Browse
Submit Data
Databases
API
Help

Dataset Information

30 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Nutrition and Rheumatoid Arthritis in the 'Omics' Era.

ABSTRACT: Modern high-throughput 'omics' science tools (including genomics, transcriptomics, proteomics, metabolomics and microbiomics) are currently being applied to nutritional sciences to unravel the fundamental processes of health effects ascribed to particular nutrients in humans and to contribute to more precise nutritional advice. Diet and food components are key environmental factors that interact with the genome, transcriptome, proteome, metabolome and the microbiota, and this life-long interplay defines health and diseases state of the individual. Rheumatoid arthritis (RA) is a chronic autoimmune disease featured by a systemic immune-inflammatory response, in genetically susceptible individuals exposed to environmental triggers, including diet. In recent years increasing evidences suggested that nutritional factors and gut microbiome have a central role in RA risk and progression. The aim of this review is to summarize the main and most recent applications of 'omics' technologies in human nutrition and in RA research, examining the possible influences of some nutrients and nutritional patterns on RA pathogenesis, following a nutrigenomics approach. The opportunities and challenges of novel 'omics technologies' in the exploration of new avenues in RA and nutritional research to prevent and manage RA will be also discussed.

SUBMITTER: Cassotta M

PROVIDER: S-EPMC7996781 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

Combination therapy for rheumatoid arthritis in the era of biologicals.

Project description:Early, aggressive disease management is critical for halting disease progression and joint destruction in patients with rheumatoid arthritis. Combination therapy with at least two disease-modifying antirheumatic drugs, such as methotrexate (MTX), sulfasalazine, or hydroxychloroquine, is often more effective than monotherapy in reducing disease activity. Biologic therapies represent more effective and tolerable treatment options that, when combined with MTX, have been shown to dramatically reduce inflammation, inhibit radiographic progression, and induce remission. Although several types of treatment strategies are used in clinical practice, the most aggressive approaches that target early disease have shown the most promise in reversing disease progression and reducing disease-related costs.

| S-EPMC2504107 | biostudies-other

Multi-omics monitoring of drug response in rheumatoid arthritis.

Project description:This SuperSeries is composed of the SubSeries listed below. Sustained clinical remission (CR) without drug treatment has not been achieved in patients with rheumatoid arthritis (RA). This implies a substantial difference between CR and the healthy state, but it has yet to be quantified. We report a longitudinal monitoring of the drug response at multi-omics levels in the peripheral blood of patients with RA. Our data reveal that drug treatments alter the molecular profile closer to that of HCs at the transcriptome, serum proteome and immunophenotype level. Patient follow-up suggests that the molecular profile after drug treatments is associated with long-term stable CR. In addition, we identify molecular signatures that are resistant to drug treatments. These signatures are associated with RA independently of known disease severity indexes and are largely explained by the imbalance of neutrophils, monocytes, and lymphocytes. This high-dimensional phenotyping provides a quantitative measure of molecular remission and illustrates a multi-omics approach to understanding drug response.

2018-07-16 | GSE93777 | GEO

Integrative omics analysis of rheumatoid arthritis identifies non-obvious therapeutic targets.

Project description:Identifying novel therapeutic targets for the treatment of disease is challenging. To this end, we developed a genome-wide approach of candidate gene prioritization. We independently collocated sets of genes that were implicated in rheumatoid arthritis (RA) pathogenicity through three genome-wide assays: (i) genome-wide association studies (GWAS), (ii) differentially expression in RA fibroblast-like synoviocytes (FLS), and (iii) differentially methylation in RA FLS. Integrated analysis of these complementary data sets identified a significant enrichment of multi-evidence genes (MEGs) within pathways relating to RA pathogenicity. One MEG is Engulfment and Cell Motility Protein-1 (ELMO1), a gene not previously considered as a therapeutic target in RA FLS. We demonstrated in RA FLS that ELMO1 is: (i) expressed, (ii) promotes cell migration and invasion, and (iii) regulates Rac1 activity. Thus, we created links between ELMO1 and RA pathogenicity, which in turn validates ELMO1 as a potential RA therapeutic target. This study illustrated the power of MEG-based approaches for therapeutic target identification.

| S-EPMC4406750 | biostudies-literature

Nutrition and Rheumatoid Arthritis Onset: A Prospective Analysis Using the UK Biobank.

