Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

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Global analyses of human immune variation reveal baseline predictors of the post-vaccination response.

ABSTRACT: 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

ORGANISM(S): Homo sapiens

SUBMITTER: Yuri Kotliarov

PROVIDER: E-GEOD-47353 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Project description:Background: Tuberculosis (TB) remains a global health problem, with vaccination likely to be a necessary part of a successful control strategy. Results of the first Phase 2b efficacy trial of a candidate vaccine, MVA85A, evaluated in BCG-vaccinated infants were published last year. Although no improvement in efficacy above BCG alone was seen, cryopreserved samples from this trial provide an opportunity to study the immune response to vaccination in this population. Methods: We investigated blood samples taken before vaccination (baseline) and one and 28 days post-vaccination with MVA85A or placebo (Candin). The IFN-γ ELISpot assay was performed at baseline and on day 28 to quantify the adaptive response to Ag85A peptides. Gene expression analysis was performed at all three timepoints to identify early gene signatures predictive of the magnitude of the subsequent adaptive T cell response using the significance analysis of microarrays (SAM) statistical package and gene set enrichment analysis. Results: One day post-MVA85A, there is an induction of inflammatory pathways compared to placebo samples. Modules associated with myeloid cells and inflammation pre- and one day post-MVA85A correlate with a higher IFN-γ ELISpot response post-vaccination. By contrast, previous work done in UK adults shows early inflammation in this population is not associated with a strong T cell response but that induction of regulatory pathways inversely correlates with the magnitude of the T cell response. This may be indicative of important mechanistic differences in how T cell responses develop in these two populations following vaccination with MVA85A. Conclusion: The results suggest the capacity of MVA85A to induce a strong innate response is key to the initiation of an adaptive immune response in South African infants but induction of regulatory pathways may be more important in UK adults. Understanding differences in immune response to vaccination between populations is likely to be an important aspect of developing successful vaccines and vaccination strategies. Trial registration: ClinicalTrials.gov number NCT00953927 PBMC collected pre or 28 days post vaccinated, stimulated with either Ag85A peptides (20 samples) or media alone (60).

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Global analyses of human immune variation reveal baseline predictors of the post-vaccination response.

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