Introduction and Objective: The prevalence of obesity and diabetes amongst persons with hemoglobin S (HbS) is rising, however incongruencies between hemoglobin A1c (HbA1c) and other glycemic measures poses a challenge to accurately diagnosing diabetes in patients with sickle cell trait (SCT) or disease (SCD) at an early stage. Recent studies indicate that sickle cell variant rs334 is associated with higher HbA1c, and having concurrent HbS and diabetes increases one’s risk for developing diabetic complications. The objective of this work is to determine the mechanisms by which HbS impacts whole-body glucose homeostasis under obesogenic conditions, which are currently not well understood. Methods: We utilized the Townes transgenic mouse model of human SCD to assess the effect of HbS on glycemic regulation. Male mice with normal human hemoglobin (WT) or SCT or SCD were fed a high fat diet for a minimum of 14 weeks. Their glycemic phenotype (weight, ad libitum glucose, fasting glucose/insulin) was assessed every four weeks. Glucose and insulin tolerance testing, along with tissue analyses, were performed at 20 weeks of age. Results: SCD mice exhibit greater fasting blood glucose at all time points compared to WT and SCT mice, as well as significantly reduced fasting serum insulin at 20 weeks, suggestive of altered pancreatic beta cell function. Following a glucose and insulin load, SCT mice exhibit a greater glucose excursion and reduced insulin sensitivity, respectively, compared to both WT and SCD mice. WT and SCD mice had comparable insulin sensitivity and glucose utilization, which may be due to reduced weight trend in SCD mice as compared to WT and SCT mice. Conclusion: HbS may alter pancreatic beta cell function and peripheral insulin sensitivity under obesogenic conditions, promoting glycemic dysregulation and diabetes. Further analyses of pancreatic beta cell insulin dynamics as well as peripheral glucose disposal are warranted to hone in on potential biochemical pathways affected by HbS. Disclosure J. Zapater: None. N. Sweis: None. S. Nicholoff: None. B.T. Layden: None.

Introduction and Objective: Understanding diabetes heterogeneity across diverse populations is critical for advancing precision medicine. However, data on diabetes subphenotypes in South America remains limited. Here we analyze the distribution of Ahlqvist clusters among a nationally representative cohort of Chilean individuals with diabetes and their relation to chronic kidney disease (CKD). Methods: This cross-sectional analysis included 627 adults with diabetes mellitus from the Chilean National Health Survey (NHS) 2009-2010 and 2016-2017 with BMI 31 ± 6 kg/m2, HbA1c of 7.8 ± 2.2% and diabetes duration of 10 ± 10 years. They were assigned to the Mild Age-Related Diabetes (MARD), Mild Obesity-Related Diabetes (MOD), Severe Insulin-Resistant Diabetes (SIRD), and Severe Insulin-Deficient Diabetes (SIDD) clusters using the approach proposed by Bello-Chavolla et al., that relies on BMI, HDL, triglycerides, waist circumference, age at diagnosis and NHS, sex, glucose, and HbA1c. CKD markers (GFR and albumin-to-creatinine ratio, ACR) and self-reported complications (retinopathy, diabetic foot ulcers) were assessed. Results: Clusters were distributed as follows: MARD 24.2 %, MOD 31.6 %, SIRD 11.5 %, and SIDD 32.7 %. Both MARD and SIRD had lower GFR and higher rates of stage 3 CKD compared to MOD. SIDD exhibited the highest HbA1c and 2-5 times higher ACR (p < 0.01 vs. all other clusters). Rates of retinopathy and diabetic foot ulcers did not differ among clusters. In a subgroup with recent diagnosis (<3 years, n=193), SIDD represented a smaller proportion (15.5 %), but CKD marker disparities across clusters were consistent. Conclusion: SIDD accounts for a substantial segment of Chilean diabetes cases, characterized by poor glycemic control and markedly elevated proteinuria. This contrasts with findings from Caucasian cohorts where SIRD is tightly linked to CKD, underscoring the importance of population-specific data for developing equitable precision medicine strategies. Disclosure S. Gancheva: None. V. Serrano: None. G. Echeverría: None. A. Rigotti: Advisory Panel; Merck Sharp & Dohme Corp. Research Support; Merck Sharp & Dohme Corp. Funding This research used information from the Health Surveys for epidemiological surveillance of the Undersecretariat of Public Health. The author thanks the Ministry of Health of Chile for allowing him/her to use the database. All results obtained from the study or research are the responsibility of the author and do not in any way compromise said institution.

