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Dehydroepiandrosterone supplementation and the impact of follicular fluid metabolome and cytokinome profiles in poor ovarian responders

BACKGROUND: Poor ovarian responders (POR) are women undergoing in-vitro fertilization who respond poorly to ovarian stimulation, resulting in the retrieval of lower number of oocytes, and subsequently lower pregnancy rates. The follicular fluid (FF) provides a crucial microenvironment for the proper...

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Autores principales: Viardot-Foucault, Veronique, Zhou, Jieliang, Bi, Dexi, Takinami, Yoshihiko, Chan, Jerry. K. Y., Lee, Yie Hou
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10239139/
https://www.ncbi.nlm.nih.gov/pubmed/37268990
http://dx.doi.org/10.1186/s13048-023-01166-6
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author Viardot-Foucault, Veronique
Zhou, Jieliang
Bi, Dexi
Takinami, Yoshihiko
Chan, Jerry. K. Y.
Lee, Yie Hou
author_facet Viardot-Foucault, Veronique
Zhou, Jieliang
Bi, Dexi
Takinami, Yoshihiko
Chan, Jerry. K. Y.
Lee, Yie Hou
author_sort Viardot-Foucault, Veronique
collection PubMed
description BACKGROUND: Poor ovarian responders (POR) are women undergoing in-vitro fertilization who respond poorly to ovarian stimulation, resulting in the retrieval of lower number of oocytes, and subsequently lower pregnancy rates. The follicular fluid (FF) provides a crucial microenvironment for the proper development of follicles and oocytes through tightly controlled metabolism and cell signaling. Androgens such as dehydroepiandrosterone (DHEA) have been proposed to alter the POR follicular microenvironment, but the impact DHEA imposes on the FF metabolome and cytokine profiles is unknown. Therefore, the objective of this study is to profile and identify metabolomic changes in the FF with DHEA supplementation in POR patients. METHODS: FF samples collected from 52 POR patients who underwent IVF with DHEA supplementation (DHEA +) and without (DHEA-; controls) were analyzed using untargeted liquid chromatography-tandem mass spectrometry (LC–MS/MS) metabolomics and a large-scale multiplex suspension immunoassay covering 65 cytokines, chemokines and growth factors. Multivariate statistical modelling by partial least squares-discriminant regression (PLSR) analysis was performed for revealing metabolome-scale differences. Further, differential metabolite analysis between the two groups was performed by PLSR β-coefficient regression analysis and Student’s t-test. RESULTS: Untargeted metabolomics identified 118 FF metabolites of diverse chemistries and concentrations which spanned three orders of magnitude. They include metabolic products highly associated with ovarian function – amino acids for regulating pH and osmolarity, lipids such fatty acids and cholesterols for oocyte maturation, and glucocorticoids for ovarian steroidogenesis. Four metabolites, namely, glycerophosphocholine, linoleic acid, progesterone, and valine were significantly lower in DHEA + relative to DHEA- (p < 0.05–0.005). The area under the curves of progesterone glycerophosphocholine, linoleic acid and valine are 0.711, 0.730, 0.785 and 0.818 (p < 0.05–0.01). In DHEA + patients, progesterone positively correlated with IGF-1 (Pearson r: 0.6757, p < 0.01); glycerophosphocholine negatively correlated with AMH (Pearson r: -0.5815; p < 0.05); linoleic acid correlated with estradiol and IGF-1 (Pearson r: 0.7016 and 0.8203, respectively; p < 0.01 for both). In DHEA- patients, valine negatively correlated with serum-free testosterone (Pearson r: -0.8774; p < 0.0001). Using the large-scale immunoassay of 45 cytokines, we observed significantly lower MCP1, IFNγ, LIF and VEGF-D levels in DHEA + relative to DHEA. CONCLUSIONS: In POR patients, DHEA supplementation altered the FF metabolome and cytokine profile. The identified four FF metabolites that significantly changed with DHEA may provide information for titrating and monitoring individual DHEA supplementation. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13048-023-01166-6.
