{"paper_id":"4e0f4db6-3197-4f95-a221-2ae1a04cc22d","body_text":"Cytokine Signature behind Occult Hepatitis B Virus Infection | 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 Cytokine Signature behind Occult Hepatitis B Virus Infection Natalia A. Arsentieva, Zoya R. Korobova, Natalia E. Lyubimova, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7846341/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract Background Hepatitis B virus (HBV) infection is a serious public health threat and one of the leading causes of acute, chronic and occult hepatitis (OBI). Standard diagnostics that detect HBsAg are insufficient for identifying OBI, defined by the presence of hepatic DNA in the absence of detectable serum HBsAg. Accumulating evidence indicate that the inadequate immune responses are responsible for HBV persistency. Cytokines are known to be important chemical mediators that regulate the differentiation, proliferation and function of immune cells. The goal of this study is to investigate the cytokine signature in OBI patients. Methods The study initially enrolled 6,773 healthy volunteers, after excluding individuals under 18 years of age, hepatitis B marker testing revealed 57 cases of OBI. As controls, 37 healthy donors with the absence of viral hepatitis markers, HIV, and somatic diseases were selected from the same initial cohort. Immune mediators (cytokines, chemokines, and growth factors) in blood plasma were measured with the MAGPIX multiplex analysis. Results We found high levels of IFNα, IFNγ, IL-1α, IL-2, IL-10, IL-15, IL-17A, IL-22, CXCL9/MIG and growth factors (EGF, FLT-3L, TGFα, G-CSF, M-CSF, VEGF) in OBI patients. Based on anti-HBsAg IgG positivity, patients with OBI were separated into two groups; seropositive cohort demonstrated an increase in CCL22/MDC. ROC analysis indicates that M-CSF, FLT-3L, G-CSF, EGF, and TGFα possess high diagnostic potential as biomarkers for OBI. Based on the results of decision tree, we established that combined detection of M-CSF and FLT-3L is more valuable in terms OBI diagnostic. Conclusions OBI is characterized by a dominant anti-inflammatory and pro-fibrotic background, mediated by cytokines such as IL-10 and TGF-α, which facilitates viral persistence and promotes liver fibrosis despite the concurrent elevation of some pro-inflammatory signals. The activation of growth factors like TGF-α and EGF drives aberrant tissue repair, resulting in incomplete regeneration and scarring. The roles of FLT-3L and IL-22 appear dual, mediating hepatoprotection while simultaneously contributing to fibrotic progression. ROC and decision tree analysis indicates that several cytokines possess high diagnostic potential as biomarkers for OBI. viral hepatitis B occult HBV cytokines multiplex analysis biomarkers Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Hepatitis B virus (HBV) infection presents with a broad spectrum of clinical outcomes. These range from self-limiting conditions, such as asymptomatic or acute hepatitis followed by recovery, to severe manifestations including chronic hepatitis or fulminant liver failure [1, 2]. Despite an estimated global prevalence of 254 million cases (WHO, 2022) and 1.2 million annual new infections [3], standard diagnostics that detect HBsAg are insufficient for identifying occult HBV infection (OBI), defined by the presence of hepatic DNA in the absence of detectable serum HBsAg [4, 5]. This diagnostic limitation suggests that the true prevalence of OBI exceeds current official estimates. The prevalence of OBI varies significantly by geographic region and population group. For instance, reported OBI rates are 2.7% in blood donors from Saint Petersburg, Russia [6], 4.9% in the Russian Ural region [7], and 15.6% in Guinea [8]. OBI is currently classified into three forms: seropositive, seronegative, and false [4, 9–11]. Seropositive OBI is characterized by detectable antibodies against the core antigen (anti-HBc), with or without antibodies to the surface antigen (anti-HBs). In contrast, seronegative OBI, which accounts for approximately 20% of cases, lacks these serological markers [12]. Consequently, the detection of viral DNA, even at very low concentrations (< 200 IU/mL), remains the only reliable diagnostic criterion [13]. False OBI results from mutations in the S-gene that lead to an altered HBsAg protein undetectable by standard assays, despite high levels of circulating HBV DNA [14–16]. The clinical significance of OBI stems from its asymptomatic nature and the associated risk of viral transmission, which can occur even at minimal viral loads (e.g., as low as 3.5 IU/mL). Furthermore, immunocompromised individuals are at risk for viral reactivation, which can lead to severe complications. These factors necessitate awareness and diagnostic vigilance among Recent years have brought a better understanding of the HBV life cycle and the molecular mechanisms of OBI. Major viral factors contributing to OBI include mutations in the HBV genome, such as in the 'a' determinant of HBsAg, and splicing variations in the pre-S region [17]. The development of OBI is influenced not only by these viral properties but also by the host's immune status [18]. Among the key immune factors are cytokines, a family of molecules that includes interferons (IFNs), interleukins (ILs), chemokines, and growth factors. Our previous work on chronic HBV infection showed that cytokines are involved in the immune response [19]. We observed specific changes in the cytokine profiles of these patients: elevated levels of IL-6, IL-27, CXCL9/MIG, CXCL10/IP-10, and M-CSF, and decreased levels of IL-2, IL-4, IL-12 (p70), CCL3/MIP-1α, CXCL1/GROα, CX3CL1/Fractalkine, PDGF, EGF, and VEGF-A. These profiles were also linked to the extent of liver damage. However, data on cytokine activity in OBI specifically remains limited. The characterization of cytokines in OBI is currently limited. Some studies, such as those by Arababadi et al., report on a narrow range of cytokines, noting elevated levels of IP-10, IL-17A, and IFN-γ in the blood plasma of OBI patients [20, 21]. Another study analyzed a broader spectrum of cytokines, revealing significant differences between OBI patients, those with classic HBV infection, and healthy donors [22]. However, cytokine profiles are known to vary across ethnicities [23], and the abovementioned studies data are primarily from studies conducted in China and Iran. A comprehensive analysis of cytokine levels in OBI patients within a European population has not been conducted, which dictated the goal of this study. Materials and Methods Patients This cross-sectional, randomized study was conducted as part of a larger program by Federal Service for Surveillance on Consumer Rights Protection and Human Wellbeing (Rospotrebnadzor) to assess herd immunity in St. Petersburg and the Leningrad Region, Russia. The study initially enrolled 6,773 healthy volunteers from St. Petersburg (n = 3,300) and the Leningrad Region ( n = 3,473) [Fig. 1 , 24]. After excluding individuals under 18 years of age, hepatitis B marker testing revealed 57 cases of occult hepatitis B (OBI). The OBI group consisted of 15 men and 42 women (26%/74%), with a mean age of 51.2 years (range 19–82). A control group of 37 individuals (11 men, 26 women; mean age 49.4 years) was formed from the same sample, selected for the absence of viral hepatitis markers, HIV, and somatic diseases. The study was conducted in accordance with the Declaration of Helsinki and the protocol was approved by the Ethics Committee of the Saint Petersburg Pasteur Institute (Protocol #88, 03.10.2023). HBV serological assay Serological and molecular markers for HBV were analyzed, including HBsAg, anti-HBs IgG, anti-HBc IgG, and HBV DNA. HBsAg, anti-HBs, and anti-HBc were detected using commercial ELISA kits (‘DS-ELISA-HBsAg’, ‘DS-ELISA-anti-HBsAg’, ‘DS-ELISA-anti-HBc’, Diagnostic Systems, Nizhniy Novgorod, Russia) according to the manufacturer's protocols. DNA detection For DNA detection, nucleic acids were extracted from 200 µl of blood plasma using «NK-Magno-UltraPure-A» kits (LabPack, Saint Petersburg, Russia). HBV DNA was identified using a highly sensitive in-house nested real-time PCR assay with hybridization-fluorescence detection, developed by the St. Petersburg Pasteur Institute. This method targets three regions of the HBV genome, enabling the detection of viral DNA even at low viral loads, as is characteristic of HBsAg-negative occult hepatitis B (OBI) [25]. Cytokine multiplex analysis Cytokine, chemokine, and growth factor concentrations in blood plasma were quantified using a multiplex assay based on xMAP technology (Luminex, Austin, TX, USA). The analysis was performed with Milliplex HCYTA-60K-PX48 kits (Merck-Millipore, Burlington, MA, USA) according to the manufacturer's instructions. Data acquisition and analysis were conducted on a Luminex MAGPIX instrument (Luminex, Austin, TX, USA). The panel measured the following analytes: IL-1α, IL-1β, IL-1RA, IL-2, IL-4, IL-5, IL-6, IL-7, IL-9, IL-10, IL-12 (p40), IL-12 (p70), IL-13, IL-15, IL-17A, IL-17-E/IL-25, IL-17F, IL-18, IL-27, IFNα, IFNγ, TNFα, TNFβ, sCD40L, CCL2/MCP-1, CCL3/MIP-1α, CCL4/MIP-1β, CCL7/MCP-3, CCL11/Eotaxin, CCL22/MDC, CXCL1/GROα, CXCL8/IL-8, CXCL9/MIG, CXCL10/IP-10, CX3CL1/Fractalkine, EGF, FGF-2, FLT-3L, G-CSF, M-CSF, GM-CSF, PDGF-AA, PDGF-AB/BB, TGFα, VEGF-A. The cytokine analysis was carried out using the equipment of the Shared Core Research Facility \"Cytokines and Biomarkers\" at the Saint Petersburg Pasteur Institute. Statistical analysis Statistical analysis was performed using GraphPad Prism 8 (Dotmatics, Boston, MA, USA). The normality of distribution was assessed with the Kolmogorov-Smirnov test, which indicated that the data did not follow a normal distribution. Consequently, the Mann-Whitney U test was used for group comparisons. Differences with a p-value < 0.05 were considered statistically significant. The results are presented as the median (Me) and interquartile range (Q25-Q75). We used receiver operating characteristic (ROC) analysis and calculated area under curve (AUC) values to compare two different predictive tests and to choose the optimal division point. To find optimal combinations of biomarkers, we used the decision tree building method with JMP 16.0 software (SAS Institute, Cary, NC, USA). Results Cytokine analysis in blood plasma of patients with OBI revealed a significant increase in IFNα and IFNγ (Fig. 2 A, B), of IL-1α, IL-2, IL-10, IL-15, IL-17A, IL-22 (Fig. 2 , C-H), CXCL9/MIG (Fig. 2 , I) and growth factors (EGF, FLT-3L, TGFα, G-CSF, M-CSF, VEGF – Fig. 2 , K-O). Based on anti-HBsAg IgG positivity, patients with OBI were separated into two groups. Seropositive cohort demonstrated an increase in CCL22/MDC (Fig. 3 ). To calculate diagnostic value of cytokines as potential biomarkers for OBI, we performed ROC analysis. The results are presented in Table 1 : Table 1 ROC analysis results for cytokines that demonstrated statistically significant differences between OBI and HD cohorts. Cytokine AUC p Cut off, pg/ml Sensitivity, % Specificity, % M-CSF 0.8556 < 0.0001 < 26.40 78.38 75.34 FLT-3L 0.7499 < 0.0001 < 12.52 78.38 59.65 G-CSF 0.7420 < 0.0001 < 54.18 78.38 65.45 EGF 0.7067 0.0007 < 151.6 78.38 59.65 TGFα 0.6932 0.0016 < 4.012 75.68 47.37 IL-10 0.6754 0.0042 < 2.932 78.38 49.12 IL-1α 0.6581 0.0099 < 22.26 75.68 54.39 IL-17A 0.6482 0.0156 < 6.937 78.38 42.11 IFNα 0.6354 0.0271 < 49.18 78.38 40.35 IL-2 0.6316 0.0318 < 0.9802 72.97 42.11 IFNγ 0.6283 0.0363 < 19.58 78.38 43.86 ROC analysis results showed little significance when testing separate plasma cytokine levels to predict disease outcome. Instead, we used a decision tree building method for that purpose. Based on the results received, we established that combined detection of M-CSF and FLT-3L is more valuable in terms occult hepatitis B diagnostic. For these two cytokines, parameters comprised: AUC 0.87; sensitivity 96%; and specificity 76%. From this analysis, we received the following threshold values for occult hepatitis B diagnostic: M-CSF — 21.53 pg/ml; and FLT-3L — 14.80 pg/ml (Fig. 4 ). Discussion Similar to other pathogens, HBV is detected by pattern recognition receptors (PRRs) located on cellular membranes or within intracellular compartments. PRR activation triggers a signaling cascade that ultimately activates transcription factors like NF-κB and interferon regulatory factors (IRFs). This, in turn, induces the expression of interferon-stimulated genes (ISGs), leading to the