Higher Risk Of Type 2 Diabetes Mellitus Research Articles

KCNQ1 rs2237895 gene polymorphism increases susceptibility to type 2 diabetes mellitus in Asian populations.

The association of single nucleotide polymorphism of KCNQ1 gene rs2237895 with type 2 diabetes mellitus (T2DM) is currently controversial. It is unknown whether this association can be gene realized across different populations. To determine the association of KCNQ1 rs2237895 with T2DM and provide reliable evidence for genetic susceptibility to T2DM. We searched PubMed, Embase, Web of Science, Cochrane Library, Medline, Baidu Academic, China National Knowledge Infrastructure, China Biomedical Liter-ature Database, and Wanfang to investigate the association between KCNQ1 gene rs2237895 and the risk of T2DM up to January 12, 2022. Review Manager 5.4 was used to analyze the association of the KCNQ1 gene rs2237895 polymorphism with T2DM and to evaluate the publication bias of the selected literature. Twelve case-control studies (including 11273 cases and 11654 controls) met our inclusion criteria. In the full population, allelic model [odds ratio (OR): 1.19; 95% confidence interval (95%CI): 1.09-1.29; P < 0.0001], recessive model (OR: 1.20; 95%CI: 1.11-1.29; P < 0.0001), dominant model (OR: 1.27. 95%CI: 1.14-1.42; P < 0.0001), and codominant model (OR: 1.36; 95%CI: 1.15-1.60; P = 0.0003) (OR: 1.22; 95%CI: 1.10-1.36; P = 0.0002) indicated that the KCNQ1 gene rs2237895 polymorphism was significantly correlated with susceptibility to T2DM. In stratified analysis, this association was confirmed in Asian populations: allelic model (OR: 1.25; 95%CI: 1.13-1.37; P < 0.0001), recessive model (OR: 1.29; 95%CI: 1.11-1.49; P = 0.0007), dominant model (OR: 1.35; 95%CI: 1.20-1.52; P < 0.0001), codominant model (OR: 1.49; 95%CI: 1.22-1.81; P < 0.0001) (OR: 1.26; 95%CI: 1.16-1.36; P < 0.0001). In non-Asian populations, this association was not significant: Allelic model (OR: 1.06, 95%CI: 0.98-1.14; P = 0.12), recessive model (OR: 1.04; 95%CI: 0.75-1.42; P = 0.83), dominant model (OR: 1.06; 95%CI: 0.98-1.15; P = 0.15), codominant model (OR: 1.08; 95%CI: 0.82-1.42; P = 0.60. OR: 1.15; 95%CI: 0.95-1.39; P = 0.14). KCNQ1 gene rs2237895 was significantly associated with susceptibility to T2DM in an Asian population. Carriers of the C allele had a higher risk of T2DM. This association was not significant in non-Asian populations.

CD36 gene variant rs1761667(G/A) as a biomarker in obese type 2 diabetes mellitus cases

BackgroundSeveral reports discussed a connection between CD36 genotypes associated with obesity, influencing the development of Type 2 diabetes mellitus (T2DM). Therefore, this study examines the prognostic value of CD36 polymorphism rs1761667 (G/A) in individuals with obese T2DM. The investigation also explores the correlation between this genetic variation and the clinical/biochemical parameters of the subjects.MethodsBlood samples of a total of 475 subjects from north India were collected from the outpatient unit (OPD), Department of Medicine, KGMU, Lucknow as per inclusion/exclusion criteria. Anthropometric details of study subjects were recorded and biochemical parameters were estimated in 250 T2DM cases, 75 obese T2DM cases, and 150 controls. The CD36 gene variant rs1761667 (G/A) was subject to genotypic analysis using the polymerase chain reaction-restriction fragment length polymorphism (PCR–RFLP) method, utilizing specific primers and HhaI enzyme. All statistical analysis was done using SPSS (ver. 21.0) and Prism (5.01) software.ResultsFasting plasma glucose (FPG), systolic blood pressure (SBP), post-prandial glucose (PPG) were significant in T2DM subjects. Lipid profile such as Total Cholesterol (TC), Low-Density Lipoprotein (LDL) and Very Low-Density Lipoprotein (VLDL) were also found significantly associated with obese T2DM cases. GA and AA genotypes of rs1761667 (G/A) showed significant associations in obese T2DM cases. The GA genotype demonstrated a considerable association (P < 0.001) with a 2.77-fold increased susceptibility to the high risk of T2DM. The AA genotype was found to be significantly associated (P = 0.008) with 2.94-fold higher risk of T2DM in obesity while 9.33 folds significant risk of developing obesity in T2DM cases.ConclusionsThe risk of obesity in T2DM cases can be assessed by genotyping the CD36 genetic variant rs1761667 (G/A). However, raised FPG, PPG, TC, LDL, and VLDL showed poor prognosis in obese T2DM cases. CD36 gene variant can be proposed as a prognostic biomarker for risk prediction of T2DM and obesity, while anthro-biochemical risk factors as preventive biomarker.

