scholarly journals Timescales of influenza A/H3N2 antibody dynamics

2017 ◽  
Author(s):  
Adam J. Kucharski ◽  
Justin Lessler ◽  
Derek A.T. Cummings ◽  
Steven Riley
Keyword(s):  
Immune Responses ◽  
Influenza A ◽  
Southern China ◽  
Influenza Infection ◽  
Recent Infection ◽  
Cross Sectional ◽  
Multiple Timescales ◽  
Serological Data ◽  
Antibody Dynamics ◽  
Reactive Antibody

AbstractHuman immunity influences the evolution and impact of novel influenza strains. Because individuals are infected with multiple influenza strains during their lifetime and each virus can generate a cross-reactive antibody response, it is challenging to quantify the processes that shape observed immune responses, or to reliably detect recent infection from serological samples. Using a Bayesian model of antibody dynamics at multiple timescales, we explain complex cross-reactive antibody landscapes by inferring participants’ histories of infection with serological data from cross-sectional and longitudinal studies of influenza A/H3N2 in southern China and Vietnam. We show an individual’s influenza antibody profile can be explained by a short-lived, broadly cross-reactive response that decays within a year to leave a smaller long-term response acting against a narrower range of strains. We also demonstrate that accounting for dynamic immune responses can provide a more accurate alternative to traditional definitions seroconversion for the estimation of infection attack rates. Our work provides a general model for explaining mechanisms of influenza immunity acting at multiple timescales based on contemporary serological data, and suggests a two-armed immune response to influenza infection consistent with competitive dynamics between B cell populations. This approach to analysing multiple timescales for antigenic responses could also be applied to other multi-strain pathogens such as dengue and related flaviviruses.

scholarly journals Estimation of Seasonal Influenza Attack Rates and Antibody Dynamics in Children Using Cross-Sectional Serological Data

2020 ◽  
Author(s):  
Amanda Minter ◽  
Katja Hoschler ◽  
Ya Jankey Jagne ◽  
Hadijatou Sallah ◽  
Edwin Armitage ◽  
...  
Keyword(s):  
Bayesian Model ◽  
Influenza A ◽  
Seasonal Influenza ◽  
Serum Antibody ◽  
Antibody Responses ◽  
Sub Saharan Africa ◽  
Cross Sectional ◽  
Sub Saharan ◽  
Serological Data ◽  
Antibody Dynamics

Abstract Directly measuring evidence of influenza infections is difficult, especially in low-surveillance settings such as sub-Saharan Africa. Using a Bayesian model, we estimated unobserved infection times and underlying antibody responses to influenza A/H3N2, using cross-sectional serum antibody responses to 4 strains in children aged 24–60 months. Among the 242 individuals, we estimated a variable seasonal attack rate and found that most children had ≥1 infection before 2 years of age. Our results are consistent with previously published high attack rates in children. The modeling approach highlights how cross-sectional serological data can be used to estimate epidemiological dynamics.

scholarly journals Long-Lasting Mucosal and Systemic Immunity against Influenza A Virus Is Significantly Prolonged and Protective by Nasal Whole Influenza Immunization with Mucosal Adjuvant N3 and DNA-Plasmid Expressing Flagellin in Aging In- and Outbred Mice

Vaccines ◽  
2019 ◽  
Vol 7 (3) ◽  
pp. 64 ◽  
Author(s):  
Jorma Hinkula ◽  
Sanna Nyström ◽  
Claudia Devito ◽  
Andreas Bråve ◽  
Steven E. Applequist
Keyword(s):  
Immune Responses ◽  
Influenza A Virus ◽  
Influenza A ◽  
Influenza Infection ◽  
Inbred Mouse ◽  
Herd Immunity ◽  
Serum Antibody ◽  
Mouse Strains ◽  
Virus Challenge ◽  
Influenza A H1n1

