Diabetes, Obesity and Metabolism

Importance Women have been under-represented in clinical trials of type 2 diabetes mellitus (T2D), and evidence on sex differences in effectiveness of T2D treatments remains limited. Objective To assess sex differences in comparative effectiveness and safety of four second-line antidiabetic agents: glucagon-like peptide-1 receptor agonists (GLP-1RA), sodium-glucose cotransporter-2 inhibitors (SGLT2i), dipeptidyl peptidase-4 inhibitors (DPP4i), and sulfonylureas (SU). Design Retrospective cohort study using an active-comparator new-user design, following each participant till treatment discontinuation or end of data. Setting Multinational study across ten real-world databases from the Observational Health Data Sciences and Informatics (OHDSI) network in the United States, United Kingdom, Germany, and Spain. Participants 5.15 million adults with T2D who initiated one of the four second-line therapies following metformin during 1992-2021. Exposures GLP-1RA, SGLT2i, DPP4i, or SU. Main Outcomes and Measures Cardiovascular effectiveness as measured through 7 outcomes (major adverse cardiovascular events and glycemic control) and safety through 18 outcomes as highlighted by ADA guideline. Hazard ratios (HRs) are estimated separately for women and men using propensity score-stratified Cox models with empirical calibration. Sex differences were tested using Z-tests on log-HR differences. Results Drug initiation rates differed by sex with 9.28% of women initiating on GLP-1RA, 11.91% SGLT2i, 27.81% DPP4i, and 50.99% SU; the rates among the men were 5.41%, 12.84%, 24.64%, and 57.10%. No significant sex differences were observed for cardiovascular effectiveness outcomes. Several safety outcomes showed significant sex differences that are consistent across drug comparisons. Focusing on GLP-1RA compared to SGLT2i for brevity, GLP-1RA users experienced the following comparative benefits and risks: higher risk of acute pancreatitis among women (HR 1.39 [1.13, 1.70]) while non-differential risk among men (HR 0.91 [0.74, 1.12]) with p = 0.005 for the test of difference; non-differential risk of hypotension among women (HR 1.08 [0.98, 1.19]) while lower risk among men (HR 0.87 [0.78, 0.96]) with p = 0.003. Where no sex differences were found, our findings were consistent with existing evidence. Conclusions and Relevance This large-scale multinational study on antidiabetic agents identified clinically relevant sex differences, which are biologically plausible but previously lacked clinical evidence. Our findings reinforce the importance of tailoring T2D management according to sex.

Importance: Glucagon like peptide 1 receptor agonists (GLP 1 RAs) and dual glucose dependent insulinotropic polypeptide/glucagon like peptide 1 receptor agonists have demonstrated what may be considered transformative efficacy in recent randomized clinical trials for the treatment of obesity, yielding substantial weight loss in a majority of participants. However, the extent to which these trial results translate into routine clinical practice particularly within the rapidly expanding direct to consumer (DTC) telehealth sector serving self pay populations remains insufficiently characterized. As access to and affordability of these therapies broaden beyond traditional insurance based care models, evaluating real world effectiveness, safety, and patient engagement among individuals shouldering the full financial cost of treatment is essential for informing future models of obesity care delivery. Objective:To assess long term medication specific weight loss outcomes, including gender specific responses and discrepancies, and explore usage trends in a real world, self pay telehealth cohort receiving GLP 1 RA therapy, using an Observational study design (Retrospective data analysis). Setting and Participants:Retrospective data of patients enrolled in electronic health records (EHR) from Carevalidate, a national US telehealth platform provider for Online TeleHealth companies. The data collected ranged for a total of 703 days from January 12, 2024, to December 15, 2025. The analysis included 572 adults with overweight or obesity diagnosis who initiated treatment with semaglutide or tirzepatide and completed a minimum of 9 months of active follow up. Patients with insufficient follow up or those utilizing insurance coverage were excluded to isolate the self pay phenotype. Exposures: Prescription of semaglutide or tirzepatide (injectable or oral formulations) via synchronous or asynchronous telehealth consultations, titrated according to standard clinical protocols adapted for patient tolerance and financial sustainability. Main Outcomes and Measures: The primary outcome was percentage total body weight loss (%TBWL) from baseline to the last recorded encounter. Secondary outcomes included categorical responder rates (5%, 10%, 15%, >20% weight loss), weight loss velocity analysis, and telehealth utilization metrics (frequency of encounters and visit intervals) including gender differences in approaching the telehealth program. Results: The final analytical cohort included 572 patients (79.2% female; 20.8% male). Overall, 95.8% (548/572) achieved weight loss, while 3.7% experienced weight gain. At 12 months, the mean %TBWL was 13.8% for the semaglutide cohort (n=450) and 12.5% for the tirzepatide cohort (n=122), with no statistically significant difference between the two medications (P >.05), contrary to standard clinical trial data suggesting tirzepatide superiority. A significant gender difference was observed: females were significantly more in number comprising 80% of the cohort and were likely to be "major responders" (>20% weight loss) compared to males (29.8% vs 5.9%; P <.001). Conversely, males demonstrated significantly higher utilisation rates, attending more frequent encounters (mean 13.5 vs 12.7; P =.028) with shorter intervals between visits (35.6 vs 44.1 days; P =.009) compared to females. Weight loss velocity for both medications peaked during months 1 to 3 (~1.07 lbs/week) and declined substantially by months 12 to 15, indicating a plateau effect independent of the specific agent used. Conclusions and Relevance: Telehealth-managed GLP 1 treatment in a self pay population demonstrates high efficacy comparable to clinical trials for semaglutide. However, tirzepatide outcomes fell short of trial benchmarks, likely due to economic barriers preventing optimal dose titration and lower sample size. The study identifies a discrepancy where females approach the telehealth based self pay system more but males engage more frequently with the digital platform which could be due to inferior physiological outcomes ( less weight loss and more non responders) compared to females.This suggests that while telehealth is a viable model for long term obesity care, the "one size fits all" approach may be insufficient for under responders, who may require distinct titration strategies or tailored behavioral interventions to overcome baseline genetic and biological resistance.

