American Diabetes Association Research Articles

Few studies have investigated blood glucose levels and complication management in elderly patients with type 2 diabetes (T2D) at community hospitals in China. The objective of this study was to investigate the factors influencing blood glucose control in elderly patients with T2D. One thousand one hundred and fifty elderly patients (age ≥ 65 years) with T2D were involved in the study to assess blood glucose control, health status (including comorbidities and cognitive status), complication management, and adherence to medication according to the guidelines of the American Diabetes Association. The FRAIL scale was used to screen for frailty syndrome in the elderly patients. Univariate and multivariate logistic regression analyses were used to investigate the factors affecting glucose control. Among the 1150 participants, 351 (30.52%) had poor glucose control. Frailty (odds ratio [OR]:2.546; 95% confidence interval [CI]: 1.267-5.117; p = 0.009), male sex (OR:0.679; 95% CI: 0.522-0.884; p = 0.004), and insulin treatment (OR: 0.229; 95% CI: 0.165-0.317; p < 0.001) were significantly independently associated with poor blood glucose control. In conclusion, for elderly patients with T2D, more attention should be paid to men, insulin therapy initiation and screening for frailty.

The study for designing an Indian menu-based equivalent of the Mediterranean diet, tailored to the context of heart failure in diabetes, was planned in the situation of, menu formulations or any formulating guidelines for a situationally suitable native diet for Indian diabetic adults in heart failure remained hypothetical, since 2010. The parameters determining situational suitability were bulkiness (that is, less bulky food for less flatulence and lesser bowel movements, in bed ridden patients) and reasonable adequacies in calories, macro and micronutrients. So, the first objective of the work was to design a menu for a less bulky but reasonably nutritious diet of 1550.00 Calories for diabetic persons in rest for heart failure (HF) calorically similar to the known diet models with carbohydrate derived energy limited to 50.00% (the Traditional Mediterranean diet or the American Diabetes Association diet for diabetic persons) and fat limited to 30.00g, using Indian native food items. The second objective was, to demonstrate deriving dietary fat according to the classic consumption recommendations, to consume saturated, monounsaturated, and poly unsaturated fats in equal amounts, keeping the ratio between the omega 6 type and omega 3 type fatty acids (the ‘omega ratio’) as 4:1 (balanced fat), from the items of the menu. The essential methodology for total calorie calculation was, mathematically combining the calorie provision pattern of the known diabetic diet models with 50.00% energy from carbohydrate and the recommendation in classic text books to reduce the fat consumption to 30.00g, while resting with HF. The methodology for constituting the menu was plotting a table with less bulky but nutritively denser food items in columns and their nutritive values in rows, selected from a panel of 592 local food items. With a few repetitions of tabulation involving permutations and combinations of certain local food items, a model was evolved with 15 of them, satisfying both the objectives. Both the methodology of formulation and its interim evaluation tables are, essential guiding gridworks for preparation and assessment of other metabolically targeted diets also. Since being a derivative of already well accepted models just substituted with some nutritionally equivalent native food items, the clinical evaluation of the formulation will be quite simpler too. The socio-economic significance of the menu combination is its highly predictable acceptability due to the compositional familiarity and lighter budgetary load, to the Indian population (traditional food items in near traditional quantities, on minimum expense).

Type 2 diabetes mellitus (T2DM)is a worldwide issue, stemming from multiple factors, primarily environmental and lifestyle habits. New medications are constantly emerging due to the chronic nature of the disease and its impact on various organ systems. The competitive market requires primary health care center (PHCC) physicians to use accurate doses, treatment durations, and novel medication practices to benefit their patients. This study aims to assess Qassim PHCC physicians' knowledge of a new class of T2DM medication. A cross-sectional study was conducted among 230 PHCC physicians using a semi-structured self-administered questionnaire, and 191 responded. A simple random method was applied to select 11 governorates from Qassim province. Then, the self-administered questionnaire link was distributed through WhatsApp, and direct messages were sent in a convenient manner to each governorate supervisor and PHCC physician. Data analysis was performed using Statistical Program for Social Sciences (SPSS) version 21 (IBM Corp., Armonk, NY), and the chi-square test was applied for categorical analysis. The study revealed that the mean age of Qassim PHCC physicians was 33.66±7.6 years, with 72.3% aged 25-35 years. Males comprised 62.3% of the group, and professional classifications included 22.5% general physicians (GPs), 33.5% family medicine (FM) residents, 28.3% FM specialists, and 15.7% FM consultants. While 88% encountered type 2 diabetes daily, only 36.1% received continued medical education (CME) training on novel medications. Awareness of glucagon-like peptide-1 receptor agonists (GLP-1 RAs) (94.8%), dipeptidyl peptidase-4 inhibitors (DPP-4is) (83.8%), and sodium-glucose co-transporter-2 inhibitors (SGLT-2is) (86.9%) was high, yet American Diabetes Association (ADA) guideline familiarity varied, significantly higher among FM specialists and consultants. GLP-1 RAs were linked to the greatest glycated hemoglobin (HbA1c) reduction (2.07% ± 0.92), while SGLT-2i and DPP-4i followed with 1.53% ± 0.78 and 1.25% ± 1.01 reductions, respectively. Most physicians (92.7%) recognize the cardiovascular benefits of GLP-1 RAs, but educational needs are required. There are significant awareness disparities between professional roles (FM specialist and FM consultant versus GP and FM residents) and with all three novel medications (p<0.05). The study highlights significant gaps in CME among Qassim PHCC physicians, with only 36.1% trained in novel diabetes medications despite daily encounters with patients with T2DM. While awareness of GLP-1 RAs and other medications was high, variations in ADA guideline familiarity indicate a need for role-specific educational interventions. Physicians acknowledged GLP-1 RAs' superior HbA1c reduction and cardiovascular benefits. Policymakers should prioritize targeted CME programs, enhance access to updated guidelines, and promote tailored training to bridge knowledge and practice gaps.

