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Women with type 1 diabetes (T1D) are at higher risk for Gestational Hypertensive Disorders (GHD) and cardiovascular disease (CVD) compared to women without diabetes. However, the long-term consequences of GHD complicated by T1D on CVD are unknown. We compared CVD risk factors pre-pregnancy (median follow-up 3 years, IQR 2-4 years) to post-pregnancy (median 2 years, IQR 1-3 years) excluding six weeks post-partum in women with T1D with a first pregnancy complicated by GHD (n=27) vs. those with an uncomplicated pregnancy (n=49), frequency matched for age (mean age 25 years) and diabetes duration (mean duration 12 years). Linear mixed models adjusted for age, diabetes duration, and weeks gestation were used to examine CVD risk factors. Pre-pregnancy, the groups did not differ in age, diabetes duration, body mass index (BMI), lipids, systolic or diastolic blood pressure (BP) (Table). A1c was higher pre-pregnancy in the complicated vs. uncomplicated group (p=0.004); post-pregnancy there was no change in the complicated group but an increase in A1c in the uncomplicated group (p=0.003). Complicated pregnancies resulted in increased systolic (p=0.001) and diastolic BP (p=0.01) post-pregnancy; uncomplicated pregnancies were not associated with significant changes in BP. Women with T1D and a pregnancy complicated by GHD had similar BP but higher A1c pre-pregnancy, and persistently higher BP post-pregnancy, suggesting a need to intervene to prevent CVD. Disclosure J.K. Snell-Bergeon: None. L. Pyle: None. R.M. Sippl: None. S. Polsky: Consultant; Self; Jaeb Center for Health Research. Research Support; Self; Barbara Davis Center for Diabetes, Children's Diabetes Foundation, Dexcom, Inc., Eli Lilly and Company, JDRF, Leona & Harry Helmsley Charitable Trust, National Institute of Diabetes and Digestive and Kidney Diseases, Sanofi US. Funding American Diabetes Association (7-13-CD-10 to J.K.S-B.)

Background: Among the modifiable risk factors, diet plays an important role in the risks and progression of atherosclerotic cardiovascular disease (ASCVD). However, few studies have examined this association in people with type 1 diabetes (T1D) who are at a greater risk of developing ASCVD than nondiabetic (non-DM) controls. Methods: We conducted cross-sectional and longitudinal analyses of data from CACTI study [n=1257; T1D: n=568; non-DM: n=689] collected between March 2000 and April 2002. Participants completed a validated food frequency questionnaire, a physical examination and fasting biochemical analyses (12h fast), and coronary artery calcification (CAC) was measured using electron beam computed tomography. At baseline, dietary patterns based on variations in food group intake were created with principal components analysis (PCA). Logistic regression was used to examine associations of dietary patterns with the CAC prevalence in a model adjusted for age and sex and stratified by diabetes status. Results: Three dietary patterns were identified using PCA as follows: ‘fruits, veggies, meats, cereal’, ‘baked desserts’ and ‘convenience foods and alcohol’ patterns. At baseline, no significant associations of dietary patterns with CAC prevalence were observed. At year-6, ‘baked dessert’ pattern was significantly associated with increased risk of CAC ( Conclusions: Habitual intake of a dietary pattern that is characterized by an increased intake of added sugar and fats, such as in baked desserts may increase risks of atherosclerosis in T1D. Thus, dietary adjustments to improve this pattern may be atheroprotective. Disclosure A. Basu: None. A.C. Alman: None. J.K. Snell-Bergeon: None. Funding American Diabetes Association (7-13-CD-10 to J.K.S-B.)

Pregnancies associated with diabetes are at high risk of adverse health outcomes. We examined associations between indices of glycemia and GV, assessed by continuous glucose monitoring, and maternal and fetal outcomes in women with T1D. Women with T1D were stratified to groups during preconception or the 1st trimester: (1) CGM Alone (n=13): women without Apple devices, or (2) CGM Share (n=15, DexCom, San Diego, CA): women with iPhone and followers with data viewing devices. Association between change in GV indices over time and gestational outcomes were measured with linear mixed models. Preeclampsia developed in 28.6% (8/28) of women. Preeclampsia was significantly associated with higher estimated A1C, mean sensor glucose, and time spent >140 mg/dL, and with lower time spent 140 mg/dL, and with higher time in range (Table 2). There were no associations found between GV indices and cesarean delivery, delivery Preeclampsia and gestational age at delivery were associated with worse A1C and CGM metrics, but not with GV indices. Disclosure S. Polsky: Consultant; Self; Jaeb Center for Health Research. Research Support; Self; Barbara Davis Center for Diabetes, Children's Diabetes Foundation, Dexcom, Inc., Eli Lilly and Company, JDRF, Leona & Harry Helmsley Charitable Trust, National Institute of Diabetes and Digestive and Kidney Diseases, Sanofi US. L. Pyle: None. R. Garcetti: None. P. Joshee: None. J.K. Demmitt: None. T.B. Vigers: None. J.K. Snell-Bergeon: None. Funding Dexcom, Inc.; National Center for Research Resources/Colorado Clinical and Translational Science Institute (UL1RR025780)

Pregnancies complicated by T1D have more glycemic variability than pregnancies associated with other kinds of diabetes. We examined whether remote monitoring of Continuous Glucose Monitoring (CGM) data by family/friends affects glycemic variability during pregnancy. Women with T1D were stratified to groups during preconception or the 1st trimester: (1) CGM Alone (n=13): women without Apple devices, or (2) CGM Share (n=15, DexCom, San Diego, CA): women with iPhone and followers with data viewing devices. Data within 12 hours of acetaminophen use were excluded. Linear mixed models were used to compare indices of glycemic variability over time between groups. A1C decreased in both groups over time and was lower in CGM Share compared to CGM Alone (p=0.0376, Table). Mean sensor glucose was lower in CGM Share than CGM Alone (p=0.0492). Times spent within targeted pregnancy ranges were not different between groups. CGM Alone had a significantly higher High Blood Glucose Index (HGBI) than CGM Share (p=0.0347). CGM Share was associated with a lower risk of hyperglycemia (as measured by HBGI) than CGM Alone among pregnant women with T1D, but other measures of glycemic variability were similar between groups. Disclosure S. Polsky: Consultant; Self; Jaeb Center for Health Research. Research Support; Self; Barbara Davis Center for Diabetes, Children's Diabetes Foundation, Dexcom, Inc., Eli Lilly and Company, JDRF, Leona & Harry Helmsley Charitable Trust, National Institute of Diabetes and Digestive and Kidney Diseases, Sanofi US. J.K. Snell-Bergeon: None. P. Joshee: None. J.K. Demmitt: None. R. Garcetti: None. T.B. Vigers: None. L. Pyle: None. Funding Dexcom, Inc.; National Center for Research Resources/Colorado Clinical and Translational Science Institute (UL1RR025780)

People with T1D have higher HDL cholesterol (HDLc) yet are more insulin resistant and have increased cardiovascular disease (CVD) risk than people without diabetes. We hypothesized that HDL is dysfunctional in people with T1D, explaining this paradox. We examined the association between eIS, serum HDL CEC, and HDL subspecies in adults with T1D. This study was conducted in a sub-cohort (N=134) randomly selected from the Coronary Artery Calcification in type 1 diabetes study (N=652). eIS was calculated using a validated equation that includes waist circumference, triglycerides, adiponectin, diastolic blood pressure and insulin dose. We quantified CEC from a macrophage cell line (J774) and through the cholesterol transport proteins ABCA1 and ABCG1 and HDL particle concentration and size using calibrated ion mobility analysis. The analyzed HDLs were extra small (XS-HDL), small (S-HDL), medium (M-HDL) and large (L-HDL) populations. Associations were assessed by multivariable linear regression. J774 and ABCA1 CEC were negatively associated with eIS, as was S-HDL (Table). eIS positively associated with L-HDL, whereas other HDL metrics were not associated with eIS. Higher eIS associated with fewer S-HDL particles and reduced macrophage- and ABCA1-mediated CEC, suggesting novel interactions among insulin sensitivity and HDL metrics, which may contribute to CVD risk in T1D. Disclosure T. Buckner: None. K. Bornfeldt: None. J. Heinecke: None. T. Vaisar: Consultant; Self; MedImmune. Research Support; Self; MedImmune. J.K. Snell-Bergeon: None. Funding American Diabetes Association (7-13-CD-10 to J.K.S-B.)

