Uterine fluid analysis as a new opportunity to increase implantation ratesin assisted reproductive technology programs


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Abstract

A significant proportion of ineffective cycles of assisted reproductive technologies (ART) prompt investigators to continue to search for new approaches to defining endometrial receptivity. Most modern methods for evaluating the functional state of the endometrium are invasive and cannot be performed in one cycle with embryo transfer in the ART programs. The introduction of new-generation technologies (epigenomics, transcriptomics, proteomics, and metabolomics) makes it possible to better understand the complex biological processes that contribute to the successful outcome of ART programs. The possibility of obtaining uterine fluid directly in the embryo transfer cycle, on the one hand, and the use of omix technologies that allow the search for prognostic and diagnostic markers, on the other hand, open up new perspectives for studying the endometrium during the implantation window. Endometrial secretion analysis will be able to identify the molecular profile of uterine fluid to detect window of displacement or disruption. This review describes the possibilities of applying modern omix technologies in identifying the molecular profile of uterine fluid during the implantation window for the elaboration of an individual treatment approach in the ART programs. Conclusion: The results of the studies conducted confirm the prospects and relevance of investigating the protein, metabolomic and transcriptomic profiles to determine the most favorable time period for embryo transfer, which can be used to enhance the effectiveness of ART programs.

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About the authors

Alina A. Babayan

Academician V.I. Kulakov National Medical Research Center of Obstetrics, Gynecology, and Perinatology, Ministry of Health of the Russian Federation

Email: a_babayan@oparina4.ru
Ph.D., Researcher at the BV. Leonov Department of Assisted Technologies for the Treatment of Infertility

Natalia P. Makarova

Academician V.I. Kulakov National Medical Research Center of Obstetrics, Gynecology, and Perinatology, Ministry of Health of the Russian Federation

Email: np_makarova@oparina4.ru
Dr. Biol. Sci., Senior Researcher at the BV. Leonov Department of Assisted Technologies for the Treatment of Infertility

Natalia V. Kondakova

Academician V.I. Kulakov National Medical Research Center of Obstetrics, Gynecology, and Perinatology, Ministry of Health of the Russian Federation

Email: n_kondakova@oparina4.ru
embryologist at the BV. Leonov Department of Assisted Technologies for the Treatment of Infertility

Yael A. Gokhberg

Academician V.I. Kulakov National Medical Research Center of Obstetrics, Gynecology, and Perinatology, Ministry of Health of the Russian Federation

Email: dr.yaelgokhberg@gmail.com
postgraduate student at the BV. Leonov Department of Assisted Technologies for the Treatment of Infertility

Oksana S. Nepsha

Academician V.I. Kulakov National Medical Research Center of Obstetrics, Gynecology, and Perinatology, Ministry of Health of the Russian Federation

Email: o_nepsha@oparina4.ru
PhD. (Biol. Sci.), Researcher at the BV. Leonov Department of Assisted Technologies for the Treatment of Infertility

Elena A. Kalinina

Academician V.I. Kulakov National Medical Research Center of Obstetrics, Gynecology, and Perinatology, Ministry of Health of the Russian Federation

Email: e_kalinina@oparina4.ru
Dr. Med. Sci., Professor, Head of the BV. Leonov Department of Assisted Technologies for the Treatment of Infertility

