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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 ∼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.

A parental report questionnaire posted to a population sample of 18-month-old twins correctly assigned zygosity in 95%of cases when validated against zygosity determined by identity of polymorphic DNA markers. The questionnaire was as accurate when readministered at 3 years of age, with 96% of children being assigned the same zygosity on both occasions. The results validate the use of parental report questionnaire data to determine zygosity in infancy.

Previous work suggests that most clinically significant language difficulties in children do not result from acquired brain lesions or adverse environmental experiences but from genetic factors that presumably influence early brain development. We conducted the first twin study of language delay to evaluate whether genetic and environmental factors at the lower extreme of delayed language are different from those operating in the normal range. Vocabulary at age two was assessed for more than 3000 pairs of twins. Group differences heritability for the lowest 5% of subjects was estimated as 73% in model-fitting analyses, significantly greater than the individual differences heritability for the entire sample (25%). This supports the view of early language delay as a distinct disorder. Shared environment was only a quarter as important for the language-delayed sample (18%) as for the entire sample (69%).

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