Association Between Triglyceride-Glucose Index and the Risk of Type 2 Diabetes Mellitus in an Older Chinese Population Aged Over 75 Years

The role of the triglyceride-glucose index as a biomarker of cardio-metabolic syndromes

BACKGROUND

The Triglyceride-glucose (TyG) index represents a simple, cost-effective, and valid proxy for insulin resistance. This surrogate marker has also been proposed as a predictor of metabolic and cardiovascular disease (CVD). In this descriptive review, we aimed to assess the utility of the TyG index as a predictive biomarker of cardiometabolic diseases.

METHODS

A search was conducted in PubMed, and Web of Science to identify cross-sectional and more importantly prospective studies examining the use of the TyG index as a predictive biomarker. The following terms were utilized in addition to the TyG index: "insulin resistance", "metabolic syndrome", "diabetes"; "cardiovascular diseases".

RESULTS

This descriptive review included thirty prospective studies in addition to cross-sectional studies. Following adjustment for confounding variables, an elevated TyG index was associated with a significantly increased risk for the development of Metabolic Syndrome (MetS), Type 2 Diabetes, hypertension, and CVD. Also in limited studies, the TyG index was associated with endothelial dysfunction, increased oxidative stress and a pro-inflammatory phenotype.

CONCLUSION

Overall, our findings support the use of the TyG index as a valid biomarker to assess the risk of developing MetS, T2DM, as well as atherosclerotic cardiovascular disease.

Role of Triglyceride-Glucose Index in Type 2 Diabetes Mellitus and Its Complications

Insulin resistance (IR) is the major mechanism in the pathogenesis of type 2 diabetes mellitus (T2DM). Early identification of IR is of great significance for preventing the onset of T2DM and delaying the progression of the disease. Previous studies have shown that triglyceride-glucose (TyG) index can be used as an effective surrogate marker for IR. There is a significant correlation between TyG index and T2DM and its common complications. In addition, the predictive efficacy of TyG index is better than that of other IR surrogate indicators. TyG index may not only become an important marker to identify people at high risk of T2DM and its complications, but is also expected to become a strong predictor of the prognosis of these diseases. However, there are still some challenges in the widespread application of TyG index in clinical practice. In the future, more high-quality studies are needed to clarify the assessment methods of TyG index for the prognosis of T2DM and its complications. Further investigations of the relationship between TyG index and T2DM and its complications will be expected to provide new ideas and methods for the prevention and treatment of T2DM and its complications.

Triglyceride-Fasting Glucose Index and Homeostatic Model Assessment for Insulin Resistance as Predictors of Type 2 Diabetes Mellitus in South Indians With Normal Body Mass Index

INTRODUCTION

 Early detection of type 2 diabetes mellitus (T2DM) is imperative to prevent the complications associated with the disease. Current guidelines for diagnosis rely on the assessment of serum glucose (fasting and post-prandial) and glycosylated hemoglobin (HbA1c) levels. Insulin resistance, a phenomenon associated with T2DM, has been observed before the changes in these metrics. The homeostatic model assessment for insulin resistance (HOMA-IR) has been widely used to assess the degree of insulin resistance. The triglyceride-fasting glucose (TyG) index is a newer marker of insulin resistance that merits further study.  Aim: The study aimed to assess the validity of the TyG index and HOMA-IR as markers for the development of T2DM in non-obese individuals.  Materials and methods: One hundred eight non-obese patients without T2DM were included in this prospective cohort study and followed up for eight years. Anthropometric and biochemical parameters, including fasting glucose levels, HbA1c, fasting serum insulin, low-density lipoprotein (LDL), high-density lipoprotein (HDL), and triglycerides (TG), were measured at enrolment and eight years follow-up, and HOMA-IR and TyG index were calculated.  Results: Twenty participants out of 108 (18.5%) developed T2DM over eight years. On performing the area under the curve (AUC)-receiver operating characteristic curve analysis, TyG of >8.61 and HOMA-IR of >1.5 had the highest validity (ability) to predict new-onset T2DM in the study population (TyG: AUC: 0.612 (95% CI: 0.514-0.705); HOMA-IR: AUC: 0.529 (95% CI: 0.431-0.626)); however, this was not statistically significant.  Conclusion: At an eight-year follow-up, TyG and HOMA-IR were unreliable predictors of the development of T2DM in non-obese individuals.

