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      Low 2012–13 Influenza Vaccine Effectiveness Associated with Mutation in the Egg-Adapted H3N2 Vaccine Strain Not Antigenic Drift in Circulating Viruses

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          Abstract

          Background

          Influenza vaccine effectiveness (VE) is generally interpreted in the context of vaccine match/mismatch to circulating strains with evolutionary drift in the latter invoked to explain reduced protection. During the 2012–13 season, however, detailed genotypic and phenotypic characterization shows that low VE was instead related to mutations in the egg-adapted H3N2 vaccine strain rather than antigenic drift in circulating viruses.

          Methods/Findings

          Component-specific VE against medically-attended, PCR-confirmed influenza was estimated in Canada by test-negative case-control design. Influenza A viruses were characterized genotypically by amino acid (AA) sequencing of established haemagglutinin (HA) antigenic sites and phenotypically through haemagglutination inhibition (HI) assay. H3N2 viruses were characterized in relation to the WHO-recommended, cell-passaged vaccine prototype (A/Victoria/361/2011) as well as the egg-adapted strain as per actually used in vaccine production. Among the total of 1501 participants, influenza virus was detected in 652 (43%). Nearly two-thirds of viruses typed/subtyped were A(H3N2) (394/626; 63%); the remainder were A(H1N1)pdm09 (79/626; 13%), B/Yamagata (98/626; 16%) or B/Victoria (54/626; 9%). Suboptimal VE of 50% (95%CI: 33–63%) overall was driven by predominant H3N2 activity for which VE was 41% (95%CI: 17–59%). All H3N2 field isolates were HI-characterized as well-matched to the WHO-recommended A/Victoria/361/2011 prototype whereas all but one were antigenically distinct from the egg-adapted strain as per actually used in vaccine production. The egg-adapted strain was itself antigenically distinct from the WHO-recommended prototype, and bore three AA mutations at antigenic sites B [H156Q, G186V] and D [S219Y]. Conversely, circulating viruses were identical to the WHO-recommended prototype at these positions with other genetic variation that did not affect antigenicity. VE was 59% (95%CI:16–80%) against A(H1N1)pdm09, 67% (95%CI: 30–85%) against B/Yamagata (vaccine-lineage) and 75% (95%CI: 29–91%) against B/Victoria (non-vaccine-lineage) viruses.

          Conclusions

          These findings underscore the need to monitor vaccine viruses as well as circulating strains to explain vaccine performance. Evolutionary drift in circulating viruses cannot be regulated, but influential mutations introduced as part of egg-based vaccine production may be amenable to improvements.

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          Most cited references27

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          Comparing influenza vaccine efficacy against mismatched and matched strains: a systematic review and meta-analysis

          Background Influenza vaccines are most effective when the antigens in the vaccine match those of circulating strains. However, antigens contained in the vaccines do not always match circulating strains. In the present work we aimed to examine the vaccine efficacy (VE) afforded by influenza vaccines when they are not well matched to circulating strains. Methods We identified randomized clinical trials (RCTs) through MEDLINE, EMBASE, the Cochrane Library, and references of included RCTs. RCTs reporting laboratory-confirmed influenza among healthy participants vaccinated with antigens of matching and non-matching influenza strains were included. Two independent reviewers screened citations/full-text articles, abstracted data, and appraised risk of bias. Conflicts were resolved by discussion. A random effects meta-analysis was conducted. VE was calculated using the following formula: (1 - relative risk × 100%). Results We included 34 RCTs, providing data on 47 influenza seasons and 94,821 participants. The live-attenuated influenza vaccine (LAIV) showed significant protection against mismatched (six RCTs, VE 54%, 95% confidence interval (CI) 28% to 71%) and matched (seven RCTs, VE 83%, 95% CI 75% to 88%) influenza strains among children aged 6 to 36 months. Differences were observed between the point estimates for mismatched influenza A (five RCTs, VE 75%, 95% CI 41% to 90%) and mismatched influenza B (five RCTs, VE 42%, 95% CI 22% to 56%) estimates among children aged 6 to 36 months. The trivalent inactivated vaccine (TIV) also afforded significant protection against mismatched (nine RCTs, VE 52%, 95% CI 37% to 63%) and matched (eight RCTs, VE 65%, 95% CI 54% to 73%) influenza strains among adults. Numerical differences were observed between the point estimates for mismatched influenza A (five RCTs, VE 64%, 95% CI 23% to 82%) and mismatched influenza B (eight RCTs, VE 52%, 95% CI 19% to 72%) estimates among adults. Statistical heterogeneity was low (I2 <50%) across all meta-analyses, except for the LAIV meta-analyses among children (I2 = 79%). Conclusions The TIV and LAIV vaccines can provide cross protection against non-matching circulating strains. The point estimates for VE were different for matching versus non-matching strains, with overlapping CIs.
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            Methodologic issues regarding the use of three observational study designs to assess influenza vaccine effectiveness.

