Diagnostic accuracy of non-invasive tests to screen for at-risk MASH-An individual participant data meta-analysis.

BACKGROUND & AIMS: There is a need to reduce the screen failure rate (SFR) in metabolic dysfunction-associated steatohepatitis (MASH) clinical trials (MASH+F2-3; MASH+F4) and identify people with high-risk MASH (MASH+F2-4) in clinical practice. We aimed to evaluate non-invasive tests (NITs) screening approaches for these target conditions. METHODS: This was an individual participant data meta-analysis for the performance of NITs against liver biopsy for MASH+F2-4, MASH+F2-3 and MASH+F4. Index tests were the FibroScan-AST (FAST) score, liver stiffness measured using vibration-controlled transient elastography (LSM-VCTE), the fibrosis-4 score (FIB-4) and the NAFLD fibrosis score (NFS). Area under the receiver operating characteristics curve (AUROC) and thresholds including those that achieved 34% SFR were reported. RESULTS: We included 2281 unique cases. The prevalence of MASH+F2-4, MASH+F2-3 and MASH+F4 was 31%, 24% and 7%, respectively. Area under the receiver operating characteristics curves for MASH+F2-4 were .78, .75, .68 and .57 for FAST, LSM-VCTE, FIB-4 and NFS. Area under the receiver operating characteristics curves for MASH+F2-3 were .73, .67, .60, .58 for FAST, LSM-VCTE, FIB-4 and NFS. Area under the receiver operating characteristics curves for MASH+F4 were .79, .84, .81, .76 for FAST, LSM-VCTE, FIB-4 and NFS. The sequential combination of FIB-4 and LSM-VCTE for the detection of MASH+F2-3 with threshold of .7 and 3.48, and 5.9 and 20 kPa achieved SFR of 67% and sensitivity of 60%, detecting 15 true positive cases from a theoretical group of 100 participants at the prevalence of 24%. CONCLUSIONS: Sequential combinations of NITs do not compromise diagnostic performance and may reduce resource utilisation through the need of fewer LSM-VCTE examinations.

Anaerobutyricum soehngenii Reduces Hepatic Lipogenic Pathways and Increases Intestinal Gluconeogenic Gene Expression in Metabolic-Dysfunction-Associated Steatotic Liver Disease (MASLD) Mice.

Metabolic-dysfunction-associated steatotic liver disease (MASLD) is a growing health problem for which no therapy exists to date. The modulation of the gut microbiome may have treatment potential for MASLD. Here, we investigated Anaerobutyricum soehngenii, a butyrate-producing anaerobic bacterium with beneficial effects in metabolic syndrome, in a diet-induced MASLD mouse model. Male C57BL/6J mice received a Western-type high-fat diet and water with 15% fructose (WDF) to induce MASLD and were gavaged with A. soehngenii (108 or 109 colony-forming units (CFU) 3 times per week) or a placebo for 6 weeks. The A. soehngenii gavage increased the cecal butyrate concentrations. Although there was no effect on histological MASLD scores, A. soehngenii improved the glycemic response to insulin. In the liver, the WDF-associated altered expression of three genes relevant to the MASLD pathophysiology was reversed upon treatment with A. soehngenii: Lipin-1 (Lpin1), insulin-like growth factor binding protein 1 (Igfbp1) and Interleukin 1 Receptor Type 1 (Il1r1). A. soehngenii administration also increased the intestinal expression of gluconeogenesis and fructolysis genes. Although these effects did not translate into significant histological improvements in MASLD, these results provide a basis for combined gut microbial approaches to induce histological improvements in MASLD.

Machine learning approaches to enhance diagnosis and staging of patients with MASLD using routinely available clinical information.

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.

Implementation of a liver health check in people with type 2 diabetes.

