Advertisement

Metabolomics

, 14:51 | Cite as

Hyper response to ovarian stimulation affects the follicular fluid metabolomic profile of women undergoing IVF similarly to polycystic ovary syndrome

  • Fernanda Bertuccez Cordeiro
  • Thaís Regiani Cataldi
  • Beatriz Zappellini de Souza
  • Raquel Cellin Rochetti
  • Renato Fraietta
  • Carlos Alberto Labate
  • Edson Guimarães Lo Turco
Original Article

Abstract

Introduction

During in vitro fertilization (IVF), the hyper response to controlled ovarian stimulation (COS) is a common characteristic among patients diagnosed with polycystic ovary syndrome (PCOS), although non-diagnosed patients may also demonstrate this response.

Objectives

In an effort to investigate follicular metabolic characteristics associated with hyper response to COS, the present study analyzed follicular fluid (FF) samples from patients undergoing IVF.

Methods

FF samples were obtained from patients with PCOS and hyper response during IVF (PCOS group, N = 15), patients without PCOS but with hyper response during IVF (HR group, N = 44), and normo-responder patients receiving IVF (control group, N = 22). FF samples underwent Bligh and Dyer extraction, followed by metabolomic analysis by ultra-performance liquid chromatography mass spectrometry, considering two technical replicates. Clinical data was analyzed by ANOVA and chi-square tests. The metabolomic dataset was analyzed by multivariate statistics, and the significance of biomarkers was confirmed by ANOVA.

Results

Clinical data showed differences regarding follicles production, oocyte and embryo quality. From the 15 proposed biomarkers, 14 were of increased abundance in the control group and attributed as fatty acids, diacylglycerol, triacylglycerol, ceramide, ceramide-phosphate, phosphatidylcholine, and sphingomyelin. The PCOS patients showed increased abundance of a metabolite of m/z 144.0023 that was not attributed to a class.

Conclusion

The clinical and metabolic similarities observed in the FF of hyper responders with and without PCOS diagnosis indicate common biomarkers that could assist on the development of accessory tools for assessment of IVF parameters.

Keywords

Polycystic ovary syndrome Hyper response Controlled ovarian stimulation Mtabolomics Mass Spectrometry 

Notes

Acknowledgements

This study was supported by the Sao Paulo Research Foundation (FAPESP—grant 06389-4) and by the National Council for Scientific and Technological Development (Cnpq—Brazil). The authors would like to thank Suzannah Colt for English edition of the manuscript.

Compliance with ethical standards

Conflict of interest

The authors declare no conflicts of interest.

Ethical approval

The authors comply with Springer’s Ethical Policies. The study received approval by the Ethics in Research Committee of São Paulo Federal University under protocol 1089/2015.

Informed consent

Informed consent was obtained from all individual participants included in the study.

Supplementary material

11306_2018_1350_MOESM1_ESM.pdf (113 kb)
Supplementary material 1 (PDF 113 KB)

