Biomarkers Of Circulating Exosomes In Diabetic Kidney Disease Based On Proteomics

ObjectDiabetic kidney disease,a common complication of diabetes mellitus,is a chronic progressive disease.In severe cases,it may eventually progress to end-stage renal disease.Due to the latent progression of diabetic kidney disease,urinary microalbumin creatinine ratio as an auxiliary indicator for early diagnosis for early diagnosis has certain limitations.Exosomes are vesicles that can realize intercellular communication and material exchange.Plasma exosomes can comprehensively and stably reflect changes in diseases,while proteomics can systematically analyze changes in proteins in samples.The aim of this study was to use plasma exosome proteomics to found possible early diagnostic markers for diabetic renal disease.MethodsPlasma of healthy people,patients with type 2 diabetes and patients with type 2 diabetic kidney disease were collected and exosomal proteins were studied.According to the urinary microalbumin creatinine ratio and clinical manifestations,patients were divided into three groups:5 people in healthy control group,5 patients in type 2 diabetes group,and 5 patients in type 2 diabetes with renal disease group.Circulating exosomes were isolated by ultracentrifugation,and proteins of three groups with difference ratio greater than 1.5 timeswere identified through label-free analysis and the protein database.Based on the differences of protein distribution in the three groups,bioinformatics analysis results and protein interaction relations,proteins were selected for validation by parallel reaction monitoring in healthy control group,type 2 diabetes group,and type 2 diabetes with renal disease group.Results391 quantifiable proteins were detected from the circulating exosomes by label-free analysis.45 differential proteins were specifically expressed in type 2 diabetes group,37 differential proteins were specifically expressed in diabetic kidney disease group,and 61 differential proteins were jointly expressed in type 2 diabetes and diabetic kidney disease groups by screening with a difference of more than 1.5 times.From the healthy group to the diabetes group to the diabetic kidney disease group,16 proteins were continuously upregulated,including IGHG2,APOC3,IHGV3-33,VCL,IGHV3-64D,IGHA1,IGHV1-69D,IGKV1-37,QSOX1,C7,CRTAC1,TRAV30,SERPINA5,CFHR3,FGL1 and IGF2R,14 proteins were continuously downregulated,including IGLV4-60,HPR,IGKV6-21,IGLV4-69,PTPN1,TTN,APOL1,PLA2G7,FLNC,FCN3,ORM2,C4BPB,PROS1 and IGKV2D-30,and EFEMP1 was firstly downregulated and then significantly upregulated.The results of protein-protein interaction network showed that the value of degree between proteins specific expressed in diabetic kidney disease and proteins common expressed in diabetes and diabetic kidney disease was higher than that between proteins specific expressed in diabetic kidney disease and proteins specific expressed in diabetes,which indicated that proteins specific expressed in diabetic kidney disease interacted more closely with proteins common expressed in diabetes and diabetic kidney disease.The expression trend of 7 proteins in the validation group was consistent with that in the discovery group,namely APOC3,APOA4,FCN3,IGKV2D-30,C7,EFEMP1 and PLA2G7.According to clinical correlation analysis and ROC curve analysis,APOA4,APOC3 and EFEMP1 proteins may play an important role in diabetic kidney disease.In the validation group,the expression of APOA4,APOC3 and EFEMP1 in the diabetic kidney disease group were higher than that in the type 2 diabetes group and significantly higher than that in the healthy control group(p<0.05),which were consistent with the results in the discovery phase,and they were positively correlated with the urinary microalbumin(rAPOA4=0.80,rAPOC3=0.65,rEFEMP1=0.91,p<0.05)and urinary microalbumin creatinine ratio(rAPOA4=0.75,rAPOC3=0.63,rEFEMP1=0.89,p<005).The AUC of APOC3 for distinguishing diabetic kidney disease from non-diabetic kidney disease was 0.775(95%CI 0.605-0.945).When the critical value was 1.0800,the sensitivity and specificity were 90%and 75%respectively.The AUC of APOA4 for distinguishing diabetic kidney disease from non-diabetic kidney disease was 0.958(95%CI was 0.892-1.000).When the critical value was 1.0500,the sensitivity and specificity were 90%and 90%respectively.The AUC of EFEMP1 for distinguishing diabetic kidney disease from non-diabetic kidney disease was 0.990(95%CI was 0.964-1.000).When the critical value was 1.1250,the sensitivity and specificity were 90%and 100%respectively.ConclusionsProteomics showed that the proteins in diabetes and diabetic kidney disease were significantly different,and their functions and pathways were also significantly different.The results of protein-protein interaction indicated the transformation from diabetes to diabetic kidney disease to a certain extent.According to clinical correlation analysis and ROC curve analysis,the circulating exosome APOA4,APOC3 and EFEMP1 can better distinguish diabetes and diabetic renal disease,which palyed an important role in diabetic kidney disease,and can provide a basis for the subsequent development of clinical marker detection methods that can quickly identify diabetes and diabetic kidney disease.