Integrative mapping of preexisting influenza immune landscapes predicts vaccine response
Stephanie Hao, … , Thushan I. de Silva, Adriana Tomic
Stephanie Hao, … , Thushan I. de Silva, Adriana Tomic
Published July 15, 2025
Citation Information: J Clin Invest. 2025;135(18):e189300. https://doi.org/10.1172/JCI189300.
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Clinical Research and Public Health Clinical Research Immunology Virology

Integrative mapping of preexisting influenza immune landscapes predicts vaccine response

Abstract

BACKGROUND Predicting individual vaccine responses is a substantial public health challenge. We developed Immunaut, an open-source, data-driven framework for systems vaccinologists to analyze and predict immunological outcomes across diverse vaccination settings, beyond traditional assessments.METHODS Using a comprehensive live attenuated influenza vaccine (LAIV) dataset from 244 Gambian children, Immunaut integrated prevaccination and postvaccination humoral, mucosal, cellular, and transcriptomic data. Through advanced modeling, our framework provided a holistic, systems-level view of LAIV-induced immunity.RESULTS The analysis identified 3 distinct immunophenotypic profiles driven by baseline immunity: (a) CD8+ T cell responders with strong preexisting immunity boosting memory T cell responses; (b) mucosal responders with prior influenza A virus immunity developing robust mucosal IgA and subsequent influenza B virus seroconversion; and (c) systemic, broad influenza A virus responders starting from immune naivety who mounted broad systemic antibody responses. Pathway analysis revealed how preexisting immune landscapes and baseline features, such as mucosal preparedness and cellular support, quantitatively dictate vaccine outcomes.CONCLUSION Our findings emphasize the power of integrative, predictive frameworks for advancing precision vaccinology. The Immunaut framework is a valuable resource for deciphering vaccine response heterogeneity and can be applied to optimize immunization strategies across diverse populations and vaccine platforms.FUNDING Wellcome Trust (110058/Z/15/Z); Bill & Melinda Gates Foundation (INV-004222); HIC-Vac Consortium; NIAID (R21 AI151917); NIAID CEIRR Network (75N93021C00045).

Authors

Stephanie Hao, Ivan Tomic, Benjamin B. Lindsey, Ya Jankey Jagne, Katja Hoschler, Adam Meijer, Juan Manuel Carreño Quiroz, Philip Meade, Kaori Sano, Chikondi Peno, André G. Costa-Martins, Debby Bogaert, Beate Kampmann, Helder Nakaya, Florian Krammer, Thushan I. de Silva, Adriana Tomic

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Figure 4

Baseline immune landscape and viral shedding profiles predictive of LAIV response groups.

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Baseline immune landscape and viral shedding profiles predictive of LAIV...
(A) Heatmap of baseline immune features predictive of LAIV response groups, organized by hierarchical clustering to show feature relationships and variations across groups (Euclidean distance, Ward’s D2 clustering method). Each cell reflects a scaled expression level, with red representing high expression and blue indicating low expression, revealing the distribution of immune features at baseline across the identified immunophenotypic clusters. (B) The proportion of seropositive children (HAI titer ≥10) at baseline (before vaccination) within each responder group and across all 3 LAIV-strains, pH1N1, H3N2, and influenza B virus. (C) The proportion of children that shed LAIV strains (pH1N1, H3N2, and B) on day 2 and day 7 after vaccination across all 3 responder groups. (D) Box plots showing baseline features, including H3N2 HAI geometric mean titer (gmt), titer of antibodies binding H3 HA from A/Switzerland/9715293/2013 analyzed by influenza virus protein microarray (H3 HA SWISS IVPM), titer of antibodies binding NA from group 2 (N2) and frequency of influenza B virus HA–specific CD8+ T cells producing IFN-γ across all 3 responder groups, CD8+ T cell responders (green); mucosal responders (orange); and systemic, broad influenza A virus responders (purple). Box plots denote minimum to maximum values, and points are all individuals within the group. *P < 0.05, **P < 0.01, ***P < 0.001, and ****P < 0.0001, by 1-way ANOVA Kruskal-Wallis test with Dunn’s multiple-comparison test to adjust for multiple testing. (E) Forest plots showing log-odds estimates from a logistic regression model. The plots illustrate the association of the mucosal responder (orange) and systemic, broad influenza A virus responder (purple) groups with the outcomes of viral shedding (day 2 and 7) and HAI seropositivity, relative to the CD8 T-cell responder group which serves as the reference category. The analysis is stratified by LAIV strain (H3N2, pH1N1, and B), and the error bars represent the confidence intervals for the log-odds estimates.