Differential Gene Profiling of Epstein-Barr Virus and Human Endogenous Retrovirus in Peripheral Blood Mononuclear Cells of Patients with Systemic Lupus Erythematosus: Implications for Immune Response

Differential Gene Profiling of Epstein-Barr Virus and Human Endogenous Retrovirus in Peripheral Blood Mononuclear Cells of Patients with Systemic Lupus Erythematosus: Implications for Immune Response | 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 Article Differential Gene Profiling of Epstein-Barr Virus and Human Endogenous Retrovirus in Peripheral Blood Mononuclear Cells of Patients with Systemic Lupus Erythematosus: Implications for Immune Response Yesit Bello Lemus, Gustavo Aroca Martínez, Lisandro Pacheco Lugo, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4361087/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 30 Aug, 2024 Read the published version in Scientific Reports → Version 1 posted 12 You are reading this latest preprint version Abstract Systemic lupus erythematosus (SLE) is a multifactorial disease characterized by the convergence of genetic, immunological, and viral elements resulting in a complex interaction of both internal and external factors. Research has recognized the role that play the Epstein-Barr virus (EBV) and Human endogenous retrovirus (HERV-E) as triggers and maintenance elements in the disease. A fundamental study area stands out in the dynamics between these viral agents and their physiopathology to unveil their influence in SLE development and progress. This study aimed at assessing the differential expression of immune regulatory genes and the incidence of specific viral pathogens (EBV and HERV-E), alongside the detailed characterization of surface markers in T- and B-lymphocytes in patients with SLE and control participants. A comparative analysis between patients with SLE and control participants was performed, evaluating the expression of phenotypic markers and genes involved in the immune response (TNF-α, IL-2, IL-6, IL-10, IFNG, TLR3), as well as HERV-E gag and EBV viral genes (LMP1 and BZLF1). A significant association between SLE and EBV was found in this study, with a marked increase in EBV LMP1 gene expression and a marked reduction in IFN-γ levels in patients with SLE. Also, a significant overexpression of HERV-E was observed, in addition to a considerable increase in the distribution of the cell surface marker CD27 + on T- and B-lymphocytes, observed in individuals with SLE compared to the control group. This study provides evidence regarding the role that EBV virus plays in lymphocytes in the context of SLE, highlighting how both the virus and the host gene expression may influence disease pathogenesis by altering immune regulatory pathways mediated by TNF-α, IFN-γ, and IL-10, as well as parallel overexpression of HERV-E gag. Biological sciences/Genetics Biological sciences/Immunology Health sciences/Nephrology Health sciences/Rheumatology Lupus T lymphocytes B lymphocytes Epstein-Barr virus (EBV) Human endogenous retrovirus (HERV-E) Figures Figure 1 Figure 2 Figure 3 1. Introduction Systemic lupus erythematosus (SLE) is a complex autoimmune disease whose progress is influenced by a series of multifactorial elements. The production of autoantibodies against nuclear antigens and the presence of antiphospholipid antibodies are crucial, thus triggering inflammatory and thrombotic processes. Among the most severe and prognostically unfavorable tissue manifestations of SLE is lupus nephritis (LN), affecting 50–70% of patients 1–3 . In SLE, chronic inflammation plays a vital role in the expression of human endogenous retrovirus elements group E (HERV-E) that are integrated into the human genome, with the possibility of exacerbation under altered immune conditions 4 . Viral infections, especially with the Epstein-Barr virus (EBV), contribute to an abnormal activation of the immune system and destabilization of the immune balance in susceptible individuals. These pathogens can serve as initial triggers and perpetuating factors in the autoimmune response, thus intensifying the production of autoantibodies and the dysregulation of T- and B-lymphocytes 5–7 . In this context, the immune system of patients with SLE is characterized by hypersensitivity, in which minor stimuli, including viral infections and inflammatory responses, may result in an exaggerated immunologic reaction. This interaction between inflammation, the expression of endogenous retroviruses, and genetic and environmental factors highlights the complex and unpredictable nature of SLE 8–10 . Despite the complex pathophysiological heterogeneity of SLE, the underlying mechanisms are not yet fully defined 11,12 . Among the immune-regulatory mechanisms, IL-6 and IL-10 cytokines, tumor necrosis factor-α (TNF-α), and interferon gamma (IFN-γ) are disrupted in SLE 13 . IL-10 is a powerful regulator of B lymphocytes, and may be negatively regulated by IFN-γ, which is overexpressed in SLE 14,15 . The environmental factors that may have an impact on the abovementioned elements include the virome, regarded as a subset of the human genome that encompasses all microscopic organisms associated with the human body, both in healthy individuals and patients suffering from a disease 16 . As for viral infections, EBV and cytomegalovirus (CMV), and genomic viral elements, such as HERV-E are considered potential factors related to SLE, involving lytic cycles between shorter periods, with autoantigenic cross-reactivity in the case of EBV and CMV 8,9 , while HERV-E is associated with global hypomethylation states, thus allowing for a greater expression of HERV-E mRNA. EBV dysregulation has been associated with the development of autoimmune diseases 4,17 ; after the early lytic infection, EBV establishes a latent and persistent infection in memory B cells. In this latency state, the virus remains immortalized within the host cells throughout the individual's life, alternating between phases of lytic activity and periods of latency, with occasional reactivation 5 . This study focuses on the description of the relative expression of human immune regulation genes (TNFA, IL-6, IL-10, IFNG, and TLR3), HERV-E gag, and EBV viral genes (LMP1 and BZLF1) related to the latency and reactivation activities, respectively. All these aspects are evaluated in peripheral blood mononuclear cells (PMBC), in addition to a phenotypic characterization of T- and B-lymphocyte subpopulations in patients with SLE and healthy individuals within a study population. 2. Method 2.1. Study Population Four ml of venous whole blood was collected in vacutainer tubes with EDTA anticoagulant from a total of 55 patients with SLE and 61 healthy control individuals. Patients diagnosed with SLE met the criteria established by the American College of Rheumatology 18 and were selected from a clinic in Barranquilla, Colombia. Participants recruited for the control group were individuals with no reported autoimmune diseases. Patients and control individuals showing the presence of infectious processes at the moment of sampling were excluded, as well as those who did not give their consent to participate in the study. The study was approved by the Ethics Committee in Clinical Research of the Costa S.A.S., in the city of Barranquilla, Colombia, on September 22, 2022, through Minute No. 390. All study participants accepted and signed the informed consent. 2.2. Total RNA Extraction Total RNA extraction was performed from 300 µl of peripheral blood from patients and control individuals and preserving it in EDTA at 4°C, using TRIzol™ reagent (Invitrogen™) as indicated by 19 . The extracted RNA product was later eluted in 50 µl of nuclease-free water and treated with (2 U) DNAse I (Promega™) incubated at 37°C for 30 minutes. DNAse was heated for 10 minutes at 85°C to inactivate it. 2.3. RT-PCR The relative gene expression of genes (TNFA; IL-2; IL-6; IL-10; IFNG; TLR3, HERV-E gag; LMP1, and BZLF1) together with a normalizing gene (GAPDH) was assessed using real-time reverse transcription-polymerase chain reaction (RT-PCR), and direct identification of the presence of EBV infection was measured with quantitative PCR (qPCR) by detection of the viral gene LMP1. Specific primers used in the study are indicated in Table 1 . Table 1 Primer sequences used in the study for expression assays. Gene Forward and Reverse Primers GAPDH 5´ GAAAAACTCGGCATCACCAT 3´ 5´ CCAGACCGTCAAAGAAACC 3´ TNFA 5´CTTCTGCCTGCTGCACTTTG3´ 5´CCTCAGCTTGAGGGTTTGCT3´ IFNG 5´AGTTATATCTTGGCTTTTCA3´ 5´ACCGAATAATTAGTCAGCTT3´ IL_6 5´GGTACATCCTCGACGGCATCT3´ 5´GTGCCTCTTTGCTGCTTTCAC3´ IL_10 5´ATGCCCCAAGCTGAGAACCAAGACCCA3´ 5´TCTCAAGGGGCTGGGTCAGCTATCCCA3´ TLR3 5´GGGAGACAGCCGTAGTAGAT3´ 5´TCCACTGATACAGACACCTCC3´ HERV-E gag 5´CACATGGTGGAG AGTCGTGTTT3´ 5´GCTTGCGGCTTTTCAGTATAGG3´ LMP1 5´CCCTTTGTATACTCCTACTGATGATCAC3´ 5´ACCCGAAGATGAACAGCACAAT3´ BZLF1 5´ACGCACACGGAAACCACAA3´ 5´CTTAAACTTGGCCCGGCATT3´ Based on the purified RNA products, RT-qPCR was performed in a total reaction volume of 20 µl, using 2 µl of RNA template and 10 µl of the iTaq™ Universal SYBR® Green Supermix (BIO-RAD, USA) (containing 0.2 mM dNTPs, 2 U of iTaq™ DNA Polymerase, 1.5 mM MgCl2, and SYBR® Green I), as well as 2 U of RT enzyme (BIO-RAD). In addition, 0.5 µM final concentration of each primer pair per reaction was added and used in separate reactions for each gene of interest in the study. Amplification cycles were programmed on the thermal cycler CFX96 TOUCH™ (BIO-RAD) as follows: an initial retrotranscription reaction was carried out at 50°C for 30 minutes, followed by denaturation at 95°C for 1 minute. followed by 50 cycles consisting of a denaturation at 95°C for 20 seconds, annealing at 58°C for 20 seconds, and an extension at 72°C for 10 seconds. Fluorescence was measured at the end of each extension cycle at 72°C. Finally, a melting curve, with a temperature range between 65°C to 95°C (0.5ºC increments) was performed. The change in the relative ARNm expression was estimated with the 2-ΔΔCT method 20 . All reactions were carried out in triplicate. 