Title

Differential effects of rapamycin on glucose metabolism in 9 inbred strains.

Document Type

Article

Publication Date

7-4-2019

Keywords

JMG

JAX Source

J Gerontol A Biol Sci Med Sci 2019 Jul 4 [Epub ahead of print]

PMID

31276577

DOI

https://doi.org/10.1093/gerona/glz157

Grant

AG022308, Barbara H. Sanford Endowed Scholarship Fund

Abstract

Studies in mice suggest that rapamycin has a negative impact on glucose homeostasis by inducing insulin resistance. However, results have been inconsistent and difficult to assess because the strains, methods of treatment, and analysis vary among studies. Using a consistent protocol, we surveyed 9 inbred strains of mice for the effect of rapamycin on various aspects of glucose metabolism. Across all strains, rapamycin significantly delayed glucose clearance after challenge. However, rapamycin showed no main effect on systemic insulin sensitivity. Analysis of individual strains shows that rapamycin induced higher glucose values at 15 minutes post challenge in 7/9 strains. However, only 3 strains show rapamycin-induced reduction in glucose clearance from 15 to 120 minutes. While pancreatic insulin content was reduced by rapamycin in 7 strains, none showed reduced serum insulin values. While one strain showed no effects of rapamycin on glucose metabolism (129), another showed increased systemic insulin sensitivity (B6). We suggest that rapamycin likely inhibits insulin production/secretion in most strains while having strain-specific effects on glucose clearance without altering systemic insulin sensitivity. This strain survey indicates that genetic differences greatly influence the metabolic response to rapamycin.

Comments

The authors wish to thank Clinton M. Astle for help procuring the diets; Vicki Ingalls, Nelson Durgin, Leonor Robidoux, and Jennifer Davidson for excellent care and maintenance of the mice; Joanne Currer for her help editing the manuscript; Dr. Kevin Flurkey for reviewing the manuscript; Zoë Reifsnyder for graphic design of the figures; Timothy Stearns for statistical analysis using R.

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