Decompensated islet beta cell function in patients with chronic hepatitis B: a retrospective case-control study

Decompensated islet beta cell function in patients with chronic hepatitis B: a retrospective case-control study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research article Decompensated islet beta cell function in patients with chronic hepatitis B: a retrospective case-control study Dafeng Liu, Lingyun Zhou, Xinyi Zhang, Yilan Zeng, Lang Bai, Dongbo Wu, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.2.16750/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Dysglycometabolism is often accompanied with decreased islet β cell function based on the homeostasis model assessment of β cell function (HOMA-β). In this study, we aimed to identify the difference in HOMA-β values between Chronic hepatitis B (CHB) and non-hepatitis B virus (non-HBV) patients.Methods The study included 110 CHB and 110 non-HBV patients matched according to gender, age, and body mass index. HOMA-β values were evaluated.Results Under the normal glucose tolerance(NGT) condition, the HOMA-β value of the CHB group was in the decompensated stage, and HOMA-β value of CHB was always lower than non-HBV patients (NGT, impaired glucose regulation, and diabetes mellitus: 47.53vs.124.19, 41.59vs.80.17, and 36.46vs.62.92mIU/mmol; t =−4.709, −2.042, and −2.091; P=0.000, 0.047, and 0.046, respectively).Conclusion Clinicians should focus on dysglycometabolism of patients with CHB. Infectious Diseases chronic hepatitis B glycometabolism hemostasis model assessment of β cells (HOMA-β) normal glucose tolerance impaired glucose regulation diabetes mellitus Figures Figure 1 Figure 2 Background Chronic hepatitis B(CHB) has affected about 300 million people worldwide 1 , of whom about 650,000 die of hepatic failure, liver cirrhosis(LC), and hepatocellular carcinoma (HCC) annually 2 . China is one of the HBV middle- and low-endemic areas worldwide, approximately 93 million people are infected with HBV, among them, 20 million present with CHB 1,3. Although the relationship between hepatitis B virus(HBV) infection and diabetes mellitus(DM) remains unclear, several studies have shown that the prevalence of DM is significantly high in the HBV-infected population 4,5 , particularly in those with high viral load, long duration of CHB, cirrhosis 4,6,7 , and Asian Americans 8 . Our previous study has shown that 59.09% of CHB patients have high homeostasis model assessment of insulin resistance(HOMA-IR) values and that 93.64% of individuals have low homeostasis model assessment of β cell function(HOMA-β) value. Moreover, 35.45% of individuals have impaired glucose tolerance(IGT) 9-11 , which indicated that the prevalence of dysglycometabolism and insulin resistance(IR) is high in patients with CHB. IR can promote the progression of liver fibrosis and cirrhosis 12-15 . Moreover, IR is independently correlated to the degree of liver fibrosis in patients with abnormal glutamyltransferase level, which is not associated with the etiology of liver diseases 9,12,13 .The higher HOMA-IR value, the higher liver stiffness measurement, indicating liver fibrosis 10,11,14,15 . In patients with cirrhosis and DM, the main cause of death is hepatic failure, not the complications of DM. Furthermore, T2DM can promote HCC and lead to poor prognosis of liver transplantation 15 . Therefore, the coexistence of dysglycometabolism and IR can promote the progression and worsen the prognosis of CHB. Dysglycometabolism and IR are commonly associated with islet β cell dysfunction in the general population, particularly in Asian populations. The HOMA-β value of patients with CHB under normal glucose tolerance(NGT) condition, the changes in HOMA-β value with the deterioration of glycometabolism, and the differences in HOMA-β value between CHB and patients without hepatitis B virus infection(non-HBV) worth much research. This study aimed to investigate the HOMA-β value of individuals with CHB under NGT condition, the difference in HOMA-β value between CHB and non-HBV patients, and changes in HOMA-β value with the deterioration of glycometabolism. Methods Study population A retrospective case-control study was conducted on 220 patients from the Public and Health Clinic Centre of Chengdu from January 1, 2012 to June 30, 2013. Among them, 110 patients with CHB were included in the CHB group, and the source of the case is in the literature 9-11 . Moreover, 110 patients without hepatitis B virus, hepatitis c virus(HCV) and human immunodeficiency virus infection who were matched according to gender, age and body mass index(BMI) were included in the non-HBV group. The inclusion criteria of the CHB group were as follows: (1)outpatients or inpatients with CHB or post-hepatitis B cirrhosis; (2)those who agreed to undergo noninvasive ultrasound elastometry of the liver; and (3)those aged 18–70 years. The selection criteria of the non-HBV group were as follows: patients without hepatitis B virus infection who were matched according to gender, age, and BMI. The following exclusion criteria were used in this study: (1)individuals with other hepatitis virus or human immunodeficiency virus infection; (2)hepatocellular carcinoma; (3)ascites; (4)decompensated cirrhosis; (5)hepatic function alanine aminotransferase(ALT) or aspartate aminotransferase(AST) level higher than the 5-fold upper limit of the normal value, total bilirubin level higher than the 2-fold upper limit of the normal value within the last 6 months, or prothrombin activity (PT%)30 kg/m 2 or <18.5kg/m 2 . The diagnostic criteria of the diseases were as follows: CHB diagnostic and typing criteria and IGR and DM diagnostic criteria 16,17 . The participants were divided in three subgroups according to glycometabolism conditions: the NGT group [fasting plasma glucose(FPG) level <6.0mmol/L and 2-h postprandial glucose(2hPG) level <7.8mmol/L], IGR group (FPG and 2hPG levels all between that in the NGT and DM), and DM group (FPG level ≥7.0mmol/L and 2hPGlevel ≥11.1mmol/L or twice than that of the FPG or 2hPG levels meeting the criteria). Clinical data collection Data, which included demographic information(age and sex), anthropometric parameters(body weight and height), glucose metabolic parameters[FPG, 2hPG, fasting insulin (FINS), 2hINS, and hemoglobinA1c(HbA1c) levels] were obtained. BMI, HOMA-IR value, and HOMA-β value were calculated using the following formulas: BMI=weight(kg)/height(m 2 ), HOMA‐IR=fasting plasma insulin (Um/L)×FPG (mmol/L)/22.5, and HOMA‐β=20×fasting plasma insulin (Um/L)/[FPG(mmol/L)−3.5] 18 . Databases were established according to the needs of the research. Two researchers simultaneously collected and entered the data. The researchers randomly selected 30% of the data for assessment to ensure data integrity, authenticity, and accuracy. Statistical analyses The Statistical Package for the Social Sciences software version 17.0(IBM Inc., Armonk, NY, the USA) and GraphPad Prism 8(GraphPad) software were used for statistical analysis. Age, BMI, FPG, FINS levels, and HOMA-IR value had a normal distribution, and statistical analysis was conducted directly. Natural HOMA-β values are logarithmic transformation before statistical analysis. The measurement data were expressed as x±SD, and a multigroup comparison was performed using ANOVA. Further comparison between the two groups was conducted using Student-Newman-Keuls(SNK) analysis. The two groups were compared using an independent-sample t -test. Chi-square test was used for the enumeration data. A p value of <0.05 was considered statistically significant. Results Similar baseline conditions between the two groups No significant difference was observed in terms of age, sex, BMI and glycometabolism conditions between the two groups. Therefore, the baseline condition of the two groups was comparable(Table 1). In the CHB group, 41 (37.27%) patients presented with LC. In the non-HBV group, there was no case of LC. Decompensated HOMA-β function under NGT condition in the CHB group Under NGT condition inthenon-HBV group, the HOMA-β value(124.19 mIU/mmol) was higher than the normal value(100.00mIU/mmol). On the contrary, under the same condition, the value(47.53mIU/mmol) was lower than the normal value in the CHB group. In non-HBV groups and the normal value, the HOMA-β value in the CHB group decreased up to 77.79 and 53.47mIU/mmol, respectively; therefore, their reducing percentages were up to 62.64% and 53.47%, respectively. The difference was significant(Figure 1A). Under NGT condition, the FINS level and HOMA-IR value of the CHB group were lower than those of the non-HBV group, and the result was significantly different(Figures1B and 1D). Although FPG level of the CHB group was slightly higher than that of the non-HBV group, no significant difference was observed(Figure 1C). Decrease in HOMA-β function along with the deterioration of glycometabolism in individuals with CHB With the deterioration of glycometabolism under NGT, IGR and DM conditions in the two groups, the FPG level and HOMA-IR value(Figure2A and2C) increased gradually, and the FINS level slightly increased(Figure2B). However, the HOMA-β value decreased gradually(Figure2D). In the non-HBV group, the HOMA-IR and HOMA-β values were higher under the same glycometabolism condition(regardless if NGT, IGR, or DM)(Figures2C and 2D), and the FPG level was lower in the non-HBV patients group than in CHB group(Figure2A). Excluding the FPG level under NGT condition and HOMA-IR value under IGR condition, significant differences were observed, particularly in the HOMA-β value under NGT condition and the FINS level, the HOMA-IR value, the FPG level under DM condition. In the non-HBV group, under IGR and DM condition, the FPG level was <6.0 