Introduction and Objective: In SOUL (NCT03914326), oral semaglutide (sema) 14 mg QD, a GLP-1 receptor agonist, reduced major adverse cardiovascular (CV) event (MACE) risk by 14%. GLP-1RAs are routinely prescribed to reduce A1c and BMI in type 2 diabetes (T2D). Whether the CV benefits of oral sema are influenced by baseline A1c or BMI is not fully known. Methods: SOUL’s primary outcome was time to first MACE, assessed for this post hoc analysis by baseline A1c, BMI and body weight using Cox regression. Results: People with T2D (n=9650; A1c 6.5–10%) and known atherosclerotic CV disease (ASCVD) or chronic kidney disease (CKD) were randomized to oral sema or placebo and followed for a mean of 47.5 months. We found significant differences in MACE outcomes associated with oral sema use by baseline A1c, with greater effects apparent with A1c &amp;gt;8.0% (Fig.). When the data were further analyzed across four A1c strata, the MACE benefit from oral sema appeared to apply to those with A1c &amp;gt;7%. The effects of oral sema on MACE were the same in those with BMI above / below 30 kg/m2, as well as across all four BMI strata, and above / below the mean body weight (87.9 kg) (Fig.). Conclusion: In SOUL, the CV benefits of oral sema appeared more pronounced with higher A1c levels at baseline but were consistent across various BMI categories. These data may help inform the individualized use of oral sema in people with T2D and ASCVD and/or CKD. Disclosure S.E. Inzucchi: Consultant; Novo Nordisk, AstraZeneca, Boehringer-Ingelheim, Merck &amp; Co., Inc, Pfizer Inc, Bayer Pharmaceuticals, Inc. R. Abdul Ghani: None. J. Deanfield: Other Relationship; Aegerion Pharmaceuticals, Amgen Inc, AstraZeneca, Bayer Pharmaceuticals, Inc, Boehringer-Ingelheim, Merck &amp; Co., Inc, Novartis Pharmaceuticals Corporation, Novo Nordisk A/S, Novo Nordisk A/S, Pfizer Inc. M.D.M. Engelmann: Employee; Novo Nordisk. G. Hovingh: Employee; Novo Nordisk. Stock/Shareholder; Novo Nordisk. O.K. Jeppesen: None. M. Kellerer: Advisory Panel; Abbott, Bayer Pharmaceuticals, Inc. Speaker's Bureau; Boehringer-Ingelheim, Johnson &amp; Johnson Medical Devices Companies. Advisory Panel; Lilly Diabetes. Speaker's Bureau; Lilly Diabetes. Advisory Panel; Novo Nordisk. Speaker's Bureau; Novo Nordisk. Advisory Panel; Sanofi. K. Mandavya: Employee; Novo Nordisk. J.F. Mann: Other Relationship; AstraZeneca, Bayer Pharmaceuticals, Inc. Advisory Panel; Novo Nordisk. Board Member; AstraZeneca, Bayer Pharmaceuticals, Inc, Boehringer-Ingelheim, Novo Nordisk. Other Relationship; Sanofi. Consultant; AstraZeneca, Bayer Pharmaceuticals, Inc, Novo Nordisk. Research Support; AstraZeneca. Other Relationship; Boehringer-Ingelheim. Research Support; Novo Nordisk, Sanofi. Speaker's Bureau; AstraZeneca, Bayer Pharmaceuticals, Inc, Novo Nordisk, Novartis AG. Other Relationship; UpToDate Inc / KDIGO. N. Marx: Speaker's Bureau; Abbott, Amgen Inc, AstraZeneca. Advisory Panel; AstraZeneca. Speaker's Bureau; Bayer Pharmaceuticals, Inc. Advisory Panel; Bayer Pharmaceuticals, Inc. Speaker's Bureau; Boehringer-Ingelheim. Advisory Panel; Boehringer-Ingelheim. Speaker's Bureau; Daiichi Sankyo. Advisory Panel; Merck Sharp &amp; Dohme Corp. Speaker's Bureau; Novo Nordisk. Advisory Panel; Novo Nordisk. Speaker's Bureau; Sanofi. Advisory Panel; Sanofi. Speaker's Bureau; Lilly Diabetes. C. Mathieu: Advisory Panel; Novo Nordisk, Sanofi, Eli Lilly and Company, Abbott, Medtronic, SAB Biotherapeutics, Inc, Roche Diabetes Care, Vertex Pharmaceuticals Incorporated, Biomea Fusion, Bayer Pharmaceuticals, Inc. D.K. McGuire: Consultant; Novo Nordisk. Advisory Panel; Novo Nordisk. Consultant; Lilly USA LLC. Advisory Panel; Lilly USA LLC. Consultant; Boehringer-Ingelheim. Advisory Panel; Boehringer-Ingelheim, AstraZeneca, ESPERION Therapeutics, Inc., NewAmsterdam Pharma, Pfizer Inc. Consultant; Applied Therapeutics, Lexicon Pharmaceuticals, Inc, Bayer Pharmaceuticals, Inc, Amgen Inc, Kailera, Idorsia, Alveus, Metsera. V. Mohan: Speaker's Bureau; Novo Nordisk. Advisory Panel; Abbott. Research Support; Servier Laboratories. Speaker's Bureau; USV Private Limited, Sanofi, Medtronic, Eli Lilly and Company. S.L. Mulvagh: Advisory Panel; Novo Nordisk, Merck &amp; Co., Inc. R. Pop-Busui: Board Member; American Diabetes Association. Consultant; Averitas Pharma, Inc. Research Support; Bayer Pharmaceuticals, Inc. Other Relationship; Biogen. Research Support; Juvenile Diabetes Research Foundation (JDRF). Advisory Panel; Lexicon Pharmaceuticals, Inc, Novo Nordisk. Research Support; Novo Nordisk, National Institute of Diabetes and Digestive and Kidney Diseases. Consultant; Roche Diagnostics. N.R. Poulter: Consultant; Servier Laboratories, Alnylam Pharmaceuticals, Inc. Research Support; Servier Laboratories. Speaker's Bureau; AstraZeneca. Consultant; Aktiia. M. Ripa: Employee; Novo Nordisk. G. Roman: Advisory Panel; AstraZeneca. Consultant; Berlin-Chemie AG. Research Support; AstraZeneca. Advisory Panel; Boehringer-Ingelheim, Medtronic, Lilly Diabetes, Novo Nordisk. Research Support; Novo Nordisk. Advisory Panel; Roche Diabetes Care, Sanofi, Viatris Inc. R. Sánchez García: None. M. Shechter: None. J.B. Buse: Other Relationship; Corcept Therapeutics, Dexcom, Inc., Novo Nordisk. Consultant; Altimmune Inc, Amgen Inc, ApStem, Aqua Medical, AstraZeneca, Boehringer-Ingelheim, CeQur, Eli Lilly and Company, embecta, GentiBio. Other Relationship; Glyscend Therapeutics. Consultant; Insulet Corporation, Medtronic. Other Relationship; Mellitus Health. Consultant; Metsera. Other Relationship; Pendulum Therapeutics, Praetego, Stability Health. Consultant; Tandem Diabetes Care, Inc, TERNS Pharmaceuticals, Vertex Pharmaceuticals Incorporated, Zealand Pharma A/S. Funding Novo Nordisk A/S

