Socioeconomic factors associated with poor medication adherence in patients with type 2 diabetes.

PURPOSE: This study aims to determine initiation and persistence for patients with type 2 diabetes receiving their first prescription of an antidiabetic agent and the associations with socioeconomic factors. METHODS: A cohort study including 8515 patients with type 2 diabetes who were prescribed their first antidiabetic medication between 2012 and 2019 in Uppsala, Sweden, was followed during 2 years. Medical records were linked to national registers on dispensed drugs and socioeconomic data. Adherence was assessed based on patients' medication claims within 30 days of prescription (initiation) and continued claims after 24 months (persistence). Multivariable logistic regression was used to determine the associations with the socioeconomic factors age, sex, living status, country of birth, education, occupation, and income. RESULTS: Within 30 days, 92.4% of the patients claimed their first prescription, and 64.0% were still being dispensed the initially prescribed medication after 24 months. Unemployed patients had lower initiation rates, and women had lower persistence rates. Factors associated with both low initiation and persistence were low income, young or old age, birth outside Europe, and being prescribed other diabetes drugs than metformin monotherapy. CONCLUSION: Socioeconomic factors have different impact on the initiation of a new medication and the persistence to treatment in type 2 diabetes. It is important to acknowledge these differences to develop appropriate interventions to improve medication nonadherence.

Sociodemographic characteristics and COVID-19 testing rates: spatiotemporal patterns and impact of test accessibility in Sweden.

BACKGROUND: Diagnostic testing is essential for disease surveillance and test-trace-isolate efforts. We aimed to investigate if residential area sociodemographic characteristics and test accessibility were associated with Coronavirus Disease 2019 (COVID-19) testing rates. METHODS: We included 426 224 patient-initiated COVID-19 polymerase chain reaction tests from Uppsala County in Sweden from 24 June 2020 to 9 February 2022. Using Poisson regression analyses, we investigated if postal code area Care Need Index (CNI; median 1.0, IQR 0.8-1.4), a composite measure of sociodemographic factors used in Sweden to allocate primary healthcare resources, was associated with COVID-19 daily testing rates after adjustments for community transmission. We assessed if the distance to testing station influenced testing, and performed a difference-in-difference-analysis of a new testing station targeting a disadvantaged neighbourhood. RESULTS: We observed that CNI, i.e. primary healthcare need, was negatively associated with COVID-19 testing rates in inhabitants 5-69 years. More pronounced differences were noted across younger age groups and in Uppsala City, with test rate ratios in children (5-14 years) ranging from 0.56 (95% CI 0.47-0.67) to 0.87 (95% CI 0.80-0.93) across three pandemic waves. Longer distance to the nearest testing station was linked to lower testing rates, e.g. every additional 10 km was associated with a 10-18% decrease in inhabitants 15-29 years in Uppsala County. The opening of the targeted testing station was associated with increased testing, including twice as high testing rates in individuals aged 70-105, supporting an intervention effect. CONCLUSIONS: Ensuring accessible testing across all residential areas constitutes a promising tool to decrease inequalities in testing.

DNA methylation partially mediates antidiabetic effects of metformin on HbA1c levels in individuals with type 2 diabetes.

AIMS: Despite metformin being used as first-line pharmacological therapy for type 2 diabetes, its underlying mechanisms remain unclear. We aimed to determine whether metformin altered DNA methylation in newly-diagnosed individuals with type 2 diabetes. METHODS AND RESULTS: We found that metformin therapy is associated with altered methylation of 26 sites in blood from Scandinavian discovery and replication cohorts (FDR < 0.05), using MethylationEPIC arrays. The majority (88%) of these 26 sites were hypermethylated in patients taking metformin for âˆ¼ 3 months compared to controls, who had diabetes but had not taken any diabetes medication. Two of these blood-based methylation markers mirrored the epigenetic pattern in muscle and adipose tissue (FDR < 0.05). Four type 2 diabetes-associated SNPs were annotated to genes with differential methylation between metformin cases and controls, e.g., GRB10, RPTOR, SLC22A18AS and TH2LCRR. Methylation correlated with expression in human islets for two of these genes. Three metformin-associated methylation sites (PKNOX2, WDTC1 and MICB) partially mediate effects of metformin on follow-up HbA1c levels. When combining methylation of these three sites into a score, which was used in a causal mediation analysis, methylation was suggested to mediate up to 32% of metformin's effects on HbA1c. CONCLUSION: Metformin-associated alterations in DNA methylation partially mediates metformin's antidiabetic effects on HbA1c in newly-diagnosed individuals with type 2 diabetes.