Social isolation, loneliness, and the risk of incident type 2 diabetes mellitus by glycemic status

AimThe modifying effect of prediabetic status on the association of social isolation and loneliness with the risk of type 2 diabetes mellitus (T2DM) remains uncertain. We aimed to explore whether prediabetic status modifies the association of social isolation and loneliness with incident T2DM. Methods358,951 participants with random blood glucose < 11.1 mmol/l, hemoglobin A1c < 6.5 % and without diagnosis of diabetes from the UK Biobank were included. Prediabetes was defined by hemoglobin A1c level at 5.7–6.4 %. Social isolation and loneliness were assessed using self-reported questionnaires. The study outcome was incident T2DM. ResultsDuring a median follow-up of 12.5 years, 13,213 (3.7 %) incident T2DM cases were documented. Social isolation and loneliness in subjects with normoglycemia (adjusted HR [95 %CI]: social isolation: 1.14 [1.07;1.23]; loneliness: 1.33 [1.20;1.47]) were more strongly associated with increased risk of T2DM than in those with prediabetes (adjusted HR [95 %CI]: social isolation: 0.97 [0.91;1.03]; loneliness: 1.04 [0.95;1.13]) (Both P for interaction < 0.001). Among individuals with prediabetes, alcoholic consumption (30.9 %), household income (23.3 %), healthy sleep (17.1 %), loneliness (14.9 %), and physical activity (12.6 %) mediated most of the variance in the association between social isolation and incident T2DM, while body mass index (17.9 %) and healthy sleep (17.6 %) mediated most of the variance in the association between loneliness and incident T2DM. ConclusionSocial isolation and loneliness were independently associated with a higher risk of T2DM among individuals without prediabetes. Among those with prediabetes, the association of social isolation and loneliness with incident T2DM were mainly mediated by some socioeconomic and lifestyle factors.

Associations of chronic exposure to a mixture of pesticides and type 2 diabetes mellitus in a Chinese elderly population

Epidemiological studies have related exposure to pesticides to increased risk of diabetes. However, few studies have evaluated the health effects of mixed pesticides exposure, especially in an elderly population. Here, we utilized gas chromatography-tandem mass spectrometry to quantify the levels of 39 pesticides in 4 categories in a Chinese elderly population. Then we used general linear models to explore the association between individual pesticide exposure and type 2 diabetes mellitus (T2DM). Restricted cubic spline (RCS) models were fitted to identify potential non-linearities between those associations. Furthermore, stratified analysis by gender was conducted to explore the gender-specific associations. Finally, we used weighted quantile sum (WQS) regression, quantile-based g computation (qgcomp), and Bayesian kernel machine regression (BKMR) to evaluate the effects of mixed exposure to 39 pesticides. The results showed that exposure to pesticides was associated with high risk of T2DM, with β-Hexachlorocyclohexane (β-BHC) and oxadiazon being the most significant independent contributors, which was pronounced among elderly women. Moreover, the association of β-BHC and oxadiazon with T2DM was linear. These indicated that it is an urgent need to take practical measures to control these harmful pesticides.

Nonrestorative Sleep and Type 2 Diabetes Incidence: the Aichi Workers' Cohort Study.

The term "nonrestorative sleep (NRS)" refers to unrefreshed feeling at wake-up and is a domain of poor sleep quality. Previous researches have demonstrated that NRS is linked to a number of diseases and adverse health outcomes, but less is known regarding the link between NRS and diabetes, particularly in Japanese. We studied 3665 middle-aged male participants of the Aichi Workers' Cohort Study who were followed-up from 2002 to 2019. Cox proportional hazards models estimated hazard ratios (HRs) and 95% confidence intervals (CIs) of incident type 2 diabetes mellitus (T2DM) in relation to NRS adjusted for potential confounding variables. During a median follow-up of 14.6 years, 421 type 2 diabetes cases were identified. Participants with NRS had a higher crude incidence rate of T2DM (11.2/1,000 person-years), compared to participants without NRS (9.3/1,000 person-years). In the fully adjusted model, individuals who reported having NRS had a significantly higher risk of developing T2DM (HR: 1.36, 95% CI: 1.10-1.67). The association was observed only in participants under 50 years old (HR: 1.82, 95% CI: 1.36-2.43), not in the older (50 years or older) participants (P for interaction =0.025). In contrast, stratified analyses by the presence of shift work, obesity or sleep duration showed similar associations in all the strata. NRS was associated with higher risk of T2DM in middle-aged Japanese male workers independent of a variety of lifestyle factors and other sleep problems.