Background: Vaccination is commonly used to prevent and control influenza infection in humans. However, improvements in the ease of delivery and strength of immunogenicity could markedly improve herd immunity. The aim of this pre-clinical study is to test the potential improvements to existing intranasal delivery of formalin-inactivated whole Influenza A vaccines (WIV) by formulation with a cationic lipid-based adjuvant (N3). Additionally, we combined WIV and N3 with a DNA-encoded TLR5 agonist secreted flagellin (pFliC(-gly)) as an adjuvant, as this adjuvant has previously been shown to improve the effectiveness of plasmid-encoded DNA antigens. Methods: Outbred and inbred mouse strains were intranasally immunized with unadjuvanted WIV A/H1N1/SI 2006 or WIV that was formulated with N3 alone. Additional groups were immunized with WIV and N3 adjuvant combined with pFliC(-gly). Homo and heterotypic humoral anti-WIV immune responses were assayed from serum and lung by ELISA and hemagglutination inhibition assay. Homo and heterotypic cellular immune responses to WIV and Influenza A NP were also determined. Results: WIV combined with N3 lipid adjuvant the pFliC(-gly) significantly increased homotypic influenza specific serum antibody responses (>200-fold), increased the IgG2 responses, indicating a mixed Th1/Th2-type immunity, and increased the HAI-titer (>100-fold). Enhanced cell-mediated IFNγ secreting influenza directed CD4+ and CD8+ T cell responses (>40-fold) to homotypic and heterosubtypic influenza A virus and peptides. Long-term and protective immunity was obtained. Conclusions: These results indicate that inactivated influenza virus that was formulated with N3 cationic adjuvant significantly enhanced broad systemic and mucosal influenza specific immune responses. These responses were broadened and further increased by incorporating DNA plasmids encoding FliC from S. typhimurum as an adjuvant providing long lasting protection against heterologous Influenza A/H1N1/CA09pdm virus challenge.

scholarly journals From influenza infection to anti-ADAMTS13 autoantibodies via cross-reactivity

2018 ◽  
Vol 7 (4) ◽  
pp. 113-120
Author(s):  
Darja Kanduc
Keyword(s):  
Immune Responses ◽  
Thrombotic Thrombocytopenic Purpura ◽  
Von Willebrand Factor ◽  
Influenza A ◽  
Influenza Infection ◽  
Cross Reactivity ◽  
Influenza Viruses ◽  
Thrombocytopenic Purpura ◽  
Von Willebrand ◽  
Willebrand Factor

Abstract Autoantibodies (AAbs) against von Willebrand factor (vWF)-cleaving protease ADAMTS13 causally relate to thrombotic thrombocytopenic purpura (TTP). How anti-ADAMTS13 AAbs are generated is unknown. Starting from reports according to which influenza infection can trigger TTP by the production of ADAMTS13 AAbs, this study explores influenza viruses and ADAMTS13 protein for common peptide sequences that might underlie anti-influenza immune responses able to cross-react with ADAMTS13. Results document that numerous peptides are shared between influenza A and B viruses and ADAMTS13, thus supporting the hypothesis of cross-reactivity as a mechanism driving the generation of anti-ADAMTS13 AAbs.

scholarly journals Impact of Influenza on Pneumococcal Vaccine Effectiveness during Streptococcus pneumoniae Infection in Aged Murine Lung

Vaccines ◽  
2020 ◽  
Vol 8 (2) ◽  
pp. 298
Author(s):  
Ermias Jirru ◽  
Stefi Lee ◽  
Rebecca Harris ◽  
Jianjun Yang ◽  
Soo Jung Cho ◽  
...  
Keyword(s):  
Streptococcus Pneumoniae ◽  
Immune Responses ◽  
Pneumococcal Vaccine ◽  
Influenza A ◽  
Secondary Infection ◽  
Influenza Infection ◽  
Vaccine Effectiveness ◽  
Murine Lung ◽  
Vaccine Responses ◽  
Secondary Infections

Changes in innate and adaptive immune responses caused by viral imprinting can have a significant direct or indirect influence on secondary infections and vaccine responses. The purpose of our current study was to investigate the role of immune imprinting by influenza on pneumococcal vaccine effectiveness during Streptococcus pneumoniae infection in the aged murine lung. Aged adult (18 months) mice were vaccinated with the pneumococcal polyvalent vaccine Pneumovax (5 mg/mouse). Fourteen days post vaccination, mice were instilled with PBS or influenza A/PR8/34 virus (3.5 × 102 PFU). Control and influenza-infected mice were instilled with PBS or S. pneumoniae (1 × 103 CFU, ATCC 6303) on day 7 of infection and antibacterial immune responses were assessed in the lung. Our results illustrate that, in response to a primary influenza infection, there was diminished bacterial clearance and heightened production of pro-inflammatory cytokines, such as IL6 and IL1β. Vaccination with Pneumovax decreased pro-inflammatory cytokine production by modulating NFҡB expression; however, these responses were significantly diminished after influenza infection. Taken together, the data in our current study illustrate that immune imprinting by influenza diminishes pneumococcal vaccine efficacy and, thereby, may contribute to increased susceptibility of older persons to a secondary infection with S. pneumoniae.

