# Metabolic Basis of Disease

> **NIH NIH P20** · LSU PENNINGTON BIOMEDICAL RESEARCH CTR · 2022 · $2,159,896

## Abstract

Project Summary:
The overall goal of this new center is to facilitate the growth of young intellectual talent and build the scientific
infrastructure that will promote biomedical research discoveries that will enhance our understanding of the
metabolic aspects of different diseases. Specifically, we have identified four junior faculty with research interests
in different, but complementary aspects of disease research. Each Research Project focuses on the metabolic
aspect of a disease (anxiety/food intake, diabetes, cancer, and preeclampsia). Despite the diversity in tissues
and diseases of interest, each project strongly fits into Pennington Biomedical’s general mission, to discover the
triggers of chronic diseases through innovative research that improves human health across the lifespan.
Within this Metabolic Basis of Disease (MBD) COBRE proposal, we are developing two new scientific cores. The
first is a Preclinical Research Core, which brings together strengths of our current Comparative Biology Core,
Animal Models and Behavior Core, and Transgenics Mouse Core. The second new core is a Molecular
Mechanisms core that will integrate aspects of our Genomic Cores and Cell Biology Bioimaging Core to provide
mentoring and technical support for the Research Project PIs and PBRC faculty.

## Key facts

- **NIH application ID:** 10333350
- **Project number:** 5P20GM135002-03
- **Recipient organization:** LSU PENNINGTON BIOMEDICAL RESEARCH CTR
- **Principal Investigator:** Jacqueline M Stephens
- **Activity code:** P20 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $2,159,896
- **Award type:** 5
- **Project period:** 2020-03-01 → 2025-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10333350

## Citation

> US National Institutes of Health, RePORTER application 10333350, Metabolic Basis of Disease (5P20GM135002-03). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10333350. Licensed CC0.

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