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. 2022 Jul 29;12(1):13043.
doi: 10.1038/s41598-022-16886-w.

Systemic long-term metabolic effects of acute non-severe paediatric burn injury

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Systemic long-term metabolic effects of acute non-severe paediatric burn injury

Sofina Begum et al. Sci Rep. .

Abstract

A growing body of evidence supports the concept of a systemic response to non-severe thermal trauma. This provokes an immunosuppressed state that predisposes paediatric patients to poor recovery and increased risk of secondary morbidity. In this study, to understand the long-term systemic effects of non-severe burns in children, targeted mass spectrometry assays for biogenic amines and tryptophan metabolites were performed on plasma collected from child burn patients at least three years post injury and compared to age and sex matched non-burn (healthy) controls. A panel of 12 metabolites, including urea cycle intermediates, aromatic amino acids and quinolinic acid were present in significantly higher concentrations in children with previous burn injury. Correlation analysis of metabolite levels to previously measured cytokine levels indicated the presence of multiple cytokine-metabolite associations in the burn injury participants that were absent from the healthy controls. These data suggest that there is a sustained immunometabolic imprint of non-severe burn trauma, potentially linked to long-term immune changes that may contribute to the poor long-term health outcomes observed in children after burn injury.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1
Figure 1
Orthogonal partial least square discriminant analysis (OPLS-DA). (A) OPLS-DA for class (burn injury or non-burn control) discrimination based on metabolic differences (R2X = 0.524, Q2Y = 0.2) (B) Log-scaled quantified metabolite concentrations, found to be significantly different between burn injury (n = 33) and non-burn (n = 33 age and gender matched (healthy)) controls (p value * < 0.05, ** < 0.01).
Figure 2
Figure 2
Correlation heatmaps integrating biogenic amines and tryptophan pathway metabolite concentrations and circulating cytokines. (A) Measurements from burn injury patients. (B) Measurements from non-burn (healthy) controls. Hierarchical clustering based on clustering from burn injury results and mirrored for direct comparison to non-burn (healthy) age and sex matched controls. Hierarchical edge clustering based on correlation analysis of significant metabolites (p value < 0.05) against cytokine measurements, visualised as (C) burn injury and (D) non-burn (healthy) controls focused on positive serine-cytokine interactions, and (E) burn injury and (F) non-burn (healthy) controls focused on positive tyrosine-cytokine interactions.
Figure 3
Figure 3
Quantitative enrichment analysis based on all 46 metabolites, discriminating burn injury and healthy controls. (A) Overview of the top 25 enriched metabolite sets and (B) corresponding metabolite network of the same top 25 enriched metabolite sets.

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