2013
DOI: 10.1371/journal.pmed.1001549
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Whole Blood Gene Expression Profiles to Assess Pathogenesis and Disease Severity in Infants with Respiratory Syncytial Virus Infection

Abstract: In this study, Mejias and colleagues found that specific blood RNA profiles of infants with RSV LRTI allowed for specific diagnosis, better understanding of disease pathogenesis, and better assessment of disease severity. Please see later in the article for the Editors' Summary

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Cited by 274 publications
(334 citation statements)
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References 38 publications
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“…Clinically, these data suggest that the inhibitory effect of Siglec‐1 on T cells mainly affects memory T cells during reinfections. Mejias et al also observed an inhibitory effect of RSV on T cells during RSV infections in infants 30. Future research should determine at what time after birth this inhibitory effect takes place, because our data indicate that in certain circumstances Siglec‐1‐dependent inhibition of T cells is not present directly after birth.…”
Section: Discussionsupporting
confidence: 54%
“…Clinically, these data suggest that the inhibitory effect of Siglec‐1 on T cells mainly affects memory T cells during reinfections. Mejias et al also observed an inhibitory effect of RSV on T cells during RSV infections in infants 30. Future research should determine at what time after birth this inhibitory effect takes place, because our data indicate that in certain circumstances Siglec‐1‐dependent inhibition of T cells is not present directly after birth.…”
Section: Discussionsupporting
confidence: 54%
“…The host initiates an innate immune response to virus infection to promote antiviral gene expression, including interferon production (52,53). To dissect the effect of IFN-␤ production and direct detection of viral RNA on NLRC5 expression, we then transfected Vero cells with viral RNA.…”
Section: Rsv Infection Upregulatesmentioning
confidence: 99%
“…A 30-gene classifier developed in this setting separated symptomatically virally infected and uninfected volunteers with 93% accuracy, and it was subsequently validated in a separate cohort of patients, where it classified naturally acquired infections as being either viral or bacterial infections with 80% accuracy (17). Gene expression-based classifiers have also been shown to differentiate between specific viral etiologies, as demonstrated by a 70-gene RSV transcriptional profile that successfully separated infants with RSV lower respiratory tract infection from those with HRV or influenza virus infection with 94% sensitivity and 98% specificity (18). In addition to successfully distinguishing viral and bacterial infections, a gene expression-based classifier of viral infection has also demonstrated the ability to diagnose subjects very early, during the presymptomatic phase, and to allow eventual severity prediction (9).…”
Section: Current Gene Expression-based Disease Classifiersmentioning
confidence: 99%