How to prevent the microvascular complications of type 2 diabetes beyond glucose control.
Valencia Willy Marcos,Florez Hermes
BMJ (Clinical research ed.)
Microvascular complications (retinopathy, nephropathy, and neuropathy) affect hundreds of millions of patients with type 2 diabetes. They usually affect people with longstanding or uncontrolled disease, but they can also be present at diagnosis or in those yet to have a diagnosis made. The presentation and progression of these complications can lead to loss of visual, renal, and neurologic functions, impaired mobility and cognition, poor quality of life, limitations for employment and productivity, and increased costs for the patient and society. If left uncontrolled or untreated, they lead to irreversible damage and even death. This review focuses on the primary and secondary prevention of diabetic microvascular complications in patients with type 2 diabetes, beyond glycemic control. Interventions discussed include standard of care interventions supported by guidelines from major organizations, as well as additional proposed interventions that are supported by research published in the past decade. High level evidence sources such as systematic reviews and large, multicenter randomized clinical trials have been prioritized. Smaller trials were included where high quality evidence was unavailable.
Modelling diabetic nephropathy in mice.
Azushima Kengo,Gurley Susan B,Coffman Thomas M
Nature reviews. Nephrology
Diabetic nephropathy (DN) is a leading cause of end-stage renal disease in the developed world. Accordingly, an urgent need exists for new, curative treatments as well as for biomarkers to stratify risk of DN among individuals with diabetes mellitus. A barrier to progress in these areas has been a lack of animal models that faithfully replicate the main features of human DN. Such models could be used to define the pathogenesis, identify drug targets and test new therapies. Owing to their tractability for genetic manipulation, mice are widely used to model human diseases, including DN. Questions have been raised, however, about the general utility of mouse models in human drug discovery. Standard mouse models of diabetes typically manifest only modest kidney abnormalities, whereas accelerated models, induced by superimposing genetic stressors, recapitulate key features of human DN. Incorporation of systems biology approaches and emerging data from genomics and metabolomics studies should enable further model refinement. Here, we discuss the current status of mouse models for DN, their limitations and opportunities for improvement. We emphasize that future efforts should focus on generating robust models that reproduce the major clinical and molecular phenotypes of human DN.
Diabetic kidney disease.
Thomas Merlin C,Brownlee Michael,Susztak Katalin,Sharma Kumar,Jandeleit-Dahm Karin A M,Zoungas Sophia,Rossing Peter,Groop Per-Henrik,Cooper Mark E
Nature reviews. Disease primers
The kidney is arguably the most important target of microvascular damage in diabetes. A substantial proportion of individuals with diabetes will develop kidney disease owing to their disease and/or other co-morbidity, including hypertension and ageing-related nephron loss. The presence and severity of chronic kidney disease (CKD) identify individuals who are at increased risk of adverse health outcomes and premature mortality. Consequently, preventing and managing CKD in patients with diabetes is now a key aim of their overall management. Intensive management of patients with diabetes includes controlling blood glucose levels and blood pressure as well as blockade of the renin-angiotensin-aldosterone system; these approaches will reduce the incidence of diabetic kidney disease and slow its progression. Indeed, the major decline in the incidence of diabetic kidney disease (DKD) over the past 30 years and improved patient prognosis are largely attributable to improved diabetes care. However, there remains an unmet need for innovative treatment strategies to prevent, arrest, treat and reverse DKD. In this Primer, we summarize what is now known about the molecular pathogenesis of CKD in patients with diabetes and the key pathways and targets implicated in its progression. In addition, we discuss the current evidence for the prevention and management of DKD as well as the many controversies. Finally, we explore the opportunities to develop new interventions through urgently needed investment in dedicated and focused research. For an illustrated summary of this Primer, visit: http://go.nature.com/NKHDzg.
Reducing VEGF-B Signaling Ameliorates Renal Lipotoxicity and Protects against Diabetic Kidney Disease.
