Zhu Xiao-Bo, Hou Yu-Qing, Ye Xiang-Yu, Zou Yi-Xin, Xia Xue-Shan, Yang Sheng, Huang Peng, Yu Rong-Bin
The People's Hospital of Danyang, Affiliated Danyang Hospital of Nantong University, Zhenjiang, China.
Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.
Front Genet. 2022 May 13;13:878607. doi: 10.3389/fgene.2022.878607. eCollection 2022.
We identify and explore the candidate susceptibility genes for cirrhosis and their underlying biological mechanism. We downloaded the genome-wide association studies summary data of 901 cirrhosis cases and 451,363 controls and integrated them with reference models of five potential tissues from the Genotype-Tissue Expression (GTEx) Project, including whole blood, liver, pancreas, spleen, and thyroid, to identify genes whose expression is predicted to be associated with cirrhosis. Then, we downloaded gene expression data of individuals with hepatocellular carcinoma from TCGA database to conduct differential expression analysis to validate these identified genes and explored their possible role in driving cirrhosis via functional enrichment and gene set enrichment analysis (GSEA). We identified 10 significant genes (, , , , , , , , , and ) associated with cirrhosis at a Bonferroni-corrected threshold of < 0.01, among which two ( and ) were identified in the liver and five (, , , , and ) were validated by differential expression analysis at an FDR-corrected threshold of < 0.01. The enrichment analysis showed that the degradation process of RNA, which is enriched by 58 genes, is significantly under-enriched in liver cancer tissues ( = 0.0268). We have identified several candidate genes for cirrhosis in multiple tissues and performed differential genetic analysis using the liver cancer database to verify the significant genes. We found that the genes and identified in the liver are of particular concern. Finally, through enrichment analysis, we speculate that the process of mRNA transcription and RNA degradation may play a role in cirrhosis.
我们识别并探索肝硬化的候选易感基因及其潜在的生物学机制。我们下载了901例肝硬化病例和451,363例对照的全基因组关联研究汇总数据,并将其与基因型-组织表达(GTEx)项目中五个潜在组织的参考模型整合,这五个组织包括全血、肝脏、胰腺、脾脏和甲状腺,以识别那些预测其表达与肝硬化相关的基因。然后,我们从TCGA数据库下载了肝细胞癌患者的基因表达数据,进行差异表达分析以验证这些已识别的基因,并通过功能富集和基因集富集分析(GSEA)探索它们在引发肝硬化过程中可能发挥的作用。我们在Bonferroni校正阈值p < 0.01的情况下,识别出10个与肝硬化相关的显著基因(、、、、、、、、和);其中两个基因(和)在肝脏中被识别出来,五个基因(、、、、和)在FDR校正阈值q < 0.01的差异表达分析中得到验证。富集分析表明,由58个基因富集的RNA降解过程在肝癌组织中显著低富集(p = 0.0268)。我们在多个组织中识别出了几个肝硬化的候选基因,并使用肝癌数据库进行差异基因分析以验证这些显著基因。我们发现肝脏中识别出的基因和尤其值得关注。最后,通过富集分析,我们推测mRNA转录和RNA降解过程可能在肝硬化中发挥作用。