Tang, Benjamin M., Shojaei, Maryam, Parnell, Grant P., Huang, Stephen, Nalos, Marek, Teoh, Sally, O'Connor, Kate, Schibeci, Stephen, Phu, Amy L., Kumar, Anand, Ho, John, Meyers, Adrienn F.A., Keynan, Yoav, Ball, Terry, Pisipati, Amarnath, Kumar, Aseem, Moore, Elizabeth, Eisen, Damon, Lai, Kevin, Gillett, Mark, Geffers, Robert, Luo, Hao, Gul, Fahad, Schreiber, Jens, Riedel, Sandra, Booth, David, McLean, Anthony, and Schughart, Klaus (2017) A novel immune biomarker IFI27 discriminates between influenza and bacteria in patients with suspected respiratory infection. European Respiratory Journal, 49 (6). 1602098.

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Abstract

Host response biomarkers can accurately distinguish between influenza and bacterial infection. However, published biomarkers require the measurement of many genes, thereby making it difficult to implement them in clinical practice. This study aims to identify a single-gene biomarker with a high diagnostic accuracy equivalent to multi-gene biomarkers.

In this study, we combined an integrated genomic analysis of 1071 individuals with in vitro experiments using well-established infection models.

We identified a single-gene biomarker, IFI27, which had a high prediction accuracy (91%) equivalent to that obtained by multi-gene biomarkers. In vitro studies showed that IFI27 was upregulated by TLR7 in plasmacytoid dendritic cells, antigen-presenting cells that responded to influenza virus rather than bacteria. In vivo studies confirmed that IFI27 was expressed in influenza patients but not in bacterial infection, as demonstrated in multiple patient cohorts (n=521). In a large prospective study (n=439) of patients presented with undifferentiated respiratory illness (aetiologies included viral, bacterial and non-infectious conditions), IFI27 displayed 88% diagnostic accuracy (AUC) and 90% specificity in discriminating between influenza and bacterial infections.

IFI27 represents a significant step forward in overcoming a translational barrier in applying genomic assay in clinical setting; its implementation may improve the diagnosis and management of respiratory infection.

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