Background: Interventions for T2DM have in part aimed to mimic exercise. Here, we have compared the independent and combined effects of a PPARdelta agonist and endurance training mimetic (GW501516) and a myostatin antibody and resistance training mimetic (PF-879) on metabolic and performance outcomes in obese insulin resistant mice.
Methodology/principal findings: Male ob/ob mice were treated for 6 weeks with vehicle, GW501516, PF-879, or GW501516 in combination with PF-879. The effects of the interventions on body composition, glucose homeostasis, glucose tolerance, energy expenditure, exercise capacity and metabolic gene expression were compared at the end of study. GW501516 attenuated body weight and fat mass accumulation and increased the expression of genes of oxidative metabolism. In contrast, PF-879 increased body weight by driving muscle growth and altered the expression of genes involved in insulin signaling and glucose metabolism. Despite their differences, both interventions alone improved glucose homeostasis. Moreover, GW501516 more effectively improved serum lipids, and PF-879 uniquely increased energy expenditure, exercise capacity and adiponectin levels. When combined the robust effects of GW501516 and/or PF-879 on body weight, adiposity, muscle mass, glycemia, serum lipids, energy expenditure and exercise capacity were highly conserved.
Conclusions/significance: The data, for the first time, demonstrate postnatal inhibition of myostatin not only promotes gains in muscle mass similar to resistance training,but improves metabolic homeostasis. In several instances, these effects were either distinct from or complimentary to those of GW501516. The data further suggest that strategies to increase muscle mass, and not necessarily oxidative capacity, may effectively counter insulin resistance and T2DM.
Postnatal PPARdelta activation and myostatin inhibition exert distinct yet complimentary effects on the metabolic profile of obese insulin-resistant mice
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基因水平:PCR Array、RT-PCR、PCR、单细胞测序
蛋白水平:MSD、Luminex、CBA、Elispot、Antibody Array、ELISA、Sengenics
细胞水平:细胞染色、细胞分选、细胞培养、细胞功能
组织水平:空间多组学、多重荧光免疫组化、免疫组化、免疫荧光
数据分析:流式数据分析、组化数据分析、多因子数据分析
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