Higher Risk Of Type 2 Diabetes Research Articles

Food additive preservatives and antioxidants and risk of type 2 diabetes - NutriNet-Santé cohort

Abstract Background Experimental studies suggested potential detrimental effects of some food additive preservatives and antioxidants (PA) on metabolic health, but epidemiological data is lacking. This study aimed to investigate for the first time the associations between exposures to a wide range of PA and type 2 diabetes (T2D) risk in a large population-based cohort. Methods Participants (n = 108,723, 79.2% women, mean age=42.5y, SD = 14.6) from the French NutriNet-Santé prospective cohort (2009-2023) completed repeated 24h-dietary records including specific brands of industrial products. PA exposure was assessed using composition databases and laboratory assays. We characterised associations between time-dependent exposures to PA and risk of T2D using multivariable Cox models adjusted for known confounders. Results 1131 T2D cases were identified during follow-up. Exposures to the following PA were associated with a higher risk of T2D: potassium sorbate E202 (HR per a 25 mg/d increment=1.12, 1.08-1.17, p < 0.001), sodium nitrite E250 (HR 0.25 mg/d = 1.06, 1.00-1.12, p = 0.04), calcium propionate E282 (HR 25 mg/d =1.07, 1.02-1.12, p = 0.008), lecithins E322 (HR 100 mg/d =1.02, 1.01-1.04, p = 0.008), citric acid E330 (HR 500 mg/d=1.08, 1.04-1.12, p < 0.001), and phosphoric acid E338 (HR 50 mg/d=1.11, 1.05-1.18, p < 0.001). Conclusions This large prospective cohort revealed positive associations between T2D risk and exposures to several PA widely used in industrial foods. Key messages • This large prospective cohort revealed positive associations between T2D risk and exposures to several PA widely used in industrial foods. • If these results are confirmed, regulations governing PA’s use by the food industry could be re-evaluated for better short- and long-term consumer protection.

Childhood maltreatment, adulthood obesity and incident type 2 diabetes: a retrospective cohort study using UK Biobank.

This study aims to explore the association of childhood maltreatment with obesity and type 2 diabetes (T2D) in adulthood, and whether obesity is a mediator of the latter. In a retrospective cohort study using UK Biobank data, participants recalled childhood maltreatment. Linear regression, logistic regression, and Cox proportional hazard models were used to investigate the associations with body mass index (BMI), obesity, and T2D, adjusted for sociodemographic factors. Decomposition analysis was used to examine the extent to which T2D excess risk was attributed to BMI. Of the 153,601 participants who completed the childhood maltreatment questions, one-third reported some form of maltreatment. Prevalence of adult obesity and incidence of T2D were higher with the number of reported childhood maltreatment types. People who reported ≥3 types of childhood maltreatment were at higher risk of obesity (OR 1.55, 95% CI 1.47-1.63) and incident T2D (HR 1.65, 95% CI 1.52-1.80). Excess T2D risk among those reporting maltreatment could be reduced by 39% if their BMI was comparable to participants who had not been maltreated, assuming causality. People who recalled maltreatment in childhood are at higher risk of T2D in adulthood, partly due to obesity.

12374 A Prospective Study Of Plasma Levels Of Asprosin And Incident Type 2 Diabetes Among Postmenopausal Women In The Women’s Health Initiative

