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Gu X, Chen C, Chen Y, Zeng C, Lin Y, Guo R, Xu S, Lin C. Bioinformatics approach reveals the critical role of inflammation-related genes in age-related hearing loss. Sci Rep 2025; 15:2687. [PMID: 39837906 PMCID: PMC11751394 DOI: 10.1038/s41598-024-83428-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2024] [Accepted: 12/16/2024] [Indexed: 01/23/2025] Open
Abstract
Age-related hearing loss (ARHL) is the most prevalent sensory impairment in the elderly. However, the pathogenesis of ARHL remains unclear. This study was aimed to explore the potential inflammation-related genes of ARHL and suggest novel therapeutic targets for this condition. Initially, a total of 105 Inflammatory related differentially expressed genes (IRDEGs) were obtained by overlapping the differentially expressed genes from the GSE49522 and GSE49543 datasets with Inflammatory related genes. The IRDEGs were mainly enriched in MAPK, PI3K-Akt, Hippo and JAK-STAT pathways by analysis of Gene Ontology and Kyoto Encyclopedia of Genes and Genomes. We then identified 10 key IRDEGs including Alox5ap, Chil1, Clec7a, Dysf, Fcgr3, etc. using Least absolute shrinkage and selection operator regression analysis and converted them into human genes. The ROC curve indicated that Alox5ap expression presented a high accuracy in distinguishing between different groups. By CIBERSORT algorithm, 8 humanized key IRDEGs were correlated with the infiltration abundance of 3 immune cells. Finally, it showed that the Alox5ap expression was significantly more effective compared to other variables in the diagnostic model of ARHL. This study suggests that inflammation might play a role in the development of ARHL, providing a deeper understanding of the underlying causes of this disease.
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Affiliation(s)
- Xi Gu
- Department of Otorhinolaryngology Head and Neck Surgery, The First Affiliated Hospital, Fujian Medical University, Fuzhou, China
- Department of Otorhinolaryngology Head and Neck Surgery, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, China
- Fujian Institute of Otolaryngology, The First Affiliated Hospital, Fujian Medical University, Fuzhou, China
| | - Chenyu Chen
- ENT Institute, Department of Otorhinolaryngology, Eye & ENT Hospital, Fudan University, Shanghai, China
- NHC Key Laboratory of Hearing Medicine, Shanghai, China
| | - Yuqing Chen
- Department of Otorhinolaryngology Head and Neck Surgery, The First Affiliated Hospital, Fujian Medical University, Fuzhou, China
- Department of Otorhinolaryngology Head and Neck Surgery, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, China
- Fujian Institute of Otolaryngology, The First Affiliated Hospital, Fujian Medical University, Fuzhou, China
| | - Chaojun Zeng
- Department of Otorhinolaryngology Head and Neck Surgery, The First Affiliated Hospital, Fujian Medical University, Fuzhou, China
- Department of Otorhinolaryngology Head and Neck Surgery, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, China
- Fujian Institute of Otolaryngology, The First Affiliated Hospital, Fujian Medical University, Fuzhou, China
| | - Yanchun Lin
- Department of Otorhinolaryngology Head and Neck Surgery, The First Affiliated Hospital, Fujian Medical University, Fuzhou, China
- Department of Otorhinolaryngology Head and Neck Surgery, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, China
- Fujian Institute of Otolaryngology, The First Affiliated Hospital, Fujian Medical University, Fuzhou, China
| | - Ruosi Guo
- Fujian Medical University, Fuzhou, China
| | - Shujin Xu
- Fujian Medical University, Fuzhou, China
| | - Chang Lin
- Department of Otorhinolaryngology Head and Neck Surgery, The First Affiliated Hospital, Fujian Medical University, Fuzhou, China.
- Department of Otorhinolaryngology Head and Neck Surgery, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, China.
- Fujian Institute of Otolaryngology, The First Affiliated Hospital, Fujian Medical University, Fuzhou, China.
