bluuebunny/crossref_metadata_2025 huggingface dataset:
1133-P: Value of Dexcom CGM for Therapy Optimization and Glycemic Outcomes in Post-Hospital Discharge Type 2 Diabetes Patients—An Exploratory Study
Authors: CRAWFORD MARGARET A. , HICKS CHRISTIAN , ZHOU TERESA , XU YING , SINGH HARSIMRAN , CHERÑAVVSKY DANIEL R. , LEVISTER CAMILLA , SHAH NIRALI , ROUVIERE MADELEINE , TAMRU ABIGAIL , KAPLAN LEAH , LAM DAVID W. , O'MALLEY GRENYE , LEVY CAROL J.
Published: June 2024

Post-hospital discharge (PHD) can be a challenging time for health care providers (HCPs) and patients. We analyzed use of Dexcom G6 CGMs in PHD T2D patient management.

This study analyzed 30 days of PHD remote monitoring data for 28 T2D patients. Hospital discharge summaries and telehealth notes were analyzed for details around hospital stay, PHD outcomes, and patient-HCP interactions.

Study sample was categorized into 3 cohorts to reflect disease severity and risk of mortality during hospitalization- Group A (Organ Transplants), Group B (High Severity), Group C (Medium Severity) (Table). Overall, Group B was the youngest (median (IQR): 37 years (37,55)) vs. Groups A & C (54 (47,59) & 55 (50,57)), had the shortest hospital stay (3 days (2,5)) vs. Groups A & C (8 (8,10) & 11 (7,15)) and the shortest diabetes duration (7 years (1,20) vs. Groups A & C (15 (2,27) & 10 (6,17)). Group A had the most telehealth encounters (20 (9,21) vs. Groups B & C (12 (11,15) & 12 (10,13)). Telehealth encounter notes detailed HCP interactions with CGM data including response to Dexcom Follow alerts, insulin titration, and diabetes self-care coaching. Using CGM, groups A & B showed decreased mean glucose and frequency of severe hypo- and hyper-glycemic events over the study period (Table).

These early findings demonstrate the value of CGM to inform critical therapy adjustments for optimizing outcomes during PHD.

Disclosure

M.A. Crawford: Employee; Dexcom, Inc. C. Hicks: Employee; Dexcom, Inc. T. Zhou: None. Y. Xu: Employee; Dexcom, Inc. H. Singh: Employee; Dexcom, Inc. D.R. Cherñavvsky: None. C. Levister: Research Support; Dexcom, Inc., Tandem Diabetes Care, Inc. N. Shah: None. M. Rouviere: None. A. Tamru: None. L. Kaplan: None. D.W. Lam: Research Support; Renalytix. G. O'Malley: Research Support; Dexcom, Inc., Insulet Corporation, Abbott, Tandem Diabetes Care, Inc., MannKind Corporation. C.J. Levy: Research Support; Dexcom, Inc. Consultant; Dexcom, Inc. Research Support; MannKind Corporation, T1D Exchange, Tandem Diabetes Care, Inc., Abbott, Insulet Corporation.
115-OR: Adipose m6A Reader YTHDF2 Regulates White Adipose Tissue Growth and Metabolism
Authors: ZHOU RUOYU , RUI LIANGYOU , KANG QIANQIAN
Published: June 2024

Introduction & Objective: White adipose tissue (WAT) releases free fatty acids (FFAs) via lipolysis to meet metabolic demand in a negative energy state. Excessive WAT growth imposes risk for type 2 diabetes and metabolic dysfunction-associated steatotic liver disease (MASLD), but mechanism for aberrant WAT growth is poorly understood. We previously reported that adipose METTL14, a m6A writer installing m6A methylation on RNA, promotes obesity by suppressing lipolysis. The objective of this work is to identify m6A readers mediating METTL14’s action.

Methods: Adipocyte-specific Ythdf2 knockout mice (Ythdf2Δfat) were generated by crossing Ythdf2f/f with Adipoq-Cre mice and fed high fat diet (HFD) for 12 weeks. Lipolysis assays were performed in mice and in WAT explants. RNA immunoprecipitation was used to assess m6A levels and YTHDF2-binding to RNA.

Results: We found that Ythdf2Δfat mice, both males and females, were resistant to HFD-induced obesity. Fat content was significantly lower in Ythdf2Δfat than in Ythdf2f/f littermates. Ablation of adipose Ythdf2 mitigated insulin resistance and MASLD. β-agonist treatment increased plasma FFAs to a higher level in Ythdf2Δfat than in Ythdf2f/f mice. β-agonists also stimulated lipolysis to a higher level in Ythdf2Δfat WAT ex vivo. Adipose triglyceride lipase (ATGL) and CGI-58 (ATGL cofactor) levels were markedly higher in Ythdf2Δfat than in Ythdf2f/f WAT. YTHDF2 bound to Atgl and Cgi-58 mRNAs, and ablation of METTL14 suppressed YTHDF2 interactions with these transcripts. These results suggest that YTHDF2 binds to m6A-marked transcripts to inhibit ATGL and CGI-58 syntheses, thereby suppressing lipolysis.

Conclusion: Our results unveil YTHDF2-based epitranscriptomic reprogramming that governs lipolysis and WAT growth.

Disclosure

R. Zhou: None. L. Rui: None. Q. Kang: None.

Funding

National Institutes of Health (R01DK130111)
1152-P: Treatment Trends in Youth-Onset Type 2 Diabetes—Changing Landscape after GLP-1RA Approval
Authors: SHIN HOJIN , PAIK JULIE M. , WEXLER DEBORAH J. , PATORNO ELISABETTA
Published: June 2024

Introduction: The approval of glucagon-like peptide-1 receptor agonists (GLP-1RA), starting with liraglutide in 2019, has expanded treatment options in youth-onset type 2 diabetes (T2D). However, the uptake of GLP-1RA in this population is unknown.

Methods: In two US commercial claims databases (Optum and MarketScan), we identified individuals aged <30 years with T2D who initiated first-line glucose-lowering drugs between 2010 (aligning with the US market entry of liraglutide) and 2023. We examined first-line use by plotting annual trends overall and within age subgroups (≤18, 19-25, 26-29 years) and escalation patterns using Sankey diagrams, comparing the periods before (2010-2018) and after (2019-2023) the 2019 approval of GLP-1RA in youth.

