Host gene expression analysis in the detection of bacterial and viral etiology in children hospitalized with a suspected severe infection - Piri, Ruut; Valta, Milla; Lempainen, Johanna; Ivaska, Lauri; Ezer, Sini; Kere, Juha; Katayama, Shintaro; Peltola, Ville (Springer Nature, 2026)
Background
Host gene expression profiling holds great potential in improving the differential diagnostics of bacterial and viral infections. We investigated its discriminative value in children with suspected serious infections.
Methods
Peripheral blood gene expression profiles were analyzed by RNA sequencing in 268 children aged between 4 weeks and 16 years: 211 hospitalized due to a suspected severe infection, 15 with a confirmed viral respiratory tract infection managed as outpatients, and 42 healthy control children. We classified children according to the bacterial, viral, or other etiology of their final diagnosis, and determined expression profiles. We derived 2-transcript signatures discriminating bacterial infections and viral-bacterial co-infections from viral infections in a discovery group (n = 101) of children with respiratory tract infections and validated them in children (n = 109) with non-respiratory infections, including cases with probable and mixed etiologies in the analyses.
Results
Here, we show that clustering of blood transcriptome cannot be unequivocally explained by the etiology of infection. A 2-transcript signature comprising TSPO and SECISBP2 genes differentiates bacterial and viral-bacterial co-infections from viral infections with an area under the curve of 0.93 and 0.87 (95% confidence interval, 0.88–0.98 and 0.82–0.92) in the discovery and discovery plus validation groups, respectively. Both groups combined, the sensitivity is 77%, and specificity 87%.
Conclusions
The identified 2-transcript signature demonstrates good accuracy in distinguishing between bacterial and viral infections in a complex population of children hospitalized for suspected severe infection. Heterogeneity of clinical manifestations needs to be considered in diagnostic gene expression studies.