Identifying Serum Metabolomic Markers Associated with Skin Disease Activity in patients with Psoriatic Arthritis
Ontology highlight
ABSTRACT:
INSTRUMENT(S): Q Exactive Plus
ORGANISM(S): Homo Sapiens (ncbitaxon:9606)
SUBMITTER: 
Vinod Chandran
PROVIDER: MSV000092967 | MassIVE |
REPOSITORIES: MassIVE
Similar Datasets
Project description:This dataset contains .RAW files acquired for the paper: Identifying Serum Metabolomic Markers Associated with Skin Disease Activity in patients with Psoriatic Arthritis.
| MSV000092967 | GNPS
Project description:Psoriatic arthritis (PsA) is a chronic, systemic, immune-mediated inflammatory disease causing cutaneous and musculoskeletal inflammation that affects 25% of patients with psoriasis. Current methods for evaluating PsA disease activity are not accurate enough for precision medicine. A metabolomics-based approach can elucidate psoriatic disease pathogenesis, providing potential objective biomarkers. With the hypothesis that serum metabolites are associated with skin disease activity, we aimed to identify serum metabolites associated with skin activity in PsA patients. We obtained serum samples from patients with PsA (n = 150) who were classified into mild, moderate and high disease activity groups based on the Psoriasis Area Severity Index. We used solid-phase microextraction (SPME) for sample preparation, followed by data acquisition via an untargeted liquid chromatography-mass spectrometry (LC-MS) approach. Disease activity levels were predicted using identified metabolites and machine learning algorithms. Some metabolites tentatively identified include eicosanoids with anti- or pro-inflammatory properties, like 12-Hydroxyeicosatetraenoic acid, which was previously implicated in joint disease activity in PsA. Other metabolites of interest were associated with dysregulation of fatty acid metabolism and belonged to classes such as bile acids, oxidized phospholipids, and long-chain fatty acids. We have identified potential metabolites associated with skin disease activity in PsA patients.
| S-EPMC10607811 | biostudies-literature
Project description:Background: Psoriasis is a systemic inflammatory disease primarily affecting the skin. Approximately one-third of psoriasis patients develop joint involvement and are diagnosed with psoriatic arthritis (PsA). While, inIn adult-onset disease, adults, the development of arthritis usually follows skin psoriasis, but approximately 15% experience arthritis first, which can delay diagnosis. While the pathophysiology of psoriasis and PsA is incompletely understood, epigenetic dysregulation affecting CD4+ and CD8+ T-cells has been suggested. Objectives: This project aimed to identify disease-associated DNA methylation signatures in CD4+ T-cells from psoriasis and PsA patients that may be used as diagnostic and/or prognostic biomarkers. Methods: PBMCs were collected from 12 patients with chronic plaque skin psoriasis and 8 PsA patients, and 8 healthy controls. CD4+ T-cells were separated through FACS sorting, and DNA methylation profiling was performed (Illumina EPIC850K arrays). Bioinformatic analyses, including gene ontology (GO) and KEGG pathway analysis, were performed using R software. To identify genes under the control of interferon (IFN), the Interferome database was consulted, and DNA Methylation Scores were calculated. Results: Numbers and proportions of CD4+ T-cell subsets (naïve, central memory, effector memory, CD45RA re-expressing effector memory cells) did not vary between controls, skin psoriasis and PsA patients. 883 differentially methylated positions (DMPs) affecting 548 genes were identified between healthy controls and “all” psoriasis patients. Principal component and partial least-squares discriminant analysis separated controls from skin psoriasis and PsA patients. GO analysis considering promoter DMPs delivered hypermethylation of genes involved in “regulation of wound healing, spreading of epidermal cells”, “negative regulation of cell-substrate junction organization” and “negative regulation of focal adhesion assembly”. Comparing controls and “all” psoriasis, a majority of DMPs mapped to IFN-related genes (69.2%). Notably, DNA methylation profiles also distinguished skin psoriasis from PsA patients (2,949 DMPs/1,084 genes) through genes affecting “cAMP-dependent protein kinase inhibitor activity” and “cAMP-dependent protein kinase regulator activity” (GO analysis). Treatment with cytokine inhibitors (IL-17/TNF) corrected DNA methylation patterns of IL-17/TNF-associated genes, and methylation scores correlated with skin disease activity scores (PASI). Conclusion: DNA methylation profiles in CD4+ T-cells discriminate between skin psoriasis and PsA. DNA methylation signatures may be applied for quantification of disease activity and patient stratification towards individualized treatment. The aim of this study was to identify disease-associated DNA methylation signatures in CD4+ T-cells from patients with psoriasis and PsA that may be used as diagnostic and/or prognostic biomarkers to inform treatment and care.