Abstract Disclosure: B. Yang: None. J. Li: None. E.S. Silva: None. L.S. Phillips: None. J.E. Manson: None. A.P. Reiner: None. A.R. Chopra: None. S. Liu: None. Background: Asprosin, a 30-kDa hormone identified from white adipose tissue, has been shown to play key roles in regulating hepatic glucose release and appetite stimulation. Despite an increasing body of experimental studies demonstrating asprosin as a promising therapeutic target, little is known about its distribution in the general population particularly concerning its association with incident type 2 diabetes (T2D). Objectives: To evaluate whether higher plasma levels of asprosin are associated with incident T2D among postmenopausal women independently of known risk factors for T2D. Methods: We conducted a case-control study nested in the Women’s Health Initiative (WHI), including 5,198 participants free of diabetes, cardiovascular diseases, and cancer at baseline (2,602 incident T2D cases and 2,596 controls). Plasma levels of asprosin were measured using a sandwich enzyme-linked immunosorbent (ELISA) assay. We used conditional logistic regression models to estimate the association between asprosin and T2D risk with adjustment for matching variables (age, race, sampling batch), education, body mass index (BMI), physical activity, tobacco smoking, alcohol drinking, family history of diabetes, age at menopause, total energy intake, the Alternate Healthy Eating Index (AHEI), and multivitamin use. Results: Approximately 43% of participants were white and the mean age at baseline was 63 years. The median plasma levels of asprosin were 38 (IQR: 30, 50) pmoL/L in the controls and 39 (IQR: 31, 50) pmoL/L among those who developed T2D during follow-up. Compared with the participants in the lowest quintile of plasma levels of asprosin at baseline, those in the highest quintile had a 26% increased risk of T2D (adjusted odds ratio: OR: 1.26 [95% CIs, 1.01, 1.57], p for trend=0.03) in the fully adjusted model. The OR estimates exhibited a large variation across race and BMI, although there was a linear dose-response relation between levels of asprosin and T2D risk (p for nonlinear=0.44). Genetic analysis revealed that women with the heterozygous allele (CG) at single nucleotide polymorphisms (SNP) rs56407701 had higher levels of asprosin compared to women with the homozygous reference allele (CC). Further, Mendelian Randomization analysis revealed that genetically predicted asprosin levels were associated with higher T2D risk. Conclusion: Among postmenopausal women, higher plasma levels of asprosin were prospectively associated with elevated T2D risk independent of known T2D risk factors. Further work is needed to confirm the potential causal role of this peptide hormone in the clinical risk stratification and potential prevention of T2D. Presentation: 6/2/2024

Metabolic Stress Levels Influence the Ability of Myelin Transcription Factors to Regulate β-Cell Identity and Survival.

A hallmark of type 2 diabetes (T2D) is endocrine islet β-cell failure, which can occur via cell dysfunction, loss-of-identity, and/or death. How each is induced remains largely unknown. Here, we use mouse β-cells that are deficient for Myelin transcription factors (Myt TFs, including Myt1, 2, and 3) to address this question. We have reported that inactivating all three Myt genes in pancreatic progenitor cells (MytPancΔ) causes β-cell failure and late onset diabetes in mice. Their lower expression in human β-cells is correlated with β-cell dysfunction and SNPs in MYT2 and MYT3 are associated in higher risk of T2D. We now show that these Myt TF-deficient postnatal β-cells also de-differentiate by reactivating several progenitor markers. Intriguingly, mosaic Myt TF inactivation in only a portion of islet β-cells does not results in overt diabetes, but this creates a condition where Myt TF-deficient β-cells stay alive while activating several markers of Ppy-expressing islet cells. By transplanting MytPancΔ islets into the anterior eye chambers of immune-compromised mice, we directly show that glycemic and obesity-related conditions influence cell fate, with euglycemia inducing several Ppy+ cell markers while hyperglycemia and insulin resistance inducing additional cell death. These findings suggest that the observed β-cell defects in T2D depend on not only their inherent genetic/epigenetic defects, but also the metabolic load.

