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Zhou W, Ma Y, Zhang J, Hu J, Zhang M, Wang Y, Li Y, Wu L, Pan Y, Zhang Y, Zhang X, Zhang X, Zhang Z, Zhang J, Li H, Lu L, Jin L, Wang J, Yuan Z, Liu J. Predictive model for inflammation grades of chronic hepatitis B: Large-scale analysis of clinical parameters and gene expressions. Liver Int 2017; 37:1632-1641. [PMID: 28328162 DOI: 10.1111/liv.13427] [Citation(s) in RCA: 45] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/29/2016] [Accepted: 03/14/2017] [Indexed: 02/07/2023]
Abstract
BACKGROUND Liver biopsy is the gold standard to assess pathological features (eg inflammation grades) for hepatitis B virus-infected patients although it is invasive and traumatic; meanwhile, several gene profiles of chronic hepatitis B (CHB) have been separately described in relatively small hepatitis B virus (HBV)-infected samples. We aimed to analyse correlations among inflammation grades, gene expressions and clinical parameters (serum alanine amino transaminase, aspartate amino transaminase and HBV-DNA) in large-scale CHB samples and to predict inflammation grades by using clinical parameters and/or gene expressions. METHODS We analysed gene expressions with three clinical parameters in 122 CHB samples by an improved regression model. Principal component analysis and machine-learning methods including Random Forest, K-nearest neighbour and support vector machine were used for analysis and further diagnosis models. Six normal samples were conducted to validate the predictive model. RESULTS Significant genes related to clinical parameters were found enriching in the immune system, interferon-stimulated, regulation of cytokine production, anti-apoptosis, and etc. A panel of these genes with clinical parameters can effectively predict binary classifications of inflammation grade (area under the ROC curve [AUC]: 0.88, 95% confidence interval [CI]: 0.77-0.93), validated by normal samples. A panel with only clinical parameters was also valuable (AUC: 0.78, 95% CI: 0.65-0.86), indicating that liquid biopsy method for detecting the pathology of CHB is possible. CONCLUSIONS This is the first study to systematically elucidate the relationships among gene expressions, clinical parameters and pathological inflammation grades in CHB, and to build models predicting inflammation grades by gene expressions and/or clinical parameters as well.
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Affiliation(s)
- Weichen Zhou
- Department of Digestive Diseases of Huashan Hospital, Collaborative Innovation Center for Genetics and Development, Fudan University, Shanghai, China.,State Key Laboratory of Genetic Engineering, Collaborative Innovation Center for Genetics and Development, School of Life Sciences and Institutes of Biomedical Sciences, Fudan University, Shanghai, China.,Department of Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Yanyun Ma
- State Key Laboratory of Genetic Engineering, Collaborative Innovation Center for Genetics and Development, School of Life Sciences and Institutes of Biomedical Sciences, Fudan University, Shanghai, China
| | - Jun Zhang
- Department of Digestive Diseases of Huashan Hospital, Collaborative Innovation Center for Genetics and Development, Fudan University, Shanghai, China
| | - Jingyi Hu
- Department of Digestive Diseases of Huashan Hospital, Collaborative Innovation Center for Genetics and Development, Fudan University, Shanghai, China.,State Key Laboratory of Genetic Engineering, Collaborative Innovation Center for Genetics and Development, School of Life Sciences and Institutes of Biomedical Sciences, Fudan University, Shanghai, China
| | - Menghan Zhang
- State Key Laboratory of Genetic Engineering, Collaborative Innovation Center for Genetics and Development, School of Life Sciences and Institutes of Biomedical Sciences, Fudan University, Shanghai, China
| | - Yi Wang
- State Key Laboratory of Genetic Engineering, Collaborative Innovation Center for Genetics and Development, School of Life Sciences and Institutes of Biomedical Sciences, Fudan University, Shanghai, China
| | - Yi Li
- State Key Laboratory of Genetic Engineering, Collaborative Innovation Center for Genetics and Development, School of Life Sciences and Institutes of Biomedical Sciences, Fudan University, Shanghai, China
| | - Lijun Wu
- Department of Digestive Diseases of Huashan Hospital, Collaborative Innovation Center for Genetics and Development, Fudan University, Shanghai, China
| | - Yida Pan
- Department of Digestive Diseases of Huashan Hospital, Collaborative Innovation Center for Genetics and Development, Fudan University, Shanghai, China
| | - Yitong Zhang
- Department of Digestive Diseases of Huashan Hospital, Collaborative Innovation Center for Genetics and Development, Fudan University, Shanghai, China.,State Key Laboratory of Genetic Engineering, Collaborative Innovation Center for Genetics and Development, School of Life Sciences and Institutes of Biomedical Sciences, Fudan University, Shanghai, China
| | - Xiaonan Zhang
- Shanghai Public Health Clinical Center, Fudan University, Shanghai, China
| | - Xinxin Zhang
- Department of Infectious Diseases, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Zhanqing Zhang
- Shanghai Public Health Clinical Center, Fudan University, Shanghai, China
| | - Jiming Zhang
- Department of Infectious Diseases, Huashan Hospital, Fudan University, Shanghai, China
| | - Hai Li
- Department of Gastroenterology, Renji Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Lungen Lu
- Department of Gastroenterology, Shanghai General Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Li Jin
- State Key Laboratory of Genetic Engineering, Collaborative Innovation Center for Genetics and Development, School of Life Sciences and Institutes of Biomedical Sciences, Fudan University, Shanghai, China
| | - Jiucun Wang
- State Key Laboratory of Genetic Engineering, Collaborative Innovation Center for Genetics and Development, School of Life Sciences and Institutes of Biomedical Sciences, Fudan University, Shanghai, China
| | - Zhenghong Yuan
- Shanghai Public Health Clinical Center, Fudan University, Shanghai, China.,Key Laboratory of Medical Molecular Virology of MOE/MOH, Department of Immunology, Institutes of Biomedical Sciences, Shanghai Medical School, Fudan University, Shanghai, China
| | - Jie Liu
- Department of Digestive Diseases of Huashan Hospital, Collaborative Innovation Center for Genetics and Development, Fudan University, Shanghai, China.,Key Laboratory of Medical Molecular Virology of MOE/MOH, Department of Immunology, Institutes of Biomedical Sciences, Shanghai Medical School, Fudan University, Shanghai, China
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