Diabetes Care

Aims/Hypothesis: Atypical forms of diabetes often provide diagnostic challenges and are suboptimally treated. We sought to determine whether type 1 and 2 diabetes polygenic scores (PS) would help improve classification of islet autoantibody-negative (IAb-) atypical diabetes cases. Methods: We implemented type 1 diabetes PS (T1D PS) and type 2 diabetes PS (T2D PS) in 309 IAb- individuals' genome sequencing from the Rare and Atypical Diabetes Network (RADIANT), the largest and most comprehensively phenotyped collection of unsolved and atypical diabetes cases. We performed regression analyses to assess associations between PS, clinical characteristics, and glycemic measures. Results: Both T1D and T2D PS were significantly higher in RADIANT than in ancestry-matched controls from UK Biobank. Both PS were associated with C-peptide measures throughout participant oral glucose tolerance tests (OGTT), although in opposite directions; T1D PS was associated with lower C-peptide measures, while T2D PS was associated with higher measures. Participants with T1D PS above a previously established optimal PS value for differentiating cases and controls (T1D PS GRS2>12.88) had 13-fold higher odds of both insulin deficiency on OGTT and use of both basal and bolus insulin therapy. Conclusions/Interpretation: Individuals in RADIANT with ambiguous diabetes subtypes displayed genetic enrichment for both type 1 and type 2 diabetes, despite ascertainment to remove standard type 1 and type 2 diabetes. T1D PS identified individuals with an unrecognized "type 1 diabetes-like" phenotype with insulin deficiency and need for intensive insulin in the absence of islet autoantibodies. PS may help identify individuals with atypical diabetes who will ultimately benefit from insulin therapy.

Most polygenic scores (PS) for type 1 diabetes were developed using European (EUR) ancestry datasets, limiting performance in non-European (non-EUR) populations. We evaluated novel type 1 diabetes PS across diverse populations to assess whether newer models improve prediction in underrepresented populations. Seven type 1 diabetes PS (T1D GRS2, T1D GRS2', T1D GRSHLA, T1GRS, TA-PS, TA-PS (S), T1D MAPS) were evaluated in All of Us and Mass General Brigham Biobank. Predictive performance was assessed using the area under the receiver operating characteristic curve (AUC). T1D GRS2 and T1D MAPS showed the highest AUC in All of Us, while other scores demonstrated comparatively lower performance. These highest-performing scores were then evaluated in a meta-analysis across three additional biobanks (Genomic Health Initiative at Endeavor Health, Penn Medicine BioBank, Geisinger MyCode). Among 2,782 individuals with type 1 diabetes and 546,577 controls, T1D MAPS showed comparable performance to T1D GRS2 in EUR populations but significantly improved discrimination in non-EUR populations (meta-analysis {Delta}AUC=0.049, p=1.7x10-7). Overall, T1D MAPS improves prediction in non-EUR populations, highlighting the importance of multi-ancestry approaches for equitable genetic risk prediction. These findings could inform precision medicine in diverse populations.

Type 2 diabetes is a complex metabolic disease with a strong genetic component, yet this genetic risk is driven by common variants in up to 600 loci with small effect sizes. Variants in the STEAP2 locus, encoding Six-transmembrane epithelial antigen of the prostate-2, are highly associated with altered glycemic traits and type 2 diabetes risk. To elucidate its function in pancreatic beta-cells, we utilized Crisp-Cas9 assisted homologous recombination to derive a conditional null allele for Steap2 (Steap2fl/fl) in mice and crossed this to the rat insulin promoter (Rip)-Cre transgene. Ablation of Steap2 induced glucose intolerance, blunted glucose-stimulated Ca2+ mobilization and stunted first phase glucose-simulated insulin secretion. In contrast, the incretin effect and second phase insulin secretion were not affected. Islet respirometry and transmission electron microscopy (TEM) identified disrupted cristate morphology and impaired glucose-stimulated oxygen consumption as causally responsible for the observed, impaired triggering pathway of insulin secretion. These findings suggest that at least part of the genetic risk for T2D conferred by Steap2 variants is likely due to its function in maintaining optimal mitochondrial respiration in pancreatic beta-cells.

