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Zheng P, Dou Y, Wang Q. Immune response and treatment targets of chronic hepatitis B virus infection: innate and adaptive immunity. Front Cell Infect Microbiol 2023; 13:1206720. [PMID: 37424786 PMCID: PMC10324618 DOI: 10.3389/fcimb.2023.1206720] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2023] [Accepted: 06/06/2023] [Indexed: 07/11/2023] Open
Abstract
Chronic hepatitis B virus (HBV) infection is a major global public health risk that threatens human life and health, although the number of vaccinated people has increased. The clinical outcome of HBV infection depends on the complex interplay between viral replication and the host immune response. Innate immunity plays an important role in the early stages of the disease but retains no long-term immune memory. However, HBV evades detection by the host innate immune system through stealth. Therefore, adaptive immunity involving T and B cells is crucial for controlling and clearing HBV infections that lead to liver inflammation and damage. The persistence of HBV leads to immune tolerance owing to immune cell dysfunction, T cell exhaustion, and an increase in suppressor cells and cytokines. Although significant progress has been made in HBV treatment in recent years, the balance between immune tolerance, immune activation, inflammation, and fibrosis in chronic hepatitis B remains unknown, making a functional cure difficult to achieve. Therefore, this review focuses on the important cells involved in the innate and adaptive immunity of chronic hepatitis B that target the host immune system and identifies treatment strategies.
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Affiliation(s)
- Peiyu Zheng
- Department of Infectious Diseases, The First Hospital of Shanxi Medical University, Taiyuan, China
- Graduate School of Shanxi Medical University, Taiyuan, China
| | - Yongqing Dou
- Department of Infectious Diseases, The First Hospital of Shanxi Medical University, Taiyuan, China
| | - Qinying Wang
- Department of Infectious Diseases, The First Hospital of Shanxi Medical University, Taiyuan, China
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Ning G, Zhen LM, Xu WX, Li XJ, Wu LN, Liu Y, Xie C, Peng L. Suppression of complement component 2 expression by hepatitis B virus contributes to the viral persistence in chronic hepatitis B patients. J Viral Hepat 2020; 27:1071-1081. [PMID: 32384193 DOI: 10.1111/jvh.13319] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/08/2019] [Revised: 03/20/2020] [Accepted: 04/08/2020] [Indexed: 12/13/2022]
Abstract
Previously, we identified rare missense mutations of complement component 2 (C2) to be associated with chronic hepatitis B (CHB) by exome sequencing. However, up to now, little is known about the role of C2 in CHB. In the present study, we aimed to perform preliminary exploration about the underlying role of C2 in CHB. Serum samples from 113 CHB patients and 30 healthy controls, and liver biopsy samples from 5 CHB patients and 3 healthy controls were obtained from the Third Affiliated Hospital of Sun Yat-sen University between January 2018 and January 2020. HepG2.2.15 and HepG2-NTCP cells infected with HBV were used to examine the influence of HBV infection on C2 expression. IFN-treated HepG2.2.15 cells were used to assess the effect of IFN on C2 expression. C2-overexpressing or C2-silencing HepG2.2.15 cells were constructed to evaluate the effect of C2 on HBV infection. Western blot and RT-qPCR were used to measure C2 expression in biopsy samples. HBeAg and HBsAg in culture medium and C2 of serum samples were measured by ELISA. HBV-DNA was measured by RT-qPCR. GSE84044, GSE54747 and GSE27555 were downloaded from GEO. C2 expression in liver tissue and serum was significantly lower in CHB patients compared to healthy controls, and significantly higher C2 expression was found in CHB patients with lower ALT, AST, Scheuer grade and stages compared to CHB patients with higher ALT, AST, Scheuer grades and Scheuer stage. Besides, HBV infection could decrease C2 expression by increasing expression of Sp1 and reducing expression of HDAC4. Moreover, C2 could enhance the anti-virus effect of IFN on HepG2.2.15 cells and also inhibit HBV replication in HepG2.2.15 cells by inhibition of p38-MAPK signalling pathway. In conclusion, HBV may promote viral persistence in CHB patients by inhibiting C2 expression.
