Citations

Alcohol-associated liver disease due to harmful alcohol use and NAFLD associated with metabolic syndrome are the 2 most common liver diseases worldwide. Control of respective risk factors is the cornerstone in the long-term management of these diseases. Furthermore, there are no effective therapies. Both diseases are characterized by metabolic derangements; thus, the focus of this review was to broaden our understanding of metabolic targets investigated in NAFLD, and how these can be applied to alcohol-associated liver disease. Conserved pathogenic pathways such as dysregulated lipid metabolism, cell death pathways including apoptosis and activation of innate immune cells, and stellate cells mediate both alcohol and NAFLDs, resulting in histological abnormalities of steatosis, inflammation, fibrosis, and cirrhosis. However, pathways such as gut microbiome changes, glucose metabolism and insulin resistance, inflammatory signaling, and microRNA abnormalities are distinct in these 2 diseases. In this review article, we describe conserved and distinct pathogenic pathways highlighting therapeutic targets that may be of potential in both diseases and those that are unique to each disease.

Abstract Alcoholic hepatitis (AH) develops in a small percentage of heavy drinkers. The adaptive immune system of AH patients is hyper-activated, yet dysregulated and ineffective against infectious diseases. Mucosal-associated invariant T (MAIT) cells are innate-like lymphocytes that are found in liver, intestinal mucosa, and peripheral blood and contribute to protection against infectious diseases. To determine whether MAIT cells were dysregulated in heavy drinkers and the effect of alcohol abstinence on MAIT cell recovery, we compared peripheral MAIT cells between AH patients and heavy drinkers without liver disease (HDC) at baseline and 6- and 12-month followup. At baseline, AH patients had severely reduced frequency of MAIT cells than HDC and healthy donor controls (HC), whereas MAIT cell frequency was not significantly different between HDC and HC. In addition, MAIT cells in AH patients expressed higher levels of the activation markers (CD69, CD38, and HLA-DR) as well as the immune checkpoint inhibitor PD-1. Multiplex immunoassays showed that plasma levels of several cytokines related to MAIT cell activation were elevated in AH patients (IFN-s, IL-7, IL-15, IL-17, IL-18, and IL-23, and TNF-a). In AH patients, the frequency MAIT cells and CD38-expressing MAIT cells correlated with levels of several cytokines and AST. At followup, AH patients had increased MAIT cell frequency and decreased MAIT cell activation with cessation of alcohol. However, abstinent AH patients still had higher levels of CD38-expressing MAIT cells than HDC at 6-month followup. Conclusion Blood MAIT cells were severely reduced and were dysregulated in AH patients and alcohol abstinence partially reversed abnormalities in MAIT cell frequency and phenotype.

SummaryBackgroundAlcohol‐associated hepatitis is an acute manifestation of alcohol‐associated liver disease (ALD) and is associated with 30%–40% mortality at 28 days. Abstinence and corticosteroids are the mainstays of treatment, but the latter only improves short‐term mortality, so new and improved therapies remain an unmet need.AimsThe aim was to review the pathophysiology of alcohol‐associated hepatitis and how various targets can be used by current and emerging therapies as treatment.MethodsA thorough literature review was conducted on acute alcohol‐associated hepatitis, current therapies and therapies under investigation.ResultsWith the increasing prevalence of alcohol use disorder and ALD, the burden of alcohol‐associated hepatitis is also expected to rise. The current understanding of alcohol‐associated hepatitis pathophysiology has led to clinical trials of several therapies involving IL‐1 antagonism, modification of the gut microbiome and liver regeneration.ConclusionsCorticosteroid therapy for alcohol‐associated hepatitis is restricted in its applicability and has limited efficacy. Developing multidisciplinary, patient‐centred care models based on digital health technologies, in combination with continued discovery of novel therapies using multiomics data and computational biology techniques will be necessary to tackle the increasing burden of alcohol‐associated hepatitis.