BCG is a well recognized old generic drug that can mold the human immune system through Immune Training. Broad basic science studies support Immune Training, but formal randomized placebo control trials are frequently lacking for confirmation of human benefits. Here we report on a randomized, double-blind, placebo-controlled phase 2 trial with up to 8 years of follow-up. The primary outcome was mean percent change from baseline in HbA1c. At year 5, HbA1c in the BCG group was reduced from baseline by 7.04% (P=0.0006) and at year 8 by 12.84% (P=0.0001), whereas HbA1c did not change from baseline in the placebo group at either time point. Longitudinal percentage changes in HbA1c from baseline using mixed model repeated measures analysis with a comparison of BCG versus Placebo arms was significant (p=0.0017). This shows durable long term improvements lowering of HbA1c only with BCG immunotherapy. Secondary outcomes were also significant. There was a statistically significant reduction in average insulin dose only in the BCG-treated group (P=0.024). Glycemic improvements occurred without recovery of C-peptide from negligible baseline levels, suggesting no pancreas contribution. Blood sugar values obtained from continuous glucose monitoring (CGM) similarly showed BCG immunotherapy lowers blood sugars compared to the Placebo arm (P=0.0189). CGM data also showed BCG immunotherapy resulted in an up to 183.7% improvement over baseline in time spent in normoglycemia (blood sugar in the normal range of 70-99 mg/dL) (P=0.0391). A sensitivity analysis confirmed BCG specific reductions in HbA1c were robust and durable at least to Year 08 (P<0.0001). BCG was safe. These finding support improved blood sugar control through immune training of metabolism without a contribution of the pancreas even after long standing T1D. Trial registration: NCT02081326.

Background. Cardiovascular disease accounts for most mortality in type 2 diabetes (T2D), yet treatment is anchored on glucose-derived metrics and fasting insulin is rarely measured. We tested whether fasting insulin carries cardiovascular-mortality information across the dysglycaemic spectrum and approaches non-diabetic levels with longer oral-therapy T2D duration. Methods and Findings. We analysed six NHANES cycles [2007-2018] linked to National Death Index follow-up through 2019. Baseline characteristics were described in participants with complete kidney-function data: normoglycaemic (n = 2,913), pre-diabetes (n = 3,993), and oral-therapy T2D (n = 1,381). Survey-weighted Cox models used the covariate-complete mortality sample (pre-diabetes n = 4,019; oral-therapy T2D n = 1,387) and adjusted for age, sex, race/ethnicity, BMI, smoking, physical activity, education, poverty:income ratio, and insulin assay generation. Per +1 natural-log-unit fasting insulin, all-cause hazard ratios (HRs) were 1.69 (95% CI 1.14-2.50; P = 0.008) in pre-diabetes and 0.71 (0.51-0.98; P = 0.039) in oral-therapy T2D; cardiovascular HRs were 3.09 (1.69-5.63; P < 0.001) and 0.50 (0.26-0.99; P = 0.046), respectively. Cancer mortality was not associated with fasting insulin. In oral-therapy T2D, geometric-mean fasting insulin remained 1.6- to 2.3-fold the normoglycaemic referent across duration bands. After BMI adjustment, fasting insulin declined during the first five years (-4.0%/year, P = 0.018) and was flat thereafter (-0.1%/year, P = 0.66). Conclusions. Fasting insulin predicted cardiovascular mortality in pre-diabetes. In oral-therapy T2D, the inverse association was most consistent with survivor effects and accumulated renal and vascular damage. Fasting insulin remained above normoglycaemic levels throughout treated T2D.

Objective: To estimate how often remission of type 2 diabetes is recorded in routine care, how long it lasts, and what ends it, separating a return of hyperglycemia from a restart of treatment. Research design and methods: We studied 136,781 adults aged 18 years or older with laboratory confirmed type 2 diabetes in the Protege linked electronic health record (EHR) and claims database. The 96,817 adults with glucose-lowering treatment recorded at or before cohort entry formed the primary (previously treated) cohort; 39,964 adults with no treatment recorded at entry were analyzed in parallel. Remission required two HbA1c values <6.5%, 90 to 365 days apart, the first at least 3 months after all glucose-lowering drugs were discontinued, with no therapy recorded between them. After remission we followed glycemic relapse (HbA1c over 6.5%) and treatment restart (a new outpatient prescription or dispensed fill) separately, with death as a competing event (Aalen Johansen). Results: Remission was documented in 4.33% of previously treated adults cohort and 15.57% in the cohort of untreated adults at entry. Five-year cumulative incidence (Aalen Johansen) was 3.82% (95% CI 3.69 ;3.93) and 13.27% (12.90;13.59) in each cohort, respectively. Remission was less common with greater baseline treatment burden: exploratory adjusted 5-year incidence was 4.65% in adults with 1 glucose-lowering class with a treatment episode recorded at or before entry, 3.62% with two, 2.69% with three, and 2.02% with four or more such drugs.. The Median Kaplan Meier duration of first remission was 226 days (IQR 93 to 855) in previously treated adults and 371 days (166 to 1,027) in adults untreated at entry; 37.9% (treated cohort) and 23.1% (untreated cohort) of episodes had ended by 152 days. Among remission episodes that had ended, median duration was 159 days (71 to 362) and 265 days (129 to 565) for the treated and untreated at entry cohort, respectively. Within 5 years of remission in previously treated adults, the first event ending remission was glycemic relapse in 31.94%, treatment restart in 47.83%, and death in 4.65%.Treatment restart was about 1.5 times as common as glycemic relapse as the first event ending remission. A second remission followed within 5 years in 19.53% of previously treated and 24.10% of untreated remitters. Conclusions: Recorded remission was uncommon and short-lived, and it ended more often with a treatment restart than with a rise in HbA1c. Studies of remission in real-world data should report relapse and restart separately and state how they confirm remission and establish that treatment stopped.

