👤 T Sparsø

Human complex metabolic traits are in part regulated by genetic determinants. Here we applied exome sequencing to identify novel associations of coding polymorphisms at minor allele frequencies (MAFs) >1% with common metabolic phenotypes. The study comprised three stages. We performed medium-depth (8×) whole exome sequencing in 1,000 cases with type 2 diabetes, BMI >27.5 kg/m(2) and hypertension and in 1,000 controls (stage 1). We selected 16,192 polymorphisms nominally associated (p < 0.05) with case-control status, from four selected annotation categories or from loci reported to associate with metabolic traits. These variants were genotyped in 15,989 Danes to search for association with 12 metabolic phenotypes (stage 2). In stage 3, polymorphisms showing potential associations were genotyped in a further 63,896 Europeans. Exome sequencing identified 70,182 polymorphisms with MAF >1%. In stage 2 we identified 51 potential associations with one or more of eight metabolic phenotypes covered by 45 unique polymorphisms. In meta-analyses of stage 2 and stage 3 results, we demonstrated robust associations for coding polymorphisms in CD300LG (fasting HDL-cholesterol: MAF 3.5%, p = 8.5 × 10(-14)), COBLL1 (type 2 diabetes: MAF 12.5%, OR 0.88, p = 1.2 × 10(-11)) and MACF1 (type 2 diabetes: MAF 23.4%, OR 1.10, p = 8.2 × 10(-10)). We applied exome sequencing as a basis for finding genetic determinants of metabolic traits and show the existence of low-frequency and common coding polymorphisms with impact on common metabolic traits. Based on our study, coding polymorphisms with MAF above 1% do not seem to have particularly high effect sizes on the measured metabolic traits. Show less

A genome-wide association study in the Japanese population reported two genome-wide significant loci associated with type 2 diabetes of which the VPS13C/C2CD4A/C2CD4B locus was replicated in Europeans. We looked for potential associations between the diabetogenic VPS13C/C2CD4A/C2CD4B rs7172432 variant and diabetes-related intermediary traits. We genotyped the rs7172432 variant in the population-based Inter99 cohort (n = 6,784) and analysed quantitative diabetes-related traits in 5,722 non-diabetic participants who all were examined by an OGTT. The diabetes-associated A allele was associated with 0.60 cm higher waist circumference (p = 0.004), 0.037 mmol/l higher fasting plasma glucose (p = 4 × 10(-5)) and 0.11 mmol/l higher plasma glucose at 30 min during an OGTT (p = 4 × 10(-4)). In analyses adjusted for concomitant insulin sensitivity levels the diabetogenic allele was associated with a lower acute glucose-stimulated insulin response (GSIR) as estimated by 30 min serum insulin (β = -0.039, p = 2 × 10(-7)), insulinogenic index (β = -0.057, p = 1 × 10(-8)) and BIGTT-acute insulin release (β = -0.041, p = 9 × 10(-9)). As rs7172432 is situated in a region previously associated with glycaemic traits, we tested linkage disequilibrium (LD) with the reported regional lead single-nucleotide polymorphisms for fasting (rs11071657) and 2 h plasma glucose (rs17271305), and performed conditional analyses of rs7172432. Rs7172432 showed moderate LD with rs11071657 and rs17271305 (R (2) < 0.34) and we found strong association by almost unchanged effect sizes of rs7172432 with plasma glucose and estimates of GSIR in analyses conditional on rs11071657 and rs17271305. The diabetogenic VPS13C/C2CD4A/C2CD4B rs7172432 A allele associates with GSIR in non-diabetic individuals from the general population, suggesting an impaired beta cell function as an intermediary diabetes-related trait. Show less

Glucose levels 2 h after an oral glucose challenge are a clinical measure of glucose tolerance used in the diagnosis of type 2 diabetes. We report a meta-analysis of nine genome-wide association studies (n = 15,234 nondiabetic individuals) and a follow-up of 29 independent loci (n = 6,958-30,620). We identify variants at the GIPR locus associated with 2-h glucose level (rs10423928, beta (s.e.m.) = 0.09 (0.01) mmol/l per A allele, P = 2.0 x 10(-15)). The GIPR A-allele carriers also showed decreased insulin secretion (n = 22,492; insulinogenic index, P = 1.0 x 10(-17); ratio of insulin to glucose area under the curve, P = 1.3 x 10(-16)) and diminished incretin effect (n = 804; P = 4.3 x 10(-4)). We also identified variants at ADCY5 (rs2877716, P = 4.2 x 10(-16)), VPS13C (rs17271305, P = 4.1 x 10(-8)), GCKR (rs1260326, P = 7.1 x 10(-11)) and TCF7L2 (rs7903146, P = 4.2 x 10(-10)) associated with 2-h glucose. Of the three newly implicated loci (GIPR, ADCY5 and VPS13C), only ADCY5 was found to be associated with type 2 diabetes in collaborating studies (n = 35,869 cases, 89,798 controls, OR = 1.12, 95% CI 1.09-1.15, P = 4.8 x 10(-18)). Show less

Levels of circulating glucose are tightly regulated. To identify new loci influencing glycemic traits, we performed meta-analyses of 21 genome-wide association studies informative for fasting glucose, fasting insulin and indices of beta-cell function (HOMA-B) and insulin resistance (HOMA-IR) in up to 46,186 nondiabetic participants. Follow-up of 25 loci in up to 76,558 additional subjects identified 16 loci associated with fasting glucose and HOMA-B and two loci associated with fasting insulin and HOMA-IR. These include nine loci newly associated with fasting glucose (in or near ADCY5, MADD, ADRA2A, CRY2, FADS1, GLIS3, SLC2A2, PROX1 and C2CD4B) and one influencing fasting insulin and HOMA-IR (near IGF1). We also demonstrated association of ADCY5, PROX1, GCK, GCKR and DGKB-TMEM195 with type 2 diabetes. Within these loci, likely biological candidate genes influence signal transduction, cell proliferation, development, glucose-sensing and circadian regulation. Our results demonstrate that genetic studies of glycemic traits can identify type 2 diabetes risk loci, as well as loci containing gene variants that are associated with a modest elevation in glucose levels but are not associated with overt diabetes. Show less