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Whole-genome risk prediction of common diseases in human preimplantation embryos
Preimplantation genetic testing (PGT) of in-vitro-fertilized embryos has been proposed as a method to reduce transmission of common disease; however, more comprehensive embryo genetic assessment, combining the effects of common variants and rare variants, remains unavailable. Here, we used a combina...
Autores principales: | , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group US
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8938270/ https://www.ncbi.nlm.nih.gov/pubmed/35314819 http://dx.doi.org/10.1038/s41591-022-01735-0 |
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author | Kumar, Akash Im, Kate Banjevic, Milena Ng, Pauline C. Tunstall, Tate Garcia, Geronimo Galhardo, Luisa Sun, Jiayi Schaedel, Oren N. Levy, Brynn Hongo, Donna Kijacic, Dusan Kiehl, Michelle Tran, Nam D. Klatsky, Peter C. Rabinowitz, Matthew |
author_facet | Kumar, Akash Im, Kate Banjevic, Milena Ng, Pauline C. Tunstall, Tate Garcia, Geronimo Galhardo, Luisa Sun, Jiayi Schaedel, Oren N. Levy, Brynn Hongo, Donna Kijacic, Dusan Kiehl, Michelle Tran, Nam D. Klatsky, Peter C. Rabinowitz, Matthew |
author_sort | Kumar, Akash |
collection | PubMed |
description | Preimplantation genetic testing (PGT) of in-vitro-fertilized embryos has been proposed as a method to reduce transmission of common disease; however, more comprehensive embryo genetic assessment, combining the effects of common variants and rare variants, remains unavailable. Here, we used a combination of molecular and statistical techniques to reliably infer inherited genome sequence in 110 embryos and model susceptibility across 12 common conditions. We observed a genotype accuracy of 99.0–99.4% at sites relevant to polygenic risk scoring in cases from day-5 embryo biopsies and 97.2–99.1% in cases from day-3 embryo biopsies. Combining rare variants with polygenic risk score (PRS) magnifies predicted differences across sibling embryos. For example, in a couple with a pathogenic BRCA1 variant, we predicted a 15-fold difference in odds ratio (OR) across siblings when combining versus a 4.5-fold or 3-fold difference with BRCA1 or PRS alone. Our findings may inform the discussion of utility and implementation of genome-based PGT in clinical practice. |
format | Online Article Text |
id | pubmed-8938270 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group US |
record_format | MEDLINE/PubMed |
spelling | pubmed-89382702022-04-07 Whole-genome risk prediction of common diseases in human preimplantation embryos Kumar, Akash Im, Kate Banjevic, Milena Ng, Pauline C. Tunstall, Tate Garcia, Geronimo Galhardo, Luisa Sun, Jiayi Schaedel, Oren N. Levy, Brynn Hongo, Donna Kijacic, Dusan Kiehl, Michelle Tran, Nam D. Klatsky, Peter C. Rabinowitz, Matthew Nat Med Article Preimplantation genetic testing (PGT) of in-vitro-fertilized embryos has been proposed as a method to reduce transmission of common disease; however, more comprehensive embryo genetic assessment, combining the effects of common variants and rare variants, remains unavailable. Here, we used a combination of molecular and statistical techniques to reliably infer inherited genome sequence in 110 embryos and model susceptibility across 12 common conditions. We observed a genotype accuracy of 99.0–99.4% at sites relevant to polygenic risk scoring in cases from day-5 embryo biopsies and 97.2–99.1% in cases from day-3 embryo biopsies. Combining rare variants with polygenic risk score (PRS) magnifies predicted differences across sibling embryos. For example, in a couple with a pathogenic BRCA1 variant, we predicted a 15-fold difference in odds ratio (OR) across siblings when combining versus a 4.5-fold or 3-fold difference with BRCA1 or PRS alone. Our findings may inform the discussion of utility and implementation of genome-based PGT in clinical practice. Nature Publishing Group US 2022-03-21 2022 /pmc/articles/PMC8938270/ /pubmed/35314819 http://dx.doi.org/10.1038/s41591-022-01735-0 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Kumar, Akash Im, Kate Banjevic, Milena Ng, Pauline C. Tunstall, Tate Garcia, Geronimo Galhardo, Luisa Sun, Jiayi Schaedel, Oren N. Levy, Brynn Hongo, Donna Kijacic, Dusan Kiehl, Michelle Tran, Nam D. Klatsky, Peter C. Rabinowitz, Matthew Whole-genome risk prediction of common diseases in human preimplantation embryos |
title | Whole-genome risk prediction of common diseases in human preimplantation embryos |
title_full | Whole-genome risk prediction of common diseases in human preimplantation embryos |
title_fullStr | Whole-genome risk prediction of common diseases in human preimplantation embryos |
title_full_unstemmed | Whole-genome risk prediction of common diseases in human preimplantation embryos |
title_short | Whole-genome risk prediction of common diseases in human preimplantation embryos |
title_sort | whole-genome risk prediction of common diseases in human preimplantation embryos |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8938270/ https://www.ncbi.nlm.nih.gov/pubmed/35314819 http://dx.doi.org/10.1038/s41591-022-01735-0 |
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