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1 Department of Biological Sciences, State University of New York at Buffalo, Buffalo, NY 14260, USA
2 Department of Pharmaceutical Sciences, State University of New York at Buffalo, Buffalo, NY 14260, USA
(Requests for offprints should be addressed to R R Almon; Email: almon{at}eng.buffalo.edu)
Elevated systemic levels of glucocorticoids are causally related to peripheral insulin resistance. The pharmacological use of synthetic glucocorticoids (corticosteroids) often results in insulin resistance/type II diabetes. Skeletal muscle is responsible for close to 80% of the insulin-induced systemic disposal of glucose and is a major target for glucocorticoid-induced insulin resistance. We used Affymetrix gene chips to profile the dynamic changes in mRNA expression in rat skeletal muscle in response to a single bolus dose of the synthetic glucocorticoid methyl-prednisolone. Temporal expression profiles (analyzed on individual chips) were obtained from tissues of 48 drug-treated animals encompassing 16 time points over 72 h following drug administration along with four vehicle-treated controls. Data mining identified 653 regulated probe sets out of 8799 present on the chip. Of these 653 probe sets we identified 29, which represented 22 gene transcripts, that were associated with the development of insulin resistance. These 29 probe sets were regulated in three fundamental temporal patterns. 16 probe sets coding for 12 different genes had a profile of enhanced expression. 10 probe sets coding for eight different genes showed decreased expression and three probe sets coding for two genes showed biphasic temporal signatures. These transcripts were grouped into four general functional categories: signal transduction, transcription regulation, carbohydrate/fat metabolism, and regulation of blood flow to the muscle. The results demonstrate the polygenic nature of transcriptional changes associated with insulin resistance that can provide a temporal scaffolding for translational and post-translational data as they become available.
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