ImportanceSemaglutide, a glucagon-like peptide-1 receptor agonist (GLP-1RA), is a highly effective medication to treat type 2 diabetes and obesity. However, concerns about potential suicidality persist, creating clinical uncertainty about its neuropsychiatric safety. ObjectiveTo assess risks of suicidality after initiating semaglutide compared to initiating SGLT2i and by duration of continuous semaglutide treatment. DesignActive-comparator, new-user target trial emulation to estimate inverse probability-weighted marginal cause-specific hazard ratios (HRs). For duration-of-treatment analyses, we used clone-censor-weight methods to estimate exposure-adjusted effects. SettingVeterans Health Administration. ParticipantsU.S. Veterans with type 2 diabetes receiving care from March 1, 2018 to September 1, 2025. ExposureInitiation of semaglutide vs SGLT2i; duration of semaglutide use ([&le;]6, 7-12, >12 months). OutcomesIncident suicidal ideation; suicide attempt or death; and a composite outcome. ResultsA total of 102,361 Veterans met inclusion criteria, including 11,478 new initiators of semaglutide and 90,883 new initiators of an SGLT2i. After overlap weighting, baseline characteristics were well balanced between treatment groups (mean [SD] age, 60.1 [11.7] years; BMI, 37.8 [6.8] kg/m2; hemoglobin A1c, 7.0% [1.4]; 85.5% male; 61.9% non-Hispanic White). During a median follow-up of 2.2 years, 9077 incident suicidal ideation events and 696 suicide attempts or deaths occurred. The incidence rate of suicidal ideation was 56.3 and 37.7 per 1000 person-years among semaglutide initiators and SGLT2i initiators, respectively (hazard ratio [HR], 0.99; 95% CI, 0.93-1.06; P = 0.86). For suicide attempts or deaths, the incidence rates were 4.30 and 2.64 per 1000 person-years, respectively (HR, 1.05; 95% CI, 0.84-1.31; P = .86). In adherence-adjusted analyses, sustained semaglutide treatment for more than 12 months, compared with 6 or fewer months, was associated with a 74% lower risk of suicide attempts or deaths (HR, 0.27; 95% CI, 0.14-0.54; P<.001). ConclusionAmong U.S. Veterans with type 2 diabetes, initiators of semaglutide were not observed to have an increased risk of suicidality compared with initiators of SGLT2i. Those with longer semaglutide treatment (beyond 12 months) had decreased risk of suicide attempt or death, suggesting longer term treatment is safe and may protect against for those outcomes.

This updated systematic review and network meta-analysis evaluated the efficacy and safety of obesity management medications (OMMs) in terms of reducing body weight and obesity related complications. Medline and Embase were searched up to 21 November 2025 for randomized controlled trials comparing OMMs versus placebo or active comparators in adults. The primary endpoint was percentage total body weight loss (TBWL%) at the end of the study. Secondary endpoints were TBWL% at 1, 2 and 3 years, anthropometric, metabolic, mental health and quality of life outcomes, cardiovascular morbidity and mortality, remission of obesity related complications, serious adverse events and all cause mortality. Sixty six RCTs (66 comparisons) were identified: orlistat (22), semaglutide (18), liraglutide (11), tirzepatide (8), naltrexone/bupropion (5) and phentermine/topiramate (2), enrolling 63,909 patients (34,861 and 29,048 with active compound and placebo, respectively). All OMMs showed significantly greater TBWL% versus placebo; tirzepatide and semaglutide exceeded 10% TBWL and showed the most favourable glycaemic effects. Semaglutide reduced major adverse cardiovascular events and all cause mortality. In dedicated complication specific trials, semaglutide and tirzepatide showed benefit on heart failure related outcomes; tirzepatide was associated with improved obstructive sleep apnoea syndrome and semaglutide with knee osteoarthritis pain remission. Tirzepatide and semaglutide were associated with improvements in metabolic dysfunction-associated steatohepatitis remission, and semaglutide with improvement in liver fibrosis. No OMMs were associated with an increased risk of serious adverse events. These updated results reinforce the need to individualize OMMs selection according to weight loss efficacy, complication profile and safety.

SGLT2 inhibitor (SGLT2i)-induced diabetic hyperketonemia is a life-threatening acute complication of diabetes. While Celastrol has been reported to exert beneficial effects on obesity; its potential role in ketogenesis remains unclear. In this study, Celastrol administration significantly attenuates the fasting-induced elevation of blood {beta}-hydroxybutyrate. Moreover, a 7-day course of Celastrol (1 mg/kg/day) leads to reductions in body weight and fat mass. Mechanistically, Celastrol specifically downregulates HMGCS2 expression and suppressess hepatic ketogenesis through inhibiting PPAR expression in the short term ([&le;] 2 days). However, after prolonged treatment for 7 days, Celastrol modulates both PPARand serum free fatty acids (FFAs) levels. Furthermore, anti-ketogenic effect of Celastrol is abolished in Ppar{square} /{square} mice. Importantly, Celastrol effectively ameliorates SGLT2i-induced hyperketonemia. In summary, Celastrol curbs hepatic ketone overproduction in a PPAR-dependent manner, indicating its protective potential against SGLT2i-induced hyperketonemia.

