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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.

Decreased insulin sensitivity, also referred to as insulin resistance (IR), is a fundamental abnormality in patients with type 2 diabetes and a risk factor for cardiovascular disease. While IR predisposition is heritable, the genetic basis remains largely unknown. The GENEticS of Insulin Sensitivity consortium conducted a genome-wide association study (GWAS) for direct measures of insulin sensitivity, such as euglycemic clamp or insulin suppression test, in 2,764 European individuals, with replication in an additional 2,860 individuals. The presence of a nonsynonymous variant of N-acetyltransferase 2 (NAT2) [rs1208 (803A>G, K268R)] was strongly associated with decreased insulin sensitivity that was independent of BMI. The rs1208 "A" allele was nominally associated with IR-related traits, including increased fasting glucose, hemoglobin A1C, total and LDL cholesterol, triglycerides, and coronary artery disease. NAT2 acetylates arylamine and hydrazine drugs and carcinogens, but predicted acetylator NAT2 phenotypes were not associated with insulin sensitivity. In a murine adipocyte cell line, silencing of NAT2 ortholog Nat1 decreased insulin-mediated glucose uptake, increased basal and isoproterenol-stimulated lipolysis, and decreased adipocyte differentiation, while Nat1 overexpression produced opposite effects. Nat1-deficient mice had elevations in fasting blood glucose, insulin, and triglycerides and decreased insulin sensitivity, as measured by glucose and insulin tolerance tests, with intermediate effects in Nat1 heterozygote mice. Our results support a role for NAT2 in insulin sensitivity.

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.

OBJECTIVE-- Type 2 diabetes is characterized by impaired pancreatic β-cell function and decreased insulin sensitivity. Genome-wide association studies have identified common, novel type 2 diabetes susceptibility loci within the FTO, CDKAL1, CDKN2A/CDKN2B, IGF2BP2, HHEX/IDE, and SLC30A8 gene regions. Our objective was to explore the relationships between the diabetes-associated alleles and measures of β-cell function and whole-body insulin sensitivity. RESEARCH DESIGN AND METHODS-- A total of 1,276 healthy subjects of European ancestry were studied at 19 centers. Indexes of β-cell function (including 30-min insulin response and glucose sensitivity) were derived from a 75-g oral glucose tolerance test, and whole-body insulin sensitivity (M/I) was assessed by hyperinsulinemic-euglycemic clamp. Genotype/ phenotype relationships were studied by linear trend analysis correcting for age, sex, and recruitment center. RESULTS-- CDKAL1 and HHEX/IDE diabetes-associated alleles were both associated with decreased 30-min insulin response (both P = 0.0002) and decreased pancreatic β-cell glucose sensitivity (P = 9.86 x 10 -5 and 0.009, respectively), and these relationships remained after correction for M/I. The FTO susceptibility allele showed a weak but consistent association with increased adiposity, which in turn was linked to a decrease in M/I. However, none of the other novel diabetes susceptibility alleles were associated with insulin sensitivity. CONCLUSIONS-- CDKAL1 and HHEX/IDE diabetes-associated alleles are associated with decreased pancreatic β-cell function, including decreased β-cell glucose sensitivity that relates insulin secretion to plasma glucose concentration. We confirmed the association between the FTO allele and increased adiposity, but none of the other novel susceptibility alleles were associated with whole-body insulin sensitivity. Diabetes 56: 3101-3104, 2007 [ABSTRACT FROM AUTHOR]

Mutations in the LMNA gene (encoding lamin A/C) underlie familial partial lipodystrophy, a syndrome of monogenic insulin resistance and diabetes. LMNA maps to the well-replicated diabetes-linkage region on chromosome 1q, and there are reported associations between LMNA single nucleotide polymorphisms (SNPs) (particularly rs4641; H566H) and metabolic syndrome components. We examined the relationship between LMNA variation and type 2 diabetes (using six tag SNPs capturing >90% of common variation) in several large datasets. Analysis of 2,490 U.K. diabetic case and 2,556 control subjects revealed no significant associations at either genotype or haplotype level: the minor allele at rs4641 was no more frequent in case subjects (allelic odds ratio [OR] 1.07 [95% CI 0.98-1.17], P = 0.15). In 390 U.K. trios, family-based association analyses revealed nominally significant overtransmission of the major allele at rs12063564 (P = 0.01), which was not corroborated in other samples. Finally, genotypes for 2,817 additional subjects from the International 1q Consortium revealed no consistent case-control or family-based associations with LMNA variants. Across all our data, the OR for the rs4641 minor allele approached but did not attain significance (1.07 [0.99-1.15], P = 0.08). Our data do not therefore support a major effect of LMNA variation on diabetes risk. However, in a meta-analysis including other available data, there is evidence that rs4641 has a modest effect on diabetes susceptibility (1.10 [1.04-1.16], P = 0.001). Diabetes 56:879-883, 2007 [ABSTRACT FROM AUTHOR]

The BAIR consortium has been formed to provide insight into the biological processes underlying insulin resistance through multidisciplinary research combining various genomic/proteomic/metabolomic approaches in animal models, followed by haman genetic analysis. Based on previously described associations, function and on BAIR biological data, we selected 11 candidate genes (ARNT; RBP4; HIF1a; EIF2S1; AKT1; ONECUT1; RPS6KB1; TRB3; FOXA2; PCK1; FOXO3A) for investigation. Pairwise tags (r²>0.8) spanning these genes were selected based on HapMap phase II CEU data to exhaustively capture common variation (MAF>0.05). 103 SNPs were genotyped in 5,602 samples (935 UKT2D, 1927 UK-controls, 926 French T2D, 934 French obese and 880 French controls) by iPLEX & SNPlex methods. Single-point analyses on 92 SNPs were carried out after stringent quality control. Coverage of common variation remained high (74%-100% per gene). There was no significant association with T2D or obesity (at the p=0.01 level) in 9 of the strong candidate genes examined. In the UK population, rs11908628 of PCK1 (encoding phosphoenolpyruvate carboxykinase 1, the main control point for the regulation of gluconeogenesis) was found to be protective against diabetes (MAFs 2.7% v 4.3%, OR(95%CIs): 0.62 (0.44-0.86); p=0.003 additive). Mantel-Haenszel meta-analysis of rs11908628 across the UK and French T2D samples provided additional support for this finding (p=0.002), although further investigation, given low MAFs, is warranted. When comparing genotypes between T2D cases and controls in the French population, 2 independent associations were seen in RPS6KB1: rs180535 (MAFs 18% v 15%; OR 1.29 (1.07 -1.55); p=0.006) and rs180531 (24% v 28%; OR 0.81 (0.69-0.95) p=0.008) (r²=0.06 in controls). RPS6KB1 codes for ribosomal protein S6 kinase 70KD 1, which negatively regulates insulin signalling. Interestingly, rs180531 (23% v 28%; OR 0.80 (0.69-0.94) p=0.005) was also associated with protection against obesity in the French. In conclusion, our genetic data suggest modest effects of the BAIR insulin resistance candidates PEPCK and S6K1 gene variation in UK (T2D) and French (T2D and obese) samples, results that require replication in additional populations. [ABSTRACT FROM AUTHOR]