Predicting type 2 diabetes risk before and after solid organ transplantation using polygenic scores in a Danish cohort.

Type 2 diabetes mellitus (T2DM) can be multifactorial where both genetics and environmental factors play a role. We aimed to investigate the use of polygenic risk scores (PRS) in the prediction of pre-transplant T2DM and post-transplant diabetes mellitus (PTDM) among solid organ transplant (SOT) patients. Using non-genetic risk scores alone; and the combination with PRS, separate logistic regression models were built and compared using receiver operator curves. Patients were assessed pre-transplant and in three post-transplant periods: 0-45, 46-365 and >365 days. A higher PRS was significantly associated with increased odds of pre-transplant T2DM. However, no improvement was observed for pre-transplant T2DM prediction when comparing PRS combined with non-genetic risk scores to using non-genetic risk scores alone. This was also true for predictions of PTDM in all three post-transplant periods. This study demonstrated that polygenic risk was only associated with the risk of T2DM among SOT recipients prior to transplant and not for PTDM. Combining PRS with a clinical model of non-genetic risk scores did not significantly improve the predictive ability, indicating its limited clinical utility in identifying patients at high risk for T2DM before transplantation, suggesting that non-genetic or different genetic factors may contribute to PTDM.

Combined effects of organochlorine pesticides on type 2 diabetes mellitus: Insights from endocrine disrupting effects of hormones

Association between organochlorine pesticides (OCPs) exposure and type 2 diabetes mellitus (T2DM) remains contradictory, and the evidence is mostly focused on a single exposure. Here, we assessed the associations between individual and combined OCPs exposure and T2DM, and explored the underlying mechanism of sex hormones and the methylation levels of sex hormone receptors in above associations. A case-control study with 1812 participants was performed. Gas chromatography mass spectrometry, liquid chromatography-tandem mass spectrometry, and pyrosequencing were used to measure plasma OCPs, serum sex hormones, and whole blood methylation levels of sex hormone receptors, respectively. Generalized linear models were used to analyze the relationships between OCPs, sex hormones, the methylation levels of sex hormone receptors, and T2DM. Quantile based g-computation (QGC) and Bayesian Kernel Machine Regression (BKMR) were employed to assess the combined OCPs exposure. The roles of sex hormones and the methylation levels of their receptors were evaluated by moderating mediation models. After adjusting for covariates, each unit (2.718 ng/ml) increase in p,p’-DDE was associated with a higher risk of T2DM in males (odds ratio (OR) and 95% confidence interval (CI): 1.066 (1.023, 1.112)). QGC and BKMR showed a positive combined effect in the associations of OCPs mixtures on T2DM among premenopausal females, and positive effects but not statistically significant among males and postmenopausal females. p,p'-DDE was the largest contributor for the positive associations. Furthermore, testosterone mediated 21.149% of the associations of p,p’-DDE with T2DM moderated by the androgen receptor methylation (ARm) located in CpG island 1. Individual and mixtures of OCPs exposure were positively linked to elevated risk of T2DM. Testosterone and ARm may participate in the related processes of OCPs with T2DM, providing new insights into the adverse endocrine effects caused by OCPs and specific pathways for the etiology and control of diabetes.

