Journal article

Quantifying the Underestimation of Relative Risks from Genome-Wide Association Studies

Chris Spencer, Eliana Hechter, Damjan Vukcevic, Peter Donnelly



Genome-wide association studies (GWAS) have identified hundreds of associated loci across many common diseases. Most risk variants identified by GWAS will merely be tags for as-yet-unknown causal variants. It is therefore possible that identification of the causal variant, by fine mapping, will identify alleles with larger effects on genetic risk than those currently estimated from GWAS replication studies. We show that under plausible assumptions, whilst the majority of the per-allele relative risks (RR) estimated from GWAS data will be close to the true risk at the causal variant, some could be considerable underestimates. For example, for an estimated RR in the range 1.2-1.3, there is app..

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University of Melbourne Researchers


Awarded by Wellcome Trust

Funding Acknowledgements

This work was supported in part by the Wellcome Trust grants [085475/Z/08/Z], [075491/Z/04] (CS, DV, PD), the Rhodes Trust (EH), and Commonwealth Scholarship and Fellowship Plan (DV). PD is a Wolfson-Royal Society Merit Award holder and CS is a Scientific Leadership Fellow in the Nuffield Department of Medicine at the University of Oxford. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.