Intact Fasting Insulin Identifies Nonalcoholic Fatty Liver Disease in Patients Without Diabetes

The role of gut microbiota augmentation in managing non-alcoholic fatty liver disease: an in-depth umbrella review of meta-analyses with grade assessment

Background and aim

Currently, there are no authorized medications specifically for non-alcoholic fatty liver disease (NAFLD) treatment. Studies indicate that changes in gut microbiota can disturb intestinal balance and impair the immune system and metabolism, thereby elevating the risk of developing and exacerbating NAFLD. Despite some debate, the potential benefits of microbial therapies in managing NAFLD have been shown.

Methods

A systematic search was undertaken to identify meta-analyses of randomized controlled trials that explored the effects of microbial therapy on the NAFLD population. The goal was to synthesize the existing evidence-based knowledge in this field.

Results

The results revealed that probiotics played a significant role in various aspects, including a reduction in liver stiffness (MD: -0.38, 95% CI: [-0.49, -0.26]), hepatic steatosis (OR: 4.87, 95% CI: [1.85, 12.79]), decrease in body mass index (MD: -1.46, 95% CI: [-2.43, -0.48]), diminished waist circumference (MD: -1.81, 95% CI: [-3.18, -0.43]), lowered alanine aminotransferase levels (MD: -13.40, 95% CI: [-17.02, -9.77]), decreased aspartate aminotransferase levels (MD: -13.54, 95% CI: [-17.85, -9.22]), lowered total cholesterol levels (MD: -15.38, 95% CI: [-26.49, -4.26]), decreased fasting plasma glucose levels (MD: -4.98, 95% CI: [-9.94, -0.01]), reduced fasting insulin (MD: -1.32, 95% CI: [-2.42, -0.21]), and a decline in homeostatic model assessment of insulin resistance (MD: -0.42, 95% CI: [-0.72, -0.11]) (P<0.05).

Conclusion

Overall, the results demonstrated that gut microbiota interventions could ameliorate a wide range of indicators including glycemic profile, dyslipidemia, anthropometric indices, and liver injury, allowing them to be considered a promising treatment strategy.

Metabolic-associated fatty liver disease is characterized by a post-oral glucose load hyperinsulinemia in individuals with mild metabolic alterations

Metabolic-associated fatty liver disease (MAFLD) has been identified as risk factor of incident type 2 diabetes (T2D), but the underlying postprandial mechanisms remain unclear. We compared the glucose metabolism, insulin resistance, insulin secretion, and insulin clearance post-oral glucose tolerance test (OGTT) between individuals with and without MAFLD. We included 50 individuals with a body mass index (BMI) between 25 and 40 kg/m2 and ≥1 metabolic alteration: increased fasting triglycerides or insulin, plasma glucose 5.5-6.9 mmol/L, or glycated hemoglobin 5.7-5.9%. Participants were grouped according to MAFLD status, defined as hepatic fat fraction (HFF) ≥5% on MRI. We used oral minimal model on a frequently sampled 3 h 75 g-OGTT to estimate insulin sensitivity, insulin secretion, and pancreatic β-cell function. Fifty percent of participants had MAFLD. Median age (IQR) [57 (45-65) vs. 57 (44-63) yr] and sex (60% vs. 56% female) were comparable between groups. Post-OGTT glucose concentrations did not differ between groups, whereas post-OGTT insulin concentrations were higher in the MAFLD group (P < 0.03). Individuals with MAFLD exhibited lower insulin clearance, insulin sensitivity, and first-phase pancreatic β-cell function. In all individuals, increased insulin incremental area under the curve and decreased insulin clearance were associated with HFF after adjusting for age, sex, and BMI (P < 0.02). Among individuals with metabolic alterations, the presence of MAFLD was characterized mainly by post-OGTT hyperinsulinemia and reduced insulin clearance while exhibiting lower first phase β-cell function and insulin sensitivity. This suggests that MAFLD is linked with impaired insulin metabolism that may precede T2D.NEW & NOTEWORTHY Using an oral glucose tolerance test, we found hyperinsulinemia, lower insulin sensitivity, lower insulin clearance, and lower first-phase pancreatic β-cell function in individuals with MAFLD. This may explain part of the increased risk of incident type 2 diabetes in this population. These data also highlight implications of hyperinsulinemia and impaired insulin clearance in the progression of MAFLD to type 2 diabetes.

Validation of a screening panel for pediatric metabolic dysfunction-associated steatotic liver disease using metabolomics

BACKGROUND

Metabolic dysfunction-associated steatotic liver disease (MASLD), formerly known as NAFLD, is the most common liver disease in children. Liver biopsy remains the gold standard for diagnosis, although more efficient screening methods are needed. We previously developed a novel NAFLD screening panel in youth using machine learning applied to high-resolution metabolomics and clinical phenotype data. Our objective was to validate this panel in a separate cohort, which consisted of a combined cross-sectional sample of 161 children with stored frozen samples (75% male, 12.8±2.6 years of age, body mass index 31.0±7.0 kg/m2, 81% with MASLD, 58% Hispanic race/ethnicity).