Objective: To investigate the association of the modified cardiometabolic index (MCMI) with cardiovascular-kidney-metabolic (CKM) syndrome staging, all-cause and cardiovascular mortality, and compare its predictive performance with traditional indices. Methods: This prospective cohort study included 5,189 adults with CKM syndrome (stages 0-4) from NHANES 1999-2018 (median follow-up 10.4 years). Associations were assessed using polynomial/ordinal logistic regression, Cox models, and restricted cubic splines. Mediation analysis explored diabetes' role. Competing risks (Fine-Gray), E-values, and sensitivity analyses ensured robustness. Predictive performance was compared using C-index and AUC. Results: MCMI showed a "decelerating increase" nonlinear association with CKM staging (adjusted OR=3.90, 95%CI: 3.38-4.50). For all-cause mortality, MCMI>3.5 exhibited a threshold effect (Q4 vs Q1: HR=1.412, 1.046-1.907); RCS curves identified MCMI<3.5 as a safety interval. For cardiovascular mortality, MCMI showed a fluctuating nonlinear pattern with low-risk (3.0-3.5) and high-risk (<2.5 or >4.0) intervals. Diabetes mediated 45.5% of MCMI-cardiovascular mortality risk (total HR=1.374, indirect HR=1.141). Competing risks revealed substantial underestimation of true effects (Q4 vs Q1 sHR=3.25, trend P<0.001). MCMI remained independently associated with all-cause mortality after extensive adjustments (HR=1.22, 1.05-1.40); E-values (1.73/1.29) indicated robustness. MCMI demonstrated superior predictive performance over CMI and TyG (mean AUC difference 0.0243). Conclusions: MCMI is an independent predictor of CKM progression and mortality. Its cardiovascular mortality risk is predominantly mediated by diabetes. MCMI>3.5 may serve as a clinical cut-off, outperforming traditional metabolic indices for CKM risk stratification. Keywords: modified cardiometabolic index, cardiovascular-kidney-metabolic syndrome, all-cause mortality, cardiovascular mortality, diabetes mellitus, competing risks model, cohort study, risk prediction

Abstract Context Lipoprotein(a) [Lp(a)] is a genetically determined and independent cardiovascular risk factor, traditionally considered stable across the lifespan, supporting a single lifetime measurement strategy. However, its longitudinal behavior during childhood and adolescence remains poorly characterized, particularly in individuals with type 1 diabetes who are at increased lifetime risk of cardiovascular disease. Objective We aimed to characterize intra- and inter-individual trajectories of Lp(a) in youth with type 1 diabetes and to assess the implications of variability for cardiovascular risk classification. Methods We conducted a retrospective single-center cohort study of children and adolescents with type 1 diabetes followed at Geneva University Hospitals between 2012 and 2023. Annual fasting Lp(a) concentrations were analyzed longitudinally. Variability was assessed in participants with more than two measurements. Clinically relevant thresholds were used to evaluate risk reclassification. Statistical analyses included paired Wilcoxon tests, Pearson and Kendall correlations, and Holm-adjusted p-values. Results A total of 287 participants contributed 1,408 Lp(a) measurements over a median follow-up of 6.2 years (IQR 2.9-9.6). At baseline, 26% had elevated Lp(a) (above or equal 300 mg/L). Among participants with serial measurements, 32% exhibited intraindividual fluctuations exceeding 50% of their maximum value. Reclassification across the 300 mg/L threshold occurred in 11.9% of participants. Lp(a) concentrations peaked between ages 10 and 13 years and declined thereafter. Modest seasonal variation was observed, with higher levels in autumn and winter (P < 0.05). Conclusions In youth with type 1 diabetes, Lp(a) demonstrates clinically relevant intraindividual variability over time. These findings suggest that reliance on a single lifetime measurement may lead to misclassification of cardiovascular risk and support repeated assessment, particularly during adolescence, to improve risk stratification.

