Insulin resistance, diabetic kidney disease, and all-cause mortality in individuals with type 2 diabetes: a prospective cohort study

Integrative analysis of mitochondrial and immune pathways in diabetic kidney disease: identification of AASS and CASP3 as key predictors and therapeutic targets

OBJECTIVES

Diabetic kidney disease (DKD) is driven by mitochondrial dysfunction and immune dysregulation, yet the mechanistic interplay remains poorly defined. This study aimed to identify key molecular networks linking mitochondrial and immune pathways to DKD progression, with a focus on uncovering biomarkers and therapeutic targets.

METHODS

We conducted an integrative analysis of human DKD cohorts (GSE30122, GSE96804) using weighted gene co-expression network analysis (WGCNA) to identify gene modules enriched for immune response genes and mitochondrial pathways (from MitoCarta3.0). Machine learning algorithms were employed to prioritize key biomarkers for further investigation. Experimental validation was performed using a DKD rat model.

RESULTS

WGCNA revealed significant gene modules associated with immune responses and mitochondrial functions. Machine learning analysis highlighted two central biomarkers: aminoadipate-semialdehyde synthase (AASS) and caspase-3 (CASP3). In the DKD rat model, elevated levels of AASS and CASP3 were found to correlate with increased oxidative stress. Mechanistically, AASS was shown to drive mitochondrial damage via lysine metabolism, while CASP3 amplified inflammatory apoptosis pathways.

CONCLUSIONS

Our findings establish AASS and CASP3 as dual biomarkers and therapeutic targets, bridging mitochondrial-immune crosstalk to DKD pathogenesis. This multi-omics framework provides actionable insights for targeting kidney damage in diabetes.

Associations of insulin resistance estimated by glucose disposal rate with frailty progression

OBJECTIVES

To investigate the relationship between estimated glucose disposal rates (eGDR) and the progression of frailty, using longitudinal data.

METHODS

We analyzed four waves of data from the China Health and Retirement Longitudinal Study (CHARLS) from 2011 to 2018, involving 6,778 middle-aged and older adults. eGDR was calculated using a specific formula, categorizing participants into high and low eGDR groups based on the lowest quartile (8.5). Frailty status was assessed using the frailty index (FI). Linear mixed-effects models were employed to analyze the association between eGDR and frailty progression, as well as the impact of transitions in eGDR.

RESULTS

We found that the baseline FI was significantly higher in the low eGDR group compared to the high eGDR group. Furthermore, participants in the low eGDR group exhibited a faster progression of frailty, compared to those in the high eGDR group. Among non-frail participants at baseline, the association between low eGDR and accelerated frailty progression was even more pronounced. Further analysis revealed that, compared to participants who maintained a stable high eGDR, those who transitioned from high to low eGDR and those who consistently remained in the low eGDR group both experienced significantly accelerated frailty progression. On the contrary, participants who transitioned from low to high eGDR did not show a significant acceleration in frailty progression compared to those who consistently maintained a high eGDR.

CONCLUSION

Low eGDR is linked to accelerated frailty progression in middle-aged and older Chinese adults. Transitioning from low to high eGDR may mitigate this progression, highlighting the importance of eGDR in frailty management.

Association between estimated glucose disposal rate with the all-cause and cause-specific mortality among the population with cardiometabolic syndrome

BACKGROUND

Estimated glucose disposal rate (eGDR) is considered as a reliable alternative indicator of insulin resistance. However, the relationship between eGDR levels and mortality among individuals with cardiometabolic syndrome (CMS), as well as within different glucose metabolic states in this population, remains unclear.

METHODS

We conducted a cohort study on 9928 CMS participants from the National Health and Nutrition Examination Survey (NHANES) database from 1999 to 2018. The relationship between eGDR levels and mortality in the CMS population was evaluated using multivariable Cox proportional hazards regression models and restricted cubic splines (RCS). Finally, stratified analysis was performed to determine the relationship between eGDR levels and mortality in different subgroups.

RESULTS

Cox regression analysis showed a significant correlation between eGDR levels and both all-cause and cause-specific mortality in the entire CMS population (all p < 0.05). RCS analysis revealed a non-linear relationship between eGDR levels and both all-cause (p for overall < 0.001, p for non-linear < 0.001) and diabetes specific mortality (p for overall < 0.001, p for non-linear = 0.004) in CMS population, while a linear relationship with cardiovascular specific mortality (p for overall < 0.001, p for non-linear = 0.091). In participants with baseline diabetes mellitus (DM), eGDR levels were significantly correlated with all-cause mortality, cardiovascular specific mortality, and diabetes specific mortality (all p < 0.05). In CMS participants with baseline pre-diabetes mellitus (Pre-DM), eGDR levels were significantly correlated with cardiovascular-specific and diabetes-specific mortality (all p < 0.05). In CMS participants with baseline normal glucose regulation (NGR), eGDR levels were only significantly related to diabetes specific mortality (p < 0.05).

CONCLUSION

There is a significant correlation between eGDR levels and both all-cause and cause-specific mortality in the entire CMS population. Furthermore, the protective effect of high eGDR levels on mortality persists across various glucose metabolic states.

Climate change and air pollution can amplify vulnerability of glucose metabolism: The mediating effects of biological aging

Climate change and air pollution pose significant global health threats, including impacts on diabetes risk; however, their long-term effects on insulin resistance (IR), a key determinant in diabetes pathophysiology, remain unclear. This study investigated whether exposure to heatwaves, temperature fluctuations, and warm-season ozone (O3) contributes to or exacerbates IR and explored the potential mediating role of biological aging. The study enrolled 6,901 participants and assessed both traditional and novel IR indicators: estimated glucose disposal rate (eGDR), triglyceride-glucose (TyG) index, triglyceride to high-density lipoprotein cholesterol ratio (TG/HDL-c), metabolic score for IR (METS-IR), TyG-body mass index (TyG-BMI), TyG-waist circumference (TyG-WC), waist-to-height ratio (WHtR), TyG-WHtR, and lipid accumulation product (LAP). Ordinary least squares regression models were applied to evaluate the long-lasting effects of heatwaves, temperature fluctuation, and warm-season O3 on IR, incorporating Huber-White robust standard errors for model stability. Causal mediation analysis was utilized to investigate the mediating effects of biological aging. We found that exposure to heatwaves and higher concentrations of warm-season O3 was associated with elevated IR levels, with males, smokers, drinkers, and low-income individuals being more vulnerable. Accelerated biological aging (including body age, metabolomic aging rate, etc.) could significant mediate the long-lasting effects of heatwaves and warm-season O3. Our findings suggest that climate change and air pollution could amplify the vulnerability of glucose metabolism, particularly in males, smokers, drinkers, and individuals with low-income. More importantly, our findings reveal the importance of mitigating biological aging to prevent IR in the future, as global diabetes prevalence escalates rapidly.

The relationship between estimated glucose disposal rate and cognitive function in older individuals

The estimated glucose disposal rate (eGDR) serves as a novel indicator of insulin resistance, which has been shown to correlate with cardiovascular disease risk; however, its relationship with cognitive function remains unclear.This article describes a cross-sectional study design based on data from the 2011-2014 National Health and Nutrition Examination Survey (NHANES). The Weighted logistic regression and the restricted cubic spline were employed to examine the relationship between eGDR and cognitive ability.The subjects were divided into two categories: the normal group and the cognitive function decline (CFD) group, based on their cognitive scores. There were significant differences in eGDR levels between the two groups(P = 0.001).After adjusting for relevant covariates, notable differences were found between eGDR and cognitive function when eGDR was expressed in both continuous and categorical data forms (P < 0.05). The stability of these findings was further confirmed through sensitivity analyses.This difference persisted in subgroups, including women, individuals with education beyond high school, moderate drinkers, and those who had not been diagnosed with stroke (P < 0.05). A restricted cubic spline revealed a non-linear relationship with an inflection point between the two (P-for-non-linear < 0.05, P-overall < 0.001). This study contributes to the understanding of the relationship between eGDR and cognitive performance by identifying a potential non-linear association.

Exploration of the association between estimated glucose disposal rate and osteoarthritis in middle-aged and older adults: An analysis of NHANES data from 2011 to 2018

Background

It is unclear how the estimated glucose disposal rate (eGDR) index relates to osteoarthritis (OA). The goal of this research is to explore the possible link between the eGDR index and the likelihood of OA development.

Methods

The study encompassed 9,051 individuals from the National Health and Nutrition Examination Survey (2011-2018). Participants were divided into quartiles according to their eGDR, calculated with the equation: eGDR (mg/kg/min) = 21.158 - (0.09 × waist circumference) - (3.407 × hypertension) - (0.551 × glycosylated hemoglobin). We assessed the independent correlation between the eGDR metric and the incidence of OA through weighted multivariate regression, stratified analysis, and threshold effect evaluation.

Results

The study encompassed 9,051 participants, who had an average eGDR of 7.09. Participants with OA had lower eGDR levels compared to those without OA (6.27 ± 0.09 vs 7.31 ± 0.06, P < 0.001). The odds ratios (ORs) for OA associated with the eGDR index in the logistic regression models were 0.87 (95% confidence interval [CI]: 0.84, 0.89) in the unadjusted model I and 0.87 (95% CI: 0.84, 0.91) in model II (adjusted for all covariates). Higher eGDR index was associated with a reduced risk of OA when compared to the lowest quartile (Q1). A restricted cubic spline analysis indicated a linear negative relationship between eGDR and OA risk.

Conclusion

An increased eGDR index is inversely related to the risk of OA. The eGDR may serve as a valuable biomarker for the detection of OA and offers a new perspective for the assessment and management of the condition.

Course and trajectories of insulin resistance, incident heart failure and all-cause mortality in nondiabetic people

BACKGROUND

In nondiabetic people, the long-term effects of insulin resistance (IR) on heart failure (HF) and all-cause mortality have not been studied.

OBJECTIVES

To examine the association between IR trajectories and incident HF and all-cause mortality in a nondiabetic population.

METHODS

We studied 7835 nondiabetic participants from the Atherosclerosis Risk in Communities (ARIC) Study. We estimated IR with several methods: Homeostatic Model Assessment-Insulin Resistance (HOMA-IR), triglyceride to high-density lipoprotein cholesterol ratio (TG/HDL-C), triglyceride glucose Index (TyG Index), and metabolic score for insulin resistance (METS-IR). The latent class analysis identified two trajectories for HOMA-IR ('low level' and 'high level'), and three trajectories for TG/HDL-C, TyG index, and METS-IR ('low level', 'moderate level', and 'high level'). Cox proportional hazard models were employed to examine the association.

RESULTS

Participants in the 'high level' group of HOMA-IR trajectory patterns were more likely to have incident HF and all-cause mortality with HRs (95% CIs) of 1.29 (1.11-1.50) and 1.31(1.19-1.44), respectively, compared to the 'low level' group. Similarly, participants in the 'moderate level' and 'high level' groups of TG/HDL-C, TyG index, and METS-IR trajectories had elevated risks of incident HF and all-cause mortality. However, no increased risk was found for all-cause mortality for men in the 'moderate level' and 'high level' group of TG/HDL-C, TyG index, and METS-IR relative to the 'low level' group.

CONCLUSIONS

Long-term moderate and high IR levels were positively associated with increased risks of incident HF for both males and females. For all-cause mortality, however, consistent associations were found only in women.