Loneliness, Discrimination, Stress, and Type 2 Diabetes Risk in Young Adults

IntroductionThe aim of this study was to determine the associations between type 2 diabetes (T2D) or prediabetes and loneliness and related social experiences in young adults, a population at increasingly high risk of T2D. MethodsThis was a cross-sectional analysis using data from adults ages 18-35 enrolled in the All of Us Research Program. Exposures included loneliness, social support, discrimination, neighborhood social cohesion, and stress, measured by standardized surveys. The main outcome was T2D or prediabetes by self-report or linked health record. Logistic regression determined odds of T2D/prediabetes for each survey measure, adjusting for age, sex, race or ethnicity, income, and family history. Latent class analysis (LCA) evaluated clustering of social experiences. Data was collected from 2018-2022 and analyzed May 2023-June 2024. ResultsThe cohort included 14,217 young adults (28.2 ± 4.4 years; 70.3% (n=9,792) women; 64.1% (n=9,111) White, 10.6% (n=1,506) Hispanic, 5.7% (n=806) Black, 9.1% (n=1,299) multiracial). Overall, 5.5% (n=777) had either prediabetes or T2D. The two highest loneliness quartiles were associated with increased odds of prediabetes/T2D (Q3: OR 1.42 [95% CI 1.15-1.76]; Q4: 1.75 [95% CI 1.43-2.16]). Greater stress and discrimination and lower social support and neighborhood social cohesion were also associated with increased odds of prediabetes/T2D. LCA revealed three distinct phenotypes, with elevated odds of prediabetes/T2D in the two with the most adverse social profiles (OR 2.32 [95% CI 1.89-2.84] and OR 1.28 [95% CI 1.04-1.58]). ConclusionsLoneliness and related experiences are strongly associated with T2D and prediabetes in young adults. Whether these factors could be leveraged to reduce T2D risk should be investigated.

Testosterone and the prevention of type 2 diabetes mellitus: therapeutic implications from recent trials.

Type 2 diabetes (T2D) is increasing to epidemic proportions and frequently associated with obesity and a low serum testosterone concentration in men. This review valuates recent randomized controlled trials (RCTs) investigating the effect of testosterone treatment on glycemic control and T2D prevention. The 2-year Testosterone for the Prevention of Type 2 diabetes Trial (T4DM) study showed that in men aged 50 years and over with visceral obesity and impaired glucose tolerance, testosterone treatment on the background of a lifestyle intervention reduced T2D risk by 40%. The Testosterone Effects on Atherosclerosis Progression in Aging Men and Testosterone Trials demonstrated modest improvements in insulin sensitivity and body composition. However, the Testosterone Replacement Therapy for Assessment of Long-Term Vascular Events and Efficacy Response in Hypogonadal Men trial found no significant glycemic benefits over 2 years. Recent data from the Diabetes Prevention Program Outcome Study support the cost efficacy and durability of metformin. In men at high risk of T2D, treatment with testosterone prevents the disease; however, there are caveats to its use and other approaches may be more applicable. Differences in trial designs, age groups, and outcome measures contribute to varying results. HbA1C is a suboptimal outcome measure. Future research should explore potential synergies between testosterone and GLP-1 receptor agonists in T2D management, while considering cost-effectiveness.

Ultra-processed food, genetic risk, and the risk of cardiometabolic diseases and cardiometabolic multimorbidity: A prospective study

Background and aimsThis study aims to evaluate the impact of ultra-processed food (UPF) on type 2 diabetes (T2D), cardiovascular disease (CVD), hypertension, and cardiometabolic multimorbidity (CMM), and to explore the role of genetic susceptibility in these associations. Methods and results90 631 participants from the UK Biobank were included (collected between 2006 and 2010). The outcomes assessed included T2D, CVD, hypertension and CMM. The Cox proportional hazards model was used to evaluate their associations and the potential modification by genetic risk, which was estimated using the polygenic risk score (PRS). Participants with high UPF consumption had a higher risk of T2D, CVD, and CMM, with the adjusted hazard ratio (HR) of 1.36 (95 % confidence interval [CI]: 1.15, 1.61), 1.13 (95%CI: 1.03, 1.23), and 1.14 (95%CI: 1.05, 1.24), respectively. Those with high UPF consumption and high PRS for T2D, CVD, and hypertension had the highest risk of T2D (HR: 4.01; 95%CI: 2.83, 5.69), CVD (HR: 2.18; 95%CI: 1.86, 2.56), and hypertension (HR: 1.79; 95%CI: 1.61, 1.99), respectively. In participants with one cardiometabolic disease (CMD), those with high UPF consumption and high PRST2D or PRSCVD had the highest risk of developing CMM. A significant additive interaction was observed between PRST2D and UPF consumption on the risk of T2D. ConclusionOur study underscored the importance of identifying individuals with high UPF consumption for targeted dietary interventions to mitigate the risk of CMDs and CMM, particularly among those with a high genetic risk of CMDs.