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Li Y, Jin J, Kang X, Feng Z. Identifying and Evaluating Biological Markers of Postherpetic Neuralgia: A Comprehensive Review. Pain Ther 2024; 13:1095-1117. [PMID: 39126594 PMCID: PMC11393369 DOI: 10.1007/s40122-024-00640-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2024] [Accepted: 07/11/2024] [Indexed: 08/12/2024] Open
Abstract
Postherpetic neuralgia (PHN) manifests as persistent chronic pain that emerges after a herpes zoster outbreak and greatly diminishes quality of life. Unfortunately, its treatment efficacy has remained elusive, with many therapeutic efforts yielding less than satisfactory results. The research to discern risk factors predicting the onset, trajectory, and prognosis of PHN has been extensive. However, these risk factors often present as nonspecific and diverse, indicating the need for more reliable, measurable, and objective detection methods. The exploration of potential biological markers, including hematological indices, pathological insights, and supportive tests, is increasing. This review highlights potential biomarkers that are instrumental for the diagnosis, management, and prognosis of PHN while also delving deeper into its genesis. Drawing from prior research, aspects such as immune responsiveness, neuronal injury, genetic makeup, cellular metabolism, and pain signal modulation have emerged as prospective biomarkers. The immune spectrum spans various cell subtypes, with an emphasis on T cells, interferons, interleukins, and other related cytokines. Studies on nerve injury are directed toward pain-related proteins and the density and health of epidermal nerve fibers. On the genetic and metabolic fronts, the focus lies in the detection of predisposition genes, atypical protein manifestations, and energy-processing dynamics, with a keen interest in vitamin metabolism. Tools such as functional magnetic resonance imaging, electromyography, and infrared imaging have come to the forefront in the pain signaling domain. This review compiles the evidence, potential clinical implications, and challenges associated with these promising biomarkers, paving the way for innovative strategies for predicting, diagnosing, and addressing PHN.
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Affiliation(s)
- Yunze Li
- Department of Pain Medicine, The First Affiliated Hospital, Zhejiang University School of Medicine, No. 79 Qingchun Road, Hangzhou, 310003, Zhejiang, China
| | - Jiali Jin
- Department of Pain Medicine, The First Affiliated Hospital, Zhejiang University School of Medicine, No. 79 Qingchun Road, Hangzhou, 310003, Zhejiang, China
| | - Xianhui Kang
- Department of Anesthesiology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Zhiying Feng
- Department of Pain Medicine, The First Affiliated Hospital, Zhejiang University School of Medicine, No. 79 Qingchun Road, Hangzhou, 310003, Zhejiang, 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: 0] [Impact Index Per Article: 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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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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5
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Torki E, Hoseininasab F, Moradi M, Sami R, Sullman MJM, Fouladseresht H. The demographic, laboratory and genetic factors associated with long Covid-19 syndrome: a case-control study. Clin Exp Med 2024; 24:1. [PMID: 38231284 PMCID: PMC10794331 DOI: 10.1007/s10238-023-01256-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Accepted: 12/15/2023] [Indexed: 01/18/2024]
Abstract
Long Covid-19 syndrome (LCS) manifests with a wide range of clinical symptoms, yet the factors associated with LCS remain poorly understood. The current study aimed to investigate the relationships that demographic characteristics, clinical history, laboratory indicators, and the frequency of HLA-I alleles have with the likelihood of developing LCS. We extracted the demographic characteristics and clinical histories from the medical records of 88 LCS cases (LCS+ group) and 96 individuals without LCS (LCS- group). Furthermore, we evaluated the clinical symptoms, serum levels of interleukin (IL)-6 and tumor necrosis factor-α, laboratory parameters, and the frequencies of HLA-I alleles. Following this we used multiple logistic regression to investigate the association these variables had with LCS. Subjects in the LCS+ group were more likely to have experienced severe Covid-19 symptoms and had higher body mass index (BMI), white blood cell, lymphocyte counts, C-reactive protein (CRP), and IL-6 levels than those in the LCS- group (for all: P < 0.05). Moreover, the frequencies of the HLA-A*11, -B*14, -B*38, -B*50, and -C*07 alleles were higher in the LCS+ group (for all: P < 0.05). After adjusting for the most important variables, the likelihood of suffering from LCS was significantly associated with BMI, CRP, IL-6, the HLA-A*11, and -C*07 alleles, as well as a positive history of severe Covid-19 (for all: P < 0.05). Our study showed that a history of severe Covid-19 during the acute phase of the disease, the HLA-A*11, and -C*07 alleles, higher BMI, as well as elevated serum CRP and IL-6 levels, were all associated with an increased likelihood of LCS.
