Developing a giant magnetoresistive (GMR)-based assay for quantification of the human immune response to influenza infection and vaccination
Abstract/Contents
- Abstract
- Seasonal and pandemic strains of influenza viruses remain among the most common and deadly respiratory viral pathogens. The gold standard for influenza testing is reverse transcription polymerase chain reaction (RT-PCR), in which amplification of influenza viral RNA is performed and quantified. However, the primers for RT-PCR testing are designed to detect specific viral sequences and the diagnostic efficacy can be reduced when a new strain emerges in the population. While detection of viral RNA is important for disease diagnosis, exploring differences in host gene expression during the time course of infection could provide useful clinical information, such as dose and duration of antiviral medications. An analysis of publicly available transcriptional data identified an eleven-gene host transcriptional signature, the Influenza Meta Signature (IMS), that could distinguish individuals infected with influenza from those with bacterial or other respiratory viral infections. Detecting and quantifying the host transcriptional response to influenza virus infection can serve as a real-time diagnostic tool for clinical management. Moreover, measuring differences in transcript levels after influenza vaccination may predict vaccine responsiveness. 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 and influenza vaccine responsiveness based on transcript levels. After characterizing GMR sensors to detect and quantify a single transcript, we show that the assay can reliably detect eleven IMS transcripts and distinguish patients with influenza infection from those with other symptomatic viral infections(AUC 0.93, 95% CI: 0.84-1.00). The assay can also predict a likely vaccine non- responder by measuring IMS expression levels before and after vaccination (paired t-test p< 0.0001). 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.
Description
| Type of resource | text |
|---|---|
| Form | electronic resource; remote; computer; online resource |
| Extent | 1 online resource. |
| Place | California |
| Place | [Stanford, California] |
| Publisher | [Stanford University] |
| Copyright date | 2021; ©2021 |
| Publication date | 2021; 2021 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | Ravi, Neeraja |
|---|---|
| Degree supervisor | Wang, Shan X |
| Thesis advisor | Wang, Shan X |
| Thesis advisor | Fordyce, Polly |
| Thesis advisor | Utz, PJ |
| Degree committee member | Fordyce, Polly |
| Degree committee member | Utz, PJ |
| Associated with | Stanford University, Department of Bioengineering |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Neeraja Ravi. |
|---|---|
| Note | Submitted to the Department of Bioengineering. |
| Thesis | Thesis Ph.D. Stanford University 2021. |
| Location | https://purl.stanford.edu/mj459rt6144 |
Access conditions
- Copyright
- © 2021 by Neeraja Ravi
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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