Epicardial and intra-thoracic adipose tissue and cardiovascular calcifications in type 1 diabetes (T1D) in epidemiology of diabetes Interventions and Complications (EDIC): A pilot study.

Objective: Coronary artery, aortic valve, and descending aorta calcification (CAC, AVC, DAC) are manifestations of atherosclerosis, and cardiac epicardial adipose tissue (EAT) indicates heart adiposity. This study explored the association between cardiac adipose tissue and cardiovascular calcification in participants with long-standing T1D. Methods: EAT and intra-thoracic adipose tissue (IAT) were measured in 100 T1D subjects with cardiac computed tomography (CT) scans in the EDIC study. Volume analysis software was used to measure fat volumes. Spearman correlations were calculated between CAC, AVC, DAC with EAT, and IAT. Associations were evaluated using multiple linear and logistic regression models. Results: Participants ranged in age from 32 to 57. Mean EAT, and IAT were 38.5 and 50.8 mm3, respectively, and the prevalence of CAC, AVC, and DAC was 43.6 %, 4.7 %, and 26.8 %, respectively. CAC was positively correlated with age (p-value = 0.0001) and EAT (p-value = 0.0149) but not with AVC and DAC; IAT was not associated with calcified lesions. In models adjusted for age and sex, higher levels of EAT and IAT were associated with higher CAC (p-value < 0.0001 for both) and higher AVC (p-values of 0.0111 and 0.0053, respectively), but not with DAC. The associations with CAC remained significant (p-value < 0.0001) after further adjustment for smoking, systolic blood pressure, BMI, and LDL, while the associations with AVC did not remain significant. Conclusion: In participants with T1D, higher EAT and IAT levels are correlated with higher CAC scores. EAT and IAT were not independently correlated with DAC or AVC.

Left Ventricular Structure, Tissue Composition, and Aortic Distensibility in the Diabetes Control and Complications Trial/Epidemiology of Diabetes Intervention and Complications.

Alterations in myocardial structure, function, tissue composition (e.g., fibrosis) may be associated with metabolic syndrome (MetS). This study aimed to determine the relation of MetS and its individual components to markers of cardiovascular disease in patients with type 1 Diabetes Mellitus (T1DM). A total of 978 subjects of the Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications T1DM cohort (age: 49 ± 7 years, 47% female, DM duration 28 ± 5 years) underwent cardiovascular magnetic resonance. In a subset of 200 patients, myocardial tissue composition was measured with cardiovascular magnetic resonance T1 mapping after contrast administration. MetS was defined as T1DM plus 2 other abnormalities based on the American Heart Association/National Cholesterol Education Program criteria. MetS was present in 34.1% of subjects. After adjustment for age, height, scanner, study cohort, gender, smoking, mean glycated hemoglobin levels, history of macroalbuminuria and end-stage renal disease, left ventricle mass was greater by 12.3 g, end-diastolic volume was higher by 5.4 ml, and mass to end-diastolic volume ratio was higher by 5% in patients with MetS versus those without MetS (p <0.001 for all). Myocardial T1 times were lower by 29 ms in patients with MetS than those without (p <0.001). Elevated waist circumference showed the strongest associations with left ventricle mass (+10.1 g), end-diastolic volume (+6.7 ml), and lower myocardial T1 times (+31 ms) in patients with MetS compared with those without (p <0.01). In conclusion, in a large cohort of patients with T1DM, 34.1% of subjects met MetS criteria. MetS was associated with adverse myocardial structural remodeling and change in myocardial tissue composition.

Refractive Error and Retinopathy Outcomes in Type 1 Diabetes: The Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications Study.

