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Tuna N, Çalıca Utku A, Vatan A, Ogutlu A, Guclu E, Karabay O. The Association Between Weight Loss and Hepatitis B Surface Antigen Seroclearence in Chronic Hepatitis B Patients. HEPATITIS MONTHLY 2024; 24. [DOI: 10.5812/hepatmon-142264] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/21/2023] [Revised: 03/04/2024] [Accepted: 04/05/2024] [Indexed: 10/08/2024]
Abstract
Background: In chronic hepatitis B (CHB) patients, hepatitis B surface antigen (HBsAg) seroclearance is the main target of therapy and is rarely observed. Objectives: This study aimed to investigate the factors affecting HBsAg loss by focusing especially on the relationship between weight loss and HBsAg loss. Methods: This study was designed retrospectively to assess HBsAg status and clinical and laboratory findings in CHB patients, as well as cross-sectionally to evaluate lifestyle factors. A total of 5600 hepatitis B (HB) infection patients who were treated or followed between 2008 and 2020 were evaluated retrospectively. In the HBsAg loss group, 94 CHB patients were examined based on exclusion criteria, and 95 patients without HBsAg loss were matched as controls. Patient data and laboratory findings were retrieved from patient files. All participants were surveyed using a questionnaire developed by the authors, which inquired about the lifestyle characteristics of CHB patients. The questionnaire covered topics such as the use of herbal products, coffee consumption, medication history, antiviral treatment, concurrent diseases, weight changes, and patient demographics. Statistical analysis was performed using SPSS version 25.0. The Student's t-test was used to compare quantitative variables, while the chi-square test was used for categorical variables. A paired samples t-test was used to compare dependent samples. The statistical significance level was set at a p value less than 0.05. Results: The basal mean hepatitis B virus (HBV) DNA level was significantly lower in the HBsAg loss group (P < 0.001). The prevalence of hyperlipidemia comorbidity (P = 0.008) and moderate/severe hepatosteatosis (P < 0.05) was significantly higher in the HBsAg loss group compared to the non-HBsAg loss group. Prior to HBsAg loss, 44 (47%) patients in the HBsAg loss group experienced weight loss, whereas only 22 (23%) patients in the non-HBsAg group had a history of weight loss (P < 0.001). Conversely, the incidence of weight gain was significantly lower in the HBsAg loss group (P = 0.001). A paired samples t-test was conducted to compare the baseline and last period body mass index (BMI) means of the HBsAg loss group, revealing a statistically significant decrease in mean BMI in the last period (P < 0.001). Conclusions: Weight loss was significantly associated with HBsAg seroclearance in patients with CHB infection. Conversely, weight gain was associated with HBsAg persistence.
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Huang SC, Su TH, Tseng TC, Chen CL, Hsu SJ, Liu CH, Liao SH, Hong CM, Lan TY, Yang HC, Liu CJ, Chen PJ, Kao JH. Metabolic Dysfunction-Associated Steatotic Liver Disease Facilitates Hepatitis B Surface Antigen Seroclearance and Seroconversion. Clin Gastroenterol Hepatol 2024; 22:581-590.e6. [PMID: 37871842 DOI: 10.1016/j.cgh.2023.09.040] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/29/2023] [Revised: 09/22/2023] [Accepted: 09/29/2023] [Indexed: 10/25/2023]
Abstract
BACKGROUND & AIMS Hepatitis B surface antigen (HBsAg) seroclearance is the goal of functional cure for hepatitis B virus (HBV) infection. However, the impact of metabolic dysfunction-associated steatotic liver disease (MASLD) on this favorable outcome remains unclear. METHODS Patients with chronic hepatitis B (CHB) were consecutively recruited. MASLD was defined by the newly proposed disease criteria. Cumulative incidences and associated factors of HBsAg seroclearance/seroconversion were compared between the MASLD and non-MASLD groups. RESULTS From 2006 to 2021, 4084 treatment-naive hepatitis B e antigen (HBeAg)-negative CHB patients were included. At baseline, CHB patients with concurrent MASLD (n = 887) had significantly lower levels of HBsAg and HBV DNA than the non-MASLD group (n = 3197). During a median follow-up of 5.0 years, MASLD was associated with a higher likelihood of HBsAg seroclearance (adjusted hazard ratio [aHR], 1.43; 95% confidence interval [CI], 1.10-1.85; P = .007), and the accumulation of individual metabolic dysfunctions additively facilitated HBsAg seroclearance. In addition, a higher rate of HBsAg seroconversion was observed in patients with MASLD versus those without MASLD (aHR, 1.37; 95% CI, 1.00-1.86; P = .049). In sensitivity analysis, patients with intermittent MASLD had an intermediate probability of HBsAg seroclearance. After balancing clinical and virologic profiles by inverse probability of treatment weighting (IPTW), MASLD was still associated with a higher HBsAg seroclearance rate (IPTW-adjusted HR, 1.41; 95% CI, 1.09-1.84; P = .010). CONCLUSIONS In untreated HBeAg-negative CHB patients, concurrent MASLD is associated with higher rates of HBsAg seroclearance and seroconversion. Metabolic dysfunctions have additive effects on the functional cure of CHB.
