Abstract
BackgroundPsoriasis is an immune-mediated disease characterised by chronically elevated pro-inflammatory cytokine levels, leading to aberrant keratinocyte proliferation and differentiation. Although certain clinical phenotypes, such as plaque psoriasis, are well defined, it is currently unclear whether there are molecular subtypes that might impact on prognosis or treatment outcomes.ResultsWe present a pipeline for patient stratification through a comprehensive analysis of gene expression in paired lesional and non-lesional psoriatic tissue samples, compared with controls, to establish differences in RNA expression patterns across all tissue types. Ensembles of decision tree predictors were employed to cluster psoriatic samples on the basis of gene expression patterns and reveal gene expression signatures that best discriminate molecular disease subtypes. This multi-stage procedure was applied to several published psoriasis studies and a comparison of gene expression patterns across datasets was performed.ConclusionOverall, classification of psoriasis gene expression patterns revealed distinct molecular sub-groups within the clinical phenotype of plaque psoriasis. Enrichment for TGFb and ErbB signaling pathways, noted in one of the two psoriasis subgroups, suggested that this group may be more amenable to therapies targeting these pathways. Our study highlights the potential biological relevance of using ensemble decision tree predictors to determine molecular disease subtypes, in what may initially appear to be a homogenous clinical group. The R code used in this paper is available upon request.
Highlights
Psoriasis is an immune-mediated disease characterised by chronically elevated pro-inflammatory cytokine levels, leading to aberrant keratinocyte proliferation and differentiation
A pipeline (Figure 1) for patient stratification according to gene expression profiles in psoriasis was implemented to generate molecular sub-groups and uncover gene signatures associated with each disease group
A set of 228 probes was shared across all datasets (Figures 1 and 2a) and corresponded to a total number of 206 unique genes, of which 130 genes were over-expressed and 76 under-expressed in Paired samples from lesional (PP) samples compared to non-lesional (PN) and normal (NN) (Additional file 1: Table S1)
Summary
Psoriasis is an immune-mediated disease characterised by chronically elevated pro-inflammatory cytokine levels, leading to aberrant keratinocyte proliferation and differentiation. Psoriasis is one of the most prevalent chronic inflammatory disorders caused by an interplay of genetic factors and the environment on the background of dysregulated immune system [1]. There are several clinical variants of psoriasis, but the most common variant, plaque psoriasis, is characterised by chronic, symmetrical, silvery-scaled, sharply circumscribed plaques [1,3]. Plaque psoriasis is the most common form of the disease and the cause of psoriasis remains unknown, it is thought to be a complex and multifactorial disorder brought about by the combination of multiple susceptibility genes [4,5,6], a dysregulated immune system [7,8] and environmental factors [9]. A unifying model that integrates genetic, environmental and immunological aspects of skin inflammation has been proposed [12]
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
