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Analysis of the Plasma Metabolome after Trauma, Novel Circulating Sphingolipid Signatures, and In-Hospital Outcomes

Anthony Cyr, Yanjun Zhong, Steven E. Reis, Rami A. Namas, Andrew Amoscato, Brian Zuckerbraun, Jason Sperry, Ruben Zamora, Yoram Vodovotz,
Journal of the American College of Surgeons , Volume 232, pp 276-287.e1; doi:10.1016/j.jamcollsurg.2020.12.022

Abstract: Background Trauma is the leading cause of death and disability for individuals under age 55. Many severely injured trauma patients experience complicated clinical courses despite appropriate initial therapy. We sought to identify novel circulating metabolomic signatures associated with clinical outcomes following trauma. Study design Untargeted metabolomics and circulating plasma immune mediator analysis was performed on plasma collected during 3 post-injury time periods ( Results Eighty-six patients were included for analysis. Sphingolipids were enriched significantly (chi-square, p < 10-6) among the top 50 metabolites. Clustering of sphingolipid patterns identified 3 patient subclasses: nonresponders (no time-dependent change in sphingolipids, n = 41), sphingosine/sphinganine-enhanced (n = 24), and glycosphingolipid-enhanced (n = 21). Compared with the sphingolipid-enhanced subclasses, nonresponders had longer mean length of stay, more ventilator days, higher MOD scores, and higher circulating levels of proinflammatory immune mediators IL-6, IL-8, IL-10, MCP1/CCL2, IP10/CXCL10, and MIG/CXCL9 (all p < 0.05), despite similar Injury Severity Scores (p = 0.12). Conclusions Metabolomic analysis identified broad alterations in circulating plasma sphingolipids after blunt trauma. Circulating sphingolipid signatures and their association with both clinical outcomes and circulating inflammatory mediators suggest a possible link between sphingolipid metabolism and the immune response to trauma.
Keywords: IL; interleukin; ISS; Injury Severity Score; LOS; length of stay; MEBA; multivariate empirical Bayesian analysis; MOD; Marshall organ dysfunction; PCA; principal component analysis; PLS-DA; partial least squares discriminant analysis

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