Results: Metformin was the most commonly initiated first-line agent (overall: 71.1%), followed by insulin (overall: 9.4%, ≤18 years: 18.8%) (Figure A). The use of GLP-1RA increased considerably (from 2.9% in 2019 to 12.6% in 2023), yet it remained low overall. This trend was consistent across all age groups. With respect to escalation patterns (Figure B), sulfonylureas and insulin were most frequently prescribed after metformin failure in 2010-2018, whereas GLP-1RA were the most frequently prescribed after metformin in 2019-2023.

Conclusion: In youth-onset T2D, the use of GLP-1RA as first-line and subsequent therapies has increased but remains overall low.

Disclosure

H. Shin: None. J.M. Paik: None. D.J. Wexler: Other Relationship; Novo Nordisk. E. Patorno: Research Support; Boehringer-Ingelheim, Food and Drug Administration (FDA), National Institutes of Health, Patient-Centered Outcomes Research Institute.
116-OR: GL0034 (Utreglutide), a Novel GLP-1RA, Increases Liver FGF-21 and Demonstrates Significant Efficacy on Weight Loss, HbA1c, and Triglycerides in db/db Mice
Authors: THENNATI RAJAMANNAR , BURADE VINOD S. , NATARAJAN MUTHUKUMARAN , GARCIA-OCANA ADOLFO , RUTTER GUY A. , PRATLEY RICHARD E. , THORENS BERNARD , VILSBØLL TINA
Published: June 2024

Introduction & Objective: Glucagon-like peptide receptor agonists (GLP-1RA) stimulate fibroblast growth factor (FGF-21) production and both have overlapping metabolic effects like glycemic control, suppression of food consumption, and body weight reduction. GL0034 has demonstrated excellent safety and tolerability in phase 1 trials. Further, a single dose of subcutaneous administration of GL0034 in individuals with obesity resulted in 3.3 kg of weight loss that was sustained till day 22

Methods: We explored a fixed dose (21nM/kg) of GL0034, semaglutide (Sema) and tirzepatide (TZP) given to db/db mice every third day for 4 weeks. Biomarkers were measured on days 14 and 28.

Results: GL0034 increased liver FGF-21 and, uncoupling protein-1 (UCP-1) in brown and white adipose tissues significantly more than Sema and similarly to TZP. The effects of GL0034 on HbA1c (↓), insulin (↑), glucagon (↓), weight loss (↑), triglycerides (↓), and cholesterol (↓) were similar to those induced by Sema and TZP. Food consumption was similar to TZP and lower than with Sema (Table).

Conclusion: In conclusion, GL0034 shows robust efficacy on multiple metabolic parameters and may serve as a promising new super GLP-1RA for individuals with obesity +/- type 2 diabetes and for the treatment of MASLD with enhanced therapeutic benefits partly due to increased liver FGF-21.

Disclosure

R. Thennati: None. V.S. Burade: None. M. Natarajan: None. A. Garcia-Ocana: Consultant; Sun Pharmaceutical Industries Ltd. G.A. Rutter: Advisory Panel; Sun Pharmaceutical Industries Ltd. R.E. Pratley: Other Relationship; Bayer AG, Dompé, Endogenex, Inc., Gasherbrum Bio, Inc., Hengrui (USA) Ltd., Intas Pharmaceuticals Ltd., Eli Lilly and Company, Merck Sharp & Dohme Corp., Novo Nordisk, Novo Nordisk, Pfizer Inc., Rivus Pharmaceuticals Inc., Sun Pharmaceutical Industries Ltd. Consultant; AbbVie Inc., AstraZeneca. Other Relationship; Bayer HealthCare Pharmaceuticals, Inc., Biomea Fusion, Carmot Therapeutics, Inc., Corcept Therapeutics, Fractyl Health, Inc., Genprex. Consultant; Getz Pharma. Other Relationship; Lilly USA LLC, Sanofi. Consultant; Scholar Rock, Inc. B. Thorens: Advisory Panel; Sun Pharmaceutical Industries Ltd. T. Vilsbøll: Consultant; AstraZeneca. Advisory Panel; Boehringer-Ingelheim. Speaker's Bureau; Mundipharma. Advisory Panel; Novo Nordisk, Lilly Diabetes, Sanofi. Speaker's Bureau; Bayer Inc., Gilead Sciences, Inc. Advisory Panel; Sun Pharmaceutical Industries Ltd. Research Support; Lilly Diabetes.
117-OR: Effects of Triple-Hormone Receptor Agonist Retatrutide on Lipid Profiling in Participants with Obesity
Authors: PIRRO VALENTINA , PEARSON MACKENZIE J. , LIN YANZHU , HARTMAN MARK L. , ROTH KENNETH D. , DUFFIN KEVIN L. , WILLENCY JILL , HAUPT AXEL , RUOTOLO GIACOMO
Published: June 2024

In phase 2 (n=338), retatrutide (RETA), an agonist of GIP, GLP-1 and glucagon receptors, reduced body weight, fasting glucose, triglycerides (TG), LDL and VLDL cholesterol in participants with obesity. To understand changes in energy metabolism, lipidomic profiling was conducted. Adult participants with obesity (BMI ≥30 kg/m2), or overweight (BMI ≥ 27 kg/m2) with a weight related comorbidity, were randomized to RETA 1, 4, 8, 12 mg or PBO for 48 wk. Fasting plasma collected at baseline, 24 and 48 wk, was used to measure acylcarnitines and complex lipid species using targeted mass spectrometry. Data were analyzed using a mixed model for repeated measures. An increase in 3-hydroxybutyrate (3-HB) was noted after 24 wk, accompanied by an increase in 3-hydroxybutyrylcarnitine (C4OH), acetylcarnitine-to-free carnitine ratio (C2/C0), and medium-chain ACs. The decrease of TGs at 48 wk was bias towards short-chain and saturated species. RETA 12 mg decreased total dihydroceramides (DhCers) at 48 wk by −20.1%, p-value <0.001. The increase in ketone body and C2/C0 observed after 24 wk is suggestive of adipose tissue lipolysis and reliance on fat oxidation. Inverse changes in TGs and DhCers were observed which associate with improved insulin sensitivity, reduced hepatic steatosis and systemic inflammation. Evaluation of potential benefits on cardiovascular events and MASLD may merit further investigation.