PURPOSE: To determine the relationship between refractive error and diabetic retinopathy (DR). DESIGN: Clinical trial. PARTICIPANTS: Type I diabetes individuals with serial refractive error and DR stage measurements over 30 years in the Diabetes Control and Complications Trial (DCCT) and Epidemiology of Diabetes Interventions and Complications (EDIC) follow-up study. METHODS: Stage of DR was measured every 6 months from standard fundus photographs, and refractive error was measured annually during the 6.5 years of DCCT; then, both were staggered every fourth year during EDIC with the full cohort measured at EDIC years 4 and 10. Outcomes of DR were 2- or 3-step progression, presence of proliferative DR (PDR), clinically significant macular edema (CSME), diabetic macular edema (DME), or ocular surgery. Myopia, emmetropia, and hyperopia were defined as a spherical equivalent of ≤-0.5, >-0.5 and <0.5, and ≥0.5, respectively. MAIN OUTCOME MEASURES: For each outcome separately, Cox proportional hazard (PH) models assessed the association between the refractive error status and the subsequent risk of that outcome, both without and with adjustment for potential risk factors. RESULTS: Hyperopia was associated with a higher risk of 2-step progression (hazard ratio [HR], 1.29; 95% confidence interval [CI], 1.05-1.59), 3-step progression (HR, 1.35; 95% CI, 1.05-1.73), and PDR (HR, 1.40; 95% CI, 1.02-1.92) compared with emmetropia in unadjusted models. These associations remained significant after adjustment for DCCT treatment group, cohort, age, sex, smoking, duration of diabetes, systolic and diastolic blood pressures, pulse, low-density lipoprotein, high-density lipoprotein, triglycerides, albumin excretion rate, and DCCT/EDIC mean updated hemoglobin A1c (HbA1c) (2-step progression: HR, 1.28; 95% CI, 1.03-1.58; 3-step progression: HR, 1.30; 95% CI, 1.00-1.68; PDR: HR, 1.38; 95% CI, 1.00-1.90). Myopia was not associated with any of the 5 DR outcomes in the unadjusted models and only marginally associated with 2-step progression (HR, 1.11; 95% CI, 1.00-1.24) in the adjusted models. CONCLUSIONS: Myopia is not associated with DR progression risk. Hyperopia is an independent risk factor for 2-step and 3-step DR progression and PDR.

The minimum intensity of a mixed exposure that increases the risk of an outcome.

Semi-quantitative exposures, such as smoking and alcohol consumption, are common in clinical studies. Their association with outcomes is captured using either a single quantitative variable that includes nonexposed with a value of zero, or using two variables by adding an additional binary variable exposed versus not exposed. Herein, we propose two approaches to determine a lower bound on the amount of such an exposure (eg, number of cigarettes smoked per day) that significantly increases the risk of outcomes. Using smoking as illustration, the first approach consists of sequentially testing the effect of 1, 2, and so on, cigarettes per day, which requires an adjustment for multiplicity to protect the overall type-I error. An alternative gatekeeping approach is also described. The proposed methods are illustrated for the association of smoking with clinically confirmed neuropathy in a logistic regression model, and for the association of smoking with the risk of CVD in a Cox PH regression model.

DNA methylation mediates development of HbA1c-associated complications in type 1 diabetes.

Metabolic memory, the persistent benefits of early glycaemic control on preventing and/or delaying the development of diabetic complications, has been observed in the Diabetes Control and Complications Trial (DCCT) and in the Epidemiology of Diabetes Interventions and Complications (EDIC) follow-up study, but the underlying mechanisms remain unclear. Here, we show the involvement of epigenetic DNA methylation (DNAme) in metabolic memory by examining its associations with preceding glycaemic history, and with subsequent development of complications over an 18-yr period in the blood DNA of 499 randomly selected DCCT participants with type 1 diabetes who are also followed up in EDIC. We demonstrate the associations between DNAme near the closeout of DCCT and mean HbA1c during DCCT (mean-DCCT HbA1c) at 186 cytosine-guanine dinucleotides (CpGs) (FDR < 15%, including 43 at FDR < 5%), many of which were located in genes related to complications. Exploration studies into biological function reveal that these CpGs are enriched in binding sites for the C/EBP transcription factor, as well as enhancer/transcription regions in blood cells and haematopoietic stem cells, and open chromatin states in myeloid cells. Mediation analyses show that, remarkably, several CpGs in combination explain 68-97% of the association of mean-DCCT HbA1c with the risk of complications during EDIC. In summary, DNAme at key CpGs appears to mediate the association between hyperglycaemia and complications in metabolic memory, through modifying enhancer activity at myeloid and other cells.

