Updates in the quantitative assessment of liver fibrosis for nonalcoholic fatty liver disease: Histological perspective

Appendicular Skeletal Muscle Mass to Visceral Fat Area Ratio Predicts Hepatic Morbidities

Background/Aims

: Reports on the association between sarcopenic visceral obesity and non-alcoholic fatty liver disease (NAFLD)-associated morbidities remain scarce. We investigated the association between sarcopenia and visceral obesity, and the influence of this association on hepatic and coronary comorbidities.

Methods

: The appendicular skeletal muscle mass to visceral fat area ratio (SV ratio) was evaluated using bioelectric impedance analysis. NAFLD and significant liver fibrosis were assessed using transient elastography, and high atherosclerotic cardiovascular disease (ASCVD) risk was defined as a 10-year ASCVD risk score >10%. Sarcopenia was defined as appendicular skeletal muscle mass adjusted by body mass index (<0.789 for men and <0.512 for women).

Results

: In total, 82.0% (n=1,205) of the entire study population had NAFLD, and 14.6% of these individuals (n=176) exhibited significant liver fibrosis. Individuals with the lowest SV ratio had a significantly increased risk of NAFLD, significant liver fibrosis, and high ASCVD risk (all p<0.05). Individuals with both the lowest SV ratio and sarcopenia had the highest risk of developing NAFLD (odds ratio [OR]=3.11), significant liver fibrosis (OR=2.03), and high ASCVD risk (OR=4.15), compared with those with a higher SV ratio and without sarcopenia (all p<0.05).

Conclusions

: Low SV ratio combined with sarcopenia was significantly associated with an increased risk of NAFLD, significant liver fibrosis, and high ASCVD risk among individuals with a high risk of NAFLD.

Digital pathology with artificial intelligence analysis provides insight to the efficacy of anti-fibrotic compounds in human 3D MASH model

Metabolic dysfunction-associated steatohepatitis (MASH) is a severe liver disease characterized by lipid accumulation, inflammation and fibrosis. The development of MASH therapies has been hindered by the lack of human translational models and limitations of analysis techniques for fibrosis. The MASH three-dimensional (3D) InSight™ human liver microtissue (hLiMT) model recapitulates pathophysiological features of the disease. We established an algorithm for automated phenotypic quantification of fibrosis of Sirius Red stained histology sections of MASH hLiMTs model using a digital pathology quantitative single-fiber artificial intelligence (AI) FibroNest™ image analysis platform. The FibroNest™ algorithm for MASH hLiMTs was validated using anti-fibrotic reference compounds with different therapeutic modalities-ALK5i and anti-TGF-β antibody. The phenotypic quantification of fibrosis demonstrated that both reference compounds decreased the deposition of fibrillated collagens in alignment with effects on the secretion of pro-collagen type I/III, tissue inhibitor of metalloproteinase-1 and matrix metalloproteinase-3 and pro-fibrotic gene expression. In contrast, clinical compounds, Firsocostat and Selonsertib, alone and in combination showed strong anti-fibrotic effects on the deposition of collagen fibers, however less pronounced on the secretion of pro-fibrotic biomarkers. In summary, the phenotypic quantification of fibrosis of MASH hLiMTs combined with secretion of pro-fibrotic biomarkers and transcriptomics represents a promising drug discovery tool for assessing anti-fibrotic compounds.

Artificial intelligence-assisted digital pathology for non-alcoholic steatohepatitis: current status and future directions

The worldwide prevalence of non-alcoholic steatohepatitis (NASH) is increasing, causing a significant medical burden, but no approved therapeutics are currently available. NASH drug development requires histological analysis of liver biopsies by expert pathologists for trial enrolment and efficacy assessment, which can be hindered by multiple issues including sample heterogeneity, inter-reader and intra-reader variability, and ordinal scoring systems. Consequently, there is a high unmet need for accurate, reproducible, quantitative, and automated methods to assist pathologists with histological analysis to improve the precision around treatment and efficacy assessment. Digital pathology (DP) workflows in combination with artificial intelligence (AI) have been established in other areas of medicine and are being actively investigated in NASH to assist pathologists in the evaluation and scoring of NASH histology. DP/AI models can be used to automatically detect, localise, quantify, and score histological parameters and have the potential to reduce the impact of scoring variability in NASH clinical trials. This narrative review provides an overview of DP/AI tools in development for NASH, highlights key regulatory considerations, and discusses how these advances may impact the future of NASH clinical management and drug development. This should be a high priority in the NASH field, particularly to improve the development of safe and effective therapeutics.

The prediction of liver decompensation using hepatic collagen deposition assessed by computer-assisted image analysis with Masson's trichrome stain

BACKGROUND & AIM

The current pathologic system classifies structural deformation caused by hepatic fibrosis semi-quantitatively, which may lead to a disagreement among pathologists. We measured hepatic fibrosis quantitatively using collagen proportionate area (CPA) in compensated cirrhotic patients and assessed its impact on predicting the development of liver decompensation.

METHOD

From January 2010 to June 2018, we assessed 101 patients who went through liver biopsy and received diagnosis as compensated cirrhosis with digital image analysis of CPA. Clinical and laboratory data were collected at the baseline and at the time of the last follow-up or progression to liver decompensation (LD).

RESULT

The mean age was 50.8 ± 10.5 years, and the most common etiology of liver disease was chronic hepatitis B (48.5%), followed by alcoholic hepatitis (18.8%). The mean CPA was 16.91 ± 9.60%. The mean CPA values were different in patients with and without LD development (21.8 ± 11.1 vs. 15.2 ± 8.5). During the median follow-up of 60.0 months, 26 out of 101 patients experienced LD. Older age (hazard ratio [HR],1.069; p = 0.015), prolonged international normalized ratio (HR, 6.449; p = 0.019) and higher CPA (HR, 1.049; p = 0.040) were independent predictors of liver decompensation on multivariate cox-regression analysis. When patients were divided according to the optimal CPA threshold (26.8%), higher CPA predicted LD better than lower CPA. (Log-rank test: p < 0.001).

CONCLUSION

CPA could be a useful quantitative prognostic value for patients with compensated cirrhosis.

Magnetic resonance elastography-based prediction model for hepatic decompensation in NAFLD: A multicenter cohort study

BACKGROUND AND AIMS

Magnetic resonance elastography (MRE) is an accurate, continuous biomarker of liver fibrosis; however, the optimal combination with clinical factors to predict the risk of incident hepatic decompensation is unknown. Therefore, we aimed to develop and validate an MRE-based prediction model for hepatic decompensation for patients with NAFLD.

