Abstract
BackgroundA novel and improved methodology is still required for the diagnosis of diabetic kidney disease (DKD). The aim of the present study was to identify novel biomarkers using extracellular vesicle (EV)-derived mRNA based on kidney tissue microarray data.MethodsCandidate genes were identified by intersecting the differentially expressed genes (DEGs) and eGFR-correlated genes using the GEO datasets GSE30528 and GSE96804, followed by clinical parameter correlation and diagnostic efficacy assessment.ResultsFifteen intersecting genes, including 8 positively correlated genes, B3GALT2, CDH10, MIR3916, NELL1, OCLM, PRKAR2B, TREM1 and USP46, and 7 negatively correlated genes, AEBP1, CDH6, HSD17B2, LUM, MS4A4A, PTN and RASSF9, were confirmed. The expression level assessment results revealed significantly increased levels of AEBP1 in DKD-derived EVs compared to those in T2DM and control EVs. Correlation analysis revealed that AEBP1 levels were positively correlated with Cr, 24-h urine protein and serum CYC and negatively correlated with eGFR and LDL, and good diagnostic efficacy for DKD was also found using AEBP1 levels to differentiate DKD patients from T2DM patients or controls.ConclusionsOur results confirmed that the AEBP1 level from plasma EVs could differentiate DKD patients from T2DM patients and control subjects and was a good indication of the function of multiple critical clinical parameters. The AEBP1 level of EVs may serve as a novel and efficacious biomarker for DKD diagnosis.
Highlights
A novel and improved methodology is still required for the diagnosis of diabetic kidney disease (DKD)
The National Kidney Foundation Kidney Disease Outcomes Quality Initiative (NKF-KDOQI) guidelines [17] and the Consensus for Prevention and Treatment of Diabetic Kidney Disease 2014 of Chinese Diabetes Society [18] were employed as the diagnostic criteria for DKD patients, and guidelines published in 2010 by the American Diabetes Association (ADA) were used for type 2 diabetes mellitus [19], whereas patients suffering from autoimmune, infectious, hematological, malignant, organic or inflammatory diseases; who underwent renal replacement therapy; who were morbidly obese with body mass index [BMI] ≥ 40 kg/m2; or who had cardiovascular diseases accompanying severe complications were excluded
Correlation between the expression level of extracellular vesicle (EV)‐derived Adipocyte enhancer binding protein 1 (AEBP1) and clinical indexes of DKD and exploration of the diagnostic efficacy of AEBP1 Since we observed the possible involvement of AEBP1 in the disease process of DKD, we evaluated the correlation between the expression level of EV-derived AEBP1
Summary
A novel and improved methodology is still required for the diagnosis of diabetic kidney disease (DKD). Extracellular vesicles (EVs), including exosomes, microvesicles and other extracellular vesicles, can be secreted by multiple types of cells under normal and disease conditions with a specific average size of approximately 50–200 nm [10, 11], and recent studies have shown that EVs could play important roles in intercellular communication signaling via several of their contents, including mRNAs, noncoding RNAs (miRNAs and long noncoding RNA) and proteins [12, 13]. Studies have shown that urinary EVs and bloodderived EVs could serve as biomarkers for DKD with the features of noninvasiveness and easy collection [14,15,16]; which type of EV-derived content is the most effective for diagnosing or monitoring a disease condition is worthy of exploration. We performed bioinformatics analysis to identify eGFR-correlated differentially expressed genes (DEGs) via previously published microarray datasets and validated the efficacy of selected genes in a cohort of DKD patients using plasma-derived EVs to provide a novel biomarker for DKD diagnosis
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