Uric acid in diabetic microvascular complications: Mechanisms and therapy

Uric acid (UA) is mainly synthesized in the liver, intestine, and vascular endothelium and excreted by the kidney (70 %) and intestine (30 %). Hyperuricemia (HUA) occurs when UA production exceeds excretion. Many studies have found that elevated UA is associated with diabetic microvascular complications (DMC), including diabetic retinopathy (DR), diabetic nephropathy (DN), and diabetic peripheral neuropathy (DPN). In addition, too high or too low UA levels will promote the occurrence and development of chronic diseases, but the relationship between UA and diabetic microvascular complications (DMC) is not clear. Therefore, the rational treatment of UA in patients with diabetes is essential. In this review, we summarize and discuss the mechanism and treatment of UA and DMC and may provide potential advice for rational drug selection.

Sarcopenia and Insulin Resistance Collective Effect on Atrial Fibrillation Risk: A Non-Diabetic Elderly Cohort Study

BACKGROUND

Appendicular skeletal muscle mass index (ASMI), a crucial indicator of sarcopenia and estimated glucose disposal rate (eGDR), a surrogate marker of insulin resistance (IR), are associated with the risk of cardiovascular diseases. However, it remains unclear whether the collective effects, including the impact of the temporal progression of ASMI and eGDR, affect atrial fibrillation (AF) risk. This study aims to elucidate the association between the collective effects of ASMI and eGDR and AF risk in the non-diabetic older population.

METHODS

A total of 8060 non-diabetic older individuals from a community-based cohort study were used to prospectively analyse the association between the collective effects of baseline ASMI and eGDR and AF risk. Among them, 7651 were eligible and used for dual-trajectory analysis of the association between dual trajectory of ASMI and eGDR and AF risk. The temporal development of ASMI and eGDR over time was determined using a dual-trajectory model. Statistical analyses involved restricted cubic splines and Fine-Gray competing risk models, adjusting for potential confounders.

RESULTS

In the prospective analysis, the hazard ratio (HR) of AF was 1.762 (95% confidence interval [CI]: 1.528-2.032) in the low ASMI group compared to the normal ASMI group in total participants. Restricted cubic splines analysis demonstrated L-shaped associations between AF risk and ASMI and eGDR, with inflection points at 7.23 kg/m2 and 7.85 mg/kg/min, respectively. Low ASMI and moderate and low eGDR exhibited a significant interplay for increasing AF risk (HR: 1.290 and 1.666, 95% CI: 1.136-1.464 and 1.492-1.861, respectively, padj. < 0.001). One-SD increment ASMI and eGDR synergistically reduced AF risk (HR: 0.896, 95% CI: 0.839-0.957, padj. < 0.001). In the dual-trajectory analysis for total participants, five distinct dual trajectories of ASMI and eGDR were identified. Group 4, characterized by moderate-stable ASMI and moderate-stable eGDR, exhibited the lowest incidence of AF (7.03 per 1000 person-years) and was used as a reference for further analyses. Group 1, characterized by high-decrease ASMI and high-decrease eGDR, had the highest AF risk (HR: 2.255, 95% CI: 1.769-2.876, padj. < 0.001), followed by Group 5, with high-decrease ASMI and low-stable eGDR (HR: 1.893, 95% CI: 1.491-2.403, padj. < 0.001) when compared to Group 4 after adjustment for potential confounders including baseline ASMI and eGDR.

CONCLUSIONS

The collective effects of ASMI and eGDR are significantly associated with AF risk in the non-diabetic older population. Collective management of skeletal muscle mass and IR might be a useful and effective management strategy for preventing and controlling AF.

Predictive value of TG/HDL-C and GFR-adjusted uric acid levels on cardiovascular mortality: the URRAH study

BACKGROUND

Insulin resistance (IR) and serum uric acid (SUA) are closely interconnected: SUA contributes to adversely affects the insulin signaling pathway and contributes to IR, while IR is a known predictor for the development of hyperuricemia. The triglyceride (TG) to high-density lipoprotein cholesterol (HDL-C) ratio has been proposed as an easily obtainable marker for IR. This research aimed to investigate the interaction between IR and glomerular filtration rate (GFR)-adjusted uricemia (SUA/GFR ratio) in determining CV risk in a large population cohort study.

METHODS

Data from 18,694 subjects were analyzed from Uric acid Right foR heArt Healt (URRAH) database. The study evaluated the association between TG/HDL-C ratio and SUA/GFR ratio, as well as their impact on the development of outcomes during the follow-up study period. The primary endpoint was CV mortality.

RESULTS

After a mean follow-up of 124 ± 64 months, 2,665 (14.2%) CV deaths occurred. The incidence of fatal and non-fatal CV events increased in parallel with the increase of TG/HDL-C quintiles. TG/HDL-C ratio showed a positive association with increasing of SUA/GFR ratio, even in non-diabetic patients. Multivariate analysis showed that the TG/HDL-C ratio increases the mortality risk even after adjustment for potential confounding factors. Finally, IR and GFR-adjusted hyperuricemia showed an additive effect on CV mortality.

CONCLUSIONS

Both IR and SUA/GFR ratio independently predict CV mortality, regardless of age, gender, BMI, diabetes, hypertension and statin use. The joint effect of the TG/HDL-C ratio and the elevated SUA/GFR ratio was greater than the presence of each single risk factor on CV mortality. This highlights the importance of monitoring these markers to better assess cardiovascular risk.

The Impact of Sodium-Glucose Co-Transporter-2 Inhibition on Insulin Resistance and Inflammation in Patients with Type 2 Diabetes: A Retrospective Study

Background and Objectives: Insulin resistance (IR) is a key factor involved in the development of type 2 diabetes (T2D). Besides its role in the pathogenesis of T2D, insulin resistance is associated with impairment of glycemic control, reduced achievement of glycemic targets, and increases in cardiovascular risk and diabetes complications, being thus a negative prognosis factor. Sodium-glucose co-transporter-2 inhibitors (SGLT2i) are therapies for T2D which demonstrated, besides glycemic control, improvements of biomarkers traditionally associated with IR and inflammation. This study aimed to evaluate the impact of SGLT2i treatment on IR and inflammation biomarkers in patients with T2D. Materials and Methods: In a retrospective study, 246 patients with T2D treated with SGLT2i for a median of 5 years were evaluated regarding IR (estimated glucose disposal rate-eGDR, triglyceride/glucose index, triglyceride/HDLc index) and inflammation biomarkers (neutrophils to lymphocyte ratio, platelets to lymphocytes ratio and C-reactive protein) before and after intervention with SGLT2i. Results: After a median 5 years of SGLT2i treatment, patients with T2D had a higher eGDR (6.07 vs. 5.24 mg/kg/min; p < 0.001), lower triglyceride/HDLc ratio (3.34 vs. 3.52, p < 0.001) and lower triglyceride/glucose index (9.23 vs. 9.58; p < 0.001). The inflammation biomarkers decreased after SGLT2i therapy: C-reactive protein (3.07 mg/L vs. 4.37 mg/L), NLR (0.68 vs. 0.72; p < 0.001), and PLR (115 vs. 122; p < 0.001). Intervention with SGLT2i also improved the biomarkers associated with diabetes complications and cardiovascular risk: HbA1c (7.1% vs. 8.4%; p < 0.001), body mass index (30.0 vs. 31.5 kg/m2; p < 0.001) and urinary albumin to creatinine ratio (4.75 vs. 11.00 mg/g; p < 0.001). Conclusions: Treatment with SGLT2i in patients with T2D leads to decreases in IR and inflammation. These mechanisms may partially explain the additional cardiovascular and renal risk reductions associated with SGLT2i therapy, alongside the improvements in glycemic control, in patients with T2D.

Association of estimated glucose disposal rate with metabolic syndrome prevalence and mortality risks: a population-based study

BACKGROUND

Insulin resistance (IR) is a central pathophysiological factor in metabolic syndrome (MetS) and an essential driver of cardiovascular disease (CVD) and mortality. The estimated glucose disposal rate (eGDR) is a reliable marker of IR and has been associated with CVD prognosis. This study aims to examine the relationship between eGDR, MetS, and their predictive roles in clinical outcomes.

METHODS

Data from the NHANES (2001-2018) were utilized, with a cross-sectional design applied to evaluate the association between eGDR and MetS prevalence, and a cohort design employed for mortality follow-up. Weighted logistic regression models were used to examine the association between eGDR and MetS. Weighted Cox proportional hazard models were applied to assess the link between eGDR and both all-cause and CVD mortality. To examine the non-linear associations between the eGDR, MetS, and mortality outcomes, restricted cubic spline (RCS) analysis was applied. Additionally, the predictive performance of eGDR, and other IR indices (TyG, HOMA-IR), for mortality was assessed using the C-statistic.

RESULTS

A robust negative association between eGDR and MetS prevalence was found, following full covariate adjustment (p < 0.001). The core findings were consistent across subgroups (all p < 0.001). Cox regression analysis indicated that in individuals with MetS, each standard deviation (SD) increment in eGDR was associated with an 11% and 18% decrement in the risk of all-cause and CVD mortality, respectively. RCS analysis displayed a non-linear association between eGDR and MetS prevalence, while a linear association between eGDR and mortality. The C-statistic showed that eGDR, compared to the TyG index and HOMA-IR, significantly improved predictive power for all-cause mortality (p = 0.007).

CONCLUSION

eGDR is strongly associated with MetS and predicts all-cause and CVD mortality in individuals with MetS. Compared to TyG and HOMA-IR, eGDR offers superior predictive value for all-cause mortality, highlighting its potential as a useful tool in clinical risk assessment.

Analyzing the impact of glycemic metabolic status on cardiovascular mortality and all-cause mortality related to the estimated glucose disposal rate: a nationwide cohort study

Objective

The Estimated Glucose Disposal Rate (eGDR) serves as a surrogate marker for insulin resistance, with numerous studies highlighting its significant prognostic value. This paper aims to analyze the impact of eGDR on cardiovascular and all-cause mortality across different glycemic metabolic statuses, including normal fasting glucose (NFG), prediabetes, and diabetes.

Methods

This study included 46,016 American adults who underwent health examinations as part of the National Health and Nutrition Examination Survey from 1999 to 2018. Multivariable Cox regression was employed to explore the relationships between eGDR and mortality rates under varying glycemic states. Additionally, Kaplan-Meier curves were used to compare the cumulative incidence of cardiovascular and all-cause mortality across different metabolic statuses. Finally, the predictive value of eGDR for mortality was assessed using receiver operating characteristic curves.

Results

During an average follow-up of 115 months, a total of 6,906 (15.01%) participants experienced all-cause mortality, with 1,798 (3.91%) deaths attributed to cardiovascular causes. Kaplan-Meier analysis revealed that higher eGDR levels were associated with gradually reduced mortality rates. After adjusting for confounders, elevated eGDR levels were protective against both cardiovascular and all-cause mortality; the protective effect was notably stronger for cardiovascular mortality [Cardiovascular mortality hazard ratio: 0.92; All-cause mortality hazard ratio: 0.94]. Further interaction tests indicated that glycemic status significantly modified the protective effect of eGDR (P-interaction<0.0001); specifically, high eGDR conferred stronger protection against cardiovascular and all-cause mortality in individuals with NFG and prediabetes compared to those with diabetes. Receiver operating characteristic analysis suggested that eGDR had superior predictive value for mortality in the NFG and prediabetic populations compared to the diabetic group.

