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With an estimated prevalence of 463 million affected, type 2 diabetes represents a major challenge to health care systems worldwide. Analyzing the plasma proteomes of individuals with type 2 diabetes may illuminate hitherto unknown functional mechanisms underlying disease pathology. We assessed the associations between type 2 diabetes and >1,000 plasma proteins in the Cooperative Health Research in the Region of Augsburg (KORA) F4 cohort ( = 993, 110 cases), with subsequent replication in the third wave of the Nord-Trøndelag Health Study (HUNT3) cohort ( = 940, 149 cases). We computed logistic regression models adjusted for age, sex, BMI, smoking status, and hypertension. Additionally, we investigated associations with incident type 2 diabetes and performed two-sample bidirectional Mendelian randomization (MR) analysis to prioritize our results. Association analysis of prevalent type 2 diabetes revealed 24 replicated proteins, of which 8 are novel. Proteins showing association with incident type 2 diabetes were aminoacylase-1, growth hormone receptor, and insulin-like growth factor-binding protein 2. Aminoacylase-1 was associated with both prevalent and incident type 2 diabetes. MR analysis yielded nominally significant causal effects of type 2 diabetes on cathepsin Z and rennin, both known to have roles in the pathophysiological pathways of cardiovascular disease, and of sex hormone-binding globulin on type 2 diabetes. In conclusion, our high-throughput proteomics study replicated previously reported type 2 diabetes-protein associations and identified new candidate proteins possibly involved in the pathogenesis of type 2 diabetes.
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http://dx.doi.org/10.2337/db20-0296 | 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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