Project description:Rheumatoid arthritis (RA) is a chronic inflammatory disease that affects the joints. The multifactorial etiopathogenesis of RA has been heavily investigated, but is still only partially understood. Diet can represent both a risk factor and a protective factor, based on some evidence that suggests specific properties of certain foods and their ability to increase/reduce inflammation. To date, the studies done on this topic provide discordant results and are heterogeneous in terms of design and cohort size. In this work, we investigated for the first time the relationship between nutrition and the risk of RA onset using a sample size of about half a million subjects from one of the largest publicly available biobanks that is the UK biobank. Results showed that oily fish, alcohol, coffee and breakfast cereals have protective roles in RA; whereas, tea can increase the risk of RA. In conclusion, the obtained results confirm that diet plays key roles in RA, either by promoting or by preventing RA onset and development. Future research should focus on unravelling the effects of dietary habits on immune-mediated diseases to establish better preventive strategies.

| S-EPMC9025922 | biostudies-literature

Rheumatoid arthritis

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

2004-11-04 | GSE1919 | GEO

Personalized therapies in the cancer "omics" era.

Project description:A molecular hallmark of cancer is the presence of genetic alterations in the tumoral DNA. Understanding how these alterations translate into the malignant phenotype is critical for the adequate treatment of oncologic diseases. Several cancer genome sequencing reports have uncovered the number and identity of proteins and pathways frequently altered in cancer. In this article we discuss how integration of these genomic data with other biological and proteomic studies may help in designing anticancer therapies "a la carte". An important conclusion is that next generation treatment of neoplasias must be based on rational drug combinations that target various pathways and cellular entities that sustain the survival of cancer cells.

| S-EPMC2920264 | biostudies-other

Multi-omics monitoring of drug response in rheumatoid arthritis in pursuit of molecular remission.

Project description:Sustained clinical remission (CR) without drug treatment has not been achieved in patients with rheumatoid arthritis (RA). This implies a substantial difference between CR and the healthy state, but it has yet to be quantified. We report a longitudinal monitoring of the drug response at multi-omics levels in the peripheral blood of patients with RA. Our data reveal that drug treatments alter the molecular profile closer to that of HCs at the transcriptome, serum proteome, and immunophenotype level. Patient follow-up suggests that the molecular profile after drug treatments is associated with long-term stable CR. In addition, we identify molecular signatures that are resistant to drug treatments. These signatures are associated with RA independently of known disease severity indexes and are largely explained by the imbalance of neutrophils, monocytes, and lymphocytes. This high-dimensional phenotyping provides a quantitative measure of molecular remission and illustrates a multi-omics approach to understanding drug response.

| S-EPMC6048065 | biostudies-literature

Rheumatoid arthritis and rheumatoid synovium

Project description:Rheumatoid arthritis (RA) is a heterogeneous disease. We used cDNA microarray technology to subclassify RA patients and disclose disease pathways in rheumatoid synovium. Hierarchical clustering of gene expression data identified two main groups of tissues (RA-I and RA-II). A total of 121 genes were significantly higher expressed in the RA-I tissues, whereas 39 genes were overexpressed in the RA-II tissues. Among the 121 genes overexpressed in RA-I tissues, a relative majority of nine genes are located on chromosome 6p21.3. An interpretation of biological processes that take place revealed that the gene expression profile in RA-I tissues is indicative for an adaptive immune response. The RA-II group showed expression of genes suggestive for fibroblast dedifferentiation. Within the RA-I group, two subgroups could be distinguished; the RA-Ia group showed predominantly immune-related gene activity, while the RA-Ib group showed an additional higher activity of genes indicative for the classical pathway of complement activation. All tissues except the RA-Ia subgroup showed elevated expression of genes involved in tissue remodeling. These results confirm the heterogeneous nature of RA and suggest the existence of distinct pathogenic mechanisms that contribute to RA. The differences in expression profiles provide opportunities to stratify patients based on molecular criteria. An all pairs experiment design type is where all labeled extracts are compared to every other labeled extract. Keywords: all_pairs

2005-12-15 | GSE3824 | GEO

Rheumatoid arthritis and rheumatoid synovium

2005-12-14 | E-GEOD-3824 | biostudies-arrayexpress

Pharmacogenomics of Anti-TNF Treatment Response Marks a New Era of Tailored Rheumatoid Arthritis Therapy.

Project description:Rheumatoid arthritis (RA) is the most commonly occurring chronic inflammatory arthritis, the exact mechanism of which is not fully understood. Tumor Necrosis Factor (TNF)-targeting drugs has been shown to exert high effectiveness for RA, which indicates the key importance of this cytokine in this disease. Nevertheless, the response to TNF inhibitors varies, and approximately one third of RA patients are non-responders, which is explained by the influence of genetic factors. Knowledge in the field of pharmacogenomics of anti-TNF drugs is growing, but has not been applied in the clinical practice so far. Different genome-wide association studies identified a few single nucleotide polymorphisms associated with anti-TNF treatment response, which largely map genes involved in T cell function. Studies of the gene expression profile of RA patients have also indicated specific gene signatures that may be useful to develop novel prognostic tools. In this article, we discuss the significance of TNF in RA and present the current knowledge in pharmacogenomics related to anti-TNF treatment response.

| S-EPMC8879844 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data