bluuebunny/crossref_metadata_2025_split huggingface dataset:
343-OR: HOMA2ß Stratifies Risk for Type 1 Diabetes (T1D) Development among TrialNet Pathway to Prevention Participants
Authors: FELTON JAMIE L. , LOHANO KULDEEP , MEAH FARAH , SOSENKO JAY , EVANS-MOLINA CARMELLA 
Published: June 2020

Identification of individuals at high risk for T1D is essential for the successful implementation of disease modifying interventions. Progression to T1D can be predicted by stimulated measures of β cell function, including oral glucose tolerance tests and hyperglycemic clamp studies. However, these assays are both time consuming and invasive. The homeostasis model assessment (HOMA2β) is a validated mathematical tool commonly used in type 2 diabetes cohorts to assess β cell function using fasting glucose and insulin measurements from a single time point. The utility of HOMA2β in predicting T1D progression has not been tested. To this end, HOMA2β at study entry was assessed in nondiabetic relatives of individuals with T1D who were positive for one or more β cell autoantibodies (aab) and followed longitudinally in the TrialNet Pathway to Prevention cohort. A total of 6598 subjects (mean age 17.2 ± 12.8 yrs) were screened and monitored for T1D. Of these, 40.2% (n=2652) were single aab+ (mean age 21.1 ± 14.0 yrs) and 57.5% (n=3794) were multiple aab+ (mean age 14.5 ± 11.2 yrs). During follow-up, 117 single and 1020 multiple aab+ individuals progressed to T1D. Kaplan-Meier survivor estimates by HOMA2β tertiles demonstrated that risk of T1D was inversely related to HOMA2β tertiles for multiple aab+ subjects. Multivariate Cox proportional hazards analysis was performed for the lowest tertile using the highest HOMA2β tertile as the reference group. After adjustments for age, sex, HLA, and BMI, T1D HRs were significant for the lowest HOMA2β tertile in single (HR 1.91, 95% CI 1.12, 3.24, p = 0.017), multiple (HR 2.43, 95% CI 2.03, 2.91, p&lt;0.001), and combined single and multiple aab+ cohorts (HR 2.36, 95% CI 1.99, 2.79, p&lt;0.001). Overall, low HOMA2β levels were able to identify a high-risk subgroup of PTP participants, suggesting that HOMA2β may have utility as a single time point measurement in stratifying individuals with established autoimmunity who are at increased risk of T1D development.

Disclosure
J.L. Felton: None. K. Lohano: None. F. Meah: None. J. Sosenko: None. C. Evans-Molina: Consultant; Self; Bristol-Myers Squibb.

Funding
National Institute of Diabetes and Digestive and Kidney Diseases (U01107014)
346-OR: In Young People with T1D, Additional Mealtime Insulin Produces a Dose-Dependent Improvement in Glycemia after a High-Fat, High-Protein Meal
Authors: SMITH TENELE A. , SMART CARMEL E. , FUERY MICHELLE E. , KNIGHT BRIGID , HOWLEY PETER , KING BRUCE R. 
Published: June 2020

Background: To manage hyperglycemia following high fat and protein (HFHP) meals, T1D guidelines recommend additional mealtime insulin. However, guidance regarding dosing adjustments for HFHP meals is unclear.
Aim: To determine the amount of additional insulin required for a HFHP meal to optimise 6 h postprandial glucose, in young people with T1D using insulin pumps.
Method: This was a 4x4 crossover trial conducted at 2 centers in Australia. On 4 days, participants (n=27) with mean age 14.5 ± 3.6 yrs and HbA1c 53 mmol/mol (7.0 ± 0.7%) ate a HFHP meal [carbohydrate (CHO) 30g, fat 40g, protein 50g]. Insulin based on the CHO: insulin ratio (CIR) was given in random order: 100% (control), 120%, 140%, 160% CIR. Postprandial sensor glucose was measured for 6 h.
Results: Compared to 100% CIR, 140% and 160% CIR resulted in significantly lower mean glucose excursions from 90- 360 min (p≤ 0.018) and mean peak glucose excursions (4.0 and 2.7 v 6.0 mmol/L, p&lt; 0.001). Hypoglycemia for 100%- 160% CIR was 7.7%, 7.7%, 12.0% and 19.2% respectively (p≥ 0.139). With increasing insulin there was a dose-dependent reduction in mean glucose excursions from 60- 360 min (p&lt; 0.01).
Conclusions: Incremental addition of mealtime insulin for fat and protein produces a dose- dependent improvement in postprandial glycemia. For HFHP meals, 140% CIR is advised with titration based on individual glucose response.

