From data to statistical analysis: Explaining genetic heritability by interaction analysis?

Prof Dr Dr Kristel Van Steen

Date and place: Wednesday September, 30th 11:00 am at amphi Jorissen (CHU)

The International HapMap Project was designed to create a genome-wide database of patterns of human genetic variation, with the expectation that these patterns would be useful for genetic association studies of common diseases. This expectation has been amply fulfilled with just the initial output of genome-wide association studies, identifying nearly 100 loci for nearly 40 common diseases and traits (Manolio et al 2008). Despite these successes, it has become clear that usually only a small percentage of total genetic heritability can be explained by the identified loci. For instance for inflammatory bowel disease (IBD), 32 loci significantly impact disease but they explain only 10% of disease risk and 20% of genetic risk (Barrett et al 2008). This may be attributed to the fact that reality shows multiple small associations (in contrast to statistical techniques that can only detect moderate to large associations), dominance or over-dominance, and involves non-SNP polymorphisms, as well as epigenetic effects and gene-gene interactions (Dixon et al 2000). The question remains: What does it take to carry out a genetic interaction analysis?