Risk Of Type 2 Diabetes Mellitus Research Articles

Baseline atherogenic index of plasma and its trajectory predict onset of type 2 diabetes in a health screened adult population: a large longitudinal study

BackgroundThe Atherogenic Index of Plasma (AIP) is a novel biomarker for assessing the severity of atherosclerosis and has been shown to be closely associated with the risk of Type 2 Diabetes Mellitus (T2DM). However, no prospective cohort study has comprehensively evaluated both the immediate risk stratification through baseline AIP and the long-term risk assessment through multi-time point AIP trajectories in health screened adults in relation to T2DM risk.MethodsThis longitudinal study included data from 42,850 participants who underwent health check-ups at Henan Provincial People’s Hospital between January 2018 and August 2024. AIP was calculated as the logarithm of the ratio of triglycerides (TG) to high-density lipoprotein cholesterol (HDL-C). The Kaplan-Meier method was employed to analyze the incidence of T2DM across different AIP groups. A Cox model with restricted cubic splines assessed the dose-response relationship between AIP and T2DM risk, while latent class trajectory models (LCTM) evaluated the trends of AIP over multiple time points. Cox proportional hazards models were used to examine the relationship between baseline AIP quartiles, AIP trajectories, and T2DM risk.ResultsDuring an average follow-up of 47.95 months, 3,228 participants developed T2DM. Stratifying by baseline AIP quartiles revealed that higher AIP levels were associated with an increased risk of T2DM. Compared to the lowest quartile, the highest quartile had a hazard ratio (HR) of 2.10 (95% CI: 1.74, 2.53). The LCTM identified three trajectory patterns for AIP: with the low-stable group as the reference, the medium-stable and high-stable groups had HRs of 1.72 (95% CI: 1.50, 1.96) and 2.50 (95% CI: 2.06, 3.03), respectively, indicating a significantly elevated risk of T2DM (P < 0.05).ConclusionElevated baseline AIP levels, medium stable trajectories and high stable trajectories are associated with an increased risk of T2DM in health screened adults.

Muscle quality index is correlated with insulin resistance and type 2 diabetes mellitus: a cross-sectional population-based study

BackgroundMuscle quality index (MQI), an emerging health index, is calculated by dividing handgrip strength by skeletal muscle mass. Current evidence on the correlation between MQI and type 2 diabetes mellitus (T2DM), insulin resistance (IR) is limited. This work aims to study that correlation.MethodsThis study involves a cross-sectional analysis on data from the National Health and Nutrition Examination Survey (NHANES) during the period from 2011 to 2014. To explore the correlation between MQI, IR and T2DM, multivariate logistic regression, receiver operating characteristic (ROC) curve, subgroup analysis, and restricted cubic spline regression were employed.ResultsA total of 2816 American adults were enrolled in this study, among whom 1264 (44.9%) had IR, and 300 (10.7%) had T2DM. Logistic regression and RCS regression analyses showed a significant negative linearly correlation between MQI and the prevalence of IR (OR = 0.708, 95%=0.514, 0.976) and T2DM (OR = 0.676, 95%CI = 0.472, 0.969). Subgroup analysis further revealed a stronger correlation between MQI and IR among individuals with obesity. ROC analysis showed that compared with skeletal muscle and grip strength, MQI (AUC = 0.679 for IR and 0.688 for T2DM) can serve as a more reliable identification factor for IR and T2DM.ConclusionThis study provides evidence that decreased levels of MQI are correlated with an increased risk of IR and T2DM, indicating the potential utility as a marker for identifying IR and T2DM.

Physical frailty, genetic predisposition, and type 2 diabetes mellitus.