BackgroundMetabolically healthy obesity (MHO) is unstable, with up to 80% of individuals progressing to metabolically abnormal obesity (MAO), yet mechanisms underlying this transition remain unclear. African Americans bear a disproportionate burden of obesity-related cardiovascular disease. Circulating extracellular vesicles (EVs) mediate inter-organ communication and may drive MAO-related vascular dysfunction. MethodsAdults of African ancestry were classified as metabolically healthy lean (MHL, n=14), MHO (n=9), or MAO (n=16). Plasma-derived EVs were characterized and their microRNA cargo profiled. Human coronary artery endothelial cells were treated with EVs from each group to assess nitric oxide signaling, oxidative stress, inflammatory activation, and mitochondrial dynamics. ResultsMHO participants exhibited preserved insulin sensitivity and lower inflammation compared with MAO despite comparable adiposity. EVs from MHO carried a distinct microRNA signature enriched in miR-148a-5p, miR-181c-5p, and miR-1255a, linked to antioxidant and matrix regulatory pathways. MAO EVs were enriched in miR-3613-3p, miR-6842-3p, and miR-326, targeting inflammation and insulin resistance pathways. Compared with both MHL and MHO EVs, MAO EVs suppressed endothelial nitric oxide synthase phosphorylation and reduced nitric oxide bioavailability, with increased reactive oxygen species and ICAM-1 expression. MHO EVs induced an intermediate phenotype with disrupted mitochondrial morphology, supporting a graded continuum of endothelial stress. ConclusionsMHO represents a biologically active intermediate state. Circulating EVs from MHO individuals convey molecular signals that impair endothelial and mitochondrial function, predisposing to vascular injury and progression toward MAO. EV-associated microRNAs are mechanistic mediators and candidate biomarkers of metabolic and vascular deterioration in obesity. CLINICAL PERSPECTIVEO_ST_ABSWhat Is New?C_ST_ABSO_LIThis study systematically investigated extracellular vesicles derived from metabolically healthy obese individuals to define direct vesicle effects on endothelial function using integrated omics coupled to functional outputs. C_LIO_LIExtracellular vesicles from metabolically healthy obesity convey a distinct molecular and biological signature that distinguishes lean and metabolically abnormal obesity. C_LIO_LIMetabolic health status, rather than obesity alone, drives extracellular vesicle-mediated endothelial nitric oxide signaling, oxidative stress, inflammation, and mitochondrial dynamics. C_LI What Are the Clinical Implications?O_LIThese findings explain why some individuals with obesity exhibit preserved vascular function while others develop early endothelial dysfunction. C_LIO_LIStratifying obesity by metabolic health status improves cardiovascular risk assessment beyond body mass index alone. C_LIO_LITargeting extracellular vesicle signaling pathways represents a novel strategy to prevent metabolically healthy individuals from progressing to metabolically abnormal obesity. C_LI

Wolfram syndrome is a rare autosomal recessive disorder caused by pathogenic variants in the WFS1 gene, characterized by early-onset diabetes mellitus, optic atrophy, sensorineural hearing loss, arginine vasopressin deficiency, and progressive neurodegeneration. The condition selectively affects pancreatic {beta} cells and neurons via chronic endoplasmic reticulum (ER) stress, and no proven disease-modifying therapy currently exists. Diabetes mellitus is typically the first manifestation, presenting at a mean age of 6 years as an insulin-dependent phenotype with preserved C-peptide and negative diabetes-related autoantibodies. Glucagon-like peptide-1 receptor agonists (GLP-1 RAs) are well-established agents in the management of type 2 diabetes, augmenting glucose-dependent insulin secretion, suppressing glucagon, slowing gastric emptying, and promoting satiety. Preclinical evidence further suggests that GLP-1 RAs preserve {beta}-cell mass, attenuate ER stress, and confer neuroprotective effects, properties of particular therapeutic relevance to Wolfram syndrome. We conducted a retrospective cohort study of 84 participants with genetically confirmed Wolfram syndrome and insulin-dependent diabetes mellitus enrolled in the Washington University Wolfram Syndrome International Registry and Clinical Study. Clinical data were extracted from medical records; for participants concurrently enrolled in the Tracking Neurodegeneration in Early Wolfram Syndrome study, longitudinal data were obtained from that source as well. Thirty-five percent of eligible participants had received a GLP-1 RA at some point during follow-up. We characterize the prevalence of GLP-1 RA use, documented rationale for initiation, observed effects on glycemic control and visual outcomes, adverse effects, and reasons for discontinuation. No statistically significant changes in hemoglobin A1c (HbA1c) or body mass index (BMI) were observed. Visual acuity declined significantly at two years, consistent with expected disease progression. Gastrointestinal adverse effects were common and contributed to frequent discontinuation. These observational data provide important clinical context and a foundation for future prospective trials evaluating GLP-1 RAs as a potential disease-modifying strategy in Wolfram syndrome.

Aims Type 2 diabetes mellitus (T2DM) increases risks of stroke and dementia, yet these risks vary across individuals. We hypothesized that clinically derived diabetes subtypes contribute to this heterogeneity. We aimed to identify data-driven subtypes using routine clinical features and examine their associations with dementia, stroke, mortality, and brain structure. Methods K-means clustering was applied to 14,353 UK Biobank participants with prevalent T2DM using age at diagnosis, body mass index, glycated hemoglobin, insulin resistance (triglyceride/HDL ratio), systolic blood pressure, and C-reactive protein. Cox models assessed associations with incident dementia (all-cause, Alzheimers disease [AD], vascular dementia [VaD]), stroke (all-cause, ischemic [IS], intracerebral hemorrhage [ICH]), and mortality. Brain MRI outcomes were analyzed in 779 participants using inverse probability-weighted linear regression. Results Three subtypes were identified: severe obesity-related inflammatory diabetes (SOID), mild metabolic diabetes (MMD, reference), and mild age-related hypertension-predominant diabetes (MARD-H). Compared with MMD, SOID showed higher risks of dementia (HR 1.24), VaD (HR 1.42), stroke (HR 1.38), IS (HR 1.48), all-cause mortality (HR 1.59), and cardiovascular death (HR 1.88). MRI showed lower gray matter volume and greater white matter hyperintensity burden in SOID. Conclusions Data-driven subtyping revealed heterogeneity in neurological risk in T2DM, with the obesity-inflammation subtype showing elevated vascular and neuroimaging risk.

