A GMR-based assay for quantification of the human response to influenza

Neeraja Ravi; Sarah E Chang; Luis M Franco; Sandesh C S Nagamani; Purvesh Khatri; Paul J Utz; Shan X Wang

doi:10.1016/j.bios.2022.114086

A GMR-based assay for quantification of the human response to influenza

Biosens Bioelectron. 2022 Jun 1:205:114086. doi: 10.1016/j.bios.2022.114086. Epub 2022 Feb 17.

Authors

Neeraja Ravi¹, Sarah E Chang², Luis M Franco³, Sandesh C S Nagamani⁴, Purvesh Khatri⁵, Paul J Utz⁶, Shan X Wang⁷

Affiliations

¹ Department of Bioengineering, Stanford University, Stanford, CA, 93405, USA. Electronic address: neravi@stanford.edu.
² 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. Electronic address: sarahechang14@gmail.com.
³ Functional Immunogenomics Unit, Systemic Autoimmunity Branch, National Institute of Arthritis and Musculoskeletal and Skin Diseases, National Institutes of Health, Bethesda, MD, USA. Electronic address: luis.franco@nih.gov.
⁴ Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA. Electronic address: nagamani@bcm.edu.
⁵ Division of Immunology and Rheumatology, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA; Division of Biomedical Informatics, Department of Medicine, Stanford University, Stanford, CA, USA. Electronic address: pkhatri@stanford.edu.
⁶ 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. Electronic address: pjutz@stanford.edu.
⁷ Department of Materials Science and Engineering, Stanford University, Stanford, CA, USA; Department of Electrical Engineering, Stanford University, Stanford, CA, USA. Electronic address: sxwang@stanford.edu.

Abstract

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.

Keywords: GMR sensors; Gene expression; Host response; Influenza; Point-of-care diagnostics.

MeSH terms

Biological Assay
Biosensing Techniques*
Humans
Influenza, Human*
Orthomyxoviridae*
Virus Diseases*

Abstract

MeSH terms

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