1
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Ge Y, Lu Y, Allen JD, Einav T, Nkaleke DI, Bai F, Handel A, Ross TM, Shen Y. Pre-existing immunity to influenza aids ferrets in developing stronger and broader H3 vaccine-induced antibody responses. Vaccine 2024; 42:126149. [PMID: 39079813 PMCID: PMC11380186 DOI: 10.1016/j.vaccine.2024.07.050] [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: 04/22/2024] [Revised: 07/12/2024] [Accepted: 07/15/2024] [Indexed: 08/23/2024]
Abstract
Influenza seasons occur annually, building immune history for individuals, but the influence of this history on subsequent influenza vaccine protection remains unclear. We extracted data from an animal trial to study its potential impact. The trial involved 80 ferrets, each receiving either one type of infection or a placebo before vaccination. We quantified the vaccine protection by evaluating hemagglutination inhibition (HAI) antibody titer responses. We tested whether hosts with different infection histories exhibited similar level of responses when receiving the same vaccine for all homologous and heterologous outcomes. We observed that different pre-existing immunities were generally beneficial to vaccine induced responses, but varied in magnitude. Without pre-immunity, post-vaccination HAI titers after the 1st dose of the vaccine were less likely to be above 1:40, and a booster shot was needed. Our study suggests that pre-existing immunity may strengthen and extend the homologous and heterologous vaccine responses.
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Affiliation(s)
- Yang Ge
- School of Health Professions, University of Southern Mississippi, Hattiesburg 39402, MS, USA
| | - Yao Lu
- Department of Epidemiology and Biostatistics, College of Public Health, University of Georgia, Athens 30602, GA, USA
| | - James D Allen
- Cleveland Clinic, Florida Research and Innovation Center, Cleveland Clinic, Port St. Lucie, FL 34987, USA
| | - Tal Einav
- Center for Vaccine Innovation, La Jolla Institute for Immunology, La Jolla, CA 92037, USA; Department of Medicine, University of California San Diego, La Jolla, CA 92037, USA
| | - Dennis I Nkaleke
- School of Health Professions, University of Southern Mississippi, Hattiesburg 39402, MS, USA
| | - Fengwei Bai
- School of Biological, Environmental, and Earth Sciences, University of Southern Mississippi, Hattiesburg 39402, MS, USA
| | - Andreas Handel
- Department of Epidemiology and Biostatistics, College of Public Health, University of Georgia, Athens 30602, GA, USA
| | - Ted M Ross
- Cleveland Clinic, Florida Research and Innovation Center, Cleveland Clinic, Port St. Lucie, FL 34987, USA; Center for Vaccines and Immunology, The University of Georgia, Athens 30606, GA, USA; Cleveland Clinic, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, 44106, USA
| | - Ye Shen
- Department of Epidemiology and Biostatistics, College of Public Health, University of Georgia, Athens 30602, GA, USA.
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2
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Welsh FC, Eguia RT, Lee JM, Haddox HK, Galloway J, Van Vinh Chau N, Loes AN, Huddleston J, Yu TC, Quynh Le M, Nhat NTD, Thi Le Thanh N, Greninger AL, Chu HY, Englund JA, Bedford T, Matsen FA, Boni MF, Bloom JD. Age-dependent heterogeneity in the antigenic effects of mutations to influenza hemagglutinin. Cell Host Microbe 2024; 32:1397-1411.e11. [PMID: 39032493 PMCID: PMC11329357 DOI: 10.1016/j.chom.2024.06.015] [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: 12/12/2023] [Revised: 04/19/2024] [Accepted: 06/25/2024] [Indexed: 07/23/2024]
Abstract
Human influenza virus evolves to escape neutralization by polyclonal antibodies. However, we have a limited understanding of how the antigenic effects of viral mutations vary across the human population and how this heterogeneity affects virus evolution. Here, we use deep mutational scanning to map how mutations to the hemagglutinin (HA) proteins of two H3N2 strains, A/Hong Kong/45/2019 and A/Perth/16/2009, affect neutralization by serum from individuals of a variety of ages. The effects of HA mutations on serum neutralization differ across age groups in ways that can be partially rationalized in terms of exposure histories. Mutations that were fixed in influenza variants after 2020 cause greater escape from sera from younger individuals compared with adults. Overall, these results demonstrate that influenza faces distinct antigenic selection regimes from different age groups and suggest approaches to understand how this heterogeneous selection shapes viral evolution.
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MESH Headings
- Humans
- Hemagglutinin Glycoproteins, Influenza Virus/genetics
- Hemagglutinin Glycoproteins, Influenza Virus/immunology
- Influenza A Virus, H3N2 Subtype/genetics
- Influenza A Virus, H3N2 Subtype/immunology
- Mutation
- Adult
- Antibodies, Viral/immunology
- Antibodies, Viral/blood
- Influenza, Human/virology
- Influenza, Human/immunology
- Age Factors
- Middle Aged
- Young Adult
- Antibodies, Neutralizing/immunology
- Antibodies, Neutralizing/blood
- Antigens, Viral/genetics
- Antigens, Viral/immunology
- Adolescent
- Evolution, Molecular
- Aged
- Child
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Affiliation(s)
- Frances C Welsh
- Molecular and Cellular Biology Graduate Program, University of Washington, and Basic Sciences Division, Fred Hutch Cancer Center, Seattle, WA 98109, USA; Basic Sciences Division and Computational Biology Program, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA
| | - Rachel T Eguia
- Basic Sciences Division and Computational Biology Program, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA; Howard Hughes Medical Institute, Seattle, WA 98109, USA
| | - Juhye M Lee
- Basic Sciences Division and Computational Biology Program, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA; Howard Hughes Medical Institute, Seattle, WA 98109, USA
| | - Hugh K Haddox
- Basic Sciences Division and Computational Biology Program, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA
| | - Jared Galloway
- Basic Sciences Division and Computational Biology Program, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA
| | - Nguyen Van Vinh Chau
- Wellcome Trust Major Overseas Programme, Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam
| | - Andrea N Loes
- Basic Sciences Division and Computational Biology Program, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA; Howard Hughes Medical Institute, Seattle, WA 98109, USA
| | - John Huddleston
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA
| | - Timothy C Yu
- Molecular and Cellular Biology Graduate Program, University of Washington, and Basic Sciences Division, Fred Hutch Cancer Center, Seattle, WA 98109, USA; Basic Sciences Division and Computational Biology Program, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA
| | - Mai Quynh Le
- National Institutes for Hygiene and Epidemiology, Hanoi, Vietnam
| | - Nguyen T D Nhat
- Wellcome Trust Major Overseas Programme, Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam; Centre for Tropical Medicine, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, UK
| | - Nguyen Thi Le Thanh
- Wellcome Trust Major Overseas Programme, Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam
| | - Alexander L Greninger
- Department of Laboratory Medicine and Pathology, University of Washington School of Medicine, Seattle, WA 98195, USA; Division of Allergy and Infectious Diseases, University of Washington School of Medicine, Seattle, WA 98195, USA
| | - Helen Y Chu
- Division of Allergy and Infectious Diseases, University of Washington School of Medicine, Seattle, WA 98195, USA
| | - Janet A Englund
- Seattle Children's Research Institute, Seattle, WA 98109, USA
| | - Trevor Bedford
- Howard Hughes Medical Institute, Seattle, WA 98109, USA; Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA
| | - Frederick A Matsen
- Basic Sciences Division and Computational Biology Program, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA; Howard Hughes Medical Institute, Seattle, WA 98109, USA
| | - Maciej F Boni
- Wellcome Trust Major Overseas Programme, Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam; Centre for Tropical Medicine, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, UK; Center for Infectious Disease Dynamics, Department of Biology, Pennsylvania State University, University Park, PA 16802, USA
| | - Jesse D Bloom
- Basic Sciences Division and Computational Biology Program, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA; Howard Hughes Medical Institute, Seattle, WA 98109, USA.
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3
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Nielsen BF, Berrig C, Grenfell BT, Andreasen V. One hundred years of influenza A evolution. Theor Popul Biol 2024; 159:25-34. [PMID: 39094981 DOI: 10.1016/j.tpb.2024.07.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Revised: 07/05/2024] [Accepted: 07/30/2024] [Indexed: 08/04/2024]
Abstract
Leveraging the simplicity of nucleotide mismatch distributions, we provide an intuitive window into the evolution of the human influenza A 'nonstructural' (NS) gene segment. In an analysis suggested by the eminent Danish biologist Freddy B. Christiansen, we illustrate the existence of a continuous genetic "backbone" of influenza A NS sequences, steadily increasing in nucleotide distance to the 1918 root over more than a century. The 2009 influenza A/H1N1 pandemic represents a clear departure from this enduring genetic backbone. Utilizing nucleotide distance maps and phylogenetic analyses, we illustrate remaining uncertainties regarding the origin of the 2009 pandemic, highlighting the complexity of influenza evolution. The NS segment is interesting precisely because it experiences less pervasive positive selection, and departs less strongly from neutral evolution than e.g. the HA antigen. Consequently, sudden deviations from neutral diversification can indicate changes in other genes via the hitchhiking effect. Our approach employs two measures based on nucleotide mismatch counts to analyze the evolutionary dynamics of the NS gene segment. The rooted Hamming map of distances between a reference sequence and all other sequences over time, and the unrooted temporal Hamming distribution which captures the distribution of genotypic distances between simultaneously circulating viruses, thereby revealing patterns of nucleotide diversity and epi-evolutionary dynamics.
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Affiliation(s)
- Bjarke Frost Nielsen
- High Meadows Environmental Institute, Princeton University, Princeton, NJ, United States of America; Department of Science and Environment, Roskilde University, Roskilde, Denmark; Niels Bohr Institute, University of Copenhagen, Copenhagen, Denmark.
| | - Christian Berrig
- Department of Science and Environment, Roskilde University, Roskilde, Denmark.
| | - Bryan T Grenfell
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, United States of America.
| | - Viggo Andreasen
- Department of Science and Environment, Roskilde University, Roskilde, Denmark.
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4
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Dadonaite B, Ahn JJ, Ort JT, Yu J, Furey C, Dosey A, Hannon WW, Baker AV, Webby RJ, King NP, Liu Y, Hensley SE, Peacock TP, Moncla LH, Bloom JD. Deep mutational scanning of H5 hemagglutinin to inform influenza virus surveillance. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.23.595634. [PMID: 38826368 PMCID: PMC11142178 DOI: 10.1101/2024.05.23.595634] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2024]
Abstract
H5 influenza is a potential pandemic threat. Previous studies have identified molecular phenotypes of the viral hemagglutinin (HA) protein that contribute to pandemic risk, including cell entry, receptor preference, HA stability, and reduced neutralization by polyclonal sera. Here we use pseudovirus deep mutational scanning to measure how all mutations to a clade 2.3.4.4b H5 HA affect each phenotype. We identify mutations that allow HA to better bind a2-6-linked sialic acids, and show that some viruses already carry mutations that stabilize HA. We also identify recent viral strains with reduced neutralization to sera elicited by candidate vaccine virus. Overall, the systematic nature of deep mutational scanning combined with the safety of pseudoviruses enables comprehensive characterization of mutations to inform surveillance of H5 influenza.
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5
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Kim K, Vieira MC, Gouma S, Weirick ME, Hensley SE, Cobey S. Measures of population immunity can predict the dominant clade of influenza A (H3N2) in the 2017-2018 season and reveal age-associated differences in susceptibility and antibody-binding specificity. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2023.10.26.23297569. [PMID: 37961288 PMCID: PMC10635207 DOI: 10.1101/2023.10.26.23297569] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Background For antigenically variable pathogens such as influenza, strain fitness is partly determined by the relative availability of hosts susceptible to infection with that strain compared to others. Antibodies to the hemagglutinin (HA) and neuraminidase (NA) confer substantial protection against influenza infection. We asked if a cross-sectionalantibody-derived estimate of population susceptibility to different clades of influenza A (H3N2) could predict the success of clades in the following season. Methods We collected sera from 483 healthy individuals aged 1 to 90 years in the summer of 2017 and analyzed neutralizing responses to the HA and NA of representative strains using Focus Reduction Neutralization Tests (FNRT) and Enzyme-Linked Lectin Assays (ELLA). We estimated relative population-average and age-specific susceptibilities to circulating viral clades and compared those estimates to changes in clade frequencies in the following 2017-18 season. Results The clade to which neutralizing antibody titers were lowest, indicating greater population susceptibility, dominated the next season. Titers to different HA and NA clades varied dramatically between individuals but showed significant associations with age, suggesting dependence on correlated past exposures. Conclusions This study indicates how representative measures of population immunity might improve evolutionary forecasts and inform selective pressures on influenza.
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Affiliation(s)
- Kangchon Kim
- Department of Ecology and Evolution, The University of Chicago, USA
| | - Marcos C. Vieira
- Department of Ecology and Evolution, The University of Chicago, USA
| | - Sigrid Gouma
- Department of Microbiology, Perelman School of Medicine, The University of Pennsylvania, USA
| | - Madison E. Weirick
- Department of Microbiology, Perelman School of Medicine, The University of Pennsylvania, USA
| | - Scott E. Hensley
- Department of Microbiology, Perelman School of Medicine, The University of Pennsylvania, USA
| | - Sarah Cobey
- Department of Ecology and Evolution, The University of Chicago, USA
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6
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Lanfermeijer J, van de Ven K, Hendriks M, van Dijken H, Lenz S, Vos M, Borghans JAM, van Baarle D, de Jonge J. The Memory-CD8+-T-Cell Response to Conserved Influenza Virus Epitopes in Mice Is Not Influenced by Time Since Previous Infection. Vaccines (Basel) 2024; 12:419. [PMID: 38675801 PMCID: PMC11054904 DOI: 10.3390/vaccines12040419] [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: 03/14/2024] [Revised: 03/24/2024] [Accepted: 04/03/2024] [Indexed: 04/28/2024] Open
Abstract
To protect older adults against influenza A virus (IAV) infection, innovative strategies are imperative to overcome the decrease in protective immune response with age. One approach involves the boosting of CD8+ T cells at middle age that were previously induced by natural infection. At this stage, the immune system is still fit. Given the high conservation of T-cell epitopes within internal viral proteins, such a response may confer lasting protection against evolving influenza strains at older age, also reducing the high number of influenza immunizations currently required. However, at the time of vaccination, some individuals may have been more recently exposed to IAV than others, which could affect the T-cell response. We therefore investigated the fundamental principle of how the interval between the last infection and booster immunization during middle age influences the CD8+ T-cell response. To model this, female mice were infected at either 6 or 9 months of age and subsequently received a heterosubtypic infection booster at middle age (12 months). Before the booster infection, 6-month-primed mice displayed lower IAV-specific CD8+ T-cell responses in the spleen and lung than 9-month-primed mice. Both groups were better protected against the subsequent heterosubtypic booster infection compared to naïve mice. Notably, despite the different CD8+ T-cell levels between the 6-month- and 9-month-primed mice, we observed comparable responses after booster infection, based on IFNγ responses, and IAV-specific T-cell frequencies and repertoire diversity. Lung-derived CD8+ T cells of 6- and 9-month-primed mice expressed similar levels of tissue-resident memory-T-cell markers 30 days post booster infection. These data suggest that the IAV-specific CD8+ T-cell response after boosting is not influenced by the time post priming.
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Affiliation(s)
- Josien Lanfermeijer
- Center for Infectious Disease Control, National Institute for Public Health and the Environment, 3720 BA Bilthoven, The Netherlands
- Center for Translational Immunology, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands
- AstraZeneca, 2594 AV Den Haag, The Netherlands
| | - Koen van de Ven
- Center for Infectious Disease Control, National Institute for Public Health and the Environment, 3720 BA Bilthoven, The Netherlands
- DICA (Dutch Institute for Clinical Auditing), 2333 AA Leiden, The Netherlands
| | - Marion Hendriks
- Center for Infectious Disease Control, National Institute for Public Health and the Environment, 3720 BA Bilthoven, The Netherlands
- Deventer Ziekenhuis, 7416 SE Deventer, The Netherlands
| | - Harry van Dijken
- Center for Infectious Disease Control, National Institute for Public Health and the Environment, 3720 BA Bilthoven, The Netherlands
| | - Stefanie Lenz
- Center for Infectious Disease Control, National Institute for Public Health and the Environment, 3720 BA Bilthoven, The Netherlands
- MSD Animal Health, 5830 AA Boxmeer, The Netherlands
| | - Martijn Vos
- Center for Infectious Disease Control, National Institute for Public Health and the Environment, 3720 BA Bilthoven, The Netherlands
| | - José A. M. Borghans
- Center for Translational Immunology, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands
| | - Debbie van Baarle
- Center for Infectious Disease Control, National Institute for Public Health and the Environment, 3720 BA Bilthoven, The Netherlands
- Center for Translational Immunology, University Medical Center Utrecht, 3584 CX Utrecht, The Netherlands
- Virology & Immunology Research, Department Medical Microbiology and Infection Prevention, University Medical Center Groningen, 9700 RB Groningen, The Netherlands
| | - Jørgen de Jonge
- Center for Infectious Disease Control, National Institute for Public Health and the Environment, 3720 BA Bilthoven, The Netherlands
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7
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Roberts MG, Hickson RI, McCaw JM. How immune dynamics shape multi-season epidemics: a continuous-discrete model in one dimensional antigenic space. J Math Biol 2024; 88:48. [PMID: 38538962 PMCID: PMC10973021 DOI: 10.1007/s00285-024-02076-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Revised: 02/25/2024] [Accepted: 03/05/2024] [Indexed: 04/01/2024]
Abstract
We extend a previously published model for the dynamics of a single strain of an influenza-like infection. The model incorporates a waning acquired immunity to infection and punctuated antigenic drift of the virus, employing a set of coupled integral equations within a season and a discrete map between seasons. The long term behaviour of the model is demonstrated by examples where immunity to infection depends on the time since a host was last infected, and where immunity depends on the number of times that a host has been infected. The first scenario leads to complicated dynamics in some regions of parameter space, and to regions of parameter space with more than one attractor. The second scenario leads to a stable fixed point, corresponding to an identical epidemic each season. We also examine the model with both paradigms in combination, almost always but not exclusively observing a stable fixed point or periodic solution. Adding stochastic perturbations to the between season map fails to destroy the model's qualitative dynamics. Our results suggest that if the level of host immunity depends on the elapsed time since the last infection then the epidemiological dynamics may be unpredictable.
