Serum Levels of Advanced Glycation Endproducts and Other Markers of Protein Damage in Early Diabetic Nephropathy in Type 1 Diabetes

Objective To determine the role of markers of plasma protein damage by glycation, oxidation and nitration in microalbuminuria onset or subsequent decline of glomerular filtration rate (termed “early GFR decline”) in patients with type 1 diabetes. Methods From the 1st Joslin Kidney Study, we selected 30 patients with longstanding normoalbuminuria and 55 patients with new onset microalbuminuria. Patients with microalbuminuria had 8–12 years follow-up during which 33 had stable GFR and 22 early GFR decline. Mean baseline GFRCYSTATIN C was similar between the three groups. Glycation, oxidation and nitration markers were measured in protein and ultrafiltrate at baseline by liquid chromatography-tandem mass spectrometry using the most reliable methods currently available. Results Though none were significantly different between patients with microalbuminuria with stable or early GFR decline, levels of 6 protein damage adduct residues of plasma protein and 4 related free adducts of plasma ultrafiltrate were significantly different in patients with microalbuminuria compared to normoalbuminuria controls. Three protein damage adduct residues were decreased and 3 increased in microalbuminuria while 3 free adducts were decreased and one increased in microalbuminuria. The most profound differences were of N-formylkynurenine (NFK) protein adduct residue and Nω-carboxymethylarginine (CMA) free adduct in which levels were markedly lower in microalbuminuria (P<0.001 for both). Conclusions Complex processes influence levels of plasma protein damage and related proteolysis product free adducts in type 1 diabetes and microalbuminuria. The effects observed point to the possibility that patients who have efficient mechanisms of disposal of damaged proteins might be at an increased risk of developing microalbuminuria but not early renal function decline. The findings support the concept that the mechanisms responsible for microalbuminuria may differ from the mechanisms involved in the initiation of early renal function decline

Genetic associations in diabetic nephropathy: a meta-analysis

Diabetes mellitus: pathophysiological changes and therap

Mortality Risk Prediction by an Insurance Company and Long-Term Follow-Up of 62,000 Men

Background: Insurance companies use medical information to classify the mortality risk of applicants. Adding genetic tests to this assessment is currently being debated. This debate would be more meaningful, if results of present-day risk prediction were known. Therefore, we compared the predicted with the observed mortality of men who applied for life insurance, and determined the prognostic value of the risk assessment. Methods: Long-term follow-up was available for 62,334 male applicants whose mortality risk was predicted with medical evaluation and they were assigned to five groups with increasing risk from 1 to 5. We calculated all cause standardized mortality ratios relative to the Dutch population and compared groups with Cox's regression. We compared the discriminative ability of risk assessments as indicated by a concordance index (c). Results: In 844,815 person years we observed 3,433 deaths. The standardized mortality relative to the Dutch male population was 0.76 (95 percent confidence interval, 0.73 to 0.78). The standardized mortality ratios ranged from 0.54 in risk group 1 to 2.37 in group 5. A large number of risk factors and diseases were significantly associated with increased mortality. The algorithm of prediction was significantly, but only slightly better than summation of the number of disorders and risk factors (c-index, 0.64 versus 0.60, P,0.001). Conclusions: Men applying for insurance clearly had better survival relative to the general population. Readily available medical evaluation enabled accurate prediction of the mortality risk of large groups, but the deceased men could not have been identified with the applied prediction method

Absence of diabetic retinopathy in a patient who has had diabetes mellitus for 69 years, and inadequate glycemic control: case presentation

The main risk factors for the development and progression of diabetic retinopathy (DR) are chronic hyperglycemia, disease duration and systemic blood pressure. So far chronic hyperglycemia is the strongest evidence concerning the risk of developing DR. However there are some patients with poor metabolic control who never develop this diabetic complication. We present a case of a 73-year-old woman with type 1 diabetes mellitus, diagnosed 69 years ago. The patient is 73 years old, with no evidence of DR, despite poor glycemic control and several risk factors for DR. This case suggests the presence of a possible protection factor, which could be genetic

Progression to microalbuminuria in type 1 diabetes: development and validation of a prediction rule

AIMS/HYPOTHESIS: Microalbuminuria is common in type 1 diabetes and is associated with an increased risk of renal and cardiovascular disease. We aimed to develop and validate a clinical prediction rule that estimates the absolute risk of microalbuminuria. METHODS: Data from the European Diabetes Prospective Complications Study (n = 1115) were used to develop the prediction rule (development set). Multivariable logistic regression analysis was used to assess the association between potential predictors and progression to microalbuminuria within 7 years. The performance of the prediction rule was assessed with calibration and discrimination (concordance statistic [c-statistic]) measures. The rule was validated in three other diabetes studies (Pittsburgh Epidemiology of Diabetes Complications [EDC] study, Finnish Diabetic Nephropathy [FinnDiane] study and Coronary Artery Calcification in Type 1 Diabetes [CACTI] study). RESULTS: Of patients in the development set, 13% were microalbuminuric after 7 years. Glycosylated haemoglobin, AER, WHR, BMI and ever smoking were found to be the most important predictors. A high-risk group (n = 87 [8%]) was identified with a risk of progression to microalbuminuria of 32%. Predictions showed reasonable discriminative ability, with c-statistic of 0.71. The rule showed good calibration and discrimination in EDC, FinnDiane and CACTI (c-statistic 0.71, 0.79 and 0.79, respectively). CONCLUSIONS/INTERPRETATION: We developed and validated a clinical prediction rule that uses relatively easily obtainable patient characteristics to predict microalbuminuria in patients with type 1 diabetes. This rule can help clinicians to decide on more frequent check-ups for patients at high risk of microalbuminuria in order to prevent long-term chronic complication