Alcoholic hepatitis (AH) is a syndrome of jaundice and liver failure that occurs in a minority of heavy consumers of alcohol. The diagnosis usually is based on a history of heavy alcohol use, findings from blood tests, and exclusion of other liver diseases by blood and imaging analyses. Liver biopsy specimens, usually collected via the transjugular route, should be analyzed to confirm a diagnosis of AH in patients with an atypical history or presentation. The optimal treatment for patients with severe AH is prednisolone, possibly in combination with N-acetyl cysteine. At present, only short-term increases in survival can be expected-no treatment has been found to increase patient survival beyond 3 months. Abstinence is essential for long-term survival. New treatment options, including liver transplantation, are being tested in trials and results eagerly are awaited.

Hepatitis C virus (HCV) is a leading cause of chronic liver disease, cirrhosis, and hepatocellular carcinoma, as well as the most common indication for liver transplantation in many countries. Although the incidence of hepatitis C infection has dramatically decreased during the past decade, the worldwide reservoir of chronically infected persons is estimated at 170 million, or 3% of the global population. There is much controversy surrounding the natural history of hepatitis C infection. The rate of chronic HCV infection is affected by a person's age, gender, race, and viral immune response. Approximately 75%-85% of HCV-infected persons will progress to chronic HCV infection, and are at risk for the development of extrahepatic manifestations, compensated and decompensated cirrhosis, and hepatocellular carcinoma (HCC). The rate of progression to cirrhosis is highly variable, and is influenced by several factors, including the amount of alcohol consumption, age of initial HCV infection, degree of inflammation and fibrosis on liver biopsy, HIV and HBV coinfection, and comordid conditions. An estimated 10%-15% of HCV-infected persons will advance to cirrhosis within the first 20 years. Persons with cirrhosis are at increased risk of developing HCC. An understanding of the natural history of hepatitis C is essential to effectively manage, treat, and counsel individuals with HCV infection.

In this perspective piece, we summarize the development and implementation of multidisciplinary liver tumor boards across the Veterans Affairs health care system dating back to 2010. Referral to multidisciplinary tumor boards (MDLTB) has been demonstrated to decrease the number of unnecessary invasive procedures, reduce health care costs and maximize patient outcomes. Although the VA is the largest single care provider in the US, there is significant heterogeneity in healthcare delivery. We have shown that receiving care at VA centers with MDLTB is associated with higher odds of receiving active therapy and a 13% reduction in mortality. Access to expert hepatology care appears to be one of the critical benefits of MDLTB resulting in 30% reduction in mortality. Integrated health care systems such as the VA have the unique capability of implementing virtual tumor boards that can easily overcome geographic barriers and standardize care across multiple facilities regardless of their access to hepatology or other disciplines. Significant barriers remain requiring implementation plans. This document serves as a roadmap to establish multidisciplinary tumor boards, including standardization of imaging reports, identifying stake holders who need to be present at tumor board, institution buy-in, and specifics for local, regional and integrated service network tumor boards.

Background

The Veterans Health Administration (VA) is the largest integrated healthcare organization in the US and cares for the largest cohort of individuals with hepatitis C (HCV). A national HCV population management dashboard enabled rapid identification and treatment uptake with direct acting antiviral agents across VA hospitals. We describe the HCV dashboard (HCVDB) and evaluate its use and user experience.

Methods

A user-centered design approach created the HCVDB to include reports based on the HCV care continuum: 1) 1945-1965 birth cohort high-risk screening, 2) linkage to care and treatment of chronic HCV, 3) treatment monitoring, 4) post-treatment to confirm cure (i.e., sustained virologic response), and 5) special populations of unstably housed Veterans. We evaluated frequency of usage and user experience with the System Usability Score (SUS) and Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) instruments.

Results

Between November 2016 and July 2021, 1302 unique users accessed the HCVDB a total of 163,836 times. The linkage report was used most frequently (71%), followed by screening (13%), sustained virologic response (11%), on-treatment (4%), and special populations (<1%). Based on user feedback (n = 105), the mean SUS score was 73±16, indicating a good user experience. Overall acceptability was high with the following UTAUT2 rated from highest to least: Price Value, Performance Expectancy, Social Influence, and Facilitating Conditions.

Conclusions

The HCVDB had rapid and widespread uptake, met provider needs, and scored highly on user experience measures. Collaboration between clinicians, clinical informatics, and population health experts was essential for dashboard design and sustained use. Population health management tools have the potential for large-scale impacts on care timeliness and efficiency.

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Background & aims

Liver disease carries significant healthcare burden and frequently requires a combination of blood tests, imaging, and invasive liver biopsy to diagnose. Distinguishing between inflammatory liver diseases, which may have similar clinical presentations, is particularly challenging. In this study, we implemented a machine learning pipeline for the identification of diagnostic gene expression biomarkers across several alcohol-associated and non-alcohol-associated liver diseases, using either liver tissue or blood-based samples.

Methods

We collected peripheral blood mononuclear cells (PBMCs) and liver tissue samples from participants with alcohol-associated hepatitis (AH), alcohol-associated cirrhosis (AC), non-alcohol-associated fatty liver disease, chronic HCV infection, and healthy controls. We performed RNA sequencing (RNA-seq) on 137 PBMC samples and 67 liver tissue samples. Using gene expression data, we implemented a machine learning feature selection and classification pipeline to identify diagnostic biomarkers which distinguish between the liver disease groups. The liver tissue results were validated using a public independent RNA-seq dataset. The biomarkers were computationally validated for biological relevance using pathway analysis tools.

