Intrahepatic distribution of nerve fibers and alterations due to fibrosis in diseased liver.

Autonomic nerve fibers in the liver are distributed along the portal tract, being involved in the regulation of blood flow, bile secretion and hepatic metabolism, thus contributing to systemic homeostasis. The present study investigated changes in hepatic nerve fibers in liver biopsy specimens from patients with normal liver, viral hepatitis and non-alcoholic steatohepatitis, in relation to clinical background. The areal ratio of nerve fibers to the total portal area was automatically calculated for each sample. The nerve fiber areal ratios (NFAR) for total nerve fibers and sympathetic nerve fibers were significantly lower in liver affected by chronic hepatitis, particularly viral hepatitis, and this was also the case for advanced liver fibrosis. However, the degree of inflammatory activity did not affect NFAR for either whole nerves or sympathetic nerves. Comparison of samples obtained before and after antiviral treatment for HCV demonstrated recovery of NFAR along with improvement of liver fibrosis.

A machine learning-based treatment prediction model using whole genome variants of hepatitis C virus.

In recent years, the development of diagnostics using artificial intelligence (AI) has been remarkable. AI algorithms can go beyond human reasoning and build diagnostic models from a number of complex combinations. Using next-generation sequencing technology, we identified hepatitis C virus (HCV) variants resistant to directing-acting antivirals (DAA) by whole genome sequencing of full-length HCV genomes, and applied these variants to various machine-learning algorithms to evaluate a preliminary predictive model. HCV genomic RNA was extracted from serum from 173 patients (109 with subsequent sustained virological response [SVR] and 64 without) before DAA treatment. HCV genomes from the 109 SVR and 64 non-SVR patients were randomly divided into a training data set (57 SVR and 29 non-SVR) and a validation-data set (52 SVR and 35 non-SVR). The training data set was subject to nine machine-learning algorithms selected to identify the optimized combination of functional variants in relation to SVR status following DAA therapy. Subsequently, the prediction model was tested by the validation-data set. The most accurate learning method was the support vector machine (SVM) algorithm (validation accuracy, 0.95; kappa statistic, 0.90; F-value, 0.94). The second-most accurate learning algorithm was Multi-layer perceptron. Unfortunately, Decision Tree, and Naive Bayes algorithms could not be fitted with our data set due to low accuracy (< 0.8). Conclusively, with an accuracy rate of 95.4% in the generalization performance evaluation, SVM was identified as the best algorithm. Analytical methods based on genomic analysis and the construction of a predictive model by machine-learning may be applicable to the selection of the optimal treatment for other viral infections and cancer.

[A case of fibrinogen storage disease with primary biliary cholangitis].

A 66-year-old woman was diagnosed as primary biliary cholangitis (PBC) and was previously hospitalized for ascites and jaundice. She came to our hospital for further examination of the liver by needle biopsy, which showed interface hepatitis that mainly comprised lymphocytes and inflammatory infiltrates in the bile duct in the portal area. On the other hand, numerous intracytoplasmic inclusions that were positive for fibrinogen immunostaining were seen in the lobular area. Finally, we histologically diagnosed as PBC with fibrinogen storage disease (FSD). FSD is rare disease that leads to liver damage caused by abnormal fibrinogen storage in the endoplasmic reticulum of hepatocytes, with only four cases reported in Japan until now.

Incidence of development of hepatocellular carcinoma in Japanese patients infected with hepatitis B virus is equivalent between genotype B and C in long term.

Hepatitis B virus (HBV) genotypes B (HBV/B) and C (HBV/C) are the most prevalent genotypes among Japanese patients with hepatitis. Reportedly, HBV/C infection has been associated with more severe disease progression, manifesting as developing cirrhosis and hepatocellular carcinoma (HCC), than HBV/B infection. However, no long-term studies have examined the development of HCC in HBV/B-infected patients in Japan. The aims of our study were to compare the incidence of HCC in HBV/B- or HBV/C-infected patients. A total of 241 patients were followed up among 295 hepatitis B surface antigen (HBsAg)-positive carriers. Genotypes of HBV were A in 1% (4/295), B in 61% (179/295), C in 37% (110/295) and D in 1% (2/295) patients, and 96% of HBV/B were infected with subgenotype Bj. The mean age at HCC diagnosis was significantly higher in HBV/B than in HBV/C (67.0 ± 10.0 vs 57.7 ± 8.0 years, P < 0.001). The value of FIB-4 index was significantly higher in HBV/B than in HBV/C (P < 0.01). The rate of HCC was higher in HBV/C than in HBV/B, and a significant difference was observed until the 20-year observation period (P = 0.048). However, thereafter, HCC associated with HBV/B increased, and no significant difference was observed between HBV/B and HBV/C. HCC development was consistently observed even in HBV/B infection, especially among elderly patients with advanced fibrosis compared with HBV/C. HBV/B-infected patients developed HCC later in life, and in the long term, we found no differences in incidence of HCC development rates between these two genotypes.