Conclusion

eGDR is a straightforward surrogate for insulin resistance, acting as a protective factor against cardiovascular and all-cause mortality in American adults, with glycemic status modifying this protective effect. Specifically, high eGDR levels offer stronger protection in individuals with NFG and prediabetes compared to those with diabetes; moreover, eGDR appears to be more suitable for predicting mortality events in the NFG and prediabetic populations.

Body Mass Index mediates the relationship between estimated glucose disposal rate and gallstones

This study examined the relationship between gallstones and estimated glucose disposal rate (eGDR) in people in the United States and the possible mediating function of body mass index (BMI). Data came from the National Health and Nutrition Examination Survey (NHANES), conducted between 2017 and March 2020. Logistic regression, subgroup analysis, smoothed curve fitting, and causal mediation studies were among the statistical techniques used to examine the participant data. There were 595 subjects with a gallstone diagnosis out of 5,656 total. A significant negative association between eGDR and gallstones was observed by fully adjusted multivariate logistic regression analysis with an OR of 0.90 and a 95% confidence interval (CI) of (0.83, 0.98). The mediation analysis indicated that BMI accounted for 58.58% of the relationship between eGDR and the occurrence of gallstones. This study identified a substantial non-linear negative relationship between the occurrence of gallstones and eGDR levels, with BMI acting as a mediating factor. A fresh viewpoint on gallstone therapy and prevention is offered by these findings.

Association between estimated glucose disposal rate and cardiovascular diseases in patients with diabetes or prediabetes: a cross-sectional study

BACKGROUND

Insulin resistance proxy indicators are significantly associated with cardiovascular disease (CVD) and diabetes. However, the correlations between the estimated glucose disposal rate (eGDR) index and CVD and its subtypes have yet to be thoroughly researched.

METHODS

10,690 respondents with diabetes and prediabetes from the NHANES 1999-2016 were enrolled in the study. Three machine learning methods (SVM-RFE, XGBoost, and Boruta algorithms) were employed to select the most critical variables. Logistic regression models were established to evaluate the association between eGDR and CVD. We applied ROC curves, C-statistics, NRI, IDI, calibration curves, and DCA curves to assess model performance. Subgroup analyses were conducted to investigate the association among different subgroups.

RESULTS

Participants in the higher quartile showed a decreased prevalence of CVD. Multivariate logistic regression models and RCS curves demonstrated that eGDR had an independently negative linear correlation with the likelihood of CVD[Q4 vs. Q1: OR 0.24(0.18,0.32)], CAD[OR 0.81(0.78,0.85)], CHF[OR 0.81(0.76,0.86)], and stroke[0.85(0.80,0.90)]. Model evaluation showed better performance in fully adjusted models than basic models[C-statistics(Model 3 vs. Model 1): CVD(0.683 vs. 0.814), CAD(0.672 vs. 0.807), CHF(0.714 vs. 0.839) and stroke(0.660 vs. 0.790)]. The AUCs of eGDR were significantly higher than the values of other IR surrogates in the unadjusted models, and slightly higher in the fully adjusted models. Subgroup analyses indicated that the results were robust.

CONCLUSION

A lower eGDR was significantly associated with a heightened likelihood of CVD and its subtypes in diabetic and prediabetic populations. And eGDR exhibited better performance in evaluating the associations compared to other IR proxies encompassing TyG, HOMA-IR, QCUIKI, METS-IR, etc.

Association between different insulin resistance indices and all-cause mortality in patients with diabetic kidney disease: a prospective cohort study

Aim

Previous research has shown a strong association between insulin resistance (IR) and both the onset and advancement of diabetic kidney disease (DKD). This research focuses on examining the relationship between IR and all-cause mortality in individuals with DKD.

Methods

This study utilized data obtained from the National Health and Nutrition Examination Survey (NHANES), spanning the years 2001 to 2018. Insulin resistance was assessed using reliable indicators (HOMA-IR, TyG, TyG-BMI, and METS-IR). The relationship between IR indices and survival outcomes was evaluated through weighted multivariate Cox regression, Kaplan-Meier survival analysis, and restricted cubic spline (RCS) modeling. To examine non-linear associations, the log-likelihood ratio test was employed, with piecewise regression models used to establish confidence intervals and identify threshold values. Diagnostic precision and efficacy were gauged using Receiver Operating Characteristic (ROC) curves, Area Under the Curve (AUC) evaluations, and calibration plots. Moreover, to verify the consistency of our results, stratified analyses and interaction tests were conducted across variables including age, gender, Body Mass Index (BMI), hypertension, and cardiovascular status.

Results

This research involved a group of 1,588 individuals diagnosed with DKD. Over a median observation period of 74 months, 630 participants passed away. Using weighted multivariate Cox regression along with restricted cubic spline modeling, we identified non-linear associations between the four insulin resistance indices and all-cause mortality. An analysis of threshold effects pinpointed essential turning points for each IR index in this research: 1.14 for HOMA-IR, 9.18 for TyG, 207.9 for TyG-BMI, and 35.85 for METS-IR. It was noted that levels below these thresholds inversely correlated with all-cause mortality. In contrast, values above these points showed a significantly positive correlation, suggesting heightened mortality risks. The accuracy of these four IR metrics as indicators of all-cause mortality was confirmed through ROC and calibration curve analyses.

Conclusion

In patients with DKD, an L-shaped association is noted between HOMA-IR and all-cause mortality, while TyG, TyG-BMI, and METS-IR exhibit U-shaped relationships. All four IR indices show good predictive performance.

Correlation between estimated glucose disposal rate, insulin resistance, and cardiovascular mortality among individuals with metabolic syndrome: a population-based analysis, evidence from NHANES 1999-2018

BACKGROUND

Estimated glucose disposal rate (eGDR), is an index of insulin resistance. It is intimately correlated with inflammation and endothelial dysfunction, both of which are contributory factors in the pathogenesis of cardiovascular disease (CVD) and premature mortality. This study aims to explore the correlation between eGDR and both all-cause and CVD-related mortality in adults with metabolic syndrome (MetS).

METHODS

A total of 8215 subjects with MetS screened from the National Health and Nutrition Examination Survey (NHANES) during the period from 1999 to 2018 were evaluated for the predictive value of eGDR for CVD and all-cause mortality.

RESULTS

Over a median follow-up for 8.3 years, a total of 1537 all-cause deaths (18.7%) and 467 CVD-related deaths (5.7%) were recorded. Logistic regression analyses revealed a significant inverse correlation between eGDR and the risk of having CVD (OR:0.845, 95%CI:0.807-0.884, p < 0.01). Multivariate Cox regression analysis and restricted cubic splines analysis demonstrated that eGDR is non-linearly correlated with both the mortality of CVD (HR: 0.906, 95% CI: 0.850-0.967, p = 0.003) and all-cause mortality (HR: 0.944, 95% CI: 0.912-0.977, p = 0.001), with an identified inflection point at 5.918. Further subgroup analyses indicated a more pronounced correlation between eGDR and all-cause mortality in individuals under 60 years old (HR: 0.893, 95%CI:0.823-0.970) or those with obesity (HR:0.891, 95%CI:0.839-0.946). Mediation analysis revealed that neutrophil to lymphocyte ratio mediated 8.9% of the correlation between eGDR and all-cause mortality.

CONCLUSION

This study demonstrates, for the first time, that a decrease in eGDR is associated with an increased risk of all-cause and CVD mortality in adults with MetS. The eGDR indices could serve as surrogate biomarkers for monitoring patients with MetS.

Saracatinib, a Src kinase inhibitor, enhances the renoprotective effect of metformin and losartan in diabetic nephropathy

OBJECTIVE

This research assesses renoprotective effects of saracatinib (Src) in diabetic nephropathy (DN) and the potential underlying processes.

MATERIALS AND METHODS

Rats were divided into: control, DN, DN + Met + Los, DN + Met + Src, and DN + Met + Los + Src. Rats' ABP, urinary albumin, urinary nephrin, and creatinine clearance were assessed. Blood samples were collected for measuring glycaemic state parameters, renal functions, oxidative stress markers, inflammatory mediators, aldosterone, and lipid profile. Kidneys were extracted for KIM-1 and nephrin gene expression, H&E, Masson's trichrome staining, and immunohistochemical assessment.

RESULTS

Significant increases in ABP, urinary albumin and nephrin, glycaemic measurements, urea, creatinine, aldosterone, inflammatory cytokines, MDA, lipids, renal fibrosis, H scores of VEGF and TGF-β, and renal KIM-1 expression were related to DN. However, there was a significant decrease in creatinine clearance, GSH, and nephrin expression in DN group compared with control group.

DISCUSSION AND CONCLUSION

The combination of metformin (Met), losartan (Los), and Src repaired DN alterations. Adding Src to Met and Los is superior to using them alone.

Gender differences in the association between insulin resistance assessed by estimated glucose disposal rate and the risk of all-cause and cardiovascular deaths in adults without diabetes

AIM

We intended to examine the relationship between estimated glucose disposal rate (eGDR) and risks of all-cause and cardiovascular deaths in non-diabetic adults.

METHODS

38,175 participants from the National Health and Nutrition Examination Survey (1999-2018) were included, and deaths were identified through the National Death Index.

RESULTS

With a median follow-up of 9.8 years, we found that dose-response relationships between eGDR level and the risk of death differed between genders. In female participants, higher eGDR level was linearly correlated with lower risks of all-cause and cardiovascular deaths. In contrast, among male participants, there were L-shaped relationships between eGDR and risks of all-cause and cardiovascular deaths, with threshold points of 8.50 and 8.49 mg/kg/min, respectively. To the left of threshold points, eGDR was negatively linked with risks of all-cause (HR 0.91, 95 % CI 0.88-0.94, P < 0.001) and cardiovascular deaths (HR 0.87, 95 % CI 0.82-0.93, P < 0.001). After the inflection point, an increase in eGDR was not related to lower risks of all-cause and cardiovascular deaths (P > 0.05).

CONCLUSION

Higher eGDR level was associated with lower risks of all-cause and cardiovascular deaths in a linear dose-response manner among non-diabetic females, while L-shaped relationships were observed among non-diabetic males.

The predictive value of estimated glucose disposal rate for all-cause and cardiovascular mortality in the US non-diabetic population aged ≥60 years: A population-based cohort study

AIMS

This study seeks to evaluate the prognostic significance of eGDR in predicting mortality outcomes within non-diabetic older adults.

METHODS

8131 non-diabetic participants aged ≥60 years from the National Health and Nutrition Examination Survey (2001-2018) was included in this study. eGDR was calculated as: eGDR (mg/kg/min) = 21.158 - [0.09 × waist circumference (cm)] - [3.407 × Hypertension (Yes = 1/No = 0)] - [0.551 × HbA1c (%)]. Weighted Cox proportional hazards models, cumulative hazard curves, restricted cubic spline (RCS), and threshold effects analyses were performed to explore the relationship between eGDR and mortality outcomes. Subgroup analyses and mediation effects analyses were conducted.

