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Recent rodent microbiome experiments suggest that besides . are important in type 2 diabetes and obesity development. In the present translational human study, we aimed to characterize in our European cross-sectional FoCus cohort (n = 1,544) followed by validation of the major results in an independent Canadian cohort (n = 438). In addition, we examined abundance in response to a weight loss intervention (n = 55). was positively associated with BMI and type 2 diabetes independently of the reduced microbiome α/β diversity and low-grade inflammation commonly found in obesity. Nutritional analysis revealed a positive association with the dietary intake of carbohydrates but not with fat or protein consumption. Out of 126 serum metabolites differentially detectable by untargeted HPLC-based MS-metabolomics, L-cysteine showed the strongest reduction in subjects with high abundance. This is of interest, since is a known high L-cysteine consumer and L-cysteine is known to improve blood glucose levels in rodents. Furthermore, metabolic network enrichment analysis identified an association of high abundance with the activation of the human fatty acid biosynthesis pathway suggesting a mechanism for body weight gain. This is supported by a significant reduction of the abundance during our weight loss intervention. Together, these data indicate a role for in human type 2 diabetes and obesity, whereby the link to L-cysteine might be relevant in type 2 diabetes development and the link to the fatty acid biosynthesis pathway for body weight gain in response to a carbohydrate-rich diet in obesity development.
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http://dx.doi.org/10.1080/19490976.2022.2057778 | 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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