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| Status |
Public on Jan 31, 2017 |
| Title |
Expression data from blood of healthy controls and ns vitiligo patients |
| Organism |
Homo sapiens |
| Experiment type |
Expression profiling by array
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| Summary |
Vitiligo Blood Transcriptomics Provides New Insights into Disease Mechanisms and Identifies Potential Novel Therapeutic Targets Abstract Background: Significant gaps remain regarding the pathomechanisms underlying the autoimmune response in vitiligo (VL), where the loss of self-tolerance leads to the targeted killing of melanocytes. Specifically, there is incomplete information regarding alterations in the systemic environment that are relevant to the disease state. Methods: We undertook a genome-wide profiling approach to examine gene expression in the peripheral blood of VL patients and healthy controls in the context of our previously published VL-skin gene expression profile. We used several in silico bioinformatics-based analyses to provide new insights into disease mechanisms and suggest novel targets for future therapy. Results: Unsupervised clustering methods of the VL-blood dataset demonstrate a “disease-state”-specific set of co-expressed genes. Ontology enrichment analysis of 99 differentially expressed genes (DEGs) uncovers a down-regulated immune/inflammatory response, B-Cell antigen receptor (BCR) pathways, apoptosis and catabolic processes in VL-blood. There is evidence for both type I and II interferon (IFN) playing a role in VL pathogenesis. We used interactome analysis to identify several key blood associated transcriptional factors (TFs) from within (STAT1, STAT6 and NF-kB), as well as “hidden” (CREB1, MYC, IRF4, IRF1, and TP53) from the dataset that potentially affect disease pathogenesis. The TFs overlap with our reported lesional-skin transcriptional circuitry, underscoring their potential importance to the disease. We also identify a shared VL-blood and -skin transcriptional “hot spot” that maps to chromosome 6, and includes three VL-blood dysregulated genes (PSMB8, PSMB9 and TAP1) described as potential VL-associated genetic susceptibility loci. Finally, we provide bioinformatics-based support for prioritizing dysregulated genes in VL-blood or skin as potential therapeutic targets. Conclusions: We examined the VL-blood transcriptome in context with our (previously published) VL-skin transcriptional profile to address a major gap in knowledge regarding the systemic changes underlying skin-specific manifestation of vitiligo. Several transcriptional “hot spots” observed in both environments offer prioritized targets for identifying disease risk genes. Finally, within the transcriptional framework of VL, we identify five novel molecules (STAT1, PRKCD, PTPN6, MYC and FGFR2) that lend themselves to being targeted by drugs for future potential VL-therapy.
We used microarrays to detail the global programme of gene expression underlying the disease state in vitiligo and established differentially expressed genes by comparing gene expression values from diseased patients to healthy controls.
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| Overall design |
Blood was drawn from vitiligo patients and healthy controls (Weill Cornell Medical College Institutional Review Board: WCM IRB # 0998-398) for RNA extraction from sepearted PBMCs and subseuent hybridization on Affymetrix microarrays. We sought to compare normalized, background subtracted genome-wide gene expression values between patients and controls and to that end conducted microarray experiments. The patients and controls were not undergoing any therapy during sampling and the patients were clearly diagnosed with ns vitiligo in the clinic.
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| Contributor(s) |
Dey-Rao R, Sinha AA |
| Citation(s) |
28129744 |
| Submission date |
Dec 05, 2016 |
| Last update date |
Dec 13, 2018 |
| Contact name |
Rama Dey-Rao |
| E-mail(s) |
dey@buffalo.edu
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| Phone |
716-878-3318
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| Organization name |
University at Buffalo
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| Department |
Dermatology
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| Lab |
Dermatology
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| Street address |
6086 CTRC Bldg, 875 Ellicott Street
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| City |
Buffalo |
| State/province |
NY |
| ZIP/Postal code |
14203 |
| Country |
USA |
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| Platforms (1) |
| GPL8300 |
[HG_U95Av2] Affymetrix Human Genome U95 Version 2 Array |
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| Samples (14)
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| Relations |
| BioProject |
PRJNA356272 |
| Supplementary file |
Size |
Download |
File type/resource |
| GSE90880_RAW.tar |
33.0 Mb |
(http)(custom) |
TAR (of CEL) |
| Processed data included within Sample table |
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