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Bayesian analysis of cytokines and chemokine identifies immune pathways of HBsAg loss during chronic hepatitis B treatment
Sriram Narayanan 1 , Veonice Bijin Au 1 , Atefeh Khakpoor 2 , Cheng Yan 2 , Patricia J Ahl 1 , Nivashini Kaliaperumal 1 , Bernett Lee 3 , Wen Wei Xiang 4 , Juling Wang 2 , Chris Lee 2 , Amy Tay 2 , Seng Gee Lim 1 2 , John E Connolly 5 6 7
Affiliations
Affiliations
1
Translational Immunology Programme, Institute of Molecular and Cell Biology (IMCB), Agency for Science, Technology, and Research, Singapore (A*STAR) Research Entities (RE), 61 Biopolis Drive, Proteos, Singapore, 138673, Singapore.
2
Division of Gastroenterology and Hepatology, Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
3
Singapore Immunology Network, A*STAR REs, Singapore, Singapore.
4
IMCB, Tessa Therapeutics Pvt Ltd, Singapore, Singapore.
5
Translational Immunology Programme, Institute of Molecular and Cell Biology (IMCB), Agency for Science, Technology, and Research, Singapore (A*STAR) Research Entities (RE), 61 Biopolis Drive, Proteos, Singapore, 138673, Singapore. [email protected].
6
Department of Microbiology and Immunology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore. [email protected].
7
Institute of Biomedical Studies, Baylor University, Waco, TX, USA. [email protected].
PMID: 33811250 DOI: 10.1038/s41598-021-86836-5
Abstract
Our objective was to examine differences in cytokine/chemokine response in chronic hepatitis B(CHB) patients to understand the immune mechanism of HBsAg loss (functional cure) during antiviral therapy. We used an unbiased machine learning strategy to unravel the immune pathways in CHB nucleo(t)side analogue-treated patients who achieved HBsAg loss with peg-interferon-α(peg-IFN-α) add-on or switch treatment in a randomised clinical trial. Cytokines/chemokines from plasma were compared between those with/without HBsAg loss, at baseline, before and after HBsAg loss. Peg-IFN-α treatment resulted in higher levels of IL-27, IL-12p70, IL-18, IL-13, IL-4, IL-22 and GM-CSF prior to HBsAg loss. Probabilistic network analysis of cytokines, chemokines and soluble factors suggested a dynamic dendritic cell driven NK and T cell immune response associated with HBsAg loss. Bayesian network analysis showed a dominant myeloid-driven type 1 inflammatory response with a MIG and I-TAC central module contributing to HBsAg loss in the add-on arm. In the switch arm, HBsAg loss was associated with a T cell activation module exemplified by high levels of CD40L suggesting T cell activation. Our findings show that more than one immune pathway to HBsAg loss was found with peg-IFN-α therapy; by myeloid-driven Type 1 response in one instance, and T cell activation in the other.
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