To examine the association between frailty and incident type 2 diabetes mellitus (T2DM), considering the joint effect of multimorbidity and genetic risk. The study included 429,022 individuals in the UK Biobank. We used Cox regression with hazard ratio (HR) and 95% confidence interval (CI) to 1) evaluate the associations of frailty with incident T2DM, 2) explore whether frailty and multimorbidity would have a joint effect, and 3) assess whether the associations were modified by genetic risk. Compared with non-frail individuals, prefrail and frail individuals were at higher risk of T2DM: HR[95%CI] = 1.42 [1.38;1.47] for prefrailty and 1.81[1.70;1.92] for frailty. Five frailty components were associated with increased risk of T2DM: HR[95%CI] = 1.21[1.17;1.26] for weight loss, 1.35[1.30;1.40] for exhaustion, 1.31[1.26;1.37] for low physical activity, 1.27[1.20;1.33] for low grip strength, and 1.47[1.41;1.52] for slow gait speed. The increased risks were more pronounced among frail individuals with more than three morbidities: HR[95%CI] = 4.10[3.76;4.46]. Frail individuals at high genetic risk had a four and a half-fold greater risk of T2DM compared with non-frail individuals at low genetic risk: HR[95%CI] = 4.54[4.14;4.97]. Frailty was associated with increased risk of T2DM, especially in individuals with higher number of morbidities and high genetic risk. Frailty may be an independent risk factor for T2DM and targeted strategies to prevent and manage frailty would contribute to reducing the risk of T2DM.

The Diabetogenic Effect of Statin Use May Interact With Polygenic Risk Scores for Type 2 Diabetes: Evidence From the UK Biobank.

Statins are essential in the prevention of cardiovascular disease; however, their association with type 2 diabetes mellitus (T2DM) risk is concerning. We examined whether genetic susceptibility to T2DM modifies the association between regular statin use and T2DM risk. This study included 447 176 individuals from the UK Biobank without baseline diabetes or major cardiovascular disease. Statin use was recorded at baseline, and T2DM incidence was determined using clinical records. Polygenic risk scores (PRS) for T2DM risk were provided by the UK Biobank. Using propensity scores adjusted for age, sex, body mass index, and comorbidities, 14 831 statin users were matched with 37 060 non-users. Cox proportional hazards models were used to estimate the interaction effect of statin use and PRS on T2DM incidence, adjusting for key confounders. In the propensity-matched cohort, 3675 of 51 891 participants developed T2DM over a mean follow-up period of 13.7 years. Within the top 5% of the PRS distribution, per 1000 person-years, the incidence of T2DM was 15.42 for statin users versus 12.18 for non-users. Among the lowest 5%, the incidence was 1.90 for statin users and 1.65 for non-users. Based on the Cox proportional hazards model, regular statin use was associated with a 1.24-fold increased T2DM risk (95% confidence interval [CI], 1.15 to 1.33). Furthermore, PRS exhibited a significant multiplicative interaction with regular statin use (odds ratio, 1.10; 95% CI, 1.02 to 1.19). PRS may help identify individuals particularly susceptible to the diabetogenic effects of statins, providing a potential path for personalized cardiovascular disease management.

The Association Between Gestational Age and Type 1 Diabetes Mellitus in Children and Adolescents: A Systematic Review and Network Meta-Analysis.

With genetics thought to explain a portion of the overall risk of type 1 diabetes mellitus (T1DM), environmental risk factors in early life have been proposed. Previous studies on the incidence of T1DM in children or adolescents by gestational age at birth have yielded inconsistent results. To clarify the association between gestational age at birth and T1DM in childhood/adolescence and to offer evidence-based support for the prevention or screening of T1DM. PubMed, Embase, Web of Science, and the Cochrane Library were searched from the inception of the databases to February 7, 2024. Data were extracted using a standardised form created a priori, and quality was assessed using the Newcastle-Ottawa Scale (NOS). Due to the diversity of gestational age groups in the original studies, a Bayesian network meta-analysis was performed to discuss the association of different gestational ages with the risk of T1DM in childhood/adolescence. A total of 13 studies on children/adolescents with T1DM were included. Compared with the gestational age of 39-40 weeks, gestational ages of < 37 weeks (odds ratio [OR] 1.35, 95% credible interval [CrI] 1.19, 1.53), 33-36 weeks (OR 1.19, 95% CrI 1.11, 1.27), and 37-38 weeks (OR 1.26, 95% CrI 1.21, 1.30) were correlated with an increased risk of T1DM, whereas gestational ages of < 32 weeks (OR 0.61, 95% CrI 0.43, 0.88) and < 33 weeks (OR 0.72, 95% CrI 0.59, 0.87) were correlated with a lower risk. A higher risk of T1DM was observed in infants born early term or preterm compared tofull-term infants. However, the results of this network meta-analysis indicate that extremely or very preterm infants were less likely to develop T1DM. Further studies are needed to validate this in the future.

