Biomarkers to distinguish bacterial from viral pediatric clinical pneumonia in a malaria endemic setting

Abstract

BACKGROUND:Differentiating the etiology of acute febrile respiratory illness in children is a challenge in lowincome, malaria-endemic settings because the main pathogens responsible (viruses, bacteria, and malaria parasites) overlap in clinical presentation and frequently occur together as mixed infections. The critical task is to rapidly identify bacterial pneumonia to enable appropriate antibiotic treatment, ideally at point of care. Current diagnostic tests are insufficient and there is a need for the discovery and development of new tools. Here we report the identification of a unique biomarker signature that can be identified in blood samples. METHODS:Blood samples from 195 pediatric Mozambican patients with clinical pneumonia were analyzed with an aptamer-based high dynamic range assay to quantify ~1200 proteins. For discovery of new biomarkers, we identified a training set of patient samples in which the underlying etiology of the pneumonia was established as bacterial, viral or malaria. Proteins whose abundances varied significantly between patients with verified etiologies (FDR<0.01) formed the basis for predictive diagnostic models that were created using machine learning techniques (Random Forest, Elastic Net). These models were validated on a dedicated test set of samples. RESULTS:219 proteins had significantly different abundances between bacterial and viral infections, and 151 differed between bacterial infections and a mixed pool of viral and malaria infections. Predictive diagnostic models achieved >90% sensitivity and >80% specificity, regardless of whether one or two pathogen classes were present. Bacterial pneumonia was strongly associated with markers of neutrophil activity, in particular neutrophil degranulation. Degranulation markers included HP, LCN2, LTF, MPO, MMP8, PGLYRP1, RETN, SERPINA1, S100A9, and SLPI. CONCLUSION: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.

Novel point-of-care biomarker combination tests to differentiate acute bacterial from viral respiratory tract infections to guide antibiotic prescribing: a systematic review

“…All identified studies were set in a secondary care environment (Table 1, S3). Included age groups were children only, (68)(69)(70)(71)(72)(73)(74) adults only, (75)(76)(77)(78)(79)(80) mixed, (81)(82)(83)(84) or not reported. (85)(86)(87) Three studies focused specifically on upper RTIs, (82,83,87) two on lower RTIs, (78,84) and seven studies included patients with both upper and lower RTIs.…”

“…(85)(86)(87) Three studies focused specifically on upper RTIs, (82,83,87) two on lower RTIs, (78,84) and seven studies included patients with both upper and lower RTIs. (69,71,76,77,80,81,85) The remaining eight studies included patients with pneumonia (community-acquired (70,75,79) or unspecified (68,(72)(73)(74)86) ). Sample sizes ranged from 25 to 657.…”

“…There were six studies with reference standards classified as expert panel, defined as aetiology decided by more-than-one clinician's judgement of patient presentation (S4). (71,78,81,84,86,87) Eight studies had reference standards classified as clinical algorithm, where determination was based upon an algorithm of clinical signs, symptoms or investigations with (82,83) /without (68,72,(74)(75)(76)(77)80) clinician override. Diagnostic microbiological investigation as a reference standard was defined as determination through a targeted-or multiplex-approach microbiological investigation and was used in four studies.…”

“…The remaining nine studies each reported unique combinations of biomarkers (Table 1), all using a nested case-control design (68)(69)(70)(72)(73)(74)(75)(76) bar one with a cohort design. (79) Two studies (68,69) had populations that allowed for comparison between groups of patients with bacterial and viral classification while a third was limited to bacterial accuracy data as mixed bacterial infections were classified as bacterial.…”

“…(76) Four studies identified pathogen-specific infections, allowing comparisons of: pneumococcal and mixed bacterial-viral against viral, (75) pneumococcal and mixed pneumococcalviral against viral, (70) bacterial and mixed bacterial-H1N1 against H1N1 (79) and Mycoplasma pneumonia (73) against respiratory syncytial virus. The remaining studies incorporated a malarial group to distinguish bacterial and viral aetiology from, (72,74) with one also adding a healthy control group. (74) J o u r n a l P r e -p r o o f…”