Falkevall Annelie,Mehlem Annika,Palombo Isolde,Heller Sahlgren Benjamin,Ebarasi Lwaki,He Liqun,Ytterberg A Jimmy,Olauson Hannes,Axelsson Jonas,Sundelin Birgitta,Patrakka Jaakko,Scotney Pierre,Nash Andrew,Eriksson Ulf
Diabetic kidney disease (DKD) is the most common cause of severe renal disease, and few treatment options are available today that prevent the progressive loss of renal function. DKD is characterized by altered glomerular filtration and proteinuria. A common observation in DKD is the presence of renal steatosis, but the mechanism(s) underlying this observation and to what extent they contribute to disease progression are unknown. Vascular endothelial growth factor B (VEGF-B) controls muscle lipid accumulation through regulation of endothelial fatty acid transport. Here, we demonstrate in experimental mouse models of DKD that renal VEGF-B expression correlates with the severity of disease. Inhibiting VEGF-B signaling in DKD mouse models reduces renal lipotoxicity, re-sensitizes podocytes to insulin signaling, inhibits the development of DKD-associated pathologies, and prevents renal dysfunction. Further, we show that elevated VEGF-B levels are found in patients with DKD, suggesting that VEGF-B antagonism represents a novel approach to treat DKD.
Plasma Triglycerides and HDL-C Levels Predict the Development of Diabetic Kidney Disease in Subjects With Type 2 Diabetes: The AMD Annals Initiative.
Russo Giuseppina T,De Cosmo Salvatore,Viazzi Francesca,Pacilli Antonio,Ceriello Antonio,Genovese Stefano,Guida Pietro,Giorda Carlo,Cucinotta Domenico,Pontremoli Roberto,Fioretto Paola,
OBJECTIVE:Despite the achievement of blood glucose, blood pressure, and LDL cholesterol (LDL-C) targets, the risk for diabetic kidney disease (DKD) remains high among patients with type 2 diabetes. This observational retrospective study investigated whether diabetic dyslipidemia-that is, high triglyceride (TG) and/or low HDL cholesterol (HDL-C) levels-contributes to this high residual risk for DKD. RESEARCH DESIGN AND METHODS:Among a total of 47,177 patients attending Italian diabetes centers, 15,362 patients with a baseline estimated glomerular filtration rate (eGFR) ≥60 mL/min/1.73 m, normoalbuminuria, and LDL-C ≤130 mg/dL completing a 4-year follow-up were analyzed. The primary outcome was the incidence of DKD, defined as either low eGFR (<60 mL/min/1.73 m) or an eGFR reduction >30% and/or albuminuria. RESULTS:Overall, 12.8% developed low eGFR, 7.6% an eGFR reduction >30%, 23.2% albuminuria, and 4% albuminuria and either eGFR <60 mL/min/1.73 m or an eGFR reduction >30%. TG ≥150 mg/dL increased the risk of low eGFR by 26%, of an eGFR reduction >30% by 29%, of albuminuria by 19%, and of developing one abnormality by 35%. HDL-C <40 mg/dL in men and <50 mg/dL in women were associated with a 27% higher risk of low eGFR and a 28% risk of an eGFR reduction >30%, with a 24% higher risk of developing albuminuria and a 44% risk of developing one abnormality. These associations remained significant when TG and HDL-C concentrations were examined as continuous variables and were only attenuated by multivariate adjustment for numerous confounders. CONCLUSIONS:In a large population of outpatients with diabetes, low HDL-C and high TG levels were independent risk factors for the development of DKD over 4 years.
CKD in diabetes: diabetic kidney disease versus nondiabetic kidney disease.
