Elevated Risk Of Type 2 Diabetes Research Articles

Genetic Subtypes of Prediabetes, Healthy Lifestyle, and Risk of Type 2 Diabetes.

Prediabetes is a heterogenous metabolic state with various risk for development of type 2 diabetes (T2D). In this study, we used genetic data on 7,227 US Hispanic/Latinos without diabetes from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) and 400,149 non-Hispanic whites without diabetes from the UK Biobank (UKBB) to calculate five partitioned polygenetic risk scores (pPRSs) representing various pathways related to T2D. Consensus clustering was performed in participants with prediabetes in HCHS/SOL (n=3,677) and UKBB (n=16,284) separately, based on these pPRSs. Six clusters of individuals with prediabetes with distinctive patterns of pPRSs and corresponding metabolic traits were identified in the HCHS/SOL, five of which were confirmed in the UKBB. Although baseline glycemic traits were similar across clusters, individuals in Cluster 5 and Cluster 6 showed elevated risk of T2D during follow-up compared to Cluster 1 (RR=1.29 [95% CI 1.08-1.53] and1.34 [1.13-1.60], respectively). Inverse associations between a healthy lifestyle score and risk of T2D were observed across different clusters, with a suggestively stronger association observed in Cluster 5 compared to Cluster 1. Among individuals with healthy lifestyle, those in Cluster 5 had a similar risk of T2D compared to those in Cluster 1 (RR=1.03 [0.91-1.18]). This study identified genetic subtypes of prediabetes which differed in risk of progression to T2D and in benefits from healthy lifestyle.

A probabilistic computation framework to estimate the dawn phenomenon in type 2 diabetes using continuous glucose monitoring.

In type 2 diabetes (T2D), the dawn phenomenon is an overnight glucose rise recognized to contribute to overall glycemia and is a potential target for therapeutic intervention. Existing CGM-based approaches do not account for sensor error, which can mask the true extent of the dawn phenomenon. To address this challenge, we developed a probabilistic framework that incorporates sensor error to assign a probability to the occurrence of dawn phenomenon. In contrast, the current approaches label glucose fluctuations as dawn phenomena as a binary yes/no. We compared the proposed probabilistic model with a standard binary model on CGM data from 173 participants (71% female, 87% Hispanic/Latino, 54 ± 12years, with either a diagnosis of T2D for six months or with an elevated risk of T2D) stratified by HbA1c levels into normal but at risk for T2D, with pre-T2D, or with non-insulin-treated T2D. The probabilistic model revealed a higher dawn phenomenon frequency in T2D [49% (95% CI 37-63%)] compared to pre-T2D [36% (95% CI 31-48%), p = 0.01] and at-risk participants [34% (95% CI 27-39%), p < 0.0001]. While these trends were also found using the binary approach, the probabilistic model identified significantly greater dawn phenomenon frequency than the traditional binary model across all three HbA1c sub-groups (p < 0.0001), indicating its potential to detect the dawn phenomenon earlier across diabetes risk categories.

Association of plasma advanced glycation end-products and their soluble receptor with type 2 diabetes among Chinese adults.

Population-based evidence regarding circulating advanced glycation end-products (AGEs) and the risk of type 2 diabetes (T2D) is conflicting and insufficient. We aimed to examine the association of plasma AGEs and plasma soluble receptors for AGEs (sRAGE) with T2D. We conducted a hospital-based case-control study including 1072 pairs (53.9±9.7years, 56.0% male) of newly diagnosed T2D and age- and sex-matched controls. We further performed a nested case-control study within an ongoing prospective cohort consisting of 127 incident T2D cases and 381 well-matched controls (62.2±5.1years, 71.7% male). Plasma AGEs were detected using liquid chromatography-tandem mass spectrometry, and plasma sRAGE was measured by enzyme-linked immunosorbent assay. Conditional logistic regression was used to evaluate the association of plasma AGEs and sRAGE concentrations with T2D. Higher plasma AGEs and lower sRAGE concentrations were associated with higher odds of T2D. The multivariable-adjusted odds ratios of T2D comparing the highest with the lowest quartile levels were 3.28 (95% CI: 2.14, 5.02) for plasma AGEs and 0.25 (95% CI: 0.16, 0.39) for plasma sRAGE. Participants in the highest quartile of plasma AGEs and the lowest quartile of sRAGE concentrations had the greatest odds of T2D. The positive association of AGEs and inverse association of sRAGE with T2D risk was confirmed in the replication-nested case-control study. Increased circulating AGEs and decreased sRAGE concentrations were associated with elevated T2D risk. Our findings may have implications for the strategies of T2D prevention and management.

