Dataset Information

Ankylosing spondylitis: from cells to genes.

ABSTRACT: Ankylosing spondylitis (AS) is a chronic inflammatory disease of unknown etiology, though it is considered an autoimmune disease. HLA-B27 is the risk factor most often associated with AS, and although the mechanism of involvement is unclear, the subtypes and other features of the relationship between HLA-B27 and AS have been studied for years. Additionally, the key role of IL-17 and Th17 cells in autoimmunity and inflammation suggests that the latter and the cytokines involved in their generation could play a role in the pathogenesis of this disease. Recent studies have described the sources of IL-17 and IL-23, as well as the characterization of Th17 cells in autoimmune diseases. Other cells, such as NK and regulatory T cells, have been implicated in autoimmunity and have been evaluated to ascertain their possible role in AS. Moreover, several polymorphisms, mutations and deletions in the regulatory proteins, protein-coding regions, and promoter regions of different genes involved in immune responses have been discovered and evaluated for possible genetic linkages to AS. In this review, we analyze the features of HLA-B27 and the suggested mechanisms of its involvement in AS while also focusing on the characterization of the immune response and the identification of genes associated with AS.

SUBMITTER: Zambrano-Zaragoza JF

PROVIDER: S-EPMC3736459 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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Ankylosing spondylitis: from cells to genes.

Zambrano-Zaragoza José Francisco JF Agraz-Cibrian Juan Manuel JM González-Reyes Christian C Durán-Avelar Ma de Jesús Mde J Vibanco-Pérez Norberto N

International journal of inflammation 20130721

Ankylosing spondylitis (AS) is a chronic inflammatory disease of unknown etiology, though it is considered an autoimmune disease. HLA-B27 is the risk factor most often associated with AS, and although the mechanism of involvement is unclear, the subtypes and other features of the relationship between HLA-B27 and AS have been studied for years. Additionally, the key role of IL-17 and Th17 cells in autoimmunity and inflammation suggests that the latter and the cytokines involved in their generatio ...[more]

PMID: 23970995

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Project description:Genotyping was performed using a custom-designed Illumina 384-SNP VeraCode microarray (Illumina) to determine possible associations of genes encoding PADI1, PADI2, PADI3, PADI4, PADI6, PRKD3, Gc, GLRX,CDSN, PSORS1C1, TXNDC5, CA1, bub3, SORBS1, VDR,SERPNA1, PCSK6, DNAH9 to rheumatoid arthrities (RA) and ankylosing spondylitis (AS). We previously found that encoding genes of PADI1, PADI2, PADI3, PADI4, PADI6, PRKD3, Gc, GLRX,CDSN, PSORS1C1, TXNDC5, CA1, bub3, SORBS1, VDR, SERPNA1, PCSK6 and DNAH9 could be associated with rheumatoid arthritis (RA) and ankylosing spondylitis (AS). We used illumina customer designed microarray to verify the above finding with an increased numbers of samples. Genotyping was performed using a custom-designed Illumina 384-SNP VeraCode microarray (Illumina) to determine possible associations of genes encoding PADI1, PADI2, PADI3, PADI4, PADI6, PRKD3, Gc, GLRX,CDSN, PSORS1C1, TXNDC5, CA1, bub3, SORBS1, VDR, SERPNA1, PCSK6, DNAH9 to RA and AS. A case-control study was performed with 51 AS patients, 266 rheumatoid arthritis (RA) and 163 health controls. Tag single nucleotide polymorphisms (tag SNPs) across the above genes were determined by searching the HapMap database. The tag SNPs were selected on the basis of linkage disequilibrium patterns observed in the Han Chinese in Beijing (CHB) samples that were genotyped as a part of the International HapMap Project. Only SNPs with a minor allele frequency of greater than 5% with a pair-wise r2 ≥ 0.8 in the HapMap were considered. SNPs that were in exons and untranslated regions (UTR), as well as promoters and introns within 500 bp of exons were also selected. Candidate SNPs were submitted to Illumina for a design score. The Illumina Assay Design Tool filtered out SNPs that were not suitable for the Illumina platform. Finally, 382 SNPs with a design score of “1” were selected. 382 SNPs within PADI1, PADI2, PADI3, PADI4, PADI6, PRKD3, Gc, GLRX,CDSN, PSORS1C1, TXNDC5, CA1, bub3, SORBS1, VDR,SERPNA1, PCSK6, DNAH9 encoding genes were selected. Genotyping was performed using Illumina VeraCode microarray in a case-control study including 51 AS patients, 266 rheumatoid arthritis (RA) and 163 health controls We performed genotyping using a custom-designed Illumina 384-SNP VeraCode microarray (Illumina). Peripheral blood samples were collected from patients with RA (n=266, 183 female) and AS (n=51, 10 female). RA patients had a mean age of 51.7 years, while AS patients had a mean age of 35.9 years. A total of 163 (60 female) healthy individuals with a mean age of 48.0 years were blood donors. Blood samples were put into Monovette tubes containing 3.8% sodium citrate. The genotyping was conducted with the BeadXpress Reader using the Illumina VeraCode GoldenGate Assay kit. 500 ng of sample DNA were used per assay. Genotype clustering and calling were performed using BeadStudio software (Genomestudio V2010.2 Genotyping module V1.6) (Illumina). This work was completed at the Beijing Institute of Genomics.

