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Humoral immune response to omicron infection in long-term Wuhan-Hu-1-imprinted population (preprint)
researchsquare; 2023.
Preprint in English | PREPRINT-RESEARCHSQUARE | ID: ppzbmed-10.21203.rs.3.rs-3024491.v1
ABSTRACT
Recent WHO vaccination guidance no longer recommends COVID-19 vaccination beyond the first booster in low risk population, citing high population-level hybrid immunity due to widespread omicron infections.1 Although SARS-CoV-2 infection confers durable protection against reinfection,2-4 it may also produce immune imprinting, which skews subsequent immune response to variant antigens toward the first-exposed antigen based on the antigenic distance.5,6 China has the earliest and exclusively Wuhan-Hu-1(WH1)-imprinted population before the 2022 nation-wide omicron outbreak,7 which offers a unique opportunity to study long-term immune imprinting between most antigenically distant strains. Here, we assessed pseudovirus neutralization activity and anti-WH1 receptor binding domain (RBD) antibodies in 4 Chinese cohorts with hybrid or vaccine-only imprinting, or naïve to SARS-CoV-2 prior to omicron BF.7 infection. Both hybrid and vaccine-only imprinting augmented post-infection serum neutralization of WH1 and omicron sub-variants BF.7/BQ.1.1/XBB.1.5 comparing to naïve background. Feedback from pre-existing high-affinity antibodies limited the magnitude of humoral immune response to omicron infection without compromising protection, while antigenic seniority of pre-existing cross-reactive B cells only slightly reduces forward neutralization breadth in hybrid- and RBD vaccine-imprinted participants. Our results support the effectiveness of hybrid immunity against omicron reinfection in long-term imprinted population and provide immunological basis for similar epidemiological findings.8-10
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Full text: Available Collection: Preprints Database: PREPRINT-RESEARCHSQUARE Main subject: COVID-19 Language: English Year: 2023 Document Type: Preprint

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Full text: Available Collection: Preprints Database: PREPRINT-RESEARCHSQUARE Main subject: COVID-19 Language: English Year: 2023 Document Type: Preprint