Association between triglyceride glucose-related markers and the risk of metabolic-associated fatty liver disease: a cross-sectional study in healthy Chinese participants

Metabolic dysfunction associated fatty liver disease in healthy weight individuals

Metabolic dysfunction associated fatty liver disease (MAFLD) is an increasing public health problem, affecting one third of the global population. Contrary to conventional wisdom, MAFLD is not exclusive to obese or overweight individuals. Epidemiological studies have revealed a remarkable prevalence among healthy weight individuals, leading investigations into the genetic, lifestyle, and dietary factors that contribute to the development of MAFLD in this population. This shift in perspective requires reconsideration of preventive strategies, diagnostic criteria and therapeutic approaches tailored to address the unique characteristics of MAFLD healthy weight individuals. It also underscores the importance of widespread awareness and education, within the medical community and among the general population, to promote a more inclusive understanding of liver metabolic disorders. With this review, we aim to provide a comprehensive exploration of MAFLD in healthy weight individuals, encompassing epidemiological, pathophysiological, and clinical aspects.

Triglyceride glucose index as a predictor for non-alcoholic fatty liver disease: insights from a longitudinal analysis in non-obese individuals

Background

A substantial portion of non-obese population is afflicted with Non-alcoholic Fatty Liver Disease (NAFLD). The Triglyceride Glucose (TyG) index, a quantifier of insulin resistance magnitude, is determined by the product of fasting plasma glucose and triglyceride concentrations. The relationship between the TyG index and NAFLD within this cohort remains ambiguous.

Methods

We conducted a retrospective analysis utilizing datasets acquired from the Dryad digital repository. Non-obese participants (BMI < 25 kg/m2) were enrolled at the Wenzhou Medical Center of Wenzhou People's Hospital between January 2010 and December 2014. Demographic information and biochemical parameters were systematically compiled, and the diagnosis of NAFLD was established through ultrasonographic evidence.

Results

This study cohort included 16,172 non-obese participants with a 5-year follow-up, among whom 2,322 (14.36%) developed NAFLD. The disparity between TyG index quartiles in the accumulative incidence of new-onset NAFLD was distinct, with an increasing risk of new-onset NAFLD as the TyG index increased. Participants in highest quartile exhibited the maximum risk of NAFLD. In the fully adjusted model 3, the hazard ratios for NAFLD in Q2, Q3, and Q4 were 2.15 (1.62, 2.87), 2.89 (2.20, 3.80) and 4.58 (3.48, 6.02), respectively. Meanwhile, the TyG index and NAFLD risk showed a highly significant overall correlation (p < 0.0001) and nonlinearity (p < 0.0001) according to the limited cubic splines. In subgroup analysis, a significant interaction was noted between new-onset NAFLD and SBP (<140 mmHg vs. ≥140 mmHg; P for interaction = 0.0114). The SBP < 140 mmHg subgroup demonstrated an enhanced TyG index influence on NAFLD risk (HR = 2.83, 95% CI: 2.48-3.23, p < 0.0001).

Conclusion

The TyG index serves as a straightforward instrument for assessing NAFLD risk in non-obese individuals, enabling prompt identification and management in this population segment.

Diagnostic Accuracy of the Triglyceride-Glucose Index (TyG), TyG Body Mass Index, and TyG Waist Circumference Index for Liver Steatosis Detection

BACKGROUND

The triglyceride-glucose index (TyG) and a combination of body mass index (BMI) and waist circumference (WC) have been proposed as predictive scores for liver steatosis (LS). The aim of this study was to determine the diagnostic accuracy of these indices compared with controlled attenuation parameters (CAPs) and other predictive scores of LS.

METHODS

A retrospective analysis of patients who attended a check-up unit in 2021 was performed. LS was determined by CAP. Anthropometric and biochemical parameters for calculating TyG, TyG-BMI, TyG-WC, fatty liver index, and hepatic steatosis index were obtained. ROC curve was used to establish the best cut-off point of each TyG index for LS detection. The accuracy was determined for all patients, as well as for overweight and diabetic patients.

RESULTS

Medical records of 855 patients with a median age of 48 [IQR, 44-54] years and a BMI of 25.7 [IQR 23.4-28.1] kg/m2 were included. According to CAP, LS prevalence was 31.8% (n = 272). TyG-BMI and TyG-WC show better AUCs compared with CAP (0.82, 0.81), FLI (0.96, both), and HSI (0.93, 0.85). For diabetic patients, TyG-WC shows an AUC of 0.70. Meanwhile, TyG-BMI shows better accuracy (0.75) compared with CAP.