Background. Type 2 diabetes (T2D) and coronary artery disease (CAD) frequently co-occur, yet the biological pathways that jointly determine risk remain incompletely understood. Most genetic studies have examined shared risk from a single-disease perspective, limiting insight into the mechanisms that generate discordant risk between conditions. Methods. We applied PLACO to multi-ancestry GWAS data of T2D and CAD to identify shared loci, prioritising shared causal signals using colocalisation. Shared variants were clustered by their associations with 77 cardiometabolic traits, and cluster-specific genetic risk scores (GRS) were tested for association with 17 clinical biomarkers and 1,254 binary outcomes in 378,772 UK Biobank (UKB) participants. Two-sample Mendelian randomisation (MR) was used to test the causal role of liver fat. Results. We identified 149 loci shared between T2D and CAD; most novel loci had discordant effects (35 of 42), in contrast to the predominantly concordant signals reported previously. Clustering 187 independent shared variants revealed seven mechanistic clusters, three of them centred on liver fat and defined by discordant T2D?CAD effects. Enrichment analyses and cluster-GRS associations in UKB highlight associations between higher liver fat and T2D risk with a cardioprotective lipid profile and reduced CAD risk. Genetically higher liver fat increased T2D risk but lowered CAD risk in MR analyses; partitioning liver fat instruments by their effect on ApoB-containing lipoproteins indicates that the CAD effects are determined more by effects of circulating ApoB rather than liver fat itself. Conclusions. Liver fat largely sets the direction of T2D risk, whereas the fate of that lipid, retained in the liver with low circulating ApoB or exported as ApoB-containing lipoproteins, sets the direction of CAD risk. This liver-centric partitioning provides a mechanistic framework for the discordant cardiometabolic effects of hepatic lipid and lipid-lowering pathways, with implications for precision prevention.

Aims/hypothesis Higher body mass index (BMI) is associated with higher levels of HbA1c and glucose in conventional observational studies from sub-Saharan Africa, but its causal relationship in this population has not been explored. Mendelian randomization (MR) which leverages genetic variants can strengthen causal inference. However, its application in African ancestry populations is limited. The aim of this study was to determine whether causal effects of BMI on glycated haemoglobin (HbA1c) and random glucose differ between African and European populations. Methods We used two-sample MR to estimate the effects of BMI on HbA1c and random glucose in adults of African and European ancestries. We conducted a cross-ancestry BMI genome-wide association study (GWAS) from the Africa-Wits International Network for the Demographic Evaluation of Populations and Their Health (INDEPTH) Partnership for Genomic Studies (AWI-Gen) dataset of African adults (N=10,476) and the largest BMI GWAS in Europeans (N~700,000). From the cross-ancestry GWAS we identified 428 independent genome-wide significant variants and of those, 363 single nucleotide polymorphisms (SNPs) had consistent direction of effect in both Africans and Europeans. These variants were then used as genetic instruments to proxy BMI for both Africans and Europeans. Primary outcome data for African and European populations were obtained from UK Biobank summary statistics for HbA1c (5,790 Africans and 400,825 Europeans) and random glucose (5,750 Africans and 314,916 Europeans), with additional results for HbA1c from the MAGIC multi-ancestry GWAS comprised of Ugandan individuals (N=4,441), African Americans (N= 6,647), and Europeans (N=146,806). Main analyses used the inverse variance weighted (IVW) method, with sensitivity analyses conducted using MR-Egger, weighed median and weighted mode approaches. Results The main IVW analyses in UK Biobank provided support for higher BMI causally increasing HbA1c levels in both Africans (0.26 SD higher HbA1c per 1 SD BMI, 95% CI 0.07, 0.45) and Europeans (0.27 SD higher HbA1c per 1 SD BMI, 95% CI 0.22, 0.32). UK Biobank main analyses also supported higher BMI increasing random glucose in Africans (0.21 SD higher mean glucose per 1 SD BMI, 95%CI 0.03, 0.37) and Europeans (0.15 SD higher mean glucose per 1 SD BMI, 95%CI 0.12, 0.18). Sensitivity analyses suggested these results were not biased by unbalanced horizontal pleiotropy. Results from MAGIC also showed that higher BMI causally increased HbA1c in Europeans (0.04% higher HbA1c per 1 SD BMI, 95% CI 0.02, 0.05), though results for African Americans (0.01% higher HbA1c per 1 SD BMI, 95% CI -0.05, 0.07) and Ugandans (0.02% lower HbA1c per 1 SD BMI, 95% CI -0.10, 0.05) spanned the null. Conclusion/interpretation We have found broadly similar effects of BMI on HbA1c and random blood glucose in African and European populations. However, much larger GWAS of glycaemic traits in African and other non European populations are needed to strengthen causal inference and support equitable translation of these findings. The method that we have used to obtain identical strong genetic instrumental variables (IVs) for both European and African populations may have value for other MR studies interested in exploring differences in effects between different population groups.

