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.

Project description:To characterize the diversity and taxonomic relative abundance of the gut microbiota in patients with never-treated, recent-onset psoriatic arthritis (PsA). Methods High-throughput 16S ribosomal RNA pyrosequencing was utilized to compare the community composition of gut microbiota in patients with PsA (n = 16), patients with psoriasis of the skin (n = 15), and healthy, matched control subjects (n = 17). Samples were further assessed for the presence and levels of fecal and serum secretory IgA (sIgA), proinflammatory proteins, and fatty acids. Results The gut microbiota observed in patients with PsA and patients with skin psoriasis was less diverse when compared to that in healthy controls. This could be attributed to the reduced presence of several taxa. Samples from both patient groups showed a relative decrease in abundance of Coprococcus species, while samples from PsA patients were also characterized by a significant reduction in Akkermansia, Ruminococcus, and Pseudobutyrivibrio. Supernatants of fecal samples from PsA patients revealed an increase in sIgA levels and decrease in RANKL levels. Analysis of fatty acids revealed low fecal quantities of hexanoate and heptanoate in both patients with PsA and patients with psoriasis. Conclusion Patients with PsA and patients with skin psoriasis had a lower relative abundance of multiple intestinal bacteria. Although some genera were concomitantly decreased in both conditions, PsA samples had a lower abundance of reportedly beneficial taxa. This gut microbiota profile in PsA was similar to that previously described in patients with inflammatory bowel disease and was associated with changes in specific inflammatory proteins unique to this group, and distinct from that in patients with skin psoriasis and healthy controls. Thus, the role of the gut microbiome in the continuum of psoriasis–PsA pathogenesis and the associated immune response merits further study. Research is published: http://onlinelibrary.wiley.com/doi/10.1002/art.38892/full

Project description:Background: Nasal epithelia are emerging as a proxy measure of gene expression of the airway epithelium in asthma. We hypothesized that epigenetic marks regulate gene expression of the nasal epithelia and consequently may provide a novel target for allergic asthma. Methods: We compared genomic DNA methylation patterns and gene expression in African American children with persistent atopic asthma [N=36] versus healthy controls [N=36]. Results were validated in an independent population of asthmatics [N=30]. Results: We identified 186 genes with significant methylation changes, either as regions (differentially methylated regions [DMRs]) or single CpGs (differentially methylated probes [DMPs]) after adjustment for age, gender, race/ethnicity, batch effects, inflation, and multiple comparisons (false discovery rate-adjusted q<0.05). Genes differentially methylated include those with established roles in asthma and atopy, components of the extracellular matrix, genes related to immunity, cell adhesion, epigenetic regulation, and airway obstruction. The methylation changes are large (median 9.5%, range: 2.6-29.5% methylation change) and similar in magnitude to those observed in malignancies. Hypo- and hyper-methylated genes were associated with increased and decreased gene expression respectively (P<2.8x10-6 for DMRs and P<7.8x10-10 for DMPs). Quantitative analysis of methylation-expression relationships in 53 differentially expressed genes demonstrated that 32 (60%) have significant (q<0.05) methylation-expression relationships within 5kb of the gene. 10 loci selected based on the relevance to asthma, magnitude of methylation change, and asthma specific methylation-expression relationships were validated in an independent cohort of children with asthma. Conclusions: Our findings that epigenetic marks in respiratory epithelia are associated with allergic asthma in inner-city children provide new targets for biomarker development, and novel approaches to understanding disease pathogenesis. case control design with nasal epithelial cells from 36 atopic asthmatic and 36 nonatopic nonasthmatic children from the inner city

Project description:Objectives: To understand the crosstalk between the immune system and keratinization in psoriatic skin, using a systems biology approach based on transcriptomics, proteomics and microbiome profiling. Methods: We collected the skin tissue biopsies and swabs in both lesion and non-lesion skin of 13 patients with psoriasis (PsO), 15 patients with psoriatic arthritis (PsA), and healthy skin from 12 patients with ankylosing spondylitis (AS). We performed transcriptome sequencing and metagenomics profiling on the local skin sites to study the similarities and differences in the molecular profiles between the three conditions. To assess the systemic nature of the disease, we performed a high-throughput proteome profiling to study the profiles of proteins circulating in the serum of the same donors. Results: We found that lesion and non-lesional samples were remarkably different in terms of their transcriptome profiles. Functional annotation of differentially expressed genes (DEGs) showed a major enrichment in neutrophil activation. By using co-expression gene networks, we identified a gene module that was associated with local psoriasis severity at the site of biopsy. From this module, we extracted a “core” set of genes that were functionally involved in neutrophil activation, epidermal cell differentiation and response to bacteria. Skin microbiome analysis revealed that the abundance of Enhydrobacter, Micrococcus and Leptotrichia were significantly correlated with the “core network” of genes. We further identified 39 circulating proteins from the serum that were significantly correlated with the corresponding local skin gene expression, highlighting systemic aberrations due to skin disease. Integration of “core” genes identified from skin with circulating protein profiles revealed PI3 as a key biomarker for psoriasis. Conclusions: We identified a core network that regulates inflammation and hyper-keratinization in psoriatic skin, and is associated with local disease severity and microbiome composition. Multi-omics analysis identified PI3 as a psoriasis-specific biomarker for disease severity and potential target for treatment strategies.

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DNA methylation patterns in CD8+ T cells discern psoriasis from psoriatic arthritis and correlate with cutaneous disease activity

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