👤 G Nijpels

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Also published as: Giel Nijpels
articles
Andrew R Wood, Anna Jonsson, Anne U Jackson +49 more · 2017 · Diabetes · added 2026-04-24
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 Show more
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 Show less
no PDF DOI: 10.2337/db16-1452
VPS13C
A Albrechtsen, N Grarup, Y Li +105 more · 2013 · Diabetologia · Springer · added 2026-04-24
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) Show more
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
📄 PDF DOI: 10.1007/s00125-012-2756-1
MACF1