Janet K. Snell-Bergeon

Low Plasma Adiponectin Levels Predict Progression of Coronary Artery Calcification

Background—Circulating adiponectin levels are lower in men than in women and lower in advanced coronary artery disease, obesity, and type 2 but not type 1 diabetes. However, it is not known whether low adiponectin levels predict development of atherosclerosis independently of other cardiovascular risk factors. Methods and Results—Progression of coronary artery calcification (CAC) over an average of 2.6 years (range, 1.6 to 3.3) was assessed in a cohort of patients with type 1 diabetes and nondiabetic subjects 19 to 59 years of age. In this nested case-control substudy, plasma adiponectin levels were measured in 101 cases with significant CAC progression and in 205 controls. Controls were oversampled on the basis of age, gender, diabetes status, and presence of baseline CAC. In conditional logistic regression adjusted for baseline CAC volume and other significant predictors of CAC progression, adiponectin levels were inversely related to progression of CAC in diabetic (OR, 0.47; 95% CI, 0.24 to 0.94) and nondiabetic (OR, 0.15; 95% CI, 0.05 to 0.40 for a doubling in adiponectin levels) subjects. Adjustment for additional cardiovascular risk factors did not change this association. In conditional logistic regression models by quartiles of plasma adiponectin levels, the probability value for trend was statistically significant for all participants (P<0.001) and nondiabetic participants (P<0.001) and was borderline for type 1 diabetics (P=0.08). Conclusions—Low plasma adiponectin levels are associated with progression of CAC in type 1 diabetic and nondiabetic subjects independently of other cardiovascular risk factors.

Insulin resistance, defective insulin-mediated fatty acid suppression, and coronary artery calcification in subjects with and without type 1 diabetes: The CACTI study

OBJECTIVE To assess insulin action on peripheral glucose utilization and nonesterified fatty acid (NEFA) suppression as a predictor of coronary artery calcification (CAC) in patients with type 1 diabetes and nondiabetic controls. RESEARCH DESIGN AND METHODS Insulin action was measured by a three-stage hyperinsulinemic-euglycemic clamp (4, 8, and 40 mU/m2/min) in 87 subjects from the Coronary Artery Calcification in Type 1 Diabetes cohort (40 diabetic, 47 nondiabetic; mean age 45 ± 8 years; 55% female). RESULTS Peripheral glucose utilization was lower in subjects with type 1 diabetes compared with nondiabetic controls: glucose infusion rate (mg/kg FFM/min) = 6.19 ± 0.72 vs. 12.71 ± 0.66, mean ± SE, P < 0.0001, after adjustment for age, sex, BMI, fasting glucose, and final clamp glucose and insulin. Insulin-induced NEFA suppression was also lower in type 1 diabetic compared with nondiabetic subjects: NEFA levels (μM) during 8 mU/m2/min insulin infusion = 370 ± 27 vs. 185 ± 25, P < 0.0001, after adjustment for age, sex, BMI, fasting glucose, and time point insulin. Lower glucose utilization and higher NEFA levels, correlated with CAC volume (r = −0.42, P < 0.0001 and r = 0.41, P < 0.0001, respectively) and predicted the presence of CAC (odds ratio [OR] = 0.45, 95% CI = 0.22–0.93, P = 0.03; OR = 2.4, 95% CI = 1.08–5.32, P = 0.032, respectively). Insulin resistance did not correlate with GHb or continuous glucose monitoring parameters. CONCLUSIONS Type 1 diabetic patients are insulin resistant compared with nondiabetic subjects, and the degree of resistance is not related to current glycemic control. Insulin resistance predicts the extent of coronary artery calcification and may contribute to the increased risk of cardiovascular disease in patients with type 1 diabetes as well as subjects without diabetes.

