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Obesity-induced overexpression of miR-802 impairs glucose metabolism through silencing of Hnf1b
(2013)
The contribution of altered post-transcriptional gene silencing to the development of insulin resistance and type 2 diabetes mellitus so far remains elusive. Here, we demonstrate that expression of microRNA (miR)-143 and 145 is upregulated in the liver of genetic and dietary mouse models of obesity. Induced transgenic overexpression of miR-143, but not miR-145, impairs insulin-stimulated AKT activation and glucose homeostasis. Conversely, mice deficient for the miR-143–145 cluster are protected from the development of obesity-associated insulin resistance. Quantitative-mass-spectrometry-based analysis of hepatic protein expression in miR-143-overexpressing mice revealed miR-143-dependent downregulation of oxysterol-binding-protein-related protein (ORP) 8. Reduced ORP8 expression in cultured liver cells impairs the ability of insulin to induce AKT activation, revealing an ORP8-dependent mechanism of AKT regulation. Our experiments provide direct evidence that dysregulated post-transcriptional gene silencing contributes to the development of obesity-induced insulin resistance, and characterize the miR-143–ORP8 pathway as a potential target for the treatment of obesity-associated diabetes.
Suppose we have k samples X₁,₁,…,X₁,ₙ₁,…,Xₖ,₁,…,Xₖ,ₙₖ with different sample sizes ₙ₁,…,ₙₖ and unknown underlying distribution functions F₁,…,Fₖ as observations plus k families of distribution functions {G₁(⋅,ϑ);ϑ∈Θ},…,{Gₖ(⋅,ϑ);ϑ∈Θ}, each indexed by elements ϑ from the same parameter set Θ, we consider the new goodness-of-fit problem whether or not (F₁,…,Fₖ) belongs to the parametric family {(G₁(⋅,ϑ),…,Gₖ(⋅,ϑ));ϑ∈Θ}. New test statistics are presented and a parametric bootstrap procedure for the approximation of the unknown null distributions is discussed. Under regularity assumptions, it is proved that the approximation works asymptotically, and the limiting distributions of the test statistics in the null hypothesis case are determined. Simulation studies investigate the quality of the new approach for small and moderate sample sizes. Applications to real-data sets illustrate how the idea can be used for verifying model assumptions.
The paper deals with an asymptotic relative efficiency concept for confidence regions of multidimensional parameters that is based on the expected volumes of the confidence regions. Under standard conditions the asymptotic relative efficiencies of confidence regions are seen to be certain powers of the ratio of the limits of the expected volumes. These limits are explicitly derived for confidence regions associated with certain plugin estimators, likelihood ratio tests and Wald tests. Under regularity conditions, the asymptotic relative efficiency of each of these procedures with respect to each one of its competitors is equal to 1. The results are applied to multivariate normal distributions and multinomial distributions in a fairly general setting.