Dataset Information

Airway gene-expression classifiers for respiratory syncytial virus (RSV) disease severity in infants.

ABSTRACT:

Background

A substantial number of infants infected with RSV develop severe symptoms requiring hospitalization. We currently lack accurate biomarkers that are associated with severe illness.

Method

We defined airway gene expression profiles based on RNA sequencing from nasal brush samples from 106 full-tem previously healthy RSV infected subjects during acute infection (day 1-10 of illness) and convalescence stage (day 28 of illness). All subjects were assigned a clinical illness severity score (GRSS). Using AIC-based model selection, we built a sparse linear correlate of GRSS based on 41 genes (NGSS1). We also built an alternate model based upon 13 genes associated with severe infection acutely but displaying stable expression over time (NGSS2).

Results

NGSS1 is strongly correlated with the disease severity, demonstrating a naïve correlation (?) of ??=?0.935 and cross-validated correlation of 0.813. As a binary classifier (mild versus severe), NGSS1 correctly classifies disease severity in 89.6% of the subjects following cross-validation. NGSS2 has slightly less, but comparable, accuracy with a cross-validated correlation of 0.741 and classification accuracy of 84.0%.

Conclusion

Airway gene expression patterns, obtained following a minimally-invasive procedure, have potential utility for development of clinically useful biomarkers that correlate with disease severity in primary RSV infection.

SUBMITTER: Wang L

PROVIDER: S-EPMC7908785 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature

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Publications

Airway gene-expression classifiers for respiratory syncytial virus (RSV) disease severity in infants.

Wang Lu L Chu Chin-Yi CY McCall Matthew N MN Slaunwhite Christopher C Holden-Wiltse Jeanne J Corbett Anthony A Falsey Ann R AR Topham David J DJ Caserta Mary T MT Mariani Thomas J TJ Walsh Edward E EE Qiu Xing X

BMC medical genomics 20210225 1

<h4>Background</h4>A substantial number of infants infected with RSV develop severe symptoms requiring hospitalization. We currently lack accurate biomarkers that are associated with severe illness.<h4>Method</h4>We defined airway gene expression profiles based on RNA sequencing from nasal brush samples from 106 full-tem previously healthy RSV infected subjects during acute infection (day 1-10 of illness) and convalescence stage (day 28 of illness). All subjects were assigned a clinical illness ...[more]

PMID: 33632195

Similar Datasets

Project description:BACKGROUND:Respiratory syncytial virus (RSV) is the number one cause of lower respiratory tract infections in infants. There are still no vaccines or specific antiviral therapies against RSV, mainly due to the inadequate understanding of RSV pathogenesis. Recent data suggest a role for gut microbiota community structure in determining RSV disease severity. Our objective was to determine the gut microbial profile associated with severe RSV patients, which could be used to help identify at-risk patients and develop therapeutically protective microbial assemblages that may stimulate immuno-protection. RESULTS:We enrolled 95 infants from Le Bonheur during the 2014 to 2016 RSV season. Of these, 37 were well-babies and 58 were hospitalized with RSV. Of the RSV infected babies, 53 remained in the pediatric ward (moderate) and 5 were moved to the pediatric intensive care unit at a later date (severe). Stool samples were collected within 72?h of admission; and the composition of gut microbiota was evaluated via 16S sequencing of fecal DNA. There was a significant enrichment in S24_7, Clostridiales, Odoribacteraceae, Lactobacillaceae, and Actinomyces in RSV (moderate and severe) vs. controls. Patients with severe RSV disease had slightly lower alpha diversity (richness and evenness of the bacterial community) of the gut microbiota compared to patients with moderate RSV and healthy controls. Beta diversity (overall microbial composition) was significantly different between all RSV patients (moderate and severe) compared to controls and had significant microbial composition separating all three groups (control, moderate RSV, and severe RSV). CONCLUSIONS:Collectively, these data demonstrate that a unique gut microbial profile is associated with RSV disease and with severe RSV disease with admission to the pediatric intensive care unit. More mechanistic experiments are needed to determine whether the differences observed in gut microbiota are the cause or consequences of severe RSV disease.

Project description:PurposePRESORS ClinRO completed by clinicians and ObsRO completed by caregivers were developed to characterize the clinical course of respiratory syncytial virus (RSV) infection. This study describes preliminary analysis of PRESORS' measurement properties using clinical trial data.Patients and methodsPRESORS ClinRO and ObsRO data were collected in a 28-day randomized, double-blind, Phase 1b trial of JNJ-53718678 or placebo in infants and children ≤24 months of age treated for RSV infection in hospitals. PRESORS data were scored and key psychometric properties of scores were evaluated, including ability to discriminate between known groups and to detect change over time. Time to resolution of RSV signs was explored using two responder definitions.ResultsDaily completion rates for PRESORS ClinRO and ObsRO were high for the 44 children in the study (median: 100% and 93%, respectively). Large floor effects were observed at baseline for signs of severe RSV infection that were either absent (cyanosis, fever, apnea) or rarely reported (reduced urination/dehydration, vomiting). Implausible ObsRO ratings suggested some caregivers could not accurately measure heart rate. Known-group validity was confirmed: children in poor health based on baseline ClinRO had mean baseline composite scores that were significantly worse for both ObsRO (p=0.001) and ClinRO (p<0.001) compared to those with better overall health. ObsRO (p=0.009) and ClinRO (p<0.001) composite scores were responsive to change in overall health status from baseline to Day 3. Mean scores for RSV sign dimensions decreased rapidly from baseline to Day 7 except for coughing and sleep ratings by caregivers. Time to recovery varied greatly depending on definitions used.ConclusionPRESORS ClinRO and ObsRO can inform endpoints and enable monitoring the clinical course of RSV in pediatric trials. Improved alignment between ClinRO and ObsRO and revisions ensuring caregivers can assess all signs will be addressed in revised PRESORS.

Dataset Information

Airway gene-expression classifiers for respiratory syncytial virus (RSV) disease severity in infants.

Background

Method

Results

Conclusion

Publications

Airway gene-expression classifiers for respiratory syncytial virus (RSV) disease severity in infants.

Similar Datasets

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