Characterization of BCP/PreC/C region quasispecies in treatment-naive patients with different phases of HBV infection using next-generation sequencing.

BACKGROUND: To analysis of quasispecies (QS) changes and high-frequency mutations in the BCP/PreC/C region of patients at different phases of hepatitis B virus (HBV) infection and provides novel biomarkers for the diagnosis of chronic hepatitis B (CHB) patients. METHODS: With the application of next-generation sequencing technology, we were able to sequence the HBV BCP/PreC/C regions in 40 patients, each at different phases of the HBV infection. The heterogeneity of QS and the frequency of mutations were calculated using MEGA 7 software. RESULTS: Our results show that the complexity and diversity of the BCP/PreC/C QS in HBeAg-positive CHB patients are significantly higher than those in HBeAg-positive chronic infection patients, while HBeAg-negative chronic infection patients had significantly higher QS complexity and diversity than HBeAg-negative CHB patients. In addition, HBeAg-negative patients showed reduced complexity but increased diversity compared with HBeAg-positive patients. Receiver operating characteristic curves showed that G1764A, C2102T, dN and complexity of QS could be used as potential biomarkers for diagnosing HBeAg-positive CHB, while the A2189C, dS and complexity of QS could be used as potential biomarkers for diagnosing HBeAg-negative chronic hepatitis. Finally, our study also found that G1896A and A2159G may be hotspot mutations affecting HBeAg seroconversion. CONCLUSION: Our research elucidates the evolution of HBV by analyzing QS heterogeneity and mutation patterns, offering novel serum biomarkers for enhancing clinical diagnosis and disease prognosis. This comprehensive approach sheds light on the intricate dynamics of HBV progression and paves the way for more precise medical interventions.

Multi-omics reveals deoxycholic acid modulates bile acid metabolism via the gut microbiota to antagonize carbon tetrachloride-induced chronic liver injury.

Deoxycholic acid (DCA) serves essential functions in both physiological and pathological liver processes; nevertheless, the relationship among DCA, gut microbiota, and metabolism in chronic liver injury remain insufficiently understood. The primary objective of this study is to elucidate the potential of DCA in ameliorating chronic liver injury and evaluate its regulatory effect on gut microbiota and metabolism via a comprehensive multi-omics approach. Our study found that DCA supplementation caused significant changes in the composition of gut microbiota, which were essential for its antagonistic effect against CCl4-induced chronic liver injury. When gut microbiota was depleted with antibiotics, the observed protective efficacy of DCA against chronic liver injury became noticeably attenuated. Mechanistically, we discovered that DCA regulates the metabolism of bile acids (BAs), including 3-epi DCA, Apo-CA, and its isomers 12-KLCA and 7-KLCA, IHDCA, and DCA, by promoting the growth of A.muciniphila in gut microbiota. This might lead to the inhibition of the IL-17 and TNF inflammatory signaling pathway, thereby effectively countering CCl4-induced chronic liver injury. This study illustrates that the enrichment of A. muciniphila in the gut microbiota, mediated by DCA, enhances the production of secondary bile acids, thereby mitigating chronic liver injury induced by CCl4. The underlying mechanism may involve the inhibition of hepatic IL-17 and TNF signaling pathways. These findings propose a promising approach to alleviate chronic liver injury by modulating both the gut microbiota and bile acids metabolism.

A novel microfluidic chip-based digital PCR method for enhanced sensitivity in the early diagnosis of colorectal cancer via mSEPT9.

BACKGROUND: To enhance the sensitivity of plasma methylated Septin9 gene (mSEPT9) detection in colorectal cancer (CRC) screening, we developed a microfluidic chip-based digital PCR (dPCR) method suitable for low-concentration samples, aiming to apply it for mSEPT9 detection in CRC diagnosis. METHODS: Our microfluidic chip-based dPCR method utilized specific primers and probes with locked nucleic acids (LNAs) modifications for mSEPT9 detection. We evaluated its performance, including detection limit, specificity, and linear range, comparing it with a commercial qPCR reagent kit using the same samples (95 CRC, 23 non-CRC). RESULTS: The LNAs-modified dPCR method showed a linear range of 100-104 copies/µL and a detection limit of 100 copies/µL. Clinical testing revealed that our dPCR method exhibited a sensitivity of 82.11 % and specificity of 95.65 % for CRC diagnosis, outperforming the commercial qPCR kit (sensitivity: 58.95 %, specificity: 91.30 %), particularly in Stage I with a diagnostic sensitivity of 90.91 %. Combining mSEPT9 and carcinoembryonic antigen (CEA) improved diagnostic sensitivity to 91.49 %. CONCLUSIONS: Our accurate microfluidic chip-based dPCR method, especially in combination with CEA, holds promise for effective CRC screening and timely interventions, offering enhanced mSEPT9 quantification over conventional qPCR.