As morbidity and mortality related to potentially preventable liver diseases are on the rise globally, early detection of liver fibrosis offers a window of opportunity to prevent disease progression. Early detection of non-alcoholic fatty liver disease allows for initiation and reinforcement of guidance on bodyweight management, risk stratification for advanced liver fibrosis, and treatment optimisation of diabetes and other metabolic complications. Identification of alcohol-related liver disease provides the opportunity to support patients with detoxification and abstinence programmes. In all patient groups, identification of cirrhosis ensures that patients are enrolled in surveillance programmes for hepatocellular carcinoma and portal hypertension. When considering early detection strategies, success can be achieved from applying ad-hoc screening for liver fibrosis in established frameworks of care. Patients with type 2 diabetes are an important group to consider case findings of advanced liver fibrosis and cirrhosis, as up to 19% have advanced fibrosis (which is ten times higher than the general population) and almost 70% have non-alcoholic fatty liver disease. Additionally, patients with type 2 diabetes with alcohol use disorders have the highest proportion of liver-related morbidity of people with type 2 diabetes generally. Patients with type 2 diabetes receive an annual diabetes review as part of their routine clinical care, in which the health of many organs are considered. Yet, liver health is seldom included in this review. This Viewpoint argues that augmenting the existing risk stratification strategy with an additional liver health check provides the opportunity to detect advanced liver fibrosis, thereby opening a window for early interventions to prevent end-stage liver disease and its complications, including hepatocellular carcinoma.

Metabolic dysfunction-associated steatotic liver disease and the heart.

The prevalence and severity of metabolic dysfunction-associated steatotic liver disease (MASLD) are increasing. Physicians who treat patients with MASLD may acknowledge the strong coincidence with cardiometabolic disease, including atherosclerotic cardiovascular disease (asCVD). This raises questions on co-occurrence, causality, and the need for screening and multidisciplinary care for MASLD in patients with asCVD, and vice versa. Here, we review the interrelations of MASLD and heart disease and formulate answers to these matters. Epidemiological studies scoring proxies for atherosclerosis and actual cardiovascular events indicate increased atherosclerosis in patients with MASLD, yet no increased risk of asCVD mortality. MASLD and asCVD share common drivers: obesity, insulin resistance and type 2 diabetes mellitus (T2DM), smoking, hypertension, and sleep apnea syndrome. In addition, Mendelian randomization studies support that MASLD may cause atherosclerosis through mixed hyperlipidemia, while such evidence is lacking for liver-derived procoagulant factors. In the more advanced fibrotic stages, MASLD may contribute to heart failure with preserved ejection fraction by reduced filling of the right ventricle, which may induce fatigue upon exertion, often mentioned by patients with MASLD. Some evidence points to an association between MASLD and cardiac arrhythmias. Regarding treatment and given the strong co-occurrence of MASLD and asCVD, pharmacotherapy in development for advanced stages of MASLD would ideally also reduce cardiovascular events, as has been demonstrated for T2DM treatments. Given the common drivers, potential causal factors and especially given the increased rate of cardiovascular events, comprehensive cardiometabolic risk management is warranted in patients with MASLD, preferably in a multidisciplinary approach.

A global survey of health care workers' awareness of non-alcoholic fatty liver disease: The AwareNASH survey.

BACKGROUND: The estimated global prevalence and burden of non-alcoholic fatty liver disease (NAFLD) and its advanced stage, non-alcoholic steatohepatitis (NASH), is increasing. Yet, NAFLD remains largely underdiagnosed. In addition to hepatic morbidity and mortality, NAFLD is associated with increased cardiovascular complications, warranting a multidisciplinary approach. Despite its rapidly increasing prevalence, knowledge of NAFLD among healthcare workers is limited, especially with specialists outside the field of hepatology and gastroenterology. OBJECTIVES: To investigate knowledge, practice and opinions/attitudes of healthcare workers towards diagnosis and management of NAFLD/NASH. METHODS: The survey was designed in collaboration with a multidisciplinary scientific committee established especially for this study. The survey was disseminated to healthcare workers from seven different disciplines through four collaborating societies, social media and at a cardiology-themed conference from February to June 2022. Median and interquartile range were mentioned for numeric responses and proportions for categorical responses or responses on a Likert scale. Likert scale responses were treated as ordinal data and analysed with the appropriate tests. RESULTS: The full dataset included 613 respondents from 88 different countries (including 488 physicians). 64% of the surveyed physicians underestimated the prevalence of NAFLD. General practitioners and cardiologists underestimated the prevalence most often (74% and 77%, respectively). Compared to the other disciplines, cardiologists were least familiar with the symptoms and diagnostic criteria and felt least confident in diagnosing and managing NAFLD. Overall, 65% of physicians reported regularly using evidence-based guidelines for managing NAFLD, yet 72% reported challenges in providing lifestyle recommendations. A lack of awareness was the most common reported reason for the lack of screening for NAFLD (68% respectively). CONCLUSIONS: Despite the growing burden of NAFLD, there is a significant gap in awareness, knowledge, and management among physicians treating patients with cardiometabolic comorbidities, particularly cardiologists. Hepatologists and gastroenterologists could play a role in educating their fellow physicians.

