OBJECTIVE: We investigated islet autoimmunity (IA) incidence trends among Colorado children born 1993-2010 in Diabetes Autoimmunity Study in the Young (DAISY) and The Environmental Determinants of Diabetes in the Young (...OBJECTIVE: We investigated islet autoimmunity (IA) incidence trends among Colorado children born 1993-2010 in Diabetes Autoimmunity Study in the Young (DAISY) and The Environmental Determinants of Diabetes in the Young (TEDDY) and whether HLA genotype or early-life environmental exposures contributed to observed increases. RESEARCH DESIGN AND METHODS: We analyzed the risk of IA among 2,734 Colorado children representing three birth cohorts (BCs): BC1 (1993-1998), BC2 (1999-August 2004), and BC3 (September 2004-2010). Cox models evaluated IA by BC, with time-varying coefficients, BC-HLA interaction, and stratification by type 1 diabetes family history. Mediation analyses examined age at gluten introduction, weight-for-age Z-score, and maternal smoking. RESULTS: IA increased across BC1-BC3 (7.0%, 10.7%, and 12.7%). At age 1, moderate-risk HLA participants in BC2 and BC3 had, respectively, 2.57 and 6.19 times the IA risk of BC1. By age 5, effects attenuated. No selected environmental exposures mediated the increased incidence. CONCLUSIONS: IA increased among Colorado children born 1993-2010, with the strongest effects among moderate-risk HLA genotypes in later BCs.
OBJECTIVE: Immune checkpoint inhibitors (ICIs) improve outcomes across multiple cancers but may cause immune-related adverse events, including ICI-induced diabetes (ICI-D). ICI-D typically presents abruptly with severe i...OBJECTIVE: Immune checkpoint inhibitors (ICIs) improve outcomes across multiple cancers but may cause immune-related adverse events, including ICI-induced diabetes (ICI-D). ICI-D typically presents abruptly with severe insulin deficiency, and published cases have largely described irreversible loss of endogenous insulin secretion. RESEARCH DESIGN AND METHODS: We report a novel case of clinical and biochemical recovery of ICI-D. RESULTS: Following melanoma treatment with ipilimumab plus nivolumab, then nivolumab monotherapy, the patient developed abrupt-onset symptomatic hyperglycemia with mild ketosis and positive GAD and insulin autoantibodies, consistent with ICI-D. The patient subsequently received infliximab for ICI-related arthritis. Insulin requirements progressively declined, allowing discontinuation of insulin therapy. GAD antibodies normalized within ∼2 months and later became undetectable. Urine C-peptide-to-creatinine ratios increased over time, consistent with endogenous insulin secretion. CONCLUSIONS: Recovery from ICI-D may occur. The temporal association suggests infliximab may have contributed, warranting further study as a potential disease-modifying therapy.
Wang R, Naeem U, Everhart AO
… +4 more, Karaca Mandic P, Dusetzina SB, Lipska KJ, McCoy RG
Diabetes Care
· 2026 Jun · PMID 42378410
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OBJECTIVE: High insulin prices are a major barrier to diabetes management in the U.S. Since 2019, several states have implemented legislation to mitigate high out-of-pocket (OOP) costs for commercially insured individual...OBJECTIVE: High insulin prices are a major barrier to diabetes management in the U.S. Since 2019, several states have implemented legislation to mitigate high out-of-pocket (OOP) costs for commercially insured individuals by setting caps on monthly OOP payments for insulin. In this study, we examine the reach of these policies. RESEARCH DESIGN AND METHODS: We identified insulin OOP cap legislation enacted through 2026 for each state and Washington, DC. Using public data on diabetes prevalence and health insurance coverage, we identified the population eligible and exposed to OOP caps legislation: adults aged 18-64 years with diabetes, using insulin, enrolled in state-regulated commercial plans, and residing in states that enacted OOP caps legislation. We then estimated the number of commercially insured individuals using insulin still left unprotected due to 1) enrolled in federally regulated plans, regardless of state of residence; or 2) enrolled in state-regulated plans but living in states without OOP cap legislation. RESULTS: By 2026, 29 states and Washington, DC, had enacted OOP caps on insulin, covering an estimated 0.99 million individuals with diabetes, using insulin, and enrolled in state-regulated commercial plans. Despite these gains, policy reach remains uneven: 0.67 million adults with diabetes using insulin and insured by state-regulated plans live in states without an insulin OOP cap, and 2.2 million more are insured by federally regulated commercial plans that fall outside of state jurisdiction. CONCLUSIONS: State OOP caps have the potential to reduce OOP insulin costs for many commercial plan enrollees but have limited reach. Legislative efforts to contain costs at the federal level are therefore needed to decrease the financial burden of insulin therapy.
