Abstract
Introduction
Several metabolomics studies have correlated follicular fluid (FF) metabolite composition with oocyte competence to fertilization, embryo development and pregnancy but there is a scarcity of research examining the metabolic effects of various gynaecological diseases.
Objectives
In this study we aimed to analyze and correlate the metabolic profile of FF from women who were following in vitro fertilization (IVF) treatments with their different infertility pathologies.
Methods
We selected 53 women undergoing IVF who were affected by: tubal diseases, unexplained infertility, endometriosis, polycystic ovary syndrome (PCOS). FF of the study participants was collected at the time of oocytes retrieval. Metabolomic analysis of FF was performed by nuclear magnetic resonance (NMR) spectroscopy.
Results
FF presents some significant differences in various infertility pathologies. Although it was not possible to discriminate between FF of control participants and women with tubal diseases and unexplained infertility, comparison of FF metabolic profile from control women with patients with endometriosis and PCOS revealed significant differences in some metabolites that can be correlated to the causes of infertility.
Conclusion
NMR-based metabolic profiling may be successfully applied to find diagnostic biomarkers for PCOS and endometriosis and it might be also used to predict oocyte developmental potential and subsequent outcome.
Similar content being viewed by others
References
Ahn, S. H., Singh, V., & Tayade, C. (2017). Biomarkers in endometriosis: Challenges and opportunities. Fertility and Sterility, 107(3), 523–532. https://doi.org/10.1016/j.fertnstert.2017.01.009.
Arya, B. K., Haq, U., A., & Chaudhury, K. (2012). Oocyte quality reflected by follicular fluid analysis in polycystic ovary syndrome (PCOS): A hypothesis based on intermediates of energy metabolism. Medical Hypotheses, 78(4), 475–478. https://doi.org/10.1016/j.mehy.2012.01.009.
Azziz, R. (2004). PCOS: a diagnostic challenge. Reproductive BioMedicine Online, 8(6), 644–648. https://doi.org/10.1016/S1472-6483(10)61644-6.
Beckonert, O., Keun, H. C., Ebbels, T. M. D., Bundy, J., Holmes, E., Lindon, J. C., et al. (2007). Metabolic profiling, metabolomic and metabonomic procedures for NMR spectroscopy of urine, plasma, serum and tissue extracts. Nature Protocols. 2(11), 2692–2703. https://doi.org/10.1038/nprot.2007.376
Bracewell-Milnes, T., Saso, S., Abdalla, H., Nikolau, D., Norman-Taylor, J., Johnson, M., et al. (2017). Metabolomics as a tool to identify biomarkers to predict and improve outcomes in reproductive medicine: A systematic review. Human Reproduction Update, 23(6), 723–736. https://doi.org/10.1093/humupd/dmx023.
Bulun, S. E. (2009). Endometriosis. New England Journal of Medicine, 360, 268–279. https://doi.org/10.1056/NEJMra0804690.
Castiglione Morelli, M. A. Iuliano, A., Schettini, S. C. A., Petruzzi, D., Ferri, A., Colucci, P., Viggiani, L., Cuviello, F., & Ostuni, A. (2018). NMR metabolomics study of follicular fluid in women with cancer resorting to fertility preservation. Journal of Assisted Reproduction and Genetics. https://doi.org/10.1007/s10815-018-1281-7.
Chen, Y. H., Heneidi, S., Lee, J. M., Layman, L. C., Stepp, D. W., Gamboa, G. M., et al. (2013). miRNA-93 inhibits GLUT4 and is over-expressed in adipose tissue of polycystic ovary syndrome patients and women with insulin resistance. Diabetes, 62(7), 2278–2286. https://doi.org/10.2337/db12-0963.
Cordeiro, F. B., Cataldi, T. R., Perkel, K. J.,, Rochetti, L., Stevanato, R. C., do Vale Teixeira da Costa J., et al (2015). Lipidomics analysis of follicular fluid by ESI-MS reveals potential biomarkers for ovarian endometriosis. Journal of Assisted Reproduction and Genetics, 32(12), 1817–1825. https://doi.org/10.1007/s10815-015-0592-1.
