Metabolic consequences of obesity and type 2 diabetes: Balancing genes and environment for personalized care.

The prevalence of type 2 diabetes and obesity has risen dramatically for decades and is expected to rise further, secondary to the growing aging, sedentary population. The strain on global health care is projected to be colossal. This review explores the latest work and emerging ideas related to genetic and environmental factors influencing metabolism. Translational research and clinical applications, including the impact of the COVID-19 pandemic, are highlighted. Looking forward, strategies to personalize all aspects of prevention, management and care are necessary to improve health outcomes and reduce the impact of these metabolic diseases.

Pragmatic Trial of Hospitalization Rate in Chronic Kidney Disease.

BACKGROUND: Despite the availability of effective therapies for patients with chronic kidney disease, type 2 diabetes, and hypertension (the kidney-dysfunction triad), the results of large-scale trials examining the implementation of guideline-directed therapy to reduce the risk of death and complications in this population are lacking. METHODS: In this open-label, cluster-randomized trial, we assigned 11,182 patients with the kidney-dysfunction triad who were being treated at 141 primary care clinics either to receive an intervention that used a personalized algorithm (based on the patient's electronic health record [EHR]) to identify patients and practice facilitators to assist providers in delivering guideline-based interventions or to receive usual care. The primary outcome was hospitalization for any cause at 1 year. Secondary outcomes included emergency department visits, readmissions, cardiovascular events, dialysis, and death. RESULTS: We assigned 71 practices (enrolling 5690 patients) to the intervention group and 70 practices (enrolling 5492 patients) to the usual-care group. The hospitalization rate at 1 year was 20.7% (95% confidence interval [CI], 19.7 to 21.8) in the intervention group and 21.1% (95% CI, 20.1 to 22.2) in the usual-care group (between-group difference, 0.4 percentage points; P = 0.58). The risks of emergency department visits, readmissions, cardiovascular events, dialysis, or death from any cause were similar in the two groups. The risk of adverse events was also similar in the trial groups, except for acute kidney injury, which was observed in more patients in the intervention group (12.7% vs. 11.3%). CONCLUSIONS: In this pragmatic trial involving patients with the triad of chronic kidney disease, type 2 diabetes, and hypertension, the use of an EHR-based algorithm and practice facilitators embedded in primary care clinics did not translate into reduced hospitalization at 1 year. (Funded by the National Institutes of Health and others; ICD-Pieces ClinicalTrials.gov number, NCT02587936.).

A multivariate genome-wide association study of psycho-cardiometabolic multimorbidity.

Coronary artery disease (CAD), type 2 diabetes (T2D) and depression are among the leading causes of chronic morbidity and mortality worldwide. Epidemiological studies indicate a substantial degree of multimorbidity, which may be explained by shared genetic influences. However, research exploring the presence of pleiotropic variants and genes common to CAD, T2D and depression is lacking. The present study aimed to identify genetic variants with effects on cross-trait liability to psycho-cardiometabolic diseases. We used genomic structural equation modelling to perform a multivariate genome-wide association study of multimorbidity (Neffective = 562,507), using summary statistics from univariate genome-wide association studies for CAD, T2D and major depression. CAD was moderately genetically correlated with T2D (rg = 0.39, P = 2e-34) and weakly correlated with depression (rg = 0.13, P = 3e-6). Depression was weakly correlated with T2D (rg = 0.15, P = 4e-15). The latent multimorbidity factor explained the largest proportion of variance in T2D (45%), followed by CAD (35%) and depression (5%). We identified 11 independent SNPs associated with multimorbidity and 18 putative multimorbidity-associated genes. We observed enrichment in immune and inflammatory pathways. A greater polygenic risk score for multimorbidity in the UK Biobank (N = 306,734) was associated with the co-occurrence of CAD, T2D and depression (OR per standard deviation = 1.91, 95% CI = 1.74-2.10, relative to the healthy group), validating this latent multimorbidity factor. Mendelian randomization analyses suggested potentially causal effects of BMI, body fat percentage, LDL cholesterol, total cholesterol, fasting insulin, income, insomnia, and childhood maltreatment. These findings advance our understanding of multimorbidity suggesting common genetic pathways.

Current Status and Principles for the Treatment and Prevention of Diabetic Foot Ulcers in the Cardiovascular Patient Population: A Scientific Statement From the American Heart Association.

