Comparative Analysis of Host Immune Signatures of Influenza and SARS-CoV-2 Infection vs. Vaccination: A Prospective Multi-Cohort Study of Host Transcriptional Responses including Single Cell RNA-Sequencing

Background and Rationale. Host transcriptional immune changes in response to infection and vaccination, known as mRNA signatures, are novel diagnostic and predictive tools in the field of Infectious Diseases (ID), acting as a "proxy" for the immune system activity at a molecular level. Several signatures have been proposed to differentiate bacterial from viral or other infections, detect specific pathogens, and even predict disease severity and treatment outcome, serving as potent biomarkers of disease. Similarly, pre- and post-vaccination signatures to predict vaccine efficacy and immune memory are currently being studied, offering new insights into vaccine immunogenicity. The identification of such complex biomarkers can only be achieved using sophisticated molecular and bioinformatics analyses enabling high-throughput profiling of massive amounts of data. Comparing immune signatures between infection and vaccination can lead to the development of valuable, clinically relevant predictive tools. It can also shed light on immune responses associated with protection and durability for vaccine development purposes, and accurately differentiate breakthrough infection from vaccine-specific immune memory in antigen-exposed hosts for diagnostic and prognostic purposes. To date, such comparative data are lacking and could be generated by combining bulk transcriptomics with single cell RNA-sequencing (scRNA-seq) profiling of immune responses.Overall Objectives and Specific Aims. The aim of the proposed project is to identify common and unique mRNA signatures between infection and vaccine response to influenza and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) using bulk transcriptomics and scRNA-seq data. To achieve this, we will define the temporal immune response to infection and vaccination, and explore whether signatures of successful vaccine response resemble those of pathogenic infection. Additionally, we will perform bulk RNA-seq cell deconvolution using scRNA-seq analysis to infer the cell types that contribute to signature performance and improve interpretability of the results.Methods. We propose a prospective, observational, multi-cohort study using array-based and RNA-seq data (referred to as transcriptomics) from blood samples of nearly 2,000 participants enrolled in studies included in the Human Immunology Project Consortium and the Immunophenotyping Assessment in a COVID-19 Cohort (IMPACC). Blood samples are collected at baseline (day 0) and at days 3, 7, 14, 28, and 29-70 following infection or vaccination. Through a standardized computational pipeline, we will identify and perform comparative analysis of mRNA signatures using differential gene expression (DGE) and B cell receptor (BCR) profiling on bulk and scRNA-seq data to identify novel, common, and unique signatures between infection and vaccination for influenza and SARS-CoV-2. Furthermore, we will match bulk and scRNA-seq data to perform bulk RNA-seq cell deconvolution and improve the resolution and interpretability of bulk signatures.Expected Results and their impact for the field. We aim to identify and compare common immune signatures between influenza and SARS-CoV-2 infection versus vaccination, with temporal response being the key component. The established global framework and analytical pipeline will promote reproducible methods for comparative signature discovery, making them accessible to the wider scientific community. In addition to developing new signatures that could be implemented as clinically relevant biomarkers, this project will expand current knowledge on immune pathways involved in the response to infections and vaccines, facilitate the development of models transferable to various settings and pathogens, and lay the foundation for subsequent human studies.