Results

Utilizing liver tissue RNA-seq data, we distinguished between AH, AC, and healthy conditions with overall accuracies of 90% in our dataset, and 82% in the independent dataset, with 33 genes. Distinguishing 4 liver conditions and healthy controls yielded 91% overall accuracy in our liver tissue dataset with 39 genes, and 75% overall accuracy in our PBMC dataset with 75 genes.

Conclusions

Our machine learning pipeline was effective at identifying a small set of diagnostic gene biomarkers and classifying several liver diseases using RNA-seq data from liver tissue and PBMCs. The methodologies implemented and genes identified in this study may facilitate future efforts toward a liquid biopsy diagnostic for liver diseases.

Lay summary

Distinguishing between inflammatory liver diseases without multiple tests can be challenging due to their clinically similar characteristics. To lay the groundwork for the development of a non-invasive blood-based diagnostic across a range of liver diseases, we compared samples from participants with alcohol-associated hepatitis, alcohol-associated cirrhosis, chronic hepatitis C infection, and non-alcohol-associated fatty liver disease. We used a machine learning computational approach to demonstrate that gene expression data generated from either liver tissue or blood samples can be used to discover a small set of gene biomarkers for effective diagnosis of these liver diseases.

Background

Liver is enriched in several innate-like unconventional T cells, but their role in alcohol-related liver disease (ALD) is not fully understood. Studies in several acute alcohol feeding models but not in chronic alcoholic steatohepatitis (ASH) model have shown that invariant natural killer T (iNKT) cells play a pathogenic role in ALD. Here, we investigated the activation of iNKT cells in an intragastric (iG) infusion model of chronic ASH as well as the frequency and cytokine phenotype of 3 different unconventional T cells: iNKT, mucosal-associated invariant T (MAIT), and CD8⁺ CD161^hi Vα7.2^- cells in peripheral blood of ALD patients.

Methods

Hepatic iNKT cells were investigated using the iG model of chronic ASH that combines feeding of high-cholesterol/high-fat diet (HCFD) with intragastric feeding of ethanol diet (HCFD + iG Alc). Human iNKT, MAIT, and CD8⁺ CD161^hi Vα7.2^- cells were examined by flow cytometry in peripheral blood of patients with severe alcoholic hepatitis (SAH) and chronic alcoholics (ChA) and compared with healthy controls.

Results

In the iG model of chronic ASH, IFNγ⁺ iNKT cells accumulate in their livers compared with pair-fed control mice and activated hepatic iNKT cells show high expression of Fas and FasL. Notably, IFNγ⁺ iNKT cells are also significantly increased in peripheral blood of ChA patients compared with SAH patients. MAIT cells are significantly reduced in all ALD patients, but CD8⁺ CD161^hi Vα7.2^- cells are increased in SAH patients. Although MAIT and CD8⁺ CD161^hi Vα7.2^- cells displayed a similar cytokine production profile, the production of IFNγ and TNFα is significantly increased in SAH patients, while significant IL-17A production is found in ChA patients.

Conclusions

We found that the 3 unconventional T cells are activated in ALD patients showing interesting differences in their frequency and cytokine production profile between SAH and ChA patients. In the iG murine model of chronic ASH, iNKT cells are also activated secreting proinflammatory cytokines suggesting their involvement in liver disease.

Binge drinking, a common pattern of alcohol ingestion, is known to potentiate liver injury caused by chronic alcohol abuse. This study was aimed at investigating the effects of acute binge alcohol on hypoxia-inducible factor-1α (HIF-1α)-mediated liver injury and the roles of alcohol-metabolizing enzymes in alcohol-induced hypoxia and hepatotoxicity. Mice and human specimens assigned to binge or nonbinge groups were analyzed for blood alcohol concentration (BAC), alcohol-metabolizing enzymes, HIF-1α-related protein nitration, and apoptosis. Binge alcohol promoted acute liver injury in mice with elevated levels of ethanol-inducible cytochrome P450 2E1 (CYP2E1) and hypoxia, both of which were colocalized in the centrilobular areas. We observed positive correlations among elevated BAC, CYP2E1, and HIF-1α in mice and humans exposed to binge alcohol. The CYP2E1 protein levels (r = 0.629, p = 0.001) and activity (r = 0.641, p = 0.001) showed a significantly positive correlation with BAC in human livers. HIF-1α levels were also positively correlated with BAC (r = 0.745, p < 0.001) or CYP2E1 activity (r = 0.792, p < 0.001) in humans. Binge alcohol promoted protein nitration and apoptosis with significant correlations observed between inducible nitric oxide synthase and BAC, CYP2E1, or HIF-1α in human specimens. Binge-alcohol-induced HIF-1α activation and subsequent protein nitration or apoptosis seen in wild type were significantly alleviated in the corresponding Cyp2e1-null mice, whereas pretreatment with an HIF-1α inhibitor, PX-478, prevented HIF-1α elevation with a trend of decreased levels of 3-nitrotyrosine and apoptosis, supporting the roles of CYP2E1 and HIF-1α in binge-alcohol-mediated protein nitration and hepatotoxicity. Thus binge alcohol promotes acute liver injury in mice and humans at least partly through a CYP2E1-HIF-1α-dependent apoptosis pathway.