Abstract
Immunomonitoring is the study of an individual’s immune responses over the course of vaccination or infection. In the infectious context, exploring the innate and adaptive immune responses will help to investigate their contribution to viral control or toxicity. After vaccination, immunomonitoring of the correlate(s) and surrogate(s) of protection is a major asset for measuring vaccine immune efficacy. Conventional immunomonitoring methods include antibody-based technologies that are easy to use. However, promising sensitive high-throughput technologies allowed the emergence of holistic approaches. This raises the question of data integration methods and tools. These approaches allow us to increase our knowledge on immune mechanisms as well as the identification of key effectors of the immune response. However, the depiction of relevant findings requires a well-rounded consideration beforehand about the hypotheses, conception, organization and objectives of the immunomonitoring. Therefore, well-standardized and comprehensive studies fuel insight to design more efficient, rationale-based vaccines and therapeutics to fight against infectious diseases. Hence, we will illustrate this review with examples of the immunomonitoring approaches used during vaccination and the COVID-19 pandemic.
Highlights
Outbreaks of emergent infectious diseases, such as Ebola, Zika or coronavirus disease2019 (COVID-19), are major healthcare issues with psychological, economical and demographic consequences for human societies
Major advances in immunomonitoring methods have seen the promise of systems biology era
Integrative data strategies taking advantage of high-throughput devices have depicted, more and more precisely and rapidly, the immune processes associated with vaccination, infection or cancers
Summary
Outbreaks of emergent infectious diseases, such as Ebola, Zika or coronavirus disease. The recent emergence of immune effector screening through complex approaches including multiparametric cell phenotyping (mass or spectral cytometry), transcriptomic, metabolomic, microbiome and proteomic analyses should lead to the discovery of new immune signatures associated with protection. These omics strategies generate large datasets which require powerful informatic and statistic tools. Machine learning would allow us to depict an overview of the immune response and provide insights about the major effectors of the immune response by systems biology-derived approaches [9]. We discuss the available methods for tracking and identifying immune parameters that are involved in protection and the related predictors of immune responsiveness
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