Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Meta-Analysis
. 2022 Sep;43(9):1314-1332.
doi: 10.1002/humu.24417. Epub 2022 Jul 8.

Benchmarking of univariate pleiotropy detection methods applied to epilepsy

Oluyomi M Adesoji  1   2 , Herbert Schulz  3 , Patrick May  4 , Roland Krause  4 , Holger Lerche  5 , Michael Nothnagel  1   2 ; ILAE Consortium on Complex Epilepsies
Affiliations
Meta-Analysis

Benchmarking of univariate pleiotropy detection methods applied to epilepsy

Oluyomi M Adesoji et al. Hum Mutat. 2022 Sep.

Abstract

Pleiotropy is a widespread phenomenon that may increase insight into the etiology of biological and disease traits. Since genome-wide association studies frequently provide information on a single trait only, only univariate pleiotropy detection methods are applicable, with yet unknown comparative performance. Here, we compared five such methods with respect to their ability to detect pleiotropy, including meta-analysis, ASSET, conditional false discovery rate (cFDR), cross-phenotype Bayes (CPBayes), and pleiotropic analysis under the composite null hypothesis (PLACO), by performing extended computer simulations that varied the underlying etiological model for pleiotropy for a pair of traits, including the number of causal variants, degree of traits' overlap, effect sizes as well as trait prevalence, and varying sample sizes. Our results indicate that ASSET provides the best trade-off between power and protection against false positives. We then applied ASSET to a previously published International League Against Epilepsy (ILAE) consortium data set on complex epilepsies, comprising genetic generalized epilepsy and focal epilepsy cases and corresponding controls. We identified a novel candidate locus at 17q21.32 and confirmed locus 2q24.3, previously identified to act pleiotropically on both epilepsy subtypes by a mega-analysis. Functional annotation, tissue-specific expression, and regulatory function analysis as well as Bayesian colocalization analysis corroborated this result, rendering 17q21.32 a worthwhile candidate for follow-up studies on pleiotropy in epilepsies.

Keywords: SNPs; association; epilepsies; meta-analysis; pleiotropy.

PubMed Disclaimer

References

REFERENCES

    1. Agarwala, V., Flannick, J., Sunyaev, S., Go, T. D. C., & Altshuler, D. (2013). Evaluating empirical bounds on complex disease genetic architecture. Nature Genetics, 45(12), 1418-1427. https://doi.org/10.1038/ng.2804
    1. Agresti, A. (2003). Categorical data analysis (Vol. 482). John Wiley & Sons.
    1. Andreassen, O. A., Thompson, W. K., Schork, A. J., Ripke, S., Mattingsdal, M., Kelsoe, J. R., Kendler, K. S., O'Donovan, M. C., Rujescu, D., Werge, T., Sklar, P., Psychiatric Genomics Consortium, (, Bipolar Disorder and Schizophrenia Working, G., Roddey, J. C., Chen, C. H., McEvoy, L., Desikan, R. S., Djurovic, S., & Dale, A. M. (2013). Improved detection of common variants associated with schizophrenia and bipolar disorder using pleiotropy-informed conditional false discovery rate. PLoS Genetics, 9(4), e1003455. https://doi.org/10.1371/journal.pgen.1003455
    1. Benjamini, Y., & Hochberg, Y. (1995). Controlling the false discovery rate: A practical and powerful approach to multiple testing. Journal of the Royal Statistical Society: Series B (Methodological), 57(1), 289-300.
    1. Bhattacharjee, S., Rajaraman, P., Jacobs, K. B., Wheeler, W. A., Melin, B. S., Hartge, P., Gliomascan, C., Yeager, M., Chung, C. C., Chanock, S. J., & Chatterjee, N. (2012). A subset-based approach improves power and interpretation for the combined analysis of genetic association studies of heterogeneous traits. American Journal of Human Genetics, 90(5), 821-835. https://doi.org/10.1016/j.ajhg.2012.03.015

Publication types