AimWe examined associations between smoking and HbA1c among U.S. adults, and whether these associations vary by diabetes status. MethodsWe analyzed NHANES data from 2015-2018 for adults aged [&ge;]20 years. Smoking was assessed by self-report and serum cotinine. Survey-weighted multivariable linear regression was used to evaluate the association between smoking and HbA1c in the full population (N=9,214) and in adults without diabetes (N=7,328), adjusting for demographics, blood pressure, waist circumference, lipids, and C-reactive protein. ResultsAfter adjustment for cardiometabolic covariates, there was no significant association between smoking and HbA1c in the full population (former: {beta}=0.029%, p=0.30; current: {beta}=0.053%, p=0.13). Among adults without diabetes, former smoking was not associated with HbA1c, whereas current smoking remained significantly associated (former: {beta}=-0.001%, p=0.923; current: {beta}=0.067%, p<0.001). These findings were similar when cotinine was used as the exposure measure, with active smoking ([&ge;]3.0 ng/mL) associated with higher HbA1c among non-diabetic adults (p<0.001), but not in the full population. ConclusionsAmong adults without diabetes, current but not former smoking was associated with higher HbA1c. The absence of an association in former smokers suggests that this effect may attenuate following cessation. These findings support early cessation interventions and may inform cessation counseling and diabetes screening.

Background: Older in-patients have a higher prevalence of diabetes and cognitive impairment. Cognitive impairment can make blood glucose management more challenging, since patients might not remember to measure blood glucose or report symptoms. Investigating the accuracy of continuous glucose monitoring (CGM) compared to usual care will inform clinical interpretations in this vulnerable population. Aim: To compare CGM derived glucose metrics and point-of-care tests (POCT) in older in-patients with T2DM and cognitive impairment and to investigate CGM accuracy compared to POCT in the hospital settings with the same population. Methods: Thirty-two older people with comorbid T2DM and cognitive impairment were recruited within a tertiary care hospital in the UK. All participants were naive to CGM and were asked to wear blinded Dexcom G7 sensors for up to 10 days. All participants received usual care in their hospital stay including the use of POCT. Key accuracy metrics comprised the mean absolute relative difference (MARD), median absolute relative difference (median ARD), and Clarke Error Grid (CEG), correlation (R2) analysis. In addition, the percentage of CGM readings falling within +/-20% of reference glucose values when the reference was >5.6 mmol/L, or within +/-1.1 mmol/L when the reference was <=5.6 mmol/L (+/-20%/1.1 mmol/L) was calculated to assess analytical and clinical accuracy. Results: Thirty participants completed the study. CGM derived mean glucose for time in range (TIR= 4-10 mmol/mol) was 36.23% (min= 0%, max= 90%), time above range (TAR >= 10 mmol/mol) was 62.87% and time below range (TBR <= 3.9 mmol/mol) was 1.03%. Mean TIR based on available POCT readings was 40.84%, TAR was 57.24% and TBR 1.81%, showing similar readings as CGM derived glucose metrics. Comparison of the two resulted in a MARD of 17.4%, and median ARD of 12.2% and the outcome of +/-20%/1.1 mmol/L analysis was 72.3%. CEG analysis revealed that 99.3% of the data points fell within the clinically acceptable zones (Zone A and Zone B), and there was a strong correlation (R2=0.82) between CGM and POCT. CGM captured more hypoglycaemic readings in our participants. Conclusion: Our study suggests that CGM and POCT derived glucose metrics are largely similar for in-patients with diabetes and cognitive impairment. CGM remains as a safe and clinically acceptable tool, and able to capture more nocturnal hypoglycaemia compared to POCT in a subgroup of patients. These initial findings show that CGM might be a viable alternative for people with comorbid T2DM and cognitive impairment.

(1) Aims and hypothesisLoss-of-function mutations in SLC30A8, encoding the zinc ion (Zn2+) transporter ZnT8 in pancreatic beta cells, lower type 2 diabetes risk dose-dependently, but the underlying mechanisms remain unclear. Here, we combine proteomic, transcriptomic and functional approaches in human stem cell-derived islet-like clusters bearing common alleles or the inactivating variant R138X. We hypothesized that this variant protects against the deleterious effect of Zn2+ depletion on cell survival and function. (2) MethodsHuman embryonic stem cells INS(GFP/w) (MEL1), and CRISPR/Cas9-derived heterozygous or homozygous R138X lines were differentiated into stem cell-derived islet-like clusters. Intracellular Zn2+ levels were reduced using the chelator N,N,N',N'-tetrakis(2-pyridylmethyl)-1,2-ethanediamine (TPEN). Apoptosis was assessed by TUNEL staining and protein expression by immunofluorescence. Glucose-stimulated calcium (Ca2+) dynamics were measured using the intracellular probe (Cal590) and insulin secretion by homogenous time-resolved fluorescence. Transcriptomic profiling was performed by bulk mRNA sequencing and proteomics by liquid chromatography-tandem mass spectrometry. (3) ResultsIntracellular Zn2+ depletion increased apoptosis in wild-type islet-like clusters, whereas R138X clusters were protected. R138X heterozygous clusters showed a mild increase in GCG+ cells and R138X homozygous clusters exhibited increased NKX6.1+ cells, without affecting polyhormonal populations. These changes were reversed under Zn2+ depletion. Transcriptomic and proteomic analyses, assessing genotype effects while accounting for Zn2+ depletion, showed that R138X clusters (versus wild-type) exhibited upregulation of genes and proteins involved in vesicle trafficking, secretion, Ca{superscript 2} signaling and mitochondrial metabolism, consistent with enhanced glucose-stimulated insulin secretion in homozygous clusters. Conversely, genes and proteins associated with extracellular matrix remodeling, metal-ion handling, apoptosis and cellular stress were downregulated. R138X clusters displayed altered Ca2+ signaling, with decreased area under the curve and oscillation amplitude, but increased frequency. These differences were reversed by TPEN, while Zn2+ depletion impaired Ca2+ response in wild-type clusters. Despite lowered overall activity, R138X homozygous clusters showed enhanced overall cell-cell connectivity, reversed by TPEN treatment. The opposite effects were observed in R138X heterozygous clusters, showing improved connectivity and activity under Zn2+ depletion. (4) Conclusion and interpretationIntracellular Zn2+ depletion compromises islet-like cluster identity and function, while the R138X variant confers protection against these effects. Under Zn2+-depleted conditions, ZnT8 deficiency promotes a more mature and metabolically active state of the R138X clusters, with enhanced Ca2+ signaling and insulin secretion, supported by a structural remodeling and the downregulation of apoptosis and cellular stress. These findings highlight the therapeutic potential of targeting ZnT8 in type 2 diabetes and support its relevance for further improving cell-based therapies. Research in ContextO_ST_ABSWhat is already know about this subject?C_ST_ABSO_LIRare inactivating mutations in the insulin granule-associated zinc transporter gene, SLC30A8/ZnT8, drive lowered type 2 diabetes risk. C_LIO_LIPrevious studies have indicated that apoptosis is lowered, and glucose-stimulated insulin secretion enhanced, after ZnT8 inactivation. C_LIO_LIThe molecular mechanisms underlying these changes are unclear. C_LI What is the key question?O_LIHow do inactivating mutations in SL30A8/ZnT8 lead to lowered apoptosis and enhanced insulin secretion from stem cell-derived islet-like clusters, and is altered susceptibility to intracellular zinc depletion involved? C_LI What are the new findings?O_LIThe rare inactivating R138X mutation in SLC30A8 leads to gene dose-dependent changes in the transcriptome and proteome of islet-like clusters. C_LIO_LIChanges include upregulation of maturity and downregulation of immaturity genes. C_LIO_LIDepletion of intracellular Zn2+ exaggerates the protective effects of the inactivating mutation on apoptosis and insulin secretion C_LI How might this impact on clinical practice in the foreseeable future?O_LIOur findings suggest that careful monitoring of both dietary zinc intake and of circulating levels of zinc ions, whose effects are mitigated in SLC30A8 mutation carriers, may be helpful in some populations to lower diabetes risk. C_LI