production of type I and III interferons, proinflammatory cytokines, and chemokines [26, 27]. Our results indicate that even the low viral load in Occult HBV Infection (OBI) can stimulate a broad immune reactivation, observed as elevated levels in blood plasma of type I IFN, the proinflammatory cytokines IL-1α, IL-2, IL-15, and IL-17A, the anti-inflammatory cytokines IL-10 and IL-22, the chemokine CXCL9/MIG, and the growth factors EGF, FLT-3L, TGFα, G-CSF, M-CSF, and VEGF. Interferons (IFNs) play a critical role in regulating antiviral immunity. IFNα, a type I interferon, is produced by a broad range of immune cells, while IFNγ, a type II interferon, is primarily secreted by T cells and NK cells [28]. In the treatment of chronic Hepatitis B, pegylated IFNα is used to suppress viral replication, reduce HBsAg and HBeAg levels, and promote HBsAg seroclearance. This therapeutic effect is associated with the activation of liver-resident monocytes and CD8 + effector T cells, which are crucial for controlling HBsAg [29]. It is plausible that the characteristic absence of HBsAg and low viral load in Occult HBV Infection (OBI) are linked to elevated levels of endogenous IFNα. Furthermore, OBI is characterized by the presence of memory T cells that respond to HBV antigens (HBsAg, HBcAg, and HBeAg). These responses are comparable to, or even stronger than, those observed in individuals who have successfully cleared the virus, and are typically higher than in HBsAg-positive patients [30]. Since IFNγ is largely produced by T cells, the sustained activity of CD8 + memory cells is instrumental in limiting viral replication in OBI. Notably, individuals with chronic OBI can maintain IFN levels similar to those of healthy individuals, particularly in the early stages, reinforcing the concept of a protective role for interferons in this condition [19]. IL-1α is generally known as a pro-inflammatory molecule, alerting the immunity and mediating primary inflammation [31]. Its increase suggests active inflammatory process in OBI individuals. IL-1α has the ability to activate other pro-inflammatory cytokine cascades. IL-2 is a key T-cell growth factor essential for the proliferation and differentiation of effector and memory T cells. Beyond its role in promoting immune responses, IL-2 is critical for immune regulation and maintaining self-tolerance; its deficiency can lead to effector cell autoreactivity [32]. It also supports the proliferation of B cells and NK cells [33]. In the context of HBV infection, IL-2 is associated with successful viral control, and HBV-specific T cells positive for IL-2 are found in individuals with lower viral loads [34]. Conversely, advanced disease stages, such as HBV-induced liver cirrhosis, are characterized by reduced IL-2 levels [19]. IL-15 belongs to the common gamma-chain (γc) cytokine family, which includes IL-2, IL-4, IL-7, IL-9, IL-21, and TSLP [35]. It functions as a homeostatic cytokine crucial for the maintenance and survival of NK cells and CD8 + memory T cells. Furthermore, IL-15 is important for the effector function and homeostatic proliferation of cytotoxic CD8 + T cells and can induce NK-like cytotoxicity during viral infections [36, 37]. It also promotes the proliferation of IFN-γ-secreting CD8 + T cells and can modulate T-cell receptor (TCR) signaling [38, 39]. Supporting its relevance, a study by Xin Liu et al. demonstrated elevated levels of both IL-2 and IL-15 in Occult HBV Infection (OBI) [22]. Given their shared receptor components, IL-15 and IL-2 exhibit overlapping biological activities and often mediate convergent effects [40]. Our findings, consistent with studies by Arababadi M.K. and Xin Liu, highlight elevated plasma levels of IL-10 and IL-17A in OBI [20, 22]. The increased IL-10 suggests an active immunosuppressive mechanism against HBV. In HBV infection, the primary source of IL-10 is regulatory T cells (Tregs), which protect liver tissue from immune-mediated damage [41]. Treg activity is more prominent in chronic HBV than in acute or HBeAg-negative infection. A more recently recognized source is regulatory B cells (Bregs), which also secrete IL-10 to suppress effector immune responses and promote tolerance [42]. In the context of HBV, however, Bregs are believed to facilitate viral replication and fibrosis, and can contribute to viral reactivation by suppressing CD8 + T cells [43]. Conversely, IL-17A may promote viral persistence by activating anti-apoptotic pathways in hepatocytes [44], thereby creating a reservoir for HBV. This theory is supported by Martin et al., who observed reduced sFas levels in OBI, indicating inhibited apoptosis as a potential mechanism for HBsAg clearance and reduced replication [45]. Furthermore, Th17 cells can contribute to viral persistence by suppressing the activity of cytotoxic CD8 + T cells. IL-22 is a member of the IL-10 cytokine family, secreted by Th17, γδ T cells, NKT cells, and innate lymphoid cells (ILC). Similar to IL-10, it functions as an immune modulator, in part by suppressing the NF-κB pathway and the production of pro-inflammatory cytokines. Its pleiotropic effects have been described in numerous tissues, including the gastrointestinal tract, liver, lungs, kidneys, thymus, and skin. IL-22 primarily targets non-hematopoietic epithelial and stromal cells, where it promotes tissue regeneration. Within the liver, its principal roles include hepatoprotection and the mediation of antifibrotic effects, yet in chronic hepatitis its role is different. IL-22 mediates hepatocyte survival, providing conditions for HBV persistence [46]. In liver diseases, IL-22 holds a dual role providing both protective and potential damaging effects. In contrast to the cytokine profile observed in chronic HBV, which is characterized by decreased IL-2 and IL-17A with levels of IL-10, IL-15, and IL-22 comparable to healthy individuals [19], OBI presents distinct pro-fibrotic signals. The chemokine CXCL9/MIG, which is induced by IFN-γ and signals through the CXCR3 receptor, plays a key role in anti-viral and anti-tumor immunity by mediating the chemotaxis of Th1 and NK cells [47]. Our previous research has established a direct correlation between elevated plasma CXCL9/MIG levels and fibrosis progression in chronic viral hepatitis [19, 48]. Therefore, its presence in OBI suggests a potential association with ongoing subclinical fibrotic processes in the liver. Furthermore, the growth factor TGFα, which was also found at high concentrations in OBI, possesses known pro-fibrotic properties. We have previously demonstrated a direct correlation between TGFα and fibrosis severity in chronic hepatitis C [48], reinforcing its role as a contributor to liver pathology that may also be active in OBI. Previously, we demonstrated that HBV-infected patients had lower concentrations of CX3CL1/Fractalkine both in comparison with healthy donors and in comparison with patients with chronic hepatitis C and autoimmune liver diseases [49]. Furthermore, in HBV-infected patients with severe fibrosis/cirrhosis, we observed significantly lower concentrations of CX3CL1/Fractalkine compared to those with mild/no fibrosis. We demonstrated that lowered CX3CL1/Fractalkine concentrations might have prognostic value for predicting fibrosis development in liver tissue. In the present study, the level of CX3CL1/Fractalkine in patients with OBI does not differ from that of healthy donors, which may indicate the absence of liver fibrosis in this cohort of patients. Colony-stimulating factors (CSFs) also appear to be involved in this pathological process. Granulocyte Colony-Stimulating Factor (G-CSF) and Macrophage Colony-Stimulating Factor (M-CSF) are responsible for the differentiation of hematopoietic stem cells into granulocytes and macrophages, respectively. Within the liver, M-CSF specifically supports the population of Kupffer cells [50]. In the context of liver damage, such as that caused by HBV or HCV, levels of G-CSF and M-CSF are frequently elevated [19, 48]. Notably, a direct correlation has been observed between M-CSF concentration and the severity of liver fibrosis [19], underscoring its significant contribution to the process of fibrogenesis. Both EGF and TGFα are ligands of the epidermal growth factor (EGF) family and share a common receptor, EGFR [51, 52]. Their binding to EGFR initiates downstream signaling cascades, such as RAS/MAPK and PI3K/AKT, which promote cell proliferation, survival, and migration. While both factors can mediate fibrogenesis by stimulating fibroblasts and interacting with other pro-fibrotic pathways, their roles are distinct. TGFα is more specifically associated with the progression of chronic fibrosis, whereas EGF acts as a more universal mediator in general tissue repair processes. Our study also identified elevated levels of Fms-like tyrosine kinase 3 ligand (FLT-3L) in OBI. FLT-3L is a key hematopoietic cytokine and a primary growth factor for dendritic cells, serving as a biomarker of bone marrow activity [53]. In the context of hepatitis—whether viral, autoimmune, or toxic—FLT-3L is implicated in modulating immune responses, liver regeneration, and fibrogenesis [54]. Its signaling pathway may promote regeneration via immune cell activation and the stimulation of growth factors like EGF, yet it may simultaneously exacerbate fibrosis through interactions with TGF-α and TGF-β. The precise, and potentially dual, role of FLT-3L in liver fibrosis remains an important subject for future investigation. The comparison of our data to other studies on the matter is presented in Table 2 . Table 2 Comparison of studies on cytokine levels in OBI. Cytokine Current study Liu X. et al., 2023 [22] Arababadi M.K. et al. 2010, 2011 [20, 21] IFNα ↑ ↑ - IFNγ ↑ нет различий ↑ IL-1α ↑ нет различий - IL-1β n/s ↑ - IL-2 ↑ ↑ - IL-8 n/s ↑ - IL-10 ↑ ↑ ↑ IL-12(p40) n/s ↑ - IL-15 ↑ ↑ - IL-17A ↑ ↑ ↑ IL-18 n/s ↑ - IL-22 ↑ n/s - CXCL9/MIG ↑ n/s - CXCL10/IP-10 n/s ↑ - TNFα n/s ↑ - EGF ↑ n/s - FLT-3L ↑ ↑ - TGFα ↑ n/s - G-CSF ↑ n/s - M-CSF ↑ n/s - VEGF ↑ n/s - Note: n/s – not significant (p > 0.05 between groups). Significant demographic disparities between the study cohorts must be considered when interpreting cytokine profiles. The OBI cohort in the study by Liu et al. was predominantly male (77%), whereas our cohort was predominantly female (74%). Although median ages were comparable within each study, the control group in Liu et al. had a significantly lower mean age (37 ± 4 years) compared to their OBI patients (p < 0.01). These demographic variations, particularly in sex distribution and age, may account for the divergent cytokine patterns observed between the studies. But the similar results between groups demonstrated statistically significant differences for 25 cytokines (IL-1RA, IL-4, IL-5, IL-6, IL-7, IL-9, IL-12 (p70), IL-13, IL-17-E/IL-25, IL-17F, IL-27, TNFβ, sCD40L, CCL2/MCP-1, CCL3/MIP-1α, CCL4/MIP-1β, CCL7/MCP-3, CCL11/Eotaxin, CCL22/MDC, CXCL1/GROα, CX3CL1/Fractalkine, FGF-2, GM-CSF, PDGF-AA, PDGF-AB/BB) [22]. Our study confirmed an elevation of IFNα, IL-2, IL-10, IL-17A, and FLT-3L in OBI, a profile consistent with other reports [20–22]. With the exception of IL-15, these cytokines represent potential biomarkers for OBI and warrant further investigation (Table 1 ). Notably, we observed a specific increase in CCL22/MDC among seropositive OBI individuals (i.e., those with anti-HBs antibodies). The presence of anti-HBs suggests a degree of immune control over the virus, which may be associated with a more active immunological state. The elevation of CCL22/MDC, a chemokine that recruits regulatory T cells (Tregs) and Th2 cells via the CCR4 receptor [55], may reflect a polarized immune response aimed at viral containment and the suppression of overt inflammation. This mirrors the concept of immune control in chronic HBV, where chemokines are pivotal for modulating inflammation and T-cell responses. Based on our findings, we propose a conceptual model for the development of Occult HBV Infection (OBI), illustrated in Fig. 5 . This model integrates the roles of the key cytokines and growth factors identified in our study within the OBI pathogenesis. The establishment of viral persistence in OBI is driven by a dynamic interplay between weak immune responses and a resulting pro-fibrotic state. The balance between pro-inflammatory and anti-inflammatory cytokines critically determines the progression or control of the infection. Pro-inflammatory responses aim to clear the virus but can inadvertently promote