Dataset Information

Whole Genome Expression Profiling and Signal Pathway Screening of MSCs in Ankylosing Spondylitis.

ABSTRACT: The pathogenesis of dysfunctional immunoregulation of mesenchymal stem cells (MSCs) in ankylosing spondylitis (AS) is thought to be a complex process that involves multiple genetic alterations. In this study, MSCs derived from both healthy donors and AS patients were cultured in normal media or media mimicking an inflammatory environment. Whole genome expression profiling analysis of 33,351 genes was performed and differentially expressed genes related to AS were analyzed by GO term analysis and KEGG pathway analysis. Our results showed that in normal media 676 genes were differentially expressed in AS, 354 upregulated and 322 downregulated, while in an inflammatory environment 1767 genes were differentially expressed in AS, 1230 upregulated and 537 downregulated. GO analysis showed that these genes were mainly related to cellular processes, physiological processes, biological regulation, regulation of biological processes, and binding. In addition, by KEGG pathway analysis, 14 key genes from the MAPK signaling and 8 key genes from the TLR signaling pathway were identified as differentially regulated. The results of qRT-PCR verified the expression variation of the 9 genes mentioned above. Our study found that in an inflammatory environment ankylosing spondylitis pathogenesis may be related to activation of the MAPK and TLR signaling pathways.

SUBMITTER: Li Y

PROVIDER: S-EPMC4269092 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Whole Genome Expression Profiling and Signal Pathway Screening of MSCs in Ankylosing Spondylitis.

Li Yuxi Y Wang Peng P Xie Zhongyu Z Huang Lin L Yang Rui R Gao Liangbin L Tang Yong Y Zhang Xin X Ye Jichao J Chen Keng K Cai Zhaopeng Z Wu Yanfeng Y Shen Huiyong H

Stem cells international 20141203

The pathogenesis of dysfunctional immunoregulation of mesenchymal stem cells (MSCs) in ankylosing spondylitis (AS) is thought to be a complex process that involves multiple genetic alterations. In this study, MSCs derived from both healthy donors and AS patients were cultured in normal media or media mimicking an inflammatory environment. Whole genome expression profiling analysis of 33,351 genes was performed and differentially expressed genes related to AS were analyzed by GO term analysis and ...[more]

PMID: 25544849

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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:Introduction: A number of genetic-association studies have identified genes contributing to AS susceptibility but such approaches provide little information as to the gene activity changes occurring during the disease process. Transcriptional profiling generates a “snapshot” of the sampled cells activity and thus can provide insights into the molecular processes driving the disease process. We undertook a whole-genome microarray approach to identify candidate genes associated with AS and validated these gene-expression changes in a larger sample cohort. Methods: 18 active AS patients, classified according to the New York criteria. and 18 gender-and age-matched controls were profiled using Illumina HT-12 Whole-Genome Expression BeadChips which carry cDNAs for 48000 genes and transcripts. Class comparison analysis identified a number of differentially expressed candidate genes. These candidate genes were then validated in a larger cohort using qPCR-based TaqMan Low Density Arrays (TLDAs). Results: 239 probes corresponding to 221 genes were identified as being significantly different between patients and controls with a p-value <0.0005 (80% confidence level of false discovery rate). Forty seven genes were then selected for validation studies, using the TLDAs. Thirteen of these genes were validated in the second patient cohort with 12 down-regulated 1.3-2-fold and only 1 upregulated (1.6-fold). Among a number of identified genes with well-documented inflammatory roles we also validated genes that might be of great interest to the understanding of AS progression such as SPOCK2 (osteonectin) and EP300 which modulate cartilage and bone metabolism. Conclusion: We have validated a gene expression signature for AS from whole blood and identified strong candidate genes that may play roles in both the inflammatory and joint destruction aspects of the disease. RNA was extracted from whole blood using PAXGene tubes. 16 AS patients with active disease and 16 gender- and age-matched controls were analysed.

Project description:Background Long non-coding RNAs (lncRNAs) are important regulators in ankylosing spondylitis (AS). Few studies have examined the lncRNA-RNA binding protein (RBP) interaction in AS. This study performed bioinformatics analysis and clinical verification to identify key lncRNAs and propose their RBP interaction. Methods Three GEO datasets of AS were analyzed by differential expression analysis. The differentially expressed lncRNAs between the AS and control groups were screened out, and the intersecting lncRNAs were regarded as target lncRNAs. Functional was performed to identify target lncRNAs by enrichment analysis, co-expressed RNA analysis, and lncRNA-RBP interaction analysis. Finally, this study analyzed the differential expression level and clinical value of lncRNAs between the AS and control groups. Results Linc00304, linc00926, and MIAT were differentially expressed and upregulated. Enrichment analysis indicated that the key KEGG terms were the T-cell receptor signaling pathway and B-cell receptor signaling pathway. The key molecular function term was protein binding, and the key biological process term was adaptive immune response. In qRT-PCR results, 44 samples were validated. linc00304 expression was positively correlated with bath ankylosing spondylitis disease activity index (BASDAI), bath ankylosing spondylitis functional index (BASFI), erythrocyte sedimentation rate (ESR), and c-reactive protein (CRP). linc00926 expression was only positively correlated with ESR, whereas MIAT expression was positively correlated with BASFI, ESR, and CRP. Logistic regression revealed that linc00304, ESR, and CRP were the independent risk factors for BASDAI activation. The area under the curve (AUC) of serum linc00304 level in the diagnosis of AS was 0.687 (cutoff value: 0.413, specificity: 0.423, sensitivity: 0.900). AUC of linc00926 was 0.664 (cutoff value: 0.299, sensitivity: 0.882, specificity: 0.417). AUC of MIAT was 0.623 (cutoff value: 0.432, specificity: 0.443, sensitivity: 0.890) (all P <0.05). Conclusion Overall, this study uncovered three novel lncRNAs, which were upregulated in AS, and proposed a new lncRNA-RBP-mRNA interaction that might regulate adaptive immune response.

Dataset Information

Whole Genome Expression Profiling and Signal Pathway Screening of MSCs in Ankylosing Spondylitis.

Publications

Whole Genome Expression Profiling and Signal Pathway Screening of MSCs in Ankylosing Spondylitis.

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