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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.<\/jats:p>","DOI":"10.1155\/2017\/3017632","type":"journal-article","created":{"date-parts":[[2017,9,28]],"date-time":"2017-09-28T17:03:17Z","timestamp":1506618197000},"page":"1-9","source":"Crossref","is-referenced-by-count":3,"title":["Exploring the Limitations of Peripheral Blood Transcriptional Biomarkers in Predicting Influenza Vaccine Responsiveness"],"prefix":"10.1155","volume":"2017","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9043-7705","authenticated-orcid":true,"given":"Luca","family":"Marchetti","sequence":"first","affiliation":[{"name":"The Microsoft Research-University of Trento Centre for Computational and Systems Biology (COSBI), 38068 Rovereto, 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