            Influenza causes substantial morbidity and annual vaccination is the most important prevention strategy. Accurately measuring vaccine effectiveness (VE) is difficult. The clinical syndrome most closely associated with influenza virus infection, influenza-like illness (ILI), is not specific. In addition, laboratory confirmation is infrequently done, and available rapid diagnostic tests are imperfect. The objective of this study was to estimate the joint impact of rapid diagnostic test sensitivity and specificity on VE for three types of study designs: a cohort study, a traditional case-control study, and a case-control study that used as controls individuals with ILI who tested negative for influenza virus infection. We developed a mathematical model with five input parameters: true VE, attack rates (ARs) of influenza-ILI and non-influenza-ILI and the sensitivity and specificity of the diagnostic test. With imperfect specificity, estimates from all three designs tended to underestimate true VE, but were similar except if fairly extreme inputs were used. Only if test specificity was 95% or more or if influenza attack rates doubled that of background illness did the case-control method slightly overestimate VE. The case-control method usually produced the highest and most accurate estimates, followed by the test-negative design. The bias toward underestimating true VE introduced by low test specificity increased as the AR of influenza- relative to non-influenza-ILI decreases and, to a lesser degree, with lower test sensitivity. Demonstration of a high influenza VE using tests with imperfect sensitivity and specificity should provide reassurance that the program has been effective in reducing influenza illnesses, assuming adequate control of confounding factors.
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              Serologic assays for influenza surveillance, diagnosis and vaccine evaluation.