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Affiliation(s)
- Ensiye Torki
- Department of Immunology, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Fahimeh Hoseininasab
- Department of Immunology, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Marjan Moradi
- Department of Genetics, School of Science, Shahrekord University, Shahrekord, Iran
| | - Ramin Sami
- Department of Internal Medicine, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Mark J M Sullman
- Department of Life and Health Sciences, University of Nicosia, Nicosia, Cyprus
- Department of Social Sciences, University of Nicosia, Nicosia, Cyprus
| | - Hamed Fouladseresht
- Department of Immunology, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran.
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6
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Palmer WH, Norman PJ. The impact of HLA polymorphism on herpesvirus infection and disease. Immunogenetics 2023; 75:231-247. [PMID: 36595060 PMCID: PMC10205880 DOI: 10.1007/s00251-022-01288-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2022] [Accepted: 11/24/2022] [Indexed: 01/04/2023]
Abstract
Human Leukocyte Antigens (HLA) are cell surface molecules, central in coordinating innate and adaptive immune responses, that are targets of strong diversifying natural selection by pathogens. Of these pathogens, human herpesviruses have a uniquely ancient relationship with our species, where coevolution likely has reciprocating impact on HLA and viral genomic diversity. Consistent with this notion, genetic variation at multiple HLA loci is strongly associated with modulating immunity to herpesvirus infection. Here, we synthesize published genetic associations of HLA with herpesvirus infection and disease, both from case/control and genome-wide association studies. We analyze genetic associations across the eight human herpesviruses and identify HLA alleles that are associated with diverse herpesvirus-related phenotypes. We find that whereas most HLA genetic associations are virus- or disease-specific, HLA-A*01 and HLA-A*02 allotypes may be more generally associated with immune susceptibility and control, respectively, across multiple herpesviruses. Connecting genetic association data with functional corroboration, we discuss mechanisms by which diverse HLA and cognate receptor allotypes direct variable immune responses during herpesvirus infection and pathogenesis. Together, this review examines the complexity of HLA-herpesvirus interactions driven by differential T cell and Natural Killer cell immune responses.
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Affiliation(s)
- William H. Palmer
- Department of Biomedical Informatics, University of Colorado, Aurora, CO USA
- Department of Immunology & Microbiology, University of Colorado, Aurora, CO USA
| | - Paul J. Norman
- Department of Biomedical Informatics, University of Colorado, Aurora, CO USA
- Department of Immunology & Microbiology, University of Colorado, Aurora, CO USA
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7
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Irham LM, Adikusuma W, Lolita L, Puspitaningrum AN, Afief AR, Sarasmita MA, Dania H, Khairi S, Djalilah GN, Purwanto BD, Chong R. Investigation of susceptibility genes for chickenpox disease across multiple continents. Biochem Biophys Rep 2023; 33:101419. [PMID: 36620086 PMCID: PMC9816662 DOI: 10.1016/j.bbrep.2022.101419] [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: 10/04/2022] [Revised: 12/01/2022] [Accepted: 12/23/2022] [Indexed: 01/01/2023] Open
Abstract
Chickenpox (varicella) is caused by infection with the varicella-zoster virus (VZV), a neurotropic alpha herpes virus with a double-stranded DNA genome. Chickenpox can cause life-threatening complications, including subsequent bacterial infections, central nervous system symptoms, and even death without any risk factors. Few studies have been reported to investigate genetic susceptibility implicated in chickenpox. Herein, our study identified global genetic variants that potentially contributed to chickenpox susceptibility by utilizing the established bioinformatic-based approach. We integrated several databases, such as genome-wide association studies (GWAS) catalog, GTEx portal, HaploReg version 4.1, and Ensembl databases analyses to investigate susceptibility genes associated with chickenpox. Notably, increased expression of HLA-S, HCG4P5, and ABHD16A genes underlie enhanced chickenpox susceptibility in the European, American, and African populations. As compared to the Asian population, Europeans, Americans, and Africans have higher allele frequencies of the extant variants rs9266089, rs10947050, and rs79501286 from the susceptibility genes. Our study suggested that these susceptibility genes and associated genetic variants might play a critical role in chickenpox progression based on host genetics with clinical implications.