Depression is increased in people with type 1 diabetes (T1D), and may lead to poor disease self-management and suboptimal glycemic control. Depressive symptoms were assessed in adults with and without longstanding T1D (mean±SD T1D duration 38±8.6 years). A total of 414 participants with T1D (mean±SD age 51±9 years) and 488 participants without T1D (mean±SD age 55±9 years) completed the Beck Depression Inventory II (BDI-II) and the Diabetes Self-Management Questionnaire (DSMQ). BDI-II scores were significantly higher in people with T1D (mean±SD 5.4±5.6%) than in those without T1D (3.8±4.7, p13), whereas 7.1% of women and 1.7% of men without T1D reported clinically elevated symptoms of depression (p=0.004). Among participants with T1D, a higher BDI-II score was significantly correlated to HbA1c (r=0.21, p=0.0005). In age, sex, and T1D duration adjusted linear regression models, BDI-II scores >13 were associated with significantly lower total scores on the DSMQ (p Our data demonstrate elevated levels of depressive symptoms in adults with T1D, particularly men, which were associated with lower self-management behaviors. Interventions are needed to address the role of depression on glycemic control and behaviors around glucose management, diet and physical activity in adults. Disclosure C.R. Geno Rasmussen: None. K.A. Driscoll: None. R.M. Sippl: None. A.C. Alman: None. A. Keshawarz: None. J.K. Snell-Bergeon: None. Funding American Diabetes Association (7-13-CD-10 to J.K.S-B.); National Heart, Lung, and Blood Institute; JDRF International

Objective: In health, circulating growth differentiation factor (GDF)-15 is low, and concentrations are thought to increase rapidly in response to cardiac and renal injuries. GDF-15 is secreted in response to inflammation, oxidative stress and hypoxia, and therefore may be a biomarker of subclinical vascular disease. Yet, the relationships between GDF-15, coronary artery disease and diabetic kidney disease (DKD) remain incompletely understood. Accordingly, the objective of this study was to delineate these relationships in adults with T1D. Methods: Participants with (n=377, HbA1c 7.8±1.3%, duration 37.1±8.6 years) and without T1D (n=456) in the Coronary Artery Calcification in type 1 diabetes (CACTI) study were assessed for serum GDF-15, coronary artery calcification (CAC) measured using 128-slice spiral CT, urinary albumin-to-creatinine ratio (UACR) and eGFR calculated by CKD-EPI creatinine. Impaired GFR was defined as eGFR Results: Participants with T1D had greater GDF-15 concentrations than nondiabetics (666.4 [95% CI 633.9-700.5] vs. 579.1 [558.7-600.4] ng/l, p Conclusion: In this cross-sectional analysis, GDF-15 was strongly associated with DKD and coronary atherosclerosis in adults with T1D, independent of glycemic control. As a biomarker, GDF-15 holds promise to aid in risk stratification and clinical trial enrichment. Disclosure P. Bjornstad: Advisory Panel; Self; Horizon, XORTX. Consultant; Self; Bayer US, Boehringer Ingelheim International GmbH, Bristol-Myers Squibb Company. R.M. Sippl: None. M. Rewers: None. J.K. Snell-Bergeon: None. Funding National Institutes of Health; JDRF

Objectives To determine trajectories of glycemic control and body mass index (BMI) z-score in a large pediatric sample with type 1 diabetes (T1D) over a 38-year period, and to evaluate sex differences and temporal changes in the prevalence of these trajectories. Methods We conducted a longitudinal, retrospective study of 7002 2 to 18 year olds with T1D followed between 1978 and 2016 at a single center. Group-based modeling was used to identify trajectories for hemoglobin A1c (HbA1c) and BMI z-score. Multinomial logistic regression identified predictors of membership to less favorable glycemic trajectories. Results Group-based modeling yielded 5 HbA1c trajectories. A total of 86% of the sample fell within 3 trajectories that were largely stable across childhood and adolescence, and 14% fell within 2 trajectories characterized by marked deterioration beginning in pre-adolescence. Girls were more likely to be in the HbA1c trajectory with the highest starting HbA1c and significant deterioration during adolescence, and in the highest two BMI z-score trajectories. Patients with non-white race had the highest odds of belonging to a less favorable HbA1c trajectory. Prevalence of the high stable HbA1c trajectory decreased and prevalence of the low stable HbA1c trajectory increased over the study period. Conclusions A minority of youth with T1D experienced deterioration of glycemic control during adolescence. Girls were more likely to belong to the worst HbA1c trajectory and to BMI z-score trajectories in the overweight/obese range, which may increase cardiometabolic risk. Addressing racial/ethnic disparities in glycemic control should remain a priority. Advances in T1D management correlated with favorable shifts in HbA1c trajectory prevalence.

Continuous glucose monitoring (CGM) is an essential part of diabetes care. Real-time CGM data are beneficial to patients for daily glucose management, and aggregate summary statistics of CGM measures are valuable to direct insulin dosing and as a tool for researchers in clinical trials. Yet, the various commercial systems still report CGM data in disparate, non-standard ways. Accordingly, there is a need for a standardized, free, open-source approach to CGM data management and analysis. Functions were developed in the free programming language R to provide a rapid, easy, and consistent methodology for CGM data management and analysis. Summary variables calculated by our package compare well to those generated by various CGM software, and our functions provide a more comprehensive list of summary measures available to clinicians and researchers. Consistent handling of CGM data using our R package may facilitate collaboration between research groups and contribute to a better understanding of free-living glucose patterns.

BACKGROUND: Although diabetic kidney disease demonstrates both familial clustering and single nucleotide polymorphism heritability, the specific genetic factors influencing risk remain largely unknown.METHODS: To identify genetic variants predisposing to diabetic kidney disease, we performed genome-wide association study (GWAS) analyses. Through collaboration with the Diabetes Nephropathy Collaborative Research Initiative, we assembled a large collection of type 1 diabetes cohorts with harmonized diabetic kidney disease phenotypes. We used a spectrum of ten diabetic kidney disease definitions based on albuminuria and renal function.RESULTS: Our GWAS meta-analysis included association results for up to 19,406 individuals of European descent with type 1 diabetes. We identified 16 genome-wide significant risk loci. The variant with the strongest association (rs55703767) is a common missense mutation in the collagen type IV alpha 3 chain (COL4A3) gene, which encodes a major structural component of the glomerular basement membrane (GBM). Mutations in COL4A3 are implicated in heritable nephropathies, including the progressive inherited nephropathy Alport syndrome. The rs55703767 minor allele (Asp326Tyr) is protective against several definitions of diabetic kidney disease, including albuminuria and ESKD, and demonstrated a significant association with GBM width; protective allele carriers had thinner GBM before any signs of kidney disease, and its effect was dependent on glycemia. Three other loci are in or near genes with known or suggestive involvement in this condition (BMP7) or renal biology (COLEC11 and DDR1).CONCLUSIONS: The 16 diabetic kidney disease-associated loci may provide novel insights into the pathogenesis of this condition and help identify potential biologic targets for prevention and treatment.

Continuous glucose monitoring (CGM) is an essential part of diabetes care. Real-time CGM data are beneficial to patients for daily glucose management, and aggregate summary statistics of CGM measures are valuable to direct insulin dosing and as a tool for researchers in clinical trials. Yet, the various commercial systems still report CGM data in disparate, non-standard ways. Accordingly, there is a need for a standardized, free, open-source approach to CGM data management and analysis. A package titled cgmanalysis was developed in the free programming language R to provide a rapid, easy, and consistent methodology for CGM data management, summary measure calculation, and descriptive analysis. Variables calculated by our package compare well to those generated by various CGM software, and our functions provide a more comprehensive list of summary measures available to clinicians and researchers. Consistent handling of CGM data using our R package may facilitate collaboration between research groups and contribute to a better understanding of free-living glucose patterns.

We investigated the efficacy and safety of continuous glucose monitoring (CGM) initiation within 1 year of type 1 diabetes (T1D) diagnosis among children, adolescents, and adults.Differences in mean A1c (primary outcome) and diabetes-related emergency visits (secondary outcome) for 2.5 years between early CGM users and non-CGM users were studied among 396 newly diagnosed patients with T1D (94% children [age18 years], 5% adults, 46% females) between January 2013 and December 2015 at Barbara Davis Center for Diabetes. The primary outcome was adjusted by age at diagnosis and gender. P 0.05 was considered significant.Gender, ethnicity, body mass index, and A1c at diagnosis were similar between the groups. Irrespective of insulin delivery methods, CGM users had a significantly greater improvement in glycemic control than non-CGM users at 1, 1.5, 2, and 2.5 years. For 2.5 years of follow-up, the multiple daily injection (MDI)+CGM group (n = 19) had 1.5% ± 0.2% lower A1c than the MDI only group (n = 225) (7.7% ± 0.2% vs. 9.2% ± 0.04%, P 0.0001), and the insulin pump (continuous subcutaneous insulin infusion [CSII])+CGM group (n = 62) had 0.7% ± 0.1% lower A1c than the CSII only group (n = 90) (8.0% ± 0.08% vs. 8.7% ± 0.07%, P 0.0001). The MDI+CGM group had significantly lower A1c than the CSII only group (7.7% ± 0.2% vs. 8.7% ± 0.07%, P 0.0001). The number of diabetes-related (severe hypoglycemia or hyperglycemia) emergency department visits was significantly lower among early CGM users compared with non-CGM users (P = 0.003).Irrespective of insulin delivery system, early initiation of CGM within 1 year from T1D diagnosis was associated with better glucose control and fewer diabetes-related emergency visits.

Diabetic kidney disease (DKD) is a heritable but poorly understood complication of diabetes. To identify genetic variants predisposing to DKD, we performed genome-wide association analyses in 19,406 individuals with type 1 diabetes (T1D) using a spectrum of DKD definitions basedon albuminuria and renal function. We identified 16 genome-wide significant loci. The variant with the strongest association (rs55703767) is a common missense mutation in the collagen type IV alpha 3 chain(COL4A3)gene, which encodes a major structural component of the glomerular basement membrane (GBM) implicated in heritable nephropathies. The rs55703767 minor allele (Asp326Tyr) is protective against several definitions of DKD, including albuminuria and end-stage renal disease. Three other loci are in or near genes with known or suggestive involvement in DKD(BMP7)or renal biology (COLEC11andDDR1). The 16 DKD-associated loci provide novel insights into the pathogenesis of DKD, identifying potential biological targets for prevention and treatment.