Faecal Microbiota transplantation affects liver DNA methylation in Non-alcoholic fatty liver disease: a multi-omics approach.

Individuals with nonalcoholic fatty liver disease (NAFLD) have an altered gut microbiota composition. Moreover, hepatic DNA methylation may be altered in the state of NAFLD. Using a fecal microbiota transplantation (FMT) intervention, we aimed to investigate whether a change in gut microbiota composition relates to altered liver DNA methylation in NAFLD. Moreover, we assessed whether plasma metabolite profiles altered by FMT relate to changes in liver DNA methylation. Twenty-one individuals with NAFLD underwent three 8-weekly vegan allogenic donor (n = 10) or autologous (n = 11) FMTs. We obtained hepatic DNA methylation profiles from paired liver biopsies of study participants before and after FMTs. We applied a multi-omics machine learning approach to identify changes in the gut microbiome, peripheral blood metabolome and liver DNA methylome, and analyzed cross-omics correlations. Vegan allogenic donor FMT compared to autologous FMT induced distinct differential changes in I) gut microbiota profiles, including increased abundance of Eubacterium siraeum and potential probiotic Blautia wexlerae; II) plasma metabolites, including altered levels of phenylacetylcarnitine (PAC) and phenylacetylglutamine (PAG) both from gut-derived phenylacetic acid, and of several choline-derived long-chain acylcholines; and III) hepatic DNA methylation profiles, most importantly in Threonyl-TRNA Synthetase 1 (TARS) and Zinc finger protein 57 (ZFP57). Multi-omics analysis showed that Gemmiger formicillis and Firmicutes bacterium_CAG_170 positively correlated with both PAC and PAG. E siraeum negatively correlated with DNA methylation of cg16885113 in ZFP57. Alterations in gut microbiota composition by FMT caused widespread changes in plasma metabolites (e.g. PAC, PAG, and choline-derived metabolites) and liver DNA methylation profiles in individuals with NAFLD. These results indicate that FMTs might induce metaorganismal pathway changes, from the gut bacteria to the liver.

An international Delphi consensus statement on metabolic dysfunction-associated fatty liver disease and risk of chronic kidney disease.

Background: With the rising global prevalence of fatty liver disease related to metabolic dysfunction, the association of this common liver condition with chronic kidney disease (CKD) has become increasingly evident. In 2020, the more inclusive term metabolic dysfunction-associated fatty liver disease (MAFLD) was proposed to replace the term non-alcoholic fatty liver disease (NAFLD). The observed association between MAFLD and CKD and our understanding that CKD can be a consequence of underlying metabolic dysfunction support the notion that individuals with MAFLD are at higher risk of having and developing CKD compared with those without MAFLD. However, to date, there is no appropriate guidance on CKD in individuals with MAFLD. Furthermore, there has been little attention paid to the link between MAFLD and CKD in the Nephrology community. Methods and Results: Using a Delphi-based approach, a multidisciplinary panel of 50 international experts from 26 countries reached a consensus on some of the open research questions regarding the link between MAFLD and CKD. Conclusions: This Delphi-based consensus statement provided guidance on the epidemiology, mechanisms, management and treatment of MAFLD and CKD, as well as the relationship between the severity of MAFLD and risk of CKD, which establish a framework for the early prevention and management of these two common and interconnected diseases.