Introduction and Objective: Painful diabetic peripheral neuropathy (pDPN) is a debilitating condition that worsens quality of life. Mixed methods allow for a deeper exploration of the lived experience of pDPN. Methods: A convenience sample of adults with T1D and pDPN were enrolled. Participants completed a 7 day ecological momentary assessment (EMA) bedtime diary to assess the following pain domains: symptoms, interference, self-efficacy, social support, and relief. Participants were also asked to upload a digital photograph (photo) and caption representing their pDPN experience for that day. Follow-up semi-structured interviews explored the daily pain experience and were analyzed using inductive thematic analysis. EMA and qualitative data were merged to summarize each participant’s pDPN experience. Results: Six participants (67% female, mean age 54 years (SD 8.5), 50% with comorbid depression) completed this study. The EMA response rate was 83.3% and photo upload rate was 80.1%. EMA, interview and photo data showed heterogeneity in pDPN experience, as shown for Participant 2 in Figure 1. Interviews highlighted participants’ fear of developing complications of pDPN. Conclusion: In this study, mixed methods allowed for a personal portrayal of the lived experience of pPDN in T1D. Further studies are needed to better understand how to support the psychosocial needs of patients with pPDN. Disclosure K. Kinger: None. M. DeJonckheere: None. Y. Huang: None. L. Ang: None. C. Martin: None. D. Albright: None. E.L. Reynolds: Employee; Michigan State University, University of Michigan. Research Support; National Institutes of Health, Juvenile Diabetes Research Foundation (JDRF). Other Relationship; American Diabetes Association, Ohio State University. B.C. Callaghan: None. E. Hirschfeld: None. J.J. Iyengar: None. H. Centola: None. J.M. Lee: Advisory Panel; GoodRx. R. Pop-Busui: Board Member; American Diabetes Association. Consultant; Averitas Pharma, Inc. Research Support; Bayer Pharmaceuticals, Inc. Other Relationship; Biogen. Research Support; Juvenile Diabetes Research Foundation (JDRF). Advisory Panel; Lexicon Pharmaceuticals, Inc, Novo Nordisk. Research Support; Novo Nordisk, National Institute of Diabetes and Digestive and Kidney Diseases. Consultant; Roche Diagnostics. K.R. Mizokami-Stout: None. Funding Breakthrough T1D and University of Michigan's Center of Diabetes Excellence; NIDDK (K23DK13129601A13, K01DK134766)

Introduction and Objective: Glucagon-like peptide-1 receptor agonist (GLP-1RA) agents have demonstrated cardiovascular disease (CVD) benefits in adults with type 2 diabetes (T2D) at high and moderate CVD risk. However, their head-to-head comparative risk of cardiovascular outcomes is unknown. Methods: We conducted a clinical trial emulation comparing CVD outcomes between patients treated with four GLP-1RAs. Using medical and pharmacy claims data from commercial, Medicare Advantage, and traditional Medicare plans between 2019-2021 for adults ≥21 years with T2D and moderate CVD risk (estimated 1-5% annualized risk of a major cardiovascular event [MACE: myocardial infarction, stroke, or death]) who initiated dulaglutide, exenatide, liraglutide, or semaglutide, we used propensity score inverse probability of treatment weighted Cox proportional hazards models to compare the hazard of MACE, expanded MACE (MACE plus heart failure hospitalization or arterial revascularization), each component of expanded MACE, and hospital/emergency department visits for hypoglycemia. Results: We identified 36,656 patients initiating dulaglutide (mean age 64.5 ± 8.5 years, 46.8% male), 4,530 initiating exenatide (64.7 ± 8.2 years, 47.3% male), 9,794 initiating liraglutide (64.7 ± 8.3 years, 45.4% male), and 34,163 initiating semaglutide (64.4 ± 8.5 years, 46.6% male). Compared to dulaglutide, semaglutide was associated with lower hazard of MACE (HR 0.86, 95% CI 0.80-0.94), expanded MACE (HR 0.92, 95% CI 0.88-0.97), death (HR 0.84, 95% CI 0.74-0.94), stroke (HR 0.84, 95% CI 0.72-0.99), and arterial revascularization (HR 0.93, 95% CI 0.88-0.99). Liraglutide was associated with a lower hazard of death when compared to dulaglutide (HR 0.77, 95% CI 0.63-0.95). Conclusion: Semaglutide may be the GLP-1RA associated with the greatest cardiovascular risk reduction in patients with T2D at moderate CVD risk. Disclosure S. Sklepinski: None. J. Herrin: None. K. Swarna: None. J.J. Neumiller: Advisory Panel; Proteomics International. R.J. Galindo: Consultant; Abbott, AstraZeneca. Advisory Panel; Bayer Pharmaceuticals, Inc, Boehringer-Ingelheim. Consultant; Dexcom, Inc., Eli Lilly and Company, Medtronic. Research Support; National Institute of Diabetes and Digestive and Kidney Diseases. Consultant; Novo Nordisk. Research Support; Novo Nordisk, Boehringer, Dexcom. G. Umpierrez: Research Support; Abbott, Dexcom, Inc., Bayer Pharmaceuticals, Inc, Corcept Therapeutics. Advisory Panel; Dexcom, Inc., GlyCare Health. J. Ross: Research Support; Janssen Pharmaceuticals, Inc. Y. Deng: None. E. Polley: None. B. Maron: Advisory Panel; Actelion. Research Support; Deerfield Corporation. Board Member; Tenax. Research Support; Montgomery County, Maryland,. R.G. McCoy: Consultant; Wolters Kluwer Health, Yale New Haven Health System. Research Support; American Diabetes Association. Other Relationship; American Diabetes Association. Funding PCORI Award (PCS-1409-24099)

Introduction and Objective: A recent trial of the Omnipod® 5 AID System showed improvement in glycemic outcomes following AID initiation in a cohort of adults with insulin-treated T2D. However, limited real-world data exist on AID use and bolus behaviors in this population. This analysis evaluated real-world outcomes with Omnipod 5 use in the management of T2D. Methods: A retrospective analysis of CGM and insulin data from Omnipod 5 users with T2D in the US aged ≥18y with sufficient CGM data (≥90 days of data, ≥75% of days with ≥220 readings) was conducted for those who self-reported baseline A1C and primarily used the 110 or 120 mg/dL targets. Outcomes were stratified by baseline A1C and bolus frequency. Results: A total of 12,327 users (median age 59y; prior therapy: 44% MDI) met inclusion criteria. Users had spent a median of one year on device at the time of analysis, with 94% of time in Automated Mode. Time in range (70-180 mg/dL) and glucose management indicator by baseline A1C and bolus frequency are shown in the Figure. Among these users, time &amp;lt;70 mg/dL was low (median 0.26%). Conclusion: These findings from a large-scale real-world dataset of long-term (~1 year) AID use are similar to those reported in the pivotal trial of Omnipod 5 in T2D and provide evidence that people with T2D requiring insulin can consistently use AID long-term and achieve glycemic benefits even with elevated baseline A1C. Disclosure S.M. Oser: Research Support; Abbott. Other Relationship; American Diabetes Association, Association of Diabetes Care &amp; Education Specialists. Advisory Panel; Ascensia Diabetes Care. Research Support; Dexcom, Inc., Insulet Corporation, Leona M. and Harry B. Helmsley Charitable Trust. Advisory Panel; National Committee for Quality Assurance. Consultant; Sequel Med Tech. A.L. Peters: Advisory Panel; Medscape. Consultant; Vertex Pharmaceuticals Incorporated. Research Support; Insulet Corporation, Abbott. Other Relationship; Omada Health. F.J. Pasquel: Consultant; Insulet Corporation. Research Support; Novo Nordisk, Dexcom, Inc., Ideal Medical Technologies, Tandem Diabetes Care, Inc, Insulet Corporation. Consultant; Dexcom, Inc. G. Aleppo: Consultant; Dexcom, Inc., Insulet Corporation. Research Support; Insulet Corporation, Fractyl Health, Inc., MannKind Corporation, Tandem Diabetes Care, Inc, WellDoc, EMMES, AbbVie Inc, Bayer Pharmaceuticals, Inc. E. Miller: Advisory Panel; Abbott, Abbott Diagnostics. Other Relationship; American Diabetes Association. Speaker's Bureau; Bayer Pharmaceuticals, Inc, Boehringer-Ingelheim, Corcept Therapeutics, Eli Lilly and Company. Advisory Panel; Insulet Corporation, embecta. Speaker's Bureau; Novo Nordisk. Research Support; Abbott. L.M. Huyett: Employee; Insulet Corporation. Stock/Shareholder; Insulet Corporation. K. Miller: Employee; Insulet Corporation. L. Conroy: Employee; Insulet Corporation. Stock/Shareholder; Insulet Corporation. J.J. Mendez: Employee; Insulet Corporation. Stock/Shareholder; Insulet Corporation. T.T. Ly: Employee; Insulet Corporation. Stock/Shareholder; Insulet Corporation. Funding This study was funded by Insulet Corporation.

