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解析甘油三酯-葡萄糖指数:肝脏脂肪含量的关键预测指标及体重指数的放大作用:来自大型体检数据的证据

Unraveling the triglyceride-glucose index: a key predictor of liver fat content and the amplifying role of BMI: evidence from a large physical examination data.

作者信息

Liu Su-Juan, Duan Jin-Hui, Chen Yang-Yang, Gu Shi-Li, He Yu-Hua, Xue Ming-Mei, Yue Jun-Yan

机构信息

Department of Radiology, The First Affiliated Hospital of Xinxiang Medical University, Xinxiang, China.

出版信息

Front Endocrinol (Lausanne). 2025 Apr 25;16:1555300. doi: 10.3389/fendo.2025.1555300. eCollection 2025.

DOI:10.3389/fendo.2025.1555300
PMID:40352458
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12061704/
Abstract

BACKGROUND

The triglyceride-glucose (TyG) index is associated with the severity of metabolic-associated fatty liver disease (MASLD), but its link to liver fat content is not fully understood. This study investigates the relationship between the TyG index and liver fat content and explores the role of body mass index (BMI) as a mediator.

METHODS

This cross-sectional study analyzed data from 12,750 participants who underwent health screenings at the first affiliated hospital of Xinxiang Medical University between January 2018 and December 2023. The TyG index, derived as Ln [triglycerides (mg/dl) * fasting plasma glucose (mg/dl)/2], was the independent variable, while liver fat content, measured by quantitative computed tomography (QCT), was the dependent variable. Participants were grouped into tertiles based on their TyG index. Univariate and multivariate analyses, smooth curve fitting (generalized additive models), threshold effect analysis, and subgroup analyses were used to assess the TyG-liver fat content relationship. BMI's mediating effect was also examined.

RESULTS

Liver fat content increased steadily across TyG index tertiles. After adjusting for confounders, the TyG index remained independently associated with liver fat content [β = 1.42, 95% CI: 1.26-1.57]. Participants in the highest TyG tertile (T3) had a 1.58-fold higher liver fat content compared to those in the lowest tertile (T1) (95% CI: 1.37-1.80, <0.001). A generalized additive model showed a nonlinear relationship between TyG index and liver fat content. When the TyG index ≤ 7.39, liver fat content increased gradually (β = 0.74, 95% CI: 0.50-0.99, <0.001). Beyond this threshold, liver fat content rose sharply (β = 2.19, 95% CI: 1.92-2.46, <0.001). Subgroup analysis indicated that the association between TyG index and liver fat content was stronger at higher BMI levels ( for interaction < 0.001). Mediation analysis revealed that BMI accounted for 26.68% of the observed effect.

CONCLUSION

The TyG index is positively associated with liver fat content in a nonlinear manner, with BMI amplifying this effect. These results suggest that the TyG index may be a useful marker for predicting liver fat content, and managing weight could help slow the progression of MASLD.

摘要

背景

甘油三酯-葡萄糖(TyG)指数与代谢相关脂肪性肝病(MASLD)的严重程度相关,但其与肝脏脂肪含量的联系尚未完全明确。本研究调查了TyG指数与肝脏脂肪含量之间的关系,并探讨了体重指数(BMI)作为中介变量的作用。

方法

这项横断面研究分析了2018年1月至2023年12月在新乡医学院第一附属医院接受健康筛查的12750名参与者的数据。TyG指数通过公式Ln[甘油三酯(mg/dl)×空腹血糖(mg/dl)/2]得出,作为自变量;通过定量计算机断层扫描(QCT)测量的肝脏脂肪含量作为因变量。参与者根据TyG指数分为三个三分位数组。采用单因素和多因素分析、平滑曲线拟合(广义相加模型)、阈值效应分析和亚组分析来评估TyG指数与肝脏脂肪含量的关系。同时也检验了BMI的中介作用。

结果

肝脏脂肪含量随着TyG指数三分位数的升高而稳步增加。在调整混杂因素后,TyG指数仍与肝脏脂肪含量独立相关[β = 1.42,95%可信区间:1.26 - 1.57]。TyG指数最高三分位数组(T3)的参与者肝脏脂肪含量比最低三分位数组(T1)高1.58倍(95%可信区间:1.37 - 1.80,P < 0.001)。广义相加模型显示TyG指数与肝脏脂肪含量之间存在非线性关系。当TyG指数≤7.39时,肝脏脂肪含量逐渐增加(β = 0.74,95%可信区间:0.50 - 0.99,P < 0.001)。超过此阈值后,肝脏脂肪含量急剧上升(β = 2.19,95%可信区间:1.92 - 2.46,P < 0.001)。亚组分析表明,在较高BMI水平下,TyG指数与肝脏脂肪含量之间的关联更强(交互作用P < 0.001)。中介分析显示,BMI占观察到的效应的26.68%。

结论

TyG指数与肝脏脂肪含量呈正相关且为非线性关系,BMI会放大这种效应。这些结果表明,TyG指数可能是预测肝脏脂肪含量的有用指标,控制体重可能有助于减缓MASLD的进展。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2c9c/12061704/42ed28dd4e97/fendo-16-1555300-g006.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2c9c/12061704/42ed28dd4e97/fendo-16-1555300-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2c9c/12061704/f1436fad0218/fendo-16-1555300-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2c9c/12061704/cf2ff9d79770/fendo-16-1555300-g002.jpg
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