Abstract | 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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Authors | Michael A Gillette, D R Mani, Christopher Uschnig, Karell G Pellé, Lola Madrid, Sozinho Acácio, Miguel Lanaspa, Pedro Alonso, Clarissa Valim, Steven A Carr, Stephen F Schaffner, Bronwyn MacInnis, Danny A Milner, Quique Bassat, Dyann F Wirth |
Journal | Clinical infectious diseases : an official publication of the Infectious Diseases Society of America
(Clin Infect Dis)
Vol. 73
Issue 11
Pg. e3939-e3948
(12 06 2021)
ISSN: 1537-6591 [Electronic] United States |
PMID | 33534888
(Publication Type: Journal Article, Research Support, Non-U.S. Gov't)
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Copyright | © The Author(s) 2021. Published by Oxford University Press for the Infectious Diseases Society of America. |
Chemical References |
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Topics |
- Biomarkers
- Child
- Humans
- Malaria
(diagnosis)
- Pneumonia, Bacterial
(diagnosis)
- Pneumonia, Viral
- Virus Diseases
(diagnosis)
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