Dataset Information

B Cells Polarize Pathogenic Inflammatory T Helper Subsets through ICOSL-Dependent Glycolysis

ABSTRACT: B cells constitute abundant cellular components in inflamed human tissues, but their role in pathogenesis of inflammatory T helper (Th) subsets is still unclear. Here, we demonstrate that B cells, particularly resting naïve B cells, have a previously unrecognized helper function that is involved in shaping the metabolic process and subsequent inflammatory differentiation of T-cell-receptor-primed Th cells. ICOS/ICOSL axis-mediated glucose incorporation and utilization were crucial for inflammatory Th subset induction by B cells, and activation of mTOR was critical for T cell glycolysis in this process. Consistently, upon encountering ICOSL+ B cells, activated effector memory Th cells from patients with rheumatoid arthritis or systemic lupus erythematosus spontaneously differentiated into inflammatory Th subsets. Immunotherapy using an anti-CD20 antibody that specifically depleted B cells in patients with rheumatoid arthritis efficiently abrogated the capabilities of memory Th cells to incorporate and utilize glucose, thereby impairing the pathogenic differentiation of inflammatory Th subsets. To examine the metabolic process of Th cells after interacting with autologous B cells, we applied RNA-sequencing to analyze their transcriptional profiles.

ORGANISM(S): Homo sapiens

PROVIDER: GSE144339 | GEO | 2022/06/30

REPOSITORIES: GEO

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Project description:Baker2013 - Cytokine Mediated Inflammation in Rheumatoid Arthritis This model by Baker M. 2013, describes the interaction between pro and anti-inflammatory cytokine signalling in rheumatoid arthritis. Using two ordinary differential equations, the first model [BIOMD0000000550] analyses bifurcation and describes different pathological states by altering inflammatory regulation parameters. The second model [BIOMD0000000549] includes the effect that ageing has on pro-inflammatory signalling, allowing for time-dependant properties and disease progression to be observed. The author also describes potential dosing for reversal of the disease state. This model is described in the article: Mathematical modelling of cytokine-mediated inflammation in rheumatoid arthritis. Baker M, Denman-Johnson S, Brook BS, Gaywood I, Owen MR. Math Med Biol 2013 Dec; 30(4): 311-337 Abstract: Rheumatoid arthritis (RA) is a chronic inflammatory disease preferentially affecting the joints and leading, if untreated, to progressive joint damage and disability. Cytokines, a group of small inducible proteins, which act as intercellular messengers, are key regulators of the inflammation that characterizes RA. They can be classified into pro-inflammatory and anti-inflammatory groups. Numerous cytokines have been implicated in the regulation of RA with complex up and down regulatory interactions. This paper considers a two-variable model for the interactions between pro-inflammatory and anti-inflammatory cytokines, and demonstrates that mathematical modelling may be used to investigate the involvement of cytokines in the disease process. The model displays a range of possible behaviours, such as bistability and oscillations, which are strongly reminiscent of the behaviour of RA e.g. genetic susceptibility and remitting-relapsing disease. We also show that the dose regimen as well as the dose level are important factors in RA treatments. This model is hosted on BioModels Database and identified by: BIOMD0000000550. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

Project description:Baker2013 - Cytokine Mediated Inflammation in Rheumatoid Arthritis - Age Dependant This model by Baker M. 2013, describes the interaction between pro and anti-inflammatory cytokine signalling in rheumatoid arthritis. Using two ordinary differential equations, the first model [BIOMD0000000550] analyses bifurcation and describes different pathological states by altering inflammatory regulation parameters. The second model [BIOMD0000000549] includes the effect that ageing has on pro-inflammatory signalling, allowing for time-dependant properties and disease progression to be observed. The author also describes potential dosing for reversal of the disease state. This model is described in the article: Mathematical modelling of cytokine-mediated inflammation in rheumatoid arthritis. Baker M, Denman-Johnson S, Brook BS, Gaywood I, Owen MR. Math Med Biol 2013 Dec; 30(4): 311-337 Abstract: Rheumatoid arthritis (RA) is a chronic inflammatory disease preferentially affecting the joints and leading, if untreated, to progressive joint damage and disability. Cytokines, a group of small inducible proteins, which act as intercellular messengers, are key regulators of the inflammation that characterizes RA. They can be classified into pro-inflammatory and anti-inflammatory groups. Numerous cytokines have been implicated in the regulation of RA with complex up and down regulatory interactions. This paper considers a two-variable model for the interactions between pro-inflammatory and anti-inflammatory cytokines, and demonstrates that mathematical modelling may be used to investigate the involvement of cytokines in the disease process. The model displays a range of possible behaviours, such as bistability and oscillations, which are strongly reminiscent of the behaviour of RA e.g. genetic susceptibility and remitting-relapsing disease. We also show that the dose regimen as well as the dose level are important factors in RA treatments. This model is hosted on BioModels Database and identified by: BIOMD0000000549. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

Dataset Information

B Cells Polarize Pathogenic Inflammatory T Helper Subsets through ICOSL-Dependent Glycolysis

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets