Introduction and Objective: Worksite interventions offer scalable diabetes and cardiovascular disease (CVD) prevention in India. INtegrating DIAbetes Prevention in WorkplaceS (INDIA-WORKS) study assessed recruitment/implementation barriers and adaptive strategies in a multi-site implementation trial. Methods: INDIA-WORKS tested implementation of a one-year, multi-level lifestyle intervention program at 11 large industrial worksites (15-50,000 employees each) across India. targeting employees with pre-diabetes (HbA1c: 5.7-6.4%) or diabetes (HbA1c ≥6.5%). Phase I screening used random capillary blood glucose (≥110 mg/dL) and Indian Diabetes Risk Score (≥30). Phase II assessments included HbA1c, fasting blood sugar, lipid profile, and cardiac markers. Post-intervention follow-up was for up to 2 years. Barriers and adaptive strategies at each phase were systematically recorded. Results: During screening, low enrolment and awareness were addressed through management-endorsed messaging and Human Resources (HR) mobilization, resulting in 6265 employees being screened and 2108 found eligible by HbA1c criteria. In the baseline phase, difficulties due to shift work and mobile phone restrictions were overcome by flexible scheduling, digital reminders, and HR mandates, resulting in 1625 (77.1%) completing baseline assessments. Intervention implementation barriers, were addressed through adjusted session hours, incentives, and announcements, resulting in 1356 (64.3%) participants completing the intervention. Maintenance-phase attendance engagement improved with batch flexibility and makeup sessions. Follow-up rates were 70.8% (n=1492) at 1 year and 64.4% (n=1358) at 2 years, aided by reminders, supervisor support, and home visits. Conclusion: Peer-led recruitment and context-specific adaptive strategies enabled effective recruitment and implementation of a scalable workplace diabetes prevention program in India. Disclosure H. Ranjani: None. B. Meena: None. S. Vijayalakshmi: None. R. Anjana: None. D. Pandiyan: None. L. Natarajan: None. J. Sivaram: None. E. Rhodes: None. M.K. Ali: Consultant; Ended; Eli Lilly and Company, Siemens, Novo Nordisk. K. Narayan: None. D. Prabhakaran: None. V. Mohan: None. P. Jeemon: None. M. Weber: None.

Abstract 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 (rs563555492 T ), carried by 1 in 12 south Asians, has been associated with a nonglycemic 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 rs563555492 T 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 Research in Context Evidence before this study We searched PubMed from database inception to Nov 1, 2025, for studies examining PIEZO1, Glycated Haemoglobin (HbA1c) and type 2 diabetes (T2D) related outcomes. Search terms included “PIEZO1”, “haemoly*”, “hemol*”, “erythrocyte*”, “HbA1c”, “glycated haemoglobin”, “glycated hemoglobin”, “type 2 diabetes”, “prediabetes”, “retinopathy”, and related terms. HbA1c is widely used to guide prevention, diagnosis, and management of T2D, but variants affecting erythrocyte structure or lifespan can alter its relationship with glycaemia. A missense variant in PIEZO1 (rs563555492 T ), carried by one in twelve south Asians, has been associated with lower HbA1c and erythrocytic biomarkers without differences in fasting glucose and with older age at T2D diagnosis, suggesting delayed diagnosis in UK-based cohorts. However, uncertainties remain. Associations have not been replicated outside the UK to confirm generalisability. Experimental animal models suggest PIEZO1 channels may influence pancreatic insulin secretion, but this has not been evaluated in human cohorts. Finally, the potential clinical and health-economic consequences associated with this variant remain largely unexplored. Added value of this study We replicated associations between rs563555492 T , lower HbA1c, and erythrocytic changes in a geographically distinct south Asian cohort based in South India. We found no association with fasting glucose, postprandial glucose, or C-peptide concentrations, supporting a predominantly erythrocytic mechanism. We examined the clinical and economic consequences of this variant on south Asians in a large UK population-based cohort, following introduction of HbA1c-based diagnostic criteria. Carriers experienced delayed diagnosis of prediabetes and T2D, and there was some evidence of increased risk of diabetic eye disease. In a modelled population aged 40-50 years, the variant was associated with approximately 1,019 missed prediabetes diagnoses and 303 missed T2D diagnoses per 100,000 adults over 10 years. Because prediabetes diagnosis initiates referral to prevention programmes, missed diagnoses represent lost opportunities for disease prevention. In a UK NHS setting, we estimated the associated opportunity cost to be between £970,000 - £1,390,000 per 100,000 individuals over a 10-year horizon. Implications of all the available evidence A south Asian ancestry enriched PIEZO1 variant can disrupt the relationship between HbA1c and glycaemia and delay detection of prediabetes and T2D. Reliance on HbA1c alone may underestimate glycaemic risk in a substantial minority of individuals of south Asian ancestry, with potential implications for prevention strategies, risk of complications and health care costs. Alternative biomarkers of glycaemia or individualisation of HbA1c may help ensure timely and accurate diabetes detection in populations where this variant is common.

