# Core D: Cardiometabolic Phenotyping Core

> **NIH NIH P01** · CLEVELAND CLINIC LERNER COM-CWRU · 2021 · $257,600

## Abstract

Cardiometabolic Phenotyping Core (Core D). ABSTRACT:
The overall goal of the Cardiometabolic Disease Phenotyping Core (Core D) is to provide centralized expertise
for performance of state-of-the-art animal model studies relevant to Cardiometabolic Diseases in support of
Projects within this Program. This core is necessary to establish consistency in mouse phenotyping studies
performed across all three Projects, and will ensure seamless data sharing and comparison of how each of the
different gut microbial metabolite pathways under investigation impact cardiometabolic disease in mice. All
projects in this PPG propose to examine the impact of select gut microbe-derived metabolites on host
cardiometbolic disease phenotypes including atherosclerosis, thrombosis, adiposity, insulin/glucose
homeostasis, and altered lipid/bile acid metabolism. Each of these phenotypes requires independent rigorous
methods to be carried out by well-trained investigators in each area. The Cardiometabolic Disease
Phenotyping Core (Core D) will provide technical expertise in a centralized mouse phenotyping service that will
collaboratively interface with all other research projects and cores to examine the effect of altering gut
microbial metabolites on cardiometabolic disease phenotypes.

## Key facts

- **NIH application ID:** 10206253
- **Project number:** 5P01HL147823-03
- **Recipient organization:** CLEVELAND CLINIC LERNER COM-CWRU
- **Principal Investigator:** Jonathan Mark Brown
- **Activity code:** P01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $257,600
- **Award type:** 5
- **Project period:** 2019-09-01 → 2024-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10206253

## Citation

> US National Institutes of Health, RePORTER application 10206253, Core D: Cardiometabolic Phenotyping Core (5P01HL147823-03). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10206253. Licensed CC0.

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