There is increasing evidence that genome-wide association (GWA) studies represent a powerful approach to the identification of genes involved in common human diseases. We describe a joint GWA study (using the Affymetrix GeneChip 500K Mapping Array Set) undertaken in the British population, which has examined approximately 2,000 individuals for each of 7 major diseases and a shared set of approximately 3,000 controls. Case-control comparisons identified 24 independent association signals at

We have genotyped 14,436 nonsynonymous SNPs (nsSNPs) and 897 major histocompatibility complex (MHC) tag SNPs from 1,000 independent cases of ankylosing spondylitis (AS), autoimmune thyroid disease (AITD), multiple sclerosis (MS) and breast cancer (BC). Comparing these data against a common control dataset derived from 1,500 randomly selected healthy British individuals, we report initial association and independent replication in a North American sample of two new loci related to ankylosing spondylitis, ARTS1 and IL23R, and confirmation of the previously reported association of AITD with TSHR and FCRL3. These findings, enabled in part by increased statistical power resulting from the expansion of the control reference group to include individuals from the other disease groups, highlight notable new possibilities for autoimmune regulation and suggest that IL23R may be a common susceptibility factor for the major 'seronegative' diseases.

Age-related macular degeneration (AMD) is a leading cause of visual loss in Western populations. Susceptibility is influenced by age, environmental and genetic factors. Known genetic risk loci do not account for all the heritability. We therefore carried out a genome-wide association study of AMD in the UK population with 893 cases of advanced AMD and 2199 controls. This showed an association with the well-established AMD risk loci ARMS2 (age-related maculopathy susceptibility 2)-HTRA1 (HtrA serine peptidase 1) (P =2.7 × 10(-72)), CFH (complement factor H) (P =2.3 × 10(-47)), C2 (complement component 2)-CFB (complement factor B) (P =5.2 × 10(-9)), C3 (complement component 3) (P =2.2 × 10(-3)) and CFI (P =3.6 × 10(-3)) and with more recently reported risk loci at VEGFA (P =1.2 × 10(-3)) and LIPC (hepatic lipase) (P =0.04). Using a replication sample of 1411 advanced AMD cases and 1431 examined controls, we confirmed a novel association between AMD and single-nucleotide polymorphisms on chromosome 6p21.3 at TNXB (tenascin XB)-FKBPL (FK506 binding protein like) [rs12153855/rs9391734; discovery P =4.3 × 10(-7), replication P =3.0 × 10(-4), combined P =1.3 × 10(-9), odds ratio (OR) = 1.4, 95% confidence interval (CI) = 1.3-1.6] and the neighbouring gene NOTCH4 (Notch 4) (rs2071277; discovery P =3.2 × 10(-8), replication P =3.8 × 10(-5), combined P =2.0 × 10(-11), OR = 1.3, 95% CI = 1.2-1.4). These associations remained significant in conditional analyses which included the adjacent C2-CFB locus. TNXB, FKBPL and NOTCH4 are all plausible AMD susceptibility genes, but further research will be needed to identify the causal variants and determine whether any of these genes are involved in the pathogenesis of AMD.

Objective: To provide data classes and methods to facilitate the analysis of whole genome association studies in the R language for statistical computing. Methods: We have implemented data classes in which each genotype call is stored as a single byte. At this density, data for single chromosomes derived from large studies and new high-throughput gene chip platforms can be handled in memory. We use the object-oriented programming model introduced with version 4 of the S-plus package, usually termed ‘S4 methods’. Results: At the current state of development the package only supports population-based studies, although we would hope to provide support for family-based studies soon. Both quantitative and qualitative phenotypes may be analysed. Flexible association testing functions are provided which can carry out single SNP tests which control for potential confounding by quantitative and qualitative covariates. Tests involving several SNPs taken together as ‘tags’ are also supported. Efficient calculation of pair-wise linkage disequilibrium measures is implemented and data input functions include a function which can download data directly from the international HapMap project website.