Introduction and Objective: Mobile health (mHealth) applications (apps) offer scalable solutions for health promotion and chronic disease prevention in India. However, their effectiveness depends on individuals’ willingness to adopt digital technologies. This study aimed to assess the influence of sociodemographic, anthropometric, and lifestyle factors on the willingness to use mHealth apps. Methods: A cross-sectional analysis of 18,932 adults aged 25-60 years screened for the Global Health Research Unit (GHRU) digital study, comprising a pilot phase (GHRU 1; n = 5,268) and main phase (GHRU 2; n = 13,664). Data were collected using a screening questionnaire that captured information on smartphone ownership, internet access, English literacy, and willingness to use mHealth apps. Multivariate logistic regression models were employed to examine associations between sociodemographic, anthropometric, and lifestyle factors and willingness to use a health app. Results: Overall, 68.2 % participants (n=12921) were willing to use mHealth apps. Males and urban residence were strong predictors of willingness to use mHealth apps in both studies. Increasing age was inversely associated with willingness, with participants aged ≥50 years showing substantially lower odds compared to those aged <35 years. Higher waist circumference was positively associated with willingness among both males and females. Participants engaging in moderate to vigorous physical activity and having a strong family history of diabetes showed significantly higher odds of using the app. Conclusion: Willingness to use mHealth apps was more common among participants who were young, males, lived in urban areas, and were at high risk of metabolic disorders. Those involved in any exercise also showed better uptake to mHealth apps. There is a need for targeted strategies to increase acceptance among females, older adults and rural populations. Disclosure H. Ranjani: None. N. Jagannathan: None. S. Nitika: None. D. Vinothini: None. K. Yuvarani: None. A. Yadav: None. M. Loomba: None. V. Jha: None. P. Avari: Research Support; Current; Dexcom, Inc., Diabetes UK. N. Oliver: Research Support; Current; Dexcom, Inc., Roche Diabetes Care. Speaker's Bureau; Current; Sanofi. Speaker's Bureau; Ended; AstraZeneca. Research Support; Current; Medtronic. Speaker's Bureau; Ended; Dexcom, Inc. J. Valabhji: None. V. Mohan: None. J. Chambers: None. R. Anjana: None.

Background Given the rising burden of diabetes and related complications in India, primary care physicians have been identified as crucial to mitigate the increasing burden at the population level. Therefore, effective training programs tailored to enhance their competencies in diabetes care become indispensable for improving patient health outcomes. Catering to this need, the Certificate Course on Evidence-Based Diabetes Management (CCEBDM) offers a structure that equips frontline care health providers with the necessary skills to provide evidence-based diabetes care. Methods The paper mostly presents descriptive and qualitative insights to explain the various components of the CCEBDM program that have contributed to its sustained success and impact. Results To date, a total of 17,557 primary care physicians (PCPs) have enrolled for the training in the CCEBDM program. The participants comprise a diverse group of physicians, encompassing clinical experience ranging from 3 to 54 years (mean: 10.4 years). Respondents have reported measurable improvements in both clinical practice and patient care following CCEBDM training. Participants from a small narrative program evaluation based on retrospective survey data reported an increase in the average patients per month from 80 to 140, showing a 76% increase in the number of patients managed. Given the extensive number of PCPs trained by CCEBDM, this indicates a significant impact in forwarding evidence-based management of diabetes in India. The undebatable decade-long success of the CCEBDM program may be attributed to two main factors. The first factor consists of adaptability & innovative methods that have helped evolve the program in tune with the changing epidemiological needs and gaps in diabetes management in India. The second factor consists of robust and valid features that have ensured and preserved the quality of the program. Conclusions The paper outlines a forward-looking agenda for optimizing the program's impact on transforming India's diabetes care landscape. Given the rising incidence of non-communicable diseases and the acute shortage of specialized care in underserved areas, the paper explains why programs like CCEBDM are well-positioned to serve as a strategic model for decentralized capacity-building.

