FARVATX: Family‐Based Rare Variant Association Test for X‐Linked Genes. Issue 6 (21st June 2016)

• Record Type: Journal Article
• Authors: Choi, Sungkyoung; Lee, Sungyoung; Qiao, Dandi; Hardin, Megan; Cho, Michael H.; Silverman, Edwin K; Park, Taesung; Won, Sungho
• Is Part Of: Genetic epidemiology. Volume 40:Issue 6(2016)
• Page Start: 475
• Page End: 485
• Publication Date: 2016-06-21
• Subjects: X chromosome -- X chromosome inactivation -- extended families -- rare variants -- genetic association analysis; Genetic epidemiology -- Periodicals; Heredity -- Periodicals; Medical geography -- Periodicals; 614
• DOI: 10.1002/gepi.21979
• Languages: English
• ISSNs: 0741-0395

Abstract

ABSTRACT: Although the X chromosome has many genes that are functionally related to human diseases, the complicated biological properties of the X chromosome have prevented efficient genetic association analyses, and only a few significantly associated X‐linked variants have been reported for complex traits. For instance, dosage compensation of X‐linked genes is often achieved via the inactivation of one allele in each X‐linked variant in females; however, some X‐linked variants can escape this X chromosome inactivation. Efficient genetic analyses cannot be conducted without prior knowledge about the gene expression process of X‐linked variants, and misspecified information can lead to power loss. In this report, we propose new statistical methods for rare X‐linked variant genetic association analysis of dichotomous phenotypes with family‐based samples. The proposed methods are computationally efficient and can complete X‐linked analyses within a few hours. Simulation studies demonstrate the statistical efficiency of the proposed methods, which were then applied to rare‐variant association analysis of the X chromosome in chronic obstructive pulmonary disease. Some promising significant X‐linked genes were identified, illustrating the practical importance of the proposed methods.