2.4. Enzyme-linked immunosorbent assay (ELISA) for antibodies to EBV. EBV serology was performed by ELISA, detecting IgG EBNA, EA, VCA, and IgM VCA antibodies (Vircell MICROBIOLOGISTS G1105; G1205; M1005), strictly according to the specifications provided by the manufacturer. The plates were read at a wavelength of 450 nm using a CLARIOstar Plus multimode luminescence microplate reader. 2.5. Flow Cytometry Analysis EDTA-preserved peripheral blood samples from a subset of the study population (5 SLE patients and 5 controls) were used in the flow cytometry assay. A VersaFix solution (Versalyse + 0.2% formaldehyde) and a 1X PBS – 2% BSA solution was used to prepare the samples followed by centrifugation for 8 minutes at 300 x g. The resulting pellet was resuspended in 1X PBS, and the cells were transferred to cytometry tubes. Surface monoclonal antibodies were added to distinguish the total lymphocyte population (T and B lymphocytes) by labeling CD3 and CD19 antigens on T and B lymphocytes, respectively. The determination of CD4 + T, CD8 + T, and B lymphocyte subpopulations—active and inactive—is based on the expression of specific markers. For the T line, anti-CD4, anti-CD8, anti-HLA-DR, and anti-CD38 antibodies were used. For the B line, anti-CD19, anti-CD27, anti-CD24, and anti-CD20 antibodies were used. Details of each fluorophore are described in Table 2 . The cytometric reading was performed once the separation and labeling process was completed using Beckman Coulter flow cytometry equipment (Navios Flow Cytometer). The results were analyzed by Kaluza cytometric analysis software and represented as percentages, reflecting the proportion of cells in each subpopulation in relation to the total number of lymphocytes. Table 2 Presentation of the anti-CD implemented in the detection of cell populations, under the antibody-fluorochrome antigen ratio. Antibody Fluorochrome Detectable cell type and/or activation anti-CD45 ORANGE KROME All hematopoietic cells anti-CD3 ECD T lymphocyte lineage anti-CD81 APC Signal transduction events mediating. Anti-CD4 PC5,5 CD4 + T lymphocyte lineage anti-CD8 FITC CD8 + T lymphocyte lineage anti-HLA-DR PACIFIC BLUE CD8 + T lymphocytes, CD4 + T lymphocytes lineage and active B lymphocytes. anti-CD19 APC 700 B lymphocyte lineage anti-CD20 ALEXA FLOUR 750 Mature B lymphocyte lineage anti-CD25 PE Treg CD4 + T-lymphocytes lineage anti-CD27 PC7 Member of the tumor necrosis factor receptor superfamily. 2.6. Statistical analysis Statistical analysis of all results was conducted using STATGRAPHICS Centurion statistical software, with all data expressed as average values and standard deviation. The differences observed in the expression of genes between patients and control subjects were analyzed using the parametric statistical test (t-test) for data with normal distribution, and the Mann-Whitney test for data with non-normal distributions. To this end, the results of the gene expression were transformed into logarithmic values, for a symmetrical distribution of the data, including normal distribution verification. A t-test was also performed to compare the percentage of the different T- and B-lymphocyte populations with their corresponding CD markers. Statistical significance was accepted when the p-value was < 0.05 with 95% confidence. We confirm that all methods used in this study were conducted in accordance with relevant guidelines and regulations, under the approval of the Scientific Committee of the Faculty of Basic Sciences at Universidad Simón Bolívar. 3. Results We assessed demographic and clinical variables, including age, gender, the Systemic Lupus Erythematosus Disease Activity Index (SLEDAI), and disease duration (Table 3 ). The age and female to male ratio was comparable between the SLE and control groups and the SLEDAI parameter for the patients was 12.3 +/- 8,76. Table 3 Characteristics of the study population: patients (SLE) and control subjects Study Population Sample (n) Age (range), SD Female/Male SLEDAI-2K Years of disease (range), SD SLE 55 37,61 (21–72), +/- 12.15 50/5 12,3 ( 3 – 33 ) +/- 8,76 4,82 ( 1 – 21 ), +/-4,72 Control subjects 61 35,60( 18 – 61 ) +/- 11.08 57/4 N/A N/A Expression profiles of immune and viral Biomarkers . This study explored immunological gene expression signals and EBV infection signatures between patients with SLE and control individuals without autoimmune disorders. We observed a significant reduction in TNF-α expression in patients with SLE compared to control individuals (p < 0.05, Fig. 1 ). Furthermore, we evaluated the relative expression of IL-6, IL-10, IFNG-γ, TLR3, HERV-E gag, LMP1, and BZLF1 from both groups (SLE n = 55; control individuals n = 61), showing significant differences in several of them (Fig. 1 ). In patients with SLE, we identified higher expression of IL-10, HERV-E gag, and LMP1, and lower expression of IFNG and TLR3. While no statistically significant differences were found in the expression of BZLF1 and IL-6 (p > 0.05). EBV Seropositivity in SLE patients. of Regarding the EBV serology, the analysis revealed distinct patterns suggestive of different infection stages. The detection of anti-VCA IgM alongside the absence of anti-EBNA IgG pointed towards primary infection, while the presence of anti-EA IgG indicated an ongoing active infection. Furthermore, the simultaneous presence of antibodies to both VCA and EBNA suggested a past infection (Table 4 ). It's noteworthy that a high proportion of both SLE patients (98%) and control subjects (96%) exhibited seropositivity for EBV antibodies. However, we observed notable differences in viral activity between the two groups. Viral gene expression was detectable in 33% of SLE patients compared to 16% of controls. Moreover, a significant majority of SLE patients (93%) displayed evidence of ongoing EBV infection, contrasting with 64% in the control group. Finally, the prevalence of anti- EBNA IgG and anti-EA IgG was notably higher in SLE patients (Fig. 1 ) supporting an active infection state. Additionally, the expression of viral protein LMP1 was significantly elevated in the SLE group (p < 0.05) again suggesting viral maintenance. Table 4 ELISA test results for the detection of IgG EBNA, IgG EA, and IgG VCA antibodies in patients with SLE and control subjects. Study Groups IgG EBNA IgG EA IgG VCA Classification n (%) SLE +/- - + Previous infection 5,2% + + + Active infection 94,5% - - - negative 1,7% CONTROL +/- - + Previous infection 28,5% + + + Active infection 64% - - - negative 3,2% B -lymphocytes showed a higher expression of TNF receptor . Flow cytometry was performed in a randomly selected subgroup (SLE n = 5 vs control individuals n = 5), obtaining total event readings in the CD45 + pan-leukocyte panel (SLE: x̄ = 111654 ± 10338; control subjects: x̄ = 87275 ± 14235). Both groups showed a similar distribution of CD45 + lymphocytes and in terms of cellular complexity and size. The proportions of CD3 + T and CD19 + B lymphocytes were also comparable in both groups. However, a significant difference in TNF-R expression was observed in CD20 + and CD27 + B lymphocytes (SLE: x̄ = 5.4% ± 2.83; NC: x̄ = 1.10% ± 1.53, p 0.>0.05). 4. Discussion Understanding the pathophysiology of systemic lupus erythematosus (SLE) remains a challenge, given its multifaceted nature involving genetic, immunological, and environmental factors 21–23 . In our study, we sought to shed light on this complex condition by evaluating a cohort of individuals diagnosed with SLE, utilizing the Systemic Lupus Erythematosus Disease Activity Index (SLEDAI) score as a measure of disease activity. Our findings revealed that the SLE group exhibited predominantly active disease, as indicated by an average SLEDAI score of 12 points. Notably, 64% of these individuals presented with classification II, III, and IV nephropathies, with respective proportions of 7%, 26%, and 31% among the total study population. This cohort comprised 50 females and 5 males, with an average disease duration of approximately 5 years. Importantly, we compared our findings with those of a control group lacking SLE, providing valuable insights into the distinctive features of SLE pathogenesis and EBV infection. The role of circulating TNF-α in inflammation is crucial, as it serves as a catalyst for the induction of various proinflammatory molecules and cytokines 24 . However, its involvement in systemic lupus erythematosus (SLE) pathogenesis is complex and somewhat controversial. For instance, studies have reported that TNF-α may contribute to susceptibility to SLE through certain polymorphisms 25 , through elevated serum levels 26 , or by effects on T lymphocytes highly susceptible to TNF-α 27 . Furthermore, dysregulated production of TNF-α and IFN-γ, coupled with aberrant B-cell responses, has been implicated in the immunological dysfunction observed in SLE patients 28 . These findings underscore the intricate interplay between TNF-α and the immune dysregulation characteristic of SLE, shedding light on potential targets for therapeutic intervention. Previous studies show upregulation of these cytokines in Europeans 26,29 ; however, in our study, where our population is different from those studies, we observed that the relative expression of both TNFA and INFG decreased significantly in patients with SLE compared to control individuals 17 , However, TNF-α also functions as an inflammatory mediator and inducer of apoptosis 30 , while deficient TNF-α production leads to the absence of both germinal centers and follicular dendritic cells 31 , which in murine models has been associated with lupus development 32 . For example, these results could be explained by various factors such as infections such as hepatitis virus, HHV, retrovirus, parvovirus B19, or EBV 33–37 , which have been associated with clinical and immunological manifestations similar to those found in SLE. We investigated immune alterations in a dual context of SLE and viral infection. For this, we explored the presence of active or latent EBV infection in