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Affiliation(s)
| | - Wirawan Adikusuma
- Department of Pharmacy, University of Muhammadiyah Mataram, Mataram, Indonesia
| | - Lolita Lolita
- Faculty of Pharmacy, Universitas Ahmad Dahlan, Yogyakarta, Indonesia
| | | | | | - Made Ary Sarasmita
- Pharmacy Study Program, Faculty of Science and Mathematics, Udayana University, Bali, Indonesia
| | - Haafizah Dania
- Faculty of Pharmacy, Universitas Ahmad Dahlan, Yogyakarta, Indonesia
| | - Sabiah Khairi
- School of Nursing, College of Nursing, Taipei Medical University, Taipei, 11031, Taiwan
| | | | - Barkah Djaka Purwanto
- Faculty of Medicine, University of Ahmad Dahlan, Yogyakarta, 55191, Indonesia
- PKU Muhammadiyah Bantul Hospital, Bantul, Yogyakarta, 55711, Indonesia
| | - Rockie Chong
- Department of Chemistry and Biochemistry, University of California, Los Angeles, USA
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8
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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: 7] [Impact Index Per Article: 3.5] [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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9
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Fouladseresht H, Safa A, Khosropanah S, Doroudchi M. Increased frequency of HLA-A*02 in patients with atherosclerosis is associated with VZV seropositivity. Arch Physiol Biochem 2021; 127:351-358. [PMID: 31306045 DOI: 10.1080/13813455.2019.1640253] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
BACKGROUND HLA molecules are inherited key molecules in the immune inflammation and specific responses to environmental pathogens. We investigated the association of HLA-A alleles with Varicella zoster virus (VZV) seropositivity in patients with atherosclerosis (AS). MATERIALS AND METHODS Plasma Anti-VZV IgG and molecular HLA type were detected in 203 (100 AS+ and 103 AS-) individuals. RESULTS Of 100 AS+ individuals, 66 were anti-VZV+ and 34 were anti-VZV-. Of 103 age/sex-matched AS- individuals, 59 were anti-VZV+ and 44 were anti-VZV-. Anti-VZV-IgG in AS+ cases was higher than AS- controls (p = .034). The mean anti-VZV IgG in HLA-A*02+AS+ individuals was higher than HLA-A*02+AS- controls (p < .001). HLA-A*02 was associated with VZV-seropositivity (p = .01) in AS+ patients. A higher frequency of HLA-A*02-allele in AS+ patients compared to AS- controls (p = .015) and an accumulation of HLA-A*02-allele in AS+ anti-VZV+ group (33.3%, p = .004) was observed. CONCLUSIONS HLA-A alleles and immune responses to VZV are associated with clinical atherosclerosis.