References

  1. Ruiz-Alonso M., Valbuena D., Gomez C., Cuzzi J., Simon C. Endometrial Receptivity Analysis (ERA): data versus opinions. Hum. Reprod. Open. 2021; 2021(2): hoab011. https://dx.doi.org/10.1093/hropen/hoab011.
  2. Varghese A.C., Goldberg E., Bhattacharyya A.K., Agarwal A. Emerging technologies for the molecular study of infertility, and potential clinical applications. Reprod. Biomed. Online. 2007; 15(4): 451-6. https://dx.doi.org/10.1016/s1472-6483(10)60372-0.
  3. Silvestri E., Lombardi A., de Lange P., Glinni D., Senese R., Cioffi F. et al. Studies of complex biological systems with applications to molecular medicine: The need to integrate transcriptomic and proteomic approaches. J. Biomed. Biotechnol. 2011; 2011: 810242. https://dx.doi.org/10.1155/2011/810242.
  4. Драпкина Ю.С., Тимофеева А.В., Чаговец В.В., Кононихин А. С., Франкевич В.Е., Калинина Е.А. Применение омиксных технологий в решении проблем репродуктивной медицины. Акушерство и гинекология. 2018; 9: 24-32. [Drapkina Yu.S., Timofeeva A.V., Chagovets V.V., Kononikhin A.S., Frankevich V.E., Kalinina E.A. Use of omics technologies to solve the problems of reproductive medicine. Obstetrics and Gynecology. 2018; 9: 24-32. (in Russian)]. https://dx.doi.org/10.18565/aig.2018.9.24-32.
  5. Гохберг Я.А., Макарова Н.П., Бабаян А.А., Калинина Е.А. Роль различных факторов воздействия на эндометрий в повышении эффективности программ вспомогательных репродуктивных технологий. Акушерство и гинекология. 2021; 1: 28-34. [Gokhberg Ya.A., Makarova N.P., Babayan A.A., Kalinina E.A. The role of various factors affecting the endometrium in enhancing the effectiveness of assisted reproductive technology programs. Obstetrics and Gynecology. 2021; 1: 28-34. (in Russian)]. https://dx.doi.org/10.18565/aig.2021.1.28-34.
  6. Egea R.R., Garrido N.G., Escriva M.M., Varghese A.C. OMICS: Current and future perspectives in reproductive medicine and technology. J. Hum. Reprod. Sci. 2014; 7(2): 73-92. https://dx.doi.org/10.4103/0974-1208.138857.
  7. Fiorentino F., Bono S., Biricik A., Nuccitelli A., Cotroneo E., Cottone G. et al. Application of next-generation sequencing technology for comprehensive aneuploidy screening of blastocysts in clinical preimplantation genetic screening cycles. Hum. Reprod. 2014; 29(12): 2802-13. https://dx.doi.org/10.1093/humrep/deu277.
  8. Yang Z., Lin J., Zhang J., Fong W.I., Li P., Zhao R. et al. Randomized comparison of next-generation sequencing and array comparative genomic hybridization for preimplantation genetic screening: a pilot study. BMC Med. Genomics. 2015; 8: 30. https://dx.doi.org/10.1186/s12920-015-0110-4.
  9. Yang Z., Liu J., Collins G.S., Salem S.A., Liu X., Lyle S.S. et al. Selection of single blastocysts for fresh transfer via standard morphology assessment alone and with array CGH for good prognosis IVF patients: results from a randomized pilot study. Mol. Cytogenet. 2012; 5(1): 24. https://dx.doi.org/10.1186/1755-8166-5-24.
  10. Hernandez-Vargas P., Munoz M., Dominguez F. Identifying biomarkers for predicting successful embryo implantation: applying single to multi-OMICs to improve reproductive outcomes. Hum. Reprod. Update. 2020; 26(2): 264-301. https://dx.doi.org/10.1093/humupd/dmz042.
  11. Macklon N.S., Brosens J.J. The human endometrium as a sensor of embryo quality. Biol. Reprod. 2014; 91(4): 98. https://dx.doi.org/10.1095/biolreprod.114.122846.
