Multi-parameter approach to evaluate the timing of memory status after 17DD-YF primary vaccination

Submitted by Priscila Nascimento ([email protected]) on 2018-06-20T18:10:46Z No. of bitstreams: 1 Multi-parameter_approach_to_evaluate_the_timing_of.pdf: 8388797 bytes, checksum: 234fb0f5fbecbf0d6e239427b5c7095d (MD5)Approved for entry into archive by Priscila Nascimento ([email protected]) on 2018-06-20T18:52:14Z (GMT) No. of bitstreams: 1 Multi-parameter_approach_to_evaluate_the_timing_of.pdf: 8388797 bytes, checksum: 234fb0f5fbecbf0d6e239427b5c7095d (MD5)Made available in DSpace on 2018-06-20T18:52:14Z (GMT). No. of bitstreams: 1 Multi-parameter_approach_to_evaluate_the_timing_of.pdf: 8388797 bytes, checksum: 234fb0f5fbecbf0d6e239427b5c7095d (MD5) Previous issue date: 2018Fundação Oswaldo Cruz. Centro de Pesquisas René Rachou.Belo Horizonte, Minas Gerais, Brasil.Governo do Estado de Minas Gerais. Secretaria de Estado de Saúde. Belo Horizonte, Minas Gerais, Brasil.Universidade Federal de Alfenas. Alfenas, Minas Gerais, Brasil.Universidade Federal de Uberlândia. Laboratório de Bioinformática e Análises Moleculares. Uberlândia, Minas Gerais, Brasil.Food and Drug Administration. Center for Biologics Evaluation and Research. Silver Spring, Maryland, United States of America.Instituto de Biologia do Exército. Rio de Janeiro, Rio de Janeiro, Brasil.Fundação Oswaldo Cruz. Instituto de Tecnologia em Imunobiológicos. Rio de Janeiro, RJ, Brasil.Ministério da Saúde. Secretaria de Vigilância em Saúde. Brasília, DF, Brasil.Universidade de Brasília. Brasília, DF, Brasil.Instituto Evandro Chagas. Ananindeua, Pará, Brasil.Fundação Oswaldo Cruz. Diretoria Regional de Brasília. Brasília, DF, Brasil.Fundação Oswaldo Cruz. Escola Nacional de Saúde Pública. Rio de Janeiro, RJ, Brasil.Nesta investigação, as técnicas melhoradas por máquina foram aplicadas para trazer insights científicos para identificar um conjunto mínimo de biomarcadores relacionados à memória fenotípica / funcional para o acompanhamento pós-vacinação da vacinação contra a febre amarela (FA). Para este propósito, o estado de memória das células T circulantes (Naïve / efetor-precoce / Memória-Central / Memória Efetiva) e células B (Naïve / memória não clássica / memória clássica) juntamente com o perfil de citocinas (IFN / TNF / IL-5 / IL-10) foram monitorizados antes do NV (dia 0) e em pontos de tempo distintos após a vacinação primária com 17DD-YF - VP (dia30-45); PV (ano1-9) e PV (ano10-11). Um conjunto de biomarcadores (eEfCD4; EMCD4; CMCD19; EMCD8; IFNCD4; IL-5CD8; TNFCD4; IFNCD8; TNFCD8; IL-5CD19; IL-5CD4) foi observado em PV (dia30-45), mas não em NV (dia0) , com a maioria deles ainda observada em VP (ano1-9). Deficiências de biomarcadores fenotípicos / funcionais foram observadas em NV (dia 0), enquanto a falta total de atributos relacionados à memória foi observada na PV (ano10-11), independentemente da idade na vacinação primária. Análise de diagrama de Venn pré-selecionada 10 atributos (eEfCD4, EMCD4, CMCD19, EMCD8, IFNCD4, IL-5CD8, TNFCD4, IFNCD8, TNFCD8 e IL-5CD4), dos quais a média geral apresentou moderada precisão para discriminar PV (dia30-45) e PV (year1-9) de NV (day0) e PV (year10-11). Abordagens multi-parâmetro e algoritmos de árvore de decisão definiram os atributos EMCD8 e IL-5CD4 como os dois principais preditores com desempenho moderado. Juntamente com os títulos PRNT, os dois principais biomarcadores levaram a um status de memória resultante observado em 80% e 51% dos voluntários em PV (dia30-45) e PV (ano1-9), contrastando com 0% e 29% encontrados em NV ( day0) e PV (year10-11), respectivamente. A deficiência de atributos relacionados à memória observada na PV (year10-11) ressalta a diminuição conspícua dependente do tempo da memória resultante após a vacinação primária com 17DD-YF, que pode ser útil para monitorar potenciais correlatos de proteção em áreas sob risco de transmissão da FA.In this investigation, machine-enhanced techniques were applied to bring about scientific insights to identify a minimum set of phenotypic/functional memory-related biomarkers for post-vaccination follow-up upon yellow fever (YF) vaccination. For this purpose, memory status of circulating T-cells (Naïve/early-effector/Central-Memory/Effector-Memory) and Bcells (Naïve/non-Classical-Memory/Classical-Memory) along with the cytokine profile (IFN/ TNF/IL-5/IL-10) were monitored before-NV(day0) and at distinct time-points after 17DD-YF primary vaccinationÐPV(day30-45); PV(year1-9) and PV(year10-11). A set of biomarkers (eEfCD4; EMCD4; CMCD19; EMCD8; IFNCD4; IL-5CD8; TNFCD4; IFNCD8; TNFCD8; IL-5CD19; IL-5CD4) were observed in PV(day30-45), but not in NV(day0), with most of them still observed in PV(year1-9). Deficiencies of phenotypic/functional biomarkers were observed in NV(day0), while total lack of memory-related attributes was observed in PV (year10-11), regardless of the age at primary vaccination. Venn-diagram analysis preselected 10 attributes (eEfCD4, EMCD4, CMCD19, EMCD8, IFNCD4, IL-5CD8, TNFCD4, IFNCD8, TNFCD8 and IL-5CD4), of which the overall mean presented moderate accuracy to discriminate PV(day30-45)&PV(year1-9) from NV(day0)&PV(year10-11). Multi-parameter approaches and decision-tree algorithms defined the EMCD8 and IL-5CD4 attributes as the top-two predictors with moderated performance. Together with the PRNT titers, the toptwo biomarkers led to a resultant memory status observed in 80% and 51% of volunteers in PV(day30-45) and PV(year1-9), contrasting with 0% and 29% found in NV(day0) and PV (year10-11), respectively. The deficiency of memory-related attributes observed at PV (year10-11) underscores the conspicuous time-dependent decrease of resultant memory following17DD-YF primary vaccination that could be useful to monitor potential correlates of protection in areas under risk of YF transmission

