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SDS Seminar Series: Dr. Arbel Harpak (Friday 3/12/21, 2pm)
Friday, March 12, 2021, 02:00pm - 03:00pm

The Spring 2021 SDS Seminar Series kicks off on Friday, March 12, 2021 from 2:00 p.m. to 3:00 p.m. via Zoom with Dr. Arbel Harpak (Assistant Professor at the Department of Population Health and Integrative Biology in the College of Natural Science at The University of Texas at Austin).

Please contact stat.admin@austin.utexas.edu for the Zoom link.

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Title: "Predicting complex human traits: Why so complex?"

Abstract: Most human traits of interest are highly “polygenic” (or “complex”): the bulk of the heritable variation is due to a combination of numerous genetic variants of small marginal effects.  A polygenic score is a predictor of a person’s complex trait value computed from his or her genotype. Polygenic scores sum over the genetic effects of the alleles carried by a person—as estimated in a genome-wide association study (GWAS) for the trait of interest.  Fields as diverse as clinical risk classification, evolutionary genetics, social sciences and embryo selection are rapidly adopting polygenic scores.  

I will show that the prediction accuracy of polygenic scores can be highly sensitive to tiny biases in GWAS effect estimates, and further that that the prediction accuracy of polygenic scores depends on characteristics such as the socio-economic status, age or sex of the people in which the GWAS and the prediction are conducted. These dependencies highlight the complexities of interpreting polygenic scores and the potential for serious inequities in their application in the clinic and beyond.

A key reason for these dependencies is in the fact that GWAS estimates are also influenced by factors other than direct genetic effects—including population structure confounding, mating patterns, indirect genetic effects of relatives and other gene-by-environment interactions.  I will discuss the development of statistical tools to tease apart the different factors contributing to GWAS associations, and ultimately improve the prediction ability and the interpretation of polygenic scores.