Untargeted Metabolomics Differentiates l-Carnitine Treated Septic Shock 1-Year Survivors and Nonsurvivors

Abstract

l-Carnitine is a candidate therapeutic for the treatment of septic shock, a condition that carries a ≥40% mortality. Responsiveness to l-carnitine may hinge on unique metabolic profiles that are not evident from the clinical phenotype. To define these profiles, we performed an untargeted metabolomic analysis of serum from 21 male sepsis patients enrolled in a placebo-controlled l-carnitine clinical trial. Although treatment with l-carnitine is known to induce changes in the sepsis metabolome, we found a distinct set of metabolites that differentiated 1-year survivors from nonsurvivors. Following feature alignment, we employed a new and innovative data reduction strategy followed by false discovery correction, and identified 63 metabolites that differentiated carnitine-treated 1-year survivors versus nonsurvivors. Following identification by MS/MS and database search, several metabolite markers of vascular inflammation were determined to be prominently elevated in the carnitine-treated nonsurvivor cohort, including fibrinopeptide A, allysine, and histamine. While preliminary, these results corroborate that metabolic profiles may be useful to differentiate l-carnitine treatment responsiveness. Furthermore, these data show that the metabolic signature of l-carnitine-treated nonsurvivors is associated with a severity of illness (e.g., vascular inflammation) that is not routinely clinically detected.

Keywords: liquid chromatography−mass spectroscopy; pharmacometabolomics; vascular inflammation.

Figure 1:

Schematic of the sample analysis and data processing workflow. Serum samples were extracted with solvent and subjected to LC-MS analysis (step 1). Features were detected and aligned in the resulting data using XCMS (step 2). Data were then processed using data reduction and annotation software Binner, which enabled removal of redundant features including isotopes, fragments and minor adducts while annotating “primary” features with putative ion type (M+H, M+Na, etc) (step 3). Remaining features were subject to univariate statistical analysis with FDR correction to detect differential features between pre and 24h post carnitine samples, as well as between 1-year sepsis survivors and non-survivors (step 4). Differential features were subject to MS/MS analysis and database search to assign metabolite identity when possible or provide putative annotation when not (step 5), resulting in the final lists of differential metabolites included in this manuscript.

Figure 2.

Heatmaps of the metabolite features (FDR<0.1) of (A) carnitine-treated and (B) placebo-treated male septic shock patients. The black bars indicate samples from the same patient.

Figure 3.

Temporal profiles of the metabolites that differentiated carnitine-treated non-survivors and survivors (FDR <0.05). These included endogenous (A-M) and an exogenous metabolites (N). With the exception of (A) N-acetyl-L-phenylalanine and (F) phenylalanyltyrosine, all endogenous metabolites were higher in carnitine-treated non-survivors. Data are the median (IQR) of 7 male carnitine-treated survivors and 4 male carnitine-treated non-survivors at all time points except T48h (non-survivors, n=3).