Comparative proteomics reveal negative effects of gonadotropin-releasing hormone agonist and antagonist on human endometrium

Abstract

Purpose:

The two major ovarian-stimulation protocols for in vitro fertilization are gonadotropin-releasing hormone agonist (GnRH-a) protocol or GnRH antagonist (GnRH-ant) protocol; however, comparisons of their relative efficacy remain controversial. Additionally, conflicting data exist regarding their effects on endometrial receptivity. Thus, this study investigated how GnRH-a and GnRH-ant treatments alter the endometrium during the mid-secretory phase.

Patients and methods:

We compared proteomic profiles across human endometrium tissues of mid-secretory phase from normal control humans (n=5), patients treated with GnRH-a (n=5), and patients treated with GnRH-ant (n=5).

Results:

We identified 2088 proteins, with 362 that exhibited significantly different expression. Fuzzy c-means clustering (FCM) using the M Fuzz algorithm analysis showed that the same 87 proteins changed significantly in both the GnRH-a and GnRH-ant groups compared with those in the control. Moreover, Gene Ontology (GO) analysis showed that, of these 87, downregulated proteins were associated with energy metabolism and upregulated proteins were linked to cytoskeleton maintenance. Upregulated proteins involved in complement-mediated immunity were present in 151 proteins that exhibited significantly different expression in the GnRH-ant group only.

Conclusion:

We demonstrated that comparative proteomic analysis is useful for accessing endometrial receptivity, which seemed more strongly impaired by GnRH-ant than GnRH-a treatments. Our findings also revealed that energy metabolism and immunity response may be the key biological mechanisms underlying human endometrial receptivity.

Keywords:

• endometrial receptivity
• proteomic profile
• energy metabolism
• complement-mediated immunity

Acknowledgments

This study was supported by the National Natural Science Foundation of China (grant no. 81671517 and no. 81100469, to Chen Qian) and Scientific Research Foundation of Shanghai Municipal Commission of Health and Planning (grant no. 201840060, to Zhu Xiaobin).

Author contributions

Qian Chen: data collection, manuscript writing. Feng Yu: data analysis. Qian Chen, Li Yan, Ai-Jun Zhang, Xiao-Bin Zhu: protocol/project development. All authors contributed toward data analysis, drafting and revising the paper, gave final approval of the version to be published, and agree to be accountable for all aspects of the work.

Disclosure

The authors report no conflicts of interest in this work.