Investigating Duchenne muscular dystrophy biology through plasma proteome
Identify disease biomarkers and deregulated pathways in Duchenne muscular dystrophy from omic data We developed a two-step computational workflow to extract...
Extract a transcriptional biomarker to predict the efficacy of trivalent influenza vaccines and expand our understanding of the early events following the vaccination.
By applying our normalization-free algorithm for biomarker identification to a transcriptomic dataset from peripheral blood mononuclear cells (PBMCs), we identified a biomarker whose early response was able to discriminate low- from high-responder subjects one month after the vaccination. The identified biomarker was then validated using a separate study including vaccination campaigns spanning a total of three years.
From the analysis of the biomarker, we identified pre-existing immunity against one or more of the vaccine antigens as a confounding factor. We also introduced a composite response measure, which better accounts for the responses to the different strains represented in the vaccine with respect to other indices introduced in literature.
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Marchetti L, Siena E, Lauria M, Maffione D, Pacchiani N, Priami C, Medini D, Exploring the Limitations of Peripheral Blood Transcriptional Biomarkers in Predicting Influenza Vaccine Responsiveness, Complexity, vol. 2017, Article ID 3017632, 9 pages, 2017. https://doi.org/10.1155/2017/3017632