RESULTS

2566 all-cause deaths and 689 cardiovascular deaths were recorded. Lower eGDR was associated with higher all-cause (HR = 0.76, 95 % CI: 0.63-0.91) and cardiovascular mortality (HR = 0.56, 95 % CI: 0.40-0.80). Inflection points were identified through RCS curve analyses, and the threshold effect was significant. The eGDR-mortality association remained consistent across subgroups. Mediation analyses showed that neutrophil to high-density lipoprotein cholesterol ratio mediated the association.

CONCLUSIONS

Lower eGDR levels are linked to higher risk of both all-cause and cardiovascular mortality in non-diabetic older adults, suggesting its potential utility for risk assessment among this population.

Association between estimated glucose disposal rate and kidney function decline in different glucose tolerance statuses from the 4 C study

AIMS

To investigate the association between estimated glucose disposal rate (eGDR) and kidney function decline among populations with different glucose tolerance statuses including normal glucose tolerance (NGT), prediabetes, and diabetes.

METHODS

The present study analyzed 5,069 participants from a cohort study. The association between eGDR and kidney function decline was assessed using binary logistic regression. Restricted cubic splines (RCS) analyses were also performed to investigate the dose-dependent associations.

RESULTS

During up to 5 years of follow-up, 116 (2.30%) individuals experienced kidney function decline. Binary logistic regression showed that an increased level of eGDR was associated with decreased risk of kidney function decline after full adjustment, in all participants (Q4 vs. Q1 HR 0.13, 95% CI 0.05-0.30, p = 0.001), prediabetes (Q4 vs. Q1HR 0.11, 95% CI 0.01-0.44, p = 0.007), and diabetes (Q4 vs. Q1 HR 0.06, 95% CI 0.00-0.37, p = 0.012), but not in those with NGT. RCS analyses suggested dose-dependent relationships of eGDR with the risk of kidney function decline in all participants (L-shaped curve) and those with prediabetes (inverted U-shaped curve) and diabetes (L-shaped curve).

CONCLUSIONS

The association between elevated baseline eGDR and reduced risk of kidney function decline was significant in participants with prediabetes and diabetes, but not in those with NGT. These dose-dependent associations may have important implications for the assessment of high-risk patients by healthcare professionals and may lead to the development of more tailored and effective prevention strategies.

Impaired insulin sensitivity measured by estimated glucose disposal rate is associated with decreased myocardial mechano-energetic efficiency in non-diabetic individuals

BACKGROUND AND AIMS

Impaired myocardial mechano-energetic efficiency (MEE) has been associated with cardiac insulin resistance measured by dynamic positron emission tomography (PET) with 18F-fluorodeoxyglucose (18F-FDG) combined with euglycemic-hyperinsulinemic clamp. Estimate glucose disposal rate (eGDR) index has a good correlation with whole-body insulin sensitivity. It remains unsettled whether eGDR index is a suitable proxy of cardiac insulin sensitivity as well as its association with myocardial MEE. The aims of this study were: 1) to compare eGDR index with HOMA-IR, QUICKI and FIRI indexes for association with myocardial glucose metabolic rate (MrGlu); and 2) to determine the association of eGDR index with myocardial MEE.

METHODS

We evaluated MrGlu using PET with 18F-FDG combined with euglycemic-hyperinsulinemic clamp in 50 individuals without history of coronary heart disease. Myocardial MEE per gram of left ventricular mass (MEEi) was measured in 1181 subjects by echocardiography. eGDR (mg kg-1/min) was calculated as: 21.158 - (0.09 × waist circumference in cm) - (3.407 × hypertension, 1 = yes 0 = no) - (0.551 × HbA1c%).

RESULTS

eGDR index was more strongly associated with myocardial MrGlu than HOMA-IR, QUICKI, and FIRI indexes (r = -0.662, r = -0.492, r = 0.570, and r = -0.492, respectively). Individuals in the lower tertiles of eGDR exhibited a significant reduction of MEEi as compared to those in the highest tertile (P < 0.001). In a stepwise multivariate linear regression analysis eGDR index was the major determinant of MEEi independently of well-established cardio-metabolic risk factors.

CONCLUSIONS

These data suggest that the eGDR index may be a useful marker to identifying individuals at high cardiovascular risk.

Evaluation of Estimated Glucose Disposal Rate with Neutrophil-to-Lymphocyte Ratio Integrated for Prognosticating Adverse Cardiovascular and Cerebrovascular Events and Risk Stratification Among Acute Coronary Syndrome with Type 2 Diabetes Mellitus Following Percutaneous Coronary Intervention

Objective

This research aimed to address the critical need for effective prognostic tools in patients with acute coronary syndrome (ACS) and type 2 diabetes mellitus (T2DM) undergoing percutaneous coronary intervention (PCI) by exploring the potential significance of integrating estimated glucose disposal rate (eGDR) and neutrophil-to-lymphocyte ratio (NLR).

Methods

Major adverse cardiovascular and cerebrovascular events (MACCE) were the primary endpoint. Log rank test was conducted to compare the Kaplan-Meier curves across the overall follow-up period, and multivariate Cox regression was used to investigate the association between the eGDR/NLR and MACCE.

Results

One hundred fifty-four patients (9.5%) experienced MACCE including 15 cardiac deaths, 97 nonfatal MI, 120 TVR, and 10 strokes. Patients were distributed into low and high eGDR/NLR groups (lower eGDR [eGDR-L] group, higher eGDR [eGDR-H] group, lower NLR [NLR-L] group, and higher NLR [NLR-H] group) based on the median value of eGDR and NLR, further divided into four groups: eGDR-L + NLR-L, eGDR-H + NLR-L, eGDR-L + NLR-H, and eGDR-H + NLR-H. eGDR-L + NLR-H group exhibited significantly higher risks of MACCE (17.4%), compared to another three groups. An independent correlation between eGDR/NLR and MACCE was demonstrated by Cox regression analysis, establishing if the eGDR and NLR was treated as a continuous or categorical variable. Compared to eGDR-H + NLR-L group, patients in eGDR-L + NLR-H group had the uppermost MACCE risk (HR: 5.201; 95% CI 2.764-7.786; P < 0.001). A linear relationship between eGDR/ NLR and MACCE was showed by restricted cubic spline curves. Incorporating the eGDR and NLR toward the baseline risk model developed the precision of forecasting MACCE (baseline risk model-AUC: 0.611 vs baseline risk model + eGDR + NLR-AUC: 0.695, P < 0.001).

Conclusion

Combining eGDR with NLR can be utilized to forecast long-term MACCE and substantially improve the accuracy of risk stratification in ACS patients with T2DM following PCI.

Discussion on the treatment of diabetic kidney disease based on the "gut-fat-kidney" axis

Diabetic kidney disease is the main cause of end-stage renal disease, and its prevention and treatment are still a major clinical problem. The human intestine has a complex flora of hundreds of millions of microorganisms, and intestinal microorganisms, and their derivatives are closely related to renal inflammatory response, immune response, and material metabolism. Brown adipose tissue is the main part of adaptive thermogenesis. Recent studies have shown that activating brown fat by regulating intestinal flora has good curative effects in diabetic kidney disease-related diseases. As an emerging medical concept, the "gut-fat-kidney" axis has received increasing attention in diabetic kidney disease and related diseases. However, the specific mechanism involved needs further study. A new theoretical basis for the prevention and treatment of diabetic kidney disease is presented in this article, based on the "gut-fat-kidney" axis.

Association between estimated glucose disposal rate and female infertility: a cross-sectional study

Background

Insulin resistance (IR) can lead to infertility in women. The primary objective of this research was to examine how estimated glucose disposal rate (eGDR) correlates with infertility in women, assessing its validity as an indicator of IR.

Methods

Data from the National Health and Nutrition Examination Survey spanning 2013 to 2018 were analyzed in this study. In order to investigate the correlation between eGDR and the prevalence of female infertility, this study used a combination of weighted multivariate regression analysis, restricted cubic spline (RCS) analysis, subgroup analyses, sensitive analysis, and receiver operating characteristic (ROC) curves.

Results

This study enrolled 2541 women, with an average age of (32.52 ± 0.23) years. The overall infertility rate was 14.27%. A negative relationship was observed between eGDR levels and female infertility. Each increment of one unit in eGDR was linked to a 14% reduction in infertility incidence (OR = 0.86, 95% CI 0.80-0.94). RCS analysis revealed a nonlinear, inverse correlation between eGDR and female infertility. Subgroup analyses indicated that age influenced the association between eGDR and female infertility. The ROC curve suggested that eGDR was significantly better than HOMA-IR in predicting infertility [eGDR: 0.632 (95% CI: 0.603, 0.660) vs. HOMA-IR: 0.543 (95% CI: 0.514, 0.572)].

Conclusion

There was an observed association where lower eGDR levels were linked with higher rates of female infertility. These results emphasize the significance of implementing measures to manage IR to protect women's reproductive health.

Estimated glucose disposal rate is correlated with increased depression: a population-based study

BACKGROUND

Recent studies have identified a correlation between insulin resistance (IR) and depression. This study aims to explore the correlation between estimated glucose disposal rate (eGDR), a practical and noninvasive measure for assessing IR, and depression in the general population.

METHODS

In this population-based cross-sectional study, data from 28,444 adults aged 18 years old or older in the NHANES during the period from 1999 to 2018 were analyzed. The correlation between eGDR and depression was examined through multivariate logistic regression analyses, subgroup analyses, restricted cubic spline, and interaction tests. Furthermore, a mediation analysis was conducted to elucidate the role of the atherogenic index of plasma (AIP) in mediating the effect of eGDR on depression.

RESULTS

Multivariate logistic regression analysis and restricted cubic splines analysis indicated that eGDR can exhibit a linearly correlation with depression (OR = 0.913; 95% CI: 0.875, 0.953). Subjects in eGDR6-8 and eGDR > 8 groups had a decrease risk of depression as 25.4% and 41.5% than those in the eGDR < 4 group. This negative correlation was more pronounced in those with obesity. Mediation analysis indicated that AIP mediated 9.6% of the correlation between eGDR and depression.

CONCLUSIONS

eGDR was linear negatively correlated with depression, with AIP playing a mediating role. This study provides a novel perspective on the mechanism connecting IR to depression. Managing IR and monitoring AIP may contribute to alleviating depression.

Changes in the estimated glucose disposal rate and incident cardiovascular disease: two large prospective cohorts in Europe and Asia

BACKGROUND AND AIMS

Previous study found that estimated glucose disposal rate (eGDR) was significantly associated with cardiovascular disease (CVD). However, little is known about the change in eGDR over time and its association with the development of CVD. The aim of this study was to investigate the association of change in eGDR with CVD risk.

METHODS

This study used data of two prospective cohorts: UK Biobank and China Health and Retirement Longitudinal Study (CHARLS) with two measurements of eGDR. Changes in the eGDR were classified using K‑means clustering analysis, and the cumulative eGDR was also calculated. Cox proportional hazard models were used to calculate the hazard ratio (HR) and 95% confidence interval (95% CI) after adjusting for potential confounders.

RESULTS

A total of 11,682 individuals from the UK Biobank, and 4,974 individuals from the CHARLS were included. The median follow-up periods were 9.7 years in the UK Biobank and 3.0 years in the CHARLS. Compared with persistently high level of eGDR (class 1), individuals with low level increasing (class 3) and persistently low level of eGDR (class 4) showed elevated risks of incident CVD in both UK Biobank (HR = 2.79, 95% 2.15-3.62 for class 3; HR = 3.19, 95% 2.50-4.08 for class 4) and CHARLS (HR = 1.66, 95% 1.29-2.13 for class 3; HR = 1.69, 95% 1.34-2.14 for class 4). In addition, lower level of cumulative eGDR were associated with elevated risks of incident CVD. The dose-response curve between cumulative eGDR and CVD risk showed a negative linear relationship.