APPROACH AND RESULTS

This international multicenter cohort study included participants with NAFLD undergoing MRE from 6 hospitals. A total of 1254 participants were randomly assigned as training (n = 627) and validation (n = 627) cohorts. The primary end point was hepatic decompensation, defined as the first occurrence of variceal hemorrhage, ascites, or HE. Covariates associated with hepatic decompensation on Cox-regression were combined with MRE to construct a risk prediction model in the training cohort and then tested in the validation cohort. The median (IQR) age and MRE values were 61 (18) years and 3.5 (2.5) kPa in the training cohort and 60 (20) years and 3.4 (2.5) kPa in the validation cohort, respectively. The MRE-based multivariable model that included age, MRE, albumin, aspartate aminotransferase, and platelets had excellent discrimination for the 3- and 5-year risk of hepatic decompensation (c-statistic 0.912 and 0.891, respectively) in the training cohort. The diagnostic accuracy remained consistent in the validation cohort with a c-statistic of 0.871 and 0.876 for hepatic decompensation at 3 and 5 years, respectively, and was superior to Fibrosis-4 in both cohorts ( p < 0.05).

CONCLUSIONS

An MRE-based prediction model allows for accurate prediction of hepatic decompensation and assists in the risk stratification of patients with NAFLD.

Diabetic MAFLD is associated with increased risk of hepatocellular carcinoma and mortality in chronic viral hepatitis patients

Metabolic dysfunction-associated fatty liver disease (MAFLD) can coexist with chronic viral hepatitis. MAFLD is a heterogeneous disease because the diagnostic criteria include various metabolic traits. We aimed to identify patients at high risk of poor long-term outcomes based on MAFLD subgroups in chronic viral hepatitis patients. We evaluated 63 273 chronic hepatitis B and C patients. Patient with a fatty liver index ≥30 was defined to have hepatic steatosis. MAFLD was defined as the presence of hepatic steatosis with any one of the following three conditions, overweight/obesity, type 2 diabetes or ≥2 metabolic risk factors. The prevalence of MAFLD was 38.4% (n = 24 290). During a median 8.8-year follow-up, 1839 HCCs and 2258 deaths were documented in MAFLD patients. Among MAFLD patients, diabetes could identify patients at high risk of HCC and mortality, whereas overweight/obesity and metabolic risk factors did not. Compared with non-MAFLD patients, risk of HCC and mortality was significantly higher in diabetic MAFLD patients (adjusted hazard ratio [aHR] = 1.34, 95% confidence interval [CI] = 1.26-1.43 for HCC; aHR = 1.15, 95% CI = 1.08-1.22 for mortality). Risk of HCC and mortality was significantly higher in diabetic MAFLD patients (aHR = 1.40, 95% CI = 1.26-1.55 for HCC; aHR = 1.77, 95% CI = 1.63-1.93 for mortality) compared with non-diabetic MAFLD patients. Diabetic MAFLD is associated with increased risk of HCC and mortality among chronic viral hepatitis patients. Our findings highlight the need for close surveillance and effective treatment for these high-risk patients to reduce HCC and mortality in patients with chronic viral hepatitis.

AutoFibroNet: A deep learning and multi-photon microscopy-derived automated network for liver fibrosis quantification in MAFLD

BACKGROUND

Liver fibrosis is the strongest histological risk factor for liver-related complications and mortality in metabolic dysfunction-associated fatty liver disease (MAFLD). Second harmonic generation/two-photon excitation fluorescence (SHG/TPEF) is a powerful tool for label-free two-dimensional and three-dimensional tissue visualisation that shows promise in liver fibrosis assessment.

AIM

To investigate combining multi-photon microscopy (MPM) and deep learning techniques to develop and validate a new automated quantitative histological classification tool, named AutoFibroNet (Automated Liver Fibrosis Grading Network), for accurately staging liver fibrosis in MAFLD.

METHODS

AutoFibroNet was developed in a training cohort that consisted of 203 Chinese adults with biopsy-confirmed MAFLD. Three deep learning models (VGG16, ResNet34, and MobileNet V3) were used to train pre-processed images and test data sets. Multi-layer perceptrons were used to fuse data (deep learning features, clinical features, and manual features) to build a joint model. This model was then validated in two further independent cohorts.

RESULTS

AutoFibroNet showed good discrimination in the training set. For F0, F1, F2 and F3-4 fibrosis stages, the area under the receiver operating characteristic curves (AUROC) of AutoFibroNet were 1.00, 0.99, 0.98 and 0.98. The AUROCs of F0, F1, F2 and F3-4 fibrosis stages for AutoFibroNet in the two validation cohorts were 0.99, 0.83, 0.80 and 0.90 and 1.00, 0.83, 0.80 and 0.94, respectively, showing a good discriminatory ability in different cohorts.

CONCLUSION

AutoFibroNet is an automated quantitative tool that accurately identifies histological stages of liver fibrosis in Chinese individuals with MAFLD.

Effect of exercise-based interventions in nonalcoholic fatty liver disease: A systematic review with meta-analysis

BACKGROUND

The global burden of nonalcoholic fatty liver disease (NAFLD) is rapidly increasing.

AIMS

This study aimed to evaluate the effect of exercise on intrahepatic lipid (IHL), serum alanine aminotransferase (ALT), body mass index (BMI), and insulin resistance in NAFLD patients.

METHODS

We searched MEDLINE, Embase, Cochrane CENTRAL, KMbase, and the Korean Studies Information Service System through April 2022. The included studies were randomised control trials (RCTs) of exercise, in which IHL was measured using magnetic resonance imaging in adult NAFLD patients.

RESULTS

Eleven RCTs with 577 participants were included in this meta-analysis. Exercise was significantly associated with a reduction in IHL (mean difference (MD), -2.03; 95% CI, -3.26 to -0.79; P = 0.001) and a decrease in ALT (MD, -4.17; 95% CI, -6.60 to -1.73; P = 0.0008). Regarding the duration of exercise, maintaining exercise for more than 3 months significantly improved IHL (MD, -3.62; 95% CI, -5.76 to -1.48; P = 0.0009), while exercise for less than 3 months did not (MD, -1.23; 95% CI, -2.74 to 0.29; P = 0.11). BMI and insulin resistance did not improve significantly with exercise.

CONCLUSIONS

We found that exercise improved IHL and ALT levels in NAFLD patients. The effect of exercise is particularly increased when one engages in exercises that last longer than 3 months.