Models to Assess the Association of a Semiquantitative Exposure With Outcomes.

A semiquantitative risk factor has 2 components: any exposure (yes/no) and the quantitative amount of exposure (if exposed). We describe the statistical properties of alternative analyses with such a risk factor using linear, logistic, or Cox proportional hazards models. Often analyses employ the amount exposed as a single quantitative covariate, including the nonexposed with value zero. However, this analysis provides a biased estimate of the exposure coefficient (slope) and we describe the magnitude of the bias. This bias can be eliminated by adding a binary covariate for exposed versus not to the model. This 2-factor analysis captures the full risk-factor effect on the outcome. However, the coefficient for any exposure versus not does not have a meaningful interpretation. Alternatively, when exposure values among those exposed are centered (by subtracting the mean), the estimate of this coefficient represents the difference in the outcome between those exposed versus not in aggregate. We also show that the biased model provides biased estimates of the coefficients for other covariates added to the model. Proper analysis of a semiquantitative risk factor should start with a 2-factor model, with centering, to assess the joint contributions of the 2 components of the risk-factor exposure. Properties of models were illustrated using data from a multisite study in North America (1983-2019).

Risk Factors for Diabetic Peripheral Neuropathy and Cardiovascular Autonomic Neuropathy in the Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications (DCCT/EDIC) Study.

The Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications (DCCT/EDIC) study demonstrated that intensive glucose control reduced the risk of developing diabetic peripheral neuropathy (DPN) and cardiovascular autonomic neuropathy (CAN). We evaluated multiple risk factors and phenotypes associated with DPN and CAN in this large, well-characterized cohort of participants with type 1 diabetes, followed for >23 years. DPN was defined by symptoms, signs, and nerve conduction study abnormalities in ≥2 nerves; CAN was assessed using standardized cardiovascular reflex tests. Generalized estimating equation models assessed the association of DPN and CAN with individual risk factors measured repeatedly. During DCCT/EDIC, 33% of participants developed DPN and 44% CAN. Higher mean HbA1c was the most significant risk factor for DPN, followed by older age, longer duration, greater height, macroalbuminuria, higher mean pulse rate, ß-blocker use, and sustained albuminuria. The most significant risk factor for CAN was older age, followed by higher mean HbA1c, sustained albuminuria, longer duration of type 1 diabetes, higher mean pulse rate, higher mean systolic blood pressure, ß-blocker use, estimated glomerular filtration rate <60 mL/min/1.73 m2, higher most recent pulse rate, and cigarette smoking. These findings identify risk factors and phenotypes of participants with diabetic neuropathy that can be used in the design of new interventional trials and for personalized approaches to neuropathy prevention.

Screening eye exams in youth with type 1 diabetes under 18 years of age: Once may be enough?

Case series and registry data suggest that diabetic retinopathy requiring treatment is rare in youth with type 1 diabetes (T1D) prior to 18 years of age. We evaluated this question in the standardized clinical trial setting by retrospectively reviewing diabetic retinopathy examinations from participants in the Diabetes Control and Complications Trial (DCCT) who were 13 to <18 years of age at randomization. Standardized stereoscopic 7-field fundus photographs were obtained every 6 months during DCCT (1983-1993). Photographs were graded centrally using the Early Treatment Diabetic Retinopathy Study (ETDRS) scale. Transitions in diabetic retinopathy status over time were described. A total of 195 participants with median baseline glycated hemoglobin (HbA1c) of 9.3% (103 in the conventional and 92 in the intensive treatment groups) had an average of 5.3 diabetic retinopathy assessments during 2.3 years of follow-up (range 1-11) while under 18 years of age during the DCCT. No participant developed severe non-proliferative diabetic retinopathy or proliferative diabetic retinopathy and only one participant (in the intensive group) reached clinically significant macular edema (CSME) while less than 18 years of age. In this incident case, baseline characteristics included diabetes duration 9.3 years, HbA1c 10.3%, LDL 131 mg/dL, and mild non-proliferative diabetic retinopathy (35/35 ETDRS scale); CSME resolved without treatment. Similar analyses using age cut-offs of <19, 20, or 21 years showed a slight rise in diabetic retinopathy requiring treatment over late adolescence. Clinical trial evidence suggests that frequent eye exams may not be universally necessary in youth <18 years of age with T1D.