Resting heart rate and the risk of incident type 2 diabetes mellitus among non-diabetic and prediabetic Iranian adults: Tehran lipid and glucose study

BackgroundResting heart rate (RHR) has been found to be a potential risk factor for developing type 2 diabetes mellitus (T2DM), with a highly significant heterogeneity among previous studies. Therefore, we examined the association of RHR and risk of incident T2DM among non-diabetic and prediabetic adults.MethodsThe study population included 2431 men and 2910 women aged ≥ 20 years without T2DM at baseline (2001–2005). Participants were followed for incident T2DM by about 3-year intervals up to April 2018. The multivariable Cox proportional models were applied to estimate the hazard ratios (HRs) and 95% confidence intervals (CIs). The models were adjusted for age, body mass index, waist circumference, educational level, physical activity, smoking, hypertension, family history of diabetes, triglycerides/ high-density lipoprotein cholesterol ratio, and fasting plasma glucose.ResultsDuring a median follow-up of 12.2 years, 313 men and 375 women developed T2DM. Interestingly, a significant sex-difference was found (all P-values for sex interaction < 0.025). Among men, compared to the first quintile (< 68 bpm: beats per minute), those who had RHR of over 84 bpm were at higher T2DM risk with a HR (95%CI) of 1.69 (1.16–2.47). Furthermore, considering RHR as a continuous variable, an increase of 10 bpm caused 17% significantly higher risk among men with a HR of 1.17 (1.05–1.30). However, among women, there was no significant association between incident T2DM and RHR. Moreover, among prediabetic participants at baseline, the association of RHR and risk of T2DM progression was generally similar to the general population, which means higher RHR increased the risk of T2DM development only among men with a HR of 1.26 (1.09–1.46) for 10 bpm increase.ConclusionsAmong men, being either non-diabetic or prediabetic at baseline, higher RHR can be associated with incident T2DM; however, women didn’t show a significant association. Further studies are needed to determine the added value of RHR as a potential modifiable risk factor in screening and risk prediction of incident T2DM.

Differential Responders to a Mixed Meal Tolerance Test Associated with Type 2 Diabetes Risk Factors and Gut Microbiota-Data from the MEDGI-Carb Randomized Controlled Trial.

The global prevalence of type 2 diabetes mellitus (T2DM) has surged in recent decades, and the identification of differential glycemic responders can aid tailored treatment for the prevention of prediabetes and T2DM. A mixed meal tolerance test (MMTT) based on regular foods offers the potential to uncover differential responders in dynamical postprandial events. We aimed to fit a simple mathematical model on dynamic postprandial glucose data from repeated MMTTs among participants with elevated T2DM risk to identify response clusters and investigate their association with T2DM risk factors and gut microbiota. Data were used from a 12-week multi-center dietary intervention trial involving high-risk T2DM adults, comparing high- versus low-glycemic index foods within a Mediterranean diet context (MEDGICarb). Model-based analysis of MMTTs from 155 participants (81 females and 74 males) revealed two distinct plasma glucose response clusters that were associated with baseline gut microbiota. Cluster A, inversely associated with HbA1c and waist circumference and directly with insulin sensitivity, exhibited a contrasting profile to cluster B. Findings imply that a standardized breakfast MMTT using regular foods could effectively distinguish non-diabetic individuals at varying risk levels for T2DM using a simple mechanistic model.

Association of serum phthalates exposure with incident type 2 diabetes risk in Chinese population: A nested case-control study

Prospective epidemiological evidence was lacking on the association of phthalates (PAEs) exposure with incident type 2 diabetes mellitus (T2DM) risk. In present nested case-control study, we identified 1006 T2DM cases and matched 1006 controls based on Dongfeng-Tongji cohort study, and 6 PAEs were detected in baseline serum. The conditional logistic regression model, Bayesian kernel machine regression (BKMR) model and Quantile-based g-computation were applied to evaluate the associations of determined PAEs, either as individuals or as a mixture, with incident T2DM risk. Subgroup analysis was conducted to identify the potential sensitive population of PAEs effects on T2DM. After multiple adjustment, no statistically significant association was observed between single or mixture of PAEs and incident T2DM risk in the whole population. However, serum levels of Di-n-butyl phthalate (DnBP) [OR= 2.06; 95% CI: (1.11–3.96)], Σdibutyl phthalate (ΣDBP) [OR= 1.96; 95% CI: (1.06–3.76)], and Σlow-molecular- weight phthalate (ΣLMW) [OR= 2.27; 95% CI: (1.17–4.57)] were significantly associated with T2DM in current drinker group. Moreover, significant potential interactions were observed among Di-iso-butyl phthalate (DiBP), DnBP, Butyl-benzyl phthalate (BBP), ΣDBP, and ΣLMW with drinking status on T2DM risk (P for interaction = 0.036, 0.005, 0.049. 0.010, and 0.005). We did not find significant associations between serum PAEs levels and T2DM in the whole population. However, current alcohol drinkers expose to higher levels of DnBP, ΣDBP, and ΣLMW had higher risk of T2DM.