Concurrent epidemics of influenza A/H3N2 and A/H1N1pdm in Southern China: A serial cross-sectional study

2016 ◽  
Vol 72 (3) ◽  
pp. 369-376 ◽  
Author(s):  
Chunli Wu ◽  
Maggie Haitian Wang ◽  
Xing Lu ◽  
Ka Chun Chong ◽  
Jason He ◽  
...  
Keyword(s):  
Influenza A ◽  
Southern China ◽  
Cross Sectional Study ◽  
Sectional Study ◽  
Cross Sectional

scholarly journals Topical exposure to triclosan inhibits Th1 immune responses and reduces T cells responding to influenza infection in mice

PLoS ONE ◽  
2020 ◽  
Vol 15 (12) ◽  
pp. e0244436
Author(s):  
Hillary L. Shane ◽  
Sreekumar Othumpangat ◽  
Nikki B. Marshall ◽  
Francoise Blachere ◽  
Ewa Lukomska ◽  
...  
Keyword(s):  
T Cells ◽  
Immune Responses ◽  
Cd8 T Cells ◽  
Healthcare Workers ◽  
Influenza A ◽  
Influenza Infection ◽  
Statistical Significance ◽  
Lethal Dose ◽  
Respiratory Pathogens ◽  
Increased Risk

Healthcare workers concurrently may be at a higher risk of developing respiratory infections and allergic disease, such as asthma, than the general public. Increased incidence of allergic diseases is thought to be caused, in part, due to occupational exposure to chemicals that induce or augment Th2 immune responses. However, whether exposure to these chemical antimicrobials can influence immune responses to respiratory pathogens is unknown. Here, we use a BALB/c murine model to test if the Th2-promoting antimicrobial chemical triclosan influences immune responses to influenza A virus. Mice were dermally exposed to 2% triclosan for 7 days prior to infection with a sub-lethal dose of mouse adapted PR8 A(H1N1) virus (50 pfu); triclosan exposure continued until 10 days post infection (dpi). Infected mice exposed to triclosan did not show an increase in morbidity or mortality, and viral titers were unchanged. Assessment of T cell responses at 10 dpi showed a decrease in the number of total and activated (CD44hi) CD4+ and CD8+ T cells at the site of infection (BAL and lung) in triclosan exposed mice compared to controls. Influenza-specific CD4+ and CD8+ T cells were assessed using MHCI and MHCII tetramers, with reduced populations, although not reaching statistical significance at these sites following triclosan exposure. Reductions in the Th1 transcription factor T-bet were seen in both activated and tetramer+ CD4+ and CD8+ T cells in the lungs of triclosan exposed infected mice, indicating reduced Th1 polarization and providing a potential mechanism for numerical reduction in T cells. Overall, these results indicate that the immune environment induced by triclosan exposure has the potential to influence the developing immune response to a respiratory viral infection and may have implications for healthcare workers who may be at an increased risk for developing infectious diseases.

scholarly journals Heterosubtypic cross-reactivity of HA1 antibodies to influenza A, with emphasis on nonhuman subtypes (H5N1, H7N7, H9N2)

2017 ◽  
Author(s):  
Dennis E. te Beest ◽  
Erwin de Bruin ◽  
Sandra Imholz ◽  
Marion Koopmans ◽  
Michiel van Boven
Keyword(s):  
Immune Responses ◽  
Influenza A ◽  
Protein Microarray ◽  
Age Distribution ◽  
Cross Reactivity ◽  
Influenza A Viruses ◽  
Cross Sectional ◽  
Before And After ◽  
2009 H1n1 ◽  
Protein Microarray Analysis

AbstractEpidemics of influenza A vary greatly in size and age distribution of cases, and this variation i attributed to varying levels of pre-existing immunity. Recent studies have shown that antibody mediated immune responses are more cross-reactive than previously believed, and shape patterns of humoral immunity to influenza A viruses over long periods. Here we quantify antibody responses to the hemagglutinin subunit 1 (HA1) across a range of subtypes using protein microarray analysis of cross-sectional serological surveys carried out in the Netherlanc before and after the A/2009 (H1N1) pandemic. We find significant associations of responses, both within and between subtypes. Interestingly, substantial overall reactivity is observed to HA1 of avian H7N7 and H9N2 viruses. Seroprevalence of H7N7 correlates with antibody titer to A/1968 (H3N2), and is highest in persons born between 1954 and 1969. Seroprevalence of H9N2 is high across all ages, and correlates strongly with A/1957 (H2N2). This correlation is most pronounced in A/2009 (H1N1) infected persons born after 1968 who have never encountered A/1957 (H2N2)-like viruses. We conclude that heterosubtypic antibody crossreactivity, both between human subtypes and between human and nonhuman subtypes, is common in the human population.