Spatio-temporal predictions of COVID-19 test positivity in Uppsala County, Sweden: a comparative approach.

Previous spatio-temporal COVID-19 prediction models have focused on the prediction of subsequent number of cases, and have shown varying accuracy and lack of high geographical resolution. We aimed to predict trends in COVID-19 test positivity, an important marker for planning local testing capacity and accessibility. We included a full year of information (June 29, 2020-July 4, 2021) with both direct and indirect indicators of transmission, e.g. mobility data, number of calls to the national healthcare advice line and vaccination coverage from Uppsala County, Sweden, as potential predictors. We developed four models for a 1-week-window, based on gradient boosting (GB), random forest (RF), autoregressive integrated moving average (ARIMA) and integrated nested laplace approximations (INLA). Three of the models (GB, RF and INLA) outperformed the naïve baseline model after data from a full pandemic wave became available and demonstrated moderate accuracy. An ensemble model of these three models slightly improved the average root mean square error to 0.039 compared to 0.040 for GB, RF and INLA, 0.055 for ARIMA and 0.046 for the naïve model. Our findings indicate that the collection of a wide variety of data can contribute to spatio-temporal predictions of COVID-19 test positivity.

Novel Subgroups of Type 2 Diabetes Display Different Epigenetic Patterns That Associate With Future Diabetic Complications.

OBJECTIVE: Type 2 diabetes (T2D) was recently reclassified into severe insulin-deficient diabetes (SIDD), severe insulin-resistant diabetes (SIRD), mild obesity-related diabetes (MOD), and mild age-related diabetes (MARD), which have different risk of complications. We explored whether DNA methylation differs between these subgroups and whether subgroup-unique methylation risk scores (MRSs) predict diabetic complications. RESEARCH DESIGN AND METHODS: Genome-wide DNA methylation was analyzed in blood from subjects with newly diagnosed T2D in discovery and replication cohorts. Subgroup-unique MRSs were built, including top subgroup-unique DNA methylation sites. Regression models examined whether MRSs associated with subgroups and future complications. RESULTS: We found epigenetic differences between the T2D subgroups. Subgroup-unique MRSs were significantly different in those patients allocated to each respective subgroup compared with the combined group of all other subgroups. These associations were validated in an independent replication cohort, showing that subgroup-unique MRSs associate with individual subgroups (odds ratios 1.6-6.1 per 1-SD increase, P < 0.01). Subgroup-unique MRSs were also associated with future complications. Higher MOD-MRS was associated with lower risk of cardiovascular (hazard ratio [HR] 0.65, P = 0.001) and renal (HR 0.50, P < 0.001) disease, whereas higher SIRD-MRS and MARD-MRS were associated with an increased risk of these complications (HR 1.4-1.9 per 1-SD increase, P < 0.01). Of 95 methylation sites included in subgroup-unique MRSs, 39 were annotated to genes previously linked to diabetes-related traits, including TXNIP and ELOVL2. Methylation in the blood of 18 subgroup-unique sites mirrors epigenetic patterns in tissues relevant for T2D, muscle and adipose tissue. CONCLUSIONS: We identified differential epigenetic patterns between T2D subgroups that associated with future diabetic complications. These data support a reclassification of diabetes and the need for precision medicine in T2D subgroups.

App-based COVID-19 syndromic surveillance and prediction of hospital admissions in COVID Symptom Study Sweden.

