Unknown

Dataset Information

0

Extracellular vesicle-derived AEBP1 mRNA as a novel candidate biomarker for diabetic kidney disease.


ABSTRACT:

Background

A 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.

Methods

Candidate 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.

Results

Fifteen 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.

Conclusions

Our 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.

SUBMITTER: Tao Y 

PROVIDER: S-EPMC8325821 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature

altmetric image

Publications

Extracellular vesicle-derived AEBP1 mRNA as a novel candidate biomarker for diabetic kidney disease.

Tao Yiying Y   Wei Xing X   Yue Yue Y   Wang Jiaxin J   Li Jianzhong J   Shen Lei L   Lu Guoyuan G   He Yang Y   Zhao Shidi S   Zhao Fan F   Weng Zhen Z   Shen Xiahong X   Zhou Ling L  

Journal of translational medicine 20210731 1


<h4>Background</h4>A 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.<h4>Methods</h4>Candidate 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 diagno  ...[more]

Similar Datasets

| S-EPMC7789228 | biostudies-literature
| S-EPMC11399882 | biostudies-literature
| S-EPMC10793515 | biostudies-literature
| S-EPMC11080797 | biostudies-literature
| S-EPMC10378442 | biostudies-literature
| S-EPMC10646536 | biostudies-literature
| S-EPMC7370073 | biostudies-literature
| S-EPMC8485336 | biostudies-literature
| S-EPMC7881020 | biostudies-literature
| S-EPMC8067192 | biostudies-literature