bluuebunny/crossref_metadata_2025_split huggingface dataset:
1254-P: Trauma and Loss-of-Control (LOC) Eating Relate to Elevated Type 2 Diabetes (T2D) Risk in Adolescents
Authors: JIMENEZ VIRGINIA , HILKIN ALLISON M. , VERROS MEGAN M. , CLARK EMMA L. , CASAMASSIMA MILENA , MILLER REAGAN L. , PYLE LAURA , KELSEY MEGAN M. , SHOMAKER LAUREN B. 
Published: June 2020

Objective: Traumatic events, including abuse, neglect, and other dangerous/shocking experiences, are commonly observed in adolescents with T2D. Research has shown there is a link between trauma and poorer health outcomes, yet, the extent to which trauma increases risk for developing T2D is not well understood. Trauma may heighten T2D risk through LOC eating, which can arise to cope with negative emotions. Our aim was to evaluate the links of trauma and LOC eating with T2D risk in adolescent girls with obesity.
Methods: Participants (n=65, mean±SD 15.2±1.6y) were girls at-risk for T2D based on BMI ≥85%ile, ≥1 family member with T2D, and elevated depression (Center for Epidemiologic Studies Depression [CES-D] score ≥21). Trauma history (presence vs. absence) was assessed with the Schedule for Affective Disorders and Schizophrenia for School-Aged Children, and LOC eating (presence vs. absence) with the Eating Disorder Examination. T2D risk was assessed as HbA1c and Matsuda Whole Body Insulin Sensitivity Index (WBISI), derived from a 7-sample 2-hr OGTT. ANCOVA tested differences in HbA1c and WBISI by trauma and LOC, controlling for age, BMIz, race/ethnicity, and depression.
Results: Trauma history was endorsed in 40.6% and LOC eating in 36.4% of girls. Girls with and without a trauma history reported similar rates of LOC (36.4% vs. 37.5%, p=.93). Girls with trauma had higher HbA1c (5.7±0.06%) vs. those with no trauma (5.5±0.05%, p=0.04), with no difference in WBISI (p=0.32). Girls with LOC had worse WBISI vs. those with no LOC (3.0±0.53 vs. 4.8±0.40, p&lt;0.01), with no difference in HbA1c (p=0.21).
Conclusions: Trauma history and LOC eating were unrelated to each other, but each related to different aspects of elevated T2D risk. Attention to both factors may warrant consideration in intervening to lessen T2D risk in teens with obesity and elevated depression.

Disclosure
V. Jimenez: None. A.M. Hilkin: None. M.M. Verros: None. E.L. Clark: None. M. Casamassima: None. R.L. Miller: None. L. Pyle: None. M.M. Kelsey: Other Relationship; Self; Boehringer Ingelheim Pharmaceuticals, Inc., Daiichi Sankyo, Janssen Pharmaceuticals, Inc., Merck Sharp & Dohme Corp. L.B. Shomaker: None.
1256-P: Gender Differences in the Copy Number of 11q11 Gene in European-American Obese Children
Authors: PHILLIPS MEGAN , SELVARAJU VAITHINATHAN , FOUTY ANNA , SANDEY MANINDER , JEGANATHAN RAMESH B. , THANGIAH GEETHA 
Published: June 2020

Copy number variants (CNV) provide numerous genetic modifications to human variability between individuals and linked with multiple human diseases. Obesity is one of the highly heritable complex disorders, which is associated with CNVs. A recent report shows that the 11q11 gene, a novel olfactory receptor, and its copy number variants are involved in the early onset of obesity. In the current study, we analyzed the link between 11q11 gene CNV and obesity measures in children. One hundred and twenty-seven participants between the ages of 6-10 years were involved in this study. As per WHO guidelines, anthropometric measurements were recorded, and salivary samples were collected. DNA was extracted from saliva, and the copy number variants for 11q11 gene was measured using digital PCR. The descriptive analysis of 11q11 copy numbers showed a significant increase in girls compared to boys; similarly, African American participants had significant increased CNV compared to European Americans. Only 37% of overweight/obese boys’ participants have high copy number variants compared to 63% of overweight/obese girls. The percentage of overweight/obese participants with high copy number variants was significantly lower in boys compared to girls only in the European American population. Overall, these results suggest that difference in the 11q11 CNV in gender is mainly in European American overweight/obese participants.

Disclosure
M. Phillips: None. V. Selvaraju: None. A. Fouty: None. M. Sandey: None. R.B. Jeganathan: None. G. Thangiah: None.

Funding
U.S. Department of Agriculture (to G.T.)
1259-P: Dyslipidemia of Insulin Resistance Is Associated with Subclinical Inflammation in Youth with Type 2 Diabetes
Authors: VILLALOBOS-PEREZ ALFREDO , CRAVALHO CELESTE K. , MATTA SAMANTHA , MEYERS ABBY , MABUNDO LILIAN , SAMPSON MAUREEN L. , WALTER MARY , COURVILLE AMBER B. , CHUNG STEPHANIE T. 
Published: June 2020

The dyslipidemia of insulin resistance (IR), characterized by high triglyceride-rich lipoproteins (TRLP) and low high-density lipoproteins (HDL), is associated with systemic inflammation, small low-density lipoproteins (LDL) and are important risk factors for atherosclerotic disease (ASCVD) in adults. Yet, in youth with type 2 diabetes (T2D) the natural history of ASCVD and the role of low-grade inflammation is still emerging. We compared lipoprotein profiles and inflammatory markers in 21 youth with T2D, within 5 years of diagnosis, to 10 age/BMI matched control youth with normal glucose tolerance (age: 15.8±2.5 (10-23 y) mean±SD (range), Tanner Stage IV-V, BMI: 38.9±6.9 (27.1-57.8 kg/m2). Fasting lipoprotein particle size and number, apolipoprotein B (apoB), and GlycA, a composite marker of inflammation, were derived from the NMR LipoProfile®. Pro-inflammatory markers were measured with multi-plex ELISA assays (C-Reactive Protein (hsCRP), IL-6, IL-8, IL-1β, TNF-alpha). IR was calculated by the Matsuda index during a multi-sample 75g OGTT. Youth with T2D, had higher A1c (7.2±1.3 vs. 5.4±0.3%, P&lt;0.01), lower Matsuda index (1.3±1.2 vs. 2.8±1.4, P&lt;0.01), higher ApoB (75.8±17.5 vs. 50.8±9.2 mg/dL, P&lt;0.01), more small LDL (903.4±413.3 vs. 575.8±146.4 nmol/L, P=0.02) and higher TRLPs particle concentrations (121.3±45 vs. 70.4±30.9 nmol/L, P&lt;0.01). HDL particles were not different between groups. GlycA (439.7±77.8 vs. 363.6±46.7 μmol/L, P=0.01) and hsCRP (0.8±0.9 vs. 0.2±0.2 μmol/L, P=0.01) were higher in T2D, but there were no differences in other inflammatory markers. Both GlycA and hsCRP correlated with small LDL and TRLP (GlycA: both r=0.4, P&lt;0.05); hsCRP: both r=0.5, P&lt;0.01), but not with HDL. The dyslipidemic profile of IR in youth with T2D was associated with subclinical inflammation, supporting the need for longitudinal studies to determine whether reducing inflammation in these youth will be effective as an ASCVD risk reduction strategy.

Disclosure
A. Villalobos-Perez: None. C.K. Cravalho: None. S. Matta: None. A. Meyers: None. L. Mabundo: None. M.L. Sampson: None. M. Walter: None. A.B. Courville: None. S.T. Chung: None.