The app-based COVID Symptom Study was launched in Sweden in April 2020 to contribute to real-time COVID-19 surveillance. We enrolled 143,531 study participants (≥18 years) who contributed 10.6 million daily symptom reports between April 29, 2020 and February 10, 2021. Here, we include data from 19,161 self-reported PCR tests to create a symptom-based model to estimate the individual probability of symptomatic COVID-19, with an AUC of 0.78 (95% CI 0.74-0.83) in an external dataset. These individual probabilities are employed to estimate daily regional COVID-19 prevalence, which are in turn used together with current hospital data to predict next week COVID-19 hospital admissions. We show that this hospital prediction model demonstrates a lower median absolute percentage error (MdAPE: 25.9%) across the five most populated regions in Sweden during the first pandemic wave than a model based on case notifications (MdAPE: 30.3%). During the second wave, the error rates are similar. When we apply the same model to an English dataset, not including local COVID-19 test data, we observe MdAPEs of 22.3% and 19.0% during the first and second pandemic waves, respectively, highlighting the transferability of the prediction model.

Individual goal-based plan based on nursing theory for adults with type 2 diabetes and self-care deficits: a study protocol of a randomised controlled trial.

INTRODUCTION: The prevalence and costs of type 2 diabetes are increasing worldwide. A cornerstone in the treatment and care of diabetes is supporting each patient in self-management. In Sweden, most patients with type 2 diabetes are cared for in the primary care setting, which is heavily burdened. Because of implementation difficulties regarding evidenced-based diabetes self-management education and support in this setting, there is a need for an instrument that is easy to use and implement. We developed an individual care plan based on the self-care deficit nursing theory of Dorothea Orem as an instrument to facilitate more individualised self-care support for patients with type 2 diabetes. In this study, we aim to determine whether a written, theory-based, individual goal-based plan for patients with type 2 diabetes and self-management deficits can affect their glycaemic control and health-related quality of life, as well as their experiences of living with diabetes and of support from diabetes care. METHODS AND ANALYSIS: The study design is a randomised controlled trial using a quantitative approach. A total of 110 patients will be included. Additionally, a qualitative interview study will be conducted 12 months after the intervention. The primary outcome will be glycosylated haemoglobin levels. Secondary outcomes will be health-related quality of life measured using the RAND-36, and the patient's experience of living with diabetes and of the support from diabetes care measured using the Diabetes Questionnaire. Quantitative data will be analysed using the paired t-test, unpaired t-test, and Mann-Whitney U test with IBM SPSS V.26.0 software. Qualitative content analysis will be used for qualitative data. ETHICS AND DISSEMINATION: This study has been approved by the Ethical Review Authority in Uppsala, Sweden (Etikprövningsmyndigheten, Uppsala, Sverige) (Dnr: 2020-03421). The results will be disseminated in peer-reviewed publications. TRIAL REGISTRATION NUMBER: ISRCTN10030245.

In-Flight Transmission of a SARS-CoV-2 Lineage B.1.617.2 Harbouring the Rare S:E484Q Immune Escape Mutation.

We describe a flight-associated infection scenario of seven individuals with a B.1.617.2 (Delta) lineage, harbouring an S:E484Q point mutation. In Sweden, at least 10% of all positive SARS-CoV-2 samples were sequenced in each county; the B.1.717.2 + S:E484Q combination was not detected in Sweden before and was imported within the scenario described in this report. The high transmission rate of the delta lineage combined with the S:E484Q mutation, associated with immune escape in other lineages, makes this specific genetic combination a possible threat to the global fight against the COVID-19 pandemic. Even within the Omicron wave, the B.1.617.2 + S:E484Q variant appeared in community samples in Sweden, as it seems that this combination has an evolutionary gain compared to other B.1.617.2 lineages. The here described genomic combination was not detectable with the common fasta file-based Pango-lineage analysis, hence increasing the probability of the true global prevalence to be higher.

Statin therapy is associated with epigenetic modifications in individuals with Type 2 diabetes.

Aim: Statins lower cholesterol and reduce the risk of cardiovascular disease. However, the exact mechanisms of statins remain unknown. We investigated whether statin therapy associates with epigenetics in Type 2 diabetes (T2D) patients. Materials & methods: DNA methylation was analyzed in blood from newly diagnosed T2D patients in All New Diabetics in Scania (ANDIS) and a replication cohort All New Diabetics in Uppsala County (ANDiU). Results: Seventy-nine sites were differentially methylated between cases on statins and controls (false discovery rate <5%) in ANDIS. These include previously statin-associated methylation sites annotated to DHCR24 (cg17901584), ABCG1 (cg27243685) and SC4MOL (cg05119988). Differential methylation of two sites related to cholesterol biosynthesis and immune response, cg17901584 (DHCR24) and cg23011663 (ARIH2), were replicated in ANDiU. Conclusion: Statin therapy associates with epigenetic modifications in T2D patients.