Prevalence and Correlates of Depression in Individuals With and Without Type 1 Diabetes

OBJECTIVE Depression is associated with poor glycemic control and complications in people with type 1 diabetes. We assessed the prevalence of depression and antidepressant medication use among adults with and without type 1 diabetes and the association between depression and diabetes complications. RESEARCH DESIGN AND METHODS In 2006–2008, the Coronary Artery Calcification in Type 1 Diabetes Study applied the Beck Depression Inventory II (BDI-II) to 458 participants with type 1 diabetes (47% male, aged 44 ± 9 years, type 1 diabetes duration 29 ± 9 years) and 546 participants without diabetes (nondiabetic group) (51% male, aged 47 ± 9 years). Use of antidepressant medication was self-reported. Depression was defined as a BDI-II score >14 and/or use of antidepressant medication. Occurrence of diabetes complications (retinopathy, blindness, neuropathy, diabetes-related amputation, and kidney or pancreas transplantation) was self-reported. RESULTS Mean BDI-II score, adjusted for age and sex, was significantly higher in participants with type 1 diabetes than in nondiabetic participants (least-squares mean ± SE: 7.4 ± 0.3 vs. 5.0 ± 0.3; P < 0.0001). Type 1 diabetic participants reported using more antidepressant medications (20.7 vs. 12.1%, P = 0.0003). More type 1 diabetic than nondiabetic participants were classified as depressed by BDI-II cut score (17.5 vs. 5.7%, P < 0.0001) or by either BDI-II cut score or antidepressant use (32.1 vs. 16.0%, P < 0.0001). Participants reporting diabetes complications (n = 209) had higher mean BDI-II scores than those without complications (10.7 ± 9.3 vs. 6.4 ± 6.3, P < 0.0001). CONCLUSIONS Compared with nondiabetic participants, adults with type 1 diabetes report more symptoms of depression and more antidepressant medication usage. Depression is highly prevalent in type 1 diabetes and requires further study on assessment and treatment.

Diagnosis and Prediction of CKD Progression by Assessment of Urinary Peptides

Progressive CKD is generally detected at a late stage by a sustained decline in eGFR and/or the presence of significant albuminuria. With the aim of early and improved risk stratification of patients with CKD, we studied urinary peptides in a large cross-sectional multicenter cohort of 1990 individuals, including 522 with follow-up data, using proteome analysis. We validated that a previously established multipeptide urinary biomarker classifier performed significantly better in detecting and predicting progression of CKD than the current clinical standard, urinary albumin. The classifier was also more sensitive for identifying patients with rapidly progressing CKD. Compared with the combination of baseline eGFR and albuminuria (area under the curve [AUC]=0.758), the addition of the multipeptide biomarker classifier significantly improved CKD risk prediction (AUC=0.831) as assessed by the net reclassification index (0.303±-0.065; P<0.001) and integrated discrimination improvement (0.058±0.014; P<0.001). Correlation of individual urinary peptides with CKD stage and progression showed that the peptides that associated with CKD, irrespective of CKD stage or CKD progression, were either fragments of the major circulating proteins, suggesting failure of the glomerular filtration barrier sieving properties, or different collagen fragments, suggesting accumulation of intrarenal extracellular matrix. Furthermore, protein fragments associated with progression of CKD originated mostly from proteins related to inflammation and tissue repair. Results of this study suggest that urinary proteome analysis might significantly improve the current state of the art of CKD detection and outcome prediction and that identification of the urinary peptides allows insight into various ongoing pathophysiologic processes in CKD.

Serum uric acid levels predict the development of albuminuria over 6 years in patients with type 1 diabetes: Findings from the Coronary Artery Calcification in Type 1 Diabetes study

