Prediction model for day 3 embryo implantation potential based on metabolites in spent embryo culture medium.
Human day 3 embryos
Implantation prediction
LC-MS
Metabolomics
Spent embryo culture medium
Journal
BMC pregnancy and childbirth
ISSN: 1471-2393
Titre abrégé: BMC Pregnancy Childbirth
Pays: England
ID NLM: 100967799
Informations de publication
Date de publication:
08 Jun 2023
08 Jun 2023
Historique:
received:
02
12
2022
accepted:
30
04
2023
medline:
12
6
2023
pubmed:
9
6
2023
entrez:
8
6
2023
Statut:
epublish
Résumé
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. 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. 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. 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.
Sections du résumé
BACKGROUND
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
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
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
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.
Identifiants
pubmed: 37291503
doi: 10.1186/s12884-023-05666-7
pii: 10.1186/s12884-023-05666-7
pmc: PMC10249307
doi:
Substances chimiques
Culture Media
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
425Subventions
Organisme : Beijing Natural Science Foundation
ID : 7222200 and 7222197
Organisme : the Chinese Medical Association Special funding Project for Clinical Medical Scientific Research
ID : 17020530722
Informations de copyright
© 2023. The Author(s).
Références
J Assist Reprod Genet. 2012 Dec;29(12):1435-42
pubmed: 23090745
Hum Reprod. 2016 Jan;31(1):199-208
pubmed: 26637492
Int J Endocrinol. 2022 Mar 12;2022:6368678
pubmed: 35313456
Hum Reprod Open. 2021 Aug 05;2021(3):hoab026
pubmed: 34377841
Reprod Sci. 2020 Dec;27(12):2271-2278
pubmed: 32840740
Pol J Vet Sci. 2019 Dec;22(4):661-666
pubmed: 31867919
Turk J Obstet Gynecol. 2017 Sep;14(3):145-150
pubmed: 29085702
Fertil Steril. 2021 Mar;115(3):627-637
pubmed: 32863013
Methods Mol Biol. 2021;2228:85-116
pubmed: 33950486
Hum Reprod. 2012 Aug;27(8):2304-11
pubmed: 22647453
Analyst. 2021 Oct 11;146(20):6156-6169
pubmed: 34515271
Int J Mol Sci. 2022 Feb 28;23(5):
pubmed: 35269848
J Biomed Opt. 2013 Dec;18(12):127003
pubmed: 24343445
Int J Mol Sci. 2021 Mar 03;22(5):
pubmed: 33802374
Int J Mol Sci. 2013 Mar 25;14(4):6556-70
pubmed: 23528887
Front Mol Biosci. 2022 Sep 08;9:952149
pubmed: 36158581
NMR Biomed. 2021 Aug;34(8):e4536
pubmed: 33955062
Biol Reprod. 2011 Jul;85(1):62-9
pubmed: 21311036
Methods Mol Biol. 2020;2104:149-163
pubmed: 31953817
Syst Biol Reprod Med. 2014 Feb;60(1):58-63
pubmed: 24261874
Hum Reprod Update. 2017 Nov 1;23(6):723-736
pubmed: 29069503
Hum Reprod. 2006 Mar;21(3):766-73
pubmed: 16311299
Reproduction. 2013 Apr 29;145(5):453-62
pubmed: 23404850
J Assist Reprod Genet. 2023 Mar;40(3):665-669
pubmed: 36690879
Reprod Biol Endocrinol. 2022 Apr 19;20(1):68
pubmed: 35439999