mmol/L. However, in the CHB group, the FPG level was higher than 6.0 mmol/L under IGR condition and 7.0 mmol/L under DM condition. In the intragroup comparison of FPG levels under NGT, IGR, and DM conditions between the two groups, significant differences were observed in terms of FINS levels, HOMA-IR value, and HOMA-β value in the CHB group(all p<0.0001) and HOMA-β value in the non-HBV group(p<0.05). Discussion Previous studies have shown that the HOMA-β value of patients newly diagnosed with T2DM was only half of the normal value, and it decreased progressively at a rate of 4.5% annually and deteriorated with the course of the disease 19 . Therefore, the HOMA-β value of CHB patients under NGT condition was lower than that of non-HBV patients who were newly diagnosed with T2DM. A new staging method for NGT, IGR, and DM was proposed according to the function of β cells: normal phase of β cell function, compensatory phase of β cell function, decompensated phase of β cell function, and failure phase of β cell function in the general population. The compensatory secretion of β cell function occurs in individuals with NGT and IR and reaches the peak of compensatory secretion. The decompensation of β cell function has occurred in individuals with prediabetes 20 . In recent years, most studies have confirmed that not all individuals with NGT were healthy and that some presented with IR 21 . The risk of developing prediabetes and/or T2DM significantly increased in individuals with NGT, but not in those with IR and dysfunction of β cell secretion 22 . However, the βcell function of the CHB population will directly go to decompensated and failure phases, without undergoing normal and compensatory phases, even under NGT condition, and this phenomenon leads to higher FPG levels and high prevalence of IGR and DM in the CHB population. The evident increase in the FPG level in CHB patients was associated with worsening β cell function compared with non-HBV patients but with similar glycometabolism status. Generally, in patients with CHB, the HOMA-β value gradually decreased and the FPG levelgradually increased along with the deterioration of glucose metabolism. Therefore, the comparisonof HOMA-β value between CHB and non-HBV patients was conducted under similar glucose metabolism conditions. Previous studies have found that chronic liver inflammation and fibrosis caused by HBV infection are associated with some indicators of glycometabolism: CHB patients with mild liver dysfunction had high serum insulin levels and HOMA-IR values. A correlation analysis has shown that ALT was positively correlated to IR. However, HBV DNA load was not correlated to IR. A regression analysis has indicated that ALT wasan independent risk factor of IR in patients with mild liver dysfunction 23 ,24 . A pathological study has found that the FINS level and HOMA-IR value of CHB patients with G3 grade inflammation are higher than those of patients with G2 grade inflammation, and the FINS level and HOMA-IR value of CHB patients with S3 grade fibrosisare higher than those of patients with S2 grade fibrosis. Moreover, HOMA-IR was positively correlated to ALT 25 . When the duration of HBV is longer, patients aremore likely to develop IR and abnormal glucose metabolism 10,11 . When glutamic transpeptidase(GGT) is less than the 1.5-fold upper limit of the normal value, IR is not observed. When the value is 1.5–2 fold than the upper limit of the normal value, IR is most significant. However, it decreases with the increase in GGT level 26 . The secretory function of islet β cells in patients with hepatitis B cirrhosis is normal, and IGT to a certain extent is observed. In CHB patients, the secretory function of islet β cells decreased significantly 9 . In particular, when the GGT level is 1.5–2 times higher than the normal value 26 , the steady-state model had the lowest HOMA-β value, with an average of only 20.34mIU/mmol. With the increase in GGT level, the HOMA-β value was more likely to increase 26 . Fundamental studies have found that HBV infection can increase the production of tumor necrosis factor(TNF). The over production of TNF can decrease the phosphorylation of insulin receptor substrates 1 and 2, inhibit phosphoinositol 3-kinase and protein kinase B, block the phosphorylation of glucose transporter 4, and preventthecell uptake of glucose 27,28 and increase in blood glucose level. Prostate six-transmembrane protein 2(STAMP2) is a factor associated with inflammation and dietary adipocyte function and system metabolism. It can be induced by nutrition, feeding, and cytokines, such as TNF alpha, interleukin (IL)-1β, and IL-6, which can inhibit IR in rats. IR and visceral and hepatic insulin signaling disorders were observed in mice lacking STAMP2. In the presence of inflammation and obesity, the increased expression of STAMP2 has protective effects against insulin signaling in the liver 29 . Moreover, HBV X protein induces liver fat accumulation and IR by reducing the expression of STAMP2. STAMP2 down-regulates the insulin-induced phosphorylation of P3K p85 subunit and protein kinase and the expression of insulin receptor substrate 1, and the post-transcriptional level of insulin receptor substrate 1 plays a role 30 , which leads to the increase in blood glucose levels. Although basic studies have confirmed that HBV infection can lead to increased hepatic glucose output and IR, it cannot explain the decrease in HOMA-β value and FINS level. Further basic studies have indicated that HBV infection affects the function of islet cells in CHB patients. This case-control study first compared the differences in HOMA-β value and FPG level between CHB patients and non-HBV patients matched according to gender, age and BMI. Results showed that the HOMA-β value of CHB patients was significantly lower than that of non-HBV patients under NGT and the normal value, and was lower than that of non-hepatitis B patients under the same glycometabolism condition. However, the FPG level of CHB patients was significantly higher than that of non-hepatitis B patients. The present study had some limitations. The sample size was small, and a single-center and retrospective study, rather than a multicenter and prospective study, was conducted. Conclusions These findings may provide a guide for clinicians to develop hypoglycemic regimens for patients with CHB and dysglycometabolism. During drug selection, clinicians should focus on protection of islet β cell function and prevention of the use of insulin secretagogues. List of Abbreviations HBV Hepatitis B virus FINS Fasting insulin IR Insulin resistance TNF Tumor necrosis factor ALT Alanine aminotransferase BMI Body mass index CHB Chronic hepatitis B DM Diabetes mellitus FPG Fasting plasma glucose GGT Glutamic transpeptidase HCC Hepatocellular carcinoma IGT Impaired glucose tolerance LC Liver cirrhosis NGT Normal glucose tolerance 2hPG 2-h postprandial glucose HOMA-β Homeostasis model assessment of β cell function IR Insulin resistance AST Aspartate aminotransferase FINS Fasting insulin HbA1c Hemoglobin A1c Declarations Ethics approval and consent to participate: The study was approved by the ethics committee of the Public and Health Clinic Centre of Chengdu. All patients provided a written informed consent. Consent for publication: Not applicable Availability of data and materials: Not applicable Competing interests: The authors declare that they have no competing interests. Funding: This research was supported by the Sichuan Province Health Commission (070385, 2013JY0153), Natural Science Foundation of China (81802468) and Sichuan Science and Technology Program(2019YFS0207). Authors' contributions: Concept and design: Dafeng Liu, Lingyun Zhou, Xinyi Zhang, Lang Bai, Dongbo Wu; Data acquisition: Dafeng Liu, Lingyun Zhou, Xinyi Zhang; data analysis and interpretation: Dafeng Liu, Lingyun Zhou, Xinyi Zhang, Lang Bai; Drafting the manuscript: Dafeng Liu, Lingyun Zhou, Xinyi Zhang; administrative, technical, or material support: Dafeng Liu, Lingyun Zhou, Xinyi Zhang; study supervision: Yilan Zeng and Hong Tang. Acknowledgments: Thanks to Dr. Rong Hu, Lin Wang, Li Wang, and Zhu Chen (the Public and Health Clinic Centre of Chengdu, one ward, two ward, and three ward of liver disease department, respectively). References Polaris Observatory Collaborators .Global prevalence, treatment, and prevention of hepatitis B virus infection in 2016: a modelling study. Lancet GastroenterolHepatol . 2018;3:383-403. Lozano R, Naghavi M, Foreman K,Lim S, Shibuya K, Aboyans V,et al. Global and regional mortality from 235 causes of death for 20 age groups in 1990 and 2010: a systematicanalysis for the Global Burden of Disease Study 2010. Lancet . 2012;380:2095-128. Lu FM, Zhuang H. Management of hepatitis B in China. Chin Med J (Engl) . 2009;122:3-4. ZhangJ, Shen Y, Cai H,Liu YM, Qin G.Hepatitis B virus infection status and risk of type 2 diabetes mellitus: A meta-analysis. Hepatol Res . 2015;45:1100-9. SpradlingPR , Simons B , Narayanan M ,Xing J, Homan C, Bulkow L,et al.Incidence of diabetes mellitus inpopulation-based cohort of personswith chronichepatitis B virus infection. J Viral Hepat . 2013;20:510-3. Shen Y , Zhang J , Cai H ,Shao JG, Zhang YY, Liu YM,et al. Identifying patients with chronic hepatitis B at high risk of type 2 diabetes mellitus: a cross-sectional study with pair-matched BMC Gastroenterol . 2015;15:32. Shen Y , Zhang S , Wang X , Wang Y, Zhang J, Qin G, et al.Comparison of type 2 diabetes mellitus incidence in different phases of hepatitis B virus infection: A meta-analysis. LiverInt .2017;37:1451-60. Li-Ng M, Tropp S, Danoff A,Bini EJ. Association between chronic hepatitis B virus infection and diabetes among Asian Americans and Pacific Islanders. Dig Liver Dis . 