通过生物信息学和机器学习方法识别子痫前期的关键生物标志物和免疫浸润。

IF 2.8 2区 医学 Q1 OBSTETRICS & GYNECOLOGY BMC Pregnancy and Childbirth Pub Date : 2025-02-11 DOI:10.1186/s12884-025-07257-0
Weiwen Li, Lijun Zhong, Kewen Zhao, Jincheng Xie, Shaodong Deng, Yunyong Fang
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Receiver operating characteristic (ROC) analysis was used to evaluate the diagnostic specificity of obtained DEGs, and the GSE35574 dataset was used for preliminary validation. Furthermore, the single-sample Gene Set Enrichment Analysis (ssGSEA) was used to elucidate the correlation between the DEGs and the 28 types of infiltrating immune cells in PE. Real-time reverse transcription polymerase chain reaction (RT-PCR) was used to verify the differential expression of DEGs in the PE placental tissues.</p><p><strong>Results: </strong>A total of 143 DEGs (DE-mRNAs) were screened using the PE datasets. The analysis of DEG modules and LASSO logistic regression were used to identify high-temperature requirement factor A4 (HtrA4), tumour suppressor candidate 3 (TUSC3), endothelial protein C receptor gene (PROCR), claudin 3 (CLDN3), and thioredoxin binding protein (TXNIP) as the hub DEGs in PE. 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Identification of critical biomarkers and immune infiltration in preeclampsia through bioinformatics and machine learning methods.

Background: Preeclampsia (PE) is a multisystem progressive disease that occurs during pregnancy. Previous studies have shown that the immune system is involved in the placental trophoblast function and the pathological process of uterine vascular remodeling in PE. However, its molecular mechanism is still unclear. This study aimed to identify critical genes and immune cells involved in the pathological process of PE.

Methods: The PE-related GSE74341 and GSE160888 datasets were downloaded from the Gene Expression Omnibus (GEO) database, and differential expression analysis, weighted gene co-expression network analysis (WGCNA), and least absolute shrinkage and selection operator (LASSO) analysis were combined to screen the PE-related DEGs. Receiver operating characteristic (ROC) analysis was used to evaluate the diagnostic specificity of obtained DEGs, and the GSE35574 dataset was used for preliminary validation. Furthermore, the single-sample Gene Set Enrichment Analysis (ssGSEA) was used to elucidate the correlation between the DEGs and the 28 types of infiltrating immune cells in PE. Real-time reverse transcription polymerase chain reaction (RT-PCR) was used to verify the differential expression of DEGs in the PE placental tissues.

Results: A total of 143 DEGs (DE-mRNAs) were screened using the PE datasets. The analysis of DEG modules and LASSO logistic regression were used to identify high-temperature requirement factor A4 (HtrA4), tumour suppressor candidate 3 (TUSC3), endothelial protein C receptor gene (PROCR), claudin 3 (CLDN3), and thioredoxin binding protein (TXNIP) as the hub DEGs in PE. Furthermore, validation with the GSE35574 dataset and ROC analysis was used to clarify that the HTRA4, PROCR, and TXNIP genes are potential markers of PE and are closely related to the infiltrating immune cells in PE, such as gamma delta T cells, mast cells, natural killer cells, and T follicular helper cells. Finally, differential HTRA4, PROCR, and TXNIP expression were confirmed in PE placental tissues (p < 0.001).

Conclusion: HTRA4, PROCR, and TXNIP can be used as potential PE biomarkers to provide a new strategy for early diagnosing and treating PE.

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来源期刊
BMC Pregnancy and Childbirth
BMC Pregnancy and Childbirth OBSTETRICS & GYNECOLOGY-
CiteScore
4.90
自引率
6.50%
发文量
845
审稿时长
3-8 weeks
期刊介绍: BMC Pregnancy & Childbirth is an open access, peer-reviewed journal that considers articles on all aspects of pregnancy and childbirth. The journal welcomes submissions on the biomedical aspects of pregnancy, breastfeeding, labor, maternal health, maternity care, trends and sociological aspects of pregnancy and childbirth.
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