Epstein-Barr virus infection as potential indicator of the occurrence and clinical presentation of systemic lupus erythematosus

Introduction

The relationship between Systemic lupus erythematosus (SLE) and Epstein-Barr virus (EBV) infection has been suggested for decades, but the underlying mechanism of the EBV influence on SLE development remains to be elucidated.

Methods

The goals of this research, which included 103 SLE patients and 99 controls, were to investigate the association of the parameters of EBV infection and SLE, to explore whether pooled demographic, clinical and EBV markers achieve a more significant effect on SLE development than each of them individually, and to evaluate EBV nuclear antigen 1 (EBNA1) and latent membrane protein 1 (LMP1) gene polymorphisms in isolates from SLE patients.

Results

Comprehensive results related to serological, molecular and sequence markers of EBV infection in SLE patients demonstrated even 24 times higher possibility of having SLE if there is the presence of anti-EBV-EA(D) (early antigen) IgG antibodies (OR=24.086 95%CI OR=2.86-216.07, p=0.004). There was the same distribution of glucocorticoids (p=0.130), antimalarials (p=0.213), and immunosuppressives (p=0.712) in anti-EBV-EA(D) IgG positive and negative SLE patients. Further, higher anti-EBV-EA(D) IgG antibodies titers were identified as independent factors associated with lymphopenia, hematological SLE manifestation (OR=1.041, 95%CI OR=1.01-1.08, p=0.025, while a higher titer of anti-CA (viral capsid antigen) IgG antibodies (OR=1.015, 95%CI OR=1.01-1.03, p=0.019) and positive RF (rheumatoid factors) (OR=4.871, 95%CI OR=1.52-15.61, p=0.008) were identified as independent factors associated with alopecia within SLE. Finally, novel data on EBV EBNA1 and LMP1 gene polymorphisms in lupus are reported.

Conclusion

The results support further investigation targeting EBV as a prognostic marker and therapeutic goal for lupus.

Markers of Epstein-Barr Virus Infection in Association with the Onset and Poor Control of Rheumatoid Arthritis: A Prospective Cohort Study

Although the connection between Epstein-Barr virus (EBV) and rheumatoid arthritis (RA) has been studied for over 40 years, many questions still need clarification. The study aimed to analyze the possible association between anti-EBV antibody titers, EBV DNA viremia, EBV infection status and EBNA1 (Epstein-Barr nuclear antigen 1-EBNA1) variants and clinical parameters of RA patients. This prospective cohort study included 133 RA patients and 50 healthy controls. Active/recent EBV infection was more prevalent in RA patients than in controls (42% vs. 16%, p < 0.001). RA patients had higher titers of anti-EBV-CA-IgM (capsid antigen-CA) and anti-EBV-EA(D)-IgG (early antigen-EA) antibodies than controls (p = 0.003 and p = 0.023, respectively). Lower levels of anti-EBNA1-IgG and anti-EBV-CA-IgG were observed in RA patients who received methotrexate (anti-EBNA1 IgG p < 0.001; anti-EBV-CA IgG p < 0.001). Based on amino acid residue on position 487, two EBNA1 prototypes were detected: P-Thr and P-Ala. Patients with active/recent EBV infection had a five times more chance of having RA and a nearly six times more chance of getting RA. Also, EBV active/recent infection is twice more likely in newly diagnosed than in methotrexate-treated patients. Further studies are needed to clarify "who is the chicken and who is the egg" in this EBV-RA relationship.

Association of IL10RA, IL10RB, and IL22RA Polymorphisms/Haplotypes with Susceptibility to and Clinical Manifestations of SLE