Dumesic, D. A., Oberfield, S. E., Stener-Victorin, E., Marshall, J. C., Laven, J. S., & Legro, R. S. (2015). Scientific statement on the diagnostic criteria, epidemiology, pathophysiology, and molecular genetics of polycystic ovary syndrome. Endocrine Reviews, 36(5), 487–525. https://doi.org/10.1210/er.2015-1018.
Dun, E. C., & Nezhat, C. H. (2012). Tubal factor: diagnosis and management in the era of assisted reproductive technology. Obstetrics and Gynecology Clinics of North America, 39, 551–566. https://doi.org/10.1016/j.ogc.2012.09.006.
Dutta, M., Joshi, M., Srivastava, S., Lodh, I., Chakravarty, B., & Chaudhury, K. (2012). A metabonomics approach as a means for identification of potential biomarkers for early diagnosis of endometriosis. Molecular BioSystems, 8, 3281–3287. https://doi.org/10.1039/c2mb25353d.
Emwas, A. H., Luchinat, C., Turano, P., Tenori, L., Roy, R., Salek, R. M., et al. (2015). Standardizing the experimental conditions for using urine in NMR-based metabolomics studies with a particular focus on diagnostic studies: A review. Metabolomics, 11, 872–894. https://doi.org/10.1007/s11306-014-0746-7.
Engmann, L., Maconochie, N., Sladkevicius, P., Bekir, J., Campbell, S., & Tan, S. L. (1999). The outcome of in-vitro fertilization treatment in women with sonographic evidence of polycystic ovarian syndrome. Human Reproduction, 14(1), 167–171. https://doi.org/10.1093/humrep/14.1.167.
Fahiminiya, S., & Gérard, N. (2010). Le liquide folliculaire chez les mammifères. Gynécologie Obstétrique & Fertilité, 38, 402–404. https://doi.org/10.1016/j.gyobfe.2010.04.010.
Fassbender, A., Burney, R. O., Dorien, F. O., D’Hooghe, T., & Giudice, L. (2015). Update on biomarkers for the detection of endometriosis. Biomed Research International. https://doi.org/10.1155/2015/130854.
Hayek, S. E., Bitar, L., Hamdar, L. H., Mirza, F. G., & Daoud, G. (2016). Poly cystic ovarian syndrome: an updated overview. Frontiers in Physiology, 7, 124. https://doi.org/10.3389/fphys.2016.00124.
Karaer, A., Tuncay, G., Mumcu, A., & Dogan, B. (2018). Metabolomics analysis of follicular fluid in women with ovarian endometriosis undergoing in vitro fertilization. Systems Biology in Reproductive Medicine. https://doi.org/10.1080/19396368.2018.1478469.
Kirkegaard, K., Svane, A. S. P., Nielsen, J. S., Hindkjær, J. J., Nielsen, N. C., & Ingerslev, H. J. (2014). Nuclear magnetic resonance metabolic profiling of day 3 and 5 embryo culture medium does not predict pregnancy outcome in good prognosis patients: A prospective cohort study on single transferred embryos. Human Reproduction, 29(11), 2413–2420. https://doi.org/10.1093/humrep/deu236.
La Marca, A., Grisendi, V., Giulini, S., Argento, C., Tirelli, A., Dondi, G., et al. (2013). Individualization of the FSH starting dose in IVF/ICSI cycles using the antral follicle count. Journal of Ovarian Research, 6, 11. https://doi.org/10.1186/1757-2215-6-11.
Li, H. W., Lee, V. C., Lau, E. Y., Yeung, W. S., Ho, P. C., & Ng, E. H. (2014). Cumulative live-birth rate in women with polycystic ovary syndrome or isolated polycystic ovaries undergoing in-vitro fertilisation treatment. Journal of Assisted Reproduction and Genetics, 31(2), 205–211. https://doi.org/10.1007/s10815-013-0151-6.
Mamas, M., Dunn, W. B., Neyes, L., & Goodacre, R. (2011). The role of metabolites and metabolomics in clinically applicable biomarkers of disease. Archives of Toxicology, 85(1), 5–17. https://doi.org/10.1007/s00204-010-0609-6.
