Genetic Linkage and Association of the Growth Hormone Secretagogue Receptor (Ghrelin Receptor) Gene in Human Obesity

There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

Abstract

The growth hormone secretagogue receptor (GHSR) (ghrelin receptor) plays an important role in the regulation of food intake and energy homeostasis. The GHSR gene lies on human chromosome 3q26 within a quantitative trait locus strongly linked to multiple phenotypes related to obesity and the metabolic syndrome. Because the biological function and location of the GHSR gene make it an excellent candidate gene, we tested the relation between common single nucleotide polymorphisms (SNPs) in the GHSR gene and human obesity. We performed a comprehensive analysis of SNPs, linkage disequilibrium (LD), and haplotype structure across the entire GHSR gene region (99.3 kb) in 178 pedigrees with multiple obese members (DNA of 1,095 Caucasians) and in an independent sample of the general population (MONICA Augsburg left ventricular hypertrophy substudy; DNA of 1,418 Caucasians). The LD analysis revealed a disequilibrium block consisting of five SNPs, consistent in both study cohorts. We found linkage among all five SNPs, their haplotypes, and BMI. Further, we found suggestive evidence for transmission disequilibrium for the minor SNP alleles (P < 0.05) and the two most common haplotypes with the obesity affection status ("susceptible" P = 0.025, "nonsusceptible" P = 0.045) in the family cohort using the family-based association test program. Replication of these findings in the general population resulted in stronger evidence for an association of the SNPs (best P = 0.00001) and haplotypes with the disease ("susceptible" P = 0.002, "nonsusceptible" P = 0.002). To our knowledge, these data are the first to demonstrate linkage and association of SNPs and haplotypes within the GHSR gene region and human obesity. This linkage, together with significant transmission disequilibrium in families and replication of this association in an independent population, provides evidence that common SNPs and haplotypes within the GHSR region are involved in the pathogenesis of human obesity.

Related collections

Most cited references 32

Record: found
Abstract: found
Article: not found

Patterns of linkage disequilibrium in the human genome.

Kristin Ardlie, Leonid Kruglyak, Mark Seielstad (2002)

Particular alleles at neighbouring loci tend to be co-inherited. For tightly linked loci, this might lead to associations between alleles in the population a property known as linkage disequilibrium (LD). LD has recently become the focus of intense study in the hope that it might facilitate the mapping of complex disease loci through whole-genome association studies. This approach depends crucially on the patterns of LD in the human genome. In this review, we draw on empirical studies in humans and Drosophila, as well as simulation studies, to assess the current state of knowledge about patterns of LD, and consider the implications for the use of LD as a mapping tool.

0 comments Cited 254 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: not found

A general test of association for quantitative traits in nuclear families.

G Abecasis, L R Cardon, W Cookson (2000)

High-resolution mapping is an important step in the identification of complex disease genes. In outbred populations, linkage disequilibrium is expected to operate over short distances and could provide a powerful fine-mapping tool. Here we build on recently developed methods for linkage-disequilibrium mapping of quantitative traits to construct a general approach that can accommodate nuclear families of any size, with or without parental information. Variance components are used to construct a test that utilizes information from all available offspring but that is not biased in the presence of linkage or familiality. A permutation test is described for situations in which maximum-likelihood estimates of the variance components are biased. Simulation studies are used to investigate power and error rates of this approach and to highlight situations in which violations of multivariate normality assumptions warrant the permutation test. The relationship between power and the level of linkage disequilibrium for this test suggests that the method is well suited to the analysis of dense maps. The relationship between power and family structure is investigated, and these results are applicable to study design in complex disease, especially for late-onset conditions for which parents are usually not available. When parental genotypes are available, power does not depend greatly on the number of offspring in each family. Power decreases when parental genotypes are not available, but the loss in power is negligible when four or more offspring per family are genotyped. Finally, it is shown that, when siblings are available, the total number of genotypes required in order to achieve comparable power is smaller if parents are not genotyped.