Human gut metagenome
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA714758 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Autoimmune diseases, such as rheumatoid arthritis, are associated with significant gut microbiota dysbiosis. Here we show that remodelling of 24h rhythms within the gut during inflammatory joint disease drives profound changes in the microbiome and gut permeability.
2023-03-15 | GSE184233 | GEO
Project description:This is the first high-throughput analysis of DNA methylation in autoimmune diseases. We have used a cohort of MZ twins discordant for three diseases whose clinical signs often overlap: systemic lupus erythematosus (SLE), rheumatoid arthritis and dermatomyositis. Only MZ twins discordant for SLE featured widespread changes in the DNA methylation status of a significant number of genes. Individual analysis confirmed the existence of DNA methylation and expression changes in genes relevant to SLE pathogenesis. Our findings not only identify potentially relevant DNA methylation markers for the clinical characterization of SLE patients but also support the notion that epigenetic changes may be critical in the clinical manifestations of autoimmune disease. Total DNA isolated by standard procedures from 59 White Blood Cell (WBC) samples corresponding to monozygotic twins discordant for three different autoimmune diseases: systemic lupus erythematosus (SLE), rheumatoid arthritis (RA) and dermatomyositis (DM) and two additional controls for each MZ twin pair.
2009-11-16 | E-GEOD-19033 | biostudies-arrayexpress
Project description:Gut microbiome associated to rheumatoid arthritis Metagenome
| PRJNA858836 | ENA
Project description:The Lung Microbiome in Rheumatoid Arthritis and Autoimmunity
| PRJNA330624 | ENA
Project description:Rheumatoid arthritis (RA) is a chronic, inflammatory joint disease of unknown etiology and pronounced inter-patient heterogeneity. To characterize RA at the molecular level and to uncover key pathomechanisms, we performed whole-genome gene expression analyses. Synovial tissues from rheumatoid arthritis patients were compared to those from osteoarthritis patients and to normal donors. Keywords: disease state analysis Two disease conditions (rheumatoid arthritis and osteoarthritis) in comparison to normal donors were investigated. For the two disease groups samples derived from three individual patients and two pools of patients were hybridised.
2004-11-04 | E-GEOD-1919 | biostudies-arrayexpress
Project description:Myocardial interstitial fibrosis is a common thread in multiple cardiovascular diseases including heart failure, atrial fibrillation, conduction disease and sudden cardiac death. To investigate the biologic pathways that underlie interstitial fibrosis in the human heart, we developed a machine learning model to measure myocardial T1 time, a marker of myocardial interstitial fibrosis, in 41,505 UK Biobank participants. Greater T1 time was associated with diabetes mellitus, renal disease, aortic stenosis, cardiomyopathy, heart failure, atrial fibrillation, conduction disease and rheumatoid arthritis. Mendelian randomization analysis supported a potential causal role for diabetes mellitus type 1 in myocardial interstitial fibrosis. In genome-wide association analysis, we identified 11 independent loci associated with native myocardial T1 time. The identified loci implicated genes involved in glucose transport (SLC2A12), iron homeostasis (HFE, TMPRSS6), tissue repair (ADAMTSL1, VEGFC), oxidative stress (SOD2), cardiac hypertrophy (MYH7B) and calcium signaling (CAMK2D). Transcriptome-wide association studies highlighted the role of expression of ADAMTSL1 and SLC2A12 in human cardiac tissue in modulating myocardial interstitial fibrosis. Using a TGFβ1-mediated cardiac fibroblast activation assay, we found that 9 out of the 11 genome-wide significant loci comprised genes that exhibited temporal changes in expression and/or open chromatin conformation supporting the biological relevance of these loci to myocardial fibrosis and myofibroblast cell state acquisition. Harnessing machine learning to perform large-scale phenotyping of interstitial fibrosis in the human heart, our results yield novel insights into biologically relevant pathways to myocardial fibrosis and prioritize a number of pathways for further investigation.
2023-03-11 | GSE225336 | GEO
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.
2014-09-25 | BIOMD0000000549 | BioModels
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.
2014-09-25 | BIOMD0000000550 | BioModels
Project description:Intent of this experiment is to define the baseline transcriptome of the synovium obtained from rheumatoid arthritis patients prior to initiation of DMARD (Disease-modifying antirheumatic drug) therapy and compare it with the synovial transcriptome of rheumatoid arthritis patients with an established disease profile.
2022-06-01 | E-MTAB-11274 | biostudies-arrayexpress