Offspring of mothers with diabetes are at increased risk of developing type 2 diabetes, and this predisposition is established during fetal life. The aim of this study was to define the functional, morphological and molecular alterations in neonatal pancreatic islets associated with maternal hyperglycaemia, with a particular focus on beta cells, an area that remains poorly understood. Given its similarity to humans in endocrine pancreas development, the pig was used as a translational animal model. Using genetically diabetic and beta cell reporter pig models, we performed functional assessments of glucose-stimulated insulin secretion in vivo and in situ using fresh pancreatic tissue slices from neonatal piglets born to hyperglycaemic mothers (PHGs) or normoglycaemic mothers (PNGs). Morphological and molecular profiling, including proteomics and single-cell RNA-seq, were performed to elucidate molecular changes reflecting the developmental impact of maternal diabetes on offspring metabolic health, with a particular focus on neonatal beta cells. PHGs were born hyperglycaemic, hyperinsulinaemic and insulin resistant, exhibiting markedly delayed glucose and insulin response curves following oral glucose administration, with more pronounced effects in male piglets. Elevated basal insulin secretion and an almost blunted glucose responsiveness of pancreatic tissue slices were associated with increased insulin and somatostatin content, expansion of beta (+35
Air pollution (AP) contributes to diabetes progression and comorbidities, but underlying mechanisms remain unclear, as no observational studies have applied gold-standard phenotyping or distinguished between the effects of type 1 diabetes, type 2 diabetes and diabetes subtypes. We examined whether AP exposure was associated with glucose homeostasis biomarkers and diabetes-related comorbidities in people with recent-onset type 1 diabetes, type 2 diabetes and diabetes subtypes. This cross-sectional analysis is based on data from 1120 participants in the German Diabetes Study (417 with type 1 diabetes and 703 with type 2 diabetes). The glucose homeostasis biomarkers used were HbA1c, insulin sensitivity (clamp-derived M value), insulin secretion (glucagon-stimulated C-peptide6min) and insulin clearance (clamp derived). Diabetes-related comorbidities included CVD risk (SCORE2-Diabetes), V̇O_2max as an indicator of cardiorespiratory fitness, albuminuria as a marker of kidney function and the presence of distal sensorimotor polyneuropathy (DSPN). Five-year means of exposure to AP (particulate matter [PM] with diameters of <2.5 μm [PM2.5] and <10 μm [PM10] and nitrogen dioxide [NO2] before baseline at individual residential addresses were examined. Associations between each exposure–outcome pair were estimated per 1 IQR increase in air pollutants using multivariable linear and logistic regression. Two-pollutant analysis, cumulative risk index (CRI) analysis and insulin-treated type 1 diabetes model analysis were performed as sensitivity analyses. Among those with type 1 diabetes, higher PM2.5 was associated with higher HbA1c (exp[β]=1.07 [95 V̇O_2max (exp[β]=0.94 [95 V̇O_2max (exp[β]=0.91 [95
Randomised controlled trials underpin the evidence base for diabetes interventions but have important limitations, including being conducted in selective populations, with restricted follow-up times and treatment pathways that differ from routine clinical practice. Real-world data (RWD) offer an opportunity to address questions beyond the scope of trials, including the comparative effectiveness of interventions, assessment of longer-term outcomes, and treatment effects in under-represented populations. However, the credibility of real-world evidence (RWE) varies widely due to data quality and methodological challenges. The REDDIE (Real-world Evidence for Decisions in Diabetes) programme examined how RWD can generate robust, decision-relevant evidence for diabetes by analysing multiple national registries, evaluating regulatory expectations and conducting target trial emulations of landmark studies. Evidence from REDDIE and the wider literature demonstrates that well-designed observational analyses can replicate major trial findings and extend evidence to broader populations. However, credibility critically depends on careful alignment between the research question, database fitness, study design and analytical methods. Target trial emulation and modern causal inference approaches can mitigate key biases but cannot overcome fundamental limitations of routine data, including unmeasured confounding and incomplete variable capture. RWE and RCTs should be viewed as complementary sources of evidence. We outline a practical framework for the design, analysis and interpretation of RWE studies in diabetes to support more robust and decision-relevant use of RWD by regulators, health technology assessment agencies and clinicians.
Metabolic dysfunction-associated steatotic liver disease (MASLD) is a global metabolic condition with a complex relationship to type 2 diabetes. Yet human genetic studies suggest the existence of a MASLD subtype with favourable glycaemic effects, raising a clinically important question: how can hepatic steatosis coexist with improved glycaemic outcomes? We aimed to determine whether MASLD comprises genetically distinct subtypes with divergent glycaemic consequences, and to define the genetic basis of a glucose-lowering MASLD subtype. We integrated genetic and triglyceride-related metabolomic profiles to cluster 18 established MASLD-associated variants and construct mutually adjusted partitioned polygenic risk scores (PRSs) in the UK Biobank. We tested associations with hepatic biomarkers, liver outcomes and type 2 diabetes, and replicated glycaemic findings in an independent Chinese cohort (the Taizhou Longitudinal Study [TZL]). We prioritised candidate loci using colocalisation and fine-mapping and performed allele-specific functional assays and structural modelling to investigate the underlying mechanism at the lead locus. Partitioned PRSs revealed bidirectional glycaemic axes: one PRS lowered fasting glucose and type 2 diabetes risk, whereas the remaining PRSs increased both, despite all associating with higher liver injury markers and adverse liver outcomes. The divergent glycaemic effects were replicated in the TZL. To pinpoint the genetic basis of the glucose-lowering axis, colocalisation and fine-mapping prioritised GCKR rs1260326 (C>T) as a shared MASLD–type 2 diabetes signal and the lead cis-pQTL for circulating glucokinase regulatory protein (GKRP). Functional experiments showed that the rs1260326 T allele promotes exon-15 skipping in GCKR, reduces the abundance of full-length GKRP and yields a truncated protein. In silico structural modelling suggested that the truncated GKRP isoform may have reduced binding affinity for glucokinase, although this predicted effect requires experimental validation. MASLD comprises genetically distinct subtypes with opposing glycaemic and type 2 diabetes risk profiles. Within the glucose-lowering subtype, rs1260326-mediated alternative splicing of GCKR provides a potential mechanistic link to reduced GKRP abundance and glycaemic protection. These findings support a more granular view of MASLD heterogeneity and may inform future subtype-specific risk stratification and prevention.
Non-healing diabetic foot ulcers are a major precursor to lower-extremity amputation (LEA) in diabetes, and gout may be an overlooked contributor. We hypothesised that individuals with both diabetes and gout have a higher risk of LEA than those with diabetes alone, with the strongest effect at more distal amputation levels. In a nationwide case–control study of 601,541 individuals with type 2 diabetes, we identified 4912 cases with LEA and 39,101 age- and sex-matched control participants. Gout exposure was determined using ICD-10 diagnoses and Anatomical Therapeutic Chemical codes for urate-lowering therapy. Associations were estimated using conditional logistic regression, adjusting for diabetes duration, peripheral arterial disease, acute myocardial infarction and late diabetes complications. Gout was associated with an increased risk of LEA (OR 1.85, 95