Risk Factors for Retinopathy in Type 1 Diabetes: The DCCT/EDIC Study.

OBJECTIVE: The Diabetes Control and Complications Trial (DCCT) demonstrated that intensive therapy reduced the development and progression of retinopathy in type 1 diabetes (T1D) compared with conventional therapy. The Epidemiology of Diabetes Interventions and Complications (EDIC) study observational follow-up showed persistent benefits. In addition to glycemia, we now examine other potential retinopathy risk factors (modifiable and nonmodifiable) over more than 30 years of follow-up in DCCT/EDIC. RESEARCH DESIGN AND METHODS: The retinopathy outcomes were proliferative diabetic retinopathy (PDR), clinically significant macular edema (CSME), and ocular surgery. The survival (event-free) probability was estimated using the Kaplan-Meier method. Cox proportional hazards models assessed the association between risk factors and subsequent risk of retinopathy. Both forward- and backward-selection approaches determined the multivariable models. RESULTS: Rate of ocular events per 1,000 person-years was 12 for PDR, 14.5 for CSME, and 7.6 for ocular surgeries. Approximately 65%, 60%, and 70% of participants remained free of PDR, CSME, and ocular surgery, respectively. The greatest risk factors for PDR in descending order were higher mean HbA1c, longer duration of T1D, elevated albumin excretion rate (AER), and higher mean diastolic blood pressure (DBP). For CSME, risk factors, in descending order, were higher mean HbA1c, longer duration of T1D, and greater age and DBP and, for ocular surgeries, were higher mean HbA1c, older age, and longer duration of T1D. CONCLUSIONS: Mean HbA1c was the strongest risk factor for the progression of retinopathy. Although glycemic control is important, elevated AER and DBP were other modifiable risk factors associated with the progression of retinopathy.

Mediation of the association of smoking and microvascular complications by glycemic control in type 1 diabetes.

Studies have demonstrated the adverse effects of smoking on the risk of microvascular complications; however, few have also examined the potential mediating effects of glycemic control. Using data from the Diabetes Control and Complications Trial (DCCT 1983-1993), we describe the acute and long-term risks of smoking on glycemic control and microvascular complications in a well-characterized cohort of participants with type 1 diabetes. The DCCT recorded self-reported smoking behaviors, glycemic exposure based on HbA1c, and complications status. Generalized linear mixed models were used to assess whether time-dependent measurements of smoking predict HbA1c levels. Cox proportional hazard models were used to assess time-dependent smoking exposures as predictors of retinopathy and nephropathy. During a mean of 6.5 years of follow-up, current smokers had consistently higher HbA1c values and were at a higher risk of retinopathy and nephropathy compared with former and never smokers. These risk differences were attenuated after adjusting for HbA1c suggesting that the negative association of smoking on glycemic control is partially responsible for the adverse association of smoking on the risk of complications in type 1 diabetes. These findings support the potential for a beneficial effect of smoking cessation on complications in type 1 diabetes.

Hearing Impairment and Type 1 Diabetes in the Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications (DCCT/EDIC) Cohort.

