The Effect of Technology-Mediated Diabetes Prevention Interventions on Weight: A Meta-Analysis.

BACKGROUND: Lifestyle interventions targeting weight loss, such as those delivered through the Diabetes Prevention Program, reduce the risk of developing type 2 diabetes. Technology-mediated interventions may be an option to help overcome barriers to program delivery, and to disseminate diabetes prevention programs on a larger scale. OBJECTIVE: We conducted a meta-analysis to evaluate the effect of such technology-mediated interventions on weight loss. METHODS: In this meta-analysis, six databases were searched to identify studies reporting weight change that used technology to mediate diet and exercise interventions, and targeted individuals at high risk for developing type 2 diabetes. Studies published between January 1, 2002 and August 4, 2016 were included. RESULTS: The search identified 1196 citations. Of those, 15 studies met the inclusion criteria and evaluated 18 technology-mediated intervention arms delivered to a total of 2774 participants. Study duration ranged from 12 weeks to 2 years. A random-effects meta-analysis showed a pooled weight loss effect of 3.76 kilograms (95% CI 2.8-4.7; P<.001) for the interventions. Several studies also reported improved glycemic control following the intervention. The small sample sizes and heterogeneity of the trials precluded an evaluation of which technology-mediated intervention method was most efficacious. CONCLUSIONS: Technology-mediated diabetes prevention programs can result in clinically significant amounts of weight loss, as well as improvements in glycaemia in patients with prediabetes. Due to their potential for large-scale implementation, these interventions will play an important role in the dissemination of diabetes prevention programs.

Acetylation of TUG protein promotes the accumulation of GLUT4 glucose transporters in an insulin-responsive intracellular compartment.

Insulin causes the exocytic translocation of GLUT4 glucose transporters to stimulate glucose uptake in fat and muscle. Previous results support a model in which TUG traps GLUT4 in intracellular, insulin-responsive vesicles termed GLUT4 storage vesicles (GSVs). Insulin triggers TUG cleavage to release the GSVs; GLUT4 then recycles through endosomes during ongoing insulin exposure. The TUG C terminus binds a GSV anchoring site comprising Golgin-160 and possibly other proteins. Here, we report that the TUG C terminus is acetylated. The TUG C-terminal peptide bound the Golgin-160-associated protein, ACBD3 (acyl-CoA-binding domain-containing 3), and acetylation reduced binding of TUG to ACBD3 but not to Golgin-160. Mutation of the acetylated residues impaired insulin-responsive GLUT4 trafficking in 3T3-L1 adipocytes. ACBD3 overexpression enhanced the translocation of GSV cargos, GLUT4 and insulin-regulated aminopeptidase (IRAP), and ACBD3 was required for intracellular retention of these cargos in unstimulated cells. Sirtuin 2 (SIRT2), a NAD(+)-dependent deacetylase, bound TUG and deacetylated the TUG peptide. SIRT2 overexpression reduced TUG acetylation and redistributed GLUT4 and IRAP to the plasma membrane in 3T3-L1 adipocytes. Mutation of the acetylated residues in TUG abrogated these effects. In mice, SIRT2 deletion increased TUG acetylation and proteolytic processing. During glucose tolerance tests, glucose disposal was enhanced in SIRT2 knock-out mice, compared with wild type controls, without any effect on insulin concentrations. Together, these data support a model in which TUG acetylation modulates its interaction with Golgi matrix proteins and is regulated by SIRT2. Moreover, acetylation of TUG enhances its function to trap GSVs within unstimulated cells and enhances insulin-stimulated glucose uptake.