CONCLUSION

Different changes in eGDR level are associated with different risks of incident CVD. Dynamic monitoring of eGDR level is of significant importance for the CVD prevention and treatment.

Management of inflammaging in kidney diseases: focusing on the current investigational drugs

INTRODUCTION

To improve kidney disease treatments, it is crucial to understand how inflammaging affects patients´ longevity. We could potentially slow down kidney disease progression and enhance longevity by targeting specific pathways involved in inflammaging with potential drugs.

AREAS OF COVERED

This review offers an updated overview of 'anti-inflammaging' drugs currently in the kidney disease research pipeline, as well as those with potential for future therapeutic use. Furthermore, these drugs are categorized according to their mechanisms, including targeting inflammation, immune and metabolic regulation, oxidative stress, senescence, and autophagy, as demonstrated in preclinical and early clinical trials. Additionally, the review provides insights into key challenges and opinions for future advancements in this field.

EXPERT OPINION

We reviewed recent advancements in applying different therapies to mitigate inflammaging in kidney diseases. We underscore the need for continued research to elucidate the complex pathways underlying inflammaging, which will be essential for the development of more precise and effective treatments. As research in this field advances, several emerging drugs appear promising for future investigation. While current findings are encouraging, further clinical studies are required to validate the therapeutic potential of these agents in kidney diseases, ultimately paving the way for more targeted and efficacious interventions.

Estimated glucose disposal rate and risk of cardiovascular disease and mortality in U.S. adults with prediabetes: a nationwide cross-sectional and prospective cohort study

AIMS

Estimated glucose disposal rate (eGDR), a noninvasive and convenient measure of insulin resistance, has been demonstrated to be associated with mortality in both type 1 and type 2 diabetes. We aimed to explore whether eGDR is associated with cardiovascular disease (CVD) risk and mortality in prediabetic adults.

METHODS

A nationwide population-based cohort of prediabetic individuals from the National Health and Nutrition Examination Survey 1999-2018 with available data on eGDR was included and categorized into eGDR ≥ 8 (reference), 6-7.99, 4-5.99, and < 4 mg/kg/min groups. Cox proportional hazards model was used to estimate the associations of eGDR with mortality.

RESULTS

A total of 4725 prediabetic adults, 60.12% men, mean age 48 years were included. The odds ratio and 95% confidence interval (CI) for CVD risk were 1.74 (1.08-2.78), 2.90 (1.79-4.67), and 4.58 (2.15-9.76) for the eGDR 6-7.99, 4-5.99, and < 4 mg/kg/min groups, respectively, compared with the reference group. There were 410 deaths (116 CVD-related) during a median follow-up of 107 months in 4,332 participants without baseline CVD. The hazard ratios and 95%CI for the eGDR 6-7.99, 4-5.99, and < 4 mg/kg/min groups were 1.70 (1.23-2.35), 2.01 (1.45-2.77), and 1.84 (1.11-3.04), respectively, for all-cause mortality (P for trend < 0.0001), and 3.84 (2.04-7.21), 4.01 (2.01-8.00), and 2.88 (1.03-8.06), respectively, for CVD mortality (P for trend = 0.01). Smoking status significantly modified the associations between eGDR and all-cause or CVD mortality.

CONCLUSIONS

Increased insulin resistance, as indicated by a lower eGDR, is associated with increased risks of all-cause and CVD mortality in U.S. prediabetic adults.

Relationship between degree of risk factor control and all-cause mortality in individuals with type 2 diabetes: A prospective cohort study

AIMS

To assess whether and to what extent excess risk of all-cause death is reduced in individuals with type 2 diabetes by achieving optimal control of traditional cardiovascular risk factors.

METHODS

This observational, prospective, cohort study enrolled 15,773 Caucasian patients in 19 Italian centres in 2006-2008. Participants were stratified according to the number of the following risk factors outside target: haemoglobin A1c, blood pressure, micro/macroalbuminuria, current smoking, LDL cholesterol, and triglycerides. All-cause mortality was retrieved for 15,656 patients (99.3 %) on 31 October 2015.

RESULTS

Age-adjusted mortality rates and hazard ratios were significantly higher in the whole RIACE cohort (by ∼20 %) and in patients with (by ∼100 %) but not in those without prior cardiovascular disease (CVD), as compared with the coeval Italian general population. In all patients and in those without prior CVD, the relationship with mortality according to the number of risk factors outside target was J-shaped, an effect that was attenuated after either excluding "overtreated " patients, i.e., those with haemoglobin A1c ≤6.0 % on anti-hyperglycaemic agents causing hypoglycaemia and/or systolic blood pressure ≤120 mmHg on anti-hypertensive agents, or adjusting for "overtreatment". Conversely, in patients with prior CVD, mortality remained higher than in the general population in all categories and increased progressively from +70 % to +314 %, without J-effect.

CONCLUSIONS

In patients with type 2 diabetes, optimal treatment of traditional cardiovascular risk factors completely eliminated the excess mortality risk versus the general population, provided that they were not "overtreated". However, this effect was observed only in participants without history of CVD.

TRIAL REGISTRATION

ClinicalTrials.gov, NCT00715481, retrospectively registered 15 July 2008.

Estimated glucose disposal rate for predicting cardiovascular events and mortality in patients with non-diabetic chronic kidney disease: a prospective cohort study

BACKGROUND

Evidence suggests that insulin resistance (IR) is an autonomous risk factor for cardiovascular disease (CVD). Nevertheless, the association between estimated glucose disposal rate (eGDR), a novel indicator of IR, and incident CVD and mortality in chronic kidney disease (CKD) patients without diabetes remains uncertain.

METHODS

The study included 19,906 participants from the UK Biobank who had an estimated glomerular filtration rate (eGFR) < 60 ml/min/1.73m2 or a urinary albumin-to-creatinine ratio (UACR) ≥ 30 mg/g and no history of CVD and diabetes. Individuals were divided into three categories based on tertiles of eGDR. The outcome was a composite CVD (coronary heart disease (CHD) and stroke) and mortality (all-cause, non-accidental, and cardiovascular mortality). Furthermore, a cohort of 1,600 individuals from the US National Health and Nutrition Examination Survey (NHANES) was applied to validate the association between eGDR and mortality. The Cox proportional hazards regression models were used to examine the association between eGDR and event outcomes.

RESULTS

During a follow-up of around 12 years, 2,860 CVD, 2,249 CHD, 783 stroke, 2,431 all-cause, 2,326 non-accidental and 492 cardiovascular deaths were recorded from UK Biobank. Higher eGDR level was not only associated with lower risk of CVD (hazard ratio [HR] 0.641, 95% confidence interval [CI] 0.559-0.734), CHD (HR 0.607, 95% CI 0.520-0.709), stroke (HR 0.748, 95% CI 0.579-0.966), but also related to reduced risk of all-cause (HR 0.803, 95% CI 0.698-0.923), non-accidental (HR 0.787, 95% CI 0.682-0.908), and cardiovascular mortality (HR 0.592, 95% CI 0.423-0.829). Validation analyses from NHANES yielded consistent relationship on mortality.

CONCLUSIONS

In these two large cohorts of CKD patients without DM, a higher eGDR level was associated with a decreased risk of CVD and mortality.

The Association Between Triglyceride Glucose-Body Mass Index and Kidney Impairment in Patients with Type 2 Diabetes Mellitus

Purpose

Insulin resistance is associated with kidney impairment in patients with type 2 diabetes mellitus (T2DM). The triglyceride glucose-body mass index (TyG-BMI), which combines the TyG index with body mass index (BMI), has received significant attention as a tool for evaluating insulin resistance. Thus, the aim of this study was to explore the association between TyG-BMI and kidney impairment in patients with type 2 diabetes mellitus (T2DM).

Patients and Methods

The cross-sectional analysis included 1080 patients with T2DM, and data were collected retrospectively. TyG-BMI was calculated by fasting blood glucose, triglyceride, and body mass index.

Results

TyG-BMI was significantly higher in T2DM patients with albuminuria than those without albuminuria (232.16 [206.52-268.02] vs 229.83 [206.11-255.64], p =0.023). T2DM patients with chronic kidney disease (CKD) showed a significantly higher value of TyG-BMI compared with those without CKD (232.23 [206.46-268.28] vs 229.73 [206.11-255.49], p=0.014). Correlation analysis showed a significantly positive association between TyG-BMI and metabolic parameters including BMI (r = 0.866, p < 0.001), TG (r = 0.630, p < 0.001), TC (r = 0.119, p < 0.001), HDL-C (r = -0.374, p < 0.001), FBG (r = 0.297, p < 0.001), and HbA1c (r = 0.116, p < 0.001) in patients with T2DM. The binary logistic regression analysis found that TyG-BMI was an independent factor for albuminuria (OR = 1.004, 95% CI: 1.001-1.008, p = 0.010) and CKD (OR = 1.005, 95% CI: 1.001-1.008, p = 0.005) in patients with T2DM respectively.

Conclusion

The study suggests that TyG-BMI is associated with kidney impairment in patients with T2DM. Given that TyG-BMI is a novel parameter of insulin resistance, the study results indicates that clinicians should pay close attention to screening for kidney impairment in T2DM patients with insulin resistance.

Clinical application of cluster analysis in patients with newly diagnosed type 2 diabetes

AIMS

Early prevention and treatment of type 2 diabetes mellitus (T2DM) is still a huge challenge for patients and clinicians. Recently, a novel cluster-based diabetes classification was proposed which may offer the possibility to solve this problem. In this study, we report our performance of cluster analysis of individuals newly diagnosed with T2DM, our exploration of each subtype's clinical characteristics and medication treatment, and the comparison carried out concerning the risk for diabetes complications and comorbidities among subtypes by adjusting for influencing factors. We hope to promote the further application of cluster analysis in individuals with early-stage T2DM.

METHODS

In this study, a k-means cluster algorithm was applied based on five indicators, namely, age, body mass index (BMI), glycosylated hemoglobin (HbA1c), homeostasis model assessment-2 insulin resistance (HOMA2-IR), and homeostasis model assessment-2 β-cell function (HOMA2-β), in order to perform the cluster analysis among 567 newly diagnosed participants with T2DM. The clinical characteristics and medication of each subtype were analyzed. The risk for diabetes complications and comorbidities in each subtype was compared by logistic regression analysis.