Abstract Objective: To identify clinical and genetic factors associated with variation in glycemic response to glucagon-like peptide-1 receptor agonist (GLP-1RA) therapy among adults with type 2 diabetes, with a focus on common GLP1R variations, polygenic risk load, and pancreas-specific regulation annotation. Research Design and Methods: We conducted a retrospective cohort study using electronic health record (EHR)-linked biobank data from the All of Us research workbench platform that included 5784 adults with type 2 diabetes who initiated GLP-1RA therapy. Baseline HbA1c was measured within 3 months before medication initiation, and follow-up HbA1c was measured after 3 months. The patients with type 2 diabetes were classified as good responders (HbA1c reduction [&ge;] 2.5 percentage point) or poor responders (HbA1c reduction <0.5 percentage point). Models adjusted for demographic characteristics, anthropometric and metabolic measures, blood pressure, body mass index (BMI), lipid profile, liver function tests, polygenic risk score, and GLP1R variant carrier status were compared between the two groups. Common GLP1R variations were further investigated for carrier frequency and associated HbA1c levels before and after medication use. Results: The cohort included 3194 good responders and 2590 poor responders. Good responders were younger than poor responders (55.2 vs. 58.6 years) and had significantly higher glycemic improvement. HbA1c levels fell from 9.2% to 6.3% in good responders and 8.4% to 8.1% in poor responders, resulting in an absolute HbA1c reduction of 2.9% and 0.3%, respectively. Good responders also showed larger decreases in fasting glucose, BMI, systolic and diastolic blood pressure, triglycerides, total cholesterol, LDL cholesterol, and liver enzymes, as well as minor improvements in HDL-C. After multivariable adjustment, Poor responders had a greater T2D polygenic risk score (0.38 vs. 0.21), more GLP1R coding variant carrier status (10.1% vs. 8.0%), and a higher overall GLP1R variant burden (22.8% vs. 19.2%). Variant-level studies revealed rs2268650 and rs2003132 enrichment among poor responders, with negative post-treatment HbA1c patterns in carriers, whereas good-response carriers showed significant HbA1c improvement. Conclusions: Response to GLP-1RA in T2D is associated with baseline clinical and metabolic status, as well as inherited genetic susceptibility, which includes common GLP1R variation and a larger polygenic risk burden. Integrating clinical and pharmacogenomic profiling may improve patient classification and provide insight into treatment failure in poor responders.

Introduction: Ethnic minority populations are disproportionately affected by type 2 diabetes (T2D). We investigated ethnic differences in the risks of diabetes-related complications and mortality in the Netherlands, and identified clinical, sociodemographic and environmental determinants associated with these differences. Methods: We included 175,112 adults with T2D from the dynamic prospective primary care cohort DIAMANT. DIAMANT data were linked to national registries from Statistics Netherlands and GECCO, a database integrating geographic, environmental and contextual exposures. Ethnic differences in complications risks were estimated using Cox proportional hazards models. Potential mediating factors were explored using machine-learning-based variable selection and association decomposition approaches. Results: At baseline, mean age was 65.4 (SD 12.3) years, 46.6% were women and median T2D duration was 11.3 [IQR 7.2; 15.8] years. Substantial heterogeneity in complication risk was observed across ethnic groups compared with Dutch-origin individuals. Retinopathy risk was consistently higher across nearly all non-Dutch groups (HRs 1.37-2.37). For macrovascular complications, elevated risks were mainly observed among Surinamese and Turkish individuals, including heart failure (HR 1.30 and 1.46, respectively). In contrast, individuals of Indonesian and Moroccan origin showed similar or lower risk for most complications. Environmental exposures (e.g. air pollution, temperature) and sociodemographic factors (e.g. main benefit, household composition) accounted for a substantial attenuation of several observed associations. Discussion: Substantial ethnic differences exist in risks of T2D complications and mortality, which showed to be heterogeneous across outcomes and populations. Our findings suggest that a considerable proportion of these disparities is attributable to differences in environmental and sociodemographic context, highlighting the importance of interventions that take into account differences in environmental and socio-demographic context.

