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Yang T, Tong F, Tang L, Li P, Li B, Ye L, Zhou J. Repeated vaccination does not appear to significantly weaken the protective effect of influenza vaccine in the elderly: A test-negative case-control study in China. Vaccine 2024:S0264-410X(24)00593-0. [PMID: 38762359 DOI: 10.1016/j.vaccine.2024.05.034] [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: 02/20/2024] [Revised: 05/02/2024] [Accepted: 05/15/2024] [Indexed: 05/20/2024]
Abstract
BACKGROUND The impact of repeated influenza vaccination on vaccine effectiveness has been a topic of debate. Conducting more multinational, multicenter studies in different influenza seasons is crucial for a better understanding of this issue. There is a lack of comprehensive related research reports in China. METHODS Using the Regional Health Information Platform, we conducted a test-negative case-control study to evaluate the impact of repeated vaccination on the prevention of laboratory-confirmed influenza in individuals aged 60 and above in Ningbo during four influenza seasons from 2018-19 to 2021-22. Influenza-positive cases and negative controls were matched in a 1:1 ratio based on the visiting hospital and the date of influenza testing. Propensity score adjustment and multivariable logistic regression were used to estimate risk and address confounding effects. RESULTS During the study period, a total of 30,630 elderly patients underwent influenza virus nucleic acid or antigen testing. After exclusions, we included 1976 cases of influenza-positive and 1976 cases of influenza-negative controls. Multivariable logistic regression analysis revealed that individuals receiving the vaccine in two consecutive seasons did not exhibit a significantly increased risk of influenza illness compared to those receiving the vaccine only in the current season (adjusted odds ratio: 1.22, 95% confidence interval: 0.94-1.58). However, the risk of influenza illness was found to be elevated in individuals who received the vaccine only in the previous season (adjusted odds ratio: 1.56, 95% confidence interval: 1.15-2.10) and even further elevated in those who had not received the vaccine in either of the consecutive two seasons (adjusted odds ratio: 3.39, 95% confidence interval: 2.80-4.09). CONCLUSIONS Regardless of the vaccination history in the previous season, receiving the current season influenza vaccine is the best choice for the elderly population. Our study supports the initiative to vaccinate elderly individuals against influenza annually.
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Affiliation(s)
- Tianchi Yang
- Institute of Immunization and Prevention, Ningbo Municipal Center for Disease Control and Prevention, Zhejiang, China
| | - Feng Tong
- Ningbo Municipal Center for Disease Control and Prevention, Zhejiang, China
| | - Ling Tang
- Ningbo Health Information Center, Zhejiang, China
| | - Pingping Li
- Jiangbei District Center for Disease Control and Prevention, Zhejiang, China
| | - Baojun Li
- Haishu District Center for Disease Control and Prevention, Zhejiang, China
| | - Lixia Ye
- Institute of Immunization and Prevention, Ningbo Municipal Center for Disease Control and Prevention, Zhejiang, China.
| | - Jifang Zhou
- School of International Pharmaceutical Business, China Pharmaceutical University, Jiangsu, China.
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Cowling BJ, Wong SS, Santos JJS, Touyon L, Ort J, Ye N, Kwok NKM, Ho F, Cheng SMS, Ip DKM, Peiris M, Webby RJ, Wilson PC, Valkenburg SA, Tsang JS, Leung NHL, Hensley SE, Cobey S. Preliminary findings from the Dynamics of the Immune Responses to Repeat Influenza Vaccination Exposures (DRIVE I) Study: a Randomized Controlled Trial. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.05.16.24307455. [PMID: 38798684 PMCID: PMC11118649 DOI: 10.1101/2024.05.16.24307455] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/29/2024]
Abstract
Background Studies have reported that repeated annual vaccination may influence the effectiveness of the influenza vaccination in the current season. The mechanisms underlying these differences are unclear but might include "focusing" of the adaptive immune response to older strains. Methods We established a 5-year randomized placebo-controlled trial of repeated influenza vaccination (Flublok, Sanofi Pasteur) in adults 18-45 years of age. Participants were randomized equally between five groups, with planned annual receipt of vaccination (V) or saline placebo (P) as follows: P-P-P-P-V, P-P-P-V-V, P-P-V-V-V, P-V-V-V-V, or V-V-V-V-V. Serum samples were collected each year just before vaccination and after 30 and 182 days. A subset of sera were tested by hemagglutination inhibition assays, focus reduction neutralization tests and enzyme-linked immunosorbent assays against vaccine strains. Results From 23 October 2020 through 11 March 2021 we enrolled and randomized 447 adults. We selected sera from 95 participants at five timepoints from the first two study years for testing. Among vaccinated individuals, antibody titers increased between days 0 and 30 against each of the vaccine strains, with substantial increases for first-time vaccinees and smaller increases for repeat vaccinees, who had higher pre-vaccination titers in year 2. There were statistically significant reductions in the proportion of participants achieving a four-fold greater rise in antibody titer for the repeat vaccinees for A(H1N1), B/Victoria and B/Yamagata, but not for influenza A(H3N2). There were no statistically significant differences between groups in geometric mean titers at day 30 or the proportions of participants with antibody titers ≥40 at day 30 for any of the vaccine strains. Conclusions In the first two years, repeat vaccinees and first-time vaccinees had similar post-vaccination geometric mean titers to all four vaccine strains, indicative of similar levels of clinical protection. The vaccine strains of A(H1N1) and A(H3N2) were updated in year 2, providing an opportunity to explore antigenic distances between those strains in humans in subsequent years.
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Zhong S, Ng TWY, Skowronski DM, Iuliano AD, Leung NHL, Perera RAPM, Ho F, Fang VJ, Tam YH, Ip DKM, Havers FG, Fry AM, Aziz-Baumgartner E, Barr IG, Peiris M, Thompson MG, Cowling BJ. Influenza A(H3N2) Antibody Responses to Standard-Dose Versus Enhanced Influenza Vaccine Immunogenicity in Older Adults and Prior Season's Vaccine Status. J Infect Dis 2024; 229:1451-1459. [PMID: 37950884 PMCID: PMC11095559 DOI: 10.1093/infdis/jiad497] [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: 07/01/2023] [Revised: 10/19/2023] [Accepted: 11/09/2023] [Indexed: 11/13/2023] Open
Abstract
BACKGROUND Annual influenza vaccination is recommended for older adults but repeated vaccination with standard-dose influenza vaccine has been linked to reduced immunogenicity and effectiveness, especially against A(H3N2) viruses. METHODS Community-dwelling Hong Kong adults aged 65-82 years were randomly allocated to receive 2017-2018 standard-dose quadrivalent, MF59-adjuvanted trivalent, high-dose trivalent, and recombinant-HA quadrivalent vaccination. Antibody response to unchanged A(H3N2) vaccine antigen was compared among participants with and without self-reported prior year (2016-2017) standard-dose vaccination. RESULTS Mean fold rise (MFR) in antibody titers from day 0 to day 30 by hemagglutination inhibition and virus microneutralization assays were lower among 2017-2018 standard-dose and enhanced vaccine recipients with (range, 1.7-3.0) versus without (range, 4.3-14.3) prior 2016-2017 vaccination. MFR was significantly reduced by about one-half to four-fifths for previously vaccinated recipients of standard-dose and all 3 enhanced vaccines (β range, .21-.48). Among prior-year vaccinated older adults, enhanced vaccines induced higher 1.43 to 2.39-fold geometric mean titers and 1.28 to 1.74-fold MFR versus standard-dose vaccine by microneutralization assay. CONCLUSIONS In the context of unchanged A(H3N2) vaccine strain, prior-year vaccination was associated with reduced antibody response among both standard-dose and enhanced influenza vaccine recipients. Enhanced vaccines improved antibody response among older adults with prior-year standard-dose vaccination.
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Affiliation(s)
- Shuyi Zhong
- World Health Organization Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, The University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Tiffany W Y Ng
- World Health Organization Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, The University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Danuta M Skowronski
- Epidemiology Services, British Columbia Centre for Disease Control, Vancouver, Canada
- School of Population and Public Health, University of British Columbia, Vancouver, Canada
| | - A Danielle Iuliano
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Nancy H L Leung
- World Health Organization Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, The University of Hong Kong, Hong Kong Special Administrative Region, China
- Laboratory of Data Discovery for Health Limited, Hong Kong Science and Technology Park, Hong Kong Special Administrative Region, China
| | - Ranawaka A P M Perera
- World Health Organization Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, The University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Faith Ho
- World Health Organization Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, The University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Vicky J Fang
- World Health Organization Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, The University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Yat Hung Tam
- World Health Organization Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, The University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Dennis K M Ip
- World Health Organization Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, The University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Fiona G Havers
- Division of Viral Diseases, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Alicia M Fry
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | | | - Ian G Barr
- World Health Organization Collaborating Centre for Reference and Research on Influenza, Peter Doherty Institute for Infection and Immunity, Melbourne, Victoria, Australia
- Department of Microbiology and Immunology, University of Melbourne, Melbourne, Victoria, Australia
| | - Malik Peiris
- World Health Organization Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, The University of Hong Kong, Hong Kong Special Administrative Region, China
- Centre of Immunology and Infection, Hong Kong Science and Technology Park, Hong Kong Special Administrative Region, China
| | - Mark G Thompson
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Benjamin J Cowling
- World Health Organization Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, The University of Hong Kong, Hong Kong Special Administrative Region, China
- Laboratory of Data Discovery for Health Limited, Hong Kong Science and Technology Park, Hong Kong Special Administrative Region, China
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Cameron CM, Raghu V, Richardson B, Zagore LL, Tamilselvan B, Golden J, Cartwright M, Schoen RE, Finn OJ, Benos PV, Cameron MJ. Pre-vaccination transcriptomic profiles of immune responders to the MUC1 peptide vaccine for colon cancer prevention. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.05.09.24305336. [PMID: 38766010 PMCID: PMC11100921 DOI: 10.1101/2024.05.09.24305336] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2024]
Abstract
Self-antigens abnormally expressed on tumors, such as MUC1, have been targeted by therapeutic cancer vaccines. We recently assessed in two clinical trials in a preventative setting whether immunity induced with a MUC1 peptide vaccine could reduce high colon cancer risk in individuals with a history of premalignant colon adenomas. In both trials, there were immune responders and non-responders to the vaccine. Here we used PBMC pre-vaccination and 2 weeks after the first vaccine of responders and non-responders selected from both trials to identify early biomarkers of immune response involved in long-term memory generation and prevention of adenoma recurrence. We performed flow cytometry, phosflow, and differential gene expression analyses on PBMCs collected from MUC1 vaccine responders and non-responders pre-vaccination and two weeks after the first of three vaccine doses. MUC1 vaccine responders had higher frequencies of CD4 cells pre-vaccination, increased expression of CD40L on CD8 and CD4 T-cells, and a greater increase in ICOS expression on CD8 T-cells. Differential gene expression analysis revealed that iCOSL, PI3K AKT MTOR, and B-cell signaling pathways are activated early in response to the MUC1 vaccine. We identified six specific transcripts involved in elevated antigen presentation, B-cell activation, and NF-kB1 activation that were directly linked to finding antibody response at week 12. Finally, a model using these transcripts was able to predict non-responders with accuracy. These findings suggest that individuals who can be predicted to respond to the MUC1 vaccine, and potentially other vaccines, have greater readiness in all immune compartments to present and respond to antigens. Predictive biomarkers of MUC1 vaccine response may lead to more effective vaccines tailored to individuals with high risk for cancer but with varying immune fitness.
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Affiliation(s)
- Cheryl M Cameron
- Department of Nutrition, Case Western Reserve University, Cleveland, OH
| | - Vineet Raghu
- Department of Computer Science, University of Pittsburgh, Pittsburgh, PA
- Massachusetts General Hospital, Harvard Medical School, Cambridge, MA
| | - Brian Richardson
- Department of Nutrition, Case Western Reserve University, Cleveland, OH
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH
| | - Leah L Zagore
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH
| | | | - Jackelyn Golden
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH
| | - Michael Cartwright
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH
| | - Robert E Schoen
- Division of Gastroenterology, Hepatology and Nutrition, University of Pittsburgh, Pittsburgh, PA
| | - Olivera J Finn
- Department of Immunology, University of Pittsburgh, Pittsburgh, PA
| | - Panayiotis V Benos
- Department of Epidemiology, University of Florida, Gainesville, FL
- Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA
| | - Mark J Cameron
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH
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McGough L, Cobey S. A speed limit on serial strain replacement from original antigenic sin. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.04.574172. [PMID: 38260288 PMCID: PMC10802292 DOI: 10.1101/2024.01.04.574172] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
Many pathogens evolve to escape immunity, yet it remains difficult to predict whether immune pressure will lead to diversification, serial replacement of one variant by another, or more complex patterns. Pathogen strain dynamics are mediated by cross-protective immunity, whereby exposure to one strain partially protects against infection by antigenically diverged strains. There is growing evidence that this protection is influenced by early exposures, a phenomenon referred to as original antigenic sin (OAS) or imprinting. In this paper, we derive new constraints on the emergence of the pattern of successive strain replacements demonstrated by influenza, SARS-CoV-2, seasonal coronaviruses, and other pathogens. We find that OAS implies that the limited diversity found with successive strain replacement can only be maintained if R 0 is less than a threshold set by the characteristic antigenic distances for cross-protection and for the creation of new immune memory. This bound implies a "speed limit" on the evolution of new strains and a minimum variance of the distribution of infecting strains in antigenic space at any time. To carry out this analysis, we develop a theoretical model of pathogen evolution in antigenic space that implements OAS by decoupling the antigenic distances required for protection from infection and strain-specific memory creation. Our results demonstrate that OAS can play an integral role in the emergence of strain structure from host immune dynamics, preventing highly transmissible pathogens from maintaining serial strain replacement without diversification.
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Affiliation(s)
- Lauren McGough
- Department of Ecology and Evolution, University of Chicago, Chicago, IL
| | - Sarah Cobey
- Department of Ecology and Evolution, University of Chicago, Chicago, IL
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6
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Bi Q, Dickerman BA, Nguyen HQ, Martin ET, Gaglani M, Wernli KJ, Balasubramani G, Flannery B, Lipsitch M, Cobey S. Reduced effectiveness of repeat influenza vaccination: distinguishing among within-season waning, recent clinical infection, and subclinical infection. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2023.03.12.23287173. [PMID: 37016669 PMCID: PMC10071822 DOI: 10.1101/2023.03.12.23287173] [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: 06/19/2023]
Abstract
Studies have reported that prior-season influenza vaccination is associated with higher risk of clinical influenza infection among vaccinees. This effect might arise from incomplete consideration of within-season waning and recent infection. Using data from the US Flu Vaccine Effectiveness (VE) Network (2011-2012 to 2018-2019 seasons), we found that repeat vaccinees were vaccinated earlier in a season by one week. After accounting for waning VE, repeat vaccinees were still more likely to test positive for A(H3N2) (OR=1.11, 95%CI:1.02-1.21) but not for influenza B or A(H1N1). We found that clinical infection influenced individuals' decision to vaccinate in the following season while protecting against clinical infection of the same (sub)type. However, adjusting for recent clinical infections did not strongly influence the estimated effect of prior-season vaccination. In contrast, we found that adjusting for subclinical infection could theoretically attenuate this effect. Additional investigation is needed to determine the impact of subclinical infections on VE.
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Affiliation(s)
- Qifang Bi
- University of Chicago, Chicago, Illinois, USA
| | | | - Huong Q. Nguyen
- Center for Clinical Epidemiology & Population Health, Marshfield Clinic Research Institute, Marshfield, Wisconsin, USA
| | - Emily T. Martin
- University of Michigan School of Public Health, Ann Arbor, Michigan, USA
| | - Manjusha Gaglani
- Baylor Scott & White Health, Temple, Texas, USA
- Texas A&M University College of Medicine, Temple, Texas, USA
| | - Karen J. Wernli
- Kaiser Permanente Bernard J. Tyson School of Medicine, Seattle, Washington, USA
| | - G.K. Balasubramani
- University of Pittsburgh School of Public Health, Pittsburgh, Pennsylvania, USA
| | - Brendan Flannery
- National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, GA, US
| | - Marc Lipsitch
- Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
| | - Sarah Cobey
- University of Chicago, Chicago, Illinois, USA
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7
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Jacobson MA, Blanc PD, Tulsky J, Tilly M, Meister R, Huen W, McNicholas JE. Risk of subsequent SARS-CoV-2 infection among vaccinated employees with or without hybrid immunity acquired early in the Omicron-predominant era of the COVID-19 pandemic. Am J Ind Med 2024; 67:334-340. [PMID: 38316635 DOI: 10.1002/ajim.23570] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Revised: 01/24/2024] [Accepted: 01/24/2024] [Indexed: 02/07/2024]
Abstract
BACKGROUND Hybrid immunity, from COVID-19 vaccination followed by SARS-CoV-2 infection acquired after its Omicron variant began predominating, has provided greater protection than vaccination alone against subsequent infection over 1-3 months of observation. Its longer-term protection is unknown. METHODS We conducted a retrospective cohort study of COVID-19 case incidence among healthcare personnel (HCP) mandated to be vaccinated and report on COVID-19-associated symptoms, high-risk exposures, or known-positive test results to an employee health hotline. We compared cases with hybrid immunity, defined as incident COVID-19 during the first 6 weeks of Omicron-variant predominance (run-in period), to those with immunity from vaccination alone during the run-in period. Time until COVID-19 infection over 13 subsequent months (observation period) was analyzed by standard survival analysis. RESULTS Of 5867 employees, 641 (10.9%, 95% confidence interval [CI]: 10.1%-11.8%) acquired hybrid immunity during the run-in period. Of these, 104 (16.2%, 95% CI: 13.5%-19.3%) experienced new SARS-CoV-2 infection during the 13-month observation period, compared to 2177 (41.7%, 95% CI: 40.3%-43.0%) of the 5226 HCP without hybrid immunity. Time until incident infection was shorter among the latter (hazard ratio: 3.09, 95% CI: 2.54-3.78). CONCLUSIONS In a cohort of vaccinated employees, Omicron-era acquired SARS-CoV-2 hybrid immunity was associated with significantly lower risk of subsequent infection over more than a year of observation-a time period far longer than previously reported and during which three, progressively more resistant, Omicron subvariants became predominant. These findings can inform institutional policy and planning for future COVID-19 additional vaccine dosing requirements for employees, for surveillance programs, and for risk modification efforts.