Circulating short-chain and branched short-chain fatty acids and the risk of incident type 2 diabetes: findings from the 4C Study

Abstract Previous studies suggested that fecal short-chain fatty acids (SCFAs) and branched short-chain fatty acids (BCFAs) are associated with glucose regulation. However, the potential relationship between circulating SCFAs and BCFAs with incident diabetes risk in both men and women remains unidentified in prospective cohort studies. In this study, we examined a panel of nine serum SCFAs and BCFAs in 3,414 subjects with incident diabetes, and matched normoglycemic controls from the China Cardiometabolic Disease and Cancer Cohort (4C) study. In fully adjusted conditional logistic regression models, total SCFAs, total BCFAs, and isovaleric acid were significantly associated with incident type 2 diabetes mellitus (T2DM) (P&amp;lt;0.05). Interestingly, gender-specific analysis showed that per standard deviation (SD) increment of SCFAs were positively associated with incident T2DM among women, with the odds ratio (OR) (95% confidence interval [CI]) of 1.16 (1.05−1.29) for total SCFAs and 1.18 ( 1.07−1.31) for propionate, respectively (P &amp;lt; 0.05, false discovery rate (FDR) &amp;lt; 0.05). No significant associations were observed in men. A significant interaction was detected between men and women for propionate (Pinteraction &amp;lt; 0.001, FDR &amp;lt; 0.01). After further adjustment of insulin measures, the associations of serum propionate with diabetes remained significant (P &amp;lt; 0.05, FDR &amp;lt; 0.05). Meanwhile, the associations of total BCFAs and isovaleric acid with diabetes were partially mediated by triglycerides, insulin resistance, and β-cell function in mediation analysis. These findings, for the first time in a large prospective cohort, provide evidence for an association between circulating SCFAs and BCFAs with T2DM risk, and support the potential role of circulating propionate with gender disparities in the early pathogenesis of diabetes.

Enhanced accuracy and stability in automated intra-pancreatic fat deposition monitoring of type 2 diabetes mellitus using Dixon MRI and deep learning.

Intra-pancreatic fat deposition (IPFD) is closely associated with the onset and progression of type 2 diabetes mellitus (T2DM). We aimed to develop an accurate and automated method for assessing IPFD on multi-echo Dixon MRI. In this retrospective study, 534 patients from two centers who underwent upper abdomen MRI and completed multi-echo and double-echo Dixon MRI were included. A pancreatic segmentation model was trained on double-echo Dixon water images using nnU-Net. Predicted masks were registered to the proton density fat fraction (PDFF) maps of the multi-echo Dixon sequence. Deep semantic segmentation feature-based radiomics (DSFR) and radiomics features were separately extracted on the PDFF maps and modeled using the support vector machine method with 5-fold cross-validation. The first deep learning radiomics (DLR) model was constructed to distinguish T2DM from non-diabetes and pre-diabetes by averaging the output scores of the DSFR and radiomics models. The second DLR model was then developed to distinguish pre-diabetes from non-diabetes. Two radiologist models were constructed based on the mean PDFF of three pancreatic regions of interest. The mean Dice similarity coefficient for pancreas segmentation was 0.958 in the total test cohort. The AUCs of the DLR and two radiologist models in distinguishing T2DM from non-diabetes and pre-diabetes were 0.868, 0.760, and 0.782 in the training cohort, and 0.741, 0.724, and 0.653 in the external test cohort, respectively. For distinguishing pre-diabetes from non-diabetes, the AUCs were 0.881, 0.688, and 0.688 in the training cohort, which included data combined from both centers. Testing was not conducted due to limited pre-diabetic patients. Intraclass correlation coefficients between radiologists' pancreatic PDFF measurements were 0.800 and 0.699 at two centers, suggesting good and moderate reproducibility, respectively. The DLR model demonstrated superior performance over radiologists, providing a more efficient, accurate and stable method for monitoring IPFD and predicting the risk of T2DM and pre-diabetes. This enables IPFD assessment to potentially serve as an early biomarker for T2DM, providing richer clinical information for disease progression and management.

Serum Medium-Chain Fatty Acids and the Risk of Incident Diabetes: Findings From the 4C Study.

