Evidence map›Paper›PMID 41613596›Full record

ArticleFrontiers in cellular and infection microbiology2025

Mitochondrial metabolic remodeling predicts therapeutic response to PegIFN-α in chronic hepatitis B.

Yingying Zhang, Xiu Han, Chengyu Xu, Yahui Song, Jinghan Zhu, Ruoran Zhou, Yiling Chen, Mingming Liu, Junchi Xu, Xiangwei Wu and 2 more

Abstract read
In one paragraph

Article in Frontiers in cellular and infection microbiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Yingying Zhang *Department of Infectious Diseases, The Fourth Affiliated Hospital of Soochow University, Suzhou Dushu Lake Hospital, Suzhou, Jiangsu, China.
Xiu Han *Center of Clinical Laboratory and Translational Medicine, The Fourth Affiliated Hospital of Soochow University, Suzhou Dushu Lake Hospital, Suzhou, Jiangsu, China.
Chengyu Xu *Center of Clinical Laboratory and Translational Medicine, The Fourth Affiliated Hospital of Soochow University, Suzhou Dushu Lake Hospital, Suzhou, Jiangsu, China.
Yahui SongCenter of Clinical Laboratory and Translational Medicine, The Fourth Affiliated Hospital of Soochow University, Suzhou Dushu Lake Hospital, Suzhou, Jiangsu, China.
Jinghan ZhuDepartment of Infectious Diseases, The Fourth Affiliated Hospital of Soochow University, Suzhou Dushu Lake Hospital, Suzhou, Jiangsu, China.
Ruoran ZhouMedical College of Soochow University, Suzhou, Jiangsu, China.
Yiling ChenMedical College of Soochow University, Suzhou, Jiangsu, China.
Mingming LiuDepartment of Infectious Diseases, The Fourth Affiliated Hospital of Soochow University, Suzhou Dushu Lake Hospital, Suzhou, Jiangsu, China.
Junchi XuCenter of Clinical Laboratory, The Fifth People's Hospital of Suzhou, Suzhou, Jiangsu, China.
Xiangwei WuCenter of Clinical Laboratory and Translational Medicine, The Fourth Affiliated Hospital of Soochow University, Suzhou Dushu Lake Hospital, Suzhou, Jiangsu, China.
Qingzhen HanCenter of Clinical Laboratory and Translational Medicine, The Fourth Affiliated Hospital of Soochow University, Suzhou Dushu Lake Hospital, Suzhou, Jiangsu, China.
Zutao ChenDepartment of Infectious Diseases, The Fourth Affiliated Hospital of Soochow University, Suzhou Dushu Lake Hospital, Suzhou, Jiangsu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

Antiviral AgentsHepatitis B, ChronicInterferon-alphaMitochondriaPolyethylene GlycolsAdultBiomarkersCD4-Positive T-LymphocytesCD8-Positive T-LymphocytesFemaleHumansMaleMembrane Potential, MitochondrialMiddle AgedRecombinant ProteinsROC CurveAntiviral AgentsBiomarkersInterferon-alphaPolyethylene GlycolsRecombinant Proteinschronic hepatitis Bfunctional cureimmune exhaustionmitochondrial metabolismpegylated interferon-α

Identifiers

PMID41613596
PMCPMC12847435

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.