2007;39:549-56. Liu Dafeng, Zeng Yilan, Lin Jun, et al. The analysis of expression of the metabolism abnormal manifestation in patients with chronic hepatitis B. Journal of Chengdu Medical College 2014;9:712-6. Liu Dafeng, Liu Yaling, Zeng Yilan, et al. Effects of metabolic abnormalities on liver fibrosis in patients with chronic hepatitis B. Chin J ExpClin Infect Dis(electronic edition)(Chin). 2016;10:541-5. Liu Dafeng, Liu Yaling, Zhang Hong, et al. Analysis of major metabolic factors affecting liver fibrosis in patients with chronic hepatitis B. Chin J ExpClin Infect Dis (electronic edition)(Chin). 2015;9:630-5. Petta S, Macaluso FS, Barcellona MR,Cammà C, Cabibi D, Di Marco V,et al.Serum γ-glutamyl transferase levels, insulin resistance and liver fibrosis in patients with chronic liver diseases. PLoS One . 2012;7:e51165. Papatheodoridis GV , Chrysanthos N , Savvas S , Sevastianos V, Kafiri G, Petraki K, et al. Diabetes mellitus in chronic hepatitis B and C: prevalence and potential association with the extent of liver fibrosis. J Viral Hepat . 2006;13:303-10. Huang YW, Wang TC, Lin SC, Chang HY, Chen DS, Hu JT,et al.Increased risk of cirrhosis and its decompensation in chronic hepatitis B patients with newly diagnosed diabetes: a nationwide cohort study. Clin Infect Dis . 2013;57:1695-702. Petta S, Cammà C, Di Marco V, Macaluso FS, Maida M, Pizzolanti G, et al. Hepatic steatosis and insulin resistance are associated with severe brosi in patients with chronic hepatitis caused by HBV orHCV Liver Int . 2011;31:507-15. Society of Hepatology, Chinese Medical Association. Society of Infectious Diseases, Chinese Medical Association. Guidelines for the Prevention and Treatment of Chronic Hepatitis B (2010 edition). Chin J Hep. 2011;19:13-24. Diabetes Society of Chinese Medical Association. Guidelines for the Prevention and Treatment of Type 2 Diabetes in China (2010 edition). Chin J Diab. 2012;20:S1-S37. Bermu´dez V, Cano R, Cano C, Bermudez F, Leal E, Acosta K,et al. Homeostasis model assessment (HOMA) as surrogate insulinization criteria in patients with type 2 diabetes. Am J Ther . 2008;15:409-16. Weng J , Li Y , Xu W , Shi L, Zhang Q, Zhu D,et al.Effect of intensive insulin therapy on beta-cell function and glycaemic control in patients with newly diagnosed type 2 diabetes: a multicentrerandomised parallel-group trial. Lancet . 2008;371:1753-60. Hou X , Liu J , Song J , Wang C, Liang K,Sun Y, et al.Relationship of hemoglobin A1c with β cell function and insulin resistance in newly diagnosed and drug naive type 2 diabetes patients. J Diabetes Res . 2016;2016:8797316. Zhou WJ, Jin JJ, Wu YH, et al.Explore the occurrence and development of β cell dysfunction and insulin resistance according to on thestratificationon normal glucose tolerance.Chin J 2017;33:741-4. Fang FS,Tian H,Li CL,Shao YH, Li J, Zhong WW,et al.The clinical characteristics and trend of conversion to type 2 diabetes mellitus of individuals withnormal glucose tolerance-hyperinsulinemia. ZhonghuaNeKeZaZhi .2010;49:480-3. Fu H,Zeng WQ,Jiang CY,et al.Assessment of the factors associated with insulin resistance in patients with chronic hepatitis B virus infection.Chin J 2012;20:517-21. Zhang PF,Zou MY,Zhao Y,et al.Clinical significance of insulin resistance in patients with chronic hepatitis B virus infection.Journal of Qiqihar Medical College2010;18:2866-9. Li BY, Wang FS, Liu HX.A study of correlation between insulin resistance and the clinical pathology characters in chronic hepatitis B patients.J Chin Phys. 2009;11:603-5. Liu DF,Zhou FX, Mao BR,et al.Influence of gamma-glutamyltranspeptidase on metabolism parameter in patients with chronic hepatitis B.Chin J ExpClin Infect Dis (Electronic Edition). 2017;11:146-50. Wang CS, Wang ST,Yao WJ,Chang TT, Chou P.Community-based study of hepatitis C virus infection and type 2 diabetes:an association affected by age and hepatitis severity status. Am J Epidemiol . 2003;158:1154-60. Wu C,Khan SA, Peng LJ,Li H, Carmella SG, Lange AJ.Perturbation of glucose flux in the liver by decreasing F26P2 levels causes hepatic insulin resistance and hyperglycemia. Am J PhysiolEndocrinolMetab .2006;291:E536-43. Kim HY,Cho HK, Yoo SK, Cheong J. Hepatic STAMP2 deceases hepatitis B virus X protein-associated metabolic deregulation.ExpMol Med.2012;44:622-32. Kim K, Kim KH, Cheong J. Hepatitis B virus X protein impairs hepatic insulin signaling through degradation of IRS1 and induction of SOCS3. PLoS One . 2010;5:e8649. Table Table 1. Baseline comparison between the two groups (n=220) Variables CHB group(n=110) Non-HBV group(n=110) t score or x 2 score P score Age(years ) 43.86±14.38 42.68±13.34 t =0.794 0.428 Male (case ,%) 90(81.92%) 90(81.92%) x 2 =0.000 1.000 BMI (kg /m 2 ) 22.52±2.74 23.14±4.07 t =−1.245 0.215 Glycometabolism conditions x 2 =0.000 1.000 NGT 50(45.46%) 50(45.46%) IGR 30(27.27%) 30(27.27%) DM 30(27.27%) 30(27.27%) Abbreviations: CHB, chronic hepatitis B; non-HBV, without hepatitis B virus infection; BMI, body mass index; NGT, normal glucose tolerance; IGR, impaired glucose regulation; DM, diabetes mellitus. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7388","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research article","associatedPublications":[],"authors":[{"id":203289,"identity":"0c6f4a43-94c4-42f3-994e-76d4ac7c3fab","order_by":1,"name":"Dafeng Liu","email":"","orcid":"","institution":"Sichuan University West China Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Dafeng","middleName":"","lastName":"Liu","suffix":""},{"id":203290,"identity":"cf727992-11b0-48ab-9d3b-8dbcb7b51d7e","order_by":2,"name":"Lingyun Zhou","email":"","orcid":"","institution":"Sichuan University West China Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Lingyun","middleName":"","lastName":"Zhou","suffix":""},{"id":203291,"identity":"51725564-827d-4718-8252-429075f79d56","order_by":3,"name":"Xinyi Zhang","email":"","orcid":"","institution":"Sichuan University West China Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Xinyi","middleName":"","lastName":"Zhang","suffix":""},{"id":203292,"identity":"abd27ebf-2828-471b-bde3-7c31f0464b01","order_by":4,"name":"Yilan Zeng","email":"","orcid":"","institution":"The Public and Health Clinic Center of Chengdu","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yilan","middleName":"","lastName":"Zeng","suffix":""},{"id":203293,"identity":"5ed1f609-b902-457e-b8fc-b5ec741d2d80","order_by":5,"name":"Lang Bai","email":"","orcid":"","institution":"Sichuan University West China Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Lang","middleName":"","lastName":"Bai","suffix":""},{"id":203294,"identity":"52eb68e8-8bf2-4b41-aa1c-a9adc268cfc2","order_by":6,"name":"Dongbo Wu","email":"","orcid":"","institution":"Sichuan University West China Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Dongbo","middleName":"","lastName":"Wu","suffix":""},{"id":203295,"identity":"598c6e68-77e5-4a82-a846-1af3067a8add","order_by":7,"name":"Hong Tang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7UlEQVRIiWNgGAWjYBACAzBZISHHz94DZvLwEdTCBiLPWBhL9pxhYDgA1MJGlBbGlorEDTdywFoYCGoxl29+9vBrg0TizJlvDz7+mGMnw8bA/PDRDTxaLNvYzI1ld0gY90vnJRsc3JYMdBibsXEOPocdYzCTljwjITtzdo6ZxMFtzEAtPGzS+LWwf5OWbJNg3HDzDEhLPTFaeMwkP7ZJKG64wQPScpgYLTll0gxnJICBnGNscHbbcR42ZkJ+OXx8m+SPijpgVJ4xfFC5rdqen7354WN8WkCAmQeVS0A5CDD+IELRKBgFo2AUjGAAAPYFR0NXVsGAAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0002-9790-6225","institution":"Center of infectious Disease, West China Hospital","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Hong","middleName":"","lastName":"Tang","suffix":""}],"badges":[],"createdAt":"2019-10-30 12:59:17","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.2.16750/v1","doiUrl":"https://doi.org/10.21203/rs.2.16750/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":148619,"identity":"158473bb-6891-452e-a496-df2fe82dff6e","added_by":"auto","created_at":"2019-11-04 21:13:27","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":445253,"visible":true,"origin":"","legend":"Comparison of the metabolic parameters between the two groups under NGT condition(n=100; CHB group, n=50, non-HBV group, n=50). A. HOMA-β value under NGT condition; B. HOMA-IR value under NGT condition; C. FPG level under NGT condition; D. FINS level under NGT condition.\nAbbreviations: FPG, fasting plasma glucose; FINS, fasting serum insulin; HOMA-IR, homeostasis model assessment of insulin resistance; HOMA-β, homeostasis model assessment of β cell function; NGT, normal glucose tolerance; CHB, cirrhosis hepatitis B; non-HBV, without hepatitis B virus infection. Matched and unmatched t-tests were used for the intergroup comparison.* P\u003c0.05,** P\u003c0.01,**** P\u003c0.0001.","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/44da3a35-24e0-497e-b784-f055b712bcbe/v1/Figure1.png"},{"id":148621,"identity":"992ac5f4-aea2-41a7-af44-ccb7a2b58d7f","added_by":"auto","created_at":"2019-11-04 21:13:27","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":292838,"visible":true,"origin":"","legend":"Comparison of the metabolic parameters between the two groups under NGT, IGR and DM conditions(n=220; NGT, IGR, and DM in the two groups, n=50, 30 and 30, respectively). A. FPG levels; B. FINS levels; C. HOMA-IR value; D. HOMA-β value. Abbreviations: FPG, fasting plasma glucose. FINS, fasting serum insulin. HOMA-IR, homeostasis model assessment of insulin resistance HOMA-β, homeostasis model assessment of β cell function; NGT, normal glucose tolerance; IGR, impaired glucose regulation; DM, diabetes mellitus.