# Aging Mitochondrial Fragmentation and Metabolic Inflexibility

> **NIH NIH R01** · UNIVERSITY OF CALIFORNIA BERKELEY · 2022 · $112,350

## Abstract

Summary/Abstract – No Changes from Parent Award
Metabolic flexibility refers to the ability to switch between carbohydrate (CHO) and fat oxidation in
response to changing physiological conditions. A mixed-model design is proposed to interrogate the
hypothesis that the loss of metabolic flexibility in aging is of mitochondrial origin. The design calls for studies on
intact humans, human skeletal muscle (SM) and white adipose tissue (WAT) as well as on rat and mouse SM
and WAT. A segment of the effort on cells and organelles isolated from young and old lab rodents will be
necessary to perform extensive respiratory control studies as well as studies of mitochondrial dynamics and
composition, whereas because of sample size limitations, studies an human mitochondrial preparations will
be involve selective analyses. To test the main hypothesis four cohortsof humans will be studied: sedentary (<
2 hr vigorous PA/wk) and physically active (>5 hr PA/wk) young healthy controls (21-35 yr), older sedentary
and physically active individuals (60-80 yr) of age. Tissues will be harvested from analogous rat populations, 3-
4-month (mo) and 21-23 mo old male and female F344 rats and young (2-3 mo) and old (15 mo) GPR81 null
mice (Aim 4).

## Key facts

- **NIH application ID:** 10548471
- **Project number:** 3R01AG059715-05S1
- **Recipient organization:** UNIVERSITY OF CALIFORNIA BERKELEY
- **Principal Investigator:** GEORGE Austin BROOKS
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $112,350
- **Award type:** 3
- **Project period:** 2018-08-15 → 2024-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10548471

## Citation

> US National Institutes of Health, RePORTER application 10548471, Aging Mitochondrial Fragmentation and Metabolic Inflexibility (3R01AG059715-05S1). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10548471. Licensed CC0.

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