Statistical Approaches to Detect Intergenerational Genetic Effects – Going Beyond GWAS.

Abstract

Statistical genetic approaches such as genome?wide association studies (GWAS) have failed to account for more than a modest amount of the human disease risks attributed to genetic variants. Genetic influences that transcend generations, intergenerational effects, provide one potential source of the remaining genetic signature. However, studies using unrelated individuals cannot be used to capture these intergenerational effects. Thus, alternative study designs and statistical approaches are needed. I will present one approach that we have taken to detect intergenerational effects, the maternal fetal genotype (MFG) incompatibility test, which can estimate any combination of maternal genetic effects, offspring genetic effects, and their interactions. I will illustrate the statistical properties of the MFG test and provide some illustrative examples using both simulated and actual data. More generally, our work demonstrates how pedigrees can be used to understand intergenerational effects as well as providing an opportunity to examine alternative mechanisms.