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Identifying modifier genes of monogenic disease: strategies and difficulties

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Abstract

Substantial clinical variability is observed in many Mendelian diseases, so that patients with the same mutation may develop a very severe form of disease, a mild form or show no symptoms at all. Among the factors that may explain these differences in disease expression are modifier genes. In this paper, we review the different strategies that can be used to identify modifier genes and explain their advantages and limitations. We focus mainly on the statistical aspects but illustrate our points with a variety of examples from the literature.

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Acknowledgments

We would like to thank three anonymous reviewers for their very constructive comments on this paper.s

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Authors and Affiliations

  1. Inserm UMR-S535, 94817, Villejuif, France

    Emmanuelle Génin, Josué Feingold & Françoise Clerget-Darpoux

  2. Université Paris Sud, 94817, Villejuif, France

    Emmanuelle Génin, Josué Feingold & Françoise Clerget-Darpoux

  3. Inserm UMR-S794, Fondation Jean Dausset-CEPH, 75010, Paris, France

    Emmanuelle Génin

  4. Inserm U535, BP 1000, 94817, Villejuif Cedex, France

    Françoise Clerget-Darpoux

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  1. Emmanuelle Génin
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Correspondence to Françoise Clerget-Darpoux.

Appendix: Multiple testing issues in association studies

Appendix: Multiple testing issues in association studies

When the number of markers tested increases, it is necessary to take into account the fact that multiple tests are performed. That is, if one defines as significant any tests with a P value below 5%, and only one test is performed, the probability of incorrectly rejecting the null hypothesis and concluding in an association is 5%. If N tests are performed, this probability is increased proportionally: when N = 100 there will be on average five false-positive results and if N = 100,000 this number will be 5,000. To limit the proportion of false positives, corrections can be made for multiple testing. One of the most commonly is the Bonferroni correction. To ensure a global type-one error of 5% for N tests, it considers significant only tests with a P value of less than 0.05/N. This correction is conservative when tests are not independent. Other less conservative corrections have been proposed, which take into account the correlation that may exist between markers through linkage disequilibrium (Li and Ji 2005; Nyholt 2004). Even after accounting for linkage disequilibrium, the significance level for ensuring a genome-wide type 1 error of 5% remains on the order of 10−7.

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Génin, E., Feingold, J. & Clerget-Darpoux, F. Identifying modifier genes of monogenic disease: strategies and difficulties. Hum Genet 124, 357–368 (2008). https://doi.org/10.1007/s00439-008-0560-2

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