Kang Jieun, Ahn Kwangjin, Oh Jiyeon, Lee Taesic, Hwang Sangwon, Uh Young, Choi Seong Jin
Department of Obstetrics and Gynecology, Yonsei University Wonju College of Medicine, 20, Ilsan-ro, Wonju-si 26426, Republic of Korea.
Department of Laboratory Medicine, Yonsei University Wonju College of Medicine, 20, Ilsan-ro, Wonju-si 26426, Republic of Korea.
Int J Mol Sci. 2025 Jan 6;26(1):424. doi: 10.3390/ijms26010424.
Endometriosis is a complex disease with diverse etiologies, including hormonal, immunological, and environmental factors; however, its exact pathogenesis remains unknown. While surgical approaches are the diagnostic and therapeutic gold standard, identifying endometriosis-associated genes is a crucial first step. Five endometriosis-related gene expression studies were selected from the available datasets. Approximately, 14,167 genes common to these 5 datasets were analyzed for differential expression. Meta-analyses utilized fold-change values and standard errors obtained from each analysis, with the binomial and continuous datasets contributing to endometriosis presence and endometriosis severity meta-analysis, respectively. Approximately 160 genes showed significant results in both meta-analyses. For Bayesian analysis, endometriosis-related single nucleotide polymorphisms (SNPs), the human transcription factor catalog, uterine SNP-related gene expression, disease-gene databases, and interactome databases were utilized. Twenty-four genes, present in at least three or more databases, were identified. Network analysis based on Pearson's correlation coefficients revealed the gene with both a high score in the Bayesian analysis and a central position in the network. Although had a lower score, it occupied a central position in the network, followed by other family members. Bayesian analysis identified genes with high confidence that could support discovering key diagnostic biomarkers and therapeutic targets for endometriosis.
子宫内膜异位症是一种病因复杂的疾病，其病因包括激素、免疫和环境因素；然而，其确切发病机制仍不清楚。虽然手术方法是诊断和治疗的金标准，但确定与子宫内膜异位症相关的基因是关键的第一步。从现有数据集中选取了五项与子宫内膜异位症相关的基因表达研究。对这5个数据集共有的约14167个基因进行了差异表达分析。荟萃分析利用了每次分析获得的倍数变化值和标准误差，二项式数据集和连续数据集分别用于子宫内膜异位症存在情况和子宫内膜异位症严重程度的荟萃分析。大约160个基因在两项荟萃分析中均显示出显著结果。对于贝叶斯分析，利用了与子宫内膜异位症相关的单核苷酸多态性（SNP）、人类转录因子目录、子宫SNP相关基因表达、疾病-基因数据库和相互作用组数据库。确定了至少存在于三个或更多数据库中的24个基因。基于皮尔逊相关系数的网络分析揭示了在贝叶斯分析中得分高且在网络中处于中心位置的基因。虽然[具体基因名称未给出]得分较低，但它在网络中占据中心位置，其次是其他[具体基因家族名称未给出]家族成员。贝叶斯分析确定了具有高可信度的基因，这些基因有助于发现子宫内膜异位症的关键诊断生物标志物和治疗靶点。