Disclosure

V. Pirro: Employee; Eli Lilly and Company. M.J. Pearson: Employee; Eli Lilly and Company. Y. Lin: Stock/Shareholder; Eli Lilly and Company, Pfizer Inc., AstraZeneca. M.L. Hartman: Employee; Eli Lilly and Company. Stock/Shareholder; Eli Lilly and Company. K.D. Roth: Employee; Eli Lilly and Company. Stock/Shareholder; Eli Lilly and Company. K.L. Duffin: Employee; Eli Lilly and Company. J. Willency: Employee; Eli Lilly and Company. A. Haupt: Employee; Lilly Diabetes. Stock/Shareholder; Lilly Diabetes. G. Ruotolo: None.

Funding

Eli Lilly and Company
1171-P: Cytokines Do Not Consistently Change Proinsulin (PI) Cargo in Global Human Islet-Derived Extracellular Vesicle (EV) Populations
Authors: DE OLIVEIRA ANDRE G. , XU JERRY , SIMS EMILY K. , RAO CHAITRA
Published: June 2024

Introduction and Objective: Multiple factors may trigger or exacerbate progression of Type 1 diabetes (T1D). EVs, nanoparticles housing molecular cargo, have been implicated in many diseases, including diabetes. β-cell EVs can present antigens and carry PI as cargo. Cytokine exposure leads to β-cell ER stress, reduces PI processing enzyme expression, and increases PI secretion relative to insulin or C-peptide. Cytokine-induced stress is also associated with changes in EV cargo, as well as intracellular formation of immunogenic peptides, including modified PI. We sought to understand if β-cell EV PI cargo might be changed under cytokine exposure.

Methods: INS1 or EndoC-βH1 cells and human islets were treated with 5 ng/mL IL-1β, or IL-1β + 100 ng/mL IFNγ + 10 ng/mL TNFα, for 48 hrs. Plasma (450 µL) from five children with recent onset type 1 diabetes and age, sex, and BMI-matched nondiabetic controls was also assayed. EVs were isolated by ultracentrifugation (30000 x g, 1.5 hrs) or size exclusion chromatography. EV proteins were precipitated by the TCA-acetone method and PI was quantified by immunoblotting or ELISA for human samples.

Results: Cytokine treatment did not consistently change EV concentration or EV PI cargo in INS1, EndoC-βH1, or islet-derived EVs. Tunicamycin, but not thapsigargin treatment of cells yielded an increase in EV PI content, suggesting a potential link to protein trafficking rather than ER stress. EV PI content in human plasma was frequently undetectable, and when detectable, was not significantly different in plasma from children with T1D vs. controls.

Conclusion: Global changes in human islet EV PI cargo were not detected under conditions of cytokine stress or recent onset T1D. These findings point away from EV-derived PI as a large-scale or frequent contributor to the development of neoantigens in T1D.

Disclosure

A.G. De Oliveira: None. J. Xu: None. E.K. Sims: Consultant; Sanofi. Board Member; American Diabetes Association. Other Relationship; American Diabetes Association, Medscape. Consultant; DRI. C. Rao: None.
1177-P: Practice Patterns of Medical Management of Pediatric Obesity and Type 1 Diabetes (T1D)
Authors: DOOLAN JADE , ISGANAITIS ELVIRA M. , LAFFEL LORI M. , MAXWELL TARA K.
Published: June 2024

Aim: Recent pediatric guidelines emphasize the need for aggressive treatment of childhood obesity, including use of recently approved pediatric weight loss medications like glucagon-like peptide receptor agonists (GLP1-RA), in order to preserve health. Given additional health risks related to T1D, we sought to assess practice patterns of obesity pharmacotherapy in a clinic sample of adolescents with T1D.

Methods: We extracted electronic health record (EHR) data from 12/1/17-12/1/23 of obese (BMI ≥95th %ile) youth with T1D aged 12 to <18 years prescribed ≥1 of FDA-approved pediatric weight loss (liraglutide, semaglutide, topiramate/phentermine, and orlistat) and type 2 diabetes (metformin and dulaglutide) medications.

Results: From 6 years of clinical observations, there were 540 unique adolescents with T1D aged 12-<18 years. Of these, 124 (23%) were obese. We identified 41 adolescents (63% female) with obesity prescribed ≥1 of the listed medications. Mean age at medication initiation was 14.6±2.2 years, and 46% saw a registered dietitian within a year before medication initiation. Metformin alone was prescribed for 33 youth and GLP1-RA for 8 adolescents (2 started directly on GLP1-RA; remaining 6 prescribed metformin first). All GLP1-RA were started after 2020 FDA approval for pediatric obesity treatment. No adolescents were prescribed topiramate/phentermine or orlistat. Of those with complete BMI data, those on metformin alone (29/33) had stable mean BMI percentile at up to 1 year follow-up, while those on GLP1-RA (6/8) experienced a small reduction in mean BMI percentile.

Conclusion: In this clinic sample, nearly 1 in 4 adolescents with T1D were obese. Despite recent FDA approval of new weight loss medications for children and adolescents, few were prescribed GLP1-RA. Further research is needed to understand patient/family and provider perspectives on these medications and their potential benefits for young people with T1D.

Disclosure

J. Doolan: None. E.M. Isganaitis: Research Support; Dexcom, Inc., Tandem Diabetes Care, Inc., Insulet Corporation, MannKind Corporation. L.M. Laffel: Consultant; Dexcom, Inc. Advisory Panel; Medscape, Medtronic, Vertex Pharmaceuticals Incorporated. Consultant; Novo Nordisk. Advisory Panel; Lilly Diabetes, Provention Bio, Inc., Sanofi-Aventis U.S., Janssen Pharmaceuticals, Inc., MannKind Corporation. T.K. Maxwell: None.
1189-P: Challenges Recruiting Adolescents and Young Adults (AYA) with Type 1 Diabetes and Higher A1Cs for Clinical Research
Authors: VOLKENING LISA K. , MORRISSEY BRENDEN , ALAMARIE SELMA A. , HERNDON CHRISTOPHER , SCHNEIDER-UTAKA AIKA K. , ADAM ATIF , HANES SARAH , OJUKWU SANDO , HOOD KOREY K. , LAFFEL LORI M.
Published: June 2024

Introduction: Recruiting a representative study sample is critical but can be challenging. We assessed potential differences between AYA with T1D who consented vs declined to participate in a 2-year RCT aimed at improving glycemic outcomes and reducing diabetes distress.