Background: Ageing is a systems level biological process underlying the onset and progression of multiple chronic disorders. Rather than arising from a single pathway, age related decline reflects interacting disturbances in metabolic regulation, inflammation, nutrient sensing, cellular stress responses, and tissue repair. Although GLP1 receptor agonists, sodium glucose cotransporter2 inhibitors, metformin, and rapamycin are usually evaluated against disease-specific endpoints. Objective: To develop an SBML compliant quantitative systems pharmacology model in which ageing is the primary pharmacological endpoint and to evaluate which combination therapy provides the greatest benefit for both metabolic and ageing related outcomes. Methods: We developed model comprising four layers: a metabolic/pharmacodynamic layer describing weight loss, HbA1c reduction, and nausea with tolerance; a drug layer capturing class-specific effects of GLP1 agonists, sodium glucose cotransporter2 inhibitors, metformin, and rapamycin; an ageing layer representing damage accumulation, repair capacity, frailty, and biological age gap; and a biomarker layer generating trajectories and estimated glucose disposal rate. Calibration was staged across semaglutide clinical endpoints. Bayesian hierarchical meta analysis, global sensitivity analysis, and practical identifiability analysis were used to assess robustness and interpretability. Results: The model reproduced semaglutide efficacy and tolerability dynamics and supported distinct drug-class profiles across metabolic and ageing axes. Rapamycin showed minimal glycaemic effect but emerged as a dominant driver of repair related ageing outcomes. Combination simulations predicted two distinct optima: one favouring metabolic improvement and one favouring ageing related benefit. Conclusion: The model supports the view that metabolic and ageing optimization are mechanistically distinct objectives and that weight loss and glycaemic improvement alone may be insufficient surrogates for health span benefit.

Aims The oral glucose tolerance test (OGTT) is effective for detecting post-load dysglycemia, but it is burdensome and therefore not routinely used. Continuous glucose monitoring (CGM) offers a convenient way to capture real-world glucose patterns, yet it remains unclear whether CGM-derived metrics reflect OGTT-defined dysglycemia. We therefore aimed to evaluate CGM-derived and clinical metrics for predicting OGTT 2-hour glucose, classifying OGTT-defined dysglycemia, and assessing day-to-day repeatability. Methods We analyzed a cohort with paired free-living CGM and OGTT. Multiple CGM-derived metrics and clinical measures were compared for prediction of OGTT 2-hour glucose, classification of OGTT-defined dysglycemia, and day-to-day stability. Predictive performance was assessed primarily by leave-one-out (LOO) R^2, and day-to-day repeatability by intraclass correlation coefficients (ICC). Results The glycemic persistence index (GPI), a metric integrating the magnitude and duration of glycemic elevation, was the strongest single predictor of OGTT 2-hour glucose (LOO R^2 = 0.439). GPI also showed strong day-to-day repeatability (ICC = 0.665) and ranked first on a combined prediction-stability score. For classification of OGTT-defined dysglycemia, HbA1c had a slightly higher AUC than GPI, but GPI plus HbA1c performed best overall, indicating complementary information. Conclusions GPI was a strong predictor of OGTT 2-hour glucose and showed a favorable balance between predictive performance and day-to-day stability, supporting its potential utility as a CGM-derived marker of dysglycemia.

