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<p>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.</p>

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Realizing the promise of genome-wide association studies for effector gene prediction

  • 期刊论文

  • 发表日期：

    2025年5月29日

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  • Maria C. Costanzo,
  • Laura W. Harris,
  • Yue Ji,
  • Aoife McMahon,
  • Noël P. Burtt,
  • Jason Flannick

摘要

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.