Is Population Structure in the genetic biobank era irrelevant, a challenge, or an opportunity?

摘要: Replicable genetic association signals have consistently been found through genome-wide studies in recent years. The dramatic expansion of study sizes improves power estimation effect sizes, genomic prediction, causal inference, and polygenic selection, but it simultaneously increases susceptibility these methods to bias due subtle population structure. Standard using principal components correct for structure might not always be appropriate we use a simulation illustrate when correction ineffective avoiding biases. New such as trans-ethnic modeling chromosome painting allow richer understanding the relationship between traits We arguments real examples (stroke educational attainment) provide more nuanced structure, which is set revisited critical aspect future analyses epidemiology. also make simple recommendations how problems can avoided future. Our results particular importance implementation GWAS meta-analysis, prediction traits, inference.