* P\u003c0.05,** P\u003c0.01,*** P\u003c0.001,**** P\u003c0.0001.","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/44da3a35-24e0-497e-b784-f055b712bcbe/v1/Figure2.png"},{"id":13479094,"identity":"f500b1f9-86ae-4fbb-bc8d-e4e1d00ac656","added_by":"auto","created_at":"2021-09-16 21:37:56","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":481456,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7388/v1/c3459f1e-43ac-4be9-bc37-b4af9e812b41.pdf"}],"financialInterests":"","formattedTitle":"Decompensated islet beta cell function in patients with chronic hepatitis B: a retrospective case-control study","fulltext":[{"header":"Background","content":"\u003cp\u003eChronic hepatitis B(CHB) has affected about 300 million people worldwide\u003csup\u003e1\u003c/sup\u003e, of whom about 650,000 die of hepatic failure, liver cirrhosis(LC), and hepatocellular carcinoma (HCC) annually\u003csup\u003e2\u003c/sup\u003e. China is one of the HBV middle- and low-endemic areas worldwide, approximately 93 million people are infected with HBV, among them, 20 million present with CHB\u003csup\u003e1,3.\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003eAlthough the relationship between hepatitis B virus(HBV) infection and diabetes mellitus(DM) remains unclear, several studies have shown that the prevalence of DM is significantly high in the HBV-infected population\u003csup\u003e4,5\u003c/sup\u003e, particularly in those with high\u0026nbsp;viral load, long duration of CHB, cirrhosis\u003csup\u003e4,6,7\u003c/sup\u003e, and Asian\u0026nbsp;Americans\u003csup\u003e8\u003c/sup\u003e. Our previous study has shown that 59.09% of CHB patients have high homeostasis model assessment of insulin resistance(HOMA-IR) values and that 93.64% of individuals have low homeostasis model assessment of \u0026beta; cell function(HOMA-\u0026beta;) value. Moreover, 35.45% of individuals have impaired glucose tolerance(IGT)\u003csup\u003e9-11\u003c/sup\u003e, which indicated that the prevalence of dysglycometabolism and insulin resistance(IR) is high in patients with CHB.\u003c/p\u003e\n\u003cp\u003eIR can promote the progression of liver fibrosis and cirrhosis\u003csup\u003e12-15\u003c/sup\u003e. Moreover, IR is independently correlated to the degree of liver fibrosis in patients with abnormal glutamyltransferase level, which is not associated with the etiology of liver diseases\u003csup\u003e9,12,13\u003c/sup\u003e.The higher HOMA-IR value, the higher liver stiffness measurement, indicating liver fibrosis\u003csup\u003e10,11,14,15\u003c/sup\u003e. In patients with cirrhosis and DM, the main cause of death is hepatic failure, not the complications of DM. Furthermore, T2DM can promote HCC and lead to poor prognosis of liver transplantation\u003csup\u003e15\u003c/sup\u003e. Therefore, the coexistence of dysglycometabolism and IR can promote the progression and worsen the prognosis of CHB.\u003c/p\u003e\n\u003cp\u003eDysglycometabolism and IR are commonly associated with islet \u0026beta; cell dysfunction in the general population, particularly in Asian populations. The HOMA-\u0026beta; value of patients with CHB under normal glucose tolerance(NGT) condition, the changes in HOMA-\u0026beta; value with the deterioration of glycometabolism, and the differences in HOMA-\u0026beta; value between CHB and patients without hepatitis B virus infection(non-HBV) worth much research. This study aimed to investigate the HOMA-\u0026beta; value of individuals with CHB under NGT condition, the difference in HOMA-\u0026beta; value between CHB and non-HBV patients, and changes in HOMA-\u0026beta; value with the deterioration of glycometabolism.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eStudy population\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA retrospective case-control study was conducted on 220 patients from the Public and Health Clinic Centre of Chengdu from January 1, 2012 to June 30, 2013. Among them, 110 patients with CHB were included in the CHB group, and the source of the case is in the literature\u003csup\u003e9-11\u003c/sup\u003e. Moreover, 110 patients without hepatitis B virus, hepatitis c virus(HCV) and human immunodeficiency virus infection who were matched according to gender, age and body mass index(BMI) were included in the non-HBV group.\u003c/p\u003e\n\u003cp\u003eThe inclusion criteria of the CHB group were as follows: (1)outpatients or inpatients with CHB or post-hepatitis B cirrhosis; (2)those who agreed to undergo noninvasive ultrasound elastometry of the liver; and (3)those aged 18\u0026ndash;70 years.\u003c/p\u003e\n\u003cp\u003eThe selection criteria of the non-HBV group were as follows: patients without hepatitis B virus infection who were matched according to gender, age, and BMI.\u003c/p\u003e\n\u003cp\u003eThe following exclusion criteria were used in this study: (1)individuals with other hepatitis virus or human immunodeficiency virus infection; (2)hepatocellular carcinoma; (3)ascites; (4)decompensated cirrhosis; (5)hepatic function alanine aminotransferase(ALT) or aspartate aminotransferase(AST) level higher than the 5-fold upper limit of the normal value, total bilirubin level higher than the 2-fold upper limit of the normal value within the last 6 months, or prothrombin activity (PT%)\u0026lt;60%; and (6)BMI\u0026gt;30 kg/m\u003csup\u003e2\u003c/sup\u003e or \u0026lt;18.5kg/m\u003csup\u003e2\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eThe diagnostic criteria of the diseases were as follows: CHB diagnostic and typing criteria and IGR and DM diagnostic criteria\u003csup\u003e16,17\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eThe participants were divided in three subgroups according to glycometabolism conditions: the NGT group [fasting plasma glucose(FPG) level \u0026lt;6.0mmol/L and 2-h postprandial glucose(2hPG) level \u0026lt;7.8mmol/L], IGR group (FPG and 2hPG levels all between that in the NGT and DM), and DM group (FPG level \u0026ge;7.0mmol/L and 2hPGlevel \u0026ge;11.1mmol/L or twice than that of the FPG or 2hPG levels meeting the criteria).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical data collection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData, which included demographic information(age and sex), anthropometric parameters(body weight and height), glucose metabolic parameters[FPG, 2hPG, fasting insulin (FINS), 2hINS, and hemoglobinA1c(HbA1c) levels] were obtained. BMI, HOMA-IR value, and HOMA-\u0026beta; value were calculated using the following formulas: BMI=weight(kg)/height(m\u003csup\u003e2\u003c/sup\u003e), HOMA‐IR=fasting plasma insulin (Um/L)\u0026times;FPG (mmol/L)/22.5, and HOMA‐\u0026beta;=20\u0026times;fasting plasma insulin (Um/L)/[FPG(mmol/L)\u0026minus;3.5]\u003csup\u003e18\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eDatabases were established according to the needs of the research. Two researchers simultaneously collected and entered the data. The researchers randomly selected 30% of the data for assessment to ensure data integrity, authenticity, and accuracy.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analyses\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Statistical Package for the Social Sciences software version 17.0(IBM Inc., Armonk, NY, the USA) and GraphPad Prism 8(GraphPad) software were used for statistical analysis. Age, BMI, FPG, FINS levels, and HOMA-IR value had a normal distribution, and statistical analysis was conducted directly. Natural HOMA-\u0026beta; values are logarithmic transformation before statistical analysis. The measurement data were expressed as x\u0026plusmn;SD, and a multigroup comparison was performed using ANOVA. Further comparison between the two groups was conducted using Student-Newman-Keuls(SNK) analysis. The two groups were compared using an independent-sample \u003cem\u003et\u003c/em\u003e-test. Chi-square test was used for the enumeration data. A p value of \u0026lt;0.05 was considered statistically significant.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eSimilar baseline \u003c/strong\u003e\u003cstrong\u003econditions\u003c/strong\u003e \u003cstrong\u003ebetween\u003c/strong\u003e\u003cstrong\u003e the two groups\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo significant difference was observed in terms of age, sex, BMI and glycometabolism conditions between the two groups. Therefore, the baseline condition of the two groups was comparable(Table 1). In the CHB group, 41 (37.27%) patients presented with LC. In the non-HBV group, there was no case of LC.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDecompensated\u003c/strong\u003e \u003cstrong\u003eHOMA-\u0026beta;\u003c/strong\u003e \u003cstrong\u003efunction\u003c/strong\u003e \u003cstrong\u003eunder \u003c/strong\u003e\u003cstrong\u003eNGT condition in the CHB group\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eUnder NGT condition inthenon-HBV group, the HOMA-\u0026beta; value(124.19 mIU/mmol) was higher than the normal value(100.00mIU/mmol). On the contrary, under the same condition, the value(47.53mIU/mmol) was lower than the normal value in the CHB group. In non-HBV groups and the normal value, the HOMA-\u0026beta; value in the CHB group decreased up to 77.79 and 53.47mIU/mmol, respectively; therefore, their reducing percentages were up to 62.64% and 53.47%, respectively. The difference was significant(Figure 1A). Under NGT condition, the FINS level and HOMA-IR value of the CHB group were lower than those of the non-HBV group, and the result was significantly different(Figures1B and 1D). Although FPG level of the CHB group was slightly higher than that of the non-HBV group, no significant difference was observed(Figure 1C).