Emerging studies have revealed associations between dietary medium-chain fatty acids (MCFAs) and glucose homeostasis. However, the relationship between serum MCFAs and the incidence of diabetes, and potential interactions with genetic predisposition, remains unclear in prospective cohort studies. This work aimed to investigate associations and genetic susceptibility between serum MCFAs and diabetes risk. We investigated baseline serum MCFAs (n = 5) in a nested case-control study comprising incident diabetes cases (n = 1707) and matched normoglycemic control individuals (n = 1707) from the China Cardiometabolic Disease and Cancer Cohort Study. Associations between MCFAs and type 2 diabetes mellitus (T2DM) were examined, both overall and stratified by diabetes genetic susceptibility. Genetic risk scores (GRS) were calculated based on 86 T2DM-associated genetic variants. In the fully adjusted conditional logistic regression model, serum octanoic acid and nonanoic acid exhibited inverse dose-response relationships with diabetes risk, showing odds ratios (95% CI) of 0.90 (0.82-0.98) and 0.84 (0.74-0.95), respectively. Subgroup analysis demonstrated that inverse associations between MCFAs and incident diabetes were more pronounced among individuals with physical inactivity (Pinteraction = .042, .034, and .037, for octanoic, nonanoic and decanoic acid, respectively). Moreover, inverse associations of octanoic acid with diabetes risk were notably enhanced among individuals with high genetic risk compared to those with low genetic risk. Statistically significant interactions were observed between octanoic acid and GRS on T2DM risk (Pinteraction = .003). These findings provide evidence supporting inverse associations between serum MCFAs and T2DM risk, and reveal potential interplay between genetic susceptibility and circulating octanoic acid in modulating diabetes risk.

Relationships Between APOE, Type 2 Diabetes, and Cardiovascular Disease in Postmenopausal Women.

The apolipoprotein E (APOE) ε4 allele, type 2 diabetes mellitus (T2DM), and cardiovascular disease (CVD) are well-established risk factors for dementia. Relationships between APOE and incidence of T2DM and CVD are not fully understood but may shed light on the mechanisms underlying dementia pathogenesis. Postmenopausal women (N = 6 795) from the Women's Health Initiative hormone therapy clinical trial with APOE genotyping and no prior diagnosis of T2DM or CVD were included. We examined associations of APOE status (APOE2+ [ε2/ε2, ε2/ε3], APOE3 [ε3/ε3], and APOE4+ [ε4/ε4, ε3/ε4] carriers) with incidence of T2DM, coronary heart disease, stroke, and total CVD events using Cox regression. CVD outcomes were examined in baseline non-statin users and adjusted for statin initiation over follow-up to account for possible confounding by statins. Among all participants (mean age 66.7 ± 6.5 years, 100% non-Hispanic White), 451 (6.6%) were using statins at baseline. Over the follow-up (mean 14.9 and 16.0 years for T2DM and CVD, respectively), 1 564 participants developed T2DM and 1 578 developed CVD. T2DM incidence did not differ significantly by APOE status (ps ≥ .09). Among non-statin users, APOE4+ had higher incidence of total CVD (hazard ratio [95% confidence interval] = 1.18 [1.02-1.38], p = .03) compared with APOE3 carriers, but risks for coronary heart disease (1.09 [0.87-1.36], p = .47) and stroke (1.14 [0.91-1.44], p = .27) were not significantly elevated when examined individually. CVD outcomes did not differ between APOE2+ and APOE3 carriers (ps ≥ 0.11). T2DM risk did not differ by APOE status among postmenopausal women, but APOE4+ carriers not using statins had an increased risk of total CVD events.

Association of homocysteine and uric acid with type 2 diabetes mellitus: a case-control study

