Dietary inflammatory index is associated with metabolic dysfunction-associated fatty liver disease among United States adults

Unraveling the Metabolic Pathways Between Metabolic-Associated Fatty Liver Disease (MAFLD) and Sarcopenia

Metabolic-Associated Fatty Liver Disease (MAFLD) is a public health concern that is constantly expanding, with a fast-growing prevalence, and it affects about a quarter of the world's population. This condition is a significant risk factor for cardiovascular, hepatic, and oncologic diseases, such as hypertension, hepatoma, and atherosclerosis. Sarcopenia was long considered to be an aging-related syndrome, but today, it is acknowledged to be secondarily related to chronic diseases such as metabolic syndrome, cardiovascular conditions, and liver diseases, among other comorbidities associated with insulin resistance and chronic inflammation, besides inactivity and poor nutrition. The physiopathology involving MAFLD and sarcopenia has still not been solved. Inflammation, oxidative stress, mitochondrial dysfunction, and insulin resistance seem to be some of the keys to this relationship since this hormone target is mainly the skeletal muscle. This review aimed to comprehensively discuss the main metabolic and physiological pathways involved in these conditions. MAFLD and sarcopenia are interconnected by a complex network of pathophysiological mechanisms, such as insulin resistance, skeletal muscle tissue production capacity, chronic inflammatory state, oxidative stress, and mitochondrial dysfunction, which are the main contributors to this relationship. In addition, in a clinical analysis, patients with sarcopenia and MAFLD manifest more severe hepatitis fibrosis when compared to patients with only MAFLD. These patients, with both disorders, also present clinical improvement in their MAFLD when treated for sarcopenia, reinforcing the association between them. Lifestyle changes accompanied by non-pharmacological interventions, such as dietary therapy and increased physical activity, undoubtedly improve this scenario.

Artificial Intelligence-Based Diets: A Role in the Nutritional Treatment of Metabolic Dysfunction-Associated Steatotic Liver Disease?

BACKGROUND

Metabolic dysfunction-associated steatotic liver disease (MASLD) is a growing global health concern. Effective management of this condition relies heavily on lifestyle modifications and dietary interventions. In this study, we sought to evaluate the dietary plans for MASLD generated by ChatGPT (GPT-4o) according to current guideline recommendations.

METHODS

ChatGPT was used to create single-day meal plans for 48 simulated patients with MASLD, tailored to individual characteristics such as age, gender, height, weight and transient elastography parameters. The plans were assessed for appropriateness according to disease-specific guidelines.

RESULTS

The mean energy content of the menus planned by ChatGPT was 1596.9 ± 141.5 kcal with a mean accuracy of 91.3 ± 11.0%, and fibre content was 22.0 ± 0.6 g with a mean accuracy of 88.1 ± 2.5%. However, they exhibited elevated levels of protein, fat and saturated fat acids. Conversely, the carbohydrate content was lower. ChatGPT recommended weight loss for obese patients but did not extend this advice to normal-weight and overweight individuals. Notably, recommendations for a Mediterranean diet and physical activity were absent.

CONCLUSIONS

ChatGPT shows potential in developing dietary plans for MASLD management. However, discrepancies in macronutrient distributions and the omission of key evidence-based recommendations highlight the need for further refinement. To enhance the effectiveness of AI tools in dietary recommendations, alignment with established guidelines must be improved.

Exploring the association between pro-inflammatory diets and chronic liver diseases: evidence from the UK Biobank

Background

Chronic liver diseases (CLD) continue to pose a significant global burden, potentially exacerbated by pro-inflammatory diets. This study explores the relationship between the Dietary Inflammatory Index (DII), a measure of dietary inflammatory potential, and CLD risk.

Methods

Utilizing data from the UK Biobank cohort, we assessed the dietary information and calculated the DII for each participant. Cox proportional hazards models and Fine-Gray competing risk models were employed to evaluate the association between DII and CLD incidence, adjusting for potential confounders.

Results

Our analysis included 121,329 participants with a median follow-up of 604.43 weeks, during which 4,018 developed CLD. A higher DII, indicating a more inflammatory diet, was associated with a 16% increased risk of CLD [hazard ratio (HR) = 1.162, P = 0.001], with each unit increase in DII elevating the risk by 3.3% (HR: 1.033, P < 0.001). A significant linear association between DII and CLD was observed. Competing risk analyses, which accounted for cirrhosis, liver cancer, and death, supported these findings. Subgroup analyses confirmed the robustness of the DII's association across various demographic and lifestyle factors. Moreover, a higher DII was positively associated with the progression of CLD to cirrhosis. Sensitivity analyses, including energy-adjusted DII and typical dietary DII, reinforced our results. Additionally, adherence to anti-inflammatory dietary patterns, as indicated by higher Healthy Eating Index 2020 and Mediterranean Diet Score values, was inversely associated with CLD risk.

Conclusion

Our study highlights the potential benefits of adopting anti-inflammatory diets as a strategy for the prevention and management of CLD. Comprehensive dietary interventions may play a pivotal role in mitigating the global burden of CLD.

Development and validation of machine learning models for MASLD: based on multiple potential screening indicators

Background

Multifaceted factors play a crucial role in the prevention and treatment of metabolic dysfunction-associated steatotic liver disease (MASLD). This study aimed to utilize multifaceted indicators to construct MASLD risk prediction machine learning models and explore the core factors within these models.

