Are the Follicular Fluid Characteristics of Recovered Coronavirus Disease 2019 Patients Different From Those of Vaccinated Women Approaching in vitro Fertilization?

The aim of this pilot study is to evaluate if SARS-CoV-2 infection or vaccination against SARS-CoV-2 infection induce observable metabolic effects in follicular fluid of women who are following in vitro fertilization (IVF) treatments. The possible impact of coronavirus disease 2019 (COVID-19) on fertility and IVF outcome is considered. We have selected for this study: six women vaccinated against SARS-CoV-2 infection, five recovered COVID-19 patients, and we used nine healthy women as the control group. At the time of oocytes retrieval from participants in the study, follicular fluids were collected and metabolomic analysis was performed by 1H NMR spectroscopy in combination with multivariate analysis to interpret the spectral data. The search for antibody positivity in the follicular fluid aspirates was also carried out, together with the western blotting analysis of some inflammatory proteins, interleukin-6, tumor necrosis factor α (TNFα), and the free radical scavenger superoxide dismutase 2. Higher levels of Ala and Pro together with lower levels of lipids and trimethylamine N-oxide (TMAO) were found in follicular fluids (FFs) of vaccinated women while lower levels of many metabolites were detected in FFs of recovered COVID patients. Expression level of TNF-α was significantly lower both in recovered COVID-19 patients and vaccinated women in comparison to healthy controls.

Metabolic changes in follicular fluids of patients treated with recombinant versus urinary human chorionic gonadotropin for triggering ovulation in assisted reproductive technologies: a metabolomics pilot study.

INTRODUCTION: The main goal of this retrospective cohort study is the assessment of the effects of administration of recombinant-hCG (r-hCG) versus urinary-hCG (u-hCG) on follicular fluid (FF) composition of women who underwent in vitro fertilization (IVF) treatments. MATERIALS AND METHODS: We selected 70 patients with infertility attributable to tubal diseases, unexplained infertility, and male factor. Metabolomics analysis of their FFs was performed by 1H nuclear magnetic resonance (1H NMR) spectroscopy in combination with multivariate analysis to interpret the spectral data. Univariate statistical analysis was applied to investigate the possible correlations between clinical parameters and between clinical parameters and metabolites identified by NMR. RESULTS: According to the type of hCG used, significant differences were detected in FFs of women with male factor and unexplained infertility, both in qualitative and quantitative terms, for some metabolites as cholesterol, citrate, creatine, ß-hydroxybutyrate, glycerol, lipids, amino acids (Glu, Gln, His, Val, Lys) and glucose. No significant difference was observed in women with tubal diseases. Besides, the number of MII oocytes in the u-hCG-treated groups correlates positively with glutamate in tubal disease and with glycerol in unexplained infertility. In the r-hCG-treated groups, the number of MII oocytes correlates positively with lipid in tubal disease, positively with citrate and negatively with glucose in male infertility. CONCLUSIONS: Metabolite composition of FF changes according to different type of hCG treatment and this can be related to oocyte development and subsequent outcome. According to the data of this study, different types of hCG should be used in relation to the diagnosis of infertility to obtain better results in inducing oocyte maturation in women undergoing IVF.

NMR metabolic profiling of follicular fluid for investigating the different causes of female infertility: a pilot study.

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.

NMR metabolomics study of follicular fluid in women with cancer resorting to fertility preservation.

PURPOSE: The purpose of this study was to evaluate the possible application of metabolomics to identify follicular fluid changes in cancer patients undergoing fertility preservation. Although metabolomics have been applied already in cancer studies, this is the first application on follicular fluid of cancer patients. METHODS: We selected for the study ten patients with breast cancer and lymphoma who resorted to oocyte cryopreservation to preserve fertility and ten healthy women undergoing in vitro fertilization treatments. Follicular fluid was collected at the time of oocytes retrieval. Metabolomic analysis of follicular fluids was performed by 1H-nuclear magnetic resonance (NMR) spectroscopy in combination with multivariate analysis to interpret the spectral data. Univariate statistical analysis was applied to find correlations between patients' features and metabolites identified by NMR. RESULTS: Partial least squares discriminant analysis allowed to discriminate samples from cancer patients and healthy controls. Univariate statistical analysis found significant correlations between patients' features and metabolites identified by NMR. This finding allowed to identify biomarkers to differentiate both healthy controls from cancer patients and the two different classes of oncological patients. CONCLUSION: The follicular fluids of cancer patients display significant metabolic alterations in comparison to healthy subjects. NMR-based metabolomics could be a valid prognostic tool for identifying and selecting the best cryopreserved oocytes and improving the outcome prediction in cancer women undergoing in vitro fertilization.