all the individuals. Previous studies have demonstrated that during EBV infection, the virus decreases IFN-g response 38–41 . In our study we also show that IFN-g is down regulated in the SLE group as well as having an active viral infection showed by the presence of anti-EBNA, anti-EA, and anti-VCA IgGs (Table 3 ). The reduction of IFN-g by EBV would probably dysregulate the already exacerbated immune response in individuals with SLE maintaining an overstimulated immune activity particular to SLE 6 . In the control group, both IFNG and TNFA are not reduced and would maintain viral expression to low levels as observed in our study where most of the population show seropositivity, but active infection is reduced significantly in the control group. We identified a significantly over expression of LMP1 in patients with SLE compared to control subjects. LMP1 is a viral protein implicated in B-cell transformation and viral maintenance 42 . Similar to our findings, others have demonstrated that EBV infection in individuals with lupus show a 10- to 100-fold higher expression of LMP1 compared to their control groups 43–45 , assessed through the viral load in peripheral blood, the frequency of infected B cells, and the amount of virus in serum. It is also important to highlight that this increase in gene expression seems not to be dependent on immunosuppressive therapy that may be ongoing to treat SLE 43,44,46 . These findings becomes relevant since LMP1 is a latent EBV protein with a high potential for altering cellular signal transduction pathways, including blocking intracellular DNA sensors, such as TLR9, and transcription factors, such as IRF3/7 47 . These are crucial pathways to promote the proliferation of target cells and, simultaneously, interfere with the regulated processes of apoptosis 48 . The influence of LMP1 is exerted through its expression in the plasma membrane, activating signaling pathways, such as NF- κB, protein kinases JNK, and p38 48,49 . In SLE patients, an increase in LMP1 could favor an increase in autoreactive B-cell survival, suggesting a mechanism for the higher activity of immune responses seen in SLE patients 50 . Different HERV-E have been identified more frequently in patients with autoimmune disorders, which suggests that the methylation state of the genome contributes to the modulation of the expression of these retrotransposons. Even more so when DNA hypomethylation has been shown to be involved in the pathogenesis of SLE 51 . Our results show evidence of a significant relative overexpression of HERV-E gag in patients with SLE, also confirmed by other authors showing increased mRNA expression of HERV-E in CD4 + T cells of patients with lupus 4 . Since HERV-E proteins may be structurally similar to autoantigens and trigger autoimmunity through molecular mimicry, potentially serving as a new therapeutic target in lupus 52,53 . There is evidence supporting the role of IL-10 in the promotion of growth and the transformation of auto-reactive B cells into plasma cells in lupus, which, in turn, influences the progress of the disease 54,55 . Our results show an increased expression of this cytokine in patients with SLE. Nonetheless, it is worth highlighting that studies on murine models indicate that IL-10 may also play a protective role in lupus as it has proinflammatory and anti-inflammatory effects 56,57 . This might also explain the lower expression of TNFA- seen in our studies as IL-10 inhibits TNF-α 58,59 . Conversely, the influence of toll-like receptors (TLR) inside the cell, acting as nucleic acid sensors, are an aspect of interest in the pathogenesis of SLE; especially TLR3, which can sense double-stranded RNA (dsRNA) of viral origin, and influence cytokine production by NF-κB signaling pathways 60 . This study reports a considerable decrease in the relative expression of TLR3 in patients with SLE; In the context of an active EBV-mediated infection, the expression of non-polyadenylated RNA forming loop structures through base pairing is observed, simulating dsRNA molecules. This phenomenon triggers signaling through TLR3, which is involved in the production of type 1 interferon (type 1 IFN) 61 . In our lupus patients, despite exhibiting increased activity of EBV viral infection, their TLR3 expression is significantly diminished, which could imply a factor hindering the immune response to the infection and facilitating viral reactivation. However, it has been demonstrated that in SLE patients infected with hepatitis C virus (HCV), the relative expression levels of TLR3 are higher compared to non-lupus controls also infected 62 reflecting the heterogeneity of these patients' response to infections. The results of the distribution of the CD45 + pan-leukocyte panel among cell populations in general (neutrophils, monocytes, and lymphocytes) are an important parameter of association with the state of disease activity 12 . Conversely, an increase in the expression of CD27 in T and B lymphocytes suggests a crucial role in the immune activation process 63,64 . The differences in the distribution of CD27 + B cells are useful for the evaluation of the disease activity in patients with SLE 65 , although a low index of disease inactivity also brings about a greater expression of CD27—both for T and B lymphocytes. The different behaviors and possible effects of over and under-expressed genes in the context of lupus are represented in a unified manner based on the results obtained in Fig. 3 . Taken together, these results provide new perspectives to understand the complex immune interactions in SLE and could pave the way for future research and therapeutic approaches. Our study highlights the way in which dysregulation in cytokine activity and the influence of genetic and viral factors, such as EBV, contribute significantly to the heterogeneity of SLE. The variability observed in the expression of TNFA, IFNG, IL-10, and HERV-E gag among patients with SLE not only reflects the diverse immune response, but also stresses the complexity of underlying mechanisms of this disease. These patterns point to a profoundly altered immune system in SLE, where the interplay between intrinsic and external immune factors, such as viral infections, plays a crucial role in pathogenesis. The fact that different patients with SLE show various responses in terms of cytokine and viral protein expression implies the underlying heterogeneity of the disease, which may be vital for customizing the treatment strategies. These findings are the basis for patient stratification and the development of more targeted therapeutic interventions based on the specific biology of each case of SLE. Declarations Author contributions Y.B.L: Conceptualization, Investigation, Writing - original draft, Writing - review & editing. G.A.M: Conceptualization, Investigation, Supervision. L.P.L: Investigation, Writing - review & editing. L.G.E: Investigation, Supervision. E.Z.P: Conceptualization, Investigation, Writing - review & editing. N.S.L: Investigation, Writing. A.C.B: Conceptualization, Investigation, Supervision. A.J.A-H: Conceptualization, Supervision, Writing - review & editing. E.N.Q: Conceptualization, Investigation, Writing - review & editing. Competing interests The authors declare no competing interests. Correspondence and requests for materials should be addressed to Y.B.L Data Availability The data supporting the findings of this study are available from the corresponding author, Y.B.L., upon request ( [email protected] ). References Karrar, S. & Cunninghame Graham, D. S. Abnormal B Cell Development in Systemic Lupus Erythematosus. Arthritis Rheumatol 70, 496–507 (2018). Lugo, L. P., Olmos, Y. D. & Martínez, G. A. 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Inhibition of IFN-gamma signaling by an Epstein-Barr virus immediate-early protein. Immunity 15, 787–799 (2001). Hohenadl, C. et al. Transcriptional Activation of Endogenous Retroviral Sequences in Human Epidermal Keratinocytes by UVB Irradiation. Journal of Investigative Dermatology 113, 587–594 (1999). Ahsan, N., Kanda, T., Nagashima, K. & Takada, K. Epstein-Barr virus transforming protein LMP1 plays a critical role in virus production. J Virol 79, 4415–4424 (2005). Harley, J. B. & James, J. A. Everyone Comes from Somewhere: Systemic lupus erythematosus (SLE) and Epstein-Barr Virus, induction of host interferon (INF) and humoral anti-EBNA1 immunity. Arthritis Rheum 62, 1571–1575 (2010). Kang, I. et al. Defective control of latent Epstein-Barr virus infection in systemic lupus erythematosus. J Immunol 172, 1287–1294 (2004). Gross, A. J., Hochberg, D., Rand, W. M. & Thorley-Lawson, D. A. EBV and systemic lupus erythematosus: a new perspective. J Immunol 174, 6599–6607 (2005). Moon, U. Y. et al. Patients with systemic lupus erythematosus have abnormally elevated Epstein-Barr virus load in blood. Arthritis Res Ther 6, R295-302 (2004). Bentz, G. L., Shackelford, J. & Pagano, J. S. Epstein-Barr Virus Latent Membrane Protein 1 Regulates the Function of Interferon Regulatory Factor 7 by Inducing Its Sumoylation. J Virol 86, 12251–12261 (2012). Johansson, P., Jansson, A., Rüetschi, U. & Rymo, L. The p38 Signaling Pathway Upregulates Expression of the Epstein-Barr Virus LMP1 Oncogene. J Virol 84, 2787–2797 (2010). Yang, L. et al. EBV-LMP1 targeted DNAzyme enhances radiosensitivity by inhibiting tumor angiogenesis via the JNKs/HIF-1 pathway in nasopharyngeal carcinoma. Oncotarget 6, 5804–5817 (2015). Lam, N. & Sugden, B. LMP1, a viral relative of the TNF receptor family, signals principally from intracellular compartments. EMBO J 22, 3027–3038 (2003). Okada, M. et al. Role of DNA methylation in transcription of human endogenous retrovirus in the pathogenesis of systemic lupus erythematosus. J Rheumatol 29, 1678–1682 (2002). Talotta, R., Atzeni, F. & Laska, M. J. The contribution of HERV-E clone 4 – 1 and other HERV-E members to the pathogenesis of rheumatic autoimmune diseases. APMIS 128, 367–377 (2020). Tugnet, N., Rylance, P., Roden, D., Trela, M. & Nelson, P. Human Endogenous Retroviruses (HERVs) and Autoimmune Rheumatic Disease: Is There a Link? Open Rheumatol J 7, 13–21 (2013). Sugita, K. et al. CD27, a member of the nerve growth factor receptor family, is preferentially expressed on CD45RA + CD4 T cell clones and involved in distinct immunoregulatory functions. J Immunol 149, 3208–3216 (1992). Dörner, T. & Lipsky, P. E. Correlation of circulating CD27high plasma cells and disease activity in systemic lupus erythematosus. Lupus 13, 283–289 (2004). Blenman, K. R. M. et al. IL-10 regulation of lupus in the NZM2410 murine model. Laboratory Investigation 86, 1136–1148 (2006). Ling, G.