Diabetes Care

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

BackgroundGenetic risk scores (GRS) for type 1 diabetes (T1D) have been developed primarily in European populations, limiting their generalisability across ancestries. Indians differ from Europeans in clinical characteristics of T1D and overall genetic architecture, yet systematic evaluation of T1D GRS performance in multi-regional Indian cohorts is lacking. MethodsThe study included 597 T1D patients and 3347 non-diabetic controls from different regions in India. Genotyping, imputation, quality control analysis, and construction of the 67-SNPs T1D GRS were performed using standardised pipelines. Discriminative performance was assessed using Receiver Operative Curve-Area under Curve (ROC-AUC) analysis, and optimal thresholds were derived using Youdens index. HLA-DQ diplotype frequencies were compared, and association analysis was conducted using multivariable logistic regression. FindingsT1D GRS showed consistent discriminative performance across Indian cohorts [ROC-AUC=0.84 (range=0{middle dot}78-0{middle dot}87)], supporting its comprehensive use for T1D classification in India. Notably, its performance was lower in islet cell autoantibody (IA) negative compared with IA positive T1D patients (ROC-AUC, 0{middle dot}75 vs 0{middle dot}85) and in adult-onset than in childhood-onset patients (0{middle dot}74 vs 0{middle dot}84). We observed a lower frequency of protective HLA-DQ diplotypes and a strong association of HLA-DQ81 containing diplotypes in childhood-onset T1D. Application of an India-specific T1D GRS score improved the sensitivity than the European cut-off. InterpretationT1D GRS is a valuable unified diagnostic tool in Indians, but its performance varies by islet cell autoantibody status and age at onset, likely reflecting population-specific HLA architecture. European-derived T1D GRS thresholds under-classify the genetic risk, highlighting the importance of ancestry-aware optimisation in Indians. FundingCDRC grant CDRC202111026 and CSIR Intramural Grant P50. Research in contextO_ST_ABSEvidence before this studyC_ST_ABSPrevious studies have shown that a 67-SNPs T1D genetic risk score (GRS) can distinguish T1D patients from non-diabetic controls and other forms of diabetes, but its performance varies across ancestries. Islet cell autoantibodies (IA) have important diagnostic value for classifying type 1 diabetes (T1D). However, their prevalence in India varies widely, with up to one-quarter of patients testing negative, limiting their clinical utility. Evidence supporting the use of the T1D GRS in India, combined with IA antibodies status is limited to a single cohort representing one linguistic group. The applicability of T1D GRS across multi-centric clinical settings has not been systematically evaluated. Added value of this studyThis study validates the 67-SNPs T1D GRS across multiple Indian cohorts representing major linguistic groups, supporting its use as a unified diagnostic tool. Differences in T1DGRS performance between childhood-and adult-onset T1D are linked to enrichment of protective HLA-DQ diplotypes in adult-onset disease, providing genetic insight into disease heterogeneity. The study also demonstrates that European-derived GRS thresholds systematically under-classify genetic risk in Indians and the population-specific threshold is essential. Implications of all the available evidenceThe European-derived T1D GRS can be applied across Indian clinical settings with consistent discriminative performance. However, its utility is influenced by islet cell autoantibody status and the age at onset of disease. Ancestry-aware threshold optimisation substantially improves diagnostic accuracy and is essential for equitable implementation of T1D GRS in Indians. Larger studies are needed to identify population-specific risk variants and further refine genetic tools for clinical diagnosis.