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Affiliation(s)
- Shang-Chin Huang
- Department of Internal Medicine, National Taiwan University Hospital Bei-Hu Branch, Taipei, Taiwan; Division of Gastroenterology and Hepatology, Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan; Hepatitis Research Center, National Taiwan University Hospital, Taipei, Taiwan; Graduate Institute of Clinical Medicine, National Taiwan University College of Medicine, Taipei, Taiwan
| | - Tung-Hung Su
- Division of Gastroenterology and Hepatology, Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan; Hepatitis Research Center, National Taiwan University Hospital, Taipei, Taiwan.
| | - Tai-Chung Tseng
- Hepatitis Research Center, National Taiwan University Hospital, Taipei, Taiwan; Department of Medical Research, National Taiwan University Hospital, Taipei, Taiwan
| | - Chi-Ling Chen
- Graduate Institute of Clinical Medicine, National Taiwan University College of Medicine, Taipei, Taiwan
| | - Shih-Jer Hsu
- Division of Gastroenterology and Hepatology, Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan; Hepatitis Research Center, National Taiwan University Hospital, Taipei, Taiwan
| | - Chen-Hua Liu
- Division of Gastroenterology and Hepatology, Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan; Hepatitis Research Center, National Taiwan University Hospital, Taipei, Taiwan
| | - Sih-Han Liao
- National Taiwan University Cancer Center, Taipei, Taiwan
| | - Chun-Ming Hong
- Division of Hospital Medicine, Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan
| | - Ting-Yuan Lan
- Division of Rheumatology, Department of Internal Medicine, National Taiwan University Hospital Hsin-Chu Branch, Hsinchu, Taiwan
| | - Hung-Chih Yang
- Division of Gastroenterology and Hepatology, Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan; Hepatitis Research Center, National Taiwan University Hospital, Taipei, Taiwan
| | - Chun-Jen Liu
- Division of Gastroenterology and Hepatology, Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan; Hepatitis Research Center, National Taiwan University Hospital, Taipei, Taiwan; Graduate Institute of Clinical Medicine, National Taiwan University College of Medicine, Taipei, Taiwan
| | - Pei-Jer Chen
- Division of Gastroenterology and Hepatology, Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan; Hepatitis Research Center, National Taiwan University Hospital, Taipei, Taiwan; Graduate Institute of Clinical Medicine, National Taiwan University College of Medicine, Taipei, Taiwan; Department of Medical Research, National Taiwan University Hospital, Taipei, Taiwan
| | - Jia-Horng Kao
- Division of Gastroenterology and Hepatology, Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan; Hepatitis Research Center, National Taiwan University Hospital, Taipei, Taiwan; Graduate Institute of Clinical Medicine, National Taiwan University College of Medicine, Taipei, Taiwan.
