背景:局灶节段肾小球硬化(FSGS),肾小球损伤的组织学模式,是全球终末期肾病(ESRD)的主要肾小球原因之一。尽管进行了广泛的研究,导致FSGS的潜在生物学改变仍然知之甚少。研究基因表达谱的变化提供了一种有前途的方法,可以全面了解FSGS分子致病性并确定关键元件作为潜在的治疗靶标。这项工作是对FSGS患者肾小球样本基因表达谱的荟萃分析。这项研究的主要目的是建立FSGS中差异表达基因的共识列表,验证这些发现,了解疾病的致病性,并确定新的治疗靶点。
方法:在对GEO数据库进行彻底搜索和随后的质量控制评估之后,选择了七个基因表达数据集进行荟萃分析:GSE47183(GPL14663),GSE47183(GPL11670),GSE99340,GSE108109,GSE121233,GSE129973,和GSE104948.随机效应大小方法用于鉴定差异表达基因(meta-DEGs),然后被用来构建一个监管网络(STRING,MiRTarBase,和TRRUST)并进行各种途径富集分析。几个meta-DEGs的表达水平,特别是ADAMTS1、PF4、EGR1和EGF,被称为血管生成调节剂,使用定量逆转录聚合酶链反应(RT-qPCR)进行分析。
结果:确定的2,898个元DEG,包括665个下调基因和669个上调基因,进行了各种分析。一个由2,859个DEG组成的共同监管网络,2,688个microRNAs(miRNAs),构建了374个转录因子(TFs),网络中的顶部分子是根据度中心性识别的。部分途径富集分析揭示了FSGS肾脏中血管生成调节途径的显著破坏。RT-qPCR结果通过证明ADAMTS1和EGR1(两个关键的血管生成调节因子)的差异表达水平证实了血管生成途径的失衡。在FSGS条件下。
结论:除了提供FSGS中差异表达基因的共识列表外,这项荟萃分析确定了FSGS肾脏中血管生成相关途径和因子的显著扭曲.针对这些因素可能会提供一个可行的策略来阻止FSGS的进展。
BACKGROUND: Focal segmental glomerulosclerosis (FSGS), a histologic pattern of injury in the glomerulus, is one of the leading glomerular causes of end-stage renal disease (ESRD) worldwide. Despite extensive research, the underlying biological alterations causing FSGS remain poorly understood. Studying variations in gene expression profiles offers a promising approach to gaining a comprehensive understanding of FSGS molecular pathogenicity and identifying key elements as potential therapeutic targets. This work is a meta-analysis of gene expression profiles from glomerular samples of FSGS patients. The main aims of this study are to establish a consensus list of differentially expressed genes in FSGS, validate these findings, understand the disease\'s pathogenicity, and identify novel therapeutic targets.
METHODS: After a thorough search in the GEO database and subsequent quality control assessments, seven gene expression datasets were selected for the meta-analysis: GSE47183 (GPL14663), GSE47183 (GPL11670), GSE99340, GSE108109, GSE121233, GSE129973, and GSE104948. The random effect size method was applied to identify differentially expressed genes (meta-DEGs), which were then used to construct a regulatory network (STRING, MiRTarBase, and TRRUST) and perform various pathway enrichment analyses. The expression levels of several meta-DEGs, specifically ADAMTS1, PF4, EGR1, and EGF, known as angiogenesis regulators, were analyzed using quantitative reverse transcription polymerase chain reaction (RT-qPCR).
RESULTS: The identified 2,898 meta-DEGs, including 665 downregulated and 669 upregulated genes, were subjected to various analyses. A co-regulatory network comprising 2,859 DEGs, 2,688 microRNAs (miRNAs), and 374 transcription factors (TFs) was constructed, and the top molecules in the network were identified based on degree centrality. Part of the pathway enrichment analysis revealed significant disruption in the angiogenesis regulatory pathways in the FSGS kidney. The RT-qPCR results confirmed an imbalance in angiogenesis pathways by demonstrating the differential expression levels of ADAMTS1 and EGR1, two key angiogenesis regulators, in the FSGS condition.
CONCLUSIONS: In addition to presenting a consensus list of differentially expressed genes in FSGS, this meta-analysis identified significant distortions in angiogenesis-related pathways and factors in the FSGS kidney. Targeting these factors may offer a viable strategy to impede the progression of FSGS.