The aim of this study was to examine the association between homocysteine (Hcy), uric acid (UA) and type 2 diabetes mellitus (T2DM), and to explore whether there was an interaction between Hcy and UA in the development of T2DM. A total of 1250 diabetic patients and 1250 non-diabetic controls were included in this case-control study. Binary logistic regression and interaction analysis were used to evaluate the association between Hcy, UA, and T2DM, and the combined effects of Hcy and UA on T2DM, respectively. Plasma Hcy and UA levels were significantly higher in diabetic patients compared to non-diabetic controls (p < 0.001, p = 0.002). Elevated Hcy and UA were risk factors for T2DM. Binary logistic regression analysis showed that compared with the lowest quartile of Hcy and UA, the highest quartile had a significantly increased risk of T2DM (OR = 1.629, 95% CI: 1.303, 2.035 for Hcy; OR = 1.596, 95% CI: 1.277, 1.995 for UA). Stratified analysis suggested a significant association between Hcy and T2DM for those aged < 65 years and males. A significant association between UA and T2DM was found in those aged ≥ 65 years, males, and BMI ≥ 24 kg/m2. No significant interaction was observed between Hcy and UA (p > 0.05). Hcy and UA were risk factors for T2DM. However, there was no interaction between Hcy and UA in the risk of T2DM.

Prevention of type 2 diabetes mellitus among people with Middle Eastern backgrounds living in high-income countries: a systematic review

ObjectivesThis systematic review aims to assess the available evidence on the prevention of type 2 diabetes mellitus (T2DM) among Middle Eastern (ME) populations residing in high-income countries (HICs). The review...

International diet quality index and revised diet quality index relationship with type 2 diabetes disease: a case-control study.

Type 2 diabetes mellitus (T2DM) is a global health crisis linked to increased cardiovascular risk. Research indicates that better dietary quality-higher intake of fruits, vegetables, and whole grains, and lower intake of processed foods-reduces T2DM risk. This study examines the relationship between T2DM and dietary quality indices (DQI-I and DQI-R) to determine if adherence can lower diabetes risk. By analyzing dietary patterns in individuals with and without diabetes, the research aims to identify key nutritional factors influencing disease risk and provide evidence-based dietary recommendations for prevention and management. This case-control study involved 128 T2DM patients and 256 controls, assessing dietary intake with a validated 168-item food frequency questionnaire to calculate the Dietary Quality Index-I (DQI-I) and Dietary Quality Index-R (DQI-R). Multivariable logistic regression analysis explored the relationship between DQI-I, DQI-R, and their components with T2DM development odds. The mean (SD) age and body mass index (BMI) of participants, comprising 53.7% men, were 37.8 (7.8) years and 27.7 (3.3) kg/m2, respectively. In the final model, each standard deviation increase in the DQI-I score was associated with reduced odds of T2DM (odds ratio [OR] = 0.61; 95% confidence interval [CI] = 0.37-0.92; p = 0.046). Among the components of the DQI-I, a high adequacy score was significantly correlated with lower odds of T2DM (OR = 0.13; 95% CI = 0.05-0.36; p < 0.001). Additionally, participants in the highest tertile of the DQI-R score exhibited lower odds of T2DM compared to those in the lowest tertile (OR = 0.29; 95% CI = 0.11-0.49; p < 0.001). Furthermore, within the components of the DQI-R, a high moderation score was associated with a decreased risk of T2DM (OR = 0.19; 95% CI = 0.09-0.45; p < 0.001). The case-control study suggests a potential protective effect of diets with higher scores on the Diet Quality Index-International (DQI-I) and Revised Diet Quality Index (DQI-R) in reducing T2DM risk. Future research should focus on larger sample sizes and prospective designs to further investigate the DQI-I, DQI-R, and their components in relation to T2DM and other chronic diseases.

The relationship between sociodemographic characteristics, lifestyle, and diet quality with diabetes risk in overweight and obese Turkish adults

BackgroundObesity and certain associated environmental factors increase the risk of type 2 diabetes mellitus (T2DM). This research aims to evaluate the relationship between sociodemographic characteristics, lifestyle, and diet quality with diabetes risk in overweight and obese Turkish adults.MethodsA questionnaire form including sociodemographic characteristics, lifestyle, body weight and height was applied. Finnish Diabetes Risk Score (FINDRISC) tool was used to identify the risk of T2DM. Dietary assessments were made by 24 h dietary recall and diet quality was evaluated by Healthy Eating Index-2015 (HEI-2015).ResultsAccording to FINDRISC score, 38.1% of adults were at mild risk, 21.9% were at moderate risk, and 20.9% were at high risk. In regression model, factors such as low educational level, being married, being employed, smoking, and the presence of comorbidities were found to increase the risk of developing diabetes. Each unit decline in HEI-2015, the risk of diabetes increased by a factor of 0.983.ConclusionsSociodemographic factors, lifestyle, and diet quality significantly contribute to the increased risk of diabetes in overweight and obese Turkish adults. This trial was registered at clinicaltrials.gov with number NCT06614075 and registration date of 26 September 2024, retrospectively registered.

