Proteogenomic analysis of psoriasis reveals discordant and concordant changes in mRNA and protein abundance

Genome Med. 2015 Aug 4;7(1):86. doi: 10.1186/s13073-015-0208-5. eCollection 2015.


Background: Psoriasis is a chronic disease characterized by the development of scaly red skin lesions and possible co-morbid conditions. The psoriasis lesional skin transcriptome has been extensively investigated, but mRNA levels do not necessarily reflect protein abundance. The purpose of this study was therefore to compare differential expression patterns of mRNA and protein in psoriasis lesions.

Methods: Lesional (PP) and uninvolved (PN) skin samples from 14 patients were analyzed using high-throughput complementary DNA sequencing (RNA-seq) and liquid chromatography-tandem mass spectrometry (LC-MS/MS).

Results: We identified 4122 differentially expressed genes (DEGs) along with 748 differentially expressed proteins (DEPs). Global shifts in mRNA were modestly correlated with changes in protein abundance (r = 0.40). We identified similar numbers of increased and decreased DEGs, but 4-fold more increased than decreased DEPs. Ribosomal subunit and translation proteins were elevated within lesions, without a corresponding shift in mRNA expression (RPL3, RPS8, RPL11). We identified 209 differentially expressed genes/proteins (DEGPs) with corresponding trends at the transcriptome and proteome levels. Most DEGPs were similarly altered in at least one other skin disease. Psoriasis-specific and non-specific DEGPs had distinct cytokine-response patterns, with only the former showing disproportionate induction by IL-17A in cultured keratinocytes.

Conclusions: Our findings reveal global imbalance between the number of increased and decreased proteins in psoriasis lesions, consistent with heightened translation. This effect could not have been discerned from mRNA profiling data alone. High-confidence DEGPs were identified through transcriptome-proteome integration. By distinguishing between psoriasis-specific and non-specific DEGPs, our analysis uncovered new functional insights that would otherwise have been overlooked.