Type 2 diabetes (T2D) is a heterogeneous disease influenced by both genetic and environmental factors. Recent studies suggest that T2D subtypes may exhibit distinct gene expression profiles. In this study, we aimed to identify T2D cluster-specific miRNA expression signatures for the previously reported five clinical subtypes that characterize the underlying pathophysiology of long-standing T2D: severe insulin-resistant diabetes (SIRD), severe insulin-deficient diabetes (SIDD), mild age-related diabetes (MARD), mild obesity-related diabetes (MOD), and mild early-onset diabetes (MEOD). We analyzed the circulating microRNAs (miRNAs) in 45 subjects representing the five T2D clusters and 7 non-T2D healthy controls by single-end small RNA sequencing. Bioinformatic analyses identified a total of 430 known circulating miRNAs and 13 previously unreported novel miRNAs. Of these, 71 were upregulated and 37 were downregulated in either controls or individual clusters. Each T2D subtype was associated with a specific dysregulated miRNA profile, distinct from that of healthy controls. Specifically, 3 upregulated miRNAs were unique to SIRD, 1 to MARD, 9 to MOD, and 18 to MEOD. Among the downregulated miRNAs, 11 were specific to SIRD, 9 to SIDD, 2 to MARD, and 1 to MEOD. Our study confirms the heterogeneity of T2D, represented by distinguishable subtypes both clinically and epigenetically and highlights the potential of miRNAs as markers for distinguishing the pathophysiology of T2D subtypes.

Background: Type 2 diabetes mellitus (T2DM) and metabolic dysfunction–associated steatotic liver disease (MASLD), which have a reciprocal relationship compounded by obesity, are highly prevalent in the Middle East affecting morbidity, mortality, and healthcare costs. Objective: This study aimed to assess the severity of MASLD and liver fibrosis among adult Emirati patients with long-standing T2DM. Design and Participants: This cross-sectional study used noninvasive methods to assess the severity of MASLD and fibrosis progression in an adult cohort of Emirati patients (N = 546) with a mean T2DM duration of 16 years. Main Measures: Fatty liver infiltration was assessed by hepatic steatosis index (HSI), while fibrosis was assessed by the fibrosis-4 (FIB-4) index and aspartate aminotransferase/platelet ratio index (APRI). Of those, 108 patients were randomly subjected to ultrasound-based FibroScan^® to assess controlled attenuation parameter (CAP) and liver stiffness measurement (LSM). Key Results: All patients had fatty liver with ~ 83% being categorized as having severe steatosis. Serum-based fibrosis biomarker panels detected significant liver fibrosis in ~ 2.5% of these patients. The APRI appeared to be more restrictive in detecting moderate fibrosis (1.5%) than the FIB-4 index (25.5%). CAP significantly correlated with the LSM, indicating that the two methods contributed to the same underlying pathophysiology. Liver steatosis was more severe in female patients, who were older and had a higher body mass index (BMI) than those with moderate or no significant fibrosis. They also had higher serum liver enzymes and were more likely to have age-related changes in kidney function. Interestingly, severity of both steatosis and fibrosis remained unaffected by age and duration of T2D except for fibrosis severity detected by FibroScan^®. Conclusions: This study highlights the critical need for routine screening of MASLD among Emirati patients with long-standing T2DM, given the high point prevalence of severe steatosis (~ 83%), predominantly among women in this population.

