Cai Hai, Chen Shao-Ming, Ke Zhi-Bin, Chen Hang, Zhu Jun-Ming, Lin Ting-Ting, Huang Fei, Wei Yong, Zheng Qing-Shui, Xue Xue-Yi, Sun Xiong-Lin, Xu Ning
Department of Urology, Urology Research Institute, The First Affiliated Hospital, Fujian Medical University, Fuzhou, 350005, People's Republic of China.
Department of Nuclear Medicine, First Affiliated Hospital of Fujian Medical University, Fuzhou, 350005, People's Republic of China.
Int J Gen Med. 2021 Dec 18;14:10003-10013. doi: 10.2147/IJGM.S330956. eCollection 2021.
To develop and validate hub genes involving in the development and progression of primary aldosteronism (PA) and adrenal aldosterone-producing adenoma (APA).
A total of four datasets of gene expression profiles related to APA were downloaded from GEO datasets. GSE60042 and GSE8514 were used to identify DEGs. Weighted gene co-expression network analysis (WGCNA) and protein-protein interaction (PPI) network module analysis were conducted. GO and KEGG enrichment analysis was performed. GSE10927 and GSE33371 were used for further external validation.
We identified a total of 892 DEGs from GSE60042 and 1167 DEGs from GSE8514. WGCNA analysis demonstrated that the blue module (255 genes) and turquoise module (303 genes) were significantly correlated with APA. PPI networks were then constructed. GO term enrichment analysis suggested that cellular divalent inorganic cation homeostasis, calcium ion homeostasis, collagen-containing extracellular matrix, transport vesicle and metal ion transmembrane transporter activity were the vital annotations. KEGG pathway analysis found that these genes were significantly enriched in neuroactive ligand-receptor interaction, calcium signaling pathway. Finally, we identified a total of 11 candidate genes involving in the development and progression of APA and PA. Besides, two independent datasets (GSE10927 and GSE33371) were used for external validation, and there were seven hub genes successfully verified, including C3, GRM3, AVPR1A, WFS1, PTGFR, NTSR2, and JUN.
These newly identified genes could contribute to the understanding of potential mechanism in APA and PA and might be promising targets for the treatment of APA and PA.
筛选并验证参与原发性醛固酮增多症（PA）及肾上腺醛固酮瘤（APA）发生发展过程的关键基因。
从基因表达综合数据库（GEO）下载了4个与APA相关的基因表达谱数据集。使用GSE60042和GSE8514数据集识别差异表达基因（DEG）。进行加权基因共表达网络分析（WGCNA）和蛋白质-蛋白质相互作用（PPI）网络模块分析。进行基因本体论（GO）和京都基因与基因组百科全书（KEGG）富集分析。使用GSE10927和GSE33371数据集进行进一步的外部验证。
我们从GSE60042数据集中共识别出892个DEG，从GSE8514数据集中识别出1167个DEG。WGCNA分析表明，蓝色模块（255个基因）和绿松石色模块（303个基因）与APA显著相关。随后构建了PPI网络。GO术语富集分析表明，细胞二价无机阳离子稳态、钙离子稳态、含胶原细胞外基质、运输囊泡和金属离子跨膜转运蛋白活性是重要的注释内容。KEGG通路分析发现，这些基因在神经活性配体-受体相互作用、钙信号通路中显著富集。最后，我们共识别出11个参与APA和PA发生发展的候选基因。此外，使用两个独立数据集（GSE10927和GSE33371）进行外部验证，成功验证了7个关键基因，包括C3、GRM3、AVPR1A、WFS1、PTGFR、NTSR2和JUN。
这些新识别出的基因有助于深入了解APA和PA的潜在发病机制，可能成为APA和PA治疗的潜在靶点。