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Astrologo NCN, Gaudillo JD, Albia JR, Roxas-Villanueva RML. Genetic risk assessment based on association and prediction studies. Sci Rep 2023; 13:15230. [PMID: 37709797 PMCID: PMC10502006 DOI: 10.1038/s41598-023-41862-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Accepted: 09/01/2023] [Indexed: 09/16/2023] Open
Abstract
The genetic basis of phenotypic emergence provides valuable information for assessing individual risk. While association studies have been pivotal in identifying genetic risk factors within a population, complementing it with insights derived from predictions studies that assess individual-level risk offers a more comprehensive approach to understanding phenotypic expression. In this study, we established personalized risk assessment models using single-nucleotide polymorphism (SNP) data from 200 Korean patients, of which 100 experienced hepatitis B surface antigen (HBsAg) seroclearance and 100 patients demonstrated high levels of HBsAg. The risk assessment models determined the predictive power of the following: (1) genome-wide association study (GWAS)-identified candidate biomarkers considered significant in a reference study and (2) machine learning (ML)-identified candidate biomarkers with the highest feature importance scores obtained by using random forest (RF). While utilizing all features yielded 64% model accuracy, using relevant biomarkers achieved higher model accuracies: 82% for 52 GWAS-identified candidate biomarkers, 71% for three GWAS-identified biomarkers, and 80% for 150 ML-identified candidate biomarkers. Findings highlight that the joint contributions of relevant biomarkers significantly influence phenotypic emergence. On the other hand, combining ML-identified candidate biomarkers into the pool of GWAS-identified candidate biomarkers resulted in the improved predictive accuracy of 90%, demonstrating the capability of ML as an auxiliary analysis to GWAS. Furthermore, some of the ML-identified candidate biomarkers were found to be linked with hepatocellular carcinoma (HCC), reinforcing previous claims that HCC can still occur despite the absence of HBsAg.
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Affiliation(s)
- Nicole Cathlene N Astrologo
- Data Analytics Research Laboratory (DARELab), Institute of Mathematical Sciences and Physics, University of the Philippines Los Baños, 4031, Los Baños, Laguna, Philippines
- Computational Interdisciplinary Research Laboratory (CINTERLabs), University of the Philippines Los Baños, 4031, Los Baños, Laguna, Philippines
| | - Joverlyn D Gaudillo
- Data Analytics Research Laboratory (DARELab), Institute of Mathematical Sciences and Physics, University of the Philippines Los Baños, 4031, Los Baños, Laguna, Philippines.
- Computational Interdisciplinary Research Laboratory (CINTERLabs), University of the Philippines Los Baños, 4031, Los Baños, Laguna, Philippines.
- Domingo AI Research Center (DARC Labs), 1606, Pasig, Philippines.
| | - Jason R Albia
- Domingo AI Research Center (DARC Labs), 1606, Pasig, Philippines
- Venn Biosciences Corporation Dba InterVenn Biosciences, Metro Manila, Pasig, Philippines
- Graduate School, University of the Philippines Los Baños, 4031, Los Baños, Laguna, Philippines
| | - Ranzivelle Marianne L Roxas-Villanueva
- Data Analytics Research Laboratory (DARELab), Institute of Mathematical Sciences and Physics, University of the Philippines Los Baños, 4031, Los Baños, Laguna, Philippines
- Computational Interdisciplinary Research Laboratory (CINTERLabs), University of the Philippines Los Baños, 4031, Los Baños, Laguna, Philippines
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Yuan X, Fu T, Xiao L, He Z, Ji Z, Seery S, Zhang W, Ye Y, Zhou H, Kong X, Zhang S, Zhou Q, Lin Y, Jia W, Liang C, Tang H, Wang F, Zhang W, Shao Z. Describing immune factors associated with Hepatitis B surface antigen loss: A nested case-control study of a Chinese sample from Wuwei City. Front Immunol 2022; 13:1025654. [PMID: 36304473 PMCID: PMC9592898 DOI: 10.3389/fimmu.2022.1025654] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2022] [Accepted: 09/20/2022] [Indexed: 12/03/2022] Open
Abstract
Background Hepatitis B surface antigen (HBsAg) loss is considered a functional cure for chronic hepatitis B (CHB), however, several factors influence HBsAg loss. Methods 29 CHB patients who had achieved HBsAg loss, were selected and 58 CHB patients with persistent HBsAg were matched, according to gender and age (+/- 3 years). Logistic regression and restricted cubic spline (RCS) modelling were performed. Results Multivariate-adjusted logistic regression, based on stepwise selection, showed that baseline HBsAg levels negatively correlated with HBsAg loss (odds ratio [OR] = 0.99, 95% confidence interval [CI] = 0.98-0.99). Interferon treatment positively related with HBsAg loss (OR = 7.99, 95%CI = 1.62-44.88). After adjusting for age, HBsAg level, ALT level, HBeAg status and interferon treatment, MMP-1 (OR = 0.66, 95%CI = 0.44-0.97), CXCL9 (OR = 0.96, 95%CI = 0.93-0.99) and TNF-R1 (OR = 0.97, 95%CI = 0.94-0.99) baseline levels all negatively correlated with HBsAg loss. Our multivariate-adjusted RCS model showed that baseline CXCL10 was associated with HBsAg loss although the relationship was “U-shaped”. Conclusions Cytokines such as MMP-1, CXCL9, CXCL10 and TNF-R1 are important factors which influence HBsAg loss. It may be possible to develop a nomogram which intercalates these factors; however, further research should consider immune processes involved in HBsAg loss.
