Abstract

Large-scale association studies, now often consisting of cohorts of over 10,000 individuals, have the potential to aid greatly our understanding of the genetic risks to complex disease associated with classical HLA and other types of variation within the human MHC .

However, genotyping samples at HLA loci using experimental techniques is time-consuming and costly and currently not feasible on such a scale. We have developed techniques for statistical imputation and analysis of classical HLA alleles from SNPs that are typed on standard genotyping platforms.

I will discuss the strengths and weaknesses of imputation-based studies, focusing on recent analyses of autoimmune diseases within the Wellcome Trust Case Control Consortium. In particular I will show how imputation was used to dissect signals of association to multiple sclerosis within the HLA . I will also describe statistical and computational methods that we are developing to enable the use of high throughput sequencing data to characterise genetic variation within and beyond the classical HLA loci.