Table_3_Identification of biomarkers for the diagnosis of chronic kidney disease (CKD) with non-alcoholic fatty liver disease (NAFLD) by bioinformatics analysis and machine learning.xlsx

BackgroundChronic kidney disease (CKD) and non-alcoholic fatty liver disease (NAFLD) are closely related to immune and inflammatory pathways. This study aimed to explore the diagnostic markers for CKD patients with NAFLD.
MethodsCKD and NAFLD microarray data sets were screened from the GEO database and analyzed the differentially expressed genes (DEGs) in GSE10495 of CKD date set. Weighted Gene Co-Expression Network Analysis (WGCNA) method was used to construct gene coexpression networks and identify functional modules of NAFLD in GSE89632 date set. Then obtaining NAFLD-related share genes by intersecting DEGs of CKD and modular genes of NAFLD. Then functional enrichment analysis of NAFLD-related share genes was performed. The NAFLD-related hub genes come from intersection of cytoscape software and machine learning. ROC curves were used to examine the diagnostic value of NAFLD related hub genes in the CKD data sets and GSE89632 date set of NAFLD. CIBERSORTx was also used to explore the immune landscape in GSE104954, and the correlation between immune infiltration and hub genes expression was investigated.
ResultsA total of 45 NAFLD-related share genes were obtained, and 4 were NAFLD-related hub genes. Enrichment analysis showed that the NAFLD-related share genes were significantly enriched in immune-related pathways, programmed cell death, and inflammatory response. ROC curve confirmed 4 NAFLD-related hub genes in CKD training set GSE104954 and other validation sets. Then they were used as diagnostic markers for CKD. Interestingly, these 4 diagnostic markers of CKD also showed good diagnostic value in the NAFLD date set GSE89632, so these genes may be important targets of NAFLD in the development of CKD. The expression levels of the 4 diagnostic markers for CKD were significantly correlated with the infiltration of immune cells.
Conclusion4 NAFLD-related genes (DUSP1, NR4A1, FOSB, ZFP36) were identified as diagnostic markers in CKD patients with NAFLD. Our study may provide diagnostic markers and therapeutic targets for CKD patients with NAFLD.

【背景】慢性肾脏病（Chronic kidney disease, CKD）与非酒精性脂肪性肝病（non-alcoholic fatty liver disease, NAFLD）均与免疫及炎症通路密切相关。本研究旨在探索合并NAFLD的CKD患者的诊断标志物。【方法】本研究从基因表达综合数据库（Gene Expression Omnibus, GEO）中筛选CKD及NAFLD的基因微阵列数据集，首先针对CKD数据集GSE10495开展差异表达基因（differentially expressed genes, DEGs）分析；采用加权基因共表达网络分析（Weighted Gene Co-Expression Network Analysis, WGCNA）方法，针对NAFLD数据集GSE89632构建基因共表达网络并识别其功能模块。通过取CKD的DEGs与NAFLD的模块基因的交集，获得NAFLD相关共有基因，随后对其开展功能富集分析。NAFLD相关核心基因通过Cytoscape软件与机器学习方法的交集筛选获得。采用受试者工作特征（Receiver Operating Characteristic, ROC）曲线评估NAFLD相关核心基因在CKD数据集及NAFLD数据集GSE89632中的诊断价值；此外，采用CIBERSORTx分析GSE104954数据集的免疫细胞浸润格局，并探究免疫浸润与核心基因表达的相关性。【结果】本研究共获得45个NAFLD相关共有基因，并筛选出4个NAFLD相关核心基因。富集分析结果显示，NAFLD相关共有基因显著富集于免疫相关通路、程序性细胞死亡及炎症反应通路。ROC曲线验证了4个NAFLD相关核心基因在CKD训练集GSE104954及其他验证集中的诊断效能，可将其作为CKD的诊断标志物。值得注意的是，这4个CKD诊断标志物在NAFLD数据集GSE89632中同样表现出良好的诊断价值，提示这些基因可能是NAFLD参与CKD发生发展的关键靶点。4个CKD诊断标志物的表达水平与免疫细胞浸润程度显著相关。【结论】本研究筛选出4个NAFLD相关基因（DUSP1、NR4A1、FOSB、ZFP36），可作为合并NAFLD的CKD患者的诊断标志物。本研究可为合并NAFLD的CKD患者提供潜在的诊断标志物及治疗靶点。