Department of Bioengineering, Stanford University, Stanford, CA, 93405, USA.
Institute for Immunity, Transplantation and Infection, Stanford University School of Medicine, Stanford, CA, USA; Division of Immunology and Rheumatology, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA.
Biosens Bioelectron. 2022 Jun 1;205:114086. doi: 10.1016/j.bios.2022.114086. Epub 2022 Feb 17.
Detecting and quantifying the host transcriptional response to influenza virus infection can serve as a real-time diagnostic tool for clinical management. We have employed the multiplexing capabilities of GMR sensors to develop a novel assay based on the influenza metasignature (IMS), which can classify influenza infection based on transcript levels. We show that the assay can reliably detect ten IMS transcripts and distinguish subjects with naturally acquired influenza infection from those with other symptomatic viral infections (AUC 0.93, 95% CI: 0.82-1.00). Separately, we validated that the gene IFI27, not included in the IMS panel, has very high single-biomarker accuracy (AUC 0.95, 95% CI: 0.90-0.99) in stratifying patients with influenza. We demonstrate that a portable GMR biosensor can be used as a tool to diagnose influenza infection by measuring the host response, simultaneously highlighting the power of immune system metrics and advancing the field of gene expression-based diagnostics.
检测和量化宿主对流感病毒感染的转录反应可以作为临床管理的实时诊断工具。我们利用 GMR 传感器的多重检测能力，开发了一种基于流感元特征（IMS）的新型检测方法，该方法可以根据转录水平对流感感染进行分类。我们表明，该检测方法可以可靠地检测十个 IMS 转录本，并区分自然获得性流感感染的患者与其他有症状的病毒感染患者（AUC 0.93，95%置信区间：0.82-1.00）。此外，我们验证了不在 IMS 面板中的基因 IFI27 在分层流感患者方面具有非常高的单生物标志物准确性（AUC 0.95，95%置信区间：0.90-0.99）。我们证明，便携式 GMR 生物传感器可通过测量宿主反应用作诊断流感感染的工具，同时突出了免疫系统指标的强大功能，并推进了基于基因表达的诊断领域。
