SMP: Genetic Epidemiological Methods (GEM)

Introduction Large-scale association studies have been proposed as a promising means of identifying pre-disposing genes in common complex diseases. Genome-wide linkage disequilibrium (LD) mapping of common diseases could be more powerful than linkage analysis if the appropriate density of polymorphic markers were known and if the genotyping effort and costs could be reduced. An obvious choice for the analysis of complex diseases are haplotypes, due to their increased informativeness and their potential to condense information on genomic variation. Haplotypes capture information on local LD and on historical recombination and mutation events, thus reflecting the diversity between populations. Haplotypes are also carriers of biological function, both transcriptional and regulatory, which is transmitted as a unit, either from the maternal or the paternal side. Recent research suggests that discrete blocks of low diversity and high LD exist in the human genome. Within such blocks, information on multiple single nucleotide polymorphisms (SNPs) may be redundant; a non-redundant subset of haplotype tagging SNPs (htSNPs) could be identified and used to distinguish the majority of haplotypes and genomic variation. Genotyping efforts could potentially be simplified by determining an optimal set of htSNPs. This can be done by genotyping a dense SNP map in a small sub-sample of the study population and subsequently restricting genotyping to these htSNPs in the full sample. Such an approach would ensure larger study samples and increased study power without the need for increased funding. Thus, to test a direct effect of a candidate gene or to fine-map an unknown gene by exploiting the pattern of LD, haplotype-based association studies in a case-control design with unrelated individuals or family controls may be more informative and cost-effective than single-marker analyses. The aims of this project are 1. to clarify basic questions regarding SNP-based association methods for gene mapping in complex diseases, 2. to incorporate the results in new mapping approaches, and 3. to offer recommendations for the application of haplotype-based methods for gene mapping in complex diseases.