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Affiliation(s)
- Gang Ning
- Department of Infectious Diseases, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Li-Min Zhen
- Department of Infectious Diseases, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Wen-Xiong Xu
- Department of Infectious Diseases, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Xue-Jun Li
- Department of Infectious Diseases, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Li-Na Wu
- Department of Infectious Diseases, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Ying Liu
- Department of Infectious Diseases, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Chan Xie
- Department of Infectious Diseases, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Liang Peng
- Department of Infectious Diseases, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
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Han J, Chen C, Wang C, Qin N, Huang M, Ma Z, Zhu M, Dai J, Jiang Y, Ma H, Jin G, Shen H, Hu Z. Transcriptome-wide association study for persistent hepatitis B virus infection and related hepatocellular carcinoma. Liver Int 2020; 40:2117-2127. [PMID: 32574393 DOI: 10.1111/liv.14577] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/16/2019] [Revised: 06/01/2020] [Accepted: 06/16/2020] [Indexed: 12/11/2022]
Abstract
Previous genome-wide association studies (GWAS) have identified multiple susceptible variants associated with persistent hepatitis B virus (HBV) infection. However, most of these variants are located in the noncoding regions, which make it difficult to determine the effective genes underlying these associations. We performed a two-stage study, in the first stage we integrated RNA sequencing data of liver tissues and high-density genotyping data from the Genotype-Tissue Expression (GTEx) project with our previous GWAS data to conduct a transcriptome-wide association study (TWAS) on HBV infection. Firstly, the cis-heritable genes were screened by a genetic relatedness matrix of genome-wide complex trait analysis (GCTA) from GTEx data. Then, the genetic expression of 2587 cis-heritable genes was predicted by restricted maximum likelihood (REML) of genome-wide efficient mixed-model association (GEMMA) in our GWAS data with 951 HBV carrier cases and 937 HBV cleared controls. Next, we investigated the associations between predictive expression levels and persistent HBV infection risk. Gene set enrichment analysis (GSEA) was applied to infer the function of the identified genes. To identify the causal single nucleotide polymorphisms (SNPs) of HBV infection risk, we conducted the expression quantitative trait loci (eQTL)-based stepwise logistic regression analysis in the regions around 1 Mb of these genes and validated the association between 994 health controls and 994 HBV-persistent infection cases by genotyping experiment. In the second stage, 1538 HBV-related hepatocellular carcinoma (HCC) cases and 1465 persistent HBV infection controls were collected to determine the effect of these variants on HBV-related HCC as well, which were examined by the additive model in logistic regression analysis. We identified seven genes associated with HBV infection. In the classic human leukocyte antigen (HLA) region, three novel genes BAK1, HLA-DOB and C4A (Z range from -3.95 to -3.64, P range from 7.84 × 10-5 to 2.00 × 10-4 ), as well as two genes (HLA-DPA1 and HLA-DPB1) were reported by previous GWAS. In the non-HLA region, immune related at newly identified loci, PARP9 (Z = 3.69, P = 2.20 × 10-4 ) at 3q21.1. At 22q11.21, we identified TMEM191A (Z = 3.55, P = 3.80 × 10-4 ) as a target gene in addition to the reported non-cis-heritable gene UBE2L3. After further stepwise logistic regression analysis and validation, we identified eight variants independently associated with persistent HBV infection. Among those variants, the additive model showed that two SNPs associated with HBV-related HCC risk (rs9272714 and rs9394194, OR range from 1.20 to 1.25, P range from 1.19 × 10-4 to 3.97 × 10-4 ). By integrating transcriptome data, our study not only identified new susceptibility loci of persistent HBV infection but also determined the potential target genes at reported loci, which provided insight into the genetic aetiology of persistent HBV infection and related HCC.
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Affiliation(s)
- Jing Han
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center For Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China.,Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, Nanjing Medical University Affiliated Cancer Hospital, Nanjing, China
| | - Congcong Chen
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center For Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China
| | - Cheng Wang
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center For Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China
| | - Na Qin
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center For Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China
| | - Mingtao Huang
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center For Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China
| | - Zijian Ma
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center For Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China
| | - Meng Zhu
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center For Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China
| | - Juncheng Dai
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center For Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China
| | - Yue Jiang
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center For Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China
| | - Hongxia Ma
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center For Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China
| | - Guangfu Jin
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center For Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China
| | - Hongbing Shen
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center For Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China
| | - Zhibin Hu
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center For Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China
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Metabolomic mechanisms of gypenoside against liver fibrosis in rats: An integrative analysis of proteomics and metabolomics data. PLoS One 2017; 12:e0173598. [PMID: 28291813 PMCID: PMC5349658 DOI: 10.1371/journal.pone.0173598] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2016] [Accepted: 02/23/2017] [Indexed: 01/04/2023] Open
Abstract
Aims To investigate mechanisms and altered pathways of gypenoside against carbon tetrachloride (CCl4)-induced liver fibrosis based on integrative analysis of proteomics and metabolomics data. Methods CCl4-induced liver fibrosis rats were administrated gypenoside. The anti-fibrosis effects were evaluated by histomorphology and liver hydroxyproline (Hyp) content. Protein profiling and metabolite profiling of rats liver tissues were examined by isobaric tags for relative and absolute quantitation (iTRAQ) approach and gas chromatography-mass spectrometer (GC-MS) technology. Altered pathways and pivotal proteins and metabolites were searched by integrative analysis of proteomics and metabolomics data. The levels of some key proteins in altered pathways were determined by western blot. Results Histopathological changes and Hyp content in gypenoside group had significant improvements (P<0.05). Compared to liver fibrosis model group, we found 301 up-regulated and 296 down-regulated proteins, and 9 up-regulated and 8 down-regulated metabolites in gypenoside group. According to integrative analysis, some important pathways were found, including glycolysis or gluconeogenesis, fructose and mannose metabolism, glycine, serine and threonine metabolism, lysine degradation, arginine and proline metabolism, glutathione metabolism, and sulfur metabolism. Furthermore, the levels of ALDH1B1, ALDH2 and ALDH7A1 were found increased and restored to normal levels after gypenoside treated (P<0.05). Conclusions Gypenoside inhibited CCl4-induced liver fibrosis, which may be involved in the alteration of glycolysis metabolism and the protection against the damage of aldehydes and lipid peroxidation by up-regulating ALDH.
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