Summary People commonly increase sleep duration on the weekend to recover from sleep loss incurred during the workweek. Whether ad libitum weekend recovery sleep prevents metabolic dysregulation caused by recurrent insufficient sleep is unknown. Here, we assessed sleep, circadian timing, energy intake, weight gain, and insulin sensitivity during sustained insufficient sleep (9 nights) and during recurrent insufficient sleep following ad libitum weekend recovery sleep. Healthy, young adults were randomly assigned to one of three groups: (1) control (CON; 9-h sleep opportunities, n = 8), (2) sleep restriction without weekend recovery sleep (SR; 5-h sleep opportunities, n = 14), and (3) sleep restriction with weekend recovery sleep (WR; insufficient sleep for 5-day workweek, then 2 days of weekend recovery, then 2 nights of insufficient sleep, n = 14). For SR and WR groups, insufficient sleep increased after-dinner energy intake and body weight versus baseline. During ad libitum weekend recovery sleep, participants cumulatively slept ∼1.1 h more than baseline, and after-dinner energy intake decreased versus insufficient sleep. However, during recurrent insufficient sleep following the weekend, the circadian phase was delayed, and after-dinner energy intake and body weight increased versus baseline. In SR, whole-body insulin sensitivity decreased ∼13% during insufficient sleep versus baseline, and in WR, whole-body, hepatic, and muscle insulin sensitivity decreased ∼9%–27% during recurrent insufficient sleep versus baseline. Furthermore, during the weekend, total sleep duration was lower in women versus men, and energy intake decreased to baseline levels in women but not in men. Our findings suggest that weekend recovery sleep is not an effective strategy to prevent metabolic dysregulation associated with recurrent insufficient sleep.

Background LpPLA 2 mass and activity have been variably related to cardiovascular disease risk, and the distribution of LpPLA 2 in patients with type 1 diabetes (T1D), wherein cardiovascular disease risk is high despite normal or higher levels of high-density lipoprotein (HDL) cholesterol, is unknown. Objective To determine whether there are differences in the distribution of LpPLA 2 mass and activity across lipoproteins and their association with coronary artery calcium (CAC) in patients with T1D. Methods Men with T1D (n = 19) not on statins, with and without CAC progression, and men without diabetes matched for HDL cholesterol (n = 25) had lipoproteins separated by fast protein liquid chromatography. Results Both LpPLA 2 mass and activity were found within low-density lipoprotein (LDL) and HDL pools with more LpPLA 2 mass being associated with HDL (54% vs 44%; P -value 2 activity being associated with LDL (56% vs 40%; P value = .02). In T1D, more LpPLA 2 activity was associated with large- or less-dense LDL compared to those without diabetes. However, no difference in LpPLA 2 activity or mass between lipoprotein subfractions was observed between all groups, and there was no relationship between LpPLA 2 activity or mass and its distribution and CAC score progression in healthy or T1D men. Conclusion LpPLA 2 is found in both LDL and HDL and is distributed differently in men with T1D without any relationship to CAC score progression.

Objective Reduced insulin sensitivity (IS) is well documented in type 1 diabetes (T1D) and may contribute to vascular complications. We examined the association of estimated IS (eIS) with incident macro- and microvascular complications in adults with T1D in the prospective CACTI study. Methods Participants (N = 652) were 19–56 years old at baseline and re-examined 6.2 ± 0.6 years later. Urinary albumin excretion was measured, and categorized as microalbuminuria or greater. Diabetic retinopathy (DR) was based on self-reported history, proliferative DR (PDR) as history of laser eye therapy and coronary artery calcium (CAC) was measured using electron-beam CT. Progression of CAC was defined as a change in the square root transformed CAC volume score of ≥ 2.5. IS was estimated (eIS) by an equation derived from clamp studies. Predictors of each complication were examined using stepwise logistic regression and subjects with complications at baseline excluded. Age, T1D duration, sex, HbA1c, SBP, LDL-C, and eIS were considered for inclusion. Results Greater eIS at baseline predicted lower odds of developing albuminuria (OR: 0.67, 95% CI 0.51–0.88), DR (OR 0.79, 0.64–0.97), PDR (OR: 0.76, 0.57–0.99) and CACp (OR: 0.71, 0.60–0.85) in multivariable models. Conclusions Greater eIS conferred protection from the development of vascular complications over 6-years in T1D.

Background and aims Pericardial adipose tissue (PAT) is located on both sides of the pericardium. We tested whether PAT was associated with prevalent diabetes at the year 25 exam of the Coronary Artery Risk Development in Young Adults (CARDIA) study. Methods and results The CARDIA Year 25 exam (2010–2011) included complete data for all covariates on 3107 participants. Prevalent diabetes ( n = 436) was defined as high fasting (≥126 mg/dl) or 2-h postload glucose (≥200 mg/dl) or HbA 1c (≥6.5%) or use of diabetes medications. Volume of PAT was measured from computed tomographic scans. Logistic regression was performed to examine the relationship between quartiles of PAT and diabetes. In regression models adjusted for field center, sex, race, age, systolic blood pressure, total cholesterol, log triglycerides, and treatment with blood pressure and cholesterol lowering medication, PAT volume in the 4th quartile was significantly associated with diabetes status after adjustment for BMI (OR 2.57, 95% CI 1.66, 3.98) or visceral adipose tissue (OR 2.08, 95% CI 1.32, 3.29). PAT volume in the 2nd and 3rd quartiles was not significantly associated with diabetes status relative to the first quartile. Conclusions Metabolically active pericardial adipose tissue is associated with prevalent diabetes only at higher volumes independent of overall obesity.

Urine uric acid (UUA) has been implicated in the pathogenesis of diabetic nephropathy via its effect on tubular cells. We hypothesized that the UUA level would be higher in adolescents with type 1 diabetes (T1D) than in those without T1D. We also hypothesized that UUA and fractional uric acid excretion (FeUA) would be higher in adolescents with T1D and hyperfiltration [estimated glomerular filtration rate (eGFR) ≥141 mL/min/1.73 m(2)] than in those without hyperfiltration.The UUA concentration was determined and FeUA calculated in adolescents with (n = 239) and without T1D (n = 75). The eGFR was calculated using the Zappitelli equation based on serum creatinine and cystatin C concentrations.Compared to the non-diabetic adolescents enrolled in the study, those with T1D had a higher eGFR (mean ± standard deviation: 120 ± 22 vs. 112 ± 16 mL/min/1.73 m(2); p = 0.0006), lower urine pH (6.2 ± 0.8 vs. 6.5 ± 1.0; p = 0.01), and higher UUA (37.7 ± 18.6 vs. 32.8 ± 18.1 mg/dL; p = 0.049) and FeUA (median [interquartile range]: 6.2 [4.3-8.7] vs. 5.2 [3.6-7.0] %; p = 0.02). Among adolescents with T1D, those with hyperfiltration had higher median FeUA (8.6 [5.2-9.9] vs. 6.0 [4.2-8.3] %; p = 0.02) than those without hyperfiltration.The adolescents with T1D enrolled in the study had higher eGFR, higher UUA and more acidic urine than the non-diabetic controls, which may have increased their risk of UUA crystallization. Adolescents with T1D and hyperfiltration had higher FeUA than those without hyperfiltration. These hypothesis-generating observations may suggest a potential pathophysiologic association between uricosuria and hyperfiltration.

Over the past several decades, insulin treatment has changed drastically, not only with the development of further insulin analogs but also with the introduction of novel insulin delivery devices such as pumps and pens. In addition, adjunct devices such as continuous glucose monitors and sensor-augmented pumps have become increasingly used in clinical care, increasing the volume of information available to patients and providers. However, with the development of new devices it has become clear that along with the many benefits of these advances, the use of these devices can also present a burden to people with diabetes. For example, some patients report being overwhelmed by too much data when using continuous glucose monitors. Furthermore, there are concerns regarding the accuracy of some of these new devices, particularly for glucose monitoring. As a result, some patients may choose not to use available devices, despite the recognized benefits. Therefore, it is critical to understand how the various insulin delivery devices available currently and in the future affect patients in terms of their diabetes management and perceived burdens and to understand which patient characteristics may predict a lack of satisfaction with these devices. This critical gap in our knowledge is addressed in an article in this issue of the journal through the development of a questionnaire that allows for a better understanding of the impact of insulin delivery devices on quality of life and diabetes management among both type 1 diabetes and insulin-dependent type 2 diabetes patients. The novelty, as well as limitations, of this new instrument for the assessment of insulin delivery device satisfaction are discussed.

Brief Summary Vasopressin exerts important cardio–renal effects, but remains problematic to measure. Copeptin is a more stable peptide derived from the same precursor molecule. In this case–control study from the Type 1 Diabetes Exchange (T1DX) Biobank registry, men with T1D and albuminuria had greater copeptin concentrations than men with normoalbuminuria.

