Determining optimal ALT cut-off values for predicting significant hepatic histological changes in patients with normal ALT in the grey zone of chronic hepatitis B virus infection.

BACKGROUND AND AIMS: We aimed to define gender-specific, optimal alanine aminotransferase (ALT) cut-off values for the prediction of significant liver histological changes (SLHC) in Chinese patients with grey zone (GZ) chronic hepatitis B (CHB) and normal ALT. METHODS: In a retrospective study, we included 1101 consecutive patients with GZ CHB and normal ALT assigned to training or internal validation cohorts. We included an independent cohort of 842 patients for external validation. We performed receiver operating characteristic (ROC) curve, smoothed curve fitting, and threshold effect analyses to determine optimal ALT cut-off values. Area under the curve (AUC) values were calculated to assess their predictive performance. RESULTS: A proportion of 79.3% of patients with GZ CHB and normal ALT (≤40 U/L) had SLHC. ROC curve analysis initially identified optimal ALT cut-off values of 29 U/L (male) and 22 U/L (female). After smoothed curve fitting and threshold effect analyses, new optimal cut-off values were 27 U/L for males and 24 U/L for females. AUCs for these values were 0.836 (male) and 0.833 (female) in the internal validation cohort, and 0.849 (male) and 0.844 (female) in the external validation cohort. The accuracy and discriminative ability of the newly defined ALT cut-off values were greater than those of the current recommendations. CONCLUSION: This study established novel optimal ALT cut-off values for more precise prediction of SLHC among Chinese patients with GZ CHB and normal ALT levels. This may help identify individuals who will benefit from timely antiviral therapy.

Hepatitis B Virus Envelope Antigen and Hepatitis B Virus Surface Antigen Both Contribute to the Innate Immune Response During Persistent Hepatitis B Virus Infection.

This study aimed to investigate the changes of toll-like receptor 4 (TLR4), proinflammatory cytokine expression, hepatitis B virus surface antigen (HBsAg), and hepatitis B virus envelope antigen (HBeAg) expression as well as innate immune cell percentages in a mouse model of persistent hepatitis B virus (HBV) infection to better understand the innate immune response. Mouse models of persistent HBV infection, HBsAg expression, and HBeAg expression were developed using high-pressure tail-vein injection of recombinant adeno-associated viruses. Enzyme-linked immunosorbent assays (ELISAs) were used to determine the serum proinflammatory cytokine levels. Immunohistochemistry and western blot assays were used to detect TLR4 expression. Flow cytometric analysis was used to assess the percentage of innate immune cells in the whole blood. Persistent HBV infection, HBsAg expression, and HBeAg expression each significantly decreased the expression of TLR4. Persistent HBV infection significantly increased the percentages of T cells and monocytes, whereas it decreased the percentage of natural killer (NK) cells. Persistent HBeAg expression also decreased the percentage of NK cells, whereas persistent HBsAg expression increased the percentage of NK cells. Both persistent HBsAg and HBeAg expression increased the percentage of monocytes. However, both persistent HBsAg and HBeAg expression decreased the percentage of T cells. HBV as well as HBsAg and HBeAg showed similar effects on the expression of TLR4 and proinflammatory cytokines as well as the percentage of monocytes. Persistent HBV infection increased the percentage of T cells and decreased the percentage of NK cells, whereas only persistent HBeAg expression contributed to a decreased percentage of NK cells.

Development a novel nomogram model for predicting significant hepatic histological changes in chronic hepatitis B virus carriers.

