Citations

A number of cell culture approaches have been described for maintenance of primary hepatocytes. Forming hepatocytes into three-dimensional (3-D) spheroids is one well-accepted method for extending epithelial phenotype of these cells. Our laboratory has previously observed enhanced function of two-dimensional (2-D, monolayer) hepatocyte cultures in microfluidic devices due to increased production of several hepato-inductive growth factors, including hepatocyte growth factor (HGF). In the present study, we wanted to test a hypothesis that culturing hepatocyte spheroids (3-D) in microfluidic devices will also result in enhanced phenotype and function. To test this hypothesis, we fabricated devices with small and large volumes. Both types of devices included a microstructured floor containing arrays of pyramidal wells to promote assembly of hepatocytes into spheroids with individual diameters of ~100 µm. The hepatocyte spheroids were found to be more functional, as evidenced by higher level of albumin synthesis, bile acid production, and hepatic enzyme expression, in low-volume compared with large-volume devices. Importantly, high functionality of spheroid cultures correlated with elevated levels of HGF secretion. Although decay of hepatic function (albumin secretion) was observed over the course 3 wk, this behavior could be abrogated by inhibiting TGF-β1 signaling. With TGF-β1 inhibitor, microfluidic hepatocyte spheroid cultures maintained high and stable levels of albumin synthesis over the course of 4 wk. To further highlight utility of this culture platform for liver disease modeling, we carried out alcohol injury experiments in microfluidic devices and tested protective effects of interleukin-22: a potential therapy for alcoholic hepatitis.

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.

BackgroundAlcoholic hepatitis (AH) is a severe inflammatory liver disease that develops in some heavy drinkers. AH patients have intense hepatic infiltration of leukocytes. Up‐regulation of cell adhesion molecules (CAMs) upon endothelial cell (EC) activation plays an important role in leukocyte transendothelial migration. CAMs can shed from EC surface and accumulate in the blood, serving as soluble markers for EC activation. In this study, we examined the impact of heavy drinking on expression of soluble forms of EC activation markers (CD146, ICAM‐1, VCAM‐1, and VEGF‐A) and the effect of alcohol abstinence on the reversal of these abnormalities in heavy drinkers with and without AH.MethodsELISA and multiplex immunoassays were used to measure soluble EC activation markers in plasma samples from 79 AH patients, 66 heavy drinkers without overt liver disease (HDC), and 44 healthy controls (HC) at baseline, 31 AH patients and 30 HDC at 6‐month follow‐up, and 18 AH patients and 25 HDC at 12‐month follow‐up.ResultsAt baseline, the 4 soluble markers were significantly up‐regulated in AH patients compared with HDC and HC, whereas only sVCAM‐1 was elevated in HDC relative to HC. At follow‐ups, plasma levels of CD146, VCAM‐1, and VEGF‐A remained higher in AH patients, even for those who stopped drinking. These dysregulated markers correlated with AH disease severity, clinical parameters, and several soluble inflammatory factors.ConclusionsThe levels of soluble CD146, ICAM‐1, VCAM‐1, and VEGF‐A were highly elevated in AH patients, and alcohol abstinence did not completely reverse these abnormalities.

Background and Aims Alcoholic hepatitis (AH) is diagnosed by clinical criteria, although several objective scores facilitate risk stratification. Extracellular vesicles (EVs) have emerged as biomarkers for many diseases and are also implicated in the pathogenesis of AH. Therefore, we investigated whether plasma EV concentration and sphingolipid cargo could serve as diagnostic biomarkers for AH and inform prognosis to permit dynamic risk profiling of AH subjects. Approach and Results EVs were isolated and quantified from plasma samples from healthy controls, heavy drinkers, and subjects with end‐stage liver disease (ESLD) attributed to cholestatic liver diseases and nonalcoholic steatohepatitis, decompensated alcohol‐associated cirrhosis (AC), and AH. Sphingolipids were quantified by tandem mass spectroscopy. The median plasma EV concentration was significantly higher in AH subjects (5.38 × 1011/mL) compared to healthy controls (4.38 × 1010/mL; P < 0.0001), heavy drinkers (1.28 × 1011/mL; P < 0.0001), ESLD (5.35 × 1010/mL; P < 0.0001), and decompensated AC (9.2 × 1010/mL; P < 0.0001) disease controls. Among AH subjects, EV concentration correlated with Model for End‐Stage Liver Disease score. When EV counts were dichotomized at the median, survival probability for AH subjects at 90 days was 63.0% in the high‐EV group and 90.0% in the low‐EV group (log‐rank P value = 0.015). Interestingly, EV sphingolipid cargo was significantly enriched in AH when compared to healthy controls, heavy drinkers, ESLD, and decompensated AC (P = 0.0001). Multiple sphingolipids demonstrated good diagnostic and prognostic performance as biomarkers for AH. Conclusions Circulating EV concentration and sphingolipid cargo signature can be used in the diagnosis and differentiation of AH from heavy drinkers, decompensated AC, and other etiologies of ESLD and predict 90‐day survival permitting dynamic risk profiling.