Introduction and Objective: Prior work by the Michigan Collaborative for Type 2 Diabetes (MCT2D) demonstrated increased adherence to non-insulin guideline-directed medical therapy (NI-GDMT) for type 2 diabetes (T2D) over the past 4 years but insulin use remains unclear. We examined insulin use in MCT2D practices over this period. Methods: We analyzed pharmacy claims from 82,207 adults with T2D insured by Blue Cross Blue Shield Preferred Provider and Blue Care Network Health Maintenance Organizations and Medicare Advantage plans, receiving care in MCT2D-practices (01/2020-06/2024). Descriptive statistics examined trends in insulin use (no insulin, any, long/intermediate) by age and glycated hemoglobin (A1c). Linear regression assessed the significance of these trends (baseline group defined as &amp;lt;45 years old with A1c &amp;lt;7%). Results: Insulin use for T2D in Michigan has remained relatively steady across age and A1c categories despite increased NI-GDMT use (Figure 1). A significant positive trend was observed in individuals aged 45-64 with A1c of 8-9% not using insulin, with a stronger effect in those aged 65-74 (p=0.03 and p=0.01, respectively). Conclusion: This data suggests insulin use has remained steady despite increased NI-GDMT for T2D. A significant trend of individuals aged 45-74 with A1c of 8-9% not using insulin highlights the need to optimize treatment and ensure appropriate care for individuals with T2D. Disclosure K. Kinger: None. K.R. Mizokami-Stout: None. K. Watson: None. L. Ang: None. J.J. Iyengar: None. N. Bhomia: None. J. Reiss: None. J. Rau: None. L.A. Young: None. J. Weisensel: Stock/Shareholder; Senseonics. R. Pop-Busui: Board Member; American Diabetes Association. Consultant; Averitas Pharma, Inc. Research Support; Bayer Pharmaceuticals, Inc. Other Relationship; Biogen. Research Support; Juvenile Diabetes Research Foundation (JDRF). Advisory Panel; Lexicon Pharmaceuticals, Inc, Novo Nordisk. Research Support; Novo Nordisk, National Institute of Diabetes and Digestive and Kidney Diseases. Consultant; Roche Diagnostics. C.R. Richardson: Other Relationship; Dexcom, Inc., Duke clinical research, American Diabetes Association, Annals of Family Medicine. H.L. Diez: None. L. Oshman: Stock/Shareholder; Procter &amp; Gamble, Merck &amp; Co., Inc, AbbVie Inc. Funding NIDDK (K23DK13129601A1)

Introduction and Objective: Concerns have been raised about potentially harmful cancer-related effects of certain medications used to manage type 2 diabetes (T2D). However, there is limited evidence from head-to-head comparisons between commonly used second-line T2D medications with respect to incident cancer risk. Methods: In a retrospective target trial emulation, we compared glucagon-like peptide-1 receptor agonists (GLP-1RA), sodium-glucose cotransporter 2 inhibitors (SGLT2i), dipeptidyl peptidase-4 inhibitors (DPP4i), and sulfonylureas with respect to incident cancer risk among adults with T2D and moderate CVD risk. We used de-identified administrative claims from the OptumLabs Data Warehouse and the Medicare fee-for-service 100% sample to identify adults ≥21 years with T2D between 2014-2021 with an estimated 1-5% annualized risk of a major adverse cardiovascular event who initiated these drugs. We then compared rates of any incident cancer (excluding non-melanoma skin cancer) and each cancer type using propensity score inverse probability of treatment weighted Cox proportional hazards models. Results: We identified 40,956 patients starting GLP-1RA (mean age 65.1 ± 8.3 years, 51.1% male), 52,050 starting SGLT2i (mean age 65.1 ± 8.4 years, 50.6% male), 74,314 starting DPP4i (mean age 65.44 ± 8.5 years, 50.9% male), and 187,960 starting sulfonylurea (mean age 65.4 ± 8.5 years, 51.0% male). Treatment with GLP-1RA was associated with a 12% higher risk of incident cancer compared to SGLT2i (HR 1.12, 95% CI 1.04-1.22), 12% higher risk compared to DPP4i (HR 1.12, 95% CI 1.05-1.20), and 15% higher risk compared to sulfonylurea (HR 1.15, 95% CI 1.08-1.22). This increase in risk was driven primarily by higher incidence of melanoma, male reproductive, and female breast cancers. Conclusion: This increased risk of some cancers observed with GLP-1RA warrants further investigation and cautious use among individuals at risk for these malignancies. Disclosure S. Sklepinski: None. J. Herrin: None. K. Swarna: None. J.J. Neumiller: Advisory Panel; Proteomics International. R.J. Galindo: Consultant; Abbott, AstraZeneca. Advisory Panel; Bayer Pharmaceuticals, Inc, Boehringer-Ingelheim. Consultant; Dexcom, Inc., Eli Lilly and Company, Medtronic. Research Support; National Institute of Diabetes and Digestive and Kidney Diseases. Consultant; Novo Nordisk. Research Support; Novo Nordisk, Boehringer, Dexcom. G. Umpierrez: Research Support; Abbott, Dexcom, Inc., Bayer Pharmaceuticals, Inc, Corcept Therapeutics. Advisory Panel; Dexcom, Inc., GlyCare Health. J. Ross: Research Support; Janssen Pharmaceuticals, Inc. Y. Deng: None. E. Polley: None. M. Mickelson: None. R.G. McCoy: Consultant; Wolters Kluwer Health, Yale New Haven Health System. Research Support; American Diabetes Association. Other Relationship; American Diabetes Association. Funding PCORI Award (PCS-1409-24099)

