Patients with type 1 diabetes and albuminuria have a reduced brain glycolytic capability that is correlated with brain atrophy.

Introduction: Patients with type 1 diabetes (T1D) demonstrate brain alterations, including white matter lesions and cerebral atrophy. In this case-control study, we investigated if a reason for this atrophy could be because of diabetes-related complications affecting cerebrovascular or cerebral glycolytic functions. Cerebral physiological dysfunction can lead to energy deficiencies and, consequently, neurodegeneration. Methods: We examined 33 patients with T1D [18 females, mean age: 50.8 years (range: 26-72)] and 19 matched healthy controls [7 females, mean age: 45.0 years (range: 24-64)]. Eleven (33%) of the patients had albuminuria. Total brain volume, brain parenchymal fraction, gray matter volume and white matter volume were measured by anatomical MRI. Cerebral vascular and glycolytic functions were investigated by measuring global cerebral blood flow (CBF), cerebral metabolic rate of oxygen (CMRO2) and cerebral lactate concentration in response to the inhalation of hypoxic air (12-14% fractional oxygen) using phase-contrast MRI and magnetic resonance spectroscopy (MRS) techniques. The inspiration of hypoxic air challenges both cerebrovascular and cerebral glycolytic physiology, and an impaired response will reveal a physiologic dysfunction. Results: Patients with T1D and albuminuria had lower total brain volume, brain parenchymal fraction, and gray matter volume than healthy controls and patients without albuminuria. The inhalation of hypoxic air increased CBF and lactate in all groups. Patients with albuminuria had a significantly (p = 0.032) lower lactate response compared to healthy controls. The CBF response was lower in patients with albuminuria compared to healthy controls, however not significantly (p = 0.24) different. CMRO2 was unaffected by the hypoxic challenge in all groups (p > 0.16). A low lactate response was associated with brain atrophy, characterized by reduced total brain volume (p = 0.003) and reduced gray matter volume (p = 0.013). Discussion: We observed a reduced response of the lactate concentration as an indication of impaired glycolytic activity, which correlated with brain atrophy. Inadequacies in upregulating cerebral glycolytic activity, perhaps from reduced glucose transporters in the brain or hypoxia-inducible factor 1 pathway dysfunction, could be a complication in diabetes contributing to the development of neurodegeneration and declining brain health.

Hepatic Fibrosis Evaluated in Patients with Type 2 Diabetes with and without Chronic Kidney Disease.

BACKGROUND: Non-alcoholic fatty liver disease (NAFLD), and particularly liver fibrosis, has been suggested as a risk factor of chronic kidney disease (CKD). Given that NAFLD affects every fourth person globally, better insight is needed. Our aim was to investigate the association between hepatic fibrosis and CKD in patients with type 2 diabetes and to compare different methods for diagnosing liver fibrosis in this study population. METHODS: Cross-sectional study including patients with type 2 diabetes with CKD stages 3-5 (N = 50) or without CKD (N = 50). CKD was defined as estimated glomerular filtration rate <60 mL/min/1.73 m2 with or without proteinuria. Three methods were used to detect significant liver fibrosis defined as either ≥8 kilopascal measured by transient elastography (FibroScan®), fibrosis-4 (FIB-4) score ≥2.67, or NAFLD fibrosis score (NFS) >0.675. RESULTS: Significant liver fibrosis was found in 38% and 28% of the patients with and without CKD, respectively, using at least one of the three methods. Both FIB-4 score and NFS were significantly higher in patients with CKD (p < 0.0009 and p < 0.0001, respectively), although insignificant after adjustments for age, sex, body mass index, and duration of diabetes. In patients without CKD, a significant association between steatosis and fibrosis was observed (p = 0.0007). CONCLUSION: Our data do not support any strong independent association between liver fibrosis and established CKD as assessed by FibroScan, FIB-4 score, and NFS, respectively.

Evaluation of the effects of ezetimibe on albuminuria and kidney fat in individuals with type 2 diabetes and chronic kidney disease.