pathology. Cytokines such as IL-1α initiate inflammatory signaling, while IL-2 and IL-15 stimulate the activity and proliferation of CD8 + T cells and NK cells. These effector cells secrete IFN-γ, which activates macrophages and enhances antigen presentation. Although both IFN-α and IFN-γ can suppress HBV replication, these responses are insufficient for viral clearance in OBI. Furthermore, IFN-γ induces the production of CXCL9/MIG, which perpetuates chronic inflammation, activates Kupffer cells, and contributes to fibrogenesis. Anti-inflammatory and pro-fibrotic mechanisms simultaneously facilitate viral persistence and tissue remodeling. IL-10 suppresses CD8 + T cells and macrophages, creating an environment permissive for HBV persistence and leading to reduced IFN-γ levels and chronic inflammation. While IL-22 and IL-17A can provide hepatoprotection by inhibiting apoptosis, they may also promote fibrosis through STAT3 signaling. Growth factors, including M-CSF and G-CSF, regulate monocyte/macrophage differentiation, with M-CSF polarizing macrophages toward a pro-fibrotic M2 phenotype. Finally, FLT3L expands the dendritic cell pool; while this enhanced antigen presentation is ultimately ineffective at eliminating the virus in OBI, it may still modulate the fibrotic environment. Conclusion OBI is characterized by a dominant anti-inflammatory and pro-fibrotic background, mediated by cytokines such as IL-10 and TGF-α, which facilitates viral persistence and promotes liver fibrosis despite the concurrent elevation of some pro-inflammatory signals. The activation of growth factors like TGF-α and EGF drives aberrant tissue repair, resulting in incomplete regeneration and scarring. The roles of FLT-3L and IL-22 appear dual, mediating hepatoprotection while simultaneously contributing to fibrotic progression. ROC analysis indicates that several cytokines possess high diagnostic potential as biomarkers for OBI. The most promising candidates include M-CSF, FLT-3L, G-CSF, EGF, and TGFα. These markers, along with others highlighted in international research (e.g., IFNα, IL-2, IL-10, IL-17A), require further validation in larger, multi-center cohorts to confirm their clinical utility. Abbreviations HBV Hepatitis B virus WHO World Health Organization HBsAg Hepatitis B surface antigen OBI Occult hepatitis B infection anti-HBc Antibodies against the core antigen anti-HBs Antibodies to the surface antigen IFN Interferon IL Interleukin ELISA Enzyme-linked immunosorbent assay TNF Tumour necrosis factor sCD40L Soluble forms of CD40 ligand MCP Monocyte chemoattractant protein MIP Macrophage inflammatory protein MDC Macrophage-derived chemokine CCL chemokine (C-C motif) ligand CXCL chemokine (C-X-C motif) ligand GROα Growth regulated oncogene-alpha MIG Monokine induced by interferon-gamma IP-10 Inflammatory protein-10 EGF Epidermal growth factor FGF-2 Fibroblast growth factor-2 FLT-3L Fms-related tyrosine kinase 3 ligand G-CSF Granulocyte colony-stimulating factor M-CSF Macrophage colony-stimulating factor GM-CSF Granulocyte-macrophage colony-stimulating factor PDGF Platelet-derived growth factor TGFα Transforming growth factor alpha VEGF-A Vascular endothelial growth factor A ROC Receiver operating characteristic AUC Analysis and calculated area under curve IgG Immunoglobulin G HD Healthy donors PRR Pattern recognition receptors NF-κB Nuclear factor kappa-light-chain-enhancer of activated B cells IRFs Interferon regulatory factors ISGs Interferon-stimulated genes Tregs Regulatory T cells RAS/MAPK Rat Sarcoma / Mitogen-activated protein kinase PI3K/AKT Phosphoinositide 3-kinase / Protein kinase B NK Natural killer cells Declarations Acknowledgements We thank the volunteers enrolled in this study. Volunteer recruitment and acquisition of biological samples was performed by the staff of Pasteur Institute Medical center. The experimental part of the study was conducted at the core facility centre, ‘Cytometry and biomarkers’. Authors’ contributions AAT and NAA designed the study, and interpreted the results. YuVO, ANS, ENS and OAP carried out the screening and epidemiological data collection in epidemic areas. ANS, ENS and OAP carried out the blood collection, serum separation and data collection of part epidemic areas. NAA and NEL performed the multiplex analysis. NAA, OKB and ZRK performed the statistical analyses. NAA, ZRK and AAT wrote the manuscript. All authors have read and agreed to the published version of the manuscript. Funding This research was funded by the Saint Petersburg Pasteur Institute within the framework of a State Task (Registration No. 121021600217-1). Data Availability Statement: The data presented in this study are available on request from the corresponding author due to institutional policy. Ethics approval and consent to participate The study was conducted in accordance with the Declaration of Helsinki and the protocol was approved by the Ethics Committee of the Saint Petersburg Pasteur Institute (Protocol #88, 03.10.2023), and all participants signed informed consent forms. Consent for publication Not applicable. Competing interests The authors declare that they have no competing interests. References Shi M, Wei J, Dong J, Meng W, Ma J, Wang T, Wang N, Wang Y. Function of interleukin-17 and -35 in the blood of patients with hepatitis B-related liver cirrhosis. Mol Med Rep. 2015;11(1):121-6. doi: 10.3892/mmr.2014.2681. Baumert TF, Thimme R, von Weizsäcker F. Pathogenesis of hepatitis B virus infection. World J Gastroenterol. 2007;13(1):82-90. doi: 10.3748/wjg.v13.i1.82. World Health Organization (WHO). Chronic Viral Hepatitis. 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Popova AY, Gorbunova AY, Ostankova YV, Egorova SA, Reingardt DE, Ivanova AR, Schemelev AN, Drozd IV, Zhimbaeva OB, Danilova EM, Milichkina AM, Ezholova EB, Melnikova AA, Bashketova NS, Buc LV, Totolyan AA. Herd Immunity to Hepatitis A Virus in the Saint Petersburg and Leningrad Region. Med Immunol (Russia). 2025;27(3):[указать страницы]. doi:10.15789/1563-0625-HIT-3224. Ostankova YV, Serikova EN, Semenov AV, Totolian AA. Method for hepatitis B virus DNA detecting in biological material at low viral load based on nested PCR with detection on three viral targets in real-time mode. Russ Clin Lab Diagn. 2022;67(9):530-537. doi: 10.51620/0869-2084-2022-67-9-530-537. Seeger C, Mason WS. Molecular biology of hepatitis B virus infection. Virology. 2015;479-480:672-686. doi: 10.1016/j.virol.2015.02.031. Shin EC, Sung PS, Park SH. Immune responses and immunopathology in acute and chronic viral hepatitis. Nat Rev Immunol. 2016;16(8):509-523. doi: 10.1038/nri.2016.69. Pestka S, Krause CD, Walter MR. Interferons, interferon-like cytokines, and their receptors. Immunol Rev. 2004;202:8-32. doi: 10.1111/j.0105-2896.2004.00204.x. Wang Y, Guo L, Shi J, Li Y, Liu S, Wang Z, ... & Wang G. Interferon stimulated immune profile changes in a humanized mouse model of HBV infection. Nat Commun. 2023;14:7393. doi: 10.1038/s41467-023-43078-5. Bes M, Vargas V, Piron M, Casamitjana N, Esteban JI, Vilanova N, Pinacho A, Quer J, Puig L, Guardia J, Sauleda S. T cell responses and viral variability in blood donation candidates with occult hepatitis B infection. J Hepatol. 2012;56(4):765-774. doi: 10.1016/j.jhep.2011.11.011. Cavalli G, Colafrancesco S, Emmi G, Imazio M, Lopalco G, Maggio MC, Sota J, Dinarello CA. Interleukin 1α: a comprehensive review on the role of IL-1α in the pathogenesis and treatment of autoimmune and inflammatory diseases. Autoimmun Rev. 2021;20(3):102763. doi: 10.1016/j.autrev.2021.102763. Abbas AK, Trotta ER, Simeonov D, Marson A, Bluestone JA. Revisiting IL-2: biology and therapeutic prospects. Sci Immunol. 2018;3(25):eaat1482. doi: 10.1126/sciimmunol.aat1482. Turner MD, Nedjai B, Hurst T, Pennington DJ. Cytokines and chemokines: at the crossroads of cell signalling and inflammatory disease. Biochim Biophys Acta. 2014;1843(11):2563-2582. doi: 10.1016/j.bbamcr.2014.07.035. Chua C, Salimzadeh L, Ma AT, Adeyi OA, Seo H, Boukhaled GM, ... & Gehring AJ. IL-2 produced by HBV-specific T cells as a biomarker of viral control and predictor of response to PD-1 therapy across clinical phases of chronic hepatitis B. Hepatol Commun. 2023;7(12):e0337. doi: 10.1097/HC9.0000000000000337. Leonard WJ, Lin JX, O'Shea JJ. The γc family of cytokines: basic biology to therapeutic ramifications. Immunity. 2019;50(4):832-850. doi: 10.1016/j.immuni.2019.03.028. Lee H, Park SH, Shin EC. IL-15 in T-Cell Responses and Immunopathogenesis. Immune Netw. 2024;24(1):e11. doi: 10.4110/in.2024.24.e11. Fawaz LM, Sharif-Askari E, Menezes J. Up-regulation of NK cytotoxic activity via IL-15 induction by different viruses: a comparative study. J Immunol. 1999;163(8):4473-4480. Richer MJ, Pewe LL, Hancox LS, Hartwig SM, Varga SM, Harty JT. Inflammatory IL-15 is required for optimal memory T cell responses. J Clin Invest. 2015;125(9):3477-3490. doi: 10.1172/JCI81261. Setoguchi R. IL-15 boosts the function and migration of human terminally differentiated CD8+ T cells by inducing a unique gene signature. Int Immunol. 2016;28(6):293-305. doi: 10.1093/intimm/dxw004. Waldmann TA. The biology of interleukin-2 and interleukin-15: implications for cancer therapy and vaccine design. Nat Rev Immunol. 2006;6(8):595-601. doi: 10.1038/nri1901. Gol-Ara M, Jadidi-Niaragh F, Sadria R, Azizi G, Mirshafiey A. The role of different subsets of regulatory T cells in immunopathogenesis of rheumatoid arthritis. Arthritis. 2012;2012:805875. doi: 10.1155/2012/805875. Vazquez MI, Catalan-Dibene J, Zlotnik A. B cells responses and cytokine production are regulated by their immune microenvironment. Cytokine. 2015;74(2):318-326. doi: 10.1016/j.cyto.2015.02.007. Alatrakchi N. Bregs in Chronic HBV: Is It Time for Bragging Rights? Dig Dis Sci. 2015;60(5):1115-1117. doi: 10.1007/s10620-015-3584-1. Hou W, Kang HS, Kim BS. Th17 cells enhance viral persistence and inhibit T cell cytotoxicity in a model of chronic virus infection. J Exp Med. 2009;206(2):313-328. doi: 10.1084/jem.20082030. Martin CM, Welge JA, Shire NJ, Shata MT, Sherman KE, Blackard JT. Cytokine expression during chronic versus occult hepatitis B virus infection in HIV co-infected individuals. Cytokine. 2009;47(3):194-198. doi: 10.1016/j.cyto.2009.06.005. Dudakov JA, Hanash AM, van den Brink MR. Interleukin-22: immunobiology and pathology. Annu Rev Immunol. 2015;33:747-785. doi: 10.1146/annurev-immunol-032414-112123. Rubinstein A, et al. CXCR3-Expressing T Cells in Infections and Autoimmunity. Front Biosci (Landmark Ed). 2024;29(8):301. doi: 10.31083/j.fbl2908301. Arsentieva NA, Batsunov OK, Lyubimova NE, Basina VV, Esaulenko EV, Totolian AA. Cytokine profiling of plasma in patients with viral hepatitis C. Med Immunol (Russia). 2024;26(6):1235-1248. doi: 10.15789/1563-0625-CPO-3117. Arsentieva NA, Korobova ZR, Batsunov OK, Lyubimova NE, Basina VV, Esaulenko EV, Totolian AA. CX3CL1/Fractalkine: A Potential Biomarker for Liver Fibrosis in Chronic HBV Infection. Curr Issues Mol Biol. 2024;46(9):9948-9957. doi: 10.3390/cimb46090593. Sauter KA, Pridans C, Sehgal A, Tsai YT, Bradford BM, Raza S, Moffat L, Gow DJ, Beard PM, Mabbott NA, Smith LB, Hume DA. Pleiotropic effects of extended blockade of CSF1R signaling in adult mice. J Leukoc Biol. 2014;96(2):265-274. doi: 10.1189/jlb.2A0114-006R. Radmanić L, Zidovec-Lepej S. The Role of Stem Cell Factor, Epidermal Growth Factor and Angiopoietin-2 in HBV, HCV, HCC and NAFLD. Life (Basel). 2022;12(12):2072. doi: 10.3390/life12122072. Chen J, Zeng F, Forrester SJ, Eguchi S, Zhang MZ, Harris RC. Expression and Function of the Epidermal Growth Factor Receptor in Physiology and Disease. Physiol Rev. 2016;96(3):1025-1069. doi: 10.1152/physrev.00030.2015. Restifo NP, Dudley ME, Rosenberg SA. Adoptive immunotherapy for cancer: harnessing the T cell response. Nat Rev Immunol. 2012;12(4):269-281. doi: 10.1038/nri3191. Bhardwaj N, Friedlander PA, Pavlick AC, Ernstoff MS, Ibrahim N, Hodi FS, ... & Dhodapkar MV. Flt3 ligand augments immune responses to anti-DEC-205-NY-ESO-1 vaccine through expansion of dendritic cell subsets. Nat Cancer. 2020;1(12):1204-1217. doi: 10.1038/s43018-020-00143-y. Korobova ZR, Arsentieva NA, Totolian AA. Macrophage-Derived Chemokine MDC/CCL22: An Ambiguous Finding in COVID-19. Int J Mol Sci. 2023;24(17):13083. doi: 10.3390/ijms241713088. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 20 Feb, 2026 Reviewers agreed at journal 11 Feb, 2026 Reviewers invited by journal 08 Feb, 2026 Editor invited by journal 15 Oct, 2025 Editor assigned by journal 14 Oct, 2025 Submission checks completed at journal 14 Oct, 2025 First submitted to journal 13 Oct, 2025 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. