| Background and objective: Uremia is a common syndrome that occurs in nearly all end-stage kidney diseases and involves a series of clinical manifestations,such as metabolic disorder and multiple organ failure.The etiology of uremia is very complex,and its molecular mechanism is more complex than other single diseases.So it has certain limitations to study the incidence and development mechanism of uremia only from the molecular aspect.Therefore,it may be a new line of research into uremia clinical treatment to study the molecular biology mechanism and explore relevant regulatory networks of uremia based on integration of various molecular omics.In this study,for a more comprehensive understanding of the mechanisms involved in uremia,a wholegenome microarray case-control study of 75 uremia patients and 20 healthy controlsare analyzed to study changes in transcriptome expression and cellular mechanisms that are relevant to uremia.Lots of methods(gene co-expression network analysis and mi RNA enrichment analysis etc.)are used in this study to investigate the molecular mechanisms from various RNA levels.Methods:(1)A whole-genome microarray case-control study of 75 uremia patients and 20 healthy controls included in the National Center for Biotechnology Information(NCBI)Gene Expression Omnibus(GEO)isanalyzed.Then the Significance Analysis of Microarrays(SAM)algorithm(|log2(fold change)|>1;FDR<0.05)is adopted to screendifferentially expressed genes(DEGs)between uremia patients and control subjects.Gene co-expression network analysis is performed to construct co-expression networks using differentially expressed genes(DEGs)in uremia(|r|>0.9 and P <0.01).The hub models of co-expressed gene networks by MCODE(degree =2,node score=0.2,k-core=2,max depth =100),and mi RNA enrichment analysis is used to detect key mi RNAs in each hub module(P<0.05).(2)The microarray isre-annotated to probe into lnc RNAs in ENCODE project.Then the Significance Analysis of Microarrays(SAM)algorithm(|log2(fold change)|>1;FDR<0.05)is used to screen differentially expressed lnc RNAs between uremia patients and control subjects.Gene co-expression network analysis and biological functional enrichment analysis are performed to construct co-expression networks related to the differentially expressed lnc RNAs a(|r|>0.9 and P <0.01).Then the up-stream regulated mi RNAs and down-stream interacted proteins arepredicted by starbase database.(3)Cytoscape software is used to integrate the mi RNA regulatory core gene coexpression network module with the lnc RNA co-expression network and the upstream and downstream regulatory network of lnc RNA,and to obtain the whole RNA interactive network including lnc RNA,m RNA and mi RNA.Then calculate the topological parameters(dgree,betweeness,Closeness,Bottleneck)of each node in the network,and extracte the nodes with high degree,betweeness,closeness or bottleneck to construct a key regulated network involved in uremia.Results:(1)We find 9 co-expressed hub modules that are implicated in uremia.Thesemodules are enriched in specific biological functions,including " proteolysis","membrane-enclosed lumen",and "apoptosis".Finally,by mi RNA enrichment analysis to detect key mi RNAs in each hub module we findfifteenmi RNAs that are specifically targeted to uremia-related hub modules.Of these,mi RNA-21-3p and mi RNA-210-3p were identified in other studies as being important to uremia.(2)We identifies three lnc RNAs(LINC00342,LINC00607,LINC01553)are differentially expressed in peripheral blood of uremia,and three gene co-expression networks are identified,and by biological functional enrichment analysis we find that these lnc RNAsare involved in biological functions and pathways related to chronic renal failure.In addition,three lnc RNAs upstream and downstream interaction molecules are screened.These findings suggest that the three lnc RNAs are associated with uremia,and that the molecular and functional aspects of these are worthy of further investigation.(3)An interaction network including m RNA,mi RNA,lnc RNAis constructed.The core sub-network consists of three RNA(LINC00342,LINC00607 and hsa-mi R-154-5p)and other relevant genes,which are worth further study and verification.Conclusions:(1)Lots of differentially expressed genes affect uremia development by participating into such biological functions as proteolysis,inflammatory response,etc.(2)LINC00342,LINC00607 and hsa-mi R-154-5p affect uremia development by participating into inflammatory response.(3)The study integrates the biological functions,genes,lnc RNAs and mi RNAs that underpin the network modules,which is of fundmental significance to elucidate the specific molecular mechanism of uremia.(4)Lots of useful and novelty bio-informatics methods and strategyare used in the study,which will serve as reference for other researches related to gene expression profile experiments. |
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