ObjectiveHbA1c thresholds used to define dysglycemia in autoantibody-positive individuals at risk for type 1 diabetes do not account for age-related increases in HbA1c and may overestimate progression risk in adults. We evaluated whether age-adjusted HbA1c or a higher HbA1c threshold improves risk stratification across age groups. Research Design and MethodsWe analyzed 5,024 autoantibody-positive relatives (3,720 children and 1,304 adults) participating in the TrialNet Pathway to Prevention study. Age-related HbA1c effects were modelled using 6,273 adults from the population-based Exeter 10,000 cohort. Progression risk was compared using the standard dysglycemia threshold (HbA1c [&ge;] 5.7% [39 mmol/mol]), age-adjusted HbA1c, and an alternative threshold of HbA1c [&ge;]6.0% (42 mmol/mol). ResultsUsing HbA1c [&ge;] 5.7%, children had higher 1-year progression risk than adults among single autoantibody-positive participants (38% [95% CI 28, 47] vs. 13% [7.2, 19]) and multiple autoantibody-positive participants (55% [49, 60] vs. 38% [27, 47]; both p<0.001). Age adjustment reduced these differences; progression risk was similar among single autoantibody-positive participants (38% [28, 47] vs. 27% [13, 39]; p=0.32), with attenuated differences among multiple autoantibody-positive participants. An HbA1c threshold [&ge;]6.0% yielded comparable progression risk between adults and children across autoantibody subgroups. In post hoc analyses, adults aged <30 years had progression risk similar to children (p=0.1). ConclusionsAge-related variation in HbA1c influences dysglycemia classification in adults at risk for type 1 diabetes. Age-adjusted HbA1c or a higher HbA1c threshold ([&ge;]6.0% [42 mmol/mol]) in adults [&ge;]30 years identifies individuals with progression risk comparable to children and may improve age-specific risk stratification in prevention seungs.

Background: Genetic variants impacting red blood cell biology disrupt the relationship between glycaemia and glycated haemoglobin (HbA1c), with implications for diagnosis and management of type 2 diabetes (T2D). Thalassaemia trait is estimated to affect 350 million people globally, but its impact on T2D and related outcomes is not clear. Methods: We explored associations between thalassaemia trait, HbA1c, and T2D diagnosis and complications in 43,088 British Bangladeshi and Pakistani participants in the Genes & Health study with linked multisource England National Health Service (NHS) electronic health record data and whole exome sequencing. Findings: 2,490 participants (5.8%) were heterozygous carriers of ClinVar pathogenic / likely pathogenic thalassaemia variants, however 3 in 4 of these were not diagnosed with thalassaemia in their NHS health records. rs33950507, a common variant causal for HbE thalassaemia, was associated with increased HbA1c (beta=0.13, 95%CI:0.08-0.18, p=7.8x10-8), but not glucose levels (beta=0.01, 95%CI:-0.04-0.06, P=0.72). rs33950507 was associated with increased hazards of prediabetes (HR=1.38, 95%CI:1.26-1.52, p=2.2x10-6) and T2D (HR=1.11, 95%CI:1.01-1.22, p=0.03), and reduced hazards of diabetic eye disease (HR=0.74, 95%CI:0.56-0.96, p=0.02) and cerebrovascular disease (HR=0.44, 95%CI:0.20-0.94, p=0.03). Sensitivity analyses suggested mediation by overdiagnosis and overtreatment of T2D. Interpretation: Alternatives to HbA1c, and/or precision medicine approaches to defining and managing hyperglycaemia, are needed, particularly on a global scale. This may be particularly relevant to individuals from ancestral groups among whom erythrocytic traits are more common but often undiagnosed. Funding: Wellcome Trust, MRC, NIHR, Barts Charity, Genes & Health Industry Consortium

IntroductionPolygenic risk scores (PRS), metabolomics, and proteomics have each shown promise in improving type 2 diabetes risk prediction, but their combined utility beyond established clinical models remains unclear. We aimed to evaluate whether integrating multi-omics biomarkers enhances 10-year type 2 diabetes risk prediction beyond single-omics extensions and the clinical Cambridge Diabetes Risk Score (CDRS), which includes HbA1c measurements. MethodsWe analysed data from 23,325 UK Biobank participants without diagnosed diabetes at baseline. Data for a PRS for type 2 diabetes, 11 metabolites, and 15 proteins were added to the CDRS to develop multi-omics prediction models. Model performance was evaluated using Harrells C-index and the net reclassification index (NRI). ResultsDuring 10 years of follow-up, 719 participants developed incident type 2 diabetes. Among individual omics layers, proteomics contributed the greatest improvement in predictive performance, increasing the C-index from 0.857 (clinical CDRS) to 0.880 ({Delta}C-index; +0.023; P < 0.001), with an NRI of 30.0%. The full multi-omics model, further significantly increased the C- index compared to a model combining the clinical CDRS with proteomics data (C-index, 0.886; {Delta}C-index; +0.006; P < 0.033). ConclusionIntegrating proteomics, metabolomics, and a diabetes-PRS into a clinical model substantially improves type 2 diabetes risk prediction beyond single-omics extensions. However, the C-index difference between the proteomics extended and full multi-omics extended models is small, and the clinical models extended with proteomics data would be easier to translate into routine care because it needs only the measurement of 15 proteins.