Despite the known higher risk of cardiovascular disease in individuals with type 2 diabetes, the pathophysiology and optimal management of diabetic foot ulcers (DFUs), a leading complication associated with diabetes, is complex and continues to evolve. Complications of type 2 diabetes, such as DFUs, are a major cause of morbidity and mortality and the leading cause of major lower extremity amputation in the United States. There has recently been a strong focus on the prevention and early treatment of DFUs, leading to the development of multidisciplinary diabetic wound and amputation prevention clinics across the country. Mounting evidence has shown that, despite these efforts, amputations associated with DFUs continue to increase. Furthermore, due to increasing patient complexity of management secondary to comorbid conditions, such as cardiovascular disease, the management of peripheral artery disease associated with DFUs has become increasingly difficult, and care delivery is often episodic and fragmented. Although structured, process-specific approaches exist at individual institutions for the management of DFUs in the cardiovascular patient population, there is insufficient awareness of these principles in the general medicine communities. Furthermore, there is growing interest in better understanding the mechanistic underpinnings of DFUs to better define personalized medicine to improve outcomes. The goals of this scientific statement are to provide salient background information on the complex pathogenesis and current management of DFUs in cardiovascular patients, to guide therapeutic and preventive strategies and future research directions, and to inform public policy makers on health disparities and other barriers to improving and advancing care in this expanding patient population.

Validation of AGA clinical care pathway and AASLD practice guidance for nonalcoholic fatty liver disease in a prospective cohort of patients with type 2 diabetes.

BACKGROUND AND AIMS: Recently, the American Gastroenterological Association and the American Association for the Study of Liver Diseases developed clinical pathways to evaluate populations at high risk for NAFLD. We assessed the diagnostic performance of the new guidance in a well-phenotyped cohort of patients with Type 2 diabetes mellitus (T2DM). APPROACH AND RESULTS: This prospective study enrolled patients age ≥50 years with T2DM. Participants underwent a standardized clinical research visit with MRI and ultrasound-based assessment of liver fat and stiffness and Enhanced Liver Fibrosis (ELF) testing. Of 417 participants (36% men) with T2DM with FIB-4 and MRE data, the prevalence of NAFLD was 64% and 12% had advanced fibrosis (MRE≥3.63 kPa). Applying the American Gastroenterological Association pathway of FIB-4 and vibration-controlled transient elastography, the false negative rate was 3.3% and 18% would qualify for specialty referral. Applying the FIB-4 + ELF American Association for the Study of Liver Diseases pathway, the false negative rate was 4.5%, but 50% would qualify for specialty referral. Applying higher ELF cut points improved the pathway, yielding a similar false negative rate of 4.9% but decreased specialty referral to 27%. CONCLUSION: Validation of the American Gastroenterological Association clinical pathway in a prospectively recruited cohort with T2DM revealed a low false negative rate and avoided specialty referral in a large percentage of patients. The American Association for the Study of Liver Diseases pathway with FIB-4 + ELF resulted in a high rate of specialty referral, which improved with the utilization of higher ELF cut points and may serve as an alternative for primary care and endocrinology clinics without access to vibration-controlled transient elastography.

Polygenic subtype identified in ACCORD trial displays a favorable type 2 diabetes phenotype in the UKBiobank population.

INTRODUCTION: We previously identified a genetic subtype (C4) of type 2 diabetes (T2D), benefitting from intensive glycemia treatment in the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial. Here, we characterized the population of patients that met the C4 criteria in the UKBiobank cohort. RESEARCH DESIGN AND METHODS: Using our polygenic score (PS), we identified C4 individuals in the UKBiobank and tested C4 status with risk of developing T2D, cardiovascular disease (CVD) outcomes, and differences in T2D medications. RESULTS: C4 individuals were less likely to develop T2D, were slightly older at T2D diagnosis, had lower HbA1c values, and were less likely to be prescribed T2D medications (P < .05). Genetic variants in MAS1 and IGF2R, major components of the C4 PS, were associated with fewer overall T2D prescriptions. CONCLUSION: We have confirmed C4 individuals are a lower risk subpopulation of patients with T2D.

Lipidomic risk scores are independent of polygenic risk scores and can predict incidence of diabetes and cardiovascular disease in a large population cohort.

Type 2 diabetes (T2D) and cardiovascular disease (CVD) represent significant disease burdens for most societies and susceptibility to these diseases is strongly influenced by diet and lifestyle. Physiological changes associated with T2D or CVD, such has high blood pressure and cholesterol and glucose levels in the blood, are often apparent prior to disease incidence. Here we integrated genetics, lipidomics, and standard clinical diagnostics to assess future T2D and CVD risk for 4,067 participants from a large prospective population-based cohort, the Malmö Diet and Cancer-Cardiovascular Cohort. By training Ridge regression-based machine learning models on the measurements obtained at baseline when the individuals were healthy, we computed several risk scores for T2D and CVD incidence during up to 23 years of follow-up. We used these scores to stratify the participants into risk groups and found that a lipidomics risk score based on the quantification of 184 plasma lipid concentrations resulted in a 168% and 84% increase of the incidence rate in the highest risk group and a 77% and 53% decrease of the incidence rate in lowest risk group for T2D and CVD, respectively, compared to the average case rates of 13.8% and 22.0%. Notably, lipidomic risk correlated only marginally with polygenic risk, indicating that the lipidome and genetic variants may constitute largely independent risk factors for T2D and CVD. Risk stratification was further improved by adding standard clinical variables to the model, resulting in a case rate of 51.0% and 53.3% in the highest risk group for T2D and CVD, respectively. The participants in the highest risk group showed significantly altered lipidome compositions affecting 167 and 157 lipid species for T2D and CVD, respectively. Our results demonstrated that a subset of individuals at high risk for developing T2D or CVD can be identified years before disease incidence. The lipidomic risk, which is derived from only one single mass spectrometric measurement that is cheap and fast, is informative and could extend traditional risk assessment based on clinical assays.

