English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

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.    Electronic supplementary material  The online version of this article (doi:10.1186/s12864-017-3510-3) contains supplementary material, which is available to authorized users.

Vitiligo blood transcriptomics provides new insights into disease mechanisms and identifies potential novel therapeutic targets