Epistatic Module Detection for Case-Control Studies: A Bayesian Model with a Gibbs Sampling Strategy

The detection of epistatic interactive effects of multiple genetic variants on the susceptibility of human complex diseases is a great challenge in genome-wide association studies (GWAS). Although methods have been proposed to identify such interactions, the lack of an explicit definition of epistatic effects, together with computational difficulties, makes the development of new methods indispensable. In this paper, we introduce epistatic modules to describe epistatic interactive effects of multiple loci on diseases. On the basis of this notion, we put forward a Bayesian marker partition model to explain observed case-control data, and we develop a Gibbs sampling strategy to facilitate the detection of epistatic modules. Comparisons of the proposed approach with three existing methods on seven simulated disease models demonstrate the superior performance of our approach. When applied to a genome-wide case-control data set for Age-related Macular Degeneration (AMD), the proposed approach successfully identifies two known susceptible loci and suggests that a combination of two other loci—one in the gene SGCD and the other in SCAPER—is associated with the disease. Further functional analysis supports the speculation that the interaction of these two genetic variants may be responsible for the susceptibility of AMD. When applied to a genome-wide case-control data set for Parkinson's disease, the proposed method identifies seven suspicious loci that may contribute independently to the disease

Adrenergic-beta(2) receptor polymorphism and athletic performance

The focus of this review is to evaluate the influence of beta(2)-adrenergic receptor (ADRB2) polymorphism on human physiological function and in turn on athletic performance. A narrative review is conducted on available literature using MedLine, Pubmed and the Cochrane Library to document the location and function of ADRB2 receptors, and specifically to address the influence of genetic polymorphisms on cardiovascular, respiratory, metabolic and musculoskeletal systems and athletic performance. Search terms included ADRB2, endurance and polymorphism. Previous literature exploring the genetic composition of athletes has proposed that alterations in the genetic structure result in an enhancement in their capacity to achieve successful aerobic phenotypes such as a higher VO(2max) and increased fat oxidation. Polymorphism of the Gly16Glu27 haplotype is believed to promote positive aerobic phenotypes and regulate optimal lipolysis. Greater knowledge of the ADRB2 polymorphism can aid in understanding the specific phenotypes that are altered, which may influence performance. Until the interaction between fatigue and athletic performance is better understood, the development of appropriate training principles to enhance genetically polymorphic aerobic phenotypes remains complicated. Following the review, there is still no distinctive evidence for the predictive ability of the polymorphism of ADRB2 genotype for the purpose of identifying potential elite athletes.Vishnu Sarpeshkar and David J Bentle