Association Analysis of Complex Diseases Using Triads, Parent -child Dyads and Singleton Monads Dyads and Singleton Monads
Introduction. In family association study, triad families are routinely used to test association between genetic variants and complex diseases. Since there is a lack of convenient algorithms and software to analyze the incomplete data, dyads and monads are usually discarded. To avoid this, this study developed likelihood-based statistical models and likelihood ratio tests to test association between complex diseases and genetic markers by using combinations of full triads, parent-child dyads, and affected singleton monads for a unified analysis. Methods. We develop likelihood-based statistical models estimated using Newton-Ralphson method, and performed likelihood ratio tests of genetic association (Dominant, Recessive, Multiplicative, Additive, and unrestricted model). Extensive simulations are carried out to evaluate the robustness of the test statistics by empirical type I rates and power. The methods are applied to analyze cleft palate data of TGFA gene of an Irish study to confirm the association found previously. Results. By simulation studies, we show that the proposed models and tests are very robust in terms of type I error evaluations, and are powerful by empirical power evaluations. When we applied our method to analyze cleft palate data of TGFA gene of an Irish study, by the test of Dominant and Additive using the 296 full triads, the association between SNP rs2166975 and cleft palate is confirmed (p-value = 0.047 and 0.05, respectively). Conclusion. By this combined analysis, it takes advantage of robustness of family studies to avoid high false positive rates and it improves power since more data are used in the analysis.
Chronic disease management and prevention
Describe statistical methods that combine data from dyads, monads and triads in genetic association studies of complex diseases
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