Abstract
The theorised risk that confounded rare variant associations will emerge from population based genetic studies has not been investigated empirically. Here, we use 306,991 sequenced exomes from the UK Biobank to demonstrate that recent demography is poorly captured by common and rare variant principal components, and accounting for haplotype sharing does not eliminate false-positive rare variant associations with non-heritable spatially structured traits. Through re-analysis of 155 phenotypes in siblings, we show a trend of higher effect estimates bias for non-uniformly distributed traits, suggesting population stratification is most pervasive in these settings. Despite its spatial structure, bias of rare variant associations with height appeared most strongly influenced by assortative mating. We explore the risk of elevated false discovery rates for recent variants private to extended families sharing polygenic liability to extreme phenotypes, as well as through local linkage with common causal variants. Overall, we consider the complex confounding mechanisms that can impact rare variant studies and demonstrate family-based approaches can enable important sensitivity analyses.
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Acknowledgements
We gratefully acknowledge the contribution of participants in the UK Biobank to this work, and the efforts of UK Biobank staff in maintaining a highly organised and well-documented resource for scientific research. Participant data was accessed under the UK Biobank application ID 81499.
Funding
A.L.H, G.J.G., S.F., S.F, G.D.S., and G.H are funded through the Medical Research Council Integrative Epidemiology Unit (MC_UU_00032/1 and MC_UU_00032/2). N.M.D is supported by a Norwegian Research Council Grant (295989).
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Hanson, A.L., Griffith, G.J., Fang, S. et al. Evaluating confounding in rare variant genome wide association studies. Nat Commun (2026). https://doi.org/10.1038/s41467-026-73776-9
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DOI: https://doi.org/10.1038/s41467-026-73776-9