Epigenetic markers associated with metformin response and intolerance in drug-naïve patients with type 2 diabetes.

Metformin is the first-line pharmacotherapy for managing type 2 diabetes (T2D). However, many patients with T2D do not respond to or tolerate metformin well. Currently, there are no phenotypes that successfully predict glycemic response to, or tolerance of, metformin. We explored whether blood-based epigenetic markers could discriminate metformin response and tolerance by analyzing genome-wide DNA methylation in drug-naïve patients with T2D at the time of their diagnosis. DNA methylation of 11 and 4 sites differed between glycemic responders/nonresponders and metformin-tolerant/intolerant patients, respectively, in discovery and replication cohorts. Greater methylation at these sites associated with a higher risk of not responding to or not tolerating metformin with odds ratios between 1.43 and 3.09 per 1-SD methylation increase. Methylation risk scores (MRSs) of the 11 identified sites differed between glycemic responders and nonresponders with areas under the curve (AUCs) of 0.80 to 0.98. MRSs of the 4 sites associated with future metformin intolerance generated AUCs of 0.85 to 0.93. Some of these blood-based methylation markers mirrored the epigenetic pattern in adipose tissue, a key tissue in diabetes pathogenesis, and genes to which these markers were annotated to had biological functions in hepatocytes that altered metformin-related phenotypes. Overall, we could discriminate between glycemic responders/nonresponders and participants tolerant/intolerant to metformin at diagnosis by measuring blood-based epigenetic markers in drug-naïve patients with T2D. This epigenetics-based tool may be further developed to help patients with T2D receive optimal therapy.

Physical Activity, Genetic Susceptibility, and the Risk of Latent Autoimmune Diabetes in Adults and Type 2 Diabetes.

PURPOSE: Physical activity (PA) has been linked to a reduced risk of type 2 diabetes by reducing weight and improving insulin sensitivity. We investigated whether PA is associated with a lower incidence of latent autoimmune diabetes in adults (LADA) and whether the association is modified by genotypes of human leukocyte antigen (HLA), transcription factor 7-like 2 (TCF7L2)-rs7903146, or the fat mass and obesity-associated gene, FTO-rs9939609. METHODS: We combined data from a Swedish case-control study and a Norwegian prospective study including 621 incident cases of LADA and 3596 cases of type 2 diabetes. We estimated adjusted pooled relative risks (RRs) and 95% CI of diabetes in relation to high (≥ 30 minutes of moderate activity 3 times/week) self-reported leisure time PA, compared to sedentariness. RESULTS: High PA was associated with a reduced risk of LADA (RR 0.61; CI, 0.43-0.86), which was attenuated after adjustment for body mass index (BMI) (RR 0.90; CI, 0.63-1.29). The reduced risk applied only to noncarriers of HLA-DQB1 and -DRB1 (RR 0.49; CI, 0.33-0.72), TCF7L2 (RR 0.62; CI, 0.45-0.87), and FTO (RR 0.51; CI, 0.32-0.79) risk genotypes. Adjustment for BMI attenuated but did not eliminate these associations. For type 2 diabetes, there was an inverse association with PA (RR 0.49; CI, 0.42-0.56), irrespective of genotype. MAIN CONCLUSIONS: Our findings indicate that high PA is associated with a reduced risk of LADA in individuals without genetic susceptibility.

Heterogeneity of Metabolic Defects in Type 2 Diabetes and Its Relation to Reactive Oxygen Species and Alterations in Beta-Cell Mass.

