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  • Down-regulation of microRNAs in type 2 diabetes implicates non-coding RNA in insulin action

    1Robin A McGregor, 1,2Pernille Keller, 1Iain Gallagher, 2Anders R Nielsen, 2Christian P Fischer, 2Bente K Pedersen and 1James A Timmons

    1School of Life Sciences, Heriot-Watt University, Edinburgh, UK 2Centre of Inflammation & Metabolism, University of Copenhagen, Denmark

    BACKGROUND Skeletal muscle insulin resistance is a hallmark of type 2 diabetes and metabolic syndrome. Microarray profiling has consistently failed to identify differentially expressed gene networks1,2 and this includes our recent analysis (n=124, U133+2 Affymetrix arrays, unpublished observation). The lack of a modified global transcriptome in human type 2 diabetes patients suggests post-transcriptional regulation must play a role in the disease process. MicroRNAs are regulators of mRNA translation. miR-1, miR-133a and miR-206 are muscle specific and regulate muscle development3,4. It is plausible that microRNA modulation could help explain the lack of transcriptional changes in human skeletal muscle insulin resistance. Thus, we proposed that impairment in glucose tolerance is regulated at the post-transcriptional level by alterations in muscle miRNA expression.

    RESULTS

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    CONCLUSION We provide the first evidence for altered miRNA expression in human insulin resistance. There is a robust down-regulation of miR-133a (and miR-206) in skeletal muscle and this was strongly associated with clinical status. Gene ontology analysis of the 186 predicted targets of miR-133a (expressed in skeletal muscle) revealed plausible interactions with genes involved with the insulin signalling pathway and thus the disease process.

    METHODS Human skeletal muscle biopsies (n=30) were taken from 3 groups defined by glucose tolerance: type 2 diabetes (DM2), impaired glucose tolerance (IGT) or normal glucose tolerance (Control). Participants were matched for age, BMI and VO2max. Real-time PCR for the detection of microRNA expression Taqman MicroRNA assay (Applied Biosystems) which detects mature miRNA was used to measure the expression of miR-1, miR-133a, and miR-206. The miRNA expression levels were normalized to RNU48. All reactions were run singleplex and quantified using the Ct method. Data are expressed relative to healthy control subject values and analyzed using ANOVA to compare differences in Ct values between the three groups followed by a post-hoc t-test where appropriate to identify specific group differences. Expression of the miRNAs were plotted against metabolic parameters to identify possible correlations. For all analyses P


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