Introduction and Objective: We evaluated i) the accuracy of SiBio CKM and ii) continuous ketone levels during two ketogenic diets, in individuals with T1D on automated insulin delivery (AID). Methods: We compared the readings of the CKM on day 7 of wear age to capillary measurements by FreeStyle Libre 2 ketone meter in adults who underwent 8-hour inpatient insulin suspension experiments. We also assessed metrics of continuous ketone levels using the CKM on two 6-day ketogenic diets: very-low carbohydrate diet (<50 g/day) and intermittent 12-hour fasting in outpatient free-living settings. Results: During insulin suspensions, 181 paired data points were collected from 14 adults (10 female, mean age of 36.5 y, HbA1c 6.9%, insulin dose 0.72 units/kg). The overall mean absolute difference (MAD) between the CKM and capillary readings was 0.2 mmol/L and the relative MAD for ketone values ≥0.6 and ≥1.0 mmol/L were 24% and 20%, respectively. During the ketogenic diets, the percent time with CKM values <0.6 and ≥0.6 mmol/L were 97.9% and 2.1% (30 min/day), respectively. The number of continuous ketosis events >0.6 and >1.0 mmol/L of more than 30 minutes were 51 and 7 events (i.e., 1 event in 2.7 and 20 days), respectively, with an average duration of 77 min/event; all events were asymptomatic. Conclusion: SiBio CKM demonstrated acceptable accuracy and reveals that benign, transient ketosis may be common in T1D. Disclosure N. Sabelli: None. A. Haidar: Research Support; Tandem Diabetes Care, Inc. Consultant; Eli Lilly and Company, Abbott. Research Support; ADOCIA, Dexcom, Inc., Ypsomed AG, Bigfoot Biomedical, Inc. D. Majdpour: None. M. Pasqua: Speaker's Bureau; Abbott, Sanofi, Medtronic. M. Tsoukas: Speaker's Bureau; Novo Nordisk, Eli Lilly and Company, Boehringer-Ingelheim, Janssen Pharmaceuticals, Inc, Sanofi. N. Perz: None. S. Jacobson: None. Funding Diabetes Quebec (Subvention de m?rite)

Introduction and Objective: Habit theory describes context stability as important for the development of habit automaticity, but its role in insulin habit automaticity and adherence is unknown. The objective of the study was to examine the roles of context and context stability on insulin habit automaticity and adherence in adults with T1D. Methods: Adults with T1D (N = 63) completed a 7-day ecological momentary assessment (EMA) protocol using a time-contingent prompt schedule corresponding to approximate mealtimes (morning, afternoon, and evening). Physical, social, and emotional contexts were assessed at each timepoint. Generalized linear mixed-effects models tested associations between specific contexts with momentary insulin habit automaticity and insulin adherence. Spearman correlations were used to assess the strength of associations of context stability with insulin habit automaticity and insulin adherence. Results: The median age of the sample was 49 years, 58.7% were female, 96.8% were using a pump and CGM, and 76.3% were using automated insulin delivery. Feeling fatigued, stressed, and depressed reduced the likelihood of adherence to insulin but were not associated with automaticity. Those who reported feeling stressed were 56% less likely to adhere to insulin compared to those who reported no stress at all. As the extent of feeling fatigued increased, the likelihood of adherence decreased. More stable emotional contexts were associated with higher insulin habit automaticity scores and with greater insulin adherence. Greater stability in emotional context was also associated with less variability in both insulin habit automaticity and insulin adherence. Social context demonstrated a similar pattern of associations to that of emotional context for adherence but not for automaticity. Conclusion: Negative emotional contexts and emotional context stability appear to be important in insulin adherence and insulin habit automaticity. Disclosure J.Y. Stone: None. M.S. Dietrich: None. L.S. Mayberry: None. K. Clouse: None. S.A. Mulvaney: None. Funding Vanderbilt Institute for Clinical and Translational Research (UL1 TR002243)

Introduction and Objective: Type 2 diabetes (T2D) is a metabolic disorder marked by persistent hyperglycemia and frequently associated with severe complications that impact various organs. MicroRNAs (miRNAs) encapsulated within extracellular vesicles (EV-miRNAs) facilitate inter-organ and intercellular communication, playing a critical role in T2D pathophysiology. These miRNAs hold significant potential as biomarkers for T2D and as targets for therapeutic intervention. In this study, we utilized next-generation sequencing to analyze miRNAs present in human urinary extracellular vesicles (ECVs). Methods: This study involved urine sample collection from 68 participants, T2D patients (n=40) and healthy (n=28). The research aimed to isolate ECVs for the extraction and sequencing of small RNAs. miRNet was used to construct the miRNA-mRNA regulatory network, and cytoHubba was employed to identify potential hub genes among the EV-miRNAs. Results: We identified 46 (27 down and 19 upregulated) EV-miRNAs that were significantly dysregulated in urinary ECVs. Functional enrichment analysis revealed that identified target genes were predominantly involved in insulin signaling, AGE-RAGE, PI3K-Akt pathways. A total of 527 genes were identified as targets of the 46 miRNAs, and an mRNA-miRNA regulatory interaction network was constructed. Bottleneck algorithms were applied to this network to identify regulatory hubs, resulting in a multicentric mRNA-miRNA regulatory network comprising nine driver genes (PTEN, IGFR, MCL1, SMAD4, CCND2, LIN28B, BTG2, VEGFA, and HMGA1) and key miRNAs (miR-30c, miR-26a, miR-320a, miR-16, miR-107 and miR-125b). Conclusion: This study highlights the dysregulation of potential exosomal miRNAs associated with glucose metabolism in T2D patients. Our findings suggest that these miRNAs could serve as a potential biomarker and therapeutic target, offering insights into the molecular mechanisms underpinning the disease and its complications. Disclosure M. Malik: None. A. Mohammad: None. M.H. Dashti: None. M. Abu-Farha: None. F. Almulla: None. H. Ali: None.