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-7846341\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":false,\"archivedVersions\":[],\"articleType\":\"Research Article\",\"associatedPublications\":[],\"authors\":[{\"id\":589586285,\"identity\":\"0571436f-4d4c-476a-a10a-b384775ac5ad\",\"order_by\":0,\"name\":\"Natalia A. 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Only cytokines with statistically significant differences between groups are shown on graphs (\\u003cem\\u003ep\\u003c/em\\u003e\\u0026lt;0.05).\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage2.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-7846341/v1/a39fe93249fbf8518d9b810f.png\"},{\"id\":102517407,\"identity\":\"f2ff2ead-af02-4f81-a053-661d92132de4\",\"added_by\":\"auto\",\"created_at\":\"2026-02-12 13:56:57\",\"extension\":\"jpeg\",\"order_by\":3,\"title\":\"Figure 3\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":103368,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eDifferences in CCL22/MDC concentrations in blood plasma of patients with OBI (ocHBV) based on anti-HBs IgG positivity: seronegative (\\u003cem\\u003en\\u003c/em\\u003e=36) and seronegative (\\u003cem\\u003en\\u003c/em\\u003e=21).\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage3.jpeg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-7846341/v1/6e13a6603cf4b2e04750cd93.jpeg\"},{\"id\":102517352,\"identity\":\"88383912-2696-450a-b82f-f795ae47a981\",\"added_by\":\"auto\",\"created_at\":\"2026-02-12 13:56:55\",\"extension\":\"png\",\"order_by\":4,\"title\":\"Figure 4\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":42003,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eDecision tree analysis for separating into two groups: healthy donors and OBI (occult hepatitis B).\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage4.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-7846341/v1/1362d17629c18afd4e0d75ee.png\"},{\"id\":102517441,\"identity\":\"12115a4f-eb55-49e7-8477-957cf343e5e0\",\"added_by\":\"auto\",\"created_at\":\"2026-02-12 13:57:09\",\"extension\":\"png\",\"order_by\":5,\"title\":\"Figure 5\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":154943,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eConcept of OBI development with cytokines and growth factors: persistence of HBV DNA within hepatocytes in the absence of HBsAg, and interactions between natural killer (NK) cells, cytotoxic T lymphocytes (CTLs), and hepatic stellate cells (HSCs). Visualization: open-source platforms Photopea (https://photopea.com, accessed on 23 September 2025) and Bioicons (https://bioicons.com, accessed on 23 September 2025).\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage5.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-7846341/v1/de6455fb3fe86c3c9e46e1c3.png\"},{\"id\":102517602,\"identity\":\"7a459382-7ac8-4310-91c6-abf8665ba1fb\",\"added_by\":\"auto\",\"created_at\":\"2026-02-12 13:57:48\",\"extension\":\"pdf\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":1285115,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"manuscript.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-7846341/v1/508de9cb-62f5-4c6c-82db-19975805f07a.pdf\"}],\"financialInterests\":\"No competing interests reported.\",\"formattedTitle\":\"Cytokine Signature behind Occult Hepatitis B Virus Infection\",\"fulltext\":[{\"header\":\"Introduction\",\"content\":\"\\u003cp\\u003eHepatitis B virus (HBV) infection presents with a broad spectrum of clinical outcomes. These range from self-limiting conditions, such as asymptomatic or acute hepatitis followed by recovery, to severe manifestations including chronic hepatitis or fulminant liver failure [1, 2]. Despite an estimated global prevalence of 254\\u0026nbsp;million cases (WHO, 2022) and 1.2\\u0026nbsp;million annual new infections [3], standard diagnostics that detect HBsAg are insufficient for identifying occult HBV infection (OBI), defined by the presence of hepatic DNA in the absence of detectable serum HBsAg [4, 5]. This diagnostic limitation suggests that the true prevalence of OBI exceeds current official estimates.\\u003c/p\\u003e \\u003cp\\u003eThe prevalence of OBI varies significantly by geographic region and population group. For instance, reported OBI rates are 2.7% in blood donors from Saint Petersburg, Russia [6], 4.9% in the Russian Ural region [7], and 15.6% in Guinea [8].\\u003c/p\\u003e \\u003cp\\u003eOBI is currently classified into three forms: seropositive, seronegative, and false [4, 9\\u0026ndash;11]. Seropositive OBI is characterized by detectable antibodies against the core antigen (anti-HBc), with or without antibodies to the surface antigen (anti-HBs). In contrast, seronegative OBI, which accounts for approximately 20% of cases, lacks these serological markers [12]. Consequently, the detection of viral DNA, even at very low concentrations (\\u0026lt;\\u0026thinsp;200 IU/mL), remains the only reliable diagnostic criterion [13]. False OBI results from mutations in the S-gene that lead to an altered HBsAg protein undetectable by standard assays, despite high levels of circulating HBV DNA [14\\u0026ndash;16].\\u003c/p\\u003e \\u003cp\\u003eThe clinical significance of OBI stems from its asymptomatic nature and the associated risk of viral transmission, which can occur even at minimal viral loads (e.g., as low as 3.5 IU/mL). Furthermore, immunocompromised individuals are at risk for viral reactivation, which can lead to severe complications. These factors necessitate awareness and diagnostic vigilance among Recent years have brought a better understanding of the HBV life cycle and the molecular mechanisms of OBI. Major viral factors contributing to OBI include mutations in the HBV genome, such as in the 'a' determinant of HBsAg, and splicing variations in the pre-S region [17]. The development of OBI is influenced not only by these viral properties but also by the host's immune status [18].\\u003c/p\\u003e \\u003cp\\u003eAmong the key immune factors are cytokines, a family of molecules that includes interferons (IFNs), interleukins (ILs), chemokines, and growth factors. Our previous work on chronic HBV infection showed that cytokines are involved in the immune response [19]. We observed specific changes in the cytokine profiles of these patients: elevated levels of IL-6, IL-27, CXCL9/MIG, CXCL10/IP-10, and M-CSF, and decreased levels of IL-2, IL-4, IL-12 (p70), CCL3/MIP-1α, CXCL1/GROα, CX3CL1/Fractalkine, PDGF, EGF, and VEGF-A. These profiles were also linked to the extent of liver damage. However, data on cytokine activity in OBI specifically remains limited.\\u003c/p\\u003e \\u003cp\\u003eThe characterization of cytokines in OBI is currently limited. Some studies, such as those by Arababadi et al., report on a narrow range of cytokines, noting elevated levels of IP-10, IL-17A, and IFN-γ in the blood plasma of OBI patients [20, 21]. Another study analyzed a broader spectrum of cytokines, revealing significant differences between OBI patients, those with classic HBV infection, and healthy donors [22]. However, cytokine profiles are known to vary across ethnicities [23], and the abovementioned studies data are primarily from studies conducted in China and Iran. A comprehensive analysis of cytokine levels in OBI patients within a European population has not been conducted, which dictated the goal of this study.\\u003c/p\\u003e\"},{\"header\":\"Materials and Methods\",\"content\":\"\\u003cdiv id=\\\"Sec3\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003ePatients\\u003c/h2\\u003e \\u003cp\\u003eThis cross-sectional, randomized study was conducted as part of a larger program by Federal Service for Surveillance on Consumer Rights Protection and Human Wellbeing (Rospotrebnadzor) to assess herd immunity in St. Petersburg and the Leningrad Region, Russia.\\u003c/p\\u003e \\u003cp\\u003eThe study initially enrolled 6,773 healthy volunteers from St. Petersburg (n\\u0026thinsp;=\\u0026thinsp;3,300) and the Leningrad Region (\\u003cem\\u003en\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;3,473) [Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e, 24]. After excluding individuals under 18 years of age, hepatitis B marker testing revealed 57 cases of occult hepatitis B (OBI). The OBI group consisted of 15 men and 42 women (26%/74%), with a mean age of 51.2 years (range 19\\u0026ndash;82). A control group of 37 individuals (11 men, 26 women; mean age 49.4 years) was formed from the same sample, selected for the absence of viral hepatitis markers, HIV, and somatic diseases. The study was conducted in accordance with the Declaration of Helsinki and the protocol was approved by the Ethics Committee of the Saint Petersburg Pasteur Institute (Protocol #88, 03.10.2023).\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003c/div\\u003e\\n\\u003ch3\\u003eHBV serological assay\\u003c/h3\\u003e\\n\\u003cp\\u003eSerological and molecular markers for HBV were analyzed, including HBsAg, anti-HBs IgG, anti-HBc IgG, and HBV DNA. HBsAg, anti-HBs, and anti-HBc were detected using commercial ELISA kits (\\u0026lsquo;DS-ELISA-HBsAg\\u0026rsquo;, \\u0026lsquo;DS-ELISA-anti-HBsAg\\u0026rsquo;, \\u0026lsquo;DS-ELISA-anti-HBc\\u0026rsquo;, Diagnostic Systems, Nizhniy Novgorod, Russia) according to the manufacturer's protocols.\\u003c/p\\u003e\\n\\u003ch3\\u003eDNA detection\\u003c/h3\\u003e\\n\\u003cp\\u003eFor DNA detection, nucleic acids were extracted from 200 \\u0026micro;l of blood plasma using \\u0026laquo;NK-Magno-UltraPure-A\\u0026raquo; kits (LabPack, Saint Petersburg, Russia). HBV DNA was identified using a highly sensitive in-house nested real-time PCR assay with hybridization-fluorescence detection, developed by the St. Petersburg Pasteur Institute. This method targets three regions of the HBV genome, enabling the detection of viral DNA even at low viral loads, as is characteristic of HBsAg-negative occult hepatitis B (OBI) [25].\\u003c/p\\u003e\\n\\u003ch3\\u003eCytokine multiplex analysis\\u003c/h3\\u003e\\n\\u003cp\\u003eCytokine, chemokine, and growth factor concentrations in blood plasma were quantified using a multiplex assay based on xMAP technology (Luminex, Austin, TX, USA). The analysis was performed with Milliplex HCYTA-60K-PX48 kits (Merck-Millipore, Burlington, MA, USA) according to the manufacturer's instructions. Data acquisition and analysis were conducted on a Luminex MAGPIX instrument (Luminex, Austin, TX, USA). The panel measured the following analytes: IL-1α, IL-1β, IL-1RA, IL-2, IL-4, IL-5, IL-6, IL-7, IL-9, IL-10, IL-12 (p40), IL-12 (p70), IL-13, IL-15, IL-17A, IL-17-E/IL-25, IL-17F, IL-18, IL-27, IFNα, IFNγ, TNFα, TNFβ, sCD40L, CCL2/MCP-1, CCL3/MIP-1α, CCL4/MIP-1β, CCL7/MCP-3, CCL11/Eotaxin, CCL22/MDC, CXCL1/GROα, CXCL8/IL-8, CXCL9/MIG, CXCL10/IP-10, CX3CL1/Fractalkine, EGF, FGF-2, FLT-3L, G-CSF, M-CSF, GM-CSF, PDGF-AA, PDGF-AB/BB, TGFα, VEGF-A. The cytokine analysis was carried out using the equipment of the Shared Core Research Facility \\\"Cytokines and Biomarkers\\\" at the Saint Petersburg Pasteur Institute.\\u003c/p\\u003e \\u003cdiv id=\\\"Sec7\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eStatistical analysis\\u003c/h2\\u003e \\u003cp\\u003eStatistical analysis was performed using GraphPad Prism 8 (Dotmatics, Boston, MA, USA). The normality of distribution was assessed with the Kolmogorov-Smirnov test, which indicated that the data did not follow a normal distribution. Consequently, the Mann-Whitney U test was used for group comparisons. Differences with a p-value\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05 were considered statistically significant. The results are presented as the median (Me) and interquartile range (Q25-Q75).\\u003c/p\\u003e \\u003cp\\u003eWe used receiver operating characteristic (ROC) analysis and calculated area under curve (AUC) values to compare two different predictive tests and to choose the optimal division point. To find optimal combinations of biomarkers, we used the decision tree building method with JMP 16.0 software (SAS Institute, Cary, NC, USA).\\u003c/p\\u003e \\u003c/div\\u003e\"},{\"header\":\"Results\",\"content\":\"\\u003cp\\u003eCytokine analysis in blood plasma of patients with OBI revealed a significant increase in IFNα and IFNγ (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003eA, B), of IL-1α, IL-2, IL-10, IL-15, IL-17A, IL-22 (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e, C-H), CXCL9/MIG (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e, I) and growth factors (EGF, FLT-3L, TGFα, G-CSF, M-CSF, VEGF \\u0026ndash; Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e, K-O).