Abstract:Abstract. We studied cross-reactive antibodies against avian influenza H5N1 and 2009 pandemic (p) H1N1 in 200 serum samples from US military personnel collected before the H1N1 pandemic. Assays used to measure antibodies against viral proteins involved in protection included a hemagglutination inhibition (HI) assay and a neuraminidase inhibition (NI) assay. Viral neutralization by antibodies against avian influenza H5N1 and 2009 pH1N1 was assessed by influenza (H5) pseudotyped lentiviral particle-based and H1N… Show more
“…Broadly neutralizing antibodies increase with age 39 and vaccination plays a role in this. For example, antibodies that neutralize influenza viruses of animal origin are present in higher titers in subjects that have received multiple vaccinations 40 , 41 . The serum samples analyzed in this work are from a highly vaccinated population.…”
Seasonal influenza vaccine formulas change almost every year yet information about how this affects the antibody repertoire of vaccine recipients is inadequate. New vaccine virus strains are selected, replacing older strains to better match the currently circulating strains. But even while the vaccine is being manufactured the circulating strains can evolve. The ideal response to a seasonal vaccine would maintain antibodies toward existing strains that might continue to circulate, and to generate crossreactive antibodies, particularly towards conserved influenza epitopes, potentially limiting infections caused by newly evolving strains. Here we use the hemagglutination inhibition assay to analyze the antibody repertoire in subjects vaccinated two years in a row with either identical vaccine virus strains or with differing vaccine virus strains. The data indicates that changing the vaccine formulation results in an antibody repertoire that is better able to react with strains emerging after the vaccine virus strains are selected. The effect is observed for both influenza A and B strains in groups of subjects vaccinated in three different seasons. Analyses include stratification by age and sex.Influenza causes widespread seasonal disease and vaccination has been shown to reduce illness among the population [1][2][3][4] . Several studies have demonstrated that vaccination confers protection against virologically confirmed influenza 5 . However, understanding vaccination effectiveness is complicated because a large portion of the population is asymptomatically infected 6 . The circulating strains evolve from season to season leading to changes in vaccine formulation which further complicates comparisons between seasons.Vaccine effectiveness can be measured by controlled clinical trials but comparisons between trials is complicated by factors such as the prevalence of the circulating virus and the closeness of virus match each season 7 . Observational studies, used in places where universal vaccination recommendations make it unethical to perform trials with placebos, are an increasingly common way of measuring vaccine effectiveness among the general population. Test-negative studies are a widely used method but the estimates for vaccine effectiveness vary widely depending on the study design and often have overlapping confidence intervals [8][9][10] . Correlates of protection, such as the hemagglutination inhibition (HI) titer, are widely used to assess vaccine efficacy. HI titers are associated with reduced risk of disease but there is significant variation in the protective titer depending on factors such as the age of the recipient and the severity of the influenza season [11][12][13] . It has also been reported that factors not detected in HI assays are associated with reduced risk of infection 14,15 .Changes in the annual vaccine formulation are compelled by the antigenic drift associated with seasonal influenza viruses. Despite the best efforts of a group of experts in selecting the candidate vaccine virus (CV...