Multi-parameter approach to evaluate the timing of memory status after 17DD-YF primary vaccination

<div><p>In this investigation, machine-enhanced techniques were applied to bring about scientific insights to identify a minimum set of phenotypic/functional memory-related biomarkers for post-vaccination follow-up upon yellow fever (YF) vaccination. For this purpose, memory status of circulating T-cells (Naïve/early-effector/Central-Memory/Effector-Memory) and B-cells (Naïve/non-Classical-Memory/Classical-Memory) along with the cytokine profile (IFN/TNF/IL-5/IL-10) were monitored before-NV(day0) and at distinct time-points after 17DD-YF primary vaccination—PV(day30-45); PV(year1-9) and PV(year10-11). A set of biomarkers (eEfCD4; EMCD4; CMCD19; EMCD8; IFNCD4; IL-5CD8; TNFCD4; IFNCD8; TNFCD8; IL-5CD19; IL-5CD4) were observed in PV(day30-45), but not in NV(day0), with most of them still observed in PV(year1-9). Deficiencies of phenotypic/functional biomarkers were observed in NV(day0), while total lack of memory-related attributes was observed in PV(year10-11), regardless of the age at primary vaccination. Venn-diagram analysis pre-selected 10 attributes (eEfCD4, EMCD4, CMCD19, EMCD8, IFNCD4, IL-5CD8, TNFCD4, IFNCD8, TNFCD8 and IL-5CD4), of which the overall mean presented moderate accuracy to discriminate PV(day30-45)&PV(year1-9) from NV(day0)&PV(year10-11). Multi-parameter approaches and decision-tree algorithms defined the EMCD8 and IL-5CD4 attributes as the top-two predictors with moderated performance. Together with the PRNT titers, the top-two biomarkers led to a resultant memory status observed in 80% and 51% of volunteers in PV(day30-45) and PV(year1-9), contrasting with 0% and 29% found in NV(day0) and PV(year10-11), respectively. The deficiency of memory-related attributes observed at PV(year10-11) underscores the conspicuous time-dependent decrease of resultant memory following17DD-YF primary vaccination that could be useful to monitor potential correlates of protection in areas under risk of YF transmission.</p></div