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Affiliation(s)
- M G Roberts
- New Zealand Institute for Advanced Study and the Infectious Disease Research Centre, Massey University, Auckland, New Zealand.
| | - R I Hickson
- Health and Biosecurity, CSIRO, Townsville, QLD, 4814, Australia
- Australian Institute of Tropical Medicine and Hygiene, and College of Public Health, Medical and Veterinary Sciences, James Cook University, Townsville, QLD, 4814, Australia
- School of Mathematics and Statistics, Faculty of Science, University of Melbourne, Melbourne, VIC, 3010, Australia
| | - J M McCaw
- School of Mathematics and Statistics, Faculty of Science, University of Melbourne, Melbourne, VIC, 3010, Australia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Melbourne, VIC, 3010, Australia
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8
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Gardner BJ, Kilpatrick AM. Predicting Vaccine Effectiveness for Hospitalization and Symptomatic Disease for Novel SARS-CoV-2 Variants Using Neutralizing Antibody Titers. Viruses 2024; 16:479. [PMID: 38543844 PMCID: PMC10975673 DOI: 10.3390/v16030479] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2024] [Revised: 03/14/2024] [Accepted: 03/19/2024] [Indexed: 05/23/2024] Open
Abstract
The emergence of new virus variants, including the Omicron variant (B.1.1.529) of SARS-CoV-2, can lead to reduced vaccine effectiveness (VE) and the need for new vaccines or vaccine doses if the extent of immune evasion is severe. Neutralizing antibody titers have been shown to be a correlate of protection for SARS-CoV-2 and other pathogens, and could be used to quickly estimate vaccine effectiveness for new variants. However, no model currently exists to provide precise VE estimates for a new variant against severe disease for SARS-CoV-2 using robust datasets from several populations. We developed predictive models for VE against COVID-19 symptomatic disease and hospitalization across a 54-fold range of mean neutralizing antibody titers. For two mRNA vaccines (mRNA-1273, BNT162b2), models fit without Omicron data predicted that infection with the BA.1 Omicron variant increased the risk of hospitalization 2.8-4.4-fold and increased the risk of symptomatic disease 1.7-4.2-fold compared to the Delta variant. Out-of-sample validation showed that model predictions were accurate; all predictions were within 10% of observed VE estimates and fell within the model prediction intervals. Predictive models using neutralizing antibody titers can provide rapid VE estimates, which can inform vaccine booster timing, vaccine design, and vaccine selection for new virus variants.
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Affiliation(s)
- Billy J. Gardner
- Department of Ecology and Evolutionary Biology, University of California, Santa Cruz, CA 95060, USA
| | - A. Marm Kilpatrick
- Department of Ecology and Evolutionary Biology, University of California, Santa Cruz, CA 95060, USA
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9
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Lee F, Nguyen D, Hentenaar I, Morrison-Porter A, Solano D, Haddad N, Castrillon C, Lamothe P, Andrews J, Roberts D, Lonial S, Sanz I. The Majority of SARS-CoV-2 Plasma Cells are Excluded from the Bone Marrow Long-Lived Compartment 33 Months after mRNA Vaccination. RESEARCH SQUARE 2024:rs.3.rs-3979237. [PMID: 38559048 PMCID: PMC10980156 DOI: 10.21203/rs.3.rs-3979237/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
The goal of any vaccine is to induce long-lived plasma cells (LLPC) to provide life-long protection. Natural infection by influenza, measles, or mumps viruses generates bone marrow (BM) LLPC similar to tetanus vaccination which affords safeguards for decades. Although the SARS-CoV-2 mRNA vaccines protect from severe disease, the serologic half-life is short-lived even though SARS-CoV-2-specific plasma cells can be found in the BM. To better understand this paradox, we enrolled 19 healthy adults at 1.5-33 months after SARS-CoV-2 mRNA vaccine and measured influenza-, tetanus-, or SARS-CoV-2-specific antibody secreting cells (ASC) in LLPC (CD19-) and non-LLPC (CD19+) subsets within the BM. All individuals had IgG ASC specific for influenza, tetanus, and SARS-CoV-2 in at least one BM ASC compartment. However, only influenza- and tetanus-specific ASC were readily detected in the LLPC whereas SARS-CoV-2 specificities were mostly excluded. The ratios of non-LLPC:LLPC for influenza, tetanus, and SARS-CoV-2 were 0.61, 0.44, and 29.07, respectively. Even in five patients with known PCR-proven history of infection and vaccination, SARS-CoV-2-specific ASC were mostly excluded from the LLPC. These specificities were further validated by using multiplex bead binding assays of secreted antibodies in the supernatants of cultured ASC. Similarly, the IgG ratios of non-LLPC:LLPC for influenza, tetanus, and SARS-CoV-2 were 0.66, 0.44, and 23.26, respectively. In all, our studies demonstrate that rapid waning of serum antibodies is accounted for by the inability of mRNA vaccines to induce BM LLPC.
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10
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Nguyen DC, Hentenaar IT, Morrison-Porter A, Solano D, Haddad NS, Castrillon C, Lamothe PA, Andrews J, Roberts D, Lonial S, Sanz I, Lee FEH. The Majority of SARS-CoV-2 Plasma Cells are Excluded from the Bone Marrow Long-Lived Compartment 33 Months after mRNA Vaccination. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.03.02.24303242. [PMID: 38496525 PMCID: PMC10942531 DOI: 10.1101/2024.03.02.24303242] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/19/2024]
Abstract
The goal of any vaccine is to induce long-lived plasma cells (LLPC) to provide life-long protection. Natural infection by influenza, measles, or mumps viruses generates bone marrow (BM) LLPC similar to tetanus vaccination which affords safeguards for decades. Although the SARS-CoV-2 mRNA vaccines protect from severe disease, the serologic half-life is short-lived even though SARS-CoV-2-specific plasma cells can be found in the BM. To better understand this paradox, we enrolled 19 healthy adults at 1.5-33 months after SARS-CoV-2 mRNA vaccine and measured influenza-, tetanus-, or SARS-CoV-2-specific antibody secreting cells (ASC) in LLPC (CD19 - ) and non-LLPC (CD19 + ) subsets within the BM. All individuals had IgG ASC specific for influenza, tetanus, and SARS-CoV-2 in at least one BM ASC compartment. However, only influenza- and tetanus-specific ASC were readily detected in the LLPC whereas SARS-CoV-2 specificities were mostly excluded. The ratios of non-LLPC:LLPC for influenza, tetanus, and SARS-CoV-2 were 0.61, 0.44, and 29.07, respectively. Even in five patients with known PCR-proven history of infection and vaccination, SARS-CoV-2-specific ASC were mostly excluded from the LLPC. These specificities were further validated by using multiplex bead binding assays of secreted antibodies in the supernatants of cultured ASC. Similarly, the IgG ratios of non-LLPC:LLPC for influenza, tetanus, and SARS-CoV-2 were 0.66, 0.44, and 23.26, respectively. In all, our studies demonstrate that rapid waning of serum antibodies is accounted for by the inability of mRNA vaccines to induce BM LLPC.
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11
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de Jong SPJ, Felix Garza ZC, Gibson JC, van Leeuwen S, de Vries RP, Boons GJ, van Hoesel M, de Haan K, van Groeningen LE, Hulme KD, van Willigen HDG, Wynberg E, de Bree GJ, Matser A, Bakker M, van der Hoek L, Prins M, Kootstra NA, Eggink D, Nichols BE, Han AX, de Jong MD, Russell CA. Determinants of epidemic size and the impacts of lulls in seasonal influenza virus circulation. Nat Commun 2024; 15:591. [PMID: 38238318 PMCID: PMC10796432 DOI: 10.1038/s41467-023-44668-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Accepted: 12/21/2023] [Indexed: 01/22/2024] Open
Abstract
During the COVID-19 pandemic, levels of seasonal influenza virus circulation were unprecedentedly low, leading to concerns that a lack of exposure to influenza viruses, combined with waning antibody titres, could result in larger and/or more severe post-pandemic seasonal influenza epidemics. However, in most countries the first post-pandemic influenza season was not unusually large and/or severe. Here, based on an analysis of historical influenza virus epidemic patterns from 2002 to 2019, we show that historic lulls in influenza virus circulation had relatively minor impacts on subsequent epidemic size and that epidemic size was more substantially impacted by season-specific effects unrelated to the magnitude of circulation in prior seasons. From measurements of antibody levels from serum samples collected each year from 2017 to 2021, we show that the rate of waning of antibody titres against influenza virus during the pandemic was smaller than assumed in predictive models. Taken together, these results partially explain why the re-emergence of seasonal influenza virus epidemics was less dramatic than anticipated and suggest that influenza virus epidemic dynamics are not currently amenable to multi-season prediction.
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Affiliation(s)
- Simon P J de Jong
- Department of Medical Microbiology & Infection Prevention, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Zandra C Felix Garza
- Department of Medical Microbiology & Infection Prevention, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Joseph C Gibson
- Department of Medical Microbiology & Infection Prevention, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Sarah van Leeuwen
- Department of Medical Microbiology & Infection Prevention, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Robert P de Vries
- Department of Chemical Biology and Drug Discovery, Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Utrecht, The Netherlands
| | - Geert-Jan Boons
- Department of Chemical Biology and Drug Discovery, Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Utrecht, The Netherlands
- Complex Carbohydrate Research Center, University of Georgia, Athens, GA, USA
- Bijvoet Center for Biomolecular Research, Utrecht University, Utrecht, The Netherlands
- Department of Chemistry, University of Georgia, Athens, GA, USA
| | - Marliek van Hoesel
- Department of Medical Microbiology & Infection Prevention, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Karen de Haan
- Department of Medical Microbiology & Infection Prevention, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Laura E van Groeningen
- Department of Medical Microbiology & Infection Prevention, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Katina D Hulme
- Department of Medical Microbiology & Infection Prevention, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Hugo D G van Willigen
- Department of Medical Microbiology & Infection Prevention, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Elke Wynberg
- Department of Medical Microbiology & Infection Prevention, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
- Department of Infectious Diseases, Public Health Service of Amsterdam, Amsterdam, The Netherlands
| | - Godelieve J de Bree
- Department of Infectious Diseases, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Amy Matser
- Department of Infectious Diseases, Public Health Service of Amsterdam, Amsterdam, The Netherlands
| | - Margreet Bakker
- Department of Medical Microbiology & Infection Prevention, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Lia van der Hoek
- Department of Medical Microbiology & Infection Prevention, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Maria Prins
- Department of Infectious Diseases, Public Health Service of Amsterdam, Amsterdam, The Netherlands
- Department of Infectious Diseases, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Neeltje A Kootstra
- Department of Experimental Immunology, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Dirk Eggink
- Department of Medical Microbiology & Infection Prevention, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
- Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, The Netherlands
| | - Brooke E Nichols
- Department of Medical Microbiology & Infection Prevention, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
- Department of Global Health, School of Public Health, Boston University, Boston, MA, USA
| | - Alvin X Han
- Department of Medical Microbiology & Infection Prevention, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Menno D de Jong
- Department of Medical Microbiology & Infection Prevention, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Colin A Russell
- Department of Medical Microbiology & Infection Prevention, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands.
- Department of Global Health, School of Public Health, Boston University, Boston, MA, USA.
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12
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Welsh FC, Eguia RT, Lee JM, Haddox HK, Galloway J, Chau NVV, Loes AN, Huddleston J, Yu TC, Le MQ, Nhat NTD, Thanh NTL, Greninger AL, Chu HY, Englund JA, Bedford T, Matsen FA, Boni MF, Bloom JD. Age-dependent heterogeneity in the antigenic effects of mutations to influenza hemagglutinin. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.12.571235. [PMID: 38168237 PMCID: PMC10760046 DOI: 10.1101/2023.12.12.571235] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/05/2024]
Abstract
Human influenza virus evolves to escape neutralization by polyclonal antibodies. However, we have a limited understanding of how the antigenic effects of viral mutations vary across the human population, and how this heterogeneity affects virus evolution. Here we use deep mutational scanning to map how mutations to the hemagglutinin (HA) proteins of the A/Hong Kong/45/2019 (H3N2) and A/Perth/16/2009 (H3N2) strains affect neutralization by serum from individuals of a variety of ages. The effects of HA mutations on serum neutralization differ across age groups in ways that can be partially rationalized in terms of exposure histories. Mutations that fixed in influenza variants after 2020 cause the greatest escape from sera from younger individuals. Overall, these results demonstrate that influenza faces distinct antigenic selection regimes from different age groups, and suggest approaches to understand how this heterogeneous selection shapes viral evolution.
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Affiliation(s)
- Frances C Welsh
- Molecular and Cellular Biology Graduate Program, University of Washington, and Basic Sciences Division, Fred Hutch Cancer Center, Seattle, WA, 98109, USA
- Basic Sciences Division and Computational Biology Program, Fred Hutchinson Cancer Center, Seattle, WA, 98109, USA
| | - Rachel T Eguia
- Basic Sciences Division and Computational Biology Program, Fred Hutchinson Cancer Center, Seattle, WA, 98109, USA
- Howard Hughes Medical Institute, Seattle, WA, 98109, USA
| | - Juhye M Lee
- Basic Sciences Division and Computational Biology Program, Fred Hutchinson Cancer Center, Seattle, WA, 98109, USA
- Howard Hughes Medical Institute, Seattle, WA, 98109, USA
| | - Hugh K Haddox
- Basic Sciences Division and Computational Biology Program, Fred Hutchinson Cancer Center, Seattle, WA, 98109, USA
| | - Jared Galloway
- Basic Sciences Division and Computational Biology Program, Fred Hutchinson Cancer Center, Seattle, WA, 98109, USA
| | - Nguyen Van Vinh Chau
- Wellcome Trust Major Overseas Programme, Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam
| | - Andrea N Loes
- Basic Sciences Division and Computational Biology Program, Fred Hutchinson Cancer Center, Seattle, WA, 98109, USA
- Howard Hughes Medical Institute, Seattle, WA, 98109, USA
| | - John Huddleston
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, WA, 98109, USA
| | - Timothy C Yu
- Molecular and Cellular Biology Graduate Program, University of Washington, and Basic Sciences Division, Fred Hutch Cancer Center, Seattle, WA, 98109, USA
- Basic Sciences Division and Computational Biology Program, Fred Hutchinson Cancer Center, Seattle, WA, 98109, USA
| | - Mai Quynh Le
- National Institutes for Hygiene and Epidemiology, Hanoi, Vietnam
| | - Nguyen T D Nhat
- Wellcome Trust Major Overseas Programme, Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam
- Centre for Tropical Medicine, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, United Kingdom
| | - Nguyen Thi Le Thanh
- Wellcome Trust Major Overseas Programme, Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam
| | - Alexander L Greninger
- Department of Laboratory Medicine and Pathology, University of Washington School of Medicine, Seattle, WA, 98195, USA
- Division of Allergy and Infectious Diseases, University of Washington School of Medicine, Seattle, WA, 98195, USA
| | - Helen Y Chu
- Division of Allergy and Infectious Diseases, University of Washington School of Medicine, Seattle, WA, 98195, USA
| | - Janet A Englund
- Seattle Children's Research Institute, Seattle, WA, 98109, USA
| | - Trevor Bedford
- Howard Hughes Medical Institute, Seattle, WA, 98109, USA
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, WA, 98109, USA
| | - Frederick A Matsen
- Basic Sciences Division and Computational Biology Program, Fred Hutchinson Cancer Center, Seattle, WA, 98109, USA
- Howard Hughes Medical Institute, Seattle, WA, 98109, USA
| | - Maciej F Boni
- Wellcome Trust Major Overseas Programme, Oxford University Clinical Research Unit, Ho Chi Minh City, Vietnam
- Centre for Tropical Medicine, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, United Kingdom
- Center for Infectious Disease Dynamics, Department of Biology, Pennsylvania State University, University Park, PA, 16802, USA
| | - Jesse D Bloom
- Basic Sciences Division and Computational Biology Program, Fred Hutchinson Cancer Center, Seattle, WA, 98109, USA
- Howard Hughes Medical Institute, Seattle, WA, 98109, USA
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13
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McGrath JJC, Wilson PC. Fate-mapping antibodies to study sinful immune dynamics. Nat Immunol 2023; 24:570-572. [PMID: 36959294 DOI: 10.1038/s41590-023-01467-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/25/2023]
Affiliation(s)
- Joshua J C McGrath
- Drukier Institute for Children's Health, Department of Pediatrics, Weill Cornell Medicine, New York, NY, USA.
| | - Patrick C Wilson
- Drukier Institute for Children's Health, Department of Pediatrics, Weill Cornell Medicine, New York, NY, USA.
