Prevalence and risk factors of herpes zoster infection in patients with rheumatic diseases not receiving biologic or targeted therapies

Identifying and Evaluating Biological Markers of Postherpetic Neuralgia: A Comprehensive Review

Postherpetic neuralgia (PHN) manifests as persistent chronic pain that emerges after a herpes zoster outbreak and greatly diminishes quality of life. Unfortunately, its treatment efficacy has remained elusive, with many therapeutic efforts yielding less than satisfactory results. The research to discern risk factors predicting the onset, trajectory, and prognosis of PHN has been extensive. However, these risk factors often present as nonspecific and diverse, indicating the need for more reliable, measurable, and objective detection methods. The exploration of potential biological markers, including hematological indices, pathological insights, and supportive tests, is increasing. This review highlights potential biomarkers that are instrumental for the diagnosis, management, and prognosis of PHN while also delving deeper into its genesis. Drawing from prior research, aspects such as immune responsiveness, neuronal injury, genetic makeup, cellular metabolism, and pain signal modulation have emerged as prospective biomarkers. The immune spectrum spans various cell subtypes, with an emphasis on T cells, interferons, interleukins, and other related cytokines. Studies on nerve injury are directed toward pain-related proteins and the density and health of epidermal nerve fibers. On the genetic and metabolic fronts, the focus lies in the detection of predisposition genes, atypical protein manifestations, and energy-processing dynamics, with a keen interest in vitamin metabolism. Tools such as functional magnetic resonance imaging, electromyography, and infrared imaging have come to the forefront in the pain signaling domain. This review compiles the evidence, potential clinical implications, and challenges associated with these promising biomarkers, paving the way for innovative strategies for predicting, diagnosing, and addressing PHN.

Assessment of the humoral immune status of varicella-zoster virus in patients with diffuse connective tissue diseases

Background

Diffuse connective tissue diseases (DCTDs) require long-term immunosuppressive treatment, increasing the risk of varicella-zoster virus (VZV) infection. This study aims to evaluate the humoral immune status against VZV in DCTD patients and explore factors that may influence their immune levels.

Methods

This is a retrospective cohort study that collected data from adult DCTD patients (≥18 years) attending our outpatient clinic. The geometric mean concentration (GMC) of VZV-specific IgG antibodies in the patients' sera was measured using the enzyme-linked immunosorbent assay (ELISA).

Results

A total of 280 RA patients, 272 SLE + MCTD patients and 280 healthy controls were included. SLE + MCTD patients had significantly higher VZV IgG antibody levels than RA patients (p < 0.05) but showed no significant difference compared to healthy controls (p > 0.05). Notable differences were observed particularly among female patients and those aged 30-49 years, (p < 0.05). SLE + MCTD patients in an active disease state had significantly higher VZV IgG antibody titers than RA patients (p < 0.05). Additionally, patients with a history of herpes zoster, regardless of being in the SLE + MCTD, RA, or control group, exhibited higher VZV IgG titers (p < 0.05).

Conclusion

Although DCTD patients, particularly those with SLE and MCTD, exhibit higher VZV IgG antibody levels, they still face a higher risk of developing herpes zoster (HZ), which may be related to their underlying disease and immunosuppressive treatment. The presence of antibodies alone may not provide complete protection, necessitating consideration of cellular immune mechanisms. It is recommended to enhance monitoring of VZV antibody levels in high-risk patients and consider herpes zoster vaccination to reduce HZ-related complications.

Safety and efficacy of anifrolumab therapy in systemic lupus erythematosus in real-world clinical practice: LOOPS registry

OBJECTIVE

To determine the safety and efficacy of anifrolumab in patients with systemic lupus erythematosus (SLE) classified based on the Lupus Low Disease Activity State (LLDAS) in real-world clinical practice.