-S., Cook, H. T., Botto, M., Lau, Y.-L. & Huang, F.-P. An essential protective role of IL-10 in the immunological mechanism underlying resistance vs susceptibility to lupus induction by dendritic cells and dying cells. Rheumatology (Oxford) 50, 1773–1784 (2011). Clarke, C. J. P., Hales, A., Hunt, A. & Foxwell, B. M. J. IL-10-mediated suppression of TNF-α production is independent of its ability to inhibit NFκB activity. European Journal of Immunology 28, 1719–1726 (1998). Maiti, S., Dai, W., Alaniz, R. C., Hahn, J. & Jayaraman, A. Mathematical Modeling of Pro- and Anti-Inflammatory Signaling in Macrophages. Processes 3, 1–18 (2015). Ranjith-Kumar, C. T. et al. Effects of single nucleotide polymorphisms on Toll-like receptor 3 activity and expression in cultured cells. J Biol Chem 282, 17696–17705 (2007). Iwakiri, D. et al. Epstein-Barr virus (EBV)-encoded small RNA is released from EBV-infected cells and activates signaling from Toll-like receptor 3. J Exp Med 206, 2091–2099 (2009). Razin, M. et al. TLR3\TLR7 as Differentially Expressed Markers Among Viral, Nonviral, and Autoimmune Diseases in Egyptian Patients. Viral Immunol 34, 607–621 (2021). Eliopoulos, A. G. & Young, L. S. LMP1 structure and signal transduction. Semin Cancer Biol 11, 435–444 (2001). Caielli, S. et al. A CD4 + T cell population expanded in lupus blood provides B cell help through interleukin-10 and succinate. Nat Med 25, 75–81 (2019). Geginat, J. et al. IL-10 producing regulatory and helper T-cells in systemic lupus erythematosus. Seminars in Immunology 44, 101330 (2019). Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 30 Aug, 2024 Read the published version in Scientific Reports → Version 1 posted Reviews received at journal 22 Jul, 2024 Reviewers agreed at journal 17 Jul, 2024 Reviews received at journal 15 Jul, 2024 Reviewers agreed at journal 15 Jul, 2024 Reviews received at journal 03 Jun, 2024 Reviewers agreed at journal 28 May, 2024 Reviewers agreed at journal 28 May, 2024 Reviewers invited by journal 23 May, 2024 Editor assigned by journal 23 May, 2024 Editor invited by journal 23 May, 2024 Submission checks completed at journal 23 May, 2024 First submitted to journal 02 May, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4361087","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":309993388,"identity":"1347a29c-91c2-45c5-ae6c-1a75572b1851","order_by":0,"name":"Yesit Bello Lemus","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABEElEQVRIie3QsUrEMBjA8a8Evi5t3STHofURIgeHcENfpeGgXbq5FBQNCHH0AcT3cKwE2iUPcHAHVoRzEvoEYtITEWwPR4f86ZT0V76vAC7XP62yT+SD1wJQwN0h2U8qQ5AAYX8m8EWQ/jgbJ6y5fVEdbI6RkPoifDxLokNVt1AuuPBVNUi0Zmaw7QwJZutQUy6nWc5A51wEWTpIVoXdRXFJgvk6lDTFaTGnnlRc0IANkue31pJrS84NSXbkYw9ZgR1MpWgIMcSTPRHjZKILVmm2PZUEl5MH2e+S0bTOZ3Jkl6hpXruy3MQH/s1T9y6vkvh+WdPucnF0N/LHTvrTXwPYz+PQ+6ZYjFy4XC6X67tPQnhbjamqFG0AAAAASUVORK5CYII=","orcid":"","institution":"Universidad Simón Bolívar","correspondingAuthor":true,"prefix":"","firstName":"Yesit","middleName":"Bello","lastName":"Lemus","suffix":""},{"id":309993390,"identity":"a8bed63e-7ce1-47e3-9993-45d9e3c74e6d","order_by":1,"name":"Gustavo Aroca Martínez","email":"","orcid":"","institution":"Clínica de la Costa","correspondingAuthor":false,"prefix":"","firstName":"Gustavo","middleName":"Aroca","lastName":"Martínez","suffix":""},{"id":309993391,"identity":"2426b4bb-da3b-4c73-a244-3d9e7ed09476","order_by":2,"name":"Lisandro Pacheco Lugo","email":"","orcid":"","institution":"Universidad Simón Bolívar","correspondingAuthor":false,"prefix":"","firstName":"Lisandro","middleName":"Pacheco","lastName":"Lugo","suffix":""},{"id":309993392,"identity":"8db8c7cf-2871-4f8f-a255-a8f039068fd2","order_by":3,"name":"Lorena Gómez Escorcia","email":"","orcid":"","institution":"Clínica de la Costa","correspondingAuthor":false,"prefix":"","firstName":"Lorena","middleName":"Gómez","lastName":"Escorcia","suffix":""},{"id":309993393,"identity":"8287f6d5-17e3-4fb9-81e5-d686fc1f0625","order_by":4,"name":"Eloína Zarate Peñata","email":"","orcid":"","institution":"Universidad Simón Bolívar","correspondingAuthor":false,"prefix":"","firstName":"Eloína","middleName":"Zarate","lastName":"Peñata","suffix":""},{"id":309993394,"identity":"6d66dc69-b52b-47e8-a7e8-ba7f648b88f9","order_by":5,"name":"Nataly Solano Llanos","email":"","orcid":"","institution":"Universidad Simón Bolívar","correspondingAuthor":false,"prefix":"","firstName":"Nataly","middleName":"Solano","lastName":"Llanos","suffix":""},{"id":309993396,"identity":"9302dfd1-81ca-40fa-a044-d21e064ccc7a","order_by":6,"name":"Andres Cadena Bonfanti","email":"","orcid":"","institution":"Clínica de la Costa","correspondingAuthor":false,"prefix":"","firstName":"Andres","middleName":"Cadena","lastName":"Bonfanti","suffix":""},{"id":309993398,"identity":"6e241cef-1fbc-4f3a-83a5-cb0c34117443","order_by":7,"name":"Antonio J. Acosta-Hoyos","email":"","orcid":"","institution":"Universidad Simón Bolívar","correspondingAuthor":false,"prefix":"","firstName":"Antonio","middleName":"J.","lastName":"Acosta-Hoyos","suffix":""},{"id":309993399,"identity":"84d38c04-48ba-411e-b03b-17ee0fb28092","order_by":8,"name":"Elkin Navarro Quiroz","email":"","orcid":"","institution":"Universidad Simón Bolívar","correspondingAuthor":false,"prefix":"","firstName":"Elkin","middleName":"Navarro","lastName":"Quiroz","suffix":""}],"badges":[],"createdAt":"2024-05-02 21:54:34","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4361087/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4361087/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-024-70913-6","type":"published","date":"2024-08-30T15:57:21+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":57952414,"identity":"e03b6698-2c0f-447c-ad30-4695e3d0cde4","added_by":"auto","created_at":"2024-06-07 22:56:33","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":49219,"visible":true,"origin":"","legend":"\u003cp\u003eBox-whisker plot of relative expression of genes (A) (TNF-α; TLR3; IFN-alfa; IL-06; IL-10) (HERV- E gag, LMP1, and BZLF1), (B) ratio of circulating plasma IgG EBNA, and IgG EA in patients (SLE) and control subjects (CN).\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4361087/v1/79fd8d19b0405239b89124f5.png"},{"id":57952413,"identity":"1a59b437-1642-4aa6-8457-ac67157ff1fb","added_by":"auto","created_at":"2024-06-07 22:56:33","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":123588,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of cell populations and their surface markers CD20+ (B lymphocyte); CD4+ (T helper lymphocyte); CD3+ (T lymphocyte); CD27+ (tumor necrosis factor receptor; TNF). Box-whisker plot of percentage distribution (%) of cell surface markers in patients (SLE) and control subjects (CN): A: CD4+ T lymphocytes expressing CD27+. CD20+ B lymphocytes expressing CD27+.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-4361087/v1/6b4958b84bc420cecd7723c8.png"},{"id":57953524,"identity":"87d3bee5-8261-4b49-bc62-e33e357fb797","added_by":"auto","created_at":"2024-06-07 23:04:33","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":67119,"visible":true,"origin":"","legend":"\u003cp\u003eOutline of relative gene expression (TNFA; TLR3; IFNG; IL-10; HERV- E gag, LMP1) showing imbalance in the context of patients with Systemic Lupus Erythematosus (SLE). The arrow and red bars represent the critical points of affectation in patients with SLE. Created with BioRender.com.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-4361087/v1/9034255e663b4b5273f01b67.png"},{"id":63820827,"identity":"44b5f67a-bd73-4b4a-a6eb-9c21c86cb87f","added_by":"auto","created_at":"2024-09-02 16:09:11","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":786444,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4361087/v1/977d1463-2968-4b68-a57b-fda984596e5a.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Differential Gene Profiling of Epstein-Barr Virus and Human Endogenous Retrovirus in Peripheral Blood Mononuclear Cells of Patients with Systemic Lupus Erythematosus: Implications for Immune Response","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eSystemic lupus erythematosus (SLE) is a complex autoimmune disease whose progress is influenced by a series of multifactorial elements. The production of autoantibodies against nuclear antigens and the presence of antiphospholipid antibodies are crucial, thus triggering inflammatory and thrombotic processes. Among the most severe and prognostically unfavorable tissue manifestations of SLE is lupus nephritis (LN), affecting 50\u0026ndash;70% of patients \u003csup\u003e1\u0026ndash;3\u003c/sup\u003e. In SLE, chronic inflammation plays a vital role in the expression of human endogenous retrovirus elements group E (HERV-E) that are integrated into the human genome, with the possibility of exacerbation under altered immune conditions \u003csup\u003e4\u003c/sup\u003e. Viral infections, especially with the Epstein-Barr virus (EBV), contribute to an abnormal activation of the immune system and destabilization of the immune balance in susceptible individuals. These pathogens can serve as initial triggers and perpetuating factors in the autoimmune response, thus intensifying the production of autoantibodies and the dysregulation of T- and B-lymphocytes \u003csup\u003e5\u0026ndash;7\u003c/sup\u003e. In this context, the immune system of patients with SLE is characterized by hypersensitivity, in which minor stimuli, including viral infections