Oncostatin M Induces IFITM1 Expression to Inhibit Hepatitis B Virus Replication Via JAK-STAT Signaling.

BACKGROUND & AIMS: Functional cure is achieved by a limited number of patients with chronic hepatitis B (CHB) after nucleotide analogue(s) and interferon treatment. It is urgent to develop therapies that can help a larger proportion of patients achieve functional cure. The present study was designed to explore the anti-hepatitis B virus (HBV) potency of interleukin-6 family cytokines and to characterize the underlying mechanisms of the cytokine displaying the highest anti-HBV potency. METHODS: HBV-infected cells were used to screened the anti-HBV potency of interleukin-6 family cytokines. The concentration of oncostatin M (OSM) in patients with chronic HBV infection was examined by enzyme-linked immunosorbent assay. The underlying mechanism of OSM anti-HBV was explored through RNA-seq. C57BL/6 mice injected with rAAV8-1.3HBV were used to explore the suppression effect of OSM on HBV in vivo. RESULTS: OSM is the most effective of the interleukin-6 family cytokines for suppression of HBV replication (percentage of average inhibition: hepatitis B surface antigen, 34.44%; hepatitis B e antigen, 32.52%; HBV DNA, 61.57%). Hepatitis B e antigen-positive CHB patients with high OSM levels had lower hepatitis B surface antigen and hepatitis B e antigen than those with low levels. OSM activated JAK-STAT signaling pathway promoting the formation of STAT1-IRF9 transcription factor complex. Following this, OSM increased the expression of various genes with known functions in innate and adaptive immunity, which was higher expression in patients with CHB in immune clearance phase than in immune tolerance phase (data from GEO: GSE65359). Interferon-induced transmembrane protein 1, one of the most differentially expressed genes, was identified as an HBV restriction factor involved in OSM-mediated anti-HBV effect. In vivo, we also found OSM significantly inhibited HBV replication and induced expression of antiviral effector interferon-induced transmembrane protein 1. CONCLUSIONS: Our study shows that OSM remodels the immune response against HBV and exerts potent anti-HBV activity, supporting its further development as a potential therapy for treating CHB.

Targeted quantitative lipidomic uncovers lipid biomarkers for predicting the presence of compensated cirrhosis and discriminating decompensated cirrhosis from compensated cirrhosis.

OBJECTIVES: This study aimed to characterize serum lipid metabolism and identify potential biomarkers for compensated cirrhosis (CC) predicting and decompensated cirrhosis (DC) discrimination using targeted quantitative lipidomics and machine learning approaches. METHODS: Serum samples from a cohort of 120 participants was analyzed, including 90 cirrhosis patients (45 CC patients and 45 DC patients) and 30 healthy individuals. Lipid metabolic profiling was performed using targeted LC-MS/MS. Two machine learning methods, least absolute shrinkage and selection operator (LASSO), and random forest (RF) were applied to screen for candidate metabolite biomarkers. RESULTS: The metabolic profiling analysis showed a significant disruption in patients with CC and DC. Compared to the CC group, the DC group exhibited a significant upregulation in the abundance of glycochenodeoxycholic acid (GCDCA), glyco-ursodeoxycholic acid (GUDCA), glycocholic acid (GCA), phosphatidylethanolamine (PE), N-acyl-lyso-phosphatidylethanolamine (LNAPE), and triglycerides (TG), and a significant downregulation in the abundance of ceramides (Cer) and lysophosphatidylcholines (LPC). Machine learning identified 11 lipid metabolites (abbreviated as BMP11) as potential CC biomarkers with excellent prediction performance, with an AUC of 0.944, accuracy of 94.7 %, precision of 95.6 %, and recall of 95.6 %. For DC discrimination, eight lipids (abbreviated as BMP8) were identified, demonstrating strong efficacy, with an AUC of 0.968, accuracy of 92.2 %, precision of 88.0 %, and recall of 97.8 %. CONCLUSIONS: This study unveiled distinct lipidomic profiles in CC and DC patients and established robust lipid-based models for CC predicting and DC discrimination.

