Metabolomics as a Driver in Advancing Precision Medicine in Sepsis

Abstract

The objective of this review is to explain the science of metabolomics-a science of systems biology that measures and studies endogenous small molecules (metabolites) that are present in a single biological sample-and its application to the diagnosis and treatment of sepsis. In addition, we discuss how discovery through metabolomics can contribute to the development of precision medicine targets for this complex disease state and the potential avenues for those new discoveries to be applied in the clinical environment. A nonsystematic literature review was performed focusing on metabolomics, pharmacometabolomics, and sepsis. Human (adult and pediatric) and animal studies were included. Metabolomics has been investigated in the diagnosis, prognosis, and risk stratification of sepsis, as well as for the identification of drug target opportunities. Metabolomics elucidates a new level of detail when compared with other systems biology sciences, with regard to the metabolites that are most relevant in the pathophysiology of sepsis, as well as highlighting specific biochemical pathways at work in sepsis. Metabolomics also highlights biochemical differences between sepsis survivors and nonsurvivors at a level of detail greater than that demonstrated by genomics, transcriptomics, or proteomics, potentially leading to actionable targets for new therapies. The application of pharmacometabolomics and its integration with other systems pharmacology to sepsis therapeutics could be particularly helpful in differentiating drug responders and nonresponders and furthering knowledge of mechanisms of drug action and response. The accumulated literature on metabolomics suggests it is a viable tool for continued discovery around the pathophysiology, diagnosis and prognosis, and treatment of sepsis in both adults and children, and it provides a greater level of biochemical detail and insight than other systems biology approaches. However, the clinical application of metabolomics in sepsis has not yet been fully realized. Prospective validation studies are needed to translate metabolites from the discovery phase into the clinical utility phase.

Keywords: critical care; pediatrics; pharmacometabolomics; pharmacotherapy; systems biology; systems pharmacology.

Figure 1

Overview of the interactions between systems biology and pharmacology sciences. (A) Systems biology consists of genomics, transcriptomics, proteomics, and metabolomics. Although the transition of these sciences is often viewed as linear, it is likely that there are bidirectional interactions among them. For example, metabolites serve as signaling molecules for gene and protein regulation. (B) Systems pharmacology includes pharmacogenomics, pharmacometabolomics, pharmacokinetics, and pharmacodynamics. These sciences interact in such a way that they can inform each other so that more detail about mechanisms of drug action and drug response phenotypes can be learned.

Figure 2

Representative steps in a typical metabolomics work flow. If prospective sampling is planned, samples should be collected (step 1) using a standard operating procedure to ensure consistent procedures and sample processing. Sample preparation (step 2) will vary depending on the sample type. The most common analytical platforms for metabolomics data acquisition include nuclear magnetic resonance (NMR) and liquid (or gas) chromatography followed by mass spectrometry (LC-MS). A number of different publically and commercially available platforms exist for spectral processing and metabolite identification and quantification (step 4). These include Chenomx (chenomx.com), XCMS (https://xcmsonline.scripps.edu/) and MS-Dial (http://prime.psc.riken.jp/Metabolomics_Software/MS-DIAL/index.html). Statistical analysis (step 5) can be performed using quantified or nonquantified data using a number of different approaches (see text). Pathway analysis or the mapping of metabolites to metabolic networks can be achieved using a number of different tools including Metscape (http://metscape.ncibi.org/) or MetaboAnalyst (http://www.metaboanalyst.ca/).