Funding
National Institutes of Health (to S.T.C., L.M., A.B.C.)
1260-P: Labcorp Data in &gt;19,000 Children with a Diagnosis Code for T2D Show Predominantly Normal Liver Function Tests: Implications for Identifying Nonalcoholic Fatty Liver Disease or Steatohepatitis (NAFLD/NASH)
Authors: PURI MALA , LIZZI-ANSOK KARINA M. , FILOZOF CLAUDIA M. , GOLDSTEIN BARRY J. 
Published: June 2020

The majority of pediatric patients with biopsy proven NASH have insulin resistance (IR), however data are scarce as to the relationship between NASH and T2D in children. Clinical guidelines advise using gender-specific ALT levels (girls 22 U/L; boys 26 U/L) to screen obese or overweight children with risk factors such as IR or T2D for NAFLD/NASH. We accessed ALT, AST, and A1C results from the LabCorp® clinical database in children 7-17 years of age with suspected or confirmed T2D, NASH, or both NASH + T2D (having ICD10 codes E11 (T2D), K75.81 (NASH), or E11 + K75.81), from March 2016-2019. Of the 19,522 patients with a T2D code, median ALT values were below the gender specified norms, while 25% were higher. Median ALT levels in both genders with a code for NASH were 2.5 times greater than those with T2D and no NASH code; 72% of those with NASH codes were male. Interestingly, boys with codes for T2D and NASH had higher ALT values, despite higher mean A1C values for girls. These vast LabCorp® data show a male predominance in use of the NASH code. As expected, ALT values are higher among patients with this code relative to the T2D code, with much higher levels among boys with codes for T2DM + NASH. Of those with T2D codes, 25% had ALT values above the cut off, suggesting need for further evaluation to confirm NAFLD/NASH.

Disclosure
M. Puri: Employee; Self; LabCorp. K.M. Lizzi-Ansok: Employee; Self; LabCorp. C.M. Filozof: Employee; Self; Covance. B.J. Goldstein: Employee; Self; Covance / LabCorp.
127-LB: Characteristics of INS-MODY Participants in a National Diabetes Registry
Authors: MCCAULEY MARY , KORKMAZ SERENA , LETOURNEAU-FREIBERG LISA R. , NAYLOR ROCHELLE N. , GREELEY SIRI ATMA W. 
Published: June 2020

Introduction: Maturity onset diabetes of the young (MODY) may represent 2-5% of diabetes under 30-35 years. Rarely MODY may be due to mutation in the INS gene. HNF1A mutations are well described causes of MODY and may be treated with low dose sulfonylurea. Our aim was to compare clinical features and treatment of INS-MODY with HNF1A-MODY cohort population.
Methods: Participants enrolled through the U.S. Monogenic Diabetes Registry, with Sanger or next-generation sequencing completed with causal mutations found in INS or HNF1A, diagnosed after 13 months of age. Those with neonatal diabetes due to INS were excluded.
Results: Each group shared similar demographics (Table 1). Common presenting symptoms in each group included polyuria, polydipsia, weight loss, fatigue (Table 1). In the INS cohort, all showed residual c-peptide. None reported DKA. The majority had used insulin, though there were a variety of treatment modalities, even among those with the same mutation (Figure 1). For HNF1A cohort, over 60% had been on insulin or sulfonylurea, with 40% having discontinued insulin.
Conclusion: Review of treatments in INS cohort consist of multiple agents with majority using insulin at some point. If clinical suspicion of MODY, genetic testing may help inform treatment. It appears that some variants of INS-MODY lead to a progressive disease eventually requiring insulin therapy and early insulin may improve outcomes.

Disclosure
M. McCauley: None. S. Korkmaz: None. L.R. Letourneau-Freiberg: None. R.N. Naylor: None. S.W. Greeley: None.

Funding
National Institute of Diabetes and Digestive and Kidney Diseases (R01DK104942, P30DK0205950); National Center for Advancing Translational Sciences (UL1TR002389)
1279-P: Early Myocardial Structural Alterations in Youth with Type 1 Diabetes: Preliminary Results from the Cardea Study
Authors: HARNOIS-LEBLANC SOREN , MCNEALIS VANESSA , FRIEDRICH MATTHIAS G. , HULST ANDRAEA VAN , NUYT ANNE MONIQUE , BIGRAS JEAN-LUC , BARNETT TRACIE A. , BENEDETTI ANDREA , DRAPEAU VICKY , HENDERSON MÉLANIE 
Published: June 2020

