# Sepsis endotyping using clinical and biological data

> **NIH NIH R35** · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · 2020 · $391,128

## Abstract

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.

## Key facts

- **NIH application ID:** 9944620
- **Project number:** 5R35GM119519-05
- **Recipient organization:** UNIVERSITY OF PITTSBURGH AT PITTSBURGH
- **Principal Investigator:** Christopher Warren Seymour
- **Activity code:** R35 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $391,128
- **Award type:** 5
- **Project period:** 2016-08-02 → 2021-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9944620

## Citation

> US National Institutes of Health, RePORTER application 9944620, Sepsis endotyping using clinical and biological data (5R35GM119519-05). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9944620. Licensed CC0.

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