ABSTRACT
Knowledge of the factors contributing to the development of protective immunity after vaccination with COVID-19 mRNA vaccines is fragmentary. Thus we employed high-temporal-resolution transcriptome profiling and in-depth characterization of antibody production approaches to investigate responses to COVID-19 mRNA vaccination. There were marked differences in the timing and amplitude of the responses to the priming and booster doses. Notably, two distinct interferon signatures were identified, that differed based on their temporal patterns of induction. The first signature (S1), which was preferentially induced by type I interferon, peaked at day 2 post-prime and at day 1 post-boost, and in both instances was associated with subsequent development of the antibody response. In contrast, the second interferon signature (S2) peaked at day 1 both post-prime and post-boost but was found to be potently induced only post-boost, where it coincided with a robust inflammation peak. Notably, we also observed post-prime-like (S1++,S20/+) and post-boost-like (S1++,S2++) patterns of interferon response among COVID-19 patients. A post-boost-like signature was observed in most severely ill patients at admission to the intensive care unit and was associated with a shorter hospital stay. Interestingly, severely ill patients who stayed hospitalized the longest showed a peculiar pattern of interferon induction (S1-/0,S2+), that we did not observe following the administration of mRNA vaccines. In summary, high temporal resolution profiling revealed an elaborate array of immune responses elicited by priming and booster doses of COVID-19 mRNA vaccines. Furthermore, it contributed to the identification of distinct interferon-response phenotypes underpinning vaccine immunogenicity and the course of COVID-19 disease.
Subject(s)
COVID-19 , Inflammation , Severe Acute Respiratory SyndromeABSTRACT
Background: Covid-19 morbidity and mortality are associated with a dysregulated immune response. Tools are needed to enhance existing immune profiling capabilities in affected patients. Here we aimed to develop an approach to support the design of focused blood transcriptome panels for profiling the immune response to SARS-CoV-2 infection. Methods: We designed a pool of candidates based on a pre-existing and well-characterized repertoire of blood transcriptional modules. Available Covid-19 blood transcriptome data was also used to guide this process. Further selection steps relied on expert curation. Additionally, we developed several custom web applications to support the evaluation of candidates. Results: As a proof of principle, we designed three targeted blood transcript panels, each with a different translational connotation: immunological relevance, therapeutic development relevance and SARS biology relevance. Conclusion: Altogether the work presented here may contribute to the future expansion of immune profiling capabilities via targeted profiling of blood transcript abundance in Covid-19 patients.
Subject(s)
COVID-19ABSTRACT
Covid-19 morbidity and mortality are associated with a dysregulated immune response. Tools are needed to enhance existing immune profiling capabilities in affected patients. Here we aimed to develop an approach to support the design of focused blood transcriptome panels for profiling the immune response to SARS-CoV-2 infection. We designed a pool of candidates based on a pre-existing and well-characterized repertoire of blood transcriptional modules. Available Covid-19 blood transcriptome data was also used to guide this process. Further selection steps relied on expert curation. Additionally, we developed several custom web applications to support the evaluation of candidates. As a proof of principle, we designed three targeted blood transcript panels, each with a different translational connotation: therapeutic development relevance, SARS biology relevance and immunological relevance. Altogether the work presented here may contribute to the future expansion of immune profiling capabilities via targeted profiling of blood transcript abundance in Covid-19 patients.