Objectives: To compare traditional risk factors for CVD (adiposity, dyslipidemia, hypertension), and novel early markers (arterial stiffness and myocardial structure), between youth with type 1 diabetes (T1D) and healthy controls.
Methods: We compared 100 youth with T1D (14-18 yrs) and 97 age- and sex-matched controls. BMI z-scores were computed and percent body fat (%BF) measured by DEXA. Age, sex and height-specific z-scores for blood pressure (BP) were calculated. HbA1c and lipids were measured fasted. Carotid-femoral pulse-wave velocity (Sphygmocor) estimated arterial stiffness. Cardiac magnetic resonance measured left ventricular diastolic myomass, papillary mass and average wall thickness. T-tests, Chi-square and Fisher’s exact determined differences between the groups.
Results: There were no differences in ethnicity, sex or pubertal stage across groups. Median T1D duration was 6.1 (IQR=3.3-10.5) yrs; average HbA1c was 8.5% (SD=1.5). Youth with T1D had higher adiposity, modestly higher triglycerides, LDL-c and diastolic BP (albeit in normal range), and increased myomass and average wall thickness, compared with controls (Table).
Conclusions: Early alterations in myocardial structure (by 14-18 yrs), along with adverse profiles in traditional risk factors suggest that CVD prevention should be initiated prior to adolescence in pediatric T1D.

Disclosure
S. Harnois-Leblanc: None. V. McNealis: None. M.G. Friedrich: Board Member; Self; Circle Cardiovascular Imaging Inc. A. Van Hulst: None. A. Nuyt: None. J. Bigras: None. T.A. Barnett: None. A. Benedetti: None. V. Drapeau: None. M. Henderson: None.

Funding
Canadian Society of Endocrinology and Metabolism/AstraZeneca; Fonds de recherche du Québec, Santé; Heart and Stroke Foundation of Canada (G-16-00012590); Canadian Institutes of Health Research (366194)
1284-P: Adolescent Type 1 Diabetes: Technology, Depression, Distress, and Glycemic Control
Authors: PATEL NISHA , SINHA SUNIL K. , HONG K. MING , GLICK BETHANY , HOFFMAN ROBERT P. 
Published: June 2020

Background: Diabetes (DM) is a chronic illness that has major impacts on patients’ physical and emotional health. Advances in technology have aimed to improve diabetes control and lessen the burden of self-care by using continuous glucose monitors (CGM) and insulin pumps (CSII) as opposed to multiple dose injections (MDI). The goal of this study was to determine the effects of technology use on depression, DM distress, and DM control.
Methods: Patients with type 1 DM were approached at their endocrinology visits from 2018-2019 to fill out Problem Areas in Diabetes in Teenagers (PAID-T) assessment and Patient Health Questionnaire (PHQ9) screen. Inclusion criteria included age&gt;13 years. Charts were abstracted for demographic (age, insurance) and clinical (A1c, duration of DM, technology use) information. Data was analyzed using x2 square, ANOVA, and Tukey’s test.
Results: Total of 310 patients (mean age 15.11 + 1.40 years) were included in the study with average DM duration of 5.37 + 3.86 years. CGM, CSII, and combined use were higher in the private insurance (PI) group vs. state insurance (SI) (p=0.000). When PAID-T scores were evaluated based on insurance and technology use, only insurance was associated (p=0.013), with SI being linked to higher PAID-T scores. PHQ9 scores were higher in patients with SI vs. PI (p=0.000), whereas technology use was not significant. PAID-T and PHQ9 were not related to DM duration. ANCOVA revealed that A1c was related to technology use (p=0.048), PHQ9 (p=0.018), and PAID-T scores (p=0.000). MDI use, higher PHQ9, and higher PAID-T scores were associated with higher A1c.
Conclusions: Insurance, a marker of socioeconomic status, is the principal determinant of technology use (CGM and CSII). Insurance, not technology use, is the best predictor of depression and DM distress, which are both strongly associated with higher A1c. Future efforts should be directed at improving both depression and DM distress via access to mental health services to ultimately improve DM control.

