Accounting for Relatedness in Family Based Genetic Association Studies

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Abstract
Objective: Assess the differences in point estimates, power and type 1 error rates when accounting for and ignoring family structure in genetic tests of association. Methods: We compare by simulation the performance of analytic models using variance components to account for family structure and regression models that ignore relatedness for a range of possible family based study designs (i.e., sib pairs vs. large sibships vs. nuclear families vs. extended families). Results: Our analyses indicate that effect size estimates and power are not significantly affected by ignoring family structure. Type 1 error rates increase when family structure is ignored, as density of family structures increases, and as trait heritability increases. For discrete traits with moderate levels of heritability and across many common sampling designs, type 1 error rates rise from a nominal 0.05 to 0.11. Conclusion: Ignoring family structure may be useful in screening although it comes at a cost of a increased type 1 error rate, the magnitude of which depends on trait heritability and pedigree configuration.