Polycystic ovary syndrome (PCOS) represents one of the leading causes of anovulatory infertility and affects 5% to 20% of women worldwide. Until today, both the subsequent etiology and pathophysiology of PCOS remain unclear, and patients with PCOS that undergo assisted reproductive techniques (ART) might present a poor to exaggerated response, low oocyte quality, ovarian hyperstimulation syndrome, as well as changes in the follicular fluid metabolites pattern. These abnormalities originate a decrease of Metaphase II (MII) oocytes and decreased rates for fertilization, cleavage, implantation, blastocyst conversion, poor egg to follicle ratio, and increased miscarriages. Focus on obtaining high-quality embryos has been taken into more consideration over the years. Nowadays, the use of metabolomic analysis in the quantification of proteins and peptides in biological matrices might predict, with more accuracy, the success in assisted reproductive technology. In this article, we review the use of human follicular fluid as the matrix in metabolomic analysis for diagnostic and ART predictor of success for PCOS patients.

Infertility is recognized globally as a social disease and a growing medical condition, posing a significant challenge to modern reproductive health. Endometriosis, the third-most frequent gynecologic disorder, is one of the most common and intricate conditions that can lead to female infertility. Despite extensive research, the etiology, malignant transformation, and biological therapy of endometriosis remain unknown. Blood and follicular fluid are two matrices that have been carefully studied and can provide insights into women’s health. These matrices are clinically significant because they contain metabolites closely associated with women’s illness stage and reproductive outcomes. Nowadays, the application of metabolomic analysis in biological matrices may be able to predict the outcome of assisted reproductive technologies with greater precision. From a molecular viewpoint on reproductive health, we evaluate and compare the utilization of human follicular fluid and blood as matrices in analysis for diagnostic and assisted reproductive technology (ART) predictors of success for endometriosis patients. In the follicular fluid (FF), plasma, and serum of endometriosis-affected women, researchers identified dysregulations of oxidative stress, upregulation of several immune factors, and aberrations in energy metabolic pathways. The altered signatures negatively correlate with the overall oocyte and embryo quality and fertilization rate.

Purpose: This case–control study was conducted in order to evaluate the potential role of polymorphic genes encoding enzymes involved in estrogen biosynthesis ( CYP19A1 ) and metabolism ( GSTM1 , GSTT1 , and GSTP1 ), and their action in modulating individual susceptibility to breast cancer. Methods: Genomic DNA was extracted from blood samples of 101 patients with histological diagnosis of breast cancer and 121 healthy women. Genotyping analyses of CYP19A1 codon 39 Trp/Arg ( T/C ), GSTM1 and GSTT1 homozygous deletions, and GSTP1 codon 105 Ile/Val ( A/G ) were performed by polymerase chain reaction–based methods. Results: Odds ratios (ORs) and 95% confidence intervals (95% CIs) were calculated by unconditional logistic regression. Significant statistical association of the TC/CC genotypes combined with breast cancer risk was found, with reference to TT genotype (OR=1.770; 95% CI=1.036–3.024; p =0.036). Also, CYP19A1 arginine allele in homozygosity or heterozygosity ( TC/CC ) was associated with a significant increased risk for breast cancer when associated to GSTM1 null genotype (OR=6.158; 95% CI=2.676–14.171; p <0.001) and GSTT1 null genotype (OR=4.870; 95% CI=2.216–10.700; p <0.001). The three-way combination of CYP19A1 TC/CC , GSTM1 null, and GSTT1 null polymorphism was related with significant increased risk for breast cancer (OR=11.429; 95% CI=3.590–36.385; p <0.001). Valine alleles compared with isoleucine alleles in codon 105 in GSTP1 , in combination with CYP19A1 genotypes, were not associated with an increase of breast cancer development. Conclusions: Our results suggest that the effect of CYP19A1 T/C polymorphism in susceptibility to breast cancer development can be modulated by the presence of GSTM1 and GSTT1 , but not GSTP1 .