Genome-wide association studies (GWAs) have identifed thousands of loci associated with complex traits, but it is challenging to pinpoint causal genes in these loci and to exploit subtle association signals. We used tissue-specifc quantitative interaction proteomics to map a network of fve genes involved in the mendelian disorder long Qt syndrome (lQts). We integrated the lQts network with GWAs loci from the corresponding common complex trait, Qt-interval variation, to identify candidate genes that were subsequently confrmed in Xenopus laevis oocytes and zebrafsh. We used the lQts protein network to flter weak GWAs signals by identifying single-nucleotide polymorphisms (snPs) in proximity to genes in the network supported by strong proteomic evidence. three snPs passing this flter reached genome-wide signifcance after replication genotyping. overall, we present a general strategy to propose candidates in GWAs loci for functional studies and to systematically flter subtle association signals using tissue-specifc quantitative interaction proteomics.,
Nature Methods
Department of Internal Medicine

Lundby, A., Rossin, E., Steffensen, K., Acha, M. R., Newton-Cheh, C., Pfeufer, A., … Olsen, J. (2014). Annotation of loci from genome-wide association studies using tissue-specifc quantitative interaction proteomics. Nature Methods, 11(8), 868–874. doi:10.1038/nmeth.2997