RT Journal Article SR Electronic T1 Common genetic variants and health outcomes appear geographically structured in the UK Biobank sample: Old concerns returning and their implications JF bioRxiv FD Cold Spring Harbor Laboratory SP 294876 DO 10.1101/294876 A1 Simon Haworth A1 Ruth Mitchell A1 Laura Corbin A1 Kaitlin H Wade A1 Tom Dudding A1 Ashley Budu-Aggrey A1 David Carslake A1 Gibran Hemani A1 Lavinia Paternoster A1 George Davey Smith A1 Neil Davies A1 Dan Lawson A1 Nicholas Timpson YR 2018 UL http://biorxiv.org/content/early/2018/04/11/294876.abstract AB The inclusion of genetic data in large studies has enabled the discovery of genetic contributions to complex traits and their application in applied analyses including those using genetic risk scores (GRS) for the prediction of phenotypic variance. If genotypes show structure by location and coincident structure exists for the trait of interest, analyses can be biased. Having illustrated structure in an apparently homogeneous collection, we aimed to a) test for geographical stratification of genotypes in UK Biobank and b) assess whether stratification might induce bias in genetic association analysis.We found that single genetic variants are associated with birth location within UK Biobank and that geographic structure in genetic data could not be accounted for using routine adjustment for study centre and principal components (PCs) derived from genotype data. We found that GRS for complex traits do appear geographically structured and analysis using GRS can yield biased associations. We discuss the likely origins of these observations and potential implications for analysis within large-scale population based genetic studies.