Markley, J. L., Brüschweiler, R., Edison, A. S., Eghbalnia, H. R., Powers, R., Raftery, D., et al. (2017). The future of NMR-based metabolomics. Current Opinion in Biotechnology, 43, 34–40. https://doi.org/10.1016/j.copbio.2016.08.001.
Matarese, G., De Placido, G., Nikas, Y., & Alviggi, C. (2003). Pathogenesis of endometriosis: Natural immunity dysfunction or autoimmune disease? Trends in Molecular Medicine, 9(5), 223–228. https://doi.org/10.1016/S1471-4914(03)00051-0.
May, K. E., Conduit-Hulbert, S. A., Villar, J., Kirtley, S., Kennedy, S. H., & Becker, C. M. (2010). Pheripheral biomarkers of endometriosis: A systematic review. Human Reproduction Update, 16(6), 651–674. https://doi.org/10.1093/humupd/dmq009.
McRae, C., Baskind, N. E., Orsi, N. M., Sharma, V., & Fisher, J. (2012). Metabolic profiling of follicular fluid and plasma from natural cycle in vitro fertilization patients-a pilot study. Fertility and Sterility, 98(6), 1449–1457. https://doi.org/10.1016/j.fertnstert.2012.07.1131.
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.
Murri, M., Insenser, M., & Escobar-Morreale, H. F. (2013). Metabolomics in polycystic ovary syndrome. Clinica Chimica Acta, 429, 181–188. https://doi.org/10.1016/j.cca.2013.12.018.
Nadal-Desbarats, L., Veau, S., Blasco, H., Emond, P., Royere, D., Andres, C. R., et al. (2013). Is NMR metabolic profiling of spent embryo culture media useful to assist in vitro human embryo selection? Magnetic Resonance Materials in Physics, Biology and Medicine, 26(2), 193–202. https://doi.org/10.1007/s10334-012-0331-x.
Nagana Gowda, G. A., Zhang, S., Gu, H., Asiago, V., Shanaiah, N., & Raftery, D. (2008). Metabolomics-based methods for early disease diagnostics: A review. Expert Review of Molecular Diagnostics, 8(5), 617–633. https://doi.org/10.1586/14737159.8.5.617.
Nel-Themaat, L., & Nagy, Z. P. (2011). A review of the promises and pitfalls of oocyte and embryo metabolomics. Placenta, 32, 257–263. https://doi.org/10.1016/j.placenta.2011.05.011.
O’Gorman, A., Wallace, M., Cottell, E., Gibney, M. J., McAuliffe, F. M., Wingfield, M., et al. (2013). Metabolic profiling of human follicular fluid identifies potential biomarkers of oocyte developmental competence. Reproduction, 146(4), 389–395. https://doi.org/10.1530/REP-13-0184.
Palomba, S., Daolio, J., & La Sala, G. B. (2017). Oocyte competence in women with polycystic ovary syndrome. Trends in Endocrinology and Metabolism, 28(3), 186–198. https://doi.org/10.1016/j.tem.2016.11.008.
Pan, J. X., Zhang, J. Y., Ke, Z. H., Wang, F. F., Barry, J. A., Hardiman, P. J., & Qu, F. (2015). Androgens as double-edged swords: Induction and suppression of follicular development. Hormones, 14(2), 190–200. https://doi.org/10.14310/horm.2002.1580.
Piñero-Sagredo, E., Nunes, S., de los Santos, M. J., Celda, B., & Esteve, V. (2010). NMR metabolic profile of human follicular fluid. NMR in Biomedicine, 23, 485–495. https://doi.org/10.1002/nbm.1488.
Ray, A., Shah, A., Gudi, A., & Homburg, R. (2012). Unexplained infertility: an update and review of practice. Reproductive Biomedicine Online, 24, 591–602. https://doi.org/10.1016/j.rbmo.2012.02.021.
Revelli, A., Delle Piane, L., Casano, S., Molinari, E., Massobrio, M., & Rinaudo, P. (2009). Follicular fluid content and oocyte quality: from single biochemical markers to metabolomics. Reproductive Biology and Endocrinology, 7, 40.
