Genomic inflation factors under polygenic inheritance

Abstract

Population structure, including population stratification and cryptic relatedness, can cause spurious associations in genome-wide association studies (GWAS). Usually, the scaled median or mean test statistic for association calculated from multiple single-nucleotide-polymorphisms across the genome is used to assess such effects, and 'genomic control' can be applied subsequently to adjust test statistics at individual loci by a genomic inflation factor. Published GWAS have clearly shown that there are many loci underlying genetic variation for a wide range of complex diseases and traits, implying that a substantial proportion of the genome should show inflation of the test statistic. Here, we show by theory, simulation and analysis of data that in the absence of population structure and other technical artefacts, but in the presence of polygenic inheritance, substantial genomic inflation is expected. Its magnitude depends on sample size, heritability, linkage disequilibrium structure and the number of causal variants. Our predictions are consistent with empirical observations on height in independent samples of ~4000 and ~133,000 individuals.

Keywords

Affiliated Institutions

• Massachusetts General Hospital US
• Icelandic Heart Association IS
• Harvard University US
• University of Maryland, Baltimore US
• The University of Melbourne AU
• Center for Human Genetics US
• Boston Children's Hospital US
• Centre for Human Genetics GB
• Montreal Heart Institute CA
• University of Exeter GB
• QIMR Berghofer Medical Research Institute AU
• Rotterdam University of Applied Sciences NL
• Oxford Centre for Diabetes, Endocrinology and Metabolism GB
• University of Michigan US
• Peninsula College of Medicine and Dentistry GB
• Université de Montréal CA
• St Thomas' Hospital GB
• University of Oxford GB
• Broad Institute US
• Washington University in St. Louis US
• Karolinska Institutet SE

Related Publications