Type 2 diabetes (T2D) is a multifactorial metabolic disorder with an increasing global prevalence and significant health burdens. Early identification of individuals at high risk is crucial for timely intervention and prevention of T2D and complications. This study aims to investigate the association between the blood plasma proteome and T2D, identify protein biomarkers associated with incident T2D, and explore the underlying biological pathways involved in the disease development in the Trondelag Health Study (HUNT). The HUNT Study is a population-based cohort with four waves of enrolment beginning in 1984. Samples from HUNT3 were analysed with SomaScan including 3,221 using SomaScanv4.0 (HUNT-Soma5k, ~5,000 proteins) and 2,181 on SomaScanv4.1 (HUNT-Soma7k, ~7,000 proteins). We performed logistic regression and least absolute shrinkage and selection operator (LASSO) to generate the protein risk scores, and gene set enrichment analysis (GSEA) to identify potential biological pathways for incident T2D. We identified 313 (308 proteins) and 142 (128 proteins) aptamers that are significantly associated with incident T2D, in HUNT-Soma5k and HUNT-Soma7k, respectively. In HUNT-Soma5k, MXRA8 has strongest association with decreased risk and PLXB2 has strongest association with increased risk; while IGFBP2 has strongest association with decreased risk and INHBC has strongest association with increased risk for incident T2D in HUNT-Soma7k. The most significant pathway from GO Biological Process is organic acid metabolic process in both datasets. The associated proteins and biological pathways identified represent insights into the underlying molecular mechanism of T2D and may serve as potential biomarkers for risk prediction and prevention for T2D.

Objectives. To evaluate the impact of reimbursement restrictions for glucagon-like peptide-1 receptor agonists (GLP-1RAs) for type 2 diabetes, introduced in Denmark in November 2024, on injectable semaglutide (Ozempic) utilization patterns and subsequent HbA1c changes among discontinuers. Design. Nationwide registry-based cohort study. Setting. Denmark. Participants. Adults treated with injectable semaglutide for diabetes (January 2018 to December 2025). Main outcome measures. We described temporal patterns in injectable semaglutide use before and after the policy change. Among semaglutide continuers after the policy change, we assessed whether continuation met a key criterion in the new policy: non-feasibility of sodium-glucose cotransporter 2 inhibitor use and high cardiovascular risk. We characterized semaglutide discontinuers around the policy implementation (March 2024 to November 2024) and subsequent treatment switches. Among discontinuers, we evaluated HbA1c changes and performed interrupted time series (ITS) analyses. Results. Following the policy change, use of injectable semaglutide declined modestly before subsequently increasing. Among 61,120 individuals classified as semaglutide continuers, 27,143 (44%) were already using an SGLT2i. Of the remaining 33,977 (56%), only 1,862 (5.5%) met a key reimbursement criterion (i.e., non-feasibility of SGLT2i use and high cardiovascular risk). Among 79,305 individuals with a semaglutide fill between March 2024 and November 2024, 22,096 (28%) were classified as discontinuers. Within six months, ~40% of discontinuers switched to other glucose-lowering therapies, most commonly SGLT2is (24%). 37% of discontinuers later reinitiated semaglutide. Among individuals with an on-treatment HbA1c measurement (within 12 months before their last semaglutide fill) and an off-treatment HbA1c measurement (6-12 months after their last semaglutide fill) (n=13,017), mean HbA1c increased from 49 to 57 mmol/mol (mean change +7.4 mmol/mol, 95% CI 7.2-7.6). ITS analysis showed that HbA1c increased by 5.9 mmol/mol (95% CI 5.1-6.7) at six months post-discontinuation, which attenuated to 3.1 mmol/mol (95% CI 2.2-4.1) at 12 months; raw monthly means (not included in the ITS model) suggested this persisted through 18 months. Conclusions. Following the policy change, population-level use of injectable semaglutide declined modestly before increasing again. Most discontinuers did not initiate another glucose-lowering therapy and experienced an increase in HbA1c that did not fully return to pre-discontinuation levels during follow-up.

