Diabetic kidney disease is the leading cause of ESRD, but few biomarkers of diabetic kidney disease are available. This study used gas chromatography-mass spectrometry to quantify 94 urine ...metabolites in screening and validation cohorts of patients with diabetes mellitus (DM) and CKD(DM+CKD), in patients with DM without CKD (DM-CKD), and in healthy controls. Compared with levels in healthy controls, 13 metabolites were significantly reduced in the DM+CKD cohorts (P≤0.001), and 12 of the 13 remained significant when compared with the DM-CKD cohort. Many of the differentially expressed metabolites were water-soluble organic anions. Notably, organic anion transporter-1 (OAT1) knockout mice expressed a similar pattern of reduced levels of urinary organic acids, and human kidney tissue from patients with diabetic nephropathy demonstrated lower gene expression of OAT1 and OAT3. Analysis of bioinformatics data indicated that 12 of the 13 differentially expressed metabolites are linked to mitochondrial metabolism and suggested global suppression of mitochondrial activity in diabetic kidney disease. Supporting this analysis, human diabetic kidney sections expressed less mitochondrial protein, urine exosomes from patients with diabetes and CKD had less mitochondrial DNA, and kidney tissues from patients with diabetic kidney disease had lower gene expression of PGC1α (a master regulator of mitochondrial biogenesis). We conclude that urine metabolomics is a reliable source for biomarkers of diabetic complications, and our data suggest that renal organic ion transport and mitochondrial function are dysregulated in diabetic kidney disease.
We assessed meal timing, meal frequency, and breakfast consumption habits of adult individuals with type 1 diabetes (n = 1007) taking part in the Finnish Diabetic Nephropathy Study, and studied ...whether they are associated with glycaemic control. Data on dietary intake and blood glucose measurements were retrieved from food records. HbA
was measured at the study visit. In the whole sample, four peaks of energy intake emerged. Energy intake was the greatest in the evening, followed by midday. Altogether 7% of the participants reported no energy intake between 05:00 and 09:59 (breakfast skippers). While breakfast skippers reported lower number of meals, no difference was observed in the total energy intake between those eating and omitting breakfast. In a multivariable model, skipping breakfast was associated with higher mean blood glucose concentrations and lower odds of good glycaemic control. A median of 6 daily meals was reported. Adjusted for confounders, the number of meals was negatively associated with HbA
, and the mean of the blood glucose measurements, but positively associated with the variability of these measurements. Our observations support the habit of a regular meal pattern, including consumption of breakfast and multiple smaller meals for good glycaemic control in adults with type 1 diabetes. However, an increase in the blood glucose variability may additionally be expected with an increase in the number of meals eaten.
Gram-negative bacteria-derived lipopolysaccharides (LPS) are associated with various negative health effects. Whether diet is associated with LPS, is an understudied phenomenon. We investigated the ...association between diet and serum LPS activity in 668 individuals with type 1 diabetes in the FinnDiane Study. Serum LPS activity was determined using the Limulus Amoebocyte Lysate assay. Diet was assessed with a food frequency questionnaire (FFQ) section of a diet questionnaire and a food record. The food record was used to calculate energy, macronutrient, and fibre intake. In a multivariable model, energy, macronutrient, or fibre intake was not associated with the LPS activity. Using factor analysis, we identified seven dietary patterns from the FFQ data ("Sweet", "Cheese", "Fish", "Healthy snack", "Vegetable", "Traditional", and "Modern"). In a multivariable model, higher factor scores of the Fish, Healthy snack, and Modern patterns predicted lower LPS activity. The validity of the diet questionnaire was also investigated. The questionnaire showed reasonable relative validity against a 6-day food record. The two methods classified participants into the dietary patterns better than expected by chance. In conclusion, healthy dietary choices, such as consumption of fish, fresh vegetables, and fruits and berries may be associated with positive health outcomes by reducing systemic endotoxaemia.