\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003eBased on anti-HBsAg IgG positivity, patients with OBI were separated into two groups. Seropositive cohort demonstrated an increase in CCL22/MDC (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003eTo calculate diagnostic value of cytokines as potential biomarkers for OBI, we performed ROC analysis. The results are presented in Table \\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e:\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab1\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 1\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003eROC analysis results for cytokines that demonstrated statistically significant differences between OBI and HD cohorts.\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"6\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c5\\\" colnum=\\\"5\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c6\\\" colnum=\\\"6\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eCytokine\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eAUC\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e\\u003cem\\u003ep\\u003c/em\\u003e\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eCut off, pg/ml\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003eSensitivity, %\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003eSpecificity, %\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eM-CSF\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.8556\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.0001\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;26.40\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e78.38\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e75.34\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eFLT-3L\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.7499\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.0001\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;12.52\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e78.38\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e59.65\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eG-CSF\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.7420\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.0001\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;54.18\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e78.38\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e65.45\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eEGF\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.7067\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.0007\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;151.6\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e78.38\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e59.65\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eTGFα\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.6932\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.0016\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;4.012\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e75.68\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e47.37\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eIL-10\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.6754\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.0042\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;2.932\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e78.38\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e49.12\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eIL-1α\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.6581\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.0099\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;22.26\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e75.68\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e54.39\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eIL-17A\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.6482\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.0156\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;6.937\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e78.38\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e42.11\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eIFNα\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.6354\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.0271\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;49.18\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e78.38\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e40.35\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eIL-2\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.6316\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.0318\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.9802\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e72.97\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e42.11\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eIFNγ\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.6283\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e0.0363\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;19.58\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e78.38\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e43.86\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003cp\\u003eROC analysis results showed little significance when testing separate plasma cytokine levels to predict disease outcome. Instead, we used a decision tree building method for that purpose. Based on the results received, we established that combined detection of M-CSF and FLT-3L is more valuable in terms occult hepatitis B diagnostic. For these two cytokines, parameters comprised: AUC 0.87; sensitivity 96%; and specificity 76%. From this analysis, we received the following threshold values for occult hepatitis B diagnostic: M-CSF \\u0026mdash; 21.53 pg/ml; and FLT-3L \\u0026mdash; 14.80 pg/ml (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e\"},{\"header\":\"Discussion\",\"content\":\"\\u003cp\\u003eSimilar to other pathogens, HBV is detected by pattern recognition receptors (PRRs) located on cellular membranes or within intracellular compartments. PRR activation triggers a signaling cascade that ultimately activates transcription factors like NF-κB and interferon regulatory factors (IRFs). This, in turn, induces the expression of interferon-stimulated genes (ISGs), leading to the production of type I and III interferons, proinflammatory cytokines, and chemokines [26, 27]. Our results indicate that even the low viral load in Occult HBV Infection (OBI) can stimulate a broad immune reactivation, observed as elevated levels in blood plasma of type I IFN, the proinflammatory cytokines IL-1α, IL-2, IL-15, and IL-17A, the anti-inflammatory cytokines IL-10 and IL-22, the chemokine CXCL9/MIG, and the growth factors EGF, FLT-3L, TGFα, G-CSF, M-CSF, and VEGF.\\u003c/p\\u003e \\u003cp\\u003eInterferons (IFNs) play a critical role in regulating antiviral immunity. IFNα, a type I interferon, is produced by a broad range of immune cells, while IFNγ, a type II interferon, is primarily secreted by T cells and NK cells [28]. In the treatment of chronic Hepatitis B, pegylated IFNα is used to suppress viral replication, reduce HBsAg and HBeAg levels, and promote HBsAg seroclearance. This therapeutic effect is associated with the activation of liver-resident monocytes and CD8\\u0026thinsp;+\\u0026thinsp;effector T cells, which are crucial for controlling HBsAg [29]. It is plausible that the characteristic absence of HBsAg and low viral load in Occult HBV Infection (OBI) are linked to elevated levels of endogenous IFNα.\\u003c/p\\u003e \\u003cp\\u003eFurthermore, OBI is characterized by the presence of memory T cells that respond to HBV antigens (HBsAg, HBcAg, and HBeAg). These responses are comparable to, or even stronger than, those observed in individuals who have successfully cleared the virus, and are typically higher than in HBsAg-positive patients [30]. Since IFNγ is largely produced by T cells, the sustained activity of CD8\\u0026thinsp;+\\u0026thinsp;memory cells is instrumental in limiting viral replication in OBI. Notably, individuals with chronic OBI can maintain IFN levels similar to those of healthy individuals, particularly in the early stages, reinforcing the concept of a protective role for interferons in this condition [19].\\u003c/p\\u003e \\u003cp\\u003eIL-1α is generally known as a pro-inflammatory molecule, alerting the immunity and mediating primary inflammation [31]. Its increase suggests active inflammatory process in OBI individuals. IL-1α has the ability to activate other pro-inflammatory cytokine cascades.\\u003c/p\\u003e \\u003cp\\u003eIL-2 is a key T-cell growth factor essential for the proliferation and differentiation of effector and memory T cells. Beyond its role in promoting immune responses, IL-2 is critical for immune regulation and maintaining self-tolerance; its deficiency can lead to effector cell autoreactivity [32]. It also supports the proliferation of B cells and NK cells [33]. In the context of HBV infection, IL-2 is associated with successful viral control, and HBV-specific T cells positive for IL-2 are found in individuals with lower viral loads [34]. Conversely, advanced disease stages, such as HBV-induced liver cirrhosis, are characterized by reduced IL-2 levels [19]. IL-15 belongs to the common gamma-chain (γc) cytokine family, which includes IL-2, IL-4, IL-7, IL-9, IL-21, and TSLP [35]. It functions as a homeostatic cytokine crucial for the maintenance and survival of NK cells and CD8\\u0026thinsp;+\\u0026thinsp;memory T cells. Furthermore, IL-15 is important for the effector function and homeostatic proliferation of cytotoxic CD8\\u0026thinsp;+\\u0026thinsp;T cells and can induce NK-like cytotoxicity during viral infections [36, 37]. It also promotes the proliferation of IFN-γ-secreting CD8\\u0026thinsp;+\\u0026thinsp;T cells and can modulate T-cell receptor (TCR) signaling [38, 39]. Supporting its relevance, a study by Xin Liu et al. demonstrated elevated levels of both IL-2 and IL-15 in Occult HBV Infection (OBI) [22]. Given their shared receptor components, IL-15 and IL-2 exhibit overlapping biological activities and often mediate convergent effects [40].\\u003c/p\\u003e \\u003cp\\u003eOur findings, consistent with studies by Arababadi M.K. and Xin Liu, highlight elevated plasma levels of IL-10 and IL-17A in OBI [20, 22]. The increased IL-10 suggests an active immunosuppressive mechanism against HBV. In HBV infection, the primary source of IL-10 is regulatory T cells (Tregs), which protect liver tissue from immune-mediated damage [41]. Treg activity is more prominent in chronic HBV than in acute or HBeAg-negative infection. A more recently recognized source is regulatory B cells (Bregs), which also secrete IL-10 to suppress effector immune responses and promote tolerance [42]. In the context of HBV, however, Bregs are believed to facilitate viral replication and fibrosis, and can contribute to viral reactivation by suppressing CD8\\u0026thinsp;+\\u0026thinsp;T cells [43].\\u003c/p\\u003e \\u003cp\\u003eConversely, IL-17A may promote viral persistence by activating anti-apoptotic pathways in hepatocytes [44], thereby creating a reservoir for HBV. This theory is supported by Martin et al., who observed reduced sFas levels in OBI, indicating inhibited apoptosis as a potential mechanism for HBsAg clearance and reduced replication [45]. Furthermore, Th17 cells can contribute to viral persistence by suppressing the activity of cytotoxic CD8\\u0026thinsp;+\\u0026thinsp;T cells.\\u003c/p\\u003e \\u003cp\\u003eIL-22 is a member of the IL-10 cytokine family, secreted by Th17, γδ T cells, NKT cells, and innate lymphoid cells (ILC). Similar to IL-10, it functions as an immune modulator, in part by suppressing the NF-κB pathway and the production of pro-inflammatory cytokines. Its pleiotropic effects have been described in numerous tissues, including the gastrointestinal tract, liver, lungs, kidneys, thymus, and skin. IL-22 primarily targets non-hematopoietic epithelial and stromal cells, where it promotes tissue regeneration. Within the liver, its principal roles include hepatoprotection and the mediation of antifibrotic effects, yet in chronic hepatitis its role is different. IL-22 mediates hepatocyte survival, providing conditions for HBV persistence [46]. In liver diseases, IL-22 holds a dual role providing both protective and potential damaging effects.