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Updated: Jan 31, 2026

LC-MS Analysis of Human Platelets as a Platform for Studying Mitochondrial Metabolism
Published on: April 4, 2016
Mitochondrial metabolic remodeling predicts therapeutic response to PegIFN-α in chronic hepatitis B
Yingying Zhang1, Xiu Han2, Chengyu Xu2
1Department of Infectious Diseases, The Fourth Affiliated Hospital of Soochow University, Suzhou Dushu Lake Hospital, Suzhou, Jiangsu, China.
Background:
Chronic hepatitis B (CHB) remains a global health challenge, with current therapies achieving low rates of functional cure (FC). Reliable biomarkers are urgently needed to guide individualized treatment. This study characterized the immune-metabolic profiles of CHB patients receiving pegylated interferon-α (PegIFN-α) or nucleos(t)ide analogues (NAs), focusing on mitochondrial function as a novel predictor of therapeutic response.
Methods:
A total of 93 CHB patients and 32 healthy controls were recruited from three centers. Peripheral blood leukocyte subsets and mitochondrial parameters, including mitochondrial mass (MM) and the percentage of cells with low mitochondrial membrane potential (MMPlow%), were assessed by flow cytometry. Multivariate logistic regression and receiver operating characteristic (ROC) analyses were used to identify independent predictors and evaluate biomarker performance for FC.
Results:
Untreated CHB patients showed marked mitochondrial depletion across immune subsets. NA therapy normalized mitochondrial parameters without improving FC rates, whereas PegIFN-α therapy selectively remodeled CD4+ T cell metabolism and promoted monocyte differentiation. Improved mitochondrial efficiency in CD8+ T cells and elevated monocyte counts were closely associated with HBsAg clearance. Lymphocyte MMPlow% showed the strongest individual predictive value, while an integrated immune-metabolic model further enhanced accuracy for FC prediction.
Conclusion:
Immune-metabolic remodeling underlies PegIFN-α-induced functional cure in CHB. Mitochondrial profiling provides a promising framework for precision stratification and immune-based therapeutic optimization.
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