Long-Term Evolution of SARS-CoV-2 in an Immunocompromised Patient with Non-Hodgkin Lymphoma

非霍奇金淋巴瘤免疫功能低下患者体内SARS-CoV-2的长期演变

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Abstract

Recent studies have shown that persistent SARS-CoV-2 infections in immunocompromised patients can trigger the accumulation of an unusual high number of mutations with potential relevance at both biological and epidemiological levels. Here, we report a case of an immunocompromised patient (non-Hodgkin lymphoma patient under immunosuppressive therapy) with a persistent SARS-CoV-2 infection (marked by intermittent positivity) over at least 6 months. Viral genome sequencing was performed at days 1, 164, and 171 to evaluate SARS-CoV-2 evolution. Among the 15 single-nucleotide polymorphisms (SNPs) (11 leading to amino acid alterations) and 3 deletions accumulated during this long-term infection, four amino acid changes (V3G, S50L, N87S, and A222V) and two deletions (18-30del and 141-144del) occurred in the virus Spike protein. Although no convalescent plasma therapy was administered, some of the detected mutations have been independently reported in other chronically infected individuals, which supports a scenario of convergent adaptive evolution. This study shows that it is of the utmost relevance to monitor the SARS-CoV-2 evolution in immunocompromised individuals, not only to identify novel potentially adaptive mutations, but also to mitigate the risk of introducing "hyper-evolved" variants in the community. IMPORTANCE Tracking the within-patient evolution of SARS-CoV-2 is key to understanding how this pandemic virus shapes its genome toward immune evasion and survival. In the present study, by monitoring a long-term COVID-19 immunocompromised patient, we observed the concurrent emergence of mutations potentially associated with immune evasion and/or enhanced transmission, mostly targeting the SARS-CoV-2 key host-interacting protein and antigen. These findings show that the frequent oscillation in the immune status in immunocompromised individuals can trigger an accelerated virus evolution, thus consolidating this study model as an accelerated pathway to better understand SARS-CoV-2 adaptive traits and anticipate the emergence of variants of concern.

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