Background: Type 2 diabetes (T2D) is associated with elevated rates of several cancers and is increasingly recognized as a heterogeneous disease, but whether its clinically distinct subtypes carry different cancer risks is unknown. Methods: In this matched retrospective cohort study using electronic health record data from the Epic Cosmos Research Platform (2012-2025), adults with newly diagnosed T2D were classified into severe insulin-deficient (SIDD, 21.6%), mild obesity-related (MOD, 23.5%), mild age-related (MARD, 40.7%), or mixed (14.1%) subtypes using validated algorithms and matched to adults without diabetes on age, sex, and body mass index. Cause-specific Cox models estimated adjusted hazard ratios (HRs) for seven site-specific cancers, accounting for competing risks. Cancer screening uptake was assessed as a secondary outcome. Results: Among 575,139 adults with T2D and 689,719 without diabetes (median follow-up, 3.8 years), MARD had the highest cancer incidence (17.3 per 1,000 person-years). Relative to adults without diabetes, rates of colorectal, pancreatic, liver, endometrial, and ovarian cancer were elevated across subtypes, with the highest hazards in SIDD (HR=3.87, 95% CI=3.51 to 4.27) and mixed phenotypes. Prostate cancer rates were lower in all subtypes, most markedly in MOD (HR=0.60, 95% CI=0.55 to 0.64). Rates of breast cancer were higher among mixed (HR=1.12, 95% CI=1.05 to 1.19) and lower among MOD (HR=0.85, 95% CI=0.80 to 0.90). Mammography and prostate-specific antigen screening were lower across subtypes. Conclusions: Site-specific cancer incidence and screening uptake differed across clinically defined subtypes of T2D. Subtype classification from routine clinical data may inform targeted cancer surveillance, though further study is needed before clinical use.

Background Glucagon-like peptide-1 (GLP-1) receptor agonists and sodium-glucose cotransporter-2 (SGLT2) inhibitors are increasingly used for type 2 diabetes. Despite established metabolic, cardiovascular, and renal benefits, it remains uncertain whether GLP-1 receptor agonists are associated with longer clinically recorded Alzheimer's disease (AD)-type dementia-free survival than sulfonylureas (SU) or SGLT2 inhibitors. Methods Using All of Us electronic health records, we emulated target trials among adults aged 55 years or older with type 2 diabetes, a 12-month washout, and no prior dementia. We compared GLP-1 receptor agonists with SU and SGLT2 inhibitors. Propensity score weighting and doubly robust estimation addressed confounding. Causal survival forests estimated individualized treatment effects on 48-month RMST free from clinically recorded AD-type dementia. Findings In the GLP-1 receptor agonist versus SU comparison (6,328 individuals; 48-month NNT approximately 202), initiation was associated with a small but statistically significant increase in AD-type dementia-free survival (ATE 0.21 months; 95% CI: 0.07-0.35). The highest-benefit stratum gained 0.45 months (95% CI: 0.28-0.62). In the SGLT2 inhibitor comparison (3,070 individuals; 48-month NNT approximately 245), the average effect was not statistically significant (ATE 0.06 months; 95% CI: -0.18 to 0.31), but treatment effects were heterogeneous. The highest-benefit stratum gained 0.83 months (95% CI: 0.49-1.17). Predicted benefit was associated with older age, insulin use, lower HbA1c, and lower BMI. Interpretation GLP-1 receptor agonists may delay clinically recorded AD-type dementia compared with SU. Comparative effectiveness versus SGLT2 inhibitors may vary, supporting further study. Given the hypothesis-generating nature of these findings, diabetes treatment selection should remain guided by glycemic, cardiovascular, renal, and patient-centered considerations. Funding German Federal Ministry of Research, Technology and Space (03LWH0181B)

Aims: The risks of dementia, stroke, and mortality increase from normoglycemia to prediabetes and type 2 diabetes (T2D). Blood pressure variability (BPV) is associated with adverse vascular and neurological outcomes, but its role in glycemia-associated risks remains unclear. We examined the interplay between glycemia, BPV, and these outcomes. Methods and Results: In a large prospective cohort, visit-to-visit BPV was quantified using absolute and directional measures of systolic (SBP), diastolic (DBP), mean arterial (MAP), and pulse pressure (PP). Glycemic status was defined as normoglycemia, prediabetes, and T2D. Time-updated Cox models estimated outcome associations, adjusting for confounders and mean blood pressure. We evaluated the joint and independent associations of BPV and glycemic status with outcomes, effect modification, and attenuation of glycemia-associated risks after BPV adjustment. Among 57,611 participants (median follow-up, 5.1 years; IQR, 3.3-9.5 years), compared with normoglycemia and low BPV, T2D with high SBP variability was associated with higher risks of all-cause mortality (HR 2.80, 95% CI 2.12-3.69) and nominally higher risk of all-cause dementia (HR 2.46, 95% CI 1.37-4.42). All absolute BPV measures were independently associated with mortality, while DBP and MAP variability were associated with overall stroke after FDR correction. Additional adjustment for BPV minimally attenuated glycemia-associated risk, and no multiplicative interaction remained significant after multiple-testing correction. Conclusions: Absolute BPV was associated with mortality, and DBP and MAP variability with overall stroke, after accounting for glycemic status and mean blood pressure. Additional BPV adjustment changed the glycemic association only minimally.