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Affiliation(s)
- Xiaojie Yuan
- Department of Epidemiology, School of Public Health, Air Force Medical University, Xi’an, China
- Ministry of Education Key Lab of Hazard Assessment and Control in Special Operational Environment, School of Public Health, Air Force Medical University, Xi’an, China
| | - Ting Fu
- Department of Epidemiology, School of Public Health, Air Force Medical University, Xi’an, China
- Ministry of Education Key Lab of Hazard Assessment and Control in Special Operational Environment, School of Public Health, Air Force Medical University, Xi’an, China
| | - Lixin Xiao
- Department of Epidemiology, School of Public Health, Air Force Medical University, Xi’an, China
- Ministry of Education Key Lab of Hazard Assessment and Control in Special Operational Environment, School of Public Health, Air Force Medical University, Xi’an, China
| | - Zhen He
- Department of Epidemiology, School of Public Health, Air Force Medical University, Xi’an, China
- Ministry of Education Key Lab of Hazard Assessment and Control in Special Operational Environment, School of Public Health, Air Force Medical University, Xi’an, China
| | - Zhaohua Ji
- Department of Epidemiology, School of Public Health, Air Force Medical University, Xi’an, China
- Ministry of Education Key Lab of Hazard Assessment and Control in Special Operational Environment, School of Public Health, Air Force Medical University, Xi’an, China
| | - Samuel Seery
- Faculty of Health and Medicine, Division of Health Research, Lancaster University, Lancaster, United Kingdom
| | - Wenhua Zhang
- Clinical Drug Experiment Institution, Gansu Wuwei Tumor Hospital, Wuwei, China
| | - Yancheng Ye
- Hepatobiliary Center, Gansu Wuwei Tumor Hospital, Wuwei, China
| | - Haowei Zhou
- Department of Epidemiology, School of Public Health, Air Force Medical University, Xi’an, China
- Ministry of Education Key Lab of Hazard Assessment and Control in Special Operational Environment, School of Public Health, Air Force Medical University, Xi’an, China
| | - Xiangyu Kong
- Department of Epidemiology, School of Public Health, Air Force Medical University, Xi’an, China
- Ministry of Education Key Lab of Hazard Assessment and Control in Special Operational Environment, School of Public Health, Air Force Medical University, Xi’an, China
| | - Shuyuan Zhang
- Department of Epidemiology, School of Public Health, Air Force Medical University, Xi’an, China
- Ministry of Education Key Lab of Hazard Assessment and Control in Special Operational Environment, School of Public Health, Air Force Medical University, Xi’an, China
| | - Qi Zhou
- Department of Epidemiology, School of Public Health, Air Force Medical University, Xi’an, China
- Ministry of Education Key Lab of Hazard Assessment and Control in Special Operational Environment, School of Public Health, Air Force Medical University, Xi’an, China
| | - Yulian Lin
- Department of Epidemiology, School of Public Health, Air Force Medical University, Xi’an, China
- Ministry of Education Key Lab of Hazard Assessment and Control in Special Operational Environment, School of Public Health, Air Force Medical University, Xi’an, China
| | - Wenling Jia
- Clinical Drug Experiment Institution, Gansu Wuwei Tumor Hospital, Wuwei, China
| | - Chunhui Liang
- Clinical Drug Experiment Institution, Gansu Wuwei Tumor Hospital, Wuwei, China
| | - Haitao Tang
- Clinical Drug Experiment Institution, Gansu Wuwei Tumor Hospital, Wuwei, China
| | - Fengmei Wang
- Clinical Drug Experiment Institution, Gansu Wuwei Tumor Hospital, Wuwei, China
| | - Weilu Zhang
- Department of Epidemiology, School of Public Health, Air Force Medical University, Xi’an, China
