title: Detecting genotype combinations that increase risk for disease: maternal-fetal genotype incompatibility test.
abstract: Biological mechanisms that involve gene-by-environment interactions have been hypothesized to explain susceptibility to complex familial disorders. Current research provides compelling evidence that one environmental factor, which acts prenatally to increase susceptibility, arises from a maternal-fetal genotype incompatibility. Because it is genetic in origin, a maternal-fetal incompatibility is one possible source of an adverse environment that can be detected in genetic analyses and precisely studied, even years after the adverse environment was present. Existing statistical models and tests for gene detection are not optimal or even appropriate for identifying maternal-fetal genotype incompatibility loci that may increase the risk for complex disorders. We describe a new test, the maternal-fetal genotype incompatibility (MFG) test, that can be used with case-parent triad data (affected individuals and their parents) to identify loci for which a maternal-fetal genotype incompatibility increases the risk for disease. The MFG test adapts a log-linear approach for case-parent triads in order to detect maternal-fetal genotype incompatibility at a candidate locus, and allows the incompatibility effects to be estimated separately from direct effects of either the maternal or the child's genotype. Through simulations of two biologically plausible maternal-fetal genotype incompatibility scenarios, we show that the type-I error rate of the MFG test is appropriate, that the estimated parameters are accurate, and that the test is powerful enough to detect a maternal-fetal genotype incompatibility of moderate effect size.
authors.affiliation: Department of Human Genetics, University of California, Los Angeles, California 90095-1766, USA. janet@mednet.ucla.edu
authors.forename: Janet S
authors.initials: JS
authors.lastname: Sinsheimer
authors.forename: Christina G S
authors.initials: CG
authors.lastname: Palmer
authors.forename: J Arthur
authors.initials: JA
authors.lastname: Woodward
mesh_terms: D015982:Bias; D002874:Chromosome Mapping / Q000379:methods*; D015987:Effect Modifier, Epidemiologic; D005260:Female; D005787:Gene Frequency; D020022:Genetic Predisposition to Disease / Q000235:genetics*; D005820:Genetic Testing / Q000379:methods*; D005828:Genetics, Population; D005838:Genotype; D006801:Humans; D016014:Linear Models; D008297:Male; D008431:Maternal-Fetal Exchange; D008957:Models, Genetic; D010375:Pedigree; D011247:Pregnancy; D012306:Risk