Association of dietary and lifestyle inflammation score with type 2 diabetes mellitus and cardiometabolic risk factors in Iranian adults: Sabzevar Persian Cohort Study.

Systemic inflammation may contribute to the initiation and progression of type 2 diabetes mellitus (T2DM) through diet and lifestyle. We examined the association of dietary inflammation score (DIS), lifestyle inflammation score (LIS) and dietary and lifestyle inflammation score (DLIS) with T2DM and cardiometabolic risk factors among Iranian adults. In this study, we identified and recruited 619 patients with T2DM and 2113 without T2DM from 35 to 75 years old men and women in the baseline phase of the Sabzevar Persian Cohort Study. Using a validated 115-item semi-quantitative FFQ, we calculated a 19-component DIS and a 3-component LIS weighted by circulating inflammation biomarkers. The DIS, LIS and DLIS associations with diabetes were assessed by multivariable logistic regression analysis. The average age of the participants was 48·29 (sd 8·53) (without T2DM: 47·66 (sd 8·42); with T2DM: 50·44 (sd 8·57)). Individuals in the highest compared with the lowest tertiles of DLIS (OR: 3·40; 95 % CI 2·65, 4·35; Ptrend < 0·001), DIS (OR: 3·41; 95 % CI 2·66, 4·38; Ptrend < 0·001) and LIS (OR: 1·15; 95 % CI 0·90, 1·46; Ptrend = 0·521) had an increased risk of T2DM. For those in the highest relative to the lowest joint DIS and LIS tertiles, the results were OR: 3·37; 95 % CI 2·13, 5·32; Pinteraction < 0·001. No significant associations were found between DLIS and cardiometabolic risk factors, including blood pressure, liver enzymes and glycaemic and lipid profiles, except for waist circumference (P < 0·001) and waist-to-hip ratio (P = 0·010). A higher DIS and DLIS score was associated with a higher risk of T2DM, while the LIS score was not associated with T2DM risk.

The association of FGF-21 with the risk of newly diagnosed type-2 diabetes mellitus: a cross-sectional study in Southern China

BackgroundThis study investigated the relationship between fibroblast growth factor 21 (FGF-21) and newly diagnosed type-2 diabetes mellitus (T2DM).MethodsIn this cross-sectional study, FGF-21 and T2DM risk were analyzed using restricted cubic splines with univariate or multivariate logistic regression analysis. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated via logistic regression analysis. Cluster and subgroup analyses were conducted to evaluate the associations between FGF-21 and diabetes in different subpopulations. Nomograms and ROC curves were used to explore the clinical utility of FGF-21 in the diabetes assessment model.ResultsHigh levels of FGF-21 were significantly associated with a high risk of T2DM after adjusting for confounding factors in both the total population and subpopulations (P for trend < 0.001). In the total population, the ORs of diabetes with increasing FGF-21 quartiles were 1.00 (reference), 1.24 (95% CI 0.56–2.80; quartile 2), 2.47 (95% CI 1.18–5.33; quartile 3), and 3.24 (95% CI 1.53–7.14; quartile 4) in Model 4 (P < 0.001), and the trend was consistent in different subpopulations. In addition, compared with the model constructed with conventional noninvasive indicators, the AUC of the model constructed by adding FGF-21 was increased from 0.668 (95% CI: 0.602–0.733) to 0.715 (95% CI: 0.654–0.777), indicating that FGF-21 could significantly improve the risk-assessment efficiency of type-2 diabetes.ConclusionThis study demonstrated that a high level of circulating FGF-21 was positively correlated with diabetes, and levels of FGF-21 could be an important biomarker for the assessment of diabetes risk.

Effect of Aerobic Exercise in Chinese Adult Individuals at Risk for Type 2 Diabetes Mellitus (T2DM) with Low Salivary Amylase Gene (AMY1) Copy Number Variation.