Overall 17DD-YF memory-related biomarker signatures at distinct time-points after primary vaccination.

<p>The phenotypic/functional biomarker signatures were built taking the proportion of subjects above the cut-off edges defined for each attribute, calculated as the median index value (17DD-YF/Control) for the study population. Diagrams were constructed for all study groups to calculate the proportion (%) of volunteers above the median cut-off indices for each biomarker (gray-shaded spots). (A) The PV(day30-45) group was used to construct the memory-related phenotypic and functional biomarker signatures and draw the reference curves, used for comparative analysis amongst the study groups, (B) NV(day0), (C) PV(year1-9) and (D) PV(year10-11). Hatched cells represent unavailable results. Data mining was carried out as proposed previously by Luiza-Silva et al., (2011), selecting from the PV(day30-45) reference curves, those biomarkers with more than 50% of volunteers above the cut-off index (surrounded by dashed rectangles). Comparative analysis amongst the study groups were carried out considering only the selected set of relevant biomarkers from the phenotypic and functional reference curves. Substantial change in the set of relevant biomarkers were highlighted by (*) when the proportion of subjects above the cut-off fell below 50%. The common set of relevant biomarkers on each study group was underscored in bold font.</p

Changes in neutralizing antibody titers and phenotypic/functional memory-related biomarkers at distinct time-points after primary 17DD-YF vaccination.

<p>Correlation analyses were performed to validate the time-dependent decline in (A) neutralizing antibody titers and 17DD-YF Memory-related (B) phenotypic and (C) functional features. Data are expressed as scattering distribution of individual values along distinct time-points after 17DD-YF primary vaccination against neutralizing antibody titers (PRNT) as well as phenotypic and functional features (YF-Ag/CC Index). Spearman’s correlation test was applied to identify significant time-dependent loss of memory-related biomarkers. Correlation indices (p and r) along with the 95% confidence band of the best-fit line are provided in the figure. Attributes with higher correlation indices (r values) are highlighted with gray background.</p

Major phenotypic/functional biomarkers useful to monitor the memory status following primary 17DD-YF vaccination.

<p>(A) Decision tree analysis was carried out to identify root attributes [Ellipses] for phenotypic/functional (P&F) biomarkers amongst NV(day0)&PV(year10-11) [white rectangle] and PV(day30-45)&PV(year1-9) [black rectangle], considered biomarkers to discriminate unprotected from protected subjects. Leave-one-out-cross-validation analysis (LOOCV) was employed to minimize biased performance estimates by using all data set for decision tree model fitting. EMCD8 and IL-5CD4 were selected as major phenotypic and functional 17DD-YF Memory-related biomarkers, respectively. (B) Heatmaps were built, taking the mean index of the top-two phenotypic/functional biomarkers (EMCD8 & IL-5CD4) and demonstrating the proportion (%) of volunteers ranging from low (White) to high (Gray) YF-Ag/CC index. A scatter plot was constructed to show the sensitivity (Gray Circle) and specificity (White Circle) of the top-two biomarkers, employing the cut-off edge (Mean Index = 1.3) provided by the ROC curve analysis. (C) Resultant memory status was defined for each subject, considering the top-two biomarkers (Mean Index >1.3) and PRNT (>2.9 Log mIU/mL, according to Simões et al., 2012). Column statistics were used to calculate the proportion of subjects displaying differing categories of resultant memory, referred as none, top-two biomarkers—P&F, PRNT and both. (D) Pie charts illustrated the overall resultant memory status within each category, as determined by the top-two biomarkers and PRNT. Significant differences at p<0.05 (Chi-square test) of resultant memory status amongst study groups were represented by letters “a”, b”, “c” and “d” in comparison to NV(day0), PV(day30-45), PV(year1-9) and PV(year10-11), respectively.</p

