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Background: Type 1 diabetes is characterised by progressive loss of functional β-cell mass, necessitating insulin treatment. We aimed to investigate the hypothesis that combining anti-interleukin (IL)-21 antibody (for low-grade and transient immunomodulation) with liraglutide (to improve β-cell function) could enable β-cell survival with a reduced risk of complications compared with traditional immunomodulation.
Methods: This randomised, parallel-group, placebo-controlled, double-dummy, double-blind, phase 2 trial was done at 94 sites (university hospitals and medical centres) in 17 countries. Eligible participants were adults aged 18-45 years with recently diagnosed type 1 diabetes and residual β-cell function. Individuals with unstable type 1 diabetes (defined by an episode of severe diabetic ketoacidosis within 2 weeks of enrolment) or active or latent chronic infections were excluded. Participants were randomly assigned (1:1:1:1), with stratification by baseline stimulated peak C-peptide concentration (mixed-meal tolerance test [MMTT]), to the combination of anti-IL-21 and liraglutide, anti-IL-21 alone, liraglutide alone, or placebo, all as an adjunct to insulin. Investigators, participants, and funder personnel were masked throughout the treatment period. The primary outcome was the change in MMTT-stimulated C-peptide concentration at week 54 (end of treatment) relative to baseline, measured via the area under the concentration-time curve (AUC) over a 4 h period for the full analysis set (intention-to-treat population consisting of all participants who were randomly assigned). After treatment cessation, participants were followed up for an additional 26-week off-treatment observation period. This trial is registered with ClinicalTrials.gov, NCT02443155.
Findings: Between Nov 10, 2015, and Feb 27, 2019, 553 adults were assessed for eligibility, of whom 308 were randomly assigned to receive either anti-IL-21 plus liraglutide, anti-IL-21, liraglutide, or placebo (77 assigned to each group). Compared with placebo (ratio to baseline 0·61, 39% decrease), the decrease in MMTT-stimulated C-peptide concentration from baseline to week 54 was significantly smaller with combination treatment (0·90, 10% decrease; estimated treatment ratio 1·48, 95% CI 1·16-1·89; p=0·0017), but not with anti-IL-21 alone (1·23, 0·97-1·57; p=0·093) or liraglutide alone (1·12, 0·87-1·42; p=0·38). Despite greater insulin use in the placebo group, the decrease in HbA (a key secondary outcome) at week 54 was greater with all active treatments (-0·50 percentage points) than with placebo (-0·10 percentage points), although the differences versus placebo were not significant. The effects diminished upon treatment cessation. Changes in immune cell subsets across groups were transient and mild (<10% change over time). The most frequently reported adverse events included gastrointestinal disorders, in keeping with the known side-effect profile of liraglutide. The rate of hypoglycaemic events did not differ significantly between active treatment groups and placebo, with an exception of a lower rate in the liraglutide group than in the placebo group during the treatment period. No events of diabetic ketoacidosis were observed. One participant died while on liraglutide (considered unlikely to be related to trial treatment) in connection with three reported adverse events (hypoglycaemic coma, pneumonia, and brain oedema).
Interpretation: The combination of anti-IL-21 and liraglutide could preserve β-cell function in recently diagnosed type 1 diabetes. The efficacy of this combination appears to be similar to that seen in trials of other disease-modifying interventions in type 1 diabetes, but with a seemingly better safety profile. Efficacy and safety should be further evaluated in a phase 3 trial programme.
Funding: Novo Nordisk.
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http://dx.doi.org/10.1016/S2213-8587(21)00019-X | DOI Listing |
Nephrol Dial Transplant
September 2025
Department of Clinical Pharmacy and Pharmacology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.
Background: We investigated circulating protein profiles and molecular pathways among various chronic kidney disease (CKD) etiologies to study its underlying molecular heterogeneity.
Methods: We conducted a proteomic biomarker analysis in the DAPA-CKD trial recruiting adults with and without type 2 diabetes with an eGFR of 25 to 75 mL/min/1.73m2 and a UACR of 200 to 5000 mg/g.
JAMA Netw Open
September 2025
Division of Cardiology, Department of Internal Medicine, New Taipei Municipal TuCheng Hospital, New Taipei, Taiwan.
Importance: The cardiovascular benefits of glucagon-like peptide-1 receptor agonists (GLP-1 RAs) may vary by body mass index (BMI), but evidence on BMI-specific outcomes remains limited.
Objective: To investigate the associations of GLP-1 RA use with cardiovascular and kidney outcomes across BMI categories in patients with type 2 diabetes.
Design, Setting, And Participants: This retrospective cohort study used the Chang Gung Research Database, a clinical dataset covering multiple hospitals in Taiwan.
JAMA Pediatr
September 2025
Diabetes Research Envisioned and Accomplished in Manitoba (DREAM) Research Theme, Children's Hospital Research Institute of Manitoba, Winnipeg, Canada.
Importance: Youth living with type 1 diabetes (T1D) are increasingly choosing automated insulin delivery (AID) systems to manage their blood glucose. Few systematic reviews meta-analyzing results from randomized clinical trials (RCTs) are available to guide decision-making.
Objective: To study the association of prolonged AID system use in an outpatient setting with measures of glucose management and quality of life in youth with T1D.
Nutr Health
September 2025
Independent researcher, Rome, Italy.
Artificial intelligence (AI) is increasingly applied in nutrition science to support clinical decision-making, prevent diet-related diseases such as obesity and type 2 diabetes, and improve nutrition care in both preventive and therapeutic settings. By analyzing diverse datasets, AI systems can support highly individualized nutritional guidance. We focus on machine learning applications and image recognition tools for dietary assessment and meal planning, highlighting their potential to enhance patient engagement and adherence through mobile apps and real-time feedback.
View Article and Find Full Text PDFCell Mol Biol (Noisy-le-grand)
September 2025
M-DT1, Roquefort-les Pins, France.
To date, the closed-loop system represents the best commercialized management of type 1 diabetes. However, mealtimes still require carbohydrate estimation and are often associated with postprandial hyperglycemia which may contribute to poor metabolic control and long -term complications. A multicentre, prospective, non-interventional clinical trial was designed to determine the effectiveness of a novel algorithm to predict changes in blood glucose levels two hours after a usual meal.
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