Systemic lupus erythematosus (SLE) is characterized by an imbalance between proinflammatory and anti-inflammatory mediators. Single-nucleotide polymorphisms (SNPs) in genes coding IL10RA, IL10RB, and IL22RA could affect their expression or function and disrupt immune homeostasis. We aimed to analyze the associations of IL10RA, IL10RB, and IL22RA polymorphisms/haplotypes with patients' susceptibility to and clinical manifestations of SLE. Our study included 103 SLE patients and 99 healthy controls. The genotypes of the selected polymorphisms within IL10RA (rs10892202, rs4252270, rs3135932, rs2228055, rs2229113, and rs9610), IL10RB (rs999788, rs2834167, and rs1058867), and IL22RA (rs3795299 and rs16829204) genes were determined by TaqMan^® Assays. IL10RB rs1058867 G allele carriers were significantly more frequent among the controls than among the SLE patients (76.8% vs. 61.2%; p = 0.017, OR = 0.477, 95% CI: 0.258-0.879). The IL10RB CAA haplotype was more frequent among the SLE patients than in the control group (42.7% vs. 30.7%; p = 0.027). The IL22RA rs3795299 C allele and rs16829204 CC genotype were associated with Hashimoto thyroiditis in the SLE patients (n = 103; p = 0.002 and p = 0.026, respectively), and in all the included participants (n = 202, p < 0.000 and p = 0.007, respectively), and the IL22RA CC haplotype was more frequent in the SLE patients with Hashimoto thyroiditis (p = 0.047) and in the overall participants with Hashimoto thyroiditis (n = 32, p = 0.004). The IL10RA, IL10RB, and IL22RA polymorphisms/haplotypes could be associated with SLE susceptibility and various clinical manifestations, and the IL22RA CC haplotype could be associated with Hashimoto thyroiditis.

New Evidence of Significant Association between EBV Presence and Lymphoproliferative Disorders Susceptibility in Patients with Rheumatoid Arthritis: A Systematic Review with Meta-Analysis

Development of lymphoproliferative disorders (LPDs) is one of the well-known life-threatening complications in rheumatoid arthritis (RA) patients. However, there is a lack of definitive conclusions regarding the role of Epstein-Barr virus (EBV) activity in RA initiation and progression, especially in promoting LPDs. A systematic review and meta-analysis of studies that reported an EBV positive result in RA-LPD patients and controls were conducted. Studies published before 27 July 2021 were identified through PubMed, Web of Science, and SCOPUS. A total of 79 articles were included in the systematic review. The prevalence of EBV positive result among RA-LPD patients was 54% (OR = 1.54, 95% CI = 1.45–1.64). There was a statistically significant association between EBV presence and LPD susceptibility in RA patients in comparison with all controls (OR = 1.88, 95% CI = 1.29–2.73) and in comparison with LPD patients only (OR = 1.92, 95% CI = 1.15–3.19). This association was not shown in comparison with patients with autoimmune diseases other than RA who developed LPD (OR = 0.79, 95% CI = 0.30–2.09). This meta-analysis confirmed a high prevalence of EBV in the RA-LPD population. Furthermore, it provides evidence for the association between EBV presence and LPD susceptibility in RA patients, but not in those with other autoimmune diseases who developed LPD.

Development of an accessible 10-year Digital CArdioVAscular (DiCAVA) risk assessment: a UK Biobank study

Aims

Cardiovascular diseases (CVDs) are among the leading causes of death worldwide. Predictive scores providing personalized risk of developing CVD are increasingly used in clinical practice. Most scores, however, utilize a homogenous set of features and require the presence of a physician. The aim was to develop a new risk model (DiCAVA) using statistical and machine learning techniques that could be applied in a remote setting. A secondary goal was to identify new patient-centric variables that could be incorporated into CVD risk assessments.

Methods and results

Across 466 052 participants, Cox proportional hazards (CPH) and DeepSurv models were trained using 608 variables derived from the UK Biobank to investigate the 10-year risk of developing a CVD. Data-driven feature selection reduced the number of features to 47, after which reduced models were trained. Both models were compared to the Framingham score. The reduced CPH model achieved a c-index of 0.7443, whereas DeepSurv achieved a c-index of 0.7446. Both CPH and DeepSurv were superior in determining the CVD risk compared to Framingham score. Minimal difference was observed when cholesterol and blood pressure were excluded from the models (CPH: 0.741, DeepSurv: 0.739). The models show very good calibration and discrimination on the test data.

Conclusion

We developed a cardiovascular risk model that has very good predictive capacity and encompasses new variables. The score could be incorporated into clinical practice and utilized in a remote setting, without the need of including cholesterol. Future studies will focus on external validation across heterogeneous samples.

