ArticleScientific reports2016
Continuous time Bayesian networks identify Prdm1 as a negative regulator of TH17 cell differentiation in humans.
Article in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 17 citations in OpenAlex.
- Single-cell RNA-seq analysis of longitudinal CD4Genome medicine · 2025Article
- BMSC-derived exosomes improve rheumatoid arthritis by regulating Th17 cell differentiation through targeting PRDM1.Regenerative medicine · 2025Article
- A systematic comparison of FOSL1, FOSL2 and BATF-mediated transcriptional regulation during early human Th17 differentiation.Nucleic acids research · 2022Article
- Review
- Modeling Approaches Reveal New Regulatory Networks inJournal of fungi (Basel, Switzerland) · 2020Article
- Meet Our Section Editor.Current genomics · 2019Article
- Comparative analysis of differential gene expression tools for RNA sequencing time course data.Briefings in bioinformatics · 2019Article
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Authors and funding
6 authors at 5 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
T helper 17 (TH17) cells represent a pivotal adaptive cell subset involved in multiple immune disorders in mammalian species. Deciphering the molecular interactions regulating TH17 cell differentiation is particularly critical for novel drug target discovery designed to control maladaptive inflammatory conditions. Using continuous time Bayesian networks over a time-course gene expression dataset, we inferred the global regulatory network controlling TH17 differentiation. From the network, we identified the Prdm1 gene encoding the B lymphocyte-induced maturation protein 1 as a crucial negative regulator of human TH17 cell differentiation. The results have been validated by perturbing Prdm1 expression on freshly isolated CD4(+) naïve T cells: reduction of Prdm1 expression leads to augmentation of IL-17 release. These data unravel a possible novel target to control TH17 polarization in inflammatory disorders. Furthermore, this study represents the first in vitro validation of continuous time Bayesian networks as gene network reconstruction method and as hypothesis generation tool for wet-lab biological experiments.
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