OBJECTIVE:Type 2 diabetes (T2D) is a significant risk factor for adverse outcomes in coronary heart disease (CHD). We investigated whether inflammation and immune dysregulation, measured using soluble urokinase plasminogen activator receptor (suPAR) and high-sensitivity C-reactive protein (hs-CRP) levels, mediate this risk. RESEARCH DESIGN AND METHODS:Patients with and without CHD enrolled in the Emory Cardiovascular Biobank had suPAR (ViroGates, Denmark) and hs-CRP levels measured and were followed for 1) cardiovascular death, 2) a composite of incident myocardial infarction and cardiovascular death, and 3) all-cause death. Fine and Gray or Cox proportional hazards models adjusted for demographic, clinical, and treatment variables were used. Regression-based causal mediation analyses were performed. RESULTS:A total of 4,324 participants (mean [SD] age 64 [11.9] years, 36% women, 31.8% with T2D) were followed for a median of 6.9 years. SuPAR levels were higher in those with T2D (median [interquartile range] 3,260 [2,503-4,463] vs. 2,792 [2,217-3,600] pg/mL). T2D was associated with a higher adjusted risk (hazard ratio [HR] 1.38; 95% CI 1.16, 1.63; P < 0.001) of cardiovascular death that was greatly attenuated (HR 1.18; 95% CI 0.99, 1.40; P = 0.1) after adjustment for suPAR, but not hs-CRP, levels. Similar findings were observed for the other outcomes. SuPAR, but not hs-CRP, levels mediated >50% of the effect of T2D on adverse outcomes. CONCLUSIONS:The impact of T2D on adverse outcomes is significantly mediated through chronic inflammation and immune dysregulation, estimated using suPAR levels. Whether novel therapies for reducing suPAR levels will impact CHD risk in T2D warrants further investigation.

Abstract Glycated hemoglobin (HbA1c) is the cornerstone for the diagnosis and the monitoring of diabetes, yet inter-individual variation in HbA1c glycation can produce marked discordance between HbA1c and true glycemic exposure, described as the “glycation gap” (GGap) or “hemoglobin glycation index”. Individuals with a low or negative GGap (“low glycators”) may have spuriously low HbA1c despite sustained hyperglycemia, leading to potential underdiagnosis and undertreatment if HbA1c is used in isolation. This study describes two adult males with persistently elevated capillary and plasma glucose values, abnormal continuous glucose monitoring (CGM) metrics, and high fructosamine, in whom serial HbA1c values remained low when compared with glucose values despite exclusion of hemoglobinopathies, anemia, or drug-induced assay interference. These case reports reinforce that low-glycator phenotypes are clinically relevant and underscore the need to integrate CGM, self-monitoring of blood glucose, fructosamine, and, when appropriate, oral glucose tolerance testing alongside HbA1c to avoid misclassification of glycemic status and to individualize treatment targets.

Dementia continues to pose a growing challenge worldwide, particularly in aging populations where effective disease-modifying treatments remain limited. In this context, attention has increasingly shifted toward non-pharmacological approaches, including physical activity and structured exercise. Evidence accumulated over the past decade suggests that regular exercise may offer modest but meaningful benefits across several domains. These include improvements in cognitive function—especially executive function and attention—as well as gains in mobility, daily functioning, and psychological well-being. While the extent of cognitive improvement varies across studies, a consistent pattern emerges indicating greater benefit when interventions are initiated earlier in the disease course. Beyond clinical outcomes, several biological mechanisms have been proposed, including enhanced cerebral perfusion, upregulation of neurotrophic factors such as brain-derived neurotrophic factor, and attenuation of neuroinflammatory processes. At the same time, challenges remain. Differences in exercise protocols, issues related to adherence, and variability in patient populations make it difficult to define an optimal approach. Despite these limitations, physical activity represents a practical, low-cost strategy that can be integrated into routine care. Further research is needed to refine intervention design and understand long-term effects.

South Asians constitute 25% of the global population yet account for 33% of individuals living with type 2 diabetes (T2D) (1). Despite this burden, they remain substantially underrepresented in genome-wide association studies (GWAS), limiting discovery of ancestry-relevant disease biology (2). This limits biological insight and hampers genomic discovery. Here we integrated genome-wide signatures of recent positive selection across 13 South Asian populations (3,4) with cross-trait genetic association data (3,4). We identified 1,797 genes residing within regions under recent positive selection and prioritised 65 shared across South Asia. Selection-prioritised loci were enriched for credible sets from the largest trans-ancestry T2D GWAS and for partitioned polygenic score clusters implicated in lipodystrophy-like fat distribution, obesity and proinsulin biology. Multi-trait fine-mapping recovered established T2D loci, including RBM6 and PEPD, and identified a signal at MAPT associated with hepatic insulin resistance, erythrocytic traits and HbA1c in two independent south Asian cohorts (5-7). These findings demonstrate that signatures of recent positive selection can be integrated with genetic association data to prioritise metabolically relevant loci and provide a complementary route to genetic discovery in underrepresented populations.