Background and Aims Hepatologists often determine whether transcatheter aortic valve replacement (TAVR) or surgical aortic valve replacement (SAVR) is preferred for patients with cirrhosis and severe aortic stenosis. The goal of this cohort study is to compare outcomes following TAVR and SAVR in patients with cirrhosis to inform the preferred intervention. Approach and Results Prospectively collected data on 105 consecutive patients with cirrhosis and aortic stenosis who underwent TAVR (n = 55) or SAVR (n = 50) between 2008 and 2016 were reviewed retrospectively. Two control groups were included: 2,680 patients without cirrhosis undergoing TAVR and SAVR and 17 patients with cirrhosis who received medical therapy alone. Among the 105 patients with cirrhosis, the median Society of Thoracic Surgeons score was 3.8% (1.5, 6.9), and the median Model for End‐Stage Liver Disease (MELD) score was 11.6 (9.4, 14.0). The TAVR group had similar in‐hospital (1.8% vs. 2.0%) and 30‐day mortality (3.6% vs. 4.2%) as the SAVR group. During the median follow‐up of 3.8 years (95% confidence interval, 3.0‐6.9), there were 63 (60%) deaths. MELD score (adjusted hazard ratio, 1.13; 95% confidence interval, 1.05‐1.21; P = 0.002) was an independent predictor of long‐term survival. In the subgroup of patients with MELD score <12, the TAVR group had reduced survival compared with the SAVR group (median survival of 2.8 vs. 4.4 years; P = 0.047). However, in those with MELD score ≥12, survival after TAVR, SAVR, and medical therapy was similar (1.3 vs. 2.1 vs. 1.6 years, respectively; P = 0.53). Conclusion In select patients with cirrhosis, both TAVR and SAVR have acceptable and comparable short‐term outcomes. MELD score, but not Society of Thoracic Surgeons score, independently predicts long‐term survival after TAVR and SAVR. For patients with MELD score <12, SAVR is a preferred procedure; however, neither procedure appears superior to medical therapy in patients with MELD score ≥12.

Background and Aims The role of the intestinal microbiome in alcoholic hepatitis is not established. The aims of this study were to (1) characterize the fecal microbial ecology associated with alcoholic hepatitis, (2) relate microbiome changes to disease severity, and (3) infer the functional relevance of shifts in microbial ecology. Approach and Results The fecal microbiome in patients with moderate alcoholic hepatitis (MAH) or severe alcoholic hepatitis (SAH) was compared with healthy controls (HCs) and heavy drinking controls (HDCs). Microbial taxa were identified by 16S pyrosequencing. Functional metagenomics was performed using PICRUSt. Fecal short chain fatty acids (SCFAs) were measured using a liquid chromatography–mass spectrometry platform. A total of 78 participants (HC, n = 24; HDC, n = 20; MAH, n = 10; SAH, n = 24) were studied. HDC had a distinct signature compared with HC with depletion of Bacteroidetes (46% vs. 26%; P = 0.01). Alcoholic hepatitis was associated with a distinct microbiome signature compared with HDC (area under the curve = 0.826); differential abundance of Ruminococcaceae , Veillonellaceae , Lachnospiraceae , Porphyromonadaceae , and Rikenellaceae families were the key contributors to these differences. The beta diversity was significantly different among the groups (permutational multivariate analysis of variance [PERMANOVA] P < 0.001). SAH was associated with increased Proteobacteria (SAH 14% vs. HDC 7% and SAH vs. HC 2%, P = 0.20 and 0.01, respectively). Firmicutes abundance declined from HDC to MAH to SAH (63% vs. 53% vs. 48%, respectively; P = 0.09, HDC vs. SAH). Microbial taxa did not distinguish between MAH and SAH (PERMANOVA P = 0.785). SCFAs producing bacteria (Lachnospiraceae and Ruminococcaceae) were decreased in alcoholic hepatitis, and a similar decrease was observed in fecal SCFAs among alcoholic hepatitis patients. Conclusions There are distinct changes in fecal microbiome associated with the development, but not severity, of alcoholic hepatitis.