Post-prandial hyperglycemia is difficult to control due to lack of an ideal prandial insulin. TI (Afrezza®) has the most rapid onset of action, lasts for 2 hours. Sixty patients with T1D on multiple daily injections (MDI) were randomized in a multi-center study, stratified by baseline A1c values ( Mean CGM glucose, SD, time in range (70-180 mg/dL), % time in hyper- (>180 mg/dL) or hypoglycemia ( We conclude that TI improves PPBG when treat-to-target algorithms are used in patients with T1D on MDI. Disclosure H.K. Akturk: None. J.K. Snell-Bergeon: Stock/Shareholder; Self; Abbott. Research Support; Self; Roche Diagnostics Corporation. A. Rewers: None. L.J. Klaff: Research Support; Self; Abbott, Intarcia Therapeutics, Inc., MannKind Corporation, Dexcom, Inc., Novartis Pharmaceuticals Corporation, Gelesis, Novo Nordisk Inc., Eli Lilly and Company, Medtronic, Sanofi. A. Peters: Advisory Panel; Self; Abbott, Bigfoot Biomedical. Research Support; Self; Dexcom, Inc.. Advisory Panel; Self; Eli Lilly and Company, Insulin Algorithms, JDRF, Lexicon Pharmaceuticals, Inc., Livongo Health. Research Support; Self; MannKind Corporation. Other Relationship; Self; Medscape. Advisory Panel; Self; Merck & Co., Inc.. Research Support; Self; National Institute of Diabetes and Digestive and Kidney Diseases. Speaker's Bureau; Self; Novo Nordisk Inc.. Advisory Panel; Self; Novo Nordisk Inc., Omada Health, Inc., Optum Rx, Inc., Sanofi. Research Support; Self; T1D Exchange. Advisory Panel; Self; The Endocrine Society. Research Support; Self; The Leona M. and Harry B. Helmsley Charitable Trust. Advisory Panel; Spouse/Partner; Johnson & Johnson Diabetes Institute, LLC. B.W. Bode: Research Support; Self; Abbott. Advisory Panel; Self; ADOCIA. Research Support; Self; Boehringer Ingelheim Pharmaceuticals, Inc.. Consultant; Self; Janssen Pharmaceuticals, Inc.. Research Support; Self; GlaxoSmithKline plc., Lexicon Pharmaceuticals, Inc., Medtronic MiniMed, Inc., Novo Nordisk Inc., Diasome Pharmaceuticals, Inc., Sanofi US, Eli Lilly and Company, MannKind Corporation, Dexcom, Inc., OmniPod, Senseonics. T.S. Bailey: Research Support; Self; Abbott. Consultant; Self; Abbott. Speaker's Bureau; Self; Abbott. Research Support; Self; Ambra BioScience, Ascensia Diabetes Care, Becton, Dickinson and Company. Consultant; Self; Becton, Dickinson and Company. Research Support; Self; Boehringer Ingelheim Pharmaceuticals, Inc., Calibra Medical. Consultant; Self; Calibra Medical. Research Support; Self; Companion Medical, Dexcom, Inc., Glooko, Inc., GlySens Incorporated, Lexicon Pharmaceuticals, Inc., Eli Lilly and Company. Consultant; Self; Eli Lilly and Company. Speaker's Bureau; Self; Eli Lilly and Company. Research Support; Self; Medtronic MiniMed, Inc.. Consultant; Self; Medtronic MiniMed, Inc.. Speaker's Bureau; Self; Medtronic MiniMed, Inc.. Research Support; Self; Novo Nordisk Inc.. Consultant; Self; Novo Nordisk Inc.. Speaker's Bureau; Self; Novo Nordisk Inc.. Research Support; Self; Sanofi. Consultant; Self; Sanofi. Speaker's Bureau; Self; Sanofi. Research Support; Self; Senseonics. Consultant; Self; Intarcia Therapeutics, Inc.. Research Support; Self; Versartis, Inc., Xeris Pharmaceuticals, Inc., MannKind Corporation. S.K. Garg: Research Support; Self; Dexcom, Inc., Eli Lilly and Company, Sanofi US. Advisory Panel; Self; Sanofi US. Research Support; Self; MannKind Corporation, Diasome Pharmaceuticals, Inc., Labstyle Innovations, Lexicon Pharmaceuticals, Inc., Medtronic. Advisory Panel; Self; Novo Nordisk A/S.

The risk for cardiovascular (CV) disease and osteoporotic fractures is higher in postmenopausal women with type 1 diabetes (T1D). However, it is unclear whether these processes have common risk factors. We examined the associations between bone mineral density (BMD), trabecular bone score (TBS), and CV risk measures in 47 postmenopausal women with T1D (62 years, diabetes duration; 41 years and A1c 7.8%) and 51 postmenopausal women without diabetes (64 years and A1c 5.5%). Age, menopausal duration, BMI, serum creatinine, calcium, 25-OH-D, parathyroid hormone (PTH) and bone turnover markers (BTMs) were similar between two groups. T1D postmenopausal women had lower left femoral neck and distal forearm BMD, and subendocardial viability index (SVI) and higher augmented pressure (AP) and carotid intima media thickness (cIMT) compared to controls (Table). HbA1c was negatively correlated with distal forearm BMD, TBS and SVI and positively correlated with AP. Total cholesterol and LDL-C were associated with arterial stiffness but not with BMD. PTH and BTMs were associated with lower BMD but not with CV risk measures. Urinary microalbumin was inversely correlated with distal forearm BMD and TBS, and positively correlated with AP and cIMT. T1D is associated with lower femoral neck and distal forearm BMD and higher arterial stiffness and cIMT. Urine microalbumin was the only factor linked to both low BMD and high CV risk.VariablesPostmenopausal women with T1D (n=47)Postmenopausal women without diabetes (n=51)P-valueLeft femoral neck BMD (g/cm2)0.6±0.10.7±0.10.01Left distal forearm BMD (g/cm2)0.61±0.090.66±0.080.008Lumbar spine BMD(g/cm2)0.9±0.10.9±0.10.9Subendocardial viability index (%)119.0±18.1149.1±23.9 Disclosure V.N. Shah: None. P. Joshee: None. R.M. Sippl: None. J.K. Snell-Bergeon: Stock/Shareholder; Self; Abbott. Research Support; Self; Roche Diagnostics Corporation.

Little is known about how tubular injury relates to intrarenal hemodynamic dysfunction in T1D. We sought to define the relationships between serum NGAL, a marker of tubular injury, and intrarenal hemodynamic function (glomerular filtration rate [GFR], effective renal plasma flow [ERPF], renal vascular resistance [RVR]) in T1D adults. The cohort consisted of patients with longstanding T1D (≥50 years duration); 44 Diabetic Nephropathy (DN) Resistors (eGFR >60mL/min/1.73m2 and Differences remained significant after adjusting for age, sex, HbA1c, SBP and LDL. DN Resistors had significantly lower serum NGAL vs. those with DN. Elevated NGAL is related to intrarenal hemodynamic dysfunction and afferent vasoconstriction in longstanding T1D. Disclosure P. Bjornstad: Consultant; Self; Boehringer Ingelheim GmbH. J.K. Snell-Bergeon: Stock/Shareholder; Self; Abbott. Research Support; Self; Roche Diagnostics Corporation. J.A. Lovshin: Other Relationship; Self; AstraZeneca. Consultant; Self; Novo Nordisk Inc.. Research Support; Self; Sanofi, Merck Sharp & Dohme Corp.. Other Relationship; Self; Novo Nordisk Inc.. S.K. Singh: None. L. Lovblom: None. J.M. Tse: None. A. Orszag: None. Y. Lytvyn: None. M.H. Brent: Research Support; Self; Novartis Canada. Advisory Panel; Self; Novartis Canada. Research Support; Self; Bayer Canada. Advisory Panel; Self; Bayer Canada, Allergan Canada. Research Support; Self; Roche Canada. N. Paul: None. A. Weisman: None. H.A. Keenan: Research Support; Self; Sanofi. Employee; Self; Sanofi Genzyme. L. Cham: None. V. Bril: Consultant; Self; Alexion Pharmaceuticals, Inc.. Research Support; Self; CSL Behring, Grifols. Advisory Panel; Self; CSL Behring. Consultant; Self; Grifols. Research Support; Self; Shire. Advisory Panel; Self; Pfizer Inc. B.A. Perkins: Advisory Panel; Self; Boehringer Ingelheim GmbH. Research Support; Self; Boehringer Ingelheim GmbH, Novo Nordisk Inc.. Advisory Panel; Self; Novo Nordisk Inc., Abbott. Speaker's Bureau; Self; Abbott, Janssen Pharmaceuticals, Inc.. Advisory Panel; Self; Insulet Corporation. Speaker's Bureau; Self; Insulet Corporation, Dexcom, Inc. D. Cherney: Consultant; Self; AbbVie Inc.. Other Relationship; Self; AstraZeneca, Boehringer Ingelheim GmbH, Eli Lilly and Company. Consultant; Self; Sanofi. Other Relationship; Self; Merck & Co., Inc.. Consultant; Self; Mitsubishi Tanabe Pharma Corporation. Other Relationship; Self; Janssen Pharmaceuticals, Inc..