BACKGROUND Recent studies suggest that uric acid is a mediator of diabetic nephropathy. We hypothesized that elevated serum uric acid levels are a strong predictor of albuminuria in patients with type 1 diabetes. METHODS We analyzed data from the Coronary Artery Calcification in Type 1 Diabetes study, a prospective observational study. A stepwise logistic regression model was applied to predict the development of micro- or macroalbuminuria after 6 years of follow-up in 324 participants who had no evidence of micro- or macroalbuminuria at baseline. A P-value <0.1 was used as the criteria for entry into and removal from the model. RESULTS The following factors were selected in the stepwise multivariate model as predictors of micro- or macroalbuminuria at the 6-year follow-up visit: baseline serum uric acid levels, HbA(1c) and pre-albuminuria. For every 1-mg/dl increase in serum uric acid levels at baseline, there was an 80% increased risk of developing micro- or macroalbuminuria at 6 years (odds ratio 1.8; 95% confidence interval 1.2, 2.8; P = 0.005). Additional covariates considered in the stepwise model were sex, age, duration of diabetes, angiotensin-converting enzyme inhibitor or angiotensin II receptor blocker treatment, waist circumference, waist/hip ratio, body mass index, systolic and diastolic blood pressure, smoking, serum creatinine, cystatin C, high-density lipoprotein cholesterol and triglycerides. CONCLUSION Elevated serum uric acid levels are a strong predictor of the development of albuminuria in patients with type 1 diabetes.

Urinary proteomic diagnosis of coronary artery disease: identification and clinical validation in 623 individuals.

Objectives We studied the urinary proteome in a total of 623 individuals with and without coronary artery disease (CAD) in order to characterize multiple biomarkers that enable prediction of the presence of CAD. Methods Urine samples were analyzed by capillary electrophoresis coupled online to micro time-of-flight mass spectrometry. Results We defined a pattern of 238 CAD-specific polypeptides from comparison of 586 spot urine samples from 408 individuals. This pattern identified patients with CAD in a blinded cohort of 138 urine samples (71 patients with CAD and 67 healthy individuals) with high sensitivity and specificity (area under the receiver operator characteristic curve 87%, 95% confidence interval 81–92) and was superior to previously developed 15-marker (area under the receiver operator characteristic curve 68%, P < 0.0001) and 17-marker panels (area under the receiver operator characteristic curve 77%, P < 0.0001). The sequences of the discriminatory polypeptides include fragments of alpha-1-antitrypsin, collagen types 1 and 3, granin-like neuroendocrine peptide precursor, membrane-associated progesterone receptor component 1, sodium/potassium-transporting ATPase gamma chain and fibrinogen-alpha chain. Several biomarkers changed significantly toward the healthy signature following 2-year treatment with irbesartan, whereas short-term treatment with irbesartan did not significantly affect the polypeptide pattern. Conclusion Urinary proteomics identifies CAD with high confidence and might also be useful for monitoring the effects of therapeutic interventions.

Evaluation of Urinary Biomarkers for Coronary Artery Disease, Diabetes, and Diabetic Kidney Disease

BACKGROUND In this study we sought to validate urinary biomarkers for diabetes and two common complications, coronary artery disease (CAD) and diabetic nephropathy (DN). METHODS A CAD score calculated by summing the product of a classification coefficient and signal amplitude of 15 urinary polypeptides was previously developed. Five sequences of biomarkers in the panel were identified as fragments of collagen alpha-1(I) and alpha-1(III). Prospectively collected urine samples available for analysis from 19 out of 20 individuals with CAD (15 with type 1 diabetes [T1D] and four without diabetes) and age-, sex-, and diabetes-matched controls enrolled in the Coronary Artery Calcification in Type 1 Diabetes study were analyzed for the CAD score using capillary electrophoresis and electrospray ionization mass spectrometry. Two panels of biomarkers that were previously defined to distinguish diabetes status were analyzed to determine their relationship to T1D. Three biomarker panels developed to distinguish DN (DNS) and two biomarker panels developed to distinguish renal disease (RDS) were examined to determine their relationship with renal function. RESULTS The CAD score was associated with CAD (odds ratio with 95% confidence interval, 2.2 [1.3-5.2]; P = 0.0016) and remained significant when adjusted individually for age, albumin excretion rate (AER), blood pressure, waist circumference, intraabdominal fat, glycosylated hemoglobin, and lipids. DNS and RDS were significantly correlated with AER, cystatin C, and serum creatinine. The biomarker panels for diabetes were both significantly associated with T1D status (P < 0.05 for both). CONCLUSIONS We validated a urinary proteome pattern associated with CAD and urinary proteome patterns associated with T1D and DN.

