To identify novel coding association signals and facilitate characterization of mechanisms influencing glycemic traits and type 2 diabetes risk, we analyzed 109,215 variants derived from exome array genotyping together with an additional 390,225 variants from exome sequence in up to 39,339 normoglycemic individuals from five ancestry groups. We identified a novel association between the coding variant (p.Pro50Thr) in AKT2 and fasting plasma insulin (FI), a gene in which rare fully penetrant mutations are causal for monogenic glycemic disorders. The low-frequency allele is associated with a 12% increase in FI levels. This variant is present at 1.1% frequency in Finns but virtually absent in individuals from other ancestries. Carriers of the FI-increasing allele had increased 2-h insulin values, decreased insulin sensitivity, and increased risk of type 2 diabetes (odds ratio 1.05). In cellular studies, the AKT2-Thr50 protein exhibited a partial loss of function. We extend the allelic spectrum for coding variants in AKT2 associated with disorders of glucose homeostasis and demonstrate bidirectional effects of variants within the pleckstrin homology domain of AKT2.

Adiponectin is strongly inversely associated with insulin resistance and type 2 diabetes, but its causal role remains controversial. We used a Mendelian randomization approach to test the hypothesis that adiponectin causally influences insulin resistance and type 2 diabetes. We used genetic variants at the ADIPOQ gene as instruments to calculate a regression slope between adiponectin levels and metabolic traits (up to 31,000 individuals) and a combination of instrumental variables and summary statistics-based genetic risk scores to test the associations with gold-standard measures of insulin sensitivity (2,969 individuals) and type 2 diabetes (15,960 case subjects and 64,731 control subjects). In conventional regression analyses, a 1-SD decrease in adiponectin levels was correlated with a 0.31-SD (95% CI 0.26-0.35) increase in fasting insulin, a 0.34-SD (0.30-0.38) decrease in insulin sensitivity, and a type 2 diabetes odds ratio (OR) of 1.75 (1.47-2.13). The instrumental variable analysis revealed no evidence of a causal association between genetically lower circulating adiponectin and higher fasting insulin (0.02 SD; 95% CI -0.07 to 0.11; N = 29,771), nominal evidence of a causal relationship with lower insulin sensitivity (-0.20 SD; 95% CI -0.38 to -0.02; N = 1,860), and no evidence of a relationship with type 2 diabetes (OR 0.94; 95% CI 0.75-1.19; N = 2,777 case subjects and 13,011 control subjects). Using the ADIPOQ summary statistics genetic risk scores, we found no evidence of an association between adiponectin-lowering alleles and insulin sensitivity (effect per weighted adiponectin-lowering allele: -0.03 SD; 95% CI -0.07 to 0.01; N = 2,969) or type 2 diabetes (OR per weighted adiponectin-lowering allele: 0.99; 95% CI 0.95-1.04; 15,960 case subjects vs. 64,731 control subjects). These results do not provide any consistent evidence that interventions aimed at increasing adiponectin levels will improve insulin sensitivity or risk of type 2 diabetes.

Phosphoinositide 3-kinase (PI3K) is a major effector in insulin signaling. rs361072, located in the promoter of the gene (PIK3CB) for the p110beta subunit, has previously been found to be associated with homeostasis model assessment for insulin resistance (HOMA-IR) in obese subjects. The aim was to investigate the influence of rs361072 on in vivo glucose metabolism, skeletal muscle PI3K subunit protein levels, and type 2 diabetes.

Genome-wide association studies and linkage studies have identified 20 validated genetic variants associated with obesity and/or related phenotypes. The variants are common, and they individually exhibit small-to-modest effect sizes.

Patients with established type 2 diabetes display both β-cell dysfunction and insulin resistance. To define fundamental processes leading to the diabetic state, we examined the relationship between type 2 diabetes risk variants at 37 established susceptibility loci, and indices of proinsulin processing, insulin secretion, and insulin sensitivity. We included data from up to 58,614 nondiabetic subjects with basal measures and 17,327 with dynamic measures. We used additive genetic models with adjustment for sex, age, and BMI, followed by fixed-effects, inverse-variance meta-analyses. Cluster analyses grouped risk loci into five major categories based on their relationship to these continuous glycemic phenotypes. The first cluster (PPARG, KLF14, IRS1, GCKR) was characterized by primary effects on insulin sensitivity. The second cluster (MTNR1B, GCK) featured risk alleles associated with reduced insulin secretion and fasting hyperglycemia. ARAP1 constituted a third cluster characterized by defects in insulin processing. A fourth cluster (TCF7L2, SLC30A8, HHEX/IDE, CDKAL1, CDKN2A/2B) was defined by loci influencing insulin processing and secretion without a detectable change in fasting glucose levels. The final group contained 20 risk loci with no clear-cut associations to continuous glycemic traits. By assembling extensive data on continuous glycemic traits, we have exposed the diverse mechanisms whereby type 2 diabetes risk variants impact disease predisposition.