Introduction and Objective: Poor glycemic control as assessed by glycated hemoglobin (A1c) is a strong risk factor for painful diabetic peripheral neuropathy (pDPN) in type 1 diabetes (T1D). However, the relationship between momentary glucose elevations and momentary increased neuropathic pain (NP) is unclear. In this study, glucose elevations prior to and following momentary NP was evaluated in T1D. Methods: Continuous glucose monitoring-derived (CGM) elevations prior to and following momentary NP symptoms were evaluated in 40 participants with T1D (62.5% with known pDPN, mean age 56 years (SD 14), 45% female, mean A1c 7.3% (SD 1.3)) who completed a 14-day ecological momentary assessment (EMA) battery of neuropathic and overall pain symptoms 4 times daily (morning, afternoon, evening, bedtime) while simultaneously wearing a personal CGM. Linear mixed models adjusted for age, sex, smoking, and 14-day mean glucose were used to evaluate inter- and intra-person associations between glucose elevations (defined as mean of the 4-hour glucose &amp;gt; mean of the 14-day CGM period) prior to and following EMA neuropathic and generalized pain prompts to determine if glucose elevations precede or follow elevations in pain (defined as momentary neuropathic or generalized pain scores &amp;gt;14-day mean). Results: Regression models revealed higher NP levels associated with subsequent CGM-derived glucose elevations (point estimate [PE]: 0.03 (95% CI 0.01-0.07)). In contrast, there were no associations between CGM-derived glucose elevations and subsequent momentary NP (PE: 0.07 (95% CI -0.02-0.17)). Similarly, there were no associations between CGM-derived glucose elevations and momentary generalized pain in either direction. Conclusion: This study suggests that, within T1D individuals, increased momentary NP precedes glucose elevations. Further studies are needed to understand the mechanisms linking NP to glucose elevations as well as whether pain reduction leads to improvements in momentary glucose. Disclosure K.R. Mizokami-Stout: None. M. Plegue: None. E. Hirschfeld: None. L. Ang: None. J.J. Iyengar: None. H. Centola: None. D. Albright: None. E.L. Reynolds: Employee; Michigan State University, University of Michigan. Research Support; National Institutes of Health, Juvenile Diabetes Research Foundation (JDRF). Other Relationship; American Diabetes Association, Ohio State University. B.C. Callaghan: None. R. Pop-Busui: Board Member; American Diabetes Association. Consultant; Averitas Pharma, Inc. Research Support; Bayer Pharmaceuticals, Inc. Other Relationship; Biogen. Research Support; Juvenile Diabetes Research Foundation (JDRF). Advisory Panel; Lexicon Pharmaceuticals, Inc, Novo Nordisk. Research Support; Novo Nordisk, National Institute of Diabetes and Digestive and Kidney Diseases. Consultant; Roche Diagnostics. J.M. Lee: Advisory Panel; GoodRx. Funding Breakthrough T1D; University of Michigan's Center of Diabetes Excellence; NIDDK (1K23DK13129601A1)

Introduction and Objective: Pancreatitis and pancreatic cancer are important causes of morbidity and mortality, particularly in people with type 2 diabetes (T2D). Evidence of potential adverse pancreatic events with glucagon-like peptide-1 receptor agonists (GLP-1RAs) and dipeptidyl peptidase-4 inhibitors (DPP-4is) has been mixed and has not included comparison to other commonly used glucose-lowering medications other than metformin. Methods: We emulated an idealized trial using de-identified administrative claims data from OptumLabs Data Warehouse and the Medicare fee-for-service 100% sample to estimate the comparative risks of incident acute pancreatitis and pancreatic cancer among adults with T2D and moderate cardiovascular risk. Propensity score inverse probability of treatment weighting was used to emulate treatment assignment to GLP-1RA, DPP4i, sodium-glucose cotransporter 2 inhibitor (SGLT2i), or sulfonylurea. Results: The weighted study cohort included 388,262 patients starting either a DPP-4i inhibitor (N=82,079), a GLP-1RA (N=44,084), an SGLT2i (N=56,463), or a sulfonylurea (N=205,636). SGLT2i use was associated with lower risk of acute pancreatitis compared to DPP4i (HR 0.82; 95% CI 0.68-0.98), while sulfonylurea use was associated with higher risk compared to GLP-1RA (HR 1.28; 95% CI 1.03-1.56) and SGLT2i (HR 1.32; 95% CI 1.12-1.57). There was no association between GLP-1RA use and acute pancreatitis risk relative to DPP4i or SGLT2i. The risk of pancreatic cancer was lower with GLP-1RA compared to DPP4i (HR 0.56; 95% CI 0.40-0.77), and was higher with SGLT2i and with sulfonylurea when compared to GLP-1RA (HR 1.67; 95% CI 1.12-2.49 and HR 1.60; 95% CI 1.17-2.19, respectively). Conclusion: GLP-1RA therapy was not associated with increased risk of adverse pancreatic outcomes. The observed lower risk of acute pancreatitis in patients treated with SGLT2i requires further exploration. Disclosure U. Kalathiya: None. J. Herrin: None. K. Swarna: None. J.J. Neumiller: Advisory Panel; Proteomics International. R.J. Galindo: Consultant; Abbott, AstraZeneca. Advisory Panel; Bayer Pharmaceuticals, Inc, Boehringer-Ingelheim. Consultant; Dexcom, Inc., Eli Lilly and Company, Medtronic. Research Support; National Institute of Diabetes and Digestive and Kidney Diseases. Consultant; Novo Nordisk. Research Support; Novo Nordisk, Boehringer, Dexcom. G. Umpierrez: Research Support; Abbott, Dexcom, Inc., Bayer Pharmaceuticals, Inc, Corcept Therapeutics. Advisory Panel; Dexcom, Inc., GlyCare Health. J. Ross: Research Support; Janssen Pharmaceuticals, Inc. Y. Deng: None. E. Polley: None. M. Mickelson: None. R.G. McCoy: Consultant; Wolters Kluwer Health, Yale New Haven Health System. Research Support; American Diabetes Association. Other Relationship; American Diabetes Association. Funding Patient-Centered Outcomes Research Institute Award (PCS-1409-24099)

