Literature DB >> 31767819

X-chromosome genetic association test incorporating X-chromosome inactivation and imprinting effects.

Wei Liu1, Bei-Qi Wang, Guojun Liu-Fu, Wing Kam Fung, Ji-Yuan Zhou.   

Abstract

Studies have shown that many complex diseases are sex-determined. When conducting genetic association studies on X-chromosome, there are two important epigenetic factors which should be considered simultaneously: X-chromosome inactivation and genomic imprinting. Currently, there have been several association tests accounting for the information on X-chromosome inactivation. However, these tests do not take the imprinting effects into account. In this paper, we propose a novel association test simultaneously incorporating X-chromosome inactivation and imprinting effects based on case-parent trios and control-parent trios for female offspring and case-control data for male offspring, denoted by MLRXCII. Extensive simulation studies are carried out to investigate the type I error rate and the test power of the proposed MLRXCII . Simulation results demonstrate that the proposed test controls the type I error rate well andis more powerful than the existing method when imprinting effects exist. The proposed MLRXCII test is valid and powerful in genetic association studies on X-chromosome for qualitative traits and thus is recommended in practice.

Mesh:

Year:  2019        PMID: 31767819

Source DB:  PubMed          Journal:  J Genet        ISSN: 0022-1333            Impact factor:   1.166


  43 in total

Review 1.  X-chromosome inactivation: counting, choice and initiation.

Authors:  P Avner; E Heard
Journal:  Nat Rev Genet       Date:  2001-01       Impact factor: 53.242

Review 2.  Development of gender differences in depression: an elaborated cognitive vulnerability-transactional stress theory.

Authors:  B L Hankin; L Y Abramson
Journal:  Psychol Bull       Date:  2001-11       Impact factor: 17.737

3.  Effect of Turner's syndrome and X-linked imprinting on cognitive status: analysis based on pedigree data.

Authors:  Danuta Z Loesch; Quang Minh Bui; Wendy Kelso; Richard M Huggins; Howard Slater; Garry Warne; Philip B Bergman; Paul Bergman; Christine Rodda; Robert John Mitchell; Margot Prior
Journal:  Brain Dev       Date:  2005-10       Impact factor: 1.961

4.  How to interpret a genome-wide association study.

Authors:  Thomas A Pearson; Teri A Manolio
Journal:  JAMA       Date:  2008-03-19       Impact factor: 56.272

5.  Genomic imprinting: employing and avoiding epigenetic processes.

Authors:  Marisa S Bartolomei
Journal:  Genes Dev       Date:  2009-09-15       Impact factor: 11.361

Review 6.  Xist and X chromosome inactivation.

Authors:  G F Kay
Journal:  Mol Cell Endocrinol       Date:  1998-05-25       Impact factor: 4.102

7.  A robust and powerful test for case-control genetic association study on X chromosome.

Authors:  Peng Wang; Si-Qi Xu; Bei-Qi Wang; Wing Kam Fung; Ji-Yuan Zhou
Journal:  Stat Methods Med Res       Date:  2018-09-20       Impact factor: 3.021

8.  A longitudinal twin study of skewed X chromosome-inactivation.

Authors:  Chloe Chung Yi Wong; Avshalom Caspi; Benjamin Williams; Renate Houts; Ian W Craig; Jonathan Mill
Journal:  PLoS One       Date:  2011-03-22       Impact factor: 3.240

9.  Impact of the X Chromosome and sex on regulatory variation.

Authors:  Kimberly R Kukurba; Princy Parsana; Brunilda Balliu; Kevin S Smith; Zachary Zappala; David A Knowles; Marie-Julie Favé; Joe R Davis; Xin Li; Xiaowei Zhu; James B Potash; Myrna M Weissman; Jianxin Shi; Anshul Kundaje; Douglas F Levinson; Philip Awadalla; Sara Mostafavi; Alexis Battle; Stephen B Montgomery
Journal:  Genome Res       Date:  2016-04-21       Impact factor: 9.043

10.  A statistical measure for the skewness of X chromosome inactivation based on family trios.

Authors:  Si-Qi Xu; Yu Zhang; Peng Wang; Wei Liu; Xian-Bo Wu; Ji-Yuan Zhou
Journal:  BMC Genet       Date:  2018-12-05       Impact factor: 2.797

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  3 in total

1.  BEXCIS: Bayesian methods for estimating the degree of the skewness of X chromosome inactivation.

Authors:  Wen-Yi Yu; Yu Zhang; Meng-Kai Li; Zi-Ying Yang; Wing Kam Fung; Pei-Zhen Zhao; Ji-Yuan Zhou
Journal:  BMC Bioinformatics       Date:  2022-05-24       Impact factor: 3.307

2.  Gene-Based Methods for Estimating the Degree of the Skewness of X Chromosome Inactivation.

Authors:  Meng-Kai Li; Yu-Xin Yuan; Bin Zhu; Kai-Wen Wang; Wing Kam Fung; Ji-Yuan Zhou
Journal:  Genes (Basel)       Date:  2022-05-06       Impact factor: 4.141

3.  A statistical measure for the skewness of X chromosome inactivation for quantitative traits and its application to the MCTFR data.

Authors:  Bao-Hui Li; Wen-Yi Yu; Ji-Yuan Zhou
Journal:  BMC Genom Data       Date:  2021-07-02
  3 in total

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