Role of Gut Microbiota in Statin-Associated New-Onset Diabetes-A Cross-Sectional and Prospective Analysis of the FINRISK 2002 Cohort.

BACKGROUND: Dyslipidemia is treated effectively with statins, but treatment has the potential to induce new-onset type-2 diabetes. Gut microbiota may contribute to this outcome variability. We assessed the associations of gut microbiota diversity and composition with statins. Bacterial associations with statin-associated new-onset type-2 diabetes (T2D) risk were also prospectively evaluated. METHODS: We examined shallow-shotgun-sequenced fecal samples from 5755 individuals in the FINRISK-2002 population cohort with a 17+-year-long register-based follow-up. Alpha-diversity was quantified using Shannon index and beta-diversity with Aitchison distance. Species-specific differential abundances were analyzed using general multivariate regression. Prospective associations were assessed with Cox regression. Applicable results were validated using gradient boosting. RESULTS: Statin use associated with differing taxonomic composition (R2, 0.02%; q=0.02) and 13 differentially abundant species in fully adjusted models (MaAsLin; q<0.05). The strongest positive association was with Clostridium sartagoforme (ß=0.37; SE=0.13; q=0.02) and the strongest negative association with Bacteroides cellulosilyticus (ß=-0.31; SE=0.11; q=0.02). Twenty-five microbial features had significant associations with incident T2D in statin users, of which only Bacteroides vulgatus (HR, 1.286 [1.136-1.457]; q=0.03) was consistent regardless of model adjustment. Finally, higher statin-associated T2D risk was seen with [Ruminococcus] torques (ΔHRstatins, +0.11; q=0.03), Blautia obeum (ΔHRstatins, +0.06; q=0.01), Blautia sp. KLE 1732 (ΔHRstatins, +0.05; q=0.01), and beta-diversity principal component 1 (ΔHRstatin, +0.07; q=0.03) but only when adjusting for demographic covariates. CONCLUSIONS: Statin users have compositionally differing microbiotas from nonusers. The human gut microbiota is associated with incident T2D risk in statin users and possibly has additive effects on statin-associated new-onset T2D risk.

Metformin in elderly type 2 diabetes mellitus: dose-dependent dementia risk reduction.

This study aimed to investigate the controversial association between metformin use and diabetes-associated dementia in elderly patients with type 2 diabetes mellitus (T2DM) and evaluate the potential protective effects of metformin, as well as its intensity of use and dose-dependency, against dementia in this population. The study used a time-dependent Cox hazards model to evaluate the effect of metformin use on the incidence of dementia. The case group included elderly patients with T2DM (≥60 years old) who received metformin, while the control group consisted of elderly patients with T2DM who did not receive metformin during the follow-up period. Our analysis revealed a significant reduction in the risk of dementia among elderly individuals using metformin, with an adjusted hazard ratio of 0.34 (95% confidence interval: 0.33 to 0.36). Notably, metformin users with a daily intensity of 1 defined daily dose (DDD) or higher had a lower risk of dementia, with an adjusted hazard ratio (95% confidence interval) of 0.46 (0.22 to 0.6), compared to those with a daily intensity of <1 DDD. Additionally, the analysis of cumulative DDDs of metformin showed a dose-response relationship, with progressively lower adjusted hazard ratio across quartiles (0.15, 0.21, 0.28, and 0.53 for quartiles 4, 3, 2 and 1, respectively), compared to never metformin users (P for trend < 0.0001). Metformin use in elderly patients with T2DM is significantly associated with a substantial reduction in the risk of dementia. Notably, the protective effect of metformin demonstrates a dose-dependent relationship, with higher daily and cumulative dosages of metformin showing a greater risk reduction.

Income variability and incident cardiovascular disease in diabetes: a population-based cohort study.