Introduction and Objective: Compare healthcare utilization between Medicaid and privately insured individuals with type 1 diabetes (T1D), type 2 diabetes (T2D) and without diabetes. Methods: Using a propensity score quasi-randomization technique, we matched persons with T1D, T2D, and without diabetes. Between 2014 and 2018, we determined healthcare utilization specific to diabetes related medications and supplies, outpatient providers visits, inpatient hospitalizations, and emergency department (ED) visits, stratified by diabetes status, age (0-20, 21-40 and 41-60 years), and insurance type (Medicaid vs. Private). Results: In 2018, compared to privately insured individuals, those covered by Medicaid had increased utilization of ED visits for T1D (0.38-0.43% vs. 0.06-0.2%) and T2D (0.32 - 0.42% vs. 0.08 - 0.2%). Inpatient hospitalizations were similar for both groups (T1D: 0.2 - 0.25% vs. 0.18 -0.21%, T2D: 0.08 - 0.22% vs. 0.13 - 0.19%). Medication utilization and overall visits to provider were lower in Medicaid. While difference in primary care provider visits were narrowing (T1D: 1.46 - 2.58 % vs. 2.24 - 2.97%, T2D: 1.45 - 2.75% vs. 2.02 - 3.33%), visits with specialists such as endocrinologists and cardiologists were lower in Medicaid. Conclusion: Medicaid patients have higher ED utilization without concomitant increases in hospitalizations, which may indicate suboptimal outpatient access in this population. Despite lower out of pocket costs compared to private insurance, medication and provider utilization in Medicaid is lower. While gaps in provider utilization are narrowing, Medicaid patients have lower specialist utilization. Further studies are needed to determine the effects of these differences on patient outcomes. Disclosure L. Muthukumar: None. E.L. Reynolds: Employee; Michigan State University, University of Michigan. Research Support; National Institutes of Health, Juvenile Diabetes Research Foundation (JDRF). Other Relationship; American Diabetes Association, Ohio State University. B.C. Callaghan: None. D. Albright: None. J.M. Lee: Advisory Panel; GoodRx. L. Ang: None. E.L. Feldman: None. K.R. Mizokami-Stout: None. R. Pop-Busui: Board Member; American Diabetes Association. Consultant; Averitas Pharma, Inc. Research Support; Bayer Pharmaceuticals, Inc. Other Relationship; Biogen. Research Support; Juvenile Diabetes Research Foundation (JDRF). Advisory Panel; Lexicon Pharmaceuticals, Inc, Novo Nordisk. Research Support; Novo Nordisk, National Institute of Diabetes and Digestive and Kidney Diseases. Consultant; Roche Diagnostics. Funding Dr. Reynolds is supported by the NIH NIDDK (R00DK129785). Dr. Pop-Busui is supported by NIH/NIDDK (1-R01-DK-107956-01; NIH U01DK119083, NIDDK/NHLBI 1UG3AT009150-01, and the Breakthrough T1D (5-COE-2019-861-S-B). Dr. Feldman is supported by NIH (R01DK129320, R01DK107956, R01DK13091)3 and the Breakthrough T1D (5-COE-2019-861-S-B). Dr. Callaghan is supported by NIH (R01DK115687) and the Breakthrough T1D.

Introduction and Objective: Continuous glucose monitoring (CGM) improves glycemic control and quality of life in insulin-using type 2 diabetes (IU-T2D) but is underutilized in primary care (PC). The objective of this study was to identify multilevel perspectives on determinants of CGM use for IU-T2D in PC. Methods: Semi-structured interviews were conducted with a purposeful sample of individuals with IU-T2D, PC clinic staff, PC clinicians and health system leaders (HSL) at a major academic medical center in Michigan, as well as convenience sample of major insurance payers in Michigan. Deductive thematic analysis was performed to determine key barriers and facilitators across levels. Results: Twenty-five interviews were completed across groups. Key facilitators for CGM use included patient awareness, positive CGM attitudes and the availability of clinical pharmacy while key barriers included knowledge gaps, training gaps, and resource challenges as shown in Figure 1. Conclusion: Participants across groups agreed on the value of CGM for IU-T2D. Utilization was facilitated by the availability of clinical pharmacists, while knowledge gaps and operational challenges prohibited implementation in many PC settings. Evidence-based strategies for overcoming knowledge gap barriers (such as collaborative care models, care manager models, and facilitation) may increase adoption of CGM for IU-T2D in PC. Disclosure A. Voleti: None. D. Hall: None. M. DeJonckheere: None. L. Ang: None. C.R. Richardson: Other Relationship; Dexcom, Inc., Duke clinical research, American Diabetes Association, Annals of Family Medicine. J.M. Lee: Advisory Panel; GoodRx. R. Pop-Busui: Board Member; American Diabetes Association. Consultant; Averitas Pharma, Inc. Research Support; Bayer Pharmaceuticals, Inc. Other Relationship; Biogen. Research Support; Juvenile Diabetes Research Foundation (JDRF). Advisory Panel; Lexicon Pharmaceuticals, Inc, Novo Nordisk. Research Support; Novo Nordisk, National Institute of Diabetes and Digestive and Kidney Diseases. Consultant; Roche Diagnostics. G. Piatt: None. K.R. Mizokami-Stout: None. Funding NIDDK (K23DK13129601A1, K01DK134766)

Introduction and Objective: Metabolic dysfunction-associated steatotic liver disease (MASLD) is the leading cause of chronic liver disease, and its prevalence in patients with T2DM is estimated to be over 60%. The American Diabetes Association (ADA) recommends that adults with T2DM with an indeterminate or high Fibrosis-4 (FIB-4) score should have additional risk stratification by liver stiffness measurement to detect liver disease early and prevent future liver complications, such as fibrosis and cirrhosis. Our study aims to describe the implementation of ADA recommended liver fibrosis screening in the primary care setting. Methods: This was a chart review of adults with T2DM from two primary care clinics within an academic medical center who were seen for a routine visit between 7/31/2023 to 12/31/2024. Adults diagnosed with hepatic steatosis, alcohol use disorder, or liver disease were excluded. Age, platelets, and liver function tests were collected to calculate FIB-4 score to estimate risk of liver fibrosis. Descriptive statistics were used to summarize patient demographics, clinical characteristics, and risk stratification. Results: A total of 751 patients were included in the analysis. The population was majority male (51.9%), White (74.2%), and Hispanic (62.3%). The mean age was 61 ± 12 years and 49.8% of patients had obesity. FIB-4 scores were unavailable for 52 (6.9%) patients due to missing labs. In those with calculable FIB-4 scores, 39.3% had indeterminate FIB-4 and 6.6% had high FIB-4. Therefore, a total of 45.9% of adults with calculable FIB-4 score and T2DM should undergo additional fibrosis screening by liver stiffness measurement based off ADA guidelines. Conclusion: This study emphasizes the importance of implementation of ADA recommended liver fibrosis screening in adults with T2DM and highlights the opportunity for early detection of liver disease in the primary care setting. Disclosure V. Nguyen: None. J. Rocco: None. T. Oberg: None. K. Gallegos Aragon: None. P.D. Deming: None. G. Ray: None.

