AUTHOR=Li Zukai , Feng Junxia , Zhong Jinting , Lu Meizhi , Gao Xuejuan , Zhang Yunfang 

TITLE=Screening of the Key Genes and Signalling Pathways for Diabetic Nephropathy Using Bioinformatics Analysis

JOURNAL=Frontiers in Endocrinology

VOLUME=Volume 13 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/endocrinology/articles/10.3389/fendo.2022.864407

DOI=10.3389/fendo.2022.864407

ISSN=1664-2392

ABSTRACT=Background: This study was to investigate biological markers in diabetic nephropathy (DN) and explore their underlying mechanisms.
Methods: Four datasets GSE30528, GSE47183 , GSE104948 and GSE96804 were downloaded from Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were identified by limma package. Using the RobustRankAggreg package to screen the overlapping DEGs.Then, the protein-protein interactions (PPIs) of the overlapping DEGs were analyzed by the search tool for the retrieval of interacting genes/proteins (STRING) database, ten algorithms to screen hub genes by R package “UpSetR”. Through logistic regression analysis further screen the hub genes. The diagnostic effectiveness of hub gene was predicted by Receiver Operator Characteristic Curve(ROC) analysis.Correlation analysis and Enrichment analysis for individual hub genes was implemented to make further identification of underlying functions of the interesting hub gene involved in DN.
Results: In total, 55 DEGs, including 38 upregulated and 17 downregulated genes, were identified from the three datasets. Four hub genes (FN1, CD44, C1QB, C1QA) were screened by R package “UpSetR”. And FN1 was identified as a crucial biological marker of DN. Correlation analysis and Enrichment analysis show that FN1 was positively correlated with four genes (COL6A3,COL1A2,THBS2 and CD44) and play a key role in ECM-receptor interaction.
Conclusions: We confirmed the FN1 may can be used as diagnostic marker of DN and play important roles in the pathogenesis of DN.