# Mechanisms of pediatric overweight and obesity underlying susceptibility to multisystem inflammatory syndrome in children (MIS-C)

> **NIH NIH R01** · BOSTON CHILDREN'S HOSPITAL · 2022 · $102,233

## Abstract

PROJECT SUMMARY
The proposed studies for this diversity supplement will provide career development and in-depth training in
translational immunology for a talented candidate with a Master’s degree in Cellular and Molecular Pathobiology.
The parent grant for this application investigates the mechanisms by which pediatric overweight and obesity
increase the risk of Multisystem Inflammatory Syndrome in Children (MIS-C), a severe pediatric complication of
SARS-CoV-2 infection. In leading the proposed studies, the candidate will develop expertise in concepts of
inflammatory signaling and in widely applicable methods used to measure human immune cell activation. From
this work, we anticipate that the candidate will publish at least one first-author paper and a present at the national
Clinical Immunology Society meeting in 2023. Mentorship from two successful physician-scientist investigators,
combined with collaborative interactions with the parent grant study team, will provide highly relevant career
development opportunities towards the candidate’s goal of obtaining an MD/PhD at the interface of immunity
and infectious pathogens.

## Key facts

- **NIH application ID:** 10544668
- **Project number:** 3R01DK130465-02S1
- **Recipient organization:** BOSTON CHILDREN'S HOSPITAL
- **Principal Investigator:** Janet Chou
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $102,233
- **Award type:** 3
- **Project period:** 2021-07-15 → 2024-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10544668

## Citation

> US National Institutes of Health, RePORTER application 10544668, Mechanisms of pediatric overweight and obesity underlying susceptibility to multisystem inflammatory syndrome in children (MIS-C) (3R01DK130465-02S1). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10544668. Licensed CC0.

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