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Genotypes and Hot Spot Mutations of Hepatitis B Virus in Northwest Chinese Population and Its Correlation with Diseases Progression

Overview
Journal Biomed Res Int
Publisher Wiley
Date 2019 Dec 31
PMID 31886206
Citations 8
Authors
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Abstract

Hepatitis B virus (HBV) infection is a critical incentive for chronic hepatitis B (CHB), liver cirrhosis (LC), and hepatocellular carcinoma (HCC). Different genotypes and genome mutations of HBV have been found to be related to the progression of these liver diseases. However, their clinical significance is still under debate. The objective of this study was to determine the association of HBV genotypes and hot spot mutations in the reverse transcriptase (RT) and basal core promoter-precore (BCP-PreC) region with HBV-infected diseases in a northwest Chinese population. HBV genotyping and DNA sequencing were performed in samples of 980 patients. Appropriate statistical methods were adopted to assess HBV genetic features and its clinical association. It was found that the prevalent HBV genotype in northwestern Chinese patients was HBV/C (61.33%), followed by HBV/B (36.63%). In RT region, in addition to the reported nucleoside analogue- (NA-) resistance missense mutations, new silent mutations at rt169 and rt180 were found to raise the risk of HCC in patients with HBV/C. And the heterozygous mutation status of rt169/rt180 was associated with the increased risk of both HCC and NA resistance (OR > 1, < 0.01) regardless of HBV genotypes. In BCP-PreC region, multiple mutations and combinations, especially at nt 1762/1764 and nt 1896/1899, were characterized to be the causes of spurious HBeAg negativity and liver function injury, as well as the risk factors for HCC progression ( < 0.01). Additionally, a novel mutation at nt1799G>C was likely found to increase the risk of HCC in patients with HBV/B. These findings revealed an association between HBV genotypes and HBV genetic mutations in RT and BCP-PreC region and progression of hepatitis B. It would be helpful for risk evaluation and diagnostic improvement based on these genetic features.

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