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Affiliation(s)
- Mark A Jacobson
- Department of Medicine, Division of Occupational, Environmental, and Climate Medicine, University of California San Francisco School of Medicine, San Francisco, California, USA
- Department of Medicine, Division of HIV, Infectious Diseases, and Global Medicine, University of California San Francisco School of Medicine, San Francisco, California, USA
- Department of Medicine, University of California San Francisco School of Medicine, San Francisco, California, USA
| | - Paul D Blanc
- Department of Medicine, Division of Occupational, Environmental, and Climate Medicine, University of California San Francisco School of Medicine, San Francisco, California, USA
- Department of Medicine, University of California San Francisco School of Medicine, San Francisco, California, USA
| | - Jacqueline Tulsky
- Department of Medicine, Division of Occupational, Environmental, and Climate Medicine, University of California San Francisco School of Medicine, San Francisco, California, USA
- Department of Medicine, Division of HIV, Infectious Diseases, and Global Medicine, University of California San Francisco School of Medicine, San Francisco, California, USA
- Department of Medicine, University of California San Francisco School of Medicine, San Francisco, California, USA
| | - Monica Tilly
- Department of Medicine, Division of Occupational, Environmental, and Climate Medicine, University of California San Francisco School of Medicine, San Francisco, California, USA
- Department of Medicine, University of California San Francisco School of Medicine, San Francisco, California, USA
| | - Raymond Meister
- Department of Medicine, Division of Occupational, Environmental, and Climate Medicine, University of California San Francisco School of Medicine, San Francisco, California, USA
- Department of Medicine, University of California San Francisco School of Medicine, San Francisco, California, USA
| | - Will Huen
- Department of Medicine, University of California San Francisco School of Medicine, San Francisco, California, USA
| | - James E McNicholas
- Department of Medicine, Division of Occupational, Environmental, and Climate Medicine, University of California San Francisco School of Medicine, San Francisco, California, USA
- Department of Medicine, University of California San Francisco School of Medicine, San Francisco, California, USA
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8
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Loes AN, Tarabi RAL, Huddleston J, Touyon L, Wong SS, Cheng SMS, Leung NHL, Hannon WW, Bedford T, Cobey S, Cowling BJ, Bloom JD. High-throughput sequencing-based neutralization assay reveals how repeated vaccinations impact titers to recent human H1N1 influenza strains. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.08.584176. [PMID: 38496577 PMCID: PMC10942427 DOI: 10.1101/2024.03.08.584176] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/19/2024]
Abstract
The high genetic diversity of influenza viruses means that traditional serological assays have too low throughput to measure serum antibody neutralization titers against all relevant strains. To overcome this challenge, we have developed a sequencing-based neutralization assay that simultaneously measures titers against many viral strains using small serum volumes via a workflow similar to traditional neutralization assays. The key innovation is to incorporate unique nucleotide barcodes into the hemagglutinin (HA) genomic segment, and then pool viruses with numerous different barcoded HA variants and quantify infectivity of all of them simultaneously using next-generation sequencing. With this approach, a single researcher performed the equivalent of 2,880 traditional neutralization assays (80 serum samples against 36 viral strains) in approximately one month. We applied the sequencing-based assay to quantify the impact of influenza vaccination on neutralization titers against recent human H1N1 strains for individuals who had or had not also received a vaccine in the previous year. We found that the viral strain specificities of the neutralizing antibodies elicited by vaccination vary among individuals, and that vaccination induced a smaller increase in titers for individuals who had also received a vaccine the previous year-although the titers six months after vaccination were similar in individuals with and without the previous-year vaccination. We also identified a subset of individuals with low titers to a subclade of recent H1N1 even after vaccination. This study demonstrates the utility of high-throughput sequencing-based neutralization assays that enable titers to be simultaneously measured against many different viral strains. We provide a detailed experimental protocol (DOI: https://dx.doi.org/10.17504/protocols.io.kqdg3xdmpg25/v1) and a computational pipeline (https://github.com/jbloomlab/seqneut-pipeline) for the sequencing-based neutralization assays to facilitate the use of this method by others.
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Affiliation(s)
- Andrea N Loes
- Howard Hughes Medical Institute, Seattle, WA
- Division of Basic Sciences, Computational Biology Program, and Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, WA
| | - Rosario Araceli L Tarabi
- Division of Basic Sciences, Computational Biology Program, and Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, WA
| | - John Huddleston
- Division of Basic Sciences, Computational Biology Program, and Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, WA
| | - Lisa Touyon
- HKU-Pasteur Research Pole, School of Public Health, The University of Hong Kong, Hong Kong, SAR, China
- World Health Organization Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, The University of Hong Kong, Hong Kong, SAR, China
| | - Sook San Wong
- HKU-Pasteur Research Pole, School of Public Health, The University of Hong Kong, Hong Kong, SAR, China
- World Health Organization Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, The University of Hong Kong, Hong Kong, SAR, China
| | - Samuel M S Cheng
- World Health Organization Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, The University of Hong Kong, Hong Kong, SAR, China
| | - Nancy H L Leung
- World Health Organization Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, The University of Hong Kong, Hong Kong, SAR, China
| | - William W Hannon
- Division of Basic Sciences, Computational Biology Program, and Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, WA
- Molecular and Cellular Biology Graduate Program, University of Washington, Seattle, WA 98109, USA
| | - Trevor Bedford
- Howard Hughes Medical Institute, Seattle, WA
- Division of Basic Sciences, Computational Biology Program, and Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, WA
| | - Sarah Cobey
- Department of Ecology and Evolution, University of Chicago, Chicago, IL
| | - Benjamin J Cowling
- World Health Organization Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, The University of Hong Kong, Hong Kong, SAR, China
| | - Jesse D Bloom
- Howard Hughes Medical Institute, Seattle, WA
- Division of Basic Sciences, Computational Biology Program, and Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, WA
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9
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Hodgson D, Sánchez-Ovando S, Carolan L, Liu Y, Hadiprodjo AJ, Fox A, Sullivan SG, Kucharski AJ. Quantifying the impact of pre-vaccination titre and vaccination history on influenza vaccine immunogenicity. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.01.24.24301614. [PMID: 38343865 PMCID: PMC10854332 DOI: 10.1101/2024.01.24.24301614] [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: 02/18/2024]
Abstract
Epidemiological studies suggest that heterogeneity in influenza vaccine antibody response is associated with host factors, including pre-vaccination immune status, age, gender, and vaccination history. However, the pattern of reported associations varies between studies. To better understand the underlying influences on antibody responses, we combined host factors and vaccine-induced in-host antibody kinetics from a cohort study conducted across multiple seasons with a unified analysis framework. We developed a flexible individual-level Bayesian model to estimate associations and interactions between host factors, including pre-vaccine HAI titre, age, sex, vaccination history and study setting, and vaccine-induced HAI titre antibody boosting and waning. We applied the model to derive population-level and individual effects of post-vaccine antibody kinetics for vaccinating and circulating strains for A(H1N1) and A(H3N2) influenza subtypes. We found that post-vaccine HAI titre dynamics were significantly influenced by pre-vaccination HAI titre and vaccination history and that lower pre-vaccination HAI titre results in longer durations of seroprotection (HAI titre equal to 1:40 or higher). Consequently, for A(H1N1), our inference finds that the expected duration of seroprotection post-vaccination was 171 (95% Posterior Predictive Interval[PPI] 128-220) and 159 (95% PPI 120-200) days longer for those who are infrequently vaccinated (<2 vaccines in last five years) compared to those who are frequently vaccinated (2 or more vaccines in the last five years) at pre-vaccination HAI titre values of 1:10 and 1:20 respectively. In addition, we found significant differences in the empirical distributions that describe the individual-level duration of seroprotection for A(H1N1) circulating strains. In future, studies that rely on serological endpoints should include the impact of pre-vaccine HAI titre and prior vaccination status on seropositivity and seroconversion estimates, as these significantly influence an individual's post-vaccination antibody kinetics.
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Affiliation(s)
- David Hodgson
- Center of Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, UK
| | - Stephany Sánchez-Ovando
- Department of Infectious Diseases, University of Melbourne, at the Peter Doherty Institute for Infection and Immunity, Melbourne, Australia
- WHO Collaborating Centre for Reference and Research on Influenza, Royal Melbourne Hospital, at the Peter Doherty Institute for Infection and Immunity, Melbourne, Australia
| | - Louise Carolan
- WHO Collaborating Centre for Reference and Research on Influenza, Royal Melbourne Hospital, at the Peter Doherty Institute for Infection and Immunity, Melbourne, Australia
| | - Yi Liu
- Department of Infectious Diseases, University of Melbourne, at the Peter Doherty Institute for Infection and Immunity, Melbourne, Australia
- WHO Collaborating Centre for Reference and Research on Influenza, Royal Melbourne Hospital, at the Peter Doherty Institute for Infection and Immunity, Melbourne, Australia
| | - A. Jessica Hadiprodjo
- Department of Infectious Diseases, University of Melbourne, at the Peter Doherty Institute for Infection and Immunity, Melbourne, Australia
- WHO Collaborating Centre for Reference and Research on Influenza, Royal Melbourne Hospital, at the Peter Doherty Institute for Infection and Immunity, Melbourne, Australia
| | - Annette Fox
- Department of Infectious Diseases, University of Melbourne, at the Peter Doherty Institute for Infection and Immunity, Melbourne, Australia
- WHO Collaborating Centre for Reference and Research on Influenza, Royal Melbourne Hospital, at the Peter Doherty Institute for Infection and Immunity, Melbourne, Australia
| | - Sheena G. Sullivan
- Department of Infectious Diseases, University of Melbourne, at the Peter Doherty Institute for Infection and Immunity, Melbourne, Australia
- WHO Collaborating Centre for Reference and Research on Influenza, Royal Melbourne Hospital, at the Peter Doherty Institute for Infection and Immunity, Melbourne, Australia
| | - Adam J. Kucharski
- Center of Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, UK
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10
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Li X, Li Y, Shang X, Kong H. A sequence-based machine learning model for predicting antigenic distance for H3N2 influenza virus. Front Microbiol 2024; 15:1345794. [PMID: 38314434 PMCID: PMC10834737 DOI: 10.3389/fmicb.2024.1345794] [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: 11/28/2023] [Accepted: 01/08/2024] [Indexed: 02/06/2024] Open
Abstract
Introduction Seasonal influenza A H3N2 viruses are constantly changing, reducing the effectiveness of existing vaccines. As a result, the World Health Organization (WHO) needs to frequently update the vaccine strains to match the antigenicity of emerged H3N2 variants. Traditional assessments of antigenicity rely on serological methods, which are both labor-intensive and time-consuming. Although numerous computational models aim to simplify antigenicity determination, they either lack a robust quantitative linkage between antigenicity and viral sequences or focus restrictively on selected features. Methods Here, we propose a novel computational method to predict antigenic distances using multiple features, including not only viral sequence attributes but also integrating four distinct categories of features that significantly affect viral antigenicity in sequences. Results This method exhibits low error in virus antigenicity prediction and achieves superior accuracy in discerning antigenic drift. Utilizing this method, we investigated the evolution process of the H3N2 influenza viruses and identified a total of 21 major antigenic clusters from 1968 to 2022. Discussion Interestingly, our predicted antigenic map aligns closely with the antigenic map generated with serological data. Thus, our method is a promising tool for detecting antigenic variants and guiding the selection of vaccine candidates.
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Affiliation(s)
- Xingyi Li
- School of Computer Science, Northwestern Polytechnical University, Xi'an, Shaanxi, China
- Big Data Storage and Management MIIT Lab, Xi'an, Shaanxi, China
| | - Yanyan Li
- School of Computer Science, Northwestern Polytechnical University, Xi'an, Shaanxi, China
- Big Data Storage and Management MIIT Lab, Xi'an, Shaanxi, China
| | - Xuequn Shang
- School of Computer Science, Northwestern Polytechnical University, Xi'an, Shaanxi, China
- Big Data Storage and Management MIIT Lab, Xi'an, Shaanxi, China
| | - Huihui Kong
- State Key Laboratory of Animal Disease Control and Prevention, Harbin Veterinary Research Institute, Chinese Academy of Agricultural Sciences (CAAS), Harbin, China
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11
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Sánchez-de Prada L, Martínez-García AM, González-Fernández B, Gutiérrez-Ballesteros J, Rojo-Rello S, Garcinuño-Pérez S, Álvaro-Meca A, Ortiz De Lejarazu R, Sanz-Muñoz I, Eiros JM. Impact on the time elapsed since SARS-CoV-2 infection, vaccination history, and number of doses, on protection against reinfection. Sci Rep 2024; 14:353. [PMID: 38172152 PMCID: PMC10764833 DOI: 10.1038/s41598-023-50335-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Accepted: 12/19/2023] [Indexed: 01/05/2024] Open
Abstract
SARS-CoV-2 reinfections have been frequent, even among those vaccinated. The aim of this study is to know if hybrid immunity (infection + vaccination) is affected by the moment of vaccination and number of doses received. We conducted a retrospective study in 746 patients with a history of COVID-19 reinfection and recovered the dates of infection and reinfection and vaccination status (date and number of doses). To assess differences in the time to reinfection(tRI) between unvaccinated, vaccinated before 6 months, and later; and comparing one, two or three doses (incomplete, complete and booster regime) we performed the log-rank test of the cumulative incidence calculated as 1 minus the Kaplan-Meier estimator. Also, an adjusted Cox-regression was performed to evaluate the risk of reinfection in all groups. The tRI was significantly higher in those vaccinated vs. non-vaccinated (p < 0.001). However, an early incomplete regime protects similar time than not receiving a vaccine. Vaccination before 6 months after infection showed a lower tRI compared to those vaccinated later with the same regime (adj-p < 0.001). Actually, early vaccination with complete and booster regimes provided lower length of protection compared to vaccinating later with incomplete and complete regime, respectively. Vaccination with complete and booster regimes significantly increases the tRI (adj-p < 0.001). Vaccination increases the time it takes for a person to become reinfected with SARS-CoV-2. Increasing the time from infection to vaccination increases the time in which a person could be reinfected and reduces the risk of reinfection, especially in complete and booster regimes. Those results emphasize the role of vaccines and boosters during the pandemic and can guide strategies on future vaccination policy.
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Affiliation(s)
- Laura Sánchez-de Prada
- Faculty of Medicine, University of Valladolid, Valladolid, Spain.
- National Influenza Center of Valladolid, Valladolid, Spain.
| | - Ana María Martínez-García
- Department of Microbiology and Immunology, Hospital Clínico Universitario de Valladolid, Valladolid, Spain
| | - Belén González-Fernández
- Department of Microbiology and Immunology, Hospital Clínico Universitario de Valladolid, Valladolid, Spain
| | | | - Silvia Rojo-Rello
- Faculty of Medicine, University of Valladolid, Valladolid, Spain
- National Influenza Center of Valladolid, Valladolid, Spain
- Department of Microbiology and Immunology, Hospital Clínico Universitario de Valladolid, Valladolid, Spain
| | - Sonsoles Garcinuño-Pérez
- Department of Microbiology and Immunology, Hospital Clínico Universitario de Valladolid, Valladolid, Spain
| | - Alejandro Álvaro-Meca
- Department of Preventive Medicine and Public Health, Rey Juan Carlos University, Madrid, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Infecciosas (CIBERINFEC), Instituto de Salud Carlos III, Madrid, Spain
| | | | | | - José M Eiros
- Faculty of Medicine, University of Valladolid, Valladolid, Spain
- National Influenza Center of Valladolid, Valladolid, Spain
- Department of Microbiology and Immunology, Hospital Clínico Universitario de Valladolid, Valladolid, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Infecciosas (CIBERINFEC), Instituto de Salud Carlos III, Madrid, Spain
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12
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Lin PH, Hsiao PJ, Pan CF, Liu MT, Wang JT, Ching C, Wu FY, Lin YH, Yang YC, Hsu LY, Yang HC, Wu UI. Association of vaccine-specific regulatory T cells with reduced antibody response to repeated influenza vaccination. Eur J Immunol 2023; 53:e2350525. [PMID: 37713727 DOI: 10.1002/eji.202350525] [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: 04/10/2023] [Revised: 08/04/2023] [Accepted: 09/14/2023] [Indexed: 09/17/2023]
Abstract
Repeated annual influenza vaccinations have been associated with reduced vaccine-induced antibody responses. This prospective study aimed to explore the role of vaccine antigen-specific regulatory T (Treg) cells in antibody response to repeated annual influenza vaccination. We analyzed pre- and postvaccination hemagglutination inhibition (HI) titers, seroconversion rates, seroprotection rates, vaccine antigen hemagglutinin (HA)-specific Treg cells, and conventional T (Tconv) cells. We compared these parameters between vaccinees with or without vaccine-induced seroconversion. Our multivariate logistic regression revealed that prior vaccination was significantly associated with a decreased likelihood of achieving seroconversion for both H1N1(adjusted OR, 0.03; 95% CI, 0.01-0.13) and H3N2 (adjusted OR, 0.09; 95% CI, 0.03-0.30). Furthermore, individuals who received repeated vaccinations had significantly higher levels of pre-existing HA-specific Treg cells than those who did not. We also found that vaccine-induced fold-increases in HI titers and seroconversion were negatively correlated with pre-existing HA-specific Treg cells and positively correlated with the ratio of Tconv to Treg cells. Overall, our findings suggest that repeated annual influenza vaccination is associated with a lower vaccine-induced antibody response and a higher frequency of vaccine-specific Treg cells. However, a lower frequency of pre-existing Treg cells correlates with a higher postvaccination antibody response.
