Background: The prediction and tracking of hepatic steatosis progression is of critical importance, yet there is a notable absence of reliable biomarkers. This study was conducted to identify a novel biomarker to enable accurate forecasting of hepatic steatosis and liver fibrosis.
Method: The data for this study were derived from the 2017-2020 National Health and Nutrition Examination Survey (NHANES). The multivariate linear regression models were used to investigate the relationship between the Gamma-glutamyl transpeptidase -to-lymphocyte ratio (GLR), controlled attenuation parameters (CAP), and liver stiffness measurements (LSM). The fitted smooth curve and threshold effect analyses were used to address non-linearity. Subgroup analyses were performed based on gender, age, diabetes, hypertension, and smoking.
Result: In total, 6481 patients were enrolled in the analysis. In the multivariate linear regression analysis, GLR is positively correlated with hepatic steatosis [CAP, β=0.29, 95% confidence interval (CI) (0.13, 0.44), P=0.0003]. This positive association is stable among all subgroups. An inverse L-shaped relationship between GLR and CAP was observed, with a stronger correlation when GLR<8.276. The correlation between GLR and liver fibrosis remained significantly linear in the multivariate regression analysis. [LSM β=0.03, 95% CI (0.02, 0.05), P<0.0001]. This association was more potent among participants over 50 years old (P for interaction < 0.05).
Conclusion: Our investigation revealed an association between GLR, CAP, and LSM. This association suggests that GLR holds predictive potential for assessing hepatic steatosis and liver fibrosis.