- Ministry of Education Key Lab of Hazard Assessment and Control in Special Operational Environment, School of Public Health, Air Force Medical University, Xi’an, China
- *Correspondence: Zhongjun Shao, ; Weilu Zhang,
| | - Zhongjun Shao
- Department of Epidemiology, School of Public Health, Air Force Medical University, Xi’an, China
- Ministry of Education Key Lab of Hazard Assessment and Control in Special Operational Environment, School of Public Health, Air Force Medical University, Xi’an, China
- *Correspondence: Zhongjun Shao, ; Weilu Zhang,
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Wang MF, Wan B, Wu YL, Huang JF, Zhu YY, Li YB. Clinic-pathological features of metabolic associated fatty liver disease with hepatitis B virus infection. World J Gastroenterol 2021; 27:336-344. [PMID: 33584066 PMCID: PMC7852586 DOI: 10.3748/wjg.v27.i4.336] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/09/2020] [Revised: 12/11/2020] [Accepted: 12/23/2020] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Metabolic associated fatty liver disease (MAFLD) is a novel concept proposed in 2020.
AIM To compare the characteristics of MAFLD and MAFLD with hepatitis B virus (HBV) infection.
METHODS Patients with histopathologically proven MAFLD from a single medical center were included. Patients were divided into MAFLD group (without HBV infection) and HBV-MAFLD group (with HBV infection). Propensity score matching was utilized to balance the baseline characteristics between two groups.
RESULTS A total of 417 cases with MAFLD were included, 359 (86.1%) of whom were infected with HBV. There were significantly more males in the HBV-MAFLD group than in the MAFLD group (P < 0.05). After propensity score matching, 58 pairs were successfully matched with no significant differences found in gender, age, body mass index, lipid levels, liver enzymes, and the other metabolic associated comorbidities between the two groups (P > 0.05). The rank sum test results showed that the degree of liver steatosis in the MAFLD group was more severe than that in the HBV-MAFLD group, while the degree of inflammation and fibrosis in the liver was less severe (P < 0.05). In multivariate analysis, HBV infection was associated with significantly lower grade of hepatic steatosis [odds ratio (OR) = 0.088, 95% confidence interval (CI): 0.027-0.291] but higher inflammation level (OR = 4.059, 95%CI: 1.403-11.742) and fibrosis level (OR = 3.016, 95%CI: 1.087-8.370) after adjusting for age, gender, and other metabolic parameters.
CONCLUSION HBV infection is associated with similar metabolic risks, lower steatosis grade, higher inflammation, and fibrosis grade in MAFLD patients.
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Affiliation(s)
- Ming-Fang Wang
- Department of Liver Research Center, The First Affiliated Hospital of Fujian Medical University, Fuzhou 350005, Fujian Province, China
| | - Bo Wan
- Institute of Neurology, University College London, London WC1N 3BG, United Kingdom
| | - Yin-Lian Wu
- Department ofLiver Research Center, The First Affiliated Hospital of Fujian Medical University, Fuzhou 350005, Fujian Province, China
| | - Jiao-Feng Huang
- Department ofLiver Research Center, The First Affiliated Hospital of Fujian Medical University, Fuzhou 350005, Fujian Province, China
| | - Yue-Yong Zhu
- Department ofLiver Research Center, The First Affiliated Hospital of Fujian Medical University, Fuzhou 350005, Fujian Province, China
| | - You-Bing Li
- Department ofLiver Research Center, The First Affiliated Hospital of Fujian Medical University, Fuzhou 350005, Fujian Province, China
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