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Abstract:
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Sequencing technology allows examining the impact of rare variants on complex diseases. However, in a conventional case-control study, large samples are needed to achieve sufficient power for testing associations of suspected rare variants to diseases. In such large samples, population structure can cause spurious signals. One approach to overcome low power and confounders is family-based study design since the count of risk variants can be enriched in a family of multiple affected members with the same genetic background. We propose a novel test for a sample of families. In each family, we first determine the inheritance vector at the locus of interest for all family members. Since affected members are more likely to share risk variants identical-by-descent, we propose to test if rare variants are shared more than expected given the inheritance vector and the founder genotypes. In addition, we develop an imputation algorithm for families with missing founders, so that this test can apply to families with arbitrary family structures. In sum, we propose a family-based test that efficiently uses sharing of rare risk variants to maximize power for detecting rare variant associations.
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