AIM: To investigate the effects of ezetimibe on the urine albumin creatinine ratio (UACR) and kidney parenchyma fat content (kidney-PF) in individuals with type 2 diabetes (T2D) and early chronic kidney disease. MATERIALS AND METHODS: A randomized, double-blind, placebo-controlled study of ezetimibe 10 mg once daily for 16 weeks in individuals with T2D and a UACR of 30 mg/g or higher was conducted. Kidney-PF was assessed with magnetic resonance spectroscopy. Geometric mean changes from baseline were derived from linear regressions. RESULTS: A total of 49 participants were randomized to ezetimibe (n = 25) or placebo (n = 24). Overall, mean ± standard deviation age was 67 ± 7 years, body mass index was 31 ± 4 kg/m2 and the proportion of men was 84%. The mean estimated glomerular filtration rate was 76 ± 22 mL/min/1.73m2 and median (first-third quartile) UACR was 95 (41-297) mg/g. Median kidney-PF was 1.0% (0.3%-2.1%). Compared with placebo, ezetimibe did not significantly reduce UACR (mean [95% confidence interval] change: -3% [-28%-31%]) or kidney-PF (mean change: -38% [-66%-14%]). In participants with baseline kidney-PF above the median, ezetimibe reduced kidney-PF significantly (mean change: -60% [-84%--3%]) compared with placebo, while the reduction in UACR was not significant (mean change: -28% [-54%-15%]). CONCLUSIONS: Ezetimibe did not reduce the UACR or kidney-PF on top of modern T2D management. However, kidney-PF was reduced with ezetimibe in participants with high baseline kidney-PF.

Nonalcoholic Fatty Liver Disease in Patients with Type 2 Diabetes and Chronic Kidney Disease.

BACKGROUND: Nonalcoholic fatty liver disease (NAFLD) is suggested as a risk factor for chronic kidney disease (CKD). The incidence of NAFLD is rising globally in parallel to the increasing incidences of obesity and type 2 diabetes. Diabetes remains the leading cause of CKD, but the co-existence of NAFLD, CKD, and type 2 diabetes is not well elucidated. Here, we evaluated the prevalence of NAFLD in patients with type 2 diabetes with and without CKD. METHODS: This was a cross-sectional study including 50 patients with type 2 diabetes and CKD stages 3-5 (no dialysis), and 50 patients with type 2 diabetes without CKD. Liver fat content was estimated by proton magnetic resonance spectroscopy and magnetic resonance imaging proton density fat fraction. NAFLD was defined as liver fat fraction ≥5.6% according to guidelines. RESULTS: Mean age was 72 ± 4.9 years in patients with CKD and 65.9 ± 7.8 years in patients without CKD (p < 0.0001). Three out of four participants were men. BMI was 28.6 ± 3.5 kg/m2 and 27 ± 4.0 kg/m2 in patients with and without CKD, respectively (p = 0.0087). NAFLD was identified in 22 (44%) patients with CKD and 19 (38%) patients without CKD (p = 0.6845). Median (IQR) liver fat fraction was 4.7% (3.0-8.5) and 4.1% (2.9-7.7) in patients with and without CKD, respectively (difference in geometric means 5.3%, 95% CI -23; 45, p = 0.7463). CONCLUSION: These findings do not support any association between NAFLD and CKD (stages 3-5) in patients with type 2 diabetes.

Biochemical profiling, pharmacological management and clinical outcomes in type 2 diabetes in Danish primary care from 2001 to 2015.

AIMS: Primary care plays an integral role in the management of type 2 diabetes (T2D). We investigated in a large group of individuals in this setting the biochemical profiles, pharmacological management and clinical outcomes as well as their changes over time. METHODS: This is a register-based study including relevant laboratory test results requested between 2000 and 2015 by general practitioners in the greater Copenhagen area. We identified 72,044 individuals with T2D on whom data concerning prescription medicine and clinical outcomes were obtained from national registries. RESULTS: The number of individuals with T2D greatly increased from 2001 to 2015. Hemoglobin A1c, estimated glomerular filtration rate and urine albumin creatinine ratio did not change, but cholestrol levels improved. The proportion redeeming anti-diabetics remained around 80%, with an increase for metformin. The use of cardiovascular drugs increased. All-cause and especially cardiovascular mortality decreased over the period. Hospital admissions for non-fatal cardiovascular events dropped. CONCLUSION: The number of individuals with T2D in primary care increased dramatically whereas pharmacological management, control of risk factors and clinical outcomes seem to have improved. Nevertheless, a conspicuous minority did not receive diabetes-related medication.