Type 2 diabetes (T2D) is a complex and heterogeneous disease which affects millions of people worldwide. The classification of diabetes is at an interesting turning point and there have been several recent reports on sub-classification of T2D based on phenotypical and metabolic characteristics. An important, and perhaps so far underestimated, factor in the pathophysiology of T2D is the role of oxidative stress and reactive oxygen species (ROS). There are multiple pathways for excessive ROS formation in T2D and in addition, beta-cells have an inherent deficit in the capacity to cope with oxidative stress. ROS formation could be causal, but also contribute to a large number of the metabolic defects in T2D, including beta-cell dysfunction and loss. Currently, our knowledge on beta-cell mass is limited to autopsy studies and based on comparisons with healthy controls. The combined evidence suggests that beta-cell mass is unaltered at onset of T2D but that it declines progressively. In order to better understand the pathophysiology of T2D, to identify and evaluate novel treatments, there is a need for in vivo techniques able to quantify beta-cell mass. Positron emission tomography holds great potential for this purpose and can in addition map metabolic defects, including ROS activity, in specific tissue compartments. In this review, we highlight the different phenotypical features of T2D and how metabolic defects impact oxidative stress and ROS formation. In addition, we review the literature on alterations of beta-cell mass in T2D and discuss potential techniques to assess beta-cell mass and metabolic defects in vivo.

Novel subgroups of adult-onset diabetes and their association with outcomes: a data-driven cluster analysis of six variables.

BACKGROUND: Diabetes is presently classified into two main forms, type 1 and type 2 diabetes, but type 2 diabetes in particular is highly heterogeneous. A refined classification could provide a powerful tool to individualise treatment regimens and identify individuals with increased risk of complications at diagnosis. METHODS: We did data-driven cluster analysis (k-means and hierarchical clustering) in patients with newly diagnosed diabetes (n=8980) from the Swedish All New Diabetics in Scania cohort. Clusters were based on six variables (glutamate decarboxylase antibodies, age at diagnosis, BMI, HbA1c, and homoeostatic model assessment 2 estimates of ß-cell function and insulin resistance), and were related to prospective data from patient records on development of complications and prescription of medication. Replication was done in three independent cohorts: the Scania Diabetes Registry (n=1466), All New Diabetics in Uppsala (n=844), and Diabetes Registry Vaasa (n=3485). Cox regression and logistic regression were used to compare time to medication, time to reaching the treatment goal, and risk of diabetic complications and genetic associations. FINDINGS: We identified five replicable clusters of patients with diabetes, which had significantly different patient characteristics and risk of diabetic complications. In particular, individuals in cluster 3 (most resistant to insulin) had significantly higher risk of diabetic kidney disease than individuals in clusters 4 and 5, but had been prescribed similar diabetes treatment. Cluster 2 (insulin deficient) had the highest risk of retinopathy. In support of the clustering, genetic associations in the clusters differed from those seen in traditional type 2 diabetes. INTERPRETATION: We stratified patients into five subgroups with differing disease progression and risk of diabetic complications. This new substratification might eventually help to tailor and target early treatment to patients who would benefit most, thereby representing a first step towards precision medicine in diabetes. FUNDING: Swedish Research Council, European Research Council, Vinnova, Academy of Finland, Novo Nordisk Foundation, Scania University Hospital, Sigrid Juselius Foundation, Innovative Medicines Initiative 2 Joint Undertaking, Vasa Hospital district, Jakobstadsnejden Heart Foundation, Folkhälsan Research Foundation, Ollqvist Foundation, and Swedish Foundation for Strategic Research.

Overweight, obesity and the risk of LADA: results from a Swedish case-control study and the Norwegian HUNT Study.

AIMS/HYPOTHESIS: Excessive weight is a risk factor for type 2 diabetes, but its role in the promotion of autoimmune diabetes is not clear. We investigated the risk of latent autoimmune diabetes in adults (LADA) in relation to overweight/obesity in two large population-based studies. METHODS: Analyses were based on incident cases of LADA (n = 425) and type 2 diabetes (n = 1420), and 1704 randomly selected control participants from a Swedish case-control study and prospective data from the Norwegian HUNT Study including 147 people with LADA and 1,012,957 person-years of follow-up (1984-2008). We present adjusted ORs and HRs with 95% CI. RESULTS: In the Swedish data, obesity was associated with an increased risk of LADA (OR 2.93, 95% CI 2.17, 3.97), which was even stronger for type 2 diabetes (OR 18.88, 95% CI 14.29, 24.94). The association was stronger in LADA with low GAD antibody (GADA;

Education, immigration and income as risk factors for hemoglobin A1c >70 mmol/mol when diagnosed with type 2 diabetes or latent autoimmune diabetes in adult: a population-based cohort study.