\\u003c/p\\u003e \\u003cp\\u003eIn contrast to the cytokine profile observed in chronic HBV, which is characterized by decreased IL-2 and IL-17A with levels of IL-10, IL-15, and IL-22 comparable to healthy individuals [19], OBI presents distinct pro-fibrotic signals.\\u003c/p\\u003e \\u003cp\\u003eThe chemokine CXCL9/MIG, which is induced by IFN-γ and signals through the CXCR3 receptor, plays a key role in anti-viral and anti-tumor immunity by mediating the chemotaxis of Th1 and NK cells [47]. Our previous research has established a direct correlation between elevated plasma CXCL9/MIG levels and fibrosis progression in chronic viral hepatitis [19, 48]. Therefore, its presence in OBI suggests a potential association with ongoing subclinical fibrotic processes in the liver.\\u003c/p\\u003e \\u003cp\\u003eFurthermore, the growth factor TGFα, which was also found at high concentrations in OBI, possesses known pro-fibrotic properties. We have previously demonstrated a direct correlation between TGFα and fibrosis severity in chronic hepatitis C [48], reinforcing its role as a contributor to liver pathology that may also be active in OBI.\\u003c/p\\u003e \\u003cp\\u003ePreviously, we demonstrated that HBV-infected patients had lower concentrations of CX3CL1/Fractalkine both in comparison with healthy donors and in comparison with patients with chronic hepatitis C and autoimmune liver diseases [49]. Furthermore, in HBV-infected patients with severe fibrosis/cirrhosis, we observed significantly lower concentrations of CX3CL1/Fractalkine compared to those with mild/no fibrosis. We demonstrated that lowered CX3CL1/Fractalkine concentrations might have prognostic value for predicting fibrosis development in liver tissue. In the present study, the level of CX3CL1/Fractalkine in patients with OBI does not differ from that of healthy donors, which may indicate the absence of liver fibrosis in this cohort of patients.\\u003c/p\\u003e \\u003cp\\u003eColony-stimulating factors (CSFs) also appear to be involved in this pathological process. Granulocyte Colony-Stimulating Factor (G-CSF) and Macrophage Colony-Stimulating Factor (M-CSF) are responsible for the differentiation of hematopoietic stem cells into granulocytes and macrophages, respectively. Within the liver, M-CSF specifically supports the population of Kupffer cells [50]. In the context of liver damage, such as that caused by HBV or HCV, levels of G-CSF and M-CSF are frequently elevated [19, 48]. Notably, a direct correlation has been observed between M-CSF concentration and the severity of liver fibrosis [19], underscoring its significant contribution to the process of fibrogenesis.\\u003c/p\\u003e \\u003cp\\u003eBoth EGF and TGFα are ligands of the epidermal growth factor (EGF) family and share a common receptor, EGFR [51, 52]. Their binding to EGFR initiates downstream signaling cascades, such as RAS/MAPK and PI3K/AKT, which promote cell proliferation, survival, and migration. While both factors can mediate fibrogenesis by stimulating fibroblasts and interacting with other pro-fibrotic pathways, their roles are distinct. TGFα is more specifically associated with the progression of chronic fibrosis, whereas EGF acts as a more universal mediator in general tissue repair processes.\\u003c/p\\u003e \\u003cp\\u003eOur study also identified elevated levels of Fms-like tyrosine kinase 3 ligand (FLT-3L) in OBI. FLT-3L is a key hematopoietic cytokine and a primary growth factor for dendritic cells, serving as a biomarker of bone marrow activity [53]. In the context of hepatitis\\u0026mdash;whether viral, autoimmune, or toxic\\u0026mdash;FLT-3L is implicated in modulating immune responses, liver regeneration, and fibrogenesis [54]. Its signaling pathway may promote regeneration via immune cell activation and the stimulation of growth factors like EGF, yet it may simultaneously exacerbate fibrosis through interactions with TGF-α and TGF-β. The precise, and potentially dual, role of FLT-3L in liver fibrosis remains an important subject for future investigation.\\u003c/p\\u003e \\u003cp\\u003eThe comparison of our data to other studies on the matter is presented in Table\\u0026nbsp;\\u003cspan refid=\\\"Tab2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e.\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab2\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 2\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003eComparison of studies on cytokine levels in OBI.\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"4\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eCytokine\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eCurrent study\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eLiu X. et al., 2023 [22]\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eArababadi M.K. et al. 2010, 2011 [20, 21]\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eIFNα\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u0026uarr;\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e\\u0026uarr;\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e-\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eIFNγ\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u0026uarr;\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eнет различий\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u0026uarr;\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eIL-1α\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u0026uarr;\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eнет различий\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e-\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eIL-1β\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003en/s\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e\\u0026uarr;\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e-\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eIL-2\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u0026uarr;\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e\\u0026uarr;\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e-\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eIL-8\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003en/s\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e\\u0026uarr;\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e-\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eIL-10\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u0026uarr;\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e\\u0026uarr;\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u0026uarr;\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eIL-12(p40)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003en/s\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e\\u0026uarr;\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e-\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eIL-15\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u0026uarr;\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e\\u0026uarr;\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e-\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eIL-17A\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u0026uarr;\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e\\u0026uarr;\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u0026uarr;\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eIL-18\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003en/s\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e\\u0026uarr;\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e-\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eIL-22\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u0026uarr;\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003en/s\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e-\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eCXCL9/MIG\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u0026uarr;\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003en/s\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e-\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eCXCL10/IP-10\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003en/s\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e\\u0026uarr;\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e-\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eTNFα\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003en/s\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e\\u0026uarr;\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e-\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eEGF\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u0026uarr;\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003en/s\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e-\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eFLT-3L\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u0026uarr;\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e\\u0026uarr;\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e-\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eTGFα\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u0026uarr;\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003en/s\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e-\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eG-CSF\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u0026uarr;\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003en/s\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e-\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eM-CSF\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u0026uarr;\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003en/s\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e-\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eVEGF\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e\\u0026uarr;\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003en/s\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e-\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003ctfoot\\u003e \\u003ctr\\u003e\\u003ctd colspan=\\\"4\\\"\\u003e\\u003cem\\u003eNote: n/s \\u0026ndash; not significant (p\\u0026thinsp;\\u0026gt;\\u0026thinsp;0.05 between groups).\\u003c/em\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e \\u003c/tfoot\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003cp\\u003eSignificant demographic disparities between the study cohorts must be considered when interpreting cytokine profiles. The OBI cohort in the study by Liu et al. was predominantly male (77%), whereas our cohort was predominantly female (74%). Although median ages were comparable within each study, the control group in Liu et al. had a significantly lower mean age (37\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;4 years) compared to their OBI patients (p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.01). These demographic variations, particularly in sex distribution and age, may account for the divergent cytokine patterns observed between the studies. But the similar results between groups demonstrated statistically significant differences for 25 cytokines (IL-1RA, IL-4, IL-5, IL-6, IL-7, IL-9, IL-12 (p70), IL-13, IL-17-E/IL-25, IL-17F, IL-27, TNFβ, sCD40L, CCL2/MCP-1, CCL3/MIP-1α, CCL4/MIP-1β, CCL7/MCP-3, CCL11/Eotaxin, CCL22/MDC, CXCL1/GROα, CX3CL1/Fractalkine, FGF-2, GM-CSF, PDGF-AA, PDGF-AB/BB) [22].\\u003c/p\\u003e \\u003cp\\u003eOur study confirmed an elevation of IFNα, IL-2, IL-10, IL-17A, and FLT-3L in OBI, a profile consistent with other reports [20\\u0026ndash;22]. With the exception of IL-15, these cytokines represent potential biomarkers for OBI and warrant further investigation (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003eNotably, we observed a specific increase in CCL22/MDC among seropositive OBI individuals (i.e., those with anti-HBs antibodies). The presence of anti-HBs suggests a degree of immune control over the virus, which may be associated with a more active immunological state. The elevation of CCL22/MDC, a chemokine that recruits regulatory T cells (Tregs) and Th2 cells via the CCR4 receptor [55], may reflect a polarized immune response aimed at viral containment and the suppression of overt inflammation. This mirrors the concept of immune control in chronic HBV, where chemokines are pivotal for modulating inflammation and T-cell responses.