ArticleiScience2025
Human indels as predictors of antibody responses to COVID-19 vaccines.
Article in iScience, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
17 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Vaccine efficacy varies significantly among adults. This variability underlies the limitation of a one-size-fits-all vaccination strategy and the need for more personalized approaches. We investigated factors influencing inter-individual variability in antibody responses to COVID-19 mRNA vaccine among adults. Neutralizing antibody (nAb) levels after the first vaccine dose were associated with infection outcomes within 1 year after vaccination, suggesting their potential as a correlate of protection. Age, sex, and Chinese ethnicity were associated with nAb and anti-spike protein antibody levels. Two indels located at chr1:31433042 and chr15:76311269 showed significant association with antibody responses. Leveraging these host factors, we developed a Random Forest model that predicted vaccine-induced antibody responses with 72.7% accuracy for mRNA vaccine and 76.9% for the Sinopharm COVID-19 inactivated virus vaccine. These findings support predictive modeling as a tool to identify individuals at risk of low vaccine responses, enabling more targeted and effective vaccination strategies.
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