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14
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Maier HE, Kuan G, Gresh L, Chowell G, Bakker K, Lopez R, Sanchez N, Lopez B, Schiller A, Ojeda S, Harris E, Balmaseda A, Gordon A. The Nicaraguan Pediatric Influenza Cohort Study, 2011-2019: Influenza Incidence, Seasonality, and Transmission. Clin Infect Dis 2023; 76:e1094-e1103. [PMID: 35639580 PMCID: PMC10169406 DOI: 10.1093/cid/ciac420] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Revised: 05/11/2022] [Accepted: 05/20/2022] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND Children account for a large portion of global influenza burden and transmission, and a better understanding of influenza in children is needed to improve prevention and control strategies. METHODS To examine the incidence and transmission of influenza we conducted a prospective community-based study of children aged 0-14 years in Managua, Nicaragua, between 2011 and 2019. Participants were provided with medical care through study physicians and symptomatic influenza was confirmed by reverse-transcription polymerase chain reaction (RT-PCR). Wavelet analyses were used to examine seasonality. Generalized growth models (GGMs) were used to estimate effective reproduction numbers. RESULTS From 2011 to 2019, 3016 children participated, with an average of ∼1800 participants per year and median follow-up time of 5 years per child, and 48.3% of the cohort in 2019 had been enrolled their entire lives. The overall incidence rates per 100 person-years were 14.5 symptomatic influenza cases (95% confidence interval [CI]: 13.9-15.1) and 1.0 influenza-associated acute lower respiratory infection (ALRI) case (95% CI: .8-1.1). Symptomatic influenza incidence peaked at age 9-11 months. Infants born during peak influenza circulation had lower incidence in the first year of their lives. The mean effective reproduction number was 1.2 (range 1.02-1.49), and we observed significant annual patterns for influenza and influenza A, and a 2.5-year period for influenza B. CONCLUSIONS This study provides important information for understanding influenza epidemiology and informing influenza vaccine policy. These results will aid in informing strategies to reduce the burden of influenza.
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Affiliation(s)
- Hannah E Maier
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, USA
| | - Guillermina Kuan
- Sustainable Sciences Institute, Managua, Nicaragua
- Centro de Salud Sócrates Flores Vivas, Ministry of Health, Managua, Nicaragua
| | - Lionel Gresh
- Sustainable Sciences Institute, Managua, Nicaragua
| | - Gerardo Chowell
- Population Health Sciences, School of Public Health, Georgia State University, Atlanta, Georgia, USA
| | - Kevin Bakker
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, USA
| | - Roger Lopez
- Sustainable Sciences Institute, Managua, Nicaragua
- Laboratorio Nacional de Virología, Centro Nacional de Diagnóstico y Referencia, Ministry of Health, Managua, Nicaragua
| | - Nery Sanchez
- Sustainable Sciences Institute, Managua, Nicaragua
| | - Brenda Lopez
- Sustainable Sciences Institute, Managua, Nicaragua
| | - Amy Schiller
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, USA
| | - Sergio Ojeda
- Sustainable Sciences Institute, Managua, Nicaragua
| | - Eva Harris
- Division of Infectious Diseases and Vaccinology, School of Public Health, University of California, Berkeley, California, USA
| | - Angel Balmaseda
- Sustainable Sciences Institute, Managua, Nicaragua
- Laboratorio Nacional de Virología, Centro Nacional de Diagnóstico y Referencia, Ministry of Health, Managua, Nicaragua
| | - Aubree Gordon
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, USA
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15
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Mapping the Antibody Repertoires in Ferrets with Repeated Influenza A/H3 Infections: Is Original Antigenic Sin Really "Sinful"? Viruses 2023; 15:v15020374. [PMID: 36851590 PMCID: PMC9959794 DOI: 10.3390/v15020374] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2023] [Revised: 01/20/2023] [Accepted: 01/27/2023] [Indexed: 01/31/2023] Open
Abstract
The influenza-specific antibody repertoire is continuously reshaped by infection and vaccination. The host immune response to contemporary viruses can be redirected to preferentially boost antibodies specific for viruses encountered early in life, a phenomenon called original antigenic sin (OAS) that is suggested to be responsible for diminished vaccine effectiveness after repeated seasonal vaccination. Using a new computational tool called Neutralization Landscapes, we tracked the progression of hemagglutination inhibition antibodies within ferret antisera elicited by repeated influenza A/H3 infections and deciphered the influence of prior exposures on the de novo antibody response to evolved viruses. The results indicate that a broadly neutralizing antibody signature can nevertheless be induced by repeated exposures despite OAS induction. Our study offers a new way to visualize how immune history shapes individual antibodies within a repertoire, which may help to inform future universal influenza vaccine design.
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16
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Kuraoka M, Curtis NC, Watanabe A, Tanno H, Shin S, Ye K, Macdonald E, Lavidor O, Kong S, Von Holle T, Windsor I, Ippolito GC, Georgiou G, Walter EB, Kelsoe G, Harrison SC, Moody MA, Bajic G, Lee J. Infant Antibody Repertoires during the First Two Years of Influenza Vaccination. mBio 2022; 13:e0254622. [PMID: 36314798 PMCID: PMC9765176 DOI: 10.1128/mbio.02546-22] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Accepted: 09/19/2022] [Indexed: 01/11/2023] Open
Abstract
The first encounter with influenza virus biases later immune responses. This "immune imprinting," formerly from infection within a few years of birth, is in the United States now largely from immunization with a quadrivalent, split vaccine (IIV4 [quadrivalent inactivated influenza vaccine]). In a pilot study of IIV4 imprinting, we used single-cell cultures, next-generation sequencing, and plasma antibody proteomics to characterize the primary antibody responses to influenza in two infants during their first 2 years of seasonal influenza vaccination. One infant, who received only a single vaccination in year 1, contracted an influenza B virus (IBV) infection between the 2 years, allowing us to compare imprinting by infection and vaccination. That infant had a shift in hemagglutinin (HA)-reactive B cell specificity from largely influenza A virus (IAV) specific in year 1 to IBV specific in year 2, both before and after the year 2 vaccination. HA-reactive B cells from the other infant maintained a more evenly distributed specificity. In year 2, class-switched HA-specific B cell IGHV somatic hypermutation (SHM) levels reached the average levels seen in adults. The HA-reactive plasma antibody repertoires of both infants comprised a relatively small number of antibody clonotypes, with one or two very abundant clonotypes. Thus, after the year 2 boost, both infants had overall B cell profiles that resembled those of adult controls. IMPORTANCE Influenza virus is a moving target for the immune system. Variants emerge that escape protection from antibodies elicited by a previously circulating variant ("antigenic drift"). The immune system usually responds to a drifted influenza virus by mutating existing antibodies rather than by producing entirely new ones. Thus, immune memory of the earliest influenza virus exposure has a major influence on later responses to infection or vaccination ("immune imprinting"). In the many studies of influenza immunity in adult subjects, imprinting has been from an early infection, since only in the past 2 decades have infants received influenza immunizations. The work reported in this paper is a pilot study of imprinting by the flu vaccine in two infants, who received the vaccine before experiencing an influenza virus infection. The results suggest that a quadrivalent (four-subtype) vaccine may provide an immune imprint less dominated by one subtype than does a monovalent infection.
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Affiliation(s)
- Masayuki Kuraoka
- Department of Immunology, Duke University, Durham, North Carolina, USA
| | - Nicholas C. Curtis
- Thayer School of Engineering, Dartmouth College, Hanover, New Hampshire, USA
| | - Akiko Watanabe
- Department of Immunology, Duke University, Durham, North Carolina, USA
| | - Hidetaka Tanno
- Department of Chemical Engineering, University of Texas, Austin, Texas, USA
- Department of Molecular Biosciences, University of Texas, Austin, Texas, USA
- Department of Biomedical Engineering, University of Texas, Austin, Texas, USA
- Institute for Cellular and Molecular Biology, University of Texas, Austin, Texas, USA
| | - Seungmin Shin
- Thayer School of Engineering, Dartmouth College, Hanover, New Hampshire, USA
| | - Kevin Ye
- Thayer School of Engineering, Dartmouth College, Hanover, New Hampshire, USA
| | - Elizabeth Macdonald
- Laboratory of Molecular Medicine, Boston Children’s Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Olivia Lavidor
- Laboratory of Molecular Medicine, Boston Children’s Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Susan Kong
- Laboratory of Molecular Medicine, Boston Children’s Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Tarra Von Holle
- Department of Pediatrics, Duke University, Durham, North Carolina, USA
- Duke Human Vaccine Institute, Duke University, Durham, North Carolina, USA
| | - Ian Windsor
- Laboratory of Molecular Medicine, Boston Children’s Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Gregory C. Ippolito
- Department of Molecular Biosciences, University of Texas, Austin, Texas, USA
- Institute for Cellular and Molecular Biology, University of Texas, Austin, Texas, USA
| | - George Georgiou
- Department of Chemical Engineering, University of Texas, Austin, Texas, USA
- Department of Molecular Biosciences, University of Texas, Austin, Texas, USA
- Department of Biomedical Engineering, University of Texas, Austin, Texas, USA
- Institute for Cellular and Molecular Biology, University of Texas, Austin, Texas, USA
| | - Emmanuel B. Walter
- Department of Pediatrics, Duke University, Durham, North Carolina, USA
- Duke Human Vaccine Institute, Duke University, Durham, North Carolina, USA
| | - Garnett Kelsoe
- Department of Immunology, Duke University, Durham, North Carolina, USA
- Department of Surgery, Duke University, Durham, North Carolina, USA
| | - Stephen C. Harrison
- Laboratory of Molecular Medicine, Boston Children’s Hospital and Harvard Medical School, Boston, Massachusetts, USA
- Howard Hughes Medical Institute, Harvard Medical School, Boston, Massachusetts, USA
| | - M. Anthony Moody
- Department of Immunology, Duke University, Durham, North Carolina, USA
- Department of Pediatrics, Duke University, Durham, North Carolina, USA
- Duke Human Vaccine Institute, Duke University, Durham, North Carolina, USA
| | - Goran Bajic
- Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Jiwon Lee
- Thayer School of Engineering, Dartmouth College, Hanover, New Hampshire, USA
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17
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Yang B, García-Carreras B, Lessler J, Read JM, Zhu H, Metcalf CJE, Hay JA, Kwok KO, Shen R, Jiang CQ, Guan Y, Riley S, Cummings DA. Long term intrinsic cycling in human life course antibody responses to influenza A(H3N2): an observational and modeling study. eLife 2022; 11:81457. [PMID: 36458815 PMCID: PMC9757834 DOI: 10.7554/elife.81457] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2022] [Accepted: 12/01/2022] [Indexed: 12/05/2022] Open
Abstract
Background Over a life course, human adaptive immunity to antigenically mutable pathogens exhibits competitive and facilitative interactions. We hypothesize that such interactions may lead to cyclic dynamics in immune responses over a lifetime. Methods To investigate the cyclic behavior, we analyzed hemagglutination inhibition titers against 21 historical influenza A(H3N2) strains spanning 47 years from a cohort in Guangzhou, China, and applied Fourier spectrum analysis. To investigate possible biological mechanisms, we simulated individual antibody profiles encompassing known feedbacks and interactions due to generally recognized immunological mechanisms. Results We demonstrated a long-term periodicity (about 24 years) in individual antibody responses. The reported cycles were robust to analytic and sampling approaches. Simulations suggested that individual-level cross-reaction between antigenically similar strains likely explains the reported cycle. We showed that the reported cycles are predictable at both individual and birth cohort level and that cohorts show a diversity of phases of these cycles. Phase of cycle was associated with the risk of seroconversion to circulating strains, after accounting for age and pre-existing titers of the circulating strains. Conclusions Our findings reveal the existence of long-term periodicities in individual antibody responses to A(H3N2). We hypothesize that these cycles are driven by preexisting antibody responses blunting responses to antigenically similar pathogens (by preventing infection and/or robust antibody responses upon infection), leading to reductions in antigen-specific responses over time until individual's increasing risk leads to an infection with an antigenically distant enough virus to generate a robust immune response. These findings could help disentangle cohort effects from individual-level exposure histories, improve our understanding of observed heterogeneous antibody responses to immunizations, and inform targeted vaccine strategy. Funding This study was supported by grants from the NIH R56AG048075 (DATC, JL), NIH R01AI114703 (DATC, BY), the Wellcome Trust 200861/Z/16/Z (SR), and 200187/Z/15/Z (SR). This work was also supported by research grants from Guangdong Government HZQB-KCZYZ-2021014 and 2019B121205009 (YG and HZ). DATC, JMR and SR acknowledge support from the National Institutes of Health Fogarty Institute (R01TW0008246). JMR acknowledges support from the Medical Research Council (MR/S004793/1) and the Engineering and Physical Sciences Research Council (EP/N014499/1). The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.
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Affiliation(s)
- Bingyi Yang
- Department of Biology, University of FloridaGainesvilleUnited States
- Emerging Pathogens Institute, University of FloridaGainesvilleUnited States
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong KongHong KongChina
| | - Bernardo García-Carreras
- Department of Biology, University of FloridaGainesvilleUnited States
- Emerging Pathogens Institute, University of FloridaGainesvilleUnited States
| | - Justin Lessler
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public HealthBaltimoreUnited States
- Department of Epidemiology, UNC Gillings School of Global Public HealthChapel HillUnited States
- UNC Carolina Population CenterChapel HillUnited States
| | - Jonathan M Read
- Centre for Health Informatics Computing and Statistics, Lancaster UniversityLancasterUnited Kingdom
| | - Huachen Zhu
- Guangdong‐Hong Kong Joint Laboratory of Emerging Infectious Diseases/MOE Joint Laboratory for International Collaboration in Virology and Emerging Infectious Diseases, Joint Institute of Virology (Shantou University/The University of Hong Kong), Shantou UniversityShantouChina
- State Key Laboratory of Emerging Infectious Diseases / World Health Organization Influenza Reference Laboratory, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong KongHong KongChina
- EKIH (Gewuzhikang) Pathogen Research InstituteGuangdongChina
| | - C Jessica E Metcalf
- Department of Ecology and Evolutionary Biology, Princeton UniversityPrincetonUnited States
| | - James A Hay
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College LondonLondonUnited Kingdom
- Center for Communicable Disease Dynamics, Harvard TH Chan School of Public HealthBostonUnited States
| | - Kin O Kwok
- The Jockey Club School of Public Health and Primary Care, Chinese University of Hong KongHong KongChina
- Stanley Ho Centre for Emerging Infectious Diseases, The Chinese University of Hong KongHong KongChina
- Shenzhen Research Institute of The Chinese University of Hong KongGuangdongChina
| | - Ruiyun Shen
- Guangzhou No.12 Hospital, GuangzhouGuangdongChina
| | - Chao Q Jiang
- Guangzhou No.12 Hospital, GuangzhouGuangdongChina
| | - Yi Guan
- Guangdong‐Hong Kong Joint Laboratory of Emerging Infectious Diseases/MOE Joint Laboratory for International Collaboration in Virology and Emerging Infectious Diseases, Joint Institute of Virology (Shantou University/The University of Hong Kong), Shantou UniversityShantouChina
- State Key Laboratory of Emerging Infectious Diseases / World Health Organization Influenza Reference Laboratory, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong KongHong KongChina
- EKIH (Gewuzhikang) Pathogen Research InstituteGuangdongChina
| | - Steven Riley
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College LondonLondonUnited Kingdom
| | - Derek A Cummings
- Department of Biology, University of FloridaGainesvilleUnited States
- Emerging Pathogens Institute, University of FloridaGainesvilleUnited States
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18
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Desikan R, Linderman SL, Davis C, Zarnitsyna VI, Ahmed H, Antia R. Vaccine models predict rules for updating vaccines against evolving pathogens such as SARS-CoV-2 and influenza in the context of pre-existing immunity. Front Immunol 2022; 13:985478. [PMID: 36263031 PMCID: PMC9574365 DOI: 10.3389/fimmu.2022.985478] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2022] [Accepted: 09/16/2022] [Indexed: 11/13/2022] Open
Abstract
Currently, vaccines for SARS-CoV-2 and influenza viruses are updated if the new vaccine induces higher antibody-titers to circulating variants than current vaccines. This approach does not account for complex dynamics of how prior immunity skews recall responses to the updated vaccine. We: (i) use computational models to mechanistically dissect how prior immunity influences recall responses; (ii) explore how this affects the rules for evaluating and deploying updated vaccines; and (iii) apply this to SARS-CoV-2. Our analysis of existing data suggests that there is a strong benefit to updating the current SARS-CoV-2 vaccines to match the currently circulating variants. We propose a general two-dose strategy for determining if vaccines need updating as well as for vaccinating high-risk individuals. Finally, we directly validate our model by reanalysis of earlier human H5N1 influenza vaccine studies.
