Study On Screening Serum MicroRNAs As Biomarkers Of Chronic Kidney Disease Based On RNA-seq

Chronic kidney disease(CKD)is a common disease that endangers human health seriously.The course of this disease is progressive and irreversible,leading to end-stage renal disease(ESRD).After KDIGO proposed a unified definition and staging of CKD,many countries around the world have successively carried out large-scale studies on epidemiology of CKD.In 2017,the number of CKD patients worldwide was nearly 700 million,with a prevalence rate of about 9.1%,and 1.23 million deaths from CKD.In China,the total prevalence of CKD for adult population was about 10.8%.The number is about 135 million,and the death toll has reached about 190 thousands.CKD has seriously affected the life quality of patients,and brought heavy mental pressure and economic burden to patients and their families.At the same time,it has consumed huge social medical resources around the world.With the improvement of people's living standards,changes in dietary patterns,population aging,infections and irrational use of drugs in daily life,the incidence of CKD worldwide will increase year by year at a rate of 8%.It is estimated that CKD will be the fifth leading cause of human death in 2040.Therefore,how to prevent CKD scientifically and effectively is an important problem that needs to be solved urgently in the world.A large number of research results have proved that the early clinical symptoms of CKD patients are often not obvious,and they can't receive early diagnosis and drug intervention in time.So,most patients are clinically diagnosed until they have obvious clinical symptoms,or even severely impaired renal function,leading to lost the best treatment opportunity.Therefore,in recent years,the focus of the international nephrology community is changed to screen,diagnose,intervene,prevent and monitor CKD in the early stage,and control the risk factors of high-risk groups,which may delay the progressive deterioration of renal function,and reduce cardiovascular complications and the overall mortality of CKD patients.However,the current diagnostic methods,such as serum creatinine(s Cr)pathological examination of kidney biopsy,and urine protein test,have not yet fully met the clinical needs.Therefore,it is of great significance and scientific value to find a dynamic,objective,highly sensitive,non-invasive or low-traumatic diagnostic method for early diagnosis of kidney disease in clinical practice.micro RNA(mi RNA)is a type of endogenous non-coding single-stranded RNA that is widely present in animals and plants.Generally,it acts on the 3'untranslated region(UTR)of the target gene to degrade or inhibit the translation process of target m RNA,which plays important physiological functions in cell proliferation,differentiation,apoptosis,and metabolism.Some studies have found that mi RNAs exist widely and stably in various body fluids such as serum,plasma,urine,and saliva,which are known as circulating mi RNAs.Because mi RNAs in serum or urine are non-invasive or low-invasive,and stable expression and convenient for storage,they are often used as new biomarkers for the diagnosis and prognosis of various diseases.A few studies have confirmed that mi RNAs in urine can be used in the diagnosis and prognosis of some kidney diseases.However,the role of serum mi RNAs in the diagnosis of CKD is limited in the literatures so far.If serum mi RNAs were used as biomarkers,their expression level must be accurately measured firstly.At present,quantitative real-time transcription PCR(q RT-PCR)or c DNA chip are commonly used methods for the quantification of serum mi RNAs.Although these methods have their own advantages,but also have some shortcomings.With the rapid development of science and technology,especially in high-throughput sequencing,next-generation sequencing(NGS),also known as RNA sequencing(RNA-seq),has emerged,which can perform parallel pairs at a time.Hundreds of thousands to millions of DNA molecules can be sequenced at the same time,which has also the characteristics of wide detection range,high throughput,high accuracy,high sensitivity,good repeatability,reliable analysis,and less RNA input.More importantly,new transcripts and spliced variants can be discovered without design probes in advance.In addition,the continuous development of large-scale sequencing platforms has simplified the sequencing process and significantly reduced the cost in recent years.Therefore,RNA-seq as a powerful tool is widely used in clinical detection and scientific research of disease-related genes.Objective: To screen the differentially expressed mi RNAs as biomarkers for the occurrence and development of CKD in the serum of patients with CKD1 and CKD5 by RNA-seq.Methods:1.Collecting serum samples: we collected serum samples of CKD1(n=15)and CKD5 patients(n=30)caused by primary glomerulonephritis and healthy controls(n=15)in this study.Each five samples from the same group were premixed with equal volume for subsequent sequencing.2.Screening differentially expressed mi RNAs by RNA-seq: total RNA from each pooled sample was isolated.RNA quality and quantity were measured,and RNA was used to prepare the mi RNA sequencing library.Then,we sequenced and performed data analysis.The criteria for differentially expressed mi RNAs in this study were: the fold change ?2.0,P<0.05,and mean read counts of mi RNA ?50.The hierarchical clustering heatmaps were constructed based on the differentially expressed mi RNAs.3.Bioinformatics analysis: the target genes of differentially expressed mi RNAs were predicted based on the Targetscan and mirdb V5 databases,and the target genes predicted by the two databases were used