Type 2 Diabetes mellitus (T2DM) has become a life-threatening health problem around the world. Studies have confirmed that aerobic exercise can prevent the risk of T2DM. Furthermore, recent research showed that salivary amylase gene (AMY1) copy number variation (CNV) could be one of the genetic factors that increased the risk of T2DM. To provide more evidence on how AMY1 CNV and exercise is correlated with the risk of T2DM, we designed this study to show the differences in postprandial carbohydrate metabolism between people with different AMY1 copy numbers, and how aerobic exercise can influence this process. Sixteen participants without cardiovascular disease were chosen, 8 with AMY1 CNV≥6 (High CNV group, HCNV), and 8 with AMY1 CNV ≤ 2 (Low CNV group, LCNV). All participants were Chinese, Han nationality, 18 to 40 years old, with fasting blood glucose lower than 6.1 mmol/L and normal blood pressure levels. They were asked to visit the laboratory in fasting state and drink a cup of solution with 75 grams of edible carbohydrate (glucose or starch). After carbohydrate intake, blood samples were taken at certain times at rest or after aerobic exercise. Blood glucose levels were tested with a portable blood glucose monitor, and insulin levels were tested with the enzyme-linked immunosorbent assay (ELISA). The LCNV group had significantly higher resting insulin levels and homeostatic model assessment of insulin resistance (HOMA-IR) than the HCNV group. Compared to the HCNV group, postprandial blood glucose levels and insulin levels were insensitive to starch intake in the LCNV group. However, this difference disappeared after aerobic exercise was added as an intervention. Lower AMY1 CNV could be associated with higher risk of T2DM and complex carbohydrate metabolism disorder, while aerobic exercise can reduce the risk by increasing the carbohydrate utilization rate.

Physical Activity as a Lifestyle Modification in Patients With Multiple Comorbidities: Emphasizing More on Obese, Prediabetic, and Type 2 Diabetes Mellitus Patients.

In this research, physical activity (PA) was shown to be inversely associated with the incidence of diabetes. This emphasizes the relevance of PA in diabetes prevention lifestyle intervention initiatives and encourages healthcare practitioners to advise high-risk patients on a healthy lifestyle combining PA for the reduction of weight in prediabetic, obese, and type 2 diabetes mellitus (T2DM) patients. The link between PA and diabetes was stronger in people with moderate or higher baseline PA, reflecting national recommendations that imply increasing activity levels may provide larger advantages for those who are comparatively less active. An intensive lifestyle intervention of eating healthier foods and increasing PA resulted in an effective decrease in weight and waist circumference after one year, which has high potential in the long term to prevent T2DM and different comorbidities such as obesity. Studies such as PRomotion Of Physical activity through structured Education with differing Levels of ongoing Support for those with prediabetes (PROPELS) demonstrate that the combination of PA interventions with telemedicine follow-ups results in ambulatory activity changes in the first year, but these changes do not last longer than four years. Acute PA practicing regularly will reduce postprandial glucose excursions. However, it is unknown what type of PA routine will benefit the most from reducing postprandial glucose levels. There are no discernible variations in the effects of different disciplines of training on glucose levels, mainly when the data are compared across time. The combination of a healthy diet and lifestyle with programs based on diabetes prevention results in comparable and clinically significant mean weight reduction with cardiometabolic advantages. Based on the reviewed and cited studies, PA in patients at high risk of T2DM and obese and non-obese patientswith T2DM results infavorable outcomes in the first few months. There is a large gap in investigations of the effects of PA in these patients and the benefits of other lifestyle modifications in long-term-based studies. However, in this study, we emphasize the importance of lifestyle modifications, putting in perspective principally the PA that the majority of patients with comorbidities do not practice, especially those with obesity, prediabetes, and T2DM. Thus, it would be necessary to conduct long-interval studies such as randomized clinical trials, where a better outcome can be given about intervals based on daily exercise times and the type of exercise in conjunction with diets that will have the greatest benefit, focusing more on the subjects that our research mentioned.

Retrospective cohort study to examine the association between serum amylase and the incidence of type 2 diabetes mellitus, Toranomon Hospital Health Management Center Study 23 (TOPICS 23)

IntroductionLow serum amylase values are cross-sectionally associated with the prevalence of type 2 diabetes mellitus (T2DM) but have not been shown to be longitudinally associated with its incidence. This retrospective...

