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Multi-omics analysis in primary T cells elucidates mechanisms behind disease associated genetic loci

ABSTRACT: Background: Genome wide association studies (GWAS) have uncovered the genetic basis behind many diseases and conditions. However, most of these genetic loci affect regulatory regions, making the interpretation challenging. Chromatin conformation has a fundamental role in gene regulation and is frequently used to associate potential target genes to regulatory regions. However, previous studies mostly used small sample sizes and immortalized cell lines instead of primary cells. Results: Here we present the most extensive dataset of chromatin conformation with matching gene expression and chromatin accessibility from primary CD4+ and CD8+ T cells to date, isolated from psoriatic arthritis patients and healthy controls. We generated 108 Hi-C libraries (49 billion reads), 128 RNA-seq libraries and 126 ATAC-seq libraries. These data enhance our understanding of the mechanisms by which GWAS variants impact gene regulation, revealing how genetic variation alters chromatin accessibility and structure in primary cells at an unprecedented scale. We refine the mapping of GWAS loci to implicated regulatory elements, such as CTCF binding sites and other enhancer elements, aiding gene assignment. We uncover BCL2L11 as the probable causal gene within the rheumatoid arthritis (RA) locus rs13396472, despite the GWAS variants’ intronic positioning relative to ACOXL, and we identify mechanisms involving SESN3 dysregulation in the RA locus rs4409785. Conclusions: Given these genes’ significant role in T cell development and maturation, our work deepens our comprehension of autoimmune disease pathogenesis, suggesting potential treatment targets. In addition, our dataset provides a valuable resource for the investigation of immune mediated diseases and gene regulatory mechanisms.

ORGANISM(S): Homo sapiens

PROVIDER: GSE282992 | GEO | 2024/12/18

REPOSITORIES: GEO

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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.

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Multi-omics analysis in primary T cells elucidates mechanisms behind disease associated genetic loci

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