High number of SARS-CoV-2 persistent infections uncovered through genetic analysis of samples from a large community-based surveillance study

Abstract

Persistent severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections may act as viral reservoirs that could seed future outbreaks1–5, give rise to highly divergent lineages6–8, and contribute to cases with post-acute Coronavirus disease 2019 (COVID-19) sequelae (Long Covid)9,10. However, the population prevalence of persistent infections, their viral load kinetics, and evolutionary dynamics over the course of infections remain largely unknown. We identified 381 infections lasting at least 30 days, of which 54 lasted at least 60 days. These persistently infected individuals had more than 50% higher odds of self-reporting Long Covid compared to the infected controls, and we estimate that 0.09-0.5% of SARS-CoV-2 infections can become persistent and last for at least 60 days. In nearly 70% of the persistent infections we identified, there were long periods during which there were no consensus changes in virus sequences, consistent with prolonged presence of non-replicating virus. Our findings also suggest reinfections with the same major lineage are rare and that many persistent infections are characterised by relapsing viral load dynamics. Furthermore, we found a strong signal for positive selection during persistent infections, with multiple amino acid substitutions in the Spike and ORF1ab genes emerging independently in different individuals, including mutations that are lineage-defining for SARS-CoV-2 variants, at target sites for several monoclonal antibodies, and commonly found in immunocompromised patients11–14. This work has significant implications for understanding and characterising SARS-CoV-2 infection, epidemiology, and evolution.

Phylogenetic meta-analysis of chronic SARS-CoV-2 infections in immunocompromised patients shows no evidence of elevated evolutionary rates

“…However, all 26 sample series included in this study exhibited genetic changes on a consensus sequence level over the course of infection. This is in contrast with the findings in [66], showing within-patient genetic variation in only around 30% of chronic infections. Differences between this study and [66] could be attributed to data discrepancies: whereas our dataset comprises viral sequences exclusively from patients with immunocompromised conditions, [66] included data from a large community-based surveillance study, likely containing individuals with a variety of clinical backgrounds including immunocompetent individuals.…”

“…The evaluation of within sample series’ genetic diversity revealed highly variable SARS-CoV- 2 diversity patterns among patients. Sample series showing lower genetic diversity despite long sampling window, such as Riddle-pt-3 with 225 days between first and last sample, conceivably indicate extremely low levels of viral replication for a lengthy period of time, as reported also in [66]. However, all 26 sample series included in this study exhibited genetic changes on a consensus sequence level over the course of infection.…”

Lineage replacement and evolution captured by 3 years of the United Kingdom Coronavirus (COVID-19) Infection Survey

“…The almost one-to-one concordance that we see between the emergence of lineages divergent compared to their predecessors, their growth rate advantage, and the resulting epidemic waves provides a clear narrative of epidemiological dynamics driven by saltational evolutionary events. Since new VOCs and other major lineages are characterized by nonsynonymous mutations [48], it has been hypothesized that they arose during long-term chronic infections with the virus subject to strong immune selection [49][50][51].…”

Using big sequencing data to identify chronic SARS-Coronavirus-2 infections

“…Despite the increased understanding that chronic SARS-COV-2 infecFons may significantly contribute to the evoluFon of the virus, our understanding of the dynamics of these infecFons and how they impact global evoluFonary pa\erns is limited and mostly conFngent on isolated case reports. Our and other previous meta-analyses 5,14 were mostly limited to the pre-VOC era and were based on a small number of cases (but see 15 ). We posit here that the ever-growing database of millions of SARS-COV-2 genomes likely harbors many sequences derived from chronic infecFons.…”

“…We reasoned that most oaen, sequences derived from chronically infected individuals will display as monophyleFc clades, i.e., all sequences derived from the ancestral node of the clade are from the same individual 7,9,10 . This reflects the following assumpFons: (i) someFmes, chronically infected individuals will be serially sampled and sequenced, (ii) sequences derived from the same individual will be very similar, and (iii) most chronically infected paFents do not create onward transmission chains 5,15 (otherwise, the clade would not be monophyleFc). We accordingly mined a global phylogeny of over 11 million sequences and inferred 271 inferred chronic-like monophyleFc clades and a set of control clades derived from transmission chains.…”