Disclosure
N. Patel: None. S.K. Sinha: None. K. Hong: None. B. Glick: None. R.P. Hoffman: Research Support; Spouse/Partner; Provention Bio, Inc.
1288-P: Novel Culturally Sensitive Shared Medical Appointment Model for High-Risk Latino Youth with Type 1 Diabetes: One-Year Follow-Up Postpilot Intervention
Authors: JENSEN RYAN , CAMPBELL KRISTEN , PYLE LAURA , GONZALEZ ANDREA GERARD 
Published: June 2020

Objective: A novel, culturally sensitive shared medical appointment (SMA) pilot program was evaluated as a continuing model of care for high risk Spanish speaking Latino patients (LP) with type 1 diabetes (T1D). We examined retention and outcomes of participants one year after the pilot research intervention ended.
Methods: Changes in outcomes for LP in the SMA from the end of the funded pilot program (year 3) to the first year post-intervention (year 4) were assessed. Retention rates, A1c and diabetes technology uptake (insulin pump and continuous glucose monitor (CGM)) were recorded for children (&lt;12 years) and teens (12+ years).
Results: Of the 75 LP enrolled by the end of the funded study period, 64 (85.3%) continued with at least one visit in the SMA in year 4. Average A1c decreased from year 3 to 4, but did not achieve statistical significance (-0.4± 0.3; p=0.128). Teens and children showed a significant increase in insulin pump use in from baseline to Year 4 (Teens: n=35, 26%; p=0.008), (Children: n=12, 75%; p=0.008). Teens and children showed a significant increase in CGM use from baseline to Year 4 (Teens: n=35, 34%; p=0.001) (Children: n=12, 75%; p=0.008).
Conclusions: The novel culturally sensitive SMA model demonstrated to be a well-received program for high-risk Spanish speaking LP youth with high retention rates one year after research concluded. Participants continued to demonstrate increase uptake of diabetes technologies. Additional studies of the effects of the SMA on glycemic control are needed.

Disclosure
R. Jensen: None. K. Campbell: None. L. Pyle: None. A. Gerard Gonzalez: None.

Funding
The Leona M. and Harry B. Helmsley Charitable Trust (2015PG-T1D060)
129-LB: Evaluation of Attitudes towards Two Glucagon Delivery Devices for Rescue Treatment of Severe Hypoglycemia
Authors: BAJPAI SANJAY K. , CAMBRON-MELLOTT JANELLE , RAIBULET NEDINA K. , PECK EUGENIA Y. , POON JIAT LING , WANG QIANQIAN , MITCHELL BETH , WILL OLIVER , BABROWICZ JANE , CHILD CHRISTOPHER J. , BEUSTERIEN KATHLEEN 
Published: June 2020

Objective: This study assessed preference, hesitation using, perceived ease of use, and feeling prepared and protected for nasal glucagon (NG) vs. autoinjector glucagon (AI) for rescue treatment of severe hypoglycemia (SH) among people with diabetes (PWDs), caregivers (CGs) and acquaintances (AQs).
Methods: US PWDs (type 1 or 2, on insulin; n=405), CGs (n=313) and AQs (n=305) completed an online survey, after viewing a description of SH and graphics and descriptions of NG and AI (based on publicly available information at the time of study; prior to access to the final commercial device or their instructions for use). Respondents rated strength of preference for NG vs. AI on 16 attributes using direct elicitation (7-point scale; 1 = ‘very strongly prefer AI‘ and 7 = ‘very strongly prefer NG’, 4 = neutral); 4 items focused on overall preference, being less likely to hesitate using, perceived ease of use, and feeling prepared and protected, and 12 items were averaged to create a preference scale (e.g., size of device, less complicated). This measure was developed using established guidelines for instrument development, including qualitative research and assessment of the measure’s psychometric properties. One sample t-tests evaluated whether mean preference ratings differed from a neutral score.
Results: Across PWDs, CGs, and AQs, NG was preferred over AI (all P&lt;0.001 compared to neutral) on overall preference (4.5, 4.9, and 5.4, respectively), being less likely to hesitate using (4.8, 5.1, and 5.4, respectively), perceived ease of use (4.8, 5.1, and 5.4, respectively) and the preference scale (4.7, 5.0, and 5.3, respectively). CGs and AQs preferred NG vs. AI on feeling prepared and protected (4.6 and 4.8, respectively; both P&lt;0.001 compared to neutral); PWDs were neutral (4.1, P=0.376).
Conclusions: This study provides insights on PWDs’, CGs’ and AQs’ attitudes towards new glucagon devices, which may be considered when making product choices among the glucagon delivery systems.

