Assisted Reproduction · Add-Ons and Adjuncts

Utility of polygenic embryo screening for disease depends on the selection strategy

Lencz T, Backenroth D, Granot-Hershkovitz E, Green A, Gettler K, Cho JH, Weissbrod O, Zuk O, Carmi S

Published October 12, 2021 eLife, 10
DOI 10.7554/eLife.64716 PMID 34635206 PMC PMC8510582

RRM Academy Synopsis

Polygenic embryo screening cuts modeled risk more by lowest-score pick

In the model, picking the lowest-scoring embryo gave much larger relative risk reductions than excluding high-scoring embryos, given enough viable embryos. This modeling study covered one disease at a time. Simulated couples came from real schizophrenia and Crohn's disease genomes. Large relative reductions may produce very small absolute changes in rare diseases.

Key Findings

  • Excluding only embryos in the top 2% of risk scores produced very small risk reductions, while choosing the embryo with the lowest score produced substantially larger relative reductions.
  • The authors note a steep drop in risk reduction when fewer than 5 embryos are available.
  • Under lowest-risk prioritization, the model gave schizophrenia (prevalence at most 1%) a 52% relative risk reduction, about 0.5 percentage points absolute: 99% chance of no disease with random selection, 99.5% with prioritization.
  • For type 2 diabetes, with US lifetime prevalence above 20%, a modeled 43% relative reduction would equal over 8 percentage points absolute if a full SNP heritability of 17% were achieved.
  • Simulated couples drawn from real genomes (about 900 schizophrenia cases and 1600 controls, about 150 Crohn's cases and 100 controls) closely matched the model, apart from a slight overestimate under lowest-risk prioritization.

Interpretation

The study is a statistical modeling analysis supported by simulated embryos. Researchers screened no real embryos and followed no children. The model addresses one disease at a time, a single embryo transfer, and embryos that would each lead to a live birth. The authors describe their estimates as an upper bound for real-world scenarios, since a score may be less accurate within families. In simulations, selecting against one disease could raise the risk of a strongly negatively correlated disease, which the authors note is uncommon.

RRM Context

Polygenic embryo screening happens inside IVF. IVF bypasses the reproductive system without finding why conception fails. The paper's model counts only embryos that would lead to a live birth. The authors note that many IVF cycles produce no live birth. Restorative reproductive medicine starts with the causes of a couple's infertility and an evaluation of both partners.

Abstract

Polygenic risk scores (PRSs) have been offered since 2019 to screen in vitro fertilization embryos for genetic liability to adult diseases, despite a lack of comprehensive modeling of expected outcomes. Here we predict, based on the liability threshold model, the expected reduction in complex disease risk following polygenic embryo screening for a single disease. A strong determinant of the potential utility of such screening is the selection strategy, a factor that has not been previously studied. When only embryos with a very high PRS are excluded, the achieved risk reduction is minimal. In contrast, selecting the embryo with the lowest PRS can lead to substantial relative risk reductions, given a sufficient number of viable embryos. We systematically examine the impact of several factors on the utility of screening, including: variance explained by the PRS, number of embryos, disease prevalence, parental PRSs, and parental disease status. We consider both relative and absolute risk reductions, as well as population-averaged and per-couple risk reductions, and also examine the risk of pleiotropic effects. Finally, we confirm our theoretical predictions by simulating 'virtual' couples and offspring based on real genomes from schizophrenia and Crohn's disease case-control studies. We discuss the assumptions and limitations of our model, as well as the potential emerging ethical concerns.

Topics

By this author

Related research

Assisted Reproduction › Add-Ons and Adjuncts › Preimplantation Genetic Testing · Research Methods › Measurement and Statistics › Statistical Methods
Todd Lencz, Daniel Backenroth, Einat Granot-Hershkovitz, Adam Green, Kyle Gettler, Judy H Cho, Omer Weissbrod, Or Zuk, Shai Carmi
T Lencz, Dan Backenroth, Danny Backenroth, D Backenroth, E Granot-Hershkovitz, A Green, K Gettler, J Cho, O Weissbrod, O Zuk, S Carmi
PMID 34635206 34635206 DOI 10.7554/eLife.64716 10.7554/eLife.64716 Lencz et al. 2021, Lencz 2021