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- Title
Cytoplasmic Localization of WT1 and Decrease of miRNA-16-1 in Nephrotic Syndrome.
- Authors
Zapata-Benavides, Pablo; Arellano-Rodríguez, Mariela; Bollain-y-Goytia, Juan José; Franco-Molina, Moisés Armides; Rangel-Ochoa, Gloria Azucena; Avalos-Díaz, Esperanza; Herrera-Esparza, Rafael; Rodríguez-Padilla, Cristina
- Abstract
Nephrotic syndrome (NS) is a glomerular disease that is defined by the leakage of protein into the urine and is associated with hypoalbuminemia, hyperlipidemia, and edema. Steroid-resistant NS (SRNS) patients do not respond to treatment with corticosteroids and show decreased Wilms tumor 1 (WT1) expression in podocytes. Downregulation of WT1 has been shown to be affected by certain microRNAs (miRNAs). Twenty-one patients with idiopathic NS (68.75% were SSNS and 31.25% SRNS) and 10 healthy controls were enrolled in the study. Podocyte number and WT1 location were determined by immunofluorescence, and the serum levels of miR-15a, miR-16-1, and miR-193a were quantified by RT-qPCR. Low expression and delocalization of WT1 protein from the nucleus to the cytoplasm were found in kidney biopsies of patients with SRNS and both nuclear and cytoplasmic localization were found in steroid-sensitive NS (SSNS) patients. In sera from NS patients, low expression levels of miR-15a and miR-16-1 were found compared with healthy controls, but only the miR-16-1 expression levels showed statistically significant decrease (p=0.019). The miR-193a expression levels only slightly increased in NS patients. We concluded that low expression and delocalization from the WT1 protein in NS patients contribute to loss of podocytes while modulation from WT1 protein is not associated with the miRNAs analyzed in sera from the patients.
- Subjects
MEXICO; ACADEMIC medical centers; BIOMARKERS; BIOPSY; STATISTICAL correlation; DRUG resistance; EPITHELIAL cells; FLUORESCENT antibody technique; GENE expression; NEPHROTIC syndrome; POLYMERASE chain reaction; PROBABILITY theory; PROTEINS; RNA; T-test (Statistics); CONTROL groups; DATA analysis software; DESCRIPTIVE statistics; SEQUENCE analysis
- Publication
BioMed Research International, 2017, Vol 2017, p1
- ISSN
2314-6133
- Publication type
Article
- DOI
10.1155/2017/9531074