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Wu Y, Zeng Y, Wu W, Lin J, Ou Q. Polymorphisms of CYP27B1 are associated with IFN efficacy in HBeAg-positive patients. J Clin Lab Anal 2018; 32:e22367. [PMID: 29457277 DOI: 10.1002/jcla.22367] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2017] [Accepted: 11/03/2017] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Host single nucleotide polymorphisms were associated with antiviral therapy in CHB patients. The CYP27B1 gene, encoding 25(OH)D3 -1α hydroxylase, might activate 25(OH)D3 to 1,25(OH)2 D3 in kidney resulted in influencing the efficacy of interferon (IFN). The aim of the study was to investigate the association between CYP27B1 polymorphisms and the response to IFN in HBeAg-positive patients. METHODS Eighty-seven HBeAg-positive CHB patients infected with HBV genotype B or C were included in the study. All patients were treated with IFN at least 1 year. According to the response to PEG-IFN therapy, they were divided into three groups: 16 complete responses (CR), 42 partial responses (PR), and 29 nonresponses (NR). Sanger-sequencing was utilized to genotype the CYP27B1 SNPs(rs4646536 and rs10877012). RESULTS In logistic regression analysis, the frequency of rs4646536 CC genotype was observed to be higher in the NR group. Besides, the GG genotype of rs10877012 differed significantly among the three groups. The GG genotype was prevalent in patients with CR, and patients with TT genotype result in NR at the end of IFN treatment. The most common haplotype TG was independently associated with CR, after adjustment, and haplotype CT appeared to be associated with NR and PR, rather than CR. The data also showed that patients with baseline 1,25(OH)2 D3 > 39.39 pg/mL had higher CR rates at the end of IFN therapy. CONCLUSION These results suggested CYP28B1 gene polymorphisms may be independently associated with the efficacy of IFN in HBeAg-positive patients.
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Affiliation(s)
- Yingying Wu
- First Clinical College, Fujian Medical University, Fuzhou, China.,Department of Laboratory Medicine, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China
| | - Yongbin Zeng
- First Clinical College, Fujian Medical University, Fuzhou, China.,Department of Laboratory Medicine, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China
| | - Wennan Wu
- First Clinical College, Fujian Medical University, Fuzhou, China.,Department of Laboratory Medicine, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China
| | - Jinpiao Lin
- First Clinical College, Fujian Medical University, Fuzhou, China.,Department of Laboratory Medicine, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China
| | - Qishui Ou
- First Clinical College, Fujian Medical University, Fuzhou, China.,Department of Laboratory Medicine, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China
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Tao J, Su K, Yu C, Liu X, Wu W, Xu W, Jiang B, Luo R, Yao J, Zhou J, Zhan Y, Ye C, Yuan W, Jiang X, Cui W, Li MD, Li L. Fine mapping analysis of HLA-DP/DQ gene clusters on chromosome 6 reveals multiple susceptibility loci for HBV infection. Amino Acids 2015. [PMID: 26197724 DOI: 10.1007/s00726-015-2054-6] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
Recent genome-wide association studies have revealed the HLA region on chromosome 6p21 as a susceptibility locus for hepatitis B virus (HBV) infection, a finding subsequently replicated in independent samples. However, only limited single nucleotide polymorphisms (SNPs) were analyzed in most of these studies, and it remains to be determined which SNPs contribute to the detected association. After genotyping 140 SNPs within this genomic region in a total of 1657 HBV-positive patients and 1456 HBV-negative controls, we conducted a series of genetic epidemiological and bioinformatics analysis, including individual SNP-based association analysis, haplotype-based association analysis, and conditional analysis. We identified 76 SNPs and 5 LD blocks in HLA-DP/DQ clusters that are significantly associated with HBV infection, with the smallest P value being 3.88 × 10(-18) for rs9277535 in HLA-DPB1. With conditional analysis, we further revealed that the genes contributing to the effects of variants in HLA-DP/DQ on infection are independent of each other, and the LD block 5 in the 3'-UTR region of HLA-DPB1 had a predominant effect in the association of HLA-DP with HBV infection. We also found that the SNPs in the 3'-UTR region of HLA-DPB1 were significant between the subgroups of inactive HBV carrier, chronic hepatitis B, or hepatic cirrhosis from the case group and the spontaneous HBV-clearance subgroup from the control group. Finally, we did further association analysis of SNPs in this region with different subgroups from the case group, which revealed no association of these SNPs with the progression of HBV-related diseases. In sum, we showed, for the first time, that the HLA-DP/DQ clusters contribute independently to HBV infection, and the 3'-UTR region of HLA-DPB1 represents an important functional region involved in HBV infection.
