# FGF21, Insulin Action and Longevity

> **NIH NIH P01** · YALE UNIVERSITY · 2020 · $335,327

## Abstract

Project Summary
Inhibiting the growth hormone (GH)-insulin-like growth factor-1 (IGF-1) signaling
pathway by dietary or genetic manipulation extends lifespan in a range of species,
including possibly humans. However, achieving this effect pharmacologically has
proven difficult. FGF21 is a hormone that is released from the liver in response to
fasting and elicits diverse aspects of the adaptive starvation response. Among its
metabolic actions in mice, FGF21 causes GH resistance and consequently a marked
reduction in circulating IGF-1 concentrations. Remarkably, transgenic mice
overexpressing FGF21 from birth live 30-40% longer than wild-type mice. In the
studies proposed in this application, we will test whether FGF21 causes a
corresponding increase in the healthspan of mice as assessed by measuring
strength, immune system and cognitive function. We will further determine whether
initiating exposure to FGF21 in adulthood also extends lifespan and healthspan.
Lastly, we will test whether FGF21 suppresses the GH-IGF-1 pathway by inducing
suppressor of cytokine signaling protein 2, which has well established anti-GH
effects. Since several pharmaceutical companies already have FGF21 in clinical
trials for treating obesity and type 2 diabetes, FGF21 administration may be a viable
approach for extending healthspan and lifespan in humans.

## Key facts

- **NIH application ID:** 9938382
- **Project number:** 5P01AG051459-05
- **Recipient organization:** YALE UNIVERSITY
- **Principal Investigator:** Steven Kliewer
- **Activity code:** P01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $335,327
- **Award type:** 5
- **Project period:** — → 2022-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9938382

## Citation

> US National Institutes of Health, RePORTER application 9938382, FGF21, Insulin Action and Longevity (5P01AG051459-05). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/9938382. Licensed CC0.

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