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Affiliation(s)
- Pin-Hung Lin
- Graduate Institute of Microbiology, College of Medicine, National Taiwan University, Taipei, Taiwan
- Department of Medical Research, National Taiwan University Hospital, Taipei, Taiwan
| | - Po-Ju Hsiao
- Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan
- Department of Internal Medicine, College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Ching-Fu Pan
- Graduate Institute of Microbiology, College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Ming-Tsan Liu
- Center for Diagnostics and Vaccine Development, Centers for Disease Control, Taipei, Taiwan
| | - Jann-Tay Wang
- Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan
- Department of Internal Medicine, College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Chi Ching
- Graduate Institute of Microbiology, College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Fang-Yi Wu
- Graduate Institute of Microbiology, College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Yi-Hsuan Lin
- Graduate Institute of Microbiology, College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Yu-Chan Yang
- Graduate Institute of Microbiology, College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Le-Yin Hsu
- Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan
- Graduate Program of Data Science, National Taiwan University and Academia Sinica, Taipei, Taiwan
| | - Hung-Chih Yang
- Graduate Institute of Microbiology, College of Medicine, National Taiwan University, Taipei, Taiwan
- Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan
| | - Un-In Wu
- Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan
- Department of Internal Medicine, College of Medicine, National Taiwan University, Taipei, Taiwan
- Department of Medicine, National Taiwan University Cancer Center, Taipei, Taiwan
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13
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Huang CQ, Vishwanath S, Carnell GW, Chan ACY, Heeney JL. Immune imprinting and next-generation coronavirus vaccines. Nat Microbiol 2023; 8:1971-1985. [PMID: 37932355 DOI: 10.1038/s41564-023-01505-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2023] [Accepted: 09/13/2023] [Indexed: 11/08/2023]
Abstract
Vaccines based on historical virus isolates provide limited protection from continuously evolving RNA viruses, such as influenza viruses or coronaviruses, which occasionally spill over between animals and humans. Despite repeated booster immunizations, population-wide declines in the neutralization of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants have occurred. This has been compared to seasonal influenza vaccinations in humans, where the breadth of immune responses induced by repeat exposures to antigenically distinct influenza viruses is confounded by pre-existing immunity-a mechanism known as imprinting. Since its emergence, SARS-CoV-2 has evolved in a population with partial immunity, acquired by infection, vaccination or both. Here we critically examine the evidence for and against immune imprinting in host humoral responses to SARS-CoV-2 and its implications for coronavirus disease 2019 (COVID-19) booster vaccine programmes.
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Affiliation(s)
- Chloe Qingzhou Huang
- Laboratory of Viral Zoonotics, Department of Veterinary Medicine, University of Cambridge, Cambridge, UK
| | - Sneha Vishwanath
- Laboratory of Viral Zoonotics, Department of Veterinary Medicine, University of Cambridge, Cambridge, UK
| | - George William Carnell
- Laboratory of Viral Zoonotics, Department of Veterinary Medicine, University of Cambridge, Cambridge, UK
| | - Andrew Chun Yue Chan
- Laboratory of Viral Zoonotics, Department of Veterinary Medicine, University of Cambridge, Cambridge, UK
| | - Jonathan Luke Heeney
- Laboratory of Viral Zoonotics, Department of Veterinary Medicine, University of Cambridge, Cambridge, UK.
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14
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Hu YF, Yuen TTT, Gong HR, Hu B, Hu JC, Lin XS, Rong L, Zhou CL, Chen LL, Wang X, Lei C, Yau T, Hung IFN, To KKW, Yuen KY, Zhang BZ, Chu H, Huang JD. Rational design of a booster vaccine against COVID-19 based on antigenic distance. Cell Host Microbe 2023; 31:1301-1316.e8. [PMID: 37527659 DOI: 10.1016/j.chom.2023.07.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Revised: 06/03/2023] [Accepted: 07/07/2023] [Indexed: 08/03/2023]
Abstract
Current COVID-19 vaccines are highly effective against symptomatic disease, but repeated booster doses using vaccines based on the ancestral strain offer limited additional protection against SARS-CoV-2 variants of concern (VOCs). To address this, we used antigenic distance to in silico select optimized booster vaccine seed strains effective against both current and future VOCs. Our model suggests that a SARS-CoV-1-based booster vaccine has the potential to cover a broader range of VOCs. Candidate vaccines including the spike protein from ancestral SARS-CoV-2, Delta, Omicron (BA.1), SARS-CoV-1, or MERS-CoV were experimentally evaluated in mice following two doses of the BNT162b2 vaccine. The SARS-CoV-1-based booster vaccine outperformed other candidates in terms of neutralizing antibody breadth and duration, as well as protective activity against Omicron (BA.2) challenge. This study suggests a unique strategy for selecting booster vaccines based on antigenic distance, which may be useful in designing future booster vaccines as new SARS-CoV-2 variants emerge.
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Affiliation(s)
- Ye-Fan Hu
- School of Biomedical Sciences, Li Ka Shing Faculty of Medicine, University of Hong Kong, 3/F, Laboratory Block, 21 Sassoon Road, Hong Kong, China; Department of Medicine, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, University of Hong Kong, 4/F Professional Block, Queen Mary Hospital, 102 Pokfulam Road, Hong Kong, China; BayVax Biotech Limited, Hong Kong Science Park, Pak Shek Kok, New Territories, Hong Kong, China
| | - Terrence Tsz-Tai Yuen
- Department of Microbiology, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, University of Hong Kong, 19/F Block T, Queen Mary Hospital, 102 Pokfulam Road, Hong Kong, China
| | - Hua-Rui Gong
- Chinese Academy of Sciences (CAS) Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, 1068 Xueyuan Avenue, Shenzhen University Town, Shenzhen 518055, China; School of Biomedical Sciences, Li Ka Shing Faculty of Medicine, University of Hong Kong, 3/F, Laboratory Block, 21 Sassoon Road, Hong Kong, China
| | - Bingjie Hu
- Department of Microbiology, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, University of Hong Kong, 19/F Block T, Queen Mary Hospital, 102 Pokfulam Road, Hong Kong, China
| | - Jing-Chu Hu
- Chinese Academy of Sciences (CAS) Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, 1068 Xueyuan Avenue, Shenzhen University Town, Shenzhen 518055, China; School of Biomedical Sciences, Li Ka Shing Faculty of Medicine, University of Hong Kong, 3/F, Laboratory Block, 21 Sassoon Road, Hong Kong, China
| | - Xuan-Sheng Lin
- School of Biomedical Sciences, Li Ka Shing Faculty of Medicine, University of Hong Kong, 3/F, Laboratory Block, 21 Sassoon Road, Hong Kong, China
| | - Li Rong
- School of Biomedical Sciences, Li Ka Shing Faculty of Medicine, University of Hong Kong, 3/F, Laboratory Block, 21 Sassoon Road, Hong Kong, China
| | - Coco Luyao Zhou
- School of Biomedical Sciences, Li Ka Shing Faculty of Medicine, University of Hong Kong, 3/F, Laboratory Block, 21 Sassoon Road, Hong Kong, China
| | - Lin-Lei Chen
- Department of Microbiology, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, University of Hong Kong, 19/F Block T, Queen Mary Hospital, 102 Pokfulam Road, Hong Kong, China
| | - Xiaolei Wang
- School of Biomedical Sciences, Li Ka Shing Faculty of Medicine, University of Hong Kong, 3/F, Laboratory Block, 21 Sassoon Road, Hong Kong, China
| | - Chaobi Lei
- Chinese Academy of Sciences (CAS) Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, 1068 Xueyuan Avenue, Shenzhen University Town, Shenzhen 518055, China
| | - Thomas Yau
- Department of Medicine, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, University of Hong Kong, 4/F Professional Block, Queen Mary Hospital, 102 Pokfulam Road, Hong Kong, China
| | - Ivan Fan-Ngai Hung
- Department of Medicine, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, University of Hong Kong, 4/F Professional Block, Queen Mary Hospital, 102 Pokfulam Road, Hong Kong, China
| | - Kelvin Kai-Wang To
- Department of Microbiology, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, University of Hong Kong, 19/F Block T, Queen Mary Hospital, 102 Pokfulam Road, Hong Kong, China
| | - Kwok-Yung Yuen
- Department of Microbiology, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, University of Hong Kong, 19/F Block T, Queen Mary Hospital, 102 Pokfulam Road, Hong Kong, China
| | - Bao-Zhong Zhang
- Chinese Academy of Sciences (CAS) Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, 1068 Xueyuan Avenue, Shenzhen University Town, Shenzhen 518055, China; School of Biomedical Sciences, Li Ka Shing Faculty of Medicine, University of Hong Kong, 3/F, Laboratory Block, 21 Sassoon Road, Hong Kong, China.
| | - Hin Chu
- Department of Microbiology, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, University of Hong Kong, 19/F Block T, Queen Mary Hospital, 102 Pokfulam Road, Hong Kong, China.
| | - Jian-Dong Huang
- Chinese Academy of Sciences (CAS) Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, 1068 Xueyuan Avenue, Shenzhen University Town, Shenzhen 518055, China; School of Biomedical Sciences, Li Ka Shing Faculty of Medicine, University of Hong Kong, 3/F, Laboratory Block, 21 Sassoon Road, Hong Kong, China; Clinical Oncology Center, Shenzhen Key Laboratory for Cancer Metastasis and Personalized Therapy, The University of Hong Kong-Shenzhen Hospital, Shenzhen 518053, China; Guangdong-Hong Kong Joint Laboratory for RNA Medicine, Sun Yat-Sen University, Guangzhou 510120, China.
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15
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Bhatnagar N, Kim KH, Subbiah J, Muhammad-Worsham S, Park BR, Liu R, Grovenstein P, Wang BZ, Kang SM. Heterologous Prime-Boost Vaccination with Inactivated Influenza Viruses Induces More Effective Cross-Protection than Homologous Repeat Vaccination. Vaccines (Basel) 2023; 11:1209. [PMID: 37515025 PMCID: PMC10386405 DOI: 10.3390/vaccines11071209] [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: 04/30/2023] [Revised: 06/24/2023] [Accepted: 06/30/2023] [Indexed: 07/30/2023] Open
Abstract
With concerns about the efficacy of repeat annual influenza vaccination, it is important to better understand the impact of priming vaccine immunity and develop an effective vaccination strategy. Here, we determined the impact of heterologous prime-boost vaccination on inducing broader protective immunity compared to repeat vaccination with the same antigen. The primed mice that were intramuscularly boosted with a heterologous inactivated influenza A virus (H1N1, H3N2, H5N1, H7N9, H9N2) vaccine showed increased strain-specific hemagglutination inhibition titers against prime and boost vaccine strains. Heterologous prime-boost vaccination of mice with inactivated viruses was more effective in inducing high levels of IgG antibodies specific for groups 1 and 2 hemagglutinin stalk domains, as well as cross-protection, compared to homologous vaccination. Both humoral and T cell immunity were found to play a critical role in conferring cross-protection by heterologous prime-boost vaccination. These results support a strategy to enhance cross-protective efficacy by heterologous prime-boost influenza vaccination.
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Affiliation(s)
- Noopur Bhatnagar
- Center for Inflammation, Immunity & Infection, Institute for Biomedical Sciences, Georgia State University, Atlanta, GA 30302, USA; (N.B.); (K.-H.K.); (J.S.); (S.M.-W.); (B.R.P.); (R.L.); (P.G.); (B.-Z.W.)
| | - Ki-Hye Kim
- Center for Inflammation, Immunity & Infection, Institute for Biomedical Sciences, Georgia State University, Atlanta, GA 30302, USA; (N.B.); (K.-H.K.); (J.S.); (S.M.-W.); (B.R.P.); (R.L.); (P.G.); (B.-Z.W.)
| | - Jeeva Subbiah
- Center for Inflammation, Immunity & Infection, Institute for Biomedical Sciences, Georgia State University, Atlanta, GA 30302, USA; (N.B.); (K.-H.K.); (J.S.); (S.M.-W.); (B.R.P.); (R.L.); (P.G.); (B.-Z.W.)
- Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, GA 30329, USA
| | - Sakinah Muhammad-Worsham
- Center for Inflammation, Immunity & Infection, Institute for Biomedical Sciences, Georgia State University, Atlanta, GA 30302, USA; (N.B.); (K.-H.K.); (J.S.); (S.M.-W.); (B.R.P.); (R.L.); (P.G.); (B.-Z.W.)
| | - Bo Ryoung Park
- Center for Inflammation, Immunity & Infection, Institute for Biomedical Sciences, Georgia State University, Atlanta, GA 30302, USA; (N.B.); (K.-H.K.); (J.S.); (S.M.-W.); (B.R.P.); (R.L.); (P.G.); (B.-Z.W.)
| | - Rong Liu
- Center for Inflammation, Immunity & Infection, Institute for Biomedical Sciences, Georgia State University, Atlanta, GA 30302, USA; (N.B.); (K.-H.K.); (J.S.); (S.M.-W.); (B.R.P.); (R.L.); (P.G.); (B.-Z.W.)
| | - Phillip Grovenstein
- Center for Inflammation, Immunity & Infection, Institute for Biomedical Sciences, Georgia State University, Atlanta, GA 30302, USA; (N.B.); (K.-H.K.); (J.S.); (S.M.-W.); (B.R.P.); (R.L.); (P.G.); (B.-Z.W.)
| | - Bao-Zhong Wang
- Center for Inflammation, Immunity & Infection, Institute for Biomedical Sciences, Georgia State University, Atlanta, GA 30302, USA; (N.B.); (K.-H.K.); (J.S.); (S.M.-W.); (B.R.P.); (R.L.); (P.G.); (B.-Z.W.)
| | - Sang-Moo Kang
- Center for Inflammation, Immunity & Infection, Institute for Biomedical Sciences, Georgia State University, Atlanta, GA 30302, USA; (N.B.); (K.-H.K.); (J.S.); (S.M.-W.); (B.R.P.); (R.L.); (P.G.); (B.-Z.W.)
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16
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Doyon-Plourde P, Przepiorkowski J, Young K, Zhao L, Sinilaite A. Intraseasonal waning immunity of seasonal influenza vaccine - A systematic review and meta-analysis. Vaccine 2023:S0264-410X(23)00713-2. [PMID: 37331840 DOI: 10.1016/j.vaccine.2023.06.038] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Revised: 06/08/2023] [Accepted: 06/09/2023] [Indexed: 06/20/2023]
Abstract
BACKGROUND Recently, studies have suggested that influenza antibody titers decline with time since vaccination. Duration of vaccine protection is an important factor to determine the optimal timing of vaccination. OBJECTIVE We aimed to systematically evaluate the implication of waning immunity on the duration of seasonal influenza vaccine antibody response. METHOD Electronic databases and clinical trial registries were systematically searched to identify phase III/IV randomized clinical trials evaluating the immunogenicity of seasonal influenza vaccines measured by hemagglutination inhibition assay in healthy individuals six months of age and older. Meta-analyses were conducted to compare adjuvanted and standard influenza vaccine responses with time since vaccination. RESULTS 1918 articles were identified, of which ten were included in qualitative synthesis and seven in quantitative analysis (children; n=3, older adults; n=4). All studies were deemed to be at low risk of bias, except one study deemed at high risk of bias due to missing outcome data. The majority of included studies found a rise in antibody titers at one-month followed by a decline at six-month post-vaccination. At six-months post-vaccination overall risk differences in seroprotection were significantly higher for children vaccinated with adjuvanted compared to standard vaccines (0.29; 95 % confidence interval (CI), 0.14-0.44). A small increase in seroprotection levels was observed among older adults vaccinated with an adjuvanted compared to standard vaccines, which remained constant over six-months (pre-vaccination: 0.03; 95 % CI, 0.00-0.09 and one- and six-months post-vaccination: 0.05; 95 % CI, 0.01-0.09). CONCLUSIONS Our results found evidence of persistent antibody responses following influenza vaccination over the course of a typical influenza season. Even if influenza vaccine responses wane over a six-month period, vaccination likely still provides a significant advantage in protection, which may be enhanced with adjuvanted vaccines, particularly in children. Further research is needed to identify the exact timing when the decline in antibody response begins to better inform the optimal timing of influenza vaccination programs. TRIAL REGISTRATION PROSPERO (CRD42019138585).