References

  1. Beall, S. A., & DeCherney, A. (2012). History and challenges surrounding ovarian stimulation in the treatment of infertility. Fertility Sterility, 97, 795–801.CrossRefPubMedPubMedCentralGoogle Scholar
  2. Belosi, C., Selvaggi, L., Apa, R., Guido, M., Romualdi, D., Fulghesu, A. M., & Lanzone, A. (2006). Is the PCOS diagnosis solved by ESHRE/ASRM 2003 consensus or could it include ultrasound examination of the ovarian stroma? Human Reproduction, 21, 3108–3115.CrossRefPubMedGoogle Scholar
  3. Bligh, E. G., & Dyer, W. J. (1959). A rapid method of total lipid extraction and purification. Canadian Journal of Biochemistry and Physiology, 37, 911–917.CrossRefPubMedGoogle Scholar
  4. Bou Khalil, M., Hou, W., Zhou, H., Elisma, F., Swayne, L. A., Blanchard, A. P., et al. (2010). Lipidomics era: Accomplishments and challenges. Mass Spectrometry Reviews, 29, 877–929.CrossRefPubMedGoogle Scholar
  5. Brassard, M., AinMelk, Y., & Baillargeon, J. P. (2008). Basic infertility including polycystic ovary syndrome. Medical Clinics of North America, 92, 1163–1192.CrossRefPubMedGoogle Scholar
  6. Carmona-Ruiz, I. O., Saucedo-de la Llata, E., Moraga-Sánchez, M. R., & Romeu-Sarró, A. (2015). Polycystic ovary syndrome: Is there a rise in the prevalence? Ginecologia y Obstetricia de Mexico, 83, 750–759.PubMedGoogle Scholar
  7. Cela, V., Obino, M. E. R., Alberga, Y., Pinelli, S., Sergiampietri, C., Casarosa, E., et al. (2017). Ovarian response to controlled ovarian stimulation in women with different polycystic ovary syndrome phenotypes. Gynecological Endocrinology, 22, 1–6.CrossRefGoogle Scholar
  8. Chen, Y., Ye, B., Yang, X., Zheng, J., Lin, J., & Zhao, J. (2017). Predicting the outcome of different protocols of in vitro fertilization with anti-Muüllerian hormone levels in patients with polycystic ovary syndrome. Journal of International Medical Research, 45, 1138–1147.CrossRefPubMedPubMedCentralGoogle Scholar
  9. Cordeiro, F. B., Cataldi, T. R., da Costa, L. V. T., de Lima, C. B., Stevanato, J., Zylbersztejn, D. S., et al. (2015). Follicular fluid lipid fingerprinting from women with PCOS and hyper response during IVF treatment. Journal of Assisted Reproduction and Genetics, 32, 45–54.CrossRefPubMedGoogle Scholar
  10. Cordeiro, F. B., Cataldi, T. R., da Costa, L. V. T., de Souza, B. Z., Montani, D. A., Fraietta, R., et al. (2017a). Metabolomic profiling in follicular fluid of patients with infertility-related deep endometriosis. Metabolomics, 13, 120.CrossRefGoogle Scholar
  11. Cordeiro, F. B., Ferreira, C. R., Sobreira, T. J. P., Yannell, K. E., Jarmusch, A. K., Cedenho, A. P., et al. (2017b). Multiple reaction monitoring (MRM)-profiling for biomarker discovery applied to human polycystic ovarian syndrome. Rapid Communications in Mass Spectrometry, 31, 1462–1470.CrossRefPubMedGoogle Scholar
  12. Ellenbogen, A., Shavit, T., & Shalom-Paz, E. (2014). IVM results are comparable and may have advantages over standard IVF. Facts, Views & Vision in ObGyn, 6, 77–80.Google Scholar
  13. Fauser, B. C., Pache, T. D., Lamberts, S. W., Hop, W. C., de Jong, F. H., & Dahl, K. D. (1991). Serum bioactive and immunoreactive LH and FSH levels in women with cycle abnormalities, with or without PCOD. Journal of Clinical Endocrinology and Metabolism, 73, 811–817.CrossRefPubMedGoogle Scholar
  14. Gervais, A., Battista, M. C., Carranza-Mamane, B., Lavoie, H. B., & Baillargeon, J. P. (2015). Follicular fluid concentrations of lipids and their metabolites are associated with intraovarian gonadotropin-stimulated androgen production in women undergoing in vitro fertilization. Journal of Clinical Endocrinology and Metabolism, 100, 1845–1854.CrossRefPubMedGoogle Scholar
  15. Karnovsky, A., Weymouth, T., Hull, T., Tarcea, V. G., Scardoni, G., Laudanna, C., et al. (2011). Metscape 2 bioinformatics tool for the analysis and visualization of metabolomics and gene expression data. Bioinformatics, 28, 373–380.CrossRefPubMedPubMedCentralGoogle Scholar
  16. Krishnan, A., & Muthusami, S. (2017). Hormonal alterations in PCOS and its influence on bone metabolism. Journal of Endocrinology, 232, 99–113.CrossRefGoogle Scholar
  17. Lucki, N. C., & Sewer, M. B. (2010). The interplay between bioactive sphingolipids and steroid hormones. Steroids, 75, 390–399.CrossRefPubMedPubMedCentralGoogle Scholar
