Suchergebnisse

AbstractFine mapping of linkage peaks is one of the great challenges facing researchers who try to identify genes and genetic variants responsible for the variation in a certain trait or complex disease. Once the trait is linked to a certain chromosomal region, most studies use a candidate gene approach followed by a selection of polymorphisms within these genes, either based on their possibility to be functional, or based on the linkage disequilibrium between adjacent markers. For both candidate gene selection and SNP selection, several approaches have been described, and different software tools are available. However, mastering all these information sources and choosing between the different approaches can be difficult and time-consuming. Therefore, this article lists several of these in silico procedures, and the authors describe an empirical two-step fine mapping approach, in which candidate genes are prioritized using a bioinformatics approach (ENDEAVOUR), and the top genes are chosen for further SNP selection with a linkage disequilibrium based method (Tagger). The authors present the different actions that were applied within this approach on two previously identified linkage regions for muscle strength. This resulted in the selection of 331 polymorphisms located in 112 different candidate genes out of an initial set of 23,300 SNPs.

AbstractInsulin resistance and obesity are underlying causes of type 2 diabetes and therefore much interest is focused on the potential genes involved. A series of anthropometric and metabolic characteristic were measured in 240 MZ and 112 DZ twin pairs recruited from the East Flanders Prospective Twin Survey. Microsatellite markers located close to ABCC8, ADIPOQ, GCK, IGF1, IGFBP1, INSR, LEP, LEPR, PPARγ and the RETN gene were genotyped. Univariate single point variance components linkage analyses were performed using two methods: (1) the standard method, only comprising the phenotypic and genotypic data of the DZ twin pairs and (2) the extended method, also incorporating the phenotypic data of the MZ twin pairs. Suggestive linkages (LOD > 1) were observed between the ABCC8 marker and waist-to-hip ratio and HDL-cholesterol levels. Both markers flanking ADIPOQ showed suggestive linkage with triglycerides levels, the upstream marker also with body mass and HDL-cholesterol levels. The IGFBP1 marker showed suggestive linkage with fat mass, fasting insulin and leptin levels and the LEP marker showed suggestive linkage with birth weight. This study suggests that DNA variants in ABCC8, ADIPOQ, IGFBP1 and LEP gene region may predispose to type 2 diabetes. In addition, the two methods used to perform linkage analyses yielded similar results. This was however not the case for birth weight where chorionicity seems to be an important confounder.