\\u003c/p\\u003e \\u003cp\\u003eBased on our findings, we propose a conceptual model for the development of Occult HBV Infection (OBI), illustrated in Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig5\\\" class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003e. This model integrates the roles of the key cytokines and growth factors identified in our study within the OBI pathogenesis.\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003eThe establishment of viral persistence in OBI is driven by a dynamic interplay between weak immune responses and a resulting pro-fibrotic state. The balance between pro-inflammatory and anti-inflammatory cytokines critically determines the progression or control of the infection.\\u003c/p\\u003e \\u003cp\\u003ePro-inflammatory responses aim to clear the virus but can inadvertently promote pathology. Cytokines such as IL-1α initiate inflammatory signaling, while IL-2 and IL-15 stimulate the activity and proliferation of CD8\\u0026thinsp;+\\u0026thinsp;T cells and NK cells. These effector cells secrete IFN-γ, which activates macrophages and enhances antigen presentation. Although both IFN-α and IFN-γ can suppress HBV replication, these responses are insufficient for viral clearance in OBI. Furthermore, IFN-γ induces the production of CXCL9/MIG, which perpetuates chronic inflammation, activates Kupffer cells, and contributes to fibrogenesis.\\u003c/p\\u003e \\u003cp\\u003eAnti-inflammatory and pro-fibrotic mechanisms simultaneously facilitate viral persistence and tissue remodeling. IL-10 suppresses CD8\\u0026thinsp;+\\u0026thinsp;T cells and macrophages, creating an environment permissive for HBV persistence and leading to reduced IFN-γ levels and chronic inflammation. While IL-22 and IL-17A can provide hepatoprotection by inhibiting apoptosis, they may also promote fibrosis through STAT3 signaling. Growth factors, including M-CSF and G-CSF, regulate monocyte/macrophage differentiation, with M-CSF polarizing macrophages toward a pro-fibrotic M2 phenotype. Finally, FLT3L expands the dendritic cell pool; while this enhanced antigen presentation is ultimately ineffective at eliminating the virus in OBI, it may still modulate the fibrotic environment.\\u003c/p\\u003e\"},{\"header\":\"Conclusion\",\"content\":\"\\u003cp\\u003eOBI is characterized by a dominant anti-inflammatory and pro-fibrotic background, mediated by cytokines such as IL-10 and TGF-α, which facilitates viral persistence and promotes liver fibrosis despite the concurrent elevation of some pro-inflammatory signals. The activation of growth factors like TGF-α and EGF drives aberrant tissue repair, resulting in incomplete regeneration and scarring. The roles of FLT-3L and IL-22 appear dual, mediating hepatoprotection while simultaneously contributing to fibrotic progression.\\u003c/p\\u003e \\u003cp\\u003eROC analysis indicates that several cytokines possess high diagnostic potential as biomarkers for OBI. The most promising candidates include M-CSF, FLT-3L, G-CSF, EGF, and TGFα. These markers, along with others highlighted in international research (e.g., IFNα, IL-2, IL-10, IL-17A), require further validation in larger, multi-center cohorts to confirm their clinical utility.\\u003c/p\\u003e\"},{\"header\":\"Abbreviations\",\"content\":\"\\u003cdiv class=\\\"DefinitionList\\\"\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003eHBV\\u003c/b\\u003e\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eHepatitis B virus\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003eWHO\\u003c/b\\u003e\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eWorld Health Organization\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003eHBsAg\\u003c/b\\u003e\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eHepatitis B surface antigen\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003eOBI\\u003c/b\\u003e\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eOccult hepatitis B infection\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003eanti-HBc\\u003c/b\\u003e\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eAntibodies against the core antigen\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003eanti-HBs\\u003c/b\\u003e\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eAntibodies to the surface antigen\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003eIFN\\u003c/b\\u003e\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eInterferon\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003eIL\\u003c/b\\u003e\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eInterleukin\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003eELISA\\u003c/b\\u003e\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eEnzyme-linked immunosorbent assay\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003eTNF\\u003c/b\\u003e\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eTumour necrosis factor\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003esCD40L\\u003c/b\\u003e\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eSoluble forms of CD40 ligand\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003eMCP\\u003c/b\\u003e\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eMonocyte chemoattractant protein\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003eMIP\\u003c/b\\u003e\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eMacrophage inflammatory protein\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003eMDC\\u003c/b\\u003e\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eMacrophage-derived chemokine\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003eCCL\\u003c/b\\u003e\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003echemokine (C-C motif) ligand\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003eCXCL\\u003c/b\\u003e\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003echemokine (C-X-C motif) ligand\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003eGROα\\u003c/b\\u003e\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eGrowth regulated oncogene-alpha\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003eMIG\\u003c/b\\u003e\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eMonokine induced by interferon-gamma\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003eIP-10\\u003c/b\\u003e\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eInflammatory protein-10\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003eEGF\\u003c/b\\u003e\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eEpidermal growth factor\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003eFGF-2\\u003c/b\\u003e\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eFibroblast growth factor-2\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003eFLT-3L\\u003c/b\\u003e\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eFms-related tyrosine kinase 3 ligand\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003eG-CSF\\u003c/b\\u003e\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eGranulocyte colony-stimulating factor\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003eM-CSF\\u003c/b\\u003e\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eMacrophage colony-stimulating factor\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003eGM-CSF\\u003c/b\\u003e\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eGranulocyte-macrophage colony-stimulating factor\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003ePDGF\\u003c/b\\u003e\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003ePlatelet-derived growth factor\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003eTGFα\\u003c/b\\u003e\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eTransforming growth factor alpha\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003eVEGF-A\\u003c/b\\u003e\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eVascular endothelial growth factor A\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003eROC\\u003c/b\\u003e\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003e \\u003cb\\u003eReceiver operating characteristic\\u003c/b\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003eAUC\\u003c/b\\u003e\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003e \\u003cb\\u003eAnalysis and calculated area under curve\\u003c/b\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003eIgG\\u003c/b\\u003e\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eImmunoglobulin G\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003eHD\\u003c/b\\u003e\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003e \\u003cb\\u003eHealthy donors\\u003c/b\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003ePRR\\u003c/b\\u003e\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003e \\u003cb\\u003ePattern recognition receptors\\u003c/b\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003eNF-κB\\u003c/b\\u003e\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eNuclear factor kappa-light-chain-enhancer of activated B cells\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003eIRFs\\u003c/b\\u003e\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003e \\u003cb\\u003eInterferon regulatory factors\\u003c/b\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003eISGs\\u003c/b\\u003e\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003e \\u003cb\\u003eInterferon-stimulated genes\\u003c/b\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003eTregs\\u003c/b\\u003e\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003e \\u003cb\\u003eRegulatory T cells\\u003c/b\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003eRAS/MAPK\\u003c/b\\u003e\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eRat Sarcoma / Mitogen-activated protein kinase\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003ePI3K/AKT\\u003c/b\\u003e\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003ePhosphoinositide 3-kinase / Protein kinase B\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003e\\u003cb\\u003eNK\\u003c/b\\u003e\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eNatural killer cells\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003c/div\\u003e\"},{\"header\":\"Declarations\",\"content\":\"\\u003cp\\u003e\\u003cstrong\\u003eAcknowledgements\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eWe thank the volunteers enrolled in this study. Volunteer recruitment and acquisition of biological samples was performed by the staff of Pasteur Institute Medical center. The experimental part of the study was conducted at \\u0026nbsp;the core facility centre, \\u0026lsquo;Cytometry and biomarkers\\u0026rsquo;.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAuthors\\u0026rsquo; contributions\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eAAT and NAA designed the study, and interpreted the results. YuVO, ANS, ENS and OAP carried out the screening and epidemiological data collection in epidemic areas. ANS, ENS and OAP carried out the blood collection, serum separation and data collection of part epidemic areas. NAA and NEL performed the multiplex analysis. NAA, OKB and ZRK performed the statistical analyses. NAA, ZRK and AAT wrote the manuscript. All authors have read and agreed to the published version of the manuscript.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eFunding\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThis research was funded by the Saint Petersburg Pasteur Institute within the framework of a State Task (Registration No. 121021600217-1).\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eData Availability Statement:\\u003c/strong\\u003e The data presented in this study are available on request from the corresponding author due to institutional policy.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eEthics approval and consent to participate\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe study was conducted in accordance with the Declaration of Helsinki and the protocol was approved by the Ethics Committee of the Saint Petersburg Pasteur\\u0026nbsp;Institute (Protocol #88, 03.10.2023), and all participants signed informed consent forms.\\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\\u003eCompeting interests\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe authors declare that they have no competing interests.