Metabolic consequences of sepsis-induced acute lung injury revealed by plasma ¹H-nuclear magnetic resonance quantitative metabolomics and computational analysis

Abstract

Metabolomics is an emerging component of systems biology that may be a viable strategy for the identification and validation of physiologically relevant biomarkers. Nuclear magnetic resonance (NMR) spectroscopy allows for establishing quantitative data sets for multiple endogenous metabolites without preconception. Sepsis-induced acute lung injury (ALI) is a complex and serious illness associated with high morbidity and mortality for which there is presently no effective pharmacotherapy. The goal of this study was to apply ¹H-NMR based quantitative metabolomics with subsequent computational analysis to begin working towards elucidating the plasma metabolic changes associated with sepsis-induced ALI. To this end, this pilot study generated quantitative data sets that revealed differences between patients with ALI and healthy subjects in the level of the following metabolites: total glutathione, adenosine, phosphatidylserine, and sphingomyelin. Moreover, myoinositol levels were associated with acute physiology scores (APS) (ρ = -0.53, P = 0.05, q = 0.25) and ventilator-free days (ρ = -0.73, P = 0.005, q = 0.01). There was also an association between total glutathione and APS (ρ = 0.56, P = 0.04, q = 0.25). Computational network analysis revealed a distinct metabolic pathway for each metabolite. In summary, this pilot study demonstrated the feasibility of plasma ¹H-NMR quantitative metabolomics because it yielded a physiologically relevant metabolite data set that distinguished sepsis-induced ALI from health. In addition, it justifies the continued study of this approach to determine whether sepsis-induced ALI has a distinct metabolic phenotype and whether there are predictive biomarkers of severity and outcome in these patients.

Fig. 1.

Representative ¹H-NMR spectra of plasma water- and lipid-soluble metabolites. FA, fatty acids; OH-butyrate, hydroxybutyrate; PL, phospholipids; PUFA, polyunsaturated fatty acids; TAG, triacylglycerol; UFA, unsaturated fatty acids.

Fig. 2.

Differentiating metabolites of mechanically ventilated sepsis-induced acute lung injury (ALI) patients (n = 13) compared with healthy subjects (n = 6). These metabolites are associated with oxidant stress (total glutathione), loss of ATP homeostasis (adenosine), apoptosis (PtdSer), and disruption of endothelial barrier function (sphingomyelin). Data are the means +SE. *P = 0.03 (q = 0.05); +P = 0.02 (q = 0.04); #P = 0.02 (q = 0.04); and ∧P = 0.006 (q = 0.02).

Fig. 3.

Possible associations between acute physiology score (APS) and myoinositol (A) and total glutathione (B). The associations, assessed by Spearman's rank correlation, suggest that myoinositol (ρ = 0.53; P = 0.05; q = 0.25) and total glutathione (ρ = 0.56; P = 0.04; q = 0.25) may be markers of sepsis-induced ALI severity.

Fig. 4.

Bioinformatics analysis of differentiating metabolites identified 4 distinct metabolic networks associated with total glutathione (A), adenosine (B), sphingomyelin (C), and phosphatidylserine (D). Networks were generated using the bioinformatics platform Cytoscape (http://www.cytoscape.org) with the Metscape plugin (http://metscape.ncibi.org/tryplugin.html). Hexagons represent compounds, and numbers are the enzyme commission (EC) number for enzymes involved in respective reactions.