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. 2020 Mar 15;204(6):1661-1673.
doi: 10.4049/jimmunol.1900922. Epub 2020 Feb 14.

Seasonal Variability and Shared Molecular Signatures of Inactivated Influenza Vaccination in Young and Older Adults

Stefan Avey  1 , Subhasis Mohanty  2 , Daniel G Chawla  1 , Hailong Meng  3 , Thilinie Bandaranayake  2 , Ikuyo Ueda  2 , Heidi J Zapata  2 , Koonam Park  4 , Tamara P Blevins  5 , Sui Tsang  2 , Robert B Belshe  5 , Susan M Kaech  4 , Albert C Shaw  6 , Steven H Kleinstein  7   3   4
Affiliations

Seasonal Variability and Shared Molecular Signatures of Inactivated Influenza Vaccination in Young and Older Adults

Stefan Avey et al. J Immunol. .

Abstract

The seasonal influenza vaccine is an important public health tool but is only effective in a subset of individuals. The identification of molecular signatures provides a mechanism to understand the drivers of vaccine-induced immunity. Most previously reported molecular signatures of human influenza vaccination were derived from a single age group or season, ignoring the effects of immunosenescence or vaccine composition. Thus, it remains unclear how immune signatures of vaccine response change with age across multiple seasons. In this study we profile the transcriptional landscape of young and older adults over five consecutive vaccination seasons to identify shared signatures of vaccine response as well as marked seasonal differences. Along with substantial variability in vaccine-induced signatures across seasons, we uncovered a common transcriptional signature 28 days postvaccination in both young and older adults. However, gene expression patterns associated with vaccine-induced Ab responses were distinct in young and older adults; for example, increased expression of killer cell lectin-like receptor B1 (KLRB1; CD161) 28 days postvaccination positively and negatively predicted vaccine-induced Ab responses in young and older adults, respectively. These findings contribute new insights for developing more effective influenza vaccines, particularly in older adults.

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Figures

Figure 1
Figure 1. Influenza-Specific Antibody Titers.
(A) An illustration of the maximum Residual after Baseline Adjustment (maxRBA) method for hemagglutination inhibition (HAI) titers. An exponential curve (blue) is fit to the data and the residual is used to stratify subjects into high and low responders. Subjects with largest positive residuals are high responders (green) and subjects with smallest negative residuals are low responders (red). Unlike the illustration, maxRBA is calculated using the maximum residual across all vaccine strains. (B and C) Violin plots of pre-vaccination HAI titers (B) and HAI responses measured by maxRBA (C) are separated by season and gender to compare age groups. Crossbars indicate the mean. Not Significant (ns) p > 0.05, * p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001 independent two-sided Wilcoxon rank sum test.
Figure 2
Figure 2. Substantial Seasonal Variability in Signatures Induced by Influenza Vaccination.
(A) A row-normalized heatmap of the 2,462 significantly differentially expressed genes (DEGs). Clusters A-G were defined by hierarchical clustering. Asterisks within the heatmap indicate genes significantly differentially expressed compared to day 0. (B) The first two principal components from a principal component analysis of all DEGs. Each point is a sample and lines connect the median of the points at each day post-vaccination within each season. (E) DUSP2 expression in sorted CD4 and CD8 T cells. ** p < 0.01, *** p < 0.001 one-sided t-test comparing day 28 and day 0 only. (F) Probability density functions calculated by QuSAGE for two representative gene modules significantly downregulated 28 days post-vaccination in four seasons. M31 contains DUSP1 while M89.1 contains both DUSP1 and DUSP2.
Figure 3
Figure 3. Vaccine-Induced Changes are Correlated Between Young and Older Adults at Day 28.
Scatter plots show the meta-analysis effect sizes of changes post-vaccination for every gene in young vs older adults on days 2 (A), 7 (B) and 28 (C) post-vaccination.
Figure 4
Figure 4. Post-Vaccination Transcriptional Predictors of Antibody Response.
(A and B) Boxplots of the area under the receiver operating characteristic curve (AUROC) in the validation data for Lasso (L1), Elastic Net (EN), and Logistic Multiple Network-constrained Regression (LogMiNeR) models built from day 7 transcriptional changes in young (A) and older (B) adults. 50 iterations of cross-validation were performed. x-labels indicate the prior knowledge network for LogMiNeR. (C and D) Heatmaps of Discovery (Disc.) and Validation (Valid.) data showing the z-score of the fold change for individual genes selected by the L1 models in any iteration for young (C) and older (D) adults. (E) Boxplots of KLRB1 expression changes in PBMCs 28 days post-vaccination in low responders (LR) and high responders (HR). (F) A scatter plot of the gene effect sizes comparing HR to LR 28 days post-vaccination in young vs older adults. KLRB1 is indicated as a gene that has a positive effect size in one age group and negative effect size in the other.
Figure 5
Figure 5. Baseline Transcriptional Predictors of Antibody Response.
(A and B) Boxplots of the area under the receiver operating characteristic curve (AUROC) in the validation data for Lasso (L1), Elastic Net (EN), and Logistic Multiple Network-constrained Regression (LogMiNeR) models built from baseline (pre-vaccination) transcriptional profiles in young (A) and older (B) adults (9). 50 iterations of cross-validation were performed. x-labels indicate the prior knowledge network for LogMiNeR. (C and D) Heatmaps of Discovery (Disc.) and Validation (Valid.) data showing the z-score of the fold change for individual genes selected by the L1 models in any iteration for young (C) and older (D) adults.
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References

    1. Ohmit SE, Victor JC, Teich ER, Truscon RK, Rotthoff JR, Newton DW, Campbell S. a, Boulton ML, and Monto AS. 2008. Prevention of symptomatic seasonal influenza in 2005–2006 by inactivated and live attenuated vaccines. J. Infect. Dis. 198: 312–317. - PMC - PubMed
    1. Frey S, Vesikari T, Szymczakiewicz-Multanowska A, Lattanzi M, Izu A, Groth N, and Holmes S. 2010. Clinical Efficacy of Cell Culture-Derived and Egg-Derived Inactivated Subunit Influenza Vaccines in Healthy Adults. Clin. Infect. Dis. 51: 997–1004. - PubMed
    1. Jackson L. Gaglani a, M. J., Keyserling HL, Balser J, Bouveret N, Fries L, and Treanor JJ 2010. Safety, efficacy, and immunogenicity of an inactivated influenza vaccine in healthy adults: a randomized, placebo-controlled trial over two influenza seasons. BMC Infect. Dis. 10: 71. - PMC - PubMed
    1. Monto AS, Ohmit SE, Petrie JG, Johnson E, Truscon R, Teich E, Rotthoff J, Boulton M, and Victor JC. 2009. Comparative efficacy of inactivated and live attenuated influenza vaccines. N. Engl. J. Med. 361: 1260–1267. - PubMed
    1. Beran J, Wertzova V, Honegr K, Kaliskova E, Havlickova M, Havlik J, Jirincova H, Van Belle P, Jain V, Innis B, and Devaster J-M. 2009. Challenge of conducting a placebo-controlled randomized efficacy study for influenza vaccine in a season with low attack rate and a mismatched vaccine B strain: a concrete example. BMC Infect. Dis. 9: 2. - PMC - PubMed

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