Host-response Transcriptional Biomarkers Accurately Discriminate Bacterial and Viral Infections of Global Relevance

Abstract

Abstract Limited diagnostics challenge management of acute febrile illness and sepsis (AFI/sepsis) globally. We generated transcriptomes for a 294-participant (USA, Sri Lanka) discovery cohort with AFI/sepsis. We used lasso to derive gene expression classifiers followed by cross-validation and generated: 1) a single model to distinguish bacterial vs. viral (Global Fever-Bacterial/Viral [GF-B/V]) and 2) a two-model system to discriminate bacterial and viral in the context of noninfection (Global Fever-Bacterial/Viral/Non-infectious [GF-B/V/N]). We then translated to a multiplex RT-PCR assay and independent validation involved 101 participants (USA, Sri Lanka, Australia, Cambodia, Tanzania). The sensitivity of the GF-B/V model in the discovery cohort was 84.2% and specificity 94.7%. Validation in an independent cohort showed the GF-B/V model had sensitivity of 78.8% and specificity of 84.3%. Similarly, the discovery cohort performance characteristics for bacterial infection for the GF-B/V/N model were was 87.7% sensitivity and 84.2% specificity, respectively. For viral infection, the sensitivity was 83.7% and specificity 81.5%. In independent validation, the sensitivity and specificity were 82.7% and 80.4%, respectively, for bacterial infection and 76.5% and 80.8%, respectively, for viral infection. Performance did not vary with age, demographics, or site. Host transcriptional response diagnostics distinguish bacterial and viral illness across global sites with different endemic pathogens.