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. 2020 Feb 20;10(1):3081.
doi: 10.1038/s41598-020-59996-z.

Hyperproliferation is the main driver of metabolomic changes in psoriasis lesional skin

Affiliations

Hyperproliferation is the main driver of metabolomic changes in psoriasis lesional skin

Liis Pohla et al. Sci Rep. .

Abstract

Systematic understanding of the metabolite signature of diseases may lead to a closer understanding of the disease pathogenesis and ultimately to the development of novel therapies and diagnostic tools. Here we compared for the first time the full metabolomic profiles of lesional and non-lesional skin biopsies obtained from plaque psoriasis patients and skin samples of healthy controls. Significant differences in the concentration levels of 29 metabolites were identified that provide several novel insights into the metabolic pathways of psoriatic lesions. The metabolomic profile of the lesional psoriatic skin is mainly characterized by hallmarks of increased cell proliferation. As no significant differences were identified between non-lesional skin and healthy controls we conclude that local inflammatory process that drives the increased cell proliferation is the main cause of the identified metabolomic shifts.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1
Figure 1
Boxplots of concentrations of six metabolites which concentrations were statistically significantly (Kruskal-Wallis rank sum test, FDR 5% corrected p-value < 0.05) elevated in psoriatic lesional skin (PS-L) compared to psoriatic non-lesional skin (PS-NL) and the skin of healthy controls (C). The levels are reported in micromolar (μM) concentrations. C5, valeryl-L-carnitine; Spermidine; Glu, glutamate; Met, methionine; ADMA, asymmetric dimethylarginine; Putrescine.
Figure 2
Figure 2
PCA plot of the targeted analysis. Psoriatic lesional skin samples are marked as red squares, psoriatic non-lesional skin samples are marked as blue triangles and control skin samples are marked as green circles. X and Y axes represent the percentage of variability explained by principal components one and two. Data is based on statistically significantly changed metabolites from Kruskal-Wallis test.

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