Department of Nephropathy, The First Hospital of Jilin University, China.
J Renin Angiotensin Aldosterone Syst. 2020 Apr-Jun;21(2):1470320320919635. doi: 10.1177/1470320320919635.
This study aims to identify immunoglobulin-A-nephropathy-related genes based on microarray data and to investigate novel potential gene targets for immunoglobulin-A-nephropathy treatment.
Immunoglobulin-A-nephropathy chip data was obtained from the Gene Expression Omnibus database, which included 10 immunoglobulin-A-nephropathy and 22 normal samples. We used the limma package of R software to screen differentially expressed genes in immunoglobulin-A-nephropathy and normal glomerular compartment tissues. Functional enrichment (including cellular components, molecular functions, biological processes) and signal pathways were performed for the differentially expressed genes. The online analysis database (STRING) was used to construct the protein-protein interaction networks of differentially expressed genes, and Cytoscape software was used to identify the hub genes of the signal pathway. In addition, we used the Connectivity Map database to predict possible drugs for the treatment of immunoglobulin-A-nephropathy.
A total of 348 differentially expressed genes were screened including 107 up-regulated and 241 down-regulated genes. Functional analysis showed that up-regulated differentially expressed genes were mainly concentrated on leukocyte migration, and the down-regulated differentially expressed genes were significantly enriched in alpha-amino acid metabolic process. A total of six hub genes were obtained: JUN, C3AR1, FN1, AGT, FOS, and SUCNR1. The small-molecule drugs thapsigargin, ciclopirox and ikarugamycin were predicted therapeutic targets against immunoglobulin-A-nephropathy.
Differentially expressed genes and hub genes can contribute to understanding the molecular mechanism of immunoglobulin-A-nephropathy and providing potential therapeutic targets and drugs for the diagnosis and treatment of immunoglobulin-A-nephropathy.
本研究旨在基于微阵列数据鉴定免疫球蛋白 A 肾病相关基因，并探讨免疫球蛋白 A 肾病治疗的新的潜在基因靶点。
从基因表达综合数据库中获取免疫球蛋白 A 肾病芯片数据，包含 10 例免疫球蛋白 A 肾病和 22 例正常肾小球组织样本。我们使用 R 软件中的 limma 包筛选免疫球蛋白 A 肾病和正常肾小球组织中的差异表达基因。对差异表达基因进行功能富集（包括细胞成分、分子功能、生物过程）和信号通路分析。使用在线分析数据库（STRING）构建差异表达基因的蛋白质-蛋白质互作网络，并用 Cytoscape 软件识别信号通路的枢纽基因。此外，我们使用 Connectivity Map 数据库预测治疗免疫球蛋白 A 肾病的可能药物。
筛选出 348 个差异表达基因，包括 107 个上调基因和 241 个下调基因。功能分析表明，上调的差异表达基因主要集中在白细胞迁移，而下调的差异表达基因在 alpha-氨基酸代谢过程中显著富集。共获得 6 个枢纽基因：JUN、C3AR1、FN1、AGT、FOS 和 SUCNR1。小分子药物 thapsigargin、ciclopirox 和 ikarugamycin 被预测为针对免疫球蛋白 A 肾病的治疗靶点。
差异表达基因和枢纽基因有助于了解免疫球蛋白 A 肾病的分子机制，并为免疫球蛋白 A 肾病的诊断和治疗提供潜在的治疗靶点和药物。