RESULTS

The 567 patients were clustered into four subtypes, as follows: severe insulin-deficient diabetes (SIDD, 24.46%), age-related diabetes (MARD, 30.86%), mild obesity-related diabetes (MOD, 25.57%), and severe insulin-resistant diabetes (SIRD, 20.11%). According to the results of the oral glucose tolerance test (OGTT) and biochemical indices, fasting blood glucose (FBG), 2-hour postprandial blood glucose (2hBG), HbA1c, total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C) and triglyceride-glucose index (TyG) were higher in SIDD and SIRD than in MARD and MOD. MOD had the highest fasting C-peptide (FCP), 2-hour postprandial C-peptide (2hCP), fasting insulin (FINS), 2-hour postprandial insulin (2hINS), serum creatinine (SCr), and uric acid (UA), while SIRD had the highest triglycerides (TGs) and TyG-BMI. Albumin transaminase (ALT) and albumin transaminase (AST) were higher in MOD and SIRD. As concerms medications, compared to the other subtypes, SIDD had a lower rate of metformin use (39.1%) and a higher rate of α-glucosidase inhibitor (AGI, 61.7%) and insulin (74.4%) use. SIRD showed the highest frequency of use of sodium-glucose cotransporter-2 inhibitors (SGLT-2i, 36.0%) and glucagon-like peptide-1 receptor agonists (GLP-1RA, 19.3%). Concerning diabetic complications and comorbidities, the prevalence of diabetic kidney disease (DKD), cardiovascular disease (CVD), non-alcoholic fatty liver disease (NAFLD), dyslipidemia, and hypertension differed significantly among subtypes. Employing logistic regression analysis, after adjusting for unmodifiable (sex and age) and modifiable related influences (e.g., BMI, HbA1c, and smoking), it was found that SIRD had the highest risk of developing DKD (odds ratio, OR = 2.001, 95% confidence interval (CI): 1.125-3.559) and dyslipidemia (OR = 3.550, 95% CI: 1.534-8.215). MOD was more likely to suffer from NAFLD (OR = 3.301, 95%CI: 1.586-6.870).

CONCLUSIONS

Patients with newly diagnosed T2DM can be successfully clustered into four subtypes with different clinical characteristics, medication treatment, and risks for diabetes-related complications and comorbidities, the cluster-based diabetes classification possibly being beneficial both for prevention of secondary diabetes and for establishment of a theoretical basis for precision medicine.

The additive effect of the triglyceride-glucose index and estimated glucose disposal rate on long-term mortality among individuals with and without diabetes: a population-based study

BACKGROUND

The triglyceride-glucose (TyG) index and estimated glucose disposal rate (eGDR), which are calculated using different parameters, are widely used as markers of insulin resistance and are associated with cardiovascular diseases and prognosis. However, whether they have an additive effect on the risk of mortality remains unclear. This study aimed to explore whether the combined assessment of the TyG index and eGDR improved the prediction of long-term mortality in individuals with and without diabetes.

METHODS

In this cross-sectional and cohort study, data were derived from the National Health and Nutrition Examination Survey (NHANES) 2001-2018, and death record information was obtained from the National Death Index. The associations of the TyG index and eGDR with all-cause and cardiovascular mortality were determined by multivariate Cox regression analysis and restricted cubic splines.

RESULTS

Among the 17,787 individuals included in the analysis, there were 1946 (10.9%) all-cause deaths and 649 (3.6%) cardiovascular deaths during a median follow-up of 8.92 years. In individuals with diabetes, the restricted cubic spline curves for the associations of the TyG index and eGDR with mortality followed a J-shape and an L-shape, respectively. The risk of mortality significantly increased after the TyG index was > 9.04 (all-cause mortality) or > 9.30 (cardiovascular mortality), and after eGDR was < 4 mg/kg/min (both all-cause and cardiovascular mortality). In individuals without diabetes, the association between eGDR and mortality followed a negative linear relationship. However, there was no association between the TyG index and mortality. Compared with individuals in the low TyG and high eGDR group, those in the high TyG and low eGDR group (TyG > 9.04 and eGDR < 4) showed the highest risk for all-cause mortality (hazard ratio [HR] = 1.592, 95% confidence interval [CI] 1.284-1.975) and cardiovascular mortality (HR = 1.683, 95% CI 1.179-2.400) in the overall population. Similar results were observed in individuals with and without diabetes.

CONCLUSIONS

There was a potential additive effect of the TyG index and eGDR on the risk of long-term mortality in individuals with and without diabetes, which provided additional information for prognostic prediction and contributed to improving risk stratification.

Non-linear association of triglyceride-glucose index with cardiovascular and all-cause mortality in T2DM patients with diabetic kidney disease: NHANES 2001-2018 retrospective cohort study

BACKGROUND

The triglyceride glucose (TyG) index is a cutting-edge and highly effective marker of insulin resistance, a crucial factor in the development and exacerbation of diabetic kidney disease (DKD). To date, there has been limited research on how the triglyceride-glucose (TyG) index affects the outlook for patients suffering from DKD.

METHODS

In this multicenter retrospective cohort study, the analysis recruited 2,203 DKD patients from the National Health and Nutrition Examination Survey (NHANES) dataset, which covers the US from 2001 to 2018. The research applied a Cox proportional hazards model with multiple variables to investigate the association of the TyG index with mortality outcomes. Restricted cubic splines (RCS) and methods for analyzing threshold effects were employed to identify possible non-linear relationships.

RESULTS

Over nearly 19 years of follow-up, this study captured data on 753 all-cause and 231 cardiovascular disease-specific fatalities. Sophisticated statistical methods, including RCS and smoothing curve adjustments via penalized splines, helped identify distinctive patterns: The baseline TyG index was observed to have a U-shaped pattern related to overall mortality and an L-shape with cardiovascular diseases(CVD) mortality among individuals with DKD. Notably, TyG index below 9.15 for overall mortality and 9.27 for CVD mortality were linked to reduced death rates (HR = 0.65, 95% CI = 0.52-0.82 for all-cause; HR = 0.58, 95% CI = 0.43-0.83 for CVD). On the other hand, TyG index exceeding these benchmarks (greater than 9.15 for all-cause and 9.27 for CVD) correlated with increased all-cause mortality risks (HR = 1.21, 95% CI = 1.02-1.43) and showed a non-significant change in CVD mortality risks (HR = 1.07, 95% CI = 0.83-1.38).

CONCLUSIONS

This study emphasizes the non-linear linkage involving the TyG index and death rates due to CVD and other factors in patients with DKD, demonstrating its effectiveness in estimating potential adverse events within this demographic.

Insulin resistance and its relationship with long-term exposure to ozone: Data based on a national population cohort

The relationship of ozone (O3), particularly the long-term exposure, with impacting metabolic homeostasis in population was understudied and under-recognised. Here, we used data from ChinaHEART, a nationwide, population-based cohort study, combined with O3 and PM2.5 concentration data with high spatiotemporal resolution, to explore the independent association of exposure to O3 with the prevalence of insulin resistance (IR). Among the 271 540 participants included, the crude prevalence of IR was 39.1%, while the age and sex standardized prevalence stood at 33.0%. Higher IR prevalence was observed with each increase of 10.0 μg/m3 in long-term O3 exposure, yielding adjusted odds ratios (OR) of 1.084 (95% CI: 1.079-1.089) in the one-pollutant model and 1.073 (95% CI: 1.067-1.079) in the two-pollutant model. Notably, a significant additive interaction between O3 and PM2.5 on the prevalence of IR was observed (P for additive interaction < 0.001). Our main findings remained consistent and robust in the sensitivity analyses. Our study suggests long-term exposure to O3 was independently and positively associated with prevalence of IR. It emphasized the benefits of policy interventions to reduce O3 and PM2.5 exposure jointly, which could ultimately alleviate the health and economic burden related to DM.

Prognostic Implications of Insulin Resistance in Heart Failure in Japan

Diabetes mellitus (DM) is a major risk and prognostic factor for heart failure (HF). Insulin resistance (IR) is an important component of DM, but the relationship between IR and HF prognosis has not yet been established across a wide variety of HF populations. We retrospectively evaluated the relationship between IR and clinical outcomes of HF patients at our hospital between 2017 and 2021. IR was defined as a homeostatic model assessment of IR (HOMA-IR) index ≥ 2.5, calculated from fasting blood glucose and insulin concentrations. The primary outcome was a composite of all-cause death and hospitalisation for HF (HHF). Among 682 patients included in the analyses, 337 (49.4%) had IR. The median age was 70 [interquartile range (IQR): 59-77] years old, and 66% of the patients were men. Among the patients, 41% had a left ventricular ejection fraction below 40%, and 32% had DM. The median follow-up period was 16.5 [IQR: 4.4-37.3] months. IR was independently associated with the primary outcome (HR: 1.91, 95% CI: 1.39-2.62, p < 0.0001), death (hazard ratio [HR]: 1.86, 95% confidence interval [CI]: 1.28-2.83, p < 0.01), and HHF (HR: 1.91, 95% CI: 1.28-2.83, p < 0.01). HOMA-IR is an independent prognostic factor of HF in a wide variety of HF populations.

Association between estimated glucose disposal rate and atrial fibrillation recurrence in patients undergoing radiofrequency catheter ablation: a retrospective study

OBJECTIVE

Previous studies have shown a clear link between insulin resistance (IR) and an elevated risk of atrial fibrillation (AF). However, the relationship between the estimated glucose disposal rate (eGDR), which serves as a marker for IR, and the risk of AF recurrence after radiofrequency catheter ablation (RFCA) remains uncertain. Therefore, this study aimed to examine the potential association between the eGDR and the risk of AF recurrence following RFCA.

METHODS

This retrospective study was conducted at Nanchang University Affiliated Second Hospital. The study enrolled 899 patients with AF who underwent RFCA between January 2015 and January 2022. The formula used to calculate the eGDR was as follows: 19.02 - (0.22 * body mass index) - (3.26 * hypertension) - (0.61 * HbA1c). Cox proportional hazard regression models and exposure-effect curves were used to explore the correlation between the baseline eGDR and AF recurrence. The ability of the eGDR to predict AF recurrence was evaluated using the area under the receiver operating characteristic curve (AUROC).

RESULTS

The study observed a median follow-up period of 11.63 months, during which 296 patients experienced AF recurrence. K‒M analyses revealed that the cumulative incidence AF recurrence rate was significantly greater in the group with the lowest eGDR (log-rank p < 0.01). Participants with an eGDR ≥ 8 mg/kg/min had a lower risk of AF recurrence than those with an eGDR < 4 mg/kg/min, with a hazard ratio (HR) of 0.28 [95% confidence interval (CI) 0.18, 0.42]. Additionally, restricted cubic spline analyses demonstrated a linear association between the eGDR and AF recurrence (p nonlinear = 0.70). The area under the curve (AUC) for predicting AF recurrence using the eGDR was 0.75.

CONCLUSIONS

The study revealed that a decrease in the eGDR is associated with a greater AF recurrence risk after RFCA. Hence, the eGDR could be used as a novel biomarker for assessing AF recurrence risk.

Insulin resistance assessed by estimated glucose disposal rate and risk of incident cardiovascular diseases among individuals without diabetes: findings from a nationwide, population based, prospective cohort study

BACKGROUND

Recent studies have suggested that insulin resistance (IR) contributes to the development of cardiovascular diseases (CVD), and the estimated glucose disposal rate (eGDR) is considered to be a reliable surrogate marker of IR. However, most existing evidence stems from studies involving diabetic patients, potentially overstating the effects of eGDR on CVD. Therefore, the primary objective of this study is to examine the relationship of eGDR with incidence of CVD in non-diabetic participants.

