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 InSignia 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 InSignia 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 InSignia 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 InSignia assay was more sensitive in detecting viral infection among hospital patients. These findings suggest that the InSignia assay, which supports high throughput workflows, may be used for the rapid detection of viral infection in patients with respiratory symptoms.
