Relationship Between the TyG Index and Diabetic Kidney Disease in Patients with Type-2 Diabetes Mellitus

Liangjing Lv, Yangmei Zhou, Xiangjun Chen, Lilin Gong, Jinshan Wu, Wenjin Luo, Yan Shen, Shichao Han, Jinbo Hu, Yue Wang, Qifu Li, Zhihong Wang, Chongqing Diabetes Registry Group, Liangjing Lv, Yangmei Zhou, Xiangjun Chen, Lilin Gong, Jinshan Wu, Wenjin Luo, Yan Shen, Shichao Han, Jinbo Hu, Yue Wang, Qifu Li, Zhihong Wang, Chongqing Diabetes Registry Group

Abstract

Background: Diabetic kidney disease (DKD) lacks a simple and relatively accurate predictor. The Triglyceride-Glucose (TyG) Index is a proxy of insulin resistance, but the association between the TyG Index and DKD is less certain. We investigated if the TyG Index can predict DKD onset effectively.

Materials and methods: Cross-sectional and longitudinal analyses were undertaken. In total, 1432 type-2 diabetes mellitus (T2DM) patients were included in the cross-sectional analysis. The TyG Index (calculated by ln [fasting triglycerides (mg/dL) × fasting glucose (mg/dL)/2]) was split into three tertiles. Associations of the TyG Index with microalbuminuria and estimated glomerular filtration rate (eGFR) <60 mL/min/1.73 m2 were calculated. Longitudinally, 424 patients without DKD at baseline were followed up for 21 (range, 12-24) months. The main outcome was DKD prevalence as defined with eGFR <60 mL/min/1.73 m2 or continuously increased urinary microalbuminuria: creatinine ratio (>30 mg/mL) over 3 months. Cox regression was used to analyze the association between the TyG Index at baseline and DKD. Receiver operating characteristics curve (ROC) analysis was used to assess the sensitivity and specificity of the TyG Index in predicting DKD.

Results: In cross-sectional analysis, patients with a higher TyG Index had a higher risk of microalbuminuria (OR = 2.342, 95% CI = 1.744-3.144, p < 0.001), and eGFR <60 mL/min/1.73 m2 (1.696, 95% CI =1.096-2.625, p = 0.018). Longitudinally, 94 of 424 participants developed DKD. After confounder adjustment, patients in the high tertile of the TyG Index at baseline had a greater risk to developing DKD than those in the low tertile (HR = 1.727, 95% CI = 1.042-2.863, p = 0.034). The area under the ROC curve was 0.69 (0.63-0.76).

Conclusion: The TyG Index is a potential predictor for DKD in T2DM patients.

Clinical trial: Clinical Trials identification number = NCT03692884.

Keywords: diabetic kidney disease; insulin resistance; triglyceride–glucose index.

Conflict of interest statement

Liangjing Lv, Yangmei Zhou, Xiangjun Chen, Lilin Gong, Jinshan Wu, Wenjin Luo, Yan Shen, Shichao Han, Jinbo Hu, Yue Wang, Qifu Li, Zhihong Wang, and Chongqing Diabetes Registry Group declare that they have no relevant conflicts of interest.

© 2021 Lv et al.

Figures

Figure 1
Figure 1
Flowchart of the study population. Type-2 diabetes mellitus (T2DM) was diagnosed based on the diagnostic criteria for T2DM set by the World Health Organization in 1999. Data used in this analysis were collected for all participants by the same instruments and methods.
Figure 2
Figure 2
Cox regression for DKD according to the tertiles of the TyG Index in longitudinal data. Model 1 was adjusted for age and sex. Model 2 was adjusted for the duration of diabetes mellitus, history of hypertension, and BMI in addition to the variables in model 1. Model 3 was adjusted for hypoglycemic therapy, hypolipidemic therapy, and anti-hypertension drugs in addition to the variables in model 2.
Figure 3
Figure 3
Receiver–operator characteristic (ROC) curves of the TyG Index adjusted for different variables to predict DKD in longitudinal data. ROC curves of the TyG Index adjusted for different variables to predict DKD in longitudinal data. (A) Model 1 was adjusted for age and sex. (B) Model 2 was adjusted for the duration of diabetes mellitus, history of hypertension, and BMI in addition to the variables in model 1. (C) Model 3 was adjusted for hypoglycemic therapy, hypolipidemic therapy, and anti-hypertension drugs in addition to the variables in model 2.

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