BACKGROUND Beige adipose tissue is associated with improved glucose homeostasis in mice. Adipose tissue contains β3-adrenergic receptors (β3-ARs), and this study was intended to determine whether the treatment of obese, insulin-resistant humans with the β3-AR agonist mirabegron, which stimulates beige adipose formation in subcutaneous white adipose tissue (SC WAT), would induce other beneficial changes in fat and muscle and improve metabolic homeostasis.METHODS Before and after β3-AR agonist treatment, oral glucose tolerance tests and euglycemic clamps were performed, and histochemical analysis and gene expression profiling were performed on fat and muscle biopsies. PET-CT scans quantified brown adipose tissue volume and activity, and we conducted in vitro studies with primary cultures of differentiated human adipocytes and muscle.RESULTS The clinical effects of mirabegron treatment included improved oral glucose tolerance (P < 0.01), reduced hemoglobin A1c levels (P = 0.01), and improved insulin sensitivity (P = 0.03) and β cell function (P = 0.01). In SC WAT, mirabegron treatment stimulated lipolysis, reduced fibrotic gene expression, and increased alternatively activated macrophages. Subjects with the most SC WAT beiging showed the greatest improvement in β cell function. In skeletal muscle, mirabegron reduced triglycerides, increased the expression of PPARγ coactivator 1 α (PGC1A) (P < 0.05), and increased type I fibers (P < 0.01). Conditioned media from adipocytes treated with mirabegron stimulated muscle fiber PGC1A expression in vitro (P < 0.001).CONCLUSION Mirabegron treatment substantially improved multiple measures of glucose homeostasis in obese, insulin-resistant humans. Since β cells and skeletal muscle do not express β3-ARs, these data suggest that the beiging of SC WAT by mirabegron reduces adipose tissue dysfunction, which enhances muscle oxidative capacity and improves β cell function.TRIAL REGISTRATION Clinicaltrials.gov NCT02919176.FUNDING NIH: DK112282, P30GM127211, DK 71349, and Clinical and Translational science Awards (CTSA) grant UL1TR001998.
Brian S. Finlin, Hasiyet Memetimin, Beibei Zhu, Amy L. Confides, Hemendra J. Vekaria, Riham H. El Khouli, Zachary R. Johnson, Philip M. Westgate, Jianzhong Chen, Andrew J. Morris, Patrick G. Sullivan, Esther E. Dupont-Versteegden, Philip A. Kern
Usage data is cumulative from January 2020 through March 2020.
Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.
Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.