Type 2 diabetes mellitus (DM) globally affects 18–20 % of adults over the age of 65 years. Diabetic kidney disease (DKD) is one of the most frequent and dangerous complications of DM2, affecting about one-third of the patients with DM2. In addition to the pancreas, adipocytes, liver, and intestines, the kidneys also play an important role in glycemic control, particularly due to renal contribution to gluconeogenesis and tubular reabsorption of glucose. In this review article, based on a report of discussions from an interdisciplinary group of experts in the areas of endocrinology, diabetology and nephrology, we detail the relationship between diabetes and kidney disease, addressing the care in the diagnosis, the difficulties in achieving glycemic control and possible treatments that can be applied according to the different degrees of impairment. Glucose homeostasis is extremely altered in patients with DKD, who are exposed to a high risk of both hyperglycemia and hypoglycemia. Both high and low glycemic levels are associated with increased morbidity and shortened survival in this group of patients. Factors that are associated with an increased risk of hypoglycemia in DKD patients include decreased renal gluconeogenesis, deranged metabolic pathways (including altered metabolism of medications) and decreased insulin clearance. On the other hand, decrease glucose filtration and excretion, and inflammation-induce insulin resistance are predisposing factors to hyperglycemic episodes. Appropriate glycaemic monitoring and control tailored for diabetic patients is required to avoid hypoglycaemia and other glycaemic disarrays in patients with DM2 and kidney disease. Understanding the renal physiology and pathophysiology of DKD has become essential to all specialties treating diabetic patients. Disseminating this knowledge and detailing the evidence will be important to initiate breakthrough research and to encourage proper treatment of this group of patients.

Studies on metabolomics and CKD have primarily addressed CKD incidence defined as a decline on eGFR or appearance of albuminuria in the general population, with very few evaluating hard outcomes. In the present study, we investigated the association between metabolites and mortality and ESRD in a CKD cohort. Data on 454 participants of the Progredir Cohort Study, Sao Paulo, Brazil were used. Metabolomics was performed by GC-MS (Agilent MassHunter) and metabolites were identified using Agilent Fiehn GC/MS and NIST libraries. After excluding metabolites present in <50% of participants, 293 metabolites were analyzed. An FDR q value <0.05 criteria was applied in Cox models on the composite outcome (mortality or incident renal replacement therapy) adjusted for batch effect, resulting in 34 metabolites associated with the outcome. Multivariable-adjusted Cox models were then built for the composite outcome, death, and ESRD incident events. Competing risk analysis was also performed for ESRD. Mean age was 68±12y, mean eGFR-CKDEPI was 38.4±14.6 ml/min/1.73m² and 57% were diabetic. After adjustments (GC-MS batch, sex, age, DM and eGFR), 18 metabolites remained significantly associated with the composite outcome. Nine metabolites were independently associated with death: D-malic acid (HR 1.84, 95%CI 1.32–2.56, p = 0.0003), acetohydroxamic acid (HR 1.90, 95%CI 1.30–2.78, p = 0.0008), butanoic acid (HR 1.59, 95%CI 1.17–2.15, p = 0.003), and docosahexaenoic acid (HR 0.58, 95%CI 0.39–0.88, p = 0.009), among the top associations. Lactose (SHR 1.49, 95%CI 1.04–2.12, p = 0.03), 2-O-glycerol-α-D-galactopyranoside (SHR 1.76, 95%CI 1.06–2.92, p = 0.03), and tyrosine (SHR 0.52, 95%CI 0.31–0.88, p = 0.02) were associated to ESRD risk, while D-threitol, mannitol and myo-inositol presented strong borderline associations. Our results identify specific metabolites related to hard outcomes in a CKD population. These findings point to the need of further exploration of these metabolites as biomarkers in CKD and the understanding of the underlying biological mechanisms related to the observed associations.

MYH9 polymorphisms have been described to be associated with the risk of CKD in non-diabetic nephropathy, HIV nephropathy and FSGS. Predominating in black descendants, MHY9 genetic variants could partially explain the excess risk of CKD associated with African ancestry. However, recent data suggests that APOL1 gene co-segregate with MYH9, and could be the gene truly associated with CKD risk. In this study, we evaluated the role of MYH9 and APOL1 gene polymorphisms in the risk of CKD in Brazilian patients with lupus nephritis (LN). A retrospective analysis of 196 LN patients was done. MYH9 rs4821480, rs2032487, rs4821481 and rs3752462, APOL 1rs73885319, rs16996616, rs60910145, rs71785313, and APOL3 rs11089781 gene polymorphisms were determined. Genetic ancestry was ascertained both by autossomal ancestry and mitochondrial haplogroup. Primary outcome was defined as doubling of serum creatinine (DC) or end stage renal disease (ESRD). Sixty-two patients presented the PO. In our population, MYH9 and APOL1 were not in LD. None APOL polymorphism was associated with the PO, whereas rs3752462 MYH9 polymorphism showed a positive association (HR3.72, 95%CI 1.47–9.38, p = 0.005). When we analyzed the MYH9 E1 haplotype, the GCCT carriers (1 or 2 alelles present in 29.7% in the PO group vs. 18.5% in controls) showed a significant association to the risk of PO, even after adjustments for baseline estimated creatinine clearance and autossomal ancestry (HR 2.0, 95%CI 1.2–3.4, p = 0.01). Our results show that in our population MYH9, but not APOL1, gene polymorphisms confer an increased risk of CKD in LN patients, independently of race.

Coronary artery calcification (CAC) is a widespread condition in chronic kidney disease (CKD). Diet may play an important role in CAC, but this role is not clear. This study evaluated the association between macro-and micronutrient intakes and CAC in non-dialysis CKD patients. We analyzed the baseline data from 454 participants of the PROGREDIR study. Dietary intake was evaluated by a food frequency questionnaire. CAC was measured by computed tomography. After exclusion of participants with a coronary stent, 373 people remained for the analyses. The highest tertile of CAC was directly associated with the intake of phosphorus, calcium and magnesium. There was a higher intake of pantothenic acid and potassium in the second tertile. After adjustments for confounding variables, the intake of pantothenic acid, phosphorus, calcium and potassium remained associated with CAC in the generalized linear mixed models. In order to handle the collinearity between these nutrients, we used the LASSO (least absolute shrinkage and selection operator) regression to evaluate the nutrients associated with CAC variability. In this approach, the nutrients that most explained the variance of CAC were phosphorus, calcium and potassium. Prospective studies are needed to confirm these findings and assess the role of interventions regarding these micronutrients on CAC prevention and progression.

KEY WORDS: Renal insufficiency, chronic; Diet; Health surveys