Clonal Hematopoiesis of Indeterminate Potential (CHIP) and Incident Type 2 Diabetes Risk.

Clonal hematopoiesis of indeterminate potential (CHIP) is an aging-related accumulation of somatic mutations in hematopoietic stem cells, leading to clonal expansion. CHIP presence has been implicated in atherosclerotic coronary heart disease (CHD) and all-cause mortality, but its association with incident type 2 diabetes (T2D) is unknown. We hypothesized that CHIP is associated with elevated risk of T2D. CHIP was derived from whole-genome sequencing of blood DNA in the National Heart, Lung, and Blood Institute Trans-Omics for Precision Medicine (TOPMed) prospective cohorts. We performed analysis for 17,637 participants from six cohorts, without prior T2D, cardiovascular disease, or cancer. We evaluated baseline CHIP versus no CHIP prevalence with incident T2D, including associations with DNMT3A, TET2, ASXL1, JAK2, and TP53 variants. We estimated multivariable-adjusted hazard ratios (HRs) and 95% CIs with adjustment for age, sex, BMI, smoking, alcohol, education, self-reported race/ethnicity, and combined cohorts' estimates via fixed-effects meta-analysis. Mean (SD) age was 63.4 (11.5) years, 76% were female, and CHIP prevalence was 6.0% (n = 1,055) at baseline. T2D was diagnosed in n = 2,467 over mean follow-up of 9.8 years. Participants with CHIP had 23% (CI 1.04, 1.45) higher risk of T2D than those with no CHIP. Specifically, higher risk was for TET2 (HR 1.48; CI 1.05, 2.08) and ASXL1 (HR 1.76; CI 1.03, 2.99) mutations; DNMT3A was nonsignificant (HR 1.15; CI 0.93, 1.43). Statistical power was limited for JAK2 and TP53 analyses. CHIP was associated with higher incidence of T2D. CHIP mutations located on genes implicated in CHD and mortality were also related to T2D, suggesting shared aging-related pathology.

Association of Sustained Low or High Income and Income Changes With Risk of Incident Type 2 Diabetes Among Individuals Aged 30 to 64 Years

Evidence of the association between income fluctuation and risk of type 2 diabetes (T2D) is scarce. To investigate whether sustained low or high income and income changes are associated with incidence of T2D. In this population-based cohort study, more than 7.8 million adults without T2D aged 30 to 64 years from a nationally representative sample from the Korean Health Insurance Service database were enrolled in 2012 and followed up to 2019 (median follow-up, 6.3 years [IQR, 6.1-6.6 years]). Twenty quantiles of monthly health insurance premiums determined income levels. Income quartiles were annually analyzed from 2008 to 2012. Beneficiaries of the Medical Aid Program were regarded as those with very low income. A decrease in income was indicated as a reduction of 25% or more in income compared with income in the previous year. The primary outcome was incident T2D based on the International Statistical Classification of Diseases and Related Health Problems, Tenth Revision codes E11 to E14, 1 or more claims of antidiabetic medication, or a fasting glucose level of 126 mg/dL or higher. Multivariable Cox proportional hazards models were used to assess the association of low- or high-income status and income changes with incidence of T2D. Of 7 821 227 participants (mean [SD] age, 46.4 [9.3] years; 54.9% men), 359 931 (4.6%) developed T2D at least 1 year after enrollment. Individuals who repeatedly experienced low and very low income for 5 years showed 22% (hazard ratio [HR], 1.22 [95% CI, 1.21-1.23]) and 57% (1.57 [95% CI, 1.53-1.62]) higher T2D risk compared with those who never experienced low and very low income, respectively. In contrast, individuals who were repeatedly in high-income quartiles showed lower T2D risk compared with those who never experienced high income (HR, 0.86 [95% CI, 0.85-0.86]). The number of income decreases was associated with elevated T2D risk (≥2 vs 0 income decreases: HR, 1.08 [95% CI, 1.06-1.11]; P < .001 for trend). When income quartile status was compared between 2008 and 2012, individuals who experienced an income increase had lowered T2D risk, while those who experienced an income decrease had elevated T2D risk in each income quartile group. This cohort study found that individuals who experienced sustained low-income status or an income decrease had elevated T2D risk, while those who had sustained high-income status or an income increase had lowered T2D risk.

Comprehensive Molecular Evaluation of HNF-1 Alpha, miR-27a, and miR-146 Gene Variants and Their Link with Predisposition and Progression in Type 2 Diabetes Patients.

