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.

Due to its high prevalence, infertility has become a prominent public health issue, posing a significant challenge to modern reproductive medicine. Some clinical conditions that lead to female infertility include polycystic ovary syndrome (PCOS), endometriosis, and premature ovarian failure (POF). Follicular fluid (FF) is the biological matrix that has the most contact with the oocyte and can, therefore, be used as a predictor of its quality. Volatilomics has emerged as a non-invasive, straightforward, affordable, and simple method for characterizing various diseases and determining the effectiveness of their current therapies. In order to find potential biomarkers of infertility, this study set out to determine the volatomic pattern of the follicular fluid from patients with PCOS, endometriosis, and POF. The chromatographic data integration was performed through solid-phase microextraction (SPME), followed by gas chromatography–mass spectrometry (GC-MS). The findings pointed to specific metabolite patterns as potential biomarkers for the studied diseases. These open the door for further research into the relevant metabolomic pathways to enhance infertility knowledge and diagnostic tools. An extended investigation may, however, produce a new mechanistic understanding of the pathophysiology of the diseases.

Background/Objectives: Volatile organic compounds (VOCs) have emerged as promising non-invasive biomarkers for assessing metabolic and reproductive health. In the context of assisted reproductive techniques (ARTs), the volatilomic composition of follicular fluid (FF) may reflect the biochemical environment surrounding the oocyte, influencing fertilization success and embryo development. This study aimed to characterize the volatilomic profile of FF in women undergoing ARTs and to explore associations between specific VOCs and female fertilization-related parameters (FFRPs). Methods: A total of 54 Caucasian women aged 19–39 years, enrolled between October 2015 and July 2019, were recruited at the Assisted Reproduction Laboratory of the Local Health Unit of Cova da Beira, Covilhã. FF samples were analyzed via gas chromatography–mass spectrometry (GC–MS) in scan mode, identifying 136 VOCs, of which 72 were selected based on prevalence. Sixteen FFRPs were evaluated, including age, body mass index (BMI), smoking habits, infertility factor, oocyte yield, embryo quality, β-hCG levels, country of birth, and reproductive history. Associations between VOCs and FFRPs were assessed using the Chi-square (χ²) test. Results: Significant correlations (p ≤ 0.05) were identified between 45 VOCs and 11 FFRPs. The detected compounds comprised alkanes, siloxanes, aromatics, alcohols, ketones, aldehydes, carboxylic acids and esters, fatty acid derivatives, epoxides, acrylates, nitriles, and sterols. Several VOCs were associated with more than one FFRP, indicating overlapping metabolic pathways that may influence reproductive performance. Conclusions: The volatilomic profile of FF demonstrates significant variability linked to individual reproductive and metabolic factors. VOC analysis may provide novel insights into follicular physiology, representing a promising approach for identifying potential biomarkers of infertility and ART outcomes.