WGCNA combined with machine learning for analysis of diagnostic markers of preeclampsia associated with the hedgehog signaling pathway.

IF 2.1 4区 医学 Q3 OBSTETRICS & GYNECOLOGY
Hypertension in Pregnancy Pub Date : 2025-12-01 Epub Date: 2025-08-08 DOI:10.1080/10641955.2025.2542869
Xiaofeng Wang, Yichi Xu, Junpeng Dong, Jinwen Zhang, Wei Gu, Xiaoli Qin
{"title":"WGCNA combined with machine learning for analysis of diagnostic markers of preeclampsia associated with the hedgehog signaling pathway.","authors":"Xiaofeng Wang, Yichi Xu, Junpeng Dong, Jinwen Zhang, Wei Gu, Xiaoli Qin","doi":"10.1080/10641955.2025.2542869","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Abnormal hedgehog (Hh) signaling is linked to preeclampsia (PE). This study aimed to identify Hh-related diagnostic biomarkers for PE and assess the role of immune infiltration.</p><p><strong>Methods: </strong>The PE dataset was obtained from GEO to screen DEGs. WGCNA was utilized to identify Hh pathway-related genes. Following the intersection of the two genes, key genes were screened by using LASSO, SVM-RFE, and RF. A model was constructed, with ROC applied for evaluating its performance. The ssGSEA was employed to analyze immune infiltration. Network Analyst was utilized to predict miRNA/TF targets.</p><p><strong>Results: </strong>Six Hh-related diagnostic genes were identified (SLC20A1, GPT2, PDK4, COASY, KRT81, CD163L1). The diagnostic model showed high accuracy (AUC > 0.8) in training and validation sets. PE patients exhibited immune dysfunction, including reduced dendritic cell, macrophage, and mast cell activity. Diagnostic genes strongly correlated with immune cells. Additionally, 25 miRNAs and 34 TFs potentially regulating these genes were predicted.</p><p><strong>Conclusions: </strong>Six potential PE diagnostic biomarkers were identified, and their immune interactions were explored. This study enhances understanding of PE pathogenesis and suggests therapeutic targets.</p>","PeriodicalId":13054,"journal":{"name":"Hypertension in Pregnancy","volume":"44 1","pages":"2542869"},"PeriodicalIF":2.1000,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Hypertension in Pregnancy","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1080/10641955.2025.2542869","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/8/8 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"OBSTETRICS & GYNECOLOGY","Score":null,"Total":0}
引用次数: 0

Abstract

Background: Abnormal hedgehog (Hh) signaling is linked to preeclampsia (PE). This study aimed to identify Hh-related diagnostic biomarkers for PE and assess the role of immune infiltration.

Methods: The PE dataset was obtained from GEO to screen DEGs. WGCNA was utilized to identify Hh pathway-related genes. Following the intersection of the two genes, key genes were screened by using LASSO, SVM-RFE, and RF. A model was constructed, with ROC applied for evaluating its performance. The ssGSEA was employed to analyze immune infiltration. Network Analyst was utilized to predict miRNA/TF targets.

Results: Six Hh-related diagnostic genes were identified (SLC20A1, GPT2, PDK4, COASY, KRT81, CD163L1). The diagnostic model showed high accuracy (AUC > 0.8) in training and validation sets. PE patients exhibited immune dysfunction, including reduced dendritic cell, macrophage, and mast cell activity. Diagnostic genes strongly correlated with immune cells. Additionally, 25 miRNAs and 34 TFs potentially regulating these genes were predicted.

Conclusions: Six potential PE diagnostic biomarkers were identified, and their immune interactions were explored. This study enhances understanding of PE pathogenesis and suggests therapeutic targets.

WGCNA结合机器学习分析与hedgehog信号通路相关的子痫前期诊断标志物。
背景:异常的hedgehog (Hh)信号与子痫前期(PE)有关。本研究旨在确定hh相关的PE诊断生物标志物,并评估免疫浸润的作用。方法:从GEO获取PE数据集,筛选DEGs。利用WGCNA鉴定Hh通路相关基因。在两个基因交叉后,通过LASSO、SVM-RFE和RF筛选关键基因。建立模型,用ROC评价模型的性能。采用ssGSEA分析免疫浸润。使用Network Analyst预测miRNA/TF靶标。结果:共鉴定出6个hh相关诊断基因(SLC20A1、GPT2、PDK4、COASY、KRT81、CD163L1)。在训练集和验证集上,该诊断模型显示出较高的准确率(AUC >.8)。PE患者表现出免疫功能障碍,包括树突状细胞、巨噬细胞和肥大细胞活性降低。诊断基因与免疫细胞密切相关。此外,还预测了25个mirna和34个tf可能调节这些基因。结论:确定了6个潜在的PE诊断生物标志物,并探讨了它们的免疫相互作用。这项研究提高了对PE发病机制的认识,并提出了治疗靶点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Hypertension in Pregnancy
Hypertension in Pregnancy 医学-妇产科学
CiteScore
3.40
自引率
0.00%
发文量
21
审稿时长
6 months
期刊介绍: Hypertension in Pregnancy is a refereed journal in the English language which publishes data pertaining to human and animal hypertension during gestation. Contributions concerning physiology of circulatory control, pathophysiology, methodology, therapy or any other material relevant to the relationship between elevated blood pressure and pregnancy are acceptable. Published material includes original articles, clinical trials, solicited and unsolicited reviews, editorials, letters, and other material deemed pertinent by the editors.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信