Introduction and Objective: US rural-urban disparities in type 2 diabetes (T2D) prevalence are incompletely described, with limited epidemiologic cohorts for evaluation. Our objective was to leverage electronic health record (EHR) data to evaluate disparities in T2D prevalence. Methods: Minnesota EHR Consortium includes data on 90% of Minnesota residents, from 2020-2023. For each year, T2D prevalence was based on ≥1 diagnosis code within the previous 5 years. Urbanicity was based on RUCA codes (Figure). We used logistic regression to model prevalence, and report OR (95% CI) per 1-year change. Results: T2D prevalence was 8.44% in 2020, 8.43% in 2021, 8.59% in 2022, and 8.80% in 2023. After adjusting for age, sex, and race/ethnicity, T2D prevalence increased in metro (1.007 [1.005-1.009]; P<.001), was unchanged in micro (1.005 [1.000-1.011]; P=.054) and small town (1.000 [0.994-1.005]; P=.88), and decreased in rural (0.994 [0.990-0.998]; P=.002) areas. Similarly, T2D prevalence in females differed with urbanicity; however, in males, there was no change in any urbanicity level. In all urbanicity levels, T2D prevalence was highest in Hispanic and Native American or Alaska Native adults. Conclusion: T2D prevalence differed by urbanicity, with disparities by sex, race and ethnicity. EHRs can provide a robust framework to identify disparities and tailor T2D interventions. Disclosure S.B. Dugani: None. Y. Yu: None. L. Vaughan: None. J. Killian: None. C. Benziger: Consultant; Novartis Pharmaceuticals Corporation. Research Support; Amgen Inc, Novartis Pharmaceuticals Corporation. T. Winkelman: None. K.L. Margolis: None. K. Bergmann: None. J. Desai: None. T. DeFor: None. P.J. O'Connor: None. P. Drawz: None. I. Essien: None. M.A. Franco: None. A. Bryan: None. A.M. Chamberlain: Research Support; Exact Sciences. Funding This project was funded by the Minnesota Department of Health through an Innovations Project grant. SBD was supported by NIH/NIMHD (K23 MD016230).

Introduction and Objective: We examined disparities in spending on new diabetes drugs (GLP-1 RAs, SGLT2i) by race/ethnicity, income, and insurance type in adults with T2D. Methods: Using the 2018-2022 Medical Expenditure Panel Survey, we calculated annual per-person, inflation-adjusted spending on new drugs for two groups: (1) adults with T2D and (2) those with T2D plus cardiovascular disease or chronic kidney disease (CVD/CKD). We used a two-part regression model to estimate associations of race/ethnicity (non-Hispanic White [NHW], non-Hispanic Black [NHB], Hispanic, Other), income (<125% of the federal poverty level [FPL], 125% to <200% FPL, 200% to <400% FPL, ≥400% FPL), and insurance type (any private, Medicaid, Medicare only) with new drug spending, adjusting for age, sex, and education. Results: We observed disparities in the adjusted new drug spending for both patient groups. Spending was highest among NHW adults for T2D and among NHB adults for T2D plus CVD/CKD. Spending showed a U shape with highest income having the highest spending. Adults with private/Medicaid insurance spent more ($1,532/$1,288 for T2D, $1,972/$1,426 for T2D plus CVD/CKD) than those with Medicare ($793/$779). Conclusion: Disparities in new drug spending varied by race/ethnicity, income, and insurance. These findings can inform policies aimed at reducing access barriers to the new diabetes therapies for those in need. Disclosure P. Zhang: None. Y. Wang: None. K.M. Bullard: None.