Anders Hans-Joachim,Huber Tobias B,Isermann Berend,Schiffer Mario
Nature reviews. Nephrology
The increasing global prevalence of type 2 diabetes mellitus (T2DM) and chronic kidney disease (CKD) has prompted research efforts to tackle the growing epidemic of diabetic kidney disease (DKD; also known as diabetic nephropathy). The limited success of much of this research might in part be due to the fact that not all patients diagnosed with DKD have renal dysfunction as a consequence of their diabetes mellitus. Patients who present with CKD and diabetes mellitus (type 1 or type 2) can have true DKD (wherein CKD is a direct consequence of their diabetes status), nondiabetic kidney disease (NDKD) coincident with diabetes mellitus, or a combination of both DKD and NDKD. Preclinical studies using models that more accurately mimic these three entities might improve the ability of animal models to predict clinical trial outcomes. Moreover, improved insights into the pathomechanisms that are shared by these entities - including sodium-glucose cotransporter 2 (SGLT2) and renin-angiotensin system-driven glomerular hyperfiltration and tubular hyper-reabsorption - as well as those that are unique to individual entities might lead to the identification of new treatment targets. Acknowledging that the clinical entity of CKD plus diabetes mellitus encompasses NDKD as well as DKD could help solve some of the urgent unmet medical needs of patients affected by these conditions.
The role of the complement system in diabetic nephropathy.
Nature reviews. Nephrology
The development of type 1 and type 2 diabetes mellitus has a substantial negative impact on morbidity and mortality and is responsible for substantial individual and socioeconomic costs worldwide. One of the most serious consequences of diabetes mellitus is the development of diabetic angiopathy, which manifests clinically as microvascular and macrovascular complications. One microvascular complication, diabetic nephropathy, is the most common cause of end-stage renal disease in developed countries. Although several available therapeutic interventions can delay the onset and progression of diabetic nephropathy, morbidity associated with this disease remains high and new therapeutic approaches are needed. In addition, not all patients with diabetes mellitus will develop diabetic nephropathy and thus new biomarkers are needed to identify individuals who will develop this life-threatening disease. An increasing body of evidence points toward a role of the complement system in the pathogenesis of diabetic nephropathy. For example, circulating levels of mannose-binding lectin (MBL), a pattern recognition molecule of the innate immune system, have emerged as a robust biomarker for the development and progression of this disease, and evidence suggests that MBL, H-ficolin, complement component C3 and the membrane attack complex might contribute to renal injury in the hyperglycaemic mileu. New approaches to modulate the complement system might lead to the development of new agents to prevent or slow the progression of diabetic nephropathy.
Establishment and Validation of a Risk Prediction Model for Early Diabetic Kidney Disease Based on a Systematic Review and Meta-Analysis of 20 Cohorts.
Jiang Wenhui,Wang Jingyu,Shen Xiaofang,Lu Wenli,Wang Yuan,Li Wen,Gao Zhongai,Xu Jie,Li Xiaochen,Liu Ran,Zheng Miaoyan,Chang Bai,Li Jing,Yang Juhong,Chang Baocheng
BACKGROUND:Identifying patients at high risk of diabetic kidney disease (DKD) helps improve clinical outcome. PURPOSE:To establish a model for predicting DKD. DATA SOURCES:The derivation cohort was from a meta-analysis. The validation cohort was from a Chinese cohort. STUDY SELECTION:Cohort studies that reported risk factors of DKD with their corresponding risk ratios (RRs) in patients with type 2 diabetes were selected. All patients had estimated glomerular filtration rate (eGFR) ≥60 mL/min/1.73 m and urinary albumin-to-creatinine ratio (UACR) <30 mg/g at baseline. DATA EXTRACTION:Risk factors and their corresponding RRs were extracted. Only risk factors with statistical significance were included in our DKD risk prediction model. DATA SYNTHESIS:Twenty cohorts including 41,271 patients with type 2 diabetes were included in our meta-analysis. Age, BMI, smoking, diabetic retinopathy, hemoglobin A, systolic blood pressure, HDL cholesterol, triglycerides, UACR, and eGFR were statistically significant. All these risk factors were included in the model except eGFR because of the significant heterogeneity among studies. All risk factors were scored according to their weightings, and the highest score was 37.0. The model was validated in an external cohort with a median follow-up of 2.9 years. A cutoff value of 16 was selected with a sensitivity of 0.847 and a specificity of 0.677. LIMITATIONS:There was huge heterogeneity among studies involving eGFR. More evidence is needed to power it as a risk factor of DKD. CONCLUSIONS:The DKD risk prediction model consisting of nine risk factors established in this study is a simple tool for detecting patients at high risk of DKD.