              Serological techniques play a critical role in various aspects of influenza surveillance, vaccine development and evaluation, and sometimes in diagnosis, particularly for novel influenza virus infections of humans. Because individuals are repeatedly exposed to antigenically and genetically diverse influenza viruses over a lifetime, the gold standard for detection of a recent influenza virus infection or response to current vaccination is the demonstration of a seroconversion, a fourfold or greater rise in antibody titer relative to a baseline sample, to a circulating influenza strain or vaccine component. The hemagglutination-inhibition assay remains the most widely used assay to detect strain-specific serum antibodies to influenza. The hemagglutination-inhibition assay is also used to monitor antigenic changes among influenza viruses which are constantly evolving; such antigenic data is essential for consideration of changes in influenza vaccine composition. The use of the hemagglutinin-specific microneutralization assay has increased, in part, owing to its sensitivity for detection of human antibodies to novel influenza viruses of animal origin. Neutralization assays using replication-incompetent pseudotyped particles may be advantageous in some laboratory settings for detection of antibodies to influenza viruses with heightened biocontainment requirements. The use of standardized protocols and antibody standards are important steps to improve reproducibility and interlaboratory comparability of results of serologic assays for influenza viruses.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2014
                25 March 2014
                : 9
                : 3
                : e92153
                Affiliations
                [1 ]Communicable Disease Prevention and Control Service, British Columbia Centre for Disease Control, Vancouver, British Columbia, Canada
                [2 ]School of Population and Public Health, University of British Columbia, Vancouver, British Columbia, Canada
                [3 ]Clinical Prevention Services, British Columbia Centre for Disease Control, Vancouver, British Columbia, Canada
                [4 ]Department of Biological and Occupational Risks, Institut National de Santé Publique du Québec, Québec (Québec), Canada
                [5 ]Department of Social and Preventive Medicine, Laval University, Québec (Québec), Canada
                [6 ]Department of Molecular Research, Public Health Ontario, Toronto, Ontario, Canada
                [7 ]Family Medicine and Community Health Sciences, University of Calgary, Calgary, Alberta, Canada
                [8 ]Department of Virology, Provincial Laboratory of Public Health, Calgary, Alberta, Canada
                [9 ]Department of Microbiology, Immunology and Infectious Diseases, University of Calgary, Calgary, Alberta, Canada
                [10 ]Communicable Disease Prevention and Control, Public Health Ontario, Toronto, Ontario, Canada
                [11 ]Department of Microbiology, Public Health Ontario, Toronto, Ontario, Canada
                [12 ]Department of Laboratory Medicine and Pathobiology and Department of Paediatrics, University of Toronto, Toronto, Ontario, Canada
                [13 ]Department of Paediatrics, The Hospital for Sick Children, Toronto, Ontario, Canada
                [14 ]Laboratoire de Santé Publique du Québec, Institut National de Santé Publique du Québec, Sainte-Anne-de-Bellevue, Québec, Canada
                [15 ]Département De Microbiologie, Infectiologie et Immunologie, Faculté de médecine, Université de Montréal, Montréal, Québec, Canada
                [16 ]Influenza and Respiratory Virus Section, National Microbiology Laboratory, Winnipeg, Manitoba, Canada
                [17 ]Community Health Sciences and Pharmacy, University of Manitoba, Winnipeg, Manitoba, Canada
                [18 ]Cadham Provincial Laboratory, Manitoba Health, Winnipeg, Manitoba, Canada
                [19 ]Department of Medical Microbiology, University of Manitoba, Winnipeg, Manitoba, Canada
                Public Health Agency of Canada, Canada
                Author notes

                Competing Interests: Within 36 months of manuscript submission, GDS received research grants from GlaxoSmithKline (GSK) and Sanofi Pasteur for unrelated vaccine studies and travel fee reimbursement to attend an ad hoc GSK Advisory Board, without honorarium. JBG has received research grants from GSK and Hoffmann-LaRoche for antiviral resistance studies. MK has received research grants from Roche, Merck, Gen-Probe and Siemens. SMM has received research grants from GSK, Sanofi Pasteur and Pfizer. SMM is a Canada Research Chair in Pharmaco-epidemiology and Vaccine Evaluation; and the Great-West Life, London Life and Canada Life Junior Investigator of the Canadian Cancer Society [grant # 2011-700644]. SS and TLK are funded by the Canadian Institutes of Health Research Grant (TPA-90193). The other authors declare that they have no competing interests to report. This does not alter adherence to all PLOS policies on sharing data and materials.

                Conceived and designed the experiments: DMS GDS JAD MP. Performed the experiments: SS AE KF JBG HC NB PVC MK MP YL. Analyzed the data: NZJ DMS GDS SS AE KF JBG HC NB PVC MK MP YL. Wrote the paper: DMS NZJ GDS SS AE JAD KF ALW JBG MK MP HC NB TLK SMM PVC YL. Data collection: DMS NZJ GDS JAD ALW SMM TLK. Literature search: TLK.

                Article
                PONE-D-13-54409
                10.1371/journal.pone.0092153
                3965421
                24667168
                63dc7e20-feee-4b1f-9b88-0da93eb78888
                Copyright @ 2014

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 29 December 2013
                : 17 February 2014
                Page count
                Pages: 15
                Funding
                Funding was provided by the Canadian Institutes of Health Research (CIHR) – Institute of Infection and Immunity, grant TPA-90193 ( http://www.cihr-irsc.gc.ca/), as well as Ministries of Health and Institutes of the investigators. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. This does not alter adherence to all PLOS policies on sharing data and materials.
                Categories
                Research Article
                Biology and Life Sciences
                Immunology
                Vaccination and Immunization
                Medicine and Health Sciences
                Epidemiology
                Infectious Disease Epidemiology
                Infectious Diseases
                Viral Diseases
                Influenza
                Public and Occupational Health

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                Uncategorized

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