Machine learning approach to dynamic risk modeling of mortality in COVID-19: a UK Biobank study

The COVID-19 pandemic has created an urgent need for robust, scalable monitoring tools supporting stratification of high-risk patients. This research aims to develop and validate prediction models, using the UK Biobank, to estimate COVID-19 mortality risk in confirmed cases. From the 11,245 participants testing positive for COVID-19, we develop a data-driven random forest classification model with excellent performance (AUC: 0.91), using baseline characteristics, pre-existing conditions, symptoms, and vital signs, such that the score could dynamically assess mortality risk with disease deterioration. We also identify several significant novel predictors of COVID-19 mortality with equivalent or greater predictive value than established high-risk comorbidities, such as detailed anthropometrics and prior acute kidney failure, urinary tract infection, and pneumonias. The model design and feature selection enables utility in outpatient settings. Possible applications include supporting individual-level risk profiling and monitoring disease progression across patients with COVID-19 at-scale, especially in hospital-at-home settings.

Hospital-acquired infections in the adult intensive care unit-Epidemiology, antimicrobial resistance patterns, and risk factors for acquisition and mortality

BACKGROUND

Acquisition of Hospital-acquired infections (HAIs) in intensive care units (ICUs) predispose patients to higher mortality rates and additional adverse events. Serbian adult ICUs are rarely investigated for HAIs. The aim of this study was to look into HAIs in an adult ICU and identify risk factors for acquisition of HAIs and mortality.

METHODS

This retrospective study included 355 patients hospitalized over a 2-year period. Patient characteristics, antimicrobial resistance patterns, and risk factors of acquisition and predictors of mortality in patients who had a HAI were examined.

RESULTS

HAIs were diagnosed in 32.7% of patients. Resistance rates > 50% were observed in all antimicrobials except for tigecycline (14%), colistin (9%), and linezolid (0%). Predictors of HAI acquisition were underlying viral CNS infections and invasive devices-urinary and central venous catheters, and nasogastric tubes. Diabetes mellitus and intubation (odds ratio 2.5 and 6.7, P = .042 and <.001) were identified as predictors for increased mortality in patients who had a HAI.

CONCLUSIONS

Prevalence of HAIs and resistance rates are high compared to ICUs in other European countries. Risk factors for both acquisition of HAI and mortality were identified. Large-scale studies are necessary to look at HAIs in adult ICUs in Serbia.

Antimicrobial resistance in patients with urinary tract infections and the impact on empiric therapy in Serbia

INTRODUCTION

Surveillance of antimicrobial resistance is essential in establishing treatment guidelines for urinary tract infections. The aim of this pilot study was to analyse resistance rates of pathogens, across different demographics and determine whether adjustments in empiric therapy should be considered for different age and gender groups.

METHODOLOGY

A 5-year retrospective study included 256 patients hospitalised, under the initial diagnosis of Fever of Unknown Origin who were then subsequently diagnosed with a urinary tract infection at the Clinic for Infectious and Tropical Diseases, Clinical Centre of Serbia. Patients were evaluated using demographic, clinical, and antimicrobial resistance data with appropriate statistical analysis including ANOVA significance testing, univariate, and multivariate analysis.

RESULTS

Resistance rates were above the threshold of 20% for the majority of the antimicrobials tested, the only exception being carbapenems. Amikacin, cefepime, and norfloxacin were agents that could be effectively used as empiric therapy in younger adults with resistance rates of 4.2, 8.0, and 10.0%, respectively. Moderate resistance rates of 17.4% for amikacin and 19.1% for cefepime were observed in the age group 35-64 years. High resistance rates were observed for all antimicrobials among patients 65 years and over. Among male patients, resistance rates to most antimicrobials were high. In female patients, amikacin and cefepime had resistance rates less than 20%. Younger age presented as a negative risk factor for infection by a multi-drug resistant pathogen.

CONCLUSION

Age and gender demonstrated to be significant factors for determining proper empiric therapy; large-scale studies from Serbia are needed to solidify these findings.