Phosphoproteomics Analysis of Endometrium in Women with or without Endometriosis

Proteomics of reproduction: Prospects and perspectives

In recent years, proteomics has been used widely in reproductive research in order to understand the molecular mechanisms related to gametes at the cellular level and the role of proteins involved in fertilization. Network and pathway analysis using bioinformatic tools have paved way to obtain a wider picture on the possible pathways associated with the key differentially expressed proteins (DEPs) and its implication in various infertility scenarios. A brief overview of advanced techniques and bioinformatic tools used for reproductive proteomics is presented. Key findings of proteomic-based studies on male and female reproduction are also presented. Furthermore, the chapter sheds light on the cellular pathways and potential biomarkers associated with male and female infertility. Proteomics coupled with bioinformatic analysis provides an ideal platform for non-invasive management of infertility in couples.

Endometriosis Fertility Index for Predicting Pregnancy after Endometriosis Surgery

BACKGROUND

The endometriosis fertility index (EFI) has a predictive value for pregnancy after surgery. In vitro fertilization and embryo transfer (IVF-ET) is a good treatment to infertility. This study aimed to provide external validation of EFI, assess the factors affecting the ability of EFI to predict cumulative spontaneous pregnancy rates (PRs), and propose reasonable advice for treatment by evaluating the effect of infertility management combining surgery and IVF-ET.

METHODS

This retrospective study enrolled 345 endometriosis-related infertile women after laparoscopic surgery from January 2012 to January 2016. Among them, 234 patients tried to conceive naturally and were divided into six groups according to their different EFI scores. Of the 345 patients, 307 with an EFI score ≥5 were divided into non-IVF-ET group (n = 209) and IVE-ET group (n = 98) to compare the cumulative PRs. Cumulative PRs' curves were calculated using the Kaplan-Meier product limit estimate and the differences were evaluated by log-rank test. Independent predictive factors for pregnancy were assessed using the Cox regression model.

RESULTS

Significant differences in spontaneous PRs among different EFI scores were identified (χ2=29.945, P< 0.05). The least function score was proved to be the most important factor for EFI (χ2 = 6.931, P< 0.05) staging system. In patients with an EFI score ≥5 after 12 months from surgery, the cumulative PRs of those who received both surgery and IVF-ET were much higher than the spontaneous PRs of those who received surgery alone (χ2=4.160, P= 0.041).

CONCLUSIONS

The EFI is a reliable staging system to predict the spontaneous PR of patients. The least function score was the most influential factor to predict the spontaneous PR. Patients with an EFI score ≥5 after 12 months from surgery are recommended to receive IVF-ET to achieve a higher PR.