Serum IL-27 levels increase in subjects with hypothyroidism and are negatively correlated with the occurrence of nonalcoholic fatty liver disease

Background

The level of serum interleukin-27 (IL-27) was significantly decreased in the obesity group. After injection of IL-27, obese mice showed significant weight loss,reduced fat accumulation, improved insulin resistance and hepatic steatosis.IL-27 plays a key role in the regulation of metabolic processes, but there are scarce data on circulating IL-27 levels in hypothyroidism. The purpose of this study was to assess the serum levels of IL-27 in patients with hypothyroidism and its relationship with NAFLD.

Methods

185 participants were included in this cross-sectional survey. According to thyroid function, the subjects were classified into three groups: euthyroidism (n = 55), subclinical hypothyroidism (n = 53), and hypothyroidism (n = 77). Serum IL-27 concentrations were measured by ELISA.

Results

Serum IL27 levels were significantly higher in subclinical hypothyroidism and hypothyroidism groups than in the euthyroidism group. Serum IL27 levels had a negative correlation with HOMA-IR,FBG,TG, subcutaneous fat,and visceral fat, and had a positive correlation with HDL-C (P< 0.05). Furthermore, logistic regression analysis indicated that IL-27 levels, HOMA-IR, and visceral fat showed significant associations with NAFLD after complete adjustment (P< 0.05). ROC curves showed that theoptimal cut-off value of serum IL-27 for discriminating NAFLD was 95.87pg/mL. The area under the ROC curve was 77.3% (95% CI = 0.694-0.851, p < 0.001).

Conclusions

Serum IL-27 levels demonstrated a compensatory increase in patients with subclinical hypothyroidism or hypothyroidism and showed an independent association with NAFLD. Circulating IL-27 levels could predict the occurrence of NAFLD in hypothyroidism. These results suggested that altering the circulating levels of IL-27 may be a potential therapeutic target for NAFLD.

Fibrotic Burden in the Liver Differs Across Metabolic Dysfunction-Associated Fatty Liver Disease Subtypes

Background/Aims

Metabolic dysfunction-associated fatty liver disease (MAFLD) is categorized into three subtypes: overweight/obese (OW), lean/normal weight with metabolic abnormalities, and diabetes mellitus (DM). We investigated whether fibrotic burden in liver differs across subtypes of MAFLD patients.

Methods

This cross-sectional multicenter study was done in cohorts of subjects who underwent a comprehensive medical health checkup between January 2014 and December 2020. A total of 42,651 patients with ultrasound-diagnosed fatty liver were included. Patients were classified as no MAFLD, OW-MAFLD, lean-MAFLD, and DM-MAFLD. Advanced liver fibrosis was defined based on the nonalcoholic fatty liver disease fibrosis score (NFS) or fibrosis-4 (FIB-4) index.

Results

The mean age of the patients was 50.0 years, and 74.1% were male. The proportion of patients with NFS-defined advanced liver fibrosis was the highest in DM-MAFLD (6.6%), followed by OW-MAFLD (2.0%), lean-MAFLD (1.3%), and no MAFLD (0.2%). The proportion of patients with FIB-4-defined advanced liver fibrosis was the highest in DM-MAFLD (8.6%), followed by lean-MAFLD (3.9%), OW-MAFLD (3.0%), and no MAFLD (2.0%). With the no MAFLD group as reference, the adjusted odds ratios (95% confidence intervals) for NFS-defined advanced liver fibrosis were 4.46 (2.09 to 9.51), 2.81 (1.12 to 6.39), and 9.52 (4.46 to 20.36) in OW-MAFLD, lean-MAFLD, and DM-MAFLD, respectively, and the adjusted odds ratios for FIB-4-defined advanced liver fibrosis were 1.03 (0.78 to 1.36), 1.14 (0.82 to 1.57), and 1.97 (1.48 to 2.62) in OW-MAFLD, lean-MAFLD, and DM-MAFLD.

Conclusions

Fibrotic burden in the liver differs across MAFLD subtypes. Optimized surveillance strategies and therapeutic options might be needed for different MAFLD subtypes.

Clinical and histologic factors associated with discordance between steatosis grade derived from histology vs. MRI-PDFF in NAFLD

BACKGROUND

Magnetic resonance imaging-proton density fat fraction (MRI-PDFF) is an excellent biomarker for the non-invasive quantification of hepatic steatosis.

AIM

To examine clinical and histologic factors associated with discordance between steatosis grade determined by histology and MRI-PDFF in patients with non-alcoholic fatty liver disease (NAFLD) METHODS: We included 728 patients with biopsy-proven NAFLD from UC San Diego (n = 414) and Yokohama City University (n = 314) who underwent MRI-PDFF and liver biopsy. Patients were stratified by steatosis, and matched with MRI-PDFF cut-points for each steatosis grade: 0 (MRI-PDFF < 6.4%), 1 (MRI-PDFF: 6.4%-17.4%), 2 (MRI-PDFF: 17.4%-22.1%), 3 (MRI-PDFF ≥ 22.1%). Primary outcome was major discordance defined as ≥2 steatosis grade difference determined by histology and MRI-PDFF.

RESULTS

Mean (±SD) age and BMI were 55.3 (±13.8) years and 29.9 (±4.9) kg/m2 , respectively. The distributions of histology and MRI-PDFF-determined steatosis were 5.5% grade 0 (n = 40), 44.8% 1 (n = 326, 44.8%), 33.9% 2 (n = 247), and 15.8% 3 (n = 115) vs. 23.5% grade 0 (n = 171), 49.7% 1 (n = 362), 12.9% 2 (n = 94), and 13.9% 3 (n = 101). Major discordance rate was 6.6% (n = 48). Most cases with major discordance had greater histology-determined steatosis grade (n = 40, 88.3%), higher serum AST and liver stiffness, and greater likelihood of fibrosis ≥2, ballooning ≥1 and lobular inflammation ≥2 (all p < 0.05).

CONCLUSION

Histology overestimates steatosis grade compared to MRI-PDFF. Patients with advanced NASH are likely to be upgraded on steatosis grade by histology. These data have important implications for steatosis estimation and reporting on histology in clinical practice and trials, especially in patients with stage 2 fibrosis.

Artifacts in two-dimensional shear wave elastography of liver

BACKGROUND

Artifacts are common when using two-dimensional shear wave elastography (2-D SWE) to measure liver stiffness (LS), but they are poorly recognized.

AIM

To investigate the presence and influence of artifacts in 2-D SWE of liver.

