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Kim TH, Lee K, Lee S, Oh J, Park J, Jo H, Son Y, Kim S, Rhee SY, Smith L, Cho H, Jung J, Yeo SG, Lee H, Yon DK. Effectiveness of the live zoster vaccine in patients with type 2 diabetes: A nationwide emulated target trial. Clin Microbiol Infect 2025:S1198-743X(25)00231-9. [PMID: 40349966 DOI: 10.1016/j.cmi.2025.05.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2024] [Revised: 04/28/2025] [Accepted: 05/01/2025] [Indexed: 05/14/2025]
Abstract
OBJECTIVES Real-world studies on its effectiveness in patients with type 2 diabetes mellitus (T2DM) remain limited. This study aimed to evaluate the effectiveness of the live zoster vaccine in patients with T2DM more than 10 years. METHODS In this target trial emulation study, we utilized a large-scale, nationwide cohort in South Korea, consisting of individuals aged 50 years and older with T2DM from January 1, 2012 to December 31, 2021 (n=934,945). This cohort was integrated using health insurance data from the Korea Health Insurance Review and Assessment Service, national health screening results from the Korean National Health Insurance Service, and live zoster vaccination data from the Korea Disease Control and Prevention Agency. Vaccine effectiveness in preventing HZ, postherpetic neuralgia, and hospital admissions for HZ based on ICD-10 codes was evaluated in patients with T2DM. In a propensity score-based overlap-weighted cohort, Cox proportional hazard models were used to evaluate the adjusted hazard ratios (aHRs) and 95% confidential intervals (CIs) for the effectiveness of the live zoster vaccine among patients with T2DM. RESULTS After propensity score-based overlap-weighting, 253,660 patients with T2DM were included (mean age, 62.4 years [standard deviation, 2.3 years]; 138,338 males, 54.5%). Live zoster vaccination was associated with a reduced risk of HZ (aHR, 0.59 [95% CI, 0.57-0.61]), postherpetic neuralgia (aHR, 0.59 [95% CI, 0.57-0.61]), and hospital admissions for HZ (aHR, 0.41 [95% CI, 0.36-0.47]). Vaccine effectiveness was highest within the first-year post-vaccination, with a sustained protective effect lasting up to six years. Furthermore, the effectiveness was greater in the non-insulin treatment group compared with the insulin treatment group. CONCLUSION Our target trial highlighted that live zoster vaccination significantly reduced the risk of HZ, postherpetic neuralgia, and hospital admissions in patients with T2DM. However, its effectiveness was attenuated in those undergoing insulin treatment.
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Affiliation(s)
- Tae Hyeon Kim
- Department of Medicine, Kyung Hee University College of Medicine, Seoul, South Korea; Center for Digital Health, Medical Science Research Institute, Kyung Hee University Medical Center, Kyung Hee University College of Medicine, Seoul, South Korea
| | - Kyeongmin Lee
- Center for Digital Health, Medical Science Research Institute, Kyung Hee University Medical Center, Kyung Hee University College of Medicine, Seoul, South Korea; Department of Regulatory Science, Kyung Hee University, Seoul, South Korea
| | - Sooji Lee
- Department of Medicine, Kyung Hee University College of Medicine, Seoul, South Korea; Center for Digital Health, Medical Science Research Institute, Kyung Hee University Medical Center, Kyung Hee University College of Medicine, Seoul, South Korea
| | - Jiyeon Oh
- Department of Medicine, Kyung Hee University College of Medicine, Seoul, South Korea; Center for Digital Health, Medical Science Research Institute, Kyung Hee University Medical Center, Kyung Hee University College of Medicine, Seoul, South Korea
| | - Jaeyu Park
- Center for Digital Health, Medical Science Research Institute, Kyung Hee University Medical Center, Kyung Hee University College of Medicine, Seoul, South Korea; Department of Precision Medicine, Kyung Hee University College of Medicine, Seoul, South Korea
| | - Hyesu Jo
- Center for Digital Health, Medical Science Research Institute, Kyung Hee University Medical Center, Kyung Hee University College of Medicine, Seoul, South Korea; Department of Regulatory Science, Kyung Hee University, Seoul, South Korea
| | - Yejun Son
- Center for Digital Health, Medical Science Research Institute, Kyung Hee University Medical Center, Kyung Hee University College of Medicine, Seoul, South Korea; Department of Precision Medicine, Kyung Hee University College of Medicine, Seoul, South Korea
| | - Soeun Kim
- Center for Digital Health, Medical Science Research Institute, Kyung Hee University Medical Center, Kyung Hee University College of Medicine, Seoul, South Korea; Department of Precision Medicine, Kyung Hee University College of Medicine, Seoul, South Korea
| | - Sang Youl Rhee
- Department of Medicine, Kyung Hee University College of Medicine, Seoul, South Korea; Center for Digital Health, Medical Science Research Institute, Kyung Hee University Medical Center, Kyung Hee University College of Medicine, Seoul, South Korea; Department of Regulatory Science, Kyung Hee University, Seoul, South Korea; Department of Precision Medicine, Kyung Hee University College of Medicine, Seoul, South Korea; Department of Endocrinology and Metabolism, Kyung Hee University School of Medicine, Seoul, Republic of Korea
| | - Lee Smith
- Centre for Health, Performance, and Wellbeing, Anglia Ruskin University, Cambridge, UK
| | - Hanseul Cho
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Junyang Jung
- Department of Anatomy and Neurobiology, College of Medicine, Kyung Hee University, Seoul, South Korea
| | - Seung Geun Yeo
- Department of Otolaryngology-Head & Neck Surgery, Kyung Hee University Medical Center, Kyung Hee University College of Medicine, Seoul, South Korea.
| | - Hayeon Lee
- Center for Digital Health, Medical Science Research Institute, Kyung Hee University Medical Center, Kyung Hee University College of Medicine, Seoul, South Korea; Department of Biomedical Engineering, Kyung Hee University, Yongin, South Korea; Department of Electronics and Information Convergence Engineering, Kyung Hee University, Yongin, South Korea.
| | - Dong Keon Yon
- Department of Medicine, Kyung Hee University College of Medicine, Seoul, South Korea; Center for Digital Health, Medical Science Research Institute, Kyung Hee University Medical Center, Kyung Hee University College of Medicine, Seoul, South Korea; Department of Regulatory Science, Kyung Hee University, Seoul, South Korea; Department of Precision Medicine, Kyung Hee University College of Medicine, Seoul, South Korea; Department of Biomedical Engineering, Kyung Hee University, Yongin, South Korea; Department of Pediatrics, Kyung Hee University Medical Center, Kyung Hee University College of Medicine, Seoul, South Korea.
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Yang X, Li D, Chen Y, Zhang X, Zhao Q. Exploring the Link Between Diabetes, Herpes Zoster, and Post-Herpetic Neuralgia: Insights From Mendelian Randomization. J Pain Res 2025; 18:1479-1489. [PMID: 40144692 PMCID: PMC11937845 DOI: 10.2147/jpr.s501674] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2024] [Accepted: 03/12/2025] [Indexed: 03/28/2025] Open
Abstract
Background Diabetes mellitus (DM), herpes zoster (HZ) and its sequelae, post-herpetic neuralgia (PHN), are common in elderly individuals. Previous observational studies have shown that the prevalence of HZ and PHN in conjunction with DM is increasing. Nonetheless, few studies have investigated the causal relationships between DM and the risk of HZ and PHN. Methods A two-sample Mendelian randomization (TSMR) analysis was conducted on genome-wide association study (GWAS) data. We obtained four separate datasets for DM: type 1 diabetes (T1D), type 2 diabetes (T2D), mother diabetes mellitus (mother-DM) and father diabetes mellitus (father-DM), and two independent datasets for HZ and anti-varicella-zoster virus IgG (VZV-IgG), a single GWAS for PHN. The inverse variance weighted (IVW), MR‒Egger, weighted median and weighted mode analyses were used to estimate the causality. Results Genetically predicted T1D increased the level of VZV-IgG (IVW: OR=1.011, 95% CI 1.006-1.016, P -FDR=8.44×10-6). T2D (IVW: OR=1.313; 95% CI 1.043-1.655, P -FDR=0.041), mother-DM (IVW: OR=7.909; 95% CI 1.232-50.777, P -FDR=0.039), and father-DM (IVW: OR=11.798; 95% CI 2.051-67.874, P -FDR=0.023) increased the risk of PHN. No reverse causality was found between HZ, PHN, and DM. Conclusion Our research reveals a causal link between genetically determined T1D and increased VZV-IgG levels. Additionally, genetically predicted T2D and a family history of DM increase the risk of PHN. These discoveries deepen our comprehension of the underlying causes of HZ and PHN.