BACKGROUND AND AIMS: Longitudinal change in income is crucial in explaining cardiovascular health inequalities. However, there is limited evidence for cardiovascular disease (CVD) risk associated with income dynamics over time among individuals with type 2 diabetes (T2D). METHODS: Using a nationally representative sample from the Korean National Health Insurance Service database, 1 528 108 adults aged 30-64 with T2D and no history of CVD were included from 2009 to 2012 (mean follow-up of 7.3 years). Using monthly health insurance premium information, income levels were assessed annually for the baseline year and the four preceding years. Income variability was defined as the intraindividual standard deviation of the percent change in income over 5 years. The primary outcome was a composite event of incident fatal and nonfatal CVD (myocardial infarction, heart failure, and stroke) using insurance claims. Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated after adjusting for potential confounders. RESULTS: High-income variability was associated with increased CVD risk (HRhighest vs. lowest quartile 1.25, 95% CI 1.22-1.27; Ptrend < .001). Individuals who experienced an income decline (4 years ago vs. baseline) had increased CVD risk, which was particularly notable when the income decreased to the lowest level (i.e. Medical Aid beneficiaries), regardless of their initial income status. Sustained low income (i.e. lowest income quartile) over 5 years was associated with increased CVD risk (HRn = 5 years vs. n = 0 years 1.38, 95% CI 1.35-1.41; Ptrend < .0001), whereas sustained high income (i.e. highest income quartile) was associated with decreased CVD risk (HRn = 5 years vs. n = 0 years 0.71, 95% CI 0.70-0.72; Ptrend < .0001). Sensitivity analyses, exploring potential mediators, such as lifestyle-related factors and obesity, supported the main results. CONCLUSIONS: Higher income variability, income declines, and sustained low income were associated with increased CVD risk. Our findings highlight the need to better understand the mechanisms by which income dynamics impact CVD risk among individuals with T2D.

Child-to-adult body size change and risk of type 2 diabetes and cardiovascular disease.

AIMS/HYPOTHESIS: Childhood overweight increases the risk of type 2 diabetes and cardiovascular disease in adulthood. However, the impact of childhood leanness on adult obesity and disease risk has been overlooked. We examined the independent and combined influences of child and adult body size on the risk of type 2 diabetes and cardiovascular disease. METHODS: Data from the UK Biobank on 364,695 individuals of European ancestry and free of type 2 diabetes and cardiovascular disease were divided into nine categories based on their self-reported body size at age 10 and measured BMI in adulthood. After a median follow-up of 12.8 years, 33,460 individuals had developed type 2 diabetes and/or cardiovascular disease. We used Cox regression models to assess the associations of body size categories with disease incidence. RESULTS: Individuals with low body size in childhood and high body size in adulthood had the highest risk of type 2 diabetes (HR 4.73; 95% CI 4.50, 4.99), compared to those with average body size in both childhood and adulthood. This was significantly higher than the risk in those with high body size in both childhood and adulthood (HR 4.05; 95% CI 3.84, 4.26). By contrast, cardiovascular disease risk was determined by adult body size, irrespective of childhood body size. CONCLUSIONS/INTERPRETATION: Low body size in childhood exacerbates the risk of type 2 diabetes associated with adult obesity but not the risk of cardiovascular disease. Thus, promoting healthy weight management from childhood to adulthood, among lean children, is crucial.

Feasibility of prevention of type 2 diabetes in low- and middle-income countries.

Type 2 diabetes is a leading cause of global mortality and morbidity. Nearly 80% of individuals with diabetes live in low- and middle-income countries (LMICs), where nearly half of those with the condition remain undiagnosed. The majority of known cases have sub-optimal clinical outcomes. Moreover, large populations with impaired glucose tolerance and/or impaired fasting glucose contribute to the rapid increase in type 2 diabetes. Globally, priority should be given to limit the population with diabetes, especially in LMICs, alongside actions to optimise the care of people diagnosed with diabetes. Primary prevention studies in LMICs have generated evidence to show the efficacy and scalability of strategies to fully prevent or delay the development of diabetes in high-risk groups. However, these are mainly limited to certain countries in Asia, particularly China and India. The studies have indicated that prevention policies are effective in populations with a high risk of type 2 diabetes, and they also have long-term benefits, not only for the risk of type 2 diabetes but also for the risk of associated metabolic disorders, such as CVDs. For the effective conduct of national programmes, innovative mechanisms must be implemented, such as the use of information technology, joint efforts of multiple teams implementing similar programmes, and involvement of governmental and non-governmental partnerships. Continuous monitoring and long-term studies are required to assess the utility of these programmes. The effectiveness of such programmes in LMICs has not been proven over the longer term, except in China. Despite the available evidence, the feasibility of prevention strategies for type 2 diabetes in LMICs at population level remains an enigma. There remain challenges in the form of cultural, societal and economic constraints; insufficient infrastructure and healthcare capacity; and the non-fully elucidated natural history and determinants of type 2 diabetes in LMICs.

Epidemiology of heart failure in diabetes: a disease in disguise.

