ArticleVirus evolution2021
Quantitative differences between intra-host HCV populations from persons with recently established and persistent infections.
Article in Virus evolution, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 15 citations in OpenAlex.
- A graph homomorphism approach for unraveling histories of metastatic cancers and viral outbreaks under evolutionary constraints.Nature communications · 2025Article
- Early detection of emerging viral variants through analysis of community structure of coordinated substitution networks.Nature communications · 2024Article
- Polyvalent immunization elicits a synergistic broadly neutralizing immune response to hypervariable region 1 variants of hepatitis C virus.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- SOPHIE: Viral outbreak investigation and transmission history reconstruction in a joint phylogenetic and network theory framework.Cell systems · 2022Article
- Scale-Free Spanning Trees and Their Application in Genomic Epidemiology.Journal of computational biology : a journal of computational molecular cell biology · 2021Article
- Accurate assembly of minority viral haplotypes from next-generation sequencing through efficient noise reduction.Nucleic acids research · 2021Article
- Intra-host evolutionary dynamics of the hepatitis C virus among people who inject drugs.Scientific reports · 2021Article
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
Abstract
Detection of incident hepatitis C virus (HCV) infections is crucial for identification of outbreaks and development of public health interventions. However, there is no single diagnostic assay for distinguishing recent and persistent HCV infections. HCV exists in each infected host as a heterogeneous population of genomic variants, whose evolutionary dynamics remain incompletely understood. Genetic analysis of such viral populations can be applied to the detection of incident HCV infections and used to understand intra-host viral evolution. We studied intra-host HCV populations sampled using next-generation sequencing from 98 recently and 256 persistently infected individuals. Genetic structure of the populations was evaluated using 245,878 viral sequences from these individuals and a set of selected features measuring their diversity, topological structure, complexity, strength of selection, epistasis, evolutionary dynamics, and physico-chemical properties. Distributions of the viral population features differ significantly between recent and persistent infections. A general increase in viral genetic diversity from recent to persistent infections is frequently accompanied by decline in genomic complexity and increase in structuredness of the HCV population, likely reflecting a high level of intra-host adaptation at later stages of infection. Using these findings, we developed a machine learning classifier for the infection staging, which yielded a detection accuracy of 95.22 per cent, thus providing a higher accuracy than other genomic-based models. The detection of a strong association between several HCV genetic factors and stages of infection suggests that intra-host HCV population develops in a complex but regular and predictable manner in the course of infection. The proposed models may serve as a foundation of cyber-molecular assays for staging infection, which could potentially complement and/or substitute standard laboratory assays.
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