Methods: AYA were recruited at 2 US sites for a study involving monthly virtual 1-1 psychoeducational sessions. Eligibility criteria included age 14-25 years, T1D ≥1 year, and A1c 7-13%.

Results: Over 15 months, we approached 482 potential participants; 217 (45%) consented, 232 (48%) declined, and 33 (7%) were ineligible. Most AYA were identified via clinic schedules (77%). Other recruitment methods were: participation in a previous study (14%), recruitment flyer (5%), provider referral (4%), and social media (1%). Reasons for decline were: too busy/not a good time (n=41, 18%), not interested (n=29, 13%), other/no reason given (n=7, 3%), and passive decline (expressed interest but no decision before enrollment closed) (n=155, 67%). There was no difference in the number of contacts made to those who consented vs declined (median=2 for both, range=1-8). Limited demographic data at 1 site for 217 potential participants (105 consented, 112 declined) showed no difference in % consented according to age (14-18 years: 46% consented; 19-25: 50% consented; p=.58) or SES using Social Deprivation Index (higher SES: 47% consented; lower SES: 51% consented; p=.49). However, there was a difference by A1c (7-8.4%: 59% consented; 8.5-13%: 39% consented; p=.002). Further, 65% of those with A1c 8.5-13% who declined were passive declines (compared to 51% of decliners with A1c 7-8.4%), suggesting that they had some interest but no follow-through. Number of contacts did not differ by age, SES, or A1c.

Conclusion: AYA with suboptimal glycemic control, often the target of research, may hesitate to participate in clinical trials. Creative outreach and extra effort (e.g., more contacts) may help to recruit them for future studies.

Disclosure

L.K. Volkening: None. B. Morrissey: None. S.A. Alamarie: None. C. Herndon: None. A.K. Schneider-Utaka: None. A. Adam: None. S. Hanes: None. S. Ojukwu: None. K.K. Hood: Consultant; Cecelia Health, Sanofi. L.M. Laffel: Consultant; Dexcom, Inc. Advisory Panel; Medscape, Medtronic, Vertex Pharmaceuticals Incorporated. Consultant; Novo Nordisk. Advisory Panel; Lilly Diabetes, Provention Bio, Inc., Sanofi-Aventis U.S., Janssen Pharmaceuticals, Inc., MannKind Corporation.

Funding

National Institutes of Health (R01DK129479)
1198-P: Sex Differences in Chinese Adult-Onset Type 1 Diabetes
Authors: CHEN SHUANG , GU YONG
Published: June 2024

Introduction & Objective: Growing evidence on the heterogeneity of type 1 diabetes (T1D) has been accumulated, there is still insufficient evidence to explore sex differences, particularly in adults with T1D. The study was to explore the sex differences among adult patients with autoimmune diabetes, focusing on the clinical characteristics, autoantibody profile, and β-cell secretion.

Methods: Clinical characteristics, islet autoantibody profile, and β cell function were assessed by sex in 191 adults with T1D between Jan 2015 to Nov 2022. Subgroup analysis was conducted in different age groups according to the age of diagnosis.

Results: Women had a higher median age at diagnosis than men (51.0 vs. 38.0 years, P=0.008) and were more likely to be positive for multi-autoantibodies (54.2% vs. 39.8%, age-adjusted odds ratio [OR] 2.21 [95% confidence interval (CI) 1.20, 4.09], P=0.011), GADA (age-adjusted OR 5.62 [1.68, 18.86], P=0.005) and IA2A (age-adjusted OR 2.16 [1.18, 3.94], P=0.012). Moreover, women were at a higher risk of experiencing a decline in fasting C-peptide to 30% from baseline (age-adjusted OR 6.97 [1.88, 25.83], P=0.004). Subgroup analysis were shown in the following figure.

Conclusion: Analyzing the sex disparities of T1D provides new insight into the heterogeneity of this disease, and demands further investigation for understanding biological mechanisms, hence guiding personalized diagnosis and management for this disease.

Disclosure

S. Chen: None. Y. Gu: None.

Funding

the National Natural Science Foundation of China (82170837, 81770777, 82230028); Jiangsu Provincial Medical Key Discipline (Laboratory)+ZDXK202202.
1200-P: Effectiveness of Real-Time, Remote Continuous Glucose Monitoring in Adolescents with Poorly Controlled Type 1 Diabetes
Authors: CHOUDHARI POOJA , MARWA ALBARA , WHITE PERRIN C. , CHOUDHARY ABHA
Published: June 2024

Introduction & Objective: Adolescents with Type 1 diabetes (T1D) have higher hemoglobin A1c (A1c) than other age groups. Poorly controlled diabetes increases the risk for diabetic ketoacidosis (DKA) and other diabetic complications. We hypothesized that real-time, remote, continuous glucose monitoring with real-time coaching via two-way text messaging will improve the A1c of adolescents with poorly controlled T1D.

Methods: We are conducting a prospective, single-arm, pilot study. Phase 1 is a run-in phase using a continuous glucose monitor (CGM). Phase 2 consists of 3 months of real-time, remote, glucose monitoring (RTM) with two-way text messaging with a pediatric endocrinologist to provide coaching, glucose trend review and insulin dose adjustments. During the 3-month final phase, we assess A1c changes after cessation of RTM. We also follow psychosocial measures. Inclusion criteria include patients with T1D ages 13 to 18 years, with 30% annual risk of developing DKA or A1c ≥ 12%. Primary exclusion criteria include other types of diabetes and chronic conditions or use of glucocorticoids that affect glycemic control.

Results: Nine participants began the RTM phase. One participant had a malfunctioning phone, which adversely impacted CGM data sharing. Therefore, the corresponding data were not included in the results. Average baseline A1c was 11.4%. Following 3 months of RTM, A1c improved by 0.7% (p = 0.15). Alc increased after cessation of RTM. Time in range improved an average of 1.8% during RTM but decreased during Phase 3. Participants with greater correspondence frequency with the monitoring physician had greater improvement in A1c (decreased by 1.6-3%). During the study, no participants were admitted for DKA.

Conclusion: RTM and coaching improved the overall glycemic control of our pilot study participants. However, the improvement was not sustained without RTM. The level of return engagement might be associated with some level of improvement in A1c.

Disclosure

P. Choudhari: None. A. Marwa: None. P.C. White: Consultant; Provention Bio, Inc. Research Support; MannKind Corporation, National Institute of Diabetes and Digestive and Kidney Diseases. A. Choudhary: None.