The T1D Exchange (T1DX) Clinic Registry assessed CVD risk factors in a large, contemporary cohort of adults with T1D living in the U.S. To understand the incidence and CVD risk factors, we evaluated the association of CVD risk factors and 5-year risk of CVD in adults ≥18 years of age, without CVD at enrollment in the T1DX. CVD was defined as a composite outcome of clinic reported fatal or non-fatal events of ischemic heart disease and heart failure. Associations between diabetic specific and traditional CVD risk factors and incident CVD were examined by logistic regression adjusting for potential confounders. The study included 4,463 participants (55% female, 91% non-Hispanic white, mean age 41 years, T1D duration 21 years). At enrollment, mean HbA1c was 7.7%, 43% used statin, and 45% used blood pressure medication. Incident CVD was reported by 419 (9.4%) participants during the 5-year follow-up. Age, diabetes duration, elevated BMI, triglycerides (TG), and diabetic nephropathy were associated with greater odds of CVD [Table]. Sex, mean HbA1c, HbA1c variability, pulse pressure, and hypertension were not associated with CVD. Markers of insulin resistance (BMI and TG) and diabetic nephropathy are important risk factors for CVD. Longer follow-up is required to assess the impact of other CVD risk factors on CVD in adults with T1D. Disclosure S.N. Mehta: None. M. Wu: None. N.C. Foster: None. R. Pop-Busui: Research Support; Self; AstraZeneca. M. Katz: None. J.P. Crandall: None. F. Bacha: Research Support; Self; AstraZeneca, JAEB Center For Health Research, National Institutes of Health, Pediatric Diabetes Consortium. K.J. Nadeau: None. I. Libman: Consultant; Self; Novo Nordisk A/S. P. Hiers: None. K.R. Mizokami-Stout: None. L. DiMeglio: Advisory Panel; Self; Eli Lilly and Company. Research Support; Self; Dexcom, Inc., Medtronic, Sanofi, Caladrius Biosciences, Inc., Janssen Research & Development, Xeris Pharmaceuticals, Inc., Sanofi. J. Sherr: Consultant; Self; Medtronic MiniMed, Inc.. Advisory Panel; Self; Insulet Corporation, Eli Lilly and Company, Bigfoot Biomedical. R.E. Pratley: Other Relationship; Self; AstraZeneca, Boehringer Ingelheim Pharmaceuticals, Inc., Eisai Inc., GlaxoSmithKline plc., Janssen Pharmaceuticals, Inc., Lexicon Pharmaceuticals, Inc., Ligand Pharmaceuticals, Inc., Eli Lilly and Company, Merck & Co., Inc., Novo Nordisk Inc., Pfizer Inc., Sanofi-Aventis, Takeda Development Center Americas, Inc.. S. Agarwal: None. J.K. Snell-Bergeon: Stock/Shareholder; Self; Abbott. Research Support; Self; Roche Diagnostics Corporation. E. Cengiz: Advisory Panel; Self; Novo Nordisk Inc.. Speaker's Bureau; Self; Novo Nordisk Inc.. Advisory Panel; Self; MannKind Corporation, ADOCIA, Arecor. S. Polsky: Research Support; Self; Dexcom, Inc.. Other Relationship; Self; T1D Exchange. Research Support; Self; National Institute of Diabetes and Digestive and Kidney Diseases. V.N. Shah: None.

Sixty patients with T1D on multiple daily injections (MDI) were randomized in a multi-center study, stratified by A1c values ( Compliance with TI was based on its use when indicated at 1- and 2-hour PPBG. Patients with at least 80% compliance were included in PPT (n=15). Seven TI patients were non-compliant; 2 dropped out of the study; and 2 did not have CGM data. CGM glucose patterns and TIR for a patient with 100% or with 56% compliant with TI are shown (Figure 1a and 1b). TIR was significantly higher in the TI-compliant group compared to control or TI-non-compliant groups (Figure 1c). PPBG was also significantly lower in the TI-compliant compared to the control group at 1- and 2-hours post-prandial but not at 3 and 4 hours. PPBG was significantly lower in the compliant vs. non-compliant TI group at all time points (Figure 1d). We conclude that TI improves TIR and PPBG values, if patients use additional inhalations as directed. Disclosure J.K. Snell-Bergeon: Stock/Shareholder; Self; Abbott. Research Support; Self; Roche Diagnostics Corporation. H.K. Akturk: None. A. Rewers: None. B.W. Bode: Research Support; Self; Abbott. Advisory Panel; Self; ADOCIA. Research Support; Self; Boehringer Ingelheim Pharmaceuticals, Inc.. Consultant; Self; Janssen Pharmaceuticals, Inc.. Research Support; Self; GlaxoSmithKline plc., Lexicon Pharmaceuticals, Inc., Medtronic MiniMed, Inc., Novo Nordisk Inc., Diasome Pharmaceuticals, Inc., Sanofi US, Eli Lilly and Company, MannKind Corporation, Dexcom, Inc., OmniPod, Senseonics. L.J. Klaff: Research Support; Self; Abbott, Intarcia Therapeutics, Inc., MannKind Corporation, Dexcom, Inc., Novartis Pharmaceuticals Corporation, Gelesis, Novo Nordisk Inc., Eli Lilly and Company, Medtronic, Sanofi. A. Peters: Advisory Panel; Self; Abbott, Bigfoot Biomedical. Research Support; Self; Dexcom, Inc.. Advisory Panel; Self; Eli Lilly and Company, Insulin Algorithms, JDRF, Lexicon Pharmaceuticals, Inc., Livongo Health. Research Support; Self; MannKind Corporation. Other Relationship; Self; Medscape. Advisory Panel; Self; Merck & Co., Inc.. Research Support; Self; National Institute of Diabetes and Digestive and Kidney Diseases. Speaker's Bureau; Self; Novo Nordisk Inc.. Advisory Panel; Self; Novo Nordisk Inc., Omada Health, Inc., Optum Rx, Inc., Sanofi. Research Support; Self; T1D Exchange. Advisory Panel; Self; The Endocrine Society. Research Support; Self; The Leona M. and Harry B. Helmsley Charitable Trust. Advisory Panel; Spouse/Partner; Johnson & Johnson Diabetes Institute, LLC. T.S. Bailey: Research Support; Self; Abbott. Consultant; Self; Abbott. Speaker's Bureau; Self; Abbott. Research Support; Self; Ambra BioScience, Ascensia Diabetes Care, Becton, Dickinson and Company. Consultant; Self; Becton, Dickinson and Company. Research Support; Self; Boehringer Ingelheim Pharmaceuticals, Inc., Calibra Medical. Consultant; Self; Calibra Medical. Research Support; Self; Companion Medical, Dexcom, Inc., Glooko, Inc., GlySens Incorporated, Lexicon Pharmaceuticals, Inc., Eli Lilly and Company. Consultant; Self; Eli Lilly and Company. Speaker's Bureau; Self; Eli Lilly and Company. Research Support; Self; Medtronic MiniMed, Inc.. Consultant; Self; Medtronic MiniMed, Inc.. Speaker's Bureau; Self; Medtronic MiniMed, Inc.. Research Support; Self; Novo Nordisk Inc.. Consultant; Self; Novo Nordisk Inc.. Speaker's Bureau; Self; Novo Nordisk Inc.. Research Support; Self; Sanofi. Consultant; Self; Sanofi. Speaker's Bureau; Self; Sanofi. Research Support; Self; Senseonics. Consultant; Self; Intarcia Therapeutics, Inc.. Research Support; Self; Versartis, Inc., Xeris Pharmaceuticals, Inc., MannKind Corporation. S.K. Garg: Research Support; Self; Dexcom, Inc., Eli Lilly and Company, Sanofi US. Advisory Panel; Self; Sanofi US. Research Support; Self; MannKind Corporation, Diasome Pharmaceuticals, Inc., Labstyle Innovations, Lexicon Pharmaceuticals, Inc., Medtronic. Advisory Panel; Self; Novo Nordisk A/S.

Coronary artery calcium (CAC), a marker of subclinical atherosclerosis, predicts coronary artery disease (CAD) events, but the best use of CAC in risk prediction remains unclear. We examined whether group-based trajectory modeling of CAC in the Coronary Artery Calcification in Type 1 Diabetes (CACTI) study could independently predict CAD events. Four CAC trajectory groups (Figure 1a) were identified using longitudinal CAC in people free from CAD (Proc TRAJ in SAS Version 9.4), and these groups were used to predict a subsequent CAD event (myocardial infarction or coronary revascularization) using survival analysis. People with type 1 diabetes (T1D) were more likely to be in higher CAC trajectory groups than those without diabetes (non-DM, p Disclosure J.K. Snell-Bergeon: Stock/Shareholder; Self; Abbott. Research Support; Self; Roche Diagnostics Corporation. A. Keshawarz: None. G.L. Kinney: None. I.E. Schauer: None. V.N. Shah: None. L. Pyle: None.

Background: Intake of sufficient dietary fiber has been recommended for glucose control, and typically low fiber intake is observed in the general population. The role of fiber in glycemic control in reported literature is inconsistent and few reports are available in populations with type 1 diabetes (T1D). Methods: We conducted a cross-sectional analysis of data from the CACTI study [n=1257; T1D: n=568; nondiabetic controls: n=689] collected between March 2000 and April 2002. Participants completed a validated food frequency questionnaire, a physical examination and fasting biochemical analyses (12h fast) at screening visit. We used linear regression models to examine associations of total dietary fiber with HbA1c as a continuous variable. Models were stratified by diabetes status, and adjusted for age, sex and total calories, and diabetes duration in the T1D group. We also examined correlations of fiber with HbA1c. Results: Baseline dietary fiber intake and HbA1c in the T1D group were 16g [median (IQ): 11-22g) and 7.9±1.3% mean (SD), respectively, and in the nondiabetic controls were 15g [median (IQ): 11-21g) and 5.4±0.4%, respectively. Pearson partial correlation coefficients revealed a significant but weak inverse association of total dietary fiber with HbA1c when adjusted for age, sex, diabetes status and total calories (r= -0.07, p=0.01). In adjusted linear regression models, total dietary fiber was significantly and inversely associated with HbA1c in the T1D group [estimate (beta±SE)= -0.32±0.15, p=0.034], as well as in the nondiabetic controls [-0.10±0.04, p=0.009]. Thus, at observed levels of intake, total dietary fiber reveals a protective association against poor glycemic control in T1D adults and in nondiabetic controls. Disclosure A. Basu: None. A.C. Alman: None. J.K. Snell-Bergeon: Stock/Shareholder; Self; Abbott. Research Support; Self; Roche Diagnostics Corporation.