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Affiliation(s)
- Xueying Yang
- Department of Anesthesiology, Sun Yat-Sen Memorial Hospital, Guangzhou, Guangdong, People’s Republic of China
| | - Dairui Li
- Department of Thyroid Surgery, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, People’s Republic of China
| | - Yuqing Chen
- Department of Anesthesiology, Sun Yat-Sen Memorial Hospital, Guangzhou, Guangdong, People’s Republic of China
| | - Xuerong Zhang
- Department of Anesthesiology, Sun Yat-Sen Memorial Hospital, Guangzhou, Guangdong, People’s Republic of China
| | - Qiong Zhao
- Department of Anesthesiology, Sun Yat-Sen Memorial Hospital, Guangzhou, Guangdong, People’s Republic of China
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Vandoren R, Boeren M, Schippers J, Bartholomeus E, Mullan K, Michels N, Aerts O, Leysen J, Bervoets A, Lambert J, Leuridan E, Wens J, Peeters K, Emonds MP, Jansens H, Casanova JL, Bastard P, Suls A, Van Tendeloo V, Ponsaerts P, Delputte P, Ogunjimi B, Laukens K, Meysman P. Unraveling the Immune Signature of Herpes Zoster: Insights Into the Pathophysiology and Human Leukocyte Antigen Risk Profile. J Infect Dis 2024; 230:706-715. [PMID: 38195164 PMCID: PMC11420803 DOI: 10.1093/infdis/jiad609] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2023] [Revised: 12/15/2023] [Accepted: 01/08/2024] [Indexed: 01/11/2024] Open
Abstract
The varicella-zoster virus (VZV) infects >95% of the population. VZV reactivation causes herpes zoster (HZ), known as shingles, primarily affecting the elderly and individuals who are immunocompromised. However, HZ can occur in otherwise healthy individuals. We analyzed the immune signature and risk profile in patients with HZ using a genome-wide association study across different UK Biobank HZ cohorts. Additionally, we conducted one of the largest HZ human leukocyte antigen association studies to date, coupled with transcriptomic analysis of pathways underlying HZ susceptibility. Our findings highlight the significance of the major histocompatibility complex locus for HZ development, identifying 5 protective and 4 risk human leukocyte antigen alleles. This demonstrates that HZ susceptibility is largely governed by variations in the major histocompatibility complex. Furthermore, functional analyses revealed the upregulation of type I interferon and adaptive immune responses. These findings provide fresh molecular insights into the pathophysiology and activation of innate and adaptive immune responses triggered by symptomatic VZV reactivation.
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Affiliation(s)
- Romi Vandoren
- Adrem Data Lab, Department of Computer Science, University of Antwerp
- Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing, University of Antwerp
- Biomedical Informatics Research Network Antwerp
| | - Marlies Boeren
- Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing, University of Antwerp
- Laboratory of Microbiology, Parasitology and Hygiene and Infla-Med Center of Excellence
- Laboratory of Experimental Hematology, Vaccine and Infectious Disease Institute
- Antwerp Center for Translational Immunology and Virology, Vaccine and Infectious Disease Institute
- Centre for Health Economics Research and Modelling Infectious Diseases, Vaccine and Infectious Disease Institute
| | - Jolien Schippers
- Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing, University of Antwerp
- Antwerp Center for Translational Immunology and Virology, Vaccine and Infectious Disease Institute
- Centre for Health Economics Research and Modelling Infectious Diseases, Vaccine and Infectious Disease Institute
| | - Esther Bartholomeus
- Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing, University of Antwerp
- Antwerp Center for Translational Immunology and Virology, Vaccine and Infectious Disease Institute
- Centre for Health Economics Research and Modelling Infectious Diseases, Vaccine and Infectious Disease Institute
| | - Kerry Mullan
- Adrem Data Lab, Department of Computer Science, University of Antwerp
- Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing, University of Antwerp
- Biomedical Informatics Research Network Antwerp
| | - Nele Michels
- Department of Family Medicine and Population Health, Center for General Practice/Family Medicine, University of Antwerp
| | - Olivier Aerts
- Department of Dermatology, Antwerp University Hospital and University of Antwerp
| | - Julie Leysen
- Department of Dermatology, Antwerp University Hospital and University of Antwerp
| | - An Bervoets
- Department of Dermatology, Antwerp University Hospital and University of Antwerp
| | - Julien Lambert
- Department of Dermatology, Antwerp University Hospital and University of Antwerp
| | - Elke Leuridan
- Centre for the Evaluation of Vaccination, Vaccine and Infectious Disease Institute, University of Antwerp
| | - Johan Wens
- Department of Family Medicine and Population Health, Center for General Practice/Family Medicine, University of Antwerp
| | - Karin Peeters
- Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing, University of Antwerp
- Antwerp Center for Translational Immunology and Virology, Vaccine and Infectious Disease Institute
- Centre for Health Economics Research and Modelling Infectious Diseases, Vaccine and Infectious Disease Institute
| | - Marie-Paule Emonds
- Histocompatibility and Immunogenetic Laboratory, Rode Kruis-Vlaanderen, Mechelen
| | - Hilde Jansens
- Department of Clinical Microbiology, Antwerp University Hospital, Belgium
| | - Jean-Laurent Casanova
- Laboratory of Human Genetics of Infectious Diseases, Necker Branch, Institut National de la Santé et de la Recherche Médicale U1163, Necker Hospital for Sick Children, Paris
- Imagine Institute, Paris Cité University, France
- St Giles Laboratory of Human Genetics of Infectious Diseases, Rockefeller Branch, The Rockefeller University
- Howard Hughes Medical Institute, New York, New York
- Department of Pediatrics, Necker Hospital for Sick Children, Paris
| | - Paul Bastard
- Laboratory of Human Genetics of Infectious Diseases, Necker Branch, Institut National de la Santé et de la Recherche Médicale U1163, Necker Hospital for Sick Children, Paris
- Imagine Institute, Paris Cité University, France
- St Giles Laboratory of Human Genetics of Infectious Diseases, Rockefeller Branch, The Rockefeller University
- Pediatric Hematology-Immunology and Rheumatology Unit, Necker Hospital for Sick Children, Assistante Publique–Hôpitaux de Paris, France
| | - Arvid Suls
- Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing, University of Antwerp
- Medical Genetics, University of Antwerp and Antwerp University Hospital
| | - Viggo Van Tendeloo
- Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing, University of Antwerp
- Laboratory of Experimental Hematology, Vaccine and Infectious Disease Institute
| | - Peter Ponsaerts
- Laboratory of Experimental Hematology, Vaccine and Infectious Disease Institute
| | - Peter Delputte
- Laboratory of Microbiology, Parasitology and Hygiene and Infla-Med Center of Excellence
| | - Benson Ogunjimi
- Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing, University of Antwerp
- Antwerp Center for Translational Immunology and Virology, Vaccine and Infectious Disease Institute
- Centre for Health Economics Research and Modelling Infectious Diseases, Vaccine and Infectious Disease Institute
- Department of Paediatrics, Antwerp University Hospital, Belgium
| | - Kris Laukens
- Adrem Data Lab, Department of Computer Science, University of Antwerp
- Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing, University of Antwerp
- Biomedical Informatics Research Network Antwerp
| | - Pieter Meysman
- Adrem Data Lab, Department of Computer Science, University of Antwerp
- Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing, University of Antwerp
- Biomedical Informatics Research Network Antwerp
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Mortimer KJ, Cruz AA, Sepúlveda-Pachón IT, Jorga A, Vroling H, Williams C. Global herpes zoster burden in adults with asthma: a systematic review and meta-analysis. Eur Respir J 2024; 64:2400462. [PMID: 38901886 PMCID: PMC11306804 DOI: 10.1183/13993003.00462-2024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2024] [Accepted: 06/12/2024] [Indexed: 06/22/2024]
Abstract
BACKGROUND Asthma is a common respiratory disease, which may be associated with an increased risk of herpes zoster (HZ), often a debilitating disease associated with severe pain. This is the first systematic review with the objective of summarising evidence on HZ burden in adults with asthma. METHODS A global systematic literature review and meta-analysis was conducted (MEDLINE and Embase, 2003-2024) on HZ burden (incidence, risk and complications) in adults (≥18 years) with asthma. RESULTS There were 19 studies included on HZ outcomes in adults with asthma. Pooled HZ incidence per 1000 person-years was 5.71 (95% CI 4.68-6.96) in adults aged ≥18 years (4.20 (95% CI 3.09-5.70) in those aged <60 years versus 10.33 (95% CI 9.17-11.64) in those aged ≥60 years). The pooled rate ratio for developing HZ was 1.23 (95% CI 1.11-1.35) in those aged ≥18 years and 1.36 (95% CI 1.15-1.61) in those aged ≥50 years. The risk of HZ was higher in people with asthma using systemic corticosteroids, long-acting β-agonists plus inhaled corticosteroids and "add-on therapy". Asthma was also associated with an increased risk of post-herpetic neuralgia (OR 1.21, 95% CI 1.06-1.37) and HZ ophthalmicus (OR 1.9, 95% CI 1.1-3.2). Differences in study design, setting, case definitions and follow-up durations led to heterogeneity. CONCLUSIONS This systematic literature review and meta-analysis found that adults with asthma have an increased risk of HZ, with higher risks in older age groups and in those on certain treatments, such as oral corticosteroids. HZ vaccines are available for adults, including those with comorbidities such as asthma, and can be considered as part of integrated respiratory care.