Diabetes is a growing public health burden across the Asia-Pacific (APAC) region. The increasing use of continuous glucose monitoring (CGM) holds significant potential to improve glycemic control and safety outcomes in individuals with diabetes. However, CGM devices in APAC vary widely in technical performance, clinical validation, and regulatory oversight, posing risks of inaccurate readings and treatment errors, especially for nonadjunctive integrated CGM (iCGM) systems. This review synthesizes the literature and regional insights on CGM regulatory frameworks, accuracy standards, and unmet needs. The authors highlight the U.S. Food and Drug Administration (FDA) iCGM standards as the most stringent global standards. Adopting FDA iCGM criteria alongside the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) reporting recommendations, with contextual modifications for diverse epidemiological, infrastructural, and socioeconomic settings in APAC, is explored. A phased, regionally coordinated approach is proposed, incorporating voluntary benchmarks, capacity-building for lower-resourced regulators, regulatory reliance mechanisms, and shared postmarketing surveillance platforms. Emphasis is placed on multistakeholder collaboration and region-specific validation studies. Harmonizing iCGM regulatory standards in APAC is anticipated to enhance device accuracy, safety, and interoperability, improve diabetes care, and streamline regulatory processes, serving as a model for regulatory excellence for other emerging medical technologies.

Background:The high-fat, salt, sugar food market is growing in India, which is linked to the rising prevalence of non-communicable diseases.Materials and Methods:An e-market survey conducted during May-July 2024 focused on evaluating the nutritional quality of packaged savory snacks sold in the Indian e-market. The data from the front and back-of-labels of 873 packaged savory snacks from 40 different categories was extracted from the manufacturer websites, Amazon, Flipkart, JioMart, and Blink It.Results:The snacks were found to be "source of protein" (93%) and "source of dietary fiber" (86%). However, 84% of the snacks had higher fat, and 75% of the snacks had high saturated fatty acid (SFA) content. Mathri had the highest fat (59/100 g), Bhujia had the highest SFA (37.7/100 g). Edible oil was the second ingredient in 60% of the products. "Salted nuts" had the highest %E from fat (71.6%). Though the "grain puffs" had a low %E from fat (11.7%), the %E from carbohydrate was higher (77.4%). Nutritional content claims and their compliance were evaluated based on the Food Safety and Standards Authority of India guidelines. The "low-fat" and "low-SFA" claims were present only in three and one product, respectively. Out of 107 "cholesterol-free" claims declared, only two complied, since the SFA content exceeded the regulatory limit (>1.5 g/100 g) in other products.Conclusions:The study emphasizes on the need for low-fat and low-sodium snack options and the exploration of alternative processing technologies to develop such snacks. A multisectoral approach involving food scientists, technologists, healthcare professionals, food safety authorities, and policymakers is essential for modifying the Indian savory snack landscape.

Background:Despite epidemiological evidence linking fine particulate matter (PM2.5) to cardiometabolic diseases, links between PM2.5 and kidney function or chronic kidney disease (CKD) remain inconclusive. Methods:In a population representative cohort of 12,271 adults (age ≥ 20 years) in 2 Indian cities (Chennai and Delhi), we investigated time-varying associations between annual average ambient PM2.5 and estimated glomerular filtration rates (eGFR) calculated using CKD-Epidemiology Collaboration (EPI) 2009 equations, at 3 time points during 2010 to 2016. Ambient PM2.5 exposures were assessed at residential geocodes using a national high-resolution spatiotemporal model for daily PM2.5 at 1 km × 1 km. City-specific linear mixed effect models were employed, incorporating inverse probability-based weighting to account for loss-to-follow-up. Effect modification by sex, waist-to-hip ratio, hypertension, and diabetes status were assessed using stratified models. Results:Annual average PM2.5 at baseline and 2 follow-ups in Chennai were 33, 37, and 30 μg/m3 whereas those in Delhi were 118, 123, and 130 μg/m3. Median eGFRs at baseline were 112 ml/min per 1.73 m2 (interquartile range [IQR]: 101.9-121.0) in Chennai and 106.4 ml/min per 1.73 m2 (IQR: 94.4-116.6) in Delhi. Over time, a 5 ug/m3 increase in annual average PM2.5 was associated with a significant decline in eGFR in both cities as follows: -0.32 (95% confidence interval [CI]: -0.49 to -0.15) ml/min per 1.73 m2 in Chennai and -0.42 (95% CI: -0.57 to -0.27) ml/min per 1.73 m2 in Delhi. Conclusion:Annual average PM2.5 levels were associated with declines in eGFR. These data from a relatively young South Asian urban cohort underscore the need to further investigate the potential renal and cardiovascular impacts of sustained air pollution exposure.