  18. March, W. A., Moore, V. M., Willson, K. J., Phillips, D. I., Norman, R. J., & Davies, M. J. (2010). The prevalence of polycystic ovary syndrome in a community sample assessed under contrasting diagnostic criteria. Human Reproduction, 25, 544–551.CrossRefPubMedGoogle Scholar
  19. McRae, C., Sharma, V., & Fisher, J. (2013). Metabolite profiling in the pursuit of biomarkers for IVF outcome: The case for metabolomics studies. International Journal of Reproductive Medicine.  https://doi.org/10.1155/2013/603167.PubMedPubMedCentralGoogle Scholar
  20. Montani, D. A., Cordeiro, F. B., Regiani, T., Victorino, A. B., Pilau, E. J., Gozzo, F. C., et al. (2012). The follicular microenviroment as a predictor of pregnancy: MALDI-TOF MS lipid profile in cumulus cells. Journal of Assisted Reproduction and Genetics, 29, 1289–1297.CrossRefPubMedPubMedCentralGoogle Scholar
  21. Mourad, S., Brown, J., & Farquhar, C. (2017). Interventions for the prevention of OHSS in ART cycles: An overview of Cochrane reviews. Cochrane Database of Systematic Reviews, 23, CD012103.Google Scholar
  22. O’Gorman, A., Wallace, M., Cottell, E., Gibney, M. J., McAuliffe, F. M., Wingfield, M., & Brennan, L. (2013). Metabolic profiling of human follicular fluid identifies potential biomarkers of oocyte developmental competence. Reproduction, 146, 389–395.CrossRefPubMedGoogle Scholar
  23. Practice Committee of the American Society for Reproductive Medicine. (2006). Ovarian hyperstimulation syndrome. Fertility and Sterility, 86, 178–183.Google Scholar
  24. Rotterdam ESHRE/ASRM-Sponsored PCOS Consensus Workshop Group. (2004). Revised 2003 consensus on diagnostic criteria and long-term health risks related to polycystic ovary syndrome (PCOS). Human Reproduction, 19, 41–47.CrossRefGoogle Scholar
  25. Snyder, N. W., Khezam, M., Mesaros, C. A., Worth, A., & Blair, I. A. (2013). Untargeted metabolomics from biological sources using ultraperformance liquid chromatography-high resolution mass spectrometry (UPLC-HRMS). Journal of Visualized Experiments, 20, e50433.Google Scholar
  26. Tan, T. Y., Lau, S. K., Loh, S. F., & Tan, H. H. (2014). Female ageing and reproductive outcome in assisted reproduction cycles. Singapore Medical Journal, 55(6), 305–309.CrossRefPubMedPubMedCentralGoogle Scholar
  27. Tarlatzis, B. C., Grimbizis, G., Pournaropoulos, F., Bontis, J., Lagos, S., Spanos, E., & Mantalenakis, S. (1995). The prognostic value of basal luteinizing hormone: Follicle-stimulating hormone ratio in the treatment of patients with polycystic ovarian syndrome by assisted reproduction techniques. Human Reproduction, 10(10), 2545–2549.CrossRefPubMedGoogle Scholar
  28. Vieira, R. C., Barcelos, I. D., Ferreira, E. M., de Araújo, M. C., dos Reis, R. M., Ferriani, R. A., & Navarro, P. A. (2008). Evaluation of meiotic abnormalities of oocytes from polycystic ovary syndrome patients submitted to ovarian stimulation. Revista Brasileira de Ginecologia e Obstetrícia, 30, 241–247.PubMedGoogle Scholar
  29. Webber, L. J., Stubbs, S., Stark, J., Trew, G. H., Margara, R., Hardy, K., & Franks, S. (2003). Formation and early development of follicles in the polycystic ovary. The Lancet, 27, 1017–1021.CrossRefGoogle Scholar
  30. Wishart, D. S. (2005). Metabolomics: The principles and potential applications to transplantation. American Journal of Transplantation, 5, 2814–2820.CrossRefPubMedGoogle Scholar
  31. Xia, J., & Wishart, D. S. (2016). Using MetaboAnalyst 3.0 for comprehensive metabolomics data analysis. Current Protocols in Bioinformatics, 7, 14.10.1–14.10.91.CrossRefGoogle Scholar
  32. Zhao, Y., Fu, L., Li, R., Wang, L. N., Yang, Y., Liu, N. N., et al. (2012). Metabolic profiles characterizing different phenotypes of polycystic ovary syndrome: Plasma metabolomics analysis. BMC Medicine, 10, 153.CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Fernanda Bertuccez Cordeiro
    • 1
  • Thaís Regiani Cataldi
    • 2
  • Beatriz Zappellini de Souza
    • 1
  • Raquel Cellin Rochetti
    • 1
  • Renato Fraietta
    • 1
  • Carlos Alberto Labate
    • 2
  • Edson Guimarães Lo Turco
    • 1
  1. 1.Human Reproduction Section, Division of Urology, Department of SurgerySao Paulo Federal UniversitySão PauloBrazil
  2. 2.Laboratório Max Feffer de Genética de Plantas, Departamento de Genética, Escola Superior de Agricultura Luiz de QueirozUniversidade de São PauloPiracicabaBrazil

Personalised recommendations