Background
Precise differential diagnosis between acute viral and bacterial infections is important to enable appropriate therapy, avoid unnecessary antibiotic prescriptions and optimize the use of hospital resources. A systems view of host response to infections provides opportunities for discovering sensitive and robust molecular diagnostics.
Methods
We combine blood transcriptomes from six independent datasets (n = 756) with a knowledge-based human protein-protein interaction network, identifies subnetworks capturing host response to each infection class, and derives common response cores separately for viral and bacterial infections. We subject the subnetworks to a series of computational filters to identify a parsimonious gene panel and a standalone diagnostic score that can be applied to individual samples. We rigorously validate the panel and the diagnostic score in a wide range of publicly available datasets and in a newly developed Bangalore-Viral Bacterial (BL-VB) cohort. Finding: We discover a 10-gene blood-based biomarker panel (Panel-VB) that demonstrates high predictive performance to distinguish viral from bacterial infections, with a weighted mean AUROC of 0.97 (95% CI: 0.96-0.99) in eleven independent datasets (n = 898). We devise a new stand-alone patient-wise score (VB10) based on the panel, which shows high diagnostic accuracy with a weighted mean AUROC of 0.94 (95% CI 0.91-0.98) in 2996 patient samples from 56 public datasets from 19 different countries. Further, we evaluate VB10 in a newly generated South Indian (BL-VB, n = 56) cohort and find 97% accuracy in the confirmed cases of viral and bacterial infections. We find that VB10 is (a) capable of accurately identifying the infection class in culture-negative indeterminate cases, (b) reflects recovery status, and (c) is applicable across different age groups, covering a wide spectrum of acute bacterial and viral infections, including uncharacterized pathogens. We tested our VB10 score on publicly available COVID-19 data and find that our score detected viral infection in patient samples. Interpretation: Our