\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDecrease in HOMA-\u0026beta; function along with the deterioration of glycometabolism in individuals with CHB\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWith the deterioration of glycometabolism under NGT, IGR and DM conditions in the two groups, the FPG level and HOMA-IR value(Figure2A and2C) increased gradually, and the FINS level slightly increased(Figure2B). However, the HOMA-\u0026beta; value decreased gradually(Figure2D). In the non-HBV group, the HOMA-IR and HOMA-\u0026beta; values were higher under the same glycometabolism condition(regardless if NGT, IGR, or DM)(Figures2C and 2D), and the FPG level was lower in the non-HBV patients group than in CHB group(Figure2A). Excluding the FPG level under NGT condition and HOMA-IR value under IGR condition, significant differences were observed, particularly in the HOMA-\u0026beta; value under NGT condition and the FINS level, the HOMA-IR value, the FPG level under DM condition. In the non-HBV group, under IGR and DM condition, the FPG level was \u0026lt;6.0 mmol/L. However, in the CHB group, the FPG level was higher than 6.0 mmol/L under IGR condition and 7.0 mmol/L under DM condition.\u003c/p\u003e\n\u003cp\u003eIn the intragroup comparison of FPG levels under NGT, IGR, and DM conditions between the two groups, significant differences were observed in terms of FINS levels, HOMA-IR value, and HOMA-\u0026beta; value in the CHB group(all p\u0026lt;0.0001) and HOMA-\u0026beta; value in the non-HBV group(p\u0026lt;0.05).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003ePrevious studies have shown that the HOMA-\u0026beta; value of patients newly diagnosed with T2DM was only half of the normal value, and it decreased progressively at a rate of 4.5% annually and deteriorated with the course of the disease\u003csup\u003e19\u003c/sup\u003e. Therefore, the HOMA-\u0026beta; value of CHB patients under NGT condition was lower than that of non-HBV patients who were newly diagnosed with T2DM.\u003c/p\u003e\n\u003cp\u003eA new staging method for NGT, IGR, and DM was proposed according to the function of \u0026beta; cells: normal phase of \u0026beta; cell function, compensatory phase of \u0026beta; cell function, decompensated phase of \u0026beta; cell function, and failure phase of \u0026beta; cell function in the general population. The compensatory secretion of \u0026beta; cell function occurs in individuals with NGT and IR and reaches the peak of compensatory secretion. The \u0026nbsp;decompensation of \u0026beta; cell function has occurred in individuals with prediabetes\u003csup\u003e20\u003c/sup\u003e. In recent years, most studies have confirmed that not all individuals with NGT were healthy and that some presented with IR\u003csup\u003e21\u003c/sup\u003e. The risk of developing prediabetes and/or T2DM significantly increased in individuals with NGT, but not in those with IR and dysfunction of \u0026beta; cell secretion\u003csup\u003e22\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eHowever, the \u0026beta;cell function of the CHB population will directly go to decompensated and failure phases, without undergoing normal and compensatory phases, even under NGT condition, and this phenomenon leads to higher FPG levels and high prevalence of IGR and DM in the CHB population. The evident increase in the FPG level in CHB patients was associated with worsening \u0026beta; cell function compared with non-HBV patients but with similar glycometabolism status.\u003c/p\u003e\n\u003cp\u003eGenerally, in patients with CHB, the HOMA-\u0026beta; value gradually decreased and the FPG levelgradually increased along with the deterioration of glucose metabolism. Therefore, the comparisonof HOMA-\u0026beta; value between CHB and non-HBV patients was conducted under similar glucose metabolism conditions.\u003c/p\u003e\n\u003cp\u003ePrevious studies have found that chronic liver inflammation and fibrosis caused by HBV infection are associated with some indicators of glycometabolism: CHB patients with mild liver dysfunction had high serum insulin levels and HOMA-IR values. A correlation analysis has shown that ALT was positively correlated to IR. However, HBV DNA load was not correlated to IR. A regression analysis has indicated that ALT wasan independent risk factor of IR in patients with mild liver dysfunction\u003csup\u003e23\u003c/sup\u003e\u003csup\u003e,24\u003c/sup\u003e. A pathological study has found that the FINS level and HOMA-IR value of CHB patients with G3 grade inflammation are higher than those of patients with G2 grade inflammation, and the FINS level and HOMA-IR value of CHB patients with S3 grade fibrosisare higher than those of patients with S2 grade fibrosis. Moreover, HOMA-IR was positively correlated to ALT\u003csup\u003e25\u003c/sup\u003e. When the duration of HBV is longer, patients aremore likely to develop IR and abnormal glucose metabolism\u003csup\u003e10,11\u003c/sup\u003e. When glutamic transpeptidase(GGT) is less than the 1.5-fold upper limit of the normal value, IR is not observed. When the value is 1.5\u0026ndash;2 fold than the upper limit of the normal value, IR is most significant. However, it decreases with the increase in GGT level\u003csup\u003e26\u003c/sup\u003e. The secretory function of islet \u0026beta; cells in patients with hepatitis B cirrhosis is normal, and IGT to a certain extent is observed. In CHB patients, the secretory function of islet \u0026beta; cells decreased significantly\u003csup\u003e9\u003c/sup\u003e. In particular, when the GGT level is 1.5\u0026ndash;2 times higher than the normal value\u003csup\u003e26\u003c/sup\u003e, the steady-state model had the lowest HOMA-\u0026beta; value, with an average of only 20.34mIU/mmol. With the increase in GGT level, the HOMA-\u0026beta; value was more likely to increase\u003csup\u003e26\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eFundamental studies have found that HBV infection can increase the production of tumor necrosis factor(TNF). The over production of TNF can decrease the phosphorylation of insulin receptor substrates 1 and 2, inhibit phosphoinositol 3-kinase and protein kinase B, block the phosphorylation of glucose transporter 4, and preventthecell uptake of glucose\u003csup\u003e27,28\u003c/sup\u003e and increase in blood glucose level. Prostate six-transmembrane protein 2(STAMP2) is a factor associated with inflammation and dietary adipocyte function and system metabolism. It can be induced by nutrition, feeding, and cytokines, such as TNF alpha, interleukin (IL)-1\u0026beta;, and IL-6, which can inhibit IR in rats. IR and visceral and hepatic insulin signaling disorders were observed in mice lacking STAMP2. In the presence of inflammation and obesity, the increased expression of STAMP2 has protective effects against insulin signaling in the liver\u003csup\u003e29\u003c/sup\u003e. Moreover, HBV X protein induces liver fat accumulation and IR by reducing the expression of STAMP2. STAMP2 down-regulates the insulin-induced phosphorylation of P3K p85 subunit and protein kinase and the expression of insulin receptor substrate 1, and the post-transcriptional level of insulin receptor substrate 1 plays a role\u003csup\u003e30\u003c/sup\u003e, which leads to the increase in blood glucose levels.\u003c/p\u003e\n\u003cp\u003eAlthough basic studies have confirmed that HBV infection can lead to increased hepatic glucose output and IR, it cannot explain the decrease in HOMA-\u0026beta; value and FINS level. Further basic studies have indicated that HBV infection affects the function of islet cells in CHB patients.\u003c/p\u003e\n\u003cp\u003eThis case-control study first compared the differences in HOMA-\u0026beta; value and FPG level between CHB patients and non-HBV patients matched according to gender, age and BMI. Results showed that the HOMA-\u0026beta; value of CHB patients was significantly lower than that of non-HBV patients under NGT and the normal value, and was lower than that of non-hepatitis B patients under the same glycometabolism condition. However, the FPG level of CHB patients was significantly higher than that of non-hepatitis B patients.\u003c/p\u003e\n\u003cp\u003eThe present study had some limitations. The sample size was small, and a single-center and retrospective study, rather than a multicenter and prospective study, was conducted.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThese findings may provide a guide for clinicians to develop hypoglycemic regimens for patients with CHB and dysglycometabolism. During drug selection, clinicians should focus on protection of islet \u0026beta; cell function and prevention of the use of insulin secretagogues.\u003c/p\u003e"},{"header":"List of Abbreviations","content":"\u003cp\u003eHBV Hepatitis B virus\u003c/p\u003e\n\u003cp\u003eFINS Fasting insulin\u003c/p\u003e\n\u003cp\u003eIR Insulin resistance\u003c/p\u003e\n\u003cp\u003eTNF Tumor necrosis factor\u003c/p\u003e\n\u003cp\u003eALT Alanine aminotransferase\u003c/p\u003e\n\u003cp\u003eBMI Body mass index\u003c/p\u003e\n\u003cp\u003eCHB Chronic hepatitis B\u003c/p\u003e\n\u003cp\u003eDM Diabetes mellitus\u003c/p\u003e\n\u003cp\u003eFPG Fasting plasma glucose\u003c/p\u003e\n\u003cp\u003eGGT Glutamic transpeptidase\u003c/p\u003e\n\u003cp\u003eHCC Hepatocellular carcinoma\u003c/p\u003e\n\u003cp\u003eIGT Impaired glucose tolerance\u003c/p\u003e\n\u003cp\u003eLC Liver cirrhosis\u003c/p\u003e\n\u003cp\u003eNGT Normal glucose tolerance\u003c/p\u003e\n\u003cp\u003e2hPG\u0026nbsp;2-h postprandial glucose\u003c/p\u003e\n\u003cp\u003eHOMA-\u0026beta; Homeostasis model assessment of \u0026beta; cell function\u003c/p\u003e\n\u003cp\u003eIR Insulin resistance\u003c/p\u003e\n\u003cp\u003eAST Aspartate aminotransferase\u003c/p\u003e\n\u003cp\u003eFINS Fasting insulin\u003c/p\u003e\n\u003cp\u003eHbA1c Hemoglobin A1c\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was approved by the ethics committee of the Public and Health Clinic Centre of Chengdu. All patients provided a written informed consent.