Background. Telemonitoring (TM), mobile‐phone technology for health, and bluetooth‐enabled self‐monitoring devices represent innovative solutions for proper glycemic control, compliance and monitoring, and access to providers. Objective. In this study, we evaluated the impact of TM devices on glycemic control and the compliance of 38 previously lost‐to‐follow‐up (LTFU) patients with type 2 diabetes mellitus (T2DM). Methods. This was an interventional single‐center study that randomly recruited LTFU patients from the Dubai Diabetes Center (DDC), UAE. After contact and recruitment by phone, patients had an initial visit at which they were provided with home‐based TM devices. A follow‐up visit was conducted three months later. Results. The mean HbA1c decreased significantly from 10.3 ± 1.9% at baseline to 7.4 ± 1.5% at the end of follow‐up, with a mean difference (MD) of −2.9% [95% CI: −3.6 to −2.2]. The percentage of patients with HbA1c <7% was 50% after three months. Home‐based blood sugar monitor devices showed a significant reduction in fasting blood glucose (FBG) after three months (MD = ‐40.1 mg/dL, 95% CI: −70.8 to −9.3). A significant reduction was observed in terms of body weight after three months (MD = −1.3 kg, 95% CI: −2.5 to −0.08). The mean number of days the participants used a device was the highest for portable pill dispensers (86.5 ± 22.8 days), followed by a OneTouch® blood glucose monitor (72.9 ± 23.5 days). Conclusions. TM led to significant improvements in overall diabetes outcomes, including glycemic control and body weight, indicating its effectiveness in a challenging population of T2DM patients who had previously been lost to follow‐up.

Background/Objectives: In type 2 diabetes (T2D), collective damage to the eyes, kidneys, and peripheral nerves constitutes microvascular complications, which significantly affect patients’ quality of life. This study aimed to prospectively evaluate the risk of microvascular complications in newly diagnosed T2D patients in Dubai, UAE. Methods: Supervised automated machine learning in the Auto-Classifier model of the IBM SPSS Modeler package was used to predict microvascular complications in a training data set of 348 long-term T2D patients with complications using 24 independent variables as predictors and complications as targets. Three automated model scenarios were tested: Full All-Variable Model; Univariate-Selected Model, and Backward Stepwise Logistic Regression Model. An independent cohort of 338 newly diagnosed T2D patients with no complications was used for the model validation. Results: Long-term T2D patients with complications (duration = ~14.5 years) were significantly older (mean age = 56.3 ± 10.9 years) than the newly diagnosed patients without complications (duration = ~2.5 years; mean age = 48.9 ± 9.6 years). The Bayesian Network was the most reliable algorithm for predicting microvascular complications in all three scenarios with an area under the curve (AUC) of 77–87%, accuracy of 68–75%, sensitivity of 86–95%, and specificity of 53–75%. Among newly diagnosed T2D patients, 22.5% were predicted positive and 49.1% negative across all models. Logistic regression applied to the 16 significant predictors between the two sub-groups showed that BMI, HDL, adjusted for age at diagnosis of T2D, age at visit, and urine albumin explained >90% of the variation in microvascular measures. Conclusions: the Bayesian Network model effectively predicts microvascular complications in newly diagnosed T2D patients, highlighting the significant roles of BMI, HDL, age at diagnosis, age at visit, and urine albumin.

The emerging concept of the cardiovascular-kidney-metabolic (CKM) syndrome encapsulates the interrelated nature of metabolic processes and metabolic dysfunction. Prediabetes, which describes the presence of elevations of blood glucose measurements insufficient to provoke a diagnosis of type 2 diabetes (T2D), is an important, – and crucially, reversible – early manifestation of the CKM syndrome. Numerous clinical studies and meta-analyses have shown that a substantial minority of people with prediabetes have microvascular and/or macrovascular complications reminiscent of those seen in clinical T2D. Prediabetes therefore represents an early stage of a continuum of increased insulin resistance, hyperglycaemia and associated vascular risk that begins at blood glucose concentrations that are well below those required for a diagnosis of diabetes. This condition also provides an opportunity for early intervention. All people with prediabetes should receive a multifactorial lifestyle intervention that focuses of weight management, nutrition, physical activity and smoking cessation. Where this is insufficient, ineffective or not followed, metformin remains the best studied pharmacotherapy for the management of prediabetes, with formal therapeutic indications for this purpose in many countries and support within international guidelines. Weight management is crucial for diabetes prevention, and weight loss during receipt of incretin agonist drugs is effective in diabetes prevention in populations with prediabetes, although consideration should be given to how long the treatment should be maintained and how the patient should be managed when it is ultimately withdrawn.