  12. Diedrich K., Fauser B.C., Devroey P., Griesinger G.; Evian Annual Reproduction (EVAR) Workshop Group. The role of the endometrium and embryo in human implantation. Hum. Reprod. Update. 2007; 13(4): 365-77. https://dx.doi.org/10.1093/humupd/dmm011.
  13. Franasiak J.M., Forman E.J., Hong K.H., Werner M.D., Upham K.M., Treff N.R., Scott R.T. Jr. The nature of aneuploidy with increasing age of the female partner: a review of 15 169 consecutive trophectoderm biopsies evaluated with comprehensive chromosomal screening. Fertil. Steril. 2014; 101(3): 656-63.e1. https://dx.doi.org/10.1016/j.fertnstert.2013.11.004.
  14. Bastu E., Mutlu M.F., Yasa C., Dural O., Nehir Aytan A., Celik C. et al. Role of mucin 1 and glycodelin A in recurrent implantation failure. Fertil. Steril. 2015; 103(4): 1059-64.e2. https://dx.doi.org/10.1016/j.fertnstert.2015.01.025.
  15. Haouzi D., Dechaud H., Assou S., De Vos J., Hamamah S. Insights into human endometrial receptivity from transcriptomic and proteomic data. Reprod. Biomed. Online. 2012; 24(1): 23-34. https://dx.doi.org/10.1016/j.rbmo.2011.09.009.
  16. Hromadova L., Tokareva I., Vesela K., Travnik P., Vesely J. Endometrial receptivity analysis - a tool to increase an implantation rate in assisted reproduction. Ceska Gynekol. 2019; 84: 177-83.
  17. Edgell T.A., Rombauts L.J.F., Salamonsen L.A. Assessing receptivity in the endometrium: the need for a rapid, non-invasive test. Reprod. Biomed. Online. 2013; 27(5): 486-96. https://dx.doi.org/10.1016/j.rbmo.2013.05.014.
  18. Van der Gaast M.H., Beier-Hellwig K., Fauser B.C.J.M., Beier H.M., Macklon N.S. Endometrial secretion aspiration prior to embryo transfer does not reduce implantation rates. Reprod. Biomed. Online. 2003; 7(1): 105-9. https://dx.doi.org/10.1016/s1472-6483(10)61737-3.
  19. Boomsma C.M., Kavelaars A., Eijkemans M.J., Lentjes E.G., Fauser B.C., Heijnen C.J. et al. Endometrial secretion analysis identifies a cytokine profile predictive of pregnancy in IVF. Hum. Reprod. 2009; 24(6): 1427-35. https://dx.doi.org/10.1093/humrep/dep011.
  20. Grasso A., Navarro R., Balaguer N., Moreno I., Alama P., Jimenez J. et al. Endometrial Liquid Biopsy Provides a miRNA roadmap of the secretory phase of the human endometrium. J. Clin. Endocrinol. Metab. 2020; 105(3): dgz146. https://dx.doi.org/10.1210/clinem/dgz146.
  21. Scotchie J.G., Fritz M.A., Mocanu M., Lessey B.A., Young S.L. Proteomic analysis of the luteal endometrial secretome. Reprod. Sci. 2009; 16(9): 883-93. https://dx.doi.org/10.1177/1933719109337165.
  22. Casado-Vela J., Rodriguez-Suarez E., Iloro I., Ametzazurra A., Alkorta N., Garcia-Velasco J.A. et al. Comprehensive proteomic analysis of human endometrial fluid aspirate. J. Proteome Res. 2009; 8(10): 4622-32. https://dx.doi.org/10.1021/pr9004426.
  23. Ametzazurra A., Matorras R., Garcia-Velasco J.A., Prieto B., Simon L., Martinez A., Nagore D. Endometrial fluid is a specific and non-invasive biological sample for protein biomarker identification in endometriosis. Hum. Reprod. 2009; 24(4): 954-65. https://dx.doi.org/10.1093/humrep/den450.
  24. Gurung S., Greening D.W., Catt S., Salamonsen L., Evans J. Exosomes and soluble secretome from hormone-treated endometrial epithelial cells direct embryo implantation. Mol. Hum. Reprod. 2020; 26(7): 510-20. https://dx.doi.org/10.1093/molehr/gaaa034.
  25. Berlanga O., Bradshaw H., Vilella-Mitjana F., Garrido-Gomez T., Simon C. How endometrial secretomics can help in predicting implantation. Placenta. 2011; 32: S271-5. https://dx.doi.org/10.1016/j.placenta.2011.06.002.
