Serum Bile Acid Profiling Across the Full Spectrum of HBV-Related Liver Diseases in Chinese Population: Implications for Diagnosis and Treatment Assessment

<b>Background/Objectives:</b> Conventional serum biomarkers such as ALT and AST exhibit limited sensitivity and specificity in distinguishing the spectrum of HBV-related liver diseases, especially chronic hepatitis (CHB), cirrhosis (LC), and hepatocellular carcinoma (HCC). This study aimed to investigate the diagnostic potential of serum bile acid profiles as novel metabolic discriminators to differentiate among healthy individuals, CHB, LC, HCC, and liver failure, thereby addressing a key unmet need in clinical practice. <b>Methods:</b> A total of 625 participants were recruited and serum concentrations of 15 bile acids were determined by LC-MS/MS using targeted absolute quantification. Machine learning was employed to establish the diagnostic panels for classifying the distinct stages of HBV-related diseases. <b>Results:</b> The combinations of taurolithocholic acid (TLCA) and taurochenodeoxycholic acid (TDCA) effectively differentiated healthy individuals from the patients with liver diseases (AUCs = 0.880-1.000 across subgroups), and the specific panel of four bile acids achieved discriminative AUCs of 0.874 between CHB and LC, and 0.825 between CHB and HCC, which outperformed conventional biomarkers. Bile acid profiles also demonstrated significant responsiveness to antiviral therapy, some bile acid concentrations consistently decreasing during the post-treatment periods. <b>Conclusion:</b> Serum bile acid panels thus offer a sensitive and reliable diagnostic performance that could significantly enhance clinical decision-making and patient management.

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Publication Details

Journal
Biomedicines
Published
2025-12-31
DOI
https://doi.org/10.3390/biomedicines14010084
Citations
1
Primary Topic
Drug Transport and Resistance Mechanisms
Type
article
Field-Weighted Citation Impact
1.05
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article

Serum Bile Acid Profiling Across the Full Spectrum of HBV-Related Liver Diseases in Chinese Population: Implications for Diagnosis and Treatment Assessment

L Chen, Jiahua Mu, Liang Lin, Deliang Huang et al.
1 citations
Biomedicines
Drug Transport and Resistance Mechanisms
1.05
article

Serum Bile Acid Profiling Across the Full Spectrum of HBV-Related Liver Diseases in Chinese Population: Implications for Diagnosis and Treatment Assessment

L Chen, Jiahua Mu, Liang Lin, Deliang Huang, Jiuxin Qu, Jun Chen, Guixue Hou, Siqi Liu, Guilan Zhu
article en
1 citations

Abstract

<b>Background/Objectives:</b> Conventional serum biomarkers such as ALT and AST exhibit limited sensitivity and specificity in distinguishing the spectrum of HBV-related liver diseases, especially chronic hepatitis (CHB), cirrhosis (LC), and hepatocellular carcinoma (HCC). This study aimed to investigate the diagnostic potential of serum bile acid profiles as novel metabolic discriminators to differentiate among healthy individuals, CHB, LC, HCC, and liver failure, thereby addressing a key unmet need in clinical practice. <b>Methods:</b> A total of 625 participants were recruited and serum concentrations of 15 bile acids were determined by LC-MS/MS using targeted absolute quantification. Machine learning was employed to establish the diagnostic panels for classifying the distinct stages of HBV-related diseases. <b>Results:</b> The combinations of taurolithocholic acid (TLCA) and taurochenodeoxycholic acid (TDCA) effectively differentiated healthy individuals from the patients with liver diseases (AUCs = 0.880-1.000 across subgroups), and the specific panel of four bile acids achieved discriminative AUCs of 0.874 between CHB and LC, and 0.825 between CHB and HCC, which outperformed conventional biomarkers. Bile acid profiles also demonstrated significant responsiveness to antiviral therapy, some bile acid concentrations consistently decreasing during the post-treatment periods. <b>Conclusion:</b> Serum bile acid panels thus offer a sensitive and reliable diagnostic performance that could significantly enhance clinical decision-making and patient management.

BiomedicinesVol. 14(1)
BGI Group (China) (CN), Southern University of Science and Technology (CN), Shenzhen Second People's Hospital (CN), University of Chinese Academy of Sciences (CN), Shenzhen Third People’s Hospital (CN)
Reduced inequalities
Openalex Percentile: Top 15%
Drug Transport and Resistance Mechanisms
1.05
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