Concept, design and implementation of a cardiovascular gene-centric 50 k SNP array for large-scale genomic association studies.

A wealth of genetic associations for cardiovascular and metabolic phenotypes in humans has been accumulating over the last decade, in particular a large number of loci derived from recent genome wide association studies (GWAS). True complex disease-associated loci often exert modest effects, so their delineation currently requires integration of diverse phenotypic data from large studies to ensure robust meta-analyses. We have designed a gene-centric 50 K single nucleotide polymorphism (SNP) array to assess potentially relevant loci across a range of cardiovascular, metabolic and inflammatory syndromes. The array utilizes a "cosmopolitan" tagging approach to capture the genetic diversity across approximately 2,000 loci in populations represented in the HapMap and SeattleSNPs projects. The array content is informed by GWAS of vascular and inflammatory disease, expression quantitative trait loci implicated in atherosclerosis, pathway based approaches and comprehensive literature searching. The custom flexibility of the array platform facilitated interrogation of loci at differing stringencies, according to a gene prioritization strategy that allows saturation of high priority loci with a greater density of markers than the existing GWAS tools, particularly in African HapMap samples. We also demonstrate that the IBC array can be used to complement GWAS, increasing coverage in high priority CVD-related loci across all major HapMap populations. DNA from over 200,000 extensively phenotyped individuals will be genotyped with this array with a significant portion of the generated data being released into the academic domain facilitating in silico replication attempts, analyses of rare variants and cross-cohort meta-analyses in diverse populations. These datasets will also facilitate more robust secondary analyses, such as explorations with alternative genetic models, epistasis and gene-environment interactions.

Genetic variability and the hypothalamic control of energy balance

Background. Obesity is a major health problem throughout the industrialized world. Despite numerous attempts to curtail the rapid growth of obesity, its incidence continues to rise. Therefore, it is crucial to better understand the etiology of obesity beyond the concept of energy balance.^ Aims. The first aim of this study was to first investigate the relationship between eating behaviors and body size. The second goal was to identify genetic variation associated with eating behaviors. Thirdly, this study aimed to examine the joint relationships between eating behavior, body size and genetic variation.^ Methods. This study utilized baseline data ascertained in young adults from the Training Interventions and Genetics of Exercise (TIGER) Study. Variables assessed included eating behavior (Emotional Eating Scale, Eating Attitudes Test-26, and the Block98 Food Frequency Questionnaire), body size (body mass index, waist and hip circumference, waist/hip ratio, and percent body fat), genetic variation in genes implicated related to the hypothalamic control of energy balance, and appropriate covariates (age, gender, race/ethnicity, smoking status, and physical activity. For the genetic association analyses, genotypes were collapsed by minor allele frequency, and haplotypes were estimated for each gene. Additionally, Bayesian networks were constructed in order to determine the relationships between genetic variation, eating behavior and body size.^ Results. We report that the EAT-26 score, Caloric intake, percent fat, fiber intake, HEAT index, and daily servings of vegetables, meats, grains, and fats were significantly associated with at least one body size measure. Multiple SNPs in 17 genes and haplotypes from 12 genes were tested for their association with body size. Variation within both DRD4 and HTR2A was found to be associated with EAT-26 score. In addition, variation in the ghrelin gene (GHRL) was significantly associated with daily Caloric intake. A significant interaction between daily servings of grains and the HEAT index and variation within the leptin receptor gene (LEPR) was shown to influence body size.^ Conclusion. This study has shown that there is a substantial genetic component to eating behavior and that genetic variation interacts with eating behavior to influence body size.^