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Affiliation(s)
- Kevin J Mortimer
- Cambridge Africa, Department of Pathology, University of Cambridge, Cambridge, UK
- Department of Paediatrics and Child Health, School of Clinical Medicine, College of Health Sciences, University of KwaZulu Natal, Durban, South Africa
- Respiratory Medicine, Liverpool University Hospitals NHS Foundation Trust, Liverpool, UK
| | - Alvaro A Cruz
- ProAR Foundation and Federal University of Bahia, Salvador, Brazil
| | | | | | - Hilde Vroling
- Pallas Health Research and Consultancy, a P95 company, Rotterdam, The Netherlands
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5
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Boeren M, de Vrij N, Ha MK, Valkiers S, Souquette A, Gielis S, Kuznetsova M, Schippers J, Bartholomeus E, Van den Bergh J, Michels N, Aerts O, Leysen J, Bervoets A, Lambert J, Leuridan E, Wens J, Peeters K, Emonds MP, Elias G, Vandamme N, Jansens H, Adriaensen W, Suls A, Vanhee S, Hens N, Smits E, Van Damme P, Thomas PG, Beutels P, Ponsaerts P, Van Tendeloo V, Delputte P, Laukens K, Meysman P, Ogunjimi B. Lack of functional TCR-epitope interaction is associated with herpes zoster through reduced downstream T cell activation. Cell Rep 2024; 43:114062. [PMID: 38588339 DOI: 10.1016/j.celrep.2024.114062] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Revised: 02/23/2024] [Accepted: 03/21/2024] [Indexed: 04/10/2024] Open
Abstract
The role of T cell receptor (TCR) diversity in infectious disease susceptibility is not well understood. We use a systems immunology approach on three cohorts of herpes zoster (HZ) patients and controls to investigate whether TCR diversity against varicella-zoster virus (VZV) influences the risk of HZ. We show that CD4+ T cell TCR diversity against VZV glycoprotein E (gE) and immediate early 63 protein (IE63) after 1-week culture is more restricted in HZ patients. Single-cell RNA and TCR sequencing of VZV-specific T cells shows that T cell activation pathways are significantly decreased after stimulation with VZV peptides in convalescent HZ patients. TCR clustering indicates that TCRs from HZ patients co-cluster more often together than TCRs from controls. Collectively, our results suggest that not only lower VZV-specific TCR diversity but also reduced functional TCR affinity for VZV-specific proteins in HZ patients leads to lower T cell activation and consequently affects the susceptibility for viral reactivation.
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Affiliation(s)
- Marlies Boeren
- Laboratory of Microbiology, Parasitology and Hygiene (LMPH), University of Antwerp, Antwerp, Belgium; Laboratory of Experimental Hematology (LEH), Vaccine and Infectious Disease Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium; Antwerp Center for Translational Immunology and Virology (ACTIV), Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium; Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), Antwerp, Belgium; Centre for Health Economics Research and Modelling Infectious Diseases (CHERMID), Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium
| | - Nicky de Vrij
- Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), Antwerp, Belgium; Adrem Data Lab, Department of Mathematics and Computer Science, University of Antwerp, Antwerp, Belgium; Biomedical Informatics Research Network Antwerp (biomina), University of Antwerp, Antwerp, Belgium; Clinical Immunology Unit, Department of Clinical Sciences, Institute of Tropical Medicine, Antwerp, Belgium
| | - My K Ha
- Antwerp Center for Translational Immunology and Virology (ACTIV), Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium; Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), Antwerp, Belgium; Centre for Health Economics Research and Modelling Infectious Diseases (CHERMID), Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium
| | - Sebastiaan Valkiers
- Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), Antwerp, Belgium; Adrem Data Lab, Department of Mathematics and Computer Science, University of Antwerp, Antwerp, Belgium; Biomedical Informatics Research Network Antwerp (biomina), University of Antwerp, Antwerp, Belgium
| | - Aisha Souquette
- Department of Immunology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Sofie Gielis
- Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), Antwerp, Belgium; Adrem Data Lab, Department of Mathematics and Computer Science, University of Antwerp, Antwerp, Belgium; Biomedical Informatics Research Network Antwerp (biomina), University of Antwerp, Antwerp, Belgium
| | - Maria Kuznetsova
- Antwerp Center for Translational Immunology and Virology (ACTIV), Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium; Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), Antwerp, Belgium; Centre for Health Economics Research and Modelling Infectious Diseases (CHERMID), Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium
| | - Jolien Schippers
- Antwerp Center for Translational Immunology and Virology (ACTIV), Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium; Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), Antwerp, Belgium; Centre for Health Economics Research and Modelling Infectious Diseases (CHERMID), Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium
| | - Esther Bartholomeus
- Antwerp Center for Translational Immunology and Virology (ACTIV), Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium; Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), Antwerp, Belgium; Centre for Health Economics Research and Modelling Infectious Diseases (CHERMID), Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium
| | - Johan Van den Bergh
- Laboratory of Experimental Hematology (LEH), Vaccine and Infectious Disease Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium
| | - Nele Michels
- Department of Family Medicine and Population Health (FAMPOP), Center for General Practice/Family Medicine, University of Antwerp, Antwerp, Belgium
| | - Olivier Aerts
- Department of Dermatology, Antwerp University Hospital and University of Antwerp, Antwerp, Belgium
| | - Julie Leysen
- Department of Dermatology, Antwerp University Hospital and University of Antwerp, Antwerp, Belgium
| | - An Bervoets
- Department of Dermatology, Antwerp University Hospital and University of Antwerp, Antwerp, Belgium
| | - Julien Lambert
- Department of Dermatology, Antwerp University Hospital and University of Antwerp, Antwerp, Belgium
| | - Elke Leuridan
- Centre for the Evaluation of Vaccination (CEV), Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium
| | - Johan Wens
- Department of Family Medicine and Population Health (FAMPOP), Center for General Practice/Family Medicine, University of Antwerp, Antwerp, Belgium
| | - Karin Peeters
- Antwerp Center for Translational Immunology and Virology (ACTIV), Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium; Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), Antwerp, Belgium; Centre for Health Economics Research and Modelling Infectious Diseases (CHERMID), Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium
| | - Marie-Paule Emonds
- Histocompatibility and Immunogenetic Laboratory, Rode Kruis-Vlaanderen, Mechelen, Belgium
| | - George Elias
- Laboratory of Experimental Hematology (LEH), Vaccine and Infectious Disease Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium; Antwerp Center for Translational Immunology and Virology (ACTIV), Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium; Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), Antwerp, Belgium; Centre for Health Economics Research and Modelling Infectious Diseases (CHERMID), Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium
| | - Niels Vandamme
- Data Mining and Modeling for Biomedicine Group, VIB-UGent Center for Inflammation Research, 9052 Ghent, Belgium; Department of Applied Mathematics, Computer Science and Statistics, Ghent University, Ghent, Belgium
| | - Hilde Jansens
