Cargando…
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...
Autores principales: | , , , , , , , , |
---|---|
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 |
_version_ | 1785055532780879872 |
---|---|
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. |
format | Online Article Text |
id | pubmed-10249307 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT liangrong predictionmodelforday3embryoimplantationpotentialbasedonmetabolitesinspentembryoculturemedium AT duanshengnan predictionmodelforday3embryoimplantationpotentialbasedonmetabolitesinspentembryoculturemedium AT fumin predictionmodelforday3embryoimplantationpotentialbasedonmetabolitesinspentembryoculturemedium AT chenyunan predictionmodelforday3embryoimplantationpotentialbasedonmetabolitesinspentembryoculturemedium AT wangping predictionmodelforday3embryoimplantationpotentialbasedonmetabolitesinspentembryoculturemedium AT fanyuan predictionmodelforday3embryoimplantationpotentialbasedonmetabolitesinspentembryoculturemedium AT mengshihui predictionmodelforday3embryoimplantationpotentialbasedonmetabolitesinspentembryoculturemedium AT chenxi predictionmodelforday3embryoimplantationpotentialbasedonmetabolitesinspentembryoculturemedium AT shicheng predictionmodelforday3embryoimplantationpotentialbasedonmetabolitesinspentembryoculturemedium |