MO616: The Genetic Background Predicts The Kind of Renal Damage and Fibrosis Progression in Diabetic Patients

Abstract

Abstract BACKGROUND AND AIMS Diabetic Nephropathy (DN) is the major causes of end-stage renal failure. DN diagnosis is based on typical histological features (Kimmelstiel–Wilson lesions, glomerular basal membrane thickening and proliferation of mesangial matrix). Not all diabetic patients with kidney disease develop true DN: kidney impairment can be due to a nondiabetic renal disease (NDRD) in the presence or absence of real DN. Thus, there is the need for noninvasive biomarkers, related to specific pathogenic processes, to discriminate DN and NDRD, and/or to predict DN onset. In the case of DN, there is extensive evidence in literature of genetic contribution to disease susceptibility and lots of efforts aim at the identification of specific loci. The research group demonstrated that a characteristic feature of DN is an increase in Lys63-ubiquitinated proteins at tubular level that leads to epithelial-to-mesenchymal transition (EMT) and finally to the progression of the tubular-interstitial fibrosis and the renal damage in DN patients (Pontrelli P et al. FASEB J 2017). Ube2V1 is the unique E2 enzyme known for producing Lys63-linked ubiquitin chains. Moreover, two miRNAs (miR27b-3p e miR1228-3p), which interact specifically with Ube2V1 transcript, predict the type of renal damage in diabetic patients and are related with kidney fibrosis (Conserva F et al. Sci Rep 2019). The goal of this project was to identify single nucleotide polymorphisms (SNPs) able to predict the different kind of renal damage and the progression of kidney disease in diabetic patients. METHOD We selected by UCSC genome, 10 HapMap SNPs of patients within coding and regulatory sequences both of miR27b-3p and miR1228-3p and Ube2V1 gene in order to evaluate their diagnostic and prognostic potential. The patients enrolled in this study were diabetic patients with a biopsy-proven DN diagnosis (DN), diabetic patients with a biopsy-proven diagnosis of other nephropathy than DN (NDRD), diabetic patients without clinical signs of impaired renal function (T2D), diabetic patients with a biopsy-proven coexistence of both conditions (ND + NDRD), non-diabetic patients with glomerulonephritis (CKD), non-diabetic patients without renal damage (CTRL). The DNA of 201 subjects (patients and controls) was isolated from blood samples, and 10 HapMap SNPs (rs3802456, rs4744422, rs10761364, rs7853195 in the control region of miR27b-3p; rs2306692, rs4759277, rs4759044, rs17547610, rs4759275 in the control region of miR1228-3p; rs761214 in the UBE2v1 gene) for each patient were analyzed using TaqMan real-time PCR. Glomerular and tubulointerstitial fibrosis in kidney biopsies was quantified on Sirius Red staining using the Aperio Imagescope software. RESULTS The analyzed SNPs showed a different genotype frequency among all the patients’ classes. Interestingly, SNPs rs4759275, rs4759277, rs4744422 and rs3802456 showed a statistically significant difference in genotype frequency comparing DN patients with CEU Population (Northern and Western European Ancestry in Utah) (P < 0.04, 0.05, 0.002, 0.001, respectively) and a control cohort enclosing CTRL and T2D (P < 0.02, 0.05, 0.001 and 0.04, respectively). SNPs rs761214, rs10761364 and rs2306692 genotypes frequency was statistically different among DN patients and the control cohort (P < 0.001). The genotype frequencies of the SNPs rs10761364 (P < 0.01) and rs7853195 (P < 0.04) resulted significantly related to tubular fibrosis in DN patients, while the SNPs rs4744422 (P < 0.03) and rs761214 (P < 0.02) to the glomerular one. In order to evaluate the diagnostic power of the identified SNPs, we used a logistic regression model, and we observed that the SNP rs10761364, adjusted for age, sex, eGFR and glycaemic index, discriminate DN from NDRD {P < 0.05; OR = 1.002–1.008; [95% confidence interval (CI)]}. CONCLUSION Our data demonstrated that the allelic forms of the analyzed SNPs are related to the different kind of renal damage in diabetic patients. Their prognostic and diagnostic potential could represent the starting point to create a new noninvasive diagnosis system based on clinical and genotyping data.