Katz, Barry P.

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.

Abstract Background: Accuracy of microbial community detection in 16S rRNA marker-gene and metagenomic studies suffers from contamination and sequencing errors that lead to either falsely identifying microbial taxa that were not in the sample or misclassifying the taxa of DNA fragment reads. Filtering is defined as removing taxa that are present in a small number of samples and have small counts in the samples where they are observed. This approach reduces extreme sparsity of microbiome data and has been shown to correctly remove contaminant taxa in cultured "mock" datasets, where the true taxa compositions are known. Although filtering is frequently used, careful evaluation of its effect on the data analysis and scientific conclusions remains unreported. Here, we assess the effect of filtering on the alpha and beta diversity estimation, as well as its impact on identifying taxa that discriminate between disease states. Results: The effect of filtering on microbiome data analysis is illustrated on four datasets: two mock quality control datasets where same cultured samples with known microbial composition are processed at different labs and two disease study datasets. Results show that in microbiome quality control datasets, filtering reduces the magnitude of differences in alpha diversity and alleviates technical variability between labs, while preserving between samples similarity (beta diversity). In the disease study datasets, DESeq2 and linear discriminant analysis Effect Size (LEfSe) methods were used to identify taxa that are differentially expressed across groups of samples, and random forest models to rank features with largest contribution towards disease classiffcation. Results reveal that filtering retains significant taxa and preserves the model classification ability measured by the area under the receiver operating characteristic curve (AUC). The comparison between filtering and contaminant removal method shows that they have complementary effects and are advised to be used in conjunction. Conclusions: Filtering reduces the complexity of microbiome data, while preserving their integrity in downstream analysis. This leads to mitigation of the classification methods' sensitivity and reduction of technical variability, allowing researchers to generate more reproducible and comparable results in microbiome data analysis.

Only a subset of subjects with excessive alcohol consumption develops alcoholic liver disease (ALD). One of the major risk factors for ALD is the genetic variant of the patatin‐like phospholipase domain‐containing protein 3 (PNPLA3) gene. Coffee is one of the most commonly consumed beverages, and coffee consumption has been associated with lower levels of serum alanine aminotransferase. The aim of this study was to investigate the role of coffee drinking and PNPLA3 rs738409 and their association with alcoholic hepatitis (AH) in a well‐characterized cohort of subjects from the Translational Research and Evolving Alcoholic Hepatitis Treatment consortium. AH subjects and heavy drinking controls without a history of liver disease who were enrolled between May 2013 and May 2016 were included (n = 339), and the details of alcohol and coffee consumption were assessed. The PNPLA3 variant was determined among participants of European ancestry (n = 183). Relationships between baseline data and AH status were determined, and multivariable logistic regression modeling was performed. During the study period, 189 cases with AH and 150 heavy drinking controls were prospectively enrolled. The prevalence of regular coffee consumption was significantly lower in patients with AH compared to controls (20% versus 43%; P < 0.0001). The overall minor allele frequency of the PNPLA3 variant was higher in AH cases. Multivariable logistic regression revealed that coffee consumption and PNPLA3 were significantly associated with AH status at baseline after adjusting for relevant patient characteristics. Conclusion: We found a higher prevalence of AH among heavy drinkers with PNPLA3 G/G and G/C genotypes regardless of coffee consumption status and a higher prevalence of AH among heavy drinkers who were not regular coffee drinkers. These findings remained after considering relevant baseline patient characteristics. Further studies are needed to confirm our observation. (Hepatology Communications 2018;2:29–34)

Intestinal dysbiosis is implicated in alcoholic hepatitis (AH). However, changes in the circulating microbiome, its association with the presence and severity of AH, and its functional relevance in AH is unknown. Qualitative and quantitative assessment of changes in the circulating microbiome were performed by sequencing bacterial DNA in subjects with moderate AH (MAH) (n = 18) or severe AH (SAH) (n = 19). These data were compared with heavy drinking controls (HDCs) without obvious liver disease (n = 19) and non–alcohol‐consuming controls (NACs, n = 20). The data were related to endotoxin levels and markers of monocyte activation. Linear discriminant analysis effect size (LEfSe) analysis, inferred metagenomics, and predictive functional analysis using PICRUSt were performed. There was a significant increase in 16S copies/ng DNA both in MAH ( P < 0.01) and SAH ( P < 0.001) subjects. Compared with NACs, the relative abundance of phylum Bacteroidetes was significantly decreased in HDCs, MAH, and SAH ( P < 0.001). In contrast, all alcohol‐consuming groups had enrichment with Fusobacteria ; this was greatest for HDCs and decreased progressively in MAH and SAH. Subjects with SAH had significantly higher endotoxemia ( P = 0.01). Compared with alcohol‐consuming groups, predictive functional metagenomics indicated an enrichment of bacteria with genes related to methanogenesis and denitrification. Furthermore, both HDCs and SAH showed activation of a type III secretion system that has been linked to gram‐negative bacterial virulence. Metagenomics in SAH versus NACs predicted increased isoprenoid synthesis via mevalonate and anthranilate degradation, known modulators of gram‐positive bacterial growth and biofilm production, respectively. Conclusion: Heavy alcohol consumption appears to be the primary driver of changes in the circulating microbiome associated with a shift in its inferred metabolic functions. (H epatology 2018;67:1284‐1302).