METHODS

We included 158 patients with chronic liver disease, who underwent 2-D SWE examination by a novice and an expert. A cross line at the center of the elastogram was drawn and was divided it into four locations: top-left, top-right, bottom-left, and bottom-right. The occurrence frequency of artifacts in different locations was compared. The influence of artifacts on the LS measurements was evaluated by comparing the elastogram with the most artifacts (EMA) and the elastogram with the least artifacts (ELA).

RESULTS

The percentage of elastograms with artifacts in the novice (51.7%) was significantly higher than that of the expert (19.6%) (P < 0.001). It was found that both operators had the highest frequency of artifacts at bottom-left, followed by top-left and bottom-right, and top-right had the lowest frequency. The LS values (LSVs) and standard deviation values of EMAs were significantly higher than those of ELAs for both operators. An intraclass correlation coefficient value of 0.96 was found in the LSVs of EMAs of the two operators, and it increased to 0.98 when the LSVs of the ELAs were used. Both operators had lower stability index values for EMAs than ELAs, but the difference was only statistically significant for the novice.

CONCLUSION

Artifacts are common when using 2-D SWE to measure LS, especially for the novice. Artifacts may lead to the overestimation of LS and reduce the repeatability and reliability of LS measurements.

Artificial intelligence and deep learning: new tools for histopathological diagnosis of nonalcoholic fatty liver disease/nonalcoholic steatohepatitis

Nonalcoholic fatty liver disease (NAFLD)/nonalcoholic steatohepatitis (NASH) is associated with metabolic syndrome and is rapidly increasing globally with the increased prevalence of obesity. Although noninvasive diagnosis of NAFLD/NASH has progressed, pathological evaluation of liver biopsy specimens remains the gold standard for diagnosing NAFLD/NASH. However, the pathological diagnosis of NAFLD/NASH relies on the subjective judgment of the pathologist, resulting in non-negligible interobserver variations. Artificial intelligence (AI) is an emerging tool in pathology to assist diagnoses with high objectivity and accuracy. An increasing number of studies have reported the usefulness of AI in the pathological diagnosis of NAFLD/NASH, and our group has already used it in animal experiments. In this minireview, we first outline the histopathological characteristics of NAFLD/NASH and the basics of AI. Subsequently, we introduce previous research on AI-based pathological diagnosis of NAFLD/NASH.

Noninvasive imaging biomarkers for liver fibrosis in nonalcoholic fatty liver disease: current and future

Nonalcoholic fatty liver disease (NAFLD) is increasingly prevalent worldwide and becoming a major cause of liver disease-related morbidity and mortality. The presence of liver fibrosis in patients with NAFLD is closely related to prognosis, including the development of hepatocellular carcinoma and other complications of cirrhosis. Therefore, assessment of the presence of significant or advanced liver fibrosis is crucial. Although liver biopsy has been considered the "gold standard" method for evaluating the degree of liver fibrosis, it is not suitable for extensive use in all patients with NAFLD owing to its invasiveness and high cost. Therefore, noninvasive biochemical and imaging biomarkers have been developed to overcome the limitations of liver biopsy. Imaging biomarkers for the stratification of liver fibrosis have been evaluated in patients with NAFLD using different imaging techniques, such as transient elastography, shear wave elastography, and magnetic resonance elastography. Furthermore, artificial intelligence and deep learning methods are increasingly being applied to improve the diagnostic accuracy of imaging techniques and overcome the pitfalls of existing imaging biomarkers. In this review, we describe the usefulness and future prospects of noninvasive imaging biomarkers that have been studied and used to evaluate the degree of liver fibrosis in patients with NAFLD.

Noninvasive serum biomarkers for liver fibrosis in NAFLD: current and future

In the last 20 years, noninvasive serum biomarkers to identify liver fibrosis in patients with non-alcoholic fatty liver disease (NAFLD) have been developed, validated against liver biopsy (the gold standard for determining the presence of liver fibrosis) and made available for clinicians to use to identify ≥F3 liver fibrosis. The aim of this review is firstly to focus on the current use of widely available biomarkers and their performance for identifying ≥F3. Secondly, we discuss whether noninvasive biomarkers have a role in identifying F2, a stage of fibrosis that is now known to be a risk factor for cirrhosis and overall mortality. We also consider whether machine learning algorithms offer a better alternative for identifying individuals with ≥F2 fibrosis. Thirdly, we summarise the utility of noninvasive serum biomarkers for predicting liver related outcomes (e.g., ascites and hepatocellular carcinoma) and non-liver related outcomes (e.g., cardiovascular-related mortality and extra hepatic cancers). Finally, we examine whether serial measurement of biomarkers can be used to monitor liver disease, and whether the use of noninvasive biomarkers in drug trials for non-alcoholic steatohepatitis can accurately, compared to liver histology, monitor liver fibrosis progression/regression. We conclude by offering our perspective on the future of serum biomarkers for the detection and monitoring of liver fibrosis in NAFLD.

Tropifexor for nonalcoholic steatohepatitis: an adaptive, randomized, placebo-controlled phase 2a/b trial

The multimodal activities of farnesoid X receptor (FXR) agonists make this class an attractive option to treat nonalcoholic steatohepatitis. The safety and efficacy of tropifexor, an FXR agonist, in a randomized, multicenter, double-blind, three-part adaptive design, phase 2 study, in patients with nonalcoholic steatohepatitis were therefore assessed. In Parts A + B, 198 patients were randomized to receive tropifexor (10-90 μg) or placebo for 12 weeks. In Part C, 152 patients were randomized to receive tropifexor 140 µg, tropifexor 200 µg or placebo (1:1:1) for 48 weeks. The primary endpoints were safety and tolerability to end-of-study, and dose response on alanine aminotransferase (ALT), aspartate aminotransferase (AST) and hepatic fat fraction (HFF) at week 12. Pruritus was the most common adverse event in all groups, with a higher frequency in the 140- and 200-µg tropifexor groups. Decreases from baseline in ALT and HFF were greater with tropifexor versus placebo at week 12, with a relative decrease in least squares mean from baseline observed with all tropifexor doses for ALT (tropifexor 10-90-μg dose groups ranged from -10.7 to -16.5 U l-1 versus placebo (-7.8 U l-1) and tropifexor 140- and 200-μg groups were -18.0 U l-1 and -23.0 U l-1, respectively, versus placebo (-8.3 U l-1)) and % HFF (tropifexor 10-90-μg dose groups ranged from -7.48% to -15.04% versus placebo (-6.19%) and tropifexor 140- and 200-μg groups were -19.07% and -39.41%, respectively, versus placebo (-10.77%)). Decreases in ALT and HFF were sustained up to week 48; however, similar trends in AST with tropifexor at week 12 were not observed. As with other FXR agonists, dose-related pruritus was frequently observed. Clinicaltrials.gov registration: NCT02855164.