1266-P: Validation of a Predictive Model of Diabetes in People with Overweight and Obesity

Obesity is the most common chronic disease in the U.S. A substantial subset of people with obesity are at high risk for type 2 diabetes mellitus (T2DM) and many of their risk factors for T2DM are modifiable. It is important to identify this at-risk subset to appropriately direct treatment and resources for earlier intervention and the prevention of T2DM. The original model was developed using EMR data of 338,653 adults &amp;lt; 65 years old with BMI ≥ 25 kg/m2 and without baseline T2DM between 2000 and 2019. Variables were selected from a literature-based pool of risk factors for T2DM using LASSO penalized Cox regression. A Cox model (adjusted for the competing risk of death) was developed using an 80% training dataset with selected variables and internally validated on a held-out 20% dataset of EMR data. This model was then externally validated on a dataset of 103,419 participants of the Nurses’ Health Study (NHS) and Health Professionals Follow-Up Study (HPFS). Over a mean of 7.0 years of follow-up, 30,100 (8.9%) patients in the EMR dataset developed T2DM (1.3% annual incidence). The predictive model included BMI (HR 1.47 for 5 kg/m2; 95% CI 1.46 - 1.49), age, history of hypertension, systolic blood pressure and family history of diabetes. The model achieved a Harrell’s C-statistic of 0.76 on the held-out EMR dataset and the calibration slope for 10-year estimates was 1.09. In the NHS-HPFS external validation dataset, 12,402 (12.0%) individuals developed T2DM over a mean 14.2 years of follow-up (0.85% annual incidence). On this dataset, the model achieved Harrell’s C-statistic of 0.72 and the calibration slope for 10-year estimates of 0.78. It is feasible to use predictive modeling to identify people with overweight and obesity at high risk of T2DM. This approach could be utilized to guide population management and clinical treatment decisions. Disclosure A.Turchin: Consultant; Proteomics International, Covance, Research Support; AstraZeneca, Edwards Lifesciences Corporation, Eli Lilly and Company, Novo Nordisk, Stock/Shareholder; Brio Systems. M.Shubina: None. F.J.Morrison: None. N.Ahmad: Employee; Eli Lilly and Company. L.M.Neff: Employee; Eli Lilly and Company, Research Support; Aegerion Pharmaceuticals, Stock/Shareholder; Eli Lilly and Company. H.Kan: Employee; Eli Lilly and Company, Stock/Shareholder; Eli Lilly and Company. Funding Eli Lilly and Company

Prevalence of type 2 diabetes mellitus and related factors among the general adult population in Saudi Arabia between 2016-2022: A systematic review and meta-analysis of the cross-sectional studies.

Health officials need current knowledge of type 2 diabetes mellitus (T2DM) and related risk factors to prioritize prevention and control measures due to lifestyle changes, population structure, and the high incidence of diabetes in Saudi Arabia. The present systematic review aims to estimate the current pooled prevalence of T2DM and related risk factors among the general adult population in Saudi Arabia between 2016 and 2022. PubMed, Web of Science, and Google Scholar databases were searched for cross-sectional studies that reported T2DM among adults in Saudi Arabia and were published between December 31, 2016, and December 31, 2022. The PRISMA guidelines and the AXIS tool were employed to report and evaluate study quality and bias risk. The meta-analysis with a fixed effect model included 10 studies comprising 8457 general men and women adults aged 18 or older. The prevalence of T2DM was 28% (95% CI = 27-28, P < .001), and risks of T2DM in persons over 40 were nearly twice as high (OR = 1.74, 95% CI = 1.34-2.27) than in age under 40 among general adult population in Saudi Arabia between 2016-2022. This difference was statistically significant (P < .0001). The evidence from this review provided alarming and highlighted points about the prevalence of T2DM between 2016 and 2022, but there was high heterogeneity between the studies. Individuals aged 40 or older had a high risk of T2DM among the general adult population in Saudi Arabia.

Association of epilepsy, anti-epileptic drugs (AEDs), and type 2 diabetes mellitus (T2DM): a population-based cohort retrospective study, impact of AEDs on T2DM-related molecular pathway, and via peroxisome proliferator-activated receptor γ transactivation.