and inflammatory responses, may result in an exaggerated immunologic reaction. This interaction between inflammation, the expression of endogenous retroviruses, and genetic and environmental factors highlights the complex and unpredictable nature of SLE \u003csup\u003e8\u0026ndash;10\u003c/sup\u003e. Despite the complex pathophysiological heterogeneity of SLE, the underlying mechanisms are not yet fully defined \u003csup\u003e11,12\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eAmong the immune-regulatory mechanisms, IL-6 and IL-10 cytokines, tumor necrosis factor-α (TNF-α), and interferon gamma (IFN-γ) are disrupted in SLE \u003csup\u003e13\u003c/sup\u003e. IL-10 is a powerful regulator of B lymphocytes, and may be negatively regulated by IFN-γ, which is overexpressed in SLE\u003csup\u003e14,15\u003c/sup\u003e. The environmental factors that may have an impact on the abovementioned elements include the virome, regarded as a subset of the human genome that encompasses all microscopic organisms associated with the human body, both in healthy individuals and patients suffering from a disease \u003csup\u003e16\u003c/sup\u003e. As for viral infections, EBV and cytomegalovirus (CMV), and genomic viral elements, such as HERV-E are considered potential factors related to SLE, involving lytic cycles between shorter periods, with autoantigenic cross-reactivity in the case of EBV and CMV \u003csup\u003e8,9\u003c/sup\u003e, while HERV-E is associated with global hypomethylation states, thus allowing for a greater expression of HERV-E mRNA. EBV dysregulation has been associated with the development of autoimmune diseases \u003csup\u003e4,17\u003c/sup\u003e; after the early lytic infection, EBV establishes a latent and persistent infection in memory B cells. In this latency state, the virus remains immortalized within the host cells throughout the individual's life, alternating between phases of lytic activity and periods of latency, with occasional reactivation \u003csup\u003e5\u003c/sup\u003e. This study focuses on the description of the relative expression of human immune regulation genes (TNFA, IL-6, IL-10, IFNG, and TLR3), HERV-E gag, and EBV viral genes (LMP1 and BZLF1) related to the latency and reactivation activities, respectively. All these aspects are evaluated in peripheral blood mononuclear cells (PMBC), in addition to a phenotypic characterization of T- and B-lymphocyte subpopulations in patients with SLE and healthy individuals within a study population.\u003c/p\u003e"},{"header":"2. Method","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Study Population\u003c/h2\u003e \u003cp\u003eFour ml of venous whole blood was collected in vacutainer tubes with EDTA anticoagulant from a total of 55 patients with SLE and 61 healthy control individuals. Patients diagnosed with SLE met the criteria established by the American College of Rheumatology \u003csup\u003e18\u003c/sup\u003e and were selected from a clinic in Barranquilla, Colombia. Participants recruited for the control group were individuals with no reported autoimmune diseases. Patients and control individuals showing the presence of infectious processes at the moment of sampling were excluded, as well as those who did not give their consent to participate in the study. The study was approved by the Ethics Committee in Clinical Research of the Costa S.A.S., in the city of Barranquilla, Colombia, on September 22, 2022, through Minute No. 390. All study participants accepted and signed the informed consent.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Total RNA Extraction\u003c/h2\u003e \u003cp\u003eTotal RNA extraction was performed from 300 \u0026micro;l of peripheral blood from patients and control individuals and preserving it in EDTA at 4\u0026deg;C, using TRIzol\u0026trade; reagent (Invitrogen\u0026trade;) as indicated by \u003csup\u003e19\u003c/sup\u003e. The extracted RNA product was later eluted in 50 \u0026micro;l of nuclease-free water and treated with (2 U) DNAse I (Promega\u0026trade;) incubated at 37\u0026deg;C for 30 minutes. DNAse was heated for 10 minutes at 85\u0026deg;C to inactivate it.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. RT-PCR\u003c/h2\u003e \u003cp\u003e The relative gene expression of genes (TNFA; IL-2; IL-6; IL-10; IFNG; TLR3, HERV-E gag; LMP1, and BZLF1) together with a normalizing gene (GAPDH) was assessed using real-time reverse transcription-polymerase chain reaction (RT-PCR), and direct identification of the presence of EBV infection was measured with quantitative PCR (qPCR) by detection of the viral gene LMP1. Specific primers used in the study are indicated in Table\u0026nbsp;\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\u003ePrimer sequences used in the study for expression assays.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGene\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eForward and Reverse Primers\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGAPDH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u0026acute; GAAAAACTCGGCATCACCAT 3\u0026acute;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u0026acute; CCAGACCGTCAAAGAAACC 3\u0026acute;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTNFA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u0026acute;CTTCTGCCTGCTGCACTTTG3\u0026acute;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u0026acute;CCTCAGCTTGAGGGTTTGCT3\u0026acute;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eIFNG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u0026acute;AGTTATATCTTGGCTTTTCA3\u0026acute;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u0026acute;ACCGAATAATTAGTCAGCTT3\u0026acute;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eIL_6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u0026acute;GGTACATCCTCGACGGCATCT3\u0026acute;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u0026acute;GTGCCTCTTTGCTGCTTTCAC3\u0026acute;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eIL_10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u0026acute;ATGCCCCAAGCTGAGAACCAAGACCCA3\u0026acute;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u0026acute;TCTCAAGGGGCTGGGTCAGCTATCCCA3\u0026acute;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTLR3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u0026acute;GGGAGACAGCCGTAGTAGAT3\u0026acute;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u0026acute;TCCACTGATACAGACACCTCC3\u0026acute;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eHERV-E gag\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u0026acute;CACATGGTGGAG AGTCGTGTTT3\u0026acute;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u0026acute;GCTTGCGGCTTTTCAGTATAGG3\u0026acute;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eLMP1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u0026acute;CCCTTTGTATACTCCTACTGATGATCAC3\u0026acute;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u0026acute;ACCCGAAGATGAACAGCACAAT3\u0026acute;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eBZLF1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u0026acute;ACGCACACGGAAACCACAA3\u0026acute;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u0026acute;CTTAAACTTGGCCCGGCATT3\u0026acute;\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\u003eBased on the purified RNA products, RT-qPCR was performed in a total reaction volume of 20 \u0026micro;l, using 2 \u0026micro;l of RNA template and 10 \u0026micro;l of the iTaq\u0026trade; Universal SYBR\u0026reg; Green Supermix (BIO-RAD, USA) (containing 0.2 mM dNTPs, 2 U of iTaq\u0026trade; DNA Polymerase, 1.5 mM MgCl2, and SYBR\u0026reg; Green I), as well as 2 U of RT enzyme (BIO-RAD). In addition, 0.5 \u0026micro;M final concentration of each primer pair per reaction was added and used in separate reactions for each gene of interest in the study.\u003c/p\u003e \u003cp\u003eAmplification cycles were programmed on the thermal cycler CFX96 TOUCH\u0026trade; (BIO-RAD) as follows: an initial retrotranscription reaction was carried out at 50\u0026deg;C for 30 minutes, followed by denaturation at 95\u0026deg;C for 1 minute. followed by 50 cycles consisting of a denaturation at 95\u0026deg;C for 20 seconds, annealing at 58\u0026deg;C for 20 seconds, and an extension at 72\u0026deg;C for 10 seconds. Fluorescence was measured at the end of each extension cycle at 72\u0026deg;C. Finally, a melting curve, with a temperature range between 65\u0026deg;C to 95\u0026deg;C (0.5\u0026ordm;C increments) was performed. The change in the relative ARNm expression was estimated with the 2-ΔΔCT method \u003csup\u003e20\u003c/sup\u003e. All reactions were carried out in triplicate.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Enzyme-linked immunosorbent assay (ELISA) for antibodies to EBV.\u003c/h2\u003e \u003cp\u003eEBV serology was performed by ELISA, detecting IgG EBNA, EA, VCA, and IgM VCA antibodies (Vircell MICROBIOLOGISTS G1105; G1205; M1005), strictly according to the specifications provided by the manufacturer. The plates were read at a wavelength of 450 nm using a CLARIOstar Plus multimode luminescence microplate reader.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5. Flow Cytometry Analysis\u003c/h2\u003e \u003cp\u003eEDTA-preserved peripheral blood samples from a subset of the study population (5 SLE patients and 5 controls) were used in the flow cytometry assay. A VersaFix solution (Versalyse\u0026thinsp;+\u0026thinsp;0.2% formaldehyde) and a 1X PBS \u0026ndash; 2% BSA solution was used to prepare the samples followed by centrifugation for 8 minutes at 300 x g. The resulting pellet was resuspended in 1X PBS, and the cells were transferred to cytometry tubes. Surface monoclonal antibodies were added to distinguish the total lymphocyte population (T and B lymphocytes) by labeling CD3 and CD19 antigens on T and B lymphocytes, respectively. The determination of CD4\u0026thinsp;+\u0026thinsp;T, CD8\u0026thinsp;+\u0026thinsp;T, and B lymphocyte subpopulations\u0026mdash;active and inactive\u0026mdash;is based on the expression of specific markers. For the T line, anti-CD4, anti-CD8, anti-HLA-DR, and anti-CD38 antibodies were used. For the B line, anti-CD19, anti-CD27, anti-CD24, and anti-CD20 antibodies were used. Details of each fluorophore are described in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. The cytometric reading was performed once the separation and labeling process was completed using Beckman Coulter flow cytometry equipment (Navios Flow Cytometer). The results were analyzed by Kaluza cytometric analysis software and represented as percentages, reflecting the proportion of cells in each subpopulation in relation to the total number of lymphocytes.