Type 2 diabetes (T2D) affects 11.1% of the global population, underscoring the need for biomarkers that inform treatment response and glycemic outcomes. We evaluated the association between the FTO variant rs9939609-A and glycemic control in a Mexican population. A total of 174 individuals living with T2D from Merida and Sisal, Yucatan, were included, of whom 85% were receiving oral hypoglycemic agents as main treatment. Glycemic control was defined cross-sectionally as good ([&le;]130 mg/dL, n=63) or poor (>130 mg/dL, n= 111) with fasting glucose. Linear mixed models incorporating relevant covariates and a family random intercept were used. Effect size estimates were transformed to logit odds ratios. After adjustment for age, sex, BMI, years with T2D, and treatment, we observed a significant association in the additive (OR = 1.15 [1.003-1.31]) and recessive (OR = 1.51 [1.03-2.23]) models. To conclude, rs9939609-A may be associated with poorer glycemic control despite pharmacologic therapy.

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.

The detection of monogenic diabetes illustrates the potential of precision medicine, with treatments tailored to specific genes and diagnosis involving targeted genetic testing. Current detection criteria are derived from White populations. We investigated detection of monogenic diabetes in an unselected multiethnic cohort comprising 1,706 participants diagnosed with diabetes before the age of 30-years. Using broad biomarker criteria (triple pancreatic antibody negative and detectable C-peptide) to select for next generation sequencing of monogenic diabetes genes, we found a non-significantly different minimum cohort prevalence of monogenic diabetes of 2.1% in White, 2.0% in South Asian, 2.5% in African-Caribbean, and 3.6% in Mixed participants. The detection rate, however, varied significantly (17.7% in White, 5.3%in South Asian, 8.0% in African-Caribbean, and 15.2% in Mixed participants, p<0.001). Those without monogenic diabetes showed significant variations in BMI. No difference in phenotype of monogenic diabetes across ancestry groups was observed. Non-white ethnicity participants were significantly more likely to have undiagnosed monogenic diabetes than White with on average a 10-year duration before receiving a correct diagnosis. By applying ancestry-specific BMI cut-offs (White <30, South Asian <27, African-Caribbean and Mixed <35 kg/m{superscript 2}), the overall detection rate increased from 8.8 to 16%, reducing the number needed to test to identify one case from 11 to 6 and boosting detection rates to 39, 11, 9 and 26% in White, South Asian, African-Caribbean and Mixed-ethnicity participants, respectively. These findings were validated in an external real-world dataset. Applying broad biomarker criteria for initial selection, mitigates clinical biases leading to misclassification of monogenic diabetes in non-White ethnicities. However, further tailoring criteria with ethnic-specific BMI cut-offs doubled detection rates, improving cost-effectiveness by minimising unnecessary testing. Our study highlights the need to develop precision medicine approaches accounting for phenotypic variation across diverse populations, to ensure accurate diagnoses and cost-efficient healthcare provision.

