Almarzouki Nawaf
Department of Ophthalmology, Faculty of Medicine, King Abdulaziz University, Jeddah 21589, Saudi Arabia.
Int J Ophthalmol. 2024 Nov 18;17(11):1987-1994. doi: 10.18240/ijo.2024.11.03. eCollection 2024.
To understand the molecular connectivity between the intraocular pressure (IOP) and glaucoma which will provide possible clues for biomarker candidates.
The current study uncovers the important genes connecting IOP with the core functional modules of glaucoma. An integrated analysis was performed using glaucoma and IOP microarray datasets to screen for differentially expressed genes (DEGs) in both conditions. To the selected DEGs, the protein interaction network was constructed and dissected to determine the core functional clusters of glaucoma. For the clusters, the connectivity of IOP DEGs was determined. Further, enrichment analyses were performed to assess the functional annotation and potential pathways of the crucial clusters.
The gene expression analysis of glaucoma and IOP with normal control showed that 408 DEGs (277 glaucoma and 131 IOP genes) were discovered from two GEO datasets. The 290 DEGs of glaucoma were extended to form a network containing 1495 proteins with 9462 edges. Using ClusterONE, the network was dissected to have 12 clusters. Among them, three clusters were linked with three IOP DEGs [N-Myc and STAT Interactor (NMI), POLR3G (RNA Polymerase III Subunit G), and APAF1-interacting protein (APIP)]. In the clusters, ontology analysis revealed that RNA processing and transport, p53 class mediators resulting in cell cycle arrest, cellular response to cytokine stimulus, regulation of phosphorylation, regulation of type I interferon production, DNA deamination, and cellular response to hypoxia were significantly enriched to be implicated in the development of glaucoma. Finally, NMI, POLR3G, and APIP may have roles that were noticed altered in glaucoma and IOP conditions.
Our findings could help to discover new potential biomarkers, elucidate the underlying pathophysiology, and identify new therapeutic targets for glaucoma.
了解眼压（IOP）与青光眼之间的分子联系，为寻找潜在的生物标志物提供线索。
本研究揭示了连接眼压与青光眼核心功能模块的重要基因。利用青光眼和眼压微阵列数据集进行综合分析，以筛选两种情况下的差异表达基因（DEG）。对选定的DEG构建并剖析蛋白质相互作用网络，以确定青光眼的核心功能簇。对于这些簇，确定眼压DEG的连接性。此外，进行富集分析以评估关键簇的功能注释和潜在途径。
青光眼和眼压与正常对照的基因表达分析表明，从两个GEO数据集中发现了408个DEG（277个青光眼基因和131个眼压基因）。青光眼的290个DEG被扩展形成一个包含1495个蛋白质和9462条边的网络。使用ClusterONE将该网络剖析为12个簇。其中，三个簇与三个眼压DEG相关联，即N-Myc和STAT相互作用因子（NMI）、POLR3G（RNA聚合酶III亚基G）以及APAF1相互作用蛋白（APIP）。在这些簇中，本体分析显示RNA加工和转运、导致细胞周期停滞的p53类介质、细胞对细胞因子刺激的反应、磷酸化调节、I型干扰素产生调节、DNA脱氨以及细胞对缺氧的反应显著富集，与青光眼的发生发展有关。最后，NMI、POLR3G和APIP在青光眼和眼压情况下可能具有明显改变的作用。
我们的研究结果有助于发现新的潜在生物标志物，阐明潜在的病理生理学机制，并确定青光眼的新治疗靶点。
