Host transcriptional signatures as predictive markers of infection in children

Abstract

Purpose of review: Analyses of the host transcriptional response to infection has proved to be an alternative diagnostic strategy to standard direct pathogen detection. This review summarizes the value of applying blood and mucosal transcriptome analyses for the diagnosis and management of children with viral and bacterial infections.

Recent findings: Over the years, studies have validated the concept that RNA transcriptional profiles derived from children with infectious diseases carry a pathogen-specific biosignature that can be qualitatively and quantitively measured. These biosignatures can be translated into a biologically meaningful context to improve patient diagnosis, as seen in children with tuberculosis, rhinovirus infections, febrile infants and children with pneumonia; understand disease pathogenesis (i.e. congenital CMV) and objectively classify patients according to clinical severity (i.e. respiratory syncytial virus).

Summary: The global assessment of host RNA transcriptional immune responses has improved our understanding of the host-pathogen interactions in the clinical setting. It has shown the potential to be used in clinical situations wherein our current diagnostic tools are inadequate, guiding the diagnosis and classification of children with infectious diseases.

Figure 1.. Blood transcriptomics as a link between Pathogenesis and clinical findings.

The exposure to external factors including different types of infectious agents, induces the expression of mRNA gene expression patterns in a specific manner. The mRNA over- or underexpression can then be qualitatively and quantitively assessed and correlated with disease severity.

Figure 2.. Host transcriptomics to differentiate viral vs bacterial infections.

An alternative approach to the pathogen-detection strategy is based on a comprehensive analysis of the host response to the infection caused by different pathogens. Each pathogen (viruses vs. bacteria) induces a disease-specific biosignature that can be measured in blood in immune cells using blood RNA transcriptional profiling with high specificity (left panel). RNA biosignatures can be visualized in a heatmap format (middle panel) where each column represents the profiling of a patient and each row of a transcript. Those transcripts can be more activated or over-expressed (red) or suppressed or under-expressed (blue) in relation to the healthy control baseline (yellow). Modular maps (right panel) as disease fingerprints. The spots represent the percentage of significantly over-expressed or under-expressed transcripts within a module (i.e. set of coordinately expressed genes). Blank spots indicate that there are no differences in the genes included in that module between patients and healthy controls.