Non-invasive glucose monitoring (NIGM) has been pursued for decades, yet no device has achieved regulatory approval despite numerous studies reporting high accuracy. This systematic review and meta-analysis of 32 studies (38 cohorts: 20 NIGM, 18 iCGM; N = 1,693) investigated methodological factors underlying this accuracy-regulatory gap. The pooled Mean Absolute Relative Difference (MARD) for NIGM (10.21%; 95% CI: 8.73-11.69%) showed no significant difference from iCGM (11.82%; 95% CI: 10.36-13.29%; p = 0.13), with extreme heterogeneity (I^2 = 95.2%). Meta-regression revealed that study duration was the strongest predictor of NIGM accuracy ({beta} = 3.94, p < 0.001), with MARD degrading from 8.7% in short-term to 15.2% in long-term studies, while iCGM accuracy remained stable. Only 15% of NIGM cohorts validated in the hypoglycemia range, compared to 89% of iCGM studies (p < 0.001). These findings suggest that reported NIGM accuracy is substantially influenced by methodological asymmetries.

Abstract Background: Despite widespread adoption of contemporary guideline-directed medical therapy (GDMT), patients with heart failure with reduced ejection fraction (HFrEF) continue to experience substantial residual morbidity and mortality. Glucagon-like peptide-1 receptor agonists (GLP-1RAs) have demonstrated cardiometabolic benefits in diabetes and obesity, but their role in HFrEF remains uncertain. Objectives: To evaluate whether the addition of GLP-1RAs to optimized GDMT is associated with improved clinical outcomes in patients with HFrEF (NYHA class II-IV). Methods: We conducted a retrospective, multicenter cohort study using the TriNetX Research Network. Adults ([&ge;]18 years) with HFrEF (LVEF [&le;]40%) receiving GDMT between January 2020 and October 2024 were included. Patients treated with GLP-1RAs were compared with those on GDMT alone. After 1:1 propensity score matching, 1,518 patients were included in each cohort. Outcomes over 2 years included all-cause mortality, major adverse cardiovascular events (MACE), critical care utilization, and acute kidney failure. Time-to-event analyses were performed using Kaplan-Meier methods and Cox proportional hazards models. Results: In the matched cohort (mean age [~]63 years, [~]33% female), GLP-1RA use was associated with significantly lower all-cause mortality compared with GDMT alone (12.8% vs 23.8%; hazard ratio [HR] 0.48; 95% CI 0.40-0.57; p<0.001), corresponding to an absolute risk reduction of 11.0%. MACE was also reduced (35.8% vs 47.4%; HR 0.64; 95% CI 0.58-0.72; p<0.001). Additionally, GLP-1RA therapy was associated with lower critical care utilization (18.4% vs 28.9%; HR 0.55; 95% CI 0.47-0.64; p<0.001) and reduced acute kidney failure (29.2% vs 37.3%; HR 0.67; 95% CI 0.59-0.76; p<0.001). Rates of pancreatitis and substance-related disorders were low and not significantly different between groups. Conclusions: Among patients with HFrEF receiving contemporary GDMT, adjunctive GLP-1RA therapy was associated with significant reductions in mortality, cardiovascular events, and healthcare utilization. These findings support the potential role of GLP-1RAs as a novel, mechanism-complementary therapy in HFrEF. Prospective randomized trials are needed to confirm these observations and determine whether GLP-1RAs should be incorporated as a fifth pillar of GDMT.

Background Glycated haemoglobin (HbA1c) underpins type 2 diabetes (T2D) and prediabetes management worldwide and reflects both glycaemia and erythrocyte biology. A missense variant in PIEZO1 (rs563555492T), carried by 1 in 12 South Asians, has been associated with a nonglycaemic reduction in HbA1c. We aimed to further characterise this association and evaluate its clinical consequences. Methods We undertook genetic and linked health data analyses across two cohorts: 19,898 (37.4% female) South Indians from the Madras Diabetes Research Foundation (MDRF) and 43,011 (54.4% female) British Bangladeshis and British Pakistanis in Genes & Health. In MDRF, we tested associations with glycaemic and erythrocytic traits using additive genetic models. In Genes & Health we modelled diagnosis of prediabetes, T2D, and diabetic eye disease using flexible parametric survival models. Ten-year absolute risks were estimated for a population aged 40-50 years. Findings PIEZO1 rs563555492T was associated with erythrocytic traits and lower HbA1c, but not with fasting glucose, postprandial glucose, or C-peptide. This variant reduced risk of prediabetes (HR 0.63, 95% CI 0.58-0.69) and T2D (0.85, 0.78-0.93) diagnosis, and increased risk of diabetic eye disease among individuals with T2D (1.20, 1.01-1.43). Modelling suggested approximately 1,019 missed prediabetes and 303 missed T2D diagnoses per 100,000 adults over 10 years. Interpretation An ancestry-enriched PIEZO1 variant is associated with lower HbA1c independent of glycaemia, reduced prediabetes and T2D diagnosis suggesting delayed detection, and increased complication risk. Reliance on HbA1c may systematically underestimate glycaemic risk in a substantial minority of South Asians. Funding The Wellcome Trust; NIHR

