Effects of Genetic Relatedness of Kin Pairs on Univariate ACE Model Performance

Abstract

Abstract Statistical power is important for genetically informed research, especially when using publicly available datasets. Such datasets can make research conclusions more generalizable, but accurate records of zygosity are not always obtainable. Some researchers tend to fit models with other kin pairs rather than MZ and DZ twins, who have a less than .5 genetic relatedness difference (ΔR). However, no research has systematically investigated the impact of using such two groups of kin pairs on ACE model performance. In our study, we did mathematical derivations and simulations to illustrate how genetic relatedness of same-sex twins (RSS) and sample sizes influence ACE model performance. Specifically, we analyzed those factors’ impact on statistical power of heritability (h2) estimation, the overall power, and the frequency of negative estimates based on univariate ACE models. Our algebraic and simulation results suggest that heritability power, overall power, and reduction of negative estimates are positively associated with larger RSS and larger sample sizes. We also found addressing sex limitations would cause slightly worse model performance under most circumstances. Simulation results were discussed from both statistical and empirical perspectives, and suggestions are proposed for studies using kin pairs with ΔR < .5.