# Age remodels kidney-adrenal-heart interorgan communication

> **NIH NIH U01** · BROWN UNIVERSITY · 2024 · $642,841

## Abstract

Project Summary/Abstract
Cardiorenal syndrome is an age-associated pathology where the dysfunction of the heart or kidney induces
excess extracellular matrix in the other organ. We propose, and our data supports, that age-associated
dysregulation between interorgan signaling promotes cardiorenal syndrome. Comorbidity, heterogeneity and
gender differences may be better managed by understanding how age affects kidney-adrenal-heart
communication and by what mechanisms these tissues induce fibrosis. This project will transplant adrenal and
kidney tissue between young and aged mice to determine how altered interorgan communication drives aging-
associated cardiac dysfunction. We will study the interaction of age-associated water-loss and interorgan
communication to determine how this impacts cardiorenal aging. Because we find that mammalian renal steroid
hormones can induce heart fibrosis in Drosophila by acting through a novel membrane receptor, we will
determine how this receptor signals to induce fibrosis and identify the corresponding receptor in mammalian
tissues. Overall, this proposal aims to understand how aging impacts interorgan communication to produce age-
associated cardiorenal syndrome and fibrosis, using models of Drosophila and mice.

## Key facts

- **NIH application ID:** 10852372
- **Project number:** 1U01AG086161-01
- **Recipient organization:** BROWN UNIVERSITY
- **Principal Investigator:** Rujun Gong
- **Activity code:** U01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $642,841
- **Award type:** 1
- **Project period:** 2024-05-15 → 2029-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10852372

## Citation

> US National Institutes of Health, RePORTER application 10852372, Age remodels kidney-adrenal-heart interorgan communication (1U01AG086161-01). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10852372. Licensed CC0.

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