METHODS

This retrospective observational study involved SLE patients who started anifrolumab therapy. The primary end point was the retention rate over 26 weeks after initiating anifrolumab therapy; 45 patients followed up for 12 weeks or longer were analysed in the following groups to determine the safety and efficacy up to week 12 after treatment initiation: (i) non-LLDAS achievement group and (ii) minor flare group. Safety and efficacy were compared between the minor flare group and the standard of care (SoC) group (treated by adding glucocorticoids [GCs] or immunosuppressants) after adjustment with inverse probability of treatment weighting using propensity score (PS-IPTW).

RESULTS

The retention rate of anifrolumab was 89.7% at week 26.The LLDAS achievement rates at week 12 were 42.9% and 66.7% in the non-LLDAS achievement and minor flare groups, respectively. In both groups, GC doses and SELENA-SLEDAI score significantly decreased. When the anifrolumab group with minor flare was compared with the SoC group or the GC dose increase group, the GC dose and SLEDAI score were significantly lower in the anifrolumab group than in either of the other groups; there was no significant difference in LLDAS achievement.

CONCLUSION

At week 26 after initiating anifrolumab therapy, ∼90% of patients remained on therapy. Anifrolumab might lower disease activity without initiating GCs and reduce GC doses, especially in patients who experience minor flares after LLDAS achievement.

Exploring blood transcriptomic signatures in patients with herpes zoster and postherpetic neuralgia

Postherpetic neuralgia (PHN) is a common, severe, and hard-to-treat chronic pain condition in clinics. Although PHN is developed from herpes zoster (HZ), the developing mechanism is unknown. A previous study investigated blood metabolomic and proteomic profiling in patients with PHN and HZ. The current study aims to explore the blood transcriptomic signature of PHN compared to HZ patients. Whole blood from eight PHN and 15 HZ patients was used for RNA-Seq analysis. There were 82 and 1,788 genes detected specifically in the PHN and HZ groups, respectively. PHN-specific genes are involved in viral infection, lipid and carbohydrate metabolism, and immune response. For genes coexpressed in PHN and HZ patients, there were 407 differential expression genes (DEGs), including 205 upregulated (UP DEGs) and 202 downregulated (DOWN DEGs) in PHN compared to HZ groups. DEGs are involved in viral infection, type I interferon (IFN), and hemoglobin and oxygen carrier activity. UP DEGs are associated with regulatory T cells (Tregs), activated NK cells, and neutrophils, while DOWN DEGs are associated with Tregs, resting NK cells, and monocytes. The results suggest that the metabolism of lipid, glycan, and nucleotides, type I IFN signaling, and altered neutrophil activation are associated with and might contribute to the development of PHN in HZ. It is also suggested that persistent or altered activation of nonspecific immunity may contribute to the development of PHN from HZ.

Risk factors for herpes zoster infections: a systematic review and meta-analysis unveiling common trends and heterogeneity patterns

PURPOSE

The burden of herpes zoster (HZ) is substantial and numerous chronic underlying conditions are known as predisposing risk factors for HZ onset. Thus, a comprehensive study is needed to synthesize existing evidence. This study aims to comprehensively identify these risk factors.

METHODS

A systematic literature search was done using MEDLINE via PubMed, EMBASE and Web of Science for studies published from January 1, 2003 to January 1, 2023. A random-effects model was used to estimate pooled Odds Ratios (OR). Heterogeneity was assessed using the I2 statistic. For sensitivity analyses basic outlier removal, leave-one-out validation and Graphic Display of Heterogeneity (GOSH) plots with different algorithms were employed to further analyze heterogeneity patterns. Finally, a multiple meta-regression was conducted.

