We use cookies to understand how you use our site and to improve your experience. This includes personalizing content and advertising. To learn more, click here. By continuing to use our site, you accept our use of cookies. Cookie Policy.

Features Partner Sites Information LinkXpress hp
Sign In
Advertise with Us
ZeptoMetrix an Antylia scientific company

Download Mobile App




RNA Analysis of Nasal Swabs Diagnoses Respiratory Virus Infection

By LabMedica International staff writers
Posted on 01 Jan 2018
A panel of three mRNAs has been shown to be able to predict presence of respiratory virus infection in nasal samples with an accuracy of 97%.

Despite the high burden of respiratory infection and the importance of early and accurate diagnosis, there is at this time no simple diagnostic test to rule in viral infection as a cause of respiratory symptoms.

To fill this gap, investigators at Yale University (New London, CT, USA) performed RNASeq on human nasal epithelial cells following stimulation of the intracellular viral recognition receptor RIG-I. More...
Next, they evaluated whether measuring identified host mRNAs and proteins from patient nasopharyngeal swabs could predict the presence of a respiratory virus in the sample. Samples were obtained from patients who were primarily older adults or young children, reflecting the population tested for respiratory viruses in the healthcare system.

RNASeq (RNA sequencing) uses next-generation sequencing (NGS) to reveal the presence and quantity of RNA in a biological sample at a given moment in time. This technique is used to analyze the continuously changing cellular transcriptome. Specifically, RNASeq facilitates the ability to look at alternative gene spliced transcripts, post-transcriptional modifications, gene fusion, mutations/SNPs, and changes in gene expression over time, or differences in gene expression in different groups or treatments. In addition to mRNA transcripts, RNASeq can look at different populations of RNA to include total RNA, small RNA, such as miRNA, tRNA, and ribosomal profiling.

The investigators initially showed that a signature of three mRNAs, CXCL10, IFIT2, and OASL, predicted respiratory virus detection with an accuracy of 97% and identified proteins correlating with virus detection. In a follow-up study, elevated CXCL11 or CXCL10 protein levels identified samples containing respiratory viruses, including viruses not on the initial test panel.

"It is a simpler test and more cost-effective for looking at viral infection," said senior author Dr. Ellen Foxman, assistant professor of laboratory medicine at Yale University. "Instead of looking for individual viruses, our test asks the question: "Is the body fighting a virus?". We found we can answer that question very well. One reason to test is to know why the patient is sick. The other reason is to make a decision about whether people who are not that sick should get antibiotics."

The respiratory virus test was described in the December 21, 2017, online edition of The Journal of Infectious Diseases.

Related Links:
Yale University


Platinum Member
COVID-19 Rapid Test
OSOM COVID-19 Antigen Rapid Test
Verification Panels for Assay Development & QC
Seroconversion Panels
Anti-Cyclic Citrullinated Peptide Test
GPP-100 Anti-CCP Kit
Gold Member
hCG Whole Blood Pregnancy Test
VEDALAB hCG-CHECK-1
Read the full article by registering today, it's FREE! It's Free!
Register now for FREE to LabMedica.com and get access to news and events that shape the world of Clinical Laboratory Medicine.
  • Free digital version edition of LabMedica International sent by email on regular basis
  • Free print version of LabMedica International magazine (available only outside USA and Canada).
  • Free and unlimited access to back issues of LabMedica International in digital format
  • Free LabMedica International Newsletter sent every week containing the latest news
  • Free breaking news sent via email
  • Free access to Events Calendar
  • Free access to LinkXpress new product services
  • REGISTRATION IS FREE AND EASY!
Click here to Register








Channels

Clinical Chemistry

view channel
Image: QIP-MS could predict and detect myeloma relapse earlier compared to currently used techniques (Photo courtesy of Adobe Stock)

Mass Spectrometry-Based Monitoring Technique to Predict and Identify Early Myeloma Relapse

Myeloma, a type of cancer that affects the bone marrow, is currently incurable, though many patients can live for over 10 years after diagnosis. However, around 1 in 5 individuals with myeloma have a high-risk... Read more

Immunology

view channel
Image: The cancer stem cell test can accurately choose more effective treatments (Photo courtesy of University of Cincinnati)

Stem Cell Test Predicts Treatment Outcome for Patients with Platinum-Resistant Ovarian Cancer

Epithelial ovarian cancer frequently responds to chemotherapy initially, but eventually, the tumor develops resistance to the therapy, leading to regrowth. This resistance is partially due to the activation... Read more

Technology

view channel
Image: Ziyang Wang and Shengxi Huang have developed a tool that enables precise insights into viral proteins and brain disease markers (Photo courtesy of Jeff Fitlow/Rice University)

Light Signature Algorithm to Enable Faster and More Precise Medical Diagnoses

Every material or molecule interacts with light in a unique way, creating a distinct pattern, much like a fingerprint. Optical spectroscopy, which involves shining a laser on a material and observing how... Read more

Industry

view channel
Image: The collaboration aims to leverage Oxford Nanopore\'s sequencing platform and Cepheid\'s GeneXpert system to advance the field of sequencing for infectious diseases (Photo courtesy of Cepheid)

Cepheid and Oxford Nanopore Technologies Partner on Advancing Automated Sequencing-Based Solutions

Cepheid (Sunnyvale, CA, USA), a leading molecular diagnostics company, and Oxford Nanopore Technologies (Oxford, UK), the company behind a new generation of sequencing-based molecular analysis technologies,... Read more
Copyright © 2000-2026 Globetech Media. All rights reserved.