  26. Matorras R., Quevedo S., Corral B., Prieto B., Exposito A., Mendoza R. et al. Proteomic pattern of implantative human endometrial fluid in in-vitro fertilization cycles. Arch. Gynecol. Obstet. 2018; 297(6): 1577-86. https://dx.doi.org/10.1007/s00404-018-4753-1.
  27. Matorras R., Martinez-Arranz I., Arretxe E., Iruarrizaga-Lejarreta M., Corral B., Ibanez-Perez J. et al. The lipidome of endometrial fluid differs between implantative and non-implantative IVF cycles. J. Assist. Reprod. Genet. 2019; 37(2): 385-94. https://dx.doi.org/10.1007/s10815-019-01670-z.
  28. Guo X., Li T.C., Chen X. The endometrial proteomic profile around the time of embryo implantation. Biol. Reprod. 2021; 104(1): 11-26. https://dx.doi.org/10.1093/biolre/ioaa150.
  29. Dunlap K.A., Filant J., Hayashi K., Rucker E.B., Song G., Deng J.M. et al. Postnatal deletion of Wnt7a inhibits uterine gland morphogenesis and compromises adult fertility in mice. Biol. Reprod. 2011; 85(2): 386-96. https://dx.doi.org/10.1095/biolreprod.111.091769.
  30. Hannan N.J., Nie G., Rainzcuk A., Rombauts L.J.F., Salamonsen L.A. Uterine lavage or aspirate: which view of the intrauterine environment? Reprod. Sci. 2012; 19(10): 1125-32. https://dx.doi.org/10.1177/1933719112443879.
  31. Fitzgerald H.C., Evans J., Johnson N., Infusini G., Webb A., Rombauts L.J.R. et al. Idiopathic infertility in women is associated with distinct changes in proliferative phase uterine fluid proteins. Biol. Reprod. 2018; 98(6): 752-64. https://dx.doi.org/10.1093/biolre/ioy063.
  32. Zhang Y., Wang Q., Wang H., Duan E. Uterine fluid in pregnancy: a biological and clinical outlook. Trends Mol. Med. 2017; 23(7): 604-14. https://dx.doi.org/10.1016/j.molmed.2017.05.002.
  33. Perez-Sanchez С., Colas E., Cabrera S., Falcon O., Sanchez-del-Rio A., Garcia E. et al. Molecular diagnosis of endometrial cancer from uterine aspirates. Int. J. Cancer. 2013; 133(10): 2383-91. https://dx.doi.org/10.1002/ijc.28243.
  34. Salamonsen L.A, Evans J., Nguyen H.P., Edgell T.A. The microenvironment of human implantation: determinant of reproductive success. Am. J. Reprod. Immunol. 2016; 75(3): 218-25. https://dx.doi.org/10.1111/aji.12450.
  35. Aslam B., Basit M., Nisar M.A., Khurshid M., Rasool M.H. Proteomics: technologies and their applications. J. Chromatogr. Sci. 2017; 55(2): 182-96. https://dx.doi.org/10.1093/chromsci/bmw167.
  36. Azkargorta M., Bregon-Villahoz M., Escobes I., Ibanez-Perez J., Iloro I., Iglesias M. et al. In-depth proteomics and natural peptidomics analyses reveal antibacterial peptides in human endometrial fluid. J. Proteomics 2020; 216: 103652. https://dx.doi.org/10.1016/j.jprot.2020.103652.
  37. Parmar T., Sachdeva G., Savardekar L., Katkam R.R., Nimbkar-Joshi S., Gadkar-Sable S. et al. Protein repertoire of human uterine fluid during the mid-secretory phase of the menstrual cycle. Hum. Reprod. 2008; 23(2): 379-86. https://dx.doi.org/10.1093/humrep/dem367.
  38. Kasvandik S., Saarma M., Kaart T., Rooda I., Velthut-Meikas A., Ehrenberg A. et al. Uterine fluid proteins for minimally invasive assessment of endometrial receptivity. J. Clin. Endocrinol. Metab. 2020; 105(1): dgz019. https://dx.doi.org/10.1210/clinem/dgz019.
  39. Azkargorta M., Escobes I., Iloro I., Osinalde N., Corral B., Ibanez-Perez J. et al. Differential proteomic analysis of endometrial fluid suggests increased inflammation and impaired glucose metabolism in non-implantative IVF cycles and pinpoints PYGB as a putative implantation marker. Hum. Reprod. 2018; 33(10): 1898-906. https://dx.doi.org/10.1093/humrep/dey274.