Prevalence of Type 2 Diabetes Risk in a Higher Education Community of North-Eastern Portugal: a Prospective Cross-sectional Observational Analysis

Objectives: Type 2 diabetes (T2D) is considered one of the most prevalent diseases worldwide. The aim of this study was to analyse the risk of developing T2D in a higher education community of Bragança, North-Eastern Portugal.Methods: The observational, cross-sectional and prospective sample comprised 3021 individuals, aged between 18 and 64 years old, of whom 1759 were women (mean age 24.16 ± 8.80 years) and 1263 were men (mean age 23.37 ± 8.70 years). The Finnish Diabetes Risk Score (FINDRISC) questionnaire was employed to estimate the risk of developing T2D over the next 10 years.Results: The results indicated that approximately 37 (1%) participants in the sample exhibited a high risk of developing T2D, 117 (4%) participants exhibited a moderate risk, 660 (22%) participants exhibited a slight risk, and 2206 (73%) participants exhibited a low risk. A higher T2D risk was observed in the staff group in comparison with the other groups (p < 0.001). Furthermore, body mass index (BMI) and waist circumference (WC) were the variables that most contributed to the increased risk of developing T2D (X2 = 1034.5; p < 0.001).Conclusions: In conclusion, the study reported a low T2D risk for the higher education community of Bragança in the Portuguese North-Eastern region. However, the risk of T2D was found to be higher in the staff group than in the student group. The FINDRISK questionnaire may be applied for the early diagnosis of T2D risk factors.

Integration of epidemiological and blood biomarker analysis links haem iron intake to increased type 2 diabetes risk.

Dietary haem iron intake is linked to an increased risk of type 2 diabetes (T2D), but the underlying plasma biomarkers are not well understood. We analysed data from 204,615 participants (79% females) in three large US cohorts over up to 36 years, examining the associations between iron intake and T2D risk. We also assessed plasma metabolic biomarkers and metabolomic profiles in subsets of 37,544 (82% females) and 9,024 (84% females) participants, respectively. Here we show that haem iron intake but not non-haem iron is associated with a higher T2D risk, with a multivariable-adjusted hazard ratio of 1.26 (95% confidence interval 1.20-1.33; P for trend <0.001) comparing the highest to the lowest quintiles. Haem iron accounts for significant proportions of the T2D risk linked to unprocessed red meat and specific dietary patterns. Increased haem iron intake correlates with unfavourable plasma profiles of insulinaemia, lipids, inflammation and T2D-linked metabolites. We also identify metabolites, including L-valine and uric acid, potentially mediating the haem iron-T2D relationship, highlighting their pivotal role in T2D pathogenesis.

Coronary microvascular dysfunction and left heart filling pressures in patients with type 2 diabetes.

Patients with type 2 diabetes (T2D) have a high prevalence of diastolic dysfunction and heart failure with preserved ejection fraction (HFpEF), which in turn leads to an increased risk of hospitalization and death. However, the factors of risk and their relative importance in leading to higher left ventricular filling pressures are still disputed. We sought to clarify the associations of a wide range of invasive and non-invasive risk factors with cardiac filling pressures in high-risk T2D patients. Patients with T2D at high risk of cardiovascular events were prospectively enrolled in this study. Participants were thoroughly phenotyped including right heart catheterization at rest and during exercise, echocardiography, urinary excretion of albumin (UACR), and quantification of their myocardial blood flow rate (MFR) using cardiac 82Rb-PET/CT. Of the 37 patients included in the study, 22 (59%) patients met invasive criteria for HFpEF. Only 2 out of 39 variables emerged as independent factors associated with left ventricular filling pressure as assessed by pulmonary capillary wedge pressure (PCWP) at rest; history of hypertension (coefficient: 2.6mmHg [0.3; 5.0], P=0.030) and MFR (P=0.026). We found a significant inverse association between MFR and PCWP with a coefficient of -2.3mmHg (-4.3; -0.3) in PCWP per integer change of MFR. The MFR ranged from 1.18 to 3.68 in our study, which corresponds to a difference in PCWP of approximately 6mmHg between patients with the lowest compared to the highest MFR. During exercise, only 2 variables emerged as borderline independent factors associated with PCWP: myocardial flow reserve (coefficient: -4.4 [-9.6; 0.8], P=0.091) and beta-blockers use (coefficient: 6.1 [-0.1; 12.4], P=0.053). In patients with type 2 diabetes without known HFpEF but risk factors for cardiovascular disease, myocardial blood flow rate was independently associated with PCWP at rest across the range from normal to abnormal left heart filling pressures. A clinically significant difference of 6mmHg in PWCP was attributable to differences in MFR in patients with the lowest compared with the highest MFR values. This suggests that strategies than attenuate microvascular dysfunction could slow progression of increased left ventricular left heart filling pressures in patients at increased risk.