Performance of non-invasive tests and histology for the prediction of clinical outcomes in patients with non-alcoholic fatty liver disease: an individual participant data meta-analysis.

BACKGROUND: Histologically assessed liver fibrosis stage has prognostic significance in patients with non-alcoholic fatty liver disease (NAFLD) and is accepted as a surrogate endpoint in clinical trials for non-cirrhotic NAFLD. Our aim was to compare the prognostic performance of non-invasive tests with liver histology in patients with NAFLD. METHODS: This was an individual participant data meta-analysis of the prognostic performance of histologically assessed fibrosis stage (F0-4), liver stiffness measured by vibration-controlled transient elastography (LSM-VCTE), fibrosis-4 index (FIB-4), and NAFLD fibrosis score (NFS) in patients with NAFLD. The literature was searched for a previously published systematic review on the diagnostic accuracy of imaging and simple non-invasive tests and updated to Jan 12, 2022 for this study. Studies were identified through PubMed/MEDLINE, EMBASE, and CENTRAL, and authors were contacted for individual participant data, including outcome data, with a minimum of 12 months of follow-up. The primary outcome was a composite endpoint of all-cause mortality, hepatocellular carcinoma, liver transplantation, or cirrhosis complications (ie, ascites, variceal bleeding, hepatic encephalopathy, or progression to a MELD score ≥15). We calculated aggregated survival curves for trichotomised groups and compared them using stratified log-rank tests (histology: F0-2 vs F3 vs F4; LSM: <10 vs 10 to <20 vs ≥20 kPa; FIB-4: <1·3 vs 1·3 to ≤2·67 vs >2·67; NFS: <-1·455 vs -1·455 to ≤0·676 vs >0·676), calculated areas under the time-dependent receiver operating characteristic curves (tAUC), and performed Cox proportional-hazards regression to adjust for confounding. This study was registered with PROSPERO, CRD42022312226. FINDINGS: Of 65 eligible studies, we included data on 2518 patients with biopsy-proven NAFLD from 25 studies (1126 [44·7%] were female, median age was 54 years [IQR 44-63), and 1161 [46·1%] had type 2 diabetes). After a median follow-up of 57 months [IQR 33-91], the composite endpoint was observed in 145 (5·8%) patients. Stratified log-rank tests showed significant differences between the trichotomised patient groups (p<0·0001 for all comparisons). The tAUC at 5 years were 0·72 (95% CI 0·62-0·81) for histology, 0·76 (0·70-0·83) for LSM-VCTE, 0·74 (0·64-0·82) for FIB-4, and 0·70 (0·63-0·80) for NFS. All index tests were significant predictors of the primary outcome after adjustment for confounders in the Cox regression. INTERPRETATION: Simple non-invasive tests performed as well as histologically assessed fibrosis in predicting clinical outcomes in patients with NAFLD and could be considered as alternatives to liver biopsy in some cases. FUNDING: Innovative Medicines Initiative 2.

Machine learning algorithm improves the detection of NASH (NAS-based) and at-risk NASH: A development and validation study.

BACKGROUND AND AIMS: Detecting NASH remains challenging, while at-risk NASH (steatohepatitis and F≥ 2) tends to progress and is of interest for drug development and clinical application. We developed prediction models by supervised machine learning techniques, with clinical data and biomarkers to stage and grade patients with NAFLD. APPROACH AND RESULTS: Learning data were collected in the Liver Investigation: Testing Marker Utility in Steatohepatitis metacohort (966 biopsy-proven NAFLD adults), staged and graded according to NASH CRN. Conditions of interest were the clinical trial definition of NASH (NAS ≥ 4;53%), at-risk NASH (NASH with F ≥ 2;35%), significant (F ≥ 2;47%), and advanced fibrosis (F ≥ 3;28%). Thirty-five predictors were included. Missing data were handled by multiple imputations. Data were randomly split into training/validation (75/25) sets. A gradient boosting machine was applied to develop 2 models for each condition: clinical versus extended (clinical and biomarkers). Two variants of the NASH and at-risk NASH models were constructed: direct and composite models.Clinical gradient boosting machine models for steatosis/inflammation/ballooning had AUCs of 0.94/0.79/0.72. There were no improvements when biomarkers were included. The direct NASH model produced AUCs (clinical/extended) of 0.61/0.65. The composite NASH model performed significantly better (0.71) for both variants. The composite at-risk NASH model had an AUC of 0.83 (clinical and extended), an improvement over the direct model. Significant fibrosis models had AUCs (clinical/extended) of 0.76/0.78. The extended advanced fibrosis model (0.86) performed significantly better than the clinical version (0.82). CONCLUSIONS: Detection of NASH and at-risk NASH can be improved by constructing independent machine learning models for each component, using only clinical predictors. Adding biomarkers only improved the accuracy of fibrosis.