Disclosure
S.K. Bajpai: Employee; Self; Eli Lilly and Company. J. Cambron-Mellott: Other Relationship; Self; Eli Lilly and Company. N.K. Raibulet: Employee; Self; Eli Lilly and Company. E.Y. Peck: None. J. Poon: Employee; Self; Eli Lilly and Company. Q. Wang: Employee; Self; Eli Lilly and Company. B. Mitchell: Employee; Self; Eli Lilly and Company. Stock/Shareholder; Self; Eli Lilly and Company. O. Will: Other Relationship; Self; Eli Lilly and Company. J. Babrowicz: Other Relationship; Self; Eli Lilly and Company. C.J. Child: Employee; Self; Eli Lilly and Company. Stock/Shareholder; Self; Eli Lilly and Company. K. Beusterien: Other Relationship; Self; Eli Lilly and Company.
1290-P: Gut Microbiota in New-Onset Pediatric Patients with Type 1 Diabetes: Machine Learning Algorithms to Classify Microorganisms Disease-Linked
Authors: D’ANNUNZIO GIUSEPPE , BIASSONI ROBERTO , SQUILLARIO MARGHERITA , UGOLOTTI ELISABETTA , BARLA ANNALISA , PICCOLO GIANLUCA , MINUTO NICOLA , MAGHNIE MOHAMAD 
Published: June 2020

Gut microbiota plays a role in human health and autoimmunity. Among environmental factor linked to type 1 diabetes (T1DM) pathogenesis, gut microbiota impairment seems to be involved. We evaluated gut microbial fingerprinting in 31 pediatric patients with new-onset T1DM and 25 healthy children using multiple polymorphic region of the 16S rRNA. We performed machine learning and metagenome functional analyses to identify significant taxa and metabolic pathways and correlate with clinical and metabolic parameters. Inclusion criteria were living in Northern Italy, born from Caucasian parents, singleton birth, personal history negative for acute/chronic gastrointestinal diseases and/or antibiotic or probiotics administration. Different Bacteroidetes species i.e., B.stercoris (q=1,473E-4), B.intestinalis (q=0.010), B.fragilis (q=0.0452) were significantly more frequent in patients as well as B.bifidum, Gammaproteobacteria, Holdemania, Synergistetes and their descendants. Abundance of the Synergistetes (q=0.001), Synergistia (q=4.798E-5), Synergistales (q=2.64E-4) and Synergistaceae (q=0.0017) was reported. Among Deltaproteobacteria descendants, the Desulfovibrionales (q=0.0016), Desulfovibrionaceae (q=0.016) and the Bilophila genus (q=0.036) were significantly lower in patients as well as B.vulgatus, Deltaproteobacteria, Parasutterella and Lactobacillus, Turicibacter genera. BMI-SDS, insulin autoantibodies, glycemia, HbA1c, Tanner and age were the most significant positively or negatively parameters related to specific clusters of taxa. The supervised analyses confirmed the importance of B. stercoris in T1DM patients and a relevant role of Synergistetes and its descendants. The robustness and coherence of our results underline the relevance of studying microbioma using multiple polymorphic regions, different types of analysis and approaches within each analysis.

Disclosure
G. d’Annunzio: Consultant; Self; Sandoz. R. Biassoni: None. M. Squillario: None. E. Ugolotti: None. A. Barla: None. G. Piccolo: None. N. Minuto: None. M. Maghnie: None.