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.

The incretin hormone glucagon-like peptide 1 (GLP-1) promotes glucose homeostasis and enhances β-cell function. GLP-1 receptor agonists (GLP-1 RAs) and dipeptidyl peptidase-4 (DPP-4) inhibitors, which inhibit the physiological inactivation of endogenous GLP-1, are used for the treatment of type 2 diabetes. Using the Metabochip, we identified three novel genetic loci with large effects (30-40%) on GLP-1-stimulated insulin secretion during hyperglycemic clamps in nondiabetic Caucasian individuals (TMEM114; CHST3 and CTRB1/2; n = 232; all P ≤ 8.8 × 10(-7)). rs7202877 near CTRB1/2, a known diabetes risk locus, also associated with an absolute 0.51 ± 0.16% (5.6 ± 1.7 mmol/mol) lower A1C response to DPP-4 inhibitor treatment in G-allele carriers, but there was no effect on GLP-1 RA treatment in type 2 diabetic patients (n = 527). Furthermore, in pancreatic tissue, we show that rs7202877 acts as expression quantitative trait locus for CTRB1 and CTRB2, encoding chymotrypsinogen, and increases fecal chymotrypsin activity in healthy carriers. Chymotrypsin is one of the most abundant digestive enzymes in the gut where it cleaves food proteins into smaller peptide fragments. Our data identify chymotrypsin in the regulation of the incretin pathway, development of diabetes, and response to DPP-4 inhibitor treatment.

We evaluated the impact on diabetes-related intermediary traits of common novel type 2 diabetes-associated variants in the JAZF1 (rs864745), CDC123/CAMK1D (rs12779790), TSPAN8 (rs7961581), THADA (rs7578597), ADAMTS9 (rs4607103), and NOTCH2 (rs10923931) loci, which were recently identified by meta-analysis of genome-wide association data.

The ADAMTS9 rs4607103 C allele is one of the few gene variants proposed to increase the risk of type 2 diabetes through an impairment of insulin sensitivity. We show that the variant is associated with increased expression of the secreted ADAMTS9 and decreased insulin sensitivity and signaling in human skeletal muscle. In line with this, mice lacking Adamts9 selectively in skeletal muscle have improved insulin sensitivity. The molecular link between ADAMTS9 and insulin signaling was characterized further in a model where ADAMTS9 was overexpressed in skeletal muscle. This selective overexpression resulted in decreased insulin signaling presumably mediated through alterations of the integrin β1 signaling pathway and disruption of the intracellular cytoskeletal organization. Furthermore, this led to impaired mitochondrial function in mouse muscle-an observation found to be of translational character because humans carrying the ADAMTS9 risk allele have decreased expression of mitochondrial markers. Finally, we found that the link between ADAMTS9 overexpression and impaired insulin signaling could be due to accumulation of harmful lipid intermediates. Our findings contribute to the understanding of the molecular mechanisms underlying insulin resistance and type 2 diabetes and point to inhibition of ADAMTS9 as a potential novel mode of treating insulin resistance.

Common variants in the melatonin receptor type 1B (MTNR1B) locus have been shown to increase fasting plasma glucose (FPG) and the risk of type 2 diabetes. The aims of this study were to evaluate whether nonsynonymous variants in MTNR1B associate with monogenic forms of hyperglycemia, type 2 diabetes, or related metabolic traits.