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Affiliation(s)
- Pamela Doyon-Plourde
- Centre for Immunization Readiness, Public Health Agency of Canada, Ottawa, Canada; Department of Microbiology, Infectious Diseases, and Immunology, Faculty of Medicine, University of Montreal, Canada.
| | | | - Kelsey Young
- Centre for Immunization Readiness, Public Health Agency of Canada, Ottawa, Canada
| | - Linlu Zhao
- Centre for Immunization Readiness, Public Health Agency of Canada, Ottawa, Canada
| | - Angela Sinilaite
- Centre for Immunization Readiness, Public Health Agency of Canada, Ottawa, Canada
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17
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Sinilaite A, Young K, Papenburg J. Summary of the National Advisory Committee on Immunization (NACI) Statement-Recommendation on Repeated Seasonal Influenza Vaccination. CANADA COMMUNICABLE DISEASE REPORT = RELEVE DES MALADIES TRANSMISSIBLES AU CANADA 2023; 49:99-102. [PMID: 38298903 PMCID: PMC10826901 DOI: 10.14745/ccdr.v49i04a02] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/02/2024]
Abstract
Background Influenza vaccination is recommended annually; however, some studies have raised questions regarding whether repeated influenza vaccine administration may have unintended negative consequences for seasonal protection. Methods The National Advisory Committee on Immunization (NACI) Influenza Working Group undertook an overview of systematic reviews on the effects of repeated influenza vaccination on vaccine effectiveness, efficacy, and immunogenicity. A systematic assessment of programmatic factors was conducted according to established NACI methods. The NACI evidence-based process was used to critically appraise the available evidence and to review recommendations. Results The evidence base consisted of four eligible systematic reviews/meta-analyses. Repeated vaccination, including the current season, was consistently more effective than no vaccination in the current season. The evidence showed no significant difference or predictable trend in vaccine efficacy or effectiveness between vaccinations in two consecutive seasons compared to vaccination in the current season only. Conclusion Overall, NACI concluded that there is evidence to recommend annual influenza vaccination, irrespective of whether an individual received the seasonal influenza vaccine in previous seasons. It is neither currently feasible nor warranted to modify existing annual influenza vaccination programs to account for potential negative or positive interference. NACI continues to strongly recommend that seasonal influenza vaccine should be offered annually to everyone six months of age and older who does not have contraindications to the vaccine, irrespective of previous seasons' influenza vaccination status.
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Affiliation(s)
- Angela Sinilaite
- Centre for Immunization Readiness, Public Health Agency of Canada, Ottawa, ON
| | - Kelsey Young
- Centre for Immunization Readiness, Public Health Agency of Canada, Ottawa, ON
| | - Jesse Papenburg
- NACI Influenza Working Group Chair
- Division of Pediatric Infectious Diseases, Department of Pediatrics, Montréal Children's Hospital of the McGill University Health Centre, Montréal, QC
- Division of Microbiology, Department of Clinical Laboratory Medicine, Optilab Montréal - McGill University Health Centre, Montréal, QC
- Department of Epidemiology, Biostatistics, and Occupational Health, School of Population and Global Health, McGill University, Montréal, QC
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18
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Currenti J, Simmons J, Oakes J, Gaudieri S, Warren CM, Gangula R, Alves E, Ram R, Leary S, Armitage JD, Smith RM, Chopra A, Halasa NB, Pilkinton MA, Kalams SA. Tracking of activated cTfh cells following sequential influenza vaccinations reveals transcriptional profile of clonotypes driving a vaccine-induced immune response. Front Immunol 2023; 14:1133781. [PMID: 37063867 PMCID: PMC10095155 DOI: 10.3389/fimmu.2023.1133781] [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: 12/29/2022] [Accepted: 03/13/2023] [Indexed: 03/30/2023] Open
Abstract
Introduction A vaccine against influenza is available seasonally but is not 100% effective. A predictor of successful seroconversion in adults is an increase in activated circulating T follicular helper (cTfh) cells after vaccination. However, the impact of repeated annual vaccinations on long-term protection and seasonal vaccine efficacy remains unclear. Methods In this study, we examined the T cell receptor (TCR) repertoire and transcriptional profile of vaccine-induced expanded cTfh cells in individuals who received sequential seasonal influenza vaccines. We measured the magnitude of cTfh and plasmablast cell activation from day 0 (d0) to d7 post-vaccination as an indicator of a vaccine response. To assess TCR diversity and T cell expansion we sorted activated and resting cTfh cells at d0 and d7 post-vaccination and performed TCR sequencing. We also single cell sorted activated and resting cTfh cells for TCR analysis and transcriptome sequencing. Results and discussion The percent of activated cTfh cells significantly increased from d0 to d7 in each of the 2016-17 (p < 0.0001) and 2017-18 (p = 0.015) vaccine seasons with the magnitude of cTfh activation increase positively correlated with the frequency of circulating plasmablast cells in the 2016-17 (p = 0.0001) and 2017-18 (p = 0.003) seasons. At d7 post-vaccination, higher magnitudes of cTfh activation were associated with increased clonality of cTfh TCR repertoire. The TCRs from vaccine-expanded clonotypes were identified and tracked longitudinally with several TCRs found to be present in both years. The transcriptomic profile of these expanded cTfh cells at the single cell level demonstrated overrepresentation of transcripts of genes involved in the type-I interferon pathway, pathways involved in gene expression, and antigen presentation and recognition. These results identify the expansion and transcriptomic profile of vaccine-induced cTfh cells important for B cell help.
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Affiliation(s)
- Jennifer Currenti
- School of Human Sciences, University of Western Australia, Crawley, WA, Australia
| | - Joshua Simmons
- Division of Infectious Diseases, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Jared Oakes
- Department of Pathology, Microbiology, and Immunology, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Silvana Gaudieri
- School of Human Sciences, University of Western Australia, Crawley, WA, Australia
- Division of Infectious Diseases, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, United States
- Institute for Immunology and Infectious Diseases, Murdoch University, Murdoch, WA, Australia
| | - Christian M. Warren
- Division of Infectious Diseases, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Rama Gangula
- Division of Infectious Diseases, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Eric Alves
- School of Human Sciences, University of Western Australia, Crawley, WA, Australia
| | - Ramesh Ram
- Institute for Immunology and Infectious Diseases, Murdoch University, Murdoch, WA, Australia
| | - Shay Leary
- Institute for Immunology and Infectious Diseases, Murdoch University, Murdoch, WA, Australia
| | - Jesse D. Armitage
- Telethon Kids Institute, University of Western Australia, Nedlands, WA, Australia
| | - Rita M. Smith
- Division of Infectious Diseases, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Abha Chopra
- Institute for Immunology and Infectious Diseases, Murdoch University, Murdoch, WA, Australia
| | - Natasha B. Halasa
- Division of Pediatric Infectious Diseases, Department of Pediatrics, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Mark A. Pilkinton
- Division of Infectious Diseases, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Spyros A. Kalams
- Division of Infectious Diseases, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, United States
- Department of Pathology, Microbiology, and Immunology, Vanderbilt University Medical Center, Nashville, TN, United States
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19
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Schiepers A, van 't Wout MFL, Greaney AJ, Zang T, Muramatsu H, Lin PJC, Tam YK, Mesin L, Starr TN, Bieniasz PD, Pardi N, Bloom JD, Victora GD. Molecular fate-mapping of serum antibody responses to repeat immunization. Nature 2023; 615:482-489. [PMID: 36646114 PMCID: PMC10023323 DOI: 10.1038/s41586-023-05715-3] [Citation(s) in RCA: 50] [Impact Index Per Article: 50.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2022] [Accepted: 01/06/2023] [Indexed: 01/18/2023]
Abstract
The protective efficacy of serum antibodies results from the interplay of antigen-specific B cell clones of different affinities and specificities. These cellular dynamics underlie serum-level phenomena such as original antigenic sin (OAS)-a proposed propensity of the immune system to rely repeatedly on the first cohort of B cells engaged by an antigenic stimulus when encountering related antigens, in detriment to the induction of de novo responses1-5. OAS-type suppression of new, variant-specific antibodies may pose a barrier to vaccination against rapidly evolving viruses such as influenza and SARS-CoV-26,7. Precise measurement of OAS-type suppression is challenging because cellular and temporal origins cannot readily be ascribed to antibodies in circulation; its effect on subsequent antibody responses therefore remains unclear5,8. Here we introduce a molecular fate-mapping approach with which serum antibodies derived from specific cohorts of B cells can be differentially detected. We show that serum responses to sequential homologous boosting derive overwhelmingly from primary cohort B cells, while later induction of new antibody responses from naive B cells is strongly suppressed. Such 'primary addiction' decreases sharply as a function of antigenic distance, allowing reimmunization with divergent viral glycoproteins to produce de novo antibody responses targeting epitopes that are absent from the priming variant. Our findings have implications for the understanding of OAS and for the design and testing of vaccines against evolving pathogens.
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Affiliation(s)
- Ariën Schiepers
- Laboratory of Lymphocyte Dynamics, The Rockefeller University, New York, NY, USA
| | | | - Allison J Greaney
- Basic Sciences Division and Computational Biology Program, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Trinity Zang
- Laboratory of Retrovirology, The Rockefeller University, New York, NY, USA
| | - Hiromi Muramatsu
- Department of Microbiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Paulo J C Lin
- Acuitas Therapeutics, Vancouver, British Columbia, Canada
| | - Ying K Tam
- Acuitas Therapeutics, Vancouver, British Columbia, Canada
| | - Luka Mesin
- Laboratory of Lymphocyte Dynamics, The Rockefeller University, New York, NY, USA
| | - Tyler N Starr
- Basic Sciences Division and Computational Biology Program, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Paul D Bieniasz
- Laboratory of Retrovirology, The Rockefeller University, New York, NY, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
| | - Norbert Pardi
- Department of Microbiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Jesse D Bloom
- Basic Sciences Division and Computational Biology Program, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
| | - Gabriel D Victora
- Laboratory of Lymphocyte Dynamics, The Rockefeller University, New York, NY, USA.
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20
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Makau DN, Prieto C, Martínez-Lobo FJ, Paploski IAD, VanderWaal K. Predicting Antigenic Distance from Genetic Data for PRRSV-Type 1: Applications of Machine Learning. Microbiol Spectr 2023; 11:e0408522. [PMID: 36511691 PMCID: PMC9927307 DOI: 10.1128/spectrum.04085-22] [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: 10/08/2022] [Accepted: 11/18/2022] [Indexed: 12/15/2022] Open
Abstract
The control of porcine reproductive and respiratory syndrome (PRRS) remains a significant challenge due to the genetic and antigenic variability of the causative virus (PRRSV). Predominantly, PRRSV management includes using vaccines and live virus inoculations to confer immunity against PRRSV on farms. While understanding cross-protection among strains is crucial for the continued success of these interventions, understanding how genetic diversity translates to antigenic diversity remains elusive. We developed machine learning algorithms to estimate antigenic distance in silico, based on genetic sequence data, and identify differences in specific amino acid sites associated with antigenic differences between viruses. First, we obtained antigenic distance estimates derived from serum neutralization assays cross-reacting PRRSV monospecific antisera with virus isolates from 27 PRRSV1 viruses circulating in Europe. Antigenic distances were weakly to moderately associated with ectodomain amino acid distance for open reading frames (ORFs) 2 to 4 (ρ < 0.2) and ORF5 (ρ = 0.3), respectively. Dividing the antigenic distance values at the median, we then categorized the sera-virus pairs into two levels: low and high antigenic distance (dissimilarity). In the machine learning models, we used amino acid distances in the ectodomains of ORFs 2 to 5 and site-wise amino acid differences between the viruses as potential predictors of antigenic dissimilarity. Using mixed-effect gradient boosting models, we estimated the antigenic distance (high versus low) between serum-virus pairs with an accuracy of 81% (95% confidence interval, 76 to 85%); sensitivity and specificity were 86% and 75%, respectively. We demonstrate that using sequence data we can estimate antigenic distance and potential cross-protection between PRRSV1 strains. IMPORTANCE Understanding cross-protection between cocirculating PRRSV1 strains is crucial to reducing losses associated with PRRS outbreaks on farms. While experimental studies to determine cross-protection are instrumental, these in vivo studies are not always practical or timely for the many cocirculating and emerging PRRSV strains. In this study, we demonstrate the ability to rapidly estimate potential immunologic cross-reaction between different PRRSV1 strains in silico using sequence data routinely collected by production systems. These models can provide fast turn-around information crucial for improving PRRS management decisions such as selecting vaccines/live virus inoculation to be used on farms and assessing the risk of outbreaks by emerging strains on farms previously exposed to certain PRRSV strains and vaccine development among others.
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Affiliation(s)
- Dennis N. Makau
- Department of Veterinary Population Medicine, College of Veterinary Medicine, University of Minnesota, Minneapolis, USA
| | - Cinta Prieto
- Departamento de Sanidad Animal, Facultad de Veterinaria, Universidad Complutense de Madrid, Madrid, Spain
| | | | - I. A. D. Paploski
- Department of Veterinary Population Medicine, College of Veterinary Medicine, University of Minnesota, Minneapolis, USA
| | - Kimberly VanderWaal
- Department of Veterinary Population Medicine, College of Veterinary Medicine, University of Minnesota, Minneapolis, USA
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21
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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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22
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King SM, Bryan SP, Hilchey SP, Wang J, Zand MS. First Impressions Matter: Immune Imprinting and Antibody Cross-Reactivity in Influenza and SARS-CoV-2. Pathogens 2023; 12:169. [PMID: 36839441 PMCID: PMC9967769 DOI: 10.3390/pathogens12020169] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2022] [Revised: 01/12/2023] [Accepted: 01/13/2023] [Indexed: 01/24/2023] Open
Abstract
Many rigorous studies have shown that early childhood infections leave a lasting imprint on the immune system. The understanding of this phenomenon has expanded significantly since 1960, when Dr. Thomas Francis Jr first coined the term "original antigenic sin", to account for all previous pathogen exposures, rather than only the first. Now more commonly referred to as "immune imprinting", this effect most often focuses on how memory B-cell responses are shaped by prior antigen exposure, and the resultant antibodies produced after subsequent exposure to antigenically similar pathogens. Although imprinting was originally observed within the context of influenza viral infection, it has since been applied to the pandemic coronavirus SARS-CoV-2. To fully comprehend how imprinting affects the evolution of antibody responses, it is necessary to compare responses elicited by pathogenic strains that are both antigenically similar and dissimilar to strains encountered previously. To accomplish this, we must be able to measure the antigenic distance between strains, which can be easily accomplished using data from multidimensional immunological assays. The knowledge of imprinting, combined with antigenic distance measures, may allow for improvements in vaccine design and development for both influenza and SARS-CoV-2 viruses.
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Affiliation(s)
- Samantha M. King
- Department of Medicine, Division of Nephrology, University of Rochester Medical Center, Rochester, NY 14642, USA
| | - Shane P. Bryan
- Department of Medicine, Division of Nephrology, University of Rochester Medical Center, Rochester, NY 14642, USA
| | - Shannon P. Hilchey
- Department of Medicine, Division of Nephrology, University of Rochester Medical Center, Rochester, NY 14642, USA
| | - Jiong Wang
- Department of Medicine, Division of Nephrology, University of Rochester Medical Center, Rochester, NY 14642, USA
| | - Martin S. Zand
- Department of Medicine, Division of Nephrology, University of Rochester Medical Center, Rochester, NY 14642, USA
- Clinical and Translational Science Institute, University of Rochester Medical Center, Rochester, NY 14618, USA
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23
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Tang W, Xie H, Ye Z, Eick-Cost AA, Scheckelhoff M, Gustin CE, Bream JH, Plant EP. Post-vaccination serum cytokines levels correlate with breakthrough influenza infections. Sci Rep 2023; 13:1174. [PMID: 36670200 PMCID: PMC9857916 DOI: 10.1038/s41598-023-28295-8] [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: 10/03/2022] [Accepted: 01/16/2023] [Indexed: 01/21/2023] Open
Abstract
Post-vaccination cytokine levels from 256 young adults who subsequently suffered breakthrough influenza infections were compared with matched controls. Modulation within the immune system is important for eliciting a protective response, and the optimal response differs according to vaccine formulation and delivery. For both inactivated influenza vaccine (IIV) and live attenuated influenza vaccines (LAIV) lower levels of IL-8 were observed in post-vaccination sera. Post-vaccination antibody levels were higher and IFN-γ levels were lower in IIV sera compared to LAIV sera. Subjects who suffered breakthrough infections after IIV vaccination had higher levels of sCD25 compared to the control group. There were differences in LAIV post-vaccination interleukin levels for subjects who subsequently suffered breakthrough infections, but these differences were masked in subjects who received concomitant vaccines. Wide variances, sex-based differences and confounders such as concomitant vaccines thwart the establishment of specific cytokine responses as a correlate of protection, but our results provide real world evidence that the status of the immune system following vaccination is important for successful vaccination and subsequent protection against disease.