Lifestyle modifies the associations of early-life smoking behaviors and genetic susceptibility with type 2 diabetes: A prospective cohort study involving 433,872 individuals from UK Biobank

BackgroundTo investigate whether and what lifestyle factors in later life modify the associations of early-life smoking behaviors and genetic susceptibility with type 2 diabetes (T2D). MethodsIn the UK Biobank, in utero tobacco exposure (n=354,493) and age of smoking initiation (n=353,557) were self-reported. A composite lifestyle score was calculated based on diet, physical activity, nicotine exposure, sleep duration, and BMI. Hazard ratio (HR) and absolute risk difference (ARD) were used to estimate the associations of early-life smoking behaviors and genetic risk with incident T2D, as well as the effect modification of the lifestyle score. ResultsDuring a median follow-up of 14.6 years, the HRs (95% CIs) of T2D for in utero tobacco exposure, and smoking initiation in adulthood, adolescence, and childhood, compared with no smoking behavior, were 1.19 (1.16-1.23), 1.34 (1.29-1.39), 1.58 (1.53-1.64), 2.22 (2.11-2.32), respectively (P for trend<0.001). Early-life smoking behaviors and high genetic risk (vs no smoking behavior and low genetic risk) were associated with a 302%-593% higher T2D risk (P for additive interaction<0.05). Compared to participants with early-life smoking behaviors, high genetic risk, and an unfavorable lifestyle, those who adhered to a favorable lifestyle had a lower T2D risk in all subgroups (HRs from 0.05 to 0.36 and ARD from -14.97% to -9.51%), with the highest ARD attributable to lifestyle in participants with early-life smoking behaviors and high genetic risk. ConclusionsThe T2D risk associated with early-life smoking behaviors and genetic risk was modified by a favorable lifestyle.

Denosumab, for osteoporosis, reduces the incidence of type 2 diabetes, risk of foot ulceration and all-cause mortality in adults, compared with bisphosphonates: An analysis of real-world, cohort data, with a systematic review and meta-analysis.

To evaluate the impact of denosumab on (i) the incidence of type 2 diabetes (T2D), and (ii) long-term health outcomes (microvascular [neuropathy, retinopathy, nephropathy] and macrovascular [cardiovascular disease, cerebrovascular accident] complications, and all-cause mortality) in patients with T2D, before (iii) combining results with prior studies using meta-analysis. A retrospective analysis of data in a large global federated database (TriNetX; Cambridge, MA) was conducted from 331 375 patients, without baseline T2D or cancer, prescribed either denosumab (treatment, n = 45 854) or bisphosphonates (control, n = 285 521), across 83 healthcare organizations. Propensity score matching (1:1) of confounders was undertaken that resulted in 45 851 in each cohort. Secondary analysis further evaluated the impact of denosumab on long-term health outcomes in patients with T2D. Additionally, we systematically searched prior literature that assessed the association between denosumab and T2D. Estimates were pooled using random-effects meta-analysis. Risk of bias and evidence quality were assessed using Cochrane-endorsed tools. Denosumab (vs. bisphosphonates) was associated with a lower risk of incident T2D over 5 years (hazard ratio 0.83 [95% confidence interval {CI} 0.78-0.88]). Secondary analysis showed significant risk reduction in all-cause mortality (0.79 [0.72-0.87]) and foot ulceration (0.67 [0.53-0.86]). Also, pooled results from four studies (three observational, one randomized controlled trial) following meta-analysis showed a reduced relative risk (RR [95% CI]) for incident T2D in patients prescribed denosumab (0.83 [0.79-0.87]) (I2 = 10.76%). This is the largest cohort study to show that denosumab treatment is associated with a reduced RR of incident T2D, as well as an associated reduced RR of all-cause mortality and microvascular complications, findings that may influence guideline development in the treatment of osteoporosis, particularly in patients who are at a high risk of T2D.