Introduction and Objective: There are more than 101 million individuals living with diabetes in India.Meeting treatment goals for HbA1c, Blood pressure and Cholesterol(ABC) can help prevent diabetes complications.We assessed diabetes awareness, management gaps and attainment of ABC goals among rural South Indian with self-reported diabetes. Methods: The Telemedicine pRoject for screENing Diabetes and its complications in rural Tamil Nadu(TREND) project[2018-2021] was a door-to-door cross-sectional study screening adults in 30 Tamil Nadu villages (n=14,117;1,462 with self-reported diabetes). Clinical/biochemical investigations were performed using standard techniques. ABC Targets were defined as HbA1c<7%, BP<140/90 mmHg and LDL-cholesterol(LDL-C)<100 mg/dl. Diabetic retinopathy(DR) was assessed using mydriatic Remidio “fundus on Phone” and classified using ETDRS criteria. Diabetic nephropathy(DN) was defined as albumin/creatinine ratio(≥30 µg/mg of creatinine). \ Results: Mean age, BMI, fasting plasma glucose and duration of diabetes were 54.7±11.5 years, 25.2±4.2, 169±81 mg/dL, 5.8±5.2 years respectively. Only 1.8% of individuals performed self-monitoring of blood glucose and only 26.3% had their HbA1c tested at least yearly. Fifty three percent were unaware of their level of diabetes control and 35% were unaware that diabetes can affect other organs. Only 4.9% achieved all three ABC goals(HbA1c 27.2%, BP 63.4%, LDL-C 24.3%). Those who did not achieve treatment goals had higher frequency of DR(16.4 vs.4.5%;p<0.05) and DN(40.2 vs.22.2%; p<0.05) than achievers. Multivariable adjustment revealed male gender(OR:0.40, 95% CI 0.2-0.7, p=0.002) and shorter duration of diabetes[<10 years] (OR:0.26, 95% CI 0.5-0.9, p=0.04) to be associated with greater likelihood of achieving goals. Conclusion: There are significant treatment gaps among individuals with diabetes in rural South India, predisposing to high complication rates. Health care systems need to be strengthened to achieve higher treatment goals. Disclosure R. Guha Pradeepa: None. L. Natarajan: None. R. Hari: None. C.N. Palmer: None. R. Unnikrishnan: None. V. Mohan: None. R. Anjana: None. Funding This research was funded by the National Institute for Health Research (NIHR) (INSPIRED 16/136/102) using UK aid from the UK Government to support global health research. The views expressed in this publication are those of the author(s) and not necessarily those of the NIHR or the UK government.

Aim: To assess the screening, diagnostic, and management practices for early gestational diabetes mellitus (EGDM) at obstetric clinics across India. Materials and Methods: A pan-India online survey was conducted among 135 obstetric clinics (both government and private) across 27 Indian states/union territories, using a structured questionnaire to capture information on institutional or hospital settings, screening strategies, diagnostic criteria, and treatment modalities for EGDM. Results: More respondents were from private sector institutions (71.9%), with the majority (63.7%) reporting high antenatal case loads (>500 pregnancies annually). Universal screening for EGDM was the predominant approach (92.6%), with early screening at <8 weeks reported by 34.4% and at 8-12 weeks by 36.8%. Various methods like oral glucose tolerance test, fasting blood glucose (FBG), glycated hemoglobin, or even random blood glucose were used. There was considerable heterogeneity in diagnostic criteria and glucose cutoffs, with FBG >= 92 mg/dL (38.5%) being the most common criterion used to diagnose EGDM. About 49.6% of EGDM women were managed on nutritional therapy alone, whereas the rest received pharmacotherapy. Conclusion: Screening for EGDM in the first trimester of pregnancy is common in India. However, the lack of standardization for screening or diagnosis of EGDM highlights the urgent need for national guidelines for screening, diagnosis, and management of EGDM in India and indeed in other countries as well.

Polished white rice (WR), high in refined carbohydrates, the main staple in South India is associated with enhanced risk of diabetes. Brown Rice (BR), with lower glycemic load, high fibre content and micronutrients, is a healthier choice. Two hundred and twelve Persons with Diabetes (PwD) attending a tertiary diabetes care centre in a city in South India responded to a questionnaire documenting types, frequency and reasons for rice consumption, awareness and beliefs about BR. A sub-set of 10, participated in qualitative interviews, which additionally, explored the influence of traditional beliefs on and consumption patterns of rice, barriers to BR consumption and willingness to accept it in their diet. Ninety-three percent reported consuming WR with traditional usage (97 %) being the main reason for its preference. Brand image, grain size, texture and taste, of rice were other decisional considerations. Awareness about health benefits of BR was limited, with 69 % and 51 % believing it to be nutritious and helping to reduce blood sugar respectively. Appearance, texture, taste and cost were deterrents to its use. Over half agreed to switch to BR if they believed it would improve their health. Participants with a shorter duration of diabetes were more willing to change to BR. The study highlights the need to promote greater literacy regarding health benefits of BR and other forms of less polished rice. Larger trials examining the effectiveness of BR viz-a viz other types of less polished rice on blood glucose levels, metabolic factors and nutritional content among PwD are needed.

