BMJ Open Diabetes Research & Care最新文献

Obesity medications may be part of a comprehensive care plan for adults with obesity. The Obesity Association, a division of the American Diabetes Association (ADA), developed comprehensive, evidence-based guidelines on the pharmacologic treatment of obesity in adults. When used in conjunction with lifestyle modifications, obesity medications have demonstrated efficacy in inducing and sustaining weight reduction while concurrently improving clinical outcomes of obesity and obesity-related diseases and complications. Healthcare professionals should engage people with obesity in a person-centered, shared decision-making approach when selecting an obesity medication to optimize health outcomes while emphasizing individual needs and preferences. The ADA's Obesity Association encourages healthcare professionals to adopt these guidelines for treatment of obesity in adults.

Introduction: Maturity-onset diabetes of the young (MODY) is a monogenic form of diabetes. MODY type 9 (MODY9) is a rare subtype caused by variants in the PAX4 gene. However, the pathogenicity and mechanisms of many PAX4 variants remain unclear. This study aimed to evaluate the clinical relevance and pathogenic mechanisms of three novel PAX4 variants identified in patients with suspected MODY.

Research design and methods: Three unrelated patients with early-onset diabetes and a family history of the disease were screened for PAX4 variants using whole-exome and Sanger sequencing. In silico predictions, evolutionary conservation analysis, and structural modeling were performed. Functional studies were conducted in MIN6 cells to assess protein expression, subcellular localization, and degradation pathways.

Results: Three novel PAX4 variants (c.83delA; p.Gln28ArgfsTer6, c.35T>C; p.Leu12Pro, and c.488G>C; p.Arg163Pro) were identified. Expression of p.Gln28ArgfsTer6 was undetectable, likely due to nonsense-mediated decay. In contrast, p.Leu12Pro and p.Arg163Pro retained nuclear localization but resulted in markedly reduced protein levels. Treatment with the proteasome inhibitor MG132 restored protein levels of the missense mutants, indicating enhanced proteasomal degradation as the likely mechanism. These findings suggest that certain PAX4 variants impair β-cell function by destabilizing the protein post-translationally.

Conclusions: This study expands the spectrum of PAX4 variants and provides novel mechanistic insights into the pathogenesis of MODY9. Our results highlight the importance of assessing protein-level consequences for variant interpretation and support the integration of functional assays into MODY genetic diagnostic workflows.

Background: Food insecurity (FI) is linked to mental health outcomes cross-sectionally, but little is known about temporal patterns of FI and changes in mental health. FI can exacerbate the mental health challenges of managing diabetes, creating a vicious cycle that worsens youth and young adults' (YYAs) mental well-being.

Purpose: We investigated the association of temporal patterns of FI with symptoms of depression, anxiety, and stress, and changes therein in YYAs with youth-onset type 1 (T1D) and type 2 diabetes (T2D).

Methods: Longitudinal data (2016-2022) including three time points (t₁, t₂, and t₃) from 747 YYAs with T1D and 97 YYAs with T2D were analyzed using multivariable linear regression. Ascertained with the Household Food Security Survey Module, food security was classified as persistently food secure, persistently food insecure (PFI), and intermittently food insecure (IFI). Mental health at t₃ and changes from t₂ to t₃ were characterized with the Center for Epidemiologic Studies Depression Scale, the Generalized Anxiety Disorder Scale, and Cohen's Perceived Stress Scale.

Findings: Among YYAs with T1D and T2D, 6.6% and 16.5% were PFI, 20.3% and 42.3% were IFI, respectively. In YYA with T1D, PFI and IFI were associated with greater depressive, anxiety, and stress symptoms at t₃, and with increased symptoms over time. In YYA with T2D, PFI was associated with greater depressive symptoms at t₃ but not with changes over time.

Interpretation: The study identified a previously unrecognized link between prolonged exposure to FI and increased incidence of mental health issues. Both persistent and intermittent FI were associated with adverse mental health symptoms in YYA with diabetes, more so for those with PFI. Subsequent research should prioritize interventions that address FI in this population to evaluate their effectiveness in enhancing both physical and psychological well-being. It should be designed to not only address FI, but also comprehensive support, including mental health services and education.

Introduction: Type 1 diabetes mellitus (T1DM) is a chronic autoimmune disease targeting insulin-producing cells in the pancreas. The rising global incidence, particularly in early childhood, suggests environmental triggers, such as infections, may contribute to its pathogenesis. Prior studies have reported spatiotemporal clustering of T1DM, and we aimed to further investigate spatial and spatiotemporal clustering in Finnish children using high-quality data with complete residential histories.

Research design and methods: We included patients under 18 diagnosed with T1DM between 1990 and 2019, identified from the Finnish Social Insurance Institution, based on insulin reimbursement. Each case was assigned three age-matched and sex-matched controls. Clustering was analyzed using the Cuzick-Edwards test, Knox test, and Jacquez's Q statistic. Multiple testing adjustments were applied using the Benjamini-Hochberg correction.

