The relative resistance of children to sepsis mortality: from pathways to drug candidates

Abstract

Attempts to develop drugs that address sepsis based on leads developed in animal models have failed. We sought to identify leads based on human data by exploiting a natural experiment: the relative resistance of children to mortality from severe infections and sepsis. Using public datasets, we identified key differences in pathway activity (Pathprint) in blood transcriptome profiles of septic adults and children. To find drugs that could promote beneficial (child) pathways or inhibit harmful (adult) ones, we built an in silico pathway drug network (PDN) using expression correlation between drug, disease, and pathway gene signatures across 58,475 microarrays. Specific pathway clusters from children or adults were assessed for correlation with drug‐based signatures. Validation by literature curation and by direct testing in an endotoxemia model of murine sepsis of the most correlated drug candidates demonstrated that the Pathprint‐PDN methodology is more effective at generating positive drug leads than gene‐level methods (e.g., CMap). Pathway‐centric Pathprint‐PDN is a powerful new way to identify drug candidates for intervention against sepsis and provides direct insight into pathways that may determine survival.

Learning lessons in sepsis from the children

“…Hence, research breakthroughs yielding new candidate drug targets, by directly analyzing human sepsis patient data, are important but remain rather underexplored. In their recent study, Kobzik and colleagues (Joachim et al , ) describe such a successful endeavor. The innovative aspect of their work is twofold (Fig ).…”

“…The authors righteously consider this relative resistant pre‐puberty population as a sort of “experiment of nature” that the research community could interrogate. Secondly, Joachim et al () employed a pathway‐level approach, rather than a common gene‐level analysis, and processed their patient transcriptomics results with a Pathway Drug Network (PDN). This PDN was newly constructed form drug–gene, disease–gene, drug–disease, and pathway–gene interaction sets, along with the expression data of more than 58,000 human publically available microarrays from the Gene Expression Omnibus (GEO) database.…”

“…The workflow used in the study by Joachim et al () involves two key aspects. First, the authors constructed the PDN , based on the Comparative Toxicogenomics Database ( CTD ), the Pharmacogenomics Knowledgebase (Pharm GKB ), the Connectivity Map ( CM ap), and Pathprint.…”

“… Sepsis research has had relatively limited therapeutic success so far. In their recent study, Kobzik and colleagues (Joachim et al , ) identify novel drug‐sensitive pathways in sepsis, derived exclusively from patient data. Their strategy is based on the analysis of a naturally sepsis‐resistant population (pre‐puberty children) and on the implementation of a novel‐rich Pathway Drug Network, constructed from human gene expression data enriched in drug–pathway–gene clusters. …”

“… Sepsis research has had relatively limited therapeutic success so far. In their recent study, Kobzik and colleagues (Joachim et al , ) use a network approach to identify new drug‐sensitive pathways, taking advantage of the knowledge that children are resistant to sepsis.

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