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

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

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 multip...

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Bibliographic Details
Published in:Nature communications 2019-01, Vol.10 (1), p.333-333, Article 333
Main Authors: Haworth, Simon, Mitchell, Ruth, Corbin, Laura, Wade, Kaitlin H, Dudding, Tom, Budu-Aggrey, Ashley, Carslake, David, Hemani, Gibran, Paternoster, Lavinia, Smith, George Davey, Davies, Neil, Lawson, Daniel J, J Timpson, Nicholas
Format: Article
Language:eng
Subjects:
Biological Specimen Banks
Epidemiology
Genetic diversity
Genetic variance
Genetic Variation
Genome-Wide Association Study
Genotype
Genotype & phenotype
Genotypes
Geography
Health
Humans
Latent class analysis
Multifactorial Inheritance
Phenotype
Pregnant Women
Sequence Alignment
United Kingdom
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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 data in large studies.
ISSN:2041-1723
2041-1723