CONCLUSIONS

TyG-BMI and TyG-WC showed a superior predictive accuracy for detecting LS compared with the TyG index.

Increased pretreatment triglyceride glucose-body mass index associated with poor prognosis in patients with advanced non-small cell lung cancer

BACKGROUND

The association between the triglyceride glucose-body mass index (TyG-BMI) and various health outcomes has been postulated. Nonetheless, the application of TyG-BMI in predicting the prognosis of non-small cell lung cancer (NSCLC) remains poorly understood. Our objective was to explore the association between TyG-BMI and both progression-free survival (PFS) and overall survival (OS) in patients with advanced NSCLC.

METHODS

A retrospective study was conducted on the data of 426 patients diagnosed with advanced NSCLC between 2018 and 2022. The TyG-BMI values were derived from the serum triglyceride, fasting plasma glucose, and BMI measurements obtained at the time of diagnosis. Cox proportional hazards regression models were applied to examine the impact of TyG-BMI on both progression-free survival (PFS) and overall survival (OS) in advanced NSCLC.

RESULTS

The median duration of follow-up was 899 days, with an interquartile range of 256-1486 days. In comparison to the lowest tertile of TyG-BMI, the highest tertile model demonstrated a significant association with worse OS (hazard ratio [HR]: 1.85; 95% confidence interval [CI]: 1.21-2.80; P = 0.001) and PFS (HR: 2.10; 95% CI: 1.40-3.10; P < 0.001). Each standard deviation increase in TyG-BMI corresponded to a 10% reduction in OS (95% CI: 1%-24%) and a 14% reduction in PFS (95% CI: 2%-27%). Subgroup analyses indicated that cigarette smokers and individuals with elevated C-reactive protein (CRP) levels exhibited a notably unfavorable prognosis in relation to TyG-BMI-associated advanced NSCLC, as evident in both OS (P for interaction: 0.046 for smoking) and PFS (P for interaction: 0.033 for smoking and 0.049 for CRP).

CONCLUSION

Our data revealed a causal relationship between TyG-BMI and an unfavorable prognosis in patients with advanced NSCLC. Furthermore, this independent association exhibits greater significance in individuals who are smokers and exhibit higher levels of CRP.

Comparison of the diagnostic performance of twelve noninvasive scores of metabolic dysfunction-associated fatty liver disease

BACKGROUND

The absence of distinct symptoms in the majority of individuals with metabolic dysfunction-associated fatty liver disease (MAFLD) poses challenges in identifying those at high risk, so we need simple, efficient and cost-effective noninvasive scores to aid healthcare professionals in patient identification. While most noninvasive scores were developed for the diagnosis of nonalcoholic fatty liver disease (NAFLD), consequently, the objective of this study was to systematically assess the diagnostic ability of 12 noninvasive scores (METS-IR/TyG/TyG-WC/TyG-BMI/TyG-WtHR/VAI/HSI/FLI/ZJU/FSI/K-NAFLD) for MAFLD.

METHODS

The study recruited eligible participants from two sources: the National Health and Nutrition Examination Survey (NHANES) 2017-2020.3 cycle and the database of the West China Hospital Health Management Center. The performance of the model was assessed using various metrics, including area under the receiver operating characteristic curve (AUC), net reclassification index (NRI), integrated discrimination improvement (IDI), decision curve analysis (DCA), and subgroup analysis.

RESULTS

A total of 7398 participants from the NHANES cohort and 4880 patients from the Western China cohort were included. TyG-WC had the best predictive power for MAFLD risk in the NHANES cohort (AUC 0.863, 95% CI 0.855-0.871), while TyG-BMI had the best predictive ability in the Western China cohort (AUC 0.903, 95% CI 0.895-0.911), outperforming other models, and in terms of IDI, NRI, DCA, and subgroup analysis combined, TyG-WC remained superior in the NAHANES cohort and TyG-BMI in the Western China cohort.

CONCLUSIONS

TyG-BMI demonstrated satisfactory diagnostic efficacy in identifying individuals at a heightened risk of MAFLD in Western China. Conversely, TyG-WC exhibited the best diagnostic performance for MAFLD risk recognition in the United States population. These findings suggest the necessity of selecting the most suitable predictive models based on regional and ethnic variations.