SIRT1 and miR-34a-5p Expression in PBMCs as Potential Biomarkers for Patients With Type 2 Diabetes With Cognitive Impairments.

CONTEXT: Patients with type 2 diabetes mellitus (T2DM) are at significantly increased risk of Alzheimer disease (AD). However, no biomarkers are available for early identification of patients with T2DM with cognitive impairment (T2DM-CI). Mitochondrial dysfunction is linked to AD. Silent Information Regulator 1 (SIRT1), which is responsible for regulating mitochondrial biogenesis, and its related miRNAs were also altered in AD. OBJECTIVE: This study aimed to determine whether mitochondrial function in peripheral blood mononuclear cells (PBMCs) of patients with T2DM-CI was altered and if these alterations could be used as biomarkers. METHODS: A total of 374 subjects were enrolled, including AD, T2DM-CI, T2DM-nCI (T2DM without cognitive impairment), and healthy controls. The mitochondrial function was determined using a commercial assay kit. The mitochondrial DNA (mtDNA) content, the expression of SIRT1, and selected miRNAs in PBMCs were measured by quantitative polymerase chain reaction. The correlations and diagnostic accuracy were assessed using the Spearman correlation coefficient or receiver operating characteristics analysis, respectively. RESULTS: We found significant changes in mitochondrial function in PBMCs of patients with AD compared with controls (all P < .05), which were not found in T2DM-CI. However, mtDNA content and SIRT1 mRNA expression were lower in PBMCs of patients with T2DM-CI, while miR-34a-5p expression was higher than in patients with T2DM-nCI (all P < .05). A combination of SIRT1 and miR-34a-5p demonstrated excellent discrimination between T2DM-CI and T2DM-nCI (area under the curve = 0.793; sensitivity: 80.01%; specificity: 78.46%). Furthermore, correlation analysis revealed a link between miR-34a-5p expression and hyperglycemia in T2DM-CI. CONCLUSION: Our findings revealed that there was an alteration of mitochondria at the peripheral level in patients with T2DM-CI. SIRT1 combined with miR-34a-5p in PBMCs performed well in identifying patients with T2DM-CI and may be a promising biomarker.

Novel function of MOTS-c in mitochondrial remodelling contributes to its antiviral role during HBV infection.

OBJECTIVE: Hepatitis B virus (HBV) infection causes substantial harm to mitochondrial activity, which hinders the development of effective treatments for chronic hepatitis B (CHB). The discovery of the mitochondrial-derived short peptide MOTS-c, which possesses multiple bioactivities, offers a promising new approach in treating HBV infection. This study aims to explore the diagnostic and therapeutic potential of MOTS-c in HBV-related diseases and its molecular mechanism. DESIGN: In total, 85 healthy subjects and 404 patients with HBV infection, including 20 clinical treatment cohorts, were recruited for this study. MOTS-c levels were measured by ELISA and its diagnostic value was evaluated by receiving operating characteristic curve analysis. The therapeutic effect of MOTS-c was observed in multiple HBV-infected mice and cells through various techniques, including transcriptomic sequencing, flow cytometry, immunofluorescence and electron microscopy. Additionally, MOTS-c's potential interaction with myosin-9 (MYH9) and actin was predicted using immunoprecipitation, proteomics and target prediction software. RESULTS: MOTS-c negatively correlates with HBV DNA expression (R=-0.71), and its AUC (the area under the curve) for distinguishing CHB from healthy controls is 0.9530, and IA (immune reactive) from IC (inactive HBV carrier) is 0.8689. Inhibition of HBV replication (with a 50-70% inhibition rate) was observed alongside improved liver function without notable toxicity in vitro or in vivo. MOTS-c was found to promote mitochondrial biogenesis and enhance the MAVS (mitochondrial antiviral signalling protein) signalling pathway. The impact is dependent on MOTS-c's ability to regulate MYH9-actin-mediated mitochondrial homeostasis. CONCLUSION: MOTS-c has the potential to serve as a biomarker for the progression of HBV infection while also enhancing antiviral efficacy. These findings present a promising innovative approach for effectively treating patients with CHB. Furthermore, our research uncovers a novel role for MOTS-c in regulating MYH9-actin-mediated mitochondrial dynamics and contributing to mitochondrial biogenesis.