Type 1 diabetes (T1D) and menopause are associated with higher risk of coronary artery calcium (CAC). Accumulation of pericardial adipose tissue (PAT), a pro-inflammatory visceral fat higher in post-menopausal women and associated with increased CAC, may be a mechanism by which T1D is associated with higher CAC risk. We examined the effect of PAT on the relationship between T1D and CAC in women over time. PAT and CAC volume data were collected from CT heart scans over 4 study visits from 725 women enrolled in the Coronary Artery Calcification in Type 1 Diabetes (CACTI) study (mean baseline age ± SD, 37 ± 9 years). We used repeated measures modeling to examine changes in square root-transformed CAC volume over time by T1D, menopausal status, and quartile of PAT volume after adjusting for age, central obesity, and study visit. PAT levels did not differ by T1D status (33.5 vs. 33.7, p=0.8), but there was a significant interaction between PAT, menopause, and T1D (p=0.02) in relation to CAC volume (Figure 1). In T1D women, higher PAT was associated with higher CAC volume regardless of menopause status, but the effect was greater in post-menopausal women. There was no difference in CAC in nondiabetic (non-DM) women across PAT quartiles or by menopause status. CAC was higher in T1D than non-DM women regardless of menopause status and PAT quartile. PAT has a greater effect on CAC in women with T1D than non-DM women, despite similar PAT volumes. Disclosure A. Keshawarz: None. L. Pyle: None. A.C. Alman: None. C. Sassano: None. E. Westfeldt: None. R.M. Sippl: None. J.K. Snell-Bergeon: Stock/Shareholder; Self; Abbott. Research Support; Self; Roche Diagnostics Corporation.

Coronary artery disease (CAD) prevalence is increased and life expectancy is reduced by more than a decade in people with type 1 diabetes (T1D) compared to nondiabetics (non-DM), but traditional risk factors do not explain all of the increased risk. We examined whether three novel risk markers, high-sensitive cardiac troponin T (hs-cTnT), N-terminal pro-B-type natriuretic peptide (NT-proBNP), and growth differentiation factor 15 (GDF-15), are elevated in T1D and predict CAD and mortality. 1,416 adults age 19-56 (652 T1D, 754 non-DM) were enrolled in the Coronary Artery Calcification in type 1 diabetes (CACTI) study from 2000-2002. We assessed CAD events (fatal or non-fatal myocardial infarction, coronary artery bypass graft, or angioplasty) with annual follow-up questionnaires. In-person visits occurred at 3, 6, and 12 years after baseline. Serum samples from the visit prior to a CAD event or death or from the last in-person visit were available for 1,389 participants and were assayed for hs-cTnT, NT-proBNP, and GDF-15 at the University of Maryland. Elevated marker levels were defined as those above the 95th percentile among non-DM participants. Biomarker levels were compared by T1D status in linear regression, and logistic regression was used to examine associations with CAD and all-cause mortality. Age- and sex-adjusted LSmeans ± SE for log hs-cTnT (2.0±0.02 vs. 1.6±0.02, p A panel of novel markers, hs-cTnT, NT-proBNP, and GDF-15, are elevated in T1D and may help identify those at risk for CAD events and mortality. Disclosure A. Keshawarz: None. R.M. Sippl: None. H. Rebuck: None. S. Donald: None. S.Y. Huang: None. R.H. Christenson: Consultant; Self; Roche Diagnostics Corporation, Siemens, Becton, Dickinson and Company. J.K. Snell-Bergeon: Stock/Shareholder; Self; Abbott. Research Support; Self; Roche Diagnostics Corporation.

Introduction: Standard lipid panel measures (e.g., low HDL cholesterol and high triglyceride levels) are associated with developing diabetes. Lipoprotein and metabolomics profiles measured by nuclear magnetic resonance (NMR) carry additional information and may add to knowledge of future diabetes risk. Hypothesis: We assessed the hypothesis that two multimarkers of insulin resistance derived from NMR LipoProfile ® analysis, LP-IR (lipoprotein insulin resistance index) and IRDRF (insulin resistance diabetes risk factor index), are associated with incident diabetes independent of traditional risk factors in non-diabetic, apparently healthy subjects. Methods: LP-IR and IRDRF were measured at LipoScience/LabCorp for 3,564 non-diabetic participants (mean age 32±4 years, 46% [n=1,646] male) in the Coronary Artery Risk Development in Young Adults (CARDIA) study. LP-IR was calculated from 6 lipoprotein subclass and size parameters. IRDRF was calculated by combining LP-IR with levels of branched-chain amino acids, the inflammatory marker GlycA, and 2 additional lipoprotein subclasses. Diabetes status was ascertained by fasting glucose levels, hemoglobin A1c, and diabetes medications. We used Cox proportional hazards to model the relationship between LP-IR and IRDRF with incident diabetes. Participants were followed for a mean time of 21±5 years. We considered 4 models that examined LP-IR and IRDRF both as continuous and categorical variables and adjusted for various traditional predictors of diabetes. Results: Model 3, which adjusted for components of metabolic syndrome, had the best model fit in all cases ( Table 1 ). LP-IR and IRDRF had a significant linear relationship with incident diabetes. Participants who had LP-IR and IRDRF scores in Q4 were significantly more likely to develop diabetes than those with scores in Q1. Conclusions: In conclusion, LP-IR and IRDRF can be derived from a clinically-available NMR LipoProfile test, and both were associated with incident diabetes independent of traditional predictors.

People with type 1 diabetes mellitus manifest a greater burden of both periodontal disease and coronary artery disease (CAD); however, little is known about their interrelation. Coronary artery calcium (CAC) measures subclinical atherosclerosis and predicts major adverse coronary events. The relation between periodontal disease and CAC progression in individuals with type 1 diabetes has not been previously described. We determined the prevalence and progression of CAC in relation to self-reported periodontal disease. Multivariate logistic and tobit regression models were used to examine the relation between periodontal disease duration and CAC progression and whether this relation differs by diabetes status after controlling for age, gender, total and high-density lipoprotein cholesterol, hypertension, smoking, body mass index (BMI), duration of diabetes, and baseline CAC. A total of 473 patients with type 1 diabetes and 548 without diabetes were followed for a mean of 6.1 years. At baseline, the prevalence and duration of periodontal disease did not differ between subjects with and without diabetes (14.5% vs 13.4%, p = 0.60; 6 vs 9 years, p = 0.18). Duration of periodontal disease was not significantly associated with baseline CAC prevalence. In patients with type 1 diabetes, periodontal disease duration was significantly related to CAC progression (p = 0.004) but not in subjects without diabetes (p = 0.63). In conclusion, this study suggests that periodontal disease is an independent predictor of long-term progression of CAC in patients with type 1 diabetes.

Aims To conduct a systematic review and meta-analysis of observational studies in order to assess the association between Type 1 diabetes and fractures. Background The risk of fracture in men and women with Type 1 diabetes has not been studied in a large prospective well designed cohort. Methods Data were selected from Medline and Embase and abstracts from annual scientific meetings of various diabetes and bone and mineral societies. Published studies that reported the fracture risk in people with Type 1 diabetes in comparison with people without diabetes between 1990 and July 2014 and abstracts from various annual meeting (2005 onwards) were included in the present meta-analysis. Data were extracted from the text of included publications or from abstracts of conferences. Results The 14 studies that met the inclusion criteria reported 2066 fracture events among 27 300 people with Type 1 diabetes (7.6%) and 136 579 fracture events among 4 364 125 people without diabetes (3.1%). The pooled relative risk of any fracture in people with Type 1 diabetes was 3.16 (95% CI 1.51–6.63; P = 0.002). Women and men with Type 1 diabetes had a four and two times higher risk of any fractures, respectively, compared with people without diabetes. The pooled relative risks of hip fractures and spinal fractures were 3.78 (95% CI 2.05–6.98; P

BACKGROUND Rapid glomerular filtration rate (GFR) decline (>3 mL/min/1.73 m(2)) is an increasingly recognized high-risk diabetic nephropathy (DN) phenotype in Type 1 diabetes. Rapid GFR decline is a recognized predictor of impaired GFR (

Haptoglobin (Hp) genotype 2-2 increases cardiovascular diabetes complications. In type 2 diabetes, α-tocopherol was shown to lower cardiovascular risk in Hp 2-2, potentially through HDL function improvements. Similar type 1 diabetes data are lacking. We conducted a randomized crossover pilot of α-tocopherol supplementation on HDL function [i.e., cholesterol efflux (CE) and HDL-associated lipid peroxides (LP)] and lipoprotein subfractions in type 1 diabetes. Hp genotype was assessed in members of two Allegheny County, PA, type 1 diabetes registries and the CACTI cohort; 30 were randomly selected within Hp genotype, and 28 Hp 1-1, 31 Hp 2-1 and 30 Hp 2-2 were allocated to daily α-tocopherol or placebo for 8 weeks with a 4-week washout. Baseline CE decreased with the number of Hp 2 alleles (p-trend = 0.003). There were no differences in LP or lipoprotein subfractions. In intention-to-treat analysis stratified by Hp, α-tocopherol increased CE in Hp 2-2 (β = 0.79, p = 0.03) and LP in Hp 1 allele carriers (β Hp 1-1 = 0.18, p = 0.05; β Hp 2-1 = 0.21, p = 0.07); reduced HDL particle size (β = −0.07, p = 0.03) in Hp 1-1 carriers; increased LDL particle concentration in Hp 1-1; and decreased it in Hp 2-2 carriers. However, no significant interactions were observed by Hp. In this type 1 diabetes study, HDL function worsened with the number of Hp 2 alleles. α-Tocopherol improved HDL function in Hp 2-2 carriers and appeared to adversely affect lipid peroxides and lipoprotein subfractions among Hp 1 allele carriers. As no significant interactions were observed, findings require replication in larger studies.