Body mass index (BMI) alone may underestimate clinically relevant obesity because it does not capture central fat distribution. We compared obesity prevalence in Mexico using BMI-only criteria, adiposity-confirmed criteria, and the clinical obesity definition proposed by the Lancet Diabetes and Endocrinology Commission. We conducted a population-based, cross-sectional study of 13,160 adults aged 18 years or older who participated in the 2018-2019 Mexican National Health and Nutrition Survey (ENSANUT). Obesity prevalence was estimated through survey-weighted analyses that accounted for the complex sampling design. The weighted prevalence of obesity based on BMI was 34.5% (95% CI, 33.1-35.9), while 30.9% (95% CI, 29.6-32.2) met criteria for clinical obesity. One quarter of individuals with clinical obesity had a BMI under 30 kg/m2, a phenotype more common among older adults. Half of adults with a BMI under 30 kg/m2 showed elevated central adiposity. BMI alone underestimates clinically relevant obesity in Mexican adults. Adding waist-based measurements could improve the identification of individuals with excess fat and metabolic risk, both in clinical settings and population monitoring.

Glucagon-like peptide-1 (GLP-1) receptor agonists produce less weight loss in people with type 2 diabetes than without, and higher compensatory doses are limited by gastrointestinal adverse events and lean-mass loss--leaving patients with obesity, type 2 diabetes, and metabolic dysfunction-associated steatohepatitis (MASH) inadequately treated. We tested whether linafexor, a pulsatile farnesoid X receptor (FXR) agonist, could augment the weight-loss efficacy of low-dose semaglutide in this population while preserving tolerability. In this multicenter, randomized, double-blind, placebo-controlled, phase 2 trial, 62 adults with obesity (body-mass index, 30-45 kg/m2), treatment-naive type 2 diabetes, and MASH (MRI-PDFF [&ge;]10%) were assigned to linafexor (4 mg orally once daily) or placebo, each with semaglutide (0.5 mg once weekly), for 16 weeks. The primary outcome was the percentage change in body weight at week 16. Adding linafexor more than doubled weight loss (-6.17% vs. -2.91%; treatment difference, -3.26%; 95% CI, -5.35 to -1.18; P=0.003), and more participants achieved at least 5% weight loss (53.3% vs. 28.1%; P=0.046). Consistent with this, combination therapy further reduced visceral adipose tissue (treatment difference, -13.85 cm2; P=0.035), the liver enzymes alanine aminotransferase and {gamma}-glutamyl transferase, and serum bile acids, whose changes correlated with weight and liver-enzyme improvements--associations absent with monotherapy. Gastrointestinal adverse events were comparable (23.3% vs. 18.8%), with no treatment-related serious adverse events or discontinuations. Thus, in a population with blunted GLP-1 responses, adding linafexor to low-dose semaglutide enhanced weight loss and improved body composition and hepatic measures while preserving tolerability--a dose-sparing, mechanism-complementary strategy (ClinicalTrials.gov number, NCT06492330).

Background: Type 2 diabetes (T2D) has been associated with reduced abdominal aortic aneurysm (AAA) risk and slower growth in observational studies, but the mechanism for this paradoxical association remains unclear. We hypothesized that T2D's mechanistic heterogeneity obscures opposing, pathway-specific effects on AAA. Methods: We performed two-sample Mendelian Randomization (MR) to investigate the effect of T2D (T2DGGI, 242,283 individuals with T2D and 1,569,730 without) on AAA (AAAgen, 37,214 individuals with AAA and 997,456 without) using 449 genetic instruments. We also performed MR within previously defined clusters representing different mechanisms of T2D. We extended the analysis to individual hyperglycemic, insulin-resistance, and insulin-sensitivity traits. Our hypothesis was tested in a porcine pancreatic elastase murine model of abdominal aortic aneurysm formation. Results: Overall T2D liability showed no net association with AAA liability (OR 1.00, 95% CI 0.96-1.04, P = 0.90), albeit with marked instrument heterogeneity (Cochran's Q = 1356, P = 5 x 10-92) and inconsistency across sensitivity analyses, with a notably protective MR-Egger result (OR 0.87, 95% CI 0.80-0.94, P = 0.0011) and non-zero intercept (P = 2 x 10-4). MR of T2D on AAA within mechanistic clusters showed opposing effects: lipodystrophy (OR 1.47, 95% CI 1.26-1.72) and obesity (OR 1.27, 95% CI 1.18-1.36) cluster membership associated with increased AAA risk, while beta-cell negative proinsulin (OR 0.83, 95% CI 0.76-0.90) and beta-cell positive proinsulin (OR 0.86, 95% CI 0.80-0.93) clusters were protective. This pattern was robust to clustering method. Traits indexing hyperglycemia (fasting glucose, 2-hour glucose, hemoglobin A1c) were associated with reduced AAA risk, while traits indexing insulin resistance (fasting insulin, BMI, waist-hip ratio, triglyceride-to-HDL ratio) were associated with increased AAA risk. In mice, those treated with a high fructose diet as a model for insulin resistance showed increased growth of the abdominal aorta compared with controls, whereas those treated with pancreatoxin streptozotocin as a model for isolated hyperglycemia showed blunted growth. Conclusion: Distinct components of T2D physiology may have differential effects on AAA development. Whereas insulin resistance may promote AAA, hyperglycemia appears to protect against it. Our findings support insulin sensitization as a rational direction for AAA pharmacotherapy and suggest that the pathways mediating the protective effect of hyperglycemia may harbor additional therapeutic targets.

