PEStimate : Predicting offspring disease risk after Polygenic Embryo Screening

Clicks: 3
ID: 313670
2026
Free PDF
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Steady

Ranked #284 of 821 articles by views in BMC Bioinformatics

Most read Least read

Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 821 in total.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Sign in to mint
Abstract
Abstract Motivation Polygenic embryo screening (PES) is a new controversial technology whereby human in-vitro fertilization embryos are screened for their genetic risk of complex, polygenic diseases. PES aims to reduce the disease burden in offspring by prioritizing the selection of low-risk embryos. However, given that polygenic diseases are usually late-onset, PES outcomes must be estimated by epidemiological modeling. The commonly used liability threshold model has been previously used to predict outcomes. However, predictions rely on complex sets of equations, some of which require numerical integration or simulation. Further, previous models failed to account for the possibility that the selected embryo will not be born. Results Here, we present PEStimate, a freely available online app for predicting PES outcomes when screening for a single disease. PEStimate predicts the offspring risk with and without PES, as well as generates plots of the risk reduction vs key parameters. Users can adjust the number of available embryos, the live birth rate, the disease prevalence, the accuracy of the genetic risk predictor, the embryo selection method, the genetic risk of parents, and the disease status of parents, siblings, uncles/aunts, and grandparents of the embryos. Our model includes for the first time the possibility of embryo implantation failure, showing that risk reductions have been previously overestimated. PEStimate provides geneticists, healthcare professionals, patients, and other stakeholders a necessary tool for examining the impact of PES and weighing its potential benefits against expected personal and societal harms. Availability and Implementation PEStimate: https://polygenicembryo.shinyapps.io/pestimate. Source code: https://github.com/Lirazk/PEStimate. Supplementary information Supplementary data are available at Bioinformatics online.
Reference Key
openalex_W7161261356 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Liraz Klausner, Ateret Revital, Todd Lencz, Shai Carmi
Journal BMC Bioinformatics
Year 2026
DOI
10.1093/bioinformatics/btag308
URL
https://doi.org/10.1093/bioinformatics/btag308
Keywords Keywords not found

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

Comments

No comments yet. Be the first to comment on this article.