Sepsis endotyping using clinical and biological data

项目摘要/摘要

PROJECT SUMMARY / ABSTRACT More than 2 million Americans are hospitalized with sepsis each year, and account for 1 out of every 2 to 3 hospital deaths. Most efforts to reduce mortality among septic patients begin with the premise that patients are largely similar, and that ether moving treatment earlier or targeting therapeutics to a single mechanism will improve outcomes. Drawing insights from rheumatology and oncology, as well as my sepsis biomarker work during my K23 mentored career development award, we argue that endotypes (biologic subtypes) play an important role in the pathogenesis and outcome of sepsis. When measured early in the sepsis syndrome, these endotypes may identify distinct subgroups comprised of immune response, host tolerance, cellular and tissue damage, and pathogen characteristics. I propose to leverage our clinical translational laboratory to derive and validate novel sepsis endotypes using bioinformatics methods in electronic health record (EHR) data linked to a biorepository of residual blood. This innovative program of research translate findings from “big data” in the EHR and efficiently enrolled biologic specimens into generalizable bio-types for enrichment strategies in future clinical trials and EHR alerts. My program will be supervised by an external advisory board of experts in endotyping, inflammation, and computational and systems biology, while promoting the independence of my clinical-translational laboratory and mentoring of junior scientists.