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Complexity
Volume 2017, Article ID 3017632, 9 pages
https://doi.org/10.1155/2017/3017632
Research Article

Exploring the Limitations of Peripheral Blood Transcriptional Biomarkers in Predicting Influenza Vaccine Responsiveness

1The Microsoft Research-University of Trento Centre for Computational and Systems Biology (COSBI), 38068 Rovereto, Italy
2GSK Vaccines, 53100 Siena, Italy
3Department of Mathematics, University of Trento, Povo, 38123 Trento, Italy
4Department of Computer Science, Stanford University, Stanford, CA, USA

Correspondence should be addressed to Luca Marchetti; ue.ibsoc@ittehcram

Received 26 April 2017; Revised 2 August 2017; Accepted 10 August 2017; Published 28 September 2017

Academic Editor: Min Li

Copyright © 2017 Luca Marchetti et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Systems biology has been recently applied to vaccinology to better understand immunological responses to the influenza vaccine. Particular attention has been paid to the identification of early signatures capable of predicting vaccine immunogenicity. Building from previous studies, we employed a recently established algorithm for signature-based clustering of expression profiles, SCUDO, to provide new insights into why blood-derived transcriptome biomarkers often fail to predict the seroresponse to the influenza virus vaccination. Specifically, preexisting immunity against one or more vaccine antigens, which was found to negatively affect the seroresponse, was identified as a confounding factor able to decouple early transcriptome from later antibody responses, resulting in the degradation of a biomarker predictive power. Finally, the broadly accepted definition of seroresponse to influenza virus vaccine, represented by the maximum response across the vaccine-targeted strains, was compared to a composite measure integrating the responses against all strains. This analysis revealed that composite measures provide a more accurate assessment of the seroresponse to multicomponent influenza vaccines.