Non-alcoholic fatty liver disease: Definition and subtypes

Non-alcoholic fatty liver disease (NAFLD) is one of the most common liver diseases worldwide, with a global prevalence of approximately 30%. However, the prevalence of NAFLD has been variously reported depending on the comorbidities. The rising prevalence of obesity in both the adult and pediatric populations is projected to consequently continue increasing NAFLD prevalence. It is a major cause of chronic liver disease worldwide, including cirrhosis and hepatocellular carcinoma (HCC). NAFLD has a variety of clinical phenotypes and heterogeneity due to the complexity of pathogenesis and clinical conditions of its occurrence, resulting in various clinical prognoses. In this article, we briefly described the basic definition of NAFLD and classified the subtypes based on current knowledge in this field.

Non-invasive biomarkers for liver inflammation in non-alcoholic fatty liver disease: present and future

Inflammation is the key driver of liver fibrosis progression in non-alcoholic fatty liver disease (NAFLD). Unfortunately, it is often challenging to assess inflammation in NAFLD due to its dynamic nature and poor correlation with liver biochemical markers. Liver histology keeps its role as the standard tool, yet it is well-known for substantial sampling, intraobserver, and interobserver variability. Serum proinflammatory cytokines and apoptotic markers, namely cytokeratin-18, are well-studied with reasonable accuracy, whereas serum metabolomics and lipidomics have been adopted in some commercially available diagnostic models. Ultrasound and computed tomography imaging techniques are attractive due to their wide availability; yet their accuracies may not be comparable with magnetic resonance imaging-based tools. Machine learning and deep learning models, be they supervised or unsupervised learning, are promising tools to identify various subtypes of NAFLD, including those with dominating liver inflammation, contributing to sustainable care pathways for NAFLD.

Screening strategy for non-alcoholic fatty liver disease

Non-alcoholic fatty liver disease (NAFLD) is the most common chronic liver disease, affecting approximately 25% of the general population worldwide, and is forecasted to increase global health burden in the 21st century. With the advancement of non-invasive tests for assessing and monitoring of steatosis and fibrosis, NAFLD screening is now feasible, and is increasingly highlighted in international guidelines related to hepatology, endocrinology, and pediatrics. Identifying high-risk populations (e.g., diabetes mellitus, obesity, metabolic syndrome) based on risk factors and metabolic characteristics for non-invasive screening is crucial and may aid in designing screening strategies to be more precise and effective. Many screening modalities are currently available, from serum-based methods to ultrasonography, transient elastography, and magnetic resonance imaging, although the diagnostic performance, cost, and accessibility of different methods may impact the actual implementation. A two-step assessment with serum-based fibrosis-4 index followed by imaging test vibration-controlled transient elastography can be an option to stratify the risk of liverrelated complications in NAFLD. There is a need for fibrosis surveillance, as well as investigating the cost-effectiveness of different screening algorithms and engaging primary care for first-stage triage screening.

Head-to-head comparison between MEFIB, MAST, and FAST for detecting stage 2 fibrosis or higher among patients with NAFLD

BACKGROUND & AIMS

Patients with non-alcoholic fatty liver disease (NAFLD) and significant fibrosis (fibrosis stage ≥2) are candidates for pharmacological trials. The aim of this study was to perform a head-to-head comparison of the diagnostic test characteristics of three non-invasive stiffness-based models including MEFIB (magnetic resonance elastography [MRE] plus FIB-4), MAST (magnetic resonance imaging [MRI]-aspartate aminotransferase [AST]), and FAST (FibroScan-AST) for detecting significant fibrosis.

METHODS

This prospective study included 563 patients with biopsy-proven NAFLD undergoing contemporaneous MRE, MRI proton density fat fraction (MRI-PDFF) and FibroScan from two prospective cohorts derived from Southern California and Japan. Diagnostic performances of models were evaluated by area under the receiver-operating characteristic curve (AUC).

RESULTS

The mean age of the cohort was 56.5 years (51% were women). Significant fibrosis was observed in 51.2%. To detect significant fibrosis, MEFIB outperformed both MAST and FAST (both p <0.001); AUCs for MEFIB, MAST, and FAST were 0.901 (95% CI 0.875-0.928), 0.770 (95% CI 0.730-0.810), and 0.725 (95% CI 0.683-0.767), respectively. Using rule-in criteria, the positive predictive value of MEFIB (95.3%) was significantly higher than that of FAST (83.5%, p = 0.001) and numerically but not statistically greater than that of MAST (90.0%, p = 0.056). Notably, MEFIB's rule-in criteria covered more of the study population than MAST (34.1% vs. 26.6%; p = 0.006). Using rule-out criteria, the negative predictive value of MEFIB (90.1%) was significantly higher than that of either MAST (69.6%) or FAST (71.8%) (both p <0.001). Furthermore, to diagnose "at risk" non-alcoholic steatohepatitis defined as NAFLD activity score ≥4 and fibrosis stage ≥2, MEFIB outperformed both MAST and FAST (both p <0.05); AUCs for MEFIB, MAST, and FAST were 0.768 (95% CI 0.728-0.808), 0.719 (95% CI 0.671-0.766), and 0.687 (95% CI 0.640-0.733), respectively.

CONCLUSIONS

MEFIB was better than MAST and FAST for detection of significant fibrosis as well as "at risk" NASH. All three models provide utility for the risk stratification of NAFLD.

LAY SUMMARY

Non-alcoholic fatty liver disease (NAFLD) affects over 25% of the general population worldwide and is one of the main causes of chronic liver disease. Because so many individuals have NAFLD, it is not practical to perform liver biopsies to identify those with more severe disease who may require pharmacological interventions. Therefore, accurate non-invasive tests are crucial. Herein, we compared three such tests and found that a test called MEFIB was the best at detecting patients who might require treatment.

Digital pathology with artificial intelligence analyses provides greater insights into treatment-induced fibrosis regression in NASH

BACKGROUND & AIMS

Liver fibrosis is a key prognostic determinant for clinical outcomes in non-alcoholic steatohepatitis (NASH). Current scoring systems have limitations, especially in assessing fibrosis regression. Second harmonic generation/two-photon excitation fluorescence (SHG/TPEF) microscopy with artificial intelligence analyses provides standardized evaluation of NASH features, especially liver fibrosis and collagen fiber quantitation on a continuous scale. This approach was applied to gain in-depth understanding of fibrosis dynamics after treatment with tropifexor (TXR), a non-bile acid farnesoid X receptor agonist in patients participating in the FLIGHT-FXR study (NCT02855164).

