Original Paper

Allowing for Missing Data at Highly Polymorphic Genes when Testing for Maternal, Offspring and Maternal-Fetal Genotype Incompatibility Effects
Hsin-Ju Hsieh^a1, Christina G.S. Palmer^{b, c}, Janet S. Sinsheimer<sup>a, c, d

a</sup>Biostatistics,
^bDepartment of Psychiatry and Biobehavioral Sciences,
^cHuman Genetics,
^dBiomathematics, University of California, Los Angeles, Calif., USA

Address of Corresponding Author

Hum Hered 2006;62:165-174 (DOI: 10.1159/000096444)

  Key Words

• Family-based study
• Association
• Identity-by-state
• Missing data
• Maternal-fetal genotype incompatibility

  Abstract

Genes can be associated with disease through an individual's inherited genotype, the maternal genotype or the interaction between these two. When the gene is highly polymorphic, it is more difficult to identify the gene's functional role than for less polymorphic loci, because different alleles at the locus may be associated with the disease through separate and joint effects from maternal and offspring genotypes. Family-based studies are used to test genetic associations because of their robustness to population stratification. However, parental genotype data are often missing, and omitting incompletely genotyped families is inefficient. Methods have been proposed to accommodate incomplete families in family-based association studies. They are not easily generalized to allow simultaneous examination of offspring allelic, maternal allelic and maternal-fetal genotype (MFG) incompatibility effects. Since many MFG incompatibility effects occur through matching between maternal and offspring's genotypes, we present an identity-by-state (IBS) framework to incorporate incomplete families in the MFG test when modeling genetic effects produced by a polymorphic gene. Using simulations, we examine the MFG test's performance with incomplete parental genotype data and an IBS framework. The MFG test using the IBS framework is immune to population stratification and efficiently uses information from incomplete families.

Copyright © 2006 S. Karger AG, Basel

  Author Contacts

Dr. Janet Sinsheimer
Department of Human Genetics, 5357C Gonda Center
695 Charles E. Young Drive South, Box 957088
Los Angeles, CA 90095-7088 (USA)
Tel. +1 310 825 8002, Fax +1 310 825 8685, E-Mail janet@mednet.ucla.edu

  Article Information

Received: April 3, 2006
Accepted after revision: August 7, 2006
Published online: October 25, 2006
Number of Print Pages : 10
Number of Figures : 2, Number of Tables : 3, Number of References : 28