Heterogeneity in renal structure has been described in t y p e 2 diabetic patients with both microalbuminuria and proteinuria; in fact, only a subset of type 2 diabetic patients have the typical diabetic glomerulopathy. Howe v e r, it is currently unknown whether abnormalities in albumin excretion rate (AER) have a different renal prognostic value depending on the underlying renal structure. Aims of this study were: 1) to study the course of renal function in type 2 diabetic patients with altered AER; 2) to evaluate the relationship between the course of glomerular filtration rate (GFR) and renal structure; and 3) to evaluate the relationship between the course of GFR and baseline AER levels, metabolic control, and blood pressure levels during a follow-up period of 4 years. A total of 108 type 2 diabetic patients, 74 with microalbuminuria (MA) and 34 with proteinuria (P), were recruited into a prospective study that encompassed: 1) a baseline kidney biopsy with morphometric measurements of glomerular parameters; 2) intensified antihypertensive treatment for an average 4-year period (blood pressure target < 1 4 0 / 9 0 mmHg); and 3) determinations of GFR at baseline and every 6 months. Mean (± SD) GFR significantly decreased from baseline in both MA (-1.3 ± 9.4 [95% CI -3.51 to +0.86], P < 0.05) and P (-3.0 ± 13.0 m l · min -1 · 1.73 m -2 per year [-7.71 to +1.61], P < 0.01). However, the changes in GFR were quite heterogeneous. Thus, on the basis of percent GFR change per year from baseline ( %GFR), both MA and P patients were defined as progressors or nonprogressors when they were below or above the median, respectively. Baseline parameters of glomerular structure had a strong influence on the course of GFR. Indeed, the odds ratios of being progressors significantly increased across the quartiles of baseline glomerular basement membrane (GBM) width and mesangial fractional volume [Vv(mes/glom)], being 2.71 and 2.85 higher, respectively, in the fourth quartile than in the first quartile (P < 0.01 for both). Conv e r s e l y, nonprogressors outnumbered progressors in the first quartile of GBM width (odds ratio: 2.14, P < 0.05) and in the first quartile of Vv(mes/glom) (odds ratio: 2.28, P < 0.01). Baseline albumin excretion rate (AER) did not influence %GFR; in fact, the number of progressors did not increase across quartiles of baseline AER among either MA or P. Similarly, mean blood pressure levels during follow-up (and intensified antihypertensive therapy) did not affect the course of GFR: the number of progressors and nonprogressors did not change across quartiles of mean blood pressure. In contrast, HbA 1 c during follow-up had an impact on % G F R : the odds ratio for being a progressor increased across quartiles of HbA 1 c , particularly for the highest quartile ( H b A 1 c >9.0%). In conclusion, the course of renal function is heterogeneous in type 2 diabetic patients with microalbuminuria or proteinuria. In fact, a subset of patients has a rapid decline in GFR over a 4-year followup period; these patient...

OBJECTIVE -Advanced glycation end products (AGEs), pentosidine and malondialdehyde (MDA), are elevated in type 2 diabetic subjects with coronary and carotid angiopathy. We investigated the relationship of AGEs, MDA, total reactive antioxidant potentials (TRAPs), and vitamin E in type 2 diabetic patients with and without peripheral artery disease (PAD).RESEARCH DESIGN AND METHODS -AGEs, pentosidine, MDA, TRAP, vitamin E, and ankle-brachial index (ABI) were measured in 99 consecutive type 2 diabetic subjects and 20 control subjects.RESULTS -AGEs, pentosidine, and MDA were higher and vitamin E and TRAP were lower in patients with PAD (ABI Ͻ0.9) than in patients without PAD (ABI Ͼ0.9) (P Ͻ 0.001). After multiple regression analysis, a correlation between AGEs and pentosidine, as independent variables, and ABI, as the dependent variable, was found in both patients with and without PAD (r ϭ 0.9198, P Ͻ 0.001 and r ϭ 0.5764, P Ͻ 0.001, respectively) but not in control subjects. When individual regression coefficients were evaluated, only that due to pentosidine was confirmed as significant. For patients with PAD, considering TRAP, vitamin E, and MDA as independent variables and ABI as the dependent variable produced an overall significant regression (r ϭ 0.6913, P Ͻ 0.001). The regression coefficients for TRAP and vitamin E were not significant, indicating that the model is best explained by a single linear regression between MDA and ABI. These findings were also confirmed by principal component analysis. CONCLUSIONS -Resultsshow that pentosidine and MDA are strongly associated with PAD in type 2 diabetic patients.

Diabetes is associated with a greatly increased risk of cardiovascular disease (CVD), which cannot be explained only by known risk factors, such as smoking, hypertension, and atherogenic dyslipidemia, so other factors, such as advanced glycation end-products (AGEs) and oxidative stress, may be involved. In this frame, hyperglycemia and an increased oxidative stress (AGE formation, increased polyol and hexosamine pathway flux, and protein kinase C activation) lead to tissue damage, thus contributing to the onset of cardiovascular complications. Several studies have identified in various cell systems, such as monocytes/macrophages and endothelial cells, specific cellular receptors (RAGE) that bind AGE proteins. The binding of AGEs on RAGE induces the production of cytokines and intracellular oxidative stress, thus leading to vascular damage. Soluble RAGE levels have been identified as hypothetical markers of CVD, but, in this regard, there are sparse and conflicting data in the literature. The purpose of this review was to examine all the available information on this issue with a view to clarifying or at least highlighting the points that are still weak, especially from the point of clinical view.

Glucose variability has recently been investigated in diabetic patients in several studies, but most of them considered only a few variability indicators and did not systematically correlate them with patients' HbA1c levels and other important characteristics. In thus study, the correlations between HbA1c levels and metabolic control (average glucose, AG), glucose variability (SD, CONGA, MAGE, MODD, BG ROC), hyperglycemia (HBGI), hypoglycemia (LBGI) and postprandial (AUC PP) indices were investigated in patients with type 1 and type 2 diabetes. The study involved 68 patients divided into 3 groups as follows: 35 patients had type 1 diabetes (group 1); 17 had type 2 diabetes and were taking multiple daily injections (MDI) of insulin (group 2); and 16 patients had type 2 diabetes treated with OHA and/or basal insulin (group 3). The indicators were obtained over at least 48 h using a continuous glucose monitoring (CGM) system. HbA1c levels were measured at the baseline and after CGM. HbA1c correlated significantly with AG (r = 0.74), AUC PP (r = 0.69) and HBGI (r = 0.74), but only in type 1 diabetic patients. Patients with longstanding disease and type 1 diabetes had a greater glucose variability, irrespective of their HbA1c levels. Insulin therapy with MDI correlated strongly with HbA1c, but not with glucose variability. HbA1c levels identify states of sustained hyperglycemia and seem to be unaffected by hypoglycemic episodes or short-lived glucose spikes, consequently revealing shortcomings as a "gold standard" indicator of metabolic control. Glucose variability indicators describe the glucose profile of type 1 diabetic patients and identify any worsening glycemic control (typical of longstanding diabetes) more accurately than HbA1c tests.

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