as the basis for further analysis.Top GO was used to perform GO analysis on the basis of the target genes of top10 differentially expressed mi RNAs.Top10 was used to perform KEGG pathway analysis on the basis of the target genes of differential mi RNAs.We selected the Genecards database,used "kidney diseases" as the key words to search for currently known genes related to kidney diseases.4.q RT-PCR validation of differentially expressed mi RNAs: serum samples were collected from 25 cases of CKD1,40 cases of CKD5 and 20 cases of healthy controls.Total RNA from each sample was isolated,and RNA quality and quantity were measured.We performed reverse transcription,q RT-PCR,and statistical analysis.Results:1.The demographic data of CKD1 and CKD5 patients,and healthy controls involved in this study: overall,there were 145 participants enrolled in this study.In the initial stage of biomarker discovery,there were 60 participants enrolled,including CKD1(n=15),CKD5(n=30),and control(n=15).There were 36 men and 24 women,with nine men and six women in the CKD1 group,18 men and 12 women in the CKD5 group,and nine men and six women in the control group.The average age of the participants in the CKD1,CKD5,and control groups was 51.40±10.12 years,53.80±12.75 years,and 52.40±7.75 years,respectively.In the following stage of biomarker validation,85 participants were enrolled,including CKD1(n=25),CKD5(n=40),and control(n=20).There were 53 men and 32 women,with 16 men and nine women in the CKD1 group,25 men and 15 women in the CKD5 group,and 12 men and eight women in the control group.The average age of participants in the CKD1,CKD5,and control groups was 51.16±9.75 years,50.70±14.75 years,and 49.39±11.10 years,respectively.2.The results of differentially expressed mi RNAs screened by RNA-seq:according to the criteria,a total of 98 differentially expressed mi RNAs were obtained.The Venn diagram analysis and hierarchical clustering heatmap analysis were constructed according to the different groups,respectively.Compared with the healthy control group,there were 20 differentially expressed mi RNAs in the CKD1 group(9 up-regulated,and 11down-regulated),and 42 differentially expressed mi RNAs in the CKD5 group(5 up-regulated and 37 down-regulated).Compared with the CKD1 group,there were 70 differentially expressed mi RNAs in the CKD5 group(14 were up-regulated and 56 down-regulated.The Venn diagram results showed that32 mi RNAs appeared 2 times,and only one mi RNAs,mi R-483-5p appeared 3times among the differentially expressed mi RNAs by pairwise comparison,which may be of great significance in the development of CKD.3.Prediction of target genes of differentially expressed mi RNAs: there were 98 differentially expressed mi RNAs predicted more than 5200 target genes,some of which can be predicted to regulate multiple target genes,and some genes can be regulated by multiple mi RNAs?4.GO analysis of differentially expressed mi RNAs: according to the predicted target genes of differentially expressed mi RNAs,we conducted GO enrichment analysis of the target genes from three aspects: biological process(BP),cell composition(CC),and molecular function(MF).In the biological process items for different groups,the predicted target genes were found to be involved mostly in various forms of metabolic processes.In the molecular function items for different groups,the predicted target genes were found to be involved mostly in different forms of transcriptional regulation.5.KEGG analysis of differentially expressed mi RNAs: according to the score,the top 10 KEGG signaling pathways in different groups were listed.The results showed that the predicted target genes were participated in a variety of metabolic pathways,such as transforming growth factor-?(TGF-?),autophagy,AMP-dependent protein kinase(AMPK),mammalian target of rapamycin(m TOR),forkhead box protein O(Fox O),mitogen-activated protein kinase(MAPK),and other signaling pathways.6.Validation of differentially expressed mi RNAs by q RT-PCR: we selected mi R-483-5p and mi R-363-3p for further verification by q RT-PCR in more clinical samples.The results showed that compared with the healthy control group,the expression of mi R-483-5p was up-regulated in both the CKD1 group and the CKD5 group,and the fold changes were 2.56(P<0.01)and 18.77(P<0.01).Compared with the healthy control group and CKD1 group,the expression of mi R-363-3p was low in the CKD5 group,and the fold changes were 0.27(P<0.05)and 0.48(P<0.05),respectively.The results of RNA-seq and q RT-PCR for mi R-483-5p and mi R-363-3p were similar,which indicated that the two mi RNAs may be used as new biomarkers for the early diagnosis and condition assessment of CKD.7.Prediction of target genes related to kidney disease for mi R-483-5p and mi R-363-3p: the results showed that mi R-483-5p had 7 target genes,and mi R-363-3p had 160 target genes associated kidney diseases.Conclusions:1.In this study,we screened the differentially expressed mi RNAs in the serum of CKD1,CKD5 patients and healthy controls by RNA-seq method,which may be acted as the basic work for identifying serum biomarkers of CKD in the following study.2.Bioinformatics analysis results showed that the predicted target genes of differentially expressed mi RNAs were involved in various forms of metabolic processes and transcriptional regulation,as well as some signal pathways related to the development of kidney diseases.3.Both RNA-seq and q RT-PCR results showed that mi R-483-5p was over-expressed in the serum of CKD1 and CKD5 patients,and mi R-363-3p was down-regulated in the serum of CKD5 patients.They were expected to be as new biomarkers for the early diagnosis and condition assessment of CKD.