BackgroundMetformin is the cornerstone therapy for type 2 diabetes, but gastrointestinal intolerance commonly limits dose escalation and long-term adherence. In the ProGasMet trial, multi-strain probiotic supplementation improved metformin tolerability. However, the underlying microbiome-metabolome mechanisms remain unclear. Methods and analysisWe performed an exploratory multi-omics analysis using Period 1 of a randomized, double-blind, placebo-controlled trial. Participants with metformin intolerance received a multi-strain probiotic or placebo for 12 weeks. Paired stool samples collected at baseline (Visit 2) and end of treatment (Visit 5) were available from 34 participants (68 samples). We integrated shotgun metagenomic species profiles, predicted gut metabolic modules, and untargeted faecal LC-MS metabolomics using multi-block sparse PLS (DIABLO), complemented by longitudinal feature-level analyses and associations with gastrointestinal symptom burden (QACSMI and a simplified GI score). ResultsMulti-omics integration showed moderate concordance across taxonomic, functional, and metabolomic blocks and separated probiotic from placebo profiles at 12 weeks. Bile acid-related metabolites were among the strongest contributors to group separation, with hyodeoxycholic acid and related compounds enriched in the probiotic arm. Global biodiversity and community-wide turnover did not differ materially between groups. Feature-level analyses suggested modest, directionally coherent changes in selected taxa, functional modules, and metabolites. Higher hyodeoxycholic acid concentrations at Visit 5 were associated with lower gastrointestinal symptom burden in probiotic-treated participants, a pattern not observed under placebo; statistical support was exploratory. ConclusionProbiotic supplementation may be associated with coordinated microbiome-metabolome shifts in metformin-intolerant type 2 diabetes, highlighting bile acid remodelling, particularly hyodeoxycholic acid, as a plausible mechanistic candidate for improved tolerability.

ObjectivesAn update to the NICE Type 2 diabetes (T2DM) guideline in February 2022 recommended an SGLT2 inhibitor be offered to people with cardiovascular disease (CVD) or heart failure (HF) as comorbidities and considered for people at high CVD risk. We report uptake of this guideline in England 18 months after its publication. DesignObservational cohort study. SettingGeneral practices contributing to the Clinical Practice Research Data Link, linked to hospital admission records. Participants587,826 people aged over 18 years with T2DM on 1st September 2023, stratified according to their CVD category (CVD only; HF only; CVD and HF; high CVD risk score; low CVD risk score) and chronic kidney disease (CKD) status, and further by age, gender, ethnicity, deprivation, and T2DM diagnosis duration. Main outcome measuresPercentage of patients with a current SGLT2 inhibitor prescription; odds ratios for association between patient characteristics and a current prescription. ResultsIn people with T2DM, the percentage with a current SGLT2 inhibitor prescription was 19.5% for people with CVD, 29.4% for people with HF, 30.5% for people with both CVD and HF, and 19.9% and 20.2% respectively for people at high and low CVD risk. In age-stratified analyses, uptake ordered from lowest to highest was as follows: low CVD risk score, high CVD risk score, CVD only, HF only, CVD and HF. In models adjusted for clinical and patient characteristics uptake was lower in people aged >60, women, Black people, and people living in areas of higher deprivation. ConclusionsWhilst prescribing of SGLT2 inhibitors continues to rise in England, an opportunity remains to increase uptake and to reduce inequalities in people with T2DM in 2026. We report inequalities by ethnicity and deprivation, and lower uptake for people with CVD without HF than people with HF, despite an equal guideline recommendation for these two groups. Additional evidence is needed on the effectiveness of SGLT2 inhibitors in frailer populations. What is already known on this topic?O_LIIn 2020 approximately 10% of people with type 2 diabetes (T2DM) and cardiovascular disease (CVD) and 14% of people with T2DM but without CVD in England had a current SGLT2 inhibitor prescription. C_LIO_LIIn February 2022 NICE recommended that an SGLT2 inhibitor should be offered to people with T2DM with heart failure or CVD, and considered for people with T2DM at high risk of CVD; network meta-analyses have found 10% to 40% lower odds of cardiovascular mortality with treatment in these groups. C_LIO_LIUptake of NICE guidelines in general practice has historically been variable, although higher when accompanied by pay-for-performance schemes such as the Quality and Outcomes Framework. C_LI What this study addsO_LIBy September 2023 the percentage of people with T2DM with a current SGLT2 inhibitor prescription had reached 19.5% in those with CVD as a comorbidity, 30.5% in those with heart failure, and 19.9% in those at high risk of CVD. C_LIO_LIWomen, people of Black ethnicity, and people living in areas of high deprivation had lower odds of a current prescription in analyses adjusted for age, gender, cardiovascular comorbidity, and renal function. C_LI How might these results change the focus of research or clinical practice?O_LIThe results highlight the need for ongoing surveillance of uptake of NICE-recommended treatments for T2DM, and consideration of actions to address barriers to uptake. This is particularly important in the context of broader eligibility for SGLT2 inhibitor treatment in type 2 diabetes in England from 2026. C_LIO_LIThese results support the development of initiatives and quality improvement programmes to improve evidence-based prescribing and address inequalities between clinical and demographic subgroups. C_LI

