Multi-omics monitoring of drug response in rheumatoid arthritis.
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ABSTRACT:
PROVIDER: PRJNA362343 | ENA |
REPOSITORIES: ENA
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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.
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Project description:Rheumatoid arthritis (RA) is a chronic autoinflammatory disorder that affects small joints. Despite intense efforts, there isno definitive marker yet for early diagnosis RA and for monitoring the progression of this disease. We sought to catalog the proteins present in the synovial fluid of patients with rheumatoid arthritis. To identify lower abundance proteins, we undertook two approaches – we depleted the abundant proteins using a multiple affinity removal system (MARS14) column and we enriched glycoproteins using a lectin affinity column. The peptides were analyzed by LC-MS/MS on a high resolution Fourier transform mass spectrometer.
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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.
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Project description:Genome-wide DNA methylation level was studied to determine whether Rheumatoid arthritis patients (cases) has methylation differences comparing to normal controls in PBLs. We used Illumina HumanMethylation450 BeadChip array to determine the genome-wide DNA methylation difference in PBLs from Rheumatoid arthritis patients (cases) and normal controls Bisulphite converted DNA from the Rheumatoid arthritis patients (cases) and normal controls were hybridized to the Illumina Illumina HumanMethylation450 BeadChip arrays
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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.
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