Search

Background and Aims: Variant in glucokinase regulatory protein (GCKR), associated with lipid and glucose traits, has been suggested to affect fatty liver infiltration. We aimed to assess whether GCKR rs780094 C→T SNP influences the expression of steatosis, lobular inflammation and fibrosis in NAFLD patients, after correction for PNPLA3 genotype. Methods: In 366 consecutive NAFLD patients (197 from Sicily, and 169 from center/northern Italy), we assessed anthropometric, biochemical and metabolic features; liver biopsy was scored according to Kleiner. PNPLA3 rs738409 C>G and GCKR rs780094 C>T single nucleotide polymorphisms were also assessed. Results: At multivariate logistic regression analysis in the entire NAFLD cohort, the presence of significant liver fibrosis (>F1) was independently linked to high HOMA (OR 1.12, 95% CI 1.01–1.23, p = 0.02), NAFLD activity score ≥5 (OR 4.09, 95% CI 2.45–6.81, p<0.001), and GCKR C>T SNP (OR 2.06, 95% CI 1.43–2.98, p<0.001). Similar results were observed considering separately the two different NAFLD cohorts. GCKR C>T SNP was also associated with higher serum triglycerides (ANOVA, p = 0.02) in the entire cohort. Conclusions: In patients with NAFLD, GCKR rs780094 C>T is associated with the severity of liver fibrosis and with higher serum triglyceride levels. [ABSTRACT FROM AUTHOR]

Aims: Metabolic dysfunction Associated Steatotic Liver Disease (MASLD) outcomes such as MASH (metabolic dysfunction associated steatohepatitis), fibrosis and cirrhosis are ordinarily determined by resource-intensive and invasive biopsies. We aim to show that routine clinical tests offer sufficient information to predict these endpoints. Methods: Using the LITMUS Metacohort derived from the European NAFLD Registry, the largest MASLD dataset in Europe, we create three combinations of features which vary in degree of procurement including a 19-variable feature set that are attained through a routine clinical appointment or blood test. This data was used to train predictive models using supervised machine learning (ML) algorithm XGBoost, alongside missing imputation technique MICE and class balancing algorithm SMOTE. Shapley Additive exPlanations (SHAP) were added to determine relative importance for each clinical variable. Results: Analysing nine biopsy-derived MASLD outcomes of cohort size ranging between 5385 and 6673 subjects, we were able to predict individuals at training set AUCs ranging from 0.719-0.994, including classifying individuals who are At-Risk MASH at an AUC = 0.899. Using two further feature combinations of 26-variables and 35-variables, which included composite scores known to be good indicators for MASLD endpoints and advanced specialist tests, we found predictive performance did not sufficiently improve. We are also able to present local and global explanations for each ML model, offering clinicians interpretability without the expense of worsening predictive performance. Conclusions: This study developed a series of ML models of accuracy ranging from 71.9—99.4% using only easily extractable and readily available information in predicting MASLD outcomes which are usually determined through highly invasive means. [ABSTRACT FROM AUTHOR]

Background: Nonalcoholic fatty liver disease (NAFLD) and gallstone disease (GD) are both highly prevalent in the general population and associated with obesity and insulin resistance. We aimed to evaluate the prevalence of GD in a cross sectional study of NAFLD patients and to define whether the presence of GD is associated with diabetes and predicts more severe liver disease. Methodology/Principal Findings: We merged databases of four Liver Units, comprising 524 consecutive biopsy-proven NAFLD (373 males) observed between January 2003 and June 2010. GD was diagnosed in 108 (20%), and 313 cases (60%) were classified by liver biopsy as nonalcoholic steatohepatitis (NASH). The GD subgroup was characterized by a significantly higher prevalence of females, prediabetes/diabetes, abdominal obesity and metabolic syndrome, older age, higher BMI, fasting glucose, HOMA-IR and lower ALT. The prevalence of GD progressively increased with advancing fibrosis and with the severity of necroinflammatory activity (p for trend = 0.0001 and = 0.01, respectively), without differences in the severity of steatosis. At multivariate analysis GD was associated with female gender (OR 1.37, 95% CI 1.04-1.8), age (OR 1.027, 95% CI1.003-1.05), fasting glucose (OR 1.21, 95% CI 1.10-1.33) and NASH (OR 1.40,95% CI 1.06-1.89), whereas ALT levels were associated with a lower GD risk (OR 0.98, 95% CI 0.97-0.99). When subjects with cirrhosis were excluded from analysis, the association between GD and fasting glucose, female gender, and NASH was maintained. Conclusion: Patients with NAFLD have a high prevalence of GD, which characterizes subjects with altered glucose regulation and more advanced liver disease. [ABSTRACT FROM AUTHOR]