Although nut consumption has been associated with several health benefits, it has not been investigated in individuals with type 1 diabetes. Therefore, our aim was to assess nut consumption and its ...association with metabolic syndrome in adult individuals with type 1 diabetes taking part in the Finnish Diabetic Nephropathy Study. The nut intake of the 1058 participants was assessed from 3-day food records that were completed twice, and the number of weekly servings, assuming a serving size of 28.4 g, was calculated. Metabolic syndrome was defined as the presence of ≥3 of the cardiovascular risk factors: central obesity, high blood pressure (≥130/85 mmHg or use of antihypertensive medication), high triglyceride concentration (≥1.70 mmol/L or use of lipid-lowering medication), low HDL-cholesterol concentration (<1.00 mmol/L in men and <1.30 mmol/L in women or use of lipid-lowering medication), and hyperglycaemia. Overweight/obesity was defined as a BMI ≥25 kg/m
. HbA
> 59 mmol/mol (>7.5%) was used as a criterion for suboptimal glycaemic control. Of the 1058 (mean age 46 years, 41.6% men) participants, 689 (54.1%) reported no nut intake. In the remaining sample, the median weekly nut intake was 40.8 g. In the adjusted models, higher nut intake, as the continuous number of weekly servings and the comparison of those with <2 and ≥2 weekly servings, was associated with lower metabolic syndrome score, waist circumference, HbA
, and BMI. Nut consumption as a continuous variable was negatively associated with the presence of metabolic syndrome, its blood pressure, triglyceride, and HDL-cholesterol components, and suboptimal glycaemic control. Consumption of ≥2 weekly servings was associated with lower odds of suboptimal glycaemic control (by 51.5%), overweight/obesity (by 33.4%), and metabolic syndrome (by 51.8%) and meeting the waist (by 37.3%), blood pressure (by 44.5%), triglyceride (by 37.7%), and HDL-cholesterol (by 36.2%) components of the metabolic syndrome. In conclusion, a weekly nut intake of ≥2 servings was beneficially associated with all the components of the metabolic syndrome in type 1 diabetes. The causality of this association will need to be investigated.
This study investigated the prevalence of nonalbuminuric chronic kidney disease in type 1 diabetes to assess whether it increases the risk of cardiovascular and renal outcomes as well as all-cause ...mortality.
This was an observational follow-up of 3,809 patients with type 1 diabetes from the Finnish Diabetic Nephropathy Study. All patients were Caucasians and thoroughly examined at baseline. Their mean age was 37.6 ± 11.8 years and duration of diabetes 21.2 ± 12.1 years. Follow-up data on cardiovascular and renal outcomes and mortality were retrieved from registers. During 13 years of median follow-up, 378 developed end-stage renal disease, 415 suffered an incident cardiovascular event, and 406 died.
At baseline, 78 (2.0%) had nonalbuminuric chronic kidney disease. This was associated with older age, female sex, history of retinal laser treatment, cardiovascular events, and the number of antihypertensive drugs in use, but not with blood pressure levels or specific antihypertensive agents. Nonalbuminuric chronic kidney disease did not increase the risk of albuminuria (hazard ratio HR 2.0 95% CI 0.9-4.4) or end-stage renal disease (HR 6.4 0.8-53.0) but did increase the risk of cardiovascular events (HR 2.0 1.4-3.5) and all-cause mortality (HR 2.4 1.4-3.9). The highest risk of cardiovascular and renal end points was observed in the patients with albuminuria.
Nonalbuminuric chronic kidney disease is not a frequent finding in patients with type 1 diabetes, but when present, it is associated with an increased risk of cardiovascular morbidity and all-cause mortality but not with renal outcomes.
Hypertension is one of the strongest risk factors for stroke in the general population, while systolic blood pressure has been shown to independently increase the risk of stroke in type 1 diabetes. ...The aim of this study was to elucidate the association between different blood pressure variables and risk of stroke in type 1 diabetes, and to explore potential nonlinearity of this relationship.
We included 4105 individuals with type 1 diabetes without stroke at baseline, participating in the nationwide Finnish Diabetic Nephropathy Study. Mean age at baseline was 37.4 ± 11.9 years, median duration of diabetes 20.9 (interquartile range 11.5-30.4) years, and 52% were men. Office systolic blood pressure (SBP) and diastolic blood pressure (DBP) were measured. Based on these pulse pressure (PP) and mean arterial pressure (MAP) were calculated. Strokes were classified based on medical and autopsy records, as well as neuroimaging. Cox proportional hazard models were performed to study how the different blood pressure variables affected the risk of stroke and its subtypes.