METHOD

Unstained sections from 198 liver biopsies (paired: baseline and end-of-treatment) from 99 patients with NASH (fibrosis stage F2 or F3) who received placebo (n = 34), TXR 140 μg (n = 37), or TXR 200 μg (n = 28) for 48 weeks were examined. Liver fibrosis (qFibrosis®), hepatic fat (qSteatosis®), and ballooned hepatocytes (qBallooning®) were quantitated using SHG/TPEF microscopy. Changes in septa morphology, collagen fiber parameters, and zonal distribution within liver lobules were also quantitatively assessed.

RESULTS

Digital analyses revealed treatment-associated reductions in overall liver fibrosis (qFibrosis®), unlike conventional microscopy, as well as marked regression in perisinusoidal fibrosis in patients who had either F2 or F3 fibrosis at baseline. Concomitant zonal quantitation of fibrosis and steatosis revealed that patients with greater qSteatosis reduction also have the greatest reduction in perisinusoidal fibrosis. Regressive changes in septa morphology and reduction in septa parameters were observed almost exclusively in F3 patients, who were adjudged as 'unchanged' with conventional scoring.

CONCLUSION

Fibrosis regression following hepatic fat reduction occurs initially in the perisinusoidal regions, around areas of steatosis reduction. Digital pathology provides new insights into treatment-induced fibrosis regression in NASH, which are not captured by current staging systems.

LAY SUMMARY

The degree of liver fibrosis (tissue scarring) in non-alcoholic steatohepatitis (NASH) is the main predictor of negative clinical outcomes. Accurate assessment of the quantity and architecture of liver fibrosis is fundamental for patient enrolment in NASH clinical trials and for determining treatment efficacy. Using digital microscopy with artificial intelligence analyses, the present study demonstrates that this novel approach has greater sensitivity in demonstrating treatment-induced reversal of fibrosis in the liver than current systems. Furthermore, additional details are obtained regarding the pathogenesis of NASH disease and the effects of therapy.

Magnetic resonance imaging improves stratification of fibrosis and steatosis in patients with chronic liver disease

PURPOSE

We aimed to compare the diagnostic accuracy of magnetic resonance imaging (MRI) and transient elastography (TE) in assessing liver fibrosis and steatosis in patients with chronic liver disease (CLD).

METHODS

Patients who underwent liver biopsy or liver surgery at two academic hospitals between 2017 and 2021 were retrospectively recruited. The stages of liver fibrosis and steatosis were evaluated using histologic examination. Liver stiffness (LS) was assessed using MR elastography (LS_MRE) and TE (LS_TE). Liver steatosis was assessed using proton density fat fraction (PDFF) and controlled attenuation parameter (CAP).

RESULTS

The mean age of the study population (n = 280) was 53.6 years and male sex predominated (n = 199, 71.1%). Nonalcoholic fatty liver disease was the most prevalent (n = 127, 45.5%), followed by hepatitis B virus (n = 112, 40.0%). Hepatocellular carcinoma was identified in 130 patients (46.4%). The proportions of F0, F1, F2, F3, and F4 fibrosis were 13.2%, 31.1%, 9.6%, 16.4%, and 29.7%, respectively. LS_MRE had a significantly greater AUROC value than LS_TE for detecting F2-F4 (0.846 vs. 0.781, P = 0.046), whereas LS_MRE and LS_TE similarly predicted F1-4, F3-4, and F4 (all P > 0.05). The proportions of S0, S1, S2, and S3 steatosis were 34.7%, 49.6%, 12.5%, and 3.2%, respectively. PDFF had significantly greater AUROC values than CAP in predicting S1-3 (0.922 vs. 0.806, P < 0.001) and S2-3 (0.924 vs. 0.795, P = 0.005); however, PDFF and CAP similarly predicted S3 (P = 0.086).

CONCLUSION

MRI exhibited significantly higher diagnostic accuracy than TE for detecting significant fibrosis and mild or moderate steatosis in patients with CLD.

Noninvasive surrogates are poor predictors of liver fibrosis in patients with Fontan circulation

OBJECTIVES

Patients with Fontan circulation exhibit a high incidence of liver fibrosis and cirrhosis. Transient elastography (TE) and the enhanced liver fibrosis (ELF) test have proven useful as noninvasive surrogate markers of liver fibrosis for other chronic liver diseases. We evaluated whether TE and the ELF score can predict the degree of liver fibrosis in patients with Fontan circulation.

METHODS

We retrospectively reviewed the medical records of 45 adult patients with at least 10 years of Fontan duration who had undergone liver biopsy and investigated the relation between the fibrosis stage and TE and the ELF test results. Additionally, the association of these variables and other biochemical and hemodynamic parameters was assessed.

RESULTS

The mean age was 25.9 years and the mean Fontan duration was 20.8 years. Advanced liver fibrosis was present in 36 (80.0%) patients. TE or ELF score are comparable for patients with and without advanced liver fibrosis (mean 23.3 vs 24.8 kPa [P = .85] for TE; mean 8.94 vs 9.25 [P = .44] for the ELF score). However, N-terminal pro-brain natriuretic peptide level and ventricular end-diastolic pressure were higher in patients with advanced liver fibrosis (mean 224 vs 80 pg/mL [P < .01]; and mean 12 vs 9 mm Hg [P = .04], respectively). No independent predictor of advanced liver fibrosis was found in multivariate analysis.

CONCLUSIONS

TE and the ELF score were unable to predict the degree of liver fibrosis in Fontan patients. Liver biopsy remains as the only valid method to assess fibrotic burden in this population.

The triglyceride glucose-body mass index: a non-invasive index that identifies non-alcoholic fatty liver disease in the general Japanese population

Background

By identifying individuals at high risk for non-alcoholic fatty liver disease (NAFLD), interventional programs could be targeted more effectively. Some studies have demonstrated that triglyceride glucose-body mass index (TyG-BMI) showed an independent positive association with NAFLD. However, research on its diagnostic value in patients with suspected NAFLD is limited. In this study, we aimed to evaluate whether TyG-BMI was accurate in detecting NAFLD in the general Japanese population.

