Using the twin resource - our scientific program is directed at identifying quantitative trait loci (QTLs) for important biomedical traits relevant to common complex disease including cardiovascular, respiratory and bone diseases. We have been working towards this goal for the past 15 years with substantial success [Spector, 2006 #2; Wilson, 2006 #5; Reneland, 2005 #14; Valdes, 2006 #1; Hammond, 2004 #19]. However, with the completion of the human genome sequence and technological advances in the genotyping, we are now seeking to accelerate this scientific discovery process and shorten timelines for productivity. Our objective in this project is to use individual genotyping and genome-wide association studies (GWAS) in a family-based cohort (twins) with multiple intermediate phenotypes to uncover novel susceptibility genes, explore gene-gene and gene-environment interactions and advance understanding about gene networks which influence disease susceptibility. The current plan will use unique data from the twins in conjunction with other adult population cohorts, which are being genotyped by Sanger (1958BC and Ely Epic study) to provide replication datasets with overlapping phenotypes. We will also compare results with overlapping phenotypes in children to explore age-gene interactions in a study which may be run in parallel (Alspac study).

The specific project aim is to use existing DNA from a sub-cohort of heavily phenotyped 1,000 dizygous (DZ) twins to perform individual genotyping using 250k Illunina Bead Chip Array. We will then conduct a genome-wide association analysis of this data using both total association and family-based statistics to test for associations with extensive existing phenotype and environmental data (i.e. greater than 1000 phenotypes) we have collected over the past 15 years GWAS projects survey common genetic variation by testing a dense set of single nucleotide polymorphisms (SNP) across the genome and we expect this will be an efficient method to uncover novel genes, gene-gene interactions and gene-environment interactions that are relevant to common chronic diseases.