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was supported by the Sichuan Province Health Commission (070385, 2013JY0153), Natural Science Foundation of China (81802468) and Sichuan Science and Technology Program(2019YFS0207).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors' contributions:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConcept and design: Dafeng Liu, Lingyun Zhou, Xinyi Zhang, Lang Bai, Dongbo Wu; Data acquisition: Dafeng Liu, Lingyun Zhou, Xinyi Zhang; data analysis and interpretation: Dafeng Liu, Lingyun Zhou, Xinyi Zhang, Lang Bai; Drafting the manuscript: Dafeng Liu, Lingyun Zhou, Xinyi Zhang; administrative, technical, or material support: Dafeng Liu, Lingyun Zhou, Xinyi Zhang; study supervision: Yilan Zeng and Hong Tang.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThanks to Dr. Rong Hu, Lin Wang, Li Wang, and Zhu Chen (the Public and Health Clinic Centre of Chengdu, one ward, two ward, and three ward of liver disease department, respectively).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003e\u003ca href=\"https://www.ncbi.nlm.nih.gov/pubmed/?term=Polaris%20Observatory%20Collaborators%5bCorporate%20Author%5d\"\u003ePolaris Observatory Collaborators\u003c/a\u003e.Global\u0026nbsp;prevalence, treatment, and prevention of\u0026nbsp;hepatitis B virus infection\u0026nbsp;in 2016: a modelling study.\u003ca href=\"https://www.ncbi.nlm.nih.gov/pubmed/29599078\"\u003eLancet GastroenterolHepatol\u003c/a\u003e. 2018;3:383-403.\u003c/li\u003e\n\u003cli\u003eLozano R, Naghavi M, Foreman K,Lim S, Shibuya K, Aboyans V,et al. Global and regional mortality from 235 causes of death for 20 age groups in 1990 and 2010: a systematicanalysis for the Global Burden of Disease Study 2010. \u003ca href=\"https://www.ncbi.nlm.nih.gov/pubmed/?term=Global+and+regional+mortality++from+235+causes+of+death+for+20+age+groups+in+1990+and+2010:+a+systematic+analysis+for+the+Global+Burden+of+Disease+Study+2010\"\u003eLancet\u003c/a\u003e. 2012;380:2095-128.\u003c/li\u003e\n\u003cli\u003eLu FM, Zhuang H. Management of hepatitis B in China. \u003ca href=\"https://www.ncbi.nlm.nih.gov/pubmed/19187608\"\u003eChin Med J (Engl)\u003c/a\u003e.\u0026nbsp;2009;122:3-4.\u003c/li\u003e\n\u003cli\u003eZhangJ, Shen Y, Cai H,Liu YM, Qin G.Hepatitis B virus infection status and risk of type 2 diabetes mellitus: A meta-analysis. \u003ca href=\"https://www.ncbi.nlm.nih.gov/pubmed/?term=Hepatitis+B+virus+infection+status+and+risk+of+type+2+diabetes+mellitus:+A+metaanalysis\"\u003eHepatol Res\u003c/a\u003e.\u0026nbsp;2015;45:1100-9.\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://www.ncbi.nlm.nih.gov/pubmed/?term=Spradling%20PR%5bAuthor%5d\u0026amp;cauthor=true\u0026amp;cauthor_uid=23730845\"\u003eSpradlingPR\u003c/a\u003e,\u003ca href=\"https://www.ncbi.nlm.nih.gov/pubmed/?term=Simons%20B%5bAuthor%5d\u0026amp;cauthor=true\u0026amp;cauthor_uid=23730845\"\u003eSimons\u0026ensp;B\u003c/a\u003e,\u003ca href=\"https://www.ncbi.nlm.nih.gov/pubmed/?term=Narayanan%20M%5bAuthor%5d\u0026amp;cauthor=true\u0026amp;cauthor_uid=23730845\"\u003eNarayanan M\u003c/a\u003e,Xing J, Homan C, Bulkow L,et al.Incidence\u0026nbsp;of\u0026nbsp;diabetes\u0026nbsp;mellitus inpopulation-based\u0026nbsp;cohort\u0026nbsp;of\u0026nbsp;personswith\u0026nbsp;chronichepatitis\u0026nbsp;B virus\u0026nbsp;infection.\u003ca href=\"https://www.ncbi.nlm.nih.gov/pubmed/?term=Incidence+of+diabetes+mellitus+in+a+population-based+cohort+of++persons+with+chronic+hepatitis+B+virus+infection\"\u003eJ Viral Hepat\u003c/a\u003e.\u0026nbsp;2013;20:510-3.\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://www.ncbi.nlm.nih.gov/pubmed/?term=Shen%20Y%5bAuthor%5d\u0026amp;cauthor=true\u0026amp;cauthor_uid=25887997\"\u003eShen Y\u003c/a\u003e,\u0026nbsp;\u003ca href=\"https://www.ncbi.nlm.nih.gov/pubmed/?term=Zhang%20J%5bAuthor%5d\u0026amp;cauthor=true\u0026amp;cauthor_uid=25887997\"\u003eZhang J\u003c/a\u003e,\u0026nbsp;\u003ca href=\"https://www.ncbi.nlm.nih.gov/pubmed/?term=Cai%20H%5bAuthor%5d\u0026amp;cauthor=true\u0026amp;cauthor_uid=25887997\"\u003eCai H\u003c/a\u003e,Shao JG, Zhang YY, Liu YM,et al. Identifying patients with chronic hepatitis B at high risk of type 2 diabetes mellitus: a cross-sectional study with pair-matched \u003ca href=\"https://www.ncbi.nlm.nih.gov/pubmed/?term=Identifying+patients+with+chronic+hepatitis+B+at+high+risk+of+type+2+diabetes+mellitus:+a+cross-sectional+study+with+pairmatched+controls\"\u003eBMC Gastroenterol\u003c/a\u003e.\u0026nbsp;2015;15:32.\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://www.ncbi.nlm.nih.gov/pubmed/?term=Shen%20Y%5bAuthor%5d\u0026amp;cauthor=true\u0026amp;cauthor_uid=27753241\"\u003eShen Y\u003c/a\u003e,\u0026nbsp;\u003ca href=\"https://www.ncbi.nlm.nih.gov/pubmed/?term=Zhang%20S%5bAuthor%5d\u0026amp;cauthor=true\u0026amp;cauthor_uid=27753241\"\u003eZhang S\u003c/a\u003e,\u0026nbsp;\u003ca href=\"https://www.ncbi.nlm.nih.gov/pubmed/?term=Wang%20X%5bAuthor%5d\u0026amp;cauthor=true\u0026amp;cauthor_uid=27753241\"\u003eWang X\u003c/a\u003e,\u0026nbsp;Wang Y, Zhang J, Qin G, et al.Comparison of type 2\u0026nbsp;diabetes mellitus\u0026nbsp;incidence in different phases of hepatitis B virus infection: A meta-analysis.\u003ca href=\"https://www.ncbi.nlm.nih.gov/pubmed/27753241\"\u003eLiverInt\u003c/a\u003e.2017;37:1451-60.\u003c/li\u003e\n\u003cli\u003eLi-Ng M, Tropp S, Danoff A,Bini EJ. Association between chronic hepatitis B virus infection and diabetes among Asian Americans and Pacific Islanders. \u003ca href=\"https://www.ncbi.nlm.nih.gov/pubmed/?term=Association+between+chronic+hepatitis+B+virus+infection+and+diabetes+among+Asian+Americans+and+Pacific+Islanders\"\u003eDig Liver Dis\u003c/a\u003e.\u0026nbsp;2007;39:549-56.\u003c/li\u003e\n\u003cli\u003eLiu Dafeng, Zeng Yilan, Lin Jun, et al. The analysis of expression of the metabolism abnormal manifestation in patients with chronic hepatitis B. Journal of Chengdu Medical College 2014;9:712-6.\u003c/li\u003e\n\u003cli\u003eLiu Dafeng, Liu Yaling, Zeng Yilan, et al. Effects of metabolic abnormalities on liver fibrosis in patients with chronic hepatitis B. Chin J ExpClin Infect Dis(electronic edition)(Chin). 2016;10:541-5.\u003c/li\u003e\n\u003cli\u003eLiu Dafeng, Liu Yaling, Zhang Hong, et al. Analysis of major metabolic factors affecting liver fibrosis in patients with chronic hepatitis B. Chin J ExpClin Infect Dis (electronic edition)(Chin). 2015;9:630-5.\u003c/li\u003e\n\u003cli\u003ePetta S, Macaluso FS, Barcellona MR,Camm\u0026agrave; C, Cabibi D, Di Marco V,et al.Serum \u0026gamma;-glutamyl transferase levels, insulin resistance and liver fibrosis in patients with chronic liver diseases.\u003ca href=\"https://www.ncbi.nlm.nih.gov/pubmed/23227248\"\u003ePLoS One\u003c/a\u003e. 2012;7:e51165.\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://www.ncbi.nlm.nih.gov/pubmed/?term=Papatheodoridis%20GV%5bAuthor%5d\u0026amp;cauthor=true\u0026amp;cauthor_uid=16637860\"\u003ePapatheodoridis GV\u003c/a\u003e,\u0026nbsp;\u003ca href=\"https://www.ncbi.nlm.nih.gov/pubmed/?term=Chrysanthos%20N%5bAuthor%5d\u0026amp;cauthor=true\u0026amp;cauthor_uid=16637860\"\u003eChrysanthos N\u003c/a\u003e,\u0026nbsp;\u003ca href=\"https://www.ncbi.nlm.nih.gov/pubmed/?term=Savvas%20S%5bAuthor%5d\u0026amp;cauthor=true\u0026amp;cauthor_uid=16637860\"\u003eSavvas S\u003c/a\u003e, Sevastianos V, Kafiri G, Petraki K, et al. Diabetes mellitus in chronic hepatitis B and C: prevalence and potential association with the extent of liver fibrosis. \u003ca href=\"https://www.ncbi.nlm.nih.gov/pubmed/?term=Diabetes+mellitus+in+chronic+hepatitis+B+and+C:+prevalence+and+potential+association+with+the+extent+of+liver+fibrosis\"\u003eJ Viral Hepat\u003c/a\u003e.\u0026nbsp;2006;13:303-10.\u003c/li\u003e\n\u003cli\u003eHuang YW, Wang TC, Lin SC, Chang HY, Chen DS, Hu JT,et al.Increased risk of cirrhosis and its decompensation in chronic hepatitis B patients with newly diagnosed diabetes: a nationwide cohort study. \u003ca href=\"https://www.ncbi.nlm.nih.gov/pubmed/?term=Increased+risk+of+cirrhosis+and+its+decompensation+in+chronic+hepatitis+B+patients+with+newly++diagnosed+diabetes:+a+nationwide+cohort+study\"\u003eClin Infect Dis\u003c/a\u003e.\u0026nbsp;2013;57:1695-702.\u003c/li\u003e\n\u003cli\u003ePetta S, Camm\u0026agrave; C, Di Marco V, Macaluso FS, Maida M, Pizzolanti G, et al. Hepatic steatosis and insulin resistance are associated with severe brosi in patients with chronic hepatitis caused by HBV orHCV \u003ca href=\"https://www.ncbi.nlm.nih.gov/pubmed/21382161\"\u003eLiver\u0026ensp;Int\u003c/a\u003e.\u0026nbsp;2011;31:507-15.\u003c/li\u003e\n\u003cli\u003eSociety of Hepatology, Chinese Medical Association. Society of Infectious Diseases, Chinese Medical Association. Guidelines for the Prevention and Treatment of Chronic Hepatitis B (2010 edition). Chin J Hep. 2011;19:13-24.\u003c/li\u003e\n\u003cli\u003eDiabetes Society of Chinese Medical Association. Guidelines for the Prevention and Treatment of Type 2 Diabetes in China (2010 edition). Chin J Diab. 2012;20:S1-S37.\u003c/li\u003e\n\u003cli\u003eBermu\u0026acute;dez V, Cano R, Cano C, Bermudez F, Leal E, Acosta K,et al. Homeostasis model assessment (HOMA) as surrogate insulinization criteria in patients with type 2 diabetes. \u003ca href=\"https://www.ncbi.nlm.nih.gov/pubmed/?term=Homeostasis+model+assessment+(HOMA)+as+surrogate+insulinization+criteria+in+patients+with+type+2+diabetes\"\u003eAm J Ther\u003c/a\u003e.\u0026nbsp;2008;15:409-16.