OBJECTIVES: Severe alcoholic hepatitis (sAH) confers substantial mortality, but the disease course is difficult to predict. As iron parameters are attractive outcome predictors in other liver diseases, we tested their prognostic ability in sAH. METHODS: Serum ferritin, transferrin, iron, transferrin saturation, nontransferrin-bound iron, soluble transferrin receptor, and hepcidin were measured in 828 patients with sAH recruited prospectively through the STOPAH trial. The cohort was randomly divided into exploratory (n = 200) and validation sets (n = 628). RESULTS: Patients with sAH had diminished serum transferrin but increased transferrin saturation. Among iron parameters, baseline transferrin was the best predictor of 28-day (area under the receiver operated characteristic 0.72 [95% confidence interval 0.67–0.78]) and 90-day survival (area under the receiver operated characteristic 0.65 [0.61–0.70]). Transferrin's predictive ability was comparable with the composite scores, namely model of end-stage liver disease, Glasgow alcoholic hepatitis score, and discriminant function, and was independently associated with survival in multivariable analysis. These results were confirmed in a validation cohort. Transferrin did not correlate with markers of liver synthesis nor with non–transferrin-bound iron or soluble transferrin receptor (as markers of excess unbound iron and functional iron deficiency, respectively). DISCUSSION: In patients with sAH, serum transferrin predicts mortality with a performance comparable with commonly used composite scoring systems. Hence, this routinely available parameter might be a useful marker alone or as a component of prognostic models.

Alcoholic hepatitis (AH) is a severe inflammatory liver disease that develops in some heavy drinkers. The immune system in patients with AH is hyperactive and yet dysfunctional. Here, we investigated whether this immune‐dysregulated state is related to the alcoholic impact on immune checkpoints (ICPs). We used multiplex immunoassays and enzyme‐linked immunosorbent assay to quantify plasma levels of 18 soluble ICPs (sICPs) from 81 patients with AH, 65 heavy drinkers without liver diseases (HDCs), and 39 healthy controls (HCs) at baseline, 33 patients with AH and 32 HDCs at 6‐month follow‐up, and 18 patients with AH and 29 HDCs at 12‐month follow‐up. We demonstrated that baseline levels of 6 sICPs (soluble T‐cell immunoglobulin and mucin domain 3 [sTIM‐3], soluble cluster of differentiation [sCD]27, sCD40, soluble Toll‐like receptor‐2 [sTLR‐2], soluble herpesvirus entry mediator [sHVEM], and soluble lymphotoxin‐like inducible protein that competes with glycoprotein D for herpes virus entry on T cells [sLIGHT]) were up‐regulated, while 11 sICPs (soluble B‐ and T‐lymphocyte attenuator [sBTLA], sCD160, soluble cytotoxic T‐lymphocyte‐associated protein 4 [sCTLA‐4], soluble lymphocyte‐activation gene 3 [sLAG‐3], soluble programmed death 1 [sPD‐1], sPD ligand 1 [sPD‐L1], sCD28, soluble glucocorticoid‐induced tumor necrosis factor receptor‐related protein [sGITR], sGITR ligand [sGITRL], sCD80, and inducible T‐cell costimulator [sICOS]) were down‐regulated in patients with AH compared to HDCs. The up‐regulated sICPs except sLIGHT and down‐regulated sCD80, sCD160, sCTLA‐4, and sLAG‐3 correlated positively or negatively with AH disease severity, bacterial translocation, and inflammatory factors. At follow‐up, abstinent patients with AH still had higher levels of several sICPs compared to HDCs. We also compared expression of 10 membrane‐bound ICPs (mICPs) on peripheral blood mononuclear cells (PBMCs) from patients with AH and HCs by flow cytometry and found that several mICPs were dysregulated on blood cells from patients with AH. The function and regulation of sICPs and mICPs were studied using PBMCs from patients with AH and HCs. Recombinant sHVEM affected tumor necrosis factor (TNF)‐α and interferon‐γ production by T cells from patients with AH and HCs. Conclusion: Both sICPs and mICPs were dysregulated in patients with AH, and alcohol abstinence did not fully reverse these abnormalities. The HVEM axis plays a role in regulating T‐cell function in patients with AH.