Effects of genetic risk on incident type 2 diabetes and glycemia: the T2D-GENE lifestyle intervention trial.

Lifestyle intervention prevents or delays type 2 diabetes (T2D) in subjects at a high risk of T2D. However, it is not known whether genetic variants modify the effect on incident T2D during lifestyle intervention. To investigate whether a low or high genetic risk has effects on incident T2D in a group-based lifestyle intervention study. The T2D-GENE trial involved 973 men from the Metabolic Syndrome in Men (METSIM) cohort, aged 50-75 years, body mass index ≥25 kg/m2, fasting plasma glucose 5.6-6.9 mmol/l, and HbA1c <48 mmol/mol and either a low or high genetic risk score for T2D. There were two intervention groups, a low (n=315) and high genetic risk for T2D (n=313). They were provided with a 3-year group-based intervention with access to a web portal focused on healthy diet and physical activity. There were also corresponding population-based control groups at low (n=196), and high genetic risk for T2D (n=149) who had two laboratory visits (0 and 3 years) and general health advice as a part of their METSIM cohort protocol. The primary outcome was incident T2D, and a secondary outcome glycemia. The intervention significantly lowered the risk of T2D among the participants with a high genetic risk for T2D (HR 0.30, 95% CI 0.16-0.56, p<0.001) whereas in the low genetic risk group the effect was not significant (HR 0.69, 95% CI 0.36-1.32, p=0.262). The intervention effect was not significantly different between the high and low genetic risk groups (p=0.135). The intervention significantly ameliorated the worsening of glycemia and decreased weight both in the low and high genetic risk groups. Our results showed that individuals with a high genetic risk for T2D benefited from a low-cost group-based intervention focusing on healthy diet and physical activity. Therefore, all individuals at risk of T2D should be encouraged to make lifestyle changes regardless of genetic risk.

Impact of periodontitis on type 2 diabetes: a bioinformatic analysis

BackgroundPeriodontitis is strongly associated with type 2 diabetes (T2D) that results in serious complications and mortality. However, the pathogenic role of periodontitis in the development of T2D and the underlain mechanism have not been fully elucidated.MethodsA Mendelian randomization (MR) was performed to estimate the causality between two diseases. Bioinformatics tools, including gene ontology and pathway enrichment analyses, were employed to analyze the common differentially expressed genes (DEGs) in periodontitis and T2D. MR and colocalization analyses were then utilized to investigate the causal associations between potential pathogenic gene expression and the risk of T2D. Single cell-type expression analysis was further performed to detect the cellular localization of these genes.ResultsGenetically predicted periodontitis was associated with a higher risk of T2D (OR, 1.469; 95% CI, 1.117–1.930; P = 0.006) and insulin resistance (OR 1.034; 95%CI 1.001–1.068; P = 0.041). 79 common DEGs associated with periodontitis and T2D were then identified and demonstrated enrichment mainly in CXC receptor chemokine receptor binding and interleutin-17 signaling pathway. The integration of GWAS with the expression quantitative trait locis of these genes from the peripheral blood genetically prioritized 6 candidate genes, including 2 risk genes (RAP2A, MCUR1) and 4 protective genes (WNK1, NFIX, FOS, PANX1) in periodontitis-related T2D. Enriched in natural killer cells, RAP2A (OR 4.909; 95% CI 1.849–13.039; P = 0.001) demonstrated high risk influence on T2D, and exhibited strong genetic evidence of colocalization (coloc.abf-PPH4 = 0.632).ConclusionsThis study used a multi-omics integration method to explore causality between periodontitis and T2D, and revealed molecular mechanisms using bioinformatics tools. Periodontitis was associated with a higher risk of T2D. MCUR1, RAP2A, FOS, PANX1, NFIX and WNK1 may play important roles in the pathogenesis of periodontitis-related T2D, shedding light on the development of potential drug targets.

