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Potential Value of Datura stramonium Agglutinin-recognized Glycopatterns in Urinary Protein on Differential Diagnosis of Diabetic Nephropathy and Nondiabetic Renal Disease
- Source :
- Chinese Medical Journal, Vol 131, Iss 2, Pp 180-187 (2018)
- Publication Year :
- 2018
- Publisher :
- Wolters Kluwer, 2018.
-
Abstract
- Background: Diabetic nephropathy (DN) is the most common and serious microvascular complication of diabetes. To date, the gold standard for identifying DN and nondiabetic renal disease (NDRD) is a renal biopsy; however, there is currently no reliable diagnostic marker to identify DN and NDRD in a noninvasive manner. This study aimed to investigate the different glycopatterns in urine specimens of DN patients and NDRD patients for a differential diagnosis. Methods: In total, 19 DN patients and 18 NDRD patients who underwent renal biopsies between March 2015 and March 2016 at the Chinese People's Liberation Army General Hospital were enrolled in this study. A lectin microarray was used to investigate the glycopatterns in the urinary protein of the 37 patients. Ratio analysis and one-way analysis of variance were used to screen altered glycopatterns. Then, the altered glycopatterns between the DN and NDRD groups were verified by a urinary protein microarray among another 32 patients (15 with DN and 17 with NDRD), and receiver operating characteristic (ROC) curve analysis was used to determine the diagnostic value of the altered glycopatterns in differentiating DN and NDRD. Finally, lectin blotting was used to evaluate the altered glycosylation in protein level. Results: The result of lectin microarrays revealed that the relative abundance of the (β-1,4)-linked N-acetyl-D-glucosamine (GlcNAc) recognized by lectin Datura stramonium agglutinin (DSA) was significantly higher in urinary protein in DN patients than that in NDRD patients (fold change >1.50, P < 0.001). Subsequently, the results of urinary protein microarrays were consistent with lectin microarrays (P < 0.05). Furthermore, the ROC curve showed that glycopatterns could effectively distinguish DN from NDRD patients (area under the ROC curve = 0.94, P < 0.001). DSA lectin blotting showed that glycoproteins, with a molecular weight of approximately 50,000, demonstrated a difference in urine samples between DN patients and NDRD patients. Conclusions: The relative abundance of (β-1,4)-linked GlcNAc recognized by lectin DSA and urinary glycoprotein with a molecular weight of approximately 50,000 are significantly different between DN and NDRD patients, indicating that the glycopatterns could be used as potential biomarkers for a differential diagnosis.
- Subjects :
- Diabetic Nephropathy
Glycopattern
Nondiabetic Renal Disease
Urinary Protein
Medicine
Subjects
Details
- Language :
- English
- ISSN :
- 03666999
- Volume :
- 131
- Issue :
- 2
- Database :
- Directory of Open Access Journals
- Journal :
- Chinese Medical Journal
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.f0ebd19846664526a576bf6101b3fc2e
- Document Type :
- article
- Full Text :
- https://doi.org/10.4103/0366-6999.222328