12th Annual IGSS Conference • October 28-29, 2021

Integrating Genetics and the Social Sciences 2021

Estimating social genetic effects on Alzheimer's disease

Qiongshi Lu, Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison

Alzheimer's disease (AD) is an etiologically complex and clinically heterogeneous neurodegenerative disease without a current cure. More than five million Americans are currently living with AD, and the number is expected to grow rapidly as the population continues to age. Marginal effect estimates in genome-wide association studies (GWAS) are mixtures of the direct and social (indirect) genetic effects due to the correlations in genotypes between parents and their children. Current studies on the genetic basis of AD ignore the social genetic effects which may bias genetic association results. We assess the potential contribution of environments provided by relatives/children on the development and diagnosis of AD by deploying novel uses of multi-generational GWAS techniques and a suite of post-GWAS analyses. In particular, we apply and compare two statistical frameworks, i.e. DONUTS and GSEM, to dissect the direct and indirect effects. We further showcase the effect of children on parental AD outcomes by estimating genetic correlations of direct and indirect components of AD with many complex traits. Our study provides novel empirical results on the role of family environments on parental AD outcomes and may have implications on future studies of later-life health outcomes.

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