“…Broadly neutralizing antibodies increase with age 39 and vaccination plays a role in this. For example, antibodies that neutralize influenza viruses of animal origin are present in higher titers in subjects that have received multiple vaccinations 40 , 41 . The serum samples analyzed in this work are from a highly vaccinated population.…”
Seasonal influenza vaccine formulas change almost every year yet information about how this affects the antibody repertoire of vaccine recipients is inadequate. New vaccine virus strains are selected, replacing older strains to better match the currently circulating strains. But even while the vaccine is being manufactured the circulating strains can evolve. The ideal response to a seasonal vaccine would maintain antibodies toward existing strains that might continue to circulate, and to generate crossreactive antibodies, particularly towards conserved influenza epitopes, potentially limiting infections caused by newly evolving strains. Here we use the hemagglutination inhibition assay to analyze the antibody repertoire in subjects vaccinated two years in a row with either identical vaccine virus strains or with differing vaccine virus strains. The data indicates that changing the vaccine formulation results in an antibody repertoire that is better able to react with strains emerging after the vaccine virus strains are selected. The effect is observed for both influenza A and B strains in groups of subjects vaccinated in three different seasons. Analyses include stratification by age and sex.Influenza causes widespread seasonal disease and vaccination has been shown to reduce illness among the population [1][2][3][4] . Several studies have demonstrated that vaccination confers protection against virologically confirmed influenza 5 . However, understanding vaccination effectiveness is complicated because a large portion of the population is asymptomatically infected 6 . The circulating strains evolve from season to season leading to changes in vaccine formulation which further complicates comparisons between seasons.Vaccine effectiveness can be measured by controlled clinical trials but comparisons between trials is complicated by factors such as the prevalence of the circulating virus and the closeness of virus match each season 7 . Observational studies, used in places where universal vaccination recommendations make it unethical to perform trials with placebos, are an increasingly common way of measuring vaccine effectiveness among the general population. Test-negative studies are a widely used method but the estimates for vaccine effectiveness vary widely depending on the study design and often have overlapping confidence intervals [8][9][10] . Correlates of protection, such as the hemagglutination inhibition (HI) titer, are widely used to assess vaccine efficacy. HI titers are associated with reduced risk of disease but there is significant variation in the protective titer depending on factors such as the age of the recipient and the severity of the influenza season [11][12][13] . It has also been reported that factors not detected in HI assays are associated with reduced risk of infection 14,15 .Changes in the annual vaccine formulation are compelled by the antigenic drift associated with seasonal influenza viruses. Despite the best efforts of a group of experts in selecting the candidate vaccine virus (CV...
“…Several studies have suggested that heterosubtypic cross-immunity could partly explain the different age patterns [ 18 , 19 ]. A(H5N1) shares the same neuraminidase subtype with A(H1N1) whereas A (H7N9) does not, so elderly people may have been exposed to the A(H1N1) virus during their lives and developed antibodies that cross-react with the A(H5N1), providing some protection against A(H5N1) infection [ 20 ]. Elderly patients may become infected with A (H7N9) because they are more likely than younger people to be exposed to live poultry and are more susceptible to the severe form of the disease [ 21 ].…”
BackgroundGuangzhou reported its first laboratory-confirmed case of influenza A (H7N9) on January 10, 2014. A total of 25 cases were reported from the first wave of the epidemic until April 8, 2014. The fatality rate was much higher than in previous reports. The objective of the current work was to describe the clinical and epidemiological characteristics of A (H7N9) patients in Guangzhou and explore possible reasons for the high fatality rate.MethodsClinical and epidemiological information regarding A (H7N9) cases in Guangzhou was collected through review of medical records and field research. Data regarding clinical and laboratory features, treatment, and outcomes were extracted.ResultsOf the 25 patients, 84 % (21/25) had one or more underlying diseases. Fifteen patients (60.0 %) developed moderate to severe acute respiratory distress syndrome (ARDS), and 14 (56 %) died of the ARDS or multiorgan failure. Patients with longer delay between onset of illness and initiation of oseltamivir treatment were more likely to develop ARDS. Elevated C-creative protein, aspartate aminotransferase, creatine kinase, and lymphocytopenia predicted a higher risk of developing ARDS.ConclusionsThe presence of underlying diseases and clinical complications predicted poor clinical outcome. Early oseltamivir treatment was associated with a reduced risk of developing ARDS.
“…However, it is possible that cross-immunity also contributed to the age distribution of reported cases. Influenza A(H1N1) and A(H5N1) viruses share the same neuraminidase subtype, N1, and there is evidence that H1N1 neuraminidase antibodies cross-react with H5N1 viruses [ 6 – 8 ]. Fig.…”
SUMMARYThe age distribution of influenza A(H5N1) cases reported during 2006–2013 varied substantially between countries. As well as underlying demographic profiles, it is possible that cross-immunity contributed to the age distribution of reported cases: seasonal influenza A(H1N1) and avian influenza A(H5N1) share the same neuraminidase subtype, N1. Using a mechanistic model, we measured the extent to which population age distribution and heterosubtypic cross-immunity could explain the observed age patterns in Cambodia, China, Egypt, Indonesia and Vietnam. Our results support experimental evidence that prior infection with H1N1 confers partial cross-immunity to H5N1, and suggest that more than 50% of spillover events did not lead to reported cases of infection as a result. We also identified age groups that have additional risk factors for influenza A(H5N1) not captured by demography or infection history.
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