Project description:We have compared synovial biopsies from ankylosing spondylitis and undifferentiated spondylitis patients with healthy controls and osteoarthritis patients Objective: In spondylarthropies, whole-genome gene expression profiling studies have been limited to peripheral blood to date. By undertaking a study in knee synovial biopsies from spondylarthropy (SpA) and ankylosing spondylitis (AS) patients we aimed to identified joint-specific candidate genes and pathways. These pathways may mediate systemic inflammation driven joint damaging processes and more specifically, the osteoproliferation that is characteristic of these conditions. Methods: RNA was extracted from six seronegative SpA, two AS, three osteoarthritis (OA) and four normal control knee synovial biopsies. Whole genome expression profiling was undertaken using the Illumina DASL system, which assays 24000 cDNA probes. Differentially expressed candidate genes were then validated using quantitative PCR and immunohistochemistry. Results: 416 differentially expressed genes were identified that clearly delineated between AS/SpA and control groups. Pathway analysis showed altered gene-expression in oxidoreductase activity, osteoblast activity, B-cell associated, matrix catabolic, and metabolic pathways. The inflammatory mediator, MMP3, was strongly upregulated in AS/SpA samples and the Wnt pathway inhibitors DKK3 and Kremen1 were downregulated. Conclusion: Pathways mediating both systemic inflammation as well as local tissue changes were identified. This suggests initial systemic inflammation in spondylarthropies transfers to and persists in the local joint environment, subsequently mediating changes in genes directly involved in the destructive tissue remodelling. Fifteen knee synovial biopsy tissue samples consisting of six seronegative spondyloarthropy (SpA), two ankylosing spondylitis (AS), three osteoarthritis (OA) and four normal control biopsies were obtained from the Synovial Tissue Bank at the Repatriation General Hospital in Adelaide, South Australia with the appropriate ethical approval (Supplementary Table 1). All patients provided informed written consent.

Project description:BackgroundCircular RNA (circRNA) is a type of closed circular noncoding RNA (ncRNA), mostly formed by back-splicing or alternative splicing of pre-messenger RNA (mRNA). The aim of this study was to explore the expression profile of circRNA in peripheral blood mononuclear cells (PBMCs) of patients with ankylosing spondylitis (AS) and discover potential molecular markers of AS.MethodsThe circRNA microarray technology was used to detect the expression of circRNAs in the peripheral blood of 6 patients with AS and 6 healthy controls (HC). To screen the differentially expressed circRNAs by fold change (FC) and P value, these differentially expressed circRNAs were analyzed by bioinformatics. In 60 cases of AS and 30 cases of HC, 4 circRNAs were subjected to real-time fluorescence quantitative polymerase chain reaction (RT-qPCR), and their correlation with various clinical indicators was analyzed. Finally, the receiver operating characteristic (ROC) curve was used to analyze their potential as AS diagnostic markers.ResultsThe microarray results showed that there were 1369 significantly differently expressed (P < 0.05, FC > 1.5) circRNAs between the AS and HC groups (675 upregulated and 694 downregulated). The results of bioinformatics analysis suggested that they were mainly involved in "enzyme binding," "adenosine ribonucleotide binding," "MAPK signaling pathway", etc. The RT-qPCR results showed that the expressions of hsa_circRNA_001544 (U = 486.5, P < 0.05) and hsa_circRNA_102532 (U = 645, P < 0.05) were significantly different between the AS group and the HC group. The AS group was further divided into two subgroups: active AS (ASA) and stable AS (ASS). After analysis, it was found that compared with the HC group, hsa_circRNA_001544 was significantly increased in both ASA (U = 214, P < 0.05) and ASS groups (U = 273, P < 0.05), while hsa_circRNA_008961 (U = 250, P < 0.05) and hsa_circRNA_102532 (U = 295, P < 0.05) were only significantly increased in the ASA group. Furthermore, hsa_circRNA_012732 was significantly different between the ASA and ASS groups (U = 194, P < 0.05), and there was no statistical significance among the remaining groups. Correlation analysis results showed that hsa_circRNA_012732 was negatively correlated with Bath Ankylosing Spondylitis Disease Activity Index (BASDAI), high-sensitivity C-reactive protein (hsCRP), and globulin (GLOB) and positively correlated with lymphocyte count (LY), mean corpusular volume, and albumin (ALB), and hsa_circRNA_008961 was negatively correlated with platelet (PLT) count. ROC curve analysis showed that hsa_circRNA_001544 (95% CI = 0.610-0.831, P < 0.05) and hsa_circRNA_102532 (95% CI = 0.521-0.762, P < 0.05) were statistically significant, and their area under curve (AUC) values were 0.720 and 0.642, respectively.ConclusionsThere are differentially expressed circRNAs in PBMCs of AS patients, and they may be involved in the occurrence and development of AS. Among these differentially expressed circRNAs, hsa_circRNA_012732 has the potential to become an indicator of disease activity, and hsa_circRNA_001544 has the potential to become a molecular marker for AS diagnosis.

Dataset Information

Ankylosing spondylitis: from cells to genes.

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Ankylosing spondylitis: from cells to genes.

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