A proportion of chronic hepatitis B virus (HBV) carriers with normal alanine transaminase (ALT) present with significant liver histological changes (SLHC). To construct a noninvasive nomogram model to identify SLHC in chronic HBV carriers with different upper limits of normal (ULNs) for ALT. The training cohort consisted of 732 chronic HBV carriers who were stratified into four sets according to different ULNs for ALT: chronic HBV carriers I, II, III, and IV. The external validation cohort comprised 277 chronic HBV carriers. Logistic regression and least absolute shrinkage and selection operator analyses were applied to develop a nomogram model to predict SLHC. A nomogram model-HBGP (based on hepatitis B surface antigen, gamma-glutamyl transpeptidase, and platelet count) demonstrated good performance in diagnosing SLHC with area under the curve (AUCs) of 0.866 (95% confidence interval [CI]: 0.839-0.892) and 0.885 (95% CI: 0.845-0.925) in the training and validation cohorts, respectively. Furthermore, HBGP displayed high diagnostic values for SLHC with AUCs of 0.866 (95% CI: 0.839-0.892), 0.868 (95% CI: 0.838-0.898), 0.865 (95% CI: 0.828-0.901), and 0.853 (95% CI: 0.798-0.908) in chronic HBV carriers I, II, III, and IV, respectively. Additionally, HBGP showed greater ability in predicting SLHC compared with the existing predictors. HBGP has shown high predictive performance for SLHC, and thus may lead to an informed decision on the initiation of antiviral treatment.

Gut microbiota of hepatitis B virus-infected patients in the immune-tolerant and immune-active phases and their implications in metabolite changes.

BACKGROUND: The microbes and metabolomics of microbiota dysbiosis in the gut in the different phases of hepatitis B virus (HBV) infection are not fully understood. AIM: To investigate the specific gut microbiota and metabolites of the immune-tolerant (IT) and immune-active (IA) phases of chronic hepatitis B (CHB). METHODS: Clinical fecal samples from healthy individuals and patients in the IT and IA phases of HBV infection were collected. Next, non-target metabolomics, bioinformatics, and 16S rDNA sequencing analyses were performed. RESULTS: A total of 293 different metabolites in 14 phyla, 22 classes, 29 orders, 51 families, and 190 genera were identified. The four phyla of Firmicutes, Bacteroidetes, Actinobacteria, and Proteobacteria were the most abundant, accounting for 99.72%, 99.79%, and 99.55% in the healthy controls, IT-phase patients, and IA-phase patients, respectively. We further identified 16 genera with different richness in the IT phase and IA phase of HBV infection. Of the 134 named metabolites, 57 were upregulated and 77 were downregulated. A total of 101 different metabolic functions were predicted in this study, with 6 metabolic pathways having the highest enrichments, namely carbohydrate metabolism (14.85%), amino acid metabolism (12.87%), lipid metabolism (11.88%), metabolism of cofactors and vitamins (11.88%), xenobiotic biodegradation (9.9%), and metabolism of terpenoids and polyketides (7.92%). CONCLUSION: These findings provide observational evidence of compositional alterations of the gut microbiome and some related metabolites in patients with IT-phase or IA-phase HBV infection. Further studies should investigate whether microbiota modulation can facilitate the progression of CHB and the cause-effect relationship between the gut microbiota and CHB.

Chromobox 7/8 serve as independent indicators for glioblastoma via promoting proliferation and invasion of glioma cells.

