<HashMap><database>biostudies-other</database><scores/><additional><omics_type>Unknown</omics_type><submitter>Dr Rose, B Joachim</submitter><funding>Jere Mead Fellowship Fund</funding><funding>HHS | National Institutes of Health (NIH)</funding><funding>Joseph D. Brain Fellowship Fund</funding><funding>DOD | Defense Advanced Research Projects Agency (DARPA)</funding><funding>Cure Alzheimer's Fund (CAF)</funding><journal>Molecular Systems Biology</journal><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-SCDT-MSB-17-7998</full_dataset_link><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 </abstract><repository>biostudies-other</repository><funding_grant_id>W911NF-10-1-0217</funding_grant_id><funding_grant_id>5T32HL007118</funding_grant_id><funding_grant_id>ES00002</funding_grant_id><pubmed_authors>Dr John, N Hutchinson</pubmed_authors><pubmed_authors>Dr Lester Kobzik</pubmed_authors><pubmed_authors>Prof Winston Hide</pubmed_authors><pubmed_authors>Gabriel Altschuler</pubmed_authors><pubmed_authors>Dr Rose, B Joachim</pubmed_authors><pubmed_authors>Dr Hector, R Wong</pubmed_authors></additional><is_claimable>false</is_claimable><name>The Relative Resistance of Children to Sepsis Mortality: From Pathways to Drug Candidates</name><description>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 </description><dates><release>2019-03-01T21:00:10Z</release><modification>2019-03-01T21:00:10Z</modification><creation>2019-03-01T21:00:10Z</creation></dates><accession>S-SCDT-MSB-17-7998</accession><cross_references><doi>10.15252/msb.20177998</doi></cross_references></HashMap>