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Affiliation(s)
- Jingjing Tao
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Zhejiang University School of Medicine, 79 Qingchun Rd., Hangzhou, 310003, Zhejiang, China
| | - Kunkai Su
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Zhejiang University School of Medicine, 79 Qingchun Rd., Hangzhou, 310003, Zhejiang, China
| | - Chengbo Yu
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Zhejiang University School of Medicine, 79 Qingchun Rd., Hangzhou, 310003, Zhejiang, China
| | - Xiaoli Liu
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Zhejiang University School of Medicine, 79 Qingchun Rd., Hangzhou, 310003, Zhejiang, China
| | - Wei Wu
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Zhejiang University School of Medicine, 79 Qingchun Rd., Hangzhou, 310003, Zhejiang, China
| | - Wei Xu
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Zhejiang University School of Medicine, 79 Qingchun Rd., Hangzhou, 310003, Zhejiang, China
| | - Bingxun Jiang
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Zhejiang University School of Medicine, 79 Qingchun Rd., Hangzhou, 310003, Zhejiang, China
| | - Rui Luo
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Zhejiang University School of Medicine, 79 Qingchun Rd., Hangzhou, 310003, Zhejiang, China
| | - Jian Yao
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Zhejiang University School of Medicine, 79 Qingchun Rd., Hangzhou, 310003, Zhejiang, China
| | - Jiawei Zhou
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Zhejiang University School of Medicine, 79 Qingchun Rd., Hangzhou, 310003, Zhejiang, China
| | - Yan Zhan
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Zhejiang University School of Medicine, 79 Qingchun Rd., Hangzhou, 310003, Zhejiang, China
| | - Chao Ye
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Zhejiang University School of Medicine, 79 Qingchun Rd., Hangzhou, 310003, Zhejiang, China
| | - Wenji Yuan
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Zhejiang University School of Medicine, 79 Qingchun Rd., Hangzhou, 310003, Zhejiang, China
| | - Xianzhong Jiang
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Zhejiang University School of Medicine, 79 Qingchun Rd., Hangzhou, 310003, Zhejiang, China
| | - Wenyan Cui
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Zhejiang University School of Medicine, 79 Qingchun Rd., Hangzhou, 310003, Zhejiang, China
| | - Ming D Li
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Zhejiang University School of Medicine, 79 Qingchun Rd., Hangzhou, 310003, Zhejiang, China. .,Department of Psychiatry and Neurobehavioral Science, University of Virginia, 450 Ray C Hunt Drive, Charlottesville, VA, 22903, USA.
| | - Lianjuan Li
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Zhejiang University School of Medicine, 79 Qingchun Rd., Hangzhou, 310003, Zhejiang, China.
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Tavis JE, Donlin MJ, Aurora R, Fan X, Di Bisceglie AM. Prospects for personalizing antiviral therapy for hepatitis C virus with pharmacogenetics. Genome Med 2011; 3:8. [PMID: 21345258 PMCID: PMC3092093 DOI: 10.1186/gm222] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
Chronic hepatitis C virus (HCV) infection is a major cause of liver disease worldwide. HCV infection is currently treated with IFNα plus ribavirin for 24 to 48 weeks. This demanding therapy fails in up to 50% of patients, so the use of pharmacogenetic biomarkers to predict the outcome of treatment would reduce futile treatment of non-responders and help identify patients in whom therapy would be justified. Both IFNα and ribavirin primarily act by modulating the immune system of the patient, and HCV uses multiple mechanisms to counteract the antiviral effects stimulated by therapy. Therefore, response to therapy is influenced by variations in human genes governing the immune system and by differences in HCV genes that blunt antiviral immune responses. This article summarizes recent advances in understanding how host and viral genetic variation affect outcome of therapy. The most notable human associations are polymorphisms within the IL28B gene, but variations in human leukocyte antigen and cytokine genes have also been associated with treatment outcome. The most prominent viral genetic association with outcome of therapy is that HCV genotype 1 is much less sensitive to treatment than genotypes 2 and 3, but genetic differences below the genotype level also influence outcome of therapy, presumably by modulating the ability of viral genes to blunt antiviral immune responses. Pharmacogenetic prediction of the outcome of IFN-based therapy for HCV will require integrating the efficacies of the immunosuppressive mechanisms of a viral isolate, and then interpreting the viral resistance potential in context of the genetic profile of the patient at loci associated with outcome of therapy. Direct-acting inhibitors of HCV that will be used in combination with IFNα are nearing approval, so genetic prediction for anti-HCV therapy will soon need to incorporate viral genetic markers of viral resistance to the new drugs.
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Affiliation(s)
- John E Tavis
- Department of Molecular Microbiology and Immunology, Saint Louis University School of Medicine, Saint Louis, MO 63104, USA.
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