A potential association between epilepsy and subsequent type 2 diabetes mellitus (T2DM) has emerged in recent studies. However, the association between epilepsy, anti-epileptic drugs (AEDs), and the risk of T2DM development remains controversial. We aimed to conduct a nationwide, population-based, retrospective, cohort study to evaluate this relationship. We extracted data from the Taiwan Longitudinal Generation Tracking Database of patients with new-onset epilepsy and compared it with that of a comparison cohort of patients without epilepsy. A Cox proportional hazards regression model was used to analyze the difference in the risk of developing T2DM between the two cohorts. Next-generation RNA sequencing was used to characterize T2DM-related molecularchanges induced by AEDs and the T2DM-associated pathways they alter. The potential of AEDs to induce peroxisome proliferator-activated receptor γ (PPARγ) transactivation was also evaluated. After adjusting for comorbidities and confounding factors, the case group (N = 14,089) had a higher risk for T2DM than the control group (N = 14,089) [adjusted hazards ratio (aHR), 1.27]. Patients with epilepsy not treated with AEDs exhibited a significantly higher risk of T2DM (aHR, 1.70) than non-epileptic controls. In those treated with AEDs, the risk of developing T2DM was significantly lower than in those not treated (all aHR ≤ 0.60). However, an increase in the defined daily dose of phenytoin (PHE), but not of valproate (VPA), increased the risk of T2DM development (aHR, 2.28). Functional enrichment analysis of differentially expressed genes showed that compared to PHE, VPA induced multiple beneficial genes associated with glucose homeostasis. Among AEDs, VPA induced the specific transactivation of PPARγ. Our study shows epilepsy increases the risk of T2DM development, however, some AEDs such as VPA might yield a protective effect against it. Thus, screening blood glucose levels in patients with epilepsy is required to explore the specific role and impact of AEDs in the development of T2DM. Future in depth research on the possibility to repurpose VPA for the treatment of T2DM, will offer valuable insight regarding the relationship between epilepsy and T2DM.

Influences of resolvin D1 and D2 on the risk of type 2 diabetes mellitus: a Chinese community-based cohort study.

Although cellular and animal studies have reported that resolvin D1 (RvD1) and resolvin D2 (RvD2) are mechanisms involved in the development of type 2 diabetes mellitus (T2DM), the impact of RvD1 and RvD2 on the risk of T2DM at a population level remains unclear. We included 2755 non-diabetic adults from a community-based cohort in China and followed them for seven years. Cox proportional hazards model was used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for the association of RvD1 and RvD2 with T2DM probability. Time-dependent receiver operator characteristics (ROC) curve was used to evaluate the predictive performance of RvD1 and RvD2 for the risk of T2DM based on the Chinese CDC T2DM prediction model (CDRS). A total of 172 incident T2DM cases were identified. Multivariate-adjusted HRs (95% CI) for T2DM across quartiles of RvD1 levels (Q1, Q2, Q3 and Q4) were 1.00, 1.64 (1.03-2.63), 1.80 (1.13-2.86) and 1.61 (1.01-2.57), respectively. Additionally, body mass index (BMI) showed a significant effect modification in the association of RvD1 with incident T2DM (P interaction = 0.026). After multivariate adjustment, the HR (95% CI) for T2DM in the fourth compared with the first quartile of RvD2 was 1.94 (95% CI: 1.24-3.03). Time-dependent ROC analysis showed that the area under time-dependent ROC curves of the "CDRS+RvD1+RvD2" model for the 3-, 5- and 7-year risk of T2DM were 0.842, 0.835 and 0.828, respectively. Higher RvD1 and RvD2 levels are associated with a higher risk of T2DM at the population level.

Type 2 Diabetes Mellitus and Periodontitis: Bidirectional Association in Population-based 15-year Retrospective Cohorts.

A two-way relationship between periodontitis and diabetes has been proposed. However, bidirectional epidemiological observation is limited and inconsistent. Using the National Health Insurance Research Database of Taiwan (covering over 99% of the entire population), we aimed to estimate the development of diabetes in periodontitis patients or that of periodontitis in patients with type 2 diabetes mellitus (T2DM), respectively. A total of 11 011 patients with severe periodontitis were recruited from 2000 to 2015. After matching by age, sex, and index date, 11 011 patients with mild periodontitis and 11 011 non-periodontitis controls were registered. Additionally, 157 798 patients with T2DM and 157 798 non-T2DM controls were enrolled, in whom the development of periodontitis was traced. Cox proportional hazards model was performed. Periodontitis patients tended to have a statistically high risk for T2DM. The adjusted hazard ratio was 1.94 (95% CI, 1.49-2.63, P < .01) and 1.72 (95% CI, 1.24-2.52, P < .01) for severe and mild periodontitis groups, respectively. The patients with severe periodontitis had a higher risk of having T2DM relative to those with mild periodontitis (1.17 [95% CI, 1.04-1.26, P < .001]). Conversely, the risk of periodontitis increased significantly in patients with T2DM (1.99 [95% CI, 1.42-2.48, P < .01]). However, high risk was observed for the outcome of severe periodontitis (2.08 [95% CI, 1.50-2.66, P < .001]), but not for mild periodontitis (0.97 [95% CI, 0.38-1.57, P = .462]). We suggest that the bidirectional association is between T2DM and severe but not mild periodontitis.