METHOD

The current analysis included individuals from the China Health and Retirement Longitudinal Study (CHARLS) who were free of CVD and diabetes mellitus but had complete data on eGDR at baseline. The formula for calculating eGDR was as follows: eGDR (mg/kg/min) = 21.158 - (0.09 × WC) - (3.407 × hypertension) - (0.551 × HbA1c) [WC (cm), hypertension (yes = 1/no = 0), and HbA1c (%)]. The individuals were categorized into four subgroups according to the quartiles (Q) of eGDR. Crude incidence rate and hazard ratios (HRs) with 95% confidence intervals (CIs) were computed to investigate the association between eGDR and incident CVD, with the lowest quartile of eGDR (indicating the highest grade of insulin resistance) serving as the reference. Additionally, the multivariate adjusted restricted cubic spine (RCS) was employed to examine the dose-response relationship.

RESULTS

We included 5512 participants in this study, with a mean age of 58.2 ± 8.8 years, and 54.1% were female. Over a median follow-up duration of 79.4 months, 1213 incident CVD cases, including 927 heart disease and 391 stroke, were recorded. The RCS curves demonstrated a significant and linear relationship between eGDR and all outcomes (all P for non-linearity > 0.05). After multivariate adjustment, the lower eGDR levels were founded to be significantly associated with a higher risk of CVD. Compared with participants with Q1 of eGDR, the HRs (95% CIs) for those with Q2 - 4 were 0.88 (0.76 - 1.02), 0.69 (0.58 - 0.82), and 0.66 (0.56 - 0.79). When assessed as a continuous variable, per 1.0-SD increase in eGDR was associated a 17% (HR: 0.83, 95% CI: 0.78 - 0.89) lower risk of CVD, with the subgroup analyses indicating that smoking status modified the association (P for interaction = 0.012). Moreover, the mediation analysis revealed that obesity partly mediated the association. Additionally, incorporating eGDR into the basic model considerably improve the predictive ability for CVD.

CONCLUSION

A lower level of eGDR was found to be associated with increased risk of incident CVD among non-diabetic participants. This suggests that eGDR may serve as a promising and preferable predictor and intervention target for CVD.

Estimated glucose disposal rate predicts the risk of diabetic peripheral neuropathy in type 2 diabetes: A 5-year follow-up study

BACKGROUND

Insulin resistance is associated with chronic complications of diabetes, including diabetic peripheral neuropathy (DPN). Estimated glucose disposal rate (eGDR), calculated by the common available clinical factors, was proved to be an excellent tool to measure insulin resistance in large patient population. Few studies have explored the association between eGDR and DPN longitudinally. Therefore, we performed the current study to analyze whether eGDR could predict the risk of DPN.

METHODS

In this prospective study, 366 type 2 diabetes (T2DM) subjects without DPN were enrolled from six communities in Shanghai in 2011-2014 and followed up until 2019-2020. Neuropathy was assessed by Michigan Neuropathy Screening Instrument (MSNI) at baseline and at the end of follow-up.

FINDINGS

After 5.91 years, 198 of 366 participants progressed to DPN according to MNSI examination scores. The incidence of DPN in the low baseline eGDR (eGDR < 9.15) group was significantly higher than in the high baseline eGDR (eGDR ≥ 9.15) group (62.37% vs. 45.56%, p = .0013). The incidence of DPN was significantly higher in patients with sustained lower eGDR level (63.69%) compared with those with sustained higher eGDR level (35.80%). Subjects with low baseline eGDR (eGDR < 9.15) had significantly higher risk of DPN at the end of follow-up (odds ratio = 1.75), even after adjusting for other known DPN risk factors.

CONCLUSIONS

The 5-year follow-up study highlights the importance of insulin resistance represented by eGDR in the development of DPN in T2DM. Diabetic patients with low eGDR are more prone to DPN and, therefore, require more intensive screening and more attention.

Correlation between alternative insulin resistance indexes and diabetic kidney disease: a retrospective study

PURPOSE

This retrospective study aimed to investigate the relationship between alternative insulin resistance (IR) indexes not reliant on insulin and diabetic kidney disease (DKD) incidence in a newly diagnosed cohort of individuals with type 2 diabetes mellitus (T2DM).

METHODS

We conducted a retrospective analysis of baseline characteristics in a cohort of 521 individuals with T2DM, then followed up on the outcome of DKD. To assess the predictive ability of IR indexes, we compared the performance of four non-insulin-based IR indexes and the homeostasis model for insulin resistance (HOMA-IR) using logistic regression and consistency-statistics (C-statistics). Furthermore, we computed the net reclassification index (NRI) and integrated discrimination improvement (IDI) to evaluate the additional effects of the indexes.

RESULTS

The four alternative IR indexes of DKD patients were significantly higher than those of non-DKD. After adjustment for other variables, the highest tertile of all indexes was significantly related to DKD incidence, compared with the lowest tertile. Furthermore, the C-statistics for the triglyceride-glucose index (TyG index) and triglyceride to high-density lipoprotein ratio (TG/HDL) were all 0.652, while triglyceride glucose-body mass index (TyG-BMI) and metabolic score for insulin resistance (METS-IR) were 0.639 and 0.651, respectively. The incorporation of the alternative IR indexes into the baseline model revealed positive additional effects, leading to an improved prediction of the risk for DKD.

CONCLUSIONS

It was discovered that the alternative IR indexes served as independent risk factors of DKD. Among the four alternative indexes, TyG index and TG/HDL had the best prediction performance for DKD, followed by METS-IR.

Association between gut microbiota and diabetic nephropathy: a mendelian randomization study

Background

The correlation between diabetic nephropathy (DN) and gut microbiota (GM) has been suggested in numerous animal experiments and cross-sectional studies. However, a causal association between GM and DN has not been ascertained.

Methods

This research adopted MR analysis to evaluate the causal link between GM and DN derived from data acquired through publicly available genome-wide association studies (GWAS). The study utilized the inverse variance weighted (IVW) approach to assess causal association between GM and DN. Four additional methods including MR-Egger, weighted median, weighted mode, and simple mode were employed to ensure comprehensive analysis and robust results. The Cochran's Q test and the MR-Egger method were conducted to identify heterogeneity and horizontal pleiotropy, respectively. The leave-one-out approach was utilized to evaluate the stability of MR results. Finally, a reverse MR was performed to identify the reverse causal association between GM and DN.

Results

According to IVW analysis, Class Verrucomicrobiae (p = 0.003), Order Verrucomicrobiales (p = 0.003), Family Verrucomicrobiaceae (p = 0.003), Genus Akkermansia (p = 0.003), Genus Catenibacterium (p = 0.031), Genus Coprococcus 1 (p = 0.022), Genus Eubacterium hallii group (p = 0.018), and Genus Marvinbryantia (p = 0.023) were associated with a higher risk of DN. On the contrary, Class Actinobacteria (p = 0.037), Group Eubacterium ventriosum group (p = 0.030), Group Ruminococcus gauvreauii group (p = 0.048), Order Lactobacillales (p = 0.045), Phylum Proteobacteria (p = 0.017) were associated with a lower risk of DN. The sensitivity analysis did not identify any substantial pleiotropy or heterogeneity in the outcomes. We found causal effects of DN on 11 GM species in the reverse MR analysis. Notably, Phylum Proteobacteria and DN are mutually causalities.

Conclusion

This study identified the causal association between GM and DN with MR analysis, which may enhance the understanding of the intestinal-renal axis and provide novel potential targets for early non-invasive diagnosis and treatment of DN.

METS-IR and all-cause mortality in Korean over 60 years old: Korean genome and epidemiology study-health examinees (KoGES-HEXA) cohorts

Background

The metabolic score for insulin resistance index (METS-IR) is a novel non insulin-based marker that indicates the risk for metabolic syndrome and type 2 diabetes mellitus (T2DM). However, METS-IR has not been investigated in relation to all-cause mortality. We investigated the longitudinal effect of METS-IR on all-cause mortality in a significantly large cohort of Korean adults over 60 years old.

Methods

Data were assessed from 30,164 Korean participants over 60 years of age from the Korean Genome and Epidemiology Study-Health Examinees (KoGES-HEXA) cohort data, linked with the death certificate database of the National Statistical Office. The participants were grouped into three according to METS-IR tertiles. We used multivariate Cox proportional-hazard regression models to prospectively assess hazard ratios (HRs) for all-cause mortality with 95% confidence intervals (CIs) over an 11-year postbaseline period.

Results

During the mean 11.7 years of follow-up, 2,821 individuals expired. The HRs of mortality for METS-IR tertiles were 1.16 (95% CI, 1.01-1.34) in T3 after adjustment for metabolic parameters, but the T2 did not show statistical significance towards increases for incident mortality respectively. In subgroup analysis depending on the cause of mortality, higher METS-IR was associated with cancer mortality (HR, 1.23, 95% CI, 1.01-1.51) but not with cardiovascular mortality (HR, 1.14, 95% CI, 0.83-1.57) after adjustment for the same confounding variables.

Conclusion

The METS-IR may be a useful predictive marker for all-cause mortality and cancer mortality, but not for cardiovascular mortality in subjects over 60 years of age. This implies that early detection and intervention strategies for metabolic syndrome could potentially benefit this identified group.

Outcomes With Finerenone in Patients With Chronic Kidney Disease and Type 2 Diabetes by Baseline Insulin Resistance

OBJECTIVE

To explore whether insulin resistance, assessed by estimated glucose disposal rate (eGDR), is associated with cardiorenal risk and whether it modifies finerenone efficacy.

RESEARCH DESIGN AND METHODS

In FIDELITY (N = 13,026), patients with type 2 diabetes, either 1) urine albumin-to-creatinine ratio (UACR) of ≥30 to <300 mg/g and estimated glomerular filtration rate (eGFR) of ≥25 to ≤90 mL/min/1.73 m2 or 2) UACR of ≥300 to ≤5,000 mg/g and eGFR of ≥25 mL/min/1.73 m2, who also received optimized renin-angiotensin system blockade, were randomized to finerenone or placebo. Outcomes included cardiovascular (cardiovascular death, nonfatal myocardial infarction, nonfatal stroke, or hospitalization for heart failure) and kidney (kidney failure, sustained decrease of ≥57% in eGFR from baseline, or renal death) composites. eGDR was calculated using waist circumference, hypertension status, and glycated hemoglobin for 12,964 patients.

RESULTS

Median eGDR was 4.1 mg/kg/min. eGDR

CONCLUSIONS

Insulin resistance was associated with increased cardiovascular (but not kidney) risk and did not modify finerenone efficacy.