Disclosure
T.A. Smith: None. C.E. Smart: None. M.E. Fuery: None. B. Knight: None. P. Howley: None. B.R. King: Other Relationship; Self; Menarini Group.

Funding
Australasian Paediatric Endocrine Group
362-OR: The Biological Variability of the BETA-2 Score in Islet Transplant Recipients
Authors: MILLOTT ROBYN , ORAM RICHARD A. , FORBES SHAREEN , SHAPIRO A.M. JAMES , SENIOR PETER A. , LAM ANNA 
Published: June 2020

Background: The BETA-2 score is a validated composite measure of beta cell function in islet transplantation. It is calculated from a fasting sample and lends itself to regular monitoring of islet graft function. To determine whether changes in the BETA-2 score are significant, it is important to understand inherent variability of the score. The aim of this study was to characterize the biological variability (coefficient of variation (CV)) of the BETA-2 score and to define the critical difference (CD) for the score which is the percentage change in score that reflects a significant change in islet function.
Methods: Islet transplant recipients with stable graft function were included in this retrospective study. BETA-2 score was calculated weekly over 8 consecutive weeks and the CV was calculated based on the root mean square method. The CD at the 95% confidence limit was calculated as follows: CD = 2.8 x CV.
Results: 21 transplant recipients were included of whom 6 were insulin dependent and 15 were insulin independent. These patients also varied in terms of kidney function: 10 subjects with eGFR ≥ 60 (76 ± 14 ml/min/1.73 m2) and 11 subjects with eGFR &lt; 60 (44 ± 10 ml/min/1.73 m2). The CV for all patients was 9.3%, 95% CI [8.7, 10.0]. The CV was similar between insulin independent and insulin dependent subjects (9.0%, 95% CI [8.1, 9.9] vs. 10.2, 95% CI [9.3, 11.1], p=0.5), as well as between subjects with eGFR &gt; 60 vs. eGFR &lt; 60 (8.9%, 95% [8.1,9.8] vs. 9.7%, 95% CI [8.7,10.7], p=0.6). The critical difference for the BETA-2 score was 26.2% for all subjects, 25.1% for insulin independent subjects, 28.5% for insulin dependent subjects, 24.9% for those with eGFR&gt;60, and 27.9% for those with GFR &lt;60.
Conclusions: The biological variability of the BETA-2 score appears stable across various clinical scenarios and a minimum difference of 26% between scores appears to constitute a significant change in BETA-2 score. Further analysis including more subjects and a greater range of kidney function is warranted.

Disclosure
R. Millott: None. R.A. Oram: None. S. Forbes: None. A. Shapiro: Consultant; Self; Viacyte, Inc. P.A. Senior: None. A. Lam: None.
38-LB: One- to Six-Month Outcomes Forecasts for Diabetes and Related Conditions
Authors: WEXLER YDO , GOLDNER DAN , MERCHANT GINA , HIRSCH ASHLEY , HUDDLESTON BRIAN , DACHIS JEFF 
Published: June 2020