Detection of serum large and middle hepatitis B virus surface proteins: A novel potential diagnostic and prognostic biomarker for chronic hepatitis B.

BACKGROUND: The significance of large (LHB) and middle (MHB) HBV surface proteins in chronic hepatitis B (CHB) remains uncertain. This study investigates the role of LHB and MHB in different infection phases and liver diseases. METHODS: Serum samples from 217 patients with HBV chronic infection, CHB, liver cirrhosis (LC), and hepatocellular carcinoma (HCC) were subjected to quantification of LHB and MHB using ELISA. RESULTS: Positive correlations were observed among LHB, MHB, and LHB/HBsAg, with HBV serum markers including HBsAg, HBeAg, and HBV DNA. (P < 0.0001). In HBeAg-positive chronic infection, LHB and MHB were higher than in HBeAg-positive CHB (P < 0.01). In HBeAg-negative chronic infection, LHB and MHB were lower than in HBeAg-negative CHB (P < 0.01). ROC analysis identified LHB and MHB as potential discriminators of CHB and chronic infection. LC and HCC exhibited lower LHB, MHB, and MHB/HBsAg than CHB (P < 0.05). Multivariate analysis found that age and the MHB/HBsAg serve as independent factors for the progression of CHB to end stage of liver disease. CONCLUSIONS: LHB and MHB emerge as novel biomarkers distinguishing chronic infection and CHB. MHB/HBsAg shows promise as a predictor for CHB progression.

A genetic variant in the CD40 gene is related to HBV infection in the Chinese Han population.

BACKGROUND: CD40 is an important immune costimulatory molecule that has recently been found to be associated with chronic hepatitis B. This study aims to explore the association between CD40 polymorphisms and HBV infection, as well as to investigate the impact of different rs1883832 genotypes on CD40 expression and its effect on the progression of chronic HBV infection. METHODS: We genotyped rs1883832 in 3433 individuals using MassARRAY, and quantified the CD40 expression, including CD40 mRNA, sCD40, and mCD40. The CD40 and HBV infection indicators were assessed to investigate the potential function of rs1883832 in suppressing HBV replication in HepG2.2.15 and HepAD38, CD40L in cytotoxic t lymphocytes (CTLs) and interferon-γ, TNF-α, granzyme B, and perforin were measured to elucidate the mechanism by which CD40 inhibits HBV replication. RESULTS: Our study revealed that the frequencies of CC genotype and C allele of rs1883832 were significantly higher in immune recovery compared to chronic hepatitis B. Individuals with CC genotype exhibited significantly elevated CD40 in serum and B cells compared to TT genotypes in chronic hepatitis B. Additionally, CD40 is capable of inhibiting HBV replication and transcription in hepatocytes by means of interaction with CD40L. A significant negative correlation was found between HBV DNA, HBeAg, and mCD40. Conversely, the expressions of ALT and mCD40 showed a positive correlation, which aligns with the trend of CD40L. CONCLUSIONS: rs1883832 C allele may have a protective role in HBV immune recovery. This protective effect could potentially be attributed to the regulation of CD40 expression. The activation of the anti-HBV immune response, which occurs through binding CD40L on CTL, can suppress HBV DNA replication and potentially facilitate immune recovery in HBV infection.

A novel TRIM22 gene polymorphism promotes the response to PegIFNα therapy through cytokine-cytokine receptor interaction signaling pathway in chronic hepatitis B.