During median follow-up time of 11.9 (9.21-13.9) years, 202 (5%) individuals suffered an incident stroke; 145 (72%) were ischemic and 57 (28%) hemorrhagic. SBP, DBP, PP, and MAP all independently increased the risk of any stroke. SBP, PP, and MAP increased the risk of ischemic stroke, while SBP, DBP, and MAP increased the risk of hemorrhagic stroke. SBP was strongly associated with stroke with a hazard ratio of 1.20 (1.11-1.29)/10 mmHg. When variables were modeled using restricted cubic splines, the risk of stroke increased linearly for SBP, MAP, and PP, and non-linearly for DBP.
The different blood pressure variables are all independently associated with increased risk of stroke in individuals with type 1 diabetes. The risk of stroke, ischemic stroke, and hemorrhagic stroke increases linearly at blood pressure levels less than the current recommended treatment guidelines.
Abstract
Context
The relationship between body mass index (BMI) and mortality may differ between patients with type 1 diabetes and the general population; it is not known which clinical ...characteristics modify the relationship.
Objective
Our aim was to assess the relationship between BMI and mortality and the interaction with clinically meaningful factors.
Design, Setting, and Participants
This prospective study included 5836 individuals with type 1 diabetes from the FinnDiane study.
Main Outcome Measure and Methods
We retrieved death data for all participants on 31 December 2015. We estimated the effect of BMI on the risk of mortality using a Cox proportional hazards model with BMI as a restricted cubic spline as well as effect modification by adding interaction terms to the spline.
Results
During a median of 13.7 years, 876 individuals died. The relationship between baseline BMI and all-cause mortality was reverse J-shaped. When analyses were restricted to those with normal albumin excretion rate, the relationship was U-shaped. The nadir BMI (BMI with the lowest mortality) was in the normal weight region (24.3 to 24.8 kg/m2); however, among individuals with diabetic nephropathy, the nadir BMI was in the overweight region (25.9 to 26.1 kg/m2). Diabetic nephropathy, diabetes-onset age, and sex modified the relationship between BMI and mortality (Pinteraction < 0.05).
Conclusions
Normal weight is optimal for individuals with type 1 diabetes to delay mortality, whereas underweight might be an indication of underlying complications. Maintaining normal weight may translate into reduced risk of mortality in type 1 diabetes, particularly for individuals of male sex, later diabetes-onset age, and normal albumin excretion rate.
Objectives
We studied apolipoprotein C‐III (apoC‐III) in relation to diabetic kidney disease (DKD), cardiovascular outcomes, and mortality in type 1 diabetes.
Methods
The cohort comprised 3966 ...participants from the prospective observational Finnish Diabetic Nephropathy Study. Progression of DKD was determined from medical records. A major adverse cardiac event (MACE) was defined as acute myocardial infarction, coronary revascularization, stroke, or cardiovascular mortality through 2017. Cardiovascular and mortality data were retrieved from national registries.
Results
ApoC‐III predicted DKD progression independent of sex, diabetes duration, blood pressure, HbA1c, smoking, LDL‐cholesterol, lipid‐lowering medication, DKD category, and remnant cholesterol (hazard ratio HR 1.43 95% confidence interval 1.05–1.94, p = 0.02). ApoC‐III also predicted the MACE in a multivariable regression analysis; however, it was not independent of remnant cholesterol (HR 1.05 0.81–1.36, p = 0.71 with remnant cholesterol; 1.30 1.03–1.64, p = 0.03 without). DKD‐specific analyses revealed that the association was driven by individuals with albuminuria, as no link between apoC‐III and the outcome was observed in the normal albumin excretion or kidney failure categories. The same was observed for mortality: Individuals with albuminuria had an adjusted HR of 1.49 (1.03–2.16, p = 0.03) for premature death, while no association was found in the other groups. The highest apoC‐III quartile displayed a markedly higher risk of MACE and death than the lower quartiles; however, this nonlinear relationship flattened after adjustment.
Conclusions
The impact of apoC‐III on MACE risk and mortality is restricted to those with albuminuria among individuals with type 1 diabetes. This study also revealed that apoC‐III predicts DKD progression, independent of the initial DKD category.
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