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Affiliation(s)
- Hamed Fouladseresht
- Department of Immunology, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Amin Safa
- Department of Immunology, Ophthalmology and ENT, School of Medicine, Complutense University, Madrid, Spain
| | - Shahdad Khosropanah
- Department of Cardiology, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Mehrnoosh Doroudchi
- Department of Immunology, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran
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10
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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: 7] [Impact Index Per Article: 1.8] [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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11
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McFarland AJ, Yousuf MS, Shiers S, Price TJ. Neurobiology of SARS-CoV-2 interactions with the peripheral nervous system: implications for COVID-19 and pain. Pain Rep 2021; 6:e885. [PMID: 33458558 PMCID: PMC7803673 DOI: 10.1097/pr9.0000000000000885] [Citation(s) in RCA: 75] [Impact Index Per Article: 18.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2020] [Revised: 10/26/2020] [Accepted: 11/14/2020] [Indexed: 02/07/2023] Open
Abstract
SARS-CoV-2 is a novel coronavirus that infects cells through the angiotensin-converting enzyme 2 receptor, aided by proteases that prime the spike protein of the virus to enhance cellular entry. Neuropilin 1 and 2 (NRP1 and NRP2) act as additional viral entry factors. SARS-CoV-2 infection causes COVID-19 disease. There is now strong evidence for neurological impacts of COVID-19, with pain as an important symptom, both in the acute phase of the disease and at later stages that are colloquially referred to as "long COVID." In this narrative review, we discuss how COVID-19 may interact with the peripheral nervous system to cause pain in the early and late stages of the disease. We begin with a review of the state of the science on how viruses cause pain through direct and indirect interactions with nociceptors. We then cover what we currently know about how the unique cytokine profiles of moderate and severe COVID-19 may drive plasticity in nociceptors to promote pain and worsen existing pain states. Finally, we review evidence for direct infection of nociceptors by SARS-CoV-2 and the implications of this potential neurotropism. The state of the science points to multiple potential mechanisms through which COVID-19 could induce changes in nociceptor excitability that would be expected to promote pain, induce neuropathies, and worsen existing pain states.
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Affiliation(s)
- Amelia J. McFarland
- Department of Neuroscience and Center for Advanced Pain Studies, University of Texas at Dallas, Richardson, TX, USA
| | - Muhammad S. Yousuf
- Department of Neuroscience and Center for Advanced Pain Studies, University of Texas at Dallas, Richardson, TX, USA
| | - Stephanie Shiers
- Department of Neuroscience and Center for Advanced Pain Studies, University of Texas at Dallas, Richardson, TX, USA
| | - Theodore J. Price
- Department of Neuroscience and Center for Advanced Pain Studies, University of Texas at Dallas, Richardson, TX, USA
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12
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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: 6] [Impact Index Per Article: 0.8] [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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13
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On the feasibility of mining CD8+ T cell receptor patterns underlying immunogenic peptide recognition. Immunogenetics 2017; 70:159-168. [PMID: 28779185 DOI: 10.1007/s00251-017-1023-5] [Citation(s) in RCA: 36] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2017] [Accepted: 07/23/2017] [Indexed: 10/19/2022]
Abstract
Current T cell epitope prediction tools are a valuable resource in designing targeted immunogenicity experiments. They typically focus on, and are able to, accurately predict peptide binding and presentation by major histocompatibility complex (MHC) molecules on the surface of antigen-presenting cells. However, recognition of the peptide-MHC complex by a T cell receptor (TCR) is often not included in these tools. We developed a classification approach based on random forest classifiers to predict recognition of a peptide by a T cell receptor and discover patterns that contribute to recognition. We considered two approaches to solve this problem: (1) distinguishing between two sets of TCRs that each bind to a known peptide and (2) retrieving TCRs that bind to a given peptide from a large pool of TCRs. Evaluation of the models on two HIV-1, B*08-restricted epitopes reveals good performance and hints towards structural CDR3 features that can determine peptide immunogenicity. These results are of particular importance as they show that prediction of T cell epitope and T cell epitope recognition based on sequence data is a feasible approach. In addition, the validity of our models not only serves as a proof of concept for the prediction of immunogenic T cell epitopes but also paves the way for more general and high-performing models.
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14
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Multidisciplinary study of the secondary immune response in grandparents re-exposed to chickenpox. Sci Rep 2017; 7:1077. [PMID: 28439065 PMCID: PMC5430877 DOI: 10.1038/s41598-017-01024-8] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2016] [Accepted: 03/23/2017] [Indexed: 11/25/2022] Open
Abstract
Re-exposure to chickenpox may boost varicella-zoster virus (VZV) immunity in the elderly. This secondary immune response is hypothesized to confer protection against herpes zoster. We longitudinally sampled 36 adults over the course of one year after re-exposure to chickenpox. The resulting 183 samples and those of 14 controls were assessed for VZV-specific T-cell immunity and antibody titres. The percentages of VZV-specific CD4+ IL-2-producing T-cells were increased in re-exposed grandparents compared to control participants up to 9 months after re-exposure. Using a longitudinal mixture modelling approach, we found that 25% and 17% of re-exposed grandparents showed a boosting of VZV-specific CD4+ IL-2-producing T-cells and VZV-specific antibodies, respectively. The antibody boosting occurred exclusively in cytomegalovirus (CMV) IgG-positive participants. CMV IgG-positive participants also had higher VZV IE62-specific CD4+ IFN-γ-producing T-cell percentages and VZV-specific antibody titres. The protective effect of re-exposure to chickenpox is likely limited, as boosting only occurred in 17–25% of the VZV re-exposed grandparents and for less than one year.
