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Noninvasive Sampling of Mucosal Lining Fluid for the Quantification of In Vivo Upper Airway Immune-mediator Levels
Published on: August 7, 2017
Transcriptomic Biomarkers Associated With Microbiological Etiology and Disease Severity in Childhood Pneumonia
Derek J Williams1, Shruti Gautam2, C Buddy Creech1
1Department of Pediatrics, Vanderbilt University School of Medicine and the Monroe Carell Jr Children's Hospital at Vanderbilt University Medical Center, Nashville, Tennessee.
Background:
Challenges remain in discerning microbiologic etiology and disease severity in childhood pneumonia. Defining host transcriptomic profiles during illness may facilitate improved diagnostic and prognostic approaches.
Methods:
Using whole blood RNA sequencing from 222 hospitalized children with radiographic pneumonia and 45 age-matched controls, we identified differentially expressed (DE) genes that best identified children according to detected microbial pathogens (viral only vs bacterial only and typical vs atypical bacterial [with or without [±] viral co-detection]) and an ordinal measure of phenotypic severity (moderate, severe, very severe).
Results:
Overall, 135 (61%) children had viral-only detections, 15 (7%) had typical bacterial detections (± viral co-detections), and 26 (12%) had atypical bacterial detections (± viral co-detections). Eleven DE genes distinguished between viral-only and bacterial-only detections. Sixteen DE genes distinguished between atypical and typical bacterial detections (± viral co-detections). Nineteen DE genes distinguished between levels of pneumonia severity, including 4 genes also identified in the viral-only versus bacterial-only model (IGHGP, PI3, CD177, RAP1GAP1) and 4 genes from the typical versus atypical bacterial model (PRSS23, IFI27, OLFM4, ABO).
Conclusions:
We identified transcriptomic biomarkers associated with microbial detections and phenotypic severity in children hospitalized with pneumonia. These DE genes are promising candidates for validation and translation into diagnostic and prognostic tools.
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