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spelling pubmed-102391392023-06-04 Dehydroepiandrosterone supplementation and the impact of follicular fluid metabolome and cytokinome profiles in poor ovarian responders Viardot-Foucault, Veronique Zhou, Jieliang Bi, Dexi Takinami, Yoshihiko Chan, Jerry. K. Y. Lee, Yie Hou J Ovarian Res Research BACKGROUND: Poor ovarian responders (POR) are women undergoing in-vitro fertilization who respond poorly to ovarian stimulation, resulting in the retrieval of lower number of oocytes, and subsequently lower pregnancy rates. The follicular fluid (FF) provides a crucial microenvironment for the proper development of follicles and oocytes through tightly controlled metabolism and cell signaling. Androgens such as dehydroepiandrosterone (DHEA) have been proposed to alter the POR follicular microenvironment, but the impact DHEA imposes on the FF metabolome and cytokine profiles is unknown. Therefore, the objective of this study is to profile and identify metabolomic changes in the FF with DHEA supplementation in POR patients. METHODS: FF samples collected from 52 POR patients who underwent IVF with DHEA supplementation (DHEA +) and without (DHEA-; controls) were analyzed using untargeted liquid chromatography-tandem mass spectrometry (LC–MS/MS) metabolomics and a large-scale multiplex suspension immunoassay covering 65 cytokines, chemokines and growth factors. Multivariate statistical modelling by partial least squares-discriminant regression (PLSR) analysis was performed for revealing metabolome-scale differences. Further, differential metabolite analysis between the two groups was performed by PLSR β-coefficient regression analysis and Student’s t-test. RESULTS: Untargeted metabolomics identified 118 FF metabolites of diverse chemistries and concentrations which spanned three orders of magnitude. They include metabolic products highly associated with ovarian function – amino acids for regulating pH and osmolarity, lipids such fatty acids and cholesterols for oocyte maturation, and glucocorticoids for ovarian steroidogenesis. Four metabolites, namely, glycerophosphocholine, linoleic acid, progesterone, and valine were significantly lower in DHEA + relative to DHEA- (p < 0.05–0.005). The area under the curves of progesterone glycerophosphocholine, linoleic acid and valine are 0.711, 0.730, 0.785 and 0.818 (p < 0.05–0.01). In DHEA + patients, progesterone positively correlated with IGF-1 (Pearson r: 0.6757, p < 0.01); glycerophosphocholine negatively correlated with AMH (Pearson r: -0.5815; p < 0.05); linoleic acid correlated with estradiol and IGF-1 (Pearson r: 0.7016 and 0.8203, respectively; p < 0.01 for both). In DHEA- patients, valine negatively correlated with serum-free testosterone (Pearson r: -0.8774; p < 0.0001). Using the large-scale immunoassay of 45 cytokines, we observed significantly lower MCP1, IFNγ, LIF and VEGF-D levels in DHEA + relative to DHEA. CONCLUSIONS: In POR patients, DHEA supplementation altered the FF metabolome and cytokine profile. The identified four FF metabolites that significantly changed with DHEA may provide information for titrating and monitoring individual DHEA supplementation. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13048-023-01166-6. BioMed Central 2023-06-02 /pmc/articles/PMC10239139/ /pubmed/37268990 http://dx.doi.org/10.1186/s13048-023-01166-6 Text en © The Author(s) 2023 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 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
Viardot-Foucault, Veronique
Zhou, Jieliang
Bi, Dexi
Takinami, Yoshihiko
Chan, Jerry. K. Y.
Lee, Yie Hou
Dehydroepiandrosterone supplementation and the impact of follicular fluid metabolome and cytokinome profiles in poor ovarian responders
title Dehydroepiandrosterone supplementation and the impact of follicular fluid metabolome and cytokinome profiles in poor ovarian responders
title_full Dehydroepiandrosterone supplementation and the impact of follicular fluid metabolome and cytokinome profiles in poor ovarian responders
title_fullStr Dehydroepiandrosterone supplementation and the impact of follicular fluid metabolome and cytokinome profiles in poor ovarian responders
title_full_unstemmed Dehydroepiandrosterone supplementation and the impact of follicular fluid metabolome and cytokinome profiles in poor ovarian responders
title_short Dehydroepiandrosterone supplementation and the impact of follicular fluid metabolome and cytokinome profiles in poor ovarian responders
title_sort dehydroepiandrosterone supplementation and the impact of follicular fluid metabolome and cytokinome profiles in poor ovarian responders
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10239139/
https://www.ncbi.nlm.nih.gov/pubmed/37268990
http://dx.doi.org/10.1186/s13048-023-01166-6
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