Harnois-Leblanc S, Brown JM, Switkowski KM
… +8 more, Aris IM, Rifas-Shiman SL, Oken E, Gervis JE, Westerman K, Dashti HS, Hivert MF, Merino J
Diabetes Care
· 2026 Jun · PMID 42371749
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OBJECTIVE: We examined associations of polygenic scores (PS) for macronutrient intake with food intake and cardiometabolic outcomes during childhood and adolescence and evaluated gene enrichment in hypothalamic cell type...OBJECTIVE: We examined associations of polygenic scores (PS) for macronutrient intake with food intake and cardiometabolic outcomes during childhood and adolescence and evaluated gene enrichment in hypothalamic cell types. RESEARCH DESIGN AND METHODS: We derived carbohydrate, fat, and protein intake PS from an adult genome-wide association study among 516 non-Hispanic White children from the Project Viva cohort. We estimated dietary intake and calculated BMI z scores from measured height and weight at ages ∼3, 8, 13, and 18 years. Waist circumference, truncal fat, fasting glucose, insulin, glycated hemoglobin, and blood lipids were measured at 18 years. We estimated associations of PS with sugar-sweetened beverages (SSB), fast food, and BMI z score using generalized estimating equations (longitudinal), and using regression models for cardiometabolic and secondary dietary outcomes (cross-sectional). We evaluated enrichment of macronutrient intake genetic signals in hypothalamic cell types in the Human HYPOMAP data set. RESULTS: A 1-SD increase in carbohydrate PS was associated with higher odds of consuming two or more servings per week of SSB (odds ratio [OR] 1.20; 95% CI 1.07, 1.33) and one or more times per week of fast food (OR 1.11; 95% CI 1.004, 1.23) from ages 3 to 18 years. Higher-protein PS was associated with lower odds of consuming SSB (OR 0.84; 95% CI 0.75, 0.93). We did not observe consistent associations between macronutrient intake PS and cardiometabolic outcomes. We observed hypothalamic regional and neurotransmitter-specific patterns of gene enrichment for carbohydrate or protein intake. CONCLUSIONS: Genetic susceptibility for carbohydrate intake is associated with SSB and fast-food consumption in youth. Underlying pathways relating to hypothalamic nutrient-specific appetite signaling may be involved.
Ahmed M, Kubota-Mishra E, Siller AF
… +11 more, Davis A, Migacz I, Sisley S, Faruqi JA, Saeed ZI, Ahmed S, Philipson L, Redondo MJ, Balasubramanyam A, Tosur M, RADIANT Study Group*
Diabetes Care
· 2026 Jun · PMID 42360321
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We developed Python-based Expeditious Program for Parsing Electronic Records (PEPPER) as a novel electronic medical record (EMR) search tool. We tested its utility and efficiency to automate the first step of identifying...We developed Python-based Expeditious Program for Parsing Electronic Records (PEPPER) as a novel electronic medical record (EMR) search tool. We tested its utility and efficiency to automate the first step of identifying patients with A-β+ ketosis-prone diabetes (KPD). Electronic charts of 1,660 youth with type 2 diabetes (T2D) were analyzed by PEPPER to identify those with diabetic ketoacidosis (DKA) within 6 months of diagnosis. The efficiency and accuracy of PEPPER were compared with manual review. Further review confirmed A-β+ KPD per the Rare and Atypical Diabetes Network criteria. PEPPER identified 110 youth with T2D and DKA, of whom 21 met full A-β+ KPD criteria. PEPPER significantly reduced chart review time for this initial critical step compared with manual searching (mean SD 13.4 ± 3.9 s vs. 26.6 ± 9.4 s per chart; P < 0.001), and was 100% accurate. PEPPER streamlines EMR review, significantly reducing manual effort without sacrificing accuracy.
