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Prediction model for day 3 embryo implantation potential based on metabolites in spent embryo culture medium

BACKGROUND: Metabolites in spent embryo culture medium correlate with the embryo’s viability. However, there is no widely accepted method using metabolite dada to predict successful implantation. We sought to combine metabolomic profiling of spent embryo culture medium and clinical variables to crea...

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Autores principales: Liang, Rong, Duan, Sheng Nan, Fu, Min, Chen, Yu Nan, Wang, Ping, Fan, Yuan, Meng, Shihui, Chen, Xi, Shi, Cheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10249307/
https://www.ncbi.nlm.nih.gov/pubmed/37291503
http://dx.doi.org/10.1186/s12884-023-05666-7
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author Liang, Rong
Duan, Sheng Nan
Fu, Min
Chen, Yu Nan
Wang, Ping
Fan, Yuan
Meng, Shihui
Chen, Xi
Shi, Cheng
author_facet Liang, Rong
Duan, Sheng Nan
Fu, Min
Chen, Yu Nan
Wang, Ping
Fan, Yuan
Meng, Shihui
Chen, Xi
Shi, Cheng
author_sort Liang, Rong
collection PubMed
description BACKGROUND: Metabolites in spent embryo culture medium correlate with the embryo’s viability. However, there is no widely accepted method using metabolite dada to predict successful implantation. We sought to combine metabolomic profiling of spent embryo culture medium and clinical variables to create an implantation prediction model as an adjunct to morphological screening of day 3 embryos. METHODS: This investigation was a prospective, nested case-control study. Forty-two day 3 embryos from 34 patients were transferred, and the spent embryo culture medium was collected. Twenty-two embryos implanted successfully, and the others failed. Metabolites in the medium relevant to implantation were detected and measured by Liquid Chromatography-Mass Spectrometry. Clinical signatures relevant to embryo implantation were subjected to univariate analysis to select candidates for a prediction model. Multivariate logistical regression of the clinical and metabolomic candidates was used to construct a prediction model for embryo implantation potential. RESULTS: The levels of 13 metabolites were significantly different between the successful and failed groups, among which five were most relevant and interpretable selected by Least Absolute Shrinkage and Selection Operator regression analysis. None of the clinical variables significantly affected day 3 embryo implantation. The most relevant and interpretable set of metabolites was used to construct a prediction model for day 3 embryo implantation potential with an accuracy of 0.88. CONCLUSIONS: Day 3 embryos’implantation potential could be noninvasively predicted by the spent embryo culture medium’s metabolites measured by LC-MS. This approach may become a useful adjunct to morphological evaluation of day 3 embryos. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12884-023-05666-7.
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spelling pubmed-102493072023-06-09 Prediction model for day 3 embryo implantation potential based on metabolites in spent embryo culture medium Liang, Rong Duan, Sheng Nan Fu, Min Chen, Yu Nan Wang, Ping Fan, Yuan Meng, Shihui Chen, Xi Shi, Cheng BMC Pregnancy Childbirth Research BACKGROUND: Metabolites in spent embryo culture medium correlate with the embryo’s viability. However, there is no widely accepted method using metabolite dada to predict successful implantation. We sought to combine metabolomic profiling of spent embryo culture medium and clinical variables to create an implantation prediction model as an adjunct to morphological screening of day 3 embryos. METHODS: This investigation was a prospective, nested case-control study. Forty-two day 3 embryos from 34 patients were transferred, and the spent embryo culture medium was collected. Twenty-two embryos implanted successfully, and the others failed. Metabolites in the medium relevant to implantation were detected and measured by Liquid Chromatography-Mass Spectrometry. Clinical signatures relevant to embryo implantation were subjected to univariate analysis to select candidates for a prediction model. Multivariate logistical regression of the clinical and metabolomic candidates was used to construct a prediction model for embryo implantation potential. RESULTS: The levels of 13 metabolites were significantly different between the successful and failed groups, among which five were most relevant and interpretable selected by Least Absolute Shrinkage and Selection Operator regression analysis. None of the clinical variables significantly affected day 3 embryo implantation. The most relevant and interpretable set of metabolites was used to construct a prediction model for day 3 embryo implantation potential with an accuracy of 0.88. CONCLUSIONS: Day 3 embryos’implantation potential could be noninvasively predicted by the spent embryo culture medium’s metabolites measured by LC-MS. This approach may become a useful adjunct to morphological evaluation of day 3 embryos. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12884-023-05666-7. BioMed Central 2023-06-08 /pmc/articles/PMC10249307/ /pubmed/37291503 http://dx.doi.org/10.1186/s12884-023-05666-7 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Liang, Rong
Duan, Sheng Nan
Fu, Min
Chen, Yu Nan
Wang, Ping
Fan, Yuan
Meng, Shihui
Chen, Xi
Shi, Cheng
Prediction model for day 3 embryo implantation potential based on metabolites in spent embryo culture medium
title Prediction model for day 3 embryo implantation potential based on metabolites in spent embryo culture medium
title_full Prediction model for day 3 embryo implantation potential based on metabolites in spent embryo culture medium
title_fullStr Prediction model for day 3 embryo implantation potential based on metabolites in spent embryo culture medium
title_full_unstemmed Prediction model for day 3 embryo implantation potential based on metabolites in spent embryo culture medium
title_short Prediction model for day 3 embryo implantation potential based on metabolites in spent embryo culture medium
title_sort prediction model for day 3 embryo implantation potential based on metabolites in spent embryo culture medium
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10249307/
https://www.ncbi.nlm.nih.gov/pubmed/37291503
http://dx.doi.org/10.1186/s12884-023-05666-7
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