Changes in neutrophil gene expression in psoriatic arthritis patients in response to sekukinumab
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE179800 | GEO | 2023/01/06
REPOSITORIES: GEO
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Project description:Characterize active synovial fluid (SF) serine proteinases in psoriatic arthritis (PsA) in comparison to osteoarthritis (OA) and rheumatoid arthritis (RA)
2021-03-29 | PXD022442 | Pride
Project description:To identify the cell populations in synovial fluid (SF) from psoriatic arthritis (PsA) patients, single cell 3’-RNA-sequencing of cells from PsA SF samples (n=3) was performed using the 10X Genomics platform. Twelve main clusters of cells were predicted and the most abundant clusters had a predominance of monocytes/macrophages gene expression patterns.
2020-12-15 | GSE161500 | GEO
Project description:CD69+CD103+ tissue-resident memory T-cells (TRM) are increasingly recognised as important drivers of inflammation. To decipher their potential role in inflammatory arthritis, we applied single cell, high-dimensional profiling (CyTOF and scRNAseq) to T-cells isolated from the joint of patients with psoriatic arthritis (PsA) or rheumatoid arthritis (RA). We identified three broad groups of synovial CD8+ TRM cells: cytotoxic and Treg-like TRM cells were present in the inflamed joints of patients with both PsA and RA, while CD161+CXCR6+ type 17-like TRM cells with a pro-inflammatory cytokine profile (IL-17A+TNFa+IFNg+) and a distinct transcriptomic signature and a polyclonal, but distinct TCR repertoire, were specifically enriched in the inflamed joints of patients with PsA. Type 17-like cells were also enriched in non-TRM CD8+ T-cells in PsA compared to RA. These findings add substantively to the accumulating evidence that the immunopathology of PsA and RA is different, with a particular role for type 17 cells in PsA.
2023-05-17 | GSE216914 | GEO
Project description:Psoriatic arthritis (PsA) is a chronic inflammatory joint disease, and the diagnosis is quite difficult due to the unavailability of reliable clinical markers. This study aimed to investigate the fecal metabolites in PsA by comparison with rheumatoid arthritis (RA), and to identify potential diagnostic biomarkers for PsA. The metabolic profiles of the fecal samples from 27 PsA and 29 RA patients as well as 36 healthy controls (HCs) were performed on ultra-high-performance liquid chromatography coupled with hybrid triple quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOF-MS). And differentially altered metabolites were screened and assessed using multivariate analysis for exploring the potential biomarkers of PsA. The results showed that 154 fecal metabolites were significantly altered in PsA patients when compared with HCs, and 45 metabolites were different when compared with RA patients. A total of 14 common differential metabolites could be defined as candidate biomarkers. Furthermore, a support vector machines (SVM) model was performed to distinguish PsA from RA patients and HCs, and 5 fecal metabolites, including α/β-turmerone, glycerol 1-hexadecanoate, dihydrosphingosine, pantothenic acid and glutamine, were determined as biomarkers for PsA. Through the metabolic pathways analysis, we found that the abnormality of amino acid metabolism, bile acid metabolism and lipid metabolism might contribute to the occurrence and development of PsA. In summary, our research provided ideas for the early diagnosis and treatment of PsA by identifying fecal biomarkers and analyzing metabolic pathways.