Chronic insomnia, high trait anxiety and their comorbidity as risk factors for incident type 2 diabetes mellitus

The main objective of this study was to evaluate the association of the insomnia-anxiety comorbidity with incident type 2 diabetes (T2D) in a large prospective cohort. We selected adults without diabetes at baseline from the French NutriNet-Santé cohort who had completed the trait anxiety subscale of the Spielberger State-Trait Anxiety Inventory (STAI-T, 2013–2016) and a sleep questionnaire (2014); insomnia was defined according to established criteria. Using multivariable Cox models, we compared T2D risk across 4 groups: no insomnia or anxiety (reference), insomnia alone, anxiety alone (STAI-T ≥ 40), and comorbid anxiety and insomnia. Among 35,014 participants (mean baseline age: 52.4 ± 14.0 years; 76% women), 378 (1.1%) developed T2D over a mean follow-up of 5.9 ± 2.1 years. Overall, 28.5% of the sample had anxiety alone, 7.5%—insomnia alone, and 12.5%—both disorders. In the fully-adjusted model, a higher T2D risk was associated with anxiety-insomnia comorbidity (HR = 1.40; 95% CI 1.01, 1.94), but not with each disorder separately, compared to the group without insomnia or anxiety. The findings supported a positive association between anxiety-insomnia comorbidity and incident T2D among general-population adults. Future research using clinical diagnoses of mental disorders could confirm the findings and guide diabetes prevention programs.

AI-enhanced integration of genetic and medical imaging data for risk assessment of Type 2 diabetes.

Type 2 diabetes (T2D) presents a formidable global health challenge, highlighted by its escalating prevalence, underscoring the critical need for precision health strategies and early detection initiatives. Leveraging artificial intelligence, particularly eXtreme Gradient Boosting (XGBoost), we devise robust risk assessment models for T2D. Drawing upon comprehensive genetic and medical imaging datasets from 68,911 individuals in the Taiwan Biobank, our models integrate Polygenic Risk Scores (PRS), Multi-image Risk Scores (MRS), and demographic variables, such as age, sex, and T2D family history. Here, we show that our model achieves an Area Under the Receiver Operating Curve (AUC) of 0.94, effectively identifying high-risk T2D subgroups. A streamlined model featuring eight key variables also maintains a high AUC of 0.939. This high accuracy for T2D risk assessment promises to catalyze early detection and preventive strategies. Moreover, we introduce an accessible online risk assessment tool for T2D, facilitating broader applicability and dissemination of our findings.

Genetic studies of type 2 diabetes, and microvascular complications of diabetes.

Genome-wide association studies (GWAS) have significantly advanced the identification of genetic susceptibility variants associated with complex diseases. As of 2023, approximately 800 variants predisposing individuals to the risk of type 2 diabetes (T2D) were identified through GWAS, and the majority of studies were predominantly conducted in European populations. Despite the shared nature of the majority of genetic susceptibility loci across diverse ethnic populations, GWAS in non-European populations, including Japanese and East Asian populations, have revealed population-specific T2D loci. Currently, polygenic risk scores (PRSs), encompassing millions of associated variants, can identify individuals with a higher T2D risk than the general population. However, GWAS focusing on microvascular complications of diabetes have identified a limited number of disease-susceptibility loci. Ongoing efforts are crucial to enhance the applicability of PRS for all ethnic groups and unravel the genetic architecture of microvascular complications of diabetes.

Smoking timing, genetic susceptibility and the risk of incident type 2 diabetes: A cohort study from the UK Biobank.