- Department of Clinical Microbiology, Antwerp University Hospital, Antwerp, Belgium
| | - Wim Adriaensen
- Clinical Immunology Unit, Department of Clinical Sciences, Institute of Tropical Medicine, Antwerp, Belgium
| | - Arvid Suls
- Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), Antwerp, Belgium; Medical Genetics, University of Antwerp and Antwerp University Hospital, Antwerp, Belgium
| | - Stijn Vanhee
- Laboratory of Immunoregulation and Mucosal Immunology, VIB Center for Inflammation Research, Ghent, Belgium; Department of Internal Medicine and Pediatrics, Ghent University, Ghent, Belgium; Department of Head and Skin, Ghent University, Ghent, Belgium
| | - Niel Hens
- Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), Antwerp, Belgium; Centre for Health Economics Research and Modelling Infectious Diseases (CHERMID), Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium; I-BioStat, Data Science Institute, Hasselt University, Hasselt, Belgium
| | - Evelien Smits
- Laboratory of Experimental Hematology (LEH), Vaccine and Infectious Disease Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium; Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), Antwerp, Belgium
| | - Pierre Van Damme
- Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), Antwerp, Belgium; Centre for the Evaluation of Vaccination (CEV), Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium
| | - Paul G Thomas
- Department of Immunology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Philippe Beutels
- Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), Antwerp, Belgium; Centre for Health Economics Research and Modelling Infectious Diseases (CHERMID), Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium
| | - Peter Ponsaerts
- Laboratory of Experimental Hematology (LEH), Vaccine and Infectious Disease Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium
| | - Viggo Van Tendeloo
- Laboratory of Experimental Hematology (LEH), Vaccine and Infectious Disease Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium; Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), Antwerp, Belgium
| | - Peter Delputte
- Laboratory of Microbiology, Parasitology and Hygiene (LMPH), University of Antwerp, Antwerp, Belgium
| | - Kris Laukens
- Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), Antwerp, Belgium; Adrem Data Lab, Department of Mathematics and Computer Science, University of Antwerp, Antwerp, Belgium; Biomedical Informatics Research Network Antwerp (biomina), University of Antwerp, Antwerp, Belgium
| | - Pieter Meysman
- Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), Antwerp, Belgium; Adrem Data Lab, Department of Mathematics and Computer Science, University of Antwerp, Antwerp, Belgium; Biomedical Informatics Research Network Antwerp (biomina), University of Antwerp, Antwerp, Belgium
| | - Benson Ogunjimi
- Antwerp Center for Translational Immunology and Virology (ACTIV), Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium; Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), Antwerp, Belgium; Centre for Health Economics Research and Modelling Infectious Diseases (CHERMID), Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium; Department of Paediatrics, Antwerp University Hospital, Antwerp, Belgium.
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6
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Wen SY, Ou-Yang C, Chang C, Chen CC, Chang HY. Impact of Type 1 Versus Type 2 Diabetes on Developing Herpes Zoster and Post-herpetic Neuralgia: A Population-based Cohort Study. Acta Derm Venereol 2023; 103:adv9400. [PMID: 37787418 PMCID: PMC10561104 DOI: 10.2340/actadv.v103.9400] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2023] [Accepted: 07/14/2023] [Indexed: 10/04/2023] Open
Abstract
Type 2 diabetes is associated with an increased risk of herpes zoster and postherpetic neuralgia. However, the association of type 1 diabetes with herpes zoster or postherpetic neuralgia remains unclear. This retrospective cohort study using Taiwan's Health Insurance Research Database included 199,566 patients with type 1 diabetes and 1,458,331 with type 2 diabetes, identified during the period 2000 to 2012. Patients with type 1 diabetes had a significantly higher risk of developing herpes zoster than those with type 2 diabetes (p < 0.001). Across all age groups, the impact of diabetes on herpes zoster was greater in type 1 than in type 2 diabetes. Patients with both type 1 and type 2 diabetes had a 1.45-fold higher risk of post-herpetic neuralgia than those without diabetes (hazard ratio 1.45, 95% confidence interval 1.28-1.65; hazard ratio 1.45, 95% confidence interval 1.37-1.52, respectively), and there was no difference between the 2 types of diabetes (hazard ratio 1.06; 95% confidence interval 0.93-1.21). The results recommend consideration of herpes zoster vaccination at an earlier age in patients with type 1 diabetes.
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Affiliation(s)
- Su-Ying Wen
- School of Management, National Taiwan University of Science and Technology, Taipei, Taiwan; Department of Dermatology, Taipei City Hospital, Renai Branch, Taipei, Taiwan; Department of Health Care Management, National Taipei University of Nursing and Health Science, Taipei, Taiwan; Department of Cosmetic Applications and Management, Mackay Junior College of Medicine, Nursing, and Management, Taipei, Taiwan; Department of Health and Welfare, University of Taipei, Taipei, Taiwan,
| | - Chao Ou-Yang
- Department of Industrial Management, National Taiwan University of Science and Technology, Taipei 106, Taiwan
| | | | - Chu-Chieh Chen
- National Taipei University of Nursing and Health Science, Taipei, Taiwan
| | - Hung-Yu Chang
- Division of Endocricrinology and Metabolism, Department of Internal Medicine, Chang Gung Memorial Hospital, Linkou, Taiwan; Health Care Center, Chang Gung Memorial Hospital, Taoyuan Branch, Taiwan.
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7
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Zeng N, Li Y, Wang Q, Chen Y, Zhang Y, Zhang L, Jiang F, Yuan W, Luo D. Development and Evaluation of a New Predictive Nomogram for Predicting Risk of Herpes Zoster Infection in a Chinese Population with Type 2 Diabetes Mellitus. Risk Manag Healthc Policy 2021; 14:4789-4797. [PMID: 34866948 PMCID: PMC8636977 DOI: 10.2147/rmhp.s310938] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2021] [Accepted: 10/20/2021] [Indexed: 12/30/2022] Open
Abstract
Purpose To identify potential risk factors for herpes zoster infection in type 2 diabetes mellitus in southeast Chinese population. Patients and Methods We built a model involving 266 herpes zoster patients collecting data from January 2018 to December 2019. The least absolute shrinkage and selection operator (Lasso) predictive model was used to test herpes zoster virus risk using the patient data. Multivariate regression was conducted to decide which variable would be the strongest to decrease the Lasso penalty. The predictive model was tested using the C-index, a calibration plot, and decision curve study. External validity was verified by bootstrapping by counting probabilities. Results In the prediction nomogram, the prediction variables included age, sex, weight, length of hospital stay, infection, and blood pressure. The C-index of 0.844 (0.798–0.896) indicated substantial variability and thus the model was adjusted appropriately. A score of 0.825 was achieved somewhere in the above interval. Examination of the decision curve estimated that herpes zoster nomogram was useful when the intervention was determined at the 16 percent of the herpes zoster infection potential threshold. Conclusion The herpes zoster nomogram combines age, weight, position of the rash, 2-hour plasma glucose, glycosuria, serum creatinine, length of the hospital stay, and hypertension. This calculator can be used to assess the individual herpes zoster risks in patients diagnosed with type 2 diabetes mellitus.