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Affiliation(s)
- Weichun Tang
- Laboratory of Pediatric and Respiratory Viral Disease, Office of Vaccine Research and Review, CBER, FDA, Silver Spring, MD, USA
| | - Hang Xie
- Laboratory of Pediatric and Respiratory Viral Disease, Office of Vaccine Research and Review, CBER, FDA, Silver Spring, MD, USA
| | - Zhiping Ye
- Laboratory of Pediatric and Respiratory Viral Disease, Office of Vaccine Research and Review, CBER, FDA, Silver Spring, MD, USA
| | - Angelia A Eick-Cost
- Armed Forces Health Surveillance Division, Defense Health Agency, Silver Spring, MD, USA
| | - Mark Scheckelhoff
- Armed Forces Health Surveillance Division, Defense Health Agency, Silver Spring, MD, USA
| | - Courtney E Gustin
- Armed Forces Health Surveillance Division, Defense Health Agency, Silver Spring, MD, USA
| | - Jay H Bream
- Department of Molecular Microbiology and Immunology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.,Graduate Program in Immunology, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Ewan P Plant
- Laboratory of Pediatric and Respiratory Viral Disease, Office of Vaccine Research and Review, CBER, FDA, Silver Spring, MD, USA.
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24
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Aguilar-Bretones M, Fouchier RA, Koopmans MP, van Nierop GP. Impact of antigenic evolution and original antigenic sin on SARS-CoV-2 immunity. J Clin Invest 2023; 133:e162192. [PMID: 36594464 PMCID: PMC9797340 DOI: 10.1172/jci162192] [Citation(s) in RCA: 25] [Impact Index Per Article: 25.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023] Open
Abstract
Infections with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and vaccinations targeting the spike protein (S) offer protective immunity against coronavirus disease 2019 (COVID-19). This immunity may further be shaped by cross-reactivity with common cold coronaviruses. Mutations arising in S that are associated with altered intrinsic virus properties and immune escape result in the continued circulation of SARS-CoV-2 variants. Potentially, vaccine updates will be required to protect against future variants of concern, as for influenza. To offer potent protection against future variants, these second-generation vaccines may need to redirect immunity to epitopes associated with immune escape and not merely boost immunity toward conserved domains in preimmune individuals. For influenza, efficacy of repeated vaccination is hampered by original antigenic sin, an attribute of immune memory that leads to greater induction of antibodies specific to the first-encountered variant of an immunogen compared with subsequent variants. In this Review, recent findings on original antigenic sin are discussed in the context of SARS-CoV-2 evolution. Unanswered questions and future directions are highlighted, with an emphasis on the impact on disease outcome and vaccine design.
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25
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Jones-Gray E, Robinson EJ, Kucharski AJ, Fox A, Sullivan SG. Does repeated influenza vaccination attenuate effectiveness? A systematic review and meta-analysis. THE LANCET. RESPIRATORY MEDICINE 2023; 11:27-44. [PMID: 36152673 PMCID: PMC9780123 DOI: 10.1016/s2213-2600(22)00266-1] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Revised: 07/13/2022] [Accepted: 07/13/2022] [Indexed: 01/11/2023]
Abstract
BACKGROUND Influenza vaccines require annual readministration; however, several reports have suggested that repeated vaccination might attenuate the vaccine's effectiveness. We aimed to estimate the reduction in vaccine effectiveness associated with repeated influenza vaccination. METHODS In this systematic review and meta-analysis, we searched MEDLINE, EMBASE, and CINAHL Complete databases for articles published from Jan 1, 2016, to June 13, 2022, and Web of Science for studies published from database inception to June 13, 2022. For studies published before Jan 1, 2016, we consulted published systematic reviews. Two reviewers (EJ-G and EJR) independently screened, extracted data using a data collection form, assessed studies' risk of bias using the Risk Of Bias In Non-Randomized Studies of Interventions (ROBINS-I) and evaluated the weight of evidence by Grading of Recommendations Assessment, Development, and Evaluation (GRADE). We included observational studies and randomised controlled trials that reported vaccine effectiveness against influenza A(H1N1)pdm09, influenza A(H3N2), or influenza B using four vaccination groups: current season; previous season; current and previous seasons; and neither season (reference). For each study, we calculated the absolute difference in vaccine effectiveness (ΔVE) for current season only and previous season only versus current and previous season vaccination to estimate attenuation associated with repeated vaccination. Pooled vaccine effectiveness and ∆VE were calculated by season, age group, and overall. This study is registered with PROSPERO, CRD42021260242. FINDINGS We identified 4979 publications, selected 681 for full review, and included 83 in the systematic review and 41 in meta-analyses. ΔVE for vaccination in both seasons compared with the current season was -9% (95% CI -16 to -1, I2=0%; low certainty) for influenza A(H1N1)pdm09, -18% (-26 to -11, I2=7%; low certainty) for influenza A(H3N2), and -7% (-14 to 0, I2=0%; low certainty) for influenza B, indicating lower protection with consecutive vaccination. However, for all types, A subtypes and B lineages, vaccination in both seasons afforded better protection than not being vaccinated. INTERPRETATION Our estimates suggest that, although vaccination in the previous year attenuates vaccine effectiveness, vaccination in two consecutive years provides better protection than does no vaccination. The estimated effects of vaccination in the previous year are concerning and warrant additional investigation, but are not consistent or severe enough to support an alternative vaccination regimen at this time. FUNDING WHO and the US National Institutes of Health.
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Affiliation(s)
- Elenor Jones-Gray
- Department of Infectious Diseases, University of Melbourne, Melbourne, VIC, Australia
| | - Elizabeth J Robinson
- Department of Infectious Diseases, University of Melbourne, Melbourne, VIC, Australia
| | - Adam J Kucharski
- Centre for the Mathematical Modelling of Infectious Diseases (CMMID), London School of Hygiene and Tropical Medicine, London, UK
| | - Annette Fox
- Department of Infectious Diseases, University of Melbourne, Melbourne, VIC, Australia; WHO Collaborating Centre for Reference and Research on Influenza, Royal Melbourne Hospital, Peter Doherty Institute for Infection and Immunity, Melbourne, VIC, Australia
| | - Sheena G Sullivan
- Department of Infectious Diseases, University of Melbourne, Melbourne, VIC, Australia; WHO Collaborating Centre for Reference and Research on Influenza, Royal Melbourne Hospital, Peter Doherty Institute for Infection and Immunity, Melbourne, VIC, Australia; Department of Epidemiology, University of California, Los Angeles, CA, USA.
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26
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Repeat vaccination and influenza vaccine effectiveness. THE LANCET. RESPIRATORY MEDICINE 2023; 11:2-3. [PMID: 36152672 DOI: 10.1016/s2213-2600(22)00305-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/07/2022] [Accepted: 08/08/2022] [Indexed: 12/27/2022]
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27
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Tawfik A, Kawaguchi T, Takahashi M, Setoh K, Yamaguchi I, Tabara Y, Van Steen K, Sakuntabhai A, Matsuda F. Trivalent inactivated influenza vaccine response and immunogenicity assessment after one week and three months in repeatedly vaccinated adults. Expert Rev Vaccines 2023; 22:826-838. [PMID: 37747798 DOI: 10.1080/14760584.2023.2262563] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2023] [Accepted: 09/20/2023] [Indexed: 09/27/2023]
Abstract
BACKGROUND The influenza vaccine administrated every year is a recommended infection control procedure for individuals above the age of six months. However, the effectiveness of repeated annual vaccination is still an active research topic. Therefore, we investigated the vaccine immunogenicity in two independent groups: previously vaccinated versus non-vaccinated individuals at three time points; prior vaccination, one week and three months post vaccination. The assessment enabled us to evaluate the elicited immune responses and the durability of the induced protection in both groups. RESEARCH DESIGN AND METHODS A research study was conducted to assess the immunogenicity of a single dose of Trivalent Inactivated Influenza Vaccine (A/H1N1, A/H3N2, and B) in 278 healthy adults aged between 32 and 66 years. Almost half of the participants, 140 (50·36%), received influenza vaccination at least once precursor to past influenza seasons. One blood sample was taken prior to vaccination for complete blood analysis and baseline immunogenicity assessment. The selected study participants received a single vaccine dose on the first day, and then followed up for three months. Two blood samples were taken after one week and three months post vaccination, respectively, for vaccine immunogenicity assessment. RESULTS Before vaccination, the seroprotection, defined as a hemagglutination-inhibiting titer of =>1:40, was detected for the three vaccine virus strains in 20 previously vaccinated participants (14·29%) [8·95%, 21·2%]. We compared the overall vaccine response for the three virus strains using a normalized response score calculated from linearly transformed titer measurements; the score before vaccination was 84% higher in the previously vaccinated group and the mean difference between the two groups was statistically significant. Three months post-vaccination, we didn't find a significant difference in vaccine responses; the number of fully seroprotected individuals became 48 (34·29%) [26·48%, 42·77%] in the previously vaccinated group and 59 (42·75%) [34·37%, 51·45%] in the non-vaccinated group. The calculated response score was almost equal in both groups and the mean difference was no longer statistically significant. CONCLUSION Our findings suggest that a single dose of influenza vaccine is equally protective after three months for annually vaccinated adults and first-time vaccine receivers.
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Affiliation(s)
- Ahmed Tawfik
- Institut Pasteur, CNRS UMR2000, Functional Genetics of Infectious Diseases Unit, Paris, France
- Pasteur International Unit at Center for Genomic Medicine, Kyoto University, Kyoto, Japan
| | - Takahisa Kawaguchi
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Meiko Takahashi
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Kazuya Setoh
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Izumi Yamaguchi
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Yasuharu Tabara
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Kristel Van Steen
- BIO3 - Laboratory for Systems Genetics, GIGA-R Medical Genomics, University of Liège, Liège, Belgium
- BIO3 - Laboratory for Systems Medicine, Department of Human Genetics, Leuven, Leuven, KU, Belgium
| | - Anavaj Sakuntabhai
- Pasteur International Unit at Center for Genomic Medicine, Kyoto University, Kyoto, Japan
- Institut Pasteur, CNRS UMR2000, Ecology and Emergence of Arthropod-borne Pathogens Unit, Paris, France
| | - Fumihiko Matsuda
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
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28
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Kajiume T, Mukai S, Toyota N, Kanazawa I, Kato A, Akimoto E, Shirakawa T. Effectiveness of seasonal influenza vaccine in elementary and middle schools: a 10-year follow-up investigation. BMC Infect Dis 2022; 22:909. [PMID: 36474168 PMCID: PMC9724312 DOI: 10.1186/s12879-022-07898-y] [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: 05/04/2022] [Accepted: 11/25/2022] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND Influenza spreads from schools to the rest of society. Thus, we conducted questionnaire surveys of influenza vaccination in elementary and middle schools in a district for 10 years to determine immunization rates and infection conditions among students who were potential sources of infection at home. METHODS The questionnaire-based survey on influenza vaccine administration, influenza infection, and influenza types contracted, as well as influenza immunization history, was conducted in 10 seasons over a period of 10 years. RESULTS In elementary schools, vaccination was associated with lower morbidity in most years, whereas in middle schools, morbidity increased among students who were vaccinated every year. Our study did not find consistent trends among faculty and staff. In addition, we found that morbidity was significantly higher among elementary (P < 0.001) and middle (P < 0.05) school students who had been vaccinated since infancy than among those who had not been vaccinated since infancy. CONCLUSIONS The results of this study suggest that vaccinating infants for influenza may increase the risk of contracting influenza later in life.
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Affiliation(s)
- Teruyuki Kajiume
- Hiroshima Akichiku Medical Association, 5-13 Sakae-machi, Kaita-cho, Aki-gun, Hiroshima, 736-0043 Japan ,Mukainada Child Clinic, 24-26 Aosaki-naka, Fuchu-cho, Aki-gun, Hiroshima, 735-0016 Japan
| | - Sumera Mukai
- Hiroshima Akichiku Medical Association, 5-13 Sakae-machi, Kaita-cho, Aki-gun, Hiroshima, 736-0043 Japan ,Mukai Clinic of Internal Medicine, 2-2-8 Tahara, Ondo-cho, Kure-city, Hiroshima 737-1216 Japan
| | - Nobutaka Toyota
- Hiroshima Akichiku Medical Association, 5-13 Sakae-machi, Kaita-cho, Aki-gun, Hiroshima, 736-0043 Japan ,Toyota Ladies Clinic, 4-30-1 Kawasumi, Kumano-cho, Aki-gun, Hiroshima, 731-4223 Japan
| | - Ikuo Kanazawa
- Hiroshima Akichiku Medical Association, 5-13 Sakae-machi, Kaita-cho, Aki-gun, Hiroshima, 736-0043 Japan ,Kanazawa Cardiology Clinic, 4-10-18 Yano-nishi, Aki-ku, Hiroshima, 736-0085 Japan
| | - Akiko Kato
- Hiroshima Akichiku Medical Association, 5-13 Sakae-machi, Kaita-cho, Aki-gun, Hiroshima, 736-0043 Japan ,Kato Gastroenterology Clinic, 3-3-14 Nakano-higashi, Aki-ku, Hiroshima, 739-0323 Japan
| | - Etsushi Akimoto
- Hiroshima Akichiku Medical Association, 5-13 Sakae-machi, Kaita-cho, Aki-gun, Hiroshima, 736-0043 Japan ,Akimoto Clinic, 3-34 Inari-machi, Kaita-cho, Aki-gun, Hiroshima, 736-0067 Japan
| | - Toshio Shirakawa
- Hiroshima Akichiku Medical Association, 5-13 Sakae-machi, Kaita-cho, Aki-gun, Hiroshima, 736-0043 Japan ,Senosirakawa Hospital, 1-28-3 Seno, Aki-ku, Hiroshima, 739-0311 Japan
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Forghani M, Firstkov AL, Alyannezhadi MM, Danilenko DM, Komissarov AB. Reduced amino acid alphabet-based encoding and its impact on modeling influenza antigenic evolution. RUSSIAN JOURNAL OF INFECTION AND IMMUNITY 2022. [DOI: 10.15789/2220-7619-raa-1968] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
Currently, vaccination is one of the most efficient ways to control and prevent influenza infection. Vaccine production largely relies on the results of laboratory assays, including hemagglutination inhibition and microneutralization assays, which are time-consuming and laborious. Viruses can escape from the immune response that results in the need to revise and update vaccines biannually. The hemagglutination inhibition assay can measure how effectively antibodies against a reference strain bind and block an antigen of the test strain. Various computer-aided models have been developed to optimize candidate vaccine strain selection. A general problem in modeling of antigenic evolution is the representation of genetic sequences for input into the research model. Our motivation stems from the well-known problem of encoding genetic information for modeling antigenic evolution. This paper introduces a two-fold encoding approach based on reduced amino acid alphabet and amino acid index databases called AAindex. We propose to apply a simplified amino acid alphabet in modeling of antigenic evolution. A simplified alphabet, also called a sub-alphabet or reduced amino acid alphabet, implies to use the 20 amino acids being clustered and divided into amino acid groups. The proposed encoding allows to redefine mutations termed for amino acid groups located in reduced alphabets. We investigated 40 reduced amino acid sets and their performance in modeling antigenic evolution. The experimental results indicate that the proposed reduced amino acid alphabets can achieve the performance of the standard alphabet in its accuracy. Moreover, these alphabets provide deeper insight into various aspects of the relationship between mutation and antigenic variation. By checking identified high-impact sites in the Influenza Research Database, we found that not only antigenic sites have a significant influence on antigenicity, but also other amino acids located in close proximity. The results indicate that all selected non-antigenic sites are related to immune responses. According to the Influenza Research Database, these have been experimentally determined to be T-cell epitopes, B-cell epitopes, and MHC-binding epitopes of different classes. This highlighted a caveat: while simulating antigenic evolution, the model should consider not only the genetic information on antigenic sites, but also that of neighboring positions, as they may indirectly impact antigenicity. Additionally, our findings indicate that structural and charge characteristics are the most beneficial in modeling antigenic evolution, which is in agreement with previous studies.
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Forst CV, Chung M, Hockman M, Lashua L, Adney E, Hickey A, Carlock M, Ross T, Ghedin E, Gresham D. Vaccination History, Body Mass Index, Age, and Baseline Gene Expression Predict Influenza Vaccination Outcomes. Viruses 2022; 14:2446. [PMID: 36366544 PMCID: PMC9697051 DOI: 10.3390/v14112446] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Revised: 10/24/2022] [Accepted: 10/28/2022] [Indexed: 11/06/2022] Open
Abstract
Seasonal influenza is a primary public health burden in the USA and globally. Annual vaccination programs are designed on the basis of circulating influenza viral strains. However, the effectiveness of the seasonal influenza vaccine is highly variable between seasons and among individuals. A number of factors are known to influence vaccination effectiveness including age, sex, and comorbidities. Here, we sought to determine whether whole blood gene expression profiling prior to vaccination is informative about pre-existing immunological status and the immunological response to vaccine. We performed whole transcriptome analysis using RNA sequencing (RNAseq) of whole blood samples obtained prior to vaccination from 275 participants enrolled in an annual influenza vaccine trial. Serological status prior to vaccination and 28 days following vaccination was assessed using the hemagglutination inhibition assay (HAI) to define baseline immune status and the response to vaccination. We find evidence that genes with immunological functions are increased in expression in individuals with higher pre-existing immunity and in those individuals who mount a greater response to vaccination. Using a random forest model, we find that this set of genes can be used to predict vaccine response with a performance similar to a model that incorporates physiological and prior vaccination status alone. A model using both gene expression and physiological factors has the greatest predictive power demonstrating the potential utility of molecular profiling for enhancing prediction of vaccine response. Moreover, expression of genes that are associated with enhanced vaccination response may point to additional biological pathways that contribute to mounting a robust immunological response to the seasonal influenza vaccine.