OBJECTIVE: To evaluate the prevalence of hearing impairment in participants with type 1 diabetes enrolled in the Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications (DCCT/EDIC) study and compare with that of a spousal control group without diabetes. Among participants with type 1 diabetes, to evaluate the association of hearing impairment with prior DCCT therapy and overall glycemia. RESEARCH DESIGN AND METHODS: DCCT/EDIC participants (n = 1,150) and 288 spouses without diabetes were recruited for the DCCT/EDIC Hearing Study. All subjects completed a self-administered questionnaire, medical history, and physical measurements. Audiometry was performed by study-certified personnel; audiograms were assessed centrally. Speech-frequency (pure-tone average [PTA] thresholds at 500, 1,000, 2,000, and 4,000 Hz) and high-frequency impairment (PTA thresholds at 3,000, 4,000, 6,000, and 8,000 Hz) were defined as PTA >25 dB hearing loss. Logistic regression models were adjusted for age and sex. RESULTS: DCCT/EDIC participants and spousal control subjects were similar in age, race, education, smoking, and systolic blood pressure. There were no statistically significant differences between groups in the prevalence or adjusted odds of speech- or high-frequency impairment in either ear. Among participants with type 1 diabetes, for every 10% increase in the time-weighted mean HbA1c, there was a 32% (95% CI 1.15-1.50) and 19% (95% CI 1.07-1.33) increase in speech- and high-frequency hearing impairment, respectively. CONCLUSIONS: We found no significant difference in the prevalence of hearing impairment between the group with type 1 diabetes and the spousal control group. Among those with type 1 diabetes, higher mean HbA1c over time was associated with hearing impairment.

Causes of Death in a Contemporary Cohort of Patients With Type 2 Diabetes and Atherosclerotic Cardiovascular Disease: Insights From the TECOS Trial.

OBJECTIVE: We evaluated the specific causes of death and their associated risk factors in a contemporary cohort of patients with type 2 diabetes and atherosclerotic cardiovascular disease (ASCVD). RESEARCH DESIGN AND METHODS: We used data from the Trial Evaluating Cardiovascular Outcomes with Sitagliptin (TECOS) study (n = 14,671), a cardiovascular (CV) safety trial adding sitagliptin versus placebo to usual care in patients with type 2 diabetes and ASCVD (median follow-up 3 years). An independent committee blinded to treatment assignment adjudicated each cause of death. Cox proportional hazards models were used to identify risk factors associated with each outcome. RESULTS: A total of 1,084 deaths were adjudicated as the following: 530 CV (1.2/100 patient-years [PY], 49% of deaths), 338 non-CV (0.77/100 PY, 31% of deaths), and 216 unknown (0.49/100 PY, 20% of deaths). The most common CV death was sudden death (n = 145, 27% of CV death) followed by acute myocardial infarction (MI)/stroke (n = 113 [MI n = 48, stroke n = 65], 21% of CV death) and heart failure (HF) (n = 63, 12% of CV death). The most common non-CV death was malignancy (n = 154, 46% of non-CV death). The risk of specific CV death subcategories was lower among patients with no baseline history of HF, including sudden death (hazard ratio [HR] 0.4; P = 0.0036), MI/stroke death (HR 0.47; P = 0.049), and HF death (HR 0.29; P = 0.0057). CONCLUSIONS: In this analysis of a contemporary cohort of patients with diabetes and ASCVD, sudden death was the most common subcategory of CV death. HF prevention may represent an avenue to reduce the risk of specific CV death subcategories.

Frequency of Evidence-Based Screening for Retinopathy in Type 1 Diabetes.