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Affiliation(s)
- Ni Zeng
- Department of Dermatology, Affiliated Hospital of Zunyi Medical University,149 Dalian Road, Huichuan District, Guizhou, 563003, People's Republic of China.,Department of Dermatology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, 210000, People's Republic of China
| | - Yueyue Li
- Department of Dermatology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, 210000, People's Republic of China
| | - Qian Wang
- Department of Endocrinology, Affiliated Hospital of Zunyi Medical University, Guizhou, 563003, People's Republic of China
| | - Yihe Chen
- Department of Dermatology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, 210000, People's Republic of China
| | - Yan Zhang
- Department of Dermatology, Affiliated Hospital of Zunyi Medical University,149 Dalian Road, Huichuan District, Guizhou, 563003, People's Republic of China
| | - Lanfang Zhang
- Department of Dermatology, Affiliated Hospital of Zunyi Medical University,149 Dalian Road, Huichuan District, Guizhou, 563003, People's Republic of China
| | - Feng Jiang
- Neonatal Department, Obstetrics and Gynecology Hospital of Fudan University, Shanghai, 200011, People's Republic of China.,Department of Pediatrics, The First Affiliated Hospital of Nanjing Medical University, Nanjing, 21000, People's Republic of China
| | - Wei Yuan
- Department of Dermatology, Affiliated Hospital of Zunyi Medical University,149 Dalian Road, Huichuan District, Guizhou, 563003, People's Republic of China
| | - Dan Luo
- Department of Dermatology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, 210000, People's Republic of China
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8
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Marra F, Parhar K, Huang B, Vadlamudi N. Risk Factors for Herpes Zoster Infection: A Meta-Analysis. Open Forum Infect Dis 2020; 7:ofaa005. [PMID: 32010734 PMCID: PMC6984676 DOI: 10.1093/ofid/ofaa005] [Citation(s) in RCA: 148] [Impact Index Per Article: 29.6] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2019] [Accepted: 01/07/2020] [Indexed: 12/19/2022] Open
Abstract
Background The burden of herpes zoster (HZ) is significant worldwide, with millions affected and the incidence rising. Current literature has identified some risk factors for this disease; however, there is yet to be a comprehensive study that pools all evidence to provide estimates of risk. Therefore, the purpose of this study is to identify various risk factors, excluding immunosuppressive medication, that may predispose an individual to developing HZ. Methods The literature search was conducted in MEDLINE, EMBASE, and Cochrane Central, yielding case control, cohort, and cross-sectional studies that were pooled from January 1966 to September 2017. Search terms included the following: zoster OR herpe* OR postherpe* OR shingle* AND risk OR immunosupp* OR stress OR trauma OR gender OR ethnicity OR race OR age OR diabetes OR asthma OR chronic obstructive pulmonary disease OR diabetes. Risk ratios (RRs) for key risk factors were calculated via natural logarithms and pooled using random-effects modeling. Results From a total of 4417 identified studies, 88 were included in analysis (N = 3, 768 691 HZ cases). Immunosuppression through human immunodeficiency virus/acquired immune deficiency syndrome (RR = 3.22; 95% confidence interval [CI], 2.40–4.33) or malignancy (RR = 2.17; 95% CI, 1.86–2.53) significantly increased the risk of HZ compared with controls. Family history was also associated with a greater risk (RR = 2.48; 95% CI, 1.70–3.60), followed by physical trauma (RR = 2.01; 95% CI, 1.39–2.91) and older age (RR = 1.65; 95% CI, 1.37–1.97). A slightly smaller risk was seen those with psychological stress, females, and comorbidities such as diabetes, rheumatoid arthritis, cardiovascular diseases, renal disease, systemic lupus erythematosus, and inflammatory bowel disease compared with controls (RR range, 2.08–1.23). We found that black race had lower rates of HZ development (RR = 0.69; 95% CI, 0.56–0.85). Conclusions This study demonstrated a number of risk factors for development of HZ infection. However, many of these characteristics are known well in advance by the patient and clinician and may be used to guide discussions with patients for prevention by vaccination.
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Affiliation(s)
- Fawziah Marra
- Faculty of Pharmaceutical Sciences, University of British Columbia, Vancouver, British Columbia, Canada
| | - Kamalpreet Parhar
- Faculty of Pharmaceutical Sciences, University of British Columbia, Vancouver, British Columbia, Canada
| | - Bill Huang
- Faculty of Pharmaceutical Sciences, University of British Columbia, Vancouver, British Columbia, Canada
| | - Nirma Vadlamudi
- Faculty of Pharmaceutical Sciences, University of British Columbia, Vancouver, British Columbia, Canada
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9
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Saadatian-Elahi M, Bauduceau B, Del-Signore C, Vanhems P. Diabetes as a risk factor for herpes zoster in adults: A synthetic literature review. Diabetes Res Clin Pract 2020; 159:107983. [PMID: 31846665 DOI: 10.1016/j.diabres.2019.107983] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/09/2019] [Revised: 11/28/2019] [Accepted: 12/12/2019] [Indexed: 01/26/2023]
Abstract
AIM The objective of this review was to evaluate the role of diabetes as a risk factor for herpes zoster (HZ) and to discuss implications of prevention by vaccination with available HZ vaccines. METHODS We reviewed studies that investigated the incidence rates of HZ in patients with diabetes. Papers in English or French published between January 2000 and December 2018 have been selected from PubMed and Google Scholarship by using appropriate key words. RESULTS The risk of HZ was significantly higher in patients with diabetes as compared to controls in 11 studies out of 16, although the magnitude of risk associated to diabetes varied across studies from 1.06 to 2.38 (p < 0.05). The incidence of HZ in patients with diabetes increased with age and was higher in women than in men. The incidence of the most common complication of HZ, i.e. post-herpetic neuralgia was also higher in patients with diabetes. CONCLUSIONS The presence of HZ adds supplementary complications to the pre-existing comorbidity in patients with diabetes. Investigating the impact of preventive measure by HZ vaccination is therefore of paramount importance in patients with diabetes.
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Affiliation(s)
- Mitra Saadatian-Elahi
- Service d'Hygiène, Epidémiologie et Prévention, Hospices Civils de Lyon, F-69437 Lyon, France; Laboratoire des Pathogènes Emergents - Fondation Mérieux, Centre International de Recherche en Infectiologie, Institut National de la Santé et de la Recherche Médicale U1111, Centre National de la Recherche Scientifique, UMR5308, Ecole Normale Supérieure de Lyon, Université Claude Bernard Lyon 1, 21, Avenue Tony Garnier, 69007 Lyon, France.
