Category Ranking
98%
Total Visits
921
Avg Visit Duration
2 minutes
Citations
20
Article Abstract
Circulating microRNAs (miRNAs) are linked to the onset and progression of type 1 diabetes mellitus (T1DM), thus representing potential disease biomarkers. In this study, we employed a multiplatform sequencing approach to analyze circulating miRNAs in an extended cohort of prospectively evaluated recent-onset T1DM individuals from the INNODIA consortium. Our findings reveal that a set of miRNAs located within T1DM susceptibility chromosomal locus 14q32 distinguishes two subgroups of individuals. To validate our results, we conducted additional analyses on a second cohort of T1DM individuals, confirming the identification of these subgroups, which we have named cluster A and cluster B. Remarkably, cluster B T1DM individuals, who exhibit increased expression of a set of 14q32 miRNAs, show better glycemic control and display a different blood immunomics profile. Our findings suggest that this set of circulating miRNAs can identify two different T1DM subgroups with distinct blood immunomics at baseline and clinical outcomes during follow-up.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11228666 | PMC |
| http://dx.doi.org/10.1016/j.xcrm.2024.101591 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Calibrating Dexcom G7 improves its performance in the context of repetitive recreational scuba diving in people with type 1 diabetes.
BMJ Open Sport Exerc Med
September 2025
Servizio di Endocrinologia e Diabetologia, Repubblica e Cantone Ticino Ente Ospedaliero Cantonale, Bellinzona, TI, Switzerland.
Background: The use of continuous glucose monitors (CGM) in scuba diving for patients with type 1 diabetes (T1DM) shows potential but faces challenges related to accuracy. Previous research has highlighted the poor accuracy of the Dexcom G7 (DG7) in repetitive diving contexts. This study investigates the impact of calibration on the accuracy of DG7, providing valuable insights for patients and clinicians.
View Article and Find Full Text PDFMauriac Syndrome in Sudanese Children: An Old Syndrome Still Existing in Resource-Limited Countries.
Pediatr Diabetes
September 2025
Pediatric Endocrinology Department, Gaafar Ibn Auf Pediatric Tertiary Hospital, Khartoum, Sudan.
Mauriac syndrome (MS) is a rare condition linked to inadequate glycemic control in type 1 diabetes mellitus (T1DM) and has also rarely been reported in patients with neonatal diabetes. MS manifests as growth failure, delayed puberty, cushingoid features, and hepatomegaly. The condition can be associated with complications like dyslipidemia, retinopathy, and nephropathy.
View Article and Find Full Text PDFCausal Associations of Iron Status With the Renal Function and Diabetic Nephropathy in Patients With Diabetes Mellitus: A Two-Sample Mendelian Randomization Study.
J Diabetes Res
September 2025
Department of Endocrinology, Shenzhen Third People's Hospital, The Second Affiliated Hospital, School of Medicine, Southern University of Science and Technology, Shenzhen, Guangdong Province, China.
This study was to explore the causal effect of iron status on renal function and the risk of diabetic nephropathy in diabetic patients. The data on exposures including ferritin, serum iron, transferrin saturation (TSAT), and total iron-binding capacity (TIBC) were obtained from a genome-wide association study (GWAS). The outcomes were diabetic nephropathy, Type 1 diabetes mellitus (T1DM) with renal complications, Type 2 diabetes mellitus (T2DM) with renal complications, estimated glomerular filtration rate (creatinine) (eGFRcrea) in diabetes mellitus, and urinary albumin-to-creatinine ratio (UACR) in diabetes mellitus.
View Article and Find Full Text PDFMachine Learning Prediction of Cardiovascular Risk in Type 1 Diabetes Mellitus Using Radiomic Features from Multimodal Retinal Images.
Ophthalmol Sci
July 2025
Institut Clínic d'Oftalmología (ICOF), Hospital Clínic de Barcelona, Barcelona, Spain.
Purpose: To develop a machine learning (ML) algorithm capable of determining cardiovascular (CV) risk in multimodal retinal images from patients with type 1 diabetes mellitus (T1DM), distinguishing between moderate, high, and very high-risk levels.
Design: Cross-sectional analysis of a retinal image data set from a previous prospective OCT angiography (OCTA) study (ClinicalTrials.gov NCT03422965).
Baseline clinical factors associated with diabetes distress in dialysis patients: Insights from the ABCD audit data.
Diabetes Obes Metab
September 2025
Allam Diabetes Centre, University of Hull, Hull, UK.
Introduction: Diabetes is the leading cause of end-stage renal disease (ESRD) in the United Kingdom, accounting for one third of individuals starting renal replacement therapy (RRT). Data on the prevalence of diabetes distress (DD) in people with Diabetic Kidney Disease (DKD) on dialysis are scarce.
Aim: To describe the prevalence of DD in people living with diabetes undergoing haemodialysis.