\\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\n\\u003cli\\u003eShi M, Wei J, Dong J, Meng W, Ma J, Wang T, Wang N, Wang Y. Function of interleukin-17 and -35 in the blood of patients with hepatitis B-related liver cirrhosis. Mol Med Rep. 2015;11(1):121-6. doi: 10.3892/mmr.2014.2681. \\u003c/li\\u003e\\n\\u003cli\\u003eBaumert TF, Thimme R, von Weizs\\u0026auml;cker F. Pathogenesis of hepatitis B virus infection. World J Gastroenterol. 2007;13(1):82-90. doi: 10.3748/wjg.v13.i1.82. \\u003c/li\\u003e\\n\\u003cli\\u003eWorld Health Organization (WHO). Chronic Viral Hepatitis. Available online: https://www.who.int/news-room/fact-sheets/detail/hepatitis-b (accessed on 30 September 2025)\\u003c/li\\u003e\\n\\u003cli\\u003eRaimondo G, Allain JP, Brunetto MR, Buendia MA, Chen DS, Colombo M, Crax\\u0026igrave; A, Donato F, Ferrari C, Gaeta GB, Gerlich WH, Levrero M, Locarnini S, Michalak T, Mondelli MU, Pawlotsky JM, Pollicino T, Prati D, Puoti M, Samuel D, Shouval D, Smedile A, Squadrito G, Tr\\u0026eacute;po C, Villa E, Will H, Zanetti AR, Zoulim F. 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Russ J Infect Immun. 2025;15(1):3. \\u003c/li\\u003e\\n\\u003cli\\u003eArababadi MK, Pourfathollah AA, Jafarzadeh A, Hassanshahi G. Serum Levels of IL-10 and IL-17A in Occult HBV-Infected South-East Iranian Patients. Hepat Mon. 2010;10(1):31-35.\\u003c/li\\u003e\\n\\u003cli\\u003eArababadi MK, Pourfathollah AA, Jafarzadeh A, Hassanshahi G, Daneshmandi S, Shamsizadeh A, Kennedy D. Non-association of IL-12 +1188 and IFN-\\u0026gamma; +874 polymorphisms with cytokines serum level in occult HBV infected patients. Saudi J Gastroenterol. 2011;17(1):30-35. doi: 10.4103/1319-3767.74461.\\u003c/li\\u003e\\n\\u003cli\\u003eLiu X, Chen SX, Liu H, Lou JL. Host immunity and HBV S gene mutation in HBsAg-negative HBV-infected patients. Front Immunol. 2023;14:1211980. doi: 10.3389/fimmu.2023.1211980.\\u003c/li\\u003e\\n\\u003cli\\u003eArsentieva NA, Lyubimova NE, Batsunov OK, Semenov AV, Totolian AA. Analysis of blood plasma cytokine profile in healthy residents of the Republic of Guinea. 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Up-regulation of NK cytotoxic activity via IL-15 induction by different viruses: a comparative study. J Immunol. 1999;163(8):4473-4480.\\u003c/li\\u003e\\n\\u003cli\\u003eRicher MJ, Pewe LL, Hancox LS, Hartwig SM, Varga SM, Harty JT. Inflammatory IL-15 is required for optimal memory T cell responses. J Clin Invest. 2015;125(9):3477-3490. doi: 10.1172/JCI81261.\\u003c/li\\u003e\\n\\u003cli\\u003eSetoguchi R. IL-15 boosts the function and migration of human terminally differentiated CD8+ T cells by inducing a unique gene signature. Int Immunol. 2016;28(6):293-305. doi: 10.1093/intimm/dxw004.\\u003c/li\\u003e\\n\\u003cli\\u003eWaldmann TA. The biology of interleukin-2 and interleukin-15: implications for cancer therapy and vaccine design. Nat Rev Immunol. 2006;6(8):595-601. doi: 10.1038/nri1901.\\u003c/li\\u003e\\n\\u003cli\\u003eGol-Ara M, Jadidi-Niaragh F, Sadria R, Azizi G, Mirshafiey A. The role of different subsets of regulatory T cells in immunopathogenesis of rheumatoid arthritis. Arthritis. 2012;2012:805875. doi: 10.1155/2012/805875.\\u003c/li\\u003e\\n\\u003cli\\u003eVazquez MI, Catalan-Dibene J, Zlotnik A. B cells responses and cytokine production are regulated by their immune microenvironment. Cytokine. 2015;74(2):318-326. doi: 10.1016/j.cyto.2015.02.007.\\u003c/li\\u003e\\n\\u003cli\\u003eAlatrakchi N. Bregs in Chronic HBV: Is It Time for Bragging Rights? Dig Dis Sci. 2015;60(5):1115-1117. doi: 10.1007/s10620-015-3584-1.\\u003c/li\\u003e\\n\\u003cli\\u003eHou W, Kang HS, Kim BS. Th17 cells enhance viral persistence and inhibit T cell cytotoxicity in a model of chronic virus infection. J Exp Med. 2009;206(2):313-328. doi: 10.1084/jem.20082030.\\u003c/li\\u003e\\n\\u003cli\\u003eMartin CM, Welge JA, Shire NJ, Shata MT, Sherman KE, Blackard JT. Cytokine expression during chronic versus occult hepatitis B virus infection in HIV co-infected individuals. Cytokine. 2009;47(3):194-198. doi: 10.1016/j.cyto.2009.06.005.\\u003c/li\\u003e\\n\\u003cli\\u003eDudakov JA, Hanash AM, van den Brink MR. Interleukin-22: immunobiology and pathology. Annu Rev Immunol. 2015;33:747-785. doi: 10.1146/annurev-immunol-032414-112123.\\u003c/li\\u003e\\n\\u003cli\\u003eRubinstein A, et al. CXCR3-Expressing T Cells in Infections and Autoimmunity. Front Biosci (Landmark Ed). 2024;29(8):301. doi: 10.31083/j.fbl2908301.\\u003c/li\\u003e\\n\\u003cli\\u003eArsentieva NA, Batsunov OK, Lyubimova NE, Basina VV, Esaulenko EV, Totolian AA. Cytokine profiling of plasma in patients with viral hepatitis C. Med Immunol (Russia). 2024;26(6):1235-1248. doi: 10.15789/1563-0625-CPO-3117.\\u003c/li\\u003e\\n\\u003cli\\u003eArsentieva NA, Korobova ZR, Batsunov OK, Lyubimova NE, Basina VV, Esaulenko EV, Totolian AA. CX3CL1/Fractalkine: A Potential Biomarker for Liver Fibrosis in Chronic HBV Infection. Curr Issues Mol Biol. 2024;46(9):9948-9957. doi: 10.3390/cimb46090593.\\u003c/li\\u003e\\n\\u003cli\\u003eSauter KA, Pridans C, Sehgal A, Tsai YT, Bradford BM, Raza S, Moffat L, Gow DJ, Beard PM, Mabbott NA, Smith LB, Hume DA. Pleiotropic effects of extended blockade of CSF1R signaling in adult mice. J Leukoc Biol. 2014;96(2):265-274. doi: 10.1189/jlb.2A0114-006R.\\u003c/li\\u003e\\n\\u003cli\\u003eRadmanić L, Zidovec-Lepej S. The Role of Stem Cell Factor, Epidermal Growth Factor and Angiopoietin-2 in HBV, HCV, HCC and NAFLD. Life (Basel). 2022;12(12):2072. doi: 10.3390/life12122072.\\u003c/li\\u003e\\n\\u003cli\\u003eChen J, Zeng F, Forrester SJ, Eguchi S, Zhang MZ, Harris RC. Expression and Function of the Epidermal Growth Factor Receptor in Physiology and Disease. Physiol Rev. 2016;96(3):1025-1069. doi: 10.1152/physrev.00030.2015.\\u003c/li\\u003e\\n\\u003cli\\u003eRestifo NP, Dudley ME, Rosenberg SA. Adoptive immunotherapy for cancer: harnessing the T cell response. Nat Rev Immunol. 2012;12(4):269-281. doi: 10.1038/nri3191.\\u003c/li\\u003e\\n\\u003cli\\u003eBhardwaj N, Friedlander PA, Pavlick AC, Ernstoff MS, Ibrahim N, Hodi FS, ... \\u0026amp; Dhodapkar MV. Flt3 ligand augments immune responses to anti-DEC-205-NY-ESO-1 vaccine through expansion of dendritic cell subsets. Nat Cancer. 2020;1(12):1204-1217. doi: 10.1038/s43018-020-00143-y.\\u003c/li\\u003e\\n\\u003cli\\u003eKorobova ZR, Arsentieva NA, Totolian AA. Macrophage-Derived Chemokine MDC/CCL22: An Ambiguous Finding in COVID-19. Int J Mol Sci. 2023;24(17):13083. doi: 10.3390/ijms241713088.\\u003c/li\\u003e\\n\\u003c/ol\\u003e\"}],\"fulltextSource\":\"\",\"fullText\":\"\",\"funders\":[],\"hasAdminPriorityOnWorkflow\":false,\"hasManuscriptDocX\":true,\"hasOptedInToPreprint\":true,\"hasPassedJournalQc\":\"\",\"hasAnyPriority\":false,\"hideJournal\":false,\"highlight\":\"\",\"institution\":\"\",\"isAcceptedByJournal\":false,\"isAuthorSuppliedPdf\":false,\"isDeskRejected\":\"\",\"isHiddenFromSearch\":false,\"isInQc\":false,\"isInWorkflow\":false,\"isPdf\":false,\"isPdfUpToDate\":true,\"isWithdrawnOrRetracted\":false,\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"bmc-infectious-diseases\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"infd\",\"sideBox\":\"Learn more about [BMC Infectious Diseases](http://bmcinfectdis.biomedcentral.com/)\",\"snPcode\":\"\",\"submissionUrl\":\"https://www.editorialmanager.com/infd\",\"title\":\"BMC Infectious Diseases\",\"twitterHandle\":\"#bmcinfectdis\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"em\",\"reportingPortfolio\":\"BMC Series\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":true},\"keywords\":\"viral hepatitis B, occult HBV, cytokines, multiplex analysis, biomarkers\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-7846341/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-7846341/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003ch2\\u003eBackground\\u003c/h2\\u003e \\u003cp\\u003eHepatitis B virus (HBV) infection is a serious public health threat and one of the leading causes of acute, chronic and occult hepatitis (OBI). Standard diagnostics that detect HBsAg are insufficient for identifying OBI, defined by the presence of hepatic DNA in the absence of detectable serum HBsAg. Accumulating evidence indicate that the inadequate immune responses are responsible for HBV persistency. Cytokines are known to be important chemical mediators that regulate the differentiation, proliferation and function of immune cells. The goal of this study is to investigate the cytokine signature in OBI patients.\\u003c/p\\u003e\\u003ch2\\u003eMethods\\u003c/h2\\u003e \\u003cp\\u003eThe study initially enrolled 6,773 healthy volunteers, after excluding individuals under 18 years of age, hepatitis B marker testing revealed 57 cases of OBI. As controls, 37 healthy donors with the absence of viral hepatitis markers, HIV, and somatic diseases were selected from the same initial cohort. Immune mediators (cytokines, chemokines, and growth factors) in blood plasma were measured with the MAGPIX multiplex analysis.\\u003c/p\\u003e\\u003ch2\\u003eResults\\u003c/h2\\u003e \\u003cp\\u003eWe found high levels of IFNα, IFNγ, IL-1α, IL-2, IL-10, IL-15, IL-17A, IL-22, CXCL9/MIG and growth factors (EGF, FLT-3L, TGFα, G-CSF, M-CSF, VEGF) in OBI patients. Based on anti-HBsAg IgG positivity, patients with OBI were separated into two groups; seropositive cohort demonstrated an increase in CCL22/MDC. ROC analysis indicates that M-CSF, FLT-3L, G-CSF, EGF, and TGFα possess high diagnostic potential as biomarkers for OBI. Based on the results of decision tree, we established that combined detection of M-CSF and FLT-3L is more valuable in terms OBI diagnostic.\\u003c/p\\u003e\\u003ch2\\u003eConclusions\\u003c/h2\\u003e \\u003cp\\u003eOBI is characterized by a dominant anti-inflammatory and pro-fibrotic background, mediated by cytokines such as IL-10 and TGF-α, which facilitates viral persistence and promotes liver fibrosis despite the concurrent elevation of some pro-inflammatory signals. The activation of growth factors like TGF-α and EGF drives aberrant tissue repair, resulting in incomplete regeneration and scarring. The roles of FLT-3L and IL-22 appear dual, mediating hepatoprotection while simultaneously contributing to fibrotic progression. ROC and decision tree analysis indicates that several cytokines possess high diagnostic potential as biomarkers for OBI.\\u003c/p\\u003e\",\"manuscriptTitle\":\"Cytokine Signature behind Occult Hepatitis B Virus Infection\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2026-02-12 13:53:40\",\"doi\":\"10.21203/rs.3.rs-7846341/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0},{\"type\":\"editorInvitedReview\",\"content\":\"\",\"date\":\"2026-02-20T11:29:29+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"51156309118106351818876750134753003170\",\"date\":\"2026-02-11T11:45:43+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewersInvited\",\"content\":\"\",\"date\":\"2026-02-09T03:03:56+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorInvited\",\"content\":\"\",\"date\":\"2025-10-15T17:36:24+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorAssigned\",\"content\":\"\",\"date\":\"2025-10-15T00:16:57+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"checksComplete\",\"content\":\"\",\"date\":\"2025-10-15T00:16:31+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"submitted\",\"content\":\"BMC Infectious Diseases\",\"date\":\"2025-10-13T08:22:04+00:00\",\"index\":\"\",\"fulltext\":\"\"}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"bmc-infectious-diseases\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"infd\",\"sideBox\":\"Learn more about [BMC Infectious Diseases](http://bmcinfectdis.biomedcentral.com/)\",\"snPcode\":\"\",\"submissionUrl\":\"https://www.editorialmanager.com/infd\",\"title\":\"BMC Infectious Diseases\",\"twitterHandle\":\"#bmcinfectdis\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"em\",\"reportingPortfolio\":\"BMC Series\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":true}}],\"origin\":\"\",\"ownerIdentity\":\"7cebe0ac-360d-4786-8a01-85f827e015ed\",\"owner\":[],\"postedDate\":\"February 12th, 2026\",\"published\":true,\"recentEditorialEvents\":[],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"under-review\",\"subjectAreas\":[],\"tags\":[],\"updatedAt\":\"2026-02-12T13:53:40+00:00\",\"versionOfRecord\":[],\"versionCreatedAt\":\"2026-02-12 13:53:40\",\"video\":\"\",\"vorDoi\":\"\",\"vorDoiUrl\":\"\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-7846341\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-7846341\",\"identity\":\"rs-7846341\",\"version\":[\"v1\"]},\"buildId\":\"XKTyCvWXoU3ODBz1xrDgd\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}