Type 2 diabetes (T2D) is a metabolic condition induced by insulin resistance and pancreatic beta cell dysfunction. MicroRNAs (miRNAs) have biological significance because they regulate processes such as the molecular signaling pathways involved in the pathophysiology of diabetes mellitus. The hepatocyte nuclear factor-1 alpha (HNF-1 alpha) is a transcription factor found in hepatocytes and the pancreas. Mutations in the HNF-1 alpha gene were reportedly associated with maturity-onset diabetes of the young (MODY). The objective of the present study was to examine the associations between MiR-27a, MiR-146, and HNF-1 alpha single-nucleotide variations (SNVs) with T2D risk in the Saudi population. We evaluated the association of SNVs of miR-27a rs895819 A>G, 146a-rs2910164 C>G, and HNF-1 alpha rs1169288 G>T (I27L) with the risk of T2D in Saudi patients with the Amplification Refractory Mutation System PCR (ARMS-PCR). For the miR-27a SNVs, we used 115 cases (82 males, 33 females) and 117 matched healthy controls (HCs); for the Mir-146 SNVs, we used 103 cases (70 males, 33 females) and 108 matched HCs; and for the HNF-1 alpha, we employed 110 patients (80 males, 30 females) and 110 HCs. The blood biochemistry of the participants was essayed using commercial kits, and the methods of statistical analysis used were the Chi-square test, the Fisher exact test, and a multivariate analysis based on logistic regression, like the odds ratio (OD) and risk ratio (RR), with 95% confidence intervals (CIs). The MiR-27a rs895819 AG genotype was linked to increased T2D susceptibility, with OR = 2.01 and p-value = 0.011, and the miR-146 rs2910164 CG genotype and C allele were linked to an elevated risk of T2D, with OR = 2.75, p-value < 0.0016, OR = 1.77, and p-value = 0.004. The results also showed that the GT genotype and T allele of the HNF-1 alpha (rs1169288) G>T is linked to T2D, with OR = 2.18, p-value = 0.0061, and 1.77, p-value = 0.0059. The SNVs in miR-27a, miR-146, and HNF-1 alpha can be potential loci for T2D risk. The limitations of this study include the relatively small sample size and the fact that it was a cross-sectional study. To our knowledge, this is the first study to highlight the association between miR-27a, miR-146, and HNF-1 alpha SNVs and the risk of T2D in the Saudi population. Future large-scale case-control studies, as well as studies on the functions of the proteins and protein interaction studies for HNF-1 alpha, are required to verify our findings. Furthermore, these findings can be used for the identification and stratification of at-risk populations via genetic testing for T2D-prevention strategies.

Association of time spent in outdoor light and genetic susceptibility with the risk of type 2 diabetes

To explore the joint association of time spent in outdoor light and genetic susceptibility with the risk of type 2 diabetes (T2D). A total of 395,809 individuals of European ancestry with diabetes-free at baseline in the UK Biobank were included. Time spent in outdoor light on a typical day in summer or winter was obtained from the questionnaire. T2D genetic risk was quantified via the polygenic risk score (PRS) and divided into three levels based on tertiles (lower, intermediate, and higher). T2D cases were ascertained according to the hospital records of diagnoses. After the median follow-up of 12.55 years, the association of outdoor light time and T2D risk demonstrated a nonlinear (J–shaped) trend. Compared to individuals with an average of 1.5–2.5 h/day of outdoor light, individuals who spent <1.5 h/day or >2.5 h/day in outdoor light both had an elevated risk of T2D, and the risk of T2D related to <1.5 h/day outdoor light time was much higher (hazard ratio [HR] = 1.10, 95 % confidence interval [CI]: 1.06 to 1.15). After combining with PRS, in comparison with the lower PRS – average 1.5–2.5 h/day outdoor light group (reference), the higher PRS – <1.5 h/day outdoor light group had the highest T2D risk (HR = 2.74, 95 % CI: 2.55 to 2.94), the higher PRS – >2.5 h/day outdoor light group also had a higher risk of T2D (HR = 2.58, 95 % CI: 2.43 to 2.74). The interaction between average outdoor light time and genetic susceptibility for T2D was statistically significant (Paverage for interaction <0.001). We found that optimal outdoor light time may modify the genetic risk for T2D. This suggests the T2D risk related to genetic factors could be prevented by spending optimal outdoor light time.

