Identification of nephropathy predictors in urine from children with a recent diagnosis of type 1 diabetes

Abstract

Despite research progresses, the chance to accurately predict the risk for diabetic nephropathy (DN) is still poor. So far, the first evidence of DN is micro-albuminuria, which is detected only 10-20 years after the onset of diabetes. Our goal is to develop new predictive tools of nephropathy starting from urine, which can be easily obtained using noninvasive procedures and it is directly related to kidney. Since it is reasonable to suppose that, in predisposed patients, the mechanisms leading to nephropathy start acting since the diabetes onset, urine from children with recent diagnosis of type 1 diabetes was subjected to proteomic analysis in comparison to age-matched controls. Targeted confirmation was performed on children with a longer history of diabetes using Western Blotting and applying a urinary lipidomic approach. To definitively understand whether the observed alterations could be related to diabetic nephropathy, urine from diabetic adults with or without albuminuria was also examined. For the first time, lipid metabolisms of prostaglandin and ceramide, which are significantly and specifically modified in association with DN, are shown to be already altered in children with a recent diabetes diagnosis. Future studies on larger cohorts are needed to improve the validity and generalizability of these findings. Data are available via ProteomeXchange with identifier PXD011183 Submission details: Project Name: Urinary proteomics by 2DE and LC-MS/MS. Project accession: PXD011183 Project DOI: https://doi.org/10.6019/PXD011183 SIGNIFICANCE: Nephropathy is a very common diabetic complication. Once established, its progression can only be slowed down but full control or remission is achieved in very few cases, thus posing a large burden on worldwide health. The first evidence of diabetic nephropathy (DN) is micro-albuminuria, but only 30% of patients with micro-albuminuria progress to proteinuria, while in some patients it spontaneously reverts to normo-albuminuria. Thus, there is clear need for biomarkers that can accurately predict the risk to develop DN. Herein, by applying proteomic and lipidomic approaches on urine samples, we show that alteration of prostaglandin and ceramide metabolisms specifically occurs in association with DN. Interestingly, we demonstrate that the modification of these metabolic pathways is an early event in diabetic patients, suggesting the identified changed proteins as possible predictive biomarkers of diabetes-induced renal function decline.

Keywords: Diabetic complications; Diabetic nephropathy.; Lipidomics; Predictive biomarkers; Proteomics; Type 1 diabetes.