To prospectively assess the association of smoking timing with the risk of type 2 diabetes (T2D) and examine whether smoking amount or genetic susceptibility might modify the relationship. A total of 294 815 participants without diabetes from the UK Biobank, including non-smokers and smokers with data on the time from waking to first cigarette, were included. Cox proportional hazards models were used to evaluate the association between smoking timing and the risk of incident T2D. During a median follow-up time of 12 years, a total of 9937 incident cases of T2D were documented. Compared with non-smokers, a shorter time from waking to first cigarette was significantly associated with a higher risk of incident T2D (P for trend < .001). In the fully adjusted model, the hazard ratios (HRs) (95% confidence interval) associated with smoking timing were 1.46 (1.17-1.81) for more than 2 hours, 1.51 (1.21-1.87) for 1-2 hours, 1.58 (1.34-1.85) for 30-60 minutes, 1.86 (1.57-2.21) for 5-15 minutes and 2.01 (1.60-2.54) for less than 5 minutes. We found that even among those who reported being light smokers, those with the shortest time from waking to first cigarette had a 105% higher risk of T2D with an HR of 2.05 (1.52-2.76), which was comparable with heavy smokers. The genetic risk score for T2D did not modify this association (P-interaction = .51). Our findings indicate that shorter time from waking to first cigarette is significantly associated with a higher risk of incident T2D.

Baseline phenotypes with preserved β-cell function and high insulin concentrations have the best improvements in glucose tolerance after weight loss: results from the prospective DEXLIFE and EGIR-RISC studies

BackgroundWeight loss and lifestyle intervention improve glucose tolerance delaying the onset of type 2 diabetes (T2D), but individual responses are highly variable. Determining the predictive factors linked to the beneficial effects of weight loss on glucose tolerance could provide tools for individualized prevention plans. Thus, the aim was to investigate the relationship between pre-intervention values of insulin sensitivity and secretion and the improvement in glucose metabolism after weight loss. MethodsIn the DEXLIFE cohort (373 individuals at high risk of T2D, assigned 3:1 to a 12-week lifestyle intervention or a control arm, Trial Registration: ISRCTN66987085), K-means clustering and logistic regression analysis were performed based on pre-intervention indices of insulin sensitivity, insulin secretion (AUC-I), and glucose-stimulated insulin response (ratio of incremental areas of insulin and glucose, iAUC I/G). The response to the intervention was evaluated in terms of reduction of OGTT-glucose concentration. Clusters' validation was done in the prospective EGIR-RISC cohort (n = 1538). ResultsFour replicable clusters with different glycemic and metabolomic profiles were identified. Individuals had similar weight loss, but improvement in glycemic profile and β-cell function was different among clusters, highly depending on pre-intervention insulin response to OGTT. Pre-intervention high insulin response was associated with the best improvement in AUC-G, while clusters with low AUC-I and iAUC I/G showed no beneficial effect of weight loss on glucose control, as also confirmed by the logistic regression model. ConclusionsIndividuals with preserved β-cell function and high insulin concentrations at baseline have the best improvement in glucose tolerance after weight loss.

Abstract P138: Smoking Timing, Genetic Susceptibility, and Risk of Incident Type 2 Diabetes: A Cohort Study in UK Biobank

Objective: Smoking is an establish risk factor for type 2 diabetes (T2D); however, little is known about how the timing patterns of smoking is related to T2D risk. We prospectively assessed the association of smoking timing with risk of T2D and examined whether smoking amount or genetic susceptibility might modify the relationship. Methods: This study analyzed 294815 participants from the UK Biobank who were free of diabetes at baseline and with complete data on the time from waking to the first cigarette. Cox proportional hazards models were used to evaluate the association between smoking timing and risk of incident T2D. Results: During a median follow-up time of 12 years, a total of 9937 incident cases of T2D were documented among the 294815 participants. Compared to non-smokers, shorter time from waking to the first cigarette was significantly associated with a higher risk of incident T2D ( P for trend &lt;0.0001). The adjusted hazard ratio (aHR) associated with smoking timing was 1.46 (95% confidence interval [CI] 1.17-1.81) for &gt;2 hours, 1.51 (1.21-1.87) for 1-2 hours, 1.58 (1.34-1.85) for 30-60 minutes, 1.86 (1.57-2.21) for 5-15 minutes, and 2.01 (1.60-2.54) for &lt;5 minutes, respectively. We found that even among light smokers, those with the shortest time from waking to the first cigarette had a 105% higher risk of T2D (HR 2.05, 95% CI 1.52-2.76), which was comparable to heavy smokers. The genetic risk score for T2D did not modify this association ( P -interaction =0.51). Conclusions: Our findings indicate that shorter time from waking to the first cigarette is significantly associated with a higher risk of incident T2D, independent of the amount of cigarettes smoked.