Background: The chromobox family, a critical component of epigenetic regulators, participates in the tumorigenesis and progression of many malignancies. However, the roles of the CBX family members (CBXs) in glioblastoma (GBM) remain unclear. Methods: The mRNA expression of CBXs was analyzed in tissues and cell lines by Oncomine and Cancer Cell Line Encyclopedia (CCLE). The differential expression of CBXs at the mRNA level was explored in The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) databases with the "beeswarm" R package. The protein expression of CBXs in GBM was further examined on Human Protein Atlas (HPA). The correlations between CBXs and IDH mutation and between CBXs and GBM subtypes were investigated in the TCGA portal and CGGA database with the "survminer" R package. The alteration of CBXs and their prognostic value were further determined via the cBioPortal and CGGA database with the "survival" R package. The univariate and multivariate analyses were performed to screen out the independent prognostic roles of CBXs in the CGGA database. Cytoscape was used to visualize the functions and related pathways of CBXs in GBM. U251 and U87 glioma cells with gene intervention were used to validate the role of CBX7/8 in tumor proliferation and invasion. Proliferation/invasion-related markers were conducted by Western blot and immunostaining. Results: CBXs presented significantly differential expressions in pan-cancers. CBX2/3/5/8 were upregulated, whereas CBX6/7 were downregulated at mRNA level in GBM of TCGA and CGGA databases. Similarly, high expression of CBX2/3/5 and low expression of CBX6/8 were further confirmed at the protein level in the HPA. CBX2/6/7 were positively correlated with IDH mutation and CBX1/2/4/5/8 were closely related to GBM subtypes. CBX7 and CBX8 presented the independent prognostic factors for GBM patient survival. GO and KEGG analyses indicated that CBXs were closely related to the histone H3-K36, PcG protein complex, ATPase, and Wnt pathway. The overexpression of CBX7 and underexpression of CBX8 significantly inhibited the proliferation and invasion of glioma cells in vivo and in vitro. Conclusion: Our results suggested that CBX7 and CBX8 served as independent prognostic indicators that promoted the proliferation and invasion of glioma cells, providing a promising strategy for diagnosing and treating GBM.

Advantages of a Novel Model for Predicting Hepatic Fibrosis in Chronic Hepatitis B Virus Carriers Compared with APRI and FIB-4 Scores.

Background and Aims: Aspartate aminotransferase-to-platelet ratio index (APRI) and fibrosis-4 index (FIB-4) are widely used to assess liver fibrosis in chronic hepatitis B virus (HBV) infection. Currently, the definition of normal alanine aminotransferase (ALT) is controversial. We aimed to examine the diagnostic value of APRI and FIB-4 in chronic HBV carriers with different upper limits of normal (ULNs) for ALT. Methods: 581 chronic HBV carriers were divided into the following four groups based on different ULNs for ALT: chronic HBV carriers I, II, III, and IV. Furthermore, 106 chronic HBV carriers formed an external validation group. Predictive values of APRI and FIB-4 were elucidated using the area under the curve (AUC). A liver fibrosis-predictive model-GPSA (named for its measure of gamma glutamyl transpeptidase, platelet count, HBsAg and albumin) was developed using multivariate logistic regression analysis. Results: In chronic HBV carriers I, the AUCs of APRI and FIB-4 were 0.680 and 0.609 for significant fibrosis and 0.678 and 0.661 for cirrhosis, respectively. The AUCs of GPSA for significant fibrosis in the training group, internal group, and external validation group were 0.877, 0.837, and 0.871, respectively. The diagnostic value of GPSA differed among chronic HBV carriers I, II, III, and IV, with AUCs for significant fibrosis being 0.857, 0.853, 0.868, and 0.905 and AUCs for cirrhosis being 0.901, 0.905, 0.886, and 0.913, respectively. GPSA showed a higher diagnostic value than APRI and FIB-4 for predicting significant fibrosis in the four groups. Conclusions: The GPSA model allows for accurate diagnosis of liver fibrosis in chronic HBV carriers with different ULN for ALT.

A novel HBsAg-based model for predicting significant liver fibrosis among Chinese patients with immune-tolerant phase chronic hepatitis B: a multicenter retrospective study.