RESULTS

Of 6392 considered records, 80 were included in the meta-analysis. 21 different conditions were identified as potential risk factors for HZ: asthma, autoimmune disorders, cancer, cardiovascular disorders, chronic heart failure (CHF), chronic obstructive pulmonary disorder (COPD), depression, diabetes, digestive disorders, endocrine and metabolic disorders, hematological disorders, HIV, inflammatory bowel disease (IBD), mental health conditions, musculoskeletal disorders, neurological disorders, psoriasis, renal disorders, rheumatoid arthritis (RA), systemic lupus erythematosus (SLE) and transplantation. Transplantation was associated with the highest risk of HZ (OR = 4.51 (95% CI [1.9-10.7])). Other risk factors ranged from OR = 1.17-2.87, indicating an increased risk for all underlying conditions. Heterogeneity was substantial in all provided analyses. Sensitivity analyses showed comparable results regarding the pooled effects and heterogeneity.

CONCLUSIONS

This study showed an increased risk of HZ infections for all identified factors.

Real-World Coverage With Influenza, Pneumococcal, and Herpes Zoster Vaccines Among Patients With Rheumatic Diseases in a Nationwide Healthcare Plan

OBJECTIVE

Vaccination against preventable infections is important for the management of rheumatic diseases (RDs). This study assessed the vaccination coverage and predictors among patients with RDs using real-world data from Israel.

METHODS

This retrospective cross-sectional study, based on a Maccabi Healthcare Services database, included adult patients diagnosed with rheumatoid arthritis (RA), psoriatic arthritis (PsA), and systemic lupus erythematosus (SLE), as of April 30, 2019. Age-specific vaccination coverage for influenza (past year), pneumococcal (23-valent pneumococcal polysaccharide vaccine [PPSV23] and/or 13-valent pneumococcal conjugate vaccine [PCV13]), and live-attenuated herpes zoster (HZ) vaccines (past 5 years) was reported. Logistic regression was used to investigate predictors of vaccination.

RESULTS

The study included 14,528 patients (RA: n = 6932; PsA: n = 4395; SLE: n = 1951; > 1 condition: n = 1250). Influenza vaccine coverage among patients with RA, PsA, and SLE was 45.1%, 36.2%, and 33.7%, respectively. For PPSV23, corresponding rates were 19.6%, 16.2%, and 12.6%, respectively. In the elderly population (≥ 65 years), 63.2% had influenza vaccine in the past year and 83.4% had a PPSV23 vaccine in the past 5 years or at age ≥ 65. For PCV13 and HZ, coverage in the overall study population was low at 4.8% and 3.6%, respectively. Central residence and treatment with corticosteroids and biologic or targeted synthetic disease-modifying antirheumatic drugs within the past 5 years were significant predictors of vaccination coverage across all vaccines (P < 0.05). Other predictors varied by vaccine, including female sex (influenza, PPSV23, PCV13), age (influenza, PPSV23), chronic comorbidities (influenza, PPSV23, PCV13), shorter disease duration (PCV13), and high socioeconomic status (PCV13, HZ).

CONCLUSION

This study demonstrated suboptimal coverage of influenza, pneumococcal, and HZ vaccination in patients with RA, PsA, and SLE, in particular among younger adults in Israel.

Exploring machine learning methods for predicting systemic lupus erythematosus with herpes

OBJECTIVES

To investigate whether machine learning, which is widely used in disease prediction and diagnosis based on demographic data and serological markers, can predict herpes occurrence in patients with systemic lupus erythematosus (SLE).

METHODS

A total of 286 SLE patients were included in this study, including 200 SLE patients without herpes and 86 SLE patients with herpes. SLE patients were randomly divided into a training group and a test group, and 18 demographic characteristics and serological indicators were compared between the two groups.

RESULTS

We selected basophil, monocyte, white blood cell, age, immunoglobulin E, SLE Disease Activity Index, complement 4, neutrophil, and immunoglobulin G as the basic features of modeling. A random forest model had the best performance, but logistic and decision tree analyses had better clinical decision-making benefits. Random forest had a good consistency between feature importance judgment and feature selection. The 10-fold cross-validation showed the optimization of five model parameters.

CONCLUSION

The random forest model may be an excellently performing model, which may help clinicians to identify SLE patients whose disease is complicated by herpes early.