MO611: Glycated Albumin Levels Predict The Type of Kidney Damage in Diabetic Patients

Abstract

Abstract BACKGROUND AND AIMS Diabetes mellitus remains the most frequent cause of end-stage renal disease (ESRD) in developing countries. The main determinant of the onset of nephropathy in diabetes is hyperglycemia which brings to glycation of albumin and haemoglobin with higher concentration of AGEs (advanced glycation end products), finally leading to fibrosis, inflammation and albuminuria. Glycated albumin (GA) was introduced as an alternative to hemoglobin A1c (HbA1c) for glycemic control in the CKD population, with some advantages for diabetic patients with diabetic kidney disease (DKD), since it is not influenced by anemia and associated treatments and it is not affected by serum albumin levels. Although some evidences in literature demonstrated that GA is superior to HbA1c in assessing blood glucose control in DKD (Gan T et al. J Diabetes Complications. 2018); however, KDIGO Guidelines still recommend HbA1c, although underlying some limitations in the context of DKD, meaning that new markers are needed in order to monitor this class of diabetic patients. Kidney disease in diabetic patients can include different kind of renal damage ranging from real diabetic nephropathy (DN, with Kimmelstiel–Wilson lesions, glomerular basal membrane thickening, proliferation of mesangial matrix) to nondiabetic renal disease (NDRD), in the presence or absence of real DN, thus influencing prognosis and treatment. The purpose of the study was to evaluate the clinical utility of the GA dosage, alone or with other molecular and clinical markers as noninvasive biomarkers for the prediction of the progression and type of kidney damage in the diabetic patient. METHOD We enrolled 108 diabetic patients in follow-up at our center, 90 with a biopsy-proven diagnosis of kidney disease and 18 with no kidney dysfunction. Among the 90 patients, 51 had real diabetic nephropathy (DN) or mixed forms (DN + NDRD) and 39 had non-diabetic renal disease (NDRD). GA dosage was obtained by QuantILab® Glycated Albumin assay (Instrumentation Laboratory SpA, Milan, Italy). qPCR was used to evaluate urinary levels of miR27b-3p, a biomarker that predicts the kind of renal damage in diabetic patients and is related to kidney fibrosis (Conserva F et al. Sci Rep. 2019). Statistical analysis was performed using ‘SPSS Statistical Software.’ RESULTS We observed that GA values had a significantly different distribution among DN, NDRD and diabetic patients without renal dysfunction (P = 0.003); conversely, there was no statistical difference in HbA1c distribution although a trend was visible. In the entire cohort, only GA levels, but not HbA1c levels, were significantly correlated with fasting glucose (P = 0.001) and the duration of diabetes (P = .001). In the single classes, only in DN patients there was a significant correlation between GA and diabetes duration (P = .02) and GA and HbA1c (P = 0.01) but not in the NDRD class (P = 0.43). We then applied a multivariate logistic regression model to discriminate real DN and NDRD. We demonstrated that GA is the only significant predictor of real DN in a model corrected for sex, age and serum creatinine {P = 0.009; OR = 0.757–0.962; [95% confidence interval (CI)]}, whereas the same logistic regression model with HbA1c demonstrated no significance (P = 0.082). In the same cohort, we also evaluated miR-27b-3p expression levels, whose levels are correlated with renal fibrosis in DN, and we observed that there was a significant and direct correlation also with GA levels (P = 0.001), thus suggesting the possibility to integrate these biomarkers to predict the kind of renal damage in diabetic patients. CONCLUSION Our study described for the first time the role played by GA as a diagnostic marker in the identification of the different kind of renal damage in diabetic patients. All these evidences support the need to introduce GA as an index of glycemic control to be associated with other molecular markers, such as miRNAs, in order to noninvasively diagnose the kind of renal damage in diabetic patients.