17DD-YF memory-related biomarker signatures according to the age at primary vaccination.

<p>The memory-related biomarker signatures were constructed using the proportion of subjects above the cut-off edges defined for each attribute, calculated as the median index value (17DD-YF/Control) for the study population. The signatures were constructed for phenotypic/functional biomarkers, compiling the proportion (%) of volunteer above the median cut-off indices. The memory-related biomarker signatures, constructed for the PV(day30-45) group, were used as the reference curves for comparative analysis amongst the PV(year10-11) subgroups, categorized according to the age at primary vaccination, including (A) 20–30 years old, (B) 31–40 years old and (C) 41–74 years old. Comparative analysis were carried out considering only the set of relevant biomarkers pre-selected from the phenotypic/functional reference curves (surrounded by dashed rectangles), including those biomarkers with more than 50% of volunteers above the cut-off index in the PV(day30-45) reference curves (surrounded by dashed rectangles). Substantial changes in the set of relevant biomarkers were underscored by (*) when the proportion of subjects above the cut-off fell below 50%. The common set of relevant biomarkers on each study group was underscored in bold font.</p

Duration of post-vaccination immunity against yellow fever in adults

Submitted by Nuzia Santos ([email protected]) on 2015-06-22T17:37:43Z No. of bitstreams: 1 2014_152.pdf: 756403 bytes, checksum: c18d98237e29e19e785cf895a2a68ddc (MD5)Approved for entry into archive by Nuzia Santos ([email protected]) on 2015-06-22T17:37:52Z (GMT) No. of bitstreams: 1 2014_152.pdf: 756403 bytes, checksum: c18d98237e29e19e785cf895a2a68ddc (MD5)Approved for entry into archive by Nuzia Santos ([email protected]) on 2015-06-22T17:58:36Z (GMT) No. of bitstreams: 1 2014_152.pdf: 756403 bytes, checksum: c18d98237e29e19e785cf895a2a68ddc (MD5)Made available in DSpace on 2015-06-22T17:58:36Z (GMT). No. of bitstreams: 1 2014_152.pdf: 756403 bytes, checksum: c18d98237e29e19e785cf895a2a68ddc (MD5) Previous issue date: 2014Fundação Oswaldo Cruz. Brasilia, DF, BrasilFundação Oswaldo Cruz. Escola Nacional de Saúde Pública. Rio de Janeiro, RJ, BrazilFundação Oswaldo Cruz. Centro de Pesquisa Rene Rachou. Laboratório de Biomarcadores Belo Horizonte, MG, BrasilFundação Oswaldo Cruz. Instituto de Tecnologia em Imunobiológicosde Bio-Manguinhos. Rio de Janeiro, RJ, BrasilFundação Oswaldo Cruz. Instituto de Tecnologia em Imunobiológicos de Bio-Manguinhos. Rio de Janeiro, RJ, BrasilFundação Oswaldo Cruz. Instituto de Tecnologia em Imunobiológicos de Bio-Manguinhos. Rio de Janeiro, RJ, BrasilFundação Oswaldo Cruz. Instituto de Tecnologia em Imunobiológicos de Bio-Manguinhos. Rio de Janeiro, RJ, BrasilFundação Oswaldo Cruz. Instituto de Tecnologia em Imunobiológicos de Bio-Manguinhos. Rio de Janeiro, RJ, BrasilFundação Oswaldo Cruz. Instituto de Tecnologia em Imunobiológicos de Bio-Manguinhos. Rio de Janeiro, RJ, BrasilFundação Oswaldo Cruz. Instituto de Tecnologia em Imunobiológicos de Bio-Manguinhos. Rio