RoyChoudhury, S., Mishra, B. P., Khan, T., Chattopadhayay, R., Lodh, I., Ray, D., C., et al (2016). Serum metabolomics of Indian women with polycystic ovary syndrome using 1H NMR coupled with a pattern recognition approach. Molecular Biosystems, 12(11), 3407–3416. https://doi.org/10.1039/C6MB00420B.
Santonastaso, M., Pucciarelli, A., Costantini, S., Caprio, F., Sorice, A., Capone, F., et al. (2017). Metabolomic profiling and biochemical evaluation of the follicular fluid of endometriosis patients. Molecular Biosystems, 13, 1213–1222. https://doi.org/10.1039/C7MB00181A.
Singh, R., & Sinclair, K. D. (2007). Metabolomics: Approaches to assessing oocyte and embryo quality. Theriogenology, 68S, S56–62. https://doi.org/10.1016/j.theriogenology.2007.04.007.
The American Fertility Society. (1985). Revised American Fertility Society classification of endometriosis: 1985. Fertility and Sterility, 43, 351–352. https://doi.org/10.1016/S0015-0282(16)48430-X.
Wallace, M., Cottell, E., Gibney, M. J., McAuliffe, F. M., Wingfield, M., & Brennan, L. (2012). An investigation into the relationship between the metabolic profile of follicular fluid, oocyte developmental potential, and implantation outcome. Fertility and Sterility, 97(5), 1078–1084. https://doi.org/10.1016/j.fertnstert.2012.01.122.
Xia, L., Zhao, X., Sun, Y., Hong, Y., Gao, Y., & Hu, S. (2014). Metabolomic profiling of human follicular fluid from patients with repeated failure of in vitro fertilization using gas chromatography/mass spectrometry. International Journal of Clinical and Experimental Pathology, 7(10), 7220–7229.
Zhang, Y., Liu, L., Yin, T. L., Yang, J., & Xiong, C. L. (2017). Follicular metabolic changes and effects on oocyte quality in polycystic ovary syndrome patients. Oncotarget, 8(46), 80472–80480. https://doi.org/10.18632/oncotarget.
Zhao, H., Zhao, Y., Li, T., Li, M., Li, J., Li, R., et al. (2015). Metabolism alteration in follicular niche: The nexus among intermediary metabolism, mitochondrial function, and classic polycystic ovary syndrome. Free Radical Biology and Medicine, 86, 295–307. https://doi.org/10.1016/j.freeradbiomed.2015.05.013.
Zullo, F., Spagnolo, E., Saccone, G., Acunzo, M., Xodo, S., Ceccaroni, M., et al. (2017). Endometriosis and obstetrics complications: A systematic review and meta-analysis. Fertility and Sterility, 108(4), 667–672. https://doi.org/10.1016/j.fertnstert.2017.07.019.
Funding
The authors received no financial support for this study.
Author information
Authors and Affiliations
Contributions
SS, AI, and AO designed the study. AI selected the participants and executed oocyte retrieval. DP executed oocyte retrieval. AF identified oocytes in follicular fluid and executed their fertilization. PC selected the follicular fluids to be used for metabolomic analyses. CM performed the analysis of NMR data and multivariate analysis. LV run the NMR experiments. FC performed statistical analysis. AO, AI, and CM were responsible for conducting the study and writing the manuscript which was critically discussed, edited and approved by all co-authors.
Corresponding author
Ethics declarations
Conflict of interest
The authors declare no conflicts of interest.
Research involving human rights
All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional, national research committee and with the 1964 Helsinki Declaration and its later amendments.
Additional information
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Electronic supplementary material
Below is the link to the electronic supplementary material.
Rights and permissions
About this article
Cite this article
Castiglione Morelli, M.A., Iuliano, A., Schettini, S.C.A. et al. NMR metabolic profiling of follicular fluid for investigating the different causes of female infertility: a pilot study. Metabolomics 15, 19 (2019). https://doi.org/10.1007/s11306-019-1481-x
Received:
Accepted:
Published:
DOI: https://doi.org/10.1007/s11306-019-1481-x