Methods

MASLD risk prediction models were constructed based on seven machine learning algorithms using all variables, insulin-related variables, demographic characteristics variables, and other indicators, respectively. Subsequently, the partial dependence plot(PDP) method and SHapley Additive exPlanations (SHAP) were utilized to explain the roles of important variables in the model to filter out the optimal indicators for constructing the MASLD risk model.

Results

Ranking the feature importance of the Random Forest (RF) model and eXtreme Gradient Boosting (XGBoost) model constructed using all variables found that both homeostasis model assessment of insulin resistance (HOMA-IR) and triglyceride glucose-waist circumference (TyG-WC) were the first and second most important variables. The MASLD risk prediction model constructed using the variables with top 10 importance was superior to the previous model. The PDP and SHAP methods were further utilized to screen the best indicators (including HOMA-IR, TyG-WC, age, aspartate aminotransferase (AST), and ethnicity) for constructing the model, and the mean area under the curve value of the models was 0.960.

Conclusions

HOMA-IR and TyG-WC are core factors in predicting MASLD risk. Ultimately, our study constructed the optimal MASLD risk prediction model using HOMA-IR, TyG-WC, age, AST, and ethnicity.

Association between the dietary inflammatory index and the risk of hepatocellular carcinoma in a cirrhotic population

BACKGROUND & AIMS

Hepatocellular carcinoma (HCC) is recognized as an inflammation-related cancer. However, the relation between inflammation deriving from the diet and HCC risk among cirrhotic patients has not yet been investigated. This study aimed to examine the association between the dietary inflammatory index (DII®) and HCC risk among cirrhotic patients.

METHODS

Clinical and dietary data were collected from the French case-control study CiRCE (Cirrhosis and Risk of hepatocellular Carcinoma in the East), which included 401 cirrhotic patients without HCC (controls) and 181 cirrhotic patients with HCC (cases) recruited between 2008 and 2012 in six French university hospitals. DII scores (36 food items and nutrients) were assessed using a validated self-administered diet history questionnaire. Odds ratios (OR) and 95 % confidence intervals (CI) were estimated with logistic regression models (adjusted for age, gender, time from cirrhosis diagnosis, etiology of cirrhosis, Child-Pugh score, and diabetes).

RESULTS

The DII scores ranged between -4.77 and +7.59 with a mean value of 1.03 ± 2.87 among cases and 0.83 ± 2.87 among controls, indicating that both groups were following a pro-inflammatory diet. After multi-variable adjustment, there was a positive association between HCC risk and the DII score when considered as a continuous variable (ORcontinuous = 1.14 [1.02-1.27], p-value = 0.021) or categorized in tertiles (ORT3vsT1 = 2.33 [1.16-4.67], p-trend = 0.021). Similar results were found when alcohol was omitted from the DII calculation but considered as a co-variate: ORcontinuous = 1.15 [1.03-1.28], p-value = 0.013, and ORT3vsT1 = 2.35 [1.18-4.68], p-trend = 0.015. A positive correlation was observed between the DII scores and two inflammatory biomarkers (CRP, IL-6) among controls.

CONCLUSION

The present study reported an association between a pro-inflammatory DII score and the risk of HCC in cirrhotic patients. Correlations between the scores and biological parameters support a potential role for inflammation in HCC among cirrhotic. Result should be confirmed in larger prospective studies, and could lead to nutritional prevention in cirrhotic patients.

CLINICAL TRIAL REGISTRY

This study was registered in www.

CLINICALTRIALS

gov as NCT01798173.

Anti-inflammatory diet reduces risk of metabolic dysfunction-associated fatty liver disease among US adults: a nationwide survey

BACKGROUND

While dietary intervention was an important public health strategy for the prevention and intervention of metabolic dysfunction-associated fatty liver disease (MAFLD), the effect of diet-induced inflammation on MAFLD has not been studied in detail. Therefore, we aimed to analyze the relationship between dietary inflammatory index (DII) and MAFLD.

METHODS

This study included data from the National Health and Nutrition Examination Survey 2017-2018. MAFLD was diagnosed based on the presence of hepatic steatosis, as determined by transient elastography, along with evidence of either overweight/obesity, type 2 diabetes mellitus, or metabolic dysfunction. DII was calculated using 27 dietary components collected through 24-hour dietary recall questionnaire. Weighted logistic regression was used to analyze the relationship between DII and MAFLD and its main components in three different models. Subgroup analyses were performed by age, sex, and alcohol use.

RESULTS

A total of 1991 participants were included, and the MAFLD group had higher DII scores. After adjusting for age, sex, race, physical activity, smoking status, and alcohol use, the highest quartile of DII was associated with increased risk of MAFLD (OR:2.90, 95% CIs: 1.46, 5.75). Overweight/obesity, central obesity, low high density lipoprotein cholesterol (HDL-C) and high C-reactive protein (CRP) also shared the same characteristics in the main components of MAFLD. Results were consistent across subgroups (age, sex, and alcohol use).

CONCLUSIONS

A higher DII diet was positively associated with the risk of MAFLD in American adults, particularly as related to overweight/obesity, central obesity, high CRP level, and low HDL-C level.