Biomarkers to Distinguish Bacterial From Viral Pediatric Clinical Pneumonia in a Malaria-Endemic Setting.

Michael AGillette; DRMani; ChristopherUschnig; Karell GPellé; LolaMadrid; SozinhoAcácio; MiguelLanaspa; PedroAlonso; ClarissaValim; Steven ACarr; +5 more... Stephen FSchaffner; BronwynMacInnis; Danny AMilner; QuiqueBassat; Dyann F Wirth ORCID logo; (2021) Biomarkers to Distinguish Bacterial From Viral Pediatric Clinical Pneumonia in a Malaria-Endemic Setting. Clinical infectious diseases : an official publication of the Infectious Diseases Society of America, 73 (11). e3939-e3948. ISSN 1058-4838 DOI: 10.1093/cid/ciaa1843
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BACKGROUND: Differential etiologies of pediatric acute febrile respiratory illness pose challenges for all populations globally, but especially in malaria-endemic settings because the pathogens responsible overlap in clinical presentation and frequently occur together. Rapid identification of bacterial pneumonia with high-quality diagnostic tools would enable appropriate, point-of-care antibiotic treatment. Current diagnostics are insufficient, and the discovery and development of new tools is needed. We report a unique biomarker signature identified in blood samples to accomplish this. METHODS: Blood samples from 195 pediatric Mozambican patients with clinical pneumonia were analyzed with an aptamer-based, high-dynamic-range, quantitative assay (~1200 proteins). We identified new biomarkers using a training set of samples from patients with established bacterial, viral, or malarial pneumonia. Proteins with significantly variable abundance across etiologies (false discovery rate <0.01) formed the basis for predictive diagnostic models derived from machine learning techniques (Random Forest, Elastic Net). Validation on a dedicated test set of samples was performed. RESULTS: Significantly different abundances between bacterial and viral infections (219 proteins) and bacterial infections and mixed (viral and malaria) infections (151 proteins) were found. Predictive models achieved >90% sensitivity and >80% specificity, regardless of number of pathogen classes. Bacterial pneumonia was strongly associated with neutrophil markers-in particular, degranulation including HP, LCN2, LTF, MPO, MMP8, PGLYRP1, RETN, SERPINA1, S100A9, and SLPI. CONCLUSIONS: Blood protein signatures highly associated with neutrophil biology reliably differentiated bacterial pneumonia from other causes. With appropriate technology, these markers could provide the basis for a rapid diagnostic for field-based triage for antibiotic treatment of pediatric pneumonia.



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