Background: Treatment goals for diabetes and related conditions including hypertension and prediabetes are defined as reductions in health metrics: blood glucose concentration (BG), blood pressure (BP) and weight. Accurately predicting these metrics enables the delivery of timely treatment and lifestyle recommendations, leading to improved outcomes. We used health and self-care data collected in the One Drop app to forecast changes in BG, BP and weight, one to six months in advance.
Method: Data from a sample of over 50,000 app users were used to train a suite of patent-pending supervised learning models, each for a different health metric (weight, BP or BG) and time horizon (1-2, 2-3, 3-4, or 4-6 months). People in the sample were not enrolled in One Drop programs focused on reducing weight or blood pressure. Data collected prior to 2019 were used for training; data from January 2019 through February 2020 were used for testing. Prediction root mean square error (RMSE) was compared to the RMSE that would result from assuming persistence (no change from current values). For each health metric, population subsets were identified, based on information available at prediction time, for whom predictions were more accurate.
Results: The test set comprised over 200,000 predictions. Error reduction relative to persistence varied by metric, forecast horizon, and subset. For weight, persistence RMSE ranged from 2.2-5.4 kg; predictions reduced RMSE by 6.0-9.3%. For 30-day average systolic BP, persistence RMSE ranged from 11.3-16.1 mm Hg; predictions reduced RMSE by 14.2-20.0%. For 30-day average BG, persistence RMSE ranged from 19.4 to 58.8 mg/dL; predictions reduced RMSE by 12.6-40.5%.
Conclusion: Machine learning models based on app-collected health and self-care data can predict changes in BG, BP and weight up to six months in advance. These predictions can contribute to prioritizing interventions and guiding self-care, potentially improving outcomes.

Disclosure
Y. Wexler: Employee; Self; One Drop. D. Goldner: Employee; Self; One Drop. G. Merchant: Employee; Self; One Drop. A. Hirsch: Employee; Self; Informed Data Systems Inc. B. Huddleston: Employee; Self; One Drop. Stock/Shareholder; Self; One Drop. J. Dachis: Board Member; Self; One Drop. Employee; Self; One Drop. Stock/Shareholder; Self; One Drop.
395-P: N-hydroxyethyl-1-deoxynojirimycin (Miglitol) Restores the Sympathoadrenal Response to Hypoglycemia following Antecedent Hypoglycemia in Diabetic Rats
Authors: DONOVAN CASEY , JOKIAHO ANNE J. 
Published: June 2020

Antecedent hypoglycemia leads to a reduction in the sympathoadrenal response during subsequent hypoglycemia, i.e., HAAF. We’ve shown previously that this can be corrected in nondiabetic rats by portal vein infusion of N-hydroxyethyl-1-deoxynojirimycin (NEOH-DNJ; miglitol). In the current study we examined the efficacy of portal vein NEOH-DNJ infusion in restoring the sympathoadrenal response for diabetic animals.
Diabetes was induced in rats via streptozotocin (STZ) injection (65mg/kg) 4 weeks prior to experiments. Conscious, unrestrained STZ-diabetic rats underwent hyperinsulinemic-hypoglycemic clamps on two consecutive days with a glycemic nadir of 2.6 ± 0.04 mM. On Day 2 animals received portal vein miglitol infusions (1.45 μmol/kg/min) either upstream, (PORups) or liver adjacent (PORadj), while hypoglycemic controls (HYPO) received normal saline infusion. Serial plasma samples were assayed for glucose, insulin, epinephrine (EPI) and norepinephrine (NE).
On Day1 peak epinephrine (22.7 ± 2.1 nM) and norepinephrine (2.92 ± 0.3 nM) values were not significantly different between HYPO, PORups and PORadj (P&gt;0.38). On Day 2, EPI values for untreated HYPO controls were suppressed by 85% relative to Day 1 (P &lt; 0.0001). In contrast, EPI responses for miglitol infused groups, PORups (21.3 ± 2.2 nM) and PORadj (16.1 ± 2.01 nM) were not significantly different from Day 1 values (P = 0.75 and 0.50, respectively). NE demonstrated similar responses with HYPO suppressed by 63% on Day 2 (P&lt;0.05), while miglitol treated groups, PORups and PORadj, demonstrated Day 2 NE values not significantly different from Day 1 (P&gt;0.85).
Conclusion: The impaired sympathoadrenal response following antecedent hypoglycemia is restored in STZ-diabetic rats by miglitol (NEOH-DNJ) treatment during subsequent hypoglycemia. As with nondiabetic rats, STZ-diabetic animals demonstrated no differences between portal miglitol infusion sites.