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Affiliation(s)
- Christian V. Forst
- Department of Genetics and Genomic Sciences, Department of Microbiology, Icahn School of Medicine at Mt Sinai, One Gustave L. Levy Place, Box 1498, New York, NY 10029-6574, USA
| | - Matthew Chung
- Systems Genomics Section, Laboratory of Parasitic Diseases, NIAID, NIH, Bethesda, MD 20894, USA
| | - Megan Hockman
- Center for Genomics and Systems Biology, Department of Biology, New York University, New York, NY 10003, USA
| | - Lauren Lashua
- Center for Genomics and Systems Biology, Department of Biology, New York University, New York, NY 10003, USA
| | - Emily Adney
- Center for Genomics and Systems Biology, Department of Biology, New York University, New York, NY 10003, USA
| | - Angela Hickey
- Center for Genomics and Systems Biology, Department of Biology, New York University, New York, NY 10003, USA
| | - Michael Carlock
- Center for Vaccines and Immunology, University of Georgia, Athens, GA 30602, USA
- Department of Infectious Diseases, University of Georgia, Athens, GA 30602, USA
| | - Ted Ross
- Center for Vaccines and Immunology, University of Georgia, Athens, GA 30602, USA
- Department of Infectious Diseases, University of Georgia, Athens, GA 30602, USA
| | - Elodie Ghedin
- Systems Genomics Section, Laboratory of Parasitic Diseases, NIAID, NIH, Bethesda, MD 20894, USA
| | - David Gresham
- Center for Genomics and Systems Biology, Department of Biology, New York University, New York, NY 10003, USA
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The impact of repeated vaccination on relative influenza vaccine effectiveness among vaccinated adults in the United Kingdom. Epidemiol Infect 2022; 150:e198. [PMID: 36331053 PMCID: PMC9987024 DOI: 10.1017/s0950268822001753] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
Abstract
Annual seasonal influenza vaccination is recommended for individuals at high risk of developing post-infection complications in many locations. However, reduced vaccine immunogenicity and effectiveness have been observed among repeat vaccinees in some influenza seasons. We investigated the impact of repeated influenza vaccination on relative vaccine effectiveness (VE) among individuals who were recommended for influenza vaccination in the United Kingdom with a retrospective cohort study using primary healthcare data from the Clinical Practice Research Datalink, a primary care database in the United Kingdom. Relative VE was estimated against general practitioner-diagnosed influenza-like illnesses (GP-ILI) and medically attended acute respiratory illnesses (MAARI) among participants who have been repeatedly vaccinated compared with first-time vaccinees using proportional hazards models. Relative VE against MAARI may be reduced for individuals above 65 years old who were vaccinated in the current and previous influenza seasons for some influenza seasons. However, these findings were not conclusive as we could not exclude the possibility of residual confounding in our dataset. The use of routinely collected data from electronic health records to examine the effects of repeated vaccination needs to be complemented with sufficient efforts to include negative control outcomes to rule out residual confounding.
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Ye B, Shu L, Pang Y, Guo Y, Guo Y, Zong K, Chen C, Zheng X, Zhang J, Liu M, Yuan X, Zhao Y, Zhang D, Wang D, Bao C, Zhang J, Chen L, Gao GF, Liu WJ. Repeated influenza vaccination induces similar immune protection as first-time vaccination but with differing immune responses. Influenza Other Respir Viruses 2022; 17:e13060. [PMID: 36271687 PMCID: PMC9835420 DOI: 10.1111/irv.13060] [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: 06/14/2022] [Revised: 09/21/2022] [Accepted: 09/24/2022] [Indexed: 01/31/2023] Open
Abstract
BACKGROUND Recent seasonal epidemics of influenza have been caused by human influenza A viruses of the H1N1 and H3N2 subtypes and influenza B viruses. Annual vaccination is recommended to prevent infection; however, how annual influenza vaccination influences vaccine effectiveness is largely unknown. METHODS To investigate the impact of repeated vaccination on immune and protective effect, we performed a prospective seroepidemiologic study. Participants with or without prior vaccination (2018-2019) were enrolled during the 2019-2020 influenza season. Inactivated quadrivalent influenza vaccine (IIV4) was administered through the intramuscular route, and venous blood samples were collected regularly to test hemagglutination inhibition (HAI) titers. RESULTS The geometric mean titers and proportion with titers ≥40 against the influenza vaccine components peaked at 30 days post-vaccination. At Day 30, the geometric mean titer and proportion with titers ≥40 in participants who had been previously vaccinated were higher for H3N2 but similar for both B lineages (Victoria and Yamagata) as compared with participants vaccinated for the first time. As for H1N1, the geometric mean titer was lower in repeated vaccinated participants, but the proportion with titers ≥40 was consistent in both groups. CONCLUSIONS Repeated vaccination provides similar or enhanced protection as compared with single vaccination in first-time vaccinees.
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Affiliation(s)
- Beiwei Ye
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and PreventionChinese Center for Disease Control and Prevention (China CDC)BeijingChina
| | - Liumei Shu
- Department of Health CareBeijing Daxing District HospitalBeijingChina
| | - Yuanyuan Pang
- Suzhou Municipal Center for Disease Control and PreventionSuzhouJiangsuChina
| | - Yaxin Guo
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and PreventionChinese Center for Disease Control and Prevention (China CDC)BeijingChina
| | - Yuanyuan Guo
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and PreventionChinese Center for Disease Control and Prevention (China CDC)BeijingChina,Department of Epidemiology, School of Public Health, Cheeloo College of MedicineShandong UniversityJinanShandongChina
| | - Kexin Zong
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and PreventionChinese Center for Disease Control and Prevention (China CDC)BeijingChina
| | - Cong Chen
- Changzhou Center for Disease Control and PreventionChangzhouJiangsuChina
| | - Xianzhi Zheng
- Changzhou Center for Disease Control and PreventionChangzhouJiangsuChina
| | - Jie Zhang
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and PreventionChinese Center for Disease Control and Prevention (China CDC)BeijingChina
| | - Maoshun Liu
- School of Laboratory Medicine and Life SciencesWenzhou Medical UniversityWenzhouZhejiangChina
| | - Xiaoju Yuan
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and PreventionChinese Center for Disease Control and Prevention (China CDC)BeijingChina
| | - Yingze Zhao
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and PreventionChinese Center for Disease Control and Prevention (China CDC)BeijingChina
| | - Danni Zhang
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and PreventionChinese Center for Disease Control and Prevention (China CDC)BeijingChina
| | - Dayan Wang
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and PreventionChinese Center for Disease Control and Prevention (China CDC)BeijingChina
| | - Changjun Bao
- Jiangsu Provincial Center for Disease Control and PreventionNanjingJiangsuChina
| | - Jun Zhang
- Suzhou Municipal Center for Disease Control and PreventionSuzhouJiangsuChina
| | - Liling Chen
- Suzhou Municipal Center for Disease Control and PreventionSuzhouJiangsuChina
| | - George F. Gao
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and PreventionChinese Center for Disease Control and Prevention (China CDC)BeijingChina,School of Laboratory Medicine and Life SciencesWenzhou Medical UniversityWenzhouZhejiangChina,CAS Key Laboratory of Pathogen Microbiology and Immunology, Institute of MicrobiologyChinese Academy of Sciences (CAS)BeijingChina,Research Unit of Adaptive Evolution and Control of Emerging VirusesChinese Academy of Medical SciencesBeijingChina
| | - William J. Liu
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and PreventionChinese Center for Disease Control and Prevention (China CDC)BeijingChina,School of Laboratory Medicine and Life SciencesWenzhou Medical UniversityWenzhouZhejiangChina,Research Unit of Adaptive Evolution and Control of Emerging VirusesChinese Academy of Medical SciencesBeijingChina
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Priming conditions shape breadth of neutralizing antibody responses to sarbecoviruses. Nat Commun 2022; 13:6285. [PMID: 36271047 PMCID: PMC9586968 DOI: 10.1038/s41467-022-34038-6] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Accepted: 10/10/2022] [Indexed: 12/25/2022] Open
Abstract
Vaccines that are broadly cross-protective against current and future SARS-CoV-2 variants of concern (VoC) or across the sarbecoviruses subgenus remain a priority for public health. Virus neutralization is the best available correlate of protection. To define the magnitude and breadth of cross-neutralization in individuals with different exposure to SARS-CoV-2 infection and vaccination, we here use a multiplex surrogate neutralization assay based on virus spike receptor binding domains of multiple SARS-CoV-2 VoC, as well as related bat and pangolin viruses. We include sera from cohorts of individuals vaccinated with two or three doses of mRNA (BNT162b2) or inactivated SARS-CoV-2 (Coronavac or Sinopharm) vaccines with or without a history of previous SARS-CoV-2 or SARS-CoV-1 infection. SARS-CoV-2 or SARS-CoV-1 infection followed by BNT162b2 vaccine, Omicron BA.2 breakthrough infection following BNT162b2 vaccine or a third dose of BNT162b2 following two doses of BNT162b2 or Coronavac elicit the highest and broadest neutralization across VoCs. For both breadth and magnitude of neutralization across all sarbecoviruses, those infected with SARS-CoV-1 immunized with BNT162b2 outperform all other combinations of infection and/or vaccination. These data may inform vaccine design strategies for generating broadly neutralizing antibodies to SARS-CoV-2 variants or across the sarbecovirus subgenus.
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Richard SA, Fairchok M, Coles C, Burgess TH, Colombo RE. Influenza Vaccine Effectiveness: Analysis of the Impact of Repeated Vaccinations in Military Health System Beneficiaries. Open Forum Infect Dis 2022; 9:ofac497. [PMID: 36275868 PMCID: PMC9578161 DOI: 10.1093/ofid/ofac497] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2022] [Accepted: 09/26/2022] [Indexed: 10/01/2023] Open
Abstract
Background Influenza has long burdened the Military Health System (MHS). This study assesses the impact of repeated annual vaccination on influenza vaccine effectiveness (VE). Methods This retrospective, case control study using the test-negative design utilized data extracted from the MHS Data Repository (MDR). Cases had a positive influenza test and controls sought care for an influenza-like illness within 2 weeks of a case, had no positive influenza tests, and were matched by sex, race, age, and location. Vaccine effectiveness was assessed using conditional logistic regression separately for those who received inactivated and live attenuated influenza vaccines (LAIV). Results A total of 6860 cases and controls were identified in the MDR, among whom 53% were vaccinated in all 3 seasons. Among those who received inactivated influenza vaccine during the current season, VE ranged from 26% to 37% (2012/13 [A(H3N2)]: VE 26%, 95% confidence interval [CI] = 1%-45%; 2013/14 [A(H1N1)pdm09]: VE 37%, 95% CI = 18%-52%; 2014/15 [A(H3N2)]: VE 31%, 95% CI = 17%-42%). The VE ranged from 25% to 49% for those only vaccinated this season (2012/13 [A(H3N2)]: VE 38%, 95% CI = -3% to 63%; 2013/14 [A(H1N1)pdm09]: VE 49%, 95% CI = 11%-71%; 2014/15 [A(H3N2)]: VE 25%, 95% CI = -7% to 48%). The VE was more variable in those who received LAIV in the current season. No statistically significant differences in VE were observed between those frequently vaccinated and those vaccinated only during the current season. Conclusions These results underscore the value of annual influenza vaccinations for preventing infection while highlighting the need for continued improvements in influenza vaccine effectiveness.
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Affiliation(s)
- Stephanie A Richard
- Infectious Disease Clinical Research Program, Department of Preventive Medicine and Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, Maryland, USA
- The Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, Maryland, USA
| | - Mary Fairchok
- Mary Bridge Children's Hospital, MultiCare Health System, Tacoma, Washington, USA
| | - Christian Coles
- Infectious Disease Clinical Research Program, Department of Preventive Medicine and Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, Maryland, USA
- The Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, Maryland, USA
| | - Timothy H Burgess
- Infectious Disease Clinical Research Program, Department of Preventive Medicine and Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, Maryland, USA
| | - Rhonda E Colombo
- Infectious Disease Clinical Research Program, Department of Preventive Medicine and Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, Maryland, USA
- The Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, Maryland, USA
- Madigan Army Medical Center, Tacoma, Washington, USA
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35
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MADE: A Computational Tool for Predicting Vaccine Effectiveness for the Influenza A(H3N2) Virus Adapted to Embryonated Eggs. Vaccines (Basel) 2022; 10:vaccines10060907. [PMID: 35746515 PMCID: PMC9227319 DOI: 10.3390/vaccines10060907] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2022] [Revised: 05/29/2022] [Accepted: 05/31/2022] [Indexed: 01/29/2023] Open
Abstract
Seasonal Influenza H3N2 virus poses a great threat to public health, but its vaccine efficacy remains suboptimal. One critical step in influenza vaccine production is the viral passage in embryonated eggs. Recently, the strength of egg passage adaptation was found to be rapidly increasing with time driven by convergent evolution at a set of functionally important codons in the hemagglutinin (HA1). In this study, we aim to take advantage of the negative correlation between egg passage adaptation and vaccine effectiveness (VE) and develop a computational tool for selecting the best candidate vaccine virus (CVV) for vaccine production. Using a probabilistic approach known as mutational mapping, we characterized the pattern of sequence evolution driven by egg passage adaptation and developed a new metric known as the adaptive distance (AD) which measures the overall strength of egg passage adaptation. We found that AD is negatively correlated with the influenza H3N2 vaccine effectiveness (VE) and ~75% of the variability in VE can be explained by AD. Based on these findings, we developed a computational package that can Measure the Adaptive Distance and predict vaccine Effectiveness (MADE). MADE provides a powerful tool for the community to calibrate the effect of egg passage adaptation and select more reliable strains with minimum egg-passaged changes as the seasonal A/H3N2 influenza vaccine.
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36
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Ainslie KEC, Riley S. Is annual vaccination best? A modelling study of influenza vaccination strategies in children. Vaccine 2022; 40:2940-2948. [PMID: 35410816 DOI: 10.1016/j.vaccine.2022.03.065] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2021] [Revised: 03/14/2022] [Accepted: 03/26/2022] [Indexed: 11/23/2022]
Abstract
INTRODUCTION Annual vaccination of children against influenza is a key component of vaccination programs in many countries. However, past infection and vaccination may affect an individual's susceptibility to infection. Little research has evaluated whether annual vaccination is the best strategy. Using the United Kingdom as our motivating example, we developed a framework to assess the impact of different childhood vaccination strategies, specifically annual and biennial (every other year), on attack rate and expected number of infections. METHODS AND FINDINGS We present a multi-annual, individual-based, stochastic, force of infection model that accounts for individual exposure histories and disease/vaccine dynamics influencing susceptibility. We simulate birth cohorts that experience yearly influenza epidemics and follow them until age 18 to determine attack rates and the number of infections during childhood. We perform simulations under baseline conditions, with an assumed vaccination coverage of 44%, to compare annual vaccination to no and biennial vaccination. We relax our baseline assumptions to explore how our model assumptions impact vaccination program performance. At baseline, we observed less than half the number of infections between the ages 2 and 10 under annual vaccination in children who had been vaccinated at least half the time compared to no vaccination. When averaged over all ages 0-18, the number of infections under annual vaccination was 2.07 (2.06, 2.08) compared to 2.63 (2.62, 2.64) under no vaccination, and 2.38 (2.37, 2.40) under biennial vaccination. When we introduced a penalty for repeated exposures, we observed a decrease in the difference in infections between the vaccination strategies. Specifically, the difference in childhood infections under biennial compared to annual vaccination decreased from 0.31 to 0.04 as exposure penalty increased. CONCLUSION Our results indicate that while annual vaccination averts more childhood infections than biennial vaccination, this difference is small. Our work confirms the value of annual vaccination in children, even with modest vaccination coverage, but also shows that similar benefits of vaccination may be obtained by implementing a biennial vaccination program. AUTHOR SUMMARY Many countries include annual vaccination of children against influenza in their vaccination programs. In the United Kingdom (UK), annual vaccination of children aged of 2 to 10 against influenza is recommended. However, little research has evaluated whether annual vaccination is the best strategy, while accounting for how past infection and vaccination may affect an individual's susceptibility to infection in the current influenza season. Prior work has suggested that there may be a negative effect of repeated vaccination. In this work we developed a stochastic, individual-based model to assess the impact of repeated vaccination strategies on childhood infections. Specifically, we first compare annual vaccination to no vaccination and then annual vaccination to biennial (every other year) vaccination. We use the UK as our motivating example. We found that an annual vaccination strategy resulted in the fewest childhood infections, followed by biennial vaccination. The difference in number of childhood infections between the different vaccination strategies decreased when we introduced a penalty for repeated exposures. Our work confirms the value of annual vaccination in children, but also shows that similar benefits of vaccination can be obtained by implementing a biennial vaccination program, particularly when there is a negative effect of repeated vaccinations.
