Learning from Failure: Deep Phenotyping of Non-Responders to mRNA Vaccines

Much attention has focused on the spectacular efficacy of leading mRNA vaccines (Baden et al., 2020; Polack et al., 2020), but reports like Kremsner et al. (2021) and Zhou et al. (2024) reveal substantial variability in vaccine efficacy across populations and variants. Instead of treating “non-responders” as statistical noise, this project would use single-cell transcriptomics, proteomics, and immune profiling to dissect the cellular and molecular basis of poor responses—considering factors like innate immune activation, mRNA metabolism, cell-type tropism, and even microbiome interactions. By identifying why certain individuals or conditions lead to suboptimal efficacy or unexpected adverse events, we could discover new checkpoints or delivery barriers—and develop next-generation mRNA vaccines that are more universally effective and safer, especially in vulnerable populations (elderly, immunocompromised, etc.).

References:

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