Global analyses of human immune variation reveal baseline predictors of post-vaccination responses

• Published in: Cell 2014-04, Vol.157 (2), p.499-513
• Main Authors: Tsang, John S., Schwartzberg, Pamela L., Kotliarov, Yuri, Biancotto, Angelique, Xie, Zhi, Germain, Ronald N., Wang, Ena, Olnes, Matthew J., Narayanan, Manikandan, Golding, Hana, Moir, Susan, Dickler, Howard B., Perl, Shira, Cheung, Foo
• Format: Article
• Language: English
• ISSN: 0092-8674; 1097-4172
• DOI: 10.1016/j.cell.2014.03.031

A major goal of systems biology is the development of models that accurately predict responses to perturbation. Constructing such models requires collection of dense measurements of system states, yet transformation of data into predictive constructs remains a challenge. To begin to model human immunity, we analyzed immune parameters in depth both at baseline and in response to influenza vaccination. Peripheral blood mononuclear cell transcriptomes, serum titers, cell subpopulation frequencies, and B cell responses were assessed in 63 individuals before and after vaccination and used to develop a systematic framework to dissect inter- and intra-individual variation and build predictive models of post-vaccination antibody responses. Strikingly, independent of age and pre-existing antibody titers, accurate models could be constructed using pre-perturbation cell populations alone, which were validated using independent baseline time-points. Most of the parameters contributing to prediction delineated temporally-stable baseline differences across individuals, raising the prospect of immune monitoring before intervention.