Left ventricular diastolic dysfunction (LVDD) without symptoms, and heart failure (HF) with preserved ejection fraction (HFpEF) represent the most common phenotypes of HF in individuals with type 2 diabetes mellitus, and are more common than HF with reduced ejection fraction (HFrEF), HF with mildly reduced ejection fraction (HFmrEF) and left ventricular systolic dysfunction (LVSD) in these individuals. However, diagnostic criteria for HF have changed over the years, resulting in heterogeneity in the prevalence/incidence rates reported in different studies. We aimed to give an overview of the diagnosis and epidemiology of HF in type 2 diabetes, using both a narrative and systematic review approach; we focus narratively on diagnosing (using the 2021 European Society of Cardiology [ESC] guidelines) and screening for HF in type 2 diabetes. We performed an updated (2016-October 2022) systematic review and meta-analysis of studies reporting the prevalence and incidence of HF subtypes in adults ≥18 years with type 2 diabetes, using echocardiographic data. Embase and MEDLINE databases were searched and data were assessed using random-effects meta-analyses, with findings presented as forest plots. From the 5015 studies found, 209 were screened using the full-text article. In total, 57 studies were included, together with 29 studies that were identified in a prior meta-analysis; these studies reported on the prevalence of LVSD (n=25 studies, 24,460 individuals), LVDD (n=65 studies, 25,729 individuals), HFrEF (n=4 studies, 4090 individuals), HFmrEF (n=2 studies, 2442 individuals) and/or HFpEF (n=8 studies, 5292 individuals), and on HF incidence (n=7 studies, 17,935 individuals). Using Hoy et al's risk-of-bias tool, we found that the studies included generally had a high risk of bias. They showed a prevalence of 43% (95% CI 37%, 50%) for LVDD, 17% (95% CI 7%, 35%) for HFpEF, 6% (95% CI 3%, 10%) for LVSD, 7% (95% CI 3%, 15%) for HFrEF, and 12% (95% CI 7%, 22%) for HFmrEF. For LVDD, grade I was found to be most prevalent. Additionally, we reported a higher incidence rate of HFpEF (7% [95% CI 4%, 11%]) than HFrEF 4% [95% CI 3%, 7%]). The evidence is limited by the heterogeneity of the diagnostic criteria over the years. The systematic section of this review provides new insights on the prevalence/incidence of HF in type 2 diabetes, unveiling a large pre-clinical target group with LVDD/HFpEF in which disease progression could be halted by early recognition and treatment.Registration PROSPERO ID CRD42022368035.

Multi-omic prediction of incident type 2 diabetes.

AIMS/HYPOTHESIS: The identification of people who are at high risk of developing type 2 diabetes is a key part of population-level prevention strategies. Previous studies have evaluated the predictive utility of omics measurements, such as metabolites, proteins or polygenic scores, but have considered these separately. The improvement that combined omics biomarkers can provide over and above current clinical standard models is unclear. The aim of this study was to test the predictive performance of genome, proteome, metabolome and clinical biomarkers when added to established clinical prediction models for type 2 diabetes. METHODS: We developed sparse interpretable prediction models in a prospective, nested type 2 diabetes case-cohort study (N=1105, incident type 2 diabetes cases=375) with 10,792 person-years of follow-up, selecting from 5759 features across the genome, proteome, metabolome and clinical biomarkers using least absolute shrinkage and selection operator (LASSO) regression. We compared the predictive performance of omics-derived predictors with a clinical model including the variables from the Cambridge Diabetes Risk Score and HbA1c. RESULTS: Among single omics prediction models that did not include clinical risk factors, the top ten proteins alone achieved the highest performance (concordance index [C index]=0.82 [95% CI 0.75, 0.88]), suggesting the proteome as the most informative single omic layer in the absence of clinical information. However, the largest improvement in prediction of type 2 diabetes incidence over and above the clinical model was achieved by the top ten features across several omic layers (C index=0.87 [95% CI 0.82, 0.92], Δ C index=0.05, p=0.045). This improvement by the top ten omic features was also evident in individuals with HbA1c <42 mmol/mol (6.0%), the threshold for prediabetes (C index=0.84 [95% CI 0.77, 0.90], Δ C index=0.07, p=0.03), the group in whom prediction would be most useful since they are not targeted for preventative interventions by current clinical guidelines. In this subgroup, the type 2 diabetes polygenic risk score was the major contributor to the improvement in prediction, and achieved a comparable improvement in performance when added onto the clinical model alone (C index=0.83 [95% CI 0.75, 0.90], Δ C index=0.06, p=0.002). However, compared with those with prediabetes, individuals at high polygenic risk in this group had only around half the absolute risk for type 2 diabetes over a 20 year period. CONCLUSIONS/INTERPRETATION: Omic approaches provided marginal improvements in prediction of incident type 2 diabetes. However, while a polygenic risk score does improve prediction in people with an HbA1c in the normoglycaemic range, the group in whom prediction would be most useful, even individuals with a high polygenic burden in that subgroup had a low absolute type 2 diabetes risk. This suggests a limited feasibility of implementing targeted population-based genetic screening for preventative interventions.

The impact of taxing sugar-sweetened beverages on diabetes: a critical review.

The global burden of type 2 diabetes is increasing at an alarming rate, fuelled by the obesity epidemic, with significant associated health and economic consequences and apparent inequalities. Sugar-sweetened beverages (SSBs) are a major source of added sugars in diets worldwide and have been linked to an increased risk of type 2 diabetes through a variety of mechanisms, including excess weight. Taxing SSBs has become a promising public health strategy to reduce consumption and mitigate the burden of type 2 diabetes. A substantial body of evidence suggests that SSB taxes lead to increased prices and subsequent reduced consumption, with a potentially greater effect among lower socioeconomic groups. This highlights the potential for tax policies to have an impact on type 2 diabetes and address health inequalities. Evidence from several ongoing SSB tax schemes, including sales and excise taxes, indicates positive effects on improving consumption patterns, and modelling studies point to health gains by averting type 2 diabetes and other cardiometabolic diseases. In contrast, evidence from empirical evaluation of the impact of SSB tax is scarce. Continued monitoring and the strengthening of evaluation research to develop context-tailored policies are required. In addition, there is a need to implement complementary efforts to amplify the impact of SSB taxation and effectively address the global burden of type 2 diabetes.

Cardiovascular and mortality outcomes with GLP-1 receptor agonists vs other glucose-lowering drugs in individuals with NAFLD and type 2 diabetes: a large population-based matched cohort study.

AIMS/HYPOTHESIS: We aimed to determine whether the use of glucagon-like peptide-1 receptor agonists (GLP-1RA) in individuals with non-alcoholic fatty liver disease (NAFLD) and type 2 diabetes mellitus decreases the risk of new-onset adverse cardiovascular events (CVEs) and mortality rate compared with other glucose-lowering drugs in a real setting at a population level. METHODS: We conducted a population-based propensity-matched retrospective cohort study using TriNetX. The cohort comprised patients over 20 years old who were newly treated with glucose-lowering drugs between 1 January 2013 and 31 December 2021, and followed until 30 September 2022. New users of GLP-1RAs were matched based on age, demographics, comorbidities and medication use by using 1:1 propensity matching with other glucose-lowering drugs. The primary outcome was the new onset of adverse CVEs, including heart failure, composite incidence of major adverse cardiovascular events (MACE; defined as unstable angina, myocardial infarction, or coronary artery procedures or surgeries) and composite cerebrovascular events (defined as the first occurrence of stroke, transient ischaemic attack, cerebral infarction, carotid intervention or surgery), and the secondary outcome was all-cause mortality. Cox proportional hazards models were used to estimate HRs. RESULTS: The study involved 2,835,398 patients with both NAFLD and type 2 diabetes. When compared with the sodium-glucose cotransporter 2 (SGLT2) inhibitors group, the GLP-1RAs group showed no evidence of a difference in terms of new-onset heart failure (HR 0.97; 95% CI 0.93, 1.01), MACE (HR 0.95; 95% CI 0.90, 1.01) and cerebrovascular events (HR 0.99; 95% CI 0.94, 1.03). Furthermore, the two groups had no evidence of a difference in mortality rate (HR 1.06; 95% CI 0.97, 1.15). Similar results were observed across sensitivity analyses. Compared with other second- or third-line glucose-lowering medications, the GLP-1RAs demonstrated a lower rate of adverse CVEs, including heart failure (HR 0.88; 95% CI 0.85, 0.92), MACE (HR 0.89; 95% CI 0.85, 0.94), cerebrovascular events (HR 0.93; 95% CI 0.89, 0.96) and all-cause mortality rate (HR 0.70; 95% CI 0.66, 0.75). CONCLUSIONS/INTERPRETATION: In individuals with NAFLD and type 2 diabetes, GLP-1RAs are associated with lower incidences of adverse CVEs and all-cause mortality compared with metformin or other second- and third-line glucose-lowering medications. However, there was no significant difference in adverse CVEs or all-cause mortality when compared with those taking SGLT2 inhibitors.

Incidence trend of type 2 diabetes from 2012 to 2021 in Germany: an analysis of health claims data of 11 million statutorily insured people.

