48 Chapter 3 play a role in cell signaling. A metabolomics approach was also adopted to identify markers that distinguish between sepsis and noninfectious causes of critical illness [67]. Serum concentrations of most acylcarnitines, glycerophospholipids and sphingolipids were altered in sepsis compared to noninfectious critical illness, and a regression model combining the sphingolipid sphingomyelin (SM) C22:3 and the glycerophospholipid lysoPCaC24:0 was discovered for sepsis diagnosis with a sensitivity of 0.84 and specificity of 0.86. Furthermore, specific metabolites could be used for the discrimination of different types of infection. Within patients with sepsis, those with bloodstream infection could be discriminated by a decrease of acetylornithine. Putrescine, lysoPCaC18:0 and SM C16:1 were associated with unfavorable outcome in patients with sepsis caused by CAP, intra-abdominal infections and bloodstream infections, respectively [67]. Sphingolipids are involved in signal transmission and cell recognition, whereas putrescine mediates the complex interplay between bacterial infection and the host immune response. Another investigation tested variable metabolites for association with 28-day mortality in patients with sepsis and found 31 metabolites that differed among ICU survivors versus those who died. In those who died 25 metabolites were increased and 6 were decreased (all of which were lipids). The investigators developed a metabolomic network of seven metabolites associated with death (gamma-glutamylphenylalanine, gamma-glutamyltyrosine, 1-arachidonoylGPC(20;4), taurochenodeoxycholate, 3-(4-hydroxyphenyl) lactate, sucrose, kynurenine)[64]. In a retrospective analysis conducted in 20 patients with septic shock changes of circulating metabolites were studied in relation to mortality using a targeted mass spectrometry-based quantitative metabolomic approach [68]. Low unsaturated long-chain phosphatidylcholines and lysophosphatidylcholines species (amongst which are glycerophospholipid lysoPCaC24:0 and lysoPCaC18:0) were associated with 90-day survival together with low circulating kynurenine, which is relevant for tryptophan catabolism [68]. In a comprehensive proteomic–metabolomic analysis on patients with communityacquired sepsis patients at higher risk of death were found relatively deficient in fatty acid transport and beta-oxidation, gluconeogenesis and the citric acid cycle [66]. Alterations in the metabolome were correlated with changes in the proteome and a seven-metabolite panel could predict sepsis mortality at the time of presentation to the ED [66]. In an approach that integrated human genetics, patient metabolite and cytokine measurements, and testing in a mouse model revealed the methionine salvage pathway as a regulator of sepsis pathophysiology that can predict prognosis in patients [69]. Elevated plasma levels of the pathway’s substrate methylthioadenosine were associated with mortality in two cohorts of sepsis patients and correlated with levels of proinflammatory cytokines, indicating that elevated methylthioadenosine marks a subgroup of patients with excessive inflammation. A machine-learning model combining methylthioadenosine and other variables produced 80% accuracy in predicting death [69]. These studies show differences in altered metabolites (e.g., glycerophospholipid PCaaC32:0 in one study and glycerophospholipid lysoPCaC24:0 in another) and similarities (e.g., higher circulating kynurenine, putrescine, lysoPCaC18:0 and lysoPCaC24:0) associated with unfavorable outcome. This can be the result of well-known pathophysiological lipid induction by bacterial components as part of the metabolic changes in patients with sepsis, as well as altered pathogen-host interactions.
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