Performance of MAST, FAST, and MEFIB in predicting metabolic dysfunction-associated steatohepatitis.

BACKGROUND AND AIM: To identify individuals with metabolic dysfunction-associated steatohepatitis (MASH) or "at-risk" MASH among patients with metabolic dysfunction-associated steatotic liver disease (MASLD), three noninvasive models are available with satisfactory efficiency, which include magnetic resonance imaging [MRI]- AST (MAST), FibroScan-AST (FAST score), and magnetic resonance elastography [MRE] plus FIB-4 (MEFIB). We aimed to evaluate the most accurate approach for diagnosing MASH or "at-risk" MASH. METHODS: We included 108 biopsy-proven MASLD patients who underwent simultaneous assessment of MRE, MRI proton density fat fraction (MRI-PDFF), and FibroScan scans. Compared with the histological diagnosis, we analyzed the AUC of each model and assessed the accuracy. RESULTS: Our study cohort consisted of 64.8% of MASH and 25.9% of "at-risk" MASH. When analyzing the performance of each model for the diagnostic accuracy of MASH, we found that the AUC [95% CI] of MAST was comparable to FAST (0.803 [0.719-0.886] vs 0.799 [0.707-0.891], P = 0.930) and better than MEFIB (0.671 [0.571-0.772], P = 0.005). Similar findings were observed in the "at-risk" MASH patients. The AUCs [95% CI] for MAST, FAST, and MEFIB were 0.810 [0.719-0.900], 0.782 [0.689-0.874], and 0.729 [0.619-0.838], respectively. The models of MAST and FAST had comparable AUCs (P = 0.347), which were statistically significantly higher than that of MEFIB (P = 0.041). Additionally, the cutoffs for diagnosis of MASH were lower than "at-risk" MASH. CONCLUSION: MAST and FAST performed better than MEFIB in diagnosing "at-risk" MASH and MASH using lower cutoff values. Our findings provided evidence for selecting the most accurate noninvasive model to identify patients with MASH or at-risk MASH.

Inflammation activity affects liver stiffness measurement by magnetic resonance elastography in MASLD.

BACKGROUND: Magnetic resonance elastography (MRE) is recognized as the most precise imaging technology for assessing liver fibrosis in individuals with metabolic dysfunction-associated steatotic liver disease (MASLD). We aimed to investigate the clinical factors and pathological characteristics that may impact LSM in MASLD patients. METHODS: This cross-sectional study recruited 124 patients who concurrently performed MRE, MRI-PDFF, and biopsy-proven MASLD. Linear regression models, Spearman's correlation, and subgroup analysis were employed to identify the variables affecting LSM. RESULTS: The AUROC (95 % CI) of MRE for diagnosing fibrosis stage ≥ 1, 2, 3, and 4 was 0.80 (0.70-0.90), 0.76 (0.66-0.85), 0.92 (0.86-0.99), and 0.99 (0.99-1.00), with corresponding cutoffs of 2.56, 2.88, 3.35, and 4.76 kPa, respectively. Multivariate analyses revealed that AST was the only independent clinical variable significantly correlated with LSM. Furthermore, LSM exhibited a notable association with the grade of lobular inflammation and hepatocellular ballooning. Subgroup analysis showed that when AST ≥ 2 ULN or inflammation grade ≥ 2, LSM of patients with early fibrosis stages showed a slight but significant increase. CONCLUSION: MRE demonstrates significant diagnostic accuracy in predicting liver fibrosis stages for MASLD patients, especially for advanced liver fibrosis and cirrhosis. However, elevated AST and the severity of liver inflammation may impact its accuracy in staging early liver fibrosis.

SAMM50-rs2073082, -rs738491 and -rs3761472 Interactions Enhancement of Susceptibility to Non-Alcoholic Fatty Liver Disease.

BACKGROUND AND AIM: Several studies have identified that three SAMM50 polymorphisms (rs2073082, rs738491, rs3761472) are associated with an increased risk of non-alcoholic fatty liver disease (NAFLD). However, the clinical significance of the SAMM50 SNP in relation to NAFLD remains largely unknown. Therefore, we conducted a clinical study and SNP-SNP interaction analysis to further elucidate the effect of the SAMM50 SNP on the progression of NAFLD in the elderly. METHODS: A total of 1053 patients over the age of 65 years were recruited. Liver fat and fibrosis were detected by abdominal ultrasound or FibroScan, respectively. Genomic DNA was extracted and then genotyped by Fluidigm 96.96 Dynamic Array. Multivariable logistic regression was used to evaluate the association between NAFLD and SNP. SNP-SNP interactions were analyzed using generalized multivariate dimensionality reduction (GMDR). RESULTS: The risk of NAFLD was substantially higher in people who carried SAMM50-rs2073082 G and -rs738491 T alleles (OR, 1.962; 95% CI, 1.448-2.659; p < 0.001; OR, 1.532; 95% CI, 1.246-1.884; p = 0.021, respectively) compared to noncarriers. Carriers of the rs738491 T and rs3761472 G alleles in the cohort showed a significant increase in liver stiffness measurements (LSM). The combination of the three SNPs showed the highest predictive power for NAFLD. The rs2073082 G allele, rs738491 T allele and rs3761472 G carriers had a two-fold higher risk of NAFLD compared to noncarriers. CONCLUSIONS: Our research has demonstrated a strong correlation between the genetic polymorphism of SAMM50 and NAFLD in the elderly, which will contribute to a better understanding of the impact of age and genetics on this condition. Additionally, this study provides a potential predictive model for the early clinical warning of NAFLD.

Network Pharmacology and Molecular Docking-Based Strategy to Investigate the Multitarget Mechanisms of Shenqi Yizhi Granule on Alzheimer's Disease.

Background: Traditional Chinese herbal medicine draws more attention to explore an effective therapeutic strategy for Alzheimer's disease (AD). Shenqi Yizhi granule (SQYG), a Chinese herbal recipe, has been applied to ameliorate cognitive impairment in mild-to-moderate AD patients. However, the overall molecular mechanism of SQYG in treating AD has not been clarified. Objective: This study aimed to investigate the molecular mechanism of SQYG on AD using an integration strategy of network pharmacology and molecular docking. Methods: The active compounds of SQYG and common targets between SQYG and AD were screened from databases. The herb-compound network, compound-target network, and protein-protein interaction network were constructed. The enrichment analysis of common targets and molecular docking were performed. Results: 816 compounds and 307 common targets between SQYG and AD were screened. KEGG analysis revealed that common targets were mainly enriched in lipid metabolism, metal ion metabolism, IL-17 signaling pathway, GABA receptor signaling, and neuroactive ligand-receptor interaction. Molecular docking analysis showed high binding affinity between ginsenoside Rg1 and Aß 1-42, tanshinone IIA and BACE1, baicalin, and AchE. Conclusions: The therapeutic mechanisms of SQYG on AD were associated with regulating lipid metabolism, metal ion metabolism, IL-17 signaling pathway, and GABA receptor signaling. Ginsenoside Rg1, tanshinone IIA, baicalin, astragaloside IV, and folic acid may play an important role in AD treatment.