2022-02-23 | MTBLS4206 | MetaboLights
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: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 T cell-mediated chronic autoimmune/inflammatory disease. While some patients experience disease limited to the skin (skin psoriasis), others develop joint involvement (psoriatic arthritis; PsA). In the absence of disease- and/or outcome-specific biomarkers, and as arthritis can precede skin manifestations, diagnostic and therapeutic delays are common and contribute to disease burden and damage accrual. Objective: Altered epigenetic marks, including DNA methylation, contribute to effector T cell phenotypes and altered cytokine expression in autoimmune/inflammatory diseases. This project aimed at the identification of disease-/outcome-specific DNA methylation signatures in CD8+ T cells from patients with psoriasis and PsA as compared to heathy controls. Method: Peripheral blood CD8+ T cells from 9 healthy controls, 10 psoriasis and 7 PsA patients were collected to analyze DNA methylation marks using Illumina Human Methylation EPIC BeadChips (>850,000 CpGs per sample). Bioinformatic analysis was performed using R (minfi, limma, ChAMP and DMRcate packages). Results: DNA methylation profiles in CD8+ T cells differentiate healthy controls from psoriasis patients (397 Differentially Methylated Positions (DMPs); 9 Differentially Methylated Regions (DMRs) when ≥CpGs per DMR were considered; 2 DMRs for ≥10 CpGs). Furthermore, patients with skin psoriasis can be discriminated from PsA patients (1861 DMPs, 20 DMRs (≥5 CpGs per region), 4 DMRs (≥10 CpGs per region)). Gene ontology (GO) analyses considering genes with ≥1 DMP in their promoter delivered methylation defects in skin psoriasis and PsA primarily affecting the BMP signaling pathway and endopeptidase regulator activity, respectively. GO analysis of genes associated with DMRs between skin psoriasis and PsA demonstrated an enrichment of GABAergic neuron and cortex neuron development pathways. Treatment with cytokine blockers associated with DNA methylation changes (2372 DMPs; 1907 DMPs within promoters, 7 DMRs (≥5CpG per regions)) affecting transforming growth factor beta receptor and transmembrane receptor protein serine/threonine kinase signaling pathways. Lastly, a methylation score including TNF and IL-17 pathway associated DMPs inverse correlates with skin disease activity scores (PASI). Conclusion: Patients with skin psoriasis exhibit DNA methylation patterns in CD8+ T cells that allow differentiation from PsA patients and healthy individuals, and reflect clinical activity of skin disease. Thus, DNA methylation profiling promises potential as diagnostic and prognostic tool to be used for molecular patient stratification towards individualized treatment. This project aimed at the identification of disease-/outcome-specific DNA methylation signatures in CD8+ T cells from patients with psoriasis and PsA as compared to heathy controls.
2021-09-22 | GSE184500 | GEO
Project description:This study shows the pronounced expansion of CD8 T cell clones at sites of active inflammation within the joints of psoriatic arthritis (PsA) patients compared to blood, and characterises the gene expression of expanded clones using droplet based single cell RNA sequencing. Mononuclear cells were separated from freshly acquired paired peripheral blood and synovial fluid samples from 3 PsA patients using density gradient separation, then enriched for CD4 and CD8 T cells using FACS. Additionally, CD45+ leukocytes were enriched by FACS from the cryopreserved synovial tissue of 2 further PsA patients. All cells were then processed using a 10x Chromium Controller and sequenced by Illumina HiSeq 4000 (peripheral blood / synovial fluid) or NovaSeq with S2 flowcell (synovial tissue).
2020-09-07 | E-MTAB-9492 | biostudies-arrayexpress
Project description:Whole genome sequencing of immune cells from patients diagnosed with psoriatic arthritis
| EGAS00001002822 | EGA
Project description:Psoriatic disease is a multifactorial inflammatory condition spanning from skin and nail psoriasis (Pso) to spine and joint involvement characterizing psoriatic arthritis (PsA). Monozygotic twins provide a model to investigate genetic, early life environmental exposure and stochastic influences to complex diseases, mainly mediated by epigenetics. We performed a genome-wide DNA methylation study on whole blood of monozygotic twins from 7 pairs discordant for Pso/PsA using the Infinium Methylation EPIC array (Illumina). MeDiP – qPCR was used to confirm specific signals. Data were replicated in an independent cohort of 7 patients with Pso/PsA and 3 healthy controls. We identified 2,564 differentially methylated positions between psoriatic disease and controls, corresponding to 1,703 genes, 59% within gene bodies. There were 19 regions with at least two DMPs within 1 kb of distance and significant within-pair Δβ-values (p<0.005), among them SNX25, BRG1 and SMAD3 genes, all involved in TGF-β signaling pathway, were identified. Co-expression analyses on transcriptome data identified IL-6/JAK/STAT3 and TNF-alpha pathways as important signaling axes involved in the disease, and they also suggested an altered glucose metabolism in patients’ immune cells, characteristic of pro-inflammatory T lymphocytes. The study suggests the presence of an epigenetic signature in affected individuals, pointing to genes involved in immunological and inflammatory responses. This result is also supported by transcriptome data, that altogether suggest a higher activation state of the immune system, that could promote the disease status.
2021-12-15 | GSE186713 | GEO