Current Cell-Based Therapies in the Chronic Liver Diseases.

Liver diseases account for one of the leading causes of deaths in global health care. Furthermore, chronic liver failure such as liver cirrhosis is, namely, responsible for these fatal conditions. However, only liver transplantation is an established treatment for this end-stage condition, although the availability of this salvage treatment option is quite limited. Thus, the novel therapy such as artificial liver devices or cellular administration has been regarded as feasible. Especially cellular therapies have been proposed in decades. The technical advancement and progress of understanding of cellular differentiation have contributed to the development of basis of cellular therapy. This attractive therapeutic option has been advanced from original embryonic stem cells to more effective cellular fractions such as Muse cells. Indeed several cellular therapies including bone marrow-derived stem cells or peripheral blood-derived stem cells were initiated; the recent most organized clinical trials could not demonstrate its efficacy. Thus, truly innovative cellular therapy is needed to meet the scientific demands, and Muse cell administration is the remaining approach to this. In this article, we will discuss the current development and status of cellular therapy toward chronic liver failure.

MiR-139-5p is associated with inflammatory regulation through c-FOS suppression, and contributes to the progression of primary biliary cholangitis.

Primary biliary cholangitis (PBC) is a chronic cholestatic liver disease characterized pathologically by destruction of intrahepatic bile ducts. PBC is largely classified into three subtypes based on clinical course: (i) gradually progressive, (ii) portal hypertension, and (iii) hepatic failure. Previous studies have indicated that serum levels of the pro-inflammatory cytokine TNF-α, is elevated in PBC patients with fibrosis. Although the severity of cholangitis might also be related to the PBC subtype, its etiology has been unclear. Several studies have shown that microRNAs (miRNAs) demonstrate specific expression patterns in various diseases. In the present study, we evaluated miRNA expression patterns among the PBC subtypes using comprehensive deep sequencing. We also carried out histologic examination by laser capture microdissection and investigated how the identified miRNAs were involved in PBC clinical progression using the miRNA transfection method. On average, ~11 million 32-mer short RNA reads per sample were obtained, and we found that the expression levels of 97 miRNAs differed significantly among the four groups. Heat mapping demonstrated that the miRNA profiles from hepatic failure and portal hypertension type were clustered differently from those of the gradually progressive type and controls. Furthermore, we focused on miR-139-5p, which has an adequate number of total short reads. Quantitative reverse transcription PCR showed that miR-139-5p was significantly downregulated in clinically advanced PBC. Also, examination of liver tissues demonstrated that the expression of lymphocyte-derived miR-139-5p was significantly higher in hepatocytes. In vitro, the level of TNF-α was significantly elevated in supernatant of cells with upregulation of miR-139-5p. Furthermore, c-FOS gene transcription was repressed. Thus, we have demonstrated a novel inflammation-regulatory mechanism involving TNF-α and c-FOS transcription through miR-139-5p in the NF-κB signaling pathway. We conclude that the specific miRNA miR-139-5p might be involved in the pathogenesis of PBC, especially during clinical progression.

Serum metabolome profiles characterized by patients with hepatocellular carcinoma associated with hepatitis B and C.

AIM: To clarify the characteristics of metabolite profiles in virus-related hepatocellular carcinoma (HCC) patients using serum metabolome analysis. METHODS: The serum levels of low-molecular-weight metabolites in 68 patients with HCC were quantified using capillary electrophoresis chromatography and mass spectrometry. Thirty and 38 of the patients suffered from hepatitis B virus-related HCC (HCC-B) and hepatitis C virus-related HCC (HCC-C), respectively. RESULTS: The main metabolites characteristic of HCC were those associated with glutathione metabolism, notably 13 γ-glutamyl peptides, which are by-products of glutathione induction. Two major profiles, i.e., concentration patterns, of metabolites were identified in HCC patients, and these were classified into two groups: an HCC-B group and an HCC-C group including some of the HCC-B cases. The receiver operating characteristic curve for the multiple logistic regression model discriminating HCC-B from HCC-C incorporating the concentrations of glutamic acid, methionine and γ-glutamyl-glycine-glycine showed a highly significant area under the curve value of 0.94 (95%CI: 0.89-1.0, P < 0.0001). CONCLUSION: The serum levels of γ-glutamyl peptides, as well as their concentration patterns, contribute to the development of potential biomarkers for virus-related HCC. The difference in metabolite profiles between HCC-B and HCC-C may reflect the respective metabolic reactions that underlie the different pathogeneses of these two types of HCC.