Derek J Williams, Shruti Gautam, C Buddy Creech, Natalia Jimenez, Evan J Anderson, Steven Bosinger, Tyler Grimes, Sandra R Arnold, Jonathan A McCullers, Johannes Goll, Kathryn M Edwards, Octavio Ramilo
{"title":"Transcriptomic Biomarkers Associated with Microbiological Etiology and Disease Severity in Childhood Pneumonia","authors":"Derek J Williams, Shruti Gautam, C Buddy Creech, Natalia Jimenez, Evan J Anderson, Steven Bosinger, Tyler Grimes, Sandra R Arnold, Jonathan A McCullers, Johannes Goll, Kathryn M Edwards, Octavio Ramilo","doi":"10.1093/infdis/jiae491","DOIUrl":null,"url":null,"abstract":"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 ribonucleic acid sequencing from 222 hospitalized children with radiographic pneumonia and 45 age-matched controls, we identified differentially expressed genes that best identified children according to detected microbial pathogens (viral-only vs. bacterial-only and typical vs. atypical bacterial [+/- 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 (+/- viral co-detections), and 26 (12%) had atypical bacterial (+/- 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 four genes also identified in the viral-only vs. bacterial-only model (IGHGP, PI3, CD177, RAP1GAP1) and four genes from the typical vs atypical bacterial model (PRSS23, IFI27, OLFM4, and 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.","PeriodicalId":501010,"journal":{"name":"The Journal of Infectious Diseases","volume":"67 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The Journal of Infectious Diseases","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/infdis/jiae491","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
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 ribonucleic acid sequencing from 222 hospitalized children with radiographic pneumonia and 45 age-matched controls, we identified differentially expressed genes that best identified children according to detected microbial pathogens (viral-only vs. bacterial-only and typical vs. atypical bacterial [+/- 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 (+/- viral co-detections), and 26 (12%) had atypical bacterial (+/- 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 four genes also identified in the viral-only vs. bacterial-only model (IGHGP, PI3, CD177, RAP1GAP1) and four genes from the typical vs atypical bacterial model (PRSS23, IFI27, OLFM4, and 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.