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Affiliation(s)
- Rajat Desikan
- Clinical Pharmacology Modeling & Simulation, GlaxoSmithKline (GSK), Stevenage, Hertfordshire, United Kingdom
| | - Susanne L. Linderman
- Department of Microbiology and Immunology, Emory University, Atlanta, GA, United States
| | - Carl Davis
- Department of Microbiology and Immunology, Emory University, Atlanta, GA, United States
| | | | - Hasan Ahmed
- Department of Biology, Emory University, Atlanta, GA, United States
| | - Rustom Antia
- Department of Biology, Emory University, Atlanta, GA, United States
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19
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Otunuga OM. Analysis of multi-strain infection of vaccinated and recovered population through epidemic model: Application to COVID-19. PLoS One 2022; 17:e0271446. [PMID: 35905113 PMCID: PMC9337708 DOI: 10.1371/journal.pone.0271446] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Accepted: 06/30/2022] [Indexed: 11/19/2022] Open
Abstract
In this work, an innovative multi-strain SV EAIR epidemic model is developed for the study of the spread of a multi-strain infectious disease in a population infected by mutations of the disease. The population is assumed to be completely susceptible to n different variants of the disease, and those who are vaccinated and recovered from a specific strain k (k ≤ n) are immune to previous and present strains j = 1, 2, ⋯, k, but can still be infected by newer emerging strains j = k + 1, k + 2, ⋯, n. The model is designed to simulate the emergence and dissemination of viral strains. All the equilibrium points of the system are calculated and the conditions for existence and global stability of these points are investigated and used to answer the question as to whether it is possible for the population to have an endemic with more than one strain. An interesting result that shows that a strain with a reproduction number greater than one can still die out on the long run if a newer emerging strain has a greater reproduction number is verified numerically. The effect of vaccines on the population is also analyzed and a bound for the herd immunity threshold is calculated. The validity of the work done is verified through numerical simulations by applying the proposed model and strategy to analyze the multi-strains of the COVID-19 virus, in particular, the Delta and the Omicron variants, in the United State.
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20
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Extrapolating missing antibody-virus measurements across serological studies. Cell Syst 2022; 13:561-573.e5. [PMID: 35798005 DOI: 10.1016/j.cels.2022.06.001] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2021] [Revised: 05/03/2022] [Accepted: 06/10/2022] [Indexed: 01/25/2023]
Abstract
The development of new vaccines, as well as our understanding of key processes that shape viral evolution and host antibody repertoires, relies on measuring multiple antibody responses against large panels of viruses. Given the enormous diversity of circulating virus strains and antibody responses, comprehensively testing all antibody-virus interactions is infeasible. Even within individual studies with limited panels, exhaustive testing is not always performed, and there is no common framework for combining information across studies with partially overlapping panels, especially when the assay type or host species differ. Prior studies have demonstrated that antibody-virus interactions can be characterized in a vastly simpler and lower dimensional space, suggesting that relatively few measurements could predict unmeasured antibody-virus interactions. Here, we apply matrix completion to several large-scale influenza and HIV-1 studies. We explore how prediction accuracy evolves as the number of measurements changes and approximates the number of additional measurements necessary in several highly incomplete datasets (suggesting ∼250,000 measurements could be saved). In addition, we show how the method can combine disparate datasets, even when the number of available measurements is below the theoretical limit that guarantees successful prediction. This approach can be readily generalized to other viruses or more broadly to other low-dimensional biological datasets.
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21
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Ertesvåg NU, Cox RJ, Lartey SL, Mohn KGI, Brokstad KA, Trieu MC. Seasonal influenza vaccination expands hemagglutinin-specific antibody breadth to older and future A/H3N2 viruses. NPJ Vaccines 2022; 7:67. [PMID: 35750781 PMCID: PMC9232600 DOI: 10.1038/s41541-022-00490-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2021] [Accepted: 05/13/2022] [Indexed: 11/09/2022] Open
Abstract
History of influenza A/H3N2 exposure, especially childhood infection, shape antibody responses after influenza vaccination and infection, but have not been extensively studied. We investigated the breadth and durability of influenza A/H3N2-specific hemagglutinin-inhibition antibodies after live-attenuated influenza vaccine in children (aged 3-17 years, n = 42), and after inactivated influenza vaccine or infection in adults (aged 22-61 years, n = 42) using 14 antigenically distinct A/H3N2 viruses circulating from 1968 to 2018. We found that vaccination and infection elicited cross-reactive antibody responses, predominantly directed against newer or future strains. Childhood H3-priming increased the breadth and magnitude of back-boosted A/H3N2-specific antibodies in adults. Broader and more durable A/H3N2-specific antibodies were observed in repeatedly vaccinated adults than in children and previously unvaccinated adults. Our findings suggest that early A/H3N2 exposure and frequent seasonal vaccination could increase the breadth and seropositivity of antibody responses, which may improve vaccine protection against future viruses.
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Affiliation(s)
- Nina Urke Ertesvåg
- Influenza Centre, Department of Clinical Science, University of Bergen, Bergen, Norway.
| | - Rebecca Jane Cox
- Influenza Centre, Department of Clinical Science, University of Bergen, Bergen, Norway.,Department of Microbiology, Haukeland University Hospital, Bergen, Norway
| | - Sarah Larteley Lartey
- Influenza Centre, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Kristin G-I Mohn
- Influenza Centre, Department of Clinical Science, University of Bergen, Bergen, Norway.,Department of Medicine, Haukeland University Hospital, Bergen, Norway
| | - Karl Albert Brokstad
- Influenza Centre, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Mai-Chi Trieu
- Influenza Centre, Department of Clinical Science, University of Bergen, Bergen, Norway.
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22
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Miller NL, Raman R, Clark T, Sasisekharan R. Complexity of Viral Epitope Surfaces as Evasive Targets for Vaccines and Therapeutic Antibodies. Front Immunol 2022; 13:904609. [PMID: 35784339 PMCID: PMC9247215 DOI: 10.3389/fimmu.2022.904609] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Accepted: 05/16/2022] [Indexed: 11/29/2022] Open
Abstract
The dynamic interplay between virus and host plays out across many interacting surfaces as virus and host evolve continually in response to one another. In particular, epitope-paratope interactions (EPIs) between viral antigen and host antibodies drive much of this evolutionary race. In this review, we describe a series of recent studies examining aspects of epitope complexity that go beyond two interacting protein surfaces as EPIs are typically understood. To structure our discussion, we present a framework for understanding epitope complexity as a spectrum along a series of axes, focusing primarily on 1) epitope biochemical complexity (e.g., epitopes involving N-glycans) and 2) antigen conformational/dynamic complexity (e.g., epitopes with differential properties depending on antigen state or fold-axis). We highlight additional epitope complexity factors including epitope tertiary/quaternary structure, which contribute to epistatic relationships between epitope residues within- or adjacent-to a given epitope, as well as epitope overlap resulting from polyclonal antibody responses, which is relevant when assessing antigenic pressure against a given epitope. Finally, we discuss how these different forms of epitope complexity can limit EPI analyses and therapeutic antibody development, as well as recent efforts to overcome these limitations.
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Affiliation(s)
- Nathaniel L. Miller
- Harvard Massachusetts Institute of Technology (MIT) Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, United States
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, United States
| | - Rahul Raman
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, United States
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, United States
| | - Thomas Clark
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, United States
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, United States
| | - Ram Sasisekharan
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, United States
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, United States
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23
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Desikan R, Linderman SL, Davis C, Zarnitsyna V, Ahmed H, Antia R. Modeling suggests that multiple immunizations or infections will reveal the benefits of updating SARS-CoV-2 vaccines. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2022:2022.05.21.492928. [PMID: 35665010 PMCID: PMC9164442 DOI: 10.1101/2022.05.21.492928] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
When should vaccines to evolving pathogens such as SARS-CoV-2 be updated? Our computational models address this focusing on updating SARS-CoV-2 vaccines to the currently circulating Omicron variant. Current studies typically compare the antibody titers to the new variant following a single dose of the original-vaccine versus the updated-vaccine in previously immunized individuals. These studies find that the updated-vaccine does not induce higher titers to the vaccine-variant compared with the original-vaccine, suggesting that updating may not be needed. Our models recapitulate this observation but suggest that vaccination with the updated-vaccine generates qualitatively different humoral immunity, a small fraction of which is specific for unique epitopes to the new variant. Our simulations suggest that these new variant-specific responses could dominate following subsequent vaccination or infection with either the currently circulating or future variants. We suggest a two-dose strategy for determining if the vaccine needs updating and for vaccinating high-risk individuals.
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Affiliation(s)
- Rajat Desikan
- Clinical Pharmacology Modeling & Simulation, GlaxoSmithKline (GSK), Gunnels Wood Rd, Stevenage, Hertfordshire, SG1 2NY, United Kingdom
- These authors contributed equally
| | - Susanne L. Linderman
- Department of Microbiology and Immunology, Emory University, Atlanta, GA 30322, USA
| | - Carl Davis
- Department of Microbiology and Immunology, Emory University, Atlanta, GA 30322, USA
| | - Veronika Zarnitsyna
- Department of Microbiology and Immunology, Emory University, Atlanta, GA 30322, USA
| | - Hasan Ahmed
- Department of Biology, Emory University, Atlanta, GA 30322, USA
| | - Rustom Antia
- Department of Biology, Emory University, Atlanta, GA 30322, USA
- These authors contributed equally
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24
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Minter A, Hoschler K, Jagne YJ, Sallah H, Armitage E, Lindsey B, Hay JA, Riley S, de Silva TI, Kucharski AJ. Estimation of Seasonal Influenza Attack Rates and Antibody Dynamics in Children Using Cross-Sectional Serological Data. J Infect Dis 2022; 225:1750-1754. [PMID: 32556290 PMCID: PMC9113438 DOI: 10.1093/infdis/jiaa338] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2020] [Accepted: 06/13/2020] [Indexed: 11/14/2022] Open
Abstract
Directly measuring evidence of influenza infections is difficult, especially in low-surveillance settings such as sub-Saharan Africa. Using a Bayesian model, we estimated unobserved infection times and underlying antibody responses to influenza A/H3N2, using cross-sectional serum antibody responses to 4 strains in children aged 24-60 months. Among the 242 individuals, we estimated a variable seasonal attack rate and found that most children had ≥1 infection before 2 years of age. Our results are consistent with previously published high attack rates in children. The modeling approach highlights how cross-sectional serological data can be used to estimate epidemiological dynamics.
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Affiliation(s)
- Amanda Minter
- Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom
| | - Katja Hoschler
- Respiratory Virus Reference Department, Public Health England, London, United Kingdom
| | - Ya Jankey Jagne
- Medical Research Council Unit The Gambia at the London School of Hygiene & Tropical Medicine, Banjul, The Gambia
| | - Hadijatou Sallah
- Medical Research Council Unit The Gambia at the London School of Hygiene & Tropical Medicine, Banjul, The Gambia
| | - Edwin Armitage
- Medical Research Council Unit The Gambia at the London School of Hygiene & Tropical Medicine, Banjul, The Gambia
| | - Benjamin Lindsey
- Medical Research Council Unit The Gambia at the London School of Hygiene & Tropical Medicine, Banjul, The Gambia
| | - James A Hay
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, United Kingdom
- Center for Communicable Disease Dynamics, Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, USA
| | - Steven Riley
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, United Kingdom
| | - Thushan I de Silva
- Medical Research Council Unit The Gambia at the London School of Hygiene & Tropical Medicine, Banjul, The Gambia
- The Florey Institute, Department of Infection, Immunity and Cardiovascular Disease, Medical School, University of Sheffield, Sheffield, United Kingdom
| | - Adam J Kucharski
- Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom
- Correspondence: Adam Kucharski, London School of Hygiene & Tropical Medicine, Keppel Street, Bloomsbury, London WC1E 7HT, United Kingdom ()
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25
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Abstract
Although the need for a universal influenza vaccine has long been recognized, only a handful of candidates have been identified so far, with even fewer advancing in the clinical pipeline. The 24–amino acid ectodomain of M2 protein (M2e) has been developed over the past two decades. However, M2e-based vaccine candidates have shortcomings, including the need for several administrations and the lack of sustained antibody titers over time. We report here a vaccine targeting strategy that has the potential to confer sustained and strong protection upon a single shot of a small amount of M2e antigen. The current COVID-19 pandemic has highlighted the importance of developing versatile, powerful platforms for the rapid deployment of vaccines against any incoming threat. Influenza, commonly referred to as “flu,” is a major global public health concern and a huge economic burden to societies. Current influenza vaccines need to be updated annually to match circulating strains, resulting in low take-up rates and poor coverage due to inaccurate prediction. Broadly protective universal flu vaccines that do not need to be updated annually have therefore been pursued. The highly conserved 24–amino acid ectodomain of M2 protein (M2e) is a leading candidate, but its poor immunogenicity has been a major roadblock in its clinical development. Here, we report a targeting strategy that shuttles M2e to a specific dendritic cell subset (cDC1) by engineering a recombinant anti-Clec9A monoclonal antibody fused at each of its heavy chains with three copies of M2e. Single administration in mice of 2 µg of the Clec9A–M2e construct triggered an exceptionally sustained anti-M2e antibody response and resulted in a strong anamnestic protective response upon influenza challenge. Furthermore, and importantly, Clec9A–M2e immunization significantly boosted preexisting anti-M2e titers from prior flu exposure. Thus, the Clec9A-targeting strategy allows antigen and dose sparing, addressing the shortcomings of current M2e vaccine candidates. As the cDC1 subset exists in humans, translation to humans is an exciting and realistic avenue.
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26
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Crowley AR, Natarajan H, Hederman AP, Bobak CA, Weiner JA, Wieland-Alter W, Lee J, Bloch EM, Tobian AAR, Redd AD, Blankson JN, Wolf D, Goetghebuer T, Marchant A, Connor RI, Wright PF, Ackerman ME. Boosting of cross-reactive antibodies to endemic coronaviruses by SARS-CoV-2 infection but not vaccination with stabilized spike. eLife 2022; 11:e75228. [PMID: 35289271 PMCID: PMC8923670 DOI: 10.7554/elife.75228] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2021] [Accepted: 02/23/2022] [Indexed: 12/12/2022] Open
Abstract
Preexisting antibodies to endemic coronaviruses (CoV) that cross-react with SARS-CoV-2 have the potential to influence the antibody response to COVID-19 vaccination and infection for better or worse. In this observational study of mucosal and systemic humoral immunity in acutely infected, convalescent, and vaccinated subjects, we tested for cross-reactivity against endemic CoV spike (S) protein at subdomain resolution. Elevated responses, particularly to the β-CoV OC43, were observed in all natural infection cohorts tested and were correlated with the response to SARS-CoV-2. The kinetics of this response and isotypes involved suggest that infection boosts preexisting antibody lineages raised against prior endemic CoV exposure that cross-react. While further research is needed to discern whether this recalled response is desirable or detrimental, the boosted antibodies principally targeted the better-conserved S2 subdomain of the viral spike and were not associated with neutralization activity. In contrast, vaccination with a stabilized spike mRNA vaccine did not robustly boost cross-reactive antibodies, suggesting differing antigenicity and immunogenicity. In sum, this study provides evidence that antibodies targeting endemic CoV are robustly boosted in response to SARS-CoV-2 infection but not to vaccination with stabilized S, and that depending on conformation or other factors, the S2 subdomain of the spike protein triggers a rapidly recalled, IgG-dominated response that lacks neutralization activity.
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Affiliation(s)
- Andrew R Crowley
- Department of Microbiology and Immunology, Geisel School of Medicine at Dartmouth, Dartmouth CollegeHanoverUnited States
| | - Harini Natarajan
- Department of Microbiology and Immunology, Geisel School of Medicine at Dartmouth, Dartmouth CollegeHanoverUnited States
| | | | - Carly A Bobak
- Biomedical Data Science, Dartmouth CollegeHanoverUnited States
| | - Joshua A Weiner
- Thayer School of Engineering, Dartmouth CollegeHanoverUnited States
| | - Wendy Wieland-Alter
- Department of Pediatrics, Geisel School of Medicine at Dartmouth, Dartmouth-Hitchcock Medical CenterLebanonUnited States
| | - Jiwon Lee
- Thayer School of Engineering, Dartmouth CollegeHanoverUnited States
| | - Evan M Bloch
- Department of Pathology, Johns Hopkins School of MedicineBaltimoreUnited States
| | - Aaron AR Tobian
- Department of Pathology, Johns Hopkins School of MedicineBaltimoreUnited States
| | - Andrew D Redd
- Department of Medicine, Division of Infectious Diseases, Johns Hopkins School of MedicineBaltimoreUnited States
- Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of HealthBethesdaUnited States
| | - Joel N Blankson
- Department of Medicine, Division of Infectious Diseases, Johns Hopkins School of MedicineBaltimoreUnited States
| | - Dana Wolf
- Hadassah University Medical CenterJerusalemIsrael
| | - Tessa Goetghebuer
- Institute for Medical Immunology, Université libre de BruxellesCharleroiBelgium
- Pediatric Department, CHU St PierreBrusselsBelgium
| | - Arnaud Marchant
- Institute for Medical Immunology, Université libre de BruxellesCharleroiBelgium
| | - Ruth I Connor
- Department of Pediatrics, Geisel School of Medicine at Dartmouth, Dartmouth-Hitchcock Medical CenterLebanonUnited States
| | - Peter F Wright
- Department of Pediatrics, Geisel School of Medicine at Dartmouth, Dartmouth-Hitchcock Medical CenterLebanonUnited States
| | - Margaret E Ackerman
- Department of Microbiology and Immunology, Geisel School of Medicine at Dartmouth, Dartmouth CollegeHanoverUnited States
- Thayer School of Engineering, Dartmouth CollegeHanoverUnited States
- Biomedical Data Science, Dartmouth CollegeHanoverUnited States
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27
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Brouwer AF, Balmaseda A, Gresh L, Patel M, Ojeda S, Schiller AJ, Lopez R, Webby RJ, Nelson MI, Kuan G, Gordon A. Birth cohort relative to an influenza A virus's antigenic cluster introduction drives patterns of children's antibody titers. PLoS Pathog 2022; 18:e1010317. [PMID: 35192673 PMCID: PMC8896668 DOI: 10.1371/journal.ppat.1010317] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2021] [Revised: 03/04/2022] [Accepted: 01/27/2022] [Indexed: 11/18/2022] Open
Abstract
An individual's antibody titers to influenza A strains are a result of the complicated interplay between infection history, cross-reactivity, immune waning, and other factors. It has been challenging to disentangle how population-level patterns of humoral immunity change as a function of age, calendar year, and birth cohort from cross-sectional data alone. We analyzed 1,589 longitudinal sera samples from 260 children across three studies in Nicaragua, 2006-16. Hemagglutination inhibition (HAI) titers were determined against four H3N2 strains, one H1N1 strain, and two H1N1pdm strains. We assessed temporal patterns of HAI titers using an age-period-cohort modeling framework. We found that titers against a given virus depended on calendar year of serum collection and birth cohort but not on age. Titer cohort patterns were better described by participants' ages relative to year of likely introduction of the virus's antigenic cluster than by age relative to year of strain introduction or by year of birth. These cohort effects may be driven by a decreasing likelihood of early-life infection after cluster introduction and by more broadly reactive antibodies at a young age. H3N2 and H1N1 viruses had qualitatively distinct cohort patterns, with cohort patterns of titers to specific H3N2 strains reaching their peak in children born 3 years prior to that virus's antigenic cluster introduction and with titers to H1N1 and H1N1pdm strains peaking for children born 1-2 years prior to cluster introduction but not being dramatically lower for older children. Ultimately, specific patterns of strain circulation and antigenic cluster introduction may drive population-level antibody titer patterns in children.