Biomarkers for staging fibrosis and non-alcoholic steatohepatitis in non-alcoholic fatty liver disease (the LITMUS project): a comparative diagnostic accuracy study.

BACKGROUND: The reference standard for detecting non-alcoholic steatohepatitis (NASH) and staging fibrosis-liver biopsy-is invasive and resource intensive. Non-invasive biomarkers are urgently needed, but few studies have compared these biomarkers in a single cohort. As part of the Liver Investigation: Testing Marker Utility in Steatohepatitis (LITMUS) project, we aimed to evaluate the diagnostic accuracy of 17 biomarkers and multimarker scores in detecting NASH and clinically significant fibrosis in patients with non-alcoholic fatty liver disease (NAFLD) and identify their optimal cutoffs as screening tests in clinical trial recruitment. METHODS: This was a comparative diagnostic accuracy study in people with biopsy-confirmed NAFLD from 13 countries across Europe, recruited between Jan 6, 2010, and Dec 29, 2017, from the LITMUS metacohort of the prospective European NAFLD Registry. Adults (aged ≥18 years) with paired liver biopsy and serum samples were eligible; those with excessive alcohol consumption or evidence of other chronic liver diseases were excluded. The diagnostic accuracy of the biomarkers was expressed as the area under the receiver operating characteristic curve (AUC) with liver histology as the reference standard and compared with the Fibrosis-4 index for liver fibrosis (FIB-4) in the same subgroup. Target conditions were the presence of NASH with clinically significant fibrosis (ie, at-risk NASH; NAFLD Activity Score ≥4 and F≥2) or the presence of advanced fibrosis (F≥3), analysed in all participants with complete data. We identified thres holds for each biomarker for reducing the number of biopsy-based screen failures when recruiting people with both NASH and clinically significant fibrosis for future trials. FINDINGS: Of 1430 participants with NAFLD in the LITMUS metacohort with serum samples, 966 (403 women and 563 men) were included after all exclusion criteria had been applied. 335 (35%) of 966 participants had biopsy-confirmed NASH and clinically significant fibrosis and 271 (28%) had advanced fibrosis. For people with NASH and clinically significant fibrosis, no single biomarker or multimarker score significantly reached the predefined AUC 0·80 acceptability threshold (AUCs ranging from 0·61 [95% CI 0·54-0·67] for FibroScan controlled attenuation parameter to 0·81 [0·75-0·86] for SomaSignal), with accuracy mostly similar to FIB-4. Regarding detection of advanced fibrosis, SomaSignal (AUC 0·90 [95% CI 0·86-0·94]), ADAPT (0·85 [0·81-0·89]), and FibroScan liver stiffness measurement (0·83 [0·80-0·86]) reached acceptable accuracy. With 11 of 17 markers, histological screen failure rates could be reduced to 33% in trials if only people who were marker positive had a biopsy for evaluating eligibility. The best screening performance for NASH and clinically significant fibrosis was observed for SomaSignal (number needed to test [NNT] to find one true positive was four [95% CI 4-5]), then ADAPT (six [5-7]), MACK-3 (seven [6-8]), and PRO-C3 (nine [7-11]). INTERPRETATION: None of the single markers or multimarker scores achieved the predefined acceptable AUC for replacing biopsy in detecting people with both NASH and clinically significant fibrosis. However, several biomarkers could be applied in a prescreening strategy in clinical trial recruitment. The performance of promising markers will be further evaluated in the ongoing prospective LITMUS study cohort. FUNDING: The Innovative Medicines Initiative 2 Joint Undertaking.