Results: The study included 16 307 cases and 48 914 controls (median age at diagnosis: 8.9 years; 56% male). The Cuzick-Edwards test identified modest spatial clustering among males 1 year prior to diagnosis, while the Knox test revealed significant spatiotemporal clustering across all cases. Analyses incorporating full residential histories confirmed these findings, with more pronounced spatiotemporal clustering in children over 6 years old.

Conclusions: These results demonstrate evidence of spatiotemporal clustering of T1DM in Finnish children, supporting the hypothesis of environmental triggers in T1DM etiology. These findings highlight the need for further research to identify the specific environmental factors and mechanisms behind the clustering.

Introduction: Adults with diabetes require regular medical care which can be costly, but little is known about factors associated with delaying or forgoing medical care due to cost among US adults with diabetes.

Research design and methods: Data were from the 2009-2010, 2014-2015 and 2022-2023 cycles of the cross-sectional National Health Interview Survey and included participants age ≥18 years who self-reported a physician diagnosis of diabetes. Descriptive statistics were used to determine the prevalence and trends in delaying or forgoing medical care by sociodemographic and clinical characteristics and health insurance coverage. Logistic regression models were used to determine the OR for delaying or forgoing medical care associated with insurance status.

Results: Among US adults aged 18-64 years with diabetes, delaying or forgoing medical care due to cost decreased from 18.1% to 10.6% and from 14.6% to 10.2%, respectively, between 2009 and 2023. In 2022-2023, the prevalence of delaying medical care due to cost for adults aged 18-64 years was highest for non-Hispanic black adults (13.3%), those with a high school education or less and poverty income ratio <4.0 (12%-13%). In 2022-2023, uninsured adults ≥18 years were significantly more likely to delay medical care compared with those who were insured (adjusted OR (aOR) =7.5, 4.8-11.8, age 18-64 years (adjusted for sociodemographic and clinical characteristics)). Adults aged 18-64 years with Medicaid were significantly less likely to delay medical care compared with those who had private insurance (aOR=0.2, 0. 1-0.4).

Conclusions: There was a decreasing trend for delaying or forgoing medical care across all subpopulations, but adults with lower education and income and who were uninsured more often reported delays in medical care due to cost. The expansion of Medicaid may have reduced the likelihood of delaying or forgoing medical care due to cost among adults aged 18-64 years with Medicaid coverage.

Introduction: Environmental heavy-metal mixtures may contribute to diabetes risk, yet their combined effects remain understudied. We investigated the association between the Metal Mixture Inflammatory Index (MMII) and prevalent diabetes in US adults.

Research design and methods: We analyzed data from 23 288 participants in the 1999-2020 National Health and Nutrition Examination Survey. Survey-weighted logistic regression, restricted cubic splines (RCS), and stratified analyses assessed the relationship between MMII and diabetes. Least absolute shrinkage and selection operator (LASSO) regression identified key predictors, which were incorporated into a nomogram. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC), calibration plots, and decision curve analysis.

Results: After multivariable adjustment, each 0.1-unit increase in MMII was associated with 2% higher odds of diabetes (OR=1.02; 95% CI 1.00 to 1.04; p=0.02). Participants in the highest quartile (Q4) had 26% greater odds than those in the lowest quartile (Q1) (OR=1.26; 95% CI 1.04 to 1.52; p=0.016). RCS analysis indicated a linear positive association between MMII and diabetes risk. Subgroup analyses revealed stronger associations among men, non-Hispanic white participants, former smokers, current alcohol users, and individuals without hypertension. The LASSO-based nomogram demonstrated excellent discrimination (AUC=0.869; 95% CI 0.863 to 0.875), good calibration, and net clinical benefit.

Conclusions: MMII is independently and linearly associated with diabetes risk. Metal exposures may enhance future risk stratification for diabetes. Prospective studies are warranted to confirm causal mechanisms.

Introduction: Hyperosmolar hyperglycemic state (HHS) is a life-threatening metabolic emergency with high mortality rate. Yet, there is no national system in the UK to monitor clinical practice or outcomes. To address this, we implemented and evaluated a multicenter surveillance system for HHS, assessing interhospital variations in management, outcomes, and barriers to guideline implementation.

Research design and methods: This mixed-methods observational study was conducted across 12 NHS hospitals between 2021 and 2024. A standardized data collection tool was developed, capturing demographics, biochemistry, treatment, and outcomes of HHS care. Adults meeting the Joint British Diabetes Societies criteria for HHS were included. Quantitative analyses were conducted to investigate care variations compared with guidelines among centers and identify predictors of HHS outcomes. In parallel, stakeholder interviews were analyzed thematically to explore implementation experiences. The Reach, Effectiveness, Adoption, Implementation, Maintenance framework guided evaluation.