| | | | - Corinne Del-Signore
- Service d'Hygiène, Epidémiologie et Prévention, Hospices Civils de Lyon, F-69437 Lyon, France; Laboratoire des Pathogènes Emergents - Fondation Mérieux, Centre International de Recherche en Infectiologie, Institut National de la Santé et de la Recherche Médicale U1111, Centre National de la Recherche Scientifique, UMR5308, Ecole Normale Supérieure de Lyon, Université Claude Bernard Lyon 1, 21, Avenue Tony Garnier, 69007 Lyon, France
| | - Philippe Vanhems
- Service d'Hygiène, Epidémiologie et Prévention, Hospices Civils de Lyon, F-69437 Lyon, France; Laboratoire des Pathogènes Emergents - Fondation Mérieux, Centre International de Recherche en Infectiologie, Institut National de la Santé et de la Recherche Médicale U1111, Centre National de la Recherche Scientifique, UMR5308, Ecole Normale Supérieure de Lyon, Université Claude Bernard Lyon 1, 21, Avenue Tony Garnier, 69007 Lyon, France; Inserm, F-CRIN, Innovative Clinical Research Network in Vaccinology (I-REIVAC), CIC 1417, Paris, France
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10
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Schmidt SAJ, Langan SM, Pedersen HS, Schønheyder HC, Thomas SL, Smeeth L, Mansfield KE, Sørensen HT, Forbes HJ, Vestergaard M. Mood Disorders and Risk of Herpes Zoster in 2 Population-Based Case-Control Studies in Denmark and the United Kingdom. Am J Epidemiol 2018; 187:1019-1028. [PMID: 29053820 PMCID: PMC5968637 DOI: 10.1093/aje/kwx338] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2017] [Revised: 10/08/2017] [Accepted: 10/09/2017] [Indexed: 11/14/2022] Open
Abstract
We examined the association between mood disorders and risk of herpes zoster in two case-control studies using data from nationwide Danish registries and practices in the UK Clinical Practice Research Datalink. We included incident zoster cases diagnosed in general practice (using systemic antivirals as a proxy in Denmark) or hospital during 1997-2013 in Denmark (n = 190,671) and during 2000-2013 in the United Kingdom (n = 177,361). We risk-set sampled 4 matched population controls per case. Conditional logistic regression analyses adjusting for zoster risk factors showed that the odds ratios for previous mood disorder among cases versus controls were 1.15 (99% confidence interval (CI): 1.12, 1.19; prevalence 7.1% vs. 6.0%) in Denmark and 1.12 (99% CI: 1.11, 1.14; prevalence 31.6% vs. 29.2%) in the United Kingdom. In Denmark, odds ratios were higher for anxiety (1.23; 99% CI: 1.17, 1.30) and severe stress and adjustment disorder (1.24; 99% CI: 1.18, 1.30) than for depression (1.11; 99% CI: 1.07, 1.14). In the United Kingdom, odds ratios for these conditions were similar: 1.12 (99% CI: 1.10, 1.13), 1.12 (99% CI: 1.10, 1.14), and 1.14 (99% CI: 1.10, 1.19) for depression, anxiety, and severe stress and adjustment disorder, respectively. In conclusion, mood disorders were associated with an increased risk of zoster.
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Affiliation(s)
- Sigrun A J Schmidt
- Department of Clinical Epidemiology, Aarhus University Hospital, Aarhus, Denmark
- Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Sinéad M Langan
- Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Henrik S Pedersen
- Research Unit for General Practice, Department of Public Health, Aarhus University, Aarhus, Denmark
| | - Henrik C Schønheyder
- Department of Clinical Microbiology, Aalborg University Hospital, Aalborg, Denmark
- Department of Clinical Medicine, Aalborg University, Aalborg, Denmark
| | - Sara L Thomas
- Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Liam Smeeth
- Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Kathryn E Mansfield
- Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Henrik T Sørensen
- Department of Clinical Epidemiology, Aarhus University Hospital, Aarhus, Denmark
| | - Harriet J Forbes
- Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Mogens Vestergaard
- Research Unit for General Practice, Department of Public Health, Aarhus University, Aarhus, Denmark
- Section for General Practice, Department of Public Health, Aarhus University, Aarhus, Denmark
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11
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Meysman P, De Neuter N, Bartholomeus E, Elias G, Van den Bergh J, Emonds MP, Haasnoot GW, Heynderickx S, Wens J, Michels NR, Lambert J, Lion E, Claas FHJ, Goossens H, Smits E, Van Damme P, Van Tendeloo V, Beutels P, Suls A, Mortier G, Laukens K, Ogunjimi B. Increased herpes zoster risk associated with poor HLA-A immediate early 62 protein (IE62) affinity. Immunogenetics 2017; 70:363-372. [PMID: 29196796 DOI: 10.1007/s00251-017-1047-x] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2017] [Accepted: 11/20/2017] [Indexed: 01/08/2023]
Abstract
Around 30% of individuals will develop herpes zoster (HZ), caused by the varicella zoster virus (VZV), during their life. While several risk factors for HZ, such as immunosuppressive therapy, are well known, the genetic and molecular components that determine the risk of otherwise healthy individuals to develop HZ are still poorly understood. We created a computational model for the Human Leukocyte Antigen (HLA-A, -B, and -C) presentation capacity of peptides derived from the VZV Immediate Early 62 (IE62) protein. This model could then be applied to a HZ cohort with known HLA molecules. We found that HLA-A molecules with poor VZV IE62 presentation capabilities were more common in a cohort of 50 individuals with a history of HZ compared to a nationwide control group, which equated to a HZ risk increase of 60%. This tendency was most pronounced for cases of HZ at a young age, where other risk factors are less prevalent. These findings provide new molecular insights into the development of HZ and reveal a genetic predisposition in those individuals most at risk to develop HZ.
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Affiliation(s)
- Pieter Meysman
- ADREM Data Lab, Department of Mathematics and Computer Science, University of Antwerp, 2020, Antwerp, Belgium. .,Biomedical Informatics Research Network Antwerp (biomina), University of Antwerp, 2020, Antwerp, Belgium. .,Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), University of Antwerp, 2020, Antwerp, Belgium.
| | - Nicolas De Neuter
- ADREM Data Lab, Department of Mathematics and Computer Science, University of Antwerp, 2020, Antwerp, Belgium.,Biomedical Informatics Research Network Antwerp (biomina), University of Antwerp, 2020, Antwerp, Belgium.,Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), University of Antwerp, 2020, Antwerp, Belgium
| | - Esther Bartholomeus
- Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), University of Antwerp, 2020, Antwerp, Belgium.,Center for Medical Genetics, Antwerp University Hospital, 2650, Edegem, Belgium.,Center for Medical Genetics, University of Antwerp, 2650, Edegem, Belgium
| | - George Elias
- Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), University of Antwerp, 2020, Antwerp, Belgium.,Laboratory of Experimental Hematology (LEH), Vaccine and Infectious Disease Institute (VAXINFECTIO), University of Antwerp, 2650, Antwerp, Belgium.,Center for Cell Therapy and Regenerative Medicine, Antwerp University Hospital, 2650, Edegem, Belgium
| | - Johan Van den Bergh
- Laboratory of Experimental Hematology (LEH), Vaccine and Infectious Disease Institute (VAXINFECTIO), University of Antwerp, 2650, Antwerp, Belgium
| | - Marie-Paule Emonds
- Laboratory for Histocompatibility and Immunogenetics (HILA), Red Cross Flanders, 2800, Mechelen, Belgium
| | - Geert W Haasnoot
- Department of Immunohaematology and Blood Transfusion, Leiden University Medical Center, 2300, Leiden, The Netherlands
| | - Steven Heynderickx
- Laboratory of Experimental Hematology (LEH), Vaccine and Infectious Disease Institute (VAXINFECTIO), University of Antwerp, 2650, Antwerp, Belgium.,Center for Cell Therapy and Regenerative Medicine, Antwerp University Hospital, 2650, Edegem, Belgium
| | - Johan Wens
- Department of Primary and Interdisciplinary Care, University of Antwerp, 2610, Wilrijk, Belgium
| | - Nele R Michels
- Department of Primary and Interdisciplinary Care, University of Antwerp, 2610, Wilrijk, Belgium
| | - Julien Lambert
- Department of Dermatology, Antwerp University Hospital/University of Antwerp, 2650, Edegem, Belgium
| | - Eva Lion
- Laboratory of Experimental Hematology (LEH), Vaccine and Infectious Disease Institute (VAXINFECTIO), University of Antwerp, 2650, Antwerp, Belgium.,Center for Cell Therapy and Regenerative Medicine, Antwerp University Hospital, 2650, Edegem, Belgium
