Case-parent Triads (case-parent + triad)

Distribution by Scientific Domains


Selected Abstracts


Using Case-parent Triads to Estimate Relative Risks Associated with a Candidate Haplotype

ANNALS OF HUMAN GENETICS, Issue 3 2009
Min Shi
Summary Estimating haplotype relative risks in a family-based study is complicated by phase ambiguity and the many parameters needed to quantify relative risks for all possible diplotypes. This problem becomes manageable if a particular haplotype has been implicated previously as relevant to risk. We fit log-linear models to estimate the risks associated with a candidate haplotype relative to the aggregate of other haplotypes. Our approach uses existing haplotype-reconstruction algorithms but requires assumptions about the distribution of haplotypes among triads in the source population. We consider three levels of stringency for those assumptions: Hardy-Weinberg Equilibrium (HWE), random mating, and no assumptions at all. We assessed our method's performance through simulations encompassing a range of risk haplotype frequencies, missing data patterns, and relative risks for either offspring or maternal genetic effects. The unconstrained model provides robustness to bias from population structure but requires excessively large sample sizes unless there are few haplotypes. Assuming HWE accommodates many more haplotypes but sacrifices robustness. The model assuming random mating is intermediate, both in the number of haplotypes it can handle and in robustness. To illustrate, we reanalyze data from a study of orofacial clefts to investigate a 9-SNP candidate haplotype of the IRF6 gene. [source]


Improved association analyses of disease subtypes in case-parent triads

GENETIC EPIDEMIOLOGY, Issue 3 2006
Michael P. Epstein
Abstract The sampling of case-parent triads is an appealing strategy for conducting association analyses of complex diseases. In certain situations, one may have interest in using the triads to identify genetic variants that are associated with a specific subtype of disease, perhaps related to a characteristic cluster of symptoms. A straightforward strategy for conducting such a subtype analysis would be to analyze only those triads with the subtype of interest. While such a strategy is valid, we show that triads without the subtype of interest can provide additional genetic information that increases power to detect association with the subtype of interest. We incorporate this additional information using a likelihood-based framework that permits flexible modeling and estimation of allelic effects on disease subtypes and also allows for missing parental data. Using simulated data under a variety of genetic models, we show that our proposed association test consistently outperforms association tests that only analyze triads with the subtype of interest. We also apply our method to a triad study of attention-deficit hyperactivity disorder and identify a genetic variant in the dopamine transporter gene that is associated with a subtype characterized by extreme levels of both inattentive and hyperactive-impulsive symptoms. Genet. Epidemiol. 2006. © 2006 Wiley-Liss, Inc. [source]


Detecting genotype combinations that increase risk for disease: Maternal-Fetal genotype incompatibility test

GENETIC EPIDEMIOLOGY, Issue 1 2003
Janet S. Sinsheimer
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. Genet Epidemiol 24:1,13, 2003. © 2003 Wiley-Liss, Inc. [source]