| Literature DB >> 35740276 |
Ana Teresa Brinca1, Ana Cristina Ramalhinho1,2,3, Ângela Sousa1, António Hélio Oliani2,4, Luiza Breitenfeld1,3, Luís A Passarinha1,5,6,7, Eugenia Gallardo1,7.
Abstract
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.Entities:
Keywords: human follicular fluid; metabolomics; polycystic ovary syndrome (PCOS); reproduction
Year: 2022 PMID: 35740276 PMCID: PMC9219683 DOI: 10.3390/biomedicines10061254
Source DB: PubMed Journal: Biomedicines ISSN: 2227-9059
Overall characteristics applied for the molecular analysis of FF.
| Technique | Advantages | Disadvantages | References |
|---|---|---|---|
| NMR | Highly reproducible; | Low sensitivity due to overlapped peaks; | [ |
| GC-MS | Presents well-established libraries of both commercial and ‘in house’ metabolite databases available; | Requires derivatization; | [ |
| LC-MS | Wide metabolite coverage that presents high sensitivity and specificity; | Untargeted screening is highly challenging; | [ |
| LC-MS/MS | Higher specificity and selectivity; | Lack of reference libraries. | [ |
Figure 1Biomarkers of oxidative stress: (a) chemical structure of 8-Isoprostane; (b) chemical structure of 8-hydroxy-2′-deoxyguanosine.
Figure 2Glucose and derivatives: (a) chemical structure of glucose; (b) chemical structure of lactate; (c) chemical structure of pyruvate; (d) chemical structure of glycerol.
Figure 3Steroid hormones: (a) chemical structure of testosterone; (b) chemical structure of dihydrotestosterone; (c) chemical structure of estradiol; (d) chemical structure of estrone; (e) chemical structure of pregnenolone; (f) chemical structure of 17-Hydroxypregnenolone; (g) chemical structure of 17-Hydroxyprogesterone.