Genetic Variants Associated With Glycine Metabolism and Their Role in Insulin Sensitivity and Type 2 Diabetes

Circulating metabolites associated with insulin sensitivity may represent useful biomarkers, but their causal role in insulin sensitivity and diabetes is less certain. We previously identified novel metabolites correlated with insulin sensitivity measured by the hyperinsulinemic-euglycemic clamp. The top-ranking metabolites were in the glutathione and glycine biosynthesis pathways. We aimed to identify common genetic variants associated with metabolites in these pathways and test their role in insulin sensitivity and type 2 diabetes. With 1,004 nondiabetic individuals from the RISC study, we performed a genome-wide association study (GWAS) of 14 insulin sensitivity-related metabolites and one metabolite ratio. We replicated our results in the Botnia study (n = 342). We assessed the association of these variants with diabetes-related traits in GWAS meta-analyses (GENESIS [including RISC, EUGENE2, and Stanford], MAGIC, and DIAGRAM). We identified four associations with three metabolites-glycine (rs715 at CPS1), serine (rs478093 at PHGDH), and betaine (rs499368 at SLC6A12; rs17823642 at BHMT)-and one association signal with glycine-to-serine ratio (rs1107366 at ALDH1L1). There was no robust evidence for association between these variants and insulin resistance or diabetes. Genetic variants associated with genes in the glycine biosynthesis pathways do not provide consistent evidence for a role of glycine in diabetes-related traits

Analytical design planning technique (ADePT): a dependency structure matrix tool to schedule the building design process

Current planning practice takes little account of the interdisciplinary, iterative nature of the building design process. This leads to a compromised design process containing inevitable cycles of rework together with associated time and cost penalties in both design and construction. The analytical design planning technique (ADePT) is a planning methodology which helps to overcome these difficulties. The central part of ADePT is a dependency structure matrix (DSM). This paper describes DSM techniques and a tool developed to optimize the design process.Adept, Design, Planning, Design Management, Matrix Analysis,

Genetic variants associated with glycine metabolism and their role in insulin sensitivity and type 2 diabetes.

Circulating metabolites associated with insulin sensitivity may represent useful biomarkers, but their causal role in insulin sensitivity and diabetes is less certain. We previously identified novel metabolites correlated with insulin sensitivity measured by the hyperinsulinemic-euglycemic clamp. The top-ranking metabolites were in the glutathione and glycine biosynthesis pathways. We aimed to identify common genetic variants associated with metabolites in these pathways and test their role in insulin sensitivity and type 2 diabetes. With 1,004 nondiabetic individuals from the RISC study, we performed a genome-wide association study (GWAS) of 14 insulin sensitivity-related metabolites and one metabolite ratio. We replicated our results in the Botnia study (n = 342). We assessed the association of these variants with diabetes-related traits in GWAS meta-analyses (GENESIS [including RISC, EUGENE2, and Stanford], MAGIC, and DIAGRAM). We identified four associations with three metabolites-glycine (rs715 at CPS1), serine (rs478093 at PHGDH), and betaine (rs499368 at SLC6A12; rs17823642 at BHMT)-and one association signal with glycine-to-serine ratio (rs1107366 at ALDH1L1). There was no robust evidence for association between these variants and insulin resistance or diabetes. Genetic variants associated with genes in the glycine biosynthesis pathways do not provide consistent evidence for a role of glycine in diabetes-related traits

Common variant in the <em>HMGA2</em> gene increases susceptibility to nephropathy in patients with type 2 diabetes

AIMS/HYPOTHESIS: Type 2 diabetes is a chronic metabolic disorder associated with devastating microvascular complications. Genome-wide association studies have identified more than 60 genetic variants associated with type 2 diabetes and/or glucose and insulin traits, but their role in the progression of diabetes is not established. The aim of this study was to explore whether these variants were also associated with the development of nephropathy in patients with type 2 diabetes. METHODS: We studied 28 genetic variants in 2,229 patients with type 2 diabetes from the local Malmö Scania Diabetes Registry (SDR) published during 2007-2010. Diabetic nephropathy (DN) was defined as micro- or macroalbuminuria and/or end-stage renal disease. Estimated glomerular filtration rate (eGFR) was assessed using the MDRD-4 formula. Replication genotyping of rs1531343 was performed in diabetic (Steno type 2 diabetes [n = 345], Genetics of Diabetes Audit and Research in Tayside Scotland [Go-DARTS] [n = 784]) and non-diabetic (Malmö Preventive Project [n = 2,523], Botnia study [n = 2,247]) cohorts. RESULTS: In the SDR, HMGA2 single-nucleotide polymorphism rs1531343 was associated with DN (OR 1.50, 95% CI 1.20, 1.87, p = 0.00035). In the combined analysis totalling 3,358 patients with type 2 diabetes (n = 1,233 cases, n = 2,125 controls), carriers of the C-allele had a 1.45-fold increased risk of developing nephropathy (95% CI 1.20, 1.75, p = 0.00010). Furthermore, the risk C-allele was associated with lower eGFR in patients with type 2 diabetes (n = 2,499, β ± SEM, -3.7 ± 1.2 ml/min, p = 0.002) and also in non-diabetic individuals (n = 17,602, β ± SEM, -0.008 ± 0.003 ml/min (log( e )), p = 0.006). CONCLUSIONS/INTERPRETATION: These data demonstrate that the HMGA2 variant seems to be associated with increased risk of developing nephropathy in patients with type 2 diabetes and lower eGFR in both diabetic and non-diabetic individuals and could thus be a common denominator in the pathogenesis of type 2 diabetes and kidney complications