\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://www.ncbi.nlm.nih.gov/pubmed/?term=Weng%20J%5bAuthor%5d\u0026amp;cauthor=true\u0026amp;cauthor_uid=18502299\"\u003eWeng J\u003c/a\u003e,\u0026nbsp;\u003ca href=\"https://www.ncbi.nlm.nih.gov/pubmed/?term=Li%20Y%5bAuthor%5d\u0026amp;cauthor=true\u0026amp;cauthor_uid=18502299\"\u003eLi Y\u003c/a\u003e,\u0026nbsp;\u003ca href=\"https://www.ncbi.nlm.nih.gov/pubmed/?term=Xu%20W%5bAuthor%5d\u0026amp;cauthor=true\u0026amp;cauthor_uid=18502299\"\u003eXu W\u003c/a\u003e, Shi L, Zhang Q, Zhu D,et al.Effect of intensive insulin therapy on beta-cell function and glycaemic control in patients with newly diagnosed type 2 diabetes: a multicentrerandomised parallel-group trial. \u003ca href=\"https://www.ncbi.nlm.nih.gov/pubmed/?term=Effect+of+intensive+insulin+therapy+On+diagnosed+type+2+diabetes:+a+multicentre+randomised+parallelgroup+trial\"\u003eLancet\u003c/a\u003e.\u0026nbsp;2008;371:1753-60.\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://www.ncbi.nlm.nih.gov/pubmed/?term=Hou%20X%5bAuthor%5d\u0026amp;cauthor=true\u0026amp;cauthor_uid=26640807\"\u003eHou X\u003c/a\u003e,\u0026nbsp;\u003ca href=\"https://www.ncbi.nlm.nih.gov/pubmed/?term=Liu%20J%5bAuthor%5d\u0026amp;cauthor=true\u0026amp;cauthor_uid=26640807\"\u003eLiu J\u003c/a\u003e,\u0026nbsp;\u003ca href=\"https://www.ncbi.nlm.nih.gov/pubmed/?term=Song%20J%5bAuthor%5d\u0026amp;cauthor=true\u0026amp;cauthor_uid=26640807\"\u003eSong J\u003c/a\u003e, Wang C, Liang K,Sun Y, et al.Relationship of hemoglobin A1c with \u0026beta; cell function and insulin resistance in\u0026nbsp;newly\u0026nbsp;diagnosed and drug naive type 2 diabetes patients.\u003ca href=\"https://www.ncbi.nlm.nih.gov/pubmed/26640807\"\u003eJ Diabetes Res\u003c/a\u003e.\u0026nbsp;2016;2016:8797316.\u003c/li\u003e\n\u003cli\u003eZhou WJ, Jin JJ, Wu YH, et al.Explore the occurrence and development of \u0026beta; cell dysfunction and insulin resistance according to on thestratificationon normal glucose tolerance.Chin J 2017;33:741-4.\u003c/li\u003e\n\u003cli\u003eFang FS,Tian H,Li CL,Shao YH, Li J, Zhong WW,et al.The clinical characteristics and trend of conversion to type 2 diabetes mellitus of individuals withnormal glucose tolerance-hyperinsulinemia.\u003ca href=\"https://www.ncbi.nlm.nih.gov/pubmed/?term=The+clinical+characteristics+and+trend+of+conversion+to+type+2+diabetes+mellitus+of+individuals+with+normal+glucose+tolerance-hyperinsulinemia\"\u003eZhonghuaNeKeZaZhi\u003c/a\u003e.2010;49:480-3.\u003c/li\u003e\n\u003cli\u003eFu H,Zeng WQ,Jiang CY,et al.Assessment of the factors associated with insulin resistance in patients with chronic hepatitis B virus infection.Chin J 2012;20:517-21.\u003c/li\u003e\n\u003cli\u003eZhang PF,Zou MY,Zhao Y,et al.Clinical significance of insulin resistance in patients with chronic hepatitis B virus infection.Journal of Qiqihar Medical College2010;18:2866-9.\u003c/li\u003e\n\u003cli\u003eLi BY, Wang FS, Liu HX.A study of correlation between insulin resistance and the clinical pathology characters in chronic hepatitis B patients.J Chin Phys. 2009;11:603-5.\u003c/li\u003e\n\u003cli\u003eLiu DF,Zhou FX, Mao BR,et al.Influence of gamma-glutamyltranspeptidase on metabolism parameter in patients with chronic hepatitis B.Chin J ExpClin Infect Dis (Electronic Edition). 2017;11:146-50.\u003c/li\u003e\n\u003cli\u003eWang CS, Wang ST,Yao WJ,Chang TT, Chou P.Community-based study of hepatitis C virus infection and type 2 diabetes:an association affected by age and hepatitis severity status. \u003ca href=\"https://www.ncbi.nlm.nih.gov/pubmed/?term=Community-based+study+of+hepatitis+C+virus+infection+and+type+2+diabetes:an+association+affected+by+age+and+hepatitis+severity+status\"\u003eAm J Epidemiol\u003c/a\u003e.\u0026nbsp;2003;158:1154-60.\u003c/li\u003e\n\u003cli\u003eWu C,Khan SA, Peng LJ,Li H, Carmella SG, Lange AJ.Perturbation of glucose flux in the liver by decreasing F26P2 levels causes hepatic insulin resistance and hyperglycemia. \u003ca href=\"https://www.ncbi.nlm.nih.gov/pubmed/?term=Perturbation+of+glucose+flux+in+the+liver+by+decreasing+F26P2+levels+causes+hepatic+insulin+resistance+and+hyperglycemia\"\u003eAm J PhysiolEndocrinolMetab\u003c/a\u003e.2006;291:E536-43.\u003c/li\u003e\n\u003cli\u003eKim HY,Cho HK, Yoo SK, Cheong J. Hepatic STAMP2 deceases hepatitis B virus X protein-associated metabolic deregulation.ExpMol Med.2012;44:622-32.\u003c/li\u003e\n\u003cli\u003eKim K, Kim KH, Cheong J. Hepatitis B virus X protein impairs hepatic insulin signaling through degradation of IRS1 and induction of SOCS3. \u003ca href=\"https://www.ncbi.nlm.nih.gov/pubmed/?term=Hepatitis+B+Virus+X+Protein+Impairs+Hepatic+Insulin+Signaling+Through+Degradation+of+IRS1+and+Induction+of+SOCS3\"\u003ePLoS One\u003c/a\u003e.\u0026nbsp;2010;5:e8649.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Table","content":"\u003cp style=\"line-height: 200%;\"\u003e\u003cspan style=\"font-size: 12.0pt; line-height: 200%; font-family: 'Times New Roman',serif;\"\u003eTable 1. Baseline comparison between the two groups (n=220)\u003c/span\u003e\u003c/p\u003e\n\u003ctable style=\"width: 100.0%; border-collapse: collapse; border: none;\" width=\"100%\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd style=\"width: 30.9%; border-top: solid windowtext 1.0pt; border-left: none; border-bottom: solid windowtext 1.0pt; border-right: none; padding: 0in 5.4pt 0in 5.4pt;\" width=\"30%\"\u003e\n\u003cp style=\"line-height: 200%;\"\u003e\u003cspan style=\"font-size: 12.0pt; line-height: 200%; font-family: 'Times New Roman',serif; color: windowtext;\"\u003eVariables\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 18.64%; border-top: solid windowtext 1.0pt; border-left: none; border-bottom: solid windowtext 1.0pt; border-right: none; padding: 0in 5.4pt 0in 5.4pt;\" width=\"18%\"\u003e\n\u003cp style=\"line-height: 200%;\"\u003e\u003cspan style=\"font-size: 12.0pt; line-height: 200%; font-family: 'Times New Roman',serif; color: windowtext;\"\u003eCHB group(n=110)\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 21.02%; border-top: solid windowtext 1.0pt; border-left: none; border-bottom: solid windowtext 1.0pt; border-right: none; padding: 0in 5.4pt 0in 5.4pt;\" width=\"21%\"\u003e\n\u003cp style=\"line-height: 200%;\"\u003e\u003cspan style=\"font-size: 12.0pt; line-height: 200%; font-family: 'Times New Roman',serif; color: windowtext;\"\u003eNon-HBV group(n=110)\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 18.64%; border-top: solid windowtext 1.0pt; border-left: none; border-bottom: solid windowtext 1.0pt; border-right: none; padding: 0in 5.4pt 0in 5.4pt;\" width=\"18%\"\u003e\n\u003cp style=\"line-height: 200%;\"\u003e\u003cem\u003e\u003cspan style=\"font-size: 12.0pt; line-height: 200%; font-family: 'Times New Roman',serif; color: windowtext;\"\u003et\u003c/span\u003e\u003c/em\u003e\u003cspan style=\"font-size: 12.0pt; line-height: 200%; font-family: 'Times New Roman',serif; color: windowtext;\"\u003e score or x\u003csup\u003e2\u003c/sup\u003escore\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 10.82%; border-top: solid windowtext 1.0pt; border-left: none; border-bottom: solid windowtext 1.0pt; border-right: none; padding: 0in 5.4pt 0in 5.4pt;\" width=\"10%\"\u003e\n\u003cp style=\"line-height: 200%;\"\u003e\u003cspan style=\"font-size: 12.0pt; line-height: 200%; font-family: 'Times New Roman',serif; color: windowtext;\"\u003eP\u003c/span\u003e\u003cspan style=\"font-size: 12.0pt; line-height: 200%; font-family: 'Times New Roman',serif; color: windowtext;\"\u003escore\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"width: 30.9%; border: none; padding: 0in 5.4pt 0in 5.4pt;\" width=\"30%\"\u003e\n\u003cp style=\"line-height: 200%;\"\u003e\u003cspan style=\"font-size: 12.0pt; line-height: 200%; font-family: 'Times New Roman',serif; color: windowtext;\"\u003eAge(years\u003c/span\u003e\u003cspan style=\"font-size: 12.0pt; line-height: 200%; font-family: 'Times New Roman',serif; color: windowtext;\"\u003e)\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 18.64%; 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font-family: 'Times New Roman',serif; color: windowtext;\"\u003e=0.794\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 10.82%; border: none; padding: 0in 5.4pt 0in 5.4pt;\" width=\"10%\"\u003e\n\u003cp style=\"line-height: 200%;\"\u003e\u003cspan style=\"font-size: 12.0pt; line-height: 200%; font-family: 'Times New Roman',serif; color: windowtext;\"\u003e0.428\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"width: 30.9%; border: none; padding: 0in 5.4pt 0in 5.4pt;\" width=\"30%\"\u003e\n\u003cp style=\"line-height: 200%;\"\u003e\u003cspan style=\"font-size: 12.0pt; line-height: 200%; font-family: 'Times New Roman',serif; color: windowtext;\"\u003eMale\u003c/span\u003e\u003cspan style=\"font-size: 12.0pt; line-height: 200%; font-family: 'Times New Roman',serif; color: windowtext;\"\u003e(case\u003c/span\u003e\u003cspan style=\"font-size: 12.0pt; line-height: 200%; font-family: 'Times New Roman',serif; color: windowtext;\"\u003e,%)\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 18.64%; border: none; padding: 0in 5.4pt 0in 5.4pt;\" width=\"18%\"\u003e\n\u003cp style=\"line-height: 200%;\"\u003e\u003cspan style=\"font-size: 12.0pt; line-height: 200%; font-family: 'Times New Roman',serif; color: windowtext;\"\u003e90(81.92%)\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 21.02%; border: none; padding: 0in 5.4pt 0in 5.4pt;\" width=\"21%\"\u003e\n\u003cp style=\"line-height: 200%;\"\u003e\u003cspan style=\"font-size: 12.0pt; line-height: 200%; font-family: 'Times New Roman',serif; color: windowtext;\"\u003e90(81.92%)\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 18.64%; border: none; padding: 0in 5.4pt 0in 5.4pt;\" width=\"18%\"\u003e\n\u003cp style=\"line-height: 200%;\"\u003e\u003cspan style=\"font-size: 12.0pt; line-height: 200%; font-family: 'Times New Roman',serif; color: windowtext;\"\u003ex\u003csup\u003e2\u003c/sup\u003e=0.000\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 10.82%; border: none; padding: 0in 5.4pt 0in 5.4pt;\" width=\"10%\"\u003e\n\u003cp style=\"line-height: 200%;\"\u003e\u003cspan style=\"font-size: 12.0pt; line-height: 200%; font-family: 'Times New Roman',serif; color: windowtext;\"\u003e1.000\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"width: 30.9%; border: none; padding: 0in 5.4pt 0in 5.4pt;\" width=\"30%\"\u003e\n\u003cp style=\"line-height: 200%;\"\u003e\u003cspan style=\"font-size: 12.0pt; line-height: 200%; font-family: 'Times New Roman',serif; color: windowtext;\"\u003eBMI\u003c/span\u003e\u003cspan style=\"font-size: 12.0pt; line-height: 200%; font-family: 'Times New Roman',serif; color: windowtext;\"\u003e(kg\u003c/span\u003e\u003cspan style=\"font-size: 12.0pt; line-height: 200%; font-family: 'Times New Roman',serif; color: windowtext;\"\u003e/m\u003csup\u003e2\u003c/sup\u003e)\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 18.64%; border: none; padding: 0in 5.4pt 0in 5.4pt;\" width=\"18%\"\u003e\n\u003cp style=\"line-height: 200%;\"\u003e\u003cspan style=\"font-size: 12.0pt; line-height: 200%; font-family: 'Times New Roman',serif; color: windowtext;\"\u003e22.52\u0026plusmn;2.74\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 21.02%; border: none; padding: 0in 5.4pt 0in 5.4pt;\" width=\"21%\"\u003e\n\u003cp style=\"line-height: 200%;\"\u003e\u003cspan style=\"font-size: 12.0pt; line-height: 200%; font-family: 'Times New Roman',serif; color: windowtext;\"\u003e23.14\u0026plusmn;4.07\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 18.64%; border: none; padding: 0in 5.4pt 0in 5.4pt;\" width=\"18%\"\u003e\n\u003cp style=\"line-height: 200%;\"\u003e\u003cem\u003e\u003cspan style=\"font-size: 12.0pt; line-height: 200%; font-family: 'Times New Roman',serif; color: windowtext;\"\u003et\u003c/span\u003e\u003c/em\u003e\u003cspan style=\"font-size: 12.0pt; line-height: 200%; font-family: 'Times New Roman',serif; color: windowtext;\"\u003e=\u0026minus;1.245\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 10.82%; border: none; padding: 0in 5.4pt 0in 5.4pt;\" width=\"10%\"\u003e\n\u003cp style=\"line-height: 200%;\"\u003e\u003cspan style=\"font-size: 12.0pt; line-height: 200%; font-family: 'Times New Roman',serif; color: windowtext;\"\u003e0.215\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"width: 30.9%; border: none; padding: 0in 5.4pt 0in 5.4pt;\" width=\"30%\"\u003e\n\u003cp style=\"line-height: 200%;\"\u003e\u003cspan style=\"font-size: 12.0pt; line-height: 200%; font-family: 'Times New Roman',serif;\"\u003eGlycometabolism conditions\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 18.64%; border: none; padding: 0in 5.4pt 0in 5.4pt;\" width=\"18%\"\u003e\n\u003cp style=\"line-height: 200%;\"\u003e\u003cspan style=\"font-size: 12.0pt; line-height: 200%; font-family: 'Times New Roman',serif; color: windowtext;\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 21.02%; border: none; padding: 0in 5.4pt 0in 5.4pt;\" width=\"21%\"\u003e\n\u003cp style=\"line-height: 200%;\"\u003e\u003cspan style=\"font-size: 12.0pt; line-height: 200%; font-family: 'Times New Roman',serif; color: windowtext;\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 18.64%; border: none; border-bottom: solid windowtext 1.0pt; padding: 0in 5.4pt 0in 5.4pt;\" rowspan=\"4\" width=\"18%\"\u003e\n\u003cp style=\"line-height: 200%;\"\u003e\u003cspan style=\"font-size: 12.0pt; line-height: 200%; font-family: 'Times New Roman',serif; color: windowtext;\"\u003ex\u003csup\u003e2\u003c/sup\u003e=0.000\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 10.82%; border: none; border-bottom: solid windowtext 1.0pt; padding: 0in 5.4pt 0in 5.4pt;\" rowspan=\"4\" width=\"10%\"\u003e\n\u003cp style=\"line-height: 200%;\"\u003e\u003cspan style=\"font-size: 12.0pt; line-height: 200%; font-family: 'Times New Roman',serif; color: windowtext;\"\u003e1.000\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"width: 30.9%; border: none; padding: 0in 5.4pt 0in 5.4pt;\" width=\"30%\"\u003e\n\u003cp style=\"text-indent: 12.0pt; line-height: 200%;\"\u003e\u003cspan style=\"font-size: 12.0pt; line-height: 200%; font-family: 'Times New Roman',serif;\"\u003eNGT\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 18.64%; border: none; padding: 0in 5.4pt 0in 5.4pt;\" width=\"18%\"\u003e\n\u003cp style=\"line-height: 200%;\"\u003e\u003cspan style=\"font-size: 12.0pt; line-height: 200%; font-family: 'Times New Roman',serif; color: windowtext;\"\u003e50(45.46%)\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 21.02%; border: none; padding: 0in 5.4pt 0in 5.4pt;\" width=\"21%\"\u003e\n\u003cp style=\"line-height: 200%;\"\u003e\u003cspan style=\"font-size: 12.0pt; line-height: 200%; font-family: 'Times New Roman',serif; color: windowtext;\"\u003e50(45.46%)\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"width: 30.9%; border: none; padding: 0in 5.4pt 0in 5.4pt;\" width=\"30%\"\u003e\n\u003cp style=\"text-indent: 12.0pt; line-height: 200%;\"\u003e\u003cspan style=\"font-size: 12.0pt; line-height: 200%; font-family: 'Times New Roman',serif;\"\u003eIGR\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 18.64%; border: none; padding: 0in 5.4pt 0in 5.4pt;\" width=\"18%\"\u003e\n\u003cp style=\"line-height: 200%;\"\u003e\u003cspan style=\"font-size: 12.0pt; line-height: 200%; font-family: 'Times New Roman',serif; color: windowtext;\"\u003e30(27.27%)\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 21.02%; border: none; padding: 0in 5.4pt 0in 5.4pt;\" width=\"21%\"\u003e\n\u003cp style=\"line-height: 200%;\"\u003e\u003cspan style=\"font-size: 12.0pt; line-height: 200%; font-family: 'Times New Roman',serif; color: windowtext;\"\u003e30(27.27%)\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"width: 30.9%; border: none; border-bottom: solid windowtext 1.0pt; padding: 0in 5.4pt 0in 5.4pt;\" width=\"30%\"\u003e\n\u003cp style=\"text-indent: 12.0pt; line-height: 200%;\"\u003e\u003cspan style=\"font-size: 12.0pt; line-height: 200%; font-family: 'Times New Roman',serif;\"\u003eDM\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 18.64%; border: none; border-bottom: solid windowtext 1.0pt; padding: 0in 5.4pt 0in 5.4pt;\" width=\"18%\"\u003e\n\u003cp style=\"line-height: 200%;\"\u003e\u003cspan style=\"font-size: 12.0pt; line-height: 200%; font-family: 'Times New Roman',serif; color: windowtext;\"\u003e30(27.27%)\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"width: 21.02%; border: none; border-bottom: solid windowtext 1.0pt; padding: 0in 5.4pt 0in 5.4pt;\" width=\"21%\"\u003e\n\u003cp style=\"line-height: 200%;\"\u003e\u003cspan style=\"font-size: 12.0pt; line-height: 200%; font-family: 'Times New Roman',serif; color: windowtext;\"\u003e30(27.27%)\u003c/span\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp style=\"line-height: 200%;\"\u003e\u003cspan style=\"font-size: 12.0pt; line-height: 200%; font-family: 'Times New Roman',serif;\"\u003eAbbreviations: CHB,\u003c/span\u003e \u003cspan style=\"font-size: 12.0pt; line-height: 200%; font-family: 'Times New Roman',serif;\"\u003echronic hepatitis B; non-HBV,\u003c/span\u003e \u003cspan style=\"font-size: 12.0pt; line-height: 200%; font-family: 'Times New Roman',serif;\"\u003ewithout hepatitis B virus infection; BMI, body mass index; NGT,\u003c/span\u003e \u003cspan style=\"font-size: 12.0pt; line-height: 200%; font-family: 'Times New Roman',serif;\"\u003enormal glucose tolerance; IGR,\u003c/span\u003e \u003cspan style=\"font-size: 12.0pt; line-height: 200%; font-family: 'Times New Roman',serif;\"\u003eimpaired glucose regulation; DM,\u003c/span\u003e \u003cspan style=\"font-size: 12.0pt; line-height: 200%; font-family: 'Times New Roman',serif;\"\u003ediabetes mellitus.\u003c/span\u003e\u003c/p\u003e\n"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"chronic hepatitis B, glycometabolism, hemostasis model assessment of β cells (HOMA-β), normal glucose tolerance, impaired glucose regulation, diabetes mellitus","lastPublishedDoi":"10.21203/rs.2.16750/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.2.16750/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Background\n\nDysglycometabolism is often accompanied with decreased islet β cell function based on the homeostasis model assessment of β cell function (HOMA-β). In this study, we aimed to identify the difference in HOMA-β values between Chronic hepatitis B (CHB) and non-hepatitis B virus (non-HBV) patients.Methods\n\nThe study included 110 CHB and 110 non-HBV patients matched according to gender, age, and body mass index. HOMA-β values were evaluated.Results\n\nUnder the normal glucose tolerance(NGT) condition, the HOMA-β value of the CHB group was in the decompensated stage, and HOMA-β value of CHB was always lower than non-HBV patients (NGT, impaired glucose regulation, and diabetes mellitus: 47.53vs.124.19, 41.59vs.80.17, and 36.46vs.62.92mIU/mmol; t =−4.709, −2.042, and −2.091; P=0.000, 0.047, and 0.046, respectively).Conclusion\n\nClinicians should focus on dysglycometabolism of patients with CHB.","manuscriptTitle":"Decompensated islet beta cell function in patients with chronic hepatitis B: a retrospective case-control study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2019-11-04 21:13:26","doi":"10.21203/rs.2.16750/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d83c0245-ad97-4faa-80fe-b2f59d110ee5","owner":[],"postedDate":"November 4th, 2019","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":34556,"name":"Infectious Diseases"}],"tags":[],"updatedAt":"","versionOfRecord":[],"versionCreatedAt":"2019-11-04 21:13:26","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7388","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"identity":"rs-7388","version":["v1"]},"buildId":"7rjqhiLT3MXkJMwkYKINL","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}