\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\u003ePresentation of the anti-CD implemented in the detection of cell populations, under the antibody-fluorochrome antigen ratio.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAntibody\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFluorochrome\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDetectable cell type and/or activation\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eanti-CD45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eORANGE KROME\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAll hematopoietic cells\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eanti-CD3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eECD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eT lymphocyte lineage\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eanti-CD81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAPC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSignal transduction events mediating.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnti-CD4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePC5,5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCD4\u0026thinsp;+\u0026thinsp;T lymphocyte lineage\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eanti-CD8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFITC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCD8\u0026thinsp;+\u0026thinsp;T lymphocyte lineage\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eanti-HLA-DR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePACIFIC BLUE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCD8\u0026thinsp;+\u0026thinsp;T lymphocytes, CD4\u0026thinsp;+\u0026thinsp;T lymphocytes lineage and active B lymphocytes.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eanti-CD19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAPC 700\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eB lymphocyte lineage\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eanti-CD20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eALEXA FLOUR 750\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMature B lymphocyte lineage\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eanti-CD25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTreg CD4\u0026thinsp;+\u0026thinsp;T-lymphocytes lineage\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eanti-CD27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePC7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMember of the tumor necrosis factor receptor superfamily.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6. Statistical analysis\u003c/h2\u003e \u003cp\u003eStatistical analysis of all results was conducted using STATGRAPHICS Centurion statistical software, with all data expressed as average values and standard deviation. The differences observed in the expression of genes between patients and control subjects were analyzed using the parametric statistical test (t-test) for data with normal distribution, and the Mann-Whitney test for data with non-normal distributions. To this end, the results of the gene expression were transformed into logarithmic values, for a symmetrical distribution of the data, including normal distribution verification. A t-test was also performed to compare the percentage of the different T- and B-lymphocyte populations with their corresponding CD markers. Statistical significance was accepted when the p-value was \u0026lt;\u0026thinsp;0.05 with 95% confidence.\u003c/p\u003e \u003cp\u003e We confirm that all methods used in this study were conducted in accordance with relevant guidelines and regulations, under the approval of the Scientific Committee of the Faculty of Basic Sciences at Universidad Sim\u0026oacute;n Bol\u0026iacute;var.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cp\u003eWe assessed demographic and clinical variables, including age, gender, the Systemic Lupus Erythematosus Disease Activity Index (SLEDAI), and disease duration (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The age and female to male ratio was comparable between the SLE and control groups and the SLEDAI parameter for the patients was 12.3 +/- 8,76.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCharacteristics of the study population: patients (SLE) and control subjects\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=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStudy Population\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSample (n)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAge (range), SD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFemale/Male\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSLEDAI-2K\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eYears of disease (range), SD\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSLE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37,61 (21\u0026ndash;72), +/- 12.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50/5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12,3 (\u003cspan additionalcitationids=\"CR4 CR5 CR6 CR7 CR8 CR9 CR10 CR11 CR12 CR13 CR14 CR15 CR16 CR17 CR18 CR19 CR20 CR21 CR22 CR23 CR24 CR25 CR26 CR27 CR28 CR29 CR30 CR31 CR32\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e)\u003c/p\u003e \u003cp\u003e+/- 8,76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4,82 (\u003cspan additionalcitationids=\"CR2 CR3 CR4 CR5 CR6 CR7 CR8 CR9 CR10 CR11 CR12 CR13 CR14 CR15 CR16 CR17 CR18 CR19 CR20\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e),\u003c/p\u003e \u003cp\u003e+/-4,72\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eControl subjects\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35,60(\u003cspan additionalcitationids=\"CR19 CR20 CR21 CR22 CR23 CR24 CR25 CR26 CR27 CR28 CR29 CR30 CR31 CR32 CR33 CR34 CR35 CR36 CR37 CR38 CR39 CR40 CR41 CR42 CR43 CR44 CR45 CR46 CR47 CR48 CR49 CR50 CR51 CR52 CR53 CR54 CR55 CR56 CR57 CR58 CR59 CR60\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e)\u003c/p\u003e \u003cp\u003e+/- 11.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e57/4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eN/A\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\u003e \u003cb\u003eExpression profiles of immune and viral Biomarkers\u003c/b\u003e. This study explored immunological gene expression signals and EBV infection signatures between patients with SLE and control individuals without autoimmune disorders. We observed a significant reduction in TNF-α expression in patients with SLE compared to control individuals (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Furthermore, we evaluated the relative expression of IL-6, IL-10, IFNG-γ, TLR3, HERV-E gag, LMP1, and BZLF1 from both groups (SLE n\u0026thinsp;=\u0026thinsp;55; control individuals n\u0026thinsp;=\u0026thinsp;61), showing significant differences in several of them (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). In patients with SLE, we identified higher expression of IL-10, HERV-E gag, and LMP1, and lower expression of IFNG and TLR3. While no statistically significant differences were found in the expression of BZLF1 and IL-6 (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e\u003cp\u003eEBV Seropositivity in SLE patients. of Regarding the EBV serology, the analysis revealed distinct patterns suggestive of different infection stages. The detection of anti-VCA IgM alongside the absence of anti-EBNA IgG pointed towards primary infection, while the presence of anti-EA IgG indicated an ongoing active infection. Furthermore, the simultaneous presence of antibodies to both VCA and EBNA suggested a past infection (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). It's noteworthy that a high proportion of both SLE patients (98%) and control subjects (96%) exhibited seropositivity for EBV antibodies. However, we observed notable differences in viral activity between the two groups. Viral gene expression was detectable in 33% of SLE patients compared to 16% of controls. Moreover, a significant majority of SLE patients (93%) displayed evidence of ongoing EBV infection, contrasting with 64% in the control group. Finally, the prevalence of anti- EBNA IgG and anti-EA IgG was notably higher in SLE patients (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) supporting an active infection state. Additionally, the expression of viral protein LMP1 was significantly elevated in the SLE group (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) again suggesting viral maintenance.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eELISA test results for the detection of IgG EBNA, IgG EA, and IgG VCA antibodies in patients with SLE and control subjects.