Development of an objective gene expression panel as an alternative to self-reported symptom scores in human influenza challenge trials.

Published online

Journal Article

BACKGROUND: Influenza challenge trials are important for vaccine efficacy testing. Currently, disease severity is determined by self-reported scores to a list of symptoms which can be highly subjective. A more objective measure would allow for improved data analysis. METHODS: Twenty-one volunteers participated in an influenza challenge trial. We calculated the daily sum of scores (DSS) for a list of 16 influenza symptoms. Whole blood collected at baseline and 24, 48, 72 and 96 h post challenge was profiled on Illumina HT12v4 microarrays. Changes in gene expression most strongly correlated with DSS were selected to train a Random Forest model and tested on two independent test sets consisting of 41 individuals profiled on a different microarray platform and 33 volunteers assayed by qRT-PCR. RESULTS: 1456 probes are significantly associated with DSS at 1% false discovery rate. We selected 19 genes with the largest fold change to train a random forest model. We observed good concordance between predicted and actual scores in the first test set (r = 0.57; RMSE = -16.1%) with the greatest agreement achieved on samples collected approximately 72 h post challenge. Therefore, we assayed samples collected at baseline and 72 h post challenge in the second test set by qRT-PCR and observed good concordance (r = 0.81; RMSE = -36.1%). CONCLUSIONS: We developed a 19-gene qRT-PCR panel to predict DSS, validated on two independent datasets. A transcriptomics based panel could provide a more objective measure of symptom scoring in future influenza challenge studies. Trial registration Samples were obtained from a clinical trial with the Identifier: NCT02014870, first registered on December 5, 2013.

Full Text

Duke Authors

Cited Authors

  • Muller, J; Parizotto, E; Antrobus, R; Francis, J; Bunce, C; Stranks, A; Nichols, M; McClain, M; Hill, AVS; Ramasamy, A; Gilbert, SC

Published Date

  • June 8, 2017

Published In

Volume / Issue

  • 15 / 1

Start / End Page

  • 134 -

PubMed ID

  • 28595644

Pubmed Central ID

  • 28595644

Electronic International Standard Serial Number (EISSN)

  • 1479-5876

Digital Object Identifier (DOI)

  • 10.1186/s12967-017-1235-3


  • eng

Conference Location

  • England