IMPORTANCE: Pegylated interferon alfa (PegIFNα) has limited efficacy in the treatment of chronic hepatitis B (CHB). Although many biomarkers related to hepatitis B virus (HBV) have been proposed to stratify patients, the response rate to PegIFNα is still unsatisfactory. Herein, our data suggest that the single-nucleotide polymorphism (SNP) rs10838543 in TRIM22 potentiates a positive clinical response to PegIFNα treatment in patients with hepatitis B e antigen-positive CHB by increasing the levels of IFNL1, CCL3, and CCL5. These observations can help guide treatment decisions for patients with CHB to improve the response rate to PegIFNα.

Diagnostic value of cerebrospinal fluid Neutrophil Gelatinase-Associated Lipocalin for differentiation of bacterial meningitis from tuberculous meningitis or cryptococcal meningitis: a prospective cohort study.

BACKGROUND: The early differential diagnosis between bacterial meningitis (BM) and tuberculous meningitis (TBM) or cryptococcal meningitis (CM) remains a significant clinical challenge. Neutrophil Gelatinase-Associated Lipocalin (NGAL) has been reported as a novel inflammatory biomarker in the early stages of infection. This study aimed to investigate whether cerebrospinal fluid (CSF) NGAL can serve as a potential biomarker for distinguishing between BM and TBM or CM. METHODS: We prospectively enrolled the patients with suspected CNS infections at admission and divided them into three case groups: BM (n = 67), TBM (n = 55), CM (n = 51), and an age- and sex-matched hospitalized control (HC, n = 58). Detected the CSF NGAL and assessed its diagnostic accuracy in distinguishing between BM and TBM or CM. Additionally, longitudinally measured the CSF NGAL levels in patients with BM to evaluate its potential as a monitoring tool for antibacterial treatment. RESULTS: The concentration of CSF NGAL in BM was significantly higher than in TBM, CM, and HC (all P < 0.05), while the serum NGAL did not show significant differences among the three case groups. The ROC analysis demonstrated that CSF NGAL presented a good diagnostic performance with an AUC of 0.834 (0.770-0.886) and at the optimal cutoff value of 74.27 ng/mL with 70.15% sensitivity and 77.36% specificity for discriminating BM with TBM and CM. Additionally, the CSF NGAL in the convalescent period of BM was significantly lower than in the acute period (P < 0.05). CONCLUSIONS: CSF NGAL may serve as a potential biomarker for distinguishing between acute BM and TBM or CM. Additionally, it holds clinical significance in monitoring the effectiveness of antibiotic therapy for BM.

Development and validation of a diagnostic model for AFP-negative hepatocellular carcinoma.

PURPOSE: AFP appears to be negative in about 30% of overall hepatocellular carcinoma (HCC). Our study aimed to develop a nomogram model to diagnose AFP-negative HCC (AFPN-HCC). PATIENTS AND METHODS: The training set included 294 AFPN-HCC patients, 159 healthy objects, 63 patients with chronic hepatitis B(CHB), and 64 patients with liver cirrhosis (LC). And the validation set enrolled 137 healthy controls objects, 47 CHB patients and 45 patients with LC. LASSO, univariate, and multivariable logistic regression analysis were performed to construct the model and then transformed into a visualized nomogram. The receiver operating characteristic (ROC) curves, the calibration curve, decision curve analysis (DCA), and clinical impact curve (CIC) were further used for validation. RESULTS: Four variables including age, PIVKA-II, platelet (PLT) counts, and prothrombin time (PT) were selected to establish the nomogram. The area under the curve (AUC) of the ROC to distinguish AFPN-HCC patients was 0.937(95% CI 0.892-0.938) in training set and 0.942(95% CI 0.921-0.963) in validation set. We also found that the model had high diagnostic value for small-size HCC (tumor size < 5 cm) (AUC = 0.886) and HBV surface antigen-positive AFPN-HCC (AUC = 0.883). CONCLUSIONS: Our model was effective for discrimination of AFPN-HCC from patients with benign liver diseases and healthy controls, and might be helpful for the diagnosis for AFPN-HCC.

miR-548c-3p targets TRIM22 to attenuate the Peg-IFN-α therapeutic efficacy in HBeAg-positive patients with chronic hepatitis B.