Results: In our cohort, a total of 218 HHS episodes were included. Median patient age was 77 years; 84.4% had type 2 diabetes, with a high comorbidity burden. The median hospital stay was 10.3 days, and the mortality rate was 16.1%. Significant interhospital variation was observed in insulin dosing, glucose monitoring, and time to discharge. Multivariate analysis identified older age and elevated sodium as independent predictors of mortality. The Digital Evaluation of Ketosis and Other Diabetes Emergencies (DEKODE)-HHS model demonstrated feasibility, high user engagement, and potential for integration into routine quality improvement structures. Qualitative findings revealed barriers, including diagnostic misclassification and resource constraints, to the adoption of the DEKODE-HHS model. However, they also highlighted the educational impact and system usability once the model was adopted.

Conclusions: The DEKODE-HHS model represents the first UK multicenter surveillance initiative for HHS. It identifies variation in practice and outcome predictors while highlighting systemic barriers to guideline adherence. This model provides a scalable framework for continuous quality improvement in HHS management and may inform future updates to national guidance.

Introduction: Dyslipidemia is a major risk factor for cardiovascular disease in type 2 diabetes mellitus (T2DM), but its association with kidney disease progression remains incompletely defined. Although low high-density lipoprotein cholesterol (HDL-C) has been linked to diabetic nephropathy, evidence regarding hard kidney outcomes is limited. We examined the associations between HDL-C and kidney events in patients with T2DM, in comparison with other lipid parameters.

Research design and methods: A total of 1,033 patients with T2DM from the Fukushima Cohort Study were included. Participants were followed for kidney events, defined as a ≥50% decrease in estimated glomerular filtration rate (eGFR) or onset of kidney failure requiring kidney replacement therapy, and all-cause mortality over a median follow-up period of 5.3 years. Lipid parameters HDL-C, triglycerides (TG), low-density lipoprotein cholesterol, non-HDL-C, and TG/HDL-C ratio were categorized into quartiles and evaluated using Cox proportional hazards models, adjusted for age, sex, smoking history, history of cardiovascular disease, body mass index, systolic blood pressure, eGFR, hemoglobin A1c, and proteinuria.

Results: The median patient age was 66 years, 56% were men, and the median eGFR was 68.6 mL/min/1.73 m². After multivariable adjustment, patients in the lowest HDL-C quartile (<42 mg/dL) had significantly higher risks of kidney events (adjusted HR 2.61, 95% CI 1.32 to 5.14) and all-cause mortality (adjusted HR 2.27, 95% CI 1.16 to 4.42) than the reference group (HDL-C 49-58 mg/dL). A U-shaped association was observed between HDL-C and all-cause mortality. Subgroup and sensitivity analyses were consistent. No significant associations were observed for other lipid parameters with either kidney events or mortality.

Conclusions: Low HDL-C levels were independently associated with kidney events and all-cause mortality in patients with T2DM. Future studies are warranted to clarify whether interventions targeting HDL-C can improve kidney disease progression in this high-risk population.

Trial registration number: UMIN000040848.

Introduction: Cardiovascular disease (CVD) is a common complication and major cause of mortality in people with type 1 diabetes (T1D). This study quantifies the prevalence of CVD among commercially insured adults with T1D in the USA from 2017 to 2021, overall and among age-defined and sex-defined subgroups.

Research design and methods: We used Merative MarketScan nationwide commercial insurance claims database (2017-2021) to identify adults ≥20 years with T1D (International Classification of Diseases, 10th Revision (ICD-10) codes). CVD ascertainment was based on ICD-10 codes for myocardial infarction, atrial fibrillation, ischemic heart disease, heart failure, peripheral artery disease, and stroke. Comorbidities included hypertension, obesity, hyperlipidemia, retinopathy, neuropathy, nephropathy, severe hypoglycemia, and diabetic ketoacidosis. Annual prevalence and age-specific and sex-specific prevalence of CVD were calculated overall and by comorbidities. Logistic regression was used to examine associations between sex, prevalent comorbidities, and odds of CVD.

Results: The sample size ranged from n=21 748 in 2017 to n=13 294 in 2021. Among adults with T1D (mean (SD) age (48.51 (13.95) years in 2017 and 46.80 (13.04) years in 2021; 47% female), the prevalence of CVD ranged from 18.18% (95% CI 17.77 to 18.66%) in 2017 to 20.58% (95% CI 19.91 to 21.24%) in 2021. In 2021, among those aged 20-39 years, 40-64 years, and 65+years, the prevalence of CVD was 4.97%, 20.41%, and 52.94%, respectively. The age-adjusted prevalence of CVD was higher in males than females (21.93% vs 19.07%). Age, sex, and all comorbidities were independently associated with CVD. Odds of CVD were highest among those with hypertension (adjusted OR 3.15, 95% CI: 2.77 to 3.57).

Conclusion: In this sample of US commercially insured adults with T1D, CVD prevalence remained stable at ~20% from 2017 to 2021. Early detection via improved screening and targeted management of comorbidities are key preventive strategies.