Non-Parenchymal Cells and the Extracellular Matrix in Hepatocellular Carcinoma in Non-Alcoholic Fatty Liver Disease.

Hepatocellular carcinoma (HCC) in the setting of non-alcoholic fatty liver disease (NAFLD)-related cirrhosis and even in the pre-cirrhotic state is increasing in incidence. NAFLD-related HCC has a poor clinical outcome as it is often advanced at diagnosis due to late diagnosis and systemic treatment response is poor due to reduced immune surveillance. Much of the focus of molecular research has been on the pathological changes in hepatocytes; however, immune cells, hepatic stellate cells, liver sinusoidal endothelial cells and the extracellular matrix may play important roles in the pathogenesis of NAFLD-related HCC as well. Here, we review the role of non-parenchymal cells in the liver in the pathogenesis of HCC in the context of NAFLD-NASH, with a particular focus on the innate and the adaptive immune system, fibrogenesis and angiogenesis. We review the key roles of macrophages, hepatic stellate cells (HSCs), T cells, natural killer (NK) cells, NKT cells and liver sinusoidal endothelial cells (LSECs) and the role of the extracellular matrix in hepatocarcinogenesis within the steatotic milieu.

Does aerobic exercise reduce NASH and liver fibrosis in patients with non-alcoholic fatty liver disease? A systematic literature review and meta-analysis.

Background: Exercise is an effective strategy for the prevention and regression of hepatic steatosis in patients with non-alcoholic fatty liver disease (NAFLD), but it is unclear whether it can reduce advanced stages of NAFLD, i.e., steatohepatitis and liver fibrosis. Furthermore, it is not evident which modality of exercise is optimal to improve/attenuate NAFLD. Objectives: The aim is to systematically review evidence for the effect of aerobic exercise (AE) on NAFLD, in particular non-alcoholic steatohepatitis (NASH) and liver fibrosis. Methods: A systematic literature search was conducted in Medline and Embase. Studies were screened and included according to predefined criteria, data were extracted, and the quality was assessed by Cochrane risk of bias tools by two researchers independently according to the protocol registered in the PROSPERO database (CRD42021270059). Meta-analyses were performed using a bivariate random-effects model when there were at least three randomized intervention studies (RCTs) with similar intervention modalities and outcome. Results: The systematic review process resulted in an inclusion a total of 24 studies, 18 RCTs and six non-RCTs, encompassing 1014 patients with NAFLD diagnosed by histological or radiological findings. Studies were grouped based on the type of AE: moderate-intensity continuous training (MICT) and high-intensity interval training (HIIT). A total of twelve meta-analyses were conducted. Compared to controls, MICT resulted in a mean difference (MD) in the NAFLD biomarkers alanine transaminase (ALT) and aspartate aminotransferase (AST) of -3.59 (CI: -5.60, -1.59, p<0.001) and -4.05 (CI: -6.39, -1.71, p<0.001), respectively. HIIT resulted in a MD of -4.31 (95% CI: -9.03, 0.41, p=0.07) and 1.02 (95% CI: -6.91, 8.94, p=0.8) for ALT and AST, respectively. Moreover, both AE types compared to controls showed a significantly lower magnetic resonance spectroscopy (MRS) determined liver fat with a MD of -5.19 (95% CI: -7.33, -3.04, p<0.001) and -3.41 (95% CI: -4.74, -2.08, p<0.001), for MICT and HIIT respectively. MICT compared to controls resulted in a significantly higher cardiorespiratory fitness (MD: 4.43, 95% CI: 0.31, 8.55, p=0.03). Conclusion: Liver fat is decreased by AE with a concomitant decrease of liver enzymes. AE improved cardiorespiratory fitness. Further studies are needed to elucidate the impact of different types of AE on hepatic inflammation and fibrosis. Systematic Review Registration: https://www.crd.york.ac.uk/prospero/, identifier (CRD42021270059).