Chronic hepatitis B (CHB) patients treated with interferon shows encouraging results. However, its clinical efficacy is limited by significant individual differences in treatment responses. We identified an interferon-inducible effector, TRIM22, as the likely causal target of such differential responses. We found that TRIM22 was highly expressed in interferon-responsive patients and negatively correlated with HBV DNA and HBeAg serum levels. Stable cells overexpressing TRIM22 carried significantly less HBsAg, HBeAg, and HBV DNA, and cells with knocked-down TRIM22 by shRNA displayed higher levels of these markers than controls. Integrated bioinformatics analysis and subsequent experiments revealed that TRIM22 overexpression significantly increased the supernatant levels of IL-1ß and IL-8, two important cytokines of NOD2/NF-κB pathway involved in interferon-induced antiviral activities. We identified three candidate microRNAs binding to 3'UTR of TRIM22 at various locations through typical imperfect paring using the TargetScan program. MiR-548c-3p appeared to be highly expressed, while the TRIM22 level was low in the suboptimal response group of CHB patients. The Luciferase reporter assay revealed an interaction between miR-548c-3p and the 3'UTR of TRIM22, leading to a controlled suppression of TRIM22 endogenous expression. This resulted in interferon's substantially weakened therapeutic efficacy, as indicated by the elevation of the serum levels of HBsAg, HBeAg and HBV DNA in miR-548c-3p-transfected HepAD38 cells. Our study demonstrated that a particular miR-548c-3p is the key negative regulator of TRIM22 in CHB patients with a weak response to interferon treatment, providing a novel marker and target in interferon-α therapy evaluation.

Identification reproducible microbiota biomarkers for the diagnosis of cirrhosis and hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is a malignant tumor with high incidence in China, which is mainly related to chronic hepatitis B (CHB) and liver cirrhosis (LC) caused by hepatitis B virus (HBV) infection. This study aimed to identify reproducible gut microbial biomarkers across Chinese population for LC and HCC diagnosis. In this study, a group of 21 CHB, 25 LC, 21 HCC and 15 healthy control (HC) were examined, and used as the training data. Four published faecal datasets from different regions of China were collected, totally including 121 CHB, 33 LC, 70 HCC and 96 HC. Beta diversity showed that the distribution of community structure in CHB, LC, HCC was significantly different from HC. Correspondingly, 14 and 10 reproducible differential genera across datasets were identified in LC and HCC, respectively, defined as LC-associated and HCC-associated genera. Two random forest (RF) models based on these reproducible genera distinguished LC or HCC from HC with an area under the curve (AUC) of 0.824 and 0.902 in the training dataset, respectively, and achieved cross-region validations. Moreover, AUCs were greatly improved when clinical factors were added. A reconstructed random forest model on eight genera with significant changes between HCC and non-HCC can accurately distinguished HCC from LC. Conclusively, two RF models based on 14 reproducible LC-associated and 10 reproducible HCC-associated genera were constructed for LC and HCC diagnosis, which is of great significance to assist clinical early diagnosis.

ATP13A2 is a Prognostic Biomarker and Correlates with Immune Infiltrates in Hepatocellular Carcinoma.

PURPOSE: To explore the expression and role of ATPase cation transporting 13A2 (ATP13A2) on hepatocellular carcinoma (HCC) progression and prognosis. METHODS: The level of ATP13A2 in 63 HCC tissues was evaluated by quantitative real-time polymerase chain reaction, Western blot, and immunohistochemistry. Then, the prognostic value of ATP13A2 for HCC was explored. GO and KEGG pathway enrichments were performed to predict ATP13A2-mediated biological functions. Besides, the correlations between ATP13A2 and key regulators involved in cell cycle and metastasis, the status of different tumor-infiltrating immune cells was investigated. RESULTS: ATP13A2 was frequently upregulated in 63 HCC tissues relatively to matched non-tumor tissues. The level of ATP13A2 significantly correlated with tumor stage and tumor grade. HCC patients with higher levels of ATP13A2 had a worse prognosis. Moreover, multivariate survival analysis supported ATP13A2 to be an independent prognostic factor for HCC. GO and KEGG analysis indicated a potential role of ATP13A2 on regulating cell cycle, metastasis, and immune infiltrates. Especially, the level of ATP13A2 was positively correlated with CCNB1, CCND3, CDC25B, CDK4, Vimentin, MMP9, MMP14, and LMNB2. A positive correlation was noticed between ATP13A2 and infiltration levels of B cells, CD8+ T cells, CD4+ T cells, macrophages, neutrophils, dendritic cells, monocytes, M2 macrophages, and exhausted T cells in HCC. CONCLUSION: Upregulation of ATP13A2 is a common feature as well as an independent prognostic biomarker for HCC. ATP13A2 are associated with key regulators involved in cell cycle, metastasis, and immune infiltrates in HCC, and may act as a potential immunotherapy target for HCC.