| | - Frans H J Claas
- Department of Immunohaematology and Blood Transfusion, Leiden University Medical Center, 2300, Leiden, The Netherlands
| | - Herman Goossens
- Department of Laboratory Medicine, Antwerp University Hospital, 2650, Edegem, Belgium.,Lab of Medical Microbiology (LMM), Vaccine and Infectious Disease Institute (VAXINFECTIO), University of Antwerp, 2610, Antwerp, Belgium
| | - Evelien Smits
- Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), University of Antwerp, 2020, Antwerp, Belgium.,Laboratory of Experimental Hematology (LEH), Vaccine and Infectious Disease Institute (VAXINFECTIO), University of Antwerp, 2650, Antwerp, Belgium.,Center for Cell Therapy and Regenerative Medicine, Antwerp University Hospital, 2650, Edegem, Belgium.,Center for Oncological Research Antwerp, University of Antwerp, 2610, Antwerp, Belgium
| | - Pierre Van Damme
- Centre for the Evaluation of Vaccination, Vaccine and Infectious Disease Institute (VAXINFECTIO), University of Antwerp, 2610, Antwerp, Belgium
| | - Viggo Van Tendeloo
- Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), University of Antwerp, 2020, Antwerp, Belgium.,Laboratory of Experimental Hematology (LEH), Vaccine and Infectious Disease Institute (VAXINFECTIO), University of Antwerp, 2650, Antwerp, Belgium
| | - Philippe Beutels
- Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), University of Antwerp, 2020, Antwerp, Belgium.,Centre for Health Economics Research and Modeling Infectious Diseases (CHERMID), Vaccine and Infectious Disease Institute (VAXINFECTIO), University of Antwerp, 2610, Antwerp, Belgium.,School of Public Health and Community Medicine, The University of New South Wales, Sydney, NSW, 2052, Australia
| | - Arvid Suls
- Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), University of Antwerp, 2020, Antwerp, Belgium.,Center for Medical Genetics, Antwerp University Hospital, 2650, Edegem, Belgium.,Center for Medical Genetics, University of Antwerp, 2650, Edegem, Belgium
| | - Geert Mortier
- Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), University of Antwerp, 2020, Antwerp, Belgium.,Center for Medical Genetics, Antwerp University Hospital, 2650, Edegem, Belgium.,Center for Medical Genetics, University of Antwerp, 2650, Edegem, Belgium
| | - Kris Laukens
- ADREM Data Lab, Department of Mathematics and Computer Science, University of Antwerp, 2020, Antwerp, Belgium.,Biomedical Informatics Research Network Antwerp (biomina), University of Antwerp, 2020, Antwerp, Belgium.,Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), University of Antwerp, 2020, Antwerp, Belgium
| | - Benson Ogunjimi
- Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), University of Antwerp, 2020, Antwerp, Belgium.,Laboratory of Experimental Hematology (LEH), Vaccine and Infectious Disease Institute (VAXINFECTIO), University of Antwerp, 2650, Antwerp, Belgium.,Centre for Health Economics Research and Modeling Infectious Diseases (CHERMID), Vaccine and Infectious Disease Institute (VAXINFECTIO), University of Antwerp, 2610, Antwerp, Belgium.,Department of Paediatric Nephrology and Rheumatology, Ghent University Hospital, 9000, Ghent, Belgium.,Department of Paediatrics, Antwerp University Hospital, 2650, Edegem, Belgium
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12
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Schmidt SAJ, Vestergaard M, Baggesen LM, Pedersen L, Schønheyder HC, Sørensen HT. Prevaccination epidemiology of herpes zoster in Denmark: Quantification of occurrence and risk factors. Vaccine 2017; 35:5589-5596. [PMID: 28874322 DOI: 10.1016/j.vaccine.2017.08.065] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2017] [Revised: 08/07/2017] [Accepted: 08/22/2017] [Indexed: 12/16/2022]
Abstract
BACKGROUND Herpes zoster (HZ) is a vaccine-preventable disease caused by reactivation of the varicella-zoster virus. Unfortunately, formulation of recommendations on routine immunization is hampered by a lack of data on disease burden, since most countries do not record cases of HZ in the general population. We developed and validated an algorithm to identify HZ based on routinely collected registry data and used it to quantify HZ occurrence and risk factors in Denmark prior to marketing of the HZ vaccine. METHODS We included patients aged ≥40years with a first-time systemic Acyclovir, Valacyclovir, or Famciclovir prescription or a hospital-based HZ diagnosis in the Danish nationwide health registries during 1997-2013. In a validation substudy (n=176), we computed the proportion of persons with HZ among patients who redeemed antiviral prescriptions. In a cohort study, we computed age-specific rates of HZ (45,297,258 person-years). In a case-control study, we then computed odds ratios (ORs) for common chronic diseases and immunosuppressive factors among HZ cases (n=189,025) vs. matched population controls (n=945,111). RESULTS Medical record review confirmed HZ in 87% (95% confidence interval: 79-93%) of persons ≥40years who dispensed antivirals at doses recommended for HZ. HZ rates increased from 2.15/1000 person-years in 40-year-olds to 9.45/1000 person-years in 95-year-olds. Rates were highest in women. HZ was diagnosed during hospitalization among 3.5%. As expected, persons with severe immunosuppressive conditions had the highest ORs of HZ (between 1.82 and 4.12), but various autoimmune diseases, asthma, chronic kidney disease, and inhaled glucocorticoids were also associated with increased ORs (between 1.06 and 1.64). CONCLUSION This algorithm is a valid tool for identifying HZ in routine healthcare data. It shows that HZ is common in Denmark, especially in patients with certain chronic conditions. Prioritized vaccination of such high-risk patients might be an option in countries considering alternatives to universal vaccination.
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Affiliation(s)
- Sigrun A J Schmidt
- Department of Clinical Epidemiology, Aarhus University Hospital, Aarhus, Denmark; Emergency Department, Regional Hospital of Randers, Randers, Denmark.
| | - Mogens Vestergaard
- Section for General Practice, Department of Public Health, Aarhus University, Aarhus, Denmark; Research Unit for General Practice, Department of Public Health, Aarhus University, Aarhus, Denmark
| | - Lisbeth M Baggesen
- Department of Clinical Epidemiology, Aarhus University Hospital, Aarhus, Denmark
| | - Lars Pedersen
- Department of Clinical Epidemiology, Aarhus University Hospital, Aarhus, Denmark
| | - Henrik C Schønheyder
- Department of Clinical Microbiology, Aalborg University Hospital, Aalborg, Denmark; Department of Clinical Medicine, Aalborg University, Aalborg, Denmark
| | - Henrik T Sørensen
- Department of Clinical Epidemiology, Aarhus University Hospital, Aarhus, Denmark
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13
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Hsia SCV, Chen LH, Tseng HF. Receipt of thyroid hormone deficiency treatment and risk of herpes zoster. Int J Infect Dis 2017; 59:90-95. [PMID: 28450196 DOI: 10.1016/j.ijid.2017.04.016] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2017] [Revised: 04/11/2017] [Accepted: 04/13/2017] [Indexed: 12/24/2022] Open
Abstract
OBJECTIVE Thyroid hormone (TH) has been suggested to control herpes virus gene expression and replication in neurons via epigenetics through its nuclear receptors. It has previously been shown that patients with hypothyroidism are predisposed to herpes zoster (HZ), suggesting that the TH deficiency may be a risk factor for varicella zoster virus (VZV) reactivation. The aim of this study was to test the hypothesis that TH treatment will ameliorate the complication of HZ. METHODS This study investigated the hypothesis by enquiring into a comprehensive medical database at Kaiser Permanente Southern California (KPSC) to verify whether patients taking TH medication experience a reduction in HZ occurrence. RESULTS It was shown by Kaplan-Meier analysis that hypothyroidism patients taking TH medicines had a lower risk of HZ. The fully adjusted analysis indicated that patients receiving medication for the treatment of TH deficiency exhibited a reduced risk of HZ (hazard ratio 0.60, 95% confidence interval 0.51-0.71). This lower risk of HZ was significant in all age groups except the 18-39 years cohort. In addition, female patients taking TH treatment exhibited a lower risk than their male counterparts. CONCLUSIONS Together these findings support the hypothesis that a constant level of TH will provide a degree of protection from contracting HZ. More studies are underway to evaluate the laboratory data for an analysis of hormonal effects on individuals.
