Abstract
Genome-wide association studies (GWAS) identify regions of the genome in which genetic variation is associated with the risk of complex diseases, such as diabetes, or the magnitude of traits, such as blood pressure. Determining which ‘effector genes’ mediate the effects of GWAS associations is essential to using GWAS to understand disease mechanisms and develop new therapies. In recent years, GWAS authors have increasingly included effector gene predictions as part of their study results. However, the research community has not yet converged on standards for generating or reporting these predictions. In this Perspective, we illustrate the diversity of the evidence types used to support effector gene predictions and argue for future initiatives to increase their accessibility and usefulness.
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Acknowledgements
The authors thank their colleagues for helpful discussions. This work was supported by the awards 5U24HG011453, 2UM1DK105554 and 1U24HG012542-01 from the National Institutes of Health and by European Molecular Biology Laboratory Core Funds.
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M.C.C., Y.J. and J.F. performed the literature analyses. M.C.C. and J.F. drafted the manuscript, M.C.C., Y.J. and A.M. drafted the figures, and L.W.H., Y.J., A.M. and N.P.B. reviewed and edited.
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Costanzo, M.C., Harris, L.W., Ji, Y. et al. Realizing the promise of genome-wide association studies for effector gene prediction. Nat Genet 57, 1578–1587 (2025). https://doi.org/10.1038/s41588-025-02210-5
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DOI: https://doi.org/10.1038/s41588-025-02210-5