Improvement of non-invasive tests of liver steatosis and fibrosis as indicators for non-alcoholic fatty liver disease in type 2 diabetes mellitus patients with elevated cardiovascular risk profile using the PPAR-α/γ agonist aleglitazar.

BACKGROUND: Peroxisome proliferator-activated receptor (PPAR) agonists may have favorable outcomes on non-alcoholic fatty liver disease. This study serves as proof of concept to evaluate whether dual PPAR-α/γ agonists improve non-invasive tests of liver steatosis and fibrosis. METHODS: This is a post-hoc analysis of a randomized, double-blind, placebo-controlled, multi-center trial comprising 7226 patients with type 2 diabetes mellitus and recent coronary artery disease randomized to receive aleglitazar, a PPAR-α/γ agonists, or placebo for two years. Main outcomes were change in non-invasive tests for liver steatosis and fibrosis: Liver Fat Score (LFS), Liver Accumulation Product (LAP), Fibrosis-4 (FIB-4), and NAFLD Fibrosis Score (NFS). RESULTS: LFS, LAP and FIB-4 decreased upon treatment, whereas scores in the placebo group remained the same or increased (P<0.001). NFS responded differently but remained consistently lower than placebo. In the treatment group more participants shifted to a lower FIB-4 and NFS category, or improved in respect to the LAP cut-off values compared to the placebo group (P<0.001 for FIB-4 and LAP, P<0.004 for NFS). LFS had a low discriminative power in this study. CONCLUSION: This post-hoc analysis showed improvement of non-invasive tests of liver steatosis and fibrosis after starting dual PPAR-α/γ agonist treatment, adding to the evidence that this pathway has potential in non-alcoholic fatty liver disease treatment.

Microbiome-derived ethanol in nonalcoholic fatty liver disease.

To test the hypothesis that the gut microbiota of individuals with nonalcoholic fatty liver disease (NAFLD) produce enough ethanol to be a driving force in the development and progression of this complex disease, we performed one prospective clinical study and one intervention study. Ethanol was measured while fasting and 120 min after a mixed meal test (MMT) in 146 individuals. In a subset of 37 individuals and in an external validation cohort, ethanol was measured in portal vein blood. In an intervention study, ten individuals with NAFLD and ten overweight but otherwise healthy controls were infused with a selective alcohol dehydrogenase (ADH) inhibitor before an MMT. When compared to fasted peripheral blood, median portal vein ethanol concentrations were 187 (interquartile range (IQR), 17-516) times higher and increased with disease progression from 2.1 mM in individuals without steatosis to 8.0 mM in NAFL 21.0 mM in nonalcoholic steatohepatitis. Inhibition of ADH induced a 15-fold (IQR,1.6- to 20-fold) increase in peripheral blood ethanol concentrations in individuals with NAFLD, although this effect was abolished after antibiotic treatment. Specifically, Lactobacillaceae correlated with postprandial peripheral ethanol concentrations (Spearman's rho, 0.42; P < 10-5) in the prospective study. Our data show that the first-pass effect obscures the levels of endogenous ethanol production, suggesting that microbial ethanol could be considered in the pathogenesis of this highly prevalent liver disease.

Self-supervised neural network improves tri-exponential intravoxel incoherent motion model fitting compared to least-squares fitting in non-alcoholic fatty liver disease.