Funding

Children's Medical Center Foundation Dexcom, Inc provided CGMs (External study number IIS-2020-076)
1201-P: The Impact of Gender on Sleep, Glycemia, and Health-Related Quality of Life (HRQOL) in Adolescents with Type 1 Diabetes
Authors: FIVEKILLER EMILY , SAKAMOTO CASEY , TAYLOR KASSERINE , PYLE LAURA , MELTZER LISA J. , PAUL WADWA R. , COBRY ERIN C.
Published: June 2024

Sleep is key to health maintenance. Adolescents with T1D are at increased risk for sleep disruptions and shorter sleep duration. We examined differences between biological genders in sleep, glycemia and HRQOL outcomes for youth aged 11-17 yes with T1D.

70 youth (mean 14.5±1.8 yrs, 51% female, 76% Non-Hispanic White) participated in an observational study. Actigraphy data (sleep duration, sleep efficiency, sleep onset latency, wake after sleep onset) and glycemic data from CGM (TIR (70-180mg/dL), time hyperglycemic (>180mg/dL), time hypoglycemic (<70mg/dL)) were collected for 1-week, followed by self-report surveys (PROMIS, Sleep-Related Disordered Breathing [SRDB], Fear of Hypoglycemia, Morningness/Eveningness).

No significant gender differences were found for demographics, actigraphic sleep, or glycemic outcomes. Statistically significant differences were found for psychological stress (p=0.01), anxiety (p=0.03), depressive symptoms (p=0.01), sleep-related impairment (p=0.03), and SRDB (p=0.03) with females reporting poorer outcomes (Table).

This study highlights gender differences in self-reported sleep and HRQOL among adolescents with T1D. Interventions to address poor sleep and psychological distress may benefit from a gender-specific lens. Further research is needed to elucidate gender differences and examine ways to improve sleep and glycemia for all adolescents.

Disclosure

E. Fivekiller: None. C. Sakamoto: None. K. Taylor: None. L. Pyle: None. L.J. Meltzer: Consultant; Egetis Therapeutics, Harmony Biosciences, Zepp Health. R. Wadwa: Research Support; Dexcom, Inc. Other Relationship; Dexcom, Inc. Research Support; Eli Lilly and Company. Advisory Panel; Eli Lilly and Company, Provention Bio, Inc. Research Support; Tandem Diabetes Care, Inc. Other Relationship; Eli Lilly and Company. E.C. Cobry: Advisory Panel; Dexcom, Inc. Other Relationship; Dexcom, Inc.

Funding

JDRF (5-ECR-2022-1179-A-N)
1208-P: Role of Galectin-9 in the Development of Gestational Diabetes Mellitus (GDM)
Authors: ALBUAYJAN HAYA H. , SUGAWARA RYOSUKE , OI YUKIKO , YANG BOXUAN , TAHARA TOSHIHISA , NAKATSUKA ATSUKO , EGUCHI JUN , WADA JUN
Published: June 2024

Introduction: Interactions between the trophoblast and NK cells is critical for the regulation of inflammation in placenta. Galectin-9 (Gal-9) induces apoptosis of Th1 and NK cells. Since Gal-9 is highly expressed in placenta, we aimed to investigate the role of Gal-9 in the development of GDM.

Methods: C57BL/6J (WT) and B6-Lgals9tm1glp (KO) female mice were assigned to standard fat diet (SFD) and high fat diet (HFD) and they were mated with WT and samples were obtained at gestational day 19. In the women with GDM, plasma at 2nd, 3rd trimester and after delivery, and placenta tissues were obtained. Mann-Whitney’s U test, one-way ANOVA with Tukey test, and Spearman correlation coefficient were used (IBM SPSS 23 and GraphPad Prism 10).

Results: In pregnant KO mice fed with HFD, the body weight was reduced compared to WT mice. Glucose tolerance tests demonstrated that blood glucose levels at 120 min were significantly higher (224 ± 22.5 mg/dL) compared to WT mice (199 ± 90.3 mg/dL) (P=0.032). The embryos from KO mice demonstrated macrosomia (1.30 ± 0.2 g) in comparison with WT mice (0.96 ± 0.2 g) (P=0.039). Gal-9 mRNA expression was upregulated in placenta from WT mice fed with HFD and Gal-9 was highly expressed in labyrinth layer. In placenta derived from KO mice fed with HFD, the number of apoptotic cells by TUNEL assay were reduced, while M1 and M2 macrophage, and NK cell markers were increased compared to WT mice. The women with GDM, plasma Gal-9 levels rapidly increased at 3rd trimester (2.01 ± 0.92 ng/mL) and immediately declined after birth (1.16 ± 0.48 ng/mL) (P=0.004). Plasma Gal-9 levels demonstrated negative correlation with HDL-C and LDL-C, and positive correlation with fasting plasma glucose and IRI.

Conclusions: Gal-9 deficiency promoted the development of GDM and Gal-9 may be involved in the maternal immune tolerance and suppression of the inflammatory process in placenta.

Disclosure

H.H. Albuayjan: None. R. Sugawara: None. Y. Oi: None. B. Yang: None. T. Tahara: None. A. Nakatsuka: Research Support; Mitsubishi Tanabe Pharma Corporation. Speaker's Bureau; Mitsubishi Tanabe Pharma Corporation, Novartis Pharmaceuticals Corporation, Novo Nordisk, Daiichi Sankyo, Kowa Company, Ltd., Otsuka Pharmaceutical. J. Eguchi: None. J. Wada: Research Support; Bayer Inc., Otsuka America Pharmaceutical, Inc., Kyowa Kirin Co., Ltd., Sumitomo Dainippon Pharma Co., Ltd., Mitsubishi Tanabe Pharma Corporation, Shionogi & Co., Ltd.
1219-P: Central Obesity, Independent of General Obesity, Is Associated with Risk of Gestational Diabetes and Postpartum Prediabetes or Diabetes
Authors: ZHU YEYI , CHEHAB RANA F. , CHEN LIWEI , NGO AMANDA , GREENBERG MARA , FERRARA ASSIAMIRA
Published: June 2024

