# Improving Sepsis Care with Deep RNA Sequencing Data

> **NIH NIH R35** · RHODE ISLAND HOSPITAL · 2024 · $185,656

## Abstract

Project Summary/Abstract:
Sepsis is responsible for one out of every five deaths worldwide. It is therefore essential to better understand
better diagnose and treat sepsis. We propose to use deep RNA sequencing of the whole blood of sepsis
patients to better identify the pathogen causing the disease, triage the appropriate resources, predict
outcomes, and identify novel therapeutic targets. Utilizing novel methods of computational analysis of deep
RNA sequencing data we will assess microbial populations, RNA biology (specifically RNA splicing entropy
and RNA lariats) and identify novel treatment targets/identify patients likely to benefit. Some RNA sequencing
data that does not match the species it came from (human) is typically discarded. We will look at this typically
discarded data for microbial (bacteria and viruses) populations to improve diagnostic ability. To assess the host
response we will study RNA biology. RNA splicing is a basic molecular function that occurs in all cells directly
after RNA transcription, but before protein translation in which introns are removed and exons are joined
together. Over 90% of human genes with multiple exons have alternative splicing events. We hope to assess if
RNA splicing entropy could be a potential biomarker in sepsis. Introns are typically degraded rapidly after
removal during splicing, however, the presence of these lariats could signify RNA metabolism dysfunction and
we will correlate this to outcomes. RNA sequencing data will also allow for application of novel interventions,
such as PD-1 antibodies, to patients most likely to benefit; essentially applying precision medicine to a critically
ill patient. We will utilize whole blood from humans with sepsis and compare to control patients in the intensive
care unit without sepsis. Samples will be collected serially over the course of the stay in the intensive care unit.
We hypothesize that data from deep RNA sequencing obtained during sepsis can be quantified and improve
care. With this equipment supplement the data will be translated to a test that will improve care.

## Key facts

- **NIH application ID:** 11035824
- **Project number:** 3R35GM142638-03S1
- **Recipient organization:** RHODE ISLAND HOSPITAL
- **Principal Investigator:** Sean Farrell Monaghan
- **Activity code:** R35 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $185,656
- **Award type:** 3
- **Project period:** 2021-09-01 → 2026-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/11035824

## Citation

> US National Institutes of Health, RePORTER application 11035824, Improving Sepsis Care with Deep RNA Sequencing Data (3R35GM142638-03S1). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/11035824. Licensed CC0.

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