Diabetes, Obesity & Metabolism最新文献

Aims: Glucagon-like peptide-1 receptor agonists (GLP-1 RAs) are widely used for type 2 diabetes mellitus and obesity, with once-weekly dosing that supports adherence. However, injection-site reactions (ISRs) and dermatologic events have been recognised, ranging from mild local events to rare systemic hypersensitivity reactions that may cause discontinuation. To evaluate dermatologic and ISR safety of GLP-1 RAs through a meta-analysis of randomised controlled trials (RCTs) and disproportionality analysis of data from the United States Food and Drug Administration Adverse Event Reporting System (FAERS).

Materials and methods: PubMed, Embase and Web of Science were searched through December 2024 to identify RCTs reporting ISR or dermatologic outcomes for GLP-1 RAs. Random-effects meta-analysis synthesised trial evidence. A retrospective disproportionality analysis of FAERS data evaluated all approved GLP-1 RAs. Lower bound reporting odds ratios (LB ROR), proportional reporting ratios (PRR) and information components (IC) were calculated.

Results: The pooled meta-analysis of 14 RCTs that reported ISRs (4861 patients; 396 ISR events) showed increased ISR risk with GLP-1 RAs versus comparators (risk ratio 3.55; 95% confidence interval, 2.35-5.36; I² = 41.4%). Dermatologic events were infrequent and not significantly elevated. FAERS data analysis revealed potential ISR signals for exenatide and dulaglutide. Exenatide was associated with injection-site haemorrhage (PRR: 27.6; LB ROR: 29.4; IC₀₂₅: 4.6). Dulaglutide showed disproportionate reporting for injection-site haemorrhage (PRR: 11.5; LB ROR: 11.5; IC₀₂₅: 3.4).

Conclusions: GLP-1 RAs are consistently linked to higher ISR risk, especially with exenatide and dulaglutide, while generalised dermatologic events are rare. Clinicians should counsel patients about ISR risk to support adherence and optimise outcomes.

Aims: The impact of steatotic liver disease (SLD) subtypes on incident type 2 diabetes remains unclear. We investigated the association of metabolic dysfunction-associated steatotic liver disease (MASLD), MetALD (MASLD with moderate alcohol consumption), and alcohol-related liver disease (ALD) with incident type 2 diabetes in Korean adults aged 20-39 years.

Materials and methods: Using the Korean National Health Insurance Service database, we included 6 250 145 adults aged 20-39 who underwent health examinations between 2009 and 2012. SLD subtypes were classified by fatty liver index and alcohol intake. Incident type 2 diabetes was assessed using Cox proportional hazards models.

Results: During a median follow-up of 10.6 years, 72 028 participants developed type 2 diabetes. Incidence rates per 1000 person-years were higher in MASLD (10.56), MetALD (9.96), and ALD (12.49) than in non-SLD (1.29). Multivariable analyses showed significantly increased risks of type 2 diabetes (adjusted hazard ratios [95% CI]: 2.81 [2.78-2.85] for MASLD, 2.92 [2.87-2.98] for MetALD, and 3.99 [3.88-4.09] for ALD).

Conclusion: All SLD subtypes significantly increased the risk of type 2 diabetes in young adults, with the greatest risk in ALD, followed by MetALD and MASLD. Early detection and management of SLD are essential to reduce the future burden of diabetes.

Aims: Obesity is a chronic metabolic inflammatory disease caused by energy excess, characterized by excessive adipose tissue accumulation, and is often accompanied by multiple complications such as type 2 diabetes mellitus, metabolic-associated fatty liver disease (MAFLD), and neurological disorders. Adipose tissue plays a central role in maintaining energy homeostasis. Under conditions of energy excess, pro-inflammatory M1-type adipose tissue macrophages (ATMs) are activated, secrete inflammatory factors, inhibit lipolysis and thermogenesis pathways, and exacerbate metabolic disorders. Insulin-like growth factor 2 (IGF2) possesses both metabolic and immunomodulatory functions and is associated with obesity risk; however, its role in ATM polarization remains unclear. This study aims to clarify the regulatory role and mechanism of IGF2 in obesity-related metabolic inflammation and cognitive function.

