Chen Yao, Liu Miao, Wang Yonghong
Department of Obstetrics, The First People's Hospital of Chenzhou, Chenzhou, China.
Front Genet. 2023 Jul 28;14:1228110. doi: 10.3389/fgene.2023.1228110. eCollection 2023.
The process of lysosomal biogenesis and exocytosis in preeclamptic placentae plays a role in causing maternal endothelial dysfunction. However, the specific lysosome-associated markers relevant to preeclampsia (PE) are not well-defined. Our objective is to discover new biomarkers and molecular subtypes associated with lysosomes that could improve the diagnosis and treatment of PE. We obtained four microarray datasets related to PE from the Gene Expression Omnibus (GEO) database. The limma package was utilized to identify genes that were differentially expressed between individuals with the disease and healthy controls. The logistic regression analysis was used to identify core diagnostic biomarkers, which were subsequently validated by independent datasets and clinical samples. Additionally, a consensus clustering method was utilized to distinguish between different subtypes of PE. Following this, functional enrichment analysis, GSEA, GSVA, and immune cell infiltration were conducted to compare the two subtypes and identify any differences in their functional characteristics and immune cell composition. We identified 16 PE-specific lysosome-related genes. Through regression analysis, two genes, and , were identified and subsequently validated in the external validation cohort GSE60438 and through qRT-PCR experiment. A nomogram model for the diagnosis of PE was developed and evaluated using these two genes. The model had a remarkably high predictive power (AUC values of the training set, validation set, and clinical samples were 0.897, 0.788, and 0.979, respectively). Additionally, two different molecular subtypes (C1 and C2) were identified, and we found notable variations in the levels of immune cells present in the two subtypes. Our results not only offered a classification system but also identified novel diagnostic biomarkers for PE patients. Our findings offered an additional understanding of how to categorize PE patients and also highlighted potential avenues for creating treatments for individuals with PE.
子痫前期胎盘的溶酶体生物发生和胞吐过程在导致母体血管内皮功能障碍中起作用。然而，与子痫前期（PE）相关的特定溶酶体相关标志物尚未明确界定。我们的目标是发现与溶酶体相关的新生物标志物和分子亚型，以改善PE的诊断和治疗。我们从基因表达综合数据库（GEO）获得了四个与PE相关的微阵列数据集。使用limma软件包来识别疾病患者和健康对照之间差异表达的基因。采用逻辑回归分析来识别核心诊断生物标志物，随后通过独立数据集和临床样本进行验证。此外，利用共识聚类方法区分PE的不同亚型。在此之后，进行功能富集分析、基因集富集分析（GSEA）、基因集变异分析（GSVA）和免疫细胞浸润分析，以比较这两种亚型，并识别它们在功能特征和免疫细胞组成上的任何差异。我们鉴定出16个PE特异性溶酶体相关基因。通过回归分析，鉴定出两个基因，并随后在外部验证队列GSE60438中以及通过qRT-PCR实验进行了验证。使用这两个基因开发并评估了一个用于诊断PE的列线图模型。该模型具有非常高的预测能力（训练集、验证集和临床样本的AUC值分别为0.897、0.788和0.979）。此外，鉴定出两种不同的分子亚型（C1和C2），并且我们发现这两种亚型中存在的免疫细胞水平有显著差异。我们的结果不仅提供了一个分类系统，还为PE患者鉴定出了新的诊断生物标志物。我们的发现为如何对PE患者进行分类提供了进一步的认识，也突出了为PE患者开发治疗方法的潜在途径。