BackgroundDysbiosis of gut microbiota plays a key role in type 1 diabetes mellitus (T1DM). Fecal microbiota transplantation represents a novel therapeutic avenue. We hypothesize that youth-derived fecal microbiota transplantation (yFMT) can remodel the gut microecosystem and improve clinical outcomes. This study aims to investigate the efficacy and safety of orally administered yFMT capsules in adults with T1DM. Methods and analysisThis single-center, randomized, double-blind, placebo-controlled pilot study will enroll adults with T1DM who have suboptimal glycemic outcomes (glycated hemoglobin[HbA1c] of 7-14% and time in range [TIR] <70%). Following a 17-day run-in period for insulin optimization, continuous glucose monitoring(CGM) wearing, baseline assessments and bowel preparation, participants will be randomly allocated (1:1) to take yFMT or placebo capsules for consecutive 6 days, alongside their standard insulin therapy, and then complete a 12-week follow-up. The primary efficacy endpoint is the change from baseline in the rate of achieving the composite target of TIR>70% and time below range<4% at 4 and 12 weeks post-randomization. Secondary efficacy endpoints comprise changes from baseline at weeks 4 and 12 in other glycemic metrics (including HbA1c, fasting glucose, 2-hour postprandial glucose, and additional CGM metrics), C-peptide, immune responses, infection markers, and gut microbiota composition. Changes from baseline at week 12 in serum metabolomic profiles will also be assessed, encompassing bile acids, short-chain fatty acids, and other related metabolites. Safety endpoints include the incidence of adverse events and serious adverse events. DiscussionOur findings will offer new insight into the feasibility and effects of oral yFMT in adult with T1DM and provide the necessary evidence to power a subsequent multicenter large-scale study. Exploratory biomarker analyses conducted within this study may further pave the way for future individualized microbiome-based therapeutics. Trial registrationChinese Clinical Trial Registry identifier: ChiCTR2500111955 (November 7, 2025).

Background: The glucagon-like peptide-1 receptor (GLP1R) is a key regulator of glucose metabolism and appetite and a major therapeutic target for type 2 diabetes (T2D) and obesity. Genetic studies have implicated the GLP1R locus in both body mass index (BMI) and T2D, but it remains unclear whether their underlying genetic associations are the same. Methods: We analyzed 431,107 participants of genetically inferred European ancestry from the Million Veteran Program. Within 500 kb of GLP1R, we performed locus-wide linear regression models for BMI and logistic regression models for T2D, adjusted for age, sex, and 10 principal components. We identified primary and secondary BMI sentinel variants using conditional analyses and evaluated their associations with T2D. Bayesian fine-mapping was used to construct credible sets of GLP1R locus for BMI and T2D. Results: Conditioning on the primary sentinel variant rs12213929 (upstream of GLP1R, {beta} = 0.11; 95% CI 0.09-0.14; p = 1.94E-17), we identified a secondary variant (rs13216992, intron of GLP1R) independently associated with BMI ({beta} = 0.10; 95% CI 0.07-0.13; p = 7.88E-14). The two sentinel variants showed low linkage disequilibrium (r2 = 0.03). A two-variant allelic burden score (0-4; sum of the rs12213929 G-allele count and rs13216992 C-allele count) showed that participants with 4 risk alleles had 0.47 kg/m2 higher BMI than those with 0 risk alleles (95% CI 0.39-0.55; p < 2E-16). Both variants were associated with higher T2D risk, but with distinct patterns after BMI adjustment: the rs12213929-T2D association persisted after adjustment for BMI (OR = 1.02; 95% CI 1.01-1.03; p = 0.0004), whereas the rs13216992-T2D association was fully attenuated (OR = 1.00; 95% CI 0.99-1.01; p = 0.68). Fine-mapping identified a compact 95% BMI credible set of 17 variants and a broader 95% T2D credible set of 42 variants, with all BMI credible variants contained within the T2D set. Conclusions: The GLP1R locus harbors at least two independent BMI-associated variants that exhibit heterogeneous relationships with T2D: rs12213929 influences T2D risk partly through BMI-independent pathways, whereas rs13216992 appears to act predominantly via adiposity. These findings refine the genetic architecture at this key therapeutic target gene and provide a foundation for functional and pharmacogenomic studies to determine whether GLP1R variation can inform precision prevention and treatment of obesity and T2D.