Dietary patterns associated with the risk of type 2 diabetes in women with and without a history of gestational diabetes mellitus: A pilot study

Introduction: There is limited evidence on dietary patterns and the risk of type 2 diabetes (T2D) in women with a history of gestational diabetes mellitus (GDM) compared to their non-GDM counterparts, especially in the Asian population. The pilot study investigated dietary patterns in women with a history of GDM (HGDM) and without a history of GDM (non-HGDM), and the association with T2D risk. Methods: This comparative cross-sectional study involved 64 women (32 HGDM, 32 non-HGDM). Food intake was assessed using a validated food frequency questionnaire. Principal component analysis derived the dietary patterns. T2D risk score was determined using the Finnish Diabetes Risk Score tool. Results: HGDM group had significantly higher proportion of first-degree family history of diabetes; higher risk of T2D and better diabetes knowledge; lower gestational weight gain and postpartum weight retention; and consumed more fast food than nonHGDM. ‘Rice-noodle-pasta-meat’ dietary pattern was significantly associated with increased T2D risk after adjusting for age (β=0.272, p=0.032). ‘Bread-cereals-fast food-meat’ dietary pattern was positively and significantly associated with T2D risk after adjusting for confounders, including age, education level, family history of diabetes, diabetes knowledge score, gestational weight gain, and postpartum weight retention (β=0.251, p=0.012). Conclusion: Dietary patterns high in bread, cereals and cereal products, fast food and meat, as well as rice, noodle, pasta and meat were associated with an elevated T2D risk. A more extensive study is warranted to establish the association between dietary patterns and risk of T2D, focusing on women with a history of GDM.

Association between Organophosphate Ester Exposure and Insulin Resistance with Glycometabolic Disorders among Older Chinese Adults 60-69 Years of Age: Evidence from the China BAPE Study.

Organophosphate esters (OPEs) are common endocrine-disrupting chemicals, and OPE exposure may be associated with type 2 diabetes (T2D). However, greater knowledge regarding the biomolecular intermediators underlying the impact of OPEs on T2D in humans are needed to understand biological etiology. We explored the associations between OPE exposure and glycometabolic markers among older Chinese adults 60-69 years of age to elucidate the underlying mechanisms using a multi-omics approach. This was a longitudinal panel study comprising 76 healthy participants 60-69 years of age who lived in Jinan city of northern China. The study was conducted once every month for 5 months, from September 2018 to January 2019. We measured a total of 17 OPEs in the blood, 11 OPE metabolites in urine, and 4 glycometabolic markers (fasting plasma glucose, glycated serum protein, fasting insulin, and homeostatic model assessment for insulin resistance). The blood transcriptome and serum/urine metabolome were also evaluated. The associations between individual OPEs and glycometabolic markers were explored. An adverse outcome pathway (AOP) was established to determine the biomolecules mediating the associations. Exposure to five OPEs and OPE metabolites (trimethylolpropane phosphate, triphenyl phosphate, tri-iso-butyl phosphate, dibutyl phosphate, and diphenyl phosphate) was associated with increased levels of glycometabolic markers. The mixture effect analysis further indicated the adverse effect of OPE mixtures. Multi-omics analyses revealed that the endogenous changes in the transcriptional and metabolic levels were associated with OPE exposure. The putative AOPs model suggested that triggers of molecular initiation events (e.g., insulin receptor and glucose transporter type 4) with subsequent key events, including disruptions in signal transduction pathways (e.g., phosphatidylinositol 3-kinase/protein kinase B and insulin secretion signaling) and biological functions (glucose uptake and insulin secretion), may constitute the diabetogenic effects of OPEs. OPEs are associated with the elevated risk of T2D among older Chinese adults 60-69 years of age. Implementing OPE exposure reduction strategies may help reduce the T2D burden among these individuals, if the relationship is causal. https://doi.org/10.1289/EHP11896.

Health coaching and genetic risk testing in primary care: Randomized controlled trial.

Accessible interventions are needed to prevent coronary heart disease (CHD) and Type 2 diabetes (T2D). This prospective, randomized, controlled trial evaluated remote health coaching (HC), genetic risk testing (GRT), or both added to standardized risk assessment (SRA) in at-risk military primary care patients. Using a 2 × 2 factorial longitudinal design, 200 Air Force at-risk participants provided primary outcomes at baseline, 3-, 6- (HC endpoint), and 12-months. Secondary measures were taken less often. Per protocol analyses used linear models and logistic regression; intent-to-treat (ITT) analyses used mixed models. Compared with those not receiving HC, the HC group was 3.6 times more likely to report moderate to intense physical activity at 6-months (p = .0009), and 2.9 times more likely to report such at 12-months (p = .0065). ITT longitudinal model did not reach significance (p = .0885). The HC group reported lower emotional representations of illness at 6-weeks and lower depression at 6 months. There were no other significant findings. HC and GRT interacted; higher T2D risk participants receiving HC were 4.7 times more likely to report higher stage of change for exercise at 6-months, and lost 2.2 kg more by 12-months. Lower T2D risk participants receiving HC perceived greater control over CHD risk at 6-weeks, and averaged lower 6-month depression. Remote HC after SRA increased physical activity, which was sustained 6-months later. Incorporating GRT into SRA warrants further exploration regarding the potential to leverage HC for weight loss in elevated T2D risk participants, and for depression in lower T2D risk participants. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Oral health professionals screening for undiagnosed type-2 diabetes and prediabetes: the iDENTify study