AIMS/HYPOTHESIS: The aim of the study is to describe the time trend of type 2 diabetes incidence in the largest state of Germany, Bavaria, from 2012 to 2021, and to compare the incidence rates during the pandemic period (2020-2021) to the pre-pandemic period (2012-2019). METHODS: This secondary data analysis uses health claims data provided by the Bavarian Association of Statutory Health Insurance Physicians (KVB), covering approximately 11 million insurees, accounting for 85% of the total population of Bavaria, Germany. Newly diagnosed type 2 diabetes cases in adults (≥20 years) coded as E11 (Diabetes mellitus, Type 2) or E14 (Unspecified diabetes mellitus) under ICD-10, German modification (ICD-10-GM) for the study period 2012 to 2021 were included. Annual and quarterly age-standardised incidence rates (ASIR) stratified by sex, age and region were calculated using the European standard population. Sex-specific crude incidence rates (CIR) were calculated using 10-year age groups. Regression analyses adjusted for time trends, seasonal effects, and pandemic effects were used to analyse the incidence trend and to assess the effect of the pandemic. RESULTS: Overall, 745,861 new cases of type 2 diabetes were diagnosed between 2012 and 2021: 50.4% (376,193 cases) in women. The male/female ratio remained stable over the observation period, while the median age at diagnosis decreased from 61 to 58 years in men and from 66 years to 61 years in women. ASIR were consistently higher for men compared with women, with the yearly difference remaining stable over time (2012: 18%; 2021: 20%). An overall decreasing trend in ASIR was observed during the study period, with a strong decrease from 2012 to 2017, followed by a less pronounced decline from 2018 to 2021 for both sexes. For men, ASIR decreased from 1514 per 100,000 person-years in 2012 to 995 per 100,000 person-years in 2021 (4.6% average annual reduction), and for women from 1238 per 100,000 person-years in 2012 to 796 per 100,000 person-years in 2021 (4.8% average annual reduction). This downward trend was also observed for age groups above 50 years. Regression analyses showed no significant change in incidence rates during the pandemic period (2020 and 2021) compared with the pre-pandemic period. CONCLUSIONS/INTERPRETATION: For the first time, a 10-year incidence trend of type 2 diabetes is reported for Germany, showing a strong decline from 2012 to 2017, followed by a less pronounced decline from 2018 to 2021. The incidence trend of type 2 diabetes appears not to have been affected by the first 2 years of the COVID-19 pandemic. Despite an overall increasing prevalence, the incidence is decreasing, potentially resulting from robust screening by family physicians, reducing the median age at diagnosis by 3 to 5 years. However, further investigation is needed to fully identify the reasons for the declining incidence trend. Continued incidence monitoring is necessary to identify the long-term trend and the potential effect of the pandemic on diagnoses of type 2 diabetes.

Trajectories of clinical characteristics, complications and treatment choices in data-driven subgroups of type 2 diabetes.

AIMS/HYPOTHESIS: This study aimed to explore the added value of subgroups that categorise individuals with type 2 diabetes by k-means clustering for two primary care registries (the Netherlands and Scotland), inspired by Ahlqvist's novel diabetes subgroups and previously analysed by Slieker et al. METHODS: We used two Dutch and Scottish diabetes cohorts (N=3054 and 6145; median follow-up=11.2 and 12.3 years, respectively) and defined five subgroups by k-means clustering with age at baseline, BMI, HbA1c, HDL-cholesterol and C-peptide. We investigated differences between subgroups by trajectories of risk factor values (random intercept models), time to diabetes-related complications (logrank tests and Cox models) and medication patterns (multinomial logistic models). We also compared directly using the clustering indicators as predictors of progression vs the k-means discrete subgroups. Cluster consistency over follow-up was assessed. RESULTS: Subgroups' risk factors were significantly different, and these differences remained generally consistent over follow-up. Among all subgroups, individuals with severe insulin resistance faced a significantly higher risk of myocardial infarction both before (HR 1.65; 95% CI 1.40, 1.94) and after adjusting for age effect (HR 1.72; 95% CI 1.46, 2.02) compared with mild diabetes with high HDL-cholesterol. Individuals with severe insulin-deficient diabetes were most intensively treated, with more than 25% prescribed insulin at 10 years of diagnosis. For severe insulin-deficient diabetes relative to mild diabetes, the relative risks for using insulin relative to no common treatment would be expected to increase by a factor of 3.07 (95% CI 2.73, 3.44), holding other factors constant. Clustering indicators were better predictors of progression variation relative to subgroups, but prediction accuracy may improve after combining both. Clusters were consistent over 8 years with an accuracy ranging from 59% to 72%. CONCLUSIONS/INTERPRETATION: Data-driven subgroup allocations were generally consistent over follow-up and captured significant differences in risk factor trajectories, medication patterns and complication risks. Subgroups serve better as a complement rather than as a basis for compressing clustering indicators.

Surveillance of the liver in type 2 diabetes: important but unfeasible?

