AUTHOR=Cao Yang , Du Yiwei , Jia Weili , Ding Jian , Yuan Juzheng , Zhang Hong , Zhang Xuan , Tao Kaishan , Yang Zhaoxu 

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

JOURNAL=Frontiers in Endocrinology

VOLUME=Volume 14 - 2023

YEAR=2023

URL=https://www.frontiersin.org/journals/endocrinology/articles/10.3389/fendo.2023.1125829

DOI=10.3389/fendo.2023.1125829

ISSN=1664-2392

ABSTRACT=Background Chronic 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 NFALD. Methods CKD 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 NFALD-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 NFALD related hub genes in the CKD datasets 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. Results A total of 30 NFALD-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, regulation of programmed cell death, and inflammatory response. ROC curve confirmed four NFALD-related hub genes in CKD training set GSE104954 and two 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 NFALD dataset GSE89632, so these genes may be important targets of NAFLD in the development of CKD. The expression levels of the four diagnostic markers for CKD were significantly correlated with the infiltration of immune cells. Conclusion Four genes were identified as diagnostic markers in CKD patients with NFALD. Our study may provide diagnostic markers and therapeutic targets for CKD patients with NAFLD.