Integrated Proteomic and N-Glycoproteomic Profiling of Placental Tissues of Patients with Preeclampsia

Int J Womens Health. 2023 Jan 13:15:59-68. doi: 10.2147/IJWH.S387672. eCollection 2023.

Abstract

Background: Preeclampsia (PE) is a multi-system disorder of pregnancy that poses a serious threat to maternal and perinatal health worldwide. This study aims to evaluate the global alterations of protein expression and N-glycosylations that are crucial for PE pathogenesis. Here, tandem mass tag labeling combined with LC-MS/MS was employed to determine the global expression of all proteins and intact glycopeptide in placentas from three healthy pregnant women, three patients with early-onset severe PE, and three patients with late-onset severe PE.

Results: A total of 2260 proteins were quantified across 9 placental tissues, of which 37 and 23 were differentially expressed in the early-onset and late-onset PE groups, compared to the controls. A total of 789 glycopeptides were accurately quantified, which were derived from 204 glycosylated sites in 159 glycoproteins and were modified by 59 N-Linked glycans. A total of 123 differently expressed glycopeptides, which were from 47 glycoproteins were identified among three groups. Through a combined analysis of proteomic and glycoproteomic data, it was found that the changes in 10 glycoproteins were caused by the difference in glycosylation level but not in the protein abundance level.

Conclusion: This is the first study to conduct an integrated proteomic and glycoproteomic characterization of placental tissues of PE patients. Our findings suggest that glycosylation modification may affect the molecular function of proteins through changes in the glycosylation structure or the occupancy of glycosylation, which will provide new insights to help elucidating the pathogenic mechanism of PE.

Keywords: glycoproteomics; glycosylation; placenta; preeclampsia; proteomics.

Grants and funding

This study was supported by grants from National Natural Science Foundation of China (81960285), Tianshan Innovation Team Plan of Xinjiang Uygur Autonomous Region (2020D14010), and Natural Science Foundation of the Xinjiang Uygur Autonomous Region (2019D01A15).