  40. Edgell T.A., Evans J., Lazzaro L., Boyes K., Sridhar M., Catt S. et al. Assessment of potential biomarkers of pre-receptive and receptive endometrium in uterine fluid and a functional evaluation of the potential role of CSF3 in fertility. Cytokine. 2018; 111: 222-9. https://dx.doi.org/10.1016/j.cyto.2018.08.026.
  41. Coughlan C., Ledger W., Wang Q., Liu F., Demirol A., Gurgan T. et al. Cutting Recurrent implantation failure: efinition and management. Reprod. Biomed. Online. 2014; 28(1): 14-38. https://dx.doi.org/10.1016/j.rbmo.2013.08.011.
  42. Sebastian-Leon P., Garrido N., Remohi J., Pellicer A., Diaz-Gimeno P. Asynchronous and pathological windows of implantation: two causes of recurrent implantation failure. Hum. Reprod. 2018; 33(4): 626-35. https://dx.doi.org/10.1093/humrep/dey023.
  43. Achache H., Tsafrir A., Prus D., Reich R., Revel A. Defective endometrial prostaglandin synthesis identified in patients with repeated implantation failure undergoing in vitro fertilization. Fertil. Steril. 2010; 94(4): 1271-8. https://dx.doi.org/10.1016/j.fertnstert.2009.07.1668.
  44. Sordelli M.S., Beltrame J.S., Celia M., Gervasi M.G., Perez Martinez S., Burdet J. et al. Interaction between lysophosphatidic acid, prostaglandins and the endocannabinoid system during the window of implantation in the rat uterus. PLoS One. 2012; 7(9): e46059. https://dx.doi.org/10.1371/journal.pone.0046059.
  45. Arosh J.A., Banu S.K., McCracken J.A. Novel concepts on the role ofprostaglandins on luteal maintenance and maternal recognition and establishment of pregnancy in ruminants. J. Dairy Sci. 2016; 99(7): 5926-40. https://dx.doi.org/10.3168/jds.2015-10335.
  46. Vilella F., Ramirez L., Berlanga O., Martinez S., Alama P., Meseguer M. et al. PGE2 and PGF2a Concentrations in Human Endometrial Fluid as Biomarkers for Embryonic Implantation. J. Clin. Endocrinol. Metab. 2013; 98(10): 4123-32. https://dx.doi.org/10.1210/jc.2013-2205.
  47. De Almeida Ferreira Braga D.P., Borges E., Godoy A.T., Montani D.A., Setti A.S., Zanetti B.F. et al. Lipidomic profile as a non-invasive tool to predict endometrial receptivity. Mol. Reprod. Dev. 2019; 86(2): 145-55. https://dx.doi.org/10.1002/mrd.23088.
  48. Almagor M., Levin Y., Halevy Amiran R., Fieldust S., Harir Y., Or Y., Shoham Z. Spontaneous in vitro hatching of the human blastocyst: the proteomics of initially hatching cells. In Vitro Cell. Dev. Biol. Anim. 2020; 56(10): 859-65. https://dx.doi.org/10.1007/s11626-020-00522-w.
  49. Cavagna M., Mantese J. Biomarkers of endometrial receptivity - a review. Placenta. 2003; 24(Suppl. B): S39-47. https://dx.doi.org/10.1016/s0143-4004(03)00184-x.
  50. Kermack A.J., Wellstead S.J., Fisk H.L., Cheong Y., Houghton F.D., Macklon N.S., Calder P.C. The fatty acid composition of human follicular fluid is altered by a 6-week dietary intervention that includes marine omega-3 fatty acids. Lipids. 2021; 56(2): 201-9. https://dx.doi.org/10.1002/lipd.12288.
  51. Yurci A., Gungor N.D., Gurbuz T. Spectroscopy analysis of endometrial metabolites is a powerful predictor of success of embryo transfer in women with implantation failure: a preliminary study. Gynecol. Endocrinol. 2021; 37(5): 415-21. https://dx.doi.org/10.1080/09513590.2021.1883584.

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