Genome-wide association studies (GWAS) have found few common variants that influence fasting measures of insulin sensitivity. We hypothesized that a GWAS of an integrated assessment of fasting and dynamic measures of insulin sensitivity would detect novel common variants. We performed a GWAS of the modified Stumvoll Insulin Sensitivity Index (ISI) within the Meta-Analyses of Glucose and Insulin-Related Traits Consortium. Discovery for genetic association was performed in 16,753 individuals, and replication was attempted for the 23 most significant novel loci in 13,354 independent individuals. Association with ISI was tested in models adjusted for age, sex, and BMI and in a model analyzing the combined influence of the genotype effect adjusted for BMI and the interaction effect between the genotype and BMI on ISI (model 3). In model 3, three variants reached genome-wide significance: rs13422522 (NYAP2; P = 8.87 × 10(-11)), rs12454712 (BCL2; P = 2.7 × 10(-8)), and rs10506418 (FAM19A2; P = 1.9 × 10(-8)). The association at NYAP2 was eliminated by conditioning on the known IRS1 insulin sensitivity locus; the BCL2 and FAM19A2 associations were independent of known cardiometabolic loci. In conclusion, we identified two novel loci and replicated known variants associated with insulin sensitivity. Further studies are needed to clarify the causal variant and function at the BCL2 and FAM19A2 loci.

Understanding the physiological mechanisms by which common variants predispose to type 2 diabetes requires large studies with detailed measures of insulin secretion and sensitivity. Here we performed the largest genome-wide association study of first-phase insulin secretion, as measured by intravenous glucose tolerance tests, using up to 5,567 individuals without diabetes from 10 studies. We aimed to refine the mechanisms of 178 known associations between common variants and glycemic traits and identify new loci. Thirty type 2 diabetes or fasting glucose-raising alleles were associated with a measure of first-phase insulin secretion at P < 0.05 and provided new evidence, or the strongest evidence yet, that insulin secretion, intrinsic to the islet cells, is a key mechanism underlying the associations at the HNF1A, IGF2BP2, KCNQ1, HNF1B, VPS13C/C2CD4A, FAF1, PTPRD, AP3S2, KCNK16, MAEA, LPP, WFS1, and TMPRSS6 loci. The fasting glucose-raising allele near PDX1, a known key insulin transcription factor, was strongly associated with lower first-phase insulin secretion but has no evidence for an effect on type 2 diabetes risk. The diabetes risk allele at TCF7L2 was associated with a stronger effect on peak insulin response than on C-peptide-based insulin secretion rate, suggesting a possible additional role in hepatic insulin clearance or insulin processing. In summary, our study provides further insight into the mechanisms by which common genetic variation influences type 2 diabetes risk and glycemic traits.

Heterozygous mutations in the human preproinsulin (INS) gene are a cause of nonsyndromic neonatal or early-infancy diabetes. Here, we sought to identify INS mutations associated with maturity-onset diabetes of the young (MODY) or nonautoimmune diabetes in mid-adult life, and to explore the molecular mechanisms involved.

Sulfonylureas (SUs) provide an efficacious first-line treatment in patients with hepatocyte nuclear factor 1α (HNF1A) diabetes, but SUs have limitations due to risk of hypoglycemia. Treatment based on the incretin hormones glucose-dependent insulinotropic peptide (GIP) and glucagon-like peptide 1 (GLP-1) is characterized by their glucose-dependent insulinotropic actions without risk of hypoglycemia. The effect of SUs together with GIP or GLP-1, respectively, on insulin and glucagon secretion in patients with HNF1A diabetes is currently unknown. To investigate this, 10 HNF1A mutation carriers and 10 control subjects without diabetes were recruited for a double-blinded, placebo-controlled, crossover study including 6 experimental days in a randomized order involving 2-h euglycemic-hyperglycemic clamps with coadministration of: 1) SU (glimepiride 1 mg) or placebo, combined with 2) infusions of GIP (1.5 pmol/kg/min), GLP-1 (0.5 pmol/kg/min), or saline (NaCl). In HNF1A mutation carriers, we observed: 1) hypoinsulinemia, 2) insulinotropic effects of both GIP and GLP-1, 3) additive to supra-additive effects on insulin secretion when combining SU+GIP and SU+GLP-1, respectively, and 4) increased fasting and arginine-induced glucagon levels compared with control subjects without diabetes. Our study suggests that a combination of SU and incretin-based treatment may be efficacious in patients with HNF1A diabetes via potentiation of glucose-stimulated insulin secretion.

