No abstract

We previously identified Nob1 as a quantitative trait locus for high-fat diet-induced obesity and diabetes in genome-wide scans of outcross populations of obese and lean mouse strains. Additional crossbreeding experiments indicated that Nob1 represents an obesity suppressor from the lean Swiss Jim Lambert (SJL) strain. Here we identify a SJL-specific mutation in the Tbc1d1 gene that results in a truncated protein lacking the TBC Rab-GTPase-activating protein domain. TBC1D1, which has been recently linked to human obesity, is related to the insulin signaling protein AS160 and is predominantly expressed in skeletal muscle. Knockdown of TBC1D1 in skeletal muscle cells increased fatty acid uptake and oxidation, whereas overexpression of TBC1D1 had the opposite effect. Recombinant congenic mice lacking TBC1D1 showed reduced body weight, decreased respiratory quotient, increased fatty acid oxidation and reduced glucose uptake in isolated skeletal muscle. Our data strongly suggest that mutation of Tbc1d1 suppresses high-fat diet-induced obesity by increasing lipid use in skeletal muscle.

A family of facilitative glucose transporters (GLUTs) is involved in regulating tissue-specific glucose uptake and metabolism in the liver, skeletal muscle, and adipose tissue to ensure homeostatic control of blood glucose levels. Reduced glucose transport activity results in aberrant use of energy substrates and is associated with insulin resistance and type 2 diabetes. It is well established that GLUT2, the main regulator of hepatic hexose flux, and GLUT4, the workhorse in insulin-and contraction-stimulated glucose uptake in skeletal muscle, are critical contributors in the control of whole-body glycemia. However, the molecular mechanism how insulin controls glucose transport across membranes and its relation to impaired glycemic control in type 2 diabetes remains not sufficiently understood. An array of circulating metabolites and hormone-like molecules and potential supplementary glucose transporters play roles in fine-tuning glucose flux between the different organs in response to an altered energy demand.

OBJECTIVEWe investigated whether metabolic biomarkers and single nucleotide polymorphisms (SNPs) improve diabetes prediction beyond age, anthropometry, and lifestyle risk factors.RESEARCH DESIGN AND METHODSA case-cohort study within a prospective study was designed. We randomly selected a subcohort (n = 2,500) from 26,444 participants, of whom 1,962 were diabetes free at baseline. Of the 801 incident type 2 diabetes cases identified in the cohort during 7 years of follow-up, 579 remained for analyses after exclusions. Prediction models were compared by receiver operatoring characteristic (ROC) curve and integrated discrimination improvement.RESULTSCase-control discrimination by the lifestyle characteristics (ROC-AUC: 0.8465) improved with plasma glucose (ROC-AUC: 0.8672, P < 0.001) and A1C (ROC-AUC: 0.8859, P < 0.001). ROC-AUC further improved with HDL cholesterol, triglycerides, γ-glutamyltransferase, and alanine aminotransferase (0.9000, P = 0.002). Twenty SNPs did not improve discrimination beyond these characteristics (P = 0.69).CONCLUSIONSMetabolic markers, but not genotyping for 20 diabetogenic SNPs, improve discrimination of incident type 2 diabetes beyond lifestyle risk factors.