Proteomic and bioinformatic analysis of human endometrium from polycystic ovarian syndrome with and without insulin resistance.

Objective: The aim of this study was to investigate the endometrial proteomic profiles of patients with polycystic ovary syndrome (PCOS) with and without insulin resistance (IR). Method of Study: We collected 40 endometrial samples, including PCOS-IR (n = 21), PCOS-non-IR (n = 12), and control (n = 7). Data-independent acquisition (DIA)-based proteomics method is used to identify the expressed proteins among the three groups. The correlation between pregnancy outcomes and identified proteins was analyzed by Lasso regression. Results: A total of 5331 proteins were identified, while 275 proteins were differentially expressed in the PCOS vs. control group and 215 proteins were differentially expressed in the PCOS-IR vs. PCOS-non-IR group. Platelet degranulation, neutrophil degranulation, and very long-chain fatty acid catabolic processes have been found to play important roles in the endometrium of patients with PCOS-IR. Lasso regression analysis found that ACTR1A, TSC22D2, CKB, ABRAXAS2, and TAGLN2 were associated with miscarriage in patients with PCOS. ACTR1A and CKB were higher in the PCOS-IR group and were positively correlated with HOMA-IR (p < .05). Conclusion: In this study, a panel of proteins was found to be differently expressed in the endometrium. ACTR1A and CKB may be considered as PCOS-IR candidate biomarkers.

Citation

Xin Yang, Wang Xiaoping, Ding Nan, Zhang Jian, Li Xiaofeng, Yuan Liwei, Mengni Zhao, Fang Wang. Proteomic and bioinformatic analysis of human endometrium from polycystic ovarian syndrome with and without insulin resistance. Gynecological endocrinology : the official journal of the International Society of Gynecological Endocrinology. 2023 Dec;39(1):2173948

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PMID: 36750132

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