BACKGROUND: In patients who have had type 1 diabetes for 5 years, current recommendations regarding screening for diabetic retinopathy include annual dilated retinal examinations to detect proliferative retinopathy or clinically significant macular edema, both of which require timely intervention to preserve vision. During 30 years of the Diabetes Control and Complications Trial (DCCT) and its longitudinal follow-up Epidemiology of Diabetes Interventions and Complications (EDIC) study, retinal photography was performed at intervals of 6 months to 4 years. METHODS: We used retinal photographs from the DCCT/EDIC study to develop a rational screening frequency for retinopathy. Markov modeling was used to determine the likelihood of progression to proliferative diabetic retinopathy or clinically significant macular edema in patients with various initial retinopathy levels (no retinopathy or mild, moderate, or severe nonproliferative diabetic retinopathy). The models included recognized risk factors for progression of retinopathy. RESULTS: Overall, the probability of progression to proliferative diabetic retinopathy or clinically significant macular edema was limited to approximately 5% between retinal screening examinations at 4 years among patients who had no retinopathy, 3 years among those with mild retinopathy, 6 months among those with moderate retinopathy, and 3 months among those with severe nonproliferative diabetic retinopathy. The risk of progression was also closely related to mean glycated hemoglobin levels. The risk of progression from no retinopathy to proliferative diabetic retinopathy or clinically significant macular edema was 1.0% over 5 years among patients with a glycated hemoglobin level of 6%, as compared with 4.3% over 3 years among patients with a glycated hemoglobin level of 10%. Over a 20-year period, the frequency of eye examinations was 58% lower with our practical, evidence-based schedule than with routine annual examinations, which resulted in substantial cost savings. CONCLUSIONS: Our model for establishing an individualized schedule for retinopathy screening on the basis of the patient's current state of retinopathy and glycated hemoglobin level reduced the frequency of eye examinations without delaying the diagnosis of clinically significant disease. (Funded by the National Institute of Diabetes and Digestive and Kidney Diseases and others; DCCT/EDIC ClinicalTrials.gov numbers, NCT00360893 and NCT00360815 .).

Association of Cardiovascular Risk Factors and Myocardial Fibrosis With Early Cardiac Dysfunction in Type 1 Diabetes: The Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications Study.

OBJECTIVE: We investigated the association of cardiovascular risk factors and myocardial fibrosis with early cardiac dysfunction in type 1 diabetes. RESEARCH DESIGN AND METHODS: Participants with type 1 diabetes aged 13-39 years without a known history of cardiovascular disease (CVD) (n = 1,441) were recruited into the Diabetes Control and Complications Trial (1983-1993) and subsequently followed in the Epidemiology of Diabetes Interventions and Complications study (1994 to present). Seven hundred fourteen participants underwent cardiac magnetic resonance (CMR) imaging (2007-2009) with late gadolinium enhancement sequences to assess ischemic and nonischemic scars and tagging sequences to evaluate circumferential strain. CMR-derived T1 mapping also was used to assess interstitial fibrosis. The influence of cardiovascular risk factors and myocardial scar on circumferential strain was assessed using linear regression. RESULTS: Circumferential dysfunction was consistently associated with older age, male sex, smoking history, obesity, higher blood pressure, lower HDL cholesterol, and higher mean HbA1c. Participants with nonischemic scars (n = 16) had the worst circumferential function compared with those without scars (ß ± SE 1.32 ± 0.60; P = 0.03). In sex-adjusted models, the correlation between T1 times and circumferential strain was not significant. In the fully adjusted models, a trend toward circumferential dysfunction in participants with nonischemic scars was found. Left ventricular ejection fraction was not associated with risk factors but was significantly lower if a myocardial scar was present. CONCLUSIONS: Traditional CVD risk factors and elevated HbA1c levels are major factors related to early cardiac dysfunction in type 1 diabetes. Nonischemic myocardial scar, possibly as a marker of chronic exposure to known risk factors, may predict early cardiac dysfunction mediated by diffuse myocardial fibrosis as seen in diabetic cardiomyopathy.

Pancreatic Safety of Sitagliptin in the TECOS Study.

