# Population-Based Characterization of Metabolic Pathways to Predict Pediatric Crohn's Disease Outcomes

> **NIH NIH R01** · UNIVERSITY OF VIRGINIA · 2022 · $718,458

## Abstract

PROJECT SUMMARY/ABSTRACT
Pediatric Crohn's Disease (CD) is a chronic, progressive disease which can have a severe impact on a child's
growth, and development. Children are more likely to develop advanced forms of the disease within years of
diagnosis. Treating pediatric Crohn's cases requires careful consideration as powerful anti-inflammatory
treatments may have adverse effects and may not be necessary depending on severity of disease. Therefore,
risk stratifying pediatric Crohn's populations, and predicting future subtypes, including structural manifestations
of disease and a lack of response to treatments, is an urgent unmet need. While genomic markers of disease
have been studied at length, exploration of the metabolic signature of pediatric Crohn's is less developed. Studies
in recent years have identified metabolic changes which occur during Crohn's, including changes in lipid, amino
acid, tricarboxylic acid and sulfur metabolism. But metabolic shifts have not been studied in enough detail or in
large enough cohorts to become clinical biomarkers, especially for delineating subtypes of disease rather than
Crohn's versus normal tissue. And although metabolic pathways are targetable and there are preliminary findings
that blocking metabolic pathways (i.e., the mevalonate pathway), can be beneficial for Crohn's outcome,
targeting metabolism has not become a widespread phenomenon. In this proposal, we will leverage
computational methods to analyze transcriptomics data from large pediatric CD cohorts and map this data onto
mathematical metabolic reconstructions to assess metabolic shifts. We hypothesize that identification of
unique metabolic shifts in population-based cohorts will inform prediction of Crohn's subtypes, both
structural and treatment-based. In Aim 1, we propose to build a novel computational metabolic network
reconstruction that will be specific to the metabolic functioning of the ileum, a primary site of Crohn's pathology.
This model will serve as a reference for understanding CD metabolic shifts but can also serve as a resource for
other groups studying metabolism shifts in the small bowel. In Aim 2, we will leverage existing data from the
large pediatric CD cohort, to computationally overlay transcriptomics from a range of subtypes onto our metabolic
network reconstruction to assess shifts in metabolism. We will also recruit a prospective cohort of CD patients
from both the University of Virginia and Emory University, collect tissue, perform RNA sequencing, and repeat
our computational metabolic modeling to validate our analysis of archived data. These results will be further
validated by mass spectrometry metabolomics and lipidomics. Finally, in Aim 3, we will profile the transcriptomic
and metabolomic signatures of pediatric Crohn's-patient derived ileal organoids, to test if organoids are a
valuable proxy for studying metabolic shifts in vivo for mechanistic intervention experiments. Together, these
experiments will pave the...

## Key facts

- **NIH application ID:** 10418965
- **Project number:** 1R01DK132369-01
- **Recipient organization:** UNIVERSITY OF VIRGINIA
- **Principal Investigator:** Sana Syed
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $718,458
- **Award type:** 1
- **Project period:** 2022-07-15 → 2027-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10418965

## Citation

> US National Institutes of Health, RePORTER application 10418965, Population-Based Characterization of Metabolic Pathways to Predict Pediatric Crohn's Disease Outcomes (1R01DK132369-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10418965. Licensed CC0.

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