tetano
Editor, Senior Moderator
Hum Vaccin Immunother. 2015 Feb 18:0. [Epub ahead of print]
[h=1]Influenza vaccine response profiles are affected by vaccine preparation and preexisting immunity, but not HIV infection.[/h] Berger CT[SUP]1[/SUP], Greiff V, Mehling M, Fritz S, Meier MA, Hoenger G, Conen A, Recher M, Battegay M, Reddy ST, Hess C.
[h=3]Author information[/h]
[h=3]Abstract[/h] Background: Vaccines dramatically reduce infection-related morbidity and mortality. Determining factors that modulate the host response is key to rational vaccine design and demands unsupervised analysis. Methods: To longitudinally resolve influenza-specific humoral immune response dynamics we constructed vaccine response profiles of influenza A- and B-specific IgM and IgG levels from 42 healthy and 31 HIV infected influenza-vaccinated individuals. Pre-vaccination antibody levels and levels at three predefined time points after vaccination were included in each profile. We performed hierarchical clustering on these profiles to study the extent to which HIV infection associated immune dysfunction, adaptive immune factors (pre-existing influenza-specific antibodies, T cell responses), an innate immune factor (Mannose Binding Lectin, MBL), demographic characteristics (gender, age), or the vaccine preparation (split vs. virosomal) impacted the immune response to influenza vaccination. Results: Hierarchical clustering associated vaccine preparation and pre-existing IgG levels with the profiles of healthy individuals. In contrast to previous in vitro and animal data, MBL levels had no impact on the adaptive vaccine response. Importantly, while HIV infected subjects with low CD4 T cell counts showed a reduced magnitude of their vaccine response, their response profiles were indistinguishable from those of healthy controls, suggesting quantitative but not qualitative deficits. Conclusion: Unsupervised profile-based analysis ranks factors impacting the vaccine-response by relative importance, with substantial implications for comparing, designing and improving vaccine preparations and strategies. Profile similarity between HIV infected and HIV negative individuals suggests merely quantitative differences in the vaccine response in these individuals, offering a rationale for boosting strategies in the HIV infected population.
[h=4]KEYWORDS:[/h] HIV; MBL; immune dysfunction; immune response; influenza vaccination; unsupervised analysis; vaccine preparation
PMID: 25692740 [PubMed - as supplied by publisher]
[h=1]Influenza vaccine response profiles are affected by vaccine preparation and preexisting immunity, but not HIV infection.[/h] Berger CT[SUP]1[/SUP], Greiff V, Mehling M, Fritz S, Meier MA, Hoenger G, Conen A, Recher M, Battegay M, Reddy ST, Hess C.
[h=3]Author information[/h]
[h=3]Abstract[/h] Background: Vaccines dramatically reduce infection-related morbidity and mortality. Determining factors that modulate the host response is key to rational vaccine design and demands unsupervised analysis. Methods: To longitudinally resolve influenza-specific humoral immune response dynamics we constructed vaccine response profiles of influenza A- and B-specific IgM and IgG levels from 42 healthy and 31 HIV infected influenza-vaccinated individuals. Pre-vaccination antibody levels and levels at three predefined time points after vaccination were included in each profile. We performed hierarchical clustering on these profiles to study the extent to which HIV infection associated immune dysfunction, adaptive immune factors (pre-existing influenza-specific antibodies, T cell responses), an innate immune factor (Mannose Binding Lectin, MBL), demographic characteristics (gender, age), or the vaccine preparation (split vs. virosomal) impacted the immune response to influenza vaccination. Results: Hierarchical clustering associated vaccine preparation and pre-existing IgG levels with the profiles of healthy individuals. In contrast to previous in vitro and animal data, MBL levels had no impact on the adaptive vaccine response. Importantly, while HIV infected subjects with low CD4 T cell counts showed a reduced magnitude of their vaccine response, their response profiles were indistinguishable from those of healthy controls, suggesting quantitative but not qualitative deficits. Conclusion: Unsupervised profile-based analysis ranks factors impacting the vaccine-response by relative importance, with substantial implications for comparing, designing and improving vaccine preparations and strategies. Profile similarity between HIV infected and HIV negative individuals suggests merely quantitative differences in the vaccine response in these individuals, offering a rationale for boosting strategies in the HIV infected population.
[h=4]KEYWORDS:[/h] HIV; MBL; immune dysfunction; immune response; influenza vaccination; unsupervised analysis; vaccine preparation
PMID: 25692740 [PubMed - as supplied by publisher]