OBJECTIVES: The aim of this research is to study education, income and immigration as risk factors for high hemoglobin A1c (HbA1c >70 mmol/mol (8.6%)) when diagnosed with type 2 diabetes (T2D) or latent autoimmune diabetes in the adult (LADA). RESEARCH DESIGN AND METHODS: Patients were included from the All New Diabetics in Scania study (2008-2013). Level of education, disposable income and immigration year were retrieved from the longitudinal integrated database for labour market research (LISA) register compiled by Statistics Sweden. Logistic regression models were used to estimate ORs for HbA1c >70 mmol/mol (8.6%) at diagnosis. RESULTS: A total of 3794 patients with incident T2D (n=3 525) or LADA (n=269) were included. Patients with T2D with a low (≤9 years) or medium (10-12 years) levels of education were more likely to have high HbA1c at diagnosis compared with patients with T2D with a high (>12 years) level of education (OR 1.34, 95% CI 1.08 to1.66, OR 1.26, 95% CI 1.03 to 1.54). Low-income patients with T2D (<60% of median) were more likely to have high HbA1c at diagnosis compared with high-income patients withT2D (>150% of median) (OR 1.35, 95% CI 1.02 to 1.79). CONCLUSIONS: Patients with lower levels of education or low income and are more likely to have HbA1c is >70 mmol/mol (8.6%) when diagnosed with T2D. An understanding of how socioeconomic position influences the clinical presentation at diagnosis may facilitate screening programs designed to target populations at risk for delayed diagnosis.

[11C]5-hydroxy-tryptophan PET for Assessment of Islet Mass During Progression of Type 2 Diabetes.

[11C]5-hydroxy-tryptophan ([11C]5-HTP) positron emission tomography of the pancreas has been shown to be a surrogate imaging biomarker of pancreatic islet mass. The change in islet mass in different stages of type 2 diabetes (T2D) as measured by noninvasive imaging is currently unknown. Here, we describe a cross-sectional study where subjects at different stages of T2D development with expected stratification of pancreatic islet mass were examined in relation to individuals without diabetes. The primary outcome was the [11C]5-HTP uptake and retention in pancreas, as a surrogate marker for the endogenous islet mass. We found that metabolic testing indicated a progressive loss of ß-cell function, but this was not mirrored by a decrease in [11C]5-HTP tracer accumulation in the pancreas. This provides evidence of retained islet mass despite decreased ß-cell function. The results herein indicate that ß-cell dedifferentiation, and not necessarily endocrine cell loss, constitutes a major cause of ß-cell failure in T2D.

Sweetened beverage intake and risk of latent autoimmune diabetes in adults (LADA) and type 2 diabetes.

OBJECTIVE: Sweetened beverage intake is associated with increased risk of type 2 diabetes, but its association with autoimmune diabetes is unclear. We aimed to investigate sweetened beverage intake and risk of latent autoimmune diabetes in adults (LADA); autoimmune diabetes with features of type 2 diabetes. DESIGN/METHODS: Data from a Swedish population-based study was used, including incident cases of LADA (n = 357) and type 2 diabetes (n = 1136) and randomly selected controls (n = 1371). Diabetes classification was based on onset age (≥35), glutamic acid decarboxylase autoantibodies (GADA) and C-peptide. Sweetened beverage intake information was derived from a validated food frequency questionnaire. ORs adjusted for age, sex, family history of diabetes, education, lifestyle, diet, energy intake and BMI were estimated using logistic regression. RESULTS: Daily intake of >2 servings of sweetened beverages (consumed by 6% of participants) was associated with increased risk of LADA (OR: 1.99, 95% CI: 1.11-3.56), and for each 200 mL daily serving, OR was 1.15 (95% CI: 1.02-1.29). Findings were similar for sugar-sweetened (OR: 1.18, 95% CI: 1.00-1.39) and artificially sweetened beverages (OR: 1.12, 95% CI: 0.95-1.32). Similarly, each daily serving increment in total sweetened beverage conferred 20% higher type 2 diabetes risk (95% CI: 1.07-1.34). In type 2 diabetes patients, high consumers displayed higher HOMA-IR levels (4.5 vs 3.5, P = 0.0002), but lower HOMA-B levels (55 vs 70, P = 0.0378) than non-consumers. Similar tendencies were seen in LADA. CONCLUSIONS: High intake of sweetened beverages was associated with increased risk of LADA. The observed relationship resembled that with type 2 diabetes, suggesting common pathways possibly involving insulin resistance.

