Risk genes for the development of chronic hepatitis B cirrhosis assessed by prediction analysis of microarrays
10.3969/j.issn.1001-5256.2016.07.022
- VernacularTitle:微阵列预测分析法筛选乙型肝炎肝硬化发生的风险基因
- Author:
Chunyang XIAO
1
;
Qinkai LI
;
Jingxi YU
Author Information
1. Department of Gastroenterology, Shanghai First People′s Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200080, China
- Publication Type:Research Article
- Keywords:
hepatitis B, chronic;
liver cirrhosis;
gene expression;
microarray analysis
- From:
Journal of Clinical Hepatology
2016;32(7):1323-1329
- CountryChina
- Language:Chinese
-
Abstract:
ObjectiveTo investigate the risk genes for predicting the development of chronic hepatitis B (CHB) cirrhosis using gene chip technology. MethodsA total of 40 CHB patients who visited Shanghai First People′s Hospital from April 2008 to December 2010 were enrolled as a clinical cohort and were divided into S0, S1, S2, S3, and S4 groups, with 8 patients in each group. Liver biopsy was performed to determine fibrosis stage with the Scheuer pathological score as the criteria, and clinical data and liver tissue samples were reserved. The Human Affymetrix GeneChip was used to establish the gene expression profiles of liver tissues in CHB patients, and the significance analysis of microarrays (SAM) and prediction analysis of microarrays (PAM) were used to screen out the risk genomes for predicting the development of CHB cirrhosis. Quantitative real-time PCR was used to measure the mRNA expression of risk genes in liver tissue. The chi-square test was used for comparison of categorical data. The t-test and a one-way analysis of variance were used for comparison of normally distributed continuous data, and SNK-q test was used for further comparison between any two groups; the Mann-Whitney U rank sum test was used for comparison of non-normally distributed continuous data. ResultsA total of 1674 differentially expressed genes were screened out by Affymetrix GeneChip. A cluster analysis of these genes showed that gene expression showed differences between groups with different fibrosis stages, which suggested that the gene expression profile was well consistent with fibrosis stage. Four different classification methods were used for analysis, and 87 significant genes were screened out by SAM and 14 “high-risk” genes were screened out by PAM. The quantitative real-time PCR showed the expression of 6 risk genes (CD24, CXCL6, EHF, ITGBL1, LUM, and SOX9) differed significantly between groups S0, S1-3, and S4 (P＜0.05), and the S1-3 and S4 groups showed significantly upregulated expression of these genes compared with the S0 group (all P＜0.05). ConclusionThe 6 high-risk factors screened out and verified by gene chip technology help to predict the probability of developing liver cirrhosis in CHB patients and can be used as the diagnostic genes for predicting hepatitis B cirrhosis.