Objective Most youth with type 1 diabetes do not meet the American Diabetes Association (ADA) and International Society for Pediatric and Adolescent Diabetes (ISPAD) targets for hemoglobin A1c (HbA1c), blood pressure (BP), lipids, and body mass index (BMI). We hypothesized that ISPAD/ADA goal achievement at baseline would be associated with cardiorenal risk factors at baseline and 2 yr follow-up in adolescents with type 1 diabetes. Methods We assessed the cross-sectional and longitudinal relationships between ISPAD/ADA goal achievement at baseline and cardiorenal health at baseline and 2-yr follow-up (n = 297; 15.4 ± 2.1 yr at baseline) in adolescents with type 1 diabetes. Goal achievement was defined as HbA1c 35 mg/dL, triglycerides (TG)

Background Coronary artery disease and diabetic nephropathy, which are thought to share pathogenic mechanisms, remain the most common causes of mortality in type 1 diabetes (T1D). Data from basic and clinical studies indicate that hypertriglyceridemia plays an important role in the pathogenesis of vascular complications, but the role of triglycerides (TG) in the normal range remains unresolved in T1D. Objective We hypothesized that fasting TG would independently predict cardiorenal disease in adults with T1D and normal-to-low levels of TG. Methods Subjects (N = 652) were 19 to 56 years old at baseline and reexamined 6 years later. Urinary albumin excretion was measured, and categorized as microalbuminuria or greater. Progression of coronary artery calcification (CACp), measured using electron beam computed tomography, was defined as a change in the square root transformed CAC volume ≥2.5. The association of low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), apolipoprotein B, non–HDL-C, natural log triglyceride (lnTG), ln(TG/HDL-C) ratio with CACp and incident albuminuria were examined in logistic regression. The models were adjusted for age, sex, T1D duration, hemoglobin A1c, systolic blood pressure, diastolic blood pressure, blood pressure medications, statins, and smoking status. Integrated discrimination index and net reclassification improvement were used to examine prediction performance. Results Incident albuminuria was independently associated with CACp. lnTG independently predicted both incident albuminuria (odds ratio: 1.53, 1.02–2.30, P = .04) and CACp (1.41, 1.11–1.80, P = .006). The addition of lnTG to ABC risk factors (HbA1c, systolic blood pressure, diastolic blood pressure, and LDL-C) moderately improved discrimination and reclassification of CACp and incident albuminuria. Conclusion In adults with T1D, fasting TG independently predicted cardiorenal disease over 6 years and improved reclassification of risk by conventional risk factors.

Objective To test the hypothesis that multitissue deficits in insulin sensitivity are greater among women than men with type 1 diabetes compared to respective controls. Research design and methods Three-stage hyperinsulinemic-euglycemic clamps (4, 8, 40 mU/m 2 /min) were performed on 41 people with type 1 diabetes and 47 adults without diabetes (mean ± SD age 46 ± 8). Infusions of [1- 13 C]palmitate, [1,1,2,3,3- 2 H 2 ]glycerol, and [6,6- 2 H 2 ]glucose isotope tracers were used to determine free fatty acid (FFA), glycerol, and glucose kinetics in 52 of these participants (25 M and 27 W). Results There was no difference in age or BMI by type 1 diabetes status in either sex. Free fatty acid rate of appearance (FFA Ra) was higher in both sexes with type 1 diabetes compared to those without diabetes during stages 1 and 2. The same was seen with glycerol for stages 1 and 2. During stage 3 glucose rate of disappearance (Rd) was lower in those with type 1 diabetes among both sexes. All had sex by type 1 diabetes interactions with greater deficits in insulin sensitivity in women. While there was no sex by diabetes interaction in regards to glucose rate of appearance (Ra), those with type 1 diabetes had a higher glucose Ra than those without diabetes. Conclusions We found that type 1 diabetes affected adipose and skeletal muscle insulin sensitivity to a greater extent in women than in men, perhaps contributing to the greater relative increase in cardiovascular risk in women with type 1 diabetes.

Objectives Copeptin, a surrogate marker for vasopressin, is elevated in participants with insulin resistance (IR) and type 2 diabetes. Whereas adults with type 1 diabetes also demonstrate elevated copeptin concentrations and IR compared to controls without diabetes, the relationship between copeptin and IR in type 1 diabetes is unclear. Methods Participants with (n=209) and without (n=244) type 1 diabetes in the Coronary Artery Calcification in Type 1 Diabetes (CACTI) study were assessed for serum copeptin, vitals, estimated glomerular filtration rate, urinary albumin-to-creatinine ratio, glycated hemoglobin and lipid panels. Estimated insulin sensitivity (eIS) was calculated by validated equations in participants with and without type 1 diabetes. The relationships among copeptin, IR, waist circumference (WC) and body mass index (BMI) were examined with unadjusted and adjusted linear regression models. Results Copeptin was correlated with eIS (R=–0.17, R2=0.029), WC (R=0.16, R2=0.026) and BMI (R=0.22, R2=0.048) for type 1 diabetes and with eIS (R=–0.37, R2=0.14), WC (R=0.40, R2=0.16) and BMI (R=0.25, R2=0.063) in non-type 1 diabetes. In multivariable analysis, copeptin correlated with total cholesterol (beta±SE: −0.12±0.04, p=0.008) and low-density lipoprotein (beta±SE: −0.11±0.04, p=0.01) in type 1 diabetes. In non-type 1 diabetes, copeptin was associated with WC (beta±SE: 0.14±0.04, p=0.0024), BMI (beta±SE: 0.13±0.04, p=0.007) and eIS (beta±SE: −0.14±0.04, p=0.0013). Conclusions Copeptin does not correlate with markers of IR in type 1 diabetes but strongly correlates in non-type 1 diabetes. Thus, elevated vasopressin activity and IR appear to be independent risk factors for vascular complications in type 1 diabetes.

BACKGROUND. Accumulation of diacylglycerol (DAG) and sphingolipids is thought to promote skeletal muscle insulin resistance by altering cellular signaling specific to their location. However,the subcellular localization of bioactive lipids in human skeletal muscle is largely unknown. METHODS. We evaluated subcellular localization of skeletal muscle DAGs and sphingolipids in lean individuals (n = 15), endurance-trained athletes (n = 16), and obese men and women with (n = 12) and without type 2 diabetes (n = 15). Muscle biopsies were fractionated into sarcolemmal, cytosolic, mitochondrial/ER, and nuclear compartments. Lipids were measured using liquid chromatography tandem mass spectrometry, and insulin sensitivity was measured using hyperinsulinemic-euglycemic clamp. RESULTS. Sarcolemmal 1,2-DAGs were not significantly related to insulin sensitivity. Sarcolemmal ceramides were inversely related to insulin sensitivity, with a significant relationship found for the C18:0 species. Sarcolemmal sphingomyelins were also inversely related to insulin sensitivity, with the strongest relationships found for the C18:1, C18:0, and C18:2 species. In the mitochondrial/ER and nuclear fractions, 1,2-DAGs were positively related to, while ceramides were inversely related to, insulin sensitivity. Cytosolic lipids as well as 1,3-DAG, dihydroceramides, and glucosylceramides in any compartment were not related to insulin sensitivity. All sphingolipids but only specific DAGs administered to isolated mitochondria decreased mitochondrial state 3 respiration. CONCLUSION. These data reveal previously unknown differences in subcellular localization of skeletal muscle DAGs and sphingolipids that relate to whole-body insulin sensitivity and mitochondrial function in humans. These data suggest that whole-cell concentrations of lipids obscure meaningful differences in compartmentalization and suggest that subcellular localization of lipids should be considered when developing therapeutic interventions to treat insulin resistance. FUNDING. National Institutes of Health General Clinical Research Center (RR-00036), National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) (R01DK089170), NIDDK (T32 DK07658), and Colorado Nutrition Obesity Research Center (P30DK048520).