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStudy Groups\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIgG EBNA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIgG EA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIgG VCA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eClassification\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eSLE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e+/-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003ePrevious infection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5,2%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eActive infection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e94,5%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003enegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1,7%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eCONTROL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e+/-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003ePrevious infection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e28,5%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eActive infection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e64%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003enegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3,2%\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\u003e \u003cb\u003eB -lymphocytes showed a higher expression of TNF receptor\u003c/b\u003e. Flow cytometry was performed in a randomly selected subgroup (SLE n\u0026thinsp;=\u0026thinsp;5 vs control individuals n\u0026thinsp;=\u0026thinsp;5), obtaining total event readings in the CD45\u0026thinsp;+\u0026thinsp;pan-leukocyte panel (SLE: x̄ = 111654\u0026thinsp;\u0026plusmn;\u0026thinsp;10338; control subjects: x̄ = 87275\u0026thinsp;\u0026plusmn;\u0026thinsp;14235). Both groups showed a similar distribution of CD45\u0026thinsp;+\u0026thinsp;lymphocytes and in terms of cellular complexity and size. The proportions of CD3\u0026thinsp;+\u0026thinsp;T and CD19\u0026thinsp;+\u0026thinsp;B lymphocytes were also comparable in both groups. However, a significant difference in TNF-R expression was observed in CD20\u0026thinsp;+\u0026thinsp;and CD27\u0026thinsp;+\u0026thinsp;B lymphocytes (SLE: x̄ = 5.4% \u0026plusmn; 2.83; NC: x̄ = 1.10% \u0026plusmn; 1.53, p\u0026thinsp;\u0026lt;\u0026thinsp;0.018, Fig.\u0026nbsp;2). No significant differences were found in HLA-DR, CD25, and CD81 markers (p\u0026thinsp;\u0026gt;\u0026thinsp;0.\u0026gt;0.05).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eUnderstanding the pathophysiology of systemic lupus erythematosus (SLE) remains a challenge, given its multifaceted nature involving genetic, immunological, and environmental factors \u003csup\u003e21\u0026ndash;23\u003c/sup\u003e. In our study, we sought to shed light on this complex condition by evaluating a cohort of individuals diagnosed with SLE, utilizing the Systemic Lupus Erythematosus Disease Activity Index (SLEDAI) score as a measure of disease activity. Our findings revealed that the SLE group exhibited predominantly active disease, as indicated by an average SLEDAI score of 12 points. Notably, 64% of these individuals presented with classification II, III, and IV nephropathies, with respective proportions of 7%, 26%, and 31% among the total study population. This cohort comprised 50 females and 5 males, with an average disease duration of approximately 5 years. Importantly, we compared our findings with those of a control group lacking SLE, providing valuable insights into the distinctive features of SLE pathogenesis and EBV infection.\u003c/p\u003e \u003cp\u003eThe role of circulating TNF-α in inflammation is crucial, as it serves as a catalyst for the induction of various proinflammatory molecules and cytokines \u003csup\u003e24\u003c/sup\u003e. However, its involvement in systemic lupus erythematosus (SLE) pathogenesis is complex and somewhat controversial. For instance, studies have reported that TNF-α may contribute to susceptibility to SLE through certain polymorphisms \u003csup\u003e25\u003c/sup\u003e, through elevated serum levels \u003csup\u003e26\u003c/sup\u003e, or by effects on T lymphocytes highly susceptible to TNF-α \u003csup\u003e27\u003c/sup\u003e. Furthermore, dysregulated production of TNF-α and IFN-γ, coupled with aberrant B-cell responses, has been implicated in the immunological dysfunction observed in SLE patients \u003csup\u003e28\u003c/sup\u003e. These findings underscore the intricate interplay between TNF-α and the immune dysregulation characteristic of SLE, shedding light on potential targets for therapeutic intervention. Previous studies show upregulation of these cytokines in Europeans \u003csup\u003e26,29\u003c/sup\u003e; however, in our study, where our population is different from those studies, we observed that the relative expression of both TNFA and INFG decreased significantly in patients with SLE compared to control individuals \u003csup\u003e17\u003c/sup\u003e, However, TNF-α also functions as an inflammatory mediator and inducer of apoptosis \u003csup\u003e30\u003c/sup\u003e, while deficient TNF-α production leads to the absence of both germinal centers and follicular dendritic cells \u003csup\u003e31\u003c/sup\u003e, which in murine models has been associated with lupus development \u003csup\u003e32\u003c/sup\u003e. For example, these results could be explained by various factors such as infections such as hepatitis virus, HHV, retrovirus, parvovirus B19, or EBV \u003csup\u003e33\u0026ndash;37\u003c/sup\u003e, which have been associated with clinical and immunological manifestations similar to those found in SLE.\u003c/p\u003e \u003cp\u003eWe investigated immune alterations in a dual context of SLE and viral infection. For this, we explored the presence of active or latent EBV infection in all the individuals. Previous studies have demonstrated that during EBV infection, the virus decreases IFN-g response \u003csup\u003e38\u0026ndash;41\u003c/sup\u003e. In our study we also show that IFN-g is down regulated in the SLE group as well as having an active viral infection showed by the presence of anti-EBNA, anti-EA, and anti-VCA IgGs (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The reduction of IFN-g by EBV would probably dysregulate the already exacerbated immune response in individuals with SLE maintaining an overstimulated immune activity particular to SLE \u003csup\u003e6\u003c/sup\u003e. In the control group, both IFNG and TNFA are not reduced and would maintain viral expression to low levels as observed in our study where most of the population show seropositivity, but active infection is reduced significantly in the control group.\u003c/p\u003e \u003cp\u003eWe identified a significantly over expression of LMP1 in patients with SLE compared to control subjects. LMP1 is a viral protein implicated in B-cell transformation and viral maintenance \u003csup\u003e42\u003c/sup\u003e. Similar to our findings, others have demonstrated that EBV infection in individuals with lupus show a 10- to 100-fold higher expression of LMP1 compared to their control groups \u003csup\u003e43\u0026ndash;45\u003c/sup\u003e, assessed through the viral load in peripheral blood, the frequency of infected B cells, and the amount of virus in serum. It is also important to highlight that this increase in gene expression seems not to be dependent on immunosuppressive therapy that may be ongoing to treat SLE \u003csup\u003e43,44,46\u003c/sup\u003e. These findings becomes relevant since LMP1 is a latent EBV protein with a high potential for altering cellular signal transduction pathways, including blocking intracellular DNA sensors, such as TLR9, and transcription factors, such as IRF3/7 \u003csup\u003e47\u003c/sup\u003e. These are crucial pathways to promote the proliferation of target cells and, simultaneously, interfere with the regulated processes of apoptosis \u003csup\u003e48\u003c/sup\u003e. The influence of LMP1 is exerted through its expression in the plasma membrane, activating signaling pathways, such as NF- κB, protein kinases JNK, and p38 \u003csup\u003e48,49\u003c/sup\u003e. In SLE patients, an increase in LMP1 could favor an increase in autoreactive B-cell survival, suggesting a mechanism for the higher activity of immune responses seen in SLE patients \u003csup\u003e50\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eDifferent HERV-E have been identified more frequently in patients with autoimmune disorders, which suggests that the methylation state of the genome contributes to the modulation of the expression of these retrotransposons. Even more so when DNA hypomethylation has been shown to be involved in the pathogenesis of SLE \u003csup\u003e51\u003c/sup\u003e. Our results show evidence of a significant relative overexpression of HERV-E gag in patients with SLE, also confirmed by other authors showing increased mRNA expression of HERV-E in CD4\u0026thinsp;+\u0026thinsp;T cells of patients with lupus \u003csup\u003e4\u003c/sup\u003e. Since HERV-E proteins may be structurally similar to autoantigens and trigger autoimmunity through molecular mimicry, potentially serving as a new therapeutic target in lupus \u003csup\u003e52,53\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThere is evidence supporting the role of IL-10 in the promotion of growth and the transformation of auto-reactive B cells into plasma cells in lupus, which, in turn, influences the progress of the disease \u003csup\u003e54,55\u003c/sup\u003e. Our results show an increased expression of this cytokine in patients with SLE. Nonetheless, it is worth highlighting that studies on murine models indicate that IL-10 may also play a protective role in lupus as it has proinflammatory and anti-inflammatory effects \u003csup\u003e56,57\u003c/sup\u003e. This might also explain the lower expression of TNFA- seen in our studies as IL-10 inhibits TNF-α \u003csup\u003e58,59\u003c/sup\u003e. Conversely, the influence of toll-like receptors (TLR) inside the cell, acting as nucleic acid sensors, are an aspect of interest in the pathogenesis of SLE; especially TLR3, which can sense double-stranded RNA (dsRNA) of viral origin, and influence cytokine production by NF-κB signaling pathways \u003csup\u003e60\u003c/sup\u003e. This study reports a considerable decrease in the relative expression of TLR3 in patients with SLE; In the context of an active EBV-mediated infection, the expression of non-polyadenylated RNA forming loop structures through base pairing is observed, simulating dsRNA molecules. This phenomenon triggers signaling through TLR3, which is involved in the production of type 1 interferon (type 1 IFN) \u003csup\u003e61\u003c/sup\u003e. In our lupus patients, despite exhibiting increased activity of EBV viral infection, their TLR3 expression is significantly diminished, which could imply a factor hindering the immune response to the infection and facilitating viral reactivation. However, it has been demonstrated that in SLE patients infected with hepatitis C virus (HCV), the relative expression levels of TLR3 are higher compared to non-lupus controls also infected \u003csup\u003e62\u003c/sup\u003e reflecting the heterogeneity of these patients' response to infections.