Work has progressed in family-based statistical methods for studying genetic effects. Case-control studies aimed at elucidating genetic contributors to the etiology of diseases are problematic because of the 'admixture' problem: If a particular variant allele is to be studied, there may be subpopulations that simultaneously have elevated prevalence of the variant allele and increased risk of the defect, for unrelated reasons. Such an admixture can produce biased estimation in a traditional population-based case-control study. A family-based design avoids this problem by effectively conditioning on the parental genotypes. One can study affected individuals and their parents, who together form a 'triad' of genotypes. Using the triads from such a study, under assumed Mendelian inheritance, in previous research we showed that one can use a log-linear model to estimate relative risks for an allelic variant and can differentiate effects that are mediated through phenotypic prenatal effects of the maternal genotype from effects mediated by the (correlated) offspring's genotype, and can also detect genomic imprinting. We have now developed SAS software to implement these methods, which we are providing to investigators on request. A further extension now allows for grandparent-based designs for studying genetic factors related to risk of birth defects and pregnancy complications. Because the mothers experiencing adverse reproductive outcomes are typically young, both the baby and the baby's grandparents will often be available for study and will also be relatively well-motivated to help. We developed methods based on transmissions of variant alleles from the grandparents to the offspring born of the affected pregnancy, and showed that studies based on grandparental transmission are substantially more powerful than the usual design, which is based on transmissions from parents. Work has also begun on methods based on genotyping of pooled DNA samples in epidemiologic studies, both case-control and case-parent designs.
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