构建并验证用于诊断子宫内膜异位症的组蛋白相关基因特征。

Hongjuan Yang, Dongmei Gao, Xinping Yu, Chang Wang, Xiangkun Li
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引用次数: 0

摘要

目的:子宫内膜异位症是育龄妇女常见的慢性疾病,也是导致不孕的主要原因之一。我们的研究旨在基于组蛋白相关基因(HRGs)鉴定和验证诊断子宫内膜异位症的新型基因特征,并研究其在子宫内膜异位症中的生物学功能:从基因表达总库(Gene Expression Omnibus)数据库下载 RNA 序列数据,从基因卡片(GeneCards)数据库检索 HRGs。我们使用 limma 软件包识别了差异表达基因,并使用 rms 软件包构建了诊断模型。我们对京都基因组百科全书(KEGG)和基因本体(GO)进行了富集分析,以实现可视化、注释和综合发现。随后,我们使用召回率和决策曲线分析(DCA)对模型进行了验证。此外,我们还使用 CIBERSORT 分析了免疫微环境特征:结果:与对照组相比,子宫内膜异位症患者中共发现了 18 个差异表达的 HRGs。GO和KEGG富集主要集中在纺锤体组织、细胞周期过程的正调控、黄体酮介导的卵母细胞成熟以及细胞衰老和细胞周期。我们获得了四个 HRGs(JUNB、FRY、LMNB1 和 SPAG1)的特征。DCA显示,无论子宫内膜异位症的发病率如何,该诊断模型都能使子宫内膜异位症患者受益。CIBERSORT分析表明,在所有四个数据集的子宫内膜异位症样本中,浆细胞的数量显著增加:我们的研究结果为了解 HRGs 在子宫内膜异位症发病过程中的功能提供了新的视角,并确定了四种 HRGs 的新特征,它们可能成为该疾病有价值的诊断标志物和治疗靶点。
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Construction and validation of a histone-related gene signature for the diagnosis of endometriosis.

Objectives: Endometriosis is a common chronic disease in childbearing women and a major cause of infertility. Our study aimed to identify and validate a novel gene signature for diagnosing endometriosis based on histone-related genes (HRGs), and to investigate their biological functions in endometriosis.

Material and methods: RNA sequence data were downloaded from the Gene Expression Omnibus database, and HRGs were retrieved from the GeneCards database. We identified differentially expressed genes using the limma package, and constructed a diagnostic model using the rms package. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analyses were performed for visualization, annotation, and integrated discovery. Subsequently, we validated the model using the recall and decision curve analysis (DCA). Additionally, we analyzed the immune microenvironment features using CIBERSORT.

Results: A total of 18 differentially expressed HRGs were identified in patients with endometriosis compared with controls. GO and KEGG enrichment was mainly in spindle organization, positive regulation of the cell cycle process, progesterone-mediated oocyte maturation, and cellular senescence and cell cycle. We obtained a signature of four HRGs (JUNB, FRY, LMNB1, and SPAG1). DCA revealed that the diagnostic model benefits patients with endometriosis, regardless of the incidence. CIBERSORT analysis showed that the number of plasma cells increased significantly in endometriosis samples from all four datasets.

Conclusions: Our findings provide novel insights into the function of HRGs in the development of endometriosis and identify a new signature of four HRGs that may serve as valuable diagnostic markers and therapeutic targets for this disease.

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