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Affiliation(s)
- Andrew F. Brouwer
- Department of Epidemiology, University of Michigan, Ann Arbor, Michigan, United States of America
- * E-mail: (AFB); (AG)
| | - Angel Balmaseda
- Sócrates Flores Vivas Health Center, Ministry of Health, Managua, Nicaragua
- Sustainable Sciences Institute, Managua, Nicaragua
| | - Lionel Gresh
- Sustainable Sciences Institute, Managua, Nicaragua
| | - Mayuri Patel
- Department of Epidemiology, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Sergio Ojeda
- Sustainable Sciences Institute, Managua, Nicaragua
| | - Amy J. Schiller
- Department of Epidemiology, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Roger Lopez
- Sócrates Flores Vivas Health Center, Ministry of Health, Managua, Nicaragua
- Sustainable Sciences Institute, Managua, Nicaragua
| | - Richard J. Webby
- Department of Infectious Diseases, St. Jude Children’s Research Hospital, Memphis, Tennessee, United States of America
| | - Martha I. Nelson
- Laboratory of Parasitic Diseases, Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Guillermina Kuan
- Sustainable Sciences Institute, Managua, Nicaragua
- Centro Nacional de Diagnóstico y Referencia, Ministry of Health, Managua, Nicaragua
| | - Aubree Gordon
- Department of Epidemiology, University of Michigan, Ann Arbor, Michigan, United States of America
- * E-mail: (AFB); (AG)
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28
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Similar severity of influenza primary and re-infections in pre-school children requiring outpatient treatment due to febrile acute respiratory illness: prospective, multicentre surveillance study (2013-2015). BMC Infect Dis 2022; 22:12. [PMID: 34983428 PMCID: PMC8724639 DOI: 10.1186/s12879-021-06988-7] [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: 02/10/2021] [Accepted: 12/16/2021] [Indexed: 12/03/2022] Open
Abstract
Background Influenza virus infections in immunologically naïve children (primary infection) may be more severe than in children with re-infections who are already immunologically primed. We compared frequency and severity of influenza virus primary and re-infections in pre-school children requiring outpatient treatment. Methods Influenza-unvaccinated children 1–5 years of age presenting at pediatric practices with febrile acute respiratory infection < 48 h after symptom onset were enrolled in a prospective, cross-sectional, multicenter surveillance study (2013–2015). Influenza types/subtypes were PCR-confirmed from oropharyngeal swabs. Influenza type/subtype-specific IgG antibodies serving as surrogate markers for immunological priming were determined using ELISA/hemagglutination inhibition assays. The acute influenza disease was defined as primary infection/re-infection by the absence/presence of influenza type-specific immunoglobulin G (IgG) and, in a second approach, by the absence/presence of subtype-specific IgG. Socio-demographic and clinical data were also recorded. Results Of 217 influenza infections, 178 were due to influenza A (87 [49%] primary infections, 91 [51%] re-infections) and 39 were due to influenza B (38 [97%] primary infections, one [3%] re-infection). Children with “influenza A primary infections” showed fever with respiratory symptoms for a shorter period than children with “influenza A re-infections” (median 3 vs. 4 days; age-adjusted p = 0.03); other disease characteristics were similar. If primary infections and re-infections were defined based on influenza A subtypes, 122 (87%) primary infections (78 “A(H3N2) primary infections”, 44 “A(H1N1)pdm09 primary infections”) and 18 (13%) re-infections could be classified (14 “A(H3N2) re-infections” and 4 “A(H1N1)pdm09 re-infections”). Per subtype, primary infections and re-infections were of similar disease severity. Children with re-infections defined on the subtype level usually had non-protective IgG titers against the subtype of their acute infection (16 of 18; 89%). Some patients infected by one of the influenza A subtypes showed protective IgG titers (≥ 1:40) against the other influenza A subtype (32/140; 23%). Conclusions Pre-school children with acute influenza A primary infections and re-infections presented with similar frequency in pediatric practices. Contrary to expectation, severity of acute “influenza A primary infections” and “influenza A re-infections” were similar. Most “influenza A re-infections” defined on the type level turned out to be primary infections when defined based on the subtype. On the subtype level, re-infections were rare and of similar disease severity as primary infections of the same subtype. Subtype level re-infections were usually associated with low IgG levels for the specific subtype of the acute infection, suggesting only short-time humoral immunity induced by previous infection by this subtype. Overall, the results indicated recurring influenza virus infections in this age group and no or only limited heterosubtypic antibody-mediated cross-protection. Supplementary Information The online version contains supplementary material available at 10.1186/s12879-021-06988-7.
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29
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Oidtman RJ, Arevalo P, Bi Q, McGough L, Russo CJ, Vera Cruz D, Costa Vieira M, Gostic KM. Influenza immune escape under heterogeneous host immune histories. Trends Microbiol 2021; 29:1072-1082. [PMID: 34218981 PMCID: PMC8578193 DOI: 10.1016/j.tim.2021.05.009] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2021] [Revised: 05/28/2021] [Accepted: 05/31/2021] [Indexed: 11/30/2022]
Abstract
In a pattern called immune imprinting, individuals gain the strongest immune protection against the influenza strains encountered earliest in life. In many recent examples, differences in early infection history can explain birth year-associated differences in susceptibility (cohort effects). Susceptibility shapes strain fitness, but without a clear conceptual model linking host susceptibility to the identity and order of past infections general conclusions on the evolutionary and epidemic implications of cohort effects are not possible. Failure to differentiate between cohort effects caused by differences in the set, rather than the order (path), of past infections is a current source of confusion. We review and refine hypotheses for path-dependent cohort effects, which include imprinting. We highlight strategies to measure their underlying causes and emergent consequences.
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Affiliation(s)
- Rachel J Oidtman
- Department of Ecology and Evolution, University of Chicago, Chicago, IL, USA
| | - Philip Arevalo
- Department of Ecology and Evolution, University of Chicago, Chicago, IL, USA
| | - Qifang Bi
- Department of Ecology and Evolution, University of Chicago, Chicago, IL, USA
| | - Lauren McGough
- Department of Ecology and Evolution, University of Chicago, Chicago, IL, USA
| | | | - Diana Vera Cruz
- Department of Ecology and Evolution, University of Chicago, Chicago, IL, USA
| | - Marcos Costa Vieira
- Department of Ecology and Evolution, University of Chicago, Chicago, IL, USA
| | - Katelyn M Gostic
- Department of Ecology and Evolution, University of Chicago, Chicago, IL, USA.
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30
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Vinh DN, Nhat NTD, de Bruin E, Vy NHT, Thao TTN, Phuong HT, Anh PH, Todd S, Quan TM, Thanh NTL, Lien NTN, Ha NTH, Hong TTK, Thai PQ, Choisy M, Nguyen TD, Simmons CP, Thwaites GE, Clapham HE, Chau NVV, Koopmans M, Boni MF. Age-seroprevalence curves for the multi-strain structure of influenza A virus. Nat Commun 2021; 12:6680. [PMID: 34795239 PMCID: PMC8602397 DOI: 10.1038/s41467-021-26948-8] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2020] [Accepted: 10/27/2021] [Indexed: 11/21/2022] Open
Abstract
The relationship between age and seroprevalence can be used to estimate the annual attack rate of an infectious disease. For pathogens with multiple serologically distinct strains, there is a need to describe composite exposure to an antigenically variable group of pathogens. In this study, we assay 24,402 general-population serum samples, collected in Vietnam between 2009 to 2015, for antibodies to eleven human influenza A strains. We report that a principal components decomposition of antibody titer data gives the first principal component as an appropriate surrogate for seroprevalence; this results in annual attack rate estimates of 25.6% (95% CI: 24.1% - 27.1%) for subtype H3 and 16.0% (95% CI: 14.7% - 17.3%) for subtype H1. The remaining principal components separate the strains by serological similarity and associate birth cohorts with their particular influenza histories. Our work shows that dimensionality reduction can be used on human antibody profiles to construct an age-seroprevalence relationship for antigenically variable pathogens.
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MESH Headings
- Algorithms
- Antibodies, Viral/blood
- Antibodies, Viral/immunology
- Geography
- Hemagglutinin Glycoproteins, Influenza Virus/immunology
- Humans
- Immunoglobulin G/blood
- Immunoglobulin G/immunology
- Influenza A Virus, H1N1 Subtype/immunology
- Influenza A Virus, H1N1 Subtype/physiology
- Influenza A Virus, H3N2 Subtype/immunology
- Influenza A Virus, H3N2 Subtype/physiology
- Influenza A virus/classification
- Influenza A virus/immunology
- Influenza A virus/physiology
- Influenza, Human/epidemiology
- Influenza, Human/immunology
- Influenza, Human/virology
- Models, Theoretical
- Seroepidemiologic Studies
- Time Factors
- Vietnam/epidemiology
- Virus Replication/immunology
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Affiliation(s)
- Dao Nguyen Vinh
- Oxford University Clinical Research Unit, Wellcome Trust Major Overseas Programme, Ho Chi Minh City, Vietnam
| | - Nguyen Thi Duy Nhat
- Oxford University Clinical Research Unit, Wellcome Trust Major Overseas Programme, Ho Chi Minh City, Vietnam
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK
- Center for Infectious Disease Dynamics, Department of Biology, Pennsylvania State University, University Park, PA, USA
| | - Erwin de Bruin
- Department of Viroscience, Erasmus Medical Centre, Rotterdam, Netherlands
| | - Nguyen Ha Thao Vy
- Oxford University Clinical Research Unit, Wellcome Trust Major Overseas Programme, Ho Chi Minh City, Vietnam
| | - Tran Thi Nhu Thao
- Oxford University Clinical Research Unit, Wellcome Trust Major Overseas Programme, Ho Chi Minh City, Vietnam
| | - Huynh Thi Phuong
- Oxford University Clinical Research Unit, Wellcome Trust Major Overseas Programme, Ho Chi Minh City, Vietnam
| | - Pham Hong Anh
- Oxford University Clinical Research Unit, Wellcome Trust Major Overseas Programme, Ho Chi Minh City, Vietnam
| | - Stacy Todd
- Oxford University Clinical Research Unit, Wellcome Trust Major Overseas Programme, Ho Chi Minh City, Vietnam
- Liverpool School of Tropical Medicine, Liverpool, UK
- Tropical and Infectious Disease Unit, Liverpool University Hospitals NHS Foundation Trust, Liverpool, England
| | - Tran Minh Quan
- Oxford University Clinical Research Unit, Wellcome Trust Major Overseas Programme, Ho Chi Minh City, Vietnam
| | - Nguyen Thi Le Thanh
- Oxford University Clinical Research Unit, Wellcome Trust Major Overseas Programme, Ho Chi Minh City, Vietnam
| | | | | | | | - Pham Quang Thai
- National Institute of Hygiene and Epidemiology, Hanoi, Vietnam
| | - Marc Choisy
- Oxford University Clinical Research Unit, Wellcome Trust Major Overseas Programme, Ho Chi Minh City, Vietnam
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Tran Dang Nguyen
- Center for Infectious Disease Dynamics, Department of Biology, Pennsylvania State University, University Park, PA, USA
| | - Cameron P Simmons
- Institute of Vector Borne Disease, Monash University, Melbourne, VIC, Australia
| | - Guy E Thwaites
- Oxford University Clinical Research Unit, Wellcome Trust Major Overseas Programme, Ho Chi Minh City, Vietnam
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Hannah E Clapham
- Oxford University Clinical Research Unit, Wellcome Trust Major Overseas Programme, Ho Chi Minh City, Vietnam
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
| | | | - Marion Koopmans
- Department of Viroscience, Erasmus Medical Centre, Rotterdam, Netherlands
| | - Maciej F Boni
- Oxford University Clinical Research Unit, Wellcome Trust Major Overseas Programme, Ho Chi Minh City, Vietnam.
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK.
- Center for Infectious Disease Dynamics, Department of Biology, Pennsylvania State University, University Park, PA, USA.
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Linderman SL, Ellebedy AH, Davis C, Eberhardt CS, Antia R, Ahmed R, Zarnitsyna VI. Influenza Immunization in the Context of Preexisting Immunity. Cold Spring Harb Perspect Med 2021; 11:a040964. [PMID: 32988981 PMCID: PMC8559541 DOI: 10.1101/cshperspect.a040964] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
Although we develop influenza immunity from an early age, it is insufficient to prevent future infection with antigenically novel strains. One proposed way to generate long-term protective immunity against a broad range of influenza virus strains is to boost responses to the conserved epitopes on the hemagglutinin, the major surface glycoprotein on the influenza virus. Influenza-specific humoral immunity comprises a large fraction of the overall immune memory in humans, and it has been long recognized that preexisting immunity to influenza shapes the response to subsequent influenza infections and vaccinations. However, the mechanisms by which preexisting immunity modulates the response to influenza vaccination are still not completely understood. Using a set of mathematical models, we explore several hypotheses that may contribute to diminished boosting of antibodies to conserved epitopes after repeated vaccinations.
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Affiliation(s)
- Susanne L Linderman
- Emory Vaccine Center and Department of Microbiology and Immunology, School of Medicine, Emory University, Atlanta, Georgia 30322, USA
| | - Ali H Ellebedy
- Emory Vaccine Center and Department of Microbiology and Immunology, School of Medicine, Emory University, Atlanta, Georgia 30322, USA
- Department of Pathology and Immunology, Washington University School of Medicine, Saint Louis, Missouri 63110, USA
| | - Carl Davis
- Emory Vaccine Center and Department of Microbiology and Immunology, School of Medicine, Emory University, Atlanta, Georgia 30322, USA
| | - Christiane S Eberhardt
- Emory Vaccine Center and Department of Microbiology and Immunology, School of Medicine, Emory University, Atlanta, Georgia 30322, USA
- Centre for Vaccinology and Department of Pediatrics, University Hospitals of Geneva and Faculty of Medicine, University of Geneva, 1205 Geneva, Switzerland
| | - Rustom Antia
- Department of Biology, Emory University, Atlanta, Georgia 30322, USA
| | - Rafi Ahmed
- Emory Vaccine Center and Department of Microbiology and Immunology, School of Medicine, Emory University, Atlanta, Georgia 30322, USA
| | - Veronika I Zarnitsyna
- Emory Vaccine Center and Department of Microbiology and Immunology, School of Medicine, Emory University, Atlanta, Georgia 30322, USA
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Crowley AR, Natarajan H, Hederman AP, Bobak CA, Weiner JA, Wieland-Alter W, Lee J, Bloch EM, Tobian AA, Redd AD, Blankson JN, Wolf D, Goetghebuer T, Marchant A, Connor RI, Wright PF, Ackerman ME. Boosting of Cross-Reactive Antibodies to Endemic Coronaviruses by SARS-CoV-2 Infection but not Vaccination with Stabilized Spike. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2021:2021.10.27.21265574. [PMID: 34729565 PMCID: PMC8562549 DOI: 10.1101/2021.10.27.21265574] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
Pre-existing antibodies to endemic coronaviruses (CoV) that cross-react with SARS-CoV-2 have the potential to influence the antibody response to COVID-19 vaccination and infection for better or worse. In this observational study of mucosal and systemic humoral immunity in acutely infected, convalescent, and vaccinated subjects, we tested for cross reactivity against endemic CoV spike (S) protein at subdomain resolution. Elevated responses, particularly to the β-CoV OC43, were observed in all natural infection cohorts tested and were correlated with the response to SARS-CoV-2. The kinetics of this response and isotypes involved suggest that infection boosts preexisting antibody lineages raised against prior endemic CoV exposure that cross react. While further research is needed to discern whether this recalled response is desirable or detrimental, the boosted antibodies principally targeted the better conserved S2 subdomain of the viral spike and were not associated with neutralization activity. In contrast, vaccination with a stabilized spike mRNA vaccine did not robustly boost cross-reactive antibodies, suggesting differing antigenicity and immunogenicity. In sum, this study provides evidence that antibodies targeting endemic CoV are robustly boosted in response to SARS-CoV-2 infection but not to vaccination with stabilized S, and that depending on conformation or other factors, the S2 subdomain of the spike protein triggers a rapidly recalled, IgG-dominated response that lacks neutralization activity.
