Daily Endocrinology Research Analysis

AIMS: The aims of the study were to develop and validate WHOLISTIIC, a data-driven cluster analysis for identifying anthropometric metabolic subtypes. MATERIALS AND METHODS: K-means cluster analysis was performed in 397 424 UK Biobank participants based on five domains, that is, central obesity (waist-to-height ratio), general obesity (body mass index [BMI]), limb strength (handgrip strength), insulin resistance (triglyceride to high-density lipoprotein cholesterol [HDLc] ratio) and inflammatory condition (neutrophil-to-lymphocyte ratio). Replication was done in the NHANES. Cox proportional hazards regression models were used to estimate the associations of clusters with incident adverse health outcomes. RESULTS: Six replicable clusters were identified. Compared with individuals in cluster 1 (lowest BMI with preserved handgrip strength), individuals in cluster 2 (highest handgrip strength) were not at increased risk of all-cause mortality despite higher BMI, but had small yet significant increased risks of cardiovascular mortality, incident major adverse cardiovascular events (MACE), chronic renal failure and decreased risks of mortality due to respiratory disease, as well as incident dementia; individuals in cluster 3 (lowest handgrip strength and borderline elevated BMI), cluster 4 (highest triglyceride-to-HDLc ratio and moderately elevated BMI), cluster 5 (highest neutrophil-to-lymphocyte ratio and borderline elevated BMI) and cluster 6 (highest BMI) had substantially increased risks of all-cause, cardiovascular, and cancer mortality, incident MACE and chronic renal failure. The associations of anthropometric clusters with the risk of mortality were replicated in the NHANES cohort. CONCLUSIONS: Anthropometric metabolic subtypes identified with easily accessible parameters reflecting multifaceted pathology of overweight and obesity were associated with distinct risks of long-term adverse health outcomes.

BACKGROUND: Glucagon-like peptide-1 receptor agonists (GLP-1RAs) have shown promising effects on liver histology in phase 2 trials enrolling patients with metabolic dysfunction-associated steatotic liver disease. However, the impact of GLP-1RAs on the long-term risk of major adverse liver-related outcomes (MALOs) remains uncertain. OBJECTIVE: We performed a meta-analysis of observational cohort studies to quantify the magnitude and direction of the association between GLP-1RA use and MALOs in people with type 2 diabetes (T2D). DESIGN: We systematically searched eligible cohort studies comparing GLP-1RA new users versus users of other glucose-lowering medications. The primary outcome was the cumulative incidence rates of MALOs. Secondary outcomes included hepatic decompensation events, hepatocellular carcinoma (HCC) and liver-related mortality. Random-effects models were used to calculate incidence rate ratios (IRRs). RESULTS: 11 retrospective cohort studies with aggregate data on 1 467 220 patients with T2D (647 903 GLP-1RA new users, 819 317 non-users) were included. GLP-1RA use was significantly associated with a lower risk of MALOs (IRR 0.71, 95% CI 0.57 to 0.88) and hepatic decompensation (IRR 0.70, 95% CI 0.52 to 0.94). Association with reduced risk of HCC was also observed (IRR 0.82, 95% CI 0.61 to 1.11). Compared with other antidiabetic medications, GLP-1RAs showed superior effectiveness versus SGLT2 inhibitors in preventing MALOs (IRR 0.93, 95% CI 0.87 to 0.99), versus DPP-4 inhibitors in preventing hepatic decompensation (IRR 0.74, 95% CI 0.66 to 0.83) and versus insulin therapy in preventing HCC (IRR 0.32, 95% CI 0.13 to 0.80). CONCLUSIONS: GLP-1RA use is associated with a lower risk of liver-related complications and hepatic decompensation in people with T2D. These findings suggest a role of GLP-1RAs in preventing liver-related complications beyond their beneficial cardiometabolic effects.

AIMS/HYPOTHESIS: Accurate understanding of type 1 diabetes risk is critical for optimisation of counselling, monitoring and interventions, yet even within established staging classifications, individual time to clinical disease varies. Previous work has associated IA-2A positivity with increased type 1 diabetes progression but a comprehensive assessment of the impact of screening for IA-2A positivity across the natural history of autoantibody positivity has not been performed. We asked whether IA-2A would consistently be associated with higher risk of progression within and across established stages of type 1 diabetes in a large natural history study. METHODS: Genetic, autoantibody and metabolic data from adult and paediatric autoantibody-negative (n=192) and autoantibody-positive (n=4577) relatives of individuals with type 1 diabetes followed longitudinally in the Type 1 Diabetes TrialNet Pathway to Prevention Study were analysed. Cox regression was used to compare cumulative incidences of clinical diabetes by autoantibody profiles and disease stages. RESULTS: Compared with IA-2A CONCLUSIONS/INTERPRETATION: IA-2A positivity is consistently associated with increased progression risk throughout the natural history of type 1 diabetes development. Individuals with single-autoantibody positivity for IA-2A have a greater risk of disease progression than those who meet stage 1 criteria but who are IA-2A