Evaluating the InSignia IFI27 expression assay for detecting viral respiratory infection compared to a traditional gene normalisation assay

Abstract

Abstract Host gene expression is crucial for understanding disease progression and developing diagnostic biomarkers. Previously, we identified a novel immune biomarker IFI27, validated with routine RT-qPCR methods employed in a research setting, that discriminates between influenza and bacteria in patients with suspected respiratory infection. This study aimed to assess the In Signia method, which employs a novel gene normalization technique to yield a variable transcript analysis (VITA) index. The VITA index measures gene expression relative to a non-transcribed region of DNA, such that it is independent of sample quality or quantity. We compared IFI27 gene expression measured by the In Signia assay to that of the research assay in blood samples collected from patients with respiratory diseases and SARS-CoV-2 vaccinated individuals. The study found a strong correlation and acceptable agreement between traditional ΔCq methods and In Signia for IFI27 levels in the higher range (log(ΔCq)Research > 1), but not for IFI27 expression levels below this range, likely due to the different normalization strategies. Notably the In Signia assay was more sensitive in detecting viral infection among hospital patients. These findings suggest that the In Signia assay, which supports high throughput workflows, may be used for the rapid detection of viral infection in patients with respiratory symptoms.