A robust and powerful test for case–control genetic association study on X chromosome

Abstract

Hundreds of genome-wide association studies were conducted to map the disease genes on autosomes in human beings. It is known that many complex diseases are sex-determined and X chromosome is expected to play an important role. However, only a few single-nucleotide polymorphisms on X chromosome were found to be significantly associated with the diseases under study. On the other hand, to balance the genetic effect between two sexes, X chromosome inactivation occurs in most of X-linked genes by silencing one copy of two X chromosomes in females and dosage compensation is achieved. A few association studies on X chromosome incorporated the information on dosage compensation. However, some of them require the assumption of Hardy–Weinberg equilibrium and some need to specify the underlying genetic model. Therefore, in this article, we propose a novel method for association by taking account of different dosage compensation patterns. The proposed test is a robust approach because it requires neither specifying the underlying genetic models nor the assumption of Hardy–Weinberg equilibrium. Further, the proposed method allows for different deviations from Hardy–Weinberg equilibrium between cases and controls. Simulation results demonstrate that our proposed method generally outperforms the existing methods in terms of controlling the size and the test power. Finally, we apply the proposed test to the meta-analysis of the Graves' disease data for its practical use.