OBJECTIVE: We evaluated the incidence of acute pancreatitis and pancreatic cancer in patients with type 2 diabetes and cardiovascular disease who were treated with sitagliptin, a dipeptidyl peptidase-4 inhibitor (DPP-4i). RESEARCH DESIGN AND METHODS: In the Trial Evaluating Cardiovascular Outcomes with Sitagliptin (TECOS) study, a cardiovascular safety study of sitagliptin, all suspected cases of acute pancreatitis and pancreatic cancer were collected prospectively for 14,671 participants during a median follow-up time of 3 years, and were adjudicated blindly. RESULTS: Baseline differences were minimal between participants confirmed to have no pancreatic events, acute pancreatitis, or pancreatic cancer. Among those participants randomized to receive sitagliptin, 23 (0.3%) (vs. 12 randomized to receive placebo [0.2%]) had pancreatitis (hazard ratio 1.93 [95% CI 0.96-3.88], P = 0.065; 0.107 vs. 0.056/100 patient-years), with 25 versus 17 events, respectively. Severe pancreatitis (two fatal) occurred in four individuals allocated to receive sitagliptin. Cases of pancreatic cancer were numerically fewer with sitagliptin (9 [0.1%]) versus placebo (14 [0.2%]) (hazard ratio 0.66 [95% CI 0.28-1.51], P = 0.32; 0.042 vs. 0.066 events/100 patient-years). Meta-analysis with two other DPP-4i cardiovascular outcome studies showed an increased risk for acute pancreatitis (risk ratio 1.78 [95% CI 1.13-2.81], P = 0.01) and no significant effect for pancreatic cancer (risk ratio 0.54 [95% CI 0.28-1.04], P = 0.07). CONCLUSIONS: Pancreatitis and pancreatic cancer were uncommon events with rates that were not statistically significantly different between the sitagliptin and placebo groups, although numerically more sitagliptin participants developed pancreatitis and fewer developed pancreatic cancer. Meta-analysis suggests a small absolute increased risk for pancreatitis with DPP-4i therapy.

Epigenomic profiling reveals an association between persistence of DNA methylation and metabolic memory in the DCCT/EDIC type 1 diabetes cohort.

We examined whether persistence of epigenetic DNA methylation (DNA-me) alterations at specific loci over two different time points in people with diabetes are associated with metabolic memory, the prolonged beneficial effects of intensive vs. conventional therapy during the Diabetes Control and Complications Trial (DCCT) on the progression of microvascular outcomes in the long-term follow-up Epidemiology of Diabetes Interventions and Complications (EDIC) Study. We compared DNA-me profiles in genomic DNA of whole blood (WB) isolated at EDIC Study baseline from 32 cases (DCCT conventional therapy group subjects showing retinopathy or albuminuria progression by EDIC Study year 10) vs. 31 controls (DCCT intensive therapy group subjects without complication progression by EDIC year 10). DNA-me was also profiled in blood monocytes (Monos) of the same patients obtained during EDIC Study years 16-17. In WB, 153 loci depicted hypomethylation, and 225 depicted hypermethylation, whereas in Monos, 155 hypomethylated loci and 247 hypermethylated loci were found (fold change ≥1.3; P < 0.005; cases vs. controls). Twelve annotated differentially methylated loci were common in both WB and Monos, including thioredoxin-interacting protein (TXNIP), known to be associated with hyperglycemia and related complications. A set of differentially methylated loci depicted similar trends of associations with prior HbA1c in both WB and Monos. In vitro, high glucose induced similar persistent hypomethylation at TXNIP in cultured THP1 Monos. These results show that DNA-me differences during the DCCT persist at certain loci associated with glycemia for several years during the EDIC Study and support an epigenetic explanation for metabolic memory.

Probabilistic measures of cost-effectiveness.

Several probability-based measures are introduced in order to assess the cost-effectiveness of a treatment. The basic measure consists of the probability that one treatment is less costly and more effective compared with another. Several variants of this measure are suggested as flexible options for cost-effectiveness analysis. The proposed measures are invariant under monotone transformations of the cost and effectiveness measures. Interval estimation of the proposed measures are investigated under a parametric model, assuming bivariate normality, and also non-parametrically. The delta method and a generalized pivotal quantity approach are both investigated under the bivariate normal model. A non-parametric U-statistics-based approach is also investigated for computing confidence intervals. Numerical results show that under bivariate normality, the solution based on generalized pivotal quantities exhibits accurate performance in terms of maintaining the coverage probability of the confidence interval. The non-parametric U-statistics-based solution is accurate for sample sizes that are at least moderately large. The results are illustrated using data from a clinical trial for prostate cancer therapy. Copyright © 2016 John Wiley & Sons, Ltd.