Introduction and Objective: Type 1 diabetes in adults is frequently misclassified as type 2, delaying appropriate insulin treatment and leading to worse outcomes. We developed a probability-based tool that combines pre-laboratory clinical characteristics and laboratory results to estimate the likelihood of type 1 vs. type 2 diabetes among adults with new-onset diabetes across four geographic regions. Methods: We convened an expert panel to design a web-based tool using demographic, anthropometric, and laboratory data. We used the published University of Exeter type 1/type 2 diabetes clinical features model for Western Europe and estimated analogous region-specific logistic regression models for Northern Europe (Scania ANDIS), Eastern Europe (Ukraine Exomes), and South Asia (Mohan Clinics). Pre-laboratory type 1 diabetes probability was modelled using log(age at onset), log(BMI), male sex, and parental history. Likelihood ratios for islet autoantibodies (glutamic acid decarboxylase autoantibodies, insulinoma-associated protein-2 autoantibodies, zinc transporter 8 autoantibodies, insulin autoantibodies) were derived from a systematic review and regional datasets. Fasting C-peptide measured at or near diagnosis was modelled with gamma distributions for type 1 and type 2 diabetes to provide continuous likelihood ratios. Results: Across 139,518 adults with new-onset diabetes, the proportion with type 1 diabetes ranged from 2.8% in South Asia to 13.2% in Western Europe. We implemented demographic, anthropometric, and laboratory data in a prototype web-based calculator that generates a pre-laboratory probability and subsequently updates it with autoantibody and C-peptide results. Conclusion: This is the first region-adapted calculator for estimating the probability of type 1 vs. type 2 diabetes in adults with new-onset diabetes. With continued validation in new datasets, this tool has the potential to improve diagnostic accuracy in diabetes and enable earlier appropriate treatment for adults with new-onset diabetes. Disclosure L.K. Billings: Advisory Panel; Current; Novo Nordisk, Lilly, Sanofi, Amgen Inc., Bayer AG. S. Misra: Other - Speaker honorarium for a single presentation at a conferences; Ended; A. Menarini Diagnostics, Lilly Diabetes. Advisory Panel; Ended; Insulet Corporation. Other - Speaker honoararium for a single presentation at a conferences; Ended; Sanofi. M.A. Kohn: None. O. Asplund: None. E. Ahlqvist: Research Support; Current; AstraZeneca. Other - Honorarium for lecture; Ended; AstraZeneca. V. Mohan: None. T.K. Oleksyk: None. M.E. Al-Sofiani: Speaker's Bureau; Ended; Medtronic, Dexcom, Inc. Research Support; Current; Dexcom, Inc. Research Support; Ended; Medtronic. Speaker's Bureau; Ended; Insulet Corporation, Abbott Diabetes, Sanofi. J.M. Brix: Advisory Panel; Current; Abbott Diabetes, Boehringer Ingelheim International GmbH. Speaker's Bureau; Current; AstraZeneca. Speaker's Bureau; Ended; Dexcom, Inc. Speaker's Bureau; Current; Bayer AG. Advisory Panel; Current; Eli Lilly and Company, Merck Sharp & Dohme Corp. Speaker's Bureau; Ended; Medtronic. Advisory Panel; Current; Novo Nordisk. L. DiMeglio: Research Support; Ended; Dompé, Lilly. Stock/Shareholder; Ended; Lilly. Research Support; Current; MannKind Corporation. Research Support; Ended; Provention Bio, Inc. Research Support; Current; Sanofi. Research Support; Ended; Zealand Pharma A/S. Consultant; Current; Tandem Diabetes Care, Inc. Other - DSMB member; Current; Merck & Co., Inc., Lilly. K.L. Fantasia: Stock/Shareholder; Current; Eli Lilly and Company. D. Kerr: Stock/Shareholder; Current; Glooko, Inc. Research Support; Current; Abbott Diabetes. R. Ma: Research Support; Current; AstraZeneca. Speaker's Bureau; Ended; AstraZeneca. Research Support; Current; Boehringer Ingelheim International GmbH. Advisory Panel; Ended; Boehringer Ingelheim International GmbH. Research Support; Ended; Roche Diagnostics. Speaker's Bureau; Current; Roche Diagnostics. Speaker's Bureau; Ended; Eli Lilly and Company. Research Support; Ended; Novo Nordisk. Stock/Shareholder; Current; GemVCare Ltd. J.K. Mader: Research Support; Current; A. Menarini Diagnostics. Advisory Panel; Current; Abbott Diabetes. Speaker's Bureau; Current; Abbott Diabetes. Advisory Panel; Current; Becton, Dickinson and Company. Speaker's Bureau; Current; Becton, Dickinson and Company. Advisory Panel; Current; Insulet Corporation, Eli Lilly and Company. Speaker's Bureau; Current; Eli Lilly and Company. Advisory Panel; Current; Sanofi. Speaker's Bureau; Current; Sanofi. Advisory Panel; Current; Novo Nordisk A/S. Speaker's Bureau; Current; Novo Nordisk A/S. Advisory Panel; Current; Roche Diagnostics. Speaker's Bureau; Current; Roche Diagnostics. Advisory Panel; Current; Medtronic, Tandem Diabetes Care, Inc., Omnipod. Stock/Shareholder; Current; decide Clinical Software GmbH. Advisory Panel; Current; Dexcom, Inc. Speaker's Bureau; Current; Dexcom, Inc., Sinocare, Buzud. Advisory Panel; Current; Biomea Fusion, Pharmasens. Stock/Shareholder; Current; elyte Diagnostics. Other - CMO (unpaid); Current; elyte Diagnostics. Speaker's Bureau; Current; A. Menarini Diagnostics. Board Member; Current; OMNIA by AI APS. Advisory Panel; Current; Triple Jump. N. Mathioudakis: None. C. Mathieu: Advisory Panel; Current; Abbott Diagnostics, Dexcom, Inc. Board Member; Current; European Association for the Study of Diabetes. Advisory Panel; Current; Novo Nordisk, Eli Lilly and Company, Sanofi, Vertex Pharmaceuticals Incorporated, Medtronic. C. Mendez: None. Z. Quandt: Advisory Panel; Ended; Sanofi. M.J. Redondo: Advisory Panel; Current; Sanofi. Other - Data Safety Monitoring committee; Current; Lilly. E.D. Schleicher: None. V. Shah: Advisory Panel; Current; Abbott Diabetes, Dexcom, Inc. Advisory Panel; Ended; Medtronic. Advisory Panel; Current; Novo Nordisk, Eli Lilly and Company. Consultant; Current; Insulet Corporation, T1D Exchange. Advisory Panel; Current; Sanofi, Tandem Diabetes Care, Inc. Consultant; Ended; DreaMed Diabetes, Ltd. N. Thomas: Advisory Panel; Current; Sanofi. Other - Travel support; Ended; Sanofi. G. Umpierrez: Research Support; Current; Abbott, Dexcom, Inc., Bayer AG. Advisory Panel; Ended; Sanofi-Aventis U.S., Dexcom, Inc. Other - Education grant; Current; Lilly Diabetes, Abbott Diabetes. Advisory Panel; Current; Glycare, Glucotrack. Research Support; Current; Corcept Therapeutics. W. Wolfsberger: None. M. Shao: None. A.F. Scheideman: None. A.M. Zhou: None. A. Ayers: Consultant; Ended; Liom Health AG. D. Klonoff: Advisory Panel; Current; Afon Technology, Atropos Health, Embecta, Glooko, Inc., Glucotrack, Lifecare, Inc. Advisory Panel; Ended; Novo Nordisk. Advisory Panel; Current; Sanofi, Synchneuro, Thirdwayv Inc.