BACKGROUND: Hepatitis B e antigen (HBeAg)-positive chronic hepatitis B (CHB) in the immune-tolerant (IT) phase is significantly associated with high risk for hepatocellular carcinoma, suggesting requirement for antiviral therapy, particularly for those with histological liver injury. This study aimed to establish a non-invasive panel to assess significant liver fibrosis in IT chronic hepatitis B. PATIENTS AND METHODS: One hundred and thirteen IT-phase CHB patients were retrospectively recruited and divided into two histopathological groups according to their histological profiles: necroinflammatory score <4 (N <4)/fibrosis score ⩽1 (F0-1), and necroinflammatory score ⩾4 (N ⩾4)/fibrosis score ⩾2 (F2-4). Multivariate analysis was conducted to assess the predictive value of the non-invasive model for significant liver fibrosis. RESULTS: IT-phase CHB patients with N <4/F0-1 had significantly higher HBsAg levels than those with N ⩾4/F2-4. The optimal HBsAg level of log 4.44 IU/mL for significant liver fibrosis (F ⩾2) gave an area under the curve (AUC) of 0.83, sensitivity of 81.1%, specificity of 81.6%, positive predictive value (PPV) of 68.2%, and negative predictive value (NPV) of 89.9%. An IT model with HBsAg and gamma glutamyl transpeptidase (GGT) in combination was established, and it had an AUC of 0.86, sensitivity of 86.5%, specificity of 81.6%, PPV of 69.6, NPV of 92.5, and accuracy of 83.2% to predict F ⩾2 in the IT-phase CHB patients. Notably, the IT model exhibited higher predictive value than the existing aspartate aminotransferase-to-platelet ratio index, Fibrosis-4 score, and GGT to platelet ratio. CONCLUSION: The established IT model combining HBsAg and GGT has good performance in predicting significant liver fibrosis in IT-phase CHB patients.

Effect of liver inflammation on accuracy of FibroScan device in assessing liver fibrosis stage in patients with chronic hepatitis B virus infection.

BACKGROUND: Transient elastography (FibroScan) is a new and non-invasive test, which has been widely recommended by the guidelines of chronic hepatitis B virus (HBV) management for assessing hepatic fibrosis staging. However, some confounders may affect the diagnostic accuracy of the FibroScan device in fibrosis staging. AIM: To evaluate the diagnostic value of the FibroScan device and the effect of hepatic inflammation on the accuracy of FibroScan in assessing the stage of liver fibrosis in patients with HBV infection. METHODS: The data of 416 patients with chronic HBV infection who accepted FibroScan, liver biopsy, clinical, and biological examination were collected from two hospitals retrospectively. Receiver operating characteristic (ROC) curves were used to analyze the diagnostic performance of FibroScan for assessing the stage of liver fibrosis. Any discordance in fibrosis staging by FibroScan and pathological scores was statistically analyzed. Logistic regression and ROC analyses were used to analyze the accuracy of FibroScan in assessing the stage of fibrosis in patients with different degrees of liver inflammation. A non-invasive model was constructed to predict the risk of misdiagnosis of fibrosis stage using FibroScan. RESULTS: In the overall cohort, the optimal diagnostic values of liver stiffness measurement (LSM) using FibroScan for significant fibrosis (≥ F2), severe fibrosis (≥ F3), and cirrhosis (F4) were 7.3 kPa [area under the curve (AUC) = 0.863], 9.7 kPa (AUC = 0.911), and 11.3 kPa (AUC = 0.918), respectively. The rate of misdiagnosis of fibrosis stage using FibroScan was 34.1% (142/416 patients). The group of patients who showed discordance between fibrosis staging using FibroScan and pathological scores had significantly higher alanine aminotransferase and aspartate aminotransferase levels, and a higher proportion of moderate to severe hepatic inflammation, compared with the group of patients who showed concordance in fibrosis staging between the two methods. Liver inflammation activity over 2 (OR = 3.53) was an independent risk factor for misdiagnosis of fibrosis stage using FibroScan. Patients with liver inflammation activity ≥ 2 showed higher LSM values using FibroScan and higher rates of misdiagnosis of fibrosis stage, whereas the diagnostic performance of FibroScan for different fibrosis stages was significantly lower than that in patients with inflammation activity < 2 (all P < 0.05). A non-invasive prediction model was established to assess the risk of misdiagnosis of fibrosis stage using FibroScan, and the AUC was 0.701. CONCLUSION: Liver inflammation was an independent risk factor affecting the diagnostic accuracy of FibroScan for fibrosis stage. A combination of other related non-invasive factors can predict the risk of misdiagnosis of fibrosis staging using FibroScan.