Progression of Electrocardiographic Abnormalities in Type 1 Diabetes During 16 Years of Follow-up: The Epidemiology of Diabetes Interventions and Complications (EDIC) Study.

BACKGROUND: The electrocardiogram (ECG) is an objective tool for cardiovascular disease (CVD) risk assessment. METHODS AND RESULTS: We evaluated distribution of ECG abnormalities and risk factors for developing new abnormalities in 1314 patients with type 1 diabetes (T1D) from the Epidemiology of Diabetes Interventions and Complications (EDIC) study. Annual ECGs were centrally read. ECG abnormalities were classified as major and minor according to the Minnesota ECG Classification. At EDIC year 1 (baseline), 356 (27.1%) of the participants had at least 1 ECG abnormality (major or minor) whereas 26 (2%) had at least one major abnormality. During 16 years of follow-up, 1016 (77.3%) participants developed at least 1 new ECG abnormality (major or minor), whereas 172 (13.1%) developed at least 1 new major abnormality. Independent risk factors for developing new major ECG abnormalities were: age, current smoking, increased systolic blood pressure, and higher glycosylated hemoglobin (hazard ratio [HR] [95% CI]: 1.04 [1.02-1.06] per 1-year increase, 1.75 [1.22-2.53], 1.03 [1.01-1.05] per 1 mm Hg increase, and 1.16 [1.04-1.29] per 10% increase, respectively). Independent risk factors for developing any new ECG abnormalities (major or minor) were age and systolic blood pressure (HR [95% CI]: 1.02 [1.01-1.03] per 1-year increase and 1.01 [1.00-1.02] per 1 mm Hg increase, respectively). CONCLUSIONS: New ECG abnormalities commonly occur in the course of T1D, consistent with the recognized increasing risk for CVD as patients age. Advanced age, increased systolic blood pressure, smoking, and higher HbA1c are independent risk factor for developing major ECG abnormalities, which underscores the importance of tight glucose control in T1D in addition to management of common CVD risk factors.

Skin collagen fluorophore LW-1 versus skin fluorescence as markers for the long-term progression of subclinical macrovascular disease in type 1 diabetes.

BACKGROUND: Skin collagen Long Wavelength Fluorescence (LWF) is widely used as a surrogate marker for accumulation of advanced glycation end-products. Here we determined the relationship of LWF with glycemia, skin fluorescence, and the progression of complications during EDIC in 216 participants from the DCCT. METHODS: LW-1 and collagen-linked fluorescence (CLF) were measured by either High Performance Liquid Chromatography (HPLC) with fluorescence detection (LW-1) or total fluorescence of collagenase digests (CLF) in insoluble skin collagen extracted from skin biopsies obtained at the end of the DCCT (1993). Skin intrinsic fluorescence (SIF) was noninvasively measured on volar forearm skin at EDIC year 16 by the SCOUT DS instrument. RESULTS: LW-1 levels significantly increased with age and diabetes duration (P < 0.0001) and significantly decreased by intensive vs. conventional glycemic therapy in both the primary (P < 0.0001) and secondary (P < 0.037) DCCT cohorts. Levels were associated with 13-16 year progression risk of retinopathy (>3 sustained microaneurysms, P = 0.0004) and albumin excretion rate (P = 0.0038), the latter despite adjustment for HbA1c. Comparative analysis for all three fluorescent measures for future risk of subclinical macrovascular disease revealed the following significant (P < 0.05) associations after adjusting for age, diabetes duration and HbA1c: coronary artery calcium with SIF and CLF; intima-media thickness with SIF and LW-1; and left ventricular mass with LW-1 and CLF. CONCLUSIONS: LW-1 is a novel risk marker that is robustly and independently associated with the future progression of microvascular disease, intima-media thickness and left ventricular mass in type 1 diabetes. Trial registration NCT00360815 and NCT00360893 at clinicaltrials.gov.