BackgroundAs part of an evaluation of an oral healthcare practice-based model that identifies patients with prediabetes or type-2 diabetes, this study reports on the proportion of patients identified with clinically confirmed type-2 diabetes (T2D)/prediabetes and barriers of implementation of the model.MethodologyUrban and rural oral healthcare practices were invited to participate. Participating practices invited eligible patients to participate in the screening program using the Australian Type-2 Diabetes Risk Assessment Tool (AUSDRISK). Participants were categorised as low, intermediate, or high-risk for prediabetes/T2D. Patients in the intermediate or high-risk category were referred to their General Medical Practitioner (GP) for further investigation.ResultsFifty-one oral healthcare practices and 76 Oral Health Professionals (OHP) participated (60 Dentists, 8 Dental Hygienists, 8 Oral Health Therapists). 797 patients were screened; 102 were low-risk; 331 intermediate-risk; and 364 high-risk for T2D. Of the 695 participants in the intermediate or high-risk groups, 386 (55.5%) were referred to their GP for T2D assessment. Of them, 96 (25.0%) results were returned to OHPs. Of the returned results, six were (6.3%) diagnosed with pre-T2D.ConclusionPatients found to have undiagnosed T2D/prediabetes (6.3%) were within the expected range reported in the literature. Findings indicate that identifying individuals at an elevated risk of having or developing T2D is effective, feasible and could be incorporated into oral healthcare settings. However, this integration may require additional OHPs training and education to ensure that patients at elevated risk of T2D are referred for further assessment.

Psychometric evaluation of three-factor eating questionnaire -R18 in aging Finnish men with increased risk for type 2 diabetes.

Deeper comprehension of eating-related behaviour (how and why people eat) can reveal new aspects to support health and prevent type 2 diabetes (T2D). However, such research is largely missing in aging men. The aim was to investigate suitability of the Three-Factor Eating Questionnaire-R18 (TFEQ-R18) in Finnish aging men which is widely used to examine factors: cognitive restraint (CR), uncontrolled eating (UE), and emotional eating (EE). Study population consisted of 420 men aged 50-75, who completed the TFEQ-R18 at the baseline of the T2D-GENE lifestyle intervention study. Inclusion criteria were impaired fasting glucose (IFG) and body mass index ≥25 kg/m2. Confirmatory factor analysis was used to study psychometrics (reliability, validity, and model fit) and factor structure of TFEQ-R18. The items loaded to the three factors (CR, UE, EE) as in previous studies, except two items at CR factor and one at UE factor, which were therefore omitted. UE was also discovered split into two sub factors (named as 'craving' and 'loss-of-control'), UE being a higher-order (h) factor. The resultant revised version was named as Three-Factor Eating Questionnaire Revised to 15-items with higher-order factor (TFEQ-R15h). The original 18-item version of the TFEQ was not optimal in the population consisting of Finnish aging men with elevated T2D risk. A modified 15-item version of the TFEQ could be used to describe EB in this population instead.

Prediction of type 2 diabetes mellitus onset using logistic regression-based scorecards.