Serum ceruloplasmin can predict liver fibrosis in hepatitis B virus-infected patients.

BACKGROUND: The presence of significant liver fibrosis in hepatitis B virus (HBV)-infected individuals with persistently normal serum alanine aminotransferase (PNALT) levels is a strong indicator for initiating antiviral therapy. Serum ceruloplasmin (CP) is negatively correlated with liver fibrosis in HBV-infected individuals. AIM: To examine the potential value of serum CP and develop a noninvasive index including CP to assess significant fibrosis among HBV-infected individuals with PNALT. METHODS: Two hundred and seventy-five HBV-infected individuals with PNALT were retrospectively evaluated. The association between CP and fibrotic stages was statistically analyzed. A predictive index including CP [Ceruloplasmin hepatitis B virus (CPHBV)] was constructed to predict significant fibrosis and compared to previously reported models. RESULTS: Serum CP had an inverse correlation with liver fibrosis (r = -0.600). Using CP, the areas under the curves (AUCs) to predict significant fibrosis, advanced fibrosis, and cirrhosis were 0.774, 0.812, and 0.853, respectively. The CPHBV model was developed using CP, platelets (PLT), and HBsAg levels to predict significant fibrosis. The AUCs of this model to predict significant fibrosis, advanced fibrosis, and cirrhosis were 0.842, 0.920, and 0.904, respectively. CPHBV was superior to previous models like the aspartate aminotransferase (AST)-to-PLT ratio index, Fibrosis-4 score, gamma-glutamyl transpeptidase-to-PLT ratio, Forn's score, and S-index in predicting significant fibrosis in HBV-infected individuals with PNALT. CONCLUSION: CPHBV could accurately predict liver fibrosis in HBV-infected individuals with PNALT. Therefore, CPHBV can be a valuable tool for antiviral treatment decisions.

Novel predictive models using serum ceruloplasmin levels for hepatic steatosis in patients with chronic hepatitis B infection.

AIMS: To evaluate the significance of serum ceruloplasmin (CP) to diagnosis hepatic steatosis (HS) in Chronic hepatitis B (CHB) patients. METHODS: A total of 360 CHB patients with HS (n = 136) or without HS (n = 224) were included. Relationships between CP and HS degrees were analyzed by Spearman rank correlation. HS-predictive models including CP were constructed using multivariate logistic regression analysis and compared to other HS predicting indexes. RESULTS: Serum CP were significantly higher in CHB patients with HS than in patients without HS (P < 0.001) and were positively correlated with HS degree (r = 0.487, P < 0.001). The area under the receiver-operating characteristic curves (AUCs) of using CP to predict HS (S ≥ 1), moderate and severe steatosis (S ≥ 2) and severe steatosis (S = 3) were 0.758, 0.794 and 0.883, respectively. Multivariate analysis showed that CP, age, high density lipoprotein (HDL) and hemoglobin were independent predictors of HS, and CP, body mass index and HDL were independent predictors of moderate and severe HS. Two novel indexes for predicting HS of CHB patients were generated. The AUC of HSCHB-1 (for S ≥ 1) and HSCHB-2 (for S ≥ 2) were 0.881 and 0.916 in the training group, and 0.865 and 0.841 in the validation group, respectively. HSCHB-1 was superior to HS index (P < 0.001), fatty liver disease index (P = 0.0043) and steatosis index of patients with hepatitis B virus infection (P = 0.0029) in predicting HS in CHB patients. CONCLUSIONS: HS of CHB patients was positively associated with serum CP. HSCHB-1 and HSCHB-2 with inclusion of CP are two novel models for predicting HS in CHB patients.