Disclosure
C. Donovan: None. A.J. Jokiaho: None.

Funding
JDRF (3-SRA-2017-486-S-B)
402-P: Comparison of the Effects of Sodium–Glucose Cotransporter 2 Inhibitor and Thiazolidinedione Treatment on Risk of Stroke among Patients with Type 2 Diabetes
Authors: LEE SEUNG EUN , NAM HYEWON , CHOI HAN SEOK , KIM KYOUNG-AH 
Published: June 2020

Background: Influential guidelines recommend using SGLT2i preferentially among antidiabetic drugs in patients with diabetes and ASCVD. Although CVOTs with SGLT2i showed reduction in risk of 3-point major adverse cardiovascular events (MACE), they did not demonstrate beneficial effect on stroke. In addition, a meta-analysis reported adverse effect of SGLT2i for stroke. On the contrary, pioglitazone, a type of TZD, demonstrated the effect in secondary stroke prevention from two large RCTs. The aim of this study was to compare the effect of SGLT2i and TZD on the risk of stroke among patients with type 2 diabetes.
Methods: Using the Korean National Health Insurance Service data, we compared a 1:1 propensity score-matched cohort of patients who were new users of SGLT2i (n = 82,044) and TZD (n = 82,044) from January 2014 to December 2018. The primary outcome was stroke. The secondary outcomes were MI, CV death, and 3-point MACE.
Results: The incidence rates of stroke were 5.2 and 5.3 per 1000 person-years in SGLT2i-treated patients and TZD-treated patients, respectively. The hazard ratio of stroke was 0.955 (95% CI: 0.841-1.084) in SGLT2i-treated patients compared with TZD-treated patients. There was no clear difference in risk of MI (HR: 1.151, 95% CI: 0.914-1.449), CV death (HR: 0.865, 95% CI: 0.660-1.132), 3-point mace (HR: 0.988, 95% CI: 0.894-1.092) between two groups. Results were consistent regardless of prior CV disease.
Conclusions: In this real-world data, the risk of stroke was comparable in patients with type 2 diabetes treated with TZD vs. SGLT2i.

Disclosure
S. Lee: None. H. Nam: None. H. Choi: None. K. Kim: None.
425-P: Mechanisms Regulating VEGF Receptors in Diabetic Angiogenesis
Authors: BHATTACHARJEE SUDARSHAN , WU HAO , XU JIAN , CHEN HONG 
Published: June 2020

Diabetes-related vascular complications underlie a number of life-threatening conditions including cardiovascular disease, stroke, and peripheral limb ulcerations, the latter of which can lead to severe infections and a multitude of serious medical issues. Our goal is to understand how chronic hyperglycemia impairs endothelial cell function to identify molecular targets that would form the basis for new therapies to treat the peripheral vascular complications associated with diabetes. Since VEGFRs are critical regulators of both angiogenesis and lymphangiogenesis, we and others have shown that VEGFRs 2 and 3 were significantly reduced in the endothelium of diabetic patients and animals. We demonstrated that loss of the endocytic adaptor proteins epsin 1 and 2 in lymphatic endothelial cells (LECs) prevents VEGFR3 endocytosis and degradation, leading to enhanced lymphangiogenesis in vivo and cell proliferation, migration, and tube formation in vitro. Mechanistically, reactive oxygen species produced in diabetes induced c-Src–dependent VEGFR3 phosphorylation and degradation, and upregulated epsins through the AP-1 transcription factor. Epsins bind to and promote the degradation of newly-synthesized VEGFR3 in the Golgi, resulting in reduced availability of VEGFR3 at the cell surface. Here, we show that diabetic conditions induce expression of the autophagosome-specific gene Ulk1, which promotes VEGFR2/3 degradation. Hence, Ulk1 deficiency inhibits autophagosome formation and enhances angiogenic responses under diabetic conditions through upregulation of multiple endothelial-specific pathways that support neovascularization. Loss of endothelial Ulk1 elevated VEGFR2/3 levels and enhanced in vitro angiogenesis as measured by endothelial proliferation, migration, and tube formation and augmented wound healing in diabetes. Collectively, our results show that inhibition of epsins and Ulk1 in diabetes can restore angiogenic and lymphangiogenic responses and provide therapeutic targets.