Evaluating the value of anti-SARS-CoV-2 antibody detection and neutralizing responses with euvirus: A population of 10776 close contacts in the epidemic of Fujian.

BACKGROUND: Nucleic acid detection represents limitations due to its false-negative rate and technical complexity in the COVID-19 pandemic. Anti-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibody tests are widely spread all over the world presently. However, there is no report on the effectiveness of anti-SARS-CoV-2 antibody testing methods in China. METHODS: We gathered 10776 serum samples from close contacts of the SARS-CoV-2 infections in Fujian of China and used 2 chemiluminescence immunoassays (Wantai Bio., Yahuilong Bio.) and 2 lateral flow immunoassays (Lizhu Bio. and Dongfang Bio.) to perform the anti-SARS-CoV-2 antibody tests in China. RESULTS: The 4 antibody tests have great diagnostic value for infected or uninfected, especially in the neutralizing antibodies tests, the AUC can reach 0.939 (Wantai Bio.) and 0.916 (Yahuilong Bio.). Furthermore, we used pseudoviruses and euvirus neutralization assay to validate the effectiveness of these antibody test, the results of pseudoviruses neutralization assay or euvirus neutralization assay shows a considerable correlation with the 4 antibody detection respectively, particularly in euvirus neutralization assay, neutralizing antibodies detected by Wantai Bio. or Yahuilong Bio., the correlation can get the level of 0.93 or 0.82. CONCLUSIONS: The findings of this study demonstrate that the detections of antibodies have profound value in the diagnosis of COVID-19.

Effectiveness of SARS-CoV-2-inactivated vaccine and the correlation to neutralizing antibodies: A test-negative case-control study.

Severe acute respiratory syndrome coronavirus 2 breakthrough infection in highly vaccinated populations raises study on the effectiveness for inactivated vaccine, including effectiveness of the vaccine dose, the continuance of effectiveness, the effectiveness against severe/critical coronavirus disease 2019 and against secondary attacks. A population of 10 870 close contacts were investigated in a Delta variant's epidemic. The effectiveness of vaccination was estimated in a test-negative case-control study. In addition, serum was used to detect neutralizing antibodies, to explore their correlation to effectiveness. The vaccine effectiveness (VE) values were estimated for populations aged 12 years or older. The overall adjusted VE was 56.2% and a two-dose vaccine was more effective than a one-dose vaccine (56.7% vs. 43.8%). In addition, the population that got the second dose vaccine within 2 months showed higher VE than the population vaccinated for longer than 2 months (61.5% vs. 52.3%). Among the population who vaccinated 2 doses or within 2 months, a higher level of neutralizing antibodies was observed. For infected cases, vaccinated populations showed lower rates of transmission (2.63% vs. 4.36%). Further, those vaccinated cases, who were not found causing transmission, had a higher level of antibodies. The study provided a full view of the effectiveness of inactivated vaccines in a real-world setting. The time-related VE against infection and lower transmission of breakthrough vaccinated cases were observed, which may indicate that a necessity of a booster vaccine to maintain the effectiveness and high level of neutralizing antibody.

IFIT3 Is Increased in Serum from Patients with Chronic Hepatitis B Virus (HBV) Infection and Promotes the Anti-HBV Effect of Interferon Alpha via JAK-STAT2 In Vitro.