Effect of sitagliptin on glucose control in adult patients with Type 1 diabetes: a pilot, double‐blind, randomized, crossover trial

Diabet. Med. 28, 1176–1181 (2011)

Inflammatory Markers Are Increased in Youth with Type 1 Diabetes: The SEARCH Case-Control Study

CONTEXT Increased inflammation may contribute to type 1 diabetes (T1D) complications. OBJECTIVE The objective of the study was to investigate the association of inflammation with obesity, hyperglycemia and dyslipidemia in youth with T1D. DESIGN This was a cross-sectional study of youth with and without T1D. SETTING The study was conducted in Colorado and South Carolina. PATIENTS SEARCH Case-Control participants with T1D [n = 553, mean age 15 yr (range 10-22), median duration 2.7 yr] and without diabetes [n = 215, mean age 15 yr (range 10-22)]. INTERVENTION This was an observational study. MAIN OUTCOME MEASURES IL-6, high-sensitivity C-reactive protein (hsCRP), fibrinogen, and leptin were measured. RESULTS Inflammatory markers were evaluated by diabetes status, quartiles of glycated hemoglobin, and obesity using multiple linear regression analyses, adjusted for age, sex, study site, race/ethnicity, T1D duration, body mass index, and pubertal status. Compared with controls, youth with T1D had higher IL-6 and fibrinogen levels at all levels of glycemia and obesity, and hsCRP levels were significantly higher in youth with T1D in the top three quartiles of glycated hemoglobin (> or = 7.2%) and among normal-weight subjects. Leptin was lower in youth with poor glycemic control. Higher hsCRP and fibrinogen were correlated with higher total and LDL cholesterol, and apolipoprotein B in youth with T1D, whereas higher fibrinogen was correlated with higher LDL and apolipoprotein B in controls. CONCLUSIONS T1D is characterized by excess inflammation, independent of adiposity and glycemic control. Even T1D youth in good glycemic control had higher levels of IL-6 and fibrinogen than controls. Elevated inflammatory markers were associated with an atherogenic lipid profile, which may contribute to accelerated atherosclerosis in youth with T1D.

Serum Cystatin C Predicts Progression of Subclinical Coronary Atherosclerosis in Individuals With Type 1 Diabetes

OBJECTIVE—Renal function is an important determinant of coronary atherosclerosis, and serum cystatin C is a novel accurate measure of glomerular filtration rate (GFR) and a predictor of cardiovascular events and mortality. We hypothesized that in individuals with type 1 diabetes, cystatin C would 1) predict progression of subclinical coronary atherosclerosis (SCA) and 2) be a stronger predictor of SCA than serum creatinine, GFR (estimated by the Cockcroft-Gault [GFRCG] and Modification of Diet in Renal Disease [GFRMDRD] formulas), and albumin excretion rate. RESEARCH DESIGN AND METHODS—Coronary artery calcification was measured twice, using Imatron C-150 Ultrafast CT, over a 2.5 ± 0.4-year interval in 509 adults with type 1 diabetes (42% male, age 36 ± 9 years, duration 23 ± 9 years). SCA progression (n = 131) was defined as a >2.5 increase in square root calcium volume score or development of clinical coronary artery disease. Predictors of SCA progression were examined in a model selected by stepwise logistic regression and an a priori–determined model. Next, each measure of renal function was inserted into the stepwise model, one at a time, and Akaike information criterion was used to compare the fit of the competing models. RESULTS—The stepwise model included cystatin C (odds ratio 1.44, 95% CI 1.00–2.18, P = 0.048), age, baseline coronary artery calcification, sex, diabetes duration, systolic blood pressure, and HDL. The stepwise model had a better fit than any of the competing models with serum creatinine, GFRCG, GFRMDRD, or albumin excretion rate replacing cystatin C. CONCLUSIONS—In individuals with type 1 diabetes, cystatin C modestly predicts SCA.