Association of triglyceride-glucose index trajectory and frailty in urban older residents: evidence from the 10-year follow-up in a cohort study

BACKGROUND

Frailty is an age-related geriatric syndrome that leads to a series of clinically negative events. A better understanding of the factors associated with frailty assists in preventing its progression. The triglyceride-glucose (TyG) index, a simple alternative index of insulin resistance, has not yet been proven to be associated with frailty. The present study aimed to investigate the association between the TyG index and its trajectory with frailty from a cross-sectional, retrospective and prospective level based on an ongoing cohort.

METHODS

This longitudinal study included 1,866 older residents from the "Fujian prospective aging cohort" (ChiCTR 2,000,032,949). The TyG index was calculated as ln [fasting triglyceride (mg/dL) ╳ fasting plasma glucose (mg/dL)/2] and group-based trajectory model (GBTM) was applied to identify the trajectory of TyG index. The association between different trajectory groups of TyG index with frailty risk were estimated using multinomial logistic regression analysis.

RESULTS

In the cross-sectional analysis, the highest quartile of the TyG index was associated with an increased risk of frailty (TyG index Q4 vs. Q1, OR = 1.50, 95% CI 1.00-2.25, P = 0.048). Restricted cubic splines demonstrated an increasing trend for TyG index and frailty risk. During a follow-up of ten years, three distinct trajectories of the TyG index were identified: low-stable (n = 697, 38.3%), moderate-stable (n = 910, 50.0%) and high-stable (n = 214, 11.7%). Compared with those in the stable-low group of TyG index trajectory, the ORs (95% CI) of prefrailty and frailty risk were 1.79 (95% CI 1.11-2.88) and 2.17 (95% CI 1.01-3.88) for the high-stable group, respectively (P = 0.017 and P = 0.038). In the subgroup analysis, the association of the high-stable trajectory of TyG and frailty status were only observed in subjects with BMI ≥ 24 kg/m2. Prospectively, the highest quartile of the TyG index was associated with a 2.09-fold significantly increased risk of one-year ADL/IADL decline (P = 0.045).

CONCLUSIONS

The present study suggests a potential role for a high and sustainable level of TyG index in the risk of frailty. The trajectories of the TyG index can help to identify older individuals at a higher risk of frailty who deserve primitive preventive and therapeutic approaches.

The association between triglyceride-glucose index and hyperferritinemia in patients with type 2 diabetes mellitus

PURPOSE

To investigate the relationship between the triglyceride-glucose (TyG) index and serum ferritin (SF) levels in patients with type 2 diabetes mellitus (T2DM).

METHODS

A total of 881 T2DM patients were divided into T1(TyG index < 1.66), T2 (1.66 ≤ TyG index < 2.21), and T3 (TyG index ≥ 2.21) groups according to the tertiles of the TyG index. The differences in SF levels and the prevalence of hyperferritinemia (SF ≥ 300 ng/mL for male or SF ≥ 150 ng/mL for female) were compared. The independent correlations between the TyG index and SF, and between hyperferritinemia and TyG in T2DM patients were analyzed, respectively.

RESULTS

SF levels in male T2DM patients were higher in the T3 group (250.12 ng/mL) than in the T1 and T2 groups (180.45 and 196.56 ng/mL, both p < 0.01),while in female patients with T2DM,SF levels were higher in the T3 group (157.25 ng/mL) than in the T1 group (111.06 ng/mL, p < 0.05).The prevalence of hyperferritinemia in male T2DM patients was higher in the T3 group (31.3%) than those in the T1 and T2 groups (10.4% and 17.3%, both p < 0.05).The TyG index was positively correlated with SF levels in T2DM patients (R = 0.178, p < 0.001).TyG index was independently and positively correlated with SF levels after adjusting for confounders (β = 0.097, 95%CI [2.870,38.148], p = 0.023).The TyG index was positively independently correlated with hyperferritinemia in male T2DM patients (OR = 1.651, 95%CI [1.120,2.432], p = 0.011).

