👤 G A Hitman

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

The autosomal recessive disorder Bardet-Biedl syndrome is characterised by retinal degeneration, polydactyly, obesity, mental retardation, hypogenitalism, renal dysplasia, and short stature. It is heterogeneous with at least four gene loci (BBS1-4) having been mapped to date. We have studied 18 multiply affected families noting the presence of both major and minor manifestations. Using a fluorescently based PCR technique, we genotyped each family member and assigned linkage to one of the four loci. Given this degree of heterogeneity we hoped to find phenotypic differences between linkage categories. We found 44% of families linked to 11q13 (BBS1) and 17% linked to 16q21 (BBS2). Only one family was linked to 15q22 (BBS4) and none to 3p12. We conclude that BBS1 is the major locus among white Bardet-Biedl patients and that BBS3 is extremely rare. Only subtle phenotypic differences were observed, the most striking of which was a finding of taller affected offspring compared with their parents in the BBS1 category. Affected subjects in the BBS2 and 4 groups were significantly shorter than their parents. Twenty eight percent of pedigrees did not show linkage to any known locus, evidence for at least a fifth gene. We conclude that the different genes responsible for Bardet-Biedl syndrome may influence growth characteristics such as height. Show less