Galindo RJ, Moazzami B, Gerges A
… +6 more, Flores I, Arevalo G, Peng L, de Boer IH, Tuttle KR, Umpierrez GE
Diabetes Care
· 2026 Jun · PMID 42360278
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OBJECTIVE: There is a need for improved glycemia monitoring tools for people with type 2 diabetes (T2D) and end-stage kidney failure (ESKF). RESEARCH DESIGN AND METHODS: This prospective, randomized, crossover trial comp...OBJECTIVE: There is a need for improved glycemia monitoring tools for people with type 2 diabetes (T2D) and end-stage kidney failure (ESKF). RESEARCH DESIGN AND METHODS: This prospective, randomized, crossover trial compared the efficacy of real-time continuous glucose monitoring (rtCGM) with capillary blood glucose (CBG) testing in adults with T2D and ESKF undergoing hemodialysis. The primary outcome was percentage of time below range (%TBR) <70 mg/dL. RESULTS: The %TBR <70 mg/dL was not significantly different between groups (mean 1.17% ± 1.8 vs. 1.29% ± 2.7; P = 0.28). Compared with CBG testing, percentage time in range (%TIR) was higher (63.4% ± 24 vs. 54.5% ± 23) and mean glucose lower (173.6 ± 37 vs. 187.7 ± 38 mg/dL) after the rtCGM intervention, while percentage time above range (%TAR) >180 mg/dL (35.3% ± 25 vs. 44.3% ± 23) and >250 mg/dL decreased (12.3% ± 15 vs. 18.8% ± 19) (all P ≤ 0.01). CONCLUSIONS: In adults with T2D and ESKF undergoing hemodialysis, TBR was minimal and not influenced by rtCGM use. Compared with CBG testing, %TIR and %TAR improved during the rtCGM intervention. Future studies are needed to confirm the benefits of rtCGM in this population.
Rooney MR, Echouffo Tcheugui JB, Chen J
… +13 more, Walker KA, Ballantyne CM, Boerwinkle E, Kelly TN, Ndumele CE, Pankow JS, Grams ME, Post WS, Ganz PJ, Wood AC, Rotter JI, Selvin E, Coresh J
Diabetes Care
· 2026 Jun · PMID 42347027
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OBJECTIVE: To identify proteomic signatures underlying 3-year progression from impaired fasting glucose (IFG) to diabetes. RESEARCH DESIGN AND METHODS: We examined IFG progression in the Atherosclerosis Risk in Communiti...OBJECTIVE: To identify proteomic signatures underlying 3-year progression from impaired fasting glucose (IFG) to diabetes. RESEARCH DESIGN AND METHODS: We examined IFG progression in the Atherosclerosis Risk in Communities (ARIC) study from visit 2 (1990-1992) to visit 3 (1993-1995). We tested associations of 4,955 plasma proteins (SomaScan version 4.0) with ∼3-year progression from IFG (FG 100-125 mg/dL without diabetes) to diabetes (diagnosis, medication, or FG ≥126 mg/dL) using logistic regression models adjusted for demographics, cardiometabolic risk factors, and baseline glucose with Bonferroni correction (P < 10-5). We explored biological pathways enriched among the top proteins and calculated improvements in prediction (ΔAUC and net reclassification using 3-year risk thresholds of 6% and 15% in 80% training and 20% internal validation subsamples). We validated results in the Multi-Ethnic Study of Atherosclerosis (MESA) cohort. RESULTS: There were 3,786 ARIC participants with IFG (mean [SD] age 57 [6] years, 52% female, 28% Black individuals). The 3-year cumulative incidence of diabetes was 6%. Six proteins were associated with ∼3-year progression to diabetes, namely lower receptor-type tyrosine-protein phosphatase S (PTPRS), anthrax toxin receptor 2 (ANTXR2), adiponectin (ADIPOQ), ciliary neurotrophic factor receptor subunit α (CNTFR), transmembrane protein 132C (TMEM132C), and higher ADAMTS-like protein 2 (ADAMTSL2). Altered carbohydrate metabolism and glycolysis were key pathways. Adding the six proteins to covariates improved discrimination (optimism-corrected AUC 0.81, ΔAUC 0.03, P = 0.005) and net reclassification (training 12.2%, internal validation 12.0%) with predicted diabetes risk quintiles spanning <1% to ∼20%. Two of the six proteins were validated in MESA (P < 0.008). CONCLUSIONS: We identified proteins associated with 3-year IFG progression, with improvements in diabetes risk stratification.