Type 2 diabetes (T2D) accounts for ~90% of all cases of diabetes, resulting in an estimated 6.7 million deaths in 2021, according to the International Diabetes Federation. Early detection of patients with high risk of developing T2D can reduce the incidence of the disease through a change in lifestyle, diet, or medication. Since populations of lower socio-demographic status are more susceptible to T2D and might have limited resources or access to sophisticated computational resources, there is a need for accurate yet accessible prediction models. In this study, we analyzed data from 44,709 nondiabetic UK Biobank participants aged 40-69, predicting the risk of T2D onset within a selected time frame (mean of 7.3 years with an SD of 2.3 years). We started with 798 features that we identified as potential predictors for T2D onset. We first analyzed the data using gradient boosting decision trees, survival analysis, and logistic regression methods. We devised one nonlaboratory model accessible to the general population and one more precise yet simple model that utilizes laboratory tests. We simplified both models to an accessible scorecard form, tested the models on normoglycemic and prediabetes subcohorts, and compared the results to the results of the general cohort. We established the nonlaboratory model using the following covariates: sex, age, weight, height, waist size, hip circumference, waist-to-hip ratio, and body mass index. For the laboratory model, we used age and sex together with four common blood tests: high-density lipoprotein (HDL), gamma-glutamyl transferase, glycated hemoglobin, and triglycerides. As an external validation dataset, we used the electronic medical record database of Clalit Health Services. The nonlaboratory scorecard model achieved an area under the receiver operating curve (auROC) of 0.81 (95% confidence interval [CI] 0.77-0.84) and an odds ratio (OR) between the upper and fifth prevalence deciles of 17.2 (95% CI 5-66). Using this model, we classified three risk groups, a group with 1% (0.8-1%), 5% (3-6%), and the third group with a 9% (7-12%) risk of developing T2D. We further analyzed the contribution of the laboratory-based model and devised a blood test model based on age, sex, and the four common blood tests noted above. In this scorecard model, we included age, sex, glycated hemoglobin (HbA1c%), gamma glutamyl-transferase, triglycerides, and HDL cholesterol. Using this model, we achieved an auROC of 0.87 (95% CI 0.85-0.90) and a deciles' OR of ×48 (95% CI 12-109). Using this model, we classified the cohort into four risk groups with the following risks: 0.5% (0.4-7%); 3% (2-4%); 10% (8-12%); and a high-risk group of 23% (10-37%) of developing T2D. When applying the blood tests model using the external validation cohort (Clalit), we achieved an auROC of 0.75 (95% CI 0.74-0.75). We analyzed several additional comprehensive models, which included genotyping data and other environmental factors. We found that these models did not provide cost-efficient benefits over the four blood test model. The commonly used German Diabetes Risk Score (GDRS) and Finnish Diabetes Risk Score (FINDRISC) models, trained using our data, achieved an auROC of 0.73 (0.69-0.76) and 0.66 (0.62-0.70), respectively, inferior to the results achieved by the four blood test model and by the anthropometry models. The four blood test and anthropometric models outperformed the commonly used nonlaboratory models, the FINDRISC and the GDRS. We suggest that our models be used as tools for decision-makers to assess populations at elevated T2D risk and thus improve medical strategies. These models might also provide a personal catalyst for changing lifestyle, diet, or medication modifications to lower the risk of T2D onset. The funders had no role in study design, data collection, interpretation, or the decision to submit the work for publication.

Arterial Stiffness, Genetic Risk, and Type 2 Diabetes: A Prospective Cohort Study.

We aimed to investigate prospective associations of pulse wave arterial stiffness index (ASI) and pulse pressure (PP) with type 2 diabetes (T2D) and assess the modifying effect of genetics. We included 152,611 participants free of diabetes and cardiovascular disease in the UK Biobank. All participants had ASI and blood pressure measurements collected at baseline visit. In total, 37 single nucleotide polymorphisms were used to calculate the genetic risk score (GRS) of T2D. During a median follow-up of 9.5 years, 3,000 participants developed T2D. Per-SD increase in ASI was associated with a 3% higher T2D risk (95% CI 2-4%). The hazard ratio (HR) (95% CI) of T2D was 1.58 (1.39-1.80) in the highest quintile group compared with the lowest quintile group of ASI. However, the association between PP and T2D was nonlinear. Compared with the lowest quintile group, the risk of T2D in higher quintile groups of PP was 0.91 (0.79-1.04), 0.98 (0.86-1.11), 1.15 (1.01-1.30), and 1.24 (1.10-1.41), respectively. Furthermore, we observed an interaction between ASI and genetic susceptibility to T2D, because the elevated HR of T2D associated with high ASI was more evident among participants with higher GRS of T2D (P interaction = 0.008), whereas the interaction between PP and GRS was nonsignificant (P interaction = 0.55). ASI was associated with an elevated risk of T2D in a dose-response fashion, whereas PP and T2D showed a nonlinear J-shaped association. Additionally, the association between ASI and T2D was partially strengthened by higher genetic susceptibility to T2D.

Associations between serum total bilirubin, obesity and type 2 diabetes

BackgroundThis study aims to examine the cross-sectional association between serum total bilirubin (STB) and type 2 diabetes (T2D) risk in the general population, and whether obesity could moderate this association.MethodsWe used data from the 1999–2018 National Health and Nutrition Examination Surveys (NHANES), including a total of 38,641 US adult participants who were 18 years or older. The STB was classified as the low, moderate, and high groups according to tertiles.ResultsWe found that participants with lower STB had a significantly higher risk of T2D than those with moderate (OR = 0.81; 95% CI 0.74, 0.89; P < 0.001) and high (OR = 0.65; 95% CI 0.59, 0.73; P < 0.001) STB. Also, a significant interaction between body mass index (BMI) and STB on T2D was observed (P < 0.001). Stratified analysis showed that low STB was associated with a 20% and 27% decrease of T2D risk for moderate and high STB groups in obese patients, however, these effect estimates were smaller in the population with lower BMI (< 30 kg/m2). Similar associations of STB with glycohemoglobin and insulin resistance were observed.ConclusionThis study suggests that STB is associated with an elevated risk of T2D. More importantly, we reported for the first time that BMI may moderate the association between bilirubin and T2D.