General obesity measured by body mass index (BMI) is a major risk factor for gestational diabetes (GDM) and postpartum diabetes; however, the role of central obesity, assessed by waist-to-hip ratio (WHR) and waist circumference (WC), is understudied. We examined the prospective associations of general and central obesity with the risk of GDM and postpartum prediabetes or diabetes. Among 3,055 pregnant individuals in the prospective PETALS cohort, BMI was assessed preconceptionally and waist and hip circumference were measured at gestational weeks 10-13. Modified Poisson and Cox regression models assessed the risk of GDM (by Carpenter and Coustan criteria) and postpartum prediabetes or diabetes (by lab, diagnosis, and/or medication), respectively, in association with general obesity (BMI: Asian ≥27.5, non-Asian ≥30.0 kg/m2) and central obesity (WHR ≥0.85 or WC ≥88cm), adjusting for cofounders including continuous BMI. In total, 304 individuals developed GDM and 631 developed postpartum prediabetes or diabetes (mean ± SD follow-up: 4.3 ± 2.5 years). Compared to individuals without general and central obesity (by WHR), GDM risk increased by 1.91 (95% CI 1.10-3.31), 2.39 (1.67-3.43), and 2.69 (1.75-4.13)-fold for those with general obesity and without central obesity, without general obesity and with central obesity, and with both general and central obesity; postpartum prediabetes or diabetes risk increased by 1.70 (1.17-2.47), 1.45 (1.15-1.82), and 1.98 (1.44-2.72)-fold, respectively. Associations were strongest in Hispanic followed by Black individuals. Similar results were observed for central obesity by WC. Central obesity was a stronger risk factor for GDM than general obesity and exhibited incremental risk beyond general obesity for both GDM and postpartum prediabetes or diabetes. Clinicians should recognize the importance of screening for central obesity to identify pregnant individuals at higher risk of future dysglycemia.

Disclosure

Y. Zhu: None. R.F. Chehab: None. L. Chen: None. A. Ngo: None. M. Greenberg: None. A. Ferrara: None.

Funding

National Institute of Environmental Health Sciences (R01ES019196), National Heart, Lung, and Blood Institute (R01HL157666), National Institute on Minority Health and Health Disparities (R01MD018459), and Kaiser Permanente Center for Upstream Prevention of Adiposity and Diabetes Mellitus (UPSTREAM).
1220-P: Management of Insulin Needs during the Menstrual Cycle in Females with Type 1 Diabetes—A Preliminary Analysis of the GLYMETY Study
Authors: BONHOURE ANNE , YARDLEY JANE E. , BOUDREAU VALERIE , MESSIER VIRGINIE , NGUYEN ELISABETH , BRAZEAU ANNE-SOPHIE , RABASA-LHORET RÉMI P.R.
Published: June 2024

Introduction & Objective: In females living with T1D (FwT1D), the impact of the menstrual cycle on glucose fluctuations is not well known. Our aim is to examine the relationship between the menstrual cycle phases, glycemic fluctuations and insulin needs in FwT1D.

Methods: This is a preliminary analysis of observational data over 3 menstrual cycles in eumenorrheic FwT1D. The menstrual cycle was split into 3 phases: follicular, periovulatory, and luteal phases. Included participants (n=15) shared their CGM and daily insulin (total, basal and bolus) data. CGM data were used to calculate mean glucose, coefficient of variance (CV), and time below (TBR), in (TIR), and above (TAR) range. One-way repeated-measures ANOVAs with Bonferroni post-hoc tests were used to compare glycemia, glycemic variation and insulin doses across the 3 menstrual cycle phases.

Results: Of the 15 FwT1D, 14 (93%) did not use hormonal contraception. Participants were (mean ± SD) 37.2 ± 5.9 years old, with a BMI of 25.7 ± 4.6 kg/m2, an HbA1c of 6.5 ± 0.7%, and diabetes duration of 19.3 ± 10.6 years. Glycemic and insulinemic data across the 3 cycle phases can be found in Table 1.

Conclusion: In FwT1D, the luteal phase of the menstrual cycle is associated with higher glucose levels, more time spent in hyperglycemia, and greater insulin needs compared to the follicular and periovulatory phases.

Disclosure

A. Bonhoure: Consultant; Dexcom, Inc. J.E. Yardley: Speaker's Bureau; Dexcom, Inc. Research Support; LifeScan Diabetes Institute. V. Boudreau: None. V. Messier: None. E. Nguyen: None. A. Brazeau: Other Relationship; Dexcom, Inc. Research Support; Canadian Institutes of Health Research, Juvenile Diabetes Research Foundation (JDRF), Diabète québec, Fonds de recherche du Québec en Santé. R.P.R. Rabasa-Lhoret: Other Relationship; Abbott, AstraZeneca, Bayer Inc., Boehringer-Ingelheim, Dexcom, Inc. Research Support; Diabetes Canada. Other Relationship; Eli Lilly and Company. Research Support; Cystic Fibrosis Canada, Canadian Institutes of Health Research, FFRD - Fondation Francophone pour la Recherche du Diabète. Other Relationship; Janssen Pharmaceuticals, Inc. Research Support; Juvenile Diabetes Research Foundation (JDRF). Other Relationship; Novo Nordisk, GlaxoSmithKline plc. Consultant; HLS Therapeutics Inc., Insulet Corporation. Speaker's Bureau; CPD Networks. Other Relationship; Medtronic. Consultant; Pfizer Inc. Speaker's Bureau; Tandem Diabetes Care, Inc. Other Relationship; Sanofi. Speaker's Bureau; Vertex Pharmaceuticals Incorporated. Research Support; SFD - Société Francophone du Diabète.
1231-P: Decreased Complexity of Glucose Time Series Index Associated with Adverse Pregnancy Outcomes in Patients with Gestational Diabetes Mellitus—A Retrospective Cohort Study
Authors: LIANG GUILING , LAI MENGYU , WANG YAXIN , LU JINGYI , ZHOU JIAN , WANG YUFAN
Published: June 2024

Introduction & Objective: According to previous researches, the complexity of glucose time series index (CGI) may be a new indicator of glucose homeostasis. We aimed to investigate the relationship between the CGI during pregnancy and adverse pregnancy outcomes in gestational diabetes mellitus (GDM) patients.

Methods: In this retrospective cohort study, a total of 388 singleton-pregnant patients with GDM were recruited and underwent continuous glucose monitoring (CGM) at a median of 26.86 gestational weeks. The CGI was measured with refined composite multiscale entropy based on CGM data. Participants were categorized into tertiles according to CGI at baseline (CGI <2.32; CGI: 2.32-3.10; CGI ≥3.10). Logistic regression was used to assess the association of the CGI with composite adverse outcomes and large for gestational age (LGA). The CGI’s discrimination performance was estimated using receiver operating characteristic (ROC) analysis.