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Affiliation(s)
- Andrew R. Crowley
- Department of Microbiology and Immunology, Geisel School of Medicine at Dartmouth, Dartmouth College, Hanover, NH, USA
| | - Harini Natarajan
- Department of Microbiology and Immunology, Geisel School of Medicine at Dartmouth, Dartmouth College, Hanover, NH, USA
| | | | - Carly A. Bobak
- Biomedical Data Science, Dartmouth College, Hanover, NH, USA
| | - Joshua A. Weiner
- Thayer School of Engineering, Dartmouth College, Hanover, NH, USA
| | - Wendy Wieland-Alter
- Department of Pediatrics, Geisel School of Medicine at Dartmouth, Dartmouth-Hitchcock Medical Center, Lebanon, NH, USA
| | - Jiwon Lee
- Thayer School of Engineering, Dartmouth College, Hanover, NH, USA
| | - Evan M. Bloch
- Department of Pathology, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Aaron A.R. Tobian
- Department of Pathology, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Andrew D. Redd
- Department of Medicine, Division of Infectious Diseases, Johns Hopkins School of Medicine, Baltimore, MD, USA
- Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Joel N. Blankson
- Department of Medicine, Division of Infectious Diseases, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Dana Wolf
- Hadassah University Medical Center, Jerusalem, Israel
| | - Tessa Goetghebuer
- Institute for Medical Immunology, Université libre de Bruxelles, Charleroi, Belgium
- Pediatric Department, CHU St Pierre, Brussels, Belgium
| | - Arnaud Marchant
- Institute for Medical Immunology, Université libre de Bruxelles, Charleroi, Belgium
| | - Ruth I. Connor
- Department of Pediatrics, Geisel School of Medicine at Dartmouth, Dartmouth-Hitchcock Medical Center, Lebanon, NH, USA
| | - Peter F. Wright
- Department of Pediatrics, Geisel School of Medicine at Dartmouth, Dartmouth-Hitchcock Medical Center, Lebanon, NH, USA
| | - Margaret E. Ackerman
- Department of Microbiology and Immunology, Geisel School of Medicine at Dartmouth, Dartmouth College, Hanover, NH, USA
- Thayer School of Engineering, Dartmouth College, Hanover, NH, USA
- Biomedical Data Science, Dartmouth College, Hanover, NH, USA
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33
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Vieira MC, Donato CM, Arevalo P, Rimmelzwaan GF, Wood T, Lopez L, Huang QS, Dhanasekaran V, Koelle K, Cobey S. Lineage-specific protection and immune imprinting shape the age distributions of influenza B cases. Nat Commun 2021; 12:4313. [PMID: 34262041 PMCID: PMC8280188 DOI: 10.1038/s41467-021-24566-y] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2020] [Accepted: 06/22/2021] [Indexed: 02/06/2023] Open
Abstract
How a history of influenza virus infections contributes to protection is not fully understood, but such protection might explain the contrasting age distributions of cases of the two lineages of influenza B, B/Victoria and B/Yamagata. Fitting a statistical model to those distributions using surveillance data from New Zealand, we found they could be explained by historical changes in lineage frequencies combined with cross-protection between strains of the same lineage. We found additional protection against B/Yamagata in people for whom it was their first influenza B infection, similar to the immune imprinting observed in influenza A. While the data were not informative about B/Victoria imprinting, B/Yamagata imprinting could explain the fewer B/Yamagata than B/Victoria cases in cohorts born in the 1990s and the bimodal age distribution of B/Yamagata cases. Longitudinal studies can test if these forms of protection inferred from historical data extend to more recent strains and other populations.
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Affiliation(s)
- Marcos C Vieira
- Department of Ecology and Evolution, University of Chicago, Chicago, IL, USA.
| | - Celeste M Donato
- Enteric Diseases Group, Murdoch Children's Research Institute, Parkville, VIC, Australia
- Department of Paediatrics, The University of Melbourne, Parkville, VIC, Australia
| | - Philip Arevalo
- Department of Ecology and Evolution, University of Chicago, Chicago, IL, USA
| | - Guus F Rimmelzwaan
- Research Center for Emerging Infections and Zoonoses, University of Veterinary Medicine Hannover, Hannover, Germany
| | - Timothy Wood
- Institute of Environmental Science and Research, Wellington, New Zealand
| | - Liza Lopez
- Institute of Environmental Science and Research, Wellington, New Zealand
| | - Q Sue Huang
- Institute of Environmental Science and Research, Wellington, New Zealand
| | - Vijaykrishna Dhanasekaran
- Department of Microbiology, Biomedicine Discovery Institute, Monash University, Melbourne, VIC, Australia
| | - Katia Koelle
- Department of Biology, Emory University, Atlanta, GA, USA
| | - Sarah Cobey
- Department of Ecology and Evolution, University of Chicago, Chicago, IL, USA.
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Jackson-Thompson BM, Goguet E, Laing ED, Olsen CH, Pollett S, Hollis-Perry KM, Maiolatesi SE, Illinik L, Ramsey KF, Reyes AE, Alcorta Y, Wong MA, Davies J, Ortega O, Parmelee E, Lindrose AR, Moser M, Graydon E, Letizia AG, Duplessis CA, Ganesan A, Pratt KP, Malloy AM, Scott DW, Anderson SK, Snow AL, Dalgard CL, Powers JH, Tribble D, Burgess TH, Broder CC, Mitre E. Prospective Assessment of SARS-CoV-2 Seroconversion (PASS) study: an observational cohort study of SARS-CoV-2 infection and vaccination in healthcare workers. BMC Infect Dis 2021; 21:544. [PMID: 34107889 PMCID: PMC8188741 DOI: 10.1186/s12879-021-06233-1] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2021] [Accepted: 05/24/2021] [Indexed: 12/17/2022] Open
Abstract
BACKGROUND SARS-CoV-2 is a recently emerged pandemic coronavirus (CoV) capable of causing severe respiratory illness. However, a significant number of infected people present as asymptomatic or pauci-symptomatic. In this prospective assessment of at-risk healthcare workers (HCWs) we seek to determine whether pre-existing antibody or T cell responses to previous seasonal human coronavirus (HCoV) infections affect immunological or clinical responses to SARS-CoV-2 infection or vaccination. METHODS A cohort of 300 healthcare workers, confirmed negative for SARS-CoV-2 exposure upon study entry, will be followed for up to 1 year with monthly serology analysis of IgM and IgG antibodies against the spike proteins of SARS-CoV-2 and the four major seasonal human coronavirus - HCoV-OC43, HCoV-HKU1, HCoV-229E, and HCoV-NL63. Participants will complete monthly questionnaires that ask about Coronavirus Disease 2019 (COVID-19) exposure risks, and a standardized, validated symptom questionnaire (scoring viral respiratory disease symptoms, intensity and severity) at least twice monthly and any day when any symptoms manifest. SARS-CoV-2 PCR testing will be performed any time participants develop symptoms consistent with COVID-19. For those individuals that seroconvert and/or test positive by SARS-CoV-2 PCR, or receive the SARS-CoV-2 vaccine, additional studies of T cell activation and cytokine production in response to SARS-CoV-2 peptide pools and analysis of Natural Killer cell numbers and function will be conducted on that participant's cryopreserved baseline peripheral blood mononuclear cells (PBMCs). Following the first year of this study we will further analyze those participants having tested positive for COVID-19, and/or having received an authorized/licensed SARS-CoV-2 vaccine, quarterly (year 2) and semi-annually (years 3 and 4) to investigate immune response longevity. DISCUSSION This study will determine the frequency of asymptomatic and pauci-symptomatic SARS-CoV-2 infection in a cohort of at-risk healthcare workers. Baseline and longitudinal assays will determine the frequency and magnitude of anti-spike glycoprotein antibodies to the seasonal HCoV-OC43, HCoV-HKU1, HCoV-229E, and HCoV-NL63, and may inform whether pre-existing antibodies to these human coronaviruses are associated with altered COVID-19 disease course. Finally, this study will evaluate whether pre-existing immune responses to seasonal HCoVs affect the magnitude and duration of antibody and T cell responses to SARS-CoV-2 vaccination, adjusting for demographic covariates.
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Affiliation(s)
- Belinda M Jackson-Thompson
- Department of Microbiology and Immunology, Uniformed Services University of the Health Science, Bethesda, MD, USA.
- Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc, Bethesda, MD, USA.
| | - Emilie Goguet
- Department of Microbiology and Immunology, Uniformed Services University of the Health Science, Bethesda, MD, USA
- Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc, Bethesda, MD, USA
| | - Eric D Laing
- Department of Microbiology and Immunology, Uniformed Services University of the Health Science, Bethesda, MD, USA
| | - Cara H Olsen
- Department of Preventive Medicine & Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, USA
| | - Simon Pollett
- Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc, Bethesda, MD, USA
- Infectious Disease Clinical Research Program, Department of Preventive Medicine and Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
| | | | - Santina E Maiolatesi
- Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc, Bethesda, MD, USA
- Clinical Trials Center, Naval Medical Research Center, Silver Spring, MD, USA
| | - Luca Illinik
- Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc, Bethesda, MD, USA
- Infectious Disease Clinical Research Program, Department of Preventive Medicine and Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
| | - Kathleen F Ramsey
- Clinical Trials Center, Naval Medical Research Center, Silver Spring, MD, USA
- General Dynamics Information Technology, Falls Church, VA, USA
| | - Anatalio E Reyes
- Clinical Trials Center, Naval Medical Research Center, Silver Spring, MD, USA
- General Dynamics Information Technology, Falls Church, VA, USA
| | - Yolanda Alcorta
- Clinical Trials Center, Naval Medical Research Center, Silver Spring, MD, USA
- General Dynamics Information Technology, Falls Church, VA, USA
| | - Mimi A Wong
- Clinical Trials Center, Naval Medical Research Center, Silver Spring, MD, USA
- General Dynamics Information Technology, Falls Church, VA, USA
| | - Julian Davies
- Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc, Bethesda, MD, USA
- Infectious Disease Clinical Research Program, Department of Preventive Medicine and Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
| | - Orlando Ortega
- Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc, Bethesda, MD, USA
- Infectious Disease Clinical Research Program, Department of Preventive Medicine and Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
| | - Edward Parmelee
- Infectious Disease Clinical Research Program, Department of Preventive Medicine and Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
| | - Alyssa R Lindrose
- Department of Microbiology and Immunology, Uniformed Services University of the Health Science, Bethesda, MD, USA
- Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc, Bethesda, MD, USA
| | - Matthew Moser
- Department of Microbiology and Immunology, Uniformed Services University of the Health Science, Bethesda, MD, USA
- Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc, Bethesda, MD, USA
| | - Elizabeth Graydon
- Department of Microbiology and Immunology, Uniformed Services University of the Health Science, Bethesda, MD, USA
| | - Andrew G Letizia
- Infectious Disease Directorate, Naval Medical Research Center, Silver Spring, MD, USA
| | | | - Anuradha Ganesan
- Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc, Bethesda, MD, USA
- Infectious Disease Clinical Research Program, Department of Preventive Medicine and Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
| | - Kathleen P Pratt
- Department of Medicine, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
| | - Allison M Malloy
- Department of Pediatrics, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
| | - David W Scott
- Department of Medicine, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
| | - Stephen K Anderson
- Basic Science Program, Frederick National Laboratory for Cancer Research, Frederick, MD, USA
| | - Andrew L Snow
- Department of Pharmacology and Molecular Therapeutics, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
| | - Clifton L Dalgard
- Department of Anatomy, Physiology, and Genetics, and The American Genome Center, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
| | - John H Powers
- Clinical Research Directorate, Leidos Biomedical Research, Inc, Frederick National Laboratory for Cancer Research, Frederick, MD, USA
| | - David Tribble
- Infectious Disease Clinical Research Program, Department of Preventive Medicine and Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
| | - Timothy H Burgess
- Infectious Disease Clinical Research Program, Department of Preventive Medicine and Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
| | - Christopher C Broder
- Department of Microbiology and Immunology, Uniformed Services University of the Health Science, Bethesda, MD, USA
| | - Edward Mitre
- Department of Microbiology and Immunology, Uniformed Services University of the Health Science, Bethesda, MD, USA.
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35
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Owers Bonner KA, Cruz JS, Sacramento GA, de Oliveira D, Nery N, Carvalho M, Costa F, Childs JE, Ko AI, Diggle PJ. Effects of Accounting for Interval-Censored Antibody Titer Decay on Seroincidence in a Longitudinal Cohort Study of Leptospirosis. Am J Epidemiol 2021; 190:893-899. [PMID: 33274738 DOI: 10.1093/aje/kwaa253] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2020] [Revised: 11/14/2020] [Accepted: 11/16/2020] [Indexed: 12/23/2022] Open
Abstract
Accurate measurements of seroincidence are critical for infections undercounted by reported cases, such as influenza, arboviral diseases, and leptospirosis. However, conventional methods of interpreting paired serological samples do not account for antibody titer decay, resulting in underestimated seroincidence rates. To improve interpretation of paired sera, we modeled exponential decay of interval-censored microscopic agglutination test titers using a historical data set of leptospirosis cases traced to a point source exposure in Italy in 1984. We then applied that decay rate to a longitudinal cohort study conducted in a high-transmission setting in Salvador, Brazil (2013-2015). We estimated a decay constant of 0.926 (95% confidence interval: 0.918, 0.934) titer dilutions per month. Accounting for decay in the cohort increased the mean infection rate to 1.21 times the conventionally defined rate over 6-month intervals (range, 1.10-1.36) and 1.82 times that rate over 12-month intervals (range, 1.65-2.07). Improved estimates of infection in longitudinal data have broad epidemiologic implications, including comparing studies with different sampling intervals, improving sample size estimation, and determining risk factors for infection and the role of acquired immunity. Our method of estimating and accounting for titer decay is generalizable to other infections defined using interval-censored serological assays.
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36
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Quandelacy TM, Cummings DAT, Jiang CQ, Yang B, Kwok KO, Dai B, Shen R, Read JM, Zhu H, Guan Y, Riley S, Lessler J. Using serological measures to estimate influenza incidence in the presence of secular trends in exposure and immuno-modulation of antibody response. Influenza Other Respir Viruses 2021; 15:235-244. [PMID: 33108707 PMCID: PMC7902255 DOI: 10.1111/irv.12807] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2020] [Revised: 08/24/2020] [Accepted: 08/30/2020] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND Influenza infection is often measured by a fourfold antibody titer increase over an influenza season (ie seroconversion). However, this approach may fail when influenza seasons are less distinct as it does not account for transient effects from recent infections. Here, we present a method to determine seroconversion for non-paired sera, adjusting for changes in individuals' antibody titers to influenza due to the transient impact of recent exposures, varied sampling times, and laboratory processes. METHODS We applied our method using data for five H3N2 strains collected from 942 individuals, aged 2-90 years, during the first two study visits of the Fluscape cohort study (2009-2012) in Guangzhou, China. RESULTS After adjustment, apparent seroconversion rates for non-circulating strains decreased while we observed a 20% increase in seroconversion rates to recently circulating strains. When examining seroconversion to the most recently circulating strain (A/Brisbane/20/2007) in our study, participants aged under 18, and over 64 had the highest seroconversion rates compared to other age groups. CONCLUSIONS Our results highlight the need for improved methods when using antibody titers as an endpoint in settings where there is no clear influenza "off" season. Methods, like those presented here, that use titers from circulating and non-circulating strains may be key.