Materials and methods: A high-fat diet (HFD)-induced obese mouse model was established, and interventions were performed via intraperitoneal injection of recombinant IGF2 (rIGF2). Phenotypic polarization of ATMs and expression of inflammatory factors were analyzed by quantitative polymerase chain reaction (qPCR) and immunofluorescence staining. Western blotting was used to detect the expression levels of key proteins in the adrenergic signaling pathway and molecules related to lipolysis/thermogenesis in adipose tissue. Changes in the expression of hippocampal synaptic proteins and cognitive function were evaluated by Western blotting and cognition-related behavioral tests.

Results: The study found that rIGF2 intervention significantly promoted the polarization of ATMs from the pro-inflammatory M1 type to the anti-inflammatory M2 type, reduced the levels of inflammatory factors such as tumor necrosis factor-α (TNF-α) and interleukin-1 (IL-1), thereby relieving the inhibition of the β-adrenergic signaling pathway, activating the expression of hormone-sensitive lipase (HSL) and uncoupling protein 1 (UCP1), promoting lipolysis and thermogenesis, and effectively improving metabolic abnormalities such as insulin resistance and hepatic steatosis in obese mice. Meanwhile, rIGF2 treatment upregulated the expression of synaptic proteins (e.g., PSD-95, Synapsin-1) in the hippocampus of obese mice and significantly ameliorated HFD-induced cognitive impairment.

Conclusions: This study is the first to systematically clarify the dual mechanism of IGF2 in regulating ATM polarization to improve metabolic inflammation, lipolysis-thermogenesis balance, and central cognitive impairment in obesity. The results suggest that IGF2 is not only a key regulator of energy metabolism but also possesses immunomodulatory and neuroprotective potential, providing a new theoretical basis and potential therapeutic target for the prevention and treatment of obesity and its related complications.

Introduction: Diabetic kidney disease (DKD) and diabetic nephropathy (DN) affect around 40% of diabetic patients but lack accurate risk prediction tools that include social determinants and demographic complexity. We developed and validated an ensemble machine learning model for three-year DKD/DN risk prediction with deployment readiness.

Methods: We analysed 18 742 eligible adult type 2 diabetic patients from Prince Sultan Military Medical City (PSMMC) registry between 2019 and 2024 in Riyadh, Saudi Arabia. Using temporal patient-level splitting, we developed a stacked ensemble model (LightGBM + CoxBoost) with several features including multiple literature-informed imputed variables including family history, non-steroidal anti-inflammatory drug (NSAID) use, socioeconomic deprivation, diabetic retinopathy severity, and antihypertensive medications, imputed via Bayesian multiple imputation by chained equations (MICE) with external study priors. Primary outcome was incident/progressive DKD/DN within 3 years' timeframe. We assessed discrimination, calibration, model utilisation, and algorithmic fairness.

Results: The final model achieved excellent discrimination (receiver operating characteristic [AUROC] of 0.852, 95% CI 0.847-0.857) and near-perfect calibration (slope 0.98, intercept -0.012) on multi-trial validation. Decision curve evaluation demonstrated superior net benefit (+22 events prevented per 1000 patients at 10% threshold) compared to treat-all strategies. Bootstrap validation showed minimal optimism in discrimination (C-statistic optimism = 0.005). No algorithmic bias was detected across demographic subgroups (maximum |Δ-AUROC| = 0.010). Prior sensitivity analysis confirmed validity and significance (AUROC variation ≤0.008). The model was engineered and deployed as an interactive web-based application (https://nephrarisk.streamlit.app/).

Conclusions: Our developed and demonstrated model provided accurate and well-fair DKD/DN risk prediction with excellent calibration, allowing for better decision making with deployment as a web-based research tool and framework for future prospective clinical validation. Further validation and testing are warranted from different centres and healthcare systems to increase confidence and dissemination of our model findings for better utilisation purposes in the future.

Aims: Obesity and type 2 diabetes mellitus (T2DM) are among the leading global health challenges of the 21st century. While caloric restriction remains the cornerstone of weight loss interventions, ketogenic diets (KD), characterised by low carbohydrate and high fat intake, have been shown to improve metabolic health partly by modulating the gut microbiome. This study investigated the effects of a short-term KD on gut microbiome composition and function in severely obese, prediabetic patients, compared to an energy-matched standard diet (SD).

Methods: In a randomised trial, patients with BMI >35 kg/m² and prediabetes underwent either a 2-week KD or isocaloric SD, both inducing a 30% energy deficit. Faecal samples collected before and after the intervention, alongside samples from healthy controls, were analysed by whole-genome metagenomic sequencing.

