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E-GEOD-47353 - Global analyses of human immune variation reveal baseline predictors of the post-vaccination response

Released on 10 April 2014, last updated on 11 April 2014
Homo sapiens
Samples (292)
Array (1)
Protocols (7)
A major goal of systems biology is the development of models that accurately predict responses of a cell or organism to perturbation. Constructing such models requires collection of dense measurements of system states, yet transformation of the data into predictive constructs remains a challenge. As a first step towards modeling human immunity, we have analyzed immune parameters in depth both at baseline and in response to perturbation with influenza vaccination. Peripheral blood cell transcriptomes, serum titers, frequencies of 126 cell subpopulations, and B cell responses were assessed before and after vaccination in 63 individuals and used to develop a systematic, computational 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 parameters alone, which were validated using data from independent baseline time-points. Most of the parameters contributing to prediction delineated temporally-stable baseline differences across individuals, raising the prospect of immune responsiveness prediction before intervention. According to CHI protocol 09-H1-0239, PBMC samples from 63 healthy voluntiers were collected 7 days prior to vaccination, immediately before vaccination (day0), and at 3 time points (day1, day7 and day70) post vaccination. The CHI Consortium
Experiment type
transcription profiling by array 
Angelique Biancotto, Ena Wang, Foo Cheung, Hana Golding, Howard B Dickler, John S Tsang, Manikandan Narayanan, Matthew J Olnes, Pamela L Schwartzberg, Ronald N Germain, Shira Perl, Susan Moir, Yuri Kotliarov, Zhi Xie