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Robust association tests for quantitative traits on the X chromosome

Abstract

The genome-wide association study is an elementary tool to assess the genetic contribution to complex human traits. However, such association tests are mainly proposed for autosomes, and less attention has been given to methods for identifying loci on the X chromosome due to their distinct biological features. In addition, the existing association tests for quantitative traits on the X chromosome either fail to incorporate the information of males or only detect variance heterogeneity. Therefore, we propose four novel methods, which are denoted as QXcat, QZmax, QMVXcat and QMVZmax. When using these methods, it is assumed that the risk alleles for females and males are the same and that the locus being studied satisfies the generalized genetic model for females. The first two methods are based on comparing the means of the trait value across different genotypes, while the latter two methods test for the difference of both means and variances. All four methods effectively incorporate the information of X chromosome inactivation. Simulation studies demonstrate that the proposed methods control the type I error rates well. Under the simulated scenarios, the proposed methods are generally more powerful than the existing methods. We also apply our proposed methods to data from the Minnesota Center for Twin and Family Research and find 10 single nucleotide polymorphisms that are statistically significantly associated with at least two traits at the significance level of 1 × 10−3.

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Fig. 1: Powers of the two mean-variance-based tests and the four mean-based tests against nf:nm.
Fig. 2: Powers of the two mean-variance-based tests, four mean-based tests and three variance-based tests against γ.
Fig. 3: Powers of the two mean-variance-based tests, four mean-based tests and three variance-based tests against nf:nm.

Data availability

The MCTFR data used for the analyses described in this article can be found on the database of Genotypes and Phenotypes with accession number phs000620.v1.p1, and dbGaP request numbers 86747-6 and 95621-5 (https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000620.v1.p1).

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Acknowledgements

The authors are grateful to the editor, the associate editor and three anonymous reviewers for insightful comments which greatly improved the presentation of the materials.

Funding

This work was supported by the National Natural Science Foundation of China (grant numbers 82173619 and 81773544), the Science and Technology Planning Project of Guangdong Province (grant number 2020B1212030008), the Hong Kong RGC GRF (grant number 17302919) and the National and Guangzhou University Students’ Innovation and Enterprise Training Project of China (grant number 201912121019). The Minnesota Center for Twin and Family Research was supported by the National Institute on Drug Abuse (grant number U01 DA024417). The sample ascertainment and data collection in MCTFR data were supported by the National Institute on Drug Abuse (grant numbers R37 DA05147 and R01 DA13240), the National Institute on Alcohol Abuse and Alcoholism (grant numbers R01 AA09367 and R01 AA11886), and the National Institute of Mental Health (grant number R01 MH66140). The funding bodies played no role in the design of the study and collection, analysis, and interpretation of data and in writing the manuscript.

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Correspondence to Wing Kam Fung or Ji-Yuan Zhou.

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Yang, ZY., Liu, W., Yuan, YX. et al. Robust association tests for quantitative traits on the X chromosome. Heredity 129, 244–256 (2022). https://doi.org/10.1038/s41437-022-00560-y

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