2023-09-14 | GSE236695 | GEO
Project description:Background: Psoriasis is a systemic inflammatory disease primarily affecting the skin. Approximately one-third of psoriasis patients develop joint involvement and are diagnosed with psoriatic arthritis (PsA). While, inIn adult-onset disease, adults, the development of arthritis usually follows skin psoriasis, but approximately 15% experience arthritis first, which can delay diagnosis. While the pathophysiology of psoriasis and PsA is incompletely understood, epigenetic dysregulation affecting CD4+ and CD8+ T-cells has been suggested. Objectives: This project aimed to identify disease-associated DNA methylation signatures in CD4+ T-cells from psoriasis and PsA patients that may be used as diagnostic and/or prognostic biomarkers. Methods: PBMCs were collected from 12 patients with chronic plaque skin psoriasis and 8 PsA patients, and 8 healthy controls. CD4+ T-cells were separated through FACS sorting, and DNA methylation profiling was performed (Illumina EPIC850K arrays). Bioinformatic analyses, including gene ontology (GO) and KEGG pathway analysis, were performed using R software. To identify genes under the control of interferon (IFN), the Interferome database was consulted, and DNA Methylation Scores were calculated. Results: Numbers and proportions of CD4+ T-cell subsets (naïve, central memory, effector memory, CD45RA re-expressing effector memory cells) did not vary between controls, skin psoriasis and PsA patients. 883 differentially methylated positions (DMPs) affecting 548 genes were identified between healthy controls and “all” psoriasis patients. Principal component and partial least-squares discriminant analysis separated controls from skin psoriasis and PsA patients. GO analysis considering promoter DMPs delivered hypermethylation of genes involved in “regulation of wound healing, spreading of epidermal cells”, “negative regulation of cell-substrate junction organization” and “negative regulation of focal adhesion assembly”. Comparing controls and “all” psoriasis, a majority of DMPs mapped to IFN-related genes (69.2%). Notably, DNA methylation profiles also distinguished skin psoriasis from PsA patients (2,949 DMPs/1,084 genes) through genes affecting “cAMP-dependent protein kinase inhibitor activity” and “cAMP-dependent protein kinase regulator activity” (GO analysis). Treatment with cytokine inhibitors (IL-17/TNF) corrected DNA methylation patterns of IL-17/TNF-associated genes, and methylation scores correlated with skin disease activity scores (PASI). Conclusion: DNA methylation profiles in CD4+ T-cells discriminate between skin psoriasis and PsA. DNA methylation signatures may be applied for quantification of disease activity and patient stratification towards individualized treatment. The aim of this study was to identify disease-associated DNA methylation signatures in CD4+ T-cells from patients with psoriasis and PsA that may be used as diagnostic and/or prognostic biomarkers to inform treatment and care.