Methods

A cross-sectional study of 14,280 individuals who underwent a comprehensive health examination was conducted. Standard protocols were followed to collect anthropometric measurements, lab data, and ultrasonography features. All participants were randomly stratified into the development group (n = 7118) and validation group (n = 7162). The TyG-BMI was calculated. Following this, the diagnostic value of the TyG-BMI was evaluated based on the area under the receiver-operating characteristic curve (AUROC). Two cutoff points were selected and used to rule out or rule in the NALFD, and the specificity, sensitivity, negative predictive value, and positive predictive value were explored, respectively. In order to verify the stability of the results, external verification was performed.

Results

There were 1272 and 1243 NAFLD participants in the development and validation groups, respectively. The area under the ROC curve (AUC) of TyG-BMI was 0.888 (95% CI 0.876–0.896) and 0.884 (95% CI 0.875–0.894) for the training and validation group, respectively. Using the low TyG-BMI (182.2) cutoff, NAFLD could be excluded with high accuracy (negative predictive value: 96.9% in estimation and 96.9% in validation). The presence of NAFLD could effectively be determined by applying the high cutoff of TyG-BMI (224.0), as the positive predictive value of the estimation and validation groups is 70.7% and 70.1%, respectively. As a result of applying this model, 9996 (70%) of the 14,280 participants would not have undergone ultrasonography, with an accurate prediction of 9308 (93.1%). AUC was 0.874 for external validation using 183,730 Chinese non-obese participants. TyG-BMI was demonstrated to be an excellent diagnostic tool by both internal and external validation.

Conclusions

In conclusion, the present study developed and validated a simple, non-invasive, and cost-effective tool to accurately separate participants with and without NAFLD in the Japanese population, rendering ultrasonography for identifying NAFLD unnecessary in a substantial proportion of people.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-022-03611-4.

Rethinking Liver Fibrosis Staging in Patients with Hepatocellular Carcinoma: New Insights from a Large Two-Center Cohort Study

Background

Hepatocellular carcinoma (HCC) is a prevalent and aggressive malignancy closely related to background chronic liver disease. This study aimed to explore predictive factors associated with background liver fibrosis burden in patients with HCC and sought to construct a practical predictive model for clinical use.

Methods

This large two-center retrospective cohort study evaluated data from Chinese medical centers. Uni- and multivariate ordinal logistic regression analyses were performed to identify variables associated with liver fibrosis stages. Predictive models based on variables identified by multivariate analysis were established in the Derivation Cohort and subjected to internal and external validation. Model performance was evaluated for discriminative and calibration abilities.

Results

Multivariate ordinal logistic regression analysis identified liver fibrosis severity score (LFSS), portal hypertension (PH) severity, plateletcrit (PCT) and model for end-stage liver disease-sodium (MELD-Na) as independent predictors of liver fibrosis stage in HCC patients. Nomograms that integrated these factors disclosed that the area under receiver operating characteristic curves (AUROCs) to predict S1 in the Derivation and External Validation cohorts were 0.850 and 0.919, respectively. Internal validation disclosed C-indexes of 0.823 and 0.833 in the Derivation and External Validation cohorts, respectively, indicating that the nomogram had good and excellent performance for distinguishing between S1 and non-S1 patients. Nomogram performance in the Derivation and External Validation cohorts, respectively, was fair and good to predict stage S2 (AUROCs 0.726, 0.806; C-indexes 0.713, 0.791); poor for S3 (AUROCs 0.648, 0.698; C-indexes 0.616, 0.666); good for S4 (AUROCs 0.812, 0.824; C-indexes 0.804, 0.792); and good for S3+S4 (AUROCs 0.806, 0.840; C-indexes 0.795, 0.811).

Conclusion

We propose new predictive models for the staging of background liver fibrosis in patients with HCC that can be implemented into clinical practice as important complements to hepatic imaging to inform HCC management strategy.

Comparison of FibroScan-Aspartate Aminotransferase (FAST) Score and Other Non-invasive Surrogates in Predicting High-Risk Non-alcoholic Steatohepatitis Criteria

Identification of non-alcoholic steatohepatitis (NASH) with high activity and fibrosis is a major priority in patients with non-alcoholic fatty liver disease. We validated the predictive value of the FibroScan-aspartate aminotransferase (FAST) score and other non-invasive fibrosis surrogates in predicting high-risk NASH criteria. This multicenter retrospective study recruited 251 biopsy-proven non-alcoholic fatty liver disease (NAFLD) patients (132 [52.6%] men) between 2011 and 2014. The FAST score was calculated using transient elastography data and aspartate aminotransferase (AST) levels. The NAFLD fibrosis score (NFS), fibrosis-4 index (FIB-4), and AST to platelet ratio index (APRI) were calculated using biochemical data. The area under the receiver operating characteristic curves (AUCs) of the FAST score, liver stiffness, NFS, FIB-4, and APRI were 0.752, 0.718, 0.609, 0.650, and 0.722 for NAFLD activity score (NAS) ≥5 (n = 117, 46.6%); 0.788, 0.754, 0.649, 0.701, and 0.747 for fatty liver inhibition of progression-NASH with histologic activity ≥3 (n = 202, 80.5%); 0.807, 0.806, 0.691, 0.732, and 0.760 for severe disease with activity ≥3 and/or fibrosis ≥3 (n = 132, 52.6%); and 0.714, 0.812, 0.748, 0.738, and 0.669 for NASH with NAS ≥4 and fibrosis ≥2 (n = 70, 27.9%), respectively. The FAST score had the highest AUC for the most high-risk NASH criteria, except for in predicting NAS ≥4 and fibrosis ≥2. The liver stiffness value showed consistently acceptable performance in predicting all high-risk NASH criteria. The FAST score has acceptable performance in identifying high-risk NASH. However, liver stiffness alone was not inferior to the FAST score.

Maternal Western diet exposure increases periportal fibrosis beginning in utero in nonhuman primate offspring

Maternal obesity affects nearly one-third of pregnancies and is a major risk factor for nonalcoholic fatty liver disease (NAFLD) in adolescent offspring, yet the mechanisms behind NAFLD remain poorly understood. Here, we demonstrate that nonhuman primate fetuses exposed to maternal Western-style diet (WSD) displayed increased fibrillar collagen deposition in the liver periportal region, with increased ACTA2 and TIMP1 staining, indicating localized hepatic stellate cell (HSC) and myofibroblast activation. This collagen deposition pattern persisted in 1-year-old offspring, despite weaning to a control diet (CD). Maternal WSD exposure increased the frequency of DCs and reduced memory CD4+ T cells in fetal liver without affecting systemic or hepatic inflammatory cytokines. Switching obese dams from WSD to CD before conception or supplementation of the WSD with resveratrol decreased fetal hepatic collagen deposition and reduced markers of portal triad fibrosis, oxidative stress, and fetal hypoxemia. These results demonstrate that HSCs and myofibroblasts are sensitive to maternal WSD-associated oxidative stress in the fetal liver, which is accompanied by increased periportal collagen deposition, indicative of early fibrogenesis beginning in utero. Alleviating maternal WSD-driven oxidative stress in the fetal liver holds promise for halting steatosis and fibrosis and preventing developmental programming of NAFLD.

