Gene/Protein Disease Symptom Drug Enzyme Compound
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Query: UMLS:C0011860 (type 2 diabetes)
 57,723 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

Diminished insulin sensitivity is a characteristic feature of type 2 diabetes. Inhibition of insulin action, resulting in reduced skeletal muscle glucose uptake, is mediated in part through stimulation of RhoA activity. One regulator of RhoA activity is leukemia-associated Rho guanine nucleotide exchange factor (LARG). The LARG gene maps to a region on chromosome 11q23-24 that shows genetic linkage to BMI and type 2 diabetes in Pima Indians. Because of its role in RhoA activation, the LARG gene was analyzed as a positional candidate gene for this linkage. Sequencing of the LARG gene and genotyping of variants identified several polymorphisms that were associated with in vivo rates of insulin-mediated glucose uptake, at both physiological and maximally stimulating insulin concentrations, among 322 nondiabetic Pima Indians who had undergone a hyperinsulinemic-euglycemic clamp. The strongest association with rate of glucose uptake was found with a Tyr1306Cys polymorphism (P < 0.0001, adjusted for age, sex, percent body fat, and nuclear family membership). In transient transfection studies in NIH3T3 cells, the LARG(Cys1306) protein had reduced activity compared with LARG(Tyr1306) protein (P < 0.05). We propose that the Tyr1306Cys substitution in LARG, through its differential activation of RhoA, increases insulin sensitivity in nondiabetic Pima Indians.
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PMID:A functional Tyr1306Cys variant in LARG is associated with increased insulin action in vivo. 1664 11

As weight-loss surgery is an effective treatment for the glycaemic control of type 2 diabetes in obese patients, yet not all patients benefit, it is valuable to find predictive factors for this diabetic remission. This will help elucidating possible mechanistic insights and form the basis for prioritising obese patients with dysregulated diabetes for surgery where diabetes remission is of interest. In this study, we combine both clinical and genomic factors using heuristic methods, informed by prior biological knowledge in order to rank factors that would have a role in predicting diabetes remission, and indeed in identifying patients who may have low likelihood in responding to bariatric surgery for improved glycaemic control. Genetic variants from the Illumina CardioMetaboChip were prioritised through single-association tests and then seeded a larger selection from protein-protein interaction networks. Artificial neural networks allowing nonlinear correlations were trained to discriminate patients with and without surgery-induced diabetes remission, and the importance of each clinical and genetic parameter was evaluated. The approach highlighted insulin treatment, baseline HbA1c levels, use of insulin-sensitising agents and baseline serum insulin levels, as the most informative variables with a decent internal validation performance (74% accuracy, area under the curve (AUC) 0.81). Adding information for the eight top-ranked single nucleotide polymorphisms (SNPs) significantly boosted classification performance to 84% accuracy (AUC 0.92). The eight SNPs mapped to eight genes - ABCA1, ARHGEF12, CTNNBL1, GLI3, PROK2, RYBP, SMUG1 and STXBP5 - three of which are known to have a role in insulin secretion, insulin sensitivity or obesity, but have not been indicated for diabetes remission after bariatric surgery before.
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PMID:Ranking factors involved in diabetes remission after bariatric surgery using machine-learning integrating clinical and genomic biomarkers. 2783 87