Background Data-driven type 2 diabetes (T2D) subtypes differ in their risks of dementia and stroke. We examined whether their metabolomic profiles also differed and whether subtype-related metabolic patterns were associated with dementia, stroke, and all-cause mortality. Methods We analyzed NMR-based metabolomic profiles across previously defined T2D subtypes in the UK Biobank. Subtype-related metabolites were summarized using principal component analysis (PCA), and their associations with incident dementia, stroke, and all-cause mortality were examined using Cox models. Attenuation analyses and two-sample Mendelian randomization further assessed subtype-outcome relationships and the potential causal relevance of outcome-associated metabolites. Results Among 7,671 individuals (mean age 59.85 years; 37% female), the first five PCs explained 76.7% of variance in subtype-related metabolites and mainly reflected lipid and lipoprotein signatures. After adjustment for T2D subtype and confounders, the HDL-remodeling PC increased risks of all-cause dementia (HR 1.17, 95% CI 1.08-1.27), VaD (HR 1.18, 95% CI 1.05-1.32), and all-cause mortality (HR 1.16, 95% CI 1.13-1.19). Lower scores on the LDL cholesterol-enriched axis increase risks of all-cause dementia (HR 0.75, 95% CI 0.62-0.91) and mortality (HR 0.76, 95% CI 0.69-0.83). The VLDL/LDL-enriched PC was inversely associated with mortality (HR 0.93, 95% CI 0.88-0.98). No significant stroke results were observed. Adjustment for the PCA-derived metabolomic patterns generally attenuated subtype-outcome associations, MR analyses identified 197 metabolite-outcome associations that remained significant after FDR correction. Conclusions Metabolomic profiling showed that the metabolic signatures differed across data-driven T2D subtypes and highlighted lipid and lipoprotein remodeling as a major metabolic feature associated with dementia, stroke, and all-cause mortality.

Objective: To determine whether continuous glucose monitoring (CGM) identifies clinically relevant glycemic heterogeneity and subclinical end-organ alterations in adults without diabetes. Research Design and Methods: We analyzed 1,017 AI-READI Year 3 participants without diabetes (558 with normoglycemia and 459 with prediabetes by A1C). Fifty-two metrics from 10-day blinded CGM were reduced to nonredundant glycemic axes. Partial Spearman correlations between representative CGM metrics and clinical measures across 13 domains were adjusted for age, sex, and BMI and controlled for false discovery rate. CGM-derived subphenotypes were identified using unsupervised UMAP-HDBSCAN-based clustering. Results: Among 462 glycemic-clinical associations tested, 99 (21.4%) remained significant after false discovery rate correction. Hyperglycemia-related metrics, including mean glucose, time above range, and time in tight range, showed more associations than variability metrics. The strongest signals involved cardiometabolic, cardiovascular, and cognitive measures. Greater hyperglycemia and glucose excursions were associated with lower language performance, slower processing speed, and lower cognitive efficiency ({rho} {approx} -0.10 to -0.14; all P < 0.01). Clustering identified four reproducible glycemic subphenotypes: Healthy, Mild Hyperglycemia, High Variability, and Hyperglycemia. CGM phenotypes reclassified A1C-defined groups: 58.1% of participants with normoglycemia fell into dysglycemic phenotypes, whereas 18.8% of participants with prediabetes fell into more favorable phenotypes. The Hyperglycemia phenotype had the most adverse cardiometabolic profile and lower cognitive performance. Conclusions: In adults without diabetes, CGM revealed glycemic patterns associated with distinct subclinical alterations. CGM-based phenotyping may complement A1C for characterizing early dysglycemia and selecting individuals for longitudinal risk-stratification studies.