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Affiliation(s)
- Talia M. Quandelacy
- Department of EpidemiologyJohns Hopkins Bloomberg School of Public HealthBaltimoreMDUSA
- Present address:
Centers for Disease Control and PreventionSan JuanPuerto Rico
| | - Derek A. T. Cummings
- Department of EpidemiologyJohns Hopkins Bloomberg School of Public HealthBaltimoreMDUSA
- Department of BiologyUniversity of FloridaGainesvilleFLUSA
| | | | - Bingyi Yang
- Department of BiologyUniversity of FloridaGainesvilleFLUSA
| | - Kin On Kwok
- The Jockey Club School of Public Health and Primary CareThe Chinese University of Hong KongHong Kong Special Administrative RegionChina
- Stanley Ho Centre for Emerging Infectious DiseasesHong Kong Special Administrative RegionThe Chinese University of Hong KongShatin, Hong KongChina
- Shenzhen Research InstituteThe Chinese University of Hong KongShenzhenChina
| | - Byran Dai
- Department of EpidemiologyJohns Hopkins Bloomberg School of Public HealthBaltimoreMDUSA
| | | | - Jonathan M. Read
- Center for Health Informatics Computing and StatisticsLancaster Medical SchoolLancaster UniversityLancasterUK
- Institute of Infection and Global HealthUniversity of LiverpoolLiverpoolUK
| | - Huachen Zhu
- State Key Laboratory of Emerging Infectious DiseasesSchool of Public HealthThe University of Hong KongHong KongChina
- Shantou University Medical CollegeShantouChina
| | - Yi Guan
- Shantou University Medical CollegeShantouChina
- School of Public HealthImperial College LondonLondonUK
| | - Steven Riley
- School of Public HealthImperial College LondonLondonUK
| | - Justin Lessler
- Department of EpidemiologyJohns Hopkins Bloomberg School of Public HealthBaltimoreMDUSA
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37
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Kistler KE, Bedford T. Evidence for adaptive evolution in the receptor-binding domain of seasonal coronaviruses OC43 and 229e. eLife 2021; 10:64509. [PMID: 33463525 PMCID: PMC7861616 DOI: 10.7554/elife.64509] [Citation(s) in RCA: 65] [Impact Index Per Article: 21.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2020] [Accepted: 12/12/2020] [Indexed: 11/13/2022] Open
Abstract
Seasonal coronaviruses (OC43, 229E, NL63, and HKU1) are endemic to the human population, regularly infecting and reinfecting humans while typically causing asymptomatic to mild respiratory infections. It is not known to what extent reinfection by these viruses is due to waning immune memory or antigenic drift of the viruses. Here we address the influence of antigenic drift on immune evasion of seasonal coronaviruses. We provide evidence that at least two of these viruses, OC43 and 229E, are undergoing adaptive evolution in regions of the viral spike protein that are exposed to human humoral immunity. This suggests that reinfection may be due, in part, to positively selected genetic changes in these viruses that enable them to escape recognition by the immune system. It is possible that, as with seasonal influenza, these adaptive changes in antigenic regions of the virus would necessitate continual reformulation of a vaccine made against them.
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Affiliation(s)
- Kathryn E Kistler
- Molecular and Cellular Biology Program, University of Washington, Seattle, United States.,Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, United States
| | - Trevor Bedford
- Molecular and Cellular Biology Program, University of Washington, Seattle, United States.,Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, United States
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38
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Furuse Y, Oshitani H. Viruses That Can and Cannot Coexist With Humans and the Future of SARS-CoV-2. Front Microbiol 2020; 11:583252. [PMID: 33042101 PMCID: PMC7530166 DOI: 10.3389/fmicb.2020.583252] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2020] [Accepted: 08/19/2020] [Indexed: 12/14/2022] Open
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become a worldwide pandemic. Many projections concerning the outbreak, such as the estimated number of cases and deaths in upcoming months, have been made available. However, what happens to the virus after the pandemic subsides has not been fully explored. In this article, we discuss the ways that past and present human viruses have emerged via zoonotic transmission, the mechanisms that they have acquired the ability for effective transmission among humans, the process to sustain a chain of transmission to coexist with humans, and the factors important for complete containment leading to eradication of viruses. These aspects of viral disease may provide clues for the future path that SARS-CoV-2 might take in relation to human infection.
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Affiliation(s)
- Yuki Furuse
- Institute for Frontier Life and Medical Sciences, Kyoto University, Kyoto, Japan
- Hakubi Center for Advanced Research, Kyoto University, Kyoto, Japan
| | - Hitoshi Oshitani
- Department of Virology, Tohoku University Graduate School of Medicine, Sendai, Japan
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39
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Original antigenic sin priming of influenza virus hemagglutinin stalk antibodies. Proc Natl Acad Sci U S A 2020; 117:17221-17227. [PMID: 32631992 DOI: 10.1073/pnas.1920321117] [Citation(s) in RCA: 48] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Immunity to influenza viruses can be long-lived, but reinfections with antigenically distinct viral strains and subtypes are common. Reinfections can boost antibody responses against viral strains first encountered in childhood through a process termed "original antigenic sin." It is unknown how initial childhood exposures affect the induction of antibodies against the hemagglutinin (HA) stalk domain of influenza viruses. This is an important consideration since broadly reactive HA stalk antibodies can protect against infection, and universal vaccine platforms are being developed to induce these antibodies. Here we show that experimentally infected ferrets and naturally infected humans establish strong "immunological imprints" against HA stalk antigens first encountered during primary influenza virus infections. We found that HA stalk antibodies are surprisingly boosted upon subsequent infections with antigenically distinct influenza A virus subtypes. Paradoxically, these heterosubtypic-boosted HA stalk antibodies do not bind efficiently to the boosting influenza virus strain. Our results demonstrate that an individual's HA stalk antibody response is dependent on the specific subtype of influenza virus that they first encounter early in life. We propose that humans are susceptible to heterosubtypic influenza virus infections later in life since these viruses boost HA stalk antibodies that do not bind efficiently to the boosting antigen.
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40
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Yang B, Lessler J, Zhu H, Jiang CQ, Read JM, Hay JA, Kwok KO, Shen R, Guan Y, Riley S, Cummings DAT. Life course exposures continually shape antibody profiles and risk of seroconversion to influenza. PLoS Pathog 2020; 16:e1008635. [PMID: 32702069 PMCID: PMC7377380 DOI: 10.1371/journal.ppat.1008635] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2020] [Accepted: 05/14/2020] [Indexed: 12/05/2022] Open
Abstract
Complex exposure histories and immune mediated interactions between influenza strains contribute to the life course of human immunity to influenza. Antibody profiles can be generated by characterizing immune responses to multiple antigenically variant strains, but how these profiles vary across individuals and determine future responses is unclear. We used hemagglutination inhibition titers from 21 H3N2 strains to construct 777 paired antibody profiles from people aged 2 to 86, and developed novel metrics to capture features of these profiles. Total antibody titer per potential influenza exposure increases in early life, then decreases in middle age. Increased titers to one or more strains were seen in 97.8% of participants during a roughly four-year interval, suggesting widespread influenza exposure. While titer changes were seen to all strains, recently circulating strains exhibited the greatest titer rise. Higher pre-existing, homologous titers at baseline reduced the risk of seroconversion to recent strains. After adjusting for homologous titer, we also found an increased frequency of seroconversion against recent strains among those with higher immunity to older previously exposed strains. Including immunity to previously exposures also improved the deviance explained by the models. Our results suggest that a comprehensive quantitative description of immunity encompassing past exposures could lead to improved correlates of risk of influenza infection.
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Affiliation(s)
- Bingyi Yang
- Department of Biology, University of Florida, Gainesville, Florida, United States of America
- Emerging Pathogens Institute, University of Florida, Gainesville, Florida, United States of America
| | - Justin Lessler
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America
| | - Huachen Zhu
- State Key Laboratory of Emerging Infectious Diseases and Centre of Influenza Research, School of Public Health, The University of Hong Kong, Hong Kong SAR, China
- Joint Institute of Virology (Shantou University–The University of Hong Kong), Shantou University, Shantou, Guangdong, China
| | | | - Jonathan M. Read
- Centre for Health Informatics Computing and Statistics, Lancaster Medical School, Lancaster University, Lancaster, United Kingdom
| | - James A. Hay
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, United Kingdom
| | - Kin On Kwok
- The Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China
- Stanley Ho Centre for Emerging Infectious Diseases, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region, China
- Shenzhen Research Institute of The Chinese University of Hong Kong, Shenzhen, Guangdong, China
| | - Ruiyin Shen
- Guangzhou No.12 Hospital, Guangzhou, Guangdong, China
| | - Yi Guan
- State Key Laboratory of Emerging Infectious Diseases and Centre of Influenza Research, School of Public Health, The University of Hong Kong, Hong Kong SAR, China
- Joint Institute of Virology (Shantou University–The University of Hong Kong), Shantou University, Shantou, Guangdong, China
| | - Steven Riley
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, United Kingdom
| | - Derek A. T. Cummings
- Department of Biology, University of Florida, Gainesville, Florida, United States of America
- Emerging Pathogens Institute, University of Florida, Gainesville, Florida, United States of America
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41
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Lam EKS, Morris DH, Hurt AC, Barr IG, Russell CA. The impact of climate and antigenic evolution on seasonal influenza virus epidemics in Australia. Nat Commun 2020; 11:2741. [PMID: 32488106 PMCID: PMC7265451 DOI: 10.1038/s41467-020-16545-6] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2019] [Accepted: 05/09/2020] [Indexed: 11/08/2022] Open
Abstract
Although seasonal influenza viruses circulate globally, prevention and treatment occur at the level of regions, cities, and communities. At these scales, the timing, duration and magnitude of epidemics vary substantially, but the underlying causes of this variation are poorly understood. Here, based on analyses of a 15-year city-level dataset of 18,250 laboratory-confirmed and antigenically-characterised influenza virus infections from Australia, we investigate the effects of previously hypothesised environmental and virological drivers of influenza epidemics. We find that anomalous fluctuations in temperature and humidity do not predict local epidemic onset timings. We also find that virus antigenic change has no consistent effect on epidemic size. In contrast, epidemic onset time and heterosubtypic competition have substantial effects on epidemic size and composition. Our findings suggest that the relationship between influenza population immunity and epidemiology is more complex than previously supposed and that the strong influence of short-term processes may hinder long-term epidemiological forecasts.
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Affiliation(s)
- Edward K S Lam
- Department of Veterinary Medicine, University of Cambridge, Cambridge, UK
| | - Dylan H Morris
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA
| | - Aeron C Hurt
- WHO Collaborating Centre for Reference and Research on Influenza, VIDRL, Peter Doherty Institute for Infection and Immunity, Melbourne, VIC, Australia
- Department of Microbiology and Immunology, University of Melbourne, Parkville, VIC, Australia
| | - Ian G Barr
- WHO Collaborating Centre for Reference and Research on Influenza, VIDRL, Peter Doherty Institute for Infection and Immunity, Melbourne, VIC, Australia
- Department of Microbiology and Immunology, University of Melbourne, Parkville, VIC, Australia
- School of Applied Biomedical Sciences, Federation University, Churchill, VIC, Australia
| | - Colin A Russell
- Department of Medical Microbiology, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands.
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42
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Yang W, Lau EHY, Cowling BJ. Dynamic interactions of influenza viruses in Hong Kong during 1998-2018. PLoS Comput Biol 2020; 16:e1007989. [PMID: 32542015 PMCID: PMC7316359 DOI: 10.1371/journal.pcbi.1007989] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2019] [Revised: 06/25/2020] [Accepted: 05/27/2020] [Indexed: 11/19/2022] Open
Abstract
Influenza epidemics cause substantial morbidity and mortality every year worldwide. Currently, two influenza A subtypes, A(H1N1) and A(H3N2), and type B viruses co-circulate in humans and infection with one type/subtype could provide cross-protection against the others. However, it remains unclear how such ecologic competition via cross-immunity and antigenic mutations that allow immune escape impact influenza epidemic dynamics at the population level. Here we develop a comprehensive model-inference system and apply it to study the evolutionary and epidemiological dynamics of the three influenza types/subtypes in Hong Kong, a city of global public health significance for influenza epidemic and pandemic control. Utilizing long-term influenza surveillance data since 1998, we are able to estimate the strength of cross-immunity between each virus-pairs, the timing and frequency of punctuated changes in population immunity in response to antigenic mutations in influenza viruses, and key epidemiological parameters over the last 20 years including the 2009 pandemic. We find evidence of cross-immunity in all types/subtypes, with strongest cross-immunity from A(H1N1) against A(H3N2). Our results also suggest that A(H3N2) may undergo antigenic mutations in both summers and winters and thus monitoring the virus in both seasons may be important for vaccine development. Overall, our study reveals intricate epidemiological interactions and underscores the importance of simultaneous monitoring of population immunity, incidence rates, and viral genetic and antigenic changes.
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Affiliation(s)
- Wan Yang
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York, United States of America
| | - Eric H. Y. Lau
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, the University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Benjamin J. Cowling
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, the University of Hong Kong, Hong Kong Special Administrative Region, China
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43
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Hay JA, Minter A, Ainslie KEC, Lessler J, Yang B, Cummings DAT, Kucharski AJ, Riley S. An open source tool to infer epidemiological and immunological dynamics from serological data: serosolver. PLoS Comput Biol 2020; 16:e1007840. [PMID: 32365062 PMCID: PMC7241836 DOI: 10.1371/journal.pcbi.1007840] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2020] [Revised: 05/21/2020] [Accepted: 04/01/2020] [Indexed: 11/19/2022] Open
Abstract
We present a flexible, open source R package designed to obtain biological and epidemiological insights from serological datasets. Characterising past exposures for multi-strain pathogens poses a specific statistical challenge: observed antibody responses measured in serological assays depend on multiple unobserved prior infections that produce cross-reactive antibody responses. We provide a general modelling framework to jointly infer infection histories and describe immune responses generated by these infections using antibody titres against current and historical strains. We do this by linking latent infection dynamics with a mechanistic model of antibody kinetics that generates expected antibody titres over time. Our aim is to provide a flexible package to identify infection histories that can be applied to a range of pathogens. We present two case studies to illustrate how our model can infer key immunological parameters, such as antibody titre boosting, waning and cross-reaction, as well as latent epidemiological processes such as attack rates and age-stratified infection risk.
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Affiliation(s)
- James A. Hay
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, United Kingdom
- Center for Communicable Disease Dynamics, Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, United States of America
| | - Amanda Minter
- Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom
| | - Kylie E. C. Ainslie
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, United Kingdom
| | - Justin Lessler
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America
| | - Bingyi Yang
- Department of Biology, University of Florida, Gainesville, Florida, United States of America
- Emerging Pathogens Institute, University of Florida, Gainesville, Florida, United States of America
| | - Derek A. T. Cummings
- Department of Biology, University of Florida, Gainesville, Florida, United States of America
- Emerging Pathogens Institute, University of Florida, Gainesville, Florida, United States of America
| | - Adam J. Kucharski
- Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom
| | - Steven Riley
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, United Kingdom
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44
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Khan ZA, Yumnamcha T, Mondal G, Devi SD, Rajiv C, Labala RK, Sanjita Devi H, Chattoraj A. Artificial Light at Night (ALAN): A Potential Anthropogenic Component for the COVID-19 and HCoVs Outbreak. Front Endocrinol (Lausanne) 2020; 11:622. [PMID: 33013700 PMCID: PMC7511708 DOI: 10.3389/fendo.2020.00622] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/02/2020] [Accepted: 07/30/2020] [Indexed: 12/18/2022] Open
Abstract
The origin of the coronavirus disease 2019 (COVID-19) pandemic is zoonotic. The circadian day-night is the rhythmic clue to organisms for their synchronized body functions. The "development for mankind" escalated the use of artificial light at night (ALAN). In this article, we tried to focus on the possible influence of this anthropogenic factor in human coronavirus (HCoV) outbreak. The relationship between the occurrences of coronavirus and the ascending curve of the night-light has also been delivered. The ALAN influences the physiology and behavior of bat, a known nocturnal natural reservoir of many Coronaviridae. The "threatened" and "endangered" status of the majority of bat species is mainly because of the destruction of their proper habit and habitat predominantly through artificial illumination. The stress exerted by ALAN leads to the impaired body functions, especially endocrine, immune, genomic integration, and overall rhythm features of different physiological variables and behaviors in nocturnal animals. Night-light disturbs "virus-host" synchronization and may lead to mutation in the genomic part of the virus and excessive virus shedding. We also proposed some future strategies to mitigate the repercussions of ALAN and for the protection of the living system in the earth as well.
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Affiliation(s)
- Zeeshan Ahmad Khan
- Biological Rhythm Laboratory, Animal Resources Programme, Institute of Bioresources and Sustainable Development, Department of Biotechnology, Government of India, Imphal, India
| | - Thangal Yumnamcha
- Biological Rhythm Laboratory, Animal Resources Programme, Institute of Bioresources and Sustainable Development, Department of Biotechnology, Government of India, Imphal, India
| | - Gopinath Mondal
- Biological Rhythm Laboratory, Animal Resources Programme, Institute of Bioresources and Sustainable Development, Department of Biotechnology, Government of India, Imphal, India
| | - Sijagurumayum Dharmajyoti Devi
- Biological Rhythm Laboratory, Animal Resources Programme, Institute of Bioresources and Sustainable Development, Department of Biotechnology, Government of India, Imphal, India
| | - Chongtham Rajiv
- Biological Rhythm Laboratory, Animal Resources Programme, Institute of Bioresources and Sustainable Development, Department of Biotechnology, Government of India, Imphal, India
| | - Rajendra Kumar Labala
- Distributed Information Sub-centre, Institute of Bioresources and Sustainable Development, Department of Biotechnology, Government of India, Imphal, India
- Biological Rhythm Laboratory, Department of Animal Science, Kazi Nazrul University, Asansol, India
| | - Haobijam Sanjita Devi
- Biological Rhythm Laboratory, Animal Resources Programme, Institute of Bioresources and Sustainable Development, Department of Biotechnology, Government of India, Imphal, India
| | - Asamanja Chattoraj
- Biological Rhythm Laboratory, Department of Animal Science, Kazi Nazrul University, Asansol, India
- *Correspondence: Asamanja Chattoraj ;
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45
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van de Sandt CE, Clemens EB, Grant EJ, Rowntree LC, Sant S, Halim H, Crowe J, Cheng AC, Kotsimbos TC, Richards M, Miller A, Tong SYC, Rossjohn J, Nguyen THO, Gras S, Chen W, Kedzierska K. Challenging immunodominance of influenza-specific CD8 + T cell responses restricted by the risk-associated HLA-A*68:01 allomorph. Nat Commun 2019; 10:5579. [PMID: 31811120 PMCID: PMC6898063 DOI: 10.1038/s41467-019-13346-4] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2019] [Accepted: 11/04/2019] [Indexed: 12/23/2022] Open
Abstract
Although influenza viruses lead to severe illness in high-risk populations, host genetic factors associated with severe disease are largely unknown. As the HLA-A*68:01 allele can be linked to severe pandemic 2009-H1N1 disease, we investigate a potential impairment of HLA-A*68:01-restricted CD8+ T cells to mount robust responses. We elucidate the HLA-A*68:01+CD8+ T cell response directed toward an extended influenza-derived nucleoprotein (NP) peptide and show that only ~35% individuals have immunodominant A68/NP145+CD8+ T cell responses. Dissecting A68/NP145+CD8+ T cells in low vs. medium/high responders reveals that high responding donors have A68/NP145+CD8+ memory T cells with clonally expanded TCRαβs, while low-responders display A68/NP145+CD8+ T cells with predominantly naïve phenotypes and non-expanded TCRαβs. Single-cell index sorting and TCRαβ analyses link expansion of A68/NP145+CD8+ T cells to their memory potential. Our study demonstrates the immunodominance potential of influenza-specific CD8+ T cells presented by a risk HLA-A*68:01 molecule and advocates for priming CD8+ T cell compartments in HLA-A*68:01-expressing individuals for establishment of pre-existing protective memory T cell pools.