Fatty liver plays a pivotal role in the pathogenesis of the metabolic syndrome and type 2 diabetes. According to an updated classification, any individual with liver steatosis and one or more features of the metabolic syndrome, without excess alcohol consumption or other known causes of steatosis, has metabolic dysfunction-associated steatotic liver disease (MASLD). Up to 60-70% of all individuals with type 2 diabetes have MASLD. However, the prevalence of advanced liver fibrosis in type 2 diabetes remains uncertain, with reported estimates of 10-20% relying on imaging tests and likely overestimating the true prevalence. All stages of MASLD impact prognosis but fibrosis is the best predictor of all-cause and liver-related mortality risk. People with type 2 diabetes face a two- to threefold increase in the risk of liver-related death and hepatocellular carcinoma, with 1.3% progressing to severe liver disease over 7.7 years. Because reliable methods for detecting steatosis are lacking, MASLD mostly remains an incidental finding on imaging. Regardless, several medical societies advocate for universal screening of individuals with type 2 diabetes for advanced fibrosis. Proposed screening pathways involve annual calculation of the Fibrosis-4 (FIB-4) index, followed by a secondary test such as transient elastography (TE) for intermediate-to-high-risk individuals. However, owing to unsatisfactory biomarker specificity, these pathways are expected to channel approximately 40% of all individuals with type 2 diabetes to TE and 20% to tertiary care, with a false discovery rate of up to 80%, raising concerns about feasibility. There is thus an urgent need to develop more effective strategies for surveying the liver in type 2 diabetes. Nonetheless, weight loss through lifestyle changes, pharmacotherapy or bariatric surgery remains the cornerstone of management, proving highly effective not only for metabolic comorbidities but also for MASLD. Emerging evidence suggests that fibrosis biomarkers may serve as tools for risk-based targeting of weight-loss interventions and potentially for monitoring response to therapy.

Paediatric diabetes subtypes in a consanguineous population: a single-centre cohort study from Kurdistan, Iraq.

AIMS/HYPOTHESIS: Monogenic diabetes is estimated to account for 1-6% of paediatric diabetes cases in primarily non-consanguineous populations, while the incidence and genetic spectrum in consanguineous regions are insufficiently defined. In this single-centre study we aimed to evaluate diabetes subtypes, obtain the consanguinity rate and study the genetic background of individuals with syndromic and neonatal diabetes in a population with a high rate of consanguinity. METHODS: Data collection was carried out cross-sectionally in November 2021 at the paediatric diabetic clinic, Dr Jamal Ahmad Rashed Hospital, in Sulaimani, Kurdistan, Iraq. At the time of data collection, 754 individuals with diabetes (381 boys) aged up to 16 years were registered. Relevant participant data was obtained from patient files. Consanguinity status was known in 735 (97.5%) participants. Furthermore, 12 families of children with neonatal diabetes and seven families of children with syndromic diabetes consented to genetic testing by next-generation sequencing. Prioritised variants were evaluated using the American College of Medical Genetics and Genomics guidelines and confirmed by Sanger sequencing. RESULTS: A total of 269 of 735 participants (36.5%) with known consanguinity status were offspring of consanguineous families. An overwhelming majority of participants (714/754, 94.7%) had clinically defined type 1 diabetes (35% of them were born to consanguineous parents), whereas only eight (1.1%) had type 2 diabetes (38% consanguineous). Fourteen (1.9%) had neonatal diabetes (50% consanguineous), seven (0.9%) had syndromic diabetes (100% consanguineous) and 11 (1.5%) had clinically defined MODY (18% consanguineous). We found that consanguinity was significantly associated with syndromic diabetes (p=0.0023) but not with any other diabetes subtype. The genetic cause was elucidated in ten of 12 participants with neonatal diabetes who consented to genetic testing (homozygous variants in GLIS3 [sibling pair], PTF1A and ZNF808 and heterozygous variants in ABCC8 and INS) and four of seven participants with syndromic diabetes (homozygous variants in INSR, SLC29A3 and WFS1 [sibling pair]). In addition, a participant referred as syndromic diabetes was diagnosed with mucolipidosis gamma and probably has type 2 diabetes. CONCLUSIONS/INTERPRETATION: This unique single-centre study confirms that, even in a highly consanguineous population, clinically defined type 1 diabetes is the prevailing paediatric diabetes subtype. Furthermore, a pathogenic cause of monogenic diabetes was identified in 83% of tested participants with neonatal diabetes and 57% of participants with syndromic diabetes, with most variants being homozygous. Causative genes in our consanguineous participants were markedly different from genes reported from non-consanguineous populations and also from those reported in other consanguineous populations. To correctly diagnose syndromic diabetes in consanguineous populations, it may be necessary to re-evaluate diagnostic criteria and include additional phenotypic features such as short stature and hepatosplenomegaly.