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Affiliation(s)
- Shao-Chung V Hsia
- Department of Pharmaceutical Sciences, School of Pharmacy and Health Professions, University of Maryland, Eastern Shore, Princess Anne, MD 21853, USA.
| | - Lie Hong Chen
- Department of Research and Evaluation, Kaiser Permanente Research, 100 S. Los Robles Ave, 2nd Floor, Pasadena, CA 91101, USA
| | - Hung-Fu Tseng
- Department of Research and Evaluation, Kaiser Permanente Research, 100 S. Los Robles Ave, 2nd Floor, Pasadena, CA 91101, USA.
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Ogunjimi B, Willem L, Beutels P, Hens N. Integrating between-host transmission and within-host immunity to analyze the impact of varicella vaccination on zoster. eLife 2015; 4. [PMID: 26259874 PMCID: PMC4530225 DOI: 10.7554/elife.07116] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2015] [Accepted: 07/17/2015] [Indexed: 01/22/2023] Open
Abstract
Varicella-zoster virus (VZV) causes chickenpox and reactivation of latent VZV causes herpes zoster (HZ). VZV reactivation is subject to the opposing mechanisms of declining and boosted VZV-specific cellular mediated immunity (CMI). A reduction in exogenous re-exposure ‘opportunities’ through universal chickenpox vaccination could therefore lead to an increase in HZ incidence. We present the first individual-based model that integrates within-host data on VZV-CMI and between-host transmission data to simulate HZ incidence. This model allows estimating currently unknown pivotal biomedical parameters, including the duration of exogenous boosting at 2 years, with a peak threefold to fourfold increase of VZV-CMI; the VZV weekly reactivation probability at 5% and VZV subclinical reactivation having no effect on VZV-CMI. A 100% effective chickenpox vaccine given to 1 year olds would cause a 1.75 times peak increase in HZ 31 years after implementation. This increase is predicted to occur mainly in younger age groups than is currently assumed. DOI:http://dx.doi.org/10.7554/eLife.07116.001 The itchy-scratchy misery of a chickenpox was until recently a rite of passage for children around the world. The varicella-zoster virus causes chickenpox infections. This virus persists in small numbers in nerve cells for many years after infection, and can reactivate from these cells. Often this reactivation causes no symptoms, but sometimes it results in a painful skin condition called shingles (or herpes zoster), especially in older adults. Some countries—including the United States, Australia, Taiwan and Greece—have virtually wiped out childhood cases of chickenpox by requiring that children be vaccinated against the varicella-zoster virus. But some countries have hesitated. One reason for this hesitation is that exposure to individuals with a chickenpox infection helps boost the immunity of individuals who have previously been infected. This may help reduce the likelihood of these people developing shingles later in life. So, some countries have worried that chickenpox vaccinations might inadvertently increase the number of shingles cases. To assess this risk, many scientists have created computer models, but the models have some limitations. Now, Ogunjimi et al. report a new individual-based model to assess the effect of childhood varicella vaccination on shingles cases that factors in the immune responses to varicella infection. The model suggests that re-exposure to the varicella virus through contact with infected people would only provide extra protection for about two years; this is much shorter than previous predictions that suggested it might last 20 years. The model also predicts that implementing a varicella vaccination program for children would almost double the number of shingles cases 31 years later. But this increase would be temporary. The predicted increase in shingles cases is likely to disproportionately occur among 31- to 40-year-olds. This is unexpected because most previous models predict that older age groups would bear the brunt of a rise in shingles, but this younger population would be less likely to develop lasting complications of shingles. Together, these findings may allay some fears about implementing childhood varicella vaccination programs by showing that the benefits of re-exposure are limited. DOI:http://dx.doi.org/10.7554/eLife.07116.002
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Affiliation(s)
- Benson Ogunjimi
- Centre for Health Economics Research and Modeling Infectious Diseases, Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium
| | - Lander Willem
- Centre for Health Economics Research and Modeling Infectious Diseases, Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium
| | - Philippe Beutels
- Centre for Health Economics Research and Modeling Infectious Diseases, Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium
| | - Niel Hens
- Centre for Health Economics Research and Modeling Infectious Diseases, Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium
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15
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Ogunjimi B, Hens N, Pebody R, Jansens H, Seale H, Quinlivan M, Theeten H, Goossens H, Breuer J, Beutels P. Cytomegalovirus seropositivity is associated with herpes zoster. Hum Vaccin Immunother 2015; 11:1394-9. [PMID: 25905443 PMCID: PMC4514428 DOI: 10.1080/21645515.2015.1037999] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2014] [Revised: 03/12/2015] [Accepted: 03/30/2015] [Indexed: 10/23/2022] Open
Abstract
Herpes zoster (HZ) is caused by VZV reactivation that is facilitated by a declined immunity against varicella-zoster virus (VZV), but also occurs in immunocompetent individuals. Cytomegalovirus (CMV) infection is associated with immunosenescence meaning that VZV-specific T-cells could be less responsive. This study aimed to determine whether CMV infection could be a risk factor for the development of HZ. CMV IgG serostatus was determined in stored serum samples from previously prospectively recruited ambulatory adult HZ patients in the UK (N = 223) in order to compare the results with those from UK population samples (N = 1545) by means of a logistic regression (controlling for age and gender). Furthermore, we compared the UK population CMV seroprevalence with those from population samples from other countries (from Belgium (N1 = 1741, N2 = 576), USA (N = 5572) and Australia (N = 2080)). Furthermore, CMV IgG titers could be compared between UK HZ patients and Belgium N2 population samples because the same experimental set-up for analysis was used. We found UK ambulatory HZ patients to have a higher CMV seroprevalence than UK population samples (OR 1.56 [1.11 2.19]). CMV IgG seropositivity was a significant risk factor for HZ in the UK (OR 3.06 [1.32 7.04]. Furthermore, high CMV IgG titers (exceeding the upper threshold) were less abundant in CMV-seropositive Belgian N2 population samples than in CMV-seropositive UK HZ patients (OR 0.51 [0.31 0.82]. We found CMV-seroprevalence to increase faster with age in the UK than in other countries (P < 0.05). We conclude that CMV IgG seropositivity is associated with HZ. This finding could add to the growing list of risk factors for HZ.
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Affiliation(s)
- Benson Ogunjimi
- Centre for Health Economics Research & Modeling Infectious Diseases (CHERMID); Vaccine & Infectious Disease Institute (VAXINFECTIO); University of Antwerp; Antwerp, Belgium
- Interuniversity Institute for Biostatistics and statistical Bioinformatics (I-BIOSTAT); Hasselt University; Hasselt, Belgium
| | - Niel Hens
- Centre for Health Economics Research & Modeling Infectious Diseases (CHERMID); Vaccine & Infectious Disease Institute (VAXINFECTIO); University of Antwerp; Antwerp, Belgium
- Interuniversity Institute for Biostatistics and statistical Bioinformatics (I-BIOSTAT); Hasselt University; Hasselt, Belgium
| | - Richard Pebody
- Respiratory Diseases Department; Public Health England; London, UK
| | - Hilde Jansens
- Department of Laboratory Medicine; Antwerp University Hospital; Edegem, Belgium
| | - Holly Seale
- School of Public Health and Community Medicine; The University of New South Wales; Sydney, Australia
| | - Mark Quinlivan
- Division of Infection and Immunity; University College London; London, UK
| | - Heidi Theeten
- Centre for the Evaluation of Vaccination (CEV); Vaccine & Infectious Disease Institute (VAXINFECTIO); University of Antwerp; Antwerp, Belgium
| | - Herman Goossens
- Department of Laboratory Medicine; Antwerp University Hospital; Edegem, Belgium
- Laboratory of Medical Microbiology; Vaccine & Infectious Disease Institute (VAXINFECTIO); University of Antwerp; Antwerp, Belgium
| | - Judy Breuer
- Division of Infection and Immunity; University College London; London, UK
| | - Philippe Beutels
- Centre for Health Economics Research & Modeling Infectious Diseases (CHERMID); Vaccine & Infectious Disease Institute (VAXINFECTIO); University of Antwerp; Antwerp, Belgium
- School of Public Health and Community Medicine; The University of New South Wales; Sydney, Australia
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