Introduction and Objective: The off-label use of GLP-1RA in patients with T1D has increased, but its GI effects remain unclear. This study aimed to investigate the GI adverse effects and all-cause mortality in T1D patients receiving GLP-1RA therapy. Methods: This retrospective study used TriNetX Research Network data on adult T1D patients. GLP-1RA users and controls were matched 1:1 for age, gender, BMI, and comorbidities. Median follow-up was 849 days for cases and 650 days for controls. Exclusions included T2D and prior GI motility disorders or medications affect motility. Outcomes (gastroparesis, constipation, ileus, mortality) were analyzed using ORs, RRs, and 95% CIs. Results: A total of 254,672 T1D patients were included, with a mean age of 49.7 ± 17.2 years for cases and 52.4 ± 19.0 years for controls post-matching. Following propensity score matching, each group contained 13,335 patients (Table 1a). The GLP-1RA cohort showed no significant difference in gastroparesis (OR = 1, 95% CI: 0.84-1.21, p = 0.9) or ileus (OR = 0.5, 95% CI: 0.24-1.13, p = 0.09) but had a significant reduction in constipation (OR = 0.8, 95% CI: 0.76-0.92, p<0.001) and lower all-cause mortality (OR = 0.4, 95% CI: 0.38-0.45, p<0.001) (Table 1b). Conclusion: GLP-1RA treatment in T1D patients was associated with lower all-cause mortality and constipation, with no effect on gastroparesis. Long-term studies are needed to assess its impact on GI outcomes. Disclosure D. Al-Deiri: None. A. Kerbage: None. S. Valencia: None. K. Zhou: Speaker's Bureau; Xeris Pharmaceuticals, Inc. Consultant; Corcept Therapeutics. Research Support; NS100. S. Garg: Research Support; Abbott. Consultant; Novo Nordisk.

Introduction and Objective: Glucokinase (GCK) maintains glucose homeostasis. Gck heterozygous inactivation mutation leads to maturity onset diabetes of the young 2 with clinical features of mild hyperglycemia and low insulin levels, and the incidence of microvascular complications is significantly low. ATP-Sensitive K+ Channel (K-ATP) is vital in regulating insulin secretion. Inactivated variants of Abcc8 encoding SUR1 subunit of the K-ATP can lead to hyperinsulinemia and kidney injury. Our study aims to elucidate the role of GCK and hyperinsulinemia in the development of kidney injury. Methods: Gck knockout mouse (Gck+/-) and Abcc8 R306C mutation mouse (Abcc8mut/+) were constructed using CRISPR-Cas9. After hybridization, we obtained Gck knockout and Abcc8 mutant heterozygote mouse (G&A), observed metabolic phenotype and evaluated the kidney injury. Results: Gck +/- mice showed hyperglycemia and impaired glucose toleranc. Abcc8mut/+ mice showed normal blood sugar, elevated fasting insulin, and significant kidney injury. Compared to Abcc8mut/+ mice, G&A mice developed elevated fasting blood glucose but lower insulin levels, and alleviated kidney injury. (Figure 1) Conclusion: Hyperinsulinemia leads to severe renal injury independent of hyperglycemia. Suppression of glucokinase on the basis of hyperinsulinemia can partially alleviate renal injury. Disclosure H. Lian: None. C. Yang: None. L. Ji: None. X. Han: None. Funding National Natural Science Foundation of China (82170814)

Introduction and Objective: This study examined the longitudinal relationship between metabolic states and cognitive function in middle-aged and older Chinese adults, a topic that remains underexplored. Methods: Data from 1,745 participants (2011-2020) in the China Health and Retirement Longitudinal Study (CHARLS) were analyzed. Participants were categorized as metabolically healthy (MH), metabolically unhealthy (MN), prediabetic (PreD), or diabetic (DM) based on metabolic syndrome and diabetes status. Cognitive function was assessed in domains of memory, orientation, calculation, and drawing. Generalized estimating equation (GEE) models determined associations between baseline metabolic states and cognitive decline, with subgroup and interaction analyses exploring effect modifiers. Results: Participants had a median age of 56 years (IQR: 49-62). Significant differences in residence, smoking, and alcohol use (p<0.001) were observed across metabolic groups, while education, marital status, and baseline cognitive scores were similar. Adjusted models identified numeracy impairments in MN participants (β = -0.088, 95% CI: -0.186 to -0.010), while memory decline worsened with advancing metabolic abnormalities: MN (β = 0.146, 95% CI: -0.116 to 0.408), PreD (β = 0.077, 95% CI: -0.071 to 0.224), and DM (β = -0.156, 95% CI: -0.357 to 0.045). Conclusion: Metabolic abnormalities were associated with specific cognitive deficits, with diabetes progression was significantly linked to memory decline. These findings underscore the importance of metabolic management for preserving cognitive health. Further studies are needed to clarify underlying mechanisms. Disclosure M. Xie: None. S. Gao: None. J. Zhang: None. M. Han: None. Y. Liu: None. T. Wang: None. L. Ma: None. H. Zhu: None. M. Li: None. Z. Song: None.