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中国山东省丙型肝炎病毒的基因型分布与传播模式:分子流行病学与系统发育研究

Genotype Distribution and Migration Patterns of Hepatitis C Virus in Shandong Province, China: Molecular Epidemiology and Phylogenetic Study.

作者信息

Lin Lin, Wang Guoyong, Hao Lianzheng, Yan Tingbin

机构信息

HIV/AIDS Control and Prevention, Key Laboratory of Infectious Disease Control and Prevention, Shandong Center for Disease Control and Prevention, Jinan, China.

Department of Orthopedic Surgery, School of Basic Medical Sciences, Qilu Hospital of Shandong University, No. 107 Wenhua West Road, Jinan, Shandong Province, 250012, China, 86 531-82169562.

出版信息

JMIR Med Inform. 2025 Aug 18;13:e60207. doi: 10.2196/60207.

Abstract

BACKGROUND

Hepatitis C virus (HCV) remains a significant public health concern in China, particularly in Shandong Province, where detailed molecular epidemiological data are limited. HCV exhibits substantial genetic diversity, and understanding its genotype distribution and transmission dynamics is critical for developing effective control strategies.

OBJECTIVE

This study aimed to investigate the genetic diversity, geographic dissemination, and evolutionary history of HCV genotypes in Shandong Province, China, using molecular techniques and phylogenetic methods.

METHODS

A total of 320 HCV-positive serum samples were collected from multiple hospitals across Shandong Province between 2013 and 2021. HCV RNA was extracted and amplified targeting the 5' untranslated region (UTR), Core, and NS5B regions. Sequencing was conducted, and genotypes were determined using the National Center for Biotechnology Information's Basic Local Alignment Search Tool (NCBI BLAST). Phylogenetic trees were constructed using maximum likelihood methods with the general time reversible with Gamma-distributed rate variation among sites [(GTR)+Gamma model]. The temporal and geographic evolution of the major subtypes (1b and 2a) was analyzed using Bayesian Markov chain Monte Carlo (MCMC) methods implemented in Bayesian Evolutionary Analysis Sampling Trees (BEAST). The Bayesian skyline plot (BSP) was used to infer population dynamics and estimate the time to the most recent common ancestor (tMRCA).

RESULTS

Genotypes 1b (n=165) and 2a (n=131) were identified as the predominant subtypes, with a small number of genotypes 3b, 6a, 6k, and potential recombinant strains also detected. Phylogenetic analysis revealed distinct evolutionary clustering of 1b and 2a strains, suggesting multiple diffusion events within the province. The tMRCA of subtypes 1b and 2a were estimated to be 1957 and 1979, respectively. Bayesian skyline analysis showed that both subtypes experienced long-term population stability, followed by a rapid expansion period between 2014 and 2019 (1b) and 2014 to 2016 (2a), respectively. The analysis also identified key transmission hubs such as Jinan, Liaocheng, Tai'an, and Dezhou, indicating city-level variations in HCV spread.

CONCLUSIONS

This study provides data-supported insights into the genotypic landscape and evolutionary patterns of HCV in Shandong Province. The identification of dominant subtypes, potential recombinant strains, and regional transmission pathways enhances our understanding of local HCV epidemiology. These findings have implications for public health policy, resource allocation, and targeted treatment strategies. The integration of molecular epidemiology and phylogenetics offers a valuable model for infectious disease surveillance and control in similar settings.

摘要

背景

丙型肝炎病毒(HCV)在中国仍然是一个重大的公共卫生问题,尤其是在山东省,该地区详细的分子流行病学数据有限。HCV具有显著的遗传多样性,了解其基因型分布和传播动态对于制定有效的控制策略至关重要。

目的

本研究旨在利用分子技术和系统发育方法,调查中国山东省HCV基因型的遗传多样性、地理传播和进化史。

方法

2013年至2021年间,从山东省多家医院共收集了320份HCV阳性血清样本。提取HCV RNA并针对5'非翻译区(UTR)、核心区和NS5B区进行扩增。进行测序,并使用美国国立生物技术信息中心的基本局部比对搜索工具(NCBI BLAST)确定基因型。使用最大似然法构建系统发育树,采用位点间伽马分布速率变化的一般时间可逆模型[(GTR)+伽马模型]。使用贝叶斯进化分析采样树(BEAST)中实现的贝叶斯马尔可夫链蒙特卡罗(MCMC)方法分析主要亚型(1b和2a)的时间和地理进化。贝叶斯天际线图(BSP)用于推断种群动态并估计最近共同祖先的时间(tMRCA)。

结果

基因型1b(n=165)和2a(n=131)被确定为主要亚型,还检测到少量基因型3b、6a、6k以及潜在的重组毒株。系统发育分析显示1b和2a毒株有明显的进化聚类,表明该省内存在多次扩散事件。亚型1b和2a的tMRCA估计分别为1957年和1979年。贝叶斯天际线分析表明,两种亚型都经历了长期的种群稳定期,随后分别在2014年至2019年(1b)和2014年至2016年(2a)经历了快速扩张期。分析还确定了济南、聊城、泰安和德州等关键传播枢纽,表明HCV传播存在市级差异。

结论

本研究为山东省HCV的基因型格局和进化模式提供了数据支持的见解。优势亚型、潜在重组毒株和区域传播途径的确定增强了我们对当地HCV流行病学的理解。这些发现对公共卫生政策、资源分配和靶向治疗策略具有重要意义。分子流行病学和系统发育学的整合为类似环境下的传染病监测和控制提供了一个有价值的模型。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/32da/12360734/a6c775cbab28/medinform-v13-e60207-g001.jpg

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