Predict Early Recurrence of Resectable Hepatocellular Carcinoma Using Multi-Dimensional Artificial Intelligence Analysis of Liver Fibrosis

Simple Summary

Hepatocellular carcinoma (HCC) is the third most commonly diagnosed cancer in the world, and surgical resection is the commonly used curative management of early-stage disease. However, the recurrence rate is high after resection, and liver fibrosis has been thought to increase the risk of recurrence. Conventional histological staging of fibrosis is highly subjective to observer variations. To overcome this limitation, we used a fully quantitative fibrosis assessment tool, qFibrosis (utilizing second harmonic generation and two-photon excitation fluorescence microscopy), with multi-dimensional artificial intelligence analysis to establish a fully-quantitative, accurate fibrotic score called a “combined index”, which can predict early recurrence of HCC after curative intent resection. Therefore, we can pay more attention on the patients with high risk of early recurrence.

Abstract

Background: Liver fibrosis is thought to be associated with early recurrence of hepatocellular carcinoma (HCC) after resection. To recognize HCC patients with higher risk of early recurrence, we used a second harmonic generation and two-photon excitation fluorescence (SHG/TPEF) microscopy to create a fully quantitative fibrosis score which is able to predict early recurrence. Methods: The study included 81 HCC patients receiving curative intent hepatectomy. Detailed fibrotic features of resected hepatic tissues were obtained by SHG/TPEF microscopy, and we used multi-dimensional artificial intelligence analysis to create a recurrence prediction model “combined index” according to the morphological collagen features of each patient’s non-tumor hepatic tissues. Results: Our results showed that the “combined index” can better predict early recurrence (area under the curve = 0.917, sensitivity = 81.8%, specificity = 90.5%), compared to alpha fetoprotein level (area under the curve = 0.595, sensitivity = 68.2%, specificity = 47.6%). Using a Cox proportional hazards analysis, a higher “combined index” is also a poor prognostic factor of disease-free survival and overall survival. Conclusions: By integrating multi-dimensional artificial intelligence and SHG/TPEF microscopy, we may locate patients with a higher risk of recurrence, follow these patients more carefully, and conduct further management if needed.

Association between telomere length and hepatic fibrosis in non-alcoholic fatty liver disease

Telomere length has been linked to the prevalence and progression of metabolic disease. However, clinical implications of telomere length in biopsy-proven non-alcoholic fatty liver disease (NAFLD) patients remain unclear. Therefore, this study aimed to investigate the association of telomere length with the histological severity of NAFLD. The cross-sectional data derived from the prospectively enrolled Boramae NAFLD registry (n = 91) were analyzed. The liver tissues and clinical information were obtained from both NAFLD patients and non-NAFLD subjects. Binary logistic regression was performed to identify the independent association between telomere length and the histological severity of NAFLD. A total of 83 subjects with or without biopsy-proven NAFLD were included for analysis: non-NAFLD in 23 (27.7%), non-alcoholic fatty liver in 15 (18.1%), and non-alcoholic steatohepatitis (NASH) in 45 (54.2%). Telomere length measured from liver tissues showed a strong negative correlation (p < 0.001) with age, regardless of NAFLD status. Therefore, telomere length was corrected for age. Age-adjusted telomere length than decreased gradually with an increasing severity of fibrosis in patients with NAFLD (p < 0.028). In multivariate analysis, age-adjusted telomere length (odds ratio [OR] 0.59; 95% CI 0.37–0.92; p = 0.019) and high-density lipoprotein cholesterol (OR 0.94; 95% CI 0.80–0.99; p = 0.039) were independently associated with significant fibrosis. The age-adjusted telomere length tends to decrease along with the fibrosis stage of NAFLD. In particular, among the histological components of NAFLD, fibrosis severity seems to be related to telomere length in the liver.

The Need for Alternatives to Liver Biopsies: Non-Invasive Analytics and Diagnostics

Histology remains essential for the diagnosis and management of many disorders affecting the liver. However, the biopsy procedure itself is associated with a low risk of harm to the patient and cost to the health services; samples may not be adequate and are subject to sampling variation. Furthermore, interpretation often depends on the skill of the pathologist. Increasingly, new techniques are becoming available that are altering the indications for liver biopsy. Many diseases of the liver can be diagnosed and managed using serological and radiological techniques; the degree of fibrosis and fat can often be assessed by serological or imaging techniques and the nature of space occupying lesions defined by serology, imaging and use of liquid biopsy. However, these techniques, too, are subject to limitations: sensitivity and specificity is not always adequate for diagnosis or management; some techniques are expensive and often also require expert interpretation. Although there may be less need for liver biopsy today, histology remains the gold standard as well as an essential tool for the diagnosis and management of many conditions, especially where there are multiple pathologies, or where a diagnosis cannot or has not been made by alternative approaches. Until less invasive techniques become more reliable and accessible, liver histology will remain a key investigation.

Dietary Polyphenols and Non-Alcoholic Fatty Liver Disease

Non-alcoholic fatty liver disease (NAFLD), which is emerging as a major public health issue worldwide, is characterized by a wide spectrum of liver disorders, ranging from simple fat accumulation in hepatocytes, also known as steatosis, to non-alcoholic steatohepatitis (NASH) and cirrhosis. At present, the pharmacological treatment of NAFLD is still debated and dietary strategies for the prevention and the treatment of this condition are strongly considered. Polyphenols are a group of plant-derived compounds whose anti-inflammatory and antioxidant properties are associated with a low prevalence of metabolic diseases, including obesity, hypertension, and insulin resistance. Since inflammation and oxidative stress are the main risk factors involved in the pathogenesis of NAFLD, recent studies suggest that the consumption of polyphenol-rich diets is involved in the prevention and treatment of NAFLD. However, few clinical trials are available on human subjects with NAFLD. Here, we reviewed the emerging existing evidence on the potential use of polyphenols to treat NAFLD. After introducing the physiopathology of NAFLD, we focused on the most investigated phenolic compounds in the setting of NAFLD and described their potential benefits, starting from basic science studies to animal models and human trials.