| Title: | Utility and First Clinical Application of Screening Embryos for Polygenic Disease Risk Reduction |
| Journal: | Frontiers in Endocrinology |
| Published: | 4 Dec 2019 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/31920964/ |
| DOI: | https://doi.org/10.3389/fendo.2019.00845 |
| URL: | https://www.frontiersin.org/articles/10.3389/fendo.2019.00845/pdf |
| Citations: | 60 (21 in last 2 years) as of 8 Aug 2024 |
Publication 7324
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Abstract
For over 2 decades preimplantation genetic testing (PGT) has been in clinical use to reduce the risk of miscarriage and genetic disease in patients with advanced maternal age and risk of transmitting disease. Recently developed methods of genome-wide genotyping and machine learning algorithms now offer the ability to genotype embryos for polygenic disease risk with accuracy equivalent to adults. In addition, contemporary studies on adults indicate the ability to predict polygenic disorders with risk equivalent to monogenic disorders. Existing biobanks provide opportunities to model the clinical utility of polygenic disease risk reduction among sibling adults. Here, we provide a mathematical model for the use of embryo screening to reduce the risk of type 1 diabetes. Results indicate a 45-72% reduced risk with blinded genetic selection of one sibling. The first clinical case of polygenic risk scoring in human preimplantation embryos from patients with a family history of complex disease is reported. In addition to these data, several common and accepted practices place PGT for polygenic disease risk in the applicable context of contemporary reproductive medicine. In addition, prediction of risk for PCOS, endometriosis, and aneuploidy are of particular interest and relevance to patients with infertility and represent an important focus of future research on polygenic risk scoring in embryos.11 Authors
- Nathan R. Treff
- Jennifer Eccles
- Lou Lello
- Elan Bechor
- Jeffrey Hsu
- Kathryn Plunkett
- Raymond Zimmerman
- Bhavini Rana
- Artem Samoilenko
- Steven Hsu
- Laurent C. A. M. Tellier
1 Application
| Application ID | Title |
|---|---|
| 15326 | Compressed Sensing and high-dimensional statistical methods in complex trait genomics |
Enabling scientific discoveries that improve human health