\u003c/p\u003e \u003cp\u003eThe results of the distribution of the CD45\u0026thinsp;+\u0026thinsp;pan-leukocyte panel among cell populations in general (neutrophils, monocytes, and lymphocytes) are an important parameter of association with the state of disease activity \u003csup\u003e12\u003c/sup\u003e. Conversely, an increase in the expression of CD27 in T and B lymphocytes suggests a crucial role in the immune activation process \u003csup\u003e63,64\u003c/sup\u003e. The differences in the distribution of CD27\u0026thinsp;+\u0026thinsp;B cells are useful for the evaluation of the disease activity in patients with SLE \u003csup\u003e65\u003c/sup\u003e, although a low index of disease inactivity also brings about a greater expression of CD27\u0026mdash;both for T and B lymphocytes. The different behaviors and possible effects of over and under-expressed genes in the context of lupus are represented in a unified manner based on the results obtained in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eTaken together, these results provide new perspectives to understand the complex immune interactions in SLE and could pave the way for future research and therapeutic approaches. Our study highlights the way in which dysregulation in cytokine activity and the influence of genetic and viral factors, such as EBV, contribute significantly to the heterogeneity of SLE. The variability observed in the expression of TNFA, IFNG, IL-10, and HERV-E gag among patients with SLE not only reflects the diverse immune response, but also stresses the complexity of underlying mechanisms of this disease. These patterns point to a profoundly altered immune system in SLE, where the interplay between intrinsic and external immune factors, such as viral infections, plays a crucial role in pathogenesis. The fact that different patients with SLE show various responses in terms of cytokine and viral protein expression implies the underlying heterogeneity of the disease, which may be vital for customizing the treatment strategies. These findings are the basis for patient stratification and the development of more targeted therapeutic interventions based on the specific biology of each case of SLE.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eY.B.L: Conceptualization, Investigation, Writing - original draft, Writing - review \u0026amp; editing. G.A.M: Conceptualization, Investigation, Supervision. L.P.L: Investigation, Writing - review \u0026amp; editing. L.G.E: Investigation, Supervision. E.Z.P: Conceptualization, Investigation, Writing - review \u0026amp; editing. N.S.L: Investigation, Writing. A.C.B: Conceptualization, Investigation, Supervision. A.J.A-H: Conceptualization, Supervision, Writing - review \u0026amp; editing. E.N.Q: Conceptualization, Investigation, Writing - review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003eCorrespondence and requests for materials should be addressed to Y.B.L\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe data supporting the findings of this study are available from the corresponding author, Y.B.L., upon request ([email protected]).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eKarrar, S. \u0026amp; Cunninghame Graham, D. S. Abnormal B Cell Development in Systemic Lupus Erythematosus. Arthritis Rheumatol 70, 496\u0026ndash;507 (2018).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLugo, L. P., Olmos, Y. D. \u0026amp; Mart\u0026iacute;nez, G. A. 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T. \u003cem\u003eet al.\u003c/em\u003e Effects of single nucleotide polymorphisms on Toll-like receptor 3 activity and expression in cultured cells. J Biol Chem 282, 17696\u0026ndash;17705 (2007).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIwakiri, D. \u003cem\u003eet al.\u003c/em\u003e Epstein-Barr virus (EBV)-encoded small RNA is released from EBV-infected cells and activates signaling from Toll-like receptor 3. J Exp Med 206, 2091\u0026ndash;2099 (2009).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRazin, M. \u003cem\u003eet al.\u003c/em\u003e TLR3\\TLR7 as Differentially Expressed Markers Among Viral, Nonviral, and Autoimmune Diseases in Egyptian Patients. Viral Immunol 34, 607\u0026ndash;621 (2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEliopoulos, A. G. \u0026amp; Young, L. S. LMP1 structure and signal transduction. Semin Cancer Biol 11, 435\u0026ndash;444 (2001).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCaielli, S. \u003cem\u003eet al.\u003c/em\u003e A CD4\u0026thinsp;+\u0026thinsp;T cell population expanded in lupus blood provides B cell help through interleukin-10 and succinate. Nat Med 25, 75\u0026ndash;81 (2019).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGeginat, J. \u003cem\u003eet al.\u003c/em\u003e IL-10 producing regulatory and helper T-cells in systemic lupus erythematosus. Seminars in Immunology 44, 101330 (2019).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Lupus, T lymphocytes, B lymphocytes, Epstein-Barr virus (EBV), Human endogenous retrovirus (HERV-E)","lastPublishedDoi":"10.21203/rs.3.rs-4361087/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4361087/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eSystemic lupus erythematosus (SLE) is a multifactorial disease characterized by the convergence of genetic, immunological, and viral elements resulting in a complex interaction of both internal and external factors. Research has recognized the role that play the Epstein-Barr virus (EBV) and Human endogenous retrovirus (HERV-E) as triggers and maintenance elements in the disease. A fundamental study area stands out in the dynamics between these viral agents and their physiopathology to unveil their influence in SLE development and progress. This study aimed at assessing the differential expression of immune regulatory genes and the incidence of specific viral pathogens (EBV and HERV-E), alongside the detailed characterization of surface markers in T- and B-lymphocytes in patients with SLE and control participants. A comparative analysis between patients with SLE and control participants was performed, evaluating the expression of phenotypic markers and genes involved in the immune response (TNF-α, IL-2, IL-6, IL-10, IFNG, TLR3), as well as HERV-E \u003csub\u003egag\u003c/sub\u003e and EBV viral genes (LMP1 and BZLF1). A significant association between SLE and EBV was found in this study, with a marked increase in EBV LMP1 gene expression and a marked reduction in IFN-γ levels in patients with SLE. Also, a significant overexpression of HERV-E was observed, in addition to a considerable increase in the distribution of the cell surface marker CD27\u0026thinsp;+\u0026thinsp;on T- and B-lymphocytes, observed in individuals with SLE compared to the control group.\u003c/p\u003e \u003cp\u003eThis study provides evidence regarding the role that EBV virus plays in lymphocytes in the context of SLE, highlighting how both the virus and the host gene expression may influence disease pathogenesis by altering immune regulatory pathways mediated by TNF-α, IFN-γ, and IL-10, as well as parallel overexpression of HERV-E gag.\u003c/p\u003e","manuscriptTitle":"Differential Gene Profiling of Epstein-Barr Virus and Human Endogenous Retrovirus in Peripheral Blood Mononuclear Cells of Patients with Systemic Lupus Erythematosus: Implications for Immune Response","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-06-07 22:56:28","doi":"10.21203/rs.3.rs-4361087/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2024-07-22T21:04:20+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"315037975013557295356473897670846085751","date":"2024-07-17T17:13:05+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-07-15T10:15:06+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"332085243803696267940803114207096915899","date":"2024-07-15T09:10:00+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-06-03T12:47:50+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"281890968365642242875662203066004117323","date":"2024-05-28T14:09:56+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"209462689523036943333154827625817265796","date":"2024-05-28T11:34:42+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-05-23T09:43:46+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-05-23T07:49:09+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-05-23T06:04:02+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-05-23T05:56:20+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2024-05-02T21:47:04+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"06c53196-8931-4890-999f-11e9c2817492","owner":[],"postedDate":"June 7th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":32755660,"name":"Biological sciences/Genetics"},{"id":32755661,"name":"Biological sciences/Immunology"},{"id":32755662,"name":"Health sciences/Nephrology"},{"id":32755663,"name":"Health sciences/Rheumatology"}],"tags":[],"updatedAt":"2024-09-02T16:00:44+00:00","versionOfRecord":{"articleIdentity":"rs-4361087","link":"https://doi.org/10.1038/s41598-024-70913-6","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2024-08-30 15:57:21","publishedOnDateReadable":"August 30th, 2024"},"versionCreatedAt":"2024-06-07 22:56:28","video":"","vorDoi":"10.1038/s41598-024-70913-6","vorDoiUrl":"https://doi.org/10.1038/s41598-024-70913-6","workflowStages":[]},"version":"v1","identity":"rs-4361087","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4361087","identity":"rs-4361087","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}