Recent literature suggests that tri-exponential models may provide additional information and fit liver intravoxel incoherent motion (IVIM) data more accurately than conventional bi-exponential models. However, voxel-wise fitting of IVIM results in noisy and unreliable parameter maps. For bi-exponential IVIM, neural networks (NN) were able to produce superior parameter maps than conventional least-squares (LSQ) generated images. Hence, to improve parameter map quality of tri-exponential IVIM, we developed an unsupervised physics-informed deep neural network (IVIM3-NET). We assessed its performance in simulations and in patients with non-alcoholic fatty liver disease (NAFLD) and compared outcomes with bi-exponential LSQ and NN fits and tri-exponential LSQ fits. Scanning was performed using a 3.0T free-breathing multi-slice diffusion-weighted single-shot echo-planar imaging sequence with 18 b-values. Images were analysed for visual quality, comparing the bi- and tri-exponential IVIM models for LSQ fits and NN fits using parameter-map signal-to-noise ratios (SNR) and adjusted R 2. IVIM parameters were compared to histological fibrosis, disease activity and steatosis grades. Parameter map quality improved with bi- and tri-exponential NN approaches, with a significant increase in average parameter-map SNR from 3.38 to 5.59 and 2.45 to 4.01 for bi- and tri-exponential LSQ and NN models respectively. In 33 out of 36 patients, the tri-exponential model exhibited higher adjusted R 2 values than the bi-exponential model. Correlating IVIM data to liver histology showed that the bi- and tri-exponential NN outperformed both LSQ models for the majority of IVIM parameters (10 out of 15 significant correlations). Overall, our results support the use of a tri-exponential IVIM model in NAFLD. We show that the IVIM3-NET can be used to improve image quality compared to a tri-exponential LSQ fit and provides promising correlations with histopathology similar to the bi-exponential neural network fit, while generating potentially complementary additional parameters.

Evaluation of nonalcoholic fatty liver disease (NAFLD) in severe obesity using noninvasive tests and imaging techniques.

The prevalence of nonalcoholic fatty liver disease (NAFLD) and the more severe and inflammatory type, nonalcoholic steatohepatitis (NASH), is increasing rapidly. Especially in high-risk patients, that is those with obesity, metabolic syndrome, and type 2 diabetes mellitus, the prevalence of NAFLD can be as high as 80% while NASH may be present in 20% of these subjects. With the worldwide increase of obesity, it is most likely that these numbers will rise. Since advanced stages of NAFLD and NASH are strongly associated with morbidity and mortality-in particular, cardiovascular disease, liver cirrhosis, and hepatocellular carcinoma-it is of great importance to identify subjects at risk. A great variety of noninvasive tests has been published to diagnose NAFLD and NASH, especially using blood- and imaging-based tests. Liver biopsy remains the gold standard for NAFLD/NASH. This review aims to summarize the different mechanisms leading to NASH and liver fibrosis, the different noninvasive liver tests to diagnose and evaluate patients with severe obesity.

Clinicians' Perspectives on Barriers and Facilitators for the Adoption of Non-Invasive Liver Tests for NAFLD: A Mixed-Method Study.

(1) Background: Given the high prevalence of non-alcoholic fatty liver disease (NAFLD) and the limitations of liver biopsies, multiple non-invasive tests (NITs) have been developed to identify non-alcoholic fatty liver disease (NAFLD) patients at-risk of progression. The availability of these new NITs varies from country to country, and little is known about their implementation and adoption in routine clinical practice. This study aims to explore barriers and facilitators that influence the adoption of NAFLD NITs, from healthcare professionals' perspectives. (2) Methods: A cross-sectional study was performed using an exploratory mixed-methods approach. Twenty-seven clinicians from eight different countries with different specialties filled in our questionnaire. Of those, 16 participated in semi-structured interviews. Qualitative and quantitative data were collected and summarized using the recently published Non-adoption, Abandonment, Scale-up, Spread, and Sustainability (NASSS) framework for new medical technologies in healthcare organizations. (3) Results: Several factors were reported as influencing the uptake of NITs for NAFLD in clinical practice. Among those: insufficient awareness of tests; lack of practical guidelines and evidence for the performance of tests in appropriate patient populations and care settings; and absence of sufficient reimbursement systems were reported as the most important barriers. Other factors, most notably 'local champions', proper functional payment systems, and sufficient resources in academic hospitals, were indicated as important facilitating factors. (4) Conclusions: Clinicians see the adoption of NITs for NAFLD as a complex process that is modulated by several factors, such as robust evidence, practical guidelines, a proper payment system, and local champions. Future research could explore perspectives from other stakeholders on the adoption of NITs.