Many genome-wide association studies have shown that the influence of each single nucleotide polymorphism is small and that most reported genetic associations could be false positives.
Is it true that many genome-wide association studies have shown that the influence of each single nucleotide polymorphism is small and that most reported genetic associations could be false positives?
Yes. Genome-wide association studies consistently demonstrate that most individual genetic variants exert very small effects, and careful methodological controls are required to account for multiple testing and manage false positive rates.
Verdict: SUPPORTED · 3 sources for, 0 against · Last checked
The retrieved papers widely acknowledge that complex traits are influenced by numerous variants with small effect sizes and that strict significance thresholds or correction methods are necessary due to the massive number of statistical tests performed in GWAS. While some papers propose methods to control false discovery rates or address genomic inflation rather than declaring most reported findings outright false, the fundamental premise that individual SNP effects are small and that multiple testing poses a major false-positive challenge is strongly supported across the literature.
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Spencer, A., Cox, A., & Walters, K. B. (2013). Comparing the Efficacy of SNP Filtering Methods for Identifying a Single Causal SNP in a Known Association Region. doi.org. https://doi.org/10.1111/ahg.12043
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Zablocki, R. W., Levine, R. A., Schork, A. J., Xu, S., Wang, Y., Fan, C. C., & Thompson, W. K. (2017). SEMI-PARAMETRIC COVARIATE-MODULATED LOCAL FALSE DISCOVERY RATE FOR GENOME-WIDE ASSOCIATION STUDIES. doi.org. https://doi.org/10.1101/183384
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CY, F., PE, S., N, Z., & B, L. (2026). A Guide for Exploring Pleiotropic Associations in Genome-Wide Association Studies Using Summary Statistics.. doi.org. https://doi.org/10.1002/sim.70717
What does the evidence say?
The retrieved papers widely acknowledge that complex traits are influenced by numerous variants with small effect sizes and that strict significance thresholds or correction methods are necessary due to the massive number of statistical tests performed in GWAS. While some papers propose methods to control false discovery rates or address genomic inflation rather than declaring most reported findings outright false, the fundamental premise that individual SNP effects are small and that multiple testing poses a major false-positive challenge is strongly supported across the literature.
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