Development and testing of a digital health acceptability model to explain the intention to use a digital diabetes prevention programme.

Digitally-delivered diabetes prevention programmes (DPPs) may improve population health by reversing the escalating trend of type 2 diabetes (T2D) incidence. Understanding the factors which determine digital health acceptability is critical to developing effective interventions. This study aimed to develop and test a digital health acceptability model of the factors influencing the intention of adults living in Ireland to use a digital DPP. A 61-item cross-sectional survey was issued online or in hard copy to a sample of adults. Participants viewed a brochure for a smartphone-based digital DPP. The FINDRISC assessed their risk of developing T2D, and Likert scale items assessed the personal health, social influence, eHealth literacy, and intervention factors of the model. Structural equationmodelling was used to assess the relationships between these factors. Three-hundred-and-sixteen eligible participants (Mage = 36) completed the survey, 42% of which had a slightly elevated T2D risk or higher. Twelve direct factor relationships were statistically significant. Subjective norm had a moderate-to-large impact on T2D risk perceptions. Health status, perceived susceptibility to T2D, eHealth readiness, communicative eHealth literacy and image had significant impacts on use intentions through mediators of perceived ease of use and perceived usefulness. The model explained 65% of the variance in digital DPP use intentions. Personal health beliefs, social influence, and eHealth literacy collectively influence a digital DPP's acceptability. These findings may inform the development of future digital DPPs and other digital health interventions. Future research should test the model with adults that have a higher T2D risk status.

Pharmacy-based screening to detect persons at elevated risk of type 2 diabetes: a cost-utility analysis

BackgroundEarly identification of people at elevated risk of type 2 diabetes (T2D) is an important step in preventing or delaying its onset. Pharmacies can serve as a significant channel to reach these people. This study aimed to assess the potential health economic impact of screening and recruitment services in pharmacies in referring people to preventive interventions.MethodsA decision analytic model was constructed to perform a cost-utility analysis of the expected national health economic consequences (in terms of costs and quality-adjusted life years, QALYs) of a hypothetical pharmacy-based service where people screened and recruited through pharmacies would participate in a digital lifestyle program. Cost-effectiveness was considered in terms of net monetary benefit (NMB). In addition, social return on investment (SROI) was calculated as the ratio of the intervention and recruitment costs and the net present value of expected savings. Payback time was the time taken to reach the break-even point in savings. In the base scenario, a 20-year time horizon was applied. Probabilistic and deterministic sensitivity analyses were applied to study robustness of the results.ResultsIn the base scenario, the expected savings from the pharmacy-based screening and recruitment among the reached target cohort were 255.3 m€ (95% CI − 185.2 m€ to 717.2 m€) in pharmacy visiting population meaning 1412€ (95% CI − 1024€ to 3967€) expected savings per person. Additionally, 7032 QALYs (95% CI − 1344 to 16,143) were gained on the population level. The intervention had an NMB of 3358€ (95% CI − 1397€ to 8431€) using a cost-effectiveness threshold of 50,000 €/QALY. The initial costs were 122.2 m€ with an SROI of 2.09€ (95% CI − 1.52€ to 5.88€). The expected payback time was 10 and 8 years for women and men, respectively. Results were most sensitive for changes in effectiveness of the intervention and selected discount rate.ConclusionsT2D screening and recruitment to prevention programs conducted via pharmacies was a dominant option providing both cost savings and QALY gains. The highest savings can be potentially reached by targeting recruitment at men at elevated risk of T2D.

Enriched Alternative Splicing in Islets of Diabetes-Susceptible Mice.

