Hunan University of Chinese Medicine, Changsha, China.
The First Affiliated Hospital of Hunan University of Chinese Medicine, Changsha, China.
Sci Rep. 2024 Jul 13;14(1):16178. doi: 10.1038/s41598-024-67284-3.
Premature ovarian failure (POF), which is often comorbid with dry eye disease (DED) is a key issue affecting female health. Here, we explored the mechanism underlying comorbid POF and DED to further elucidate disease mechanisms and improve treatment. Datasets related to POF (GSE39501) and DED (GSE44101) were identified from the Gene Expression Omnibus (GEO) database and subjected to weighted gene coexpression network (WGCNA) and differentially expressed genes (DEGs) analyses, respectively, with the intersection used to obtain 158 genes comorbid in POF and DED. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analyses of comorbid genes revealed that identified genes were primarily related to DNA replication and Cell cycle, respectively. Protein-Protein interaction (PPI) network analysis of comorbid genes obtained the 15 hub genes: CDC20, BIRC5, PLK1, TOP2A, MCM5, MCM6, MCM7, MCM2, CENPA, FOXM1, GINS1, TIPIN, MAD2L1, and CDCA3. To validate the analysis results, additional POF- and DED-related datasets (GSE48873 and GSE171043, respectively) were selected. miRNAs-lncRNAs-genes network and machine learning methods were used to further analysis comorbid genes. The DGIdb database identified valdecoxib, amorfrutin A, and kaempferitrin as potential drugs. Herein, the comorbid genes of POF and DED were identified from a bioinformatics perspective, providing a new strategy to explore the comorbidity mechanism, opening up a new direction for the diagnosis and treatment of comorbid POF and DED.
卵巢早衰（POF）常与干燥性角结膜炎（DED）并存，是影响女性健康的关键问题。本研究旨在探讨 POF 和 DED 并存的发病机制，以进一步阐明疾病机制并改善治疗方法。从基因表达综合数据库（GEO）中分别鉴定出与 POF（GSE39501）和 DED（GSE44101）相关的数据集，并分别进行加权基因共表达网络分析（WGCNA）和差异表达基因（DEGs）分析，取交集获得 158 个 POF 和 DED 共病基因。对共病基因进行京都基因与基因组百科全书（KEGG）和基因本体论（GO）分析显示，鉴定出的基因主要与 DNA 复制和细胞周期有关。通过共病基因的蛋白质-蛋白质相互作用（PPI）网络分析，得到 15 个核心基因：CDC20、BIRC5、PLK1、TOP2A、MCM5、MCM6、MCM7、MCM2、CENPA、FOXM1、GINS1、TIPIN、MAD2L1 和 CDCA3。为了验证分析结果，还选择了其他与 POF 和 DED 相关的数据集（GSE48873 和 GSE171043）。通过 miRNA-lncRNA-基因网络和机器学习方法进一步分析共病基因。通过 DGIdb 数据库鉴定出 valdecoxib、amorfrutin A 和 kaempferitrin 可能是潜在的药物。本研究从生物信息学角度鉴定了 POF 和 DED 的共病基因，为探索共病机制提供了新策略，为 POF 和 DED 共病的诊断和治疗开辟了新方向。