AIMS:This systematic scoping review was conducted to map and synthesize literature on retinal biomarkers associated with type 2 diabetes (T2D), including conventional and Artificial Intelligence(AI)-derived features, while considering ethnic/geographic diversity. METHODS:Following PRISMA-ScR statement, seven databases were searched up to January 28, 2026 for cross-sectional and longitudinal studies in adults (≥18 years) with or without T2D. Included studies required a normoglycemic comparator and quantitative retinal assessment, with or without AI. Two reviewers independently performed title/abstract screening, full-text review and quality appraisal (using Newcastle Ottawa scale(NOS)/modified NOS); disagreements were resolved by a third reviewer. Data extraction focused on biomarker type, methodology, and population characteristics. RESULT:Thirty-four studies (27 cross-sectional; 7 longitudinal) were included, mostly evaluating Caucasian/White [n = 18], Asian [n = 15] and Mixed/Latin American [n = 1] populations. Consistent vascular diabetes biomarkers included wider arteriolar and venular calibers. Arteriolar narrowing predicted incident diabetes in longitudinal analyses. Increased vessel tortuosity and altered fractal dimension were frequently observed. Ethnic variation was more pronounced in longitudinal studies; AI-based research was largely confined to China. CONCLUSIONS:Retinal biomarkers show promise for early diabetes detection, but research remains geographically skewed and requires multiethnic validation to ensure clinical impact. These findings provide the biological ground truth necessary for handcrafted feature extraction in the development of interpretative artificial intelligence.

