Epigenomic analysis of sperm cells from patients with psoriatic arthritis, psoriasis without arthritis, and healthy controls
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE126017 | GEO | 2019/02/02
REPOSITORIES: GEO
Similar Datasets
Project description:Genetic Analysis of Psoriasis and Psoriatic Arthritis
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Project description:We report changes in gene expression in human peripheral blood neutrophils from patients with psoriatic arthritis (PsA) before and 12-weeks after treatment with Secukinumab (SKB, 150mg). All patients achieved a good PSARC (Psoriatic Arthritis Response Criteria) and PASI 90 (Psoriasis Area and Severity Index) response to treatment. We also report gene expression in healthy control neutrophils compared to patients wth psoriatic arthritis.
2023-01-06 | GSE179800 | GEO
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:This is a pilot single cell mRNA sequencing experiment to study immune cells in psoriatic arthritis.
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Project description:Whole genome sequencing of immune cells from patients diagnosed with psoriatic arthritis
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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:<p>This study is a genome-wide study of genetic associations with psoriatic arthritis (PsA), an inflammatory musculoskeletal condition that develops in up to 30% of people who have chronic psoriasis skin lesions. 1,526 cases affected with psoriatic arthritis and 1,508 unaffected controls were recruited and typed on the Illumina HumanOmni1-Quad BeadChip array. After application of quality control measures to both samples and SNPs, genotypes for 791,217 autosomal SNPs were available for 1,430 PsA cases and 1,417 controls. Imputation using phased haplotypes for the EUR subpopulation of release 3, phase 1 of the 1000 Genomes Project as a reference, resulted in genotypes for 11,532,644 SNPs and 918,976 indels passing our imputation quality threshold (Mach r<sup>2</sup> ≥ 0.3) that were available for downstream analysis. Association at a genome-wide threshold of significance was found for five regions (near genes <i>TNIP1</i>, <i>IL12B</i>, <i>HLA-C</i>, <i>TRAF3IP2</i>, and <i>TYK2</i>).</p>
| phs000982 | dbGaP
Project description:Epigenomic analysis of sperm cells from patients with psoriatic arthritis, psoriasis without arthritis, and healthy controls
| PRJNA518901 | ENA
Project description:Genome-wide DNA methylation was analyzed to screen for differentially methylated CpG sites in the discovery phase to explore the role of DNA methylation CpG markers in the diagnosis of psoriatic arthritis patients.
2023-06-01 | GSE200376 | GEO