2023-09-14 | GSE236694 | GEO
Project description:Psoriatic arthritis skin lesions and uninvolved bulk RNA-seq
| PRJNA847432 | ENA
Project description:The lack of diagnostic markers limits the window of effectiveness for rheumatoid arthritis (RA) therapies. Here, we isolated exosomes of serum samples from four distinct groups RA patients, according to disease activity and with/without medication. Then, total RNA of exosomes was extracted for whole-transcriptome sequencing. Focusing on lncRNA sequencing, gene ontology (GO) and kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analyses were performed. We found that the number of upregulated lncRNAs were significantly higher than that of downregulated lncRNAs in each four RA groups. And most importantly, we identified two specific lncRNAs from differentially expressed lncRNAs, TCONS_I2_00013502 (up-regulated) and ENST00000363624 (down-regulated) in RA. Receiver Operating Characteristic (ROC) curve analysis showed that the two lncRNAs were promising biomarkers for RA diagnosis. These findings highlight lncRNAs of the serum exosome are important biomarkers and provide application potential for diagnosis of RA.
2024-07-04 | GSE271161 | GEO
Project description:ObjectiveA considerable proportion of patients with rheumatoid arthritis (RA) do not have a satisfactory response to biological therapies. We investigated the use of metabolomics approach to identify biomarkers able to anticipate the response to biologics in RA patients.MethodsDue to gender differences in metabolomic profiling, the analysis was restricted to female patients starting etanercept as the first biological treatment and having a minimum of six months' follow-up. Each patient was evaluated by the same rheumatologist before and after six months of treatment. At this time, the clinical response (good, moderate, none) was determined according to the EUropean League Against Rheumatism (EULAR) criteria, based on both erythrocyte sedimentation rate (EULAR-ESR) and C-reactive protein (EULAR-CRP). Sera collected prior and after six months of etanercept were analyzed by 1H-nuclear magnetic resonance (NMR) spectroscopy in combination with multivariate data analysis.ResultsTwenty-seven patients were enrolled: 18 had a good/moderate response and 9 were non responders according to both EULAR-ESR and EULAR-CRP after six months of etanercept. Metabolomic analysis at baseline was able to discriminate good, moderate, and non-responders with a very good predictivity (Q2 = 0.68) and an excellent sensitivity, specificity, and accuracy (100%). In good responders, we found an increase in isoleucine, leucine, valine, alanine, glutamine, tyrosine, and glucose levels and a decrease in 3-hydroxybutyrate levels after six months of treatment with etanercept with respect to baseline.ConclusionOur study confirms the potential of metabolomic analysis to predict the response to biological agents. Changes in metabolic profiles during treatment may help elucidate their mechanism of action.
| S-EPMC4641599 | biostudies-literature
Project description:Anti-TNF therapy has transformed the management of rheumatoid arthritis (RA); however little is known about its effects on cell mediated immune responses and TNF-inducible activity at the site of inflammation. Here, we used the tuberculin skin test (TST) as a standardised in vivo human challenge model to make systems level assessments of the effects of anti-TNF therapy in a prototypic cell mediated immune response. RA patients (treated with monoclonal anti-TNF antibodies (adalimumab or infliximab), the soluble TNF receptor etanercept or the standard therapy methotrexate) and healthy volunteers with immunological memory to Mycobacterium tuberculosis antigens were identified using an interferon-γ release assay of peripheral blood. Two units tuberculin or an equivalent volume of saline was injected into the forearm of study participants (n=50). After 72 hours, 3 mm skin punch biopsies were taken from the injection site and processed for whole genome transcriptional profiling by Agilent gene microarray.
2017-08-04 | E-MTAB-5093 | biostudies-arrayexpress
Project description:Gene expression alterations in ankle joints of wild type or mast cell-deficient mice during serum transferred arthritis. Specific genes were selected from the whole array by gene name and their expression levels were compared. All other genes have been excluded from the data files.
2011-11-17 | E-MTAB-844 | biostudies-arrayexpress
Project description:Genome wide DNA methylation profiling of monocytes from healthy donors and rheumatoid arthritis patients. The Illumina Infinium MethylationEPIC Beadchip was used to obtain DNA methylation profiles across approximately 850,000 CpGs in CD11b+CD33+CD15neg monocytes isolated from PBMCs of 17 healthy donors and 47 rheumatoid arthritis patients with different disease activity scores (DAS28).
2019-12-31 | GSE134429 | GEO