Outdoor air pollution exposure and the risk of type 2 diabetes mellitus: A systematic umbrella review and meta-analysis.

The association between different air pollutants and Type 2 Diabetes Mellitus (T2DM) is a growing topic of interest in public health research. This umbrella review and meta-analysis aimed to consolidate current literature on the association between various outdoor air pollutants and T2DM. Subgroups and dose-response relationships were also analyzed to further quantify the association, especially by the factors such as the type of pollutants, duration of exposure, and geographical variation, etc. A thorough literature search of three databases revealed a total of 71 records for umbrella review and 1524 records for meta-analysis where 8 studies were included in the final review of umbrella review and 46 studies for meta-analysis. The evaluation of the study's quality in umbrella review and meta-analysis were conducted using the AMSTAR 2 criteria and the Newcastle-Ottawa Scale (NOS), respectively. Exposure to Particulate Matter (PM) 2.5, PM10, Nitrogen dioxides (NO2) and Ozone (O3) were significantly associated with the risk of T2DM [OR=1.12 (95% Confidence Interval (CI): 1.09, 1.15), 1.12 (95% CI: 1.06, 1.18), 1.09 (95%CI: 1.07, 1.12), 1.05 (95%CI: 1.03, 1.08), respectively] and subgroup analysis further revealed that PM2.5, PM10, and NO2 associations were confounded by factors such as ages, study design, regions of exposure and air pollution concentration levels. Lastly, only exposure to PM10 had a significant dose-response relationship with the risk of T2DM (p-value=0.000). These findings further emphasized the need for standardized methods in conducting air pollution research and additional research on other air pollutants to further explore the relationships between these air pollutants and T2DM.

Associations of Tea Consumption With the Risk of All-Cause and Cause-Specific Mortality Among Adults With Type 2 Diabetes: A Prospective Cohort Study in China.

To investigate the associations of tea consumption with all-cause and cause-specific mortality among type 2 diabetes mellitus (T2DM) Chinese patients. The present study included 15 718 participants from the Comprehensive Research on the Prevention and Control of Diabetes between 2013 and 2014 in Jiangsu, China. Information on tea consumption (including frequency, amount, and duration) was collected at baseline using interviewer-administered questionnaires. Death data were identified by linkage to the Death Certificate System. Cox proportional hazard regression models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs). During a median follow-up of 9.77 (9.69, 9.82) years, 3046 deaths were documented, including 922 from cardiovascular disease (CVD) and 736 from cancer. Compared with nonconsumers, regular tea consumption (≥ 3 times/week, 1 cup/day, > 30 years) was associated with reduced all-cause mortality risk in T2DM, with HRs (95% CIs) of 0.82 (0.74, 0.91), 0.80 (0.72, 0.89), and 0.77 (0.68, 0.86). For cardiovascular mortality, the HRs (95% CIs) were 0.79 (0.65, 0.96), 0.72 (0.59, 0.89), and 0.75 (0.60, 0.93). The exposure-response relationship suggested that consuming 4 g/day may offer the most evident health benefits. Among Chinese T2DM patients, higher tea frequency and amount intake were associated with lower risk of all-cause and CVD mortality. It is suggested that consuming 4 g/day of tea could potentially serve as an intervention target. These findings suggest that tea consumption can be a part of a healthy diet for T2DM patients.

Performance of the 1h oral glucose tolerance test in predicting type 2 diabetes and association with impaired β-cell function in Asians: a national prospective cohort study.

