Abstract
Background: Preeclampsia (PE) is a common pregnancy-specific disease with potential adverse maternal and neonatal outcomes.
Objective: We aimed to estimate proteomic profiles of serum-derived exosomes obtained from PE offspring with bioinformatics methods.
Methods: Serum samples were collected from 12 h, 24 h, and 72 h newborns delivered by preeclamptic and normal pregnant women. Exosomes were extracted, and the concentration and size distribution were determined. The exosome surface markers CD9, CD63, CD81, and TSG101, were assayed by Western blot. The exosome proteins were screened by quantitative proteomics with tandem mass tag (TMT). All the identified proteins were subjected to the Weighted Gene Co- Expression Network Analysis (WGCNA), GO function, and KEGG pathway analysis. A proteinprotein interaction network (PPI) was used to extract hub proteins through the Cytohubba plugin of Cytoscape.
Results: The extracted exosomes were round or oval vesicular structures at a 100-200 nm concentration, and the size distribution was standard and uniform. Exosome surface markers CD9, CD63, and CD81 were detected, and TSG101 was not detected. A total of 450 expressed proteins were selected, and 444 proteins were mapped with gene names. A blue module with 66 proteins highly correlated with phenotype at 12 h. Functional analyses revealed that module proteins were mainly enriched in the extracellular matrix. The top 10 selected hub proteins were identified as hub proteins, including COL6A2, HSPG2, COL4A1, COL3A1, etc.
Conclusion: Our study provides important information for exploring molecular mechanisms of preeclampsia and potential biomarkers for future diagnosis and treatment in the clinic.
Keywords: Preeclampsia, newborn, exosome, proteome, biomarker, WGCNA.
Graphical Abstract
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