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Affiliation(s)
- Kylie E C Ainslie
- School of Public Health, Imperial College London, London, UK; MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, UK.
| | - Steven Riley
- School of Public Health, Imperial College London, London, UK; MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, UK
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Abstract
Emergency vaccine use requires weighing a large number of uncertain risks and possible benefits. In the COVID-19 pandemic, decisions about what evidence is necessary to authorize emergency use have proven controversial, and vary between countries. We construct a simple mathematical model of the risks and benefits of emergency vaccination to an individual, and apply this to the hypothetical scenario of individual decision-making between emergency use of a COVID-19 vaccine without safety and efficacy data, versus waiting for efficacy and safety to be established. Even with conservative modelling assumptions and uncertainty distributions for vaccine efficacy (mean expectation = 17%) and serious adverse event risk (mean expectation = 0.3%), high risk individuals (e.g. those who are elderly and have a household contact with COVID-19) are better off using the ’emergency vaccine’ rather than waiting for more information (absolute risk reduction for mortality up to 2%). Very early emergency authorization of vaccines despite very limited data may be the better public health strategy when confronted with a dangerous emerging infectious disease.
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38
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Azim Majumder MA, Razzaque MS. Repeated vaccination and 'vaccine exhaustion': relevance to the COVID-19 crisis. Expert Rev Vaccines 2022; 21:1011-1014. [PMID: 35475680 DOI: 10.1080/14760584.2022.2071705] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
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Fox A, Carolan L, Leung V, Phuong HVM, Khvorov A, Auladell M, Tseng YY, Thai PQ, Barr I, Subbarao K, Mai LTQ, van Doorn HR, Sullivan SG. Opposing Effects of Prior Infection versus Prior Vaccination on Vaccine Immunogenicity against Influenza A(H3N2) Viruses. Viruses 2022; 14:v14030470. [PMID: 35336877 PMCID: PMC8949461 DOI: 10.3390/v14030470] [Citation(s) in RCA: 4] [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: 08/23/2021] [Revised: 11/10/2021] [Accepted: 11/28/2021] [Indexed: 02/05/2023] Open
Abstract
Prior vaccination can alternately enhance or attenuate influenza vaccine immunogenicity and effectiveness. Analogously, we found that vaccine immunogenicity was enhanced by prior A(H3N2) virus infection among participants of the Ha Nam Cohort, Viet Nam, but was attenuated by prior vaccination among Australian Health Care Workers (HCWs) vaccinated in the same year. Here, we combined these studies to directly compare antibody titers against 35 A(H3N2) viruses spanning 1968–2018. Participants received licensed inactivated vaccines containing A/HongKong/4801/2014 (H3N2). The analysis was limited to participants aged 18–65 Y, and compared those exposed to A(H3N2) viruses circulating since 2009 by infection (Ha Nam) or vaccination (HCWs) to a reference group who had no recent A(H3N2) infection or vaccination (Ha Nam). Antibody responses were compared by fitting titer/titer-rise landscapes across strains, and by estimating titer ratios to the reference group of 2009–2018 viruses. Pre-vaccination, titers were lowest against 2009–2014 viruses among the reference (no recent exposure) group. Post-vaccination, titers were, on average, two-fold higher among participants with prior infection and two-fold lower among participants with 3–5 prior vaccinations compared to the reference group. Titer rise was negligible among participants with 3–5 prior vaccinations, poor among participants with 1–2 prior vaccinations, and equivalent or better among those with prior infection compared to the reference group. The enhancing effect of prior infection versus the incrementally attenuating effect of prior vaccinations suggests that these exposures may alternately promote and constrain the generation of memory that can be recalled by a new vaccine strain.
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Affiliation(s)
- Annette Fox
- WHO Collaborating Centre for Reference and Research on Influenza, Royal Melbourne Hospital, Peter Doherty Institute for Infection and Immunity, Melbourne, VIC 3000, Australia; (L.C.); (V.L.); (I.B.); (K.S.); (S.G.S.)
- Department of Infectious Diseases, University of Melbourne, Peter Doherty Institute for Infection and Immunity, Melbourne, VIC 3000, Australia; (A.K.); (Y.-Y.T.)
- Correspondence: ; Tel.: +61-393-429-313
| | - Louise Carolan
- WHO Collaborating Centre for Reference and Research on Influenza, Royal Melbourne Hospital, Peter Doherty Institute for Infection and Immunity, Melbourne, VIC 3000, Australia; (L.C.); (V.L.); (I.B.); (K.S.); (S.G.S.)
| | - Vivian Leung
- WHO Collaborating Centre for Reference and Research on Influenza, Royal Melbourne Hospital, Peter Doherty Institute for Infection and Immunity, Melbourne, VIC 3000, Australia; (L.C.); (V.L.); (I.B.); (K.S.); (S.G.S.)
| | - Hoang Vu Mai Phuong
- National Institute of Hygiene and Epidemiology, Ha Noi 100000, Vietnam; (H.V.M.P.); (P.Q.T.); (L.T.Q.M.)
| | - Arseniy Khvorov
- Department of Infectious Diseases, University of Melbourne, Peter Doherty Institute for Infection and Immunity, Melbourne, VIC 3000, Australia; (A.K.); (Y.-Y.T.)
| | - Maria Auladell
- Department of Microbiology and Immunology, Peter Doherty Institute for Infection and Immunity, University of Melbourne, Melbourne, VIC 3000, Australia;
| | - Yeu-Yang Tseng
- Department of Infectious Diseases, University of Melbourne, Peter Doherty Institute for Infection and Immunity, Melbourne, VIC 3000, Australia; (A.K.); (Y.-Y.T.)
| | - Pham Quang Thai
- National Institute of Hygiene and Epidemiology, Ha Noi 100000, Vietnam; (H.V.M.P.); (P.Q.T.); (L.T.Q.M.)
| | - Ian Barr
- WHO Collaborating Centre for Reference and Research on Influenza, Royal Melbourne Hospital, Peter Doherty Institute for Infection and Immunity, Melbourne, VIC 3000, Australia; (L.C.); (V.L.); (I.B.); (K.S.); (S.G.S.)
| | - Kanta Subbarao
- WHO Collaborating Centre for Reference and Research on Influenza, Royal Melbourne Hospital, Peter Doherty Institute for Infection and Immunity, Melbourne, VIC 3000, Australia; (L.C.); (V.L.); (I.B.); (K.S.); (S.G.S.)
- Department of Microbiology and Immunology, Peter Doherty Institute for Infection and Immunity, University of Melbourne, Melbourne, VIC 3000, Australia;
| | - Le Thi Quynh Mai
- National Institute of Hygiene and Epidemiology, Ha Noi 100000, Vietnam; (H.V.M.P.); (P.Q.T.); (L.T.Q.M.)
| | - H. Rogier van Doorn
- Oxford University Clinical Research Unit, Wellcome Africa Asia Programme, National Hospital of Tropical Diseases, Ha Noi 100000, Vietnam;
- Centre of Tropical Medicine and Global Health, Nuffield Department of Clinical Medicine, University of Oxford, Oxford OX3 7LG, UK
| | - Sheena G. Sullivan
- WHO Collaborating Centre for Reference and Research on Influenza, Royal Melbourne Hospital, Peter Doherty Institute for Infection and Immunity, Melbourne, VIC 3000, Australia; (L.C.); (V.L.); (I.B.); (K.S.); (S.G.S.)
- Department of Infectious Diseases, University of Melbourne, Peter Doherty Institute for Infection and Immunity, Melbourne, VIC 3000, Australia; (A.K.); (Y.-Y.T.)
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40
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Affinity maturation for an optimal balance between long-term immune coverage and short-term resource constraints. Proc Natl Acad Sci U S A 2022; 119:2113512119. [PMID: 35177475 PMCID: PMC8872716 DOI: 10.1073/pnas.2113512119] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/07/2022] [Indexed: 12/15/2022] Open
Abstract
Humoral immunity relies on the mutation and selection of B cells to better recognize pathogens. This affinity maturation process produces cells with diverse recognition capabilities. Examining optimal immune strategies that maximize the long-term immune coverage at a minimal metabolic cost, we show when the immune system should mount a de novo response rather than rely on existing memory cells. Our theory recapitulates known modes of the B cell response, predicts the empirical form of the distribution of clone sizes, and rationalizes as a trade-off between metabolic and immune costs the antigenic imprinting effects that limit the efficacy of vaccines (original antigenic sin). Our predictions provide a framework to interpret experimental results that could be used to inform vaccination strategies. In order to target threatening pathogens, the adaptive immune system performs a continuous reorganization of its lymphocyte repertoire. Following an immune challenge, the B cell repertoire can evolve cells of increased specificity for the encountered strain. This process of affinity maturation generates a memory pool whose diversity and size remain difficult to predict. We assume that the immune system follows a strategy that maximizes the long-term immune coverage and minimizes the short-term metabolic costs associated with affinity maturation. This strategy is defined as an optimal decision process on a finite dimensional phenotypic space, where a preexisting population of cells is sequentially challenged with a neutrally evolving strain. We show that the low specificity and high diversity of memory B cells—a key experimental result—can be explained as a strategy to protect against pathogens that evolve fast enough to escape highly potent but narrow memory. This plasticity of the repertoire drives the emergence of distinct regimes for the size and diversity of the memory pool, depending on the density of de novo responding cells and on the mutation rate of the strain. The model predicts power-law distributions of clonotype sizes observed in data and rationalizes antigenic imprinting as a strategy to minimize metabolic costs while keeping good immune protection against future strains.
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41
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Valkenburg SA, Poon LLM. Exploring the landscape of immune responses to influenza infection and vaccination. Nat Med 2022; 28:239-240. [PMID: 35177856 DOI: 10.1038/s41591-021-01656-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Affiliation(s)
- Sophie A Valkenburg
- HKU-Pasteur Research Pole, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
| | - Leo L M Poon
- HKU-Pasteur Research Pole, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China. .,Division of Public Health Laboratory Sciences, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China. .,Centre for Immunology & Infection, Hong Kong Science Park, Hong Kong SAR, China.
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42
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Auladell M, Phuong HVM, Mai LTQ, Tseng YY, Carolan L, Wilks S, Thai PQ, Price D, Duong NT, Hang NLK, Thanh LT, Thuong NTH, Huong TTK, Diep NTN, Bich VTN, Khvorov A, Hensen L, Duong TN, Kedzierska K, Anh DD, Wertheim H, Boyd SD, Good-Jacobson KL, Smith D, Barr I, Sullivan S, van Doorn HR, Fox A. Influenza virus infection history shapes antibody responses to influenza vaccination. Nat Med 2022; 28:363-372. [PMID: 35177857 DOI: 10.1038/s41591-022-01690-w] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2021] [Accepted: 01/10/2022] [Indexed: 02/06/2023]
Abstract
Studies of successive vaccination suggest that immunological memory against past influenza viruses may limit responses to vaccines containing current strains. The impact of memory induced by prior infection is rarely considered and is difficult to ascertain, because infections are often subclinical. This study investigated influenza vaccination among adults from the Ha Nam cohort (Vietnam), who were purposefully selected to include 72 with and 28 without documented influenza A(H3N2) infection during the preceding 9 years (Australian New Zealand Clinical Trials Registry 12621000110886). The primary outcome was the effect of prior influenza A(H3N2) infection on hemagglutinin-inhibiting antibody responses induced by a locally available influenza vaccine administered in November 2016. Baseline and postvaccination sera were titrated against 40 influenza A(H3N2) strains spanning 1968-2018. At each time point (baseline, day 14 and day 280), geometric mean antibody titers against 2008-2018 strains were higher among participants with recent infection (34 (29-40), 187 (154-227) and 86 (72-103)) than among participants without recent infection (19 (17-22), 91 (64-130) and 38 (30-49)). On days 14 and 280, mean titer rises against 2014-2018 strains were 6.1-fold (5.0- to 7.4-fold) and 2.6-fold (2.2- to 3.1-fold) for participants with recent infection versus 4.8-fold (3.5- to 6.7-fold) and 1.9-fold (1.5- to 2.3-fold) for those without. One of 72 vaccinees with recent infection versus 4 of 28 without developed symptomatic A(H3N2) infection in the season after vaccination (P = 0.021). The range of A(H3N2) viruses recognized by vaccine-induced antibodies was associated with the prior infection strain. These results suggest that recall of immunological memory induced by prior infection enhances antibody responses to inactivated influenza vaccine and is important to attain protective antibody titers.
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Affiliation(s)
- Maria Auladell
- Department of Microbiology and Immunology, University of Melbourne, at The Peter Doherty Institute for Infection and Immunity, Melbourne, Victoria, Australia
| | | | | | - Yeu-Yang Tseng
- WHO Collaborating Centre for Reference and Research on Influenza, Royal Melbourne Hospital, at The Peter Doherty Institute for Infection and Immunity, Melbourne, Victoria, Australia.,Department of Infectious Diseases, University of Melbourne, at The Peter Doherty Institute for Infection and Immunity, Melbourne, Victoria, Australia
| | - Louise Carolan
- WHO Collaborating Centre for Reference and Research on Influenza, Royal Melbourne Hospital, at The Peter Doherty Institute for Infection and Immunity, Melbourne, Victoria, Australia
| | - Sam Wilks
- Centre for Pathogen Evolution, Department of Zoology, University of Cambridge, Cambridge, UK
| | - Pham Quang Thai
- National Institute of Hygiene and Epidemiology, Ha Noi, Vietnam
| | - David Price
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Victoria, Australia.,Victorian Infectious Diseases Reference Laboratory Epidemiology Unit and The Peter Doherty Institute for Infection and Immunity, University of Melbourne and Royal Melbourne Hospital, Melbourne, Victoria, Australia
| | | | | | - Le Thi Thanh
- National Institute of Hygiene and Epidemiology, Ha Noi, Vietnam
| | - Nguyen Thi Hong Thuong
- Oxford University Clinical Research Unit, Wellcome Africa Asia Programme, National Hospital of Tropical Diseases, Ha Noi, Vietnam
| | - Tran Thi Kieu Huong
- Oxford University Clinical Research Unit, Wellcome Africa Asia Programme, National Hospital of Tropical Diseases, Ha Noi, Vietnam
| | - Nguyen Thi Ngoc Diep
- Oxford University Clinical Research Unit, Wellcome Africa Asia Programme, National Hospital of Tropical Diseases, Ha Noi, Vietnam
| | - Vu Thi Ngoc Bich
- Oxford University Clinical Research Unit, Wellcome Africa Asia Programme, National Hospital of Tropical Diseases, Ha Noi, Vietnam
| | - Arseniy Khvorov
- WHO Collaborating Centre for Reference and Research on Influenza, Royal Melbourne Hospital, at The Peter Doherty Institute for Infection and Immunity, Melbourne, Victoria, Australia.,Department of Infectious Diseases, University of Melbourne, at The Peter Doherty Institute for Infection and Immunity, Melbourne, Victoria, Australia
| | - Luca Hensen
- Department of Microbiology and Immunology, University of Melbourne, at The Peter Doherty Institute for Infection and Immunity, Melbourne, Victoria, Australia
| | - Tran Nhu Duong
- National Institute of Hygiene and Epidemiology, Ha Noi, Vietnam
| | - Katherine Kedzierska
- Department of Microbiology and Immunology, University of Melbourne, at The Peter Doherty Institute for Infection and Immunity, Melbourne, Victoria, Australia
| | - Dang Duc Anh
- National Institute of Hygiene and Epidemiology, Ha Noi, Vietnam
| | - Heiman Wertheim
- Oxford University Clinical Research Unit, Wellcome Africa Asia Programme, National Hospital of Tropical Diseases, Ha Noi, Vietnam.,Department of Medical Microbiology, Radboudumc Center for Infectious Diseases, Radboudumc, Nijmegen, The Netherlands
| | - Scott D Boyd
- Stanford University Medical Centre, Stanford University, Stanford, CA, USA
| | - Kim L Good-Jacobson
- Department of Biochemistry and Molecular Biology, Monash University, Clayton, Victoria, Australia.,Biomedicine Discovery Institute, Monash University, Clayton, Victoria, Australia
| | - Derek Smith
- Centre for Pathogen Evolution, Department of Zoology, University of Cambridge, Cambridge, UK
| | - Ian Barr
- WHO Collaborating Centre for Reference and Research on Influenza, Royal Melbourne Hospital, at The Peter Doherty Institute for Infection and Immunity, Melbourne, Victoria, Australia
| | - Sheena Sullivan
- WHO Collaborating Centre for Reference and Research on Influenza, Royal Melbourne Hospital, at The Peter Doherty Institute for Infection and Immunity, Melbourne, Victoria, Australia.,Department of Infectious Diseases, University of Melbourne, at The Peter Doherty Institute for Infection and Immunity, Melbourne, Victoria, Australia
| | - H Rogier van Doorn
- Oxford University Clinical Research Unit, Wellcome Africa Asia Programme, National Hospital of Tropical Diseases, Ha Noi, Vietnam.,Centre of Tropical Medicine and Global Health, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, UK
| | - Annette Fox
- Department of Microbiology and Immunology, University of Melbourne, at The Peter Doherty Institute for Infection and Immunity, Melbourne, Victoria, Australia. .,WHO Collaborating Centre for Reference and Research on Influenza, Royal Melbourne Hospital, at The Peter Doherty Institute for Infection and Immunity, Melbourne, Victoria, Australia. .,Department of Infectious Diseases, University of Melbourne, at The Peter Doherty Institute for Infection and Immunity, Melbourne, Victoria, Australia.
