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The statistical power of genome-wide association studies for threshold traits with different frequencies of causal variants

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Abstract

This study aimed to investigate the effects of incidence rate, heritability, and polygenic variance on the statistical power of genome-wide association studies (GWAS) for threshold traits. Different incidence rates of threshold trait (1, 3, 5, 10, 25, 40, 50, 60, 75 and 90%), heritability (10 and 25%), and polygenic variance ratio (0 and 25%) were simulated separately for common (MAF ≥ 0.05), low-frequency (0.05 > MAF ≥ 0.01), and rare (MAF < 0.01) variants. Association studies were performed by logistic and linear mixed models. The highest statistical powers were observed in common and low-frequency variants with an incidence of 25–50% and 10–40%, respectively, but for rare variants, the highest statistical power was observed at low incidence. For all causal variant frequencies, the estimated heritability decline with an increase in incidence rate. We found high statistical power for traits with high heritability. In contrast, those with a high polygenic variance ratio have lower statistical power to detect common causal variants using a linear mixed model. These results demonstrate that the incidence rate of threshold traits, heritability, and polygenic variance may affect the statistical power of GWAS. Therefore, it is recommended that the effect of incidence rate, heritability, and polygenic variance be considered in designing GWAS for threshold traits.

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The authors affirm that all simulated data for confirming the conclusions of the current article are available from the corresponding author on reasonable request.

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The authors declare that they have no acknowledgments.

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The authors did not receive support from any organization for the submitted work. The authors have no relevant financial or non-financial interests to disclose.

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HK simulated, analyzed, and interpreted the scenarios and wrote the manuscript. NGHZ gave scientific advice, and was a major contributor in planning and writing the manuscript. SG gave scientific advice. All authors read and approved the final manuscript.

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Correspondence to Navid Ghavi Hossein-Zadeh.

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This article does not contain any studies with human participants performed by any of the authors.

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Khanzadeh, H., Ghavi Hossein-Zadeh, N. & Ghovvati, S. The statistical power of genome-wide association studies for threshold traits with different frequencies of causal variants. Genetica 150, 51–57 (2022). https://doi.org/10.1007/s10709-021-00140-8

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  • DOI: https://doi.org/10.1007/s10709-021-00140-8

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