Results: Of the 388 GDM patients, 71 (18.3%) had LGA infants, and 63 (16.2%) had composite adverse outcomes. Compared to those with a high CGI (CGI ≥3.10), patients with a low CGI (CGI <2.32) had higher risks of composite adverse outcomes (OR: 9.87, 95% CI: 3.76-25.88) and LGA (OR: 11.92, 95% CI: 3.88-36.59) after adjusting for confounders. In ROC analysis, the CGI showed significantly better performance than the HbA1c level, time in range and coefficient of variation in predicting adverse pregnancy outcomes (all p < 0.05).

Conclusion: A lower CGI during pregnancy was associated with composite adverse outcomes and LGA. The CGI, a novel glucose homeostasis predictor, seems to be superior to conventional glucose indicators for predicting adverse pregnancy outcomes in GDM patients.

Disclosure

G. Liang: None. M. Lai: None. Y. Wang: None. J. Lu: None. J. Zhou: None. Y. Wang: None.

Funding

the National Key Research and Development Program of China (2021YFC2501600, 2021YFC2501601); the Shanghai Science and Technology Commission Foundation (No. 21Y11904800; No. 23ZR1451500).
1239-P: Utilizing Continuous Glucose Monitoring for Early Detection of Gestational Diabetes Mellitus in a Multiethnic Asian Population
Authors: LIM BETH , YANG QIAN , CHOOLANI MAHESH , GARDNER DAPHNE , SENG CHONG YAP , ZHANG CUILIN , CHAN SHIAO-YNG , LI LING-JUN
Published: June 2024

Introduction & Objective: Continuous Glucose Monitoring (CGM) proves reliable glycemic monitoring in subjects with gestational diabetes mellitus (GDM) during pregnancy. Therefore, we further explored the early GDM prediction potential of CGM in the first trimester.

Methods: We recruited 113 overweight or obese multi-ethnic Asian pregnant women (BMI ≥ 23 kg/m2) from a hospital-based, prospective cohort. Blinded CGM devices were worn for 10-14 days at gestation week 11-13 and universal GDM screening was performed at 24-28 week of gestation. EasyGV software was used to derive CGM parameters, including average glucose and glycemic variability parameters (e.g., liability index [LI], mean amplitude of glycemic excursions [MAGE], mean of daily differences [MODD], J-index, % in coefficient variability [% CV]) were assessed between GDM and non-GDM subjects. Forward stepwise logistic regression among 50 multiple imputation datasets identified parsimonious models for traditional risk factors and novel CGM parameters. We compared the predictive value of GDM using both sets of variables.

Results: Twenty-one GDM cases (18.6%) were ascertained using IADPSG criteria. Mothers with GDM had significantly higher values in mean glucose, time-above-range duration and all glycemic variability parameters mentioned above (all p<0.001). The novel CGM prediction Model (average glucose, LI & J-index) demonstrated better sensitivity (0.762 vs. 0.600), specificity (0.859 vs. 0.815), AUC (0.870 vs. 0.665), and superior R2 (0.332 vs. 0.058, p=0.021) for incident GDM prediction, compared with the traditional risk model (maternal age, baseline BMI & baseline systolic blood pressure).

Conclusion: Our pilot data suggested CGM's potential clinical utility in early pregnancy for predicting GDM, particularly in individuals at risk due to BMI concerns.

Disclosure

B. Lim: None. Q. Yang: None. M. Choolani: None. D. Gardner: None. Y. Chong: None. C. Zhang: None. S. Chan: Research Support; Nestlé Health Science. L. Li: None.

Funding

Singapore NMRC CSAINV/002/2021
1240-P: Effects of Maternal Body Mass Index and Gestational Weight Gain upon Pregnancy Outcomes in Women with Type 1 Diabetes—A Systematic Review and Meta-analysis
Authors: ATTA NOORIA , EZEOKE ANULI , KUSINSKI LAURA C. , MEEK CLAIRE L.
Published: June 2024

Pregnant women with type 1 diabetes have a higher risk of perinatal complications. Maternal hyperglycaemia is a key modifiable risk factor for perinatal complications, but it is unclear if maternal body mass index (BMI) and excessive gestational weight gain (GWG) also contribute to the risk in this population.

Objective: We assessed the association of maternal BMI and GWG with perinatal complications in women with type 1 diabetes.

Research Design and Methods: We searched MEDLINE, Embase, Scopus, Web of Science, and Cochran databases to identify studies examining the association between periconception BMI and GWG and perinatal complications (defined by a core outcome set) in women with type 1 diabetes and conducted random effects meta-analyses.

Results: We screened 209 studies and included 24 studies (11,655 pregnancies which occurred between 1978 and 2019) in the meta-analyses. Periconception BMI and excessive GWG were associated with increased odds of perinatal complications overall (OR 1.06, 95%CI 1.03-1.10 and OR 1.35, 95%CI 1.21-1.51 respectively). BMI was associated with preeclampsia (OR 1.27, 95%CI 1.11-1.45), macrosomia (OR 1.06, 95%CI 1.02-1.11), Neonatal-Intensive-Care-Unit (NICU) admission (OR 1.08, 95%CI 1.03-1.13) and congenital malformation (OR 1.22, 95%CI 1.02-1.47). Excessive GWG was associated with an increased risk of preeclampsia (OR 1.10, 95%CI 1.04-1.16), Caesarean delivery (OR 1.70, 95%CI 1.28-2.25), large-for-gestational-age (OR 1.74, 95%CI 1.38-2.18) and macrosomia (OR 1.87, 95%CI 1.26-2.79).

Conclusions: Maternal BMI and GWG are modifiable determinants of perinatal complications in type 1 diabetes. Addressing maternal BMI pre-pregnancy and preventing excessive GWG should be key clinical priorities in women with type 1 diabetes.

Disclosure

N. Atta: None. A. Ezeoke: None. L.C. Kusinski: None. C.L. Meek: Research Support; Dexcom, Inc.
1243-P: Continuous Glucose Monitoring Metrics in Gestational Diabetes—Relationship with Neonatal Outcomes and Postpartum Glucose Metabolism
Authors: ELKIND-HIRSCH KAREN , ARMATTA MISSY , VEILLON EDWARD , SCHIAVON SARA , CAPPON GIACOMO
Published: June 2024

Objective: Continuous glucose monitoring (CGM) has shown to improve maternal and neonatal outcomes in diabetic pregnancies. We investigated the use of CGM-derived metrics and normally monitored glucose measures in women with gestational diabetes (GDM) to study maternal and neonatal outcomes and postpartum glucose metabolism.

