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Primary biliary cholangitis (PBC) is a chronic autoimmune liver disease associated with profound metabolic changes. The purpose of this study was to identify a distinctive metabolic signature from the training set with 29 PBC patients, 30 hepatitis B virus (HBV)-caused cirrhosis (HBC) and 41 healthy controls, and to validate the applicability and stability of the distinctive model from the validation set with 21 PBC patients, 7 autoimmune hepatitis (AIH) and 9 HBC. The sera were investigated using high resolution nuclear magnetic resonance (NMR) and the datasets were analyzed pairwise using pattern recognition methods. 45 distinguishable metabolites were identified and 15 metabolic pathways were reprogrammed. The altered metabolic pathways were associated with glucose, fatty acid and amino acid metabolites. Logistic regression and ROC analysis were used to establish a diagnostic model with the equated (p) = -12.22-3.46*log(4-hydroxyproline) + 6.62*log(3-hydroxyisovalerate) - 2.44*log(citraconate) - 3.80*log(pyruvate). The area under the curve (AUC) of the optimized model was 0.937 (95% confidence interval (CI): 0.868-0.976) in the training set and 0.890 (95% CI: 0.743-0.969) in the validation set. These results not only revealed the potential pathogenesis of PBC, but also provided a feasible diagnostic tool for PBC populations through detection of serum metabolites.
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Hao et al. (2017) studied this question.
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