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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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Boeren M, Meysman P, Laukens K, Ponsaerts P, Ogunjimi B, Delputte P. T cell immunity in HSV-1- and VZV-infected neural ganglia. Trends Microbiol 2023; 31:51-61. [PMID: 35987880 DOI: 10.1016/j.tim.2022.07.008] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Revised: 07/20/2022] [Accepted: 07/21/2022] [Indexed: 11/17/2022]
Abstract
Herpesviruses hijack the MHC class I (MHC I) and class II (MHC II) antigen-presentation pathways to manipulate immune recognition by T cells. First, we illustrate herpes simplex virus-1 (HSV-1) and varicella-zoster virus (VZV) MHC immune evasion strategies. Next, we describe MHC-T cell interactions in HSV-1- and VZV- infected neural ganglia. Although studies on the topic are scarce, and use different models, most reports indicate that neuronal HSV-1 infection is mainly controlled by CD8+ T cells through noncytolytic mechanisms, whereas VZV seems to be largely controlled through CD4+ T cell-specific immune responses. Autologous human stem-cell-derived in vitro models could substantially aid in elucidating these neuroimmune interactions and are fit for studies on both herpesviruses.
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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
| | - Pieter Meysman
- Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), Antwerp, Belgium; Adrem Data Lab, Department of Computer Science, University of Antwerp, Antwerp, Belgium; Biomedical Informatics Research Network Antwerp (biomina), 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 Computer Science, University of Antwerp, Antwerp, Belgium; Biomedical Informatics Research Network Antwerp (biomina), University of Antwerp, Antwerp, Belgium
| | - Peter Ponsaerts
- Laboratory of Experimental Hematology (LEH), Vaccine and Infectious Disease Institute (VAXINFECTIO), 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 & Modeling Infectious Diseases (CHERMID), Vaccine & Infectious Disease Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium; Department of Paediatrics, Antwerp University Hospital, Antwerp, Belgium
| | - Peter Delputte
- Laboratory of Microbiology, Parasitology and Hygiene (LMPH), University of Antwerp, Antwerp, Belgium; Infla-med, University of Antwerp, Antwerp, Belgium.
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de Vrij N, Meysman P, Gielis S, Adriaensen W, Laukens K, Cuypers B. HLA-DRB1 Alleles Associated with Lower Leishmaniasis Susceptibility Share Common Amino Acid Polymorphisms and Epitope Binding Repertoires. Vaccines (Basel) 2021; 9:270. [PMID: 33803005 PMCID: PMC8002611 DOI: 10.3390/vaccines9030270] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2021] [Revised: 03/12/2021] [Accepted: 03/16/2021] [Indexed: 02/08/2023] Open
Abstract
Susceptibility for leishmaniasis is largely dependent on host genetic and immune factors. Despite the previously described association of human leukocyte antigen (HLA) gene cluster variants as genetic susceptibility factors for leishmaniasis, little is known regarding the mechanisms that underpin these associations. To better understand this underlying functionality, we first collected all known leishmaniasis-associated HLA variants in a thorough literature review. Next, we aligned and compared the protection- and risk-associated HLA-DRB1 allele sequences. This identified several amino acid polymorphisms that distinguish protection- from risk-associated HLA-DRB1 alleles. Subsequently, T cell epitope binding predictions were carried out across these alleles to map the impact of these polymorphisms on the epitope binding repertoires. For these predictions, we used epitopes derived from entire proteomes of multiple Leishmania species. Epitopes binding to protection-associated HLA-DRB1 alleles shared common binding core motifs, mapping to the identified HLA-DRB1 amino acid polymorphisms. These results strongly suggest that HLA polymorphism, resulting in differential antigen presentation, affects the association between HLA and leishmaniasis disease development. Finally, we established a valuable open-access resource of putative epitopes. A set of 14 HLA-unrestricted strong-binding epitopes, conserved across species, was prioritized for further epitope discovery in the search for novel subunit-based vaccines.
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Affiliation(s)
- Nicky de Vrij
- Department of Computer Science, University of Antwerp, 2020 Antwerp, Belgium; (N.d.V.); (P.M.); (S.G.)
- Department of Clinical Sciences, Institute of Tropical Medicine, 2000 Antwerp, Belgium;
- Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), University of Antwerp, 2020 Antwerp, Belgium
- Biomedical Informatics Network Antwerpen (Biomina), University of Antwerp, 2020 Antwerp, Belgium
| | - Pieter Meysman
- Department of Computer Science, University of Antwerp, 2020 Antwerp, Belgium; (N.d.V.); (P.M.); (S.G.)
- Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), University of Antwerp, 2020 Antwerp, Belgium
- Biomedical Informatics Network Antwerpen (Biomina), University of Antwerp, 2020 Antwerp, Belgium
| | - Sofie Gielis
- Department of Computer Science, University of Antwerp, 2020 Antwerp, Belgium; (N.d.V.); (P.M.); (S.G.)
- Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), University of Antwerp, 2020 Antwerp, Belgium
- Biomedical Informatics Network Antwerpen (Biomina), University of Antwerp, 2020 Antwerp, Belgium
| | - Wim Adriaensen
- Department of Clinical Sciences, Institute of Tropical Medicine, 2000 Antwerp, Belgium;
| | - Kris Laukens
- Department of Computer Science, University of Antwerp, 2020 Antwerp, Belgium; (N.d.V.); (P.M.); (S.G.)
- Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), University of Antwerp, 2020 Antwerp, Belgium
- Biomedical Informatics Network Antwerpen (Biomina), University of Antwerp, 2020 Antwerp, Belgium
| | - Bart Cuypers
- Department of Computer Science, University of Antwerp, 2020 Antwerp, Belgium; (N.d.V.); (P.M.); (S.G.)
- Biomedical Informatics Network Antwerpen (Biomina), University of Antwerp, 2020 Antwerp, Belgium
- Department of Biomedical Sciences, Institute of Tropical Medicine, 2000 Antwerp, Belgium
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Santoro JD, Saucier LE, Tanna R, Wiegand SE, Pagarkar D, Tempchin AF, Khoshnood M, Ahsan N, Van Haren K. Inadequate Vaccine Responses in Children With Multiple Sclerosis. Front Pediatr 2021; 9:790159. [PMID: 34926358 PMCID: PMC8678906 DOI: 10.3389/fped.2021.790159] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/06/2021] [Accepted: 11/10/2021] [Indexed: 01/05/2023] Open
Abstract
Objective: Immunizations against Hepatitis B virus (HBV) and Varicella Zoster virus (VZV), are recommended for patients with pediatric onset multiple sclerosis (POMS) and may be required prior to initiation of some disease modifying therapies. However, the efficacy of routine vaccine administration in POMS has never been studied. We sought to assess the humoral mediated vaccine response to HBV and VZV in children with POMS. Methods: A multi-center retrospective chart-based review of 62 patients with POMS was performed. Clinical data and antibody titers against HBV and VZV were collected prior to initiation of disease modifying therapy or steroids and compared to institutional control data, using t-test and chi squared analysis. Results: There were low rates of immunity against both HBV and VZV (33 and 25% respectively) among individuals with POMS. Fifteen individuals (24%) were non-immune to both. Compared to institutional control data, individuals with POMS were significantly less likely to be immune to and HBV (p = 0.003, 95% CI: 0.22-0.75) and VZV (p < 0.001, 95% CI: 0.09-0.39). Interpretation: Individuals with POMS have low rates of antibody-mediated immunity against HBV and VZV, despite receiving the appropriate vaccinations. This suggests an association between POMS and systemic immune dysregulation although further study is needed.
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Affiliation(s)
- Jonathan D Santoro
- Division of Neurology, Department of Pediatrics, Children's Hospital Los Angeles, Los Angeles, CA, United States.,Department of Neurology, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | - Laura E Saucier
- Department of Neurology, Massachusetts General Hospital, Boston, MA, United States
| | - Runi Tanna
- Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | - Sarah E Wiegand
- Division of Neurology, Department of Pediatrics, Children's Hospital Los Angeles, Los Angeles, CA, United States
| | - Dania Pagarkar
- Department of Neurology, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | - Adam F Tempchin
- Department of Neurology, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | - Mellad Khoshnood
- Division of Neurology, Department of Pediatrics, Children's Hospital Los Angeles, Los Angeles, CA, United States
| | - Nusrat Ahsan
- Division of Neurology, Department of Pediatrics, Children's Hospital Los Angeles, Los Angeles, CA, United States.,Department of Neurology, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | - Keith Van Haren
- Department of Neurology, Stanford University School of Medicine, Stanford, CA, United States
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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: 102] [Impact Index Per Article: 25.5] [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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