Results: At baseline, prediabetic patients exhibited greater interindividual variability and lower alpha diversity than healthy controls. KD resulted in a significant reduction of alpha diversity, largely driven by a selective loss of Lachnospiraceae, with a concomitant increase in Bacteroidaceae. Functional profiling revealed that KD, but not SD, altered genes coding for enzymes involved in energy metabolism, amino acid synthesis, nucleic acid activity, RNA modification, and vitamin biosynthesis. Additionally, serum acetate levels increased significantly following KD.

Conclusions: These findings underscore that KD, independent of caloric intake, acutely remodels the gut microbiome's taxonomic and functional landscape, highlighting the microbiome as a potential mediator of KD's metabolic effects.

Aims: To evaluate the efficacy and safety of transitioning from multiple daily injections (MDIs) insulin regimen to once-daily, fixed-ratio combination of basal insulin analog glargine 100 U/mL and a glucagon-like peptide 1 receptor agonist lixisenatide (iGlarLixi) in people with type 2 diabetes (PwT2D).

Materials and methods: Insulin therapy DE-intensificAtion with iglarLixi was a five-centre, open-label, parallel-group, active comparator, phase IV randomised controlled trial with a 24-week active treatment period. Eligible PwT2D (age 18-80 years, HbA1c ≤9% [75 mmol/mol], total daily dose of insulin ≤0.8 IU/kg, and fasting C-peptide above the lower limit of normal) were randomised in a 1:1 fashion to iGlarLixi initiation or continuation with MDI regimen. The primary endpoint was the mean change in HbA1c from baseline to 24 weeks after randomisation between the two treatment groups.

Results: Ninety individuals (n = 45 in both treatment groups), 71/91 (79.0%) male with mean (SD) age 66.2 (8.7) years, HbA1c 7.9 (1.0) % (62.8 [10.9] mmol/mol), diabetes duration 17.5 (8.7) years and body mass index (BMI) 33.6 (5.5) kg/m² were analysed. The mean (95% confidence interval) difference in the change in HbA1c between the iGlarLixi and the MDI group was -0.12 (-0.48, 0.23)% (-1.39 [-5.21, 2.43] mmol/mol), indicating comparable glycaemic control in both treatment groups. Significant between-group differences in favour of iGlarLixi were observed in body weight: -4.19 (-5.95, -2.43) kg, BMI: -1.49 (-2.11, -0.86) kg/m², total daily dose of insulin: -28.57 (-34.89, -22.24) IU, time spent in level 2 hyperglycaemia: -4.9 (-9.4, -0.34)%, and glycaemia risk index: -13.6 (-25.1, -2.1).

Conclusions: Insulin therapy simplification from MDI regimen to once-daily iGlarLixi is an efficient and safe treatment option for PwT2D.

Aims: Clinical guidelines recommend sodium-glucose cotransporter-2 inhibitors (SGLT2is) for individuals with type 2 diabetes mellitus (T2DM) and established or high risk of cardiorenal disease. This study examined real-world SGLT2i use patterns among older adults with T2DM in British Columbia, Canada.

Materials and methods: We conducted a drug utilisation study on all individuals aged ≥75 years with T2DM in British Columbia between January 1, 2016, and December 31, 2023, using administrative healthcare databases. We examined prevalence, incidence, characteristics of incident users, and discontinuation.

Results: The prevalence of SGLT2i use increased gradually from 2.0% in the first half of 2016 to 14% in the second half of 2022, then more sharply to 21% in the second half of 2023, with comparable prevalence in individuals with and without cardiorenal disease (20% vs. 22% in 2023). SGLT2i initiation increased from 1.3 to 2.8 per 1000 individuals between 2016 and 2022, spiked to 5.4 per 1000 individuals in January 2023, and then stabilised. Of the 14 320 SGLT2i initiators between 2021 and 2023, 62% had cardiorenal disease, most used other glucose-lowering drugs concomitantly (particularly metformin [68%], sulfonylureas [39%], and insulins [19%]), and 62% were started on treatment by a general practitioner. Additionally, 17% discontinued treatment within a year.

Conclusions: SGLT2i use among older adults with T2DM in British Columbia increased steadily from 2016 to 2022, followed by a spike in 2023, aligned with the expansion in publicly funded drug coverage. By the end of 2023, around one in five used SGLT2is, regardless of cardiorenal disease status.