scholarly journals Seasonal trends of Influenza in Islamabad, Pakistan

2021 ◽  
Vol 10 (1) ◽  
pp. 318-322
Author(s):  
Sania Raza ◽  
Muhammad Usman ◽  
Imran Ahmad
Keyword(s):  
Influenza Virus ◽  
Influenza A ◽  
Influenza Infection ◽  
Age Groups ◽  
Cross Sectional Study ◽  
Peak Activity ◽  
Pathology Laboratory ◽  
Cross Sectional ◽  
Negative Results ◽  
Set Up

Background: Viral outbreaks have always been a challenging task for clinicians and Influenza virus has been on top of the list. The history of influenza epidemic reveals its devastating effects in the form of multiple deaths and economic burden. Hence this study was planned to recognize the peak activity time span of Influenza infection and its frequency in our set-up at Shifa International Hospital, Islamabad Pakistan. Material and Methods: A cross sectional study was performed in Pathology Laboratory, Shifa international hospital Islamabad from April 2016 to March 2019. Nasopharyngeal swabs were collected from patients of all age groups, with clinically suspected influenza infection throughout the year, irrespective of gender, according to hospital’s standard policy. Samples were analysed on GeneXpert kit (Xpert Flu Assay). Data collected was entered and then analysed in SPSS version 17. Results: Of the total 591 samples included in study, 233 (39.4%) were positive for influenza (Flu A or Flu B), while 358 (60.6%) showed negative results. Total 172 (73.8%) were positive for Flu A while 61 (26.1%) were positive for Flu B. Among Flu A cases, 107 (62.2%) were positive for H1N1. Most of the positive cases (n=206; 88.4%) were reported in the months of January and February during the three-year period (2016-2019) of this study. Conclusions: Influenza virus has peak activity in the months of January and February. Both Influenza A and B are circulating in the environment but Flu A is predominant and H1N1 is more prevalent.

scholarly journals Joint modelling of serological and hospitalization data reveals that high levels of pre-existing immunity and school holidays shaped the influenza A pandemic of 2009 in The Netherlands

2015 ◽  
Vol 12 (103) ◽  
pp. 20141244 ◽  
Author(s):  
Dennis E. te Beest ◽  
Paul J Birrell ◽  
Jacco Wallinga ◽  
Daniela De Angelis ◽  
Michiel van Boven
Keyword(s):  
The Netherlands ◽  
Disease Transmission ◽  
Influenza A ◽  
Transmission Model ◽  
Cross Sectional ◽  
Intervention Measures ◽  
Probabilistic Classification ◽  
Quantitative Understanding ◽  
Serological Data ◽  
The Impact

Obtaining a quantitative understanding of the transmission dynamics of influenza A is important for predicting healthcare demand and assessing the likely impact of intervention measures. The pandemic of 2009 provides an ideal platform for developing integrative analyses as it has been studied intensively, and a wealth of data sources is available. Here, we analyse two complementary datasets in a disease transmission framework: cross-sectional serological surveys providing data on infection attack rates, and hospitalization data that convey information on the timing and duration of the pandemic. We estimate key epidemic determinants such as infection and hospitalization rates, and the impact of a school holiday. In contrast to previous approaches, our novel modelling of serological data with mixture distributions provides a probabilistic classification of individual samples (susceptible, immune and infected), propagating classification uncertainties to the transmission model and enabling serological classifications to be informed by hospitalization data. The analyses show that high levels of immunity among persons 20 years and older provide a consistent explanation of the skewed attack rates observed during the pandemic and yield precise estimates of the probability of hospitalization per infection (1–4 years: 0.00096 (95%CrI: 0.00078–0.0012); 5–19 years: 0.00036 (0.00031–0.0044); 20–64 years: 0.0015 (0.00091–0.0020); 65+ years: 0.0084 (0.0028–0.016)). The analyses suggest that in The Netherlands, the school holiday period reduced the number of infectious contacts between 5- and 9-year-old children substantially (estimated reduction: 54%; 95%CrI: 29–82%), thereby delaying the unfolding of the pandemic in The Netherlands by approximately a week.

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