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.

IntroductionDysglycemia is a well-established risk factor for cardiovascular disease (CVD); yet traditional glycemic traits, including fasting plasma glucose (FPG) and HbA1c, do not capture dynamic glucose fluctuations that may inform CVD risk. We cross-sectionally investigated the association of continuous glucose monitor (CGM)-derived metrics and 2-h post-prandial glucose (2-h PPG) with estimated 10-year CVD risk among individuals without diabetes. MethodsWe included 1,360 Framingham Heart Study participants (Third Generation, New Offspring Spouse, and Omni 2 cohorts at exam 4) without prevalent diabetes or CVD who had [&ge;]3 days of CGM data and completed a mixed meal tolerance test (MMTT) with corresponding 2-PPG. We included 7 CGM summary metrics and defined data-driven glucotypes according to CGM measures of glycemic burden and variability. The 10-year CVD risk was estimated using the Predicting Risk of CVD EVENTs (PREVENT) base equations. We performed linear regression on standardized glycemic traits and glucotypes with log-transformed PREVENT risk scores and multinomial regression to relate standardized CGM metrics and 2-h PPG with PREVENT categories (low <5%[reference], borderline 5-<7.5%, intermediate/high [&ge;]7.5%). All models were adjusted for FPG and body mass index (BMI). ResultsAmong participants (55.9% women, 43.4% with prediabetes), mean age was 59.3 years, and mean BMI was 27.9 kg/m2. All CGM-derived metrics and 2-h PPG were positively associated with higher overall 10-year CVD risk (per 1 SD increase of each exposure variable, {beta} range: 0.06-0.16, all p<0.001). A glucotype representing high glycemic burden and high glycemic variability was associated with higher overall 10-year CVD risk, compared with the glucotype representing low glycemic burden and low glycemic variability. Higher CGM-derived metrics and 2-h PPG were also associated with higher odds being in the intermediate/high CVD risk (OR range: 1.20-1.65, all p<0.001), adjusting for FPG and BMI. ConclusionDynamic glycemic traits, including novel glucotypes that capture glycemic burden and variability, may provide novel insights into CVD risk prevention among individuals without T2D.

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.

