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Perfluorooctane sulfonate (PFOS) is a widely used chemical in industrial production. It can be introduced into the environment through multiple pathways and exhibits resistance to degradation. Recent research has demonstrated a significant correlation between its exposure levels in the human body and the incidence of various diseases. The expression of genes related to endometrial receptivity and the differentiation of human endometrial stromal cells (hESCs) were assessed in this study concerning PFOS. In this study, we investigated the effect of PFOS exposure on endometrial tolerance by cell and animal experiments. The activity against endometrial mesenchymal cells was significantly reduced by PFOS intervention, and the apoptosis flow assay results showed that PFOS significantly promoted cell death in a concentration-dependent manner. Transmission electron microscopy results revealed mitochondrial damage in the PFOS-intervened group, and WB results showed that the expression levels of endometrial tolerance-related proteins Homeobox A10 (HOXA10) and integrin beta3 (ITGB3) were decreased, and the expression level of Forkhead box O1 (FOXO1) protein was increased. Animal studies have shown that PFOS exposure can change uterine morphology, cause obvious damage to pinopodes morphology, change the estrous cycle of mice, and affect endometrial receptivity In the present study, we found that PFOS may synergistically affect the viability of endometrial mesenchymal stromal cells through accumulation in vivo, and that PFOS may contribute to the failure of embryo implantation by affecting mitochondrial function and consequently endometrial permissive sites. [ABSTRACT FROM AUTHOR]

Objective: More and more studies have found that polycystic ovary syndrome (PCOS) is significantly associated with recurrent spontaneous abortion (RSA), but the specific mechanism is not yet clear., Methods: Based on the GEO database, we downloaded the PCOS (GSE10946, GSE6798 and GSE137684) and RSA (GSE165004, GSE26787 and GSE22490) datasets and performed differential analysis, weighted gene co-expression network (WGCNA), functional enrichment, and machine learning, respectively, on the datasets of the two diseases, Nomogram and integrated bioinformatics analysis such as immune infiltration analysis. Finally, the reliability of the diagnostic gene was verified by external verification and collection of human specimens., Results: In this study, PCOS and RSA datasets were obtained from Gene Expression Omnibus (GEO) database, and a total of 23 shared genes were obtained by differential analysis and WGCNA analysis. GO results showed that the shared genes were mainly enriched in the functions of lipid catabolism and cell cycle transition (G1/S). DO enrichment revealed that shared genes are mainly involved in ovarian diseases, lipid metabolism disorders and psychological disorders. KEGG analysis showed significant enrichment of Regulation of lipolysis in adipocytes, Prolactin signaling pathway, FoxO signaling pathway, Hippo signaling pathway and other pathways. A diagnostic gene FAM166 B was obtained by machine learning and Nomogram screening, which mainly played an important role in Cellular component. GSEA analysis revealed that FAM166B may be involved in the development of PCOS and RSA by regulating the cell cycle, amino acid metabolism, lipid metabolism, and carbohydrate metabolism. CIBERSORT analysis showed that the high expression of FAM166 B was closely related to the imbalance of multiple immune cells. Further verification by qPCR suggested that FAM166 B could be used as a common marker of PCOS and RSA., Conclusions: In summary, this study identified FAM166B as a common biomarker for PCOS and RSA, and conducted in-depth research and analysis of this gene, providing new data for basic experimental research and early prognosis, diagnosis and treatment of clinical diseases., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 He, Liu, Shen, Jiang, Gao, Yu, Du, Zhang and Fu.)