Cross-sectional study of proteomic differences between moderate and severe psoriasis

Abstract

Although an ongoing understanding of psoriasis vulgaris (PV) pathogenesis, little is known about the proteomic differences between moderate and severe psoriasis. In this cross-sectional study, we evaluated the proteomic differences between moderate and severe psoriasis using data-independent acquisition mass spectrometry (DIA-MS). 173 differentially expressed proteins (DEPs) were significantly differentially expressed between the two groups. Among them, 85 proteins were upregulated, while 88 were downregulated (FC ≥ ± 1.5, P < 0.05). Eighteen DEPs were mainly enriched in the IL - 17 signalling pathway, Neutrophil extracellular trap formation, Neutrophil degranulation and NF - kappa B signalling pathway, which were associated with psoriasis pathogenesis. Ingenuity pathway Analysis (IPA) identified TNF and TDP53 as the top upstream up-regulators, while Lipopolysaccharide and YAP1 were the top potential down-regulators. The main active pathways were antimicrobial peptides and PTEN signalling, while the inhibitory pathways were the neutrophil extracellular trap pathway, neutrophil degranulation, and IL-8 signalling. 4D-parallel reaction monitoring (4D-PRM) suggested that KRT6A were downregulated in severe psoriasis. Our data identify Eighteen DEPs as biomarkers of disease severity, and are associated with IL - 17 signalling pathway, Neutrophil extracellular trap formation, NF - kappa B signalling pathway, and defence response to the bacterium. Targeting these molecules and measures to manage infection may improve psoriasis's severity and therapeutic efficacy.

Keywords: 4D-parallel reaction monitoring; Biomarker; Data-independent acquisition mass spectrometry; Ingenuity pathway analysis; Proteomics; Psoriasis vulgaris.

Fig. 1

Box plot analysis of nine proteins with the highest ± FC in the upregulated and down-regulated DEPs, respectively. (a)Nine proteins (OSBPL6, CYFIP2, MYOCD, AGO3, DCD, PCBP4, LRIF1, DLG5 and KRT15) with the highest + FC in the up-regulated DEPs. (b)Inversely, the nine proteins with the highest -FC were MTMR10, CCNDBP1, STK3, LAMP1, UBE2D1, APBB3, BPI, SULT1B1 and IGHM in the down-regulated DEPs. The statistical analysis was performed using Student’s t-test with a p-value ≤ 0.05. *, ** and *** represent the p-values less than 0.05, 0.005 and 0.0005, respectively.

Fig. 2

GO and KEGG enrichment analyses were performed in 173 DEPs (FC ≥ ± 1.5, P-value < 0.05). Dotplot displayed the top 10 significant difference GO terms (a) and the top 20 enriched pathways in Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis (b). A p-value < 0.05 was used for biological process selection.

Fig. 3

Correlation between DEPs (FC ≥ ± 2.0, P-value < 0.05) and clinical PASI score. Circos plot presenting the Pearson correlation between DEPs and the PASI score (|cor|>0.6, p-value < 0.05). Red ribbons indicate positive Pearson correlation coefficients. Green ribbons represent negative Pearson correlation coefficients. The width of the ribbons indicates the correlation value.

Fig. 4

Protein-protein interaction networks of DEPs (FC ≥ ± 1.5, P-value < 0.05) were obtained from STRING (Confidence score > 0.5). Cytoscape (Version 3.10.2) was used to visualize the networks. Nodes represent proteins, and edges represent the interaction between them. Edge width corresponds to the combined score of specific protein pairs. A larger edge width indicated a higher score. PPI: protein-protein interaction.

Fig. 5

Upstream regulator analysis (URA) of 173 DEPs (FC ≥ ± 1.5, P-value < 0.05) according to Z-score using ingenuity pathway analysis (IPA), with P < 0.05, Z score > 0 or < 0). It determines likely upstream regulators that are connected to data set genes through a set of direct or indirect relationships. The top potential upstream up-regulators were TNF (a) and TDP53 (b), while the top potential down-regulators were Lipopolysaccharide (c) and YAP1 (d). Causal network analysis of DEPs using IPA. The highest-score network is displayed. The relationship among molecules is represented by lines (solid lines for direct association and dotted lines for indirect association) (e).

Fig. 5

Upstream regulator analysis (URA) of 173 DEPs (FC ≥ ± 1.5, P-value < 0.05) according to Z-score using ingenuity pathway analysis (IPA), with P < 0.05, Z score > 0 or < 0). It determines likely upstream regulators that are connected to data set genes through a set of direct or indirect relationships. The top potential upstream up-regulators were TNF (a) and TDP53 (b), while the top potential down-regulators were Lipopolysaccharide (c) and YAP1 (d). Causal network analysis of DEPs using IPA. The highest-score network is displayed. The relationship among molecules is represented by lines (solid lines for direct association and dotted lines for indirect association) (e).