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Key Words Collapse

MESH Headings

• Humans
• Diabetes Mellitus, Type 2/complications
• Diabetes Mellitus, Type 2/drug therapy
• Insulin Resistance
• Double-Blind Method
• Renal Insufficiency, Chronic/complications
• Glucose/therapeutic use
• Insulins/therapeutic use
• Naphthyridines

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Grants

• P30 DK111024 NIDDK NIH HHS
• Bayer

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Affiliation(s)

Thomas Ebert Medical Department III – Endocrinology, Nephrology, Rheumatology, University of Leipzig Medical Center, Leipzig, Germany
Stefan D. Anker Department of Cardiology of German Heart Center Charité; Institute of Health Center for Regenerative Therapies, German Centre for Cardiovascular Research partner site Berlin, Charité Universitätsmedizin, Berlin, Germany
Luis M. Ruilope Cardiorenal Translational Laboratory and Hypertension Unit, Institute of Research imas12, Madrid, Spain CIBER-CV, Hospital Universitario 12 de Octubre, Madrid, Spain Faculty of Sport Sciences, European University of Madrid, Madrid, Spain
Paola Fioretto Department of Medicine, University of Padua, Italy
Vivian Fonseca Tulane University Health Sciences Center, New Orleans, LA
Guillermo E. Umpierrez Division of Endocrinology, Emory University School of Medicine, Atlanta, GA
Andreas L. Birkenfeld Department of Diabetology, Endocrinology and Nephrology, University Clinic, Tübingen, Germany Institute for Diabetes Research and Metabolic Diseases, Helmholtz Center Munich, University of Tübingen, Tübingen, Germany German Center for Diabetes Research, Neuherberg, Germany
Robert Lawatscheck Clinical Research, Bayer AG, Berlin, Germany
Charlie Scott Data Science and Analytics, Bayer PLC, Reading, U.K
Katja Rohwedder Medical Affairs, Bayer AG, Berlin, Germany
Peter Rossing Steno Diabetes Center Copenhagen, Herlev, Denmark Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
FIDELIO-DKD and FIGARO-DKD Investigators

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Non-linear associations of HOMA2-IR with all-cause mortality in general populations: insights from NHANES 1999-2006

BACKGROUND

The association between homeostatic model assessment (HOMA2-IR) and mortality in obese and non-obese populations has not been clearly explained.

METHODS

A total of 7,085 individuals aged ≥ 20 years from the 1999-2006 National Health and Nutrition Examination Survey were included in the study. Study endpoints were all-cause and cardiovascular mortality. Multivariate Cox proportional hazards regression models with restricted cubic spline analysis were used for analysis.

RESULTS

In the study populations, a total of 1666 all-cause deaths and 555 cardiovascular (CV) deaths were recorded during a mean follow-up of 195.53 months. Notably, a significant difference in obesity was observed in the association between HOMA2-IR and mortality. After adjustment for multiple variables, HOMA2-IR was positively associated with all-cause mortality in all participants, in those with normal BMI, and in those with obesity. Conversely, tertile 2 of HOMA2-IR was associated with a lower risk of all-cause mortality in participants with obesity compared with tertile 1 (adjusted hazard ratio, 0.68; 95% confidence interval, 0.52-0.89; P = 0.005). Results from restricted cubic spline analysis showed a J-shaped association between HOMA2-IR and all-cause and CV mortality. In addition, a nonlinear U-shaped correlation with all-cause (P for nonlinear < 0.001) and CV (P for nonlinear = 0.002) mortality was observed in the population with obesity, with inflection points of HOMA2-IR identified at 1.85 and 1.75. Below the inflection point of 1.85, a negative relationship between HOMA2-IR and all-cause mortality was observed.

CONCLUSIONS

Elevated HOMA2-IR showed a notable correlation with increased risk of all-cause mortality. It was noteworthy that excessively reduced levels of insulin resistance showed a distinct association with increased mortality in individuals with obesity.

Association of systemic immune-inflammation index with diabetic kidney disease in patients with type 2 diabetes: a cross-sectional study in Chinese population

Objective

Systemic immune-inflammation index (SII), a novel inflammatory marker, has been reported to be associated with diabetic kidney disease (DKD) in the U.S., however, such a close relationship with DKD in other countries, including China, has not been never determined. We aimed to explore the association between SII and DKD in Chinese population.

Methods

A total of 1922 hospitalized patients with type 2 diabetes mellitus (T2DM) included in this cross-sectional study were divided into three groups based on estimated glomerular filtration rate (eGFR) and urinary albumin-to-creatinine ratio (ACR): non-DKD group, DKD stages 1-2 Alb group, and DKD-non-Alb+DKD stage 3 Alb group. The possible association of SII with DKD was investigated by correlation and multivariate logistic regression analysis, and receiver-operating characteristic (ROC) curves analysis.

Results

Moving from the non-DKD group to the DKD-non-Alb+DKD stage 3 Alb group, SII level was gradually increased (P for trend <0.01). Partial correlation analysis revealed that SII was positively associated with urinary ACR and prevalence of DKD, and negatively with eGFR (all P<0.01). Multivariate logistic regression analysis showed that SII remained independently significantly associated with the presence of DKD after adjustment for all confounding factors [(odds ratio (OR), 2.735; 95% confidence interval (CI), 1.840-4.063; P < 0.01)]. Moreover, compared with subjects in the lowest quartile of SII (Q1), the fully adjusted OR for presence of DKD was 1.060 (95% CI 0.773-1.455) in Q2, 1.167 (95% CI 0.995-1.368) in Q3, 1.266 (95% CI 1.129-1.420) in the highest quartile (Q4) (P for trend <0.01). Similar results were observed in presence of DKD stages 1-2 Alb or presence of DKD-non- Alb+DKD stage 3 Alb among SII quartiles. Last, the analysis of ROC curves revealed that the best cutoff values for SII to predict DKD, Alb DKD stages 1- 2, and DKD-non-Alb+ DKD stage 3 Alb were 609.85 (sensitivity: 48.3%; specificity: 72.8%), 601.71 (sensitivity: 43.9%; specificity: 72.3%), and 589.27 (sensitivity: 61.1%; specificity: 71.1%), respectively.

Conclusion

Higher SII is independently associated with an increased risk of the presence and severity of DKD, and SII might be a promising biomarker for DKD and its distinct phenotypes in Chinese population.

Estimated glucose disposal rate and risk of arterial stiffness and long-term all-acuse mortality: a 10-year prospective study

BACKGROUND

To assess the applicability of the association between estimated glucose disposal rate (eGDR) and all-cause mortality in the elderly population, and the mediating role of brachial-ankle pulse wave velocity (baPWV).

METHODS

This was a follow-up cohort study based on the cross-sectional survey of community-dwelling elderly. All participants in the study were included between September 2009 and June 2010, and the follow-up time was December 2020. Participants included 1862 Chinese community-dwelling elderly aged 60 years and above. Insulin resistance assessed by eGDR and arterial stiffness assessed by baPWV were the primary exposures of interest. Mortality, which was followed up until December 2020, was the primary outcome. Cox proportional hazards regression models were used to estimate the association of eGDR with mortality. The mediating effect of baPWV in this association was assessed by mediation analysis.

RESULTS

A total of 1826 participants with a mean age of 71.03 years old were included in the study. During the median follow-up of 10.75 years, 334 participants died. The adjusted HR comparing the highest versus the lowest eGDR quartile was 0.22 (95% CI 0.09 to 0.54; p<0.001) in the Cox proportional hazards model. The results of mediation analysis showed that baPWV had a significant mediation impact on the link between eGDR and all-cause mortality both as continuous or categorical variables.

CONCLUSION

eGDR is an independent predictor of all-cause mortality in the elderly population. baPWV partially mediated the association of eGDR and long-term all-cause mortality as a mediator factor.

Triglyceride-glucose index, renal function and cardiovascular disease: a national cohort study

BACKGROUND

The triglyceride-glucose (TyG) index is a predictor of cardiovascular diseases; however, to what extent the TyG index is associated with cardiovascular diseases through renal function is unclear. This study aimed to evaluate the complex association of the TyG index and renal function with cardiovascular diseases using a cohort design.

METHODS

This study included participants from the China Health and Retirement Longitudinal Study (CHARLS) free of cardiovascular diseases at baseline. We performed adjusted regression analyses and mediation analyses using Cox models. The TyG index was calculated as Ln [fasting triglyceride (mg/dL) × fasting glucose (mg/dL)/2]. Renal function was defined by the estimated glomerular filtration rate (eGFR).

RESULTS

A total of 6 496 participants were included in this study. The mean age of the participants was 59.6 ± 9.5 years, and 2996 (46.1%) were females. During a maximum follow-up of 7.0 years, 1 996 (30.7%) people developed cardiovascular diseases, including 1 541 (23.7%) cases of heart diseases and 651 (10.0%) cases of stroke. Both the TyG index and eGFR level were significantly associated with cardiovascular diseases. Compared with people with a lower TyG index (median level) and eGFR ≥ 60 ml/minute/1.73 m2, those with a higher TyG index and decreased eGFR had the highest risk of cardiovascular diseases (HR, 1.870; 95% CI 1.131-3.069). Decreased eGFR significantly mediated 29.6% of the associations between the TyG index and cardiovascular diseases.

CONCLUSIONS

The combination of a higher TyG index and lower eGFR level was associated with the highest risk of cardiovascular diseases. Renal function could mediate the association between the TyG index and cardiovascular risk.

The relationship between serum γ-glutamyltransferase (GGT) and diabetic nephropathy in patients with type 2 diabetes mellitus: a cross-sectional study

The relationship between serum γ-glutamyltransferase (GGT) and renal dysfunction is controversial. In this study, we examined the relationship of serum GGT to diabetic nephropathy (DN) in patients with type 2 diabetes mellitus (T2DM). A total of 577 patients with T2DM were enrolled and their basic information and laboratory data were collected and analyzed. The prevalence of DN increased with the elevated serum GGT tertiles. The level of serum GGT in the DN group was higher than in the non-DN groups. Multivariate logistic analysis showed that high GGT was independent risks for DN (OR = 1.041, 95% CIs 1.023-1.059). And the OR of log-transformed serum GGT for DN was 6.190 (95% CIs 4.248-9.021). The OR of DN across increasing tertiles of serum GGT were 1.00, 3.288 (1.851-5.840), and 5.059 (2.620-9.769) (P for trend < 0.001). Stratified receiver operating characteristic (ROC) analysis by gender showed that the area under ROC curve (AUC) value for GGT was 0.781 (0.732-0.825, P < 0.05) in male and was 0.817 (0.761-0.864, P < 0.05) in female. Compared with female, GGT in male showed lower sensitivity (52.86% vs. 82.05%) and higher specificity (90.32% vs. 55.26%). And the AUC value for GGT was greater than creatinine (Cr) and estimated glomerular filtration rate (eGFR) in male and smaller than Cr and eGFR in female, respectively. In Conclusion, there was an independently positive relationship between serum GGT levels and DN, which suggested that elevated GGT was a potential indicator for risk of DN. There were gender differences in the predictive property of GGT for DN.

Prediction of Diabetic Kidney Disease in Newly Diagnosed Type 2 Diabetes Mellitus

Background

Diabetic kidney disease (DKD), a common microvascular complication of diabetes mellitus (DM), is always asymptomatic until it develops to the advanced stage. Thus, we aim to develop a nomogram prediction model for progression to DKD in newly diagnosed type 2 diabetes mellitus (T2DM).

Methods

This was a single-center analysis of prospective data collected from 521 newly diagnosed patients with T2DM. All related clinical records were incorporated, including the triglyceride-glucose index (TyG index). The least absolute shrinkage and selection operator (LASSO) was used to build a prediction model. In addition, discrimination, calibration, and clinical practicality of the nomogram were evaluated.

Results

In this study, 156 participants were incorporated as the validation set, while the remaining 365 were incorporated into the training set. The predictive factors included in the individualized nomogram prediction model included 5 variables. The area under the curve (AUC) for the prediction model was 0.826 (95% CI 0.775 to 0.876), indicating excellent discrimination performance. The model performed exceptionally well in terms of predictive accuracy and clinical applicability, according to calibration curves and decision curve analysis.

Conclusion

The predictive nomogram for the risk of DKD in newly diagnosed T2DM patients had outstanding discrimination and calibration, which could help in clinical practice.