Mechanistic study of pre-eclampsia and macrophage-associated molecular networks: bioinformatics insights from multiple datasets

作者全名：Cao, Jinfeng; Jiang, Wenxin; Yin, Zhe; Li, Na; Tong, Chao; Qi, Hongbo

作者地址：[Cao, Jinfeng; Jiang, Wenxin; Yin, Zhe; Li, Na; Tong, Chao] Chongqing Med Univ, Affiliated Hosp 1, Dept Obstet, Chongqing, Peoples R China; [Cao, Jinfeng; Jiang, Wenxin; Yin, Zhe; Li, Na; Qi, Hongbo] Chongqing Med Univ, Chongqing Key Lab Maternal & Fetal Med, Chongqing, Peoples R China; [Cao, Jinfeng; Jiang, Wenxin; Yin, Zhe; Li, Na; Qi, Hongbo] Chongqing Med Univ, Joint Int Res Lab Reprod & Dev, Chinese Minist Educ, Chongqing, Peoples R China; [Qi, Hongbo] Chongqing Med Univ, Women & Childrens Hosp, Dept Obstet & Gynecol, Chongqing, Peoples R China

通信作者：Tong, C (通讯作者)，Chongqing Med Univ, Affiliated Hosp 1, Dept Obstet, Chongqing, Peoples R China.; Qi, HB (通讯作者)，Chongqing Med Univ, Chongqing Key Lab Maternal & Fetal Med, Chongqing, Peoples R China.; Qi, HB (通讯作者)，Chongqing Med Univ, Joint Int Res Lab Reprod & Dev, Chinese Minist Educ, Chongqing, Peoples R China.; Qi, HB (通讯作者)，Chongqing Med Univ, Women & Childrens Hosp, Dept Obstet & Gynecol, Chongqing, Peoples R China.

来源：FRONTIERS IN GENETICS

ESI学科分类：MOLECULAR BIOLOGY & GENETICS

WOS号：WOS:001239175400001

JCR分区：Q2

影响因子：2.8

年份：2024

卷号：15

期号：　

开始页：　

结束页：　

文献类型：Article

关键词：pre-eclampsia; macrophages; immune infiltration; GSEA; CMAP

摘要：Background Pre-eclampsia is a pregnancy-related disorder characterized by hypertension and proteinuria, severely affecting the health and quality of life of patients. However, the molecular mechanism of macrophages in pre-eclampsia is not well understood.Methods In this study, the key biomarkers during the development of pre-eclampsia were identified using bioinformatics analysis. The GSE75010 and GSE74341 datasets from the GEO database were obtained and merged for differential analysis. A weighted gene co-expression network analysis (WGCNA) was constructed based on macrophage content, and machine learning methods were employed to identify key genes. Immunoinfiltration analysis completed by the CIBERSORT method, R package "ClusterProfiler" to explore functional enrichment of these intersection genes, and potential drug predictions were conducted using the CMap database. Lastly, independent analysis of protein levels, localization, and quantitative analysis was performed on placental tissues collected from both preeclampsia patients and healthy control groups.Results We identified 70 differentially expressed NETs genes and found 367 macrophage-related genes through WGCNA analysis. Machine learning identified three key genes: FNBP1L, NMUR1, and PP14571. These three key genes were significantly associated with immune cell content and enriched in multiple signaling pathways. Specifically, these genes were upregulated in PE patients. These findings establish the expression patterns of three key genes associated with M2 macrophage infiltration, providing potential targets for understanding the pathogenesis and treatment of PE. Additionally, CMap results suggested four potential drugs, including Ttnpb, Doxorubicin, Tyrphostin AG 825, and Tanespimycin, which may have the potential to reverse pre-eclampsia.Conclusion Studying the expression levels of three key genes in pre-eclampsia provides valuable insights into the prevention and treatment of this condition. We propose that these genes play a crucial role in regulating the maternal-fetal immune microenvironment in PE patients, and the pathways associated with these genes offer potential avenues for exploring the molecular mechanisms underlying preeclampsia and identifying therapeutic targets. Additionally, by utilizing the Connectivity Map database, we identified drug targets like Ttnpb, Doxorubicin, Tyrphostin AG 825, and Tanespimycin as potential clinical treatments for preeclampsia.

基金机构：Joint Funds of the National Natural Science Foundation of China [U21A20346]

基金资助正文：The author(s) declare that financial support was received for the research, authorship, and/or publication of this article. Joint Funds of the National Natural Science Foundation of China (No. U21A20346).r The author(s) declare that financial support was received for the research, authorship, and/or publication of this article. Joint Funds of the National Natural Science Foundation of China (No. U21A20346).