Disclosure
S. Bhattacharjee: None. H. Wu: None. J. Xu: None. H. Chen: None.

Funding
National Institutes of Health (R01HAO130845)
426-P: Serum Cholesterol Earlier vs. Later in Life as a Predictor of CAD and Cardiovascular Mortality
Authors: LEIHERER ANDREAS , ULMER HANNO , MUENDLEIN AXEL , SAELY CHRISTOPH H. , VONBANK ALEXANDER , FRAUNBERGER PETER , FOEGER BERNHARD , BROZEK WOLFGANG , NAGEL GABRIELE , DREXEL HEINZ , CONCIN HANS 
Published: June 2020

We here aim at comparing the value of total cholesterol (TC) earlier versus later in life to predict CAD and cardiovascular mortality. In a cardiovascular observation study (CVOS) we performed coronary angiography and prospectively recorded cardiovascular events over up to 19 years in 1090 patients, of whom 288 had T2DM at baseline. These patients had participated in a health survey 15 years prior to the CVOS baseline. TC was measured both at the health survey and at the baseline of the CVOS. Patients in the highest versus the lowest TC ESC/EAS SCORE category at the health survey had an OR of 6.18 [3.35-11.38]; p=0.001) for significant CAD at angiography and a HR of 9.50 [1.30-69.19]; p=0.026) for cardiovascular death after multivariate adjustment including T2DM. In contrast, TC as measured at the baseline of the CVOS was neither significantly associated with CAD nor with cardiovascular death during follow-up. ESC-SCORES were more powerful in predicting cardiovascular death when using earlier instead of recent TC (Figure), with a net reclassification improvement of 0.250, p=0.02.We conclude that TC assessed earlier in life independently of the presence of T2DM is a better predictor of CAD and of cardiovascular mortality than TC assessed later in life.

Disclosure
A. Leiherer: None. H. Ulmer: None. A. Muendlein: None. C.H. Saely: None. A. Vonbank: None. P. Fraunberger: None. B. Foeger: None. W. Brozek: None. G. Nagel: None. H. Drexel: None. H. Concin: None.
43-LB: Glycemic Control Affects Heart-Rate Variability in Adults with Type 1 Diabetes
Authors: PARK MINSUN , CHU MINSEUNG , SONG YOUNGKWAN , SEVIL MERT , CINAR ALI , QUINN LAURIE T. , BRONAS ULF G. 
Published: June 2020

People with type 1 diabetes (T1D) have an increased risk for autonomic dysfunction and those with poorly controlled blood glucose levels have an increased risk for cardiovascular disease. The purpose of this study was to determine heart rate variability (HRV) and glucose variability (GV) parameters in less than optimally controlled patients (Group 2: A1C ≥ 7.0%, n = 6]) compared to well-controlled patients (Group 1: A1C ≤ 6.9% [n = 7]) during steady state treadmill exercise took and rest.
Methods: Thirteen T1D participants, (32.42 ± 10.46 years), performed steady state treadmill exercise (40% VO2Peak) for 30 minutes. Prior to exercise, participants rested for 30-minutes for determination of resting HRV and GV. Participants wore continuous glucose monitors and a Zephyr Bioharness™ to determine GV and HRV, respectively. Nonparametric, paired samples T-tests were conducted using SPSS 24.
Results: In group 2, there were significant differences between the resting period and treadmill exercise in the (1) root mean score of successive differences (RMSSD) (27.71 ± 13.43 vs. 8.01 ± 3.90; z = -2.201, respectively; p &lt;.05); (2) standard deviation of RR intervals (SDNN) (36.54 ± 16.04 vs. 11.68 ± 6.19; z = -2.201, respectively; p &lt;.05); and (3) the stress index (11.17 ± 5.48 vs. 23.07 ± 6.31; z = -2.201, respectively; p &lt;.05). However, during treadmill exercise, there were no significant differences in GV, compared to a resting period. In group 1, there were no significant differences in HRV, during treadmill exercise compared to the resting period. However, there were significant differences in GV (.26 ± .18 vs. .54 ± .38; z = -2.197, respectively; p &lt;.05)., between resting and exercise period.
Conclusion: This study suggests that during steady state aerobic exercise, people with poorer glucose control exhibit a pattern of metabolic inflexibility; however, HRV decreased with steady state exercise in both groups suggesting that exercise training may help to normalize HRV in patients with poorly controlled glucose levels.

