The Analysis Of Transcriptomics Characteristics And Potential Biomarkers In Acute Kidney Injury

Acute kidney injury(AKI)is one of the common severe diseases in clinic.It is estimated that about 2.9 million adult AKI patients were hospitalized and 700,000 patients of them died in 2013 in China.Serum creatinine and urine volume are important indicators for the diagnosis of AKI,but these indicators do not have kidney specificity due to their susceptibility to many factors.In recent years,with the development of human genomics and biological data,the use of the microarray data of AKI can help us discover new biomarkers and potential pathophysiological mechanism of AKI at the gene level.Objective:To Mining the information characteristics of AKI microarray data;To Search for new and accurate biomarkers that can predict AKI early;To explore the pathophysiological mechanism related to this biomarker.Methods:AKI-related datasets were retrieved in the NCBI-GEO and EBI array-express databases.Then we re-analyzed for their associated renal cell microarray data by using web tools,R software.To screen differentially expressed genes(DEGs),we compared the experimental and control data in each study using “limma” package and GEO2 R.Then,we use “clusterProfiler” and “VennDiagram” packages to carry out gene ontology(GO)functional annotation and conduct Kyoto Encyclopedia Genes and Genomes(KEGG)pathway enrichment analysis.Through the construction of functional networks,cross-alignment,we determine key regulatory factors and mechanisms.Results:After screening,we determined four experimental data sets,GSE85957,GSE58438,GSE52004 and GSE27274.In GSE85957,1mg/kg and 3mg/kg Cisplatin(dose-dependent)AKI and 3-day,5-day,8-day,and 26-day(time-dependent)AKI models were established.we identified 1201,842,1849,1255,3940,3343,5220 and 2372 DEGs.At 1mg/kg group,7 common DEGs were obtained,including 2 consistently up-regulated and 1 consistently down-regulated;at 3mg/kg group,there were 224 common DEGs,109 up-regulated and 52 down-regulated.Comparing to 1mg/kg,158 DEGs were increased in 3mg/kg,including MDM2,JUNB,CD44,etc.Then we analyzed all experimental groups data,resulting in three genes with consistent expression,named NR1D1,CDKN1 A and LINGO4,of which the first two are up-regulated and the latter are down-regulated.In GSE52004,1559 DEGs were obtained,including 744 up-regulated and 815 down-regulated;in GSE27274,587 DEGs were obtained,of which 233 up-regulated and 354 down-regulated;in GSE58438,721 DEGs were obtained,including 438 up-regulated and 283 down-regulated.Finally,comparing all the datasets,10 common DEGs were obtained,which were TUBB6,LAMC2,PVR,ANXA2,FBLIM1,CD44,EGR2,RUNX1,ATF3,JUNB.GO function and KEGG pathway enrichment analysis of DEGs mentioned above,when AKI occurs,the main GO terms are DNA damage repair,regulation of cell cycle and stress response to various metabolic outputs.The main key signaling pathway is the MAPK signaling pathway.Conclusion:1.JUNB is a key target of AKI disease and a potential biomarker.2.DNA damage exists in the early stage of AKI.JUNB has a certain relationship with DNA damage and cell cycle arrest.MAPK signaling pathway is involved in this process.In AKI,the MAPK pathway up-regulates the expression of JUNB,causing cell cycle arrest to cope with DNA damage and provide a favorable protective mechanism,but with the increased expression of JUNB,it may lead to prolongation of cell cycle arrest and cause fibrosis.Therefore,it may become a biomarker for the early onset of AKI,revealing a new pathophysiological mechanism of AKI-CKD progression,and the upstream and downstream related proteins involved in this mechanism may be important indicators for evaluating AKI.