Nonalcoholic fatty liver disease (NAFLD) is the most common chronic liver disease worldwide. The mechanisms involved in NAFLD onset are complicated and multifactorial. Recent literature has indicated that altered intestinal barrier function is related to the occurrence and progression of liver disease. The intestinal barrier is important for absorbing nutrients and electrolytes and for defending against toxins and antigens in the enteric environment. Major mechanisms by which the intestinal barrier influences the development of NAFLD involve the altered epithelial layer, decreased intracellular junction integrity, and increased intestinal barrier permeability. Increased intestinal permeability leads to luminal dysbiosis and allows the translocation of pathogenic bacteria and metabolites into the liver, inducing inflammation, immune response, and hepatocyte injury in NAFLD. Although research has been directed to NAFLD in recent decades, the pathophysiological changes in NAFLD initiation and progression are still not completely understood, and the therapeutic targets remain limited. A deeper understanding on the correlation between NAFLD pathogenesis and intestinal barrier regulation must be attained. Therefore, in this review, the components of the intestinal barrier and their respective functions and disruptions during the progression of NAFLD are discussed.
Background: Although nonalcoholic fatty liver disease (NAFLD) is related to obesity, it may also affect lean individuals. Recent data suggest that lean NAFLD patients can develop the whole spectrum of NASH. However, the NAFLD predictive model for lean populations remains lacking. Methods: A total of 5037 lean individuals were included in this study, and the data were separated for training and validation. The logistic regression method was used, and a nomogram, a type of prediction model, was constructed according to the logistic regression analysis and the significant clinical factors. The performance of this model was evaluated based on its discrimination, calibration, and clinical utility. Results: The individuals were divided into the training (n = 4068) or validation (n = 969) cohorts at a ratio of 8 to 2. The overall prevalence of NAFLD in the lean cohort was 6.43%. The nomogram was constructed based on seven predictors: alanine aminotransferase, total cholesterol, triglycerides, low-density lipoprotein cholesterol, creatinine, uric acid, and hemoglobin A1C. The model based on these factors showed good predictive accuracy in the training set and in the internal validation set, with areas under the curve (AUCs) of 0.870 and 0.887, respectively. The calibration curves and decision curve analysis (DCA) displayed good clinical utility. Conclusion: the nomogram model provides a simple and reliable ability to predict the risk of NAFLD in lean subjects. The model can predict lean NAFLD and can help physicians screen and identify lean subjects at a high risk of NAFLD.
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