Dysfunctional islets of Langerhans are a hallmark of type 2 diabetes (T2D). We hypothesize that differences in islet gene expression alternative splicing which can contribute to altered protein function also participate in islet dysfunction. RNA sequencing (RNAseq) data from islets of obese diabetes-resistant and diabetes-susceptible mice were analyzed for alternative splicing and its putative genetic and epigenetic modulators. We focused on the expression levels of chromatin modifiers and SNPs in regulatory sequences. We identified alternative splicing events in islets of diabetes-susceptible mice amongst others in genes linked to insulin secretion, endocytosis or ubiquitin-mediated proteolysis pathways. The expression pattern of 54 histones and chromatin modifiers, which may modulate splicing, were markedly downregulated in islets of diabetic animals. Furthermore, diabetes-susceptible mice carry SNPs in RNA-binding protein motifs and in splice sites potentially responsible for alternative splicing events. They also exhibit a larger exon skipping rate, e.g., in the diabetes gene Abcc8, which might affect protein function. Expression of the neuronal splicing factor Srrm4 which mediates inclusion of microexons in mRNA transcripts was markedly lower in islets of diabetes-prone compared to diabetes-resistant mice, correlating with a preferential skipping of SRRM4 target exons. The repression of Srrm4 expression is presumably mediated via a higher expression of miR-326-3p and miR-3547-3p in islets of diabetic mice. Thus, our study suggests that an altered splicing pattern in islets of diabetes-susceptible mice may contribute to an elevated T2D risk.

Substantial PCSK9 inactivation in β-cells does not modify glucose homeostasis or insulin secretion in mice

Proprotein convertase subtilisin/kexin type 9 (PCSK9) plays an important role in cholesterol homeostasis by promoting the degradation of the LDL receptor (LDLR). PCSK9 loss-of-function mutations are associated with increased fasting plasma glucose levels and slightly elevated risk of type 2-diabetes. Considering the known detrimental effects of cholesterol accumulation in β-cell, and the widespread use of PCSK9 inhibitors to treat hypercholesterolemia, it is important to gain insight into the role of pancreatic PCSK9 in glucose homeostasis and β-cell function. We generated the first β-cell-specific KO of PCSK9 (βKO). PCSK9 mRNA and protein expression were reduced by 48% and 78% in βKO islets, respectively, indicating that β-cells constitute a major site of PCSK9 expression. In islets, loss of β-cell PCSK9 resulted in unchanged LDLR protein levels, but reduced LDLR mRNA, indicating that cholesterol internalization is enhanced and that β-cell PCSK9 promotes LDLR degradation. In contrast, whole body PCSK9 KO mice exhibited 2-fold higher LDLR protein levels in islets and a stable expression of cholesterogenic genes. Whole body KO and βKO mice presented normal glucose tolerance, insulin release in response to glucose load and insulin sensitivity. Ex vivo glucose-stimulated insulin secretion in presence or absence of fatty acids was similar in WT and KO islets. Like KO mice, individuals carrying loss-of-function PCSK9 variants may be protected from cholesterol-induced toxicity due to reduced circulating cholesterol levels. Using both whole body KO or βKO models, our data demonstrate that PCSK9 deletion in mouse does not have any toxic effect on β-cell function and glucose homeostasis.

Egg consumption, overall diet quality, and risk of type 2 diabetes and coronary heart disease: A pooling project of US prospective cohorts

Data on the relation of egg consumption with risk of type 2 diabetes (T2D) and coronary heart disease (CHD) are limited and inconsistent. Few studies have controlled for overall dietary patterns in egg-T2D or egg-CHD analyses, and it is unclear whether any observed elevated risks of T2D and CHD with frequent egg consumption is real or due to confounding by dietary habits. We tested the hypothesis that frequent egg consumption is associated with a higher risk of T2D and CHD risk after adjustment for overall dietary patterns among adults. We used prospective cohort design to complete time-to-event analyses. We pooled de novo, harmonized, individual-level analyses from nine US cohorts (n=103,811). Cox regression was used to estimate hazard ratios separately in each cohort adjusting for age, ethnicity, body mass index (BMI), exercise, smoking, alcohol intake, and dietary patterns. We pooled cohort-specific results using an inverse-variance weighted method to estimate summary relative risks. Median age ranged from 25 to 72 years. Median egg consumption was 1 egg per week in most of the cohorts. While egg consumption up to one per week was not associated with T2D risk, consumption of ≥2 eggs per week was associated with elevated risk [27% elevated risk of T2D comparing 7+ eggs/week with none (95% CI: 16%-37%)]. There was little evidence for heterogeneity across cohorts and we observed similar conclusions when stratified by BMI. Overall, egg consumption was not associated with the risk of CHD. However, in a sensitivity analysis, there was a 30% higher risk of CHD (95% CI: 3%-56%) restricted to older adults consuming 5-6 eggs/week. Our data showed an elevated risk of T2D with egg consumption of ≥2 eggs per week but not with <2 eggs/week. While there was no overall association of egg consumption with CHD risk, the elevated CHD observed with consumption of 5-6 eggs/week in older cohorts merits further investigation.