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15
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Chung HY, Song EY, Yoon JA, Suh DH, Lee SC, Kim YC, Park MH. Association of human leukocyte antigen with postherpetic neuralgia in Koreans. APMIS 2016; 124:865-71. [DOI: 10.1111/apm.12575] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2016] [Accepted: 06/09/2016] [Indexed: 11/27/2022]
Affiliation(s)
- Hye Yoon Chung
- Department of Laboratory Medicine; Seoul National University College of Medicine; Seoul Korea
| | - Eun Young Song
- Department of Laboratory Medicine; Seoul National University College of Medicine; Seoul Korea
| | - Jung Ah Yoon
- Department of Laboratory Medicine; Seoul National University College of Medicine; Seoul Korea
| | - Dae Hun Suh
- Department of Dermatology; Seoul National University College of Medicine; Seoul Korea
| | - Sang Chul Lee
- Department of Anesthesiology; Seoul National University College of Medicine; Seoul Korea
| | - Yong Chul Kim
- Department of Anesthesiology; Seoul National University College of Medicine; Seoul Korea
| | - Myoung Hee Park
- Department of Laboratory Medicine; Seoul National University College of Medicine; Seoul Korea
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Meysman P, Fedorov D, Van Tendeloo V, Ogunjimi B, Laukens K. Immunological evasion of immediate-early varicella zoster virus proteins. Immunogenetics 2016; 68:483-486. [PMID: 27020058 DOI: 10.1007/s00251-016-0911-4] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2015] [Accepted: 03/22/2016] [Indexed: 12/22/2022]
Abstract
The varicella zoster virus (VZV) causes the childhood disease commonly known as chickenpox and can later in life reactivate as herpes zoster. The adaptive immune system is known to play an important role in suppressing VZV reactivation. A central aspect of this system is the presentation of VZV-derived peptides by the major histocompatibility complex (MHC) proteins. Here, we investigate if key VZV proteins have evolved their amino acid sequence to avoid presentation by MHC based on predictive models of MHC-peptide affinity. This study shows that the immediate-early proteins of all characterized VZV strains are profoundly depleted for high-affinity MHC-I-restricted epitopes. The same depletion can be found in its closest animal analog, the simian varicella virus. Further orthology analysis towards other herpes viruses suggests that the protein amino acid frequency is one of the primary drivers of targeted epitope depletion.
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Affiliation(s)
- Pieter Meysman
- Department of Mathematics and Computer Science, University of Antwerp, Antwerp, Belgium. .,Biomedical Informatics Research Center Antwerp (biomina), University of Antwerp/Antwerp University Hospital, Edegem, Belgium.
| | - Dmitry Fedorov
- Institute of Cellular Neurosciences, University of Bonn, Bonn, Germany
| | - Viggo Van Tendeloo
- Laboratory of Experimental Hematology (LEH), Vaccine and Infectious Disease Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium
| | - Benson Ogunjimi
- Laboratory of Experimental Hematology (LEH), Vaccine and Infectious Disease Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium.,Centre for Health Economics Research and Modeling Infectious Diseases (CHERMID), Vaccine & Infectious Disease Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium.,Interuniversity Institute for Biostatistics and Statistical Bioinformatics, Hasselt University, Hasselt, Belgium
| | - Kris Laukens
- Department of Mathematics and Computer Science, University of Antwerp, Antwerp, Belgium.,Biomedical Informatics Research Center Antwerp (biomina), University of Antwerp/Antwerp University Hospital, Edegem, Belgium
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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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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: 9] [Impact Index Per Article: 0.9] [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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