Background Diabetic nephropathy (DN) is one of the major late complications of diabetes. Treatment aimed at slowing down the progression of DN is available but methods for early and definitive detection of DN progression are currently lacking. The ‘Proteomic prediction and Renin angiotensin aldosterone system Inhibition prevention Of early diabetic nephRopathy In TYpe 2 diabetic patients with normoalbuminuria trial' (PRIORITY) aims to evaluate the early detection of DN in patients with type 2 diabetes (T2D) using a urinary proteome-based classifier (CKD273). Methods In this ancillary study of the recently initiated PRIORITY trial we aimed to validate for the first time the CKD273 classifier in a multicentre (9 different institutions providing samples from 165 T2D patients) prospective setting. In addition we also investigated the influence of sample containers, age and gender on the CKD273 classifier. Results We observed a high consistency of the CKD273 classification scores across the different centres with areas under the curves ranging from 0.95 to 1.00. The classifier was independent of age (range tested 16-89 years) and gender. Furthermore, the use of different urine storage containers did not affect the classification scores. Analysis of the distribution of the individual peptides of the classifier over the nine different centres showed that fragments of blood-derived and extracellular matrix proteins were the most consistently found. Conclusion We provide for the first time validation of this urinary proteome-based classifier in a multicentre prospective setting and show the suitability of the CKD273 classifier to be used in the PRIORITY trial

AIM Diabetic kidney disease is one of the leading complications of Type 1 diabetes, but its prediction remains a challenge. We examined predictors of rapid decline in estimated GFR (eGFR) in two Type 1 diabetes cohorts: the Coronary Artery Calcification in Type 1 Diabetes (CACTI) and the Pittsburgh Epidemiology of Diabetes Complications (EDC). METHODS A select subset of participants (CACTI: n = 210 and EDC: n = 98) diagnosed before 17 years of age with Type 1 diabetes duration ≥ 7 years, and follow-up data on eGFR by CKD-EPI creatinine for up to 8 years were included in the analyses. Early renal function decline was defined as annual decline in eGFR ≥ 3 ml/min/1.73 m2 , and normal age-related decline as eGFR ≤ 1 ml/min/1.73 m2 . Parallel logistic regression models were constructed in the two cohorts. RESULTS Early renal function decline incidence was 36% in CACTI and 41% in EDC. In both cohorts, greater baseline eGFR (CACTI: OR 3.12, 95% CI 1.97-5.05; EDC: OR 1.92, 95% CI 1.17-3.15 per 10 ml/min/1.73 m2 ) and log albumin-to-creatinine (ACR) (CACTI: OR 3.24, 95% CI 1.80-5.83; EDC: OR 1.87, 95% CI 1.18-2.96 per 1 unit) predicted greater odds of early renal function decline in fully adjusted models. Conversely, ACE inhibition predicted lower odds of early renal function decline in women in CACTI, but similar relationships were not observed in women in EDC. CONCLUSIONS A substantial proportion of people with Type 1 diabetes in the EDC and CACTI cohorts experienced early renal function decline over time. ACE inhibition appeared to be protective only in women in CACTI where the prevalence of its use was twofold higher compared with the EDC.

BACKGROUND: The objective of the study was to determine whether plasma biomarkers of kidney injury improve the prediction of diabetic kidney disease (DKD) in adults with type 1 diabetes (T1D) over a period of 12 years. METHODS: Participants (n = 527, 53% females) in the Coronary Artery Calcification in T1D (CACTI) Study were examined during 2002–04, at a mean (± standard deviation) age of 39.6 ± 9.0 years with 24.8 years as the median duration of diabetes. Urine albumin-to-creatinine (ACR) and estimated glomerular filtration rate (eGFR) by CKD-EPI (chronic kidney disease epidemiology collaboration) creatinine were measured at the baseline and after mean follow-up of 12.1 ± 1.5 years. Albuminuria was defined as ACR ≥30 mg/g and impaired GFR as eGFR

We performed a meta-analysis to evaluate the femoral neck and lumbar spine bone mineral density (BMD) in adults with type 1 diabetes (T1D) compared with controls. Adults with T1D have modestly lower BMD at femoral neck and lumbar spine than adults without diabetes. Fracture risk is four to sixfold higher in adults with T1D. Since BMD is one of the major contributors for fracture risk, we performed a meta-analysis to evaluate differences in femoral neck and lumbar spine BMD between adults with T1D and controls. MEDLINE, Ovid, and the Cochrane library and abstracts from various scientific meetings were searched. Studies reporting the femoral neck and/or lumbar spine BMD in adults (age > 20 years) with T1D in comparison with people without diabetes were selected. General linear mixed models were used to assess differences in BMD at femoral neck and lumbar spine between subjects with T1D and controls adjusting for age, sex, and dual x-ray absorptiometry (DXA) instruments. Sixteen studies met the inclusion criteria. The femoral neck BMD was modestly lower in adults with T1D compared to controls (−0.055 g/cm2; 95% CI: −0.065, −0.045). There were no differences in lumbar spine BMD between adults with T1D and controls (0.0062 g/cm2; 95% CI −0.04, 0.016). However, in a sensitivity analysis, lumbar spine BMD was modestly lower in adults with T1D compared to controls (−0.035 g/cm2; −0.049, −0.02). Studies using Lunar DXA instruments have reported higher lumbar spine and femoral neck BMD compared to studies using Hologic DXA instruments. Femoral neck and lumbar spine BMD were modestly lower in adults with T1D compared to controls. However, this modest reduction in femoral neck and lumbar spine BMD cannot explain much higher observed fracture risk in adults with T1D.

Aims To investigate changes in retinal vessel diameter during acute hyperglycemia in patients with type 1 diabetes. Methods We conducted a study on 11 subjects with type 1 diabetes. Euglycemia was maintained for 3 h followed by induction of hyperglycemia and simultaneous bolus of rapid acting insulin. Two fundus photos were captured during euglycemia and five fundus photos, blood glucose and blood pressure were taken every 30 min for 2.5 h post-prandial. Central retinal artery equivalent (CRAE) and central retinal vein equivalent (CRVE) were measured over the study visit and examined using generalized linear mixed models. Results In a multivariate mixed model, mean CRAE and CRVE were reduced at 90 min post-prandial in both zones B and C. In repeated measures analysis, arterioles exhibited a significant association with change in vessel caliber per change in blood glucose. Inconsistent effects of blood pressure on vessel diameter were also measured. Conclusions We document a change in retinal vessel diameter during acute hyperglycemia in persons with type 1 diabetes. Larger controlled studies are required to further investigate this phenomenon and to more accurately assess if hyperglycemia has direct effects on retinal vessel diameter.

Epidemiologic evidence supports a link between serum uric acid (SUA) and vascular complications in diabetes, but it remains unclear whether SUA improves the ability of conventional risk factor to predict complications. We hypothesized that SUA at baseline would independently predict the development of vascular complications over 6 years and that the addition of SUA to American Diabetes Association’s ABC risk factors (HbA1c, BP, LDL-C) would improve vascular complication prediction over 6 years in adults with type 1 diabetes. Study participants (N = 652) were 19–56 year old at baseline and re-examined 6 years later. Diabetic nephropathy was defined as incident albuminuria or rapid GFR decline (>3.3 %/year) estimated by the CKD-EPI cystatin C. Diabetic retinopathy (DR) was based on self-reported history, and proliferative diabetic retinopathy (PDR) was defined as laser eye therapy; coronary artery calcium (CAC) was measured using electron-beam computed tomography. Progression of CAC (CACp) was defined as a change in the square-root-transformed CAC volume ≥2.5. Predictors of each complication were examined in stepwise logistic regression with subjects with complications at baseline excluded from analyses. C-statistics, integrated discrimination indices and net-reclassification improvement were utilized for prediction performance analyses. SUA independently predicted development of incident albuminuria (OR 1.8, 95 % CI 1.2–2.7), rapid GFR decline (1.9, 1.1–3.3), DR (1.4, 1.1–1.9), PDR (2.1, 1.4–3.0) and CACp (1.5, 1.1–1.9). SUA improved the discrimination and net-classification risk of vascular complications over 6 years. SUA independently predicted the development of vascular complications in type 1 diabetes and also improved the reclassification of vascular complications.

Adults with type 1 diabetes have lower serum uric acid levels compared with nondiabetic adults. Little is known about the relationship between serum uric acid and blood pressure in type 1 diabetes and whether it differs from the positive relationship found in nondiabetic adults. The authors assessed the cross-sectional and longitudinal relationships over 6 years between serum uric acid and blood pressure in adults with (35±9 years [n=393]) and without (38±9 years [n=685]) type 1 diabetes in the Coronary Artery Calcification in Type 1 Diabetes study. In nondiabetic adults, serum uric acid was associated with systolic blood pressure in multivariable models adjusted for cardiovascular risk factors. In adults with type 1 diabetes, a negative association was observed between serum uric acid and systolic blood pressure after multivariable adjustments. A positive association was observed between serum uric acid and systolic blood pressure in nondiabetic adults. In contrast, an inverse relationship was demonstrated after multivariable adjustments in type 1 diabetes.

OBJECTIVE In 2010, the American Heart Association defined seven metrics (smoking, BMI, physical activity, diet, total cholesterol, blood pressure, and fasting plasma glucose) for ideal cardiovascular health (ICH). Subsequent studies have shown that the prevalence of achieving these metrics is very low in the general population. Adults with type 1 diabetes are at increased risk of cardiovascular disease (CVD), but no studies to date have been published on the prevalence of ICH in this population. RESEARCH DESIGN AND METHODS Data for this analysis were collected as part of the prospective Coronary Artery Calcification in Type 1 Diabetes study. This analysis involved 546 subjects with type 1 diabetes and 631 subjects without diabetes who had complete information for calculating the ICH metrics. RESULTS Overall, the prevalence of ICH was low in this population, with none meeting the ideal criteria for all seven metrics. The prevalence of ideal physical activity (10.0%) and diet (1.1%) were particularly low. ICH was significantly associated with both decreased prevalence (odds ratio [OR] 0.70; 95% CI 0.62–0.80) and progression (OR 0.77; 95% CI 0.66–0.90) of coronary artery calcification (CAC). CONCLUSIONS ICH is significantly associated with decreased prevalence and progression of CAC; however, prevalence of ICH metrics was low in adults both with and without type 1 diabetes. Efforts to increase the prevalence of ICH could have a significant impact on reducing the burden of CVD.