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Affiliation(s)
- C E van de Sandt
- Department of Microbiology and Immunology, University of Melbourne at The Peter Doherty Institute, Melbourne, VIC, 3000, Australia.,Department of Hematopoiesis, Sanquin Research and Landsteiner Laboratory, Amsterdam UMC, University of Amsterdam, 1066CX, Amsterdam, Netherlands
| | - E B Clemens
- Department of Microbiology and Immunology, University of Melbourne at The Peter Doherty Institute, Melbourne, VIC, 3000, Australia
| | - E J Grant
- Department of Microbiology and Immunology, University of Melbourne at The Peter Doherty Institute, Melbourne, VIC, 3000, Australia.,Department of Biochemistry and Molecular Biology, Biomedicine Discovery Institute, Infection and Immunity Program, Monash University, Clayton, VIC, 3800, Australia
| | - L C Rowntree
- Department of Microbiology and Immunology, University of Melbourne at The Peter Doherty Institute, Melbourne, VIC, 3000, Australia
| | - S Sant
- Department of Microbiology and Immunology, University of Melbourne at The Peter Doherty Institute, Melbourne, VIC, 3000, Australia
| | - H Halim
- Infection and Immunity Program and The Department of Biochemistry and Molecular Biology, Biomedicine Discovery Institute, Monash University, Clayton, VIC, 3800, Australia
| | - J Crowe
- Deepdene Surgery, Deepdene, VIC, 3103, Australia
| | - A C Cheng
- School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, 3004, Australia.,Infection Prevention and Healthcare Epidemiology Unit, Alfred Health, Melbourne, VIC, 3004, Australia
| | - T C Kotsimbos
- Department of Allergy, Immunology and Respiratory Medicine, The Alfred Hospital, Melbourne, VIC, 3004, Australia.,Department of Medicine, Monash University, Central Clinical School, The Alfred Hospital, Melbourne, VIC, 3004, Australia
| | - M Richards
- Victorian Infectious Diseases Service, The Royal Melbourne Hospital, at the Peter Doherty Institute for Infection and Immunity, Parkville, VIC, 3050, Australia
| | - A Miller
- Indigenous Research Network, Griffith University, Brisbane, QLD, 4222, Australia.,Office of Indigenous Engagement, CQUniversity, Townsvillle, QLD, Australia
| | - S Y C Tong
- Victorian Infectious Diseases Service, The Royal Melbourne Hospital, at the Peter Doherty Institute for Infection and Immunity, Parkville, VIC, 3050, Australia.,Menzies School of Health Research, Charles Darwin University, Darwin, NT, 0811, Australia
| | - J Rossjohn
- Infection and Immunity Program and The Department of Biochemistry and Molecular Biology, Biomedicine Discovery Institute, Monash University, Clayton, VIC, 3800, Australia.,Australian Research Council Centre of Excellence for Advanced Molecular Imaging, Monash University, Clayton, VIC, Australia.,Institute of Infection and Immunity, Cardiff University School of Medicine, Heath Park, Cardiff, CF14 4XN, United Kingdom
| | - T H O Nguyen
- Department of Microbiology and Immunology, University of Melbourne at The Peter Doherty Institute, Melbourne, VIC, 3000, Australia
| | - S Gras
- Infection and Immunity Program and The Department of Biochemistry and Molecular Biology, Biomedicine Discovery Institute, Monash University, Clayton, VIC, 3800, Australia.,Australian Research Council Centre of Excellence for Advanced Molecular Imaging, Monash University, Clayton, VIC, Australia
| | - W Chen
- Department of Biochemistry and Genetics, La Trobe Institute of Molecular Science, La Trobe University, Bundoora, VIC, 3086, Australia
| | - K Kedzierska
- Department of Microbiology and Immunology, University of Melbourne at The Peter Doherty Institute, Melbourne, VIC, 3000, Australia.
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46
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Brugger J, Althaus CL. Transmission of and susceptibility to seasonal influenza in Switzerland from 2003 to 2015. Epidemics 2019; 30:100373. [PMID: 31635972 DOI: 10.1016/j.epidem.2019.100373] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2018] [Revised: 09/30/2019] [Accepted: 10/01/2019] [Indexed: 12/16/2022] Open
Abstract
Understanding the seasonal patterns of influenza transmission is critical to help plan public health measures for the management and control of epidemics. Mathematical models of infectious disease transmission have been widely used to quantify the transmissibility of and susceptibility to past influenza seasons in many countries. The objective of this study was to obtain a detailed picture of the transmission dynamics of seasonal influenza in Switzerland from 2003 to 2015. To this end, we developed a compartmental influenza transmission model taking into account social mixing between different age groups and seasonal forcing. We applied a Bayesian approach using Markov chain Monte Carlo (MCMC) methods to fit the model to the reported incidence of influenza-like-illness (ILI) and virological data from Sentinella, the Swiss Sentinel Surveillance Network. The maximal basic reproduction number, R0, ranged from 1.46 to 1.81 (median). Median estimates of susceptibility to influenza ranged from 29% to 98% for different age groups, and typically decreased with age. We also found a decline in ascertainability of influenza cases with age. Our study illustrates how influenza surveillance data from Switzerland can be integrated into a Bayesian modeling framework in order to assess age-specific transmission of and susceptibility to influenza.
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Affiliation(s)
- Jon Brugger
- Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland.
| | - Christian L Althaus
- Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland.
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47
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Islam S, Zhou F, Lartey S, Mohn KGI, Krammer F, Cox RJ, Brokstad KA. Functional immune response to influenza H1N1 in children and adults after live attenuated influenza virus vaccination. Scand J Immunol 2019; 90:e12801. [PMID: 31269273 DOI: 10.1111/sji.12801] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2019] [Revised: 06/20/2019] [Accepted: 06/28/2019] [Indexed: 02/02/2023]
Abstract
Influenza virus is a major respiratory pathogen, and vaccination is the main method of prophylaxis. In 2012, the trivalent live attenuated influenza vaccine (LAIV) was licensed in Europe for use in children. Vaccine-induced antibodies directed against the main viral surface glycoproteins, haemagglutinin (HA) and neuraminidase (NA) play important roles in limiting virus infection. The objective of this study was to dissect the influenza-specific antibody responses in children and adults, and T cell responses in children induced after LAIV immunization to the A/H1N1 virus. Blood samples were collected pre- and at 28 and 56 days post-vaccination from 20 children and 20 adults. No increase in micro-neutralization (MN) antibodies against A/H1N1 was observed after vaccination. A/H1N1 stalk-specific neutralizing and NA-inhibiting (NI) antibodies were boosted in children after LAIV. Interferon γ-producing T cells increased significantly in children, and antibody-dependent cellular-mediated cytotoxic (ADCC) cell activity increased slightly in children after vaccination, although this change was not significant. The results indicate that the NI assay is more sensitive to qualitative changes in serum antibodies after LAIV. There was a considerable difference in the immune response in children and adults after vaccination, which may be related to priming and previous influenza history. Our findings warrant further studies for evaluating LAIV vaccination immunogenicity.
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Affiliation(s)
- Shahinul Islam
- Department of Clinical Science, Influenza Centre, University of Bergen, Bergen, Norway.,Department of Clinical Science, K.G. Jebsen Centre for Influenza Vaccine Research, University of Bergen, Bergen, Norway
| | - Fan Zhou
- Department of Clinical Science, Influenza Centre, University of Bergen, Bergen, Norway.,Department of Clinical Science, K.G. Jebsen Centre for Influenza Vaccine Research, University of Bergen, Bergen, Norway
| | - Sarah Lartey
- Department of Clinical Science, Influenza Centre, University of Bergen, Bergen, Norway.,Department of Clinical Science, K.G. Jebsen Centre for Influenza Vaccine Research, University of Bergen, Bergen, Norway
| | - Kristin G I Mohn
- Department of Clinical Science, Influenza Centre, University of Bergen, Bergen, Norway.,Emergency Care Clinic, Haukeland University Hospital, Bergen, Norway
| | - Florian Krammer
- Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Rebecca Jane Cox
- Department of Clinical Science, Influenza Centre, University of Bergen, Bergen, Norway.,Department of Clinical Science, K.G. Jebsen Centre for Influenza Vaccine Research, University of Bergen, Bergen, Norway.,Department of Research & Development, Haukeland University Hospital, Bergen, Norway
| | - Karl Albert Brokstad
- Department of Clinical Science, Broegelmann Research Laboratory, University of Bergen, Bergen, Norway
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48
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Lee JM, Eguia R, Zost SJ, Choudhary S, Wilson PC, Bedford T, Stevens-Ayers T, Boeckh M, Hurt AC, Lakdawala SS, Hensley SE, Bloom JD. Mapping person-to-person variation in viral mutations that escape polyclonal serum targeting influenza hemagglutinin. eLife 2019; 8:e49324. [PMID: 31452511 PMCID: PMC6711711 DOI: 10.7554/elife.49324] [Citation(s) in RCA: 60] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2019] [Accepted: 07/27/2019] [Indexed: 12/11/2022] Open
Abstract
A longstanding question is how influenza virus evolves to escape human immunity, which is polyclonal and can target many distinct epitopes. Here, we map how all amino-acid mutations to influenza's major surface protein affect viral neutralization by polyclonal human sera. The serum of some individuals is so focused that it selects single mutations that reduce viral neutralization by over an order of magnitude. However, different viral mutations escape the sera of different individuals. This individual-to-individual variation in viral escape mutations is not present among ferrets that have been infected just once with a defined viral strain. Our results show how different single mutations help influenza virus escape the immunity of different members of the human population, a phenomenon that could shape viral evolution and disease susceptibility.
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Affiliation(s)
- Juhye M Lee
- Basic Sciences DivisionFred Hutchinson Cancer Research CenterSeattleUnited States
- Department of Genome SciencesUniversity of WashingtonSeattleUnited States
| | - Rachel Eguia
- Basic Sciences DivisionFred Hutchinson Cancer Research CenterSeattleUnited States
| | - Seth J Zost
- Department of MicrobiologyPerelman School of Medicine, University of PennsylvaniaPhiladelphiaUnited States
| | - Saket Choudhary
- Department of Biological SciencesUniversity of Southern CaliforniaLos AngelesUnited States
| | - Patrick C Wilson
- Department of MedicineSection of Rheumatology, University of ChicagoChicagoUnited States
| | - Trevor Bedford
- Vaccine and Infectious Disease DivisionFred Hutchinson Cancer Research CenterSeattleUnited States
| | - Terry Stevens-Ayers
- Vaccine and Infectious Disease DivisionFred Hutchinson Cancer Research CenterSeattleUnited States
| | - Michael Boeckh
- Vaccine and Infectious Disease DivisionFred Hutchinson Cancer Research CenterSeattleUnited States
| | - Aeron C Hurt
- WHO Collaborating Centre for Reference and Research on Influenza, Peter Doherty Institute for Infection and ImmunityMelbourneAustralia
| | - Seema S Lakdawala
- Department of Microbiology and Molecular GeneticsSchool of Medicine, University of PittsburghPittsburghUnited States
| | - Scott E Hensley
- Department of MicrobiologyPerelman School of Medicine, University of PennsylvaniaPhiladelphiaUnited States
| | - Jesse D Bloom
- Basic Sciences DivisionFred Hutchinson Cancer Research CenterSeattleUnited States
- Department of Genome SciencesUniversity of WashingtonSeattleUnited States
- Howard Hughes Medical InstituteSeattleUnited States
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49
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Hirotsu N, Saisho Y, Hasegawa T, Kitano M, Shishido T. Antibody dynamics in Japanese paediatric patients with influenza A infection treated with neuraminidase inhibitors in a randomised trial. Sci Rep 2019; 9:11891. [PMID: 31417163 PMCID: PMC6695405 DOI: 10.1038/s41598-019-47884-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2018] [Accepted: 07/16/2019] [Indexed: 12/24/2022] Open
Abstract
Neuraminidase inhibitors (NAIs) complement influenza virus infection management by helping to clear virus, alleviate symptoms, and reduce transmission. In a previous randomised study, we examined the effect of 4 NAIs on virus clearance and influenza symptoms in Japanese paediatric patients. In this second analysis, we examined the effects of NAI treatment on antibody responses and virus clearance, and the relationships between antibody responses and patients' infection histories (previous infection; asymptomatic infection via household members of same virus type/subtype; vaccination), and between infection histories and viral kinetics. Haemagglutination inhibition (HI) antibody responses produced HI titres ≥40 by Day 14 of NAI treatment, in parallel with virus clearance (trend test P = 0.001). Comparing patients with and without influenza infection histories (directly or asymptomatic infection via household members) showed that infection history had a marked positive effect on HI antibody responses in patients vaccinated before the current influenza season (before enrolment). Current virus clearance was significantly faster in patients previously infected with the same virus type/subtype than in those not previously infected, and clearance pattern depended on the NAI. Assessment of anti-influenza effects of antiviral drugs and vaccines should consider virus and antibody dynamics in response to vaccination and natural infection histories.
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Hay JA, Laurie K, White M, Riley S. Characterising antibody kinetics from multiple influenza infection and vaccination events in ferrets. PLoS Comput Biol 2019; 15:e1007294. [PMID: 31425503 PMCID: PMC6715255 DOI: 10.1371/journal.pcbi.1007294] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2019] [Revised: 08/29/2019] [Accepted: 07/29/2019] [Indexed: 12/20/2022] Open
Abstract
The strength and breadth of an individual's antibody repertoire is an important predictor of their response to influenza infection or vaccination. Although progress has been made in understanding qualitatively how repeated exposures shape the antibody mediated immune response, quantitative understanding remains limited. We developed a set of mathematical models describing short-term antibody kinetics following influenza infection or vaccination and fit them to haemagglutination inhibition (HI) titres from 5 groups of ferrets which were exposed to different combinations of trivalent inactivated influenza vaccine (TIV with or without adjuvant), A/H3N2 priming inoculation and post-vaccination A/H1N1 inoculation. We fit models with various immunological mechanisms that have been empirically observed but have not previously been included in mathematical models of antibody landscapes, including: titre ceiling effects, antigenic seniority and exposure-type specific cross reactivity. Based on the parameter estimates of the best supported models, we describe a number of key immunological features. We found quantifiable differences in the degree of homologous and cross-reactive antibody boosting elicited by different exposure types. Infection and adjuvanted vaccination generally resulted in strong, broadly reactive responses whereas unadjuvanted vaccination resulted in a weak, narrow response. We found that the order of exposure mattered: priming with A/H3N2 improved subsequent vaccine response, and the second dose of adjuvanted vaccination resulted in substantially greater antibody boosting than the first. Either antigenic seniority or a titre ceiling effect were included in the two best fitting models, suggesting a role for a mechanism describing diminishing antibody boosting with repeated exposures. Although there was considerable uncertainty in our estimates of antibody waning parameters, our results suggest that both short and long term waning were present and would be identifiable with a larger set of experiments. These results highlight the potential use of repeat exposure animal models in revealing short-term, strain-specific immune dynamics of influenza.
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MESH Headings
- Adjuvants, Immunologic/administration & dosage
- Animals
- Antibodies, Viral/blood
- Computational Biology
- Cross Reactions
- Disease Models, Animal
- Ferrets/immunology
- Humans
- Immunization, Secondary
- Influenza A Virus, H1N1 Subtype/immunology
- Influenza A Virus, H3N2 Subtype/immunology
- Influenza Vaccines/administration & dosage
- Influenza, Human/immunology
- Influenza, Human/prevention & control
- Kinetics
- Models, Immunological
- Orthomyxoviridae Infections/immunology
- Orthomyxoviridae Infections/virology
- Vaccines, Inactivated/administration & dosage
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Affiliation(s)
- James A. Hay
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, United Kingdom
| | - Karen Laurie
- WHO Collaborating Centre for Reference and Research on Influenza, Peter Doherty Institute for Infection and Immunity, Melbourne, Australia
- Seqirus, 63 Poplar Road, Parkville, Victoria, Australia
| | - Michael White
- Malaria: Parasites and Hosts, Department of Parasites and Insect Vectors, Institut Pasteur, Paris, France
| | - Steven Riley
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, United Kingdom
- * E-mail:
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