de Janeiro, RJ, BrasilFundação Oswaldo Cruz. Instituto de Tecnologia em Imunobiológicos de Bio-Manguinhos. Rio de Janeiro, RJ, BrasilFundação Oswaldo Cruz. Instituto de Tecnologia em Imunobiológicos de Bio-Manguinhos. Rio de Janeiro, RJ, BrasilFundação Oswaldo Cruz. Instituto de Tecnologia em Imunobiológicos de Bio-Manguinhos. Rio de Janeiro, RJ, BrasilFundação Oswaldo Cruz. Instituto de Tecnologia em Imunobiológicos de Bio-Manguinhos. Rio de Janeiro, RJ, BrasilFundação Oswaldo Cruz. Instituto de Tecnologia em Imunobiológicos de Bio-Manguinhos. Rio de Janeiro, RJ, BrasilFundação Oswaldo Cruz. Instituto de Tecnologia em Imunobiológicos de Bio-Manguinhos. Rio de Janeiro, RJ, BrasilFundação Oswaldo Cruz. Instituto de Tecnologia em Imunobiológicos de Bio-Manguinhos. Rio de Janeiro, RJ, BrasilFundação Oswaldo Cruz. Instituto de Tecnologia em Imunobiológicos de Bio-Manguinhos. Rio de Janeiro, RJ, BrasilFundação Oswaldo Cruz. Instituto de Tecnologia em Imunobiológicos de Bio-Manguinhos. Rio de Janeiro, RJ, BrasilFundação Oswaldo Cruz. Instituto de Tecnologia em Imunobiológicos de Bio-Manguinhos. Rio de Janeiro, RJ, BrasilFundação Oswaldo Cruz. Instituto de Tecnologia em Imunobiológicos de Bio-Manguinhos. Rio de Janeiro, RJ, BrasilFundação Oswaldo Cruz. Instituto de Tecnologia em Imunobiológicos de Bio-Manguinhos. Rio de Janeiro, RJ, BrasilFundação Oswaldo Cruz. Instituto de Tecnologia em Imunobiológicos de Bio-Manguinhos. Rio de Janeiro, RJ, BrasilFundação Oswaldo Cruz. Instituto de Tecnologia em Imunobiológicos de Bio-Manguinhos. Rio de Janeiro, RJ, BrasilFundação Oswaldo Cruz. Instituto de Tecnologia em Imunobiológicos de Bio-Manguinhos. Rio de Janeiro, RJ, BrasilFundação Oswaldo Cruz. Instituto de Tecnologia em Imunobiológicos de Bio-Manguinhos. Rio de Janeiro, RJ, BrasilFundação Oswaldo Cruz. Instituto de Tecnologia em Imunobiológicos de Bio-Manguinhos. Rio de Janeiro, RJ, BrasilFundação Oswaldo Cruz. Instituto de Tecnologia em Imunobiológicos de Bio-Manguinhos. Rio de Janeiro, RJ, BrasilFundação Oswaldo Cruz. Instituto de Tecnologia em Imunobiológicos de Bio-Manguinhos. Rio de Janeiro, RJ, BrasilFundação Oswaldo Cruz. Instituto de Tecnologia em Imunobiológicos de Bio-Manguinhos. Rio de Janeiro, RJ, BrasilFundação Oswaldo Cruz. Instituto de Tecnologia em Imunobiológicos de Bio-Manguinhos. Rio de Janeiro, RJ, BrasilFundação Oswaldo Cruz. Instituto de Tecnologia em Imunobiológicos de Bio-Manguinhos. Rio de Janeiro, RJ, BrasilFundação Oswaldo Cruz. Centro de Pesquisa Rene Rachou. Laboratório de Biomarcadores. Belo Horizonte, MG, BrasilFundação Oswaldo Cruz. Centro de Pesquisa Rene Rachou. Laboratório de Biomarcadores. Belo Horizonte, MG, BrasilFundação Oswaldo Cruz. Centro de Pesquisa Rene Rachou. Laboratório de Imunopatologia .Belo Horizonte, MG, BrasilFundação Oswaldo Cruz. Centro de Pesquisa Rene Rachou. Laboratório de Esquistossomose. Belo Horizonte, MG, BrasilFundação Oswaldo Cruz. Centro de Pesquisa Rene Rachou. Laboratório de Biomarcadores. Belo Horizonte, MG, BrasilFundação Oswaldo Cruz. Centro de Pesquisa Rene Rachou. Laboratório de Biomarcadores. Belo Horizonte, MG, BrasilFood and Drug Administration Center for Biologics Evaluation and Research. Bethesda, USA.