Pulse Brain · Growing Health Evidence Index
Peer-reviewed

Apparent latent structure within the UK Biobank sample has implications for epidemiological analysis

Simon Haworth, Ruth E. Mitchell, Laura J. Corbin, Kaitlin H. Wade, Tom Dudding, Ashley Budu‐Aggrey, David Carslake, Gibran Hemani, Lavinia Paternoster, George Davey Smith, Neil M Davies, Daniel J. Lawson, Nicholas J. Timpson

Nature Communications · 2019

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Summary

Large studies use genotype data to discover genetic contributions to complex traits and infer relationships between those traits. Co-incident geographical variation in genotypes and health traits can bias these analyses. Here we show that single genetic variants and genetic scores composed of multiple variants are associated with birth location within UK Biobank and that geographic structure in genotype data cannot be accounted for using routine adjustment for study centre and principal components derived from genotype data. We find that major health outcomes appear geographically structured and that coincident structure in health outcomes and genotype data can yield biased associations. Understanding and accounting for this phenomenon will be important when making inference from genotype

Source type
Peer-reviewed study
DOI
10.1038/s41467-018-08219-1
Catalogue ID
BFmoef2ocf-9lykxg
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