ABSTRACT Objective To estimate the benefit and risk of replacing regular salt with potassium-enriched salt. Design Comparative risk assessment modelling. Setting Worldwide Participants Adult populations aged 25 and above. Intervention (1) worldwide replacement of all salt (discretionary salt used for seasoning or cooking in the home, and non-discretionary salt used in processed and restaurant foods); (2) worldwide replacement of just discretionary salt; (3) worldwide replacement of just non-discretionary salt; (4) replacement of discretionary salt just for people with diagnosed hypertension; and (5) replacement of discretionary salt just for people with treated hypertension. Main outcome measures For scenarios 1-3, we estimated benefits including deaths, new cases and disability-adjusted-life-years (DALYs) from cardiovascular disease and chronic kidney disease (CKD), from blood pressure-lowering as well as harms (CVD deaths) caused by hyperkalaemia among people with CKD stages G3-G5. Results Replacement of all salt worldwide could prevent 2.96 (95% uncertainty interval 2.81-3.12) million deaths, 10.17 (9.59-10.70) million new cases of disease and 69.43 (65.61-72.92) million disability-adjusted life years (DALYs) each year. These figures represent 14.6%, 13.1% and 16.5% of the annual global disease burden attributable to CVD and CKD. Replacement of all discretionary salt (1.85, 1.74-1.97 million deaths) would have a greater impact on mortality than replacement of all non-discretionary salt (1.56, 1.46-1.67 million deaths). In people with CKD Stage G3-G5, there would be a net benefit - replacement of all salt would prevent 0.75 (0.71-0.80) million deaths but might cause 0.10 (0.09-0.11) million deaths from hyperkalaemia. Discretionary salt replacement only among diagnosed or treated hypertensives would prevent 0.59 (0.55-0.63) million and 0.48 (0.45-0.52) million deaths, respectively. Conclusion Switching regular salt to potassium-enriched salt appears to offer large potential for health gains under diverse scenarios, including for people with CKD.

BackgroundNon-adherence to lipid-lowering therapy (LLT) affects up to half of patients and contributes substantially to preventable cardiovascular morbidity and mortality. Existing measures, such as the proportion of days covered, provide cross-sectional summaries but fail to capture the dynamic patterns of adherence over time. Although group-based trajectory modelling identifies distinct longitudinal adherence patterns, no approach currently predicts trajectory membership prospectively while incorporating patient-reported barriers. We developed BRIDGE, a barrier-informed Bayesian model to predict adherence trajectories and identify their underlying drivers. MethodsBRIDGE incorporates patient-reported barriers as structured prior information within a Bayesian framework for adherence-trajectory prediction. The model was designed not only to estimate which patients are likely to follow different adherence trajectories, but also to generate clinically interpretable probability estimates that help explain why those trajectories may arise and what modifiable factors may be most relevant for intervention. ResultsBRIDGE achieved a macro AUROC of 0.809 (95% CI 0.806 to 0.813), comparable to random forest (0.815 (95% CI 0.812 to 0.819)) and XGBoost (0.821 (95% CI 0.818 to 0.824)), two widely used machine-learning benchmarks for structured clinical prediction. Calibration was superior to random forest (Brier score 0.530 vs 0.545; ), and performance was stable across six independent training runs (AUROC SD = 0.003). Incorporating barrier-informed priors improved accuracy by 3.5% and calibration by 5.5% compared to flat priors, showing that incorporation of patient-reported barriers added value beyond electronic medical record data alone. Four clinically distinct adherence trajectories were identified: gradual decline associated with treatment deprioritisation amid polypharmacy (10.4%), early discontinuation linked to asymptomatic risk dismissal (40.5%), rapid decline associated with intolerance (28.8%), and persistent adherence (20.2%). Counterfactual analysis identified trajectory-specific intervention levers. ConclusionsBRIDGE provides accurate and well-calibrated prediction of adherence trajectories while offering clinically actionable insights into their underlying drivers. By integrating patient-reported barriers with routine clinical data, the model supports targeted, mechanism-informed interventions at the point of prescribing to improve adherence to cardioprotective therapies. FundingMRFF CVD Mission Grant 2017451 Evidence before this studyWe searched PubMed and Scopus from database inception to December 2025 using the terms "medication adherence", "trajectory", "prediction model", "Bayesian", "lipid-lowering therapy", and "barriers", with no language restrictions. Group-based trajectory modelling has consistently identified three to five adherence patterns across cardiovascular cohorts; however, these applications have been descriptive rather than predictive. Machine-learning models for adherence prediction achieve moderate discrimination but treat adherence as a binary or continuous outcome, thereby overlooking the clinically meaningful heterogeneity captured by trajectory approaches. One prior study applied a Bayesian dynamic linear model to examine adherence-outcome associations, but it did not predict adherence trajectories or incorporate patient-reported barriers. To our knowledge, no published model integrates patient-reported barriers into trajectory prediction. Added value of this studyBRIDGE is, to our knowledge, the first model to incorporate patient-reported adherence barriers as hierarchical domain-informed priors within a Bayesian framework for trajectory prediction. Using 108 predictors derived from routine electronic medical records, the model achieves discrimination comparable to state-of-the-art machine-learning approaches while additionally providing uncertainty quantification, barrier-level interpretability, and counterfactual insights to inform intervention strategies. The identified trajectories differed not only in adherence level but also in switching behaviour, drug-class evolution, and medication burden, suggesting distinct underlying mechanisms of non-adherence that may require tailored clinical responses. Implications of all the available evidenceEach adherence trajectory implies a distinct intervention target: asymptomatic risk communication for early discontinuers (40.5% of patients), proactive tolerability management for rapid decliners, medication simplification for patients with gradual decline associated with polypharmacy, and maintenance support for persistent adherers. By integrating routinely collected clinical data with patient-reported barriers, BRIDGE can be deployed within existing primary care EMR infrastructure to generate actionable, trajectory and patient--specific recommendations at the point of prescribing, helping to bridge the gap between adherence measurement and targeted adherence management.