Integrating proteomics and targeted metabolomics to reveal the material basis of liver-gallbladder damp-heat syndrome in chronic hepatitis B
[DOI] 10.1016/j.dcmed.2025.01.005
- VernacularTitle:联合蛋白质组学和靶向代谢组学揭示慢性乙型肝炎中肝胆湿热证的物质基础
- Author:
LI Ni’ao
;
GONG Yuefeng
;
WANG Jia
;
CHEN Qingqing
;
SU Shibing
;
ZHANG Hua
;
LU Yiyu
- Publication Type:Journal Article
- Keywords:
[Key words] Liver-gallbladder damp-heat syndrome (LGDHS);
Chronic hepatitis B (CHB);
Proteomics;
Targeted metabolomics;
Molecular mechanism;
Biomarkers
- From:
Digital Chinese Medicine
2024;7(4):320-331
- CountryChina
- Language:English
-
Abstract:
Methods:CHB patients and healthy volunteers were enrolled from Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine between August 21, 2018 and December 31, 2020. They were divided into three groups: healthy group, LGDHS group, and latent syndrome (LP) group. Proteomic analysis using isobaric tags for relative and absolute quantitation (iTRAQ) was performed to identify differentially expressed proteins (DEPs). Metabolomic profiling via ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) was applied to serum samples to detect differentially regulated metabolites (DMs). Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment were employed to explore dysregulated pathways. Principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were utilized to visualize group separation and identify key metabolites and proteins contributing to LGDHS differentiation. Receiver operating characteristic (ROC) curve analysis evaluated the diagnostic performance of key biomarkers, while logistic regression models assessed their predictive accuracy. P values were corrected for multiple tests using the Benjamini-Hochberg method to control the false discovery rate (FDR). Validation of potential biomarkers was conducted using independent microarray data and real-time quantitative polymerase chain reaction (RT-qPCR).
Results: A total of 150 participants were enrolled, including healthy group (n = 45), LGDHS group (n = 60), and LP group (n = 45). 254 DEPs from proteomics data and 72 DMs from metabolomic profiling were identified by PCA and OPLS-DA. DEPs were mainly enriched in immune and complement pathways, while DMs involved in amino acid and energy metabolism. The integrated analysis identified seven key biomarkers: α1-acid glycoprotein (ORM1), asparagine synthetase (ASNS), solute carrier family 27 member 5 (SLC27A5), glucosidase II alpha subunit (GANAB), hexokinase 2 (HK2), 5-methyltetrahydrofolate-homocysteine methyltransferase (MTR), and maltase-glucoamylase (MGAM). Microarray validation confirmed the diagnostic potential of these genes, with area under the curve (AUC) values for ROC analysis ranging from 0.536 to 0.759. Among these, ORM1, ASNS, and SLC27A5 showed significant differential ability in differentiating LGDHS patients (P = 0.016, P = 0.035, and P < 0.001, respectively), with corresponding AUC of 0.749, 0.743, and 0.759, respectively. A logistic regression model incorporating these three genes demonstrated an AUC of 0.939, indicating a high discriminatory power for LGDHS. RT-qPCR further validated the differential expression of ORM1 and SLC27A5 between LGDHS and LP groups (P = 0.011 and P = 0.034, respectively), with ASNS showing a consistent trend in expression (P = 0.928).
Conclusion:This study integrates multi-omics approaches to uncover the molecular mechanisms underlying LGDHS in CHB. The identification of biomarkers ORM1, ASNS, and SLC27A5 offers a solid basis for the objective diagnosis of LGDHS, contributing to the standardization and modernization of TCM diagnostic practices.
- Full text:2025021715491553939liniao.pdf
