Blood-Based Test Accurately Identifies Viral Infection Before Symptoms Develop
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By LabMedica International staff writers Posted on 07 Oct 2020 |

Image: The Applied Biosystems ViiA 7 Real-Time PCR System combines all of the qPCR features in a single high performance instrument (Photo courtesy of Thermo Fisher Scientific).
Acute viral infections are one of the most common reasons for visits to primary care physicians in high-income countries. The usefulness of traditional pathogen-focused diagnostic methods for viral infection (e.g., culture, serology, antigen detection, and PCR) is limited by the fact they can be slow, costly, and restricted in terms of breadth of pathogens detected.
Previous studies on diagnostics for naturally acquired infection has focused on identifying symptomatic individuals at the time of clinical presentation for medical care, which is often late in the time course of many viral infections. Identification of infectious causes in earlier, presymptomatic phases of illness provides an opportunity to optimize and deliver timely, and thus more effective, therapy, refine prophylaxis decisions, and guide public health interventions such as isolation and quarantine.
Infectious Disease specialists at Duke University Medical Center (Durham, NC, USA) and their associates enrolled 1,465 college students at the university between 2009 and 2015 and monitored them for the entire academic year for the presence and severity of eight symptoms of respiratory tract infections. Participants filled out a daily web-based survey, rating symptoms on a scale of 0-4. Index cases were defined as study participants who reported a 6-point increase in a cumulative daily symptom score. Biospecimens were collected from 264 index cases with clinical illness, of whom 150 had a respiratory viral cause confirmed by traditional PCR testing of nasopharyngeal samples.
Blood (20 mL) and nasopharyngeal swab samples were collected daily by study staff from confirmed index cases at the time of illness identification. The nasopharyngeal samples were tested for the presence of viruses using commercial multiplex PCR assays (ResPlex II Panel, Qiagen, Hilden, Germany), xTAG respiratory viral panel (Luminex Corporation, Austin, TX, USA), or BioFire FilmArray Respiratory Panel (BioFire Diagnostics, Salt Lake City, UT, USA). The team selected 36 pre-designed TaqMan probes representing genes comprising the acute respiratory viral signature (and normalization controls) to be used on a TaqMan Low Density Array platform run on a ViiA7 Real-Time PCR System (Applied Biosystems, Foster City, CA, USA).
The scientists reported that of the 555 close contacts enrolled and sampled, 162 developed symptoms of respiratory tract infection during observation, of whom 106 had confirmed illness based on traditional viral PCR testing. For most of the study participants, the gene expression test accurately predicted viral infection up to three days before maximum symptoms, often prior to any symptom onset or detectable viral shedding. For influenza, the assay was 99% accurate in predicting illness, 95% accurate for adenovirus and 93% accurate for the cold-causing coronavirus strain.
Micah McClain, MD, PhD, associate professor of Medicine and lead author of a study, said, “Our study demonstrates the potential of this gene expression-based testing approach. We can use the body's natural immune response signals to detect a viral infection with a high degree of accuracy even at a time when people have been exposed to the pathogen but don't yet feel sick.” The study was published on September 24, 2020 in the journal The Lancet Infectious Diseases.
Previous studies on diagnostics for naturally acquired infection has focused on identifying symptomatic individuals at the time of clinical presentation for medical care, which is often late in the time course of many viral infections. Identification of infectious causes in earlier, presymptomatic phases of illness provides an opportunity to optimize and deliver timely, and thus more effective, therapy, refine prophylaxis decisions, and guide public health interventions such as isolation and quarantine.
Infectious Disease specialists at Duke University Medical Center (Durham, NC, USA) and their associates enrolled 1,465 college students at the university between 2009 and 2015 and monitored them for the entire academic year for the presence and severity of eight symptoms of respiratory tract infections. Participants filled out a daily web-based survey, rating symptoms on a scale of 0-4. Index cases were defined as study participants who reported a 6-point increase in a cumulative daily symptom score. Biospecimens were collected from 264 index cases with clinical illness, of whom 150 had a respiratory viral cause confirmed by traditional PCR testing of nasopharyngeal samples.
Blood (20 mL) and nasopharyngeal swab samples were collected daily by study staff from confirmed index cases at the time of illness identification. The nasopharyngeal samples were tested for the presence of viruses using commercial multiplex PCR assays (ResPlex II Panel, Qiagen, Hilden, Germany), xTAG respiratory viral panel (Luminex Corporation, Austin, TX, USA), or BioFire FilmArray Respiratory Panel (BioFire Diagnostics, Salt Lake City, UT, USA). The team selected 36 pre-designed TaqMan probes representing genes comprising the acute respiratory viral signature (and normalization controls) to be used on a TaqMan Low Density Array platform run on a ViiA7 Real-Time PCR System (Applied Biosystems, Foster City, CA, USA).
The scientists reported that of the 555 close contacts enrolled and sampled, 162 developed symptoms of respiratory tract infection during observation, of whom 106 had confirmed illness based on traditional viral PCR testing. For most of the study participants, the gene expression test accurately predicted viral infection up to three days before maximum symptoms, often prior to any symptom onset or detectable viral shedding. For influenza, the assay was 99% accurate in predicting illness, 95% accurate for adenovirus and 93% accurate for the cold-causing coronavirus strain.
Micah McClain, MD, PhD, associate professor of Medicine and lead author of a study, said, “Our study demonstrates the potential of this gene expression-based testing approach. We can use the body's natural immune response signals to detect a viral infection with a high degree of accuracy even at a time when people have been exposed to the pathogen but don't yet feel sick.” The study was published on September 24, 2020 in the journal The Lancet Infectious Diseases.
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