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

• Published in: JMIR medical informatics Vol. 13; p. e60207
• Main Authors: Lin, Lin, Wang, Guoyong, Hao, Lianzheng, Yan, Tingbin
• Format: Journal Article
• Language: English
• Published: Canada JMIR Publications 18.08.2025
• Subjects: Algorithms; Bioinformatics; Bioinformatics, Genomics, Tools and Databases; Descriptive Epidemiology and Population Size Estimates; Disease prevention; Epidemiology; Genomes; Genomics and Bioinformatics for Clinical Use; Genotype & phenotype; Hepatitis C; Immunoinformatics and Pathology informatics; Infections; Liver cancer; Liver cirrhosis; Machine learning; Medical research; Microbial Genomics and Metagenomics; Multimedia; Original Paper; Phylogenetics; Polymerase chain reaction; Precision Medicine; Public health; Questionnaires; RNA polymerase; Trends; China; Shandong China; Bayesian skyline plot; epidemiological; phylogenetic; migration patterns; genotypic diversity; genotype; Shandong Province; phylogenetic analysis; China; disease control; hepatitis C virus; migration; HCV; migration pattern; prevention
• ISSN: 2291-9694; 2291-9694
• DOI: 10.2196/60207

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. 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. 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). 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. 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.