SARS-CoV-2 genomic diversity and within-host evolution in individuals with persistent infection in the UK: an observational, longitudinal, population-based surveillance study

作者：Mahan Ghafari, Steven A. Kemp, Matthew Hall, Joseph Clarke, Luca Ferretti, Laura Thomson, Ruth Studley, A. Sarah Walker, Tanya Golubchik, Katrina Lythgoe · 发表于：The Lancet Microbe · 年份：2025 · DOI：10.1016/j.lanmic.2025.101154 · 被引用次数：6 · 研究领域：SARS-CoV-2 and COVID-19 Research、COVID-19 Clinical Research Studies、Long-Term Effects of COVID-19

BACKGROUND: Persistent SARS-CoV-2 infections in hospitalised immunocompromised individuals are known to facilitate accelerated within-host viral evolution, potentially contributing to the emergence of highly divergent variants. However, little is known about the evolutionary dynamics and transmission risks of persistent infections in the general population. We aimed to characterise the within-host evolution of SARS-CoV-2 during persistent infections identified through a large community surveillance study. METHODS: We used data from the Office for National Statistics COVID-19 Infection Survey (ONS-CIS), a large-scale, longitudinal, population-based surveillance study conducted in the UK from April, 2020, to March, 2023. For this analysis, we focused on infections with high viral load (cycle threshold ≤30) and available genome sequences, from seven major SARS-CoV-2 lineages (alpha, delta, BA.1, BA.2, BA.4, BA.5, and XBB). ONS-CIS participants were randomly selected from the general population and tested regularly by RT-PCR, regardless of symptoms. We defined persistent infections as those with sustained or rebounding high viral RNA titres for 26 days or longer. We examined associated host characteristics and used raw sequence data to identify de novo mutations and estimate within-host synonymous and non-synonymous evolutionary rates across the SARS-CoV-2 genome. FINDINGS: ), with high inter-individual variability driven largely by non-synonymous mutations, particularly in the N...