Systematic characterization of human response to H1N1 influenza vaccination through the construction and integration of personalized transcriptome response profiles

Carlo De Intinis,Margherita Bodini,Denise Maffione,Emilio Siena,Laurane De Mot,Duccio Medini,Margherita Coccia

doi:10.1038/s41598-021-99870-0

Carlo De Intinis, Margherita Bodini + Show 5 more

Open Access

https://doi.org/10.1038/s41598-021-99870-0

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Abstract

Gene expression data is commonly used in vaccine studies to characterize differences between treatment groups or sampling time points. Group-wise comparisons of the transcriptional perturbations induced by vaccination have been applied extensively for investigating the mechanisms of action of vaccines. Such approaches, however, may not be sensitive enough for detecting changes occurring within a minority of the population under investigation or in single individuals. In this study, we developed a data analysis framework to characterize individual subject response profiles in the context of repeated measure experiments, which are typical of vaccine mode of action studies. Following the definition of the methodology, this was applied to the analysis of human transcriptome responses induced by vaccination with a subunit influenza vaccine. Results highlighted a substantial heterogeneity in how different subjects respond to vaccination. Moreover, the extent of transcriptional modulation experienced by each individual subject was found to be associated with the magnitude of vaccine-specific functional antibody response, pointing to a mechanistic link between genes involved in protein production and innate antiviral response. Overall, we propose that the improved characterization of the intersubject heterogeneity, enabled by our approach, can help driving the improvement and optimization of current and next-generation vaccines.

Highlights

Gene expression data is commonly used in vaccine studies to characterize differences between treatment groups or sampling time points
Inspired by the work of Menche et al, we developed a new data analysis pipeline, for the characterization of individual subject response profiles, and applied it to investigate the transcriptional responses induced by the administration of a subunit influenza vaccine
We set out to analyze the transcriptional response to vaccination using publicly available data (Tsang et al 2014) consisting in PBMC transcriptome responses derived from 63 healthy adults vaccinated with the seasonal and pandemic H1N1 subunit influenza vaccines

Summary

Introduction

Gene expression data is commonly used in vaccine studies to characterize differences between treatment groups or sampling time points. Despite the general success in identifying molecular signatures of increased vaccine immunogenicity, these studies highlighted the fact that establishing causality in the chain of reactions triggered by vaccination is not trivial This is due, at least in part, to the pervasive heterogeneity that characterizes the human population, which results in distinct individuals to respond differently to the same v accine[11]. Menche et al.[14] developed an approach to derive personalized transcriptome response profiles in individuals affected by either asthma, Parkinson’s or Huntington’s disease Their method allowed for the characterization of genes being modulated within individual subjects, based on the comparison with a healthy control group. Their approach proved to be more sensitive than conventional techniques in identifying transcriptional signatures associated to a particular disease and allowed to diagnose subjects affected by Huntington’s disease with 100% accuracy

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