METHODS

Clinical data were collected from all children, and high-resolution metabolomics was performed using their fasting serum samples. MASLD was assessed by MRI-proton density fat fraction or liver biopsy and cardiometabolic factors. Our previously developed panel included waist circumference, triglycerides, whole-body insulin sensitivity index, 3 amino acids, 2 phospholipids, dihydrothymine, and 2 unknowns. To improve feasibility, a simplified version without the unknowns was utilized in the present study. Since the panel was modified, the data were split into training (67%) and test (33%) sets to assess the validity of the panel.

RESULTS

Our present highest-performing modified model, with 4 clinical variables and 8 metabolomics features, achieved an AUROC of 0.92, 95% sensitivity, and 80% specificity for detecting MASLD in the test set.

CONCLUSIONS

Therefore, this panel has promising potential for use as a screening tool for MASLD in youth.

Automated machine learning models for nonalcoholic fatty liver disease assessed by controlled attenuation parameter from the NHANES 2017-2020

Background

Nonalcoholic fatty liver disease (NAFLD) is recognized as one of the most common chronic liver diseases worldwide. This study aims to assess the efficacy of automated machine learning (AutoML) in the identification of NAFLD using a population-based cross-sectional database.

Methods

All data, including laboratory examinations, anthropometric measurements, and demographic variables, were obtained from the National Health and Nutrition Examination Survey (NHANES). NAFLD was defined by controlled attenuation parameter (CAP) in liver transient ultrasound elastography. The least absolute shrinkage and selection operator (LASSO) regression analysis was employed for feature selection. Six algorithms were utilized on the H2O-automated machine learning platform: Gradient Boosting Machine (GBM), Distributed Random Forest (DRF), Extremely Randomized Trees (XRT), Generalized Linear Model (GLM), eXtreme Gradient Boosting (XGBoost), and Deep Learning (DL). These algorithms were selected for their diverse strengths, including their ability to handle complex, non-linear relationships, provide high predictive accuracy, and ensure interpretability. The models were evaluated by area under receiver operating characteristic curves (AUC) and interpreted by the calibration curve, the decision curve analysis, variable importance plot, SHapley Additive exPlanation plot, partial dependence plots, and local interpretable model agnostic explanation plot.

Results

A total of 4177 participants (non-NAFLD 3167 vs NAFLD 1010) were included to develop and validate the AutoML models. The model developed by XGBoost performed better than other models in AutoML, achieving an AUC of 0.859, an accuracy of 0.795, a sensitivity of 0.773, and a specificity of 0.802 on the validation set.

Conclusions

We developed an XGBoost model to better evaluate the presence of NAFLD. Based on the XGBoost model, we created an R Shiny web-based application named Shiny NAFLD (http://39.101.122.171:3838/App2/). This application demonstrates the potential of AutoML in clinical research and practice, offering a promising tool for the real-world identification of NAFLD.

Liver insulinization as a driver of triglyceride dysmetabolism

Metabolic dysfunction-associated fatty liver disease (MAFLD) is an increasingly prevalent fellow traveller with the insulin resistance that underlies type 2 diabetes mellitus. However, the mechanistic connection between MAFLD and impaired insulin action remains unclear. In this Perspective, we review data from humans to elucidate insulin's aetiological role in MAFLD. We focus particularly on the relative preservation of insulin's stimulation of triglyceride (TG) biosynthesis despite its waning ability to curb hepatic glucose production (HGP). To explain this apparent 'selective insulin resistance', we propose that hepatocellular processes that lead to TG accumulation require less insulin signal transduction, or 'insulinization,' than do those that regulate HGP. As such, mounting hyperinsulinaemia that barely compensates for aberrant HGP in insulin-resistant states more than suffices to maintain hepatic TG biosynthesis. Thus, even modestly elevated or context-inappropriate insulin levels, when sustained day and night within a heavily pro-lipogenic metabolic milieu, may translate into substantial cumulative TG biosynthesis in the insulin-resistant state.

Associations of NAFLD with circulating ceramides and impaired glycemia

AIM

Determine the association of circulating ceramides with NAFLD and glycemic impairment.

METHODS

Sample: 669 participants in the Mediators of Atherosclerosis in South Asians Living in America (MASALA) cohort aged 40-84 years without cardiovascular disease, cirrhosis, or significant alcohol intake.

CLINICAL MEASURES

Computed tomography scans at baseline for hepatic attenuation. Fasting serum specimens at baseline and after 5 years. Lipidomics: LC-MS-based analysis of 19 known ceramide signals.

STATISTICAL ANALYSIS

Linear and logistic regression models of log-transformed ceramides, hepatic attenuation and glucose adjusted for age, sex, calories, study site, BMI, exercise, diet quality, alcohol, saturated fat, lipid-lowering medications and fasting glucose.

RESULTS

Average age was 55 years, 44% were women, mean BMI was 25.9 kg/m2, and 8% had NAFLD. In adjusted models, Cer(d16:1/20:0) and Cer(d18:1/18:0) were associated with lower mean hepatic attenuation (increased liver fat) (β -4.29; 95% CI [-5.98, -2.59]) and (β -3.40; 95% CI [-5.11, -1.70]), and LacCer(d18:1/16:0) with higher attenuation (β 4.44; 95% CI [2.15, 6.73]). All three ceramides partially mediated the relationship between hepatic attenuation and fasting glucose by 16%, 11% and 5%, respectively, after 5-years.

CONCLUSIONS

Three circulating ceramides were strongly associated with NAFLD and fasting glucose after 5 years, and partially mediated this association.