Qian J, Stefanovski D, Andersen PAK
… +11 more, Vujovic N, Kelly L, Lepson J, Nguyen H, Byrne S, Wang W, Mandrup-Poulsen T, Adler G, Garaulet M, Saxena R, Scheer FAJL
Diabetes Care
· 2026 Jun · PMID 42346809
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OBJECTIVE: Melatonin use quintupled in recent decades. The common melatonin receptor 1B gene (MTNR1B) variant increases risk of type 2 diabetes, raising concerns about melatonin's adverse metabolic effects and highlighti...OBJECTIVE: Melatonin use quintupled in recent decades. The common melatonin receptor 1B gene (MTNR1B) variant increases risk of type 2 diabetes, raising concerns about melatonin's adverse metabolic effects and highlighting the need for a genotype-based personalized approach. We aimed to comprehensively characterize the actions of melatonin on glucose homeostasis, including first- and second-phase β-cell responsivity to glucose, β-cell negative feedback by exogeneous insulin, insulin sensitivity, and whether such effects are stronger in MTNR1B G-allele risk carriers compared with noncarriers. RESEARCH DESIGN AND METHODS: Twenty-one healthy participants of European ancestry were studied in a randomized, double-blind, placebo-controlled, crossover trial, including 10 MTNR1B risk carriers and 11 noncarriers. Each participant underwent a highly controlled 5-day laboratory protocol, during which they received 5 mg oral melatonin or placebo in randomized order on two nonconsecutive days. Glycemic dynamics were assessed using insulin-modified intravenous glucose tolerance tests with minimal-model analysis. RESULTS: Melatonin worsened glucose tolerance and reduced early C-peptide responses in risk allele carriers (vs. placebo: 11.7% [95% CI 1.0-22.3] and -19.2% [-33.9 to -1.2], respectively; Padj < 0.05) but not in noncarriers. In carriers, impairments stemmed from a 40% (-52.4 to -24.3; Padj = 0.0003) suppression of glucose-stimulated first-phase β-cell responsivity, along with a slower insulin-induced decline in second-phase insulin secretion rate (64.3% [23.1-119.2]; Padj = 0.001). In carriers, melatonin also prevented exogenous insulin-induced hypoglycemia compared with placebo (zero vs. seven events, P = 0.001), but not in noncarriers. CONCLUSIONS: These findings identify blunted β-cell responsivity to glucose and dysregulated insulin negative feedback as key mechanisms linking melatonin signaling to diabetes risk.
Diabetes Care
· 2026 Jun · PMID 42339949
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Advances in diabetes technologies are transforming the management of type 1 diabetes. In this review, we reflect on the successful translation from bench to bedside of hybrid automated insulin delivery (AID) systems, inc...Advances in diabetes technologies are transforming the management of type 1 diabetes. In this review, we reflect on the successful translation from bench to bedside of hybrid automated insulin delivery (AID) systems, including development of the core components as well as commercialization, and then we focus on progress toward next-generation fully automated systems. With the availability of greater choice, we review the factors that influence users and health care professionals when selecting an AID system while recognizing the challenges of comparing AID systems. We discuss the importance of the diabetes technology ecosystem in ensuring equity of access and effective implementation. We contrast the different potential approaches to fully automated systems that could reduce burden, including the use of ultrarapid insulins, adjunctive therapies, integration of signals from additional wearables, and dual-hormone systems. Finally, we review emerging evidence for the use of AID in more vulnerable people with type 1 diabetes, in adults with type 2 diabetes, in people with cystic fibrosis-related diabetes, and in the inpatient setting.
Hennekes MHCL, Haugvik S, Wit M
… +6 more, Toschi E, Desjardins CD, Skrivarhaug T, Dahl-Jørgensen K, Stice E, Wisting L
Diabetes Care
· 2026 Jun · PMID 42335186
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In the article cited above, funding information was inadvertently omitted. The following text has been added: "This research was supported in part by National Institutes of Health grant P30 DK036836, which supports the J...In the article cited above, funding information was inadvertently omitted. The following text has been added: "This research was supported in part by National Institutes of Health grant P30 DK036836, which supports the Joslin Diabetes Center's Clinical Research Center." The authors apologize for the omission. The online version of the article (https://doi.org/10.2337/dc24-1599) has been updated with the correct funding information.