BackgroundVisceral adiposity is widely regarded as the pathogenic component of central obesity in cardiometabolic disease. However, emerging evidence suggests that abdominal subcutaneous adiposity may also confer metabolic risk in South Asian populations, although data in young, lean individuals are scarce. We investigated associations of MRI-measured abdominal subcutaneous adipose tissue (ASAT) and visceral adipose tissue (VAT) with cardiometabolic risk markers in young rural Indian adults. MethodsWe quantified ASAT and VAT using MRI in 590 participants (310 men) aged 18 years from the Pune Maternal Nutrition Study cohort. Sex-specific multiple regression models were used to examine associations with glucose-insulin indices, blood pressure, lipids, adipokines, and inflammatory markers. ResultsASAT showed broad and consistent associations with adverse cardiometabolic profiles, including higher 120-min glucose, dyslipidaemia, elevated blood pressure, leptin, CRP and leukocyte count, and lower insulin sensitivity and adiponectin, particularly in men; in women, ASAT was associated with most cardiometabolic risk markers except HDL-cholesterol. In contrast, VAT was associated with fewer risk markers and exhibited weaker, sex-specific patterns of association. Across outcomes, associations with ASAT were generally stronger than those observed for VAT. ConclusionsIn young, lean Indians, abdominal subcutaneous adiposity exhibits stronger associations with insulin resistance, dyslipidaemia and inflammation than visceral adiposity, challenging the prevailing VAT-centric paradigm derived largely from Western populations. These findings provide human evidence that the hierarchy of metabolic risk across abdominal fat depots is population-specific. This suggests genetic and early-life risk stratification, and supports early targeted preventive strategies. Research InsightsWhat is currently known about this topic? (max. 3 highlights, each < 100 characters) Indians have higher central obesity-adiposity than Europeans at similar BMI. Western data links VAT with cardiometabolic risk, while ASAT is protective. VAT & ASAT risk patterns vary across native and migrant South Asians. What is the key research question? (formatted as a question, < 100 characters) How do VAT and ASAT associate with cardiometabolic risk in lean rural Indian youth? What is new? (max. 3 highlights, each < 100 characters) ASAT shows stronger links with cardiometabolic risk than VAT in rural Indian youth. ASAT may contribute to high diabetes and CVD risk at low BMI in young Indians. How might this study influence clinical practice? (max. 1 highlight, < 100 characters) Early-life ASAT accumulation may raise later cardiometabolic risk, supporting early prevention strategies.

BackgroundEffective interventions are needed to support co-creation of diabetes care plans that fit patients lives. We evaluated the QBSafe agenda-setting kit (14 conversation cards) for its impact on care fit and glycemic control when added to usual primary care. MethodsThis single-center, clinician-level cluster-randomized, open-label trial was conducted at a federally qualified health center in New Haven, Connecticut (ClinicalTrials.gov NCT05553912). Clinicians and their patients with type 2 diabetes and HbA1c >8% were randomized 1:1 to usual care with or without QBSafe cards. In the intervention arm, patients selected up to 3 cards highlighting concerns about life with diabetes prior to their visit. Primary outcomes were change at 6 months in care fit (Illness Intrusiveness Ratings Scale, IIRS) and HbA1c, analyzed by intention to treat. Secondary outcomes were treatment burden (Treatment Burden Questionnaire, TBQ) and diabetes distress (Diabetes Distress Scale, DDS), and satisfaction with visits. ResultsBetween February 2023 and July 2024, 143 participants (mean age 56 years; 61% female; 73% Hispanic; mean HbA1c 10%) were enrolled: 74 received usual care with QBSafe, 69 usual care alone. At 6 months, there were no significant between-arm differences in changes in IIRS (-3.9 [95% CI -10.4, 2.6]), HbA1c (-0.2% [95% CI -0.9, 0.5]), TBQ (1.0 [95% CI -16.6, 18.6]), or DDS (-0.1 [95% CI -0.4, 0.2]). Clinicians reported greater satisfaction when using QBSafe. Patient satisfaction was high and did not differ across arms. ConclusionsQBSafe cards improved clinician satisfaction but did not improve care fit or glycemic control. Future tools should focus on helping clinicians respond effectively to patient-identified challenges.

