Fully-automated, high-throughput micro-computed tomography analysis of body composition enables therapeutic efficacy monitoring in preclinical models.

BACKGROUND: The ability to non-invasively measure body composition in mouse models of obesity and obesity-related disorders is essential for elucidating mechanisms of metabolic regulation and monitoring the effects of novel treatments. These studies aimed to develop a fully automated, high-throughput micro-computed tomography (micro-CT)-based image analysis technique for longitudinal quantitation of adipose, non-adipose and lean tissue as well as bone and demonstrate utility for assessing the effects of two distinct treatments. METHODS: An initial validation study was performed in diet-induced obesity (DIO) and control mice on a vivaCT 75 micro-CT system. Subsequently, four groups of DIO mice were imaged pre- and post-treatment with an experimental agonistic antibody specific for anti-fibroblast growth factor receptor 1 (anti-FGFR1, R1MAb1), control immunoglobulin G antibody, a known anorectic antiobesity drug (rimonabant, SR141716), or solvent control. The body composition analysis technique was then ported to a faster micro-CT system (CT120) to markedly increase throughput as well as to evaluate the use of micro-CT image intensity for hepatic lipid content in DIO and control mice. Ex vivo chemical analysis and colorimetric analysis of the liver triglycerides were performed as the standard metrics for correlation with body composition and hepatic lipid status, respectively. RESULTS: Micro-CT-based body composition measures correlate with ex vivo chemical analysis metrics and enable distinction between DIO and control mice. R1MAb1 and rimonabant have differing effects on body composition as assessed by micro-CT. High-throughput body composition imaging is possible using a modified CT120 system. Micro-CT also provides a non-invasive assessment of hepatic lipid content. CONCLUSIONS: This work describes, validates and demonstrates utility of a fully automated image analysis technique to quantify in vivo micro-CT-derived measures of adipose, non-adipose and lean tissue, as well as bone. These body composition metrics highly correlate with standard ex vivo chemical analysis and enable longitudinal evaluation of body composition and therapeutic efficacy monitoring.

Impaired Akt phosphorylation in insulin-resistant human muscle is accompanied by selective and heterogeneous downstream defects.

AIMS/HYPOTHESIS: Muscle insulin resistance, one of the earliest defects associated with type 2 diabetes, involves changes in the phosphoinositide 3-kinase/Akt network. The relative contribution of obesity vs insulin resistance to perturbations in this pathway is poorly understood. METHODS: We used phosphospecific antibodies against targets in the Akt signalling network to study insulin action in muscle from lean, overweight/obese and type 2 diabetic individuals before and during a hyperinsulinaemic-euglycaemic clamp. RESULTS: Insulin-stimulated Akt phosphorylation at Thr309 and Ser474 was highly correlated with whole-body insulin sensitivity. In contrast, impaired phosphorylation of Akt substrate of 160 kDa (AS160; also known as TBC1D4) was associated with adiposity, but not insulin sensitivity. Neither insulin sensitivity nor obesity was associated with defective insulin-dependent phosphorylation of forkhead box O (FOXO) transcription factor. In view of the resultant basal hyperinsulinaemia, we predicted that this selective response within the Akt pathway might lead to hyperactivation of those processes that were spared. Indeed, the expression of genes targeted by FOXO was downregulated in insulin-resistant individuals. CONCLUSIONS/INTERPRETATION: These results highlight non-linearity in Akt signalling and suggest that: (1) the pathway from Akt to glucose transport is complex; and (2) pathways, particularly FOXO, that are not insulin-resistant, are likely to be hyperactivated in response to hyperinsulinaemia. This facet of Akt signalling may contribute to multiple features of the metabolic syndrome.