Methods: Sixty women with GDM were recruited prior to scheduled labor induction or caesarean section (C-section). A blinded Dexcom G6 Pro CGM was used for 10 days, starting 1-3 days predelivery. A 75-g oral glucose tolerance test (OGTT) was administered at 6-24 weeks postpartum with a subset of participants (n=28) using an additional blinded CGM for 10 days.

Results: Thirty-three participants had a vaginal delivery, 13 an unplanned (primary)C-section and 14 a repeat C-section. Infants of women having either an induction (25/33; 75.8%) or primary C-section (10/13;76.9%) were significantly more likely than repeat C-section-(4/14; 28.6%) to have neonatal hypoglycemia (χ²test= 10.7; p=0.005). Mothers treated with medication during pregnancy had a higher rate of large for gestational age (LGA) neonates and neonatal hypoglycemia (28/39; 72%) compared to diet alone (11/21; 52%) (p=.048). No direct association was demonstrated between the CGM-derived metrics prior to delivery and the postnatal glucose adaptation in the newborn. While there was only a slight positive relationship of mean glucose and glycemic variability in early postdelivery and postpartum OGTT values, there were strong linear associations of postpartum OGTT-derived estimates (mean OGTT) and postpartum CGM metrics (MBG r=.72, P<0.001; TITR r=-.74, p <0.001; MAGE r=.82 p<0.001).

Conclusion: GDM is associated with adverse pregnancy outcomes, including LGA and neonatal hypoglycemia. Further larger studies are needed to assess pre- and postpartum CGM metrics and their relationship with delivery in women with GDM, neonatal outcomes, and OGTT.

Disclosure

K. Elkind-Hirsch: Research Support; Novo Nordisk A/S, Dexcom, Inc. Consultant; Dexcom, Inc. Advisory Panel; Lilly Diabetes. M. Armatta: None. E. Veillon: None. S. Schiavon: None. G. Cappon: None.

Funding

Dexcom, Inc. (IIS-2021-120)
1250-P: Racial and Ethnic Disparities Associated with Diabetes and Pregnancy in a Large Health Care System
Authors: LANE RASHON , FARROKHI FARNOOSH , GUO YIAN , SCOTT ALEXANDRA , KERR DAVID
Published: June 2024

Introduction: In the United States, healthcare and social inequities produce disproportionate diabetes rates for racial and ethnic minoritized groups, including gestational diabetes (GDM). Addressing risk factors for GDM could help mitigate and improve maternal and neonatal health disparities. This study aims to compare differences in established risk factors associated with GDM and adverse maternal and fetal outcomes during pregnancy among different racial and ethnic groups.

Methods: Clinical and demographic data of pregnant women with diabetes who gave birth at Sutter Health - a large, integrated health delivery system in Northern California, were stratified (using ICD-10 codes) by diabetes diagnosis and race/ethnicity.

Results: A total of 11,916 deliveries between 1/1/2021 and 8/31/2023 were associated with diabetes; 25% were White, 26% Asian, 35% Hispanic/Latino, 4.7% Black African American (BAA), 1.1% American Indian, Alaskan Native, Native Hawaiian/other Pacific Islander (AIAN/NHOPI). AIAN/NHOPI and BAA had higher preconception BMI, higher rates of hypertension and higher average HbA1c in the first and third trimesters (Table).

Conclusion: Pre-existing risk factors and diabetes during pregnancy vary by race and ethnicity. Culturally tailored and appropriate policies and interventions are needed to reduce health disparities and improve maternal and fetal outcomes.

Disclosure

R. Lane: None. F. Farrokhi: None. Y. Guo: None. A. Scott: None. D. Kerr: Advisory Panel; Abbott Diagnostics. Consultant; Sanofi, Better Therapeutics, Inc. Stock/Shareholder; Glooko, Inc.
1253-P: Differential Risk of Dementia in Older Adults with Diabetes by Race/Ethnicity, Gender, and Age—Health and Retirement Study 1992–2020
Authors: DAWSON APRILL Z. , EGEDE LEONARD E.
Published: June 2024

While it is known that adults with diabetes have two times the risk of developing dementia compared to adults without diabetes, it is unknown whether the risk differs by race/ethnicity, gender, and age amongst older adults with diabetes. The aim of this analysis was to determine the risk of developing dementia in older adults with diabetes and to determine whether the risk differs by race/ethnicity, gender, and age. Data from the Health and Retirement Study(1992-2020) Harmonized Cognitive Assessment Protocol participants aged 50 and older were used (n=3496). Time to dementia was the dependent variable. The primary independent variable was diabetes (yes/no). Covariates included race/ethnicity, gender, age, education, employment, metropolitan statistical area, and region. Unadjusted and fully adjusted Cox proportional hazards models were run. Interactions between diabetes and race/ethnicity, gender, and age were tested. Models with significant interactions were stratified. Analyses were conducted using Stata v17.0, and statistical significance was p-value<0.05.In unadjusted models, older adults with diabetes had 24% increased risk of developing dementia (HR 1.24; 95%CI 1.03,1.50) compared to those without diabetes. There was a significant interaction between diabetes and age. Fully adjusted, age stratified models showed adults with diabetes aged 50-64 (HR 1.73; 95%CI 1.01,2.95) and 65-74 years (HR 1.39; 95%CI: 1.02,1.88) had increased risk of developing dementia compared to those without diabetes; and there was no association for adults aged 75 and older. The effect of diabetes on dementia happens earlier in age, is more prominent in older adults aged 50 -74, and does not have an impact in older age groups (75 years and older). Targeted intervention is critical and may be more beneficial in older adults aged 50-74, and there is need for early recognition of cognitive decline in this population to mitigate adverse outcomes.

Disclosure

A.Z. Dawson: None. L.E. Egede: None.

Funding

American Diabetes Association (11-22-JDFHD-01); NIDDDK (1R21DK135965-01, PI:Dawson; R01DK118038, R01DK120861; PI: Egede)NIMHD (R01MD013826, PI: Egede/Walker; R01MD018012, R01MD017574, PI: Egede/Linde)