Abstract Aims Readmission is frequent among patients with cirrhosis and is a complex multifactorial process. To examine the association of alcohol use disorder (AUD) and risk of readmission in patients with alcohol-associated cirrhosis. Methods and Results National Readmission Dataset (2016–2017) was used to extract a retrospective cohort of 53,348 patients with primary or secondary discharge diagnosis code of alcohol-associated cirrhosis with their first admission (26,674 patients with vs. propensity matched 26,674 without a primary or secondary discharge diagnosis code of AUD). Readmission within 30-day was lower (43.9 vs. 48%, P < 0.001) among patients identified to have AUD at the time of discharge. In a conditional logistic regression model, a diagnosis of AUD was associated with 15% reduced odds of 30-day readmission, 0.85 (0.83–0.88). Furthermore, the reason for readmission among patients identified vs. not identified to have AUD was less likely to be liver disease complication. The findings remained similar in a matched cohort of patients where the AUD diagnosis at discharge was listed as one of the secondary diagnoses only. Conclusion Although, our study findings suggest that identification of AUD at the time of discharge among patients hospitalized for alcohol-associated cirrhosis reduces the risk of 30-day readmission, unavailable information on patient counseling, referral for mental health specialist and treatment received for AUD limit the causality assessment. Future studies are needed overcoming the inherent limitations of the database to establish the role of identification and treatment of AUD in reducing readmission and liver decompensation in patients with alcohol-associated cirrhosis.

Abstract Alcoholic hepatitis is the acute deterioration of alcoholic liver disease with rapid onset or worsening of jaundice, which in severe cases, may transition to acute-on-chronic liver failure with extremely high short-term mortality, increasing with the number and severity of hepatic and extra-hepatic organ dysfunction. Diagnosis and treatment are insufficient and challenging, especially due to the complex, multi-factorial and as yet not fully understood pathogenesis. While current management is limited to steroids and best supportive care, debate is ongoing concerning liver transplantation for selected patients, and several novel approaches are under way with mixed results. These drawbacks in disease management together with increasing prevalence in Germany, and generally in Western countries, constitute an unmet need for the healthcare systems. This review tries to summarize the current status of these aspects and provides an overview for pathogenesis, management and potential future treatments.

INTRODUCTION: Cirrhosis is associated with cardiac dysfunction and distinct electrocardiogram (ECG) abnormalities. This study aimed to develop a proof-of-concept deep learning-based artificial intelligence (AI) model that could detect cirrhosis-related signals on ECG and generate an AI-Cirrhosis-ECG (ACE) score that would correlate with disease severity. METHODS: A review of Mayo Clinic's electronic health records identified 5,212 patients with advanced cirrhosis ≥18 years who underwent liver transplantation at the 3 Mayo Clinic transplant centers between 1988 and 2019. The patients were matched by age and sex in a 1:4 ratio to controls without liver disease and then divided into training, validation, and test sets using a 70%-10%-20% split. The primary outcome was the performance of the model in distinguishing patients with cirrhosis from controls using their ECGs. In addition, the association between the ACE score and the severity of patients' liver disease was assessed. RESULTS: The model's area under the curve in the test set was 0.908 with 84.9% sensitivity and 83.2% specificity, and this performance remained consistent after additional matching for medical comorbidities. Significant elevations in the ACE scores were seen with increasing model for end-stage liver disease-sodium score. Longitudinal trends in the ACE scores before and after liver transplantation mirrored the progression and resolution of liver disease. DISCUSSION: The ACE score, a deep learning model, can accurately discriminate ECGs from patients with and without cirrhosis. This novel relationship between AI-enabled ECG analysis and cirrhosis holds promise as the basis for future low-cost tools and applications in the care of patients with liver disease.

Abstract The rise in innovative digital health technologies has led a paradigm shift in health care toward personalized, patient‐centric medicine that is reaching beyond traditional brick‐and‐mortar facilities into patients’ homes and everyday lives. Digital solutions can monitor and detect early changes in physiological data, predict disease progression and health‐related outcomes based on individual risk factors, and manage disease intervention with a range of accessible telemedicine and mobile health options. In this review, we discuss the unique transformation underway in the care of patients with liver disease, specifically examining the digital transformation of diagnostics, prediction and clinical decision‐making, and management. Additionally, we discuss the general considerations needed to confirm validity and oversight of new technologies, usability and acceptability of digital solutions, and equity and inclusivity of vulnerable populations.