Prevalence and risk factors for diabetic retinopathy at diagnosis (DRAD) in patients recently diagnosed with type 2 diabetes (T2D) or latent autoimmune diabetes in the adult (LADA).

PURPOSE: To study prevalence of diabetic retinopathy (DR) at diagnosis (DRAD) and to estimate contributing risk by sociodemographic, cardiovascular and metabolic characteristics present in patients recently diagnosed with type 2 diabetes (T2D) or latent autoimmune diabetes in the adult (LADA). METHODS: Patients (n=2174) recently diagnosed T2D (93%) or LADA (7%) were included upon arrival for their baseline DR screening. Fundus photographs of 4902 eyes were graded by a senior ophthalmologist according to the International Diabetic Retinopathy Disease Severity Scale. Official registers held by Statistics Sweden provided sociodemographic variables. The National Patient Register and Swedish Prescribed Drug Register were used to assess cardiovascular risk. Beta cell function (HOMA2%b) and insulin sensitivity (HOMA2%s) were estimated from fasting (f) C-Peptide using the homeostasis model assessment (HOMA) 2 calculator. Odds ratios (OR) for DRAD were estimated using generalized estimating equation models. RESULTS: The prevalence of DRAD was 12% (7% mild and 5% moderate) and of diabetic macular edema it was 11% (all within vascular arch). The prevalence did not significantly differ between T2D and LADA. Due to sample size, the regression analysis of LADA patients did not yield any significant estimates. In T2D low educational level (≤9years) increased risk for DRAD by 44% (OR 1.44; 95% CI 1.07-1.93) and <50% beta-cell function adjusted for HbA1c and insulin sensitivity at diagnosis increased the risk by 77% (OR 1.77; 95% CI 1.28-2.44). For every unit increase in BMI, risk for DRAD decreased by 3% (OR 0.97; 95% CI 0.95-0.99). CONCLUSIONS: DRAD prevalence in patients recently diagnosed with T2D or is 12%. Low educational level and low beta cell function at diagnosis are risk factors for DRAD. Estimation of beta cell function from (f)C-Peptide and (f)P-Glucose may be a valuable tool in identifying patients at risk for DRAD.

Smoking and the Risk of LADA: Results From a Swedish Population-Based Case-Control Study.

OBJECTIVE: Smoking is an established risk factor for type 2 diabetes. In contrast, it has been proposed that smoking may reduce the risk of latent autoimmune diabetes in adults (LADA), but studies are scarce. We aimed to study the impact of smoking on LADA and type 2 diabetes risks. RESEARCH DESIGN AND METHODS: We used data from a Swedish case-control study including incident case patients with LADA (GAD antibody [GADA] positive, n = 377) and type 2 diabetes (GADA negative, n = 1,188) and control subjects randomly selected from the population (n = 1,472). We calculated odds ratios (ORs) with 95% CIs by logistic regression, adjusted for age, sex, BMI, family history of diabetes, and alcohol consumption. RESULTS: There was no indication of reduced risk of LADA in smokers; instead, heavy smoking was associated with an increased risk of LADA (OR 1.37, 95% CI 1.02-1.84). Heavy smokers had higher levels of HOMA of insulin resistance (9.89 vs. 4.38, P = 0.0479) and HOMA of ß-cell function (55.7 vs. 42.5, P = 0.0204), but lower levels of GADA (75 vs. 250, P = 0.0445), compared with never smokers. Smokers also displayed an increased risk of type 2 diabetes (OR in ever smokers 1.53, 95% CI 1.25-1.88). CONCLUSIONS: In this large population of LADA patients, we did not observe a protective effect of smoking on autoimmunity and the risk of LADA. A protective effect could possibly be masked by a smoking-induced aggravation of insulin resistance, akin to the diabetogenic effect seen in individuals with type 2 diabetes.