Introduction and Objective: Continuous glucose monitoring (CGM) improves glycemia and is in ADA Standards of Care, but uptake is limited in primary care, where most diabetes care occurs. We compared 3 CGM implementation strategies in 76 Colorado primary care clinics. Methods: Hybrid type 3 effectiveness-implementation study of 3 CGM implementation strategies: online education using American Academy of Family Physicians Transformation in Practice Series (TIPS), TIPS + practice facilitation (PF), and a virtual CGM initiation service (virCIS). Relationships between outcomes (CGM prescriptions, A1C) and independent variables (time, clinic characteristics, participant demographics) were assessed via generalized linear mixed models. Results: Table 1 shows baseline characteristics. All strategies increased CGM prescribing (F(2,110)=48.2, p&amp;lt;.001); TIPS+PF and virCIS had greater increases than TIPS (F(4,110)=4.0, p=.005). All strategies decreased A1C (F(1,155)=32.3, p&amp;lt;.001), with no difference between strategies (p&amp;gt;.05). Conclusion: All 3 strategies increased CGM implementation and decreased A1C in primary care settings. These strategies could be applied in other primary care clinics. Wider uptake would increase CGM access beyond endocrinology and may improve outcomes for primary care patients with diabetes. Disclosure S.M. Oser: Research Support; Abbott. Other Relationship; American Diabetes Association, Association of Diabetes Care &amp; Education Specialists. Advisory Panel; Ascensia Diabetes Care. Research Support; Dexcom, Inc., Insulet Corporation, Leona M. and Harry B. Helmsley Charitable Trust. Advisory Panel; National Committee for Quality Assurance. Consultant; Sequel Med Tech. L. Dickinson: None. K.T. Wiggins: None. B. Jortberg: None. M. Gritz: None. S. Kirchner: None. T. Hall: None. W.P. Dickinson: None. T. Oser: Consultant; Dexcom, Inc. Research Support; Abbott, Insulet Corporation, Dexcom, Inc. Advisory Panel; Medscape. Funding Helmsley Charitable Trust (G-2204-05191)

Introduction and Objective: HbA1c reflects average blood glucose over a period determined by individuals’ MRBC. Adjusting HbA1c for MRBC variation could enable personalized diabetes management. Computational methods that estimate MRBC using CGM and HbA1c (CGM-MRBC) offer a cost-effective and time-efficient alternative to in-vivo measurements (SI-MRBC). However, the accuracy of CGM-MRBC compared to SI-MRBC has yet to be evaluated. Methods: We analyzed 63 individuals without hematological abnormalities who exhibited a discrepancy &amp;gt;±0.5% between HbA1c-based and CGM-based glycemic estimates. Individuals had multiple HbA1c measurements preceded by at least 2 weeks of CGM data. CGM-MRBC was inferred at each HbA1c measurement using the model in Malka et al. (2016) and averaged to minimize noise. SI-MRBC was obtained using oral15N-glycine heme labeling for all 63 subjects, and was repeated for 7 subjects whose average was considered. Results: Individuals had an average of 6±2 estimates of CGM-MRBC with a mean (SD) intra-patient coefficient of variation of 7 (3) % corresponding on average to ~3 days. In the population, CGM-MRBC was lower than SI-MRBC, with means (SD) of 47.4 (7.3) and 59.9 (6.5) days respectively (two-sided one-sample t-test p&amp;lt;0.0001). CGM-MRBC and SI-MRBC were correlated with an R2 [95% CI] of 0.52 [0.38, 0.68] (p&amp;lt;0.0001). Conclusion: Initial analysis suggests CGM-MRBC explains more than half of the variance in SI-MRBC and might provide an efficient means to personalize HbA1c interpretation in patient care. Further work on the computational model used to estimate CGM-MRBC is needed to improve its accuracy. Disclosure V. Tozzo: None. J. Craig: None. S.O. Omololu: None. M. Genco: None. E.P. Smith: None. D. Thibault: None. S. Arbabi: None. W. Abplanalp: None. C.T. Quinn: Advisory Panel; Disc Medicine. Consultant; NovoNordisk. Research Support; Emmaus Medical. C.J. Lindsell: Research Support; Biomeme, biomerieux. Other Relationship; Rocket Phrmaceuticals, Regeneron Pharmaceuticals. Stock/Shareholder; Bioscape Digital. Research Support; Cytokinetics. Consultant; PersistenceBio. Advisory Panel; AstraZeneca, Novo Nordisk, Novartis Pharmaceuticals Corporation. R.M. Bergenstal: Advisory Panel; Abbott. Research Support; Abbott. Consultant; Abbott. Research Support; Dexcom, Inc. Consultant; Dexcom, Inc., Eli Lilly and Company. Research Support; Eli Lilly and Company. Consultant; Novo Nordisk. Research Support; Novo Nordisk. Consultant; Roche Diabetes Care, Sanofi, Medtronic. Research Support; Medtronic, Insulet Corporation, Hemsley Charitable Trust. Other Relationship; MannKind Corporation. Consultant; Medscape. Research Support; National Institute of Diabetes and Digestive and Kidney Diseases, Tandem Diabetes Care, Inc, UnitedHealth Group. Consultant; Vertex Pharmaceuticals Incorporated, Ascensia Diabetes Care, American Diabetes Association, Hygieia, embecta, Senseonics, Zealand Pharma A/S. R.S. Franco: None. J. Higgins: None. R.M. Cohen: Research Support; Dexcom, Inc. Stock/Shareholder; Abbott. Research Support; National Institute of Diabetes and Digestive and Kidney Diseases. Funding National Institutes of Health R01 DK123330 (rmc); National Institutes of Health UL1 TR001425 (Center for Clinical &amp; Translational Science &amp; Training); Dexcom Corporation

Introduction and Objective: Extracellular vesicles (EVs) are small membrane-bound particles secreted by cells, playing a crucial role in intercellular communication and cellular homeostasis. Methods: Human EndoC βH1 beta cells were obtained from Human Cell Design. To assess impacts of EV transfer on recipient cells, small EVs from cells treated with or without a cytokine mix were isolated using ultracentrifugation and wild-type recipient EndoC βH1 cells were treated with 5x108 EVs from each group for 48 hours, followed by total and small RNA-sequencing. Data analysis was performed using Qiagen's Ingenuity Pathway Analysis (IPA). To fluorescently label EVs for quantification of transfer, EndoC βH1-CD81-mCherry and EndoC βH1-iRFP720 cells were generated by transfecting plasmids encoding CD81-mCherry and iRFP720 into EndoC βH1 cells. To assess impacts of proinflammatory cytokine treatment on EV transfer, cells were co-seeded on the same plate and after 48 hours of treatment with or without 5 ng/mL IL-1β, 100 ng/mL IFN-γ, CD81+ EV transfer to neighboring cells was assessed using flow cytometry quantification of mCherry+ iRFP720+ cells. Results: Treatment with EVs from cytokine-treated parent cells, yielded differential gene expression in recipient cells, marked by increased type I and type II interferon signaling, antigen presentation, macrophage classical activation signaling, and class I MHC-mediated antigen processing. Treatment of cocultured cells with cytokine mix significantly enhanced EV transfer, as evidenced by a 1.7-fold increase in mCherry+ iRFP720+ cells compared to controls (p&amp;lt;0.05). Conclusion: Inflammatory EVs exhibited altered mRNA and miRNA expression profiles, consistent with activation of interferon signaling and antigen presentation in recipient cells. Further, cytokine-exposure enhanced EV transfer to neighboring cells. These findings suggest that beta cell derived EVs may play a role in propagating and amplifying beta cell cytokine signaling. Disclosure J. Xu: None. E.K. Sims: Consultant; Sanofi. Speaker's Bureau; Med Learning Group. Other Relationship; American Diabetes Association.

