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High-dimensional analysis of 16 SARS-CoV-2 vaccine combinations reveals lymphocyte signatures correlating with immunogenicity.

Nicolás Gonzalo NuñezJonas SchmidLaura PowerChiara AlbertiSinduya KrishnarajahStefanie KreutmairSusanne UngerSebastián BlancoBrenda KonigheimConstanza MarínLuisina OnofrioJenny Christine KienzlerSara Costa-PereiraFlorian Ingelfingernull nullnull nullMarina E PasinovichJuan M CastelliCarla VizzottiMaximilian SchaeferJuan Villar-VesgaSarah MundtCarla Helena MertenAakriti SethiTobias WertheimerMirjam LutzDanusia VanoaicaClaudia SotomayorAdriana GruppiChristian MünzDiego CardozoGabriela BarbásLaura LopezPaula CarreñoGonzalo CastroElias RaboySandra GallegoGabriel MorónLaura CerviEva Virginia Acosta RodríguezBelkys A MalettoMariana MaccioniBurkhard Becher
Published in: Nature immunology (2023)
The range of vaccines developed against severe acute respiratory syndrome coronavirus 2 (SARS‑CoV‑2) provides a unique opportunity to study immunization across different platforms. In a single-center cohort, we analyzed the humoral and cellular immune compartments following five coronavirus disease 2019 (COVID-19) vaccines spanning three technologies (adenoviral, mRNA and inactivated virus) administered in 16 combinations. For adenoviral and inactivated-virus vaccines, heterologous combinations were generally more immunogenic compared to homologous regimens. The mRNA vaccine as the second dose resulted in the strongest antibody response and induced the highest frequency of spike-binding memory B cells irrespective of the priming vaccine. Priming with the inactivated-virus vaccine increased the SARS-CoV-2-specific T cell response, whereas boosting did not. Distinct immune signatures were elicited by the different vaccine combinations, demonstrating that the immune response is shaped by the type of vaccines applied and the order in which they are delivered. These data provide a framework for improving future vaccine strategies against pathogens and cancer.
Keyphrases
  • sars cov
  • respiratory syndrome coronavirus
  • coronavirus disease
  • immune response
  • squamous cell carcinoma
  • dendritic cells
  • dna methylation
  • working memory
  • gene expression
  • saccharomyces cerevisiae
  • machine learning