ObjectivesTo characterize ultra-processed food (UPF) circulating metabolic signatures associated with Crohns disease (CD) and to localize key metabolic mediators linking UPF intake to CD risk. DesignProspective cohort study. SettingTwo large multi-center cohorts (UK Biobank [UKB] and Whitehall II [WHII] study) across the UK and an Eastern multi-center cohort ONE-IBD Study from China. ParticipantsUK Biobank discovery cohort (n=10,229) for signature derivation, internal validation cohort (n=91,306), external validation cohort Whitehall-II (n=7,893), and three additional cohorts (two Western and ONE-IBD) for validation of key metabolic drivers. Main outcome measuresPrimary outcomes were UPF-related circulating metabolic signatures and their associations with CD risk; secondary outcomes included evidence supporting causal roles of candidate metabolites and genetic pathways assessed by Mendelian randomization, colocalization, and gene-environment analysis. ResultsA UPF metabolic signature of 73 metabolites was constructed and validated across cohorts (Spearman {rho}: 0.20-0.25). More pronounced UPF metabolic signature was associated with increased CD risk (HRper SD=2.65, 95% CI 1.57-4.48). WGCNA revealed a cluster enriched in fatty acids. Within this cluster, docosahexaenoic acid (DHA) emerged as the strongest, which mediated 17.1% of the UPF-CD association. External validation in ONE-IBD supported DHA as the strongest associated metabolite with UPF and CD. Mendelian randomization supported a causal protective effect of DHA on CD (OR=0.72, 95% CI 0.61- 0.83; P<0.001), with colocalization implicating rs174546 in the FADS1 gene. ConclusionThe adverse effects of UPF on CD risk may be driven by a relative deficiency of protective metabolites such as DHA, apart from additive harm to metabolic depletion. This reframes UPF-related risk and highlighting potential targets for precision nutrition in CD prevention.

Stratifying progression from early-stage type 1 diabetes to clinical disease is essential for optimally timing disease-modifying therapies. We previously developed a progression likelihood score (PLS) that includes quantitative IA-2 autoantibody (IA-2A) measurements. This study aligned IA-2A thresholds used for PLS calculation between the radiobinding assay (RBA) and a commercially available RSR IA-2A ELISA to support broader clinical application. Serum samples from 349 children with stage 1 type 1 diabetes were analyzed using both assays. IA-2A positivity was similar by RBA (61.6%) and ELISA (59.0%). Centile-based alignment of ELISA-positive samples defined thresholds corresponding to RBA IA-2A categories. ELISA-derived PLS low (PLS < 0.5), moderate (PLS 0.5-4.0) and high (PLS > 4.0) risk groups stratified progression to stage 3 disease comparably to RBA-derived groups. The 3-year progression rate for children with an ELISA IA-2A PLS >4.0 was 52.4% (95% CI, 30.5- 66.1), similar to the RBA-derived PLS >4.0 group (58.7%; 95% CI, 37.1-72.8). These results demonstrate that the commercial ELISA can be used for PLS-based risk stratification.

ContextThe environmental or other genetic factors might influence the effect of Klotho (KL) on glucose metabolism. ObjectiveWe investigated mitochondrial genetic variants that interact with KL single nucleotide polymorphisms (SNPs) to modulate diabetes risk. MethodsWe used the data from 7,047 non-Hispanic white participants of the Health and Retirement Study, a prospective observational study including adults aged 50 years and older from the United States. First, we performed single gene-wide association scans to identify KL SNPs associated with diabetes. Next, we performed a nuclear-by-mitochondrial interaction test (NuMIT) in which we use an identified KL SNP from the gene-wide scan to evaluate potential interactions with 85 mitochondrial SNPs in relation to diabetes. ResultsWe failed to identify a significant association between diabetes and the KL SNP in our single gene-wide association test. However, we identified a novel variant (KL rs9563121) which showed a trend of increasing klotho mRNA levels with each additional minor allele. A NuMIT analysis identified mitochondrial SNPs, which showed significant interactions with rs9563121 in relation to diabetes risk. MitoG15929A showed significant interactions with rs9563121 in both men and women. MitoG15929A diminished the potential beneficial effect of KL rs9563121 on diabetes risk in women. Among men with the MitoG15929A variant, KL rs9563121 was associated with higher prevalence of diabetes. ConclusionThe NuMIT approach revealed significant interactions between mitochondrial and nuclear DNA variants of KL. Furthermore, MitoG15929A may have a role in the interaction between diabetes and KL in a sex-dependent manner.