The predictive value of triglyceride-glucose-high density lipoprotein-body mass index (TGH-BMI) for different degrees of hepatic steatosis and liver fibrosis in metabolic dysfunction-associated steatotic liver disease (MASLD)

Abstract

Background & aims

The triglyceride-glucose index (TyG) and triglyceride-glucose body mass index (TyG-BMI) have been identified as potential predictive factors for metabolic dysfunction-associated steatotic liver disease (MASLD). However, they do not include high density lipoprotein (HDL-C), which is closely related to lipid metabolism. Furthermore, there is a lack of comprehensive and longitudinal data to determine the cut-off points for different degrees of hepatic steatosis and liver fibrosis in MASLD. This study aimed to investigate the predictive capability of triglyceride-glucose-high density lipoprotein-body mass index (TGH-BMI) in determining hepatic steatosis and liver fibrosis in MASLD, as well as to establish the predictive cut-off points.

Methods

We analyzed the relationships of TGH-BMI (TGH-BMI = ln [TG (mg/dL) ∗FBG (mg/dL)/HDL-C (mg/dL)] ∗ BMI (kg/m2)) with different degrees of hepatic steatosis and fibrosis in 35,114 participants who underwent health check-ups. A total of 2262 subjects without MASLD were selected for the analysis of cumulative hazard of hepatic steatosis and liver fibrosis in TGH-BMI dichotomous groups over a follow-up period of 1001 days.

Results

Controlled attenuation parameter (CAP) and liver stiffness measurement (LSM) demonstrated a consistent upward trend as TGH-BMI increased across quartile groups, as determined by One-way analysis of variance (P < 0.001). TGH-BMI and CAP, LSM exhibit distinct curve-like relationships between males and females when utilizing smoothing functions and conducting threshold effect analysis (P < 0.05). In males, prior to the inflection point at TGH-BMI = 177.733, there was a significant increase of 0.807 in CAP for every 1 unit increase in TGH-BMI (P < 0.05), after the inflection point, there was still an increase of 0.417 in CAP for every 1 unit increase in TGH-BMI (P < 0.05); There was no significant correlation between LSM and TGH-BMI before the first inflection point at TGH-BMI = 131.689 (P > 0.05) and after the second inflection point at TGH-BMI = 253.268 (P > 0.05). Between the first and the second inflection, LSM showed an increase of 0.015 for every 1 unit increase in TGH-BMI (P < 0.05). In females, before the inflection point at TGH-BMI = 94.686, there was a significant increase of 0.272 in CAP for every 1 unit increase in TGH-BMI (P < 0.05), after the inflection point, there was a notable change as CAP increased by 0.806 for every 1 unit increase in TGH-BMI (P < 0.05). There was no significant correlation between LSM and TGH-BMI before the inflection point at TGH-BMI = 118.098 (P > 0.05), after the inflection point, LSM showed an increase of 0.017 for every 1 unit increase in TGH-BMI (P < 0.05). Notably, TGH-BMI has been shown to be a strong predictor for the severity of hepatic steatosis and liver fibrosis in MASLD. The Area Under Curves (AUCs) for hepatic steatosis, moderate or above hepatic steatosis, severe hepatic steatosis and liver fibrosis in males were 0.845, 0.846, 0.882 and 0.668 respectively, the AUCs for hepatic steatosis, moderate or above hepatic steatosis, severe hepatic steatosis and liver fibrosis in females were 0.855, 0.895, 0.939 and 0.705 respectively (P < 0.05). In individuals without MASLD, the cumulative hazard of hepatic steatosis was found to be strongly associated with the dichotomy of increased TGH-BMI (TGH-BMID2: Hazard Ratio (HR) = 2.412, 95 % Confidence interval (CI): 2.0164–2.9071, P < 0.0001), while the same is true in liver fibrosis (TGH-BMID2: HR = 1.454, 95 % CI: 1.0633–1.9883, P = 0.0191).

Conclusions

The TGH-BMI demonstrates a strong predictive value for hepatic steatosis and liver fibrosis, with significantly different cut-off points for men and women. Therefore, it is important to consider the potential need for gender-specific cut-off points for triglyceride, glucose, high density lipoprotein and body mass index in clinical practice. In individuals without MASLD, a higher TGH-BMI is associated with an increased risk of developing MASLD in the future.