Increasing evidence indicates that interferon alpha (IFN-α) therapy is an effective treatment option for a subgroup of patients with chronic hepatitis B virus (HBV) infection. It has been confirmed that interferon-induced protein with tetratricopeptide repeats 3 (IFIT3), a member of the interferon-stimulated genes (ISGs), could inhibit the replication of various viruses. However, its effect on HBV replication is unclear. The present study sought to explore the role and mechanism of IFIT3 in IFN-α antiviral activities against HBV. IFIT3 mRNA levels in the peripheral blood of 108 treatment-naive patients and 70 healthy controls were analyzed first. The effect of IFIT3 on the Janus kinase-signal transducer and activator of transcription (JAK-STAT) signaling pathway under the dual intervention of IFN-α and HBV was also explored in vitro. Treatment-naive individuals exhibited elevated levels of IFIT3 mRNA compared to the controls (P < 0.0001). Mechanistically, the knockdown of IFIT3 inhibited the phosphorylation of signal transducer and activator of transcription 2 (STAT2), whereas the overexpression of IFIT3 produced the opposite effect in vitro. Meanwhile, the overexpression of IFIT3 enhanced the expression of IFN-α-triggered ISGs, including myxovirus resistance A (MxA), 2'-5'-oligoadenylate synthetase 1 (OAS1), and double-stranded RNA-activated protein kinase (PKR), while a weaker induction of IFN-α-triggered ISGs was observed in ruxolitinib-treated cells. After decreasing IFIT3 expression by validated small hairpin RNAs (shRNAs), the levels of hepatitis B surface antigen (HBsAg), hepatitis B e antigen (HBeAg), and HBV DNA secreted by HepG2 cells transiently transfected with the pHBV1.2 plasmid were increased. Our findings suggest that IFIT3 works in a STAT2-dependent manner to promote the antiviral effect of IFN-α through the JAK-STAT pathway in HBV infection in both human hepatocytes and hepatocarcinoma cells. IMPORTANCE Our study contributes new insights into the understanding of the functions and roles of interferon-induced protein with tetratricopeptide repeats 3 (IFIT3), which is one of the interferon-stimulated genes induced by hepatitis B virus infection in human hepatocytes and hepatocarcinoma cells, and may help to identify targeted genes promoting the efficacy of interferon alpha.

Using machine learning models to predict HBeAg seroconversion in CHB patients receiving pegylated interferon-α monotherapy.

BACKGROUND AND OBJECTIVE: Though there are many advantages of pegylated interferon-α (PegIFN-α) treatment to chronic hepatitis B (CHB) patients, the response rate of PegIFN-α is only 30 ~ 40%. Therefore, it is important to explore predictors at baseline and establish models to improve the response rate of PegIFN-α. METHODS: We randomly divided 260 HBeAg-positive CHB patients who were not previously treated and received PegIFN-α monotherapy (180 µg/week) into a training dataset (70%) and testing dataset (30%). The intersect features were extracted from 50 routine laboratory variables using the recursive feature elimination method algorithm, Boruta algorithm, and Least Absolute Shrinkage and Selection Operator Regression algorithm in the training dataset. After that, based on the intersect features, eight machine learning models including Logistic Regression, k-Nearest Neighbors, Support Vector Machine, Decision Tree, Random Forest, Gradient Boosting, Extreme Gradient Boosting (XGBoost), and Naïve Bayes were applied to evaluate HBeAg seroconversion in HBeAg-positive CHB patients receiving PegIFN-α monotherapy in the training dataset and testing dataset. RESULTS: XGBoost model showed the best performance, which had largest AUROC (0.900, 95% CI: 0.85-0.95 and 0.910, 95% CI: 0.84-0.98, in training dataset and testing dataset, respectively), and the best calibration curve performance to predict HBeAg seroconversion. The importance of XGBoost model indicated that treatment time contributed greatest to HBeAg seroconversion, followed by HBV DNA(log), HBeAg, HBeAb, HBcAb, ALT, triglyceride, and ALP. CONCLUSIONS: XGBoost model based on common laboratory variables had good performance in predicting HBeAg seroconversion in HBeAg-positive CHB patients receiving PegIFN-α monotherapy.