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43
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Wen FT, Malani A, Cobey S. The Potential Beneficial Effects of Vaccination on Antigenically Evolving Pathogens. Am Nat 2022; 199:223-237. [DOI: 10.1086/717410] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Affiliation(s)
- Frank T. Wen
- Department of Ecology and Evolution, University of Chicago, Chicago, Illinois 60637
| | - Anup Malani
- Department of Ecology and Evolution, University of Chicago, Chicago, Illinois 60637
- University of Chicago Law School, Chicago, Illinois 60637; and University of Chicago Pritzker School of Medicine, Chicago, Illinois 60637
| | - Sarah Cobey
- Department of Ecology and Evolution, University of Chicago, Chicago, Illinois 60637
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Park BR, Subbiah J, Kim KH, Kwon YM, Oh J, Kim MC, Shin CH, Seong BL, Kang SM. Enhanced cross protection by hetero prime-boost vaccination with recombinant influenza viruses containing chimeric hemagglutinin-M2e epitopes. Virology 2021; 566:143-152. [PMID: 34929590 DOI: 10.1016/j.virol.2021.12.003] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2021] [Revised: 12/06/2021] [Accepted: 12/08/2021] [Indexed: 11/29/2022]
Abstract
Annual repeat influenza vaccination raises concerns about protective efficacy against mismatched viruses. We investigated the impact of heterologous prime-boost vaccination on inducing cross protection by designing recombinant influenza viruses with chimeric hemagglutinin (HA) carrying M2 extracellular domains (M2e-HA). Heterologous prime-boost vaccination of C57BL/6 mice with M2e-HA chimeric virus more effectively induced M2e and HA stalk specific IgG antibodies correlating with cross protection than homologous prime-boost vaccination. Induction of M2e and HA stalk specific IgG antibodies was compromised in 1-year old mice, indicating significant aging effects on priming subdominant M2e and HA stalk IgG antibody responses. This study demonstrates that a heterologous prime-boost strategy with recombinant influenza virus expressing extra M2e epitopes provides more effective cross protection than homologous vaccination.
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Affiliation(s)
- Bo Ryoung Park
- Institute for Biomedical Sciences, Georgia State University, Atlanta, GA, 30303, USA
| | - Jeeva Subbiah
- Institute for Biomedical Sciences, Georgia State University, Atlanta, GA, 30303, USA
| | - Ki-Hye Kim
- Institute for Biomedical Sciences, Georgia State University, Atlanta, GA, 30303, USA
| | - Young-Man Kwon
- Institute for Biomedical Sciences, Georgia State University, Atlanta, GA, 30303, USA
| | - Judy Oh
- Institute for Biomedical Sciences, Georgia State University, Atlanta, GA, 30303, USA
| | - Min-Chul Kim
- Institute for Biomedical Sciences, Georgia State University, Atlanta, GA, 30303, USA; CARESIDE Co., Ltd., Seongnam, Gyeonggi-do, Republic of Korea
| | - Chong-Hyun Shin
- Institute for Biomedical Sciences, Georgia State University, Atlanta, GA, 30303, USA
| | - Baik Lin Seong
- Department of Microbiology, College of Medicine, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Republic of Korea; Vaccine Innovative Technology ALliance (VITAL)-Korea, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Republic of Korea
| | - Sang-Moo Kang
- Institute for Biomedical Sciences, Georgia State University, Atlanta, GA, 30303, USA.
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45
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Rijkers GT, van Overveld FJ. The "original antigenic sin" and its relevance for SARS-CoV-2 (COVID-19) vaccination. CLINICAL IMMUNOLOGY COMMUNICATIONS 2021; 1:13-16. [PMID: 38620690 PMCID: PMC8500682 DOI: 10.1016/j.clicom.2021.10.001] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/04/2021] [Accepted: 10/04/2021] [Indexed: 04/14/2023]
Abstract
Imprinting of the specific molecular image of a given protein antigen into immunological memory is one of the hallmarks of immunity. A later contact with a related, but different antigen should not trigger the memory response (because the produced antibodies would not be effective). The preferential expansion of cross-reactive antibodies, or T-lymphocytes for that matter, by a related antigen has been termed the original antigenic sin and was first described by Thomas Francis Jr. in 1960. The phenomenon was initially described for influenza virus, but also has been found for dengue and rotavirus. The antibody dependent enhancement observed in feline coronavirus vaccination also may be related to the original antigenic sin. For a full interpretation of the effectivity of the immune response against SARS-CoV-2, as well as for the success of vaccination, the role of existing immunological memory against circulating corona viruses is reviewed and analyzed.
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Affiliation(s)
- Ger T Rijkers
- Science Department, University College Roosevelt, Middelburg, the Netherlands
- Microvida Laboratory of Medical Microbiology and Immunology, St. Elizabeth Hospital, Tilburg, the Netherlands
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46
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Jang H, Ross TM. Influence of the H1N1 influenza pandemic on the humoral immune response to seasonal flu vaccines. PLoS One 2021; 16:e0258453. [PMID: 34679115 PMCID: PMC8535392 DOI: 10.1371/journal.pone.0258453] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2021] [Accepted: 09/27/2021] [Indexed: 11/18/2022] Open
Abstract
In this study, we hypothesized that the humoral response to trivalent seasonal influenza virus vaccines was influenced by rapid antigenic switching of H1 HA. We tested archived sera and peripheral blood mononuclear cells (PBMC) collected at prior to vaccination at day 0, as well as days 30 and 90 after vaccination during the 2009/2010 and 2010/2011 influenza virus seasons. During the 2009/2010 season, vaccination successfully induced antibodies with hemagglutinin inhibition (HAI) activity against both H1N1 and H3N2 vaccine components. For the 2010/2011 season, the A/California/04/2009 (CA/09) H1N1 elicited seroconversion (HAI titer = 1:40) and novel memory B cell (Bmem) responses from most individuals. However, the H3N2 influenza virus component of the vaccine, A/Perth/16/2009 (Perth/09), back-boosted and elicited antibodies with HAI activity and Bmem response to historical H3N2 influenza virus strains. Following stratification of the pre-existing antibody with HAI against the CA/09 H1N1, there was a negative correlation with HAI seroconversion to other vaccine strains. Overall, strong immune responses against CA/09 H1N1 influenza virus negatively influenced the induction of novel humoral responses.
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Affiliation(s)
- Hyesun Jang
- Center for Vaccines and Immunology, University of Georgia, Athens, Georgia, United States of America
- Department of Infectious Diseases, University of Georgia, Athens, Georgia, United States of America
| | - Ted M. Ross
- Center for Vaccines and Immunology, University of Georgia, Athens, Georgia, United States of America
- Department of Infectious Diseases, University of Georgia, Athens, Georgia, United States of America
- * E-mail:
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47
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Lemke MM, McLean MR, Lee CY, Lopez E, Bozich ER, Rerks-Ngarm S, Pitisuttithum P, Nitayaphan S, Kratochvil S, Wines BD, Hogarth PM, Kent SJ, Chung AW, Arnold KB. A systems approach to elucidate personalized mechanistic complexities of antibody-Fc receptor activation post-vaccination. CELL REPORTS MEDICINE 2021; 2:100386. [PMID: 34622227 PMCID: PMC8484512 DOI: 10.1016/j.xcrm.2021.100386] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/11/2021] [Revised: 06/16/2021] [Accepted: 08/11/2021] [Indexed: 11/25/2022]
Abstract
Immunoglobulin G (IgG) antibodies that activate Fc-mediated immune functions have been correlated with vaccine efficacy, but it is difficult to unravel the relative roles of multiple IgG and Fc receptor (FcR) features that have the capacity to influence IgG-FcR complex formation but vary on a personalized basis. Here, we develop an ordinary differential-equation model to determine how personalized variability in IgG subclass concentrations and binding affinities influence IgG-FcγRIIIa complex formation and validate it with samples from the HIV RV144 vaccine trial. The model identifies individuals who are sensitive, insensitive, or negatively affected by increases in HIV-specific IgG1, which is validated with the addition of HIV-specific IgG1 monoclonal antibodies to vaccine samples. IgG1 affinity to FcγRIIIa is also prioritized as the most influential parameter for dictating activation broadly across a population. Overall, this work presents a quantitative tool for evaluating personalized differences underlying FcR activation, which is relevant to ongoing efforts to improve vaccine efficacy. Fc-mediated immune functions have been correlated with protection in HIV vaccine trials A model reveals personalized mechanisms that drive variation in FcγR activation The model predicts individuals who are sensitive to changes in IgG1 concentration IgG1 affinity to FcγR best dictates activation across a heterogeneous population
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Affiliation(s)
- Melissa M Lemke
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA
| | - Milla R McLean
- Department of Microbiology and Immunology, The University of Melbourne, at the Peter Doherty Institute for Infection and Immunity, Melbourne, VIC, Australia
| | - Christina Y Lee
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA
| | - Ester Lopez
- Department of Microbiology and Immunology, The University of Melbourne, at the Peter Doherty Institute for Infection and Immunity, Melbourne, VIC, Australia
| | - Emily R Bozich
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA
| | | | - Punnee Pitisuttithum
- Vaccine Trial Centre, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand
| | | | - Sven Kratochvil
- The Ragon Institute of Massachusetts General Hospital, Massachusetts Institute of Technology and Harvard University, Cambridge, MA, USA
| | - Bruce D Wines
- Immune Therapies Group, Burnet Institute, Melbourne, VIC, Australia.,Department of Immunology and Pathology, Monash University, Melbourne, VIC, Australia.,Department of Clinical Pathology, The University of Melbourne, Melbourne, VIC, Australia
| | - P Mark Hogarth
- Immune Therapies Group, Burnet Institute, Melbourne, VIC, Australia.,Department of Immunology and Pathology, Monash University, Melbourne, VIC, Australia.,Department of Clinical Pathology, The University of Melbourne, Melbourne, VIC, Australia
| | - Stephen J Kent
- Department of Microbiology and Immunology, The University of Melbourne, at the Peter Doherty Institute for Infection and Immunity, Melbourne, VIC, Australia.,ARC Centre of Excellence in Convergent Bio-Nano Science and Technology, The University of Melbourne, Melbourne, VIC, Australia.,Melbourne Sexual Health Centre, Alfred Hospital, Monash University Central Clinical School, Carlton, VIC, Australia
| | - Amy W Chung
- Department of Microbiology and Immunology, The University of Melbourne, at the Peter Doherty Institute for Infection and Immunity, Melbourne, VIC, Australia
| | - Kelly B Arnold
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA
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48
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Claudino Formiga FF, Silva CA, Pedrosa TDN, Aikawa NE, Pasoto SG, Garcia CC, Capão ASV, Martins VADO, Proença ACTD, Fuller R, Yuki EFN, Vendramini MBG, Rosário DCD, Brandão LMKR, Sartori AMC, Antonangelo L, Bonfá E, Borba EF. Influenza A/Singapore (H3N2) component vaccine in systemic lupus erythematosus: A distinct pattern of immunogenicity. Lupus 2021; 30:1915-1922. [PMID: 34459317 DOI: 10.1177/09612033211040371] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
INTRODUCTION Influenza A (H3N2) virus is the most important cause of seasonal influenza morbidity and mortality in the last 50 years, surpassing the impact of H1N1. Data assessing immunogenicity and safety of this virus component are lacking in systemic lupus erythematosus (SLE) and restricted to small reports with other H3N2 strains. OBJECTIVE This study aims to evaluate short-term immunogenicity and safety of influenza A/Singapore (H3N2) vaccine in SLE. METHODS 81 consecutive SLE patients and 81 age- and sex-matched healthy controls (HC) were vaccinated with the influenza A/Singapore/INFIMH-16-0019/2016(H3N2)-like virus. Seroprotection (SP) and seroconversion (SC) rates, geometric mean titers(GMT), and factor increase in GMT(FI-GMT) and adverse events were assessed before and 4 weeks post-vaccination. Disease activity and therapies were also evaluated. RESULTS Before immunization, SLE and HC groups had high SP rates (89% vs 77%, p = 0.061) and elevated GMT titer with higher levels in SLE (129.1(104.1-154.1) vs 54.8(45.0-64.6), p < 0.001). Frequency of two previous years' influenza vaccination was high and comparable in SLE and HC (89% vs 90%, p = 1.000). Four weeks post-vaccination, median GMT increased for both groups and remained higher in SLE compared to HC (239.9(189.5-290.4) vs 94.5(72.6-116.4), p < 0.0001) with a comparable FI-GMT (2.3(1.8-2.9) vs 1.9(1.5-2.3), p = 0.051). SC rates were low and comparable for both groups (16% vs 11%, respectively, p = 0.974). Disease activity scores remained stable throughout the study (p = 1.000) and severe adverse events were not identified. CONCLUSION Influenza A/Singapore (H3N2) vaccine has an adequate safety profile. The distinct immunogenicity pattern from other influenza A components characterized by a remarkably high pre- and post-vaccination SP rate and high GMT levels may be associated with previous influenza A vaccination. (www.clinicaltrials.gov, NCT03540823).
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Affiliation(s)
| | - Clovis Artur Silva
- Pediatric Rheumatology Unit, Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, Brazil
| | - Tatiana do Nascimento Pedrosa
- Rheumatology Division, Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, Brazil
| | - Nadia Emi Aikawa
- Pediatric Rheumatology Unit, Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, Brazil
| | - Sandra Gofinet Pasoto
- Rheumatology Division, Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, Brazil
| | - Cristiana Couto Garcia
- Laboratory of Respiratory Virus and Measles, Instituto Oswaldo Cruz, FIOCRUZ, Rio de Janeiro, Brazil
| | - Artur Silva Vidal Capão
- Laboratory of Respiratory Virus and Measles, Instituto Oswaldo Cruz, FIOCRUZ, Rio de Janeiro, Brazil
| | | | - Adriana Coracini Tonacio de Proença
- Department of Infectious and Parasitic Diseases, Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, Brazil
| | - Ricardo Fuller
- Rheumatology Division, Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, Brazil
| | - Emily Figueiredo Neves Yuki
- Rheumatology Division, Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, Brazil
| | | | - Debora Cordeiro do Rosário
- Rheumatology Division, Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, Brazil
| | | | - Ana Marli Christovam Sartori
- Department of Infectious and Parasitic Diseases, Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, Brazil
| | - Leila Antonangelo
- Clinical Laboratory Division - Department of Pathology, Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, Brazil
| | - Eloisa Bonfá
- Rheumatology Division, Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, Brazil
| | - Eduardo Ferreira Borba
- Rheumatology Division, Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, Brazil
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49
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Kim SS, Flannery B, Foppa IM, Chung JR, Nowalk MP, Zimmerman RK, Gaglani M, Monto AS, Martin ET, Belongia EA, McLean HQ, Jackson ML, Jackson LA, Patel M. Effects of Prior Season Vaccination on Current Season Vaccine Effectiveness in the United States Flu Vaccine Effectiveness Network, 2012-2013 Through 2017-2018. Clin Infect Dis 2021; 73:497-505. [PMID: 32505128 DOI: 10.1093/cid/ciaa706] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2020] [Accepted: 06/01/2020] [Indexed: 01/08/2023] Open
Abstract
BACKGROUND We compared effects of prior vaccination and added or lost protection from current season vaccination among those previously vaccinated. METHODS Our analysis included data from the US Flu Vaccine Effectiveness Network among participants ≥9 years old with acute respiratory illness from 2012-2013 through 2017-2018. Vaccine protection was estimated using multivariate logistic regression with an interaction term for effect of prior season vaccination on current season vaccine effectiveness. Models were adjusted for age, calendar time, high-risk status, site, and season for combined estimates. We estimated protection by combinations of current and prior vaccination compared to unvaccinated in both seasons or current vaccination among prior vaccinated. RESULTS A total of 31 819 participants were included. Vaccine protection against any influenza averaged 42% (95% confidence interval [CI], 38%-47%) among those vaccinated only the current season, 37% (95% CI, 33-40) among those vaccinated both seasons, and 26% (95% CI, 18%-32%) among those vaccinated only the prior season, compared with participants vaccinated neither season. Current season vaccination reduced the odds of any influenza among patients unvaccinated the prior season by 42% (95% CI, 37%-46%), including 57%, 27%, and 55% against A(H1N1), A(H3N2), and influenza B, respectively. Among participants vaccinated the prior season, current season vaccination further reduced the odds of any influenza by 15% (95% CI, 7%-23%), including 29% against A(H1N1) and 26% against B viruses, but not against A(H3N2). CONCLUSIONS Our findings support Advisory Committee on Immunization Practices recommendations for annual influenza vaccination. Benefits of current season vaccination varied among participants with and without prior season vaccination, by virus type/subtype and season.
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Affiliation(s)
- Sara S Kim
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA.,Oak Ridge Institute for Science and Education, Oak Ridge, Tennessee, USA
| | - Brendan Flannery
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Ivo M Foppa
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Jessie R Chung
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Mary Patricia Nowalk
- University of Pittsburgh Schools of the Health Sciences, Pittsburgh, Pennsylvania, USA
| | - Richard K Zimmerman
- University of Pittsburgh Schools of the Health Sciences, Pittsburgh, Pennsylvania, USA
| | - Manjusha Gaglani
- Baylor Scott and White Health, Texas A&M University College of Medicine, Temple, Texas, USA
| | - Arnold S Monto
- University of Michigan School of Public Health, Ann Arbor, Michigan, USA
| | - Emily T Martin
- University of Michigan School of Public Health, Ann Arbor, Michigan, USA
| | | | - Huong Q McLean
- Marshfield Clinical Research Institute, Marshfield, Wisconsin, USA
| | - Michael L Jackson
- Kaiser Permanente Washington Health Research Institute, Seattle, Washington, USA
| | - Lisa A Jackson
- Kaiser Permanente Washington Health Research Institute, Seattle, Washington, USA
| | - Manish Patel
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
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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 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] [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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