Associations between cardiometabolic indices and the onset of metabolic dysfunction-associated steatotic liver disease as well as its progression to liver fibrosis: a cohort study.

BACKGROUND

This study sought to examine the associations between cardiometabolic indices and the onset of metabolic dysfunction-associated steatotic liver disease (MASLD) as well as its progression to liver fibrosis.

METHODS

This study comprised 25,366 subjects aged 18 years and older, free of MASLD at baseline, from the Dalian Health Management Cohort (DHMC). Cardiometabolic indices include cardiometabolic index (CMI), atherogenic index of plasma (AIP), triglyceride glucose (TyG), triglyceride glucose-body mass index (TyG-BMI), triglyceride glucose-waist circumference (TyG-WC) and triglyceride glucose-waist height ratio (TyG-WHtR). All participants were categorized into quartile groups based on cardiometabolic indices. Cox proportional hazards regression models and restricted cubic splines were employed to examine the relationship between cardiometabolic indices and the incidence of MASLD as well as its progression to liver fibrosis, and analyses were performed between different subgroups. Mediation analysis was employed to explore how obesity and inflammation serve as mediators in the connection between cardiometabolic indices and MASLD. To evaluate the predictive ability of cardiometabolic indices for the onset of MASLD, the time-dependent receiver operating characteristic (ROC) curve was utilized.

RESULTS

A total of 5378 (21.2%) individuals developed MASLD during the follow-up period of 82,445 person-years. Multivariates Cox regression analyses showed that participants in the highest quartile of cardiometabolic indices had greater risk of MASLD than those in the lowest quartile (CMI: HR = 6.11, 95% CI 5.45-6.86; AIP: HR = 4.58, 95% CI 4.11-5.10; TyG: HR = 3.55, 95% CI 3.21-3.92; TyG-BMI: HR = 13.55, 95% CI 11.80-15.57; TyG-WC: HR = 12.52, 95% CI 10.93-14.34; TyG-WHtR: HR = 11.37, 95% CI 9.96-12.98). TyG-BMI (HR = 1.36, 95% CI 1.18-1.57), but not other cardiometabolic indices, was associated with liver fibrosis. Mediation analysis indicated that BMI mediated 40.4%, 33.2%, 36.5%, - 10.4%, 37.4%, 48.5% of the associations between CMI, AIP, TyG, TyG-BMI, TyG-WC, TyG-WHtR and MASLD. Time-dependent ROC curves demonstrated that TyG-BMI had a superior predictive ability for MASLD onset compared to other indicators.

CONCLUSIONS

The risk of developing MASLD increases as the level of cardiometabolic indices increases. Obesity may serve as a mediating factor in the aforementioned association. TyG-BMI showed the strongest association with the onset of MASLD and its progression to liver fibrosis, proved to be outperformed other cardiometabolic indicators, and could be the best clinical non-invasive biomarker for early screening of MASLD and liver fibrosis.