A recent genome-wide association study identified hepatocyte nuclear factor 1-α (HNF1A) as a key regulator of fucosylation. We hypothesized that loss-of-function HNF1A mutations causal for maturity-onset diabetes of the young (MODY) would display altered fucosylation of N-linked glycans on plasma proteins and that glycan biomarkers could improve the efficiency of a diagnosis of HNF1A-MODY. In a pilot comparison of 33 subjects with HNF1A-MODY and 41 subjects with type 2 diabetes, 15 of 29 glycan measurements differed between the two groups. The DG9-glycan index, which is the ratio of fucosylated to nonfucosylated triantennary glycans, provided optimum discrimination in the pilot study and was examined further among additional subjects with HNF1A-MODY (n = 188), glucokinase (GCK)-MODY (n = 118), hepatocyte nuclear factor 4-α (HNF4A)-MODY (n = 40), type 1 diabetes (n = 98), type 2 diabetes (n = 167), and nondiabetic controls (n = 98). The DG9-glycan index was markedly lower in HNF1A-MODY than in controls or other diabetes subtypes, offered good discrimination between HNF1A-MODY and both type 1 and type 2 diabetes (C statistic ≥ 0.90), and enabled us to detect three previously undetected HNF1A mutations in patients with diabetes. In conclusion, glycan profiles are altered substantially in HNF1A-MODY, and the DG9-glycan index has potential clinical value as a diagnostic biomarker of HNF1A dysfunction.

More than 40 genetic risk variants for type 2 diabetes have been validated. We aimed to test whether a genetic risk score associates with the incidence of type 2 diabetes and with 5-year changes in glycemic traits and whether the effects were modulated by changes in BMI and lifestyle. The Inter99 study population was genotyped for 46 variants, and a genetic risk score was constructed. During a median follow-up of 11 years, 327 of 5,850 individuals developed diabetes. Physical examinations and oral glucose tolerance tests were performed at baseline and after 5 years (n = 3,727). The risk of incident type 2 diabetes was increased with a hazard ratio of 1.06 (95% CI 1.03-1.08) per risk allele. While the population in general had improved glucose regulation during the 5-year follow-up period, each additional allele in the genetic risk score was associated with a relative increase in fasting, 30-min, and 120-min plasma glucose values and a relative decrease in measures of β-cell function over the 5-year period, whereas indices of insulin sensitivity were unaffected. The effect of the genetic risk score on 5-year changes in fasting plasma glucose was stronger in individuals who increased their BMI. In conclusion, a genetic risk score based on 46 variants associated strongly with incident type 2 diabetes and 5-year changes in plasma glucose and β-cell function. Individuals who gain weight may be more susceptible to the cumulative impact of type 2 diabetes risk variants on fasting plasma glucose.

Genome-wide association studies have identified several variants within the MTNR1B locus that are associated with fasting plasma glucose (FPG) and type 2 diabetes. We refined the association signal by direct genotyping and examined for associations of the variant displaying the most independent effect on FPG with isolated impaired fasting glycemia (i-IFG), isolated impaired glucose tolerance (i-IGT), type 2 diabetes, and measures of insulin release and peripheral and hepatic insulin sensitivity.

To characterize type 2 diabetes (T2D)-associated variation across the allele frequency spectrum, we conducted a meta-analysis of genome-wide association data from 26,676 T2D case and 132,532 control subjects of European ancestry after imputation using the 1000 Genomes multiethnic reference panel. Promising association signals were followed up in additional data sets (of 14,545 or 7,397 T2D case and 38,994 or 71,604 control subjects). We identified 13 novel T2D-associated loci (P < 5 × 10-8), including variants near the GLP2R, GIP, and HLA-DQA1 genes. Our analysis brought the total number of independent T2D associations to 128 distinct signals at 113 loci. Despite substantially increased sample size and more complete coverage of low-frequency variation, all novel associations were driven by common single nucleotide variants. Credible sets of potentially causal variants were generally larger than those based on imputation with earlier reference panels, consistent with resolution of causal signals to common risk haplotypes. Stratification of T2D-associated loci based on T2D-related quantitative trait associations revealed tissue-specific enrichment of regulatory annotations in pancreatic islet enhancers for loci influencing insulin secretion and in adipocytes, monocytes, and hepatocytes for insulin action-associated loci. These findings highlight the predominant role played by common variants of modest effect and the diversity of biological mechanisms influencing T2D pathophysiology.