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Testing for genetic association in the presence of linkage and gene-covariate interactions.

Authors
  • Callegaro, Andrea
  • Lebrec, Jeremie J P
  • Houwing-Duistermaat, Jeanine J
Type
Published Article
Journal
Biometrical journal. Biometrische Zeitschrift
Publication Date
Feb 01, 2010
Volume
52
Issue
1
Pages
22–33
Identifiers
DOI: 10.1002/bimj.200900057
PMID: 20166130
Source
Medline
License
Unknown

Abstract

In order to study family-based association in the presence of linkage, we extend a generalized linear mixed model proposed for genetic linkage analysis (Lebrec and van Houwelingen (2007), Human Heredity 64, 5-15) by adding a genotypic effect to the mean. The corresponding score test is a weighted family-based association tests statistic, where the weight depends on the linkage effect and on other genetic and shared environmental effects. For testing of genetic association in the presence of gene-covariate interaction, we propose a linear regression method where the family-specific score statistic is regressed on family-specific covariates. Both statistics are straightforward to compute. Simulation results show that adjusting the weight for the within-family variance structure may be a powerful approach in the presence of environmental effects. The test statistic for genetic association in the presence of gene-covariate interaction improved the power for detecting association. For illustration, we analyze the rheumatoid arthritis data from GAW15. Adjusting for smoking and anti-cyclic citrullinated peptide increased the significance of the association with the DR locus.

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