Yin Xiaodan, Yang Wei, Xin Mingwei, Han Qian, Guan Siqi, He Junqin
Department of TCM, Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing Maternal and Child Health Care Hospital, Beijing, 100026, China.
Sci Rep. 2025 Jan 9;15(1):1452. doi: 10.1038/s41598-024-77642-w.
Recurrent miscarriage (RM) is a reproductive disorder affecting couples worldwide. The underlying molecular mechanisms remain elusive, even though emerging evidence has implicated endoplasmic reticulum stress (ERS). We investigated RM- and ERS-related genes to develop a diagnostic model that can enhance predictive ability. We utilized the R package GEO query to extract and process Gene Expression Omnibus data, applying batch correction, normalization, and differential gene expression analysis with limma. ERS-related differentially expressed genes (ERSRGs) were identified through Gene Ontology and Kyoto Encyclopedia of genes and genomes analyses, and their diagnostic potential was assessed. Diagnostic models were developed using logistic regression, support vector machines, and least absolute shrinkage and selection operators, complemented by immune infiltration analysis and regulatory network construction. Integrated analysis revealed 1395 differentially expressed genes (DEGs), including 626 upregulated and 769 downregulated genes. Seventeen ERSRGs were identified. KEAP1 and YIPF5 displayed high diagnostic accuracy (area under the curve [AUC] > 0.9). Gene Ontology and Kyoto Encyclopedia of genes and genomes analyses highlighted the role of ESRDEGs in cellular responses to ERS, protein processing, and apoptosis. Diagnostic models demonstrated robust predictive performance (AUC > 0.9). A molecular interaction was found between RM and the ERS response, and the identified ESRDEGs could serve as potential biomarkers for diagnosis.
复发性流产(RM)是一种影响全球夫妇的生殖障碍。尽管有新证据表明内质网应激(ERS)与之相关,但其潜在的分子机制仍不清楚。我们研究了与RM和ERS相关的基因,以开发一种可以提高预测能力的诊断模型。我们使用R包GEOquery来提取和处理基因表达综合数据库(Gene Expression Omnibus)的数据,应用批次校正、标准化以及使用limma进行差异基因表达分析。通过基因本体论(Gene Ontology)和京都基因与基因组百科全书(Kyoto Encyclopedia of genes and genomes)分析确定了与ERS相关的差异表达基因(ERSRGs),并评估了它们的诊断潜力。使用逻辑回归、支持向量机和最小绝对收缩和选择算子(least absolute shrinkage and selection operators)开发诊断模型,并辅以免疫浸润分析和调控网络构建。综合分析揭示了1395个差异表达基因(DEGs),包括626个上调基因和769个下调基因。鉴定出17个ERSRGs。KEAP1和YIPF5显示出较高的诊断准确性(曲线下面积[AUC]>0.9)。基因本体论和京都基因与基因组百科全书分析突出了ERS相关差异表达基因在细胞对ERS的反应、蛋白质加工和细胞凋亡中的作用。诊断模型表现出强大的预测性能(AUC>0.9)。发现RM与ERS反应之间存在分子相互作用,并且鉴定出的ERS相关差异表达基因可作为潜在的诊断生物标志物。