Problems with Using Polygenic Scores to Select Embryos

Abstract

Companies have recently begun to sell a new service to patients considering in vitro fertilization: embryo selection based on polygenic scores (ESPS). These scores represent individualized predictions of health and other outcomes derived from genomewide association studies in adults to partially predict these outcomes. This article includes a discussion of many factors that lower the predictive power of polygenic scores in the context of embryo selection and quantifies these effects for a variety of clinical and nonclinical traits. Also discussed are potential unintended consequences of ESPS (including selecting for adverse traits, altering population demographics, exacerbating inequalities in society, and devaluing certain traits). Recommendations for the responsible communication about ESPS by practitioners are provided, and a call for a society-wide conversation about this technology is made. (Funded by the National Institute on Aging and others.).

Figure 1.. Expected Difference in Educational Attainment between the Person with the Highest Polygenic Score and a Person Selected Randomly from a Group of 10 Persons.

“Between-family” indicates that each person was drawn from a different family, and “within-family” indicates that each person was drawn from the same family and shares the same two biologic parents. The hatch marks indicate the assumption that the distribution of family environments is the same as that in the genomewide association studies (GWAS) from which the polygenic score was constructed. The solid red and blue bars indicate the assumption that the distribution of family environments differs from the distribution in the GWAS from which the polygenic score was constructed, with a genetic correlation across environments equal to 0.87 (see Section 7 in the Supplementary Appendix). Ancestry groups (European [EUR], admixed American [AMR], East Asian [EAS], and African [AFR]) are defined in accordance with the groupings in the 1000 Genomes Project. The smaller expected differences among persons of non-EUR ancestries are due to the fact that the GWAS were conducted with the use of EUR samples. Plus–minus values represent the 95% prediction interval of the difference in educational attainment. Assumptions err on the side of increasing expected gains and narrowing prediction intervals; therefore, these values may be considered best-case-scenario estimates. Full details of all calculations are available in the Supplementary Appendix.

Figure 2.. Absolute and Relative Reductions in Risk for Hypertension, Type 2 Diabetes, and Coronary Artery Disease According to Ancestry.

The calculations used to obtain the data provided are available in the Supplementary Appendix, where data on other clinical outcomes are also available. Risk without ESPS (embryo selection based on polygenic scores) may differ across embryos owing to family history or environmental conditions. Ancestry groups (EUR, AMR, EAS, and AFR) are defined in accordance with the groupings in the 1000 Genomes Project.