CONCLUSIONS

In parallel with increasing TyG index SF levels gradually increased. The TyG index was positively correlated with SF levels in patients with T2DM and was positively correlated with hyperferritinemia in male T2DM patients.

Association of four lipid-derived indicators with the risk of developing type 2 diabetes: a Chinese population-based cohort study

BACKGROUND

Studies have reported that lipid-derived indicators are associated with type 2 diabetes (T2D) in various populations; however, it is unclear which lipid-derived indicators could effectively predict T2D risk. Therefore, this study aimed to explore the association between four lipid-derived indicators and T2D risk.

METHODS

This was a post-hoc analysis from a large cohort that included data from 114,700 Chinese individuals aged 20 years and older from 11 cities and 32 sites. The association between four lipid-derived indicators and T2D risk was determined using Kaplan-Meier (KM) survival curves, Cox regression, and restricted cubic spline analyses. This study used receiver operating characteristic (ROC) curves for assessing the ability of four lipid-derived indicators to accurately predict the development of T2D during follow-up.

RESULTS

This study included a total of 114,700 participants, with a mean age of 44.15. These individuals were followed up for 3.1 years, of which 2668 participants developed T2D. ROC curve analysis showed that TyG was the most robust predictor of 3-year [aera under the ROC (AUC) = 0.77, 95% CI: 0.768, 0.772] and 5-year T2D risk (AUC = 0.763, 95% CI: 0.760, 0.765). In addition, sensitivity analysis showed an association between TyG and an increased incidence of T2D.

CONCLUSIONS

The results suggest that TyG was a superior for predicting the risk of developing T2D in the general Chinese population.

The Novel Predictive Biomarkers for Type 2 Diabetes Mellitus in Active Pulmonary Tuberculosis Patients

Purpose

This study was to explore the predictive value of monocyte to high-density lipoprotein cholesterol ratio (MHR), neutrophils to high-density lipoprotein cholesterol ratio (NHR), C-reactive protein-to-lymphocyte ratio (CLR), and C-reactive protein-to-albumin ratio (CAR) for type 2 diabetes mellitus (T2DM) in patients with active pulmonary tuberculosis (APTB).

Patients and Methods

A total of 991 active pulmonary tuberculosis (APTB) patients (201 with T2DM) were hospitalized in the Department of Tuberculosis, Wuhan Jinyintan Hospital, Tongji Medical College, Huazhong University of Science and Technology were included. The routine blood examination indicators and biochemical parameters were collected to calculate MHR, NHR, CLR, and CAR. The Pearson correlation analysis, Univariate Logistic regression analysis, and receiver operating characteristic (ROC) curve analysis were performed to assess the predictive value of MHR, NHR, CLR, and CAR for APTB-T2DM patients.

Results

The levels of MHR, NHR, CLR, and CAR in the APTB-T2DM patients were significantly higher than in the APTB-no T2DM patients (P < 0.05). Additionally, the MHR, NHR, CLR, and CAR have a positive correlation with fasting blood glucose in the whole study population. However, in the APTB-T2DM patients, MHR, NHR, and CAR were not correlated with fasting blood glucose, and only CLR was positively correlated with fasting blood glucose. The area under curve (AUC) predicting APTB-T2DM patients of the MHR, NHR, CLR, and CAR was 0.632, 0.72, 0.715, and 0.713, respectively. Further, univariate logistic regression analyses showed that the higher MHR, NHR, CLR, and CAR were independent risk factors for APTB-T2DM (P < 0.01). The MHR, NHR, CLR, and CAR quartiles were used to divide the APTB patients into four groups for further analysis. The prevalence of T2DM was significantly higher in APTB individuals as MHR, NHR, CLR, and CAR values increased (P < 0.05).

Conclusion

MHR, NHR, CLR, and CAR are simple and practicable inflammatory parameters that could be used for assessing T2DM in APTB. APTB patients have a greater possibility to be diagnosed with T2DM with the higher MHR, NHR CLR, and CAR values. Therefore, more attention should be given to the indicator in the examination of APTB.