Reference-free computational method identifies spike-specific BCR sequences with over 90% purity in mRNA vaccinees

This observational methodological study evaluated LM-QASAS, a reference-free computational framework for identifying antigen-specific B-cell receptor (BCR) sequences. The population included healthy individuals vaccinated with SARS-CoV-2 mRNA vaccines and a separate influenza vaccine cohort. The method was compared against approaches based on simple sequence identity or abundance. The primary outcome was the purity of identified spike-specific sequences. The study also assessed accuracy in reconstructing immune dynamics in unseen individuals without external references and sensitivity in the influenza vaccine cohort.

The main results showed the method identified spike-specific sequences with over 90% purity in the SARS-CoV-2 mRNA vaccine cohort, significantly outperforming the comparator methods. It could accurately reconstruct immune dynamics in unseen individuals. However, it demonstrated limited sensitivity when applied to the influenza vaccine cohort. Safety and tolerability data were not reported.

Key limitations include that the approach is most effective under conditions of robust clonal expansion (high signal-to-noise ratio), such as those induced by mRNA vaccines, and its limited sensitivity in the influenza cohort suggests performance may vary by vaccine type. The sample size, setting, follow-up duration, and statistical measures like p-values or confidence intervals were not reported. The study provides a rapid, high-precision platform for methodological research into humoral immunity monitoring, but its clinical utility requires validation across diverse vaccine platforms and conditions.