Oxidative stress in metabolic dysfunction-associated steatotic liver disease (MASLD): How does the animal model resemble human disease?

Despite decades of research, the pathogenesis of metabolic dysfunction-associated steatotic liver disease (MASLD) is still not completely understood. Based on the evidence from preclinical models, one of the factors proposed as a main driver of disease development is oxidative stress. This study aimed to search for the resemblance between the profiles of oxidative stress and antioxidant defense in the animal model of MASLD and the group of MASLD patients. C57BL/6J mice were fed with the Western diet for up to 24 weeks and served as the animal model of MASLD. The antioxidant profile of mice hepatic tissue was determined by liquid chromatography-MS3 spectrometry (LC-MS/MS). The human cohort consisted of 20 patients, who underwent bariatric surgery, and 6 controls. Based on histological analysis, 4 bariatric patients did not have liver steatosis and as such were also classified as controls. Total antioxidant activity was measured in sera and liver biopsy samples. The hepatic levels of antioxidant enzymes and oxidative damage were determined by Western Blot. The levels of antioxidant enzymes were significantly altered in the hepatic tissue of mice with MASLD. In contrast, there were no significant changes in the antioxidant profile of hepatic tissue of MASLD patients, except for the decreased level of carbonylated proteins. Decreased protein carbonylation together with significant correlations between the thioredoxin system and parameters describing metabolic health suggest alterations in the thiol-redox signaling. Altogether, these data show that even though the phenotype of mice closely resembles human MASLD, the animal-to-human translation of cellular and molecular processes such as oxidative stress may be more challenging.

Quantitative digital pathology enables automated and quantitative assessment of inflammatory activity in patients with autoimmune hepatitis.

Background: Chronic liver disease diagnoses depend on liver biopsy histopathological assessment. However, due to the limitations associated with biopsy, there is growing interest in the use of quantitative digital pathology to support pathologists. We evaluated the performance of computational algorithms in the assessment of hepatic inflammation in an autoimmune hepatitis in which inflammation is a major component. Methods: Whole-slide digital image analysis was used to quantitatively characterize the area of tissue covered by inflammation [Inflammation Density (ID)] and number of inflammatory foci per unit area [Focal Density (FD)] on tissue obtained from 50 patients with autoimmune hepatitis undergoing routine liver biopsy. Correlations between digital pathology outputs and traditional categorical histology scores, biochemical, and imaging markers were assessed. The ability of ID and FD to stratify between low-moderate (both portal and lobular inflammation ≤1) and moderate-severe disease activity was estimated using the area under the receiver operating characteristic curve (AUC). Results: ID and FD scores increased significantly and linearly with both portal and lobular inflammation grading. Both ID and FD correlated moderately-to-strongly and significantly with histology (portal and lobular inflammation; 0.36≤R≤0.69) and biochemical markers (ALT, AST, GGT, IgG, and gamma globulins; 0.43≤R≤0.57). ID (AUC: 0.85) and FD (AUC: 0.79) had good performance for stratifying between low-moderate and moderate-severe inflammation. Conclusion: Quantitative assessment of liver biopsy using quantitative digital pathology metrics correlates well with traditional pathology scores and key biochemical markers. Whole-slide quantification of disease can support stratification and identification of patients with more advanced inflammatory disease activity.