Disclosure
M. Park: None. M. Chu: None. Y. Song: None. M. Sevil: None. A. Cinar: Research Support; Self; Dexcom, Inc., JDRF. Stock/Shareholder; Self; Dexcom, Inc., Eli Lilly and Company, Insulet Corporation, Medtronic, Novo Nordisk A/S, Tandem Diabetes Care. L.T. Quinn: None. U.G. Bronas: None.

Funding
JDRF
44-LB: Training Load and Time-in-Range Affect Sleep Time of Professional Cyclists with Type 1 Diabetes
Authors: SCOTT SAM N. , FONTANA FEDERICO Y. , MARTINEZ-GONZALEZ BORJA , HAYES CHARLOTTE A. , LAGROU PETER H. , MARCORA SAMUELE , ZUEGER THOMAS , STETTLER CHRISTOPH 
Published: June 2020

Background and Aims: People with type 1 diabetes (T1D) experience higher rates of sleep disturbances than those without diabetes, and this can have negative implications for glycemic control. Sleep is critical for optimal athletic performance and recovery so it is important to have an understanding of factors that can influence sleep in athletes with T1D. This study investigated whether there is a relationship between i) daily training load and ii) time in glycemic ranges on sleep time of professional cyclists with T1D.
Methods: Sixteen professional cyclists from Team Novo Nordisk (age 27 ± 4 y; HbA1c 6.8 ± 0.5%) used a wrist-worn actigraph device (Actiwatch Spectrum Plus, Philips Respironics, Murrysville, PA) to monitor sleep-wake activity over a 10-day training camp. Training variables (distance (km), elevation (m), work (kJ)) were used to determine a training stress score (TSS) for each day of the camp and glycemia was recorded using Dexcom, G6 (San Diego, CA). Summary statistics and correlations were run over the measured variables.
Results: On average, riders spent 8.6 ± 1 h in bed with a total sleep time of 7 ± 1.3 h (6.0 ÷ 7.8). The riders cycled 115 ± 26 km with 1849 ± 1086 m of elevation gain per day, corresponding to a mean TSS of 221 ± 142. Total sleep time was negatively associated with TSS (-0.29, p=0.01). Greater time in range (4-10 mmol/l) was positively associated with sleep time (r=0.21, p=0.03), with hyperglycemia, particularly level 2 (&gt;14 mmol/l), being negatively associated with sleep time (-0.21, p=0.03).
Conclusions: We provide preliminary evidence that a greater TSS is negatively associated with total sleep time in professional athletes with T1D. Second, greater time spent in euglycemia is associated with greater sleep time, with time above target having a negative association with sleep. Further data should be collected longitudinally to strengthen these results to serve as a basis to promote better sleep hygiene practices to overcome the effects of higher training loads.

Disclosure
S.N. Scott: None. F.Y. Fontana: None. B. Martinez-Gonzalez: None. C.A. Hayes: Other Relationship; Self; Novo Nordisk A/S. P.H. Lagrou: None. S. Marcora: None. T. Zueger: None. C. Stettler: None.