receiver operating characteristic curve, sensitivity, specificity, accuracy, and kappa index. RESULTS: Five BA glycine : taurine ratios were calculated, and glycocholic acid/taurocholic acid, glycodeoxycholic acid/taurodeoxycholic acid, and glycochenodeoxycholic acid/taurochenocholic acid were identified as candidates. Three diagnostic models were constructed for the differentiation of healthy control and early CLD (NAFL + NASH), early and advanced CLD (fibrosis + cirrhosis + liver cancer), and NAFL and NASH, respectively. The areas under the receiver operating characteristic curve of the models ranged from 0.91 to 0.97. The addition of age and gender improved model performances further. The alterations of the candidates and the performances of the diagnostic models were successfully validated by independent test sets (n = 291). CONCLUSIONS: Our findings revealed stage-specific BA perturbation patterns and provided new biomarkers and tools for the monitoring of liver disease progression.