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratorio de Fla-vivirus. Rio de JaneiroFundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratorio de Fla-vivirus. Rio de JaneiroFundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratorio de Fla-vivirus. Rio de JaneiroInstituto de Biologia do Exército. Rio de Janeiro, RJ, BrasilInstituto de Biologia do Exército. Rio de Janeiro, RJ, BrasilInstituto de Biologia do Exército. Rio de Janeiro, RJ, BrasilInstituto de Biologia do Exército. Rio de Janeiro, RJ, BrasilInstituto de Biologia do Exército. Rio de Janeiro, RJ, BrasilInstituto de Biologia do Exército. Rio de Janeiro, RJ, BrasilMinas Gerais. Secretaria Estadual de Saude. Belo Horizonte, MG, BrasilMinas Gerais. Secretaria Estadual de Saude. Belo Horizonte, MG, BrasilMinas Gerais. Secretaria Estadual de Saude. Belo Horizonte, MG, BrasilMinas Gerais. Secretaria Estadual de Saude. Belo Horizonte, MG, BrasilUniversidade Federal de Alfenas. Alfenas, MG, BrasilUniversidade de Brasília. Faculdade de Medicina. Brasilia, DF, BrasilFundação Oswaldo Cruz. Instituto Evandro Chagas. Ananindeua, PA, BrasilINTRODUCTION: Available scientific evidence to recommend or to advise against booster doses of yellow fever vaccine (YFV) is inconclusive. A study to estimate the seropositivity rate and geometric mean titres (GMT) of adults with varied times of vaccination was aimed to provide elements to revise the need and the timing of revaccination. METHODS: Adults from the cities of Rio de Janeiro and Alfenas located in non-endemic areas in the Southeast of Brazil, who had one dose of YFV, were tested for YF neutralising antibodies and dengue IgG. Time (in years) since vaccination was based on immunisation cards and other reliable records. RESULTS: From 2011 to 2012 we recruited 691 subjects (73% males), aged 18-83 years. Time since vaccination ranged from 30 days to 18 years. Seropositivity rates (95%C.I.) and GMT (International Units/mL; 95%C.I.) decreased with time since vaccination: 93% (88-96%), 8.8 (7.0-10.9) IU/mL for newly vaccinated; 94% (88-97), 3.0 (2.5-3.6) IU/mL after 1-4 years; 83% (74-90), 2.2 (1.7-2.8) IU/mL after 5-9 years; 76% (68-83), 1.7 (1.4-2.0) IU/mL after 10-11 years; and 85% (80-90), 2.1 (1.7-2.5) IU/mL after 12 years or more. YF seropositivity rates were not affected by previous dengue infection. CONCLUSIONS:Eventhough serological correlates of protection for yellow fever are unknown, seronegativity in vaccinated subjects may indicate primary immunisation failure, or waning of immunity to levels below the protection threshold. Immunogenicity of YFV under routine conditions of immunisation services is likely to be lower than in controlled studies. Moreover, infants and toddlers, who comprise the main target group in YF endemic regions, and populations with high HIV infection rates, respond to YFV with lower antibody levels. In those settings one booster dose, preferably sooner than currently recommended, seems to be necessary to ensure longer protection for all vaccinee