The TREAT Consortium has carried out clinical studies on alcoholic hepatitis (AH) for over 4 years. We encountered problems with participant recruitment, retention, and eligibility for specific protocols. To improve our ability to carry out such trials, we reviewed recruitment screening logs, end of study logs, and surveyed study coordinators to learn the reasons for missing patients, why patients declined enrollment, and the number of patients eligible for treatment trials. Associations of the recruited subjects’ demographics with their adherence to follow‐up appointments were examined. Three hundred eight‐seven patients (AH and heavy drinking controls) were enrolled in the observational study, and 55 AH patients were recruited into treatment trials. About half of patients identified with AH could not be recruited; no specific reason could be determined for about two‐thirds of these. Among the patients who gave a reason for not participating, the most common reasons were feeling too sick to participate, desire to concentrate on abstinence, and lack of interest in research. Approximately a quarter of the AH patients met eligibility criteria for treatment trials for moderate or severe AH and we were able to recruit half to two‐thirds of those eligible. Approximately 35% of participants in the observational study returned for both 6‐ and 12‐month follow‐up visits. We did not identify biopsychosocial or demographic correlates of retention in the study. This analysis revealed that attempts at recruitment into trials for AH miss some subjects because of structural issues surrounding their hospital admission, and encounter a high rate of patient refusal to participate. Nonetheless, more than half of the patients who met the eligibility criteria for moderate or severe AH were entered into clinical trials. Retention rates for the observational study are relatively low. These findings need to be accounted for in clinical trial design and power analysis.

Alcoholic hepatitis (AH) develops in only a small proportion of heavy drinkers. To better understand the mechanisms underlying this disparity, we conducted a study to define the relationship between AH development and dysregulated immune responses that might be ameliorated by alcohol abstinence. Sixty‐eight AH patients, 65 heavy drinking controls without liver disease (HDC), and 20 healthy controls were enrolled and followed up to 12 months. At baseline, HDC and healthy controls had no significant differences in their plasma levels of 38 inflammatory cytokines/chemokines measured using multiplex immunoassays. However, compared to HDC, AH patients had higher baseline levels of 11 cytokines/chemokines (tumor necrosis factor alpha, interleukin 6 [IL‐6], IL‐8, interferon gamma–induced protein 10, IL‐4, IL‐9, IL‐10, fibroblast growth factor 2, IL‐7, IL‐15, and transforming growth factor alpha) but lower levels of the anti‐inflammatory macrophage‐derived chemokine. AH patients also had more activated yet dysfunctional immune cells as monocytes, T cells, and B cells expressed higher levels of cluster of differentiation 38 (CD38) and CD69 but low levels of human leukocyte antigen DR, CD80, and CD86 at baseline. In addition, CD4 T cells produced less interferon‐gamma in response to T‐cell stimulation. Up‐regulated IL‐6, IL‐8, CD38, and CD69 and down‐regulated macrophage‐derived chemokine, human leukocyte antigen DR, CD86, and CD80 correlated positively and negatively, respectively, with disease severity. Longitudinal analysis indicated that levels of IL‐6, IL‐8, CD38, and CD69 were reduced, whereas levels of macrophage‐derived chemokine, human leukocyte antigen DR, CD80, and CD86 were increased in abstinent AH patients. All of the cellular immune abnormalities were reversed by day 360 in abstinent AH patients; however, plasma levels of tumor necrosis factor alpha, IL‐8, IL‐10, fibroblast growth factor 2, and IL‐7 remained higher. Conclusion: AH patients were in a highly immune‐dysregulated state, whereas HDC showed little evidence of immune activation; alcohol abstinence reversed most, but not all, of the immunological abnormalities. (Hepatology 2017;66:575–590).