Incorporating Serotypes into Family Based Association Studies Using the MFG Test

• Published in: Annals of human genetics 2006-07, Vol.70 (4), p.541-553
• Main Authors: Minassian, S. L., Palmer, C. G. S., Turunen, J. A., Paunio, T., Lönnqvist, J., Peltonen, L., Woodward, J. A., Sinsheimer, J. S.
• Format: Article
• Language: English
• Subjects: Blood Group Incompatibility - genetics; Blood Grouping and Crossmatching; Computer Simulation; Female; gene by environment; gene by gene; Genetic Linkage; Genotype; Histocompatibility Testing - methods; Humans; Likelihood Functions; Male; maternal‐fetal genotype incompatibility; missing data; Models, Genetic; non‐codominant data; Nuclear Family; Pregnancy; Rh-Hr Blood-Group System - blood; Rh-Hr Blood-Group System - genetics; rhesus incompatibility; Risk Factors; Sample Size; Schizophrenia - genetics; serotypes; Serotyping
• ISSN: 0003-4800; 1469-1809
• DOI: 10.1111/j.1469-1809.2005.00243.x

Summary Family based association tests are widely used to detect genetic effects. The focus of this paper is the maternal‐fetal genotype (MFG) incompatibility test, a family based association test which can be used to detect genetic effects that contribute to disease, including alleles in the child that increase disease risk, maternal alleles that increase disease risk in the child, and maternal‐fetal genotype incompatibilities. Consideration of incomplete data resulting from using serotypes could expand the power of the MFG test for detecting genetic effects. Serotypes may be all that are available in certain families, or preferred because of convenience or low cost, and thus a modification of the MFG test will allow optimal use of such data. The modified MFG likelihood can accommodate the incomplete data that result from using serotypes rather than the corresponding codominant genotypes. The modified MFG test was evaluated with serotypes and genotypes from families with members affected with schizophrenia. In addition, simulation studies were performed. Results of the data analyses and simulation studies showed that serotypes can be used to augment genotypes within a sample, to increase power to detect effects when the candidate gene produces serotypes.