Rapid changes in urbanization in India have paralleled increased prevalence in noncommunicable diseases (NCDs), including type 2 diabetes (T2D), hypertension (HTN), and obesity. To examine sex-specific temporal trends in the prevalence of T2D, HTN, general obesity (GO), and abdominal obesity (AO) among urban populations in India since 2000, a systematic review and meta-analysis was conducted in accordance with a registered Prospective Register of Systematic Reviews protocol (CRD42024548962). PubMed, Global Health (via EBSCOhost), Embase, Scopus, and Web of Science were searched for studies from 2000-2025 (initial search: October 12, 2024; update: July 4, 2025). Eligible studies were cross-sectional and reported the prevalence of T2D or HTN or obesity in urban Indian populations. Screening, data extraction, and risk-of-bias assessment using the Hoy tool were performed independently by 2 reviewers, with a third resolving conflicts. Pooled prevalence was estimated via random-effects meta-analysis in R (version 4.5.3), with forest and funnel plots generated using ggplot2. Out of 3143 records screened, 57 studies were included. The pooled prevalence demonstrated upward trajectory. T2D rose from 13% in 2000-2005 to 21% in 2021-2025, and HTN from 29% to 31%. For obesity, GO increased from 24% in 2000-2005 to 36% in 2016-2020, while AO rose from 47% to 72% over the same period. Sex-stratified analyses showed greater increases among males for T2D and HTN, whereas AO increased more among females. These findings underscore increasing T2D, HTN, and obesity in urban India, highlighting the need for strengthened primary care and supportive environmental and policy measures address the urban NCD burden.

Abstract Late-onset autoimmune diabetes is an increasingly recognized but underdiagnosed entity in older adults and is often misclassified as type 2 diabetes mellitus. Here, we report a case of a 71-year-old lean male with 2 years of poorly controlled diabetes, progressive weight loss, and newly detected hypothyroidism. Investigations revealed strongly positive glutamic acid decarboxylase antibodies (>2000 IU/mL) and absent C-peptide levels, confirming autoimmune β-cell failure. Initial management with premixed insulin was followed by stepwise intensification to a basal–bolus regimen, resulting in significant glycemic improvement. This case report highlights the importance of considering autoimmune diabetes across the adult age spectrum and tailoring insulin strategies to real-world rural settings.

Introduction and Objective: Adolescence represents a critical window for the development of eating behaviors that influence future risk of obesity, diabetes, and other noncommunicable diseases (NCDs). Data linking eating patterns, body image perceptions, and NCD awareness among Indian adolescents remain limited. This study examined these factors among urban Indian adolescents Methods: We conducted a school-based cross-sectional study among 219 adolescents aged 13-17 years in Chennai, India. Participants completed a structured questionnaire assessing eating habits, binge eating behavior, body image perceptions, and awareness of NCDs. Anthropometric measurements, body fat percentage, and blood pressure were assessed using standardized protocols. Sex-specific differences were evaluated using independent t-tests and chi-square analyses. Results: The mean age was 14.5±1.3 years, with 61% boys. Girls had significantly higher body fat percentage compared to boys (23.6±5.2% vs 15.0±6.1%, p<0.001), despite similar BMI (20.5±4.6 vs 19.7±4.4 kg/m², p=0.178). Boys had higher systolic blood pressure (114±12 vs 108±11 mmHg, p<0.001) compared to girls. Eating disorders were common among adolescents, with 55% reporting binge eating (frequent 20%, occasional 25%), more often in boys than girls. Food restriction for weight control was reported by 59%(frequent 21%, occasional 20%), with no sex differences. Body image dissatisfaction was reported by 24%, while 41% perceived pressure to maintain body weight or shape, higher among boys than girls (66% vs 49%, p<0.05). Awareness about NCDs was limited, with only 26% recognizing the link between eating behaviours and increased NCD risk(boys 30%, girls 21%). Conclusion: Urban Indian adolescents demonstrate a high burden of binge eating with body image concerns, and limited awareness about NCDs. Early, school-based interventions targeting healthy eating behaviors and NCD awareness may be critical for diabetes and NCD prevention in this population Disclosure P. Ranjit: None. P. Thyparambil Aravindakshan: None. R. Guha Pradeepa: None. H. Ranjani: None. J. Narayanaswamy: None. P. Dhanakotti: None. R. Unnikrishnan: None. V. Mohan: None. R. Anjana: None. Funding Madras Diabetes Research Foundation, Chennai, India