Introduction and Objective: Evidence suggests that terminology and expressions used in healthcare environments contribute to the stigma associated with diabetes. The American Diabetes Association and the Association of Diabetes Care &amp; Education Specialists published guidance to help healthcare professionals minimize the use of diabetes-stigmatizing language in patient-provider interactions. We developed an intervention designed to reduce the use of diabetes-stigmatizing language among healthcare providers (HCPs) during patient-provider interactions. The intervention has three components: 1) an encounter with a standardized patient, 2) an educational video addressing diabetes-stigmatizing language, and 3) a self-reflection exercise focused on the standardized patient interaction. The objective was to pilot the intervention and assess its acceptability among HCPs. Methods: Participants (N=22) were randomly assigned to the intervention or control groups. Theory of Planned Behavior measures were collected pre- and post-intervention/control. T-tests were utilized to analyze within-group and between-group differences. Results: The intervention group demonstrated greater change in attitude scores, indicating more negative attitudes toward the use of diabetes-stigmatizing language compared to the control group (p&amp;lt;0.001). There was a trend toward greater change in intention scores to avoid the use of diabetes-stigmatizing language in the intervention group compared to the control group (p=0.13). The intervention group reported higher acceptability ratings for clarity (p&amp;lt;0.05), helpfulness (p&amp;lt;0.05), and likelihood of recommending the training (p&amp;lt;0.05), compared to the control group. Conclusion: This pilot study demonstrates the intervention’s acceptability and suggests its potential effectiveness in modifying HCP attitudes toward reducing the use of diabetes-stigmatizing language use in patient-provider interactions. Disclosure K. Joiner: None. A. Agapiou: None. A.G. Carmichael: None. H. Tarraf: None. B.P. Labbree: None. R. Gonzalez: None. Funding American Diabetes Association (CDTR-03)

Introduction and Objective: Latin American (LAm) populations are disproportionately affected by type 2 diabetes (T2D) but are underrepresented in genome-wide association studies (GWAS). Polygenic risk scores (PRS) constructed using European (EUR) GWAS exhibit limited predictive accuracy in other populations. We aim to improve the performance of a T2D PRS in individuals of LAm ancestry by increasing their representation in GWAS. Methods: We conducted the largest T2D GWAS meta-analysis for LAm individuals (N=207,055) using 17 datasets, including the Mexico City Prospective Study (N=125,042). We used this data to develop a new genome-wide LAm PRS and compare its performance with a previous PRS derived from a smaller LAm GWAS meta-analysis (N=82,013). We also combined the new LAm GWAS with those from four other ancestries (N=2,310,590, 9% LAm) to construct a multi-ancestry PRS. PRSs were evaluated in independent LAm cohorts (N=11,377). Results: The new LAm PRS, based on 200K LAm GWAS sample, showed a 30% increase in the proportion of variance explained by the additive genetic model (liability r2=7% vs. 5% in the previous LAm PRS). Compared with individuals in the interquartile range, those above the 95th percentile of the new LAm PRS had 3.4 times higher T2D odds (95% CI: 2.8-4.2). In contrast, the odds ratio for the same comparison using the previous LAm PRS was 1.8 (95% CI: 1.5-2.1). Integrating the LAm GWAS into a multi-ancestry PRS further improved the performance, explaining up to 16% of the variance (vs. 14% with a EUR PRS, GWAS N=1,486,934). Individuals above the 95th percentile of the multi-ancestry PRS distribution had a 6.7-fold higher T2D odds [95% CI: 5.3-8.4] compared to those in the interquartile range. Conclusion: This study demonstrates the improved predictive power of a T2D PRS achieved by a 60% increased sample size of an LAm GWAS and underscores the importance of further expanding the representation of LAm populations in genetic research. Disclosure A. Huerta: None. P. Baca Peynado: None. F. Rivas: None. M. Ng: None. R. Mandla: None. J. Kim: None. Y. Lu: None. J.E. Below: None. R. Tapia-Conyer: None. J. Berumen: None. J. Alegre-Diaz: None. J. Emberson: Research Support; Regeneron Pharmaceuticals, AstraZeneca. J.M. Torres: None. P. Kuri: None. J.M. Mercader: None. Funding NIDDK (UM1-DK078616); American Diabetes Association Innovative and Clinical Translational Award (1-19-ICTS-068); American Diabetes Association (11-22-ICTSPM-16); NHGRI (U01HG011723)

Introduction and Objective: The placenta provides nutrients for the growing fetus; however, when the mother has diabetes, the placenta does not function appropriately impacting fetal growth and development. Epigenetic mechanisms such as miRNA abundance appear to be important to placental function. The goal of the present investigation was to identify miRNA abundances altered by diabetes during pregnancy. Methods: Pregnant women, 40 control and 25 women with diabetes, presenting for elective caesarian section at term were recruited. The diagnosis of gestational diabetes or type 2 diabetes was based on the criteria by the American Diabetes Association. Women were excluded if they had type 1 diabetes, preeclampsia, or chronic hypertension. Placental samples were collected evenly around the circumference of the fetal side of the placenta and ground to a fine powder in liquid nitrogen before combining to make a representative specimen. RNA was extracted using miRNeasy kit. nCounter Human v3 miRNA Panel (NanoString Technologies) was used for miRNA profiling. Raw gene counts were normalized by log2 counts-per-million. Transformed data were fit to linear models using generalized least squares and a moderated t-statistic was computed using empirical Bayes methods. Results were considered significant if log2 fold change ± 0.5 and p-value &amp;lt;0.05. Results: The women with diabetes (DM) delivered on average 1 week earlier (38.5 weeks DM versus 39.2 in Control, p=0.0075). Maternal age, race/ethnicity, infant sex, and birth weight were not different. The BMI in the mothers with diabetes was higher (36.2 kg/m2 in DM versus 30.6 kg/m2 in control). miR-30c-5p and miR-372-3p were lower in abundance while miR-324-5p and miR-1323 were higher in abundance in the placental samples from the DM group compared to the control group. Conclusion: All four miRNA species have been associated with adverse outcomes in the mother and offspring, but specifically, miR-1323 has been demonstrated to be predictive of GDM in pregnancy. Further studies will elucidate the mechanisms underlying the miRNA changes. Disclosure W. Lee: None. B. Nelson: None. M. Onopiuk: None. A. Teague: None. S.J. Borengasser: None. J.B. Tryggestad: Research Support; Abbott. Other Relationship; Ascendis Pharma, Lilly Diabetes. Funding Harold Hamm Diabetes Center Team Science Grant