Diagnosis of paediatric infectious diseases and the utility of host immune signatures

Thesis

Background: It can be difficult to distinguish between bacterial and viral infections in children. Current diagnostics lack the sensitivity to confidently rule out serious bacterial infections. The aims of this thesis include discovery of novel host biomarkers to identify bacterial infections, and evaluation of the role of expanded molecular testing in detecting pathogens.

Methods: The data in this thesis come from two prospective cohort studies recruiting children admitted to Patan Hospital, a tertiary-level hospital in the Kathmandu Valley, Nepal. The first cohort study recruited children with lower respiratory tract infections (LRTIs). Whole blood samples from these children were sent for RNA-sequencing and plasma samples were sent for mass spectrometry proteomics and cytokine analysis. The LRTI cases were grouped together based on aetiology; RNA and protein levels were compared between different LRTI groups. Data were divided into training and test datasets; using a partial least squares approach, signatures were identified to differentiate between bacterial and viral LRTIs. The data in the RNA and protein platforms were integrated to identify a multi-platform signature.

The second cohort study recruited children with any signs of infection. Causes of infection were described using routine diagnostics; samples were tested using four additional research molecular panels.

Results: In the LRTI study, samples from 258 LRTI cases were tested. The median age was 2 years and 38% were female. The most common pathogens detected were RSV, influenza and Streptococcus pneumoniae. Using a training subset of cases classified as bacterial, n = 47, or viral, n = 53, a three-gene RNA signature was identified; this signature identified bacterial infections, in the test dataset, with a sensitivity of 89% and a specificity of 100%. Integrating data from the RNA and protein platforms identified a signature with 100% sensitivity and 94% specificity for identifying bacterial LRTIs.

In the second cohort study, 574 cases were enrolled, median age was 3 years and 35% were female, 498 cases had additional molecular testing. Using routine diagnostics only, 28.7% (143/498) of cases were classified as having a confirmed bacterial or viral aetiology. After additional molecular testing, 45.6% (227/498) of cases had a likely pathogen identified. Molecular testing for RSV infection, influenza virus infection, Neisseria meningitidis, enterovirus infection and dengue fever showed potential diagnostic utility.

Conclusions: The signatures identified in this thesis have the potential to improve the identification of serious bacterial infections. A small number of molecular tests which had the potential to alter clinical management were identified.

Authors: O'Reilly, PJ

• DOI: 10.5287/ora-kzrdgm97j
• Type of award: DPhil
• Level of award: Doctoral
• Awarding institution: University of Oxford
• Language: English
• Keywords: host immune; transcriptomics; proteomics; diagnostics; infectious diseases
• Subjects: Diagnostics; Infectious diseases