The Accuracy of Hemoglobin A1c and Fructosamine Evaluated by Long-Term Continuous Glucose Monitoring in Patients with Type 2 Diabetes Undergoing Hemodialysis.

INTRODUCTION: The accuracy of hemoglobin A1c (HbA1c) as a glycemic marker in patients with type 2 diabetes (T2D) receiving hemodialysis (HD) remains unknown. To assess accuracy, we compared HbA1c and fructosamine levels with interstitial glucose measured by continuous glucose monitoring (CGM) in patients with T2D receiving HD. METHODS: Thirty patients in the HD group and 36 patients in the control group (T2D and an estimated glomerular filtration rate >60 mL/min/1.73 m2) completed the study period of 17 weeks. CGM (Ipro2®, Medtronic) was performed 5 times for periods of up to 7 days (with 4-week intervals) during a 16-week period. HbA1c (mmol/mol), the estimated mean plasma glucose from HbA1c (eMPGA1c [mmol/L]) and fructosamine (µmol/L) was measured at week 17 and compared with mean sensor glucose levels from CGM. FINDINGS: In the HD group, mean sensor glucose was 1.4 mmol/L (95% confidence interval [CI]: 1.0-1.8) higher than the eMPGA1c, whereas the difference for controls was 0.1 mmol/L (95% CI: -0.1-[0.4]; p < 0.001). Adjusted for mean sensor glucose, HbA1c was lower in the HD group (-7.3 mmol/mol, 95% CI: -10.0-[-4.7]) than in the control group (p < 0.001), with no difference detected for fructosamine (p = 0.64). DISCUSSION: HbA1c evaluated by CGM underestimates plasma glucose levels in patients receiving HD. The underestimation represents a clinical challenge in optimizing glycemic control in the HD population. Fructosamine is unaffected by the factors affecting HbA1c and appears to be more accurate for glycemic monitoring. CGM or fructosamine could thus complement HbA1c in obtaining more accurate glycemic control in this patient group.

Lipoprotein(a)and renal function decline, cardiovascular disease and mortality in type 2 diabetes and microalbuminuria.

AIMS: Lipoprotein(a)(Lp(a)) has emerged as an independent risk marker for cardiovascular disease (CVD) in the general population and among persons with existing CVD. We investigated associations between serum Lp(a)concentrations and renal function decline, incident CVD and all-cause mortality in individuals with type 2 diabetes (T2D) and microalbuminuria. METHODS: Prospective study including 198 individuals with T2D, microalbuminuria and no CVD. Yearly p-creatinine was measured after baseline in 176 of the participants. The renal endpoint was defined as decline in eGFR of >30% from baseline. CVD events and mortality were tracked from national registries. Cox regression analyses were applied both unadjusted and adjusted for traditional risk factors (sex, age, systolic blood pressure, LDL-cholesterol, smoking, HbA1c, creatinine and urinary albumin creatinine ratio (UAER)). RESULTS: Baseline mean (SD) age was 59 (9)years, eGFR 89 (17) mL/min/1.73 m2, 77% were male, and median [IQR] UAER was 103 [38-242] mg/24-h. Median Lp(a)was 8.04 [3.42-32.3] mg/dL. Median follow-up was 6.1 years; 38 CVD events, 26 deaths and 43 renal events were recorded. For each doubling of baseline Lp(a), the following hazard ratios (95% confidence intervals) were found before and after adjustment respectively: 0.98 (0.84-1.15) and 1.01 (0.87-1.18) for decline in eGFR > 30%, 0.96 (0.81-1.13) and 0.99 (0.82-1.18) for CVD events, 1.04 (0.85-1.27) and 1.06 (0.87-1.30) for all-cause mortality. CONCLUSIONS: In this cohort of individuals with T2D and microalbuminuria, the baseline concentration of Lp(a)was not a risk marker for renal function decline, CVD events or all-cause mortality.