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Genome-wide association studies: Lessons from studying a large clinical cohort

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The Cohorte Lausannoise (CoLaus) is a population-based study of more than 6’000 subjects living in Lausanne, Switzerland. All individuals have been extensively phenotyped with respect to various traits reflecting cardiovascular risk factors, and the large majority has also been genotyped using SNP -arrays. Comparing the country of origin of these individual with the projection of their genotypic profile onto the principal components of the entire genotypic dataset revealed an astonishingly close correspondence between genetic and geographic distances, such that the geographical map of Europe provides an efficient two-dimensional summary of the genetic variation. Genome-wide association studies (GWAS) using CoLaus data have elucidated many loci with highly significant associations to various organismal traits. Yet, it also became apparent that for most complex traits these loci explain only a small fraction of the phenotypic variance, even for highly heritable traits that are known to have a significant genetic component to their variability. I will discuss our research aimed at increasing the predictive power of GWAS , including (a) the identification of other genetic variability like copy number variants from SNP arrays, (b) accessing the contribution of SNP -SNP or SNP -environment interactions, (c) the integration of molecular data like transcriptomics or metabolomics data, and (d) a novel framework for genotype-phenotype associations.

This talk is part of the Seminars on Quantitative Biology @ CRUK Cambridge Institute series.

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