Postprandial glucose concentration 1-h (1h-PG) after an oral glucose tolerance test (OGTT) has similar or superior performance to 2h-PG in predicting type-2 diabetes mellitus (T2DM) in several populations, and is simpler to obtain in clinical practice. However, studies in Asians are scarce. We investigated the utility of elevated baseline 1h-PG in predicting T2DM incidence within three years, and its relationship with β-cell function in 1250 non-diabetic Asian participants. Participants underwent an OGTT, an intravenous glucose challenge and a hyperinsulinemic-euglycemic clamp to determine glucose tolerance, acute insulin response (AIR) and insulin sensitivity at baseline. OGTTs were repeated every six months until study completion to monitor T2DM conversion. The area under the receiver operating characteristic curve of 1h-PG was not significantly different from 2h-PG (AUC1h-PG=0.883 vs. AUC2h-PG=0.907; ΔAUC=-0.024, P=0.124) and the optimal 1h-PG cut-off was ≥10.7mmol/L. When groups of high/low 1h-PG and 2h-PG at baseline were compared, AIR and disposition index were significantly lower in groups with high 1h-PG, and both had a stronger correlation with 1h-PG, indicating that impaired β-cell function was more strongly associated with elevated 1h-PG than 2h-PG. The ability of 1h-PG to detect Asians at risk of developing T2DM within three years is on par with 2h-PG and the optimal cut-off is 10.7mmol/L. Elevated 1h-PG is associated with β-cell dysfunction. We conclude that 1h-PG can be considered as a primary OGTT time point to identify Asians at risk for T2DM, allowing for screening at a reduced time and cost, and with lower patient burden. National Medical Research Council (NMRC), Ministry of Health (MOH; Singapore) Industry Alignment Fund [NMRC/MOHIAFCat1/0048/2016] and Janssen Pharmaceuticals Inc. (USA).

Elevated levels of serum alpha-2-macroglobulin associate with diabetes status and incident CVD in type 1 diabetes.

Atherosclerotic CVD is a major cause of death in individuals with type 1 diabetes mellitus (T1DM). However, conventional risk factors do not fully account for the increased risk. This study aimed to investigate whether serum proteins associate with diabetes status and the occurrence of CVD in T1DM. We used isotope dilution-MS/MS to quantify 28 serum proteins in 228 subjects participating in the prospective Coronary Artery Calcification in Type 1 Diabetes study. We used linear regression to analyze the association between serum protein levels and T1DM status using 47 healthy controls and 134 T1DM patients without CVD and Cox proportional hazards regression to assess their prediction for incident CVD by a case-cohort study using a subcohort of 145 T1DM subjects and a total of 47 CVD events. Of the 28 serum proteins studied, five of them-alpha-2-macroglobulin (A2M), apolipoprotein A-IV, apolipoprotein L1, insulin-like growth factor 2, and phospholipid transfer protein-were significantly associated with T1DM status, with A2M being 1.6-fold higher in T1DM. After adjusting for potential confounders, A2M independently predicted incident CVD, with a mean hazard ratio of 3.3 and 95% CI of 1.8-6.1. In our study, A2M showed the largest increase in serum levels when comparing patients with T1DM to control subjects. A2M also predicted incident CVD, suggesting that it could serve as both a marker and possibly a mediator of atherosclerosis in T1DM. These findings emphasize the importance of specific serum proteins in assessing and managing CVD risk in T1DM.

Dissecting Causal Relationships Between Antihypertensive Drug, Gut Microbiota, and Type 2 Diabetes Mellitus and Its Complications: A Mendelian Randomization Study.

Limited research has investigated the impact of antihypertensive medications on type 2 diabetes mellitus (T2DM) and whether gut microbiome (GM) mediates this association. Thus, we conducted a two-sample Mendelian randomization (MR) analysis to estimate the potential impact of various antihypertensive drug target genes on T2DM and its complications. Genetic instruments for the expression of antihypertensive drug target genes were identified with expression quantitative trait loci (eQTL) in blood, which should be associated with systolic blood pressure (SBP). Sensitivity analysis, including reverse causality detection, horizontal pleiotropy, phenotype scanning, and Bayesian colocalization, was used to validate our findings. We performed a two-step MR to detect the mediating role of GM. A 1-standard deviation (SD) decrease of KCNJ11 (acting on arteriolar smooth muscle, e.g., Pinacidil) gene expression was associated with lower SBP of 1.12 (95% confidence interval [CI], 0.93-1.31) mmHg, and a decreased risk of diabetic retinopathy (odds ratio [OR], 0.63; 95% CI, 0.52-0.76). Similarly, a 1-SD decrease of SLC12A2 (genetically a proxy for diuretics, for example, Torasemide) gene expression was correlated with a reduced risk of T2DM (OR, 0.88; 95% CI, 0.83-0.92). Interestingly, this causal effect was influenced by a decrease in the gut microbiota abundance of the genus Ruminococcus (effect proportion = 11.2%). Colocalization supports these results (KCNJ11: 98% for diabetic retinopathy; SLC12A2: 99% for T2DM). Findings provide novel targets for the treatment of T2DM and its complications, emphasize the importance of KCNJ11 and SLC12A2 in future drug development, and highlight the significant mediating role of the genus Ruminococcus.

A lower eGFRcystatin C/eGFRcreatinine ratio is associated with greater cardiovascular risk (higher Framingham Risk Score) in Chinese patients with newly diagnosed type 2 diabetes mellitus

Background Cardiovascular disease (CVD) is the leading cause of mortality in type 2 diabetes mellitus (T2DM) patients. Shrunken pore syndrome (SPS) is defined as eGFRcystatin C/eGFRcreatinine ratio <0.70 and predicts high CVD mortality. The Framingham Risk Score (FRS) is used to estimate an individual’s 10-year CVD risk. This study investigated the association between FRS and eGFRcystatin C/eGFRcreatinine ratio in T2DM patients. Methods Patients aged 18-80 years who were newly diagnosed with T2DM were included in this retrospective study. Ordinal logistic regression analysis was used to investigate the association between risk factors of T2DM and FRS. A Generalized Linear Model was used to calculate odds ratios (OR) and 95% confidence intervals (CI). Results There were 270 patients included in the study. Only 27 patients (10%) met the diagnostic criteria of SPS. Ordinal logistic regression analysis showed that SPS was not correlated with FRS risk (OR = 1.99, 95%CI = 0.94–4.23, p = 0.07), whereas eGFRcystatin C/eGFRcreatinine (OR = 0.86, 95%CI = 0.77–0.97, p = 0.01) showed a significant negative association with FRS risk. Compared with eGFRcystatin C/eGFRcreatinine>0.85, eGFRcystatin C/eGFRcreatinine≤0.85 increased FRS risk (OR = 1.95, 95%CI = 1.18–3.21, p < 0.01). After adjustment for confounding factors, increased eGFRcystatin C/eGFRcreatinine ratio was associated with decreased FRS risk when considered as a continuous variable (OR = 0.87, 95%CI = 0.77–0.99, p = 0.03). The FRS risk in patients with eGFRcystatin C/eGFRcreatinine≤0.85 is 1.86 times higher than that in patients with eGFRcystatin C/eGFRcreatinine>0.85 (OR = 1.86, 95%CI = 1.08–3.21, p = 0.03). Conclusions In the current study, no significant association between SPS and FRS was identified. However, lower eGFRcystatin C/eGFRcreatinine and eGFRcystatin C/eGFRcreatinine≤0.85 were associated with a significantly increased CVD risk in T2DM.

Association between the triglyceride to high-density lipoprotein cholesterol ratio and type 2 diabetes mellitus in non-alcoholic fatty liver disease

This study evaluated the ability of the triglyceride (TG) to high-density lipoprotein cholesterol (TG/HDL-C) ratio to identify individuals at risk of type 2 diabetes mellitus (T2DM) in the non-alcoholic fatty liver disease (NAFLD) population. We retrospectively studied 4,769 patients with NAFLD from the Affiliated Hospital of Hangzhou Normal University (2020–2023). Binary logistic regression models were used to evaluate the association between the TG/HDL-C ratio and lipid parameters with T2DM. TG/HDL-C ratio was positively associated with T2DM in patients with NAFLD, with an odds ratio (OR) of 2.72 (95% confidence interval, 2.23–3.31, p < 0.001) for T2DM in the highest TG/HDL-C ratio quartile compared with the lowest one after adjusting for known confounders. The OR for the TG/HDL-C ratio had a stronger predictive value than those of TG, total cholesterol, HDL-